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428188756320088902201545Characterization of microbiome in Lisbon subwayCharacterization of microbiome in Lisbon subway-1096786880Andreia Daniela Cardoso FernandesMestrado em Genética ForenseDepartamento de Biologia 2016Orientador Manuela Oliveira, Ph.D.Faculdade de Ciências da Universidade do PortoIpatimup – Instituto de Patologia e Imunologia Molecular da Universidade do Porto Coorientador Luísa Azevedo, Ph.D.Faculdade de Ciências da Universidade do PortoIpatimup – Instituto de Patologia e Imunologia Molecular da Universidade do PortoAndreia Daniela Cardoso FernandesMestrado em Genética ForenseDepartamento de Biologia 2016Orientador Manuela Oliveira, Ph.D.Faculdade de Ciências da Universidade do PortoIpatimup – Instituto de Patologia e Imunologia Molecular da Universidade do Porto Coorientador Luísa Azevedo, Ph.D.Faculdade de Ciências da Universidade do PortoIpatimup – Instituto de Patologia e Imunologia Molecular da Universidade do Porto4255026412242038610121176931Todas as corre??es determinadas pelo júri, e só essas, foram efetuadas.O Presidente do Júri,Porto, ______/______/_________00Todas as corre??es determinadas pelo júri, e só essas, foram efetuadas.O Presidente do Júri,Porto, ______/______/_________Acknowledgment In the first place, I want to thank, Christopher Mason for the opportunity to participate in this international project and being part of MetaSub Consortium. Also, I want to thanks all MetaSub collaborators, namely Ebrahim Afshinnekoo, Jorge Gandara, and Sofia Ahsanuddin, for the availability showed in all steps of this process. The personnel from Transportes de Lisboa - Metro de Lisboa, namely Doutora Maria Helena Campos, Eng. Pedro Pereira, Dr? Mariza Motta, and Doutora Carla Santos, that allowed the collections to happen in their installations. To Eng? Ana Paula Gon?alves from the Metro do Porto, that help us to establish initial contacts with colleagues in Lisbon. To Manuela Oliveira, thanks for all the help, what was much, in this project and advice, and for giving me the opportunity in participate in this international project.To Luisa Azevedo, for the availability showed in helping and advicing me in all the project.To Leticia and Cátia, that to all the sample collections were called and help me, even when we had to go to Lisbon. Thank you for all.To my friends, that always help me in this project, for all the advice and to make this way with me. Thank for all.And in the last, to my parents, my brothers, and all of my family, thanks for helping and believing me in this journey of my life. Abstract The subway system is one of the most used means of transportation in cities, due to the easy access and the lower cost to commuters. The aims of this study were to determine the subway microbiome and to understand the interactions between commuters-commuters and commuters-surface. This study also allowed identifying potential sources of microorganisms, providing useful information to develop preventive measures to decrease the microbiological load, and to detect possible imbalances of microbiome that can lead to the excessive proliferation of pathogenic species. In January of 2016, a total of 155 samples were collected from different surfaces in stations and trains from the Lisbon’s subway. All the samples taken were analyzed to determine the DNA concentration. Then, statistical analyses were performed to determine the influence of several parameters associated with subway system (line, station, type of surface, sampling duration, and a period when the sample was collected) in the DNA concentration collected. The diversity of microorganism presence in the subway was determined for 28 samples, using new-generation sequencing (NGS). Data related to the species identification were used to determine possible sources of microbial diversity. Finally, the identification of functional pathways was performed. In the samples sequenced, 47 families were found, being the Moraxellacea, Pseudomonadaceae, and Sphigobacteriacea the most frequent. A total of 117 species were identified, none being considered of elevated public health hazard. Bacteria usually described as soil, water and vegetation habitats were identified as the main sources of microbiome (50%), followed by human-associated microbiome (38%), being identified bacteria frequently isolated from the gastrointestinal tract, skin, and urogenital tract. Finally, bacteria commonly associated with food products (cheese, yogurts, processed meats) and meat (mainly pigeons) (12%) were identified. Finally, more than 500 different functional pathways were detected, revealing that the microorganisms present in the subway system are metabolically active. Through the results gathered in this work, the Lisbon subways system features a microbiome within the expected, not representing any danger to public health. However, further studies must be conducted to improve the knowledge of the microbiome of this system and to detect and prevent possible weaknesses in cases of infectious diseases outbreaks or, in worst-case scenarios, in the event of a bioterrorism attack.Keywords Functional Pathways; Microbiome; Next-Generation Sequencing; Potencial microbial sources; Subway; ResumoA rede de metro é um dos meios de transporte mais utilizados nas cidades, principalmente devido ao fácil acesso e ao baixo custo para os passageiros. Os objetivos deste estudo foram determinar o microbioma do metro e compreender as intera??es passageiro-passageiro e passageiros-superfície. Este estudo permitirá ainda conhecer as potenciais fontes de microrganismos de modo a desencadear medidas de redu??o da carga microbiológica e detetar antecipadamente possíveis desequilíbrios do microbioma que possam conduzir à prolifera??o exagerada de espécies patogénicas. Em Janeiro de 2016, foram recolhidas 155 amostras das superfícies das esta??es e das carruagens do Metro de Lisboa. Foi determinada a concentra??o de DNA presente nas amostras recolhidas. Seguidamente, foram realizadas análises estatísticas para determinar a influência diferentes par?metros associados à rede de metro (linha, esta??o, tipo de superfície, dura??o da amostragem e período do dia em que se realizou a amostragem) na concentra??o de DNA. A diversidade de microrganismos presentes no metro foi determinada, em 28 das amostras recolhidas, recorrendo a sequencia??o de nova gera??o (NGS). Os dados relativos às espécies identificadas foram usados para identifica??o de possíveis fontes de diversidade microbiana. Finalmente, procedeu-se à identifica??o das vias metabólicas presentes nestas amostras. Foram identificadas 47 famílias de microorganismos, Moraxellacea, Pseudomonadaceae e Sphigobacteriacea as mais representadas. No total foram identificadas 117 espécies, n?o sendo nenhuma destas especies considerada de alto risco para a saúde pública. Bactérias habitualmente descritas como habitantes solo, água e vegeta??o, foram identificadas como a principal fonte de diversidade do microbioma (50%). Seguiram-se as bactérias associadas ao microbioma humano (38%), sendo identificadas bactérias frequentemente isoladas a partir do tracto gastrointestinal, pele e tracto urogenital. Finalmente, foram encontradas outras fontes de bactérias (12%), como alimentos (queijo, iogurtes, carnes procesadas) e animais (sobretudo pombos). Finalmente foram identificadas mais de 500 vias metabólicas diferentes, revelando que os microorganismos presentes na rede do metro se encontram metabolicamente activos. Através dos resultados reunidos ao longo deste trabalho, considera-se que o Metro de Lisboa apresenta um microbioma dentro do esperado, n?o sendo representando qualquer perigo para a saúde pública. Contudo, mais estudos tem de ser conduzidos para melhorar o conhecimento do microbioma do Metro de Lisboa, de forma a detetar e prevenir possíveis debilidades em casos de surtos de doen?as infecciosas ou, em piores cenários, na eventualidade da ocorrência de ataques de bioterrorismo.Palavras-Chave Microbioma; Metro; Potenciais fontes de microrganismos; Sequencia??o de Nova Gera??o; Vias funcionais. Index TOC \o "1-3" \h \z \u Acknowledgment PAGEREF _Toc462917469 \h iAbstract PAGEREF _Toc462917470 \h iiResumo PAGEREF _Toc462917471 \h ivIndex PAGEREF _Toc462917472 \h 1List of tables PAGEREF _Toc462917473 \h 2List of figures PAGEREF _Toc462917474 \h 3List of abbreviations PAGEREF _Toc462917475 \h 4Introduction PAGEREF _Toc462917476 \h 5Material and Methods PAGEREF _Toc462917477 \h 12Results PAGEREF _Toc462917478 \h 18Discussion PAGEREF _Toc462917479 \h 29Conclusion PAGEREF _Toc462917480 \h 35Bibliography PAGEREF _Toc462917481 \h 36Attachments PAGEREF _Toc462917482 \h 39Supplementary table 1 PAGEREF _Toc462917483 \h 43Supplementary table 2 PAGEREF _Toc462917484 \h 51Supplementary table 3 PAGEREF _Toc462917485 \h 52Supplementary table 4 PAGEREF _Toc462917486 \h 59Supplementary table 5 PAGEREF _Toc462917487 \h 64List of tables Table 1 - Surfaces in the subway stations and cars of the subway were sampled……14List of figures Figure 1 - Representation of the four lines that constitute the Lisbon’s subway ………..13Figure 2 – DNA concentration collected in each sample in Lisbon subway………….…..20Figure 3 - DNA concentration collected in subway station and car ……………………….20Figure 4 - Average the quantification of DNA collected by time intervals………………...21Figure 5 - Distribution, by kingdoms, of the microorganisms identified in the Lisbon’s subway.………...............................................................................................................21Figure 6 - Relative abundances of bacterial families in the surfaces analyzed………….22Figure 7 - Main microorganism on subway surfaces (stations and cars) ………………23Figure 8 - Main microorganism on subway’s station surfaces…………………………….24Figure 9 - Main microorganism on subway’s cars surfaces……………………………….25Figure 10 - Possible sources of the microbial diversity found in the subway system……26Figure 11 - Possible environment-associated sources for the microbial diversity identified in the subway system…………………………………………………………………………26Figure 12 - Possible human-associated sources the microbial diversity identified in the subway system……………………………………………………………...…………….…..27Figure 13 - Possible animal and food-associated product sources the microbial diversity identified in the subway system.......………………………………………………………...27Figure 14 - Possible host organisms for the actives pathways identified in the subway system………………………………………………………………………………………….28Figure 15 - Main superclass’s from the actives pathways identified in the subway system………………………………………………………………………………………….29List of abbreviationsAMR – Antibiotic Resistance BGC – Biosynthetic Gene ClusterDNA – Deoxyribonucleic acidHMP - Human Microbiome Project MetaSUB - The Metagenomics and Metadesign of the Subways and Urban BiomesNGS – New Generation Sequencing Introduction Micrography, a specimen of Mucor, a microfungus, was the first microorganism to be described, in 1665, by Robert Hooke. Later, in 1676, Leeuwenhoek described the first bacteria and protozoa. The biggest contribute from Leeuwenhoek to biology, the discovery of bacteria, happened with his interest in taste. Due to an illness, he lost this sense. When examining his tongue, he described the existence of small organisms - “animalcules”. After this first report, Leeuwenhoek turn identified bacteria in other samples, such as teeth ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1098/rsnr.2004.0055", "author" : [ { "dropping-particle" : "", "family" : "Society", "given" : "Royal", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issue" : "2", "issued" : { "date-parts" : [ [ "2016" ] ] }, "page" : "187-201", "title" : "The Discovery of Microorganisms by Robert Hooke and Antoni van Leeuwenhoek , Fellows of the Royal Society Author ( s ): Howard Gest Source : Notes and Records of the Royal Society of London , Vol . 58 , No . 2 ( May , 2004 ), pp . 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Pasteur, who lives 100 years after was the first to describe anaerobic bacteria ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1098/rsnr.2004.0055", "author" : [ { "dropping-particle" : "", "family" : "Society", "given" : "Royal", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issue" : "2", "issued" : { "date-parts" : [ [ "2016" ] ] }, "page" : "187-201", "title" : "The Discovery of Microorganisms by Robert Hooke and Antoni van Leeuwenhoek , Fellows of the Royal Society Author ( s ): Howard Gest Source : Notes and Records of the Royal Society of London , Vol . 58 , No . 2 ( May , 2004 ), pp . 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The human body has its one microbiome, such as others animals, being a resident for microorganisms and their metabolic functions for at least 500 million years ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1038/nrg3182", "ISBN" : "1471-0064 (Electronic)\\n1471-0056 (Linking)", "ISSN" : "1471-0064", "PMID" : "22411464", "abstract" : "Interest in the role of the microbiome in human health has burgeoned over the past decade with the advent of new technologies for interrogating complex microbial communities. The large-scale dynamics of the microbiome can be described by many of the tools and observations used in the study of population ecology. Deciphering the metagenome and its aggregate genetic information can also be used to understand the functional properties of the microbial community. 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This microbial counterpart has an active participation in several host function, such as defense, metabolism, and reproduction ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1038/nrg3182", "ISBN" : "1471-0064 (Electronic)\\n1471-0056 (Linking)", "ISSN" : "1471-0064", "PMID" : "22411464", "abstract" : "Interest in the role of the microbiome in human health has burgeoned over the past decade with the advent of new technologies for interrogating complex microbial communities. The large-scale dynamics of the microbiome can be described by many of the tools and observations used in the study of population ecology. Deciphering the metagenome and its aggregate genetic information can also be used to understand the functional properties of the microbial community. 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Although external and stochastic factors clearly contribute to the individuality of the microbiota, the fundamental principles dictating how environmental factors and host genetic factors combine to shape this complex ecosystem are largely unknown and require systematic study. Here we examined factors that affect microbiota composition in a large (n = 645) mouse advanced intercross line originating from a cross between C57BL/6J and an ICR-derived outbred line (HR). Quantitative pyrosequencing of the microbiota defined a core measurable microbiota (CMM) of 64 conserved taxonomic groups that varied quantitatively across most animals in the population. Although some of this variation can be explained by litter and cohort effects, individual host genotype had a measurable contribution. Testing of the CMM abundances for cosegregation with 530 fully informative SNP markers identified 18 host quantitative trait loci (QTL) that show significant or suggestive genome-wide linkage with relative abundances of specific microbial taxa. These QTL affect microbiota composition in three ways; some loci control individual microbial species, some control groups of related taxa, and some have putative pleiotropic effects on groups of distantly related organisms. These data provide clear evidence for the importance of host genetic control in shaping individual microbiome diversity in mammals, a key step toward understanding the factors that govern the assemblages of gut microbiota associated with complex diseases.", "author" : [ { "dropping-particle" : "", "family" : "Benson", "given" : "Andrew K", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kelly", "given" : "Scott a", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Legge", "given" : "Ryan", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Ma", "given" : "Fangrui", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Low", "given" : "Soo Jen", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kim", "given" : "Jaehyoung", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Zhang", "given" : "Min", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Oh", "given" : "Phaik Lyn", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Nehrenberg", "given" : "Derrick", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Hua", "given" : "Kunjie", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kachman", "given" : "Stephen D", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Moriyama", "given" : "Etsuko N", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Walter", "given" : "Jens", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Peterson", "given" : "Daniel a", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Pomp", "given" : "Daniel", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Proceedings of the National Academy of Sciences of the United States of America", "id" : "ITEM-2", "issue" : "44", "issued" : { "date-parts" : [ [ "2010" ] ] }, "page" : "18933-18938", "title" : "Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors.", "type" : "article-journal", "volume" : "107" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Cho & Blaser 2012; Benson et al. 2010)", "plainTextFormattedCitation" : "(Cho & Blaser 2012; Benson et al. 2010)", "previouslyFormattedCitation" : "(Cho & Blaser 2012; Benson et al. 2010)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Cho & Blaser 2012; Benson et al. 2010). Existing theories postulate that the specific actual microbiome in the human body is the result of natural selection based on co-adaptation mechanism ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1038/nrg3182", "ISBN" : "1471-0064 (Electronic)\\n1471-0056 (Linking)", "ISSN" : "1471-0064", "PMID" : "22411464", "abstract" : "Interest in the role of the microbiome in human health has burgeoned over the past decade with the advent of new technologies for interrogating complex microbial communities. The large-scale dynamics of the microbiome can be described by many of the tools and observations used in the study of population ecology. Deciphering the metagenome and its aggregate genetic information can also be used to understand the functional properties of the microbial community. 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Undoubtedly, the microbiome contributes to the human struggle against diverse society’s challenges ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Leroy Hood", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Science", "id" : "ITEM-1", "issue" : "June", "issued" : { "date-parts" : [ [ "2012" ] ] }, "page" : "1225475", "title" : "Tackling the Microbiome", "type" : "article-journal", "volume" : "336" }, "uris" : [ "", "" ] } ], "mendeley" : { "formattedCitation" : "(Leroy Hood 2012)", "plainTextFormattedCitation" : "(Leroy Hood 2012)", "previouslyFormattedCitation" : "(Anon 2012)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Leroy Hood 2012). The microbiome influences both human health and well-being in several ways. Bacterial cells are ten times more numerous than human cells (Qin et al., 2010ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Leroy Hood", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Science", "id" : "ITEM-1", "issue" : "June", "issued" : { "date-parts" : [ [ "2012" ] ] }, "page" : "1225475", "title" : "Tackling the Microbiome", "type" : "article-journal", "volume" : "336" }, "uris" : [ "", "" ] } ], "mendeley" : { "formattedCitation" : "(Leroy Hood 2012)", "manualFormatting" : "; Anon 2012)", "plainTextFormattedCitation" : "(Leroy Hood 2012)", "previouslyFormattedCitation" : "(Anon 2012)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }; Anon 2012), microorganisms produce multiple active molecules present in the human bloodstream (Hood, 2012), for example 36% of these molecules are produced by the gut microbiome ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "author" : [ { "dropping-particle" : "", "family" : "Leroy Hood", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Science", "id" : "ITEM-1", "issue" : "June", "issued" : { "date-parts" : [ [ "2012" ] ] }, "page" : "1225475", "title" : "Tackling the Microbiome", "type" : "article-journal", "volume" : "336" }, "uris" : [ "", "" ] } ], "mendeley" : { "formattedCitation" : "(Leroy Hood 2012)", "plainTextFormattedCitation" : "(Leroy Hood 2012)", "previouslyFormattedCitation" : "(Anon 2012)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Leroy Hood 2012). Also, concerning the genes, the ratio is from 130 microbial genes to one human gene, in a healthy human. Moreover, these microorganisms act as a source of both pathogen protection (Vaarala, 2012) and hazards (Markle et al., 2013). Despite essential to human health, is not clear how the microbiome influences human health. 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In 1980, Robert Koch, postulate that bacteria are present in all cases of the disease. To prove this assumption, bacteria were extracted for the host, grown in pure culture, re-introduced in a healthy host, and finally recovered from the infected host. However, now like in the past, this postulate has some limitations. For example, some bacteria cannot be grown in pure culture, and some human disease do not have a similar “model” in animals. In other words, in animals the same bacteria do not have the same impact, do not cause the same disease or any disease ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1098/rspb.1998.0336", "ISBN" : "1098-6618", "ISSN" : "08938512", "PMID" : "8665474", "author" : [ { "dropping-particle" : "", "family" : "Fredericks", "given" : "D N", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Relman", "given" : "D a", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Clin Microbiol Rev", "id" : "ITEM-1", "issue" : "1", "issued" : { "date-parts" : [ [ "1996" ] ] }, "page" : "18-33", "title" : "Sequence-based identification of microbial pathogens : a reconsideration of Koch ' s Sequence-Based Identification of Microbial Pathogens : a Reconsideration of Koch \u2019 s Postulates", "type" : "article-journal", "volume" : "9" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Fredericks & Relman 1996)", "plainTextFormattedCitation" : "(Fredericks & Relman 1996)", "previouslyFormattedCitation" : "(Fredericks & Relman 1996)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Fredericks & Relman 1996). Therefore, is important to understand how bacteria cause diseases. Bacteria can be infected by virus or can gain access to a deep tissue and then cause a disease. In immunocompromised patients, harmless bacteria may cause diseases. In other cases, the same bacteria may cause a disease in a healthy human, but not in an another healthy human. Bearing these principals in mind, it makes more sense that community characteristics may be more relevant that one single bacteria cause a disease. However, a long way is still needed to understand the mechanism associated with pathogen-host interactions ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1038/nrg3182", "ISBN" : "1471-0064 (Electronic)\\n1471-0056 (Linking)", "ISSN" : "1471-0064", "PMID" : "22411464", "abstract" : "Interest in the role of the microbiome in human health has burgeoned over the past decade with the advent of new technologies for interrogating complex microbial communities. 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Being important the application of new tools to improve the knowledge of this relation ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1038/nrg3182", "ISBN" : "1471-0064 (Electronic)\\n1471-0056 (Linking)", "ISSN" : "1471-0064", "PMID" : "22411464", "abstract" : "Interest in the role of the microbiome in human health has burgeoned over the past decade with the advent of new technologies for interrogating complex microbial communities. The large-scale dynamics of the microbiome can be described by many of the tools and observations used in the study of population ecology. Deciphering the metagenome and its aggregate genetic information can also be used to understand the functional properties of the microbial community. 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As such, microorganisms profoundly influence human health. In environments where the people are in direct contact with each other and can circulate among different environments, in a short space, such as cities, the impact of microorganisms in a human health can be facilitated (Afshinnekoo et al., 2015).Although the human microbiome, has been highly studied, with the HMP project, the same does not apply for the city’s microbiome (indoor air), at least in large-scale studies (Afshinnekoo et al., 2015; Peterson et al., 2009). The characterization of this microbiome is important once, people in modern societies, especially in cities, spend more the 90% of their time indoors. 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Every day and worldwide, millions of people use this public transport system, allowing the interaction between commuters and between commuters and subway surfaces. Nonetheless, little is known about microbiome characteristics of this public transport system, and the impact of the surface type, season, commuter type, or subway design on their commute in the microbiome characteristics. However, the effect of the architecture, specifically, indoor ventilation, has been demonstrated in previous studies play roles in shaping the indoor microbiome ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/AEM.02244-14", "ISSN" : "10985336", "PMID" : "25172855", "abstract" : "Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. 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This indoor ventilation, due to the architecture of the subway, been mainly an underground transportation, is very present. Microbial DNA studies show too, that the indoor microbiome is influenced by their human occupants ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/mSystems.00018-16", "ISSN" : "2379-5077", "abstract" : "Public transit systems are ideal for studying the urban microbiome and interindividual community transfer. In this study, we used 16S amplicon and shotgun metagenomic sequencing to profile microbial communities on multiple transit surfaces across train lines and stations in the Boston metropolitan transit system. The greatest determinant of microbial community structure was the transit surface type. In contrast, little variation was observed between geographically distinct train lines and stations serving different demographics. All surfaces were dominated by human skin and oral commensals such as Propionibacterium, Corynebacterium, Staphylococcus, and Streptococcus. The detected taxa not associated with humans included generalists from alphaproteobacteria, which were especially abundant on outdoor touchscreens. Shotgun metagenomics further identified viral and eukaryotic microbes, including Propionibacterium phage and Malassezia globosa. Functional profiling showed that Propionibacterium acnes pathways such as propionate production and porphyrin synthesis were enriched on train holding surfaces (holds), while electron transport chain components for aerobic respiration were enriched on touchscreens and seats. Lastly, the transit environment was not found to be a reservoir of antimicrobial resistance and virulence genes. Our results suggest that microbial communities on transit surfaces are maintained from a metapopulation of human skin commensals and environmental generalists, with enrichments corresponding to local interactions with the human body and environmental exposures.IMPORTANCE Mass transit environments, specifically, urban subways, are distinct microbial environments with high occupant densities, diversities, and turnovers, and they are thus especially relevant to public health. Despite this, only three culture-independent subway studies have been performed, all since 2013 and all with widely differing designs and conclusions. In this study, we profiled the Boston subway system, which provides 238 million trips per year overseen by the Massachusetts Bay Transportation Authority (MBTA). This yielded the first high-precision microbial survey of a variety of surfaces, ridership environments, and microbiological functions (including tests for potential pathogenicity) in a mass transit environment. Characterizing microbial profiles for multiple transit systems will become increasingly important for biosurveillance of antibiotic resistance genes or \u2026", "author" : [ { "dropping-particle" : "", "family" : "Hsu", "given" : "Tiffany", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Joice", "given" : "Regina", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Vallarino", "given" : "Jose", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Abu-Ali", "given" : "Galeb", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Hartmann", "given" : "Erica M", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Shafquat", "given" : "Afrah", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "DuLong", "given" : "Casey", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Baranowski", "given" : "Catherine", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Gevers", "given" : "Dirk", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Green", "given" : "Jessica L", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Morgan", "given" : "Xochitl C", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Spengler", "given" : "John D", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Huttenhower", "given" : "Curtis", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "mySystems", "id" : "ITEM-1", "issue" : "3", "issued" : { "date-parts" : [ [ "2016" ] ] }, "page" : "1-18", "title" : "Urban Transit System Microbial Communities Differ by Surface Type and Interaction with Humans and the Environment", "type" : "article-journal", "volume" : "1" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Hsu et al. 2016)", "plainTextFormattedCitation" : "(Hsu et al. 2016)", "previouslyFormattedCitation" : "(Hsu et al. 2016)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Hsu et al. 2016).Previous studies investigated the microbial composition in the subway and other indoor areas. However, some limitations in the methodologies used underestimated the diversity of microbial exposure for the commuters ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/AEM.02244-14", "ISSN" : "10985336", "PMID" : "25172855", "abstract" : "Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on \u03b1- and \u03b2-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. 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This studies primarily focused on culture-dependent techniques (viable counts of bacteria and fungi and with the biochemical or molecular identification of cultures) ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/AEM.00331-13", "ISBN" : "1098-5336 (Electronic)\\n0099-2240 (Linking)", "ISSN" : "00992240", "PMID" : "23542619", "abstract" : "The goal of this study was to determine the composition and diversity of microorganisms associated with bioaerosols in a heavily trafficked metropolitan subway environment. We collected bioaerosols by fluid impingement on several New York City subway platforms and associated sites in three sampling sessions over a 1.5-year period. The types and quantities of aerosolized microorganisms were determined by culture-independent phylogenetic analysis of small-subunit rRNA gene sequences by using both Sanger (universal) and pyrosequencing (bacterial) technologies. Overall, the subway bacterial composition was relatively simple; only 26 taxonomic families made up ~75% of the sequences determined. The microbiology was more or less similar throughout the system and with time and was most similar to outdoor air, consistent with highly efficient air mixing in the system. Identifiable bacterial sequences indicated that the subway aerosol assemblage was composed of a mixture of genera and species characteristic of soil, environmental water, and human skin commensal bacteria. Eukaryotic diversity was mainly fungal, dominated by organisms of types associated with wood rot. Human skin bacterial species (at 99% rRNA sequence identity) included the Staphylococcus spp. Staphylococcus epidermidis (the most abundant and prevalent commensal of the human integument), S. hominis, S. cohnii, S. caprae, and S. haemolyticus, all well-documented human commensal bacteria. We encountered no organisms of public health concern. This study is the most extensive culture-independent survey of subway microbiota so far and puts in place pre-event information required for any bioterrorism surveillance activities or monitoring of the microbiological impact of recent subway flooding events.", "author" : [ { "dropping-particle" : "", "family" : "Robertson", "given" : "Charles E.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Baumgartner", "given" : "Laura K.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Harris", "given" : "J. 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Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on \u03b1- and \u03b2-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. This Hong Kong data set and communities from previous studies conducted in the United States formed distinct community clusters, indicating that additional work is required to unravel the mechanisms that shape subway microbiomes around the globe.", "author" : [ { "dropping-particle" : "", "family" : "Leung", "given" : "Marcus H Y", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wilkins", "given" : "David", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Li", "given" : "Ellen K T", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kong", "given" : "Fred K F", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Lee", "given" : "Patrick K H", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Applied and Environmental Microbiology", "id" : "ITEM-2", "issue" : "21", "issued" : { "date-parts" : [ [ "2014" ] ] }, "page" : "6760-6770", "title" : "Indoor-air microbiome in an urban subway network: Diversity and dynamics", "type" : "article-journal", "volume" : "80" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Robertson et al. 2013; Leung et al. 2014)", "plainTextFormattedCitation" : "(Robertson et al. 2013; Leung et al. 2014)", "previouslyFormattedCitation" : "(Robertson et al. 2013; Leung et al. 2014)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Robertson et al. 2013; Leung et al. 2014). Using culture-dependent techniques, only a small fraction of microorganism can be grown and identified, bringing a reduced perspective of the microbial diversity found in subway air ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/AEM.00331-13", "ISBN" : "1098-5336 (Electronic)\\n0099-2240 (Linking)", "ISSN" : "00992240", "PMID" : "23542619", "abstract" : "The goal of this study was to determine the composition and diversity of microorganisms associated with bioaerosols in a heavily trafficked metropolitan subway environment. We collected bioaerosols by fluid impingement on several New York City subway platforms and associated sites in three sampling sessions over a 1.5-year period. The types and quantities of aerosolized microorganisms were determined by culture-independent phylogenetic analysis of small-subunit rRNA gene sequences by using both Sanger (universal) and pyrosequencing (bacterial) technologies. Overall, the subway bacterial composition was relatively simple; only 26 taxonomic families made up ~75% of the sequences determined. The microbiology was more or less similar throughout the system and with time and was most similar to outdoor air, consistent with highly efficient air mixing in the system. Identifiable bacterial sequences indicated that the subway aerosol assemblage was composed of a mixture of genera and species characteristic of soil, environmental water, and human skin commensal bacteria. Eukaryotic diversity was mainly fungal, dominated by organisms of types associated with wood rot. Human skin bacterial species (at 99% rRNA sequence identity) included the Staphylococcus spp. Staphylococcus epidermidis (the most abundant and prevalent commensal of the human integument), S. hominis, S. cohnii, S. caprae, and S. haemolyticus, all well-documented human commensal bacteria. We encountered no organisms of public health concern. This study is the most extensive culture-independent survey of subway microbiota so far and puts in place pre-event information required for any bioterrorism surveillance activities or monitoring of the microbiological impact of recent subway flooding events.", "author" : [ { "dropping-particle" : "", "family" : "Robertson", "given" : "Charles E.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Baumgartner", "given" : "Laura K.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Harris", "given" : "J. 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Using the conventional microbiological methods (culture-dependent) is impossible to determine the diversity of the microorganisms in a sample. Many factors, like fungal and bacterial viability, the use of the inappropriate growing medium, the final concentration of the microorganism in the sample makes the use of conventional methods rather limited (Leung et al. 2014).The challenge to disclosure the majority of the organisms increase the interest and outset the improvement of the technical capacities for metagenomics surveys of aerosol environments. ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1007/s00248-014-0517-z", "author" : [ { "dropping-particle" : "", "family" : "Be", "given" : "Nicholas A", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Thissen", "given" : "James B", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Fofanov", "given" : "Viacheslav Y", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Allen", "given" : "Jonathan E", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Rojas", "given" : "Mark", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Golovko", "given" : "George", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Fofanov", "given" : "Yuriy", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Koshinsky", "given" : "Heather", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Jaing", "given" : "Crystal J", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2015" ] ] }, "page" : "346-355", "title" : "Metagenomic Analysis of the Airborne Environment in Urban Spaces", "type" : "article-journal" }, "uris" : [ "", "" ] } ], "mendeley" : { "formattedCitation" : "(Be et al. 2015)", "plainTextFormattedCitation" : "(Be et al. 2015)", "previouslyFormattedCitation" : "(Be et al. 2015)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Be et al. 2015). The advent of Next Generation Sequencing (NGS; culture-independent) brought the possibility of profiling entire microbial communities from complex samples, uncovering new organisms, and following the dynamic nature of microbial populations under changing conditions. Being a constant scientific effort and frequently reviewed since its first application in 2002, the NGS has been used in virus discovery in basic and applied research, being without surprise its increasing application as a diagnostic tools ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.3389/fmicb.2015.00224", "ISSN" : "1664302X", "PMID" : "25859244", "abstract" : "Powered by recent advances in next-generation sequencing technologies, metagenomics has already unveiled vast microbial biodiversity in a range of environments, and is increasingly being applied in clinics for difficult-to-diagnose cases. It can be tempting to suggest that metagenomics could be used as a \"universal test\" for all pathogens without the need to conduct lengthy serial testing using specific assays. While this is an exciting prospect, there are issues that need to be addressed before metagenomic methods can be applied with rigor as a diagnostic tool, including the potential for incidental findings, unforeseen consequences for trade and regulatory authorities, privacy and cultural issues, data sharing, and appropriate reporting of results to end-users. These issues will require consideration and discussion across a range of disciplines, with inclusion of scientists, ethicists, clinicians, diagnosticians, health practitioners, and ultimately the public. Here, we provide a primer for consideration on some of these issues.", "author" : [ { "dropping-particle" : "", "family" : "Hall", "given" : "Richard J.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Draper", "given" : "Jenny L.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Nielsen", "given" : "Fiona G G", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Dutilh", "given" : "Bas E.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Frontiers in Microbiology", "id" : "ITEM-1", "issue" : "MAR", "issued" : { "date-parts" : [ [ "2015" ] ] }, "page" : "1-8", "title" : "Beyond research: A primer for considerations on using viral metagenomics in the field and clinic", "type" : "article-journal", "volume" : "6" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Hall et al. 2015)", "plainTextFormattedCitation" : "(Hall et al. 2015)", "previouslyFormattedCitation" : "(Hall et al. 2015)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Hall et al. 2015). The potential diagnostic applications of viral metagenomics extend to other areas of expertise ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.3389/fmicb.2015.00224", "ISSN" : "1664302X", "PMID" : "25859244", "abstract" : "Powered by recent advances in next-generation sequencing technologies, metagenomics has already unveiled vast microbial biodiversity in a range of environments, and is increasingly being applied in clinics for difficult-to-diagnose cases. It can be tempting to suggest that metagenomics could be used as a \"universal test\" for all pathogens without the need to conduct lengthy serial testing using specific assays. While this is an exciting prospect, there are issues that need to be addressed before metagenomic methods can be applied with rigor as a diagnostic tool, including the potential for incidental findings, unforeseen consequences for trade and regulatory authorities, privacy and cultural issues, data sharing, and appropriate reporting of results to end-users. These issues will require consideration and discussion across a range of disciplines, with inclusion of scientists, ethicists, clinicians, diagnosticians, health practitioners, and ultimately the public. 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With rapid and accurate detection, preventive measures can be put in place early, thereby preventing loss of life and further spread of a disease. From a preparedness perspective, early detection and response are important in order to minimize the consequences. During the past 2 decades, advances in next-generation sequencing (NGS) technology have changed the playing field of molecular methods. Today, it is within reach to completely sequence the total microbiological content of a clinical sample, creating a metagenome, in a single week of laboratory work. As new technologies emerge, their dissemination and capacity building must be facilitated, and criteria for use, as well as guidelines on how to report results, must be established. This article focuses on the use of metagenomics, from sample collection to data analysis and to some extent NGS, for the detection of pathogens, the integration of the technique in outbreak response systems, and the risk-based evaluation of sample processing in routine diagnostics labs. The article covers recent advances in the field, current debate, gaps in research, and future directions. Examples of metagenomic detection, as well as possible applications of the methods, are described in various biopreparedness outbreak scenarios.", "author" : [ { "dropping-particle" : "", "family" : "Karlsson", "given" : "Oskar Erik", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Hansen", "given" : "Trine", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Knutsson", "given" : "Rickard", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "L\u00f6fstr\u00f6m", "given" : "Charlotta", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Granberg", "given" : "Fredrik", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Berg", "given" : "Mikael", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Biosecurity and bioterrorism : biodefense strategy, practice, and science", "id" : "ITEM-2", "issued" : { "date-parts" : [ [ "2013" ] ] }, "page" : "S146-57", "title" : "Metagenomic detection methods in biopreparedness outbreak scenarios.", "type" : "article-journal", "volume" : "11 Suppl 1" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Hall et al. 2015; Karlsson et al. 2013)", "plainTextFormattedCitation" : "(Hall et al. 2015; Karlsson et al. 2013)", "previouslyFormattedCitation" : "(Hall et al. 2015; Karlsson et al. 2013)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Hall et al. 2015; Karlsson et al. 2013). Therefore, this tool has been applied in forensics ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.3389/fmicb.2015.00224", "ISSN" : "1664302X", "PMID" : "25859244", "abstract" : "Powered by recent advances in next-generation sequencing technologies, metagenomics has already unveiled vast microbial biodiversity in a range of environments, and is increasingly being applied in clinics for difficult-to-diagnose cases. It can be tempting to suggest that metagenomics could be used as a \"universal test\" for all pathogens without the need to conduct lengthy serial testing using specific assays. While this is an exciting prospect, there are issues that need to be addressed before metagenomic methods can be applied with rigor as a diagnostic tool, including the potential for incidental findings, unforeseen consequences for trade and regulatory authorities, privacy and cultural issues, data sharing, and appropriate reporting of results to end-users. 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A metagenomics analysis of purified viral particles in untreated sewage from the United States (San Francisco, CA), Nigeria (Maiduguri), Thailand (Bangkok), and Nepal (Kathmandu) revealed sequences related to 29 eukaryotic viral families infecting vertebrates, invertebrates, and plants (BLASTx E score, <10\u22124), including known pathogens (>90% protein identities) in numerous viral families infecting humans (Adenoviridae, Astroviridae, Caliciviridae, Hepeviridae, Parvoviridae, Picornaviridae, Picobirnaviridae, and Reoviridae), plants (Alphaflexiviridae, Betaflexiviridae, Partitiviridae, Sobemovirus, Secoviridae, Tombusviridae, Tymoviridae, Virgaviridae), and insects (Dicistroviridae, Nodaviridae, and Parvoviridae). The full and partial genomes of a novel kobuvirus, salivirus, and sapovirus are described. A novel astrovirus (casa astrovirus) basal to those infecting mammals and birds, potentially representing a third astrovirus genus, was partially characterized. Potential new genera and families of viruses distantly related to members of the single-stranded RNA picorna-like virus superfamily were genetically characterized and named Picalivirus, Secalivirus, Hepelivirus, Nedicistrovirus, Cadicistrovirus, and Niflavirus. Phylogenetic analysis placed these highly divergent genomes near the root of the picorna-like virus superfamily, with possible vertebrate, plant, or arthropod hosts inferred from nucleotide composition analysis. Circular DNA genomes distantly related to the plant-infecting Geminiviridae family were named Baminivirus, Nimivirus, and Niminivirus. These results highlight the utility of analyzing sewage to monitor shedding of viral pathogens and the high viral diversity found in this common pollutant and provide genetic information to facilitate future studies of these newly characterized viruses.", "author" : [ { "dropping-particle" : "", "family" : "Ng", "given" : "Terry Fei Fan", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Marine", "given" : "Rachel", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wang", "given" : "Chunlin", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Simmonds", "given" : "Peter", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kapusinszky", "given" : "Beatrix", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Bodhidatta", "given" : "Ladaporn", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Oderinde", "given" : "Bamidele Soji", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wommack", "given" : "K Eric", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Delwart", "given" : "Eric", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Journal of Virology", "id" : "ITEM-2", "issue" : "22", "issued" : { "date-parts" : [ [ "2012" ] ] }, "page" : "12161-12175", "title" : "High Variety of Known and New RNA and DNA Viruses of Diverse Origins in Untreated Sewage", "type" : "article-journal", "volume" : "86" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Hall et al. 2015; Ng et al. 2012)", "plainTextFormattedCitation" : "(Hall et al. 2015; Ng et al. 2012)", "previouslyFormattedCitation" : "(Hall et al. 2015; Ng et al. 2012)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Hall et al. 2015; Ng et al. 2012).The NGS, a non-Sanger-based sequencing technology ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1038/NMETH1156", "author" : [ { "dropping-particle" : "", "family" : "Schuster", "given" : "Stephan C", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issue" : "1", "issued" : { "date-parts" : [ [ "2008" ] ] }, "page" : "16-18", "title" : "Next-generation sequencing transforms today \u2019 s biology", "type" : "article-journal", "volume" : "5" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Schuster 2008)", "plainTextFormattedCitation" : "(Schuster 2008)", "previouslyFormattedCitation" : "(Schuster 2008)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Schuster 2008), allows processing millions of sequences in a single run, rather than 96 sequences per run, being only necessary to complete the samples processing in one or two instruments ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1016/j.tig.2007.12.007", "author" : [ { "dropping-particle" : "", "family" : "Mardis", "given" : "Elaine R", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Cell Press", "id" : "ITEM-1", "issue" : "February", "issued" : { "date-parts" : [ [ "2008" ] ] }, "page" : "133-141", "title" : "The impact of next-generation sequencing technology on genetics", "type" : "article-journal" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Mardis 2008)", "plainTextFormattedCitation" : "(Mardis 2008)", "previouslyFormattedCitation" : "(Mardis 2008)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Mardis 2008). Also, some of the cloning bias issues are avoided, once NGS do not use the “libraries” that have been subject to a conventional vector-based cloning and Escherichia coli – based amplification stages associated with capillary sequencing. 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Such technique permits a better understanding of the microbial community and its dynamics throughout time and space. However, with the development of NGS, a high diversity of microorganism was found in several environments, such as the case of subways. However, this high diversity brings the alarming situation of new strains of microorganism that are known to be resistant to antimicrobial agents. 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This is a public health concern due to the increase of worldwide infections. 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Mol. Biol.", "id" : "ITEM-3", "issued" : { "date-parts" : [ [ "1970" ] ] }, "page" : "267-286", "title" : "Chromosomal Location of Antibiotic Resistance Markers in Bacillus subtilis", "type" : "article-journal", "volume" : "51" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Aspevall et al. 2015; Singer et al. 1989; Sueoka 1970)", "plainTextFormattedCitation" : "(Aspevall et al. 2015; Singer et al. 1989; Sueoka 1970)", "previouslyFormattedCitation" : "(Aspevall et al. 2015; Singer et al. 1989; Sueoka 1970)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Aspevall et al. 2015; Singer et al. 1989; Sueoka 1970). Additionally, in some geographic areas, surveillance programs to monitoring the microorganism resistance to antimicrobial have been created. 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In a general view, these programs intend to prevent worldwide infections and to prevent and control the possible mutations in some strains that they are known for cause disease in human or bining the studies on genomes with the advance of the computational tools, was possible to identify biosynthetic gene clusters (BGC). These are physically clustered group of two or more genes that encode for a biosynthetic pathway to produce a specific metabolite. Nowadays, is possible systematically explore and prioritize the BGC for experimental characterization ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1038/nchembio.1890", "ISBN" : "1552-4469 (Electronic)\\r1552-4450 (Linking)", "ISSN" : "1552-4450", "PMID" : "26284661", "abstract" : "A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. 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However, not all biosynthetic genes are encoded in the producer’s genomes, making that in the laboratory conditions they are often not expressed. Techniques are now available to successfully activate “silent” gene clusters. These techniques allow optimizing production yields and manipulate biosynthesis pathways ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1007/s10295-015-1685-7", "ISBN" : "1029501516857", "ISSN" : "14765535", "PMID" : "26433383", "abstract" : "Streptomycetes are prolific sources of novel biologically active secondary metabolites with pharmaceutical potential. S. collinus T\u00fc 365 is a Streptomyces strain, isolated 1972 from Kouroussa (Guinea). It is best known as producer of the antibiotic kirromycin, an inhibitor of the protein biosynthesis interacting with elongation factor EF-Tu. 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While industrial efforts to find and develop novel antimicrobials have been severely reduced during the past two decades, the increasing threat of multidrug-resistant pathogens and the development of new technologies to find and produce such compounds have again attracted interest in this field. Based on improvements in whole-genome sequencing, novel methods have been developed to identify the secondary metabolite biosynthetic gene clusters by genome mining, to clone them, and to express them in heterologous hosts in much higher throughput than before. 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One of the techniques to activated the pathways in the native host strains is to resort to the insertion of the additional promoters upstream of the biosynthesis genes. The biosynthetic genes can be independently regulated or constitutively expressed. The expression of the gene clusters in a heterologous host can lead to expression and biosynthesis of the new products. These products can represent a promising alternative for activation of secondary metabolite gene clusters presents in harmful strains ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1007/s10295-015-1685-7", "ISBN" : "1029501516857", "ISSN" : "14765535", "PMID" : "26433383", "abstract" : "Streptomycetes are prolific sources of novel biologically active secondary metabolites with pharmaceutical potential. S. collinus T\u00fc 365 is a Streptomyces strain, isolated 1972 from Kouroussa (Guinea). 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This synthetic biology allows the redesign of BGCs for effective heterologous expression in pre-engineered hosts. This will finally allow the construction of the standardized high-throughput platforms for natural product discovery ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1038/nchembio.1890", "ISBN" : "1552-4469 (Electronic)\\r1552-4450 (Linking)", "ISSN" : "1552-4450", "PMID" : "26284661", "abstract" : "A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard. \u00a9 2015 Nature America, Inc. 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"parse-names" : false, "suffix" : "" } ], "container-title" : "Nature Chemical Biology", "id" : "ITEM-1", "issue" : "9", "issued" : { "date-parts" : [ [ "2015" ] ] }, "page" : "625-631", "title" : "Minimum Information about a Biosynthetic Gene cluster", "type" : "article-journal", "volume" : "11" }, "uris" : [ "" ] }, { "id" : "ITEM-2", "itemData" : { "DOI" : "10.1073/pnas.1319584111", "ISBN" : "1091-6490 (Electronic)\\r0027-8424 (Linking)", "ISSN" : "1091-6490", "PMID" : "24449899", "abstract" : "Recent developments in next-generation sequencing technologies have brought recognition of microbial genomes as a rich resource for novel natural product discovery. However, owing to the scarcity of efficient procedures to connect genes to molecules, only a small fraction of secondary metabolomes have been investigated to date. Transformation-associated recombination (TAR) cloning takes advantage of the natural in vivo homologous recombination of Saccharomyces cerevisiae to directly capture large genomic loci. Here we report a TAR-based genetic platform that allows us to directly clone, refactor, and heterologously express a silent biosynthetic pathway to yield a new antibiotic. With this method, which involves regulatory gene remodeling, we successfully expressed a 67-kb nonribosomal peptide synthetase biosynthetic gene cluster from the marine actinomycete Saccharomonospora sp. CNQ-490 and produced the dichlorinated lipopeptide antibiotic taromycin A in the model expression host Streptomyces coelicolor. The taromycin gene cluster (tar) is highly similar to the clinically approved antibiotic daptomycin from Streptomyces roseosporus, but has notable structural differences in three amino acid residues and the lipid side chain. With the activation of the tar gene cluster and production of taromycin A, this study highlights a unique \"plug-and-play\" approach to efficiently gaining access to orphan pathways that may open avenues for novel natural product discoveries and drug development.", "author" : [ { "dropping-particle" : "", "family" : "Yamanaka", "given" : "Kazuya", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Reynolds", "given" : "Kirk A", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kersten", "given" : "Roland D", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Ryan", "given" : "Katherine S", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Gonzalez", "given" : "David J", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Nizet", "given" : "Victor", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Dorrestein", "given" : "Pieter C", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Moore", "given" : "Bradley S", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Proceedings of the National Academy of Sciences of the United States of America", "id" : "ITEM-2", "issue" : "5", "issued" : { "date-parts" : [ [ "2014" ] ] }, "page" : "1957-62", "title" : "Direct cloning and refactoring of a silent lipopeptide biosynthetic gene cluster yields the antibiotic taromycin A.", "type" : "article-journal", "volume" : "111" }, "uris" : [ "" ] }, { "id" : "ITEM-3", "itemData" : { "DOI" : "10.1021/sb400058n", "ISBN" : "2161-5063", "ISSN" : "21615063", "PMID" : "23968564", "abstract" : "Natural products (secondary metabolites) are a rich source of compounds with important biological activities. Eliciting pathway expression is always challenging but extremely important in natural product discovery because an individual pathway is tightly controlled through a unique regulation mechanism and hence often remains silent under the routine culturing conditions. To overcome the drawbacks of the traditional approaches that lack general applicability, we developed a simple synthetic biology approach that decouples pathway expression from complex native regulations. Briefly, the entire silent biosynthetic pathway is refactored using a plug-and-play scaffold and a set of heterologous promoters that are functional in a heterologous host under the target culturing condition. Using this strategy, we successfully awakened the silent spectinabilin pathway from Streptomyces orinoci. This strategy bypasses the traditional laborious processes to elicit pathway expression and represents a new platform for discovering novel natural products.", "author" : [ { "dropping-particle" : "", "family" : "Shao", "given" : "Zengyi", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Rao", "given" : "Guodong", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Li", "given" : "Chun", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Abil", "given" : "Zhanar", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Luo", "given" : "Yunzi", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Zhao", "given" : "Huimin", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "ACS Synthetic Biology", "id" : "ITEM-3", "issue" : "11", "issued" : { "date-parts" : [ [ "2013" ] ] }, "page" : "662-669", "title" : "Refactoring the silent spectinabilin gene cluster using a plug-and-play scaffold", "type" : "article-journal", "volume" : "2" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Medema et al. 2015; Yamanaka et al. 2014; Shao et al. 2013)", "plainTextFormattedCitation" : "(Medema et al. 2015; Yamanaka et al. 2014; Shao et al. 2013)", "previouslyFormattedCitation" : "(Medema et al. 2015; Yamanaka et al. 2014; Shao et al. 2013)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Medema et al. 2015; Yamanaka et al. 2014; Shao et al. 2013). With the changes happening in the researched environment, there is an increasing need to access all the experimental and contextual data on characterized BGC’s for comparative analysis, for function prediction and for collecting building blocks for the design of novel biosynthetic pathways. Some projects are now being designed to assign the informatics platform to the information are more easily ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1038/nchembio.1890", "ISBN" : "1552-4469 (Electronic)\\r1552-4450 (Linking)", "ISSN" : "1552-4450", "PMID" : "26284661", "abstract" : "A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard. \u00a9 2015 Nature America, Inc. 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However, owing to the scarcity of efficient procedures to connect genes to molecules, only a small fraction of secondary metabolomes have been investigated to date. Transformation-associated recombination (TAR) cloning takes advantage of the natural in vivo homologous recombination of Saccharomyces cerevisiae to directly capture large genomic loci. Here we report a TAR-based genetic platform that allows us to directly clone, refactor, and heterologously express a silent biosynthetic pathway to yield a new antibiotic. With this method, which involves regulatory gene remodeling, we successfully expressed a 67-kb nonribosomal peptide synthetase biosynthetic gene cluster from the marine actinomycete Saccharomonospora sp. CNQ-490 and produced the dichlorinated lipopeptide antibiotic taromycin A in the model expression host Streptomyces coelicolor. The taromycin gene cluster (tar) is highly similar to the clinically approved antibiotic daptomycin from Streptomyces roseosporus, but has notable structural differences in three amino acid residues and the lipid side chain. 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Eliciting pathway expression is always challenging but extremely important in natural product discovery because an individual pathway is tightly controlled through a unique regulation mechanism and hence often remains silent under the routine culturing conditions. To overcome the drawbacks of the traditional approaches that lack general applicability, we developed a simple synthetic biology approach that decouples pathway expression from complex native regulations. Briefly, the entire silent biosynthetic pathway is refactored using a plug-and-play scaffold and a set of heterologous promoters that are functional in a heterologous host under the target culturing condition. Using this strategy, we successfully awakened the silent spectinabilin pathway from Streptomyces orinoci. This strategy bypasses the traditional laborious processes to elicit pathway expression and represents a new platform for discovering novel natural products.", "author" : [ { "dropping-particle" : "", "family" : "Shao", "given" : "Zengyi", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Rao", "given" : "Guodong", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Li", "given" : "Chun", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Abil", "given" : "Zhanar", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Luo", "given" : "Yunzi", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Zhao", "given" : "Huimin", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "ACS Synthetic Biology", "id" : "ITEM-3", "issue" : "11", "issued" : { "date-parts" : [ [ "2013" ] ] }, "page" : "662-669", "title" : "Refactoring the silent spectinabilin gene cluster using a plug-and-play scaffold", "type" : "article-journal", "volume" : "2" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Medema et al. 2015; Yamanaka et al. 2014; Shao et al. 2013)", "plainTextFormattedCitation" : "(Medema et al. 2015; Yamanaka et al. 2014; Shao et al. 2013)", "previouslyFormattedCitation" : "(Medema et al. 2015; Yamanaka et al. 2014; Shao et al. 2013)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Medema et al. 2015; Yamanaka et al. 2014; Shao et al. 2013).These novels markers, AMR and BGC’s, allow to discriminate and validate the small molecules encoded by these microorganism’s genomes and dynamically regulated transcriptomes ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1186/s40168-016-0168-z", "ISSN" : "2049-2618", "abstract" : "The Metagenomics and Metadesign of the Subways and Urban Biomes (MetaSUB) International Consortium is a novel, interdisciplinary initiative comprised of experts across many fields, including genomics, data analysis, engineering, public health, and architecture. The ultimate goal of the Met aSUB Consortium is to improve city utilization and planning through the detection, measurement, and design of metag enomics within urban environments. Although continual measures occur for temperature, air pressure, weather, and human activity, including lon gitudinal, cross-kingdom ecosystem dynamics can alter and improve the design of ci ties. The MetaSUB Consortium is aiding these efforts by developing and testing metagenomic methods and standards, including optimized methods for sample collection, DNA/ RNA isolation, taxa characterization, and data visualization. The data produced by the consortium can aid city planners, public health officials, and architectur al designers. In addition, the study wil l continue to lead to the discovery of new species, global maps of antimicrobial resistance (AMR) marker s, and novel biosynthetic gene clusters (BGCs). Finally, we note that engineered metagenomic ecosystems can help en able more responsive, safer , and quantified cities.", "author" : [ { "dropping-particle" : "", "family" : "The MetaSUB International Consortium", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Microbiome", "id" : "ITEM-1", "issue" : "4", "issued" : { "date-parts" : [ [ "2016" ] ] }, "page" : "1-14", "title" : "The Metagenomics and Metadesign of the Subways and Urban Biomes", "type" : "article-journal", "volume" : "24" }, "uris" : [ "" ] }, { "id" : "ITEM-2", "itemData" : { "DOI" : "10.1093/nar/gkr323", "ISBN" : "0305-1048", "ISSN" : "03051048", "PMID" : "21558170", "abstract" : "The products of many bacterial non-ribosomal peptide synthetases (NRPS) are highly important secondary metabolites, including vancomycin and other antibiotics. The ability to predict substrate specificity of newly detected NRPS Adenylation (A-) domains by genome sequencing efforts is of great importance to identify and annotate new gene clusters that produce secondary metabolites. Prediction of A-domain specificity based on the sequence alone can be achieved through sequence signatures or, more accurately, through machine learning methods. We present an improved predictor, based on previous work (NRPSpredictor), that predicts A-domain specificity using Support Vector Machines on four hierarchical levels, ranging from gross physicochemical properties of an A-domain's substrates down to single amino acid substrates. The three more general levels are predicted with an F-measure better than 0.89 and the most detailed level with an average F-measure of 0.80. We also modeled the applicability domain of our predictor to estimate for new A-domains whether they lie in the applicability domain. Finally, since there are also NRPS that play an important role in natural products chemistry of fungi, such as peptaibols and cephalosporins, we added a predictor for fungal A-domains, which predicts gross physicochemical properties with an F-measure of 0.84. The service is available at .", "author" : [ { "dropping-particle" : "", "family" : "R\u00f6ttig", "given" : "Marc", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Medema", "given" : "Marnix H.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Blin", "given" : "Kai", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Weber", "given" : "Tilmann", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Rausch", "given" : "Christian", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kohlbacher", "given" : "Oliver", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Nucleic Acids Research", "id" : "ITEM-2", "issue" : "SUPPL. 2", "issued" : { "date-parts" : [ [ "2011" ] ] }, "page" : "1-6", "title" : "NRPSpredictor2 - A web server for predicting NRPS adenylation domain specificity", "type" : "article-journal", "volume" : "39" }, "uris" : [ "" ] }, { "id" : "ITEM-3", "itemData" : { "DOI" : "10.1371/journal.pone.0062136", "ISSN" : "19326203", "PMID" : "23637983", "abstract" : "There is a growing interest in the Non-ribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs) of microbes, fungi and plants because they can produce bioactive peptides such as antibiotics. The ability to identify the substrate specificity of the enzyme's adenylation (A) and acyl-transferase (AT) domains is essential to rationally deduce or engineer new products. We here report on a Hidden Markov Model (HMM)-based ensemble method to predict the substrate specificity at high quality. We collected a new reference set of experimentally validated sequences. An initial classification based on alignment and Neighbor Joining was performed in line with most of the previously published prediction methods. We then created and tested single substrate specific HMMs and found that their use improved the correct identification significantly for A as well as for AT domains. A major advantage of the use of HMMs is that it abolishes the dependency on multiple sequence alignment and residue selection that is hampering the alignment-based clustering methods. Using our models we obtained a high prediction quality for the substrate specificity of the A domains similar to two recently published tools that make use of HMMs or Support Vector Machines (NRPSsp and NRPS predictor2, respectively). Moreover, replacement of the single substrate specific HMMs by ensembles of models caused a clear increase in prediction quality. We argue that the superiority of the ensemble over the single model is caused by the way substrate specificity evolves for the studied systems. It is likely that this also holds true for other protein domains. The ensemble predictor has been implemented in a simple web-based tool that is available at .", "author" : [ { "dropping-particle" : "", "family" : "Khayatt", "given" : "Barzan I.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Overmars", "given" : "Lex", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Siezen", "given" : "Roland J.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Francke", "given" : "Christof", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "PLoS ONE", "id" : "ITEM-3", "issue" : "4", "issued" : { "date-parts" : [ [ "2013" ] ] }, "title" : "Classification of the Adenylation and Acyl-Transferase Activity of NRPS and PKS Systems Using Ensembles of Substrate Specific Hidden Markov Models", "type" : "article-journal", "volume" : "8" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(The MetaSUB International Consortium 2016; R\u00f6ttig et al. 2011; Khayatt et al. 2013)", "plainTextFormattedCitation" : "(The MetaSUB International Consortium 2016; R\u00f6ttig et al. 2011; Khayatt et al. 2013)", "previouslyFormattedCitation" : "(The MetaSUB International Consortium 2016; R\u00f6ttig et al. 2011; Khayatt et al. 2013)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(The MetaSUB International Consortium 2016; R?ttig et al. 2011; Khayatt et al. 2013). Bacteria use these small molecules to mediate microbial competition, cooperation, environment sensing and adaptation. It has been hypothesized that identifying these small molecules produced by the bacteria, will reveal hidden traits of their adaptation, what to leave to their successful colonization of variegated surfaces and environments ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1186/s40168-016-0168-z", "ISSN" : "2049-2618", "abstract" : "The Metagenomics and Metadesign of the Subways and Urban Biomes (MetaSUB) International Consortium is a novel, interdisciplinary initiative comprised of experts across many fields, including genomics, data analysis, engineering, public health, and architecture. The ultimate goal of the Met aSUB Consortium is to improve city utilization and planning through the detection, measurement, and design of metag enomics within urban environments. Although continual measures occur for temperature, air pressure, weather, and human activity, including lon gitudinal, cross-kingdom ecosystem dynamics can alter and improve the design of ci ties. The MetaSUB Consortium is aiding these efforts by developing and testing metagenomic methods and standards, including optimized methods for sample collection, DNA/ RNA isolation, taxa characterization, and data visualization. The data produced by the consortium can aid city planners, public health officials, and architectur al designers. In addition, the study wil l continue to lead to the discovery of new species, global maps of antimicrobial resistance (AMR) marker s, and novel biosynthetic gene clusters (BGCs). Finally, we note that engineered metagenomic ecosystems can help en able more responsive, safer , and quantified cities.", "author" : [ { "dropping-particle" : "", "family" : "The MetaSUB International Consortium", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Microbiome", "id" : "ITEM-1", "issue" : "4", "issued" : { "date-parts" : [ [ "2016" ] ] }, "page" : "1-14", "title" : "The Metagenomics and Metadesign of the Subways and Urban Biomes", "type" : "article-journal", "volume" : "24" }, "uris" : [ "" ] }, { "id" : "ITEM-2", "itemData" : { "DOI" : "10.1007/s10295-013-1322-2", "ISBN" : "1476-5535 (Electronic)\\r1367-5435 (Linking)", "ISSN" : "13675435", "PMID" : "24104398", "abstract" : "Successful genome mining is dependent on accurate prediction of protein function from sequence. This often involves dividing protein families into functional subtypes (e.g., with different substrates). In many cases, there are only a small number of known functional subtypes, but in the case of the adenylation domains of nonribosomal peptide synthetases (NRPS), there are >500 known substrates. Latent semantic indexing (LSI) was originally developed for text processing but has also been used to assign proteins to families. Proteins are treated as ''documents'' and it is necessary to encode properties of the amino acid sequence as ''terms'' in order to construct a term-document matrix, which counts the terms in each document. This matrix is then processed to produce a document-concept matrix, where each protein is represented as a row vector. A standard measure of the closeness of vectors to each other (cosines of the angle between them) provides a measure of protein similarity. Previous work encoded proteins as oligopeptide terms, i.e. counted oligopeptides, but used no information regarding location of oligopeptides in the proteins. A novel tokenization method was developed to analyze information from multiple alignments. LSI successfully distinguished between two functional subtypes in five well-characterized families. Visualization of different ''concept'' dimensions allows exploration of the structure of protein families. LSI was also used to predict the amino acid substrate of adenylation domains of NRPS. Better results were obtained when selected residues from multiple alignments were used rather than the total sequence of the adenylation domains. Using ten residues from the substrate binding pocket performed better than using 34 residues within 8 \u00c5 of the active site. Prediction efficiency was somewhat better than that of the best published method using a support vector machine.", "author" : [ { "dropping-particle" : "", "family" : "Barana\u0161i\u0107", "given" : "Damir", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Zucko", "given" : "Jurica", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Diminic", "given" : "Janko", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Gacesa", "given" : "Ranko", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Long", "given" : "Paul F.", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Cullum", "given" : "John", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Hranueli", "given" : "Daslav", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Starcevic", "given" : "Antonio", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Journal of Industrial Microbiology and Biotechnology", "id" : "ITEM-2", "issue" : "2", "issued" : { "date-parts" : [ [ "2014" ] ] }, "page" : "461-467", "title" : "Predicting substrate specificity of adenylation domains of nonribosomal peptide synthetases and other protein properties by latent semantic indexing", "type" : "article-journal", "volume" : "41" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(The MetaSUB International Consortium 2016; Barana\u0161i\u0107 et al. 2014)", "plainTextFormattedCitation" : "(The MetaSUB International Consortium 2016; Barana\u0161i\u0107 et al. 2014)", "previouslyFormattedCitation" : "(The MetaSUB International Consortium 2016; Barana\u0161i\u0107 et al. 2014)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(The MetaSUB International Consortium 2016; Barana?i? et al. 2014).The news technologies available combined with the new scientific questions resulted in several publication concerning the microbiome composition, using the NGS, in metropolitan area either by studying the air and rodents ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/AEM.02244-14", "ISSN" : "10985336", "PMID" : "25172855", "abstract" : "Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on \u03b1- and \u03b2-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. This Hong Kong data set and communities from previous studies conducted in the United States formed distinct community clusters, indicating that additional work is required to unravel the mechanisms that shape subway microbiomes around the globe.", "author" : [ { "dropping-particle" : "", "family" : "Leung", "given" : "Marcus H Y", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wilkins", "given" : "David", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Li", "given" : "Ellen K T", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kong", "given" : "Fred K F", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Lee", "given" : "Patrick K H", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Applied and Environmental Microbiology", "id" : "ITEM-1", "issue" : "21", "issued" : { "date-parts" : [ [ "2014" ] ] }, "page" : "6760-6770", "title" : "Indoor-air microbiome in an urban subway network: Diversity and dynamics", "type" : "article-journal", "volume" : "80" }, "uris" : [ "" ] }, { "id" : "ITEM-2", "itemData" : { "DOI" : "10.1016/j.cels.2015.01.001", "ISBN" : "2405-4712", "ISSN" : "24054712", "PMID" : "26594662", "abstract" : "Summary The panoply of microorganisms and other species present in our environment influence human health and disease, especially in cities, but have not been profiled with metagenomics at a city-wide scale. We sequenced DNA from surfaces across the entire New York City (NYC) subway system, the Gowanus Canal, and public parks. Nearly half of the DNA (48%) does not match any known organism; identified organisms spanned 1,688 bacterial, viral, archaeal, and eukaryotic taxa, which were enriched for genera associated with skin (e.g., Acinetobacter). Predicted ancestry of human DNA left on subway surfaces can recapitulate U.S. Census demographic data, and bacterial signatures can match a station's history, such as marine-associated bacteria in a hurricane-flooded station. This baseline metagenomic map of NYC could help long-term disease surveillance, bioterrorism threat mitigation, and health management in the built environment of cities.", "author" : [ { "dropping-particle" : "", "family" : "Afshinnekoo", "given" : "Ebrahim", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Meydan", "given" : "Cem", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Chowdhury", "given" : "Shanin", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Jaroudi", "given" : "Dyala", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Boyer", "given" : "Collin", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Bernstein", "given" : "Nick", "non-dropping-particle" : "", "parse-names" : 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The Metagenomics and Metadesign of the Subways and Urban Biomes (MetaSUB) International Consortium, recently published data on the microbiome of New York, Boston Subway and Hong Kong Subways ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1186/s40168-016-0168-z", "ISSN" : "2049-2618", "abstract" : "The Metagenomics and Metadesign of the Subways and Urban Biomes (MetaSUB) International Consortium is a novel, interdisciplinary initiative comprised of experts across many fields, including genomics, data analysis, engineering, public health, and architecture. The ultimate goal of the Met aSUB Consortium is to improve city utilization and planning through the detection, measurement, and design of metag enomics within urban environments. Although continual measures occur for temperature, air pressure, weather, and human activity, including lon gitudinal, cross-kingdom ecosystem dynamics can alter and improve the design of ci ties. The MetaSUB Consortium is aiding these efforts by developing and testing metagenomic methods and standards, including optimized methods for sample collection, DNA/ RNA isolation, taxa characterization, and data visualization. The data produced by the consortium can aid city planners, public health officials, and architectur al designers. In addition, the study wil l continue to lead to the discovery of new species, global maps of antimicrobial resistance (AMR) marker s, and novel biosynthetic gene clusters (BGCs). 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The greatest determinant of microbial community structure was the transit surface type. In contrast, little variation was observed between geographically distinct train lines and stations serving different demographics. All surfaces were dominated by human skin and oral commensals such as Propionibacterium, Corynebacterium, Staphylococcus, and Streptococcus. The detected taxa not associated with humans included generalists from alphaproteobacteria, which were especially abundant on outdoor touchscreens. Shotgun metagenomics further identified viral and eukaryotic microbes, including Propionibacterium phage and Malassezia globosa. Functional profiling showed that Propionibacterium acnes pathways such as propionate production and porphyrin synthesis were enriched on train holding surfaces (holds), while electron transport chain components for aerobic respiration were enriched on touchscreens and seats. Lastly, the transit environment was not found to be a reservoir of antimicrobial resistance and virulence genes. Our results suggest that microbial communities on transit surfaces are maintained from a metapopulation of human skin commensals and environmental generalists, with enrichments corresponding to local interactions with the human body and environmental exposures.IMPORTANCE Mass transit environments, specifically, urban subways, are distinct microbial environments with high occupant densities, diversities, and turnovers, and they are thus especially relevant to public health. Despite this, only three culture-independent subway studies have been performed, all since 2013 and all with widely differing designs and conclusions. In this study, we profiled the Boston subway system, which provides 238 million trips per year overseen by the Massachusetts Bay Transportation Authority (MBTA). This yielded the first high-precision microbial survey of a variety of surfaces, ridership environments, and microbiological functions (including tests for potential pathogenicity) in a mass transit environment. 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Also, this Consortium is currently implementing the same studies in others cities, such as Lisbon and Porto.In the New York study, half of all DNA present on the subway’s surfaces matches no known organism and the hundreds of the species of bacteria identify were harmless, being the Pseudomonas stuzeri the most frequent microorganism. In this study was concluded that more commuters bring more diversity ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1016/j.cels.2015.01.001", "ISBN" : "2405-4712", "ISSN" : "24054712", "PMID" : "26594662", "abstract" : "Summary The panoply of microorganisms and other species present in our environment influence human health and disease, especially in cities, but have not been profiled with metagenomics at a city-wide scale. We sequenced DNA from surfaces across the entire New York City (NYC) subway system, the Gowanus Canal, and public parks. 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On other hand, in Hong Kong, Proteobacteria were the phylum more represented, like in New York with the Pseudomonas (belonging to Proteobacteria phylum). The authors suggested that the lines influenced the microbiome, considering that the stations with interchanging are more similar between them, that the stations that have none interchanging ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/AEM.02244-14", "ISSN" : "10985336", "PMID" : "25172855", "abstract" : "Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. 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Note, that the subway system from Hong Kong has many stations with interchanging between stations. Finally, the studies conducted in the Boston subway system, revealed that microbiome is influenced by the combination of two factors. The human body interactions and the material composition of the surfaces, ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/mSystems.00018-16", "ISSN" : "2379-5077", "abstract" : "Public transit systems are ideal for studying the urban microbiome and interindividual community transfer. In this study, we used 16S amplicon and shotgun metagenomic sequencing to profile microbial communities on multiple transit surfaces across train lines and stations in the Boston metropolitan transit system. The greatest determinant of microbial community structure was the transit surface type. In contrast, little variation was observed between geographically distinct train lines and stations serving different demographics. 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As a public transport system, the subway constitutes a favorable route for the dispersion of microorganisms, from one place for another. Therefore, as previously stated, the dynamics of the microbiome is important to understand the behavior of the microorganisms, to analyze emission sources and transmission routes, which may be useful in cases of an infection or a more dramatic case, in cases of bioterrorism. As a part of the international METASUB project (coordinated by Professor C. 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This aim will be achieved by the identification of microorganisms, using NGS strategies (shotgun), in the subway system of Lisbon.Material and MethodsSampling area The Lisbon’s subway system (Metro de Lisboa), is a member of the Transportes de Lisboa company. Lisbon’s subway comprises four lines and 55 stations. The four lines were named with the first four letters of the alphabet and represented by symbols of the city History (Figure 1).Figure SEQ Figure \* ARABIC 1 – Representation of the four lines that constitute the Lisbon’s subway, with the names and the directions of the lines. All the lines and stations are underground except line B, where a section of the path at the begging of the line (such as Odivelas and Senhor Roubado) are aboveground. Annually, the Lisbon’s subway is used by 140.1 millions of people (547,733 habitants). The totality of the metro systems is located inside the city limits, with a total extension of 43,2Km. The Lisbon’s subway fleet is composed of 334 carriages, produced by Sorafame/Siemens ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "URL" : "", "accessed" : { "date-parts" : [ [ "2016", "9", "22" ] ] }, "author" : [ { "dropping-particle" : "", "family" : "MetropolitanoLisboa", "given" : "", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "id" : "ITEM-1", "issued" : { "date-parts" : [ [ "2002" ] ] }, "title" : "Metropolitano de Lisboa, E.P.E.", "type" : "webpage" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(MetropolitanoLisboa 2002)", "plainTextFormattedCitation" : "(MetropolitanoLisboa 2002)", "previouslyFormattedCitation" : "(MetropolitanoLisboa 2002)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(MetropolitanoLisboa 2002).Sample collectionSamples (swabs) were collected at the 55 stations of Lisbon’s subway. Samples were collected in triplicates: two surfaces in each station, and one surface of the train (total of 159 samples in Lisboa, with the 4 control samples). The sampled surfaces were preselected according to the MetaSUB project guidelines (Table 1 and Supplementary Tables 1).Table SEQ Table_ \* ARABIC 1 – Surfaces in the subway stations and cars of the subway were sampled. The description of the material for each surface was presented in Supplementary Table 1.Samples were collected at Lisbon’s subway between the 6th and 9th January 2016. Also, in the station of Saldanha, two additional samples were collected inside of the subway station (Supplementary Table 2). Line A, was collected on the 6th January, lines B, and D on the 7th January and, finally, line C on the 8th January.For sample collection, a nylon flocked swab with transport medium (Copan Liquid Amies Elution Swab 481C, Italia) was used. The transport medium consists of sodium chloride (51.3 mmol NaCl), potassium chloride (2.7 mmol KCl), calcium chloride (0.9 mmol CaCl2), magnesium chloride (1.1 mmol MgCl2), monopotassium phosphate (1.5 mmol KH2PO4), disodium phosphate (8.1 mmol Na2HPO4), and sodium thioglycollate (8.8 mmol HSCH2COONa), pH 7.0±0.5 (Amies, 1967). Each surface was swabbed for three minutes, except the samples collected inside the subway train (the swabbing time depended on the duration between two adjacent stations). Four controls samples, one in each line, were collected. Controls were collected by exposing the nylon flocked swab to the air, during 30 seconds. After a surface sampling, the swab was placed immediately into the collection tube, in contact with the transport medium. Samples were then stored at 80?C until further use. DNA Extraction and QuantificationAccording to the methodology previously published by the MetaSUB Consortium (MetaSUB International Consortium, 2016), DNA extraction was performed using the MoBio Powersoil isolation kit. Briefly, cells were lysed, and the inorganic materials were precipitated. The DNA was bound to the silica membrane of the kit’s spin filters. Then, the DNA was purified with an ethanol wash and Agencourt AMPure XP magnetic beads. Samples were incubated at 25?C, for 15 min, and placed on an Invitrogen magnetic separation rack (MagnaRack), for 5 min. 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In this set of samples were include 16 samples from subway stations’ (seven samples elevators, five samples from turnstiles, two samples from escalators, one garbage can, one ticket validation, one info button, one vending machine) and 11 from the subway cars (four samples from the vertical support post, three from the bench support, two from the air conditioned, and one from the seat). The samples were chosen to include samples from begin, middle, and the end of each line.Once again, the procedures from manufacturer’s standard protocols were followed. Subsequently, using Truseq Nano DNA library preparation protocols (FC-121-4001), the DNA fractions were prepared for Illumina sequencing libraries. Some samples were also prepared with QIAGEN genes Reader DNA Library Prep I Kit (cat. No. 180984). 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These samples were sent to the Broad Institute for the shotgun library construction. For shotgun library construction, the Illumina Nextera XT method was used. The samples were sequenced on an Illumina Hiseq 2000 platform with 100-bp paired-end (PE) reads. The sequencing complexity was 16.7 x 106 PE reads per sample. 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After the removal of low-quality reads, the remaining reads were first clipped with the FASTX toolkit, to guarantee 99% base-level accuracy (Q20). The reads were prepared to MegaBLAST and only trimmed reads with more than 10 bases with quality scores and less of 20 were removed. Also, only one read from each pair was analyzed further, once MegaBlast does not lodge paired sequences. Next, the reads were aligned with MegaBLAST to search for a match to any organism in the full NCBI NT/NR database. Once, the MegaBLAST output for one read, returned with multiple hits to sequence from different taxa, the hits covering less than 65 bp of the 80 bp enquiry sequences were removed. Although, existed the necessity to filter once again the hits from the MegaBLAST. So for that, following the protocol of the MEGAN software, was required a min-score of 60 and a top percent of 10. Consequently, hits with a score lower than 60 were ignored, and hits that were not within 10 percent of the best bit score were, once again, ignored. Finally, a top percent of 100 was implemented, for that, at least one hit had a bit score bigger than 100. Once again, bit scores with less than 100 were ignored (Huson et?al., 2007; Afshinnekoo et al. 2015). To select the single “best” taxa, the LCA algorithm was used. LCA is a bioinformatics method for estimating the taxonomic composition of metagenomics DNA samples (Huson et?al., 2007; Afshinnekoo et al. 2015).To classify bacterial and viral sequences, samples were analyzed using the software MetaPhlAn 2.0. This program profiles the composition of microbial communities, obtained in metagenomics shotgun sequencing with species-level resolution and allows to identify specific strains and track strains across samples for all species (Segata et?al., 2012; Afshinnekoo et al. 2015). To classify specific pathogens SURPI and the BWA software were used. With the BWA, the sample sequences were aligned against several reference genomes, including the virulence plasmid (Naccache et al.; Li and Durbin, 2010; Afshinnekoo et al. 2015). 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PCR conditions were as following: 1 μl of template (1:50), 10 μl of HotMasterMix with the HotMaster Taq DNA Polymerase (5 Prime), and 1 μl of primer mix (for a final concentration of 10 μM). Cycling conditions consisted of an initial denaturation of 94°C for 3 min, followed by 24 cycles of denaturation at 94°C for 45 sec, annealing at 50 °C for 60 sec, extension at 72°C for 5 min, and a final extension at 72°C for 10 min.To reduce non-specific amplification products from host DNA, amplicons were quantified on the Caliper LabChipGX (PerkinElmer, Waltham, MA), size selected (375-425 bp) on the Pippin Prep (Sage Sciences, Beverly, MA). The final library size and quantification was performed on an Agilent Bioanalyzer 2100 DNA 1000 chip (Agilent Technologies, Santa Clara, CA). Sequencing was performed on the Illumina MiSeq platform according to the manufacturer’s specifications ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/mSystems.00018-16.Editor", "author" : [ { "dropping-particle" : "", "family" : "Hsu", "given" : "Tiffany", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Joice", "given" : "Regina", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Vallarino", "given" : "Jose", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Abu-ali", "given" : "Galeb", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Hartmann", "given" : "Erica M", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Shafquat", "given" : "Afrah", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Dulong", "given" : "Casey", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Baranowski", "given" : "Catherine", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Gevers", "given" : "Dirk", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Green", "given" : "Jessica L", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Morgan", "given" : "Xochitl C", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Spengler", "given" : "John D", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Huttenhower", "given" : "Curtis", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Science", "id" : "ITEM-1", "issue" : "3", "issued" : { "date-parts" : [ [ "2013" ] ] }, "page" : "1-18", "title" : "Urban Transit System Microbial Communities Differ by Surface Type and Interaction with Humans and the", "type" : "article-journal", "volume" : "1" }, "uris" : [ "", "" ] } ], "mendeley" : { "formattedCitation" : "(Hsu et al. 2013)", "plainTextFormattedCitation" : "(Hsu et al. 2013)", "previouslyFormattedCitation" : "(Science et al. 2013)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Hsu et al. 2013).Identification of possible sources of microbial diversity The association between the species identified in the microbiome and the possible sources - environmental, human or animal - where these microorganisms can be found was performed using the available online library.Human body part association The association between the species identified in the microbiome and the body parts where these microorganisms can be found was performed using the Human Microbiome Project (HMP) database ().Functional pathways analysisThe association between the functional pathways identified in the metabolome and the kingdoms and their superclass’s where this pathway can be found was performed using the MetaCyc database ().Statistical AnalysisFor the statistical analysis, data was grouped into categories. The categories were time (morning, afternoon), line (A, B, C, D), surface, the surface material, sampling time, and place of sampling (subway station or car). Data was verified for a normal distribution using the Shapiro test, verifying that none of the categories followed a normal distribution, even when applying the transformations (Log, Ln, etc.) in attempt to normalize the data. To verify if the categories had significant differences between them, non-parametric tests were applied. The non-parametric test used was Spearman test, and the p-value considered was 0.05. P values of 0.05 or lower were considered as statistically significant.Results DNA QuantificationDNA was extracted in the totality of the 159 samples collected from the Lisbon’s subway, including the control samples. The DNA concentration ranged from less of 0.5??g (negative control) to more the 600 ?g, from sample B21-Handrail, and D32-Turnstile. The average of DNA collected in all the lines was, 76.9±110.4 ?g; in Line, A was 69.1±60.0 ?g, in line B was 170.6±152.2 ?g; in line, C was 39.8±22.2 ?g, and in line, D was 77.6±116.5 ?g.In almost all the parameters studies no statistically significant difference was found. Therefore, no significant difference was observed between the stations (Figure 2 B, Supplementary table 2), or the surfaces (Figure 2 C, Supplementary table 2). Contrarily, statistically significant differences were observed between line A and line B (p=0.02) and between line B and Line C (p=0.02) (Figure 2 A, Supplementary table 2). Only the 12 surfaces analyzed in the subway station, in terms of the average of DNA collected in all the surfaces, per line, no statistically significant differences were found (Figure 3 A; Supplementary Table 2). The five surfaces analyzed in the subway car, in terms of the average of DNA collected in all the surfaces, per line, once again, no statistically significant differences were found (Figure 3 B, Supplementary Table 2). Figure SEQ Figure \* ARABIC 2 – DNA concentration collected in each sample in Lisboa Subway. (A) Average DNA concentration per line; (B) Average DNA concentration per station (C) Average DNA concentration per surfaces. The line was discriminated by color: Line A – Blue; Line B – Red; Line C – Green: Line D – Yellow; Data are mean ± stdev. Values significantly different between lines (*P < 0.05 **P < 0.01; t-test). ABAB Figure SEQ Figure \* ARABIC 3 – DNA concentration collected in subway stations and cars (A) Average DNA concentration collected in the subway stations (grouped by lines); (B) Average DNA concentration collected in the interior of a subway car (grouped by lines). Data are mean ± stdev.Samples were collected in a different times of the day, in both the subway station or car, being possible to divide the collection time into two time periods, morning and afternoon. Significant differences were found between the two time periods (p-value = 0.000), being the highest DNA concentrations found in the afternoon period (Figure 4; Supplementary table 2).Figure SEQ Figure \* ARABIC 4 – Average DNA concentration collected per time interval. Data are mean ± stdev. Values significantly different between lines (*P < 0.05; t-test).Microbiome analysisThe shotgun technique was used to identify the microorganisms present in Lisbon’s subway subway system. Bacteria corresponded to the most predominant kingdom detected (94.4%, 153 organisms), followed by fungi (3.1%, five organisms) and virus (2.5%, five organisms) (Figure 5).Figure SEQ Figure \* ARABIC 5 – Distribution, by kingdoms, of the microorganisms identified in the Lisbon’s subway.The bacterial species found in Lisbon subway’s surfaces were grouped into the families. A total of 47 bacterial families were identified, being Moraxellaceae family with higher relative abundance, followed by Enterobacteriaceae, Pseudomonadaceae, Oxolobaxteriaceae (Figure 6). Moraxellaceae were present in almost all surfaces analysed, like the Pseudomonas. No distribution pattern was found, once for example in the pole, in one sample the Moraxellaceae is clearly dominant, in another sample for the same surface, the same family is not present. Like on this surface, this happens in others, which does not show a pattern. Figure SEQ Figure \* ARABIC 6 – Relative abundances of bacterial families in the analyzed surfaces. Colored with blue, are the surfaces that are in the subway car (pole, air conditioner, grip - bench support, and seat). In green are the surfaces in the subway station (turnstile, elevator, escalator, garbage can, ticket validation, info button, and vending machine). Only families that appear in at least present in five of the 28 sequenced samples.In the Lisbon subway system, including both subway’s station and cars, Acinetobacter Iwoffi (39.8%) was the bacterial species most frequently detected, followed by Pseudomonas (10.1%), Massila (7.5%), Panteoa (7.4%), and Aceinobacter ursingii (6.5%) (Figure 7). Figure SEQ Figure \* ARABIC 7 – Main microorganism on subway surfaces (stations and cars).In subway’s stations, species such as Acinobacter Iowffi (50.7%) and Pseudomonas (8.8%) remained as the species most frequently found. However, other species such as Pantoea (unclassified) (6.2%), Massila timonae (5.1%), Acinobacter johsonii (2.7%), Pseudomonas stutzeri (1.4%), and Pantoea agglomerans (1.0%) presented higher frequency than in the general view. On other hand, species such as Dermacoccus sp Ellin185, Staphylococcus haemolyticus, Carnobacterium maltaromaticum, Weissella. and Ruminococcus torques were absent from the subway station (Figure 8).Figure SEQ Figure \* ARABIC 8 – Main microorganism on subway’s station surfaces.In subway’s car, Acinobacter Iwooffii (15,9%) remained as the most frequently detected species in the microbiome with. Other species such as Pantoea (13.9%), Enhydrobacter aerosaccus (10.1%), Acinetobacter (3%), Sphingobacterium sp IITKGP BTPF85 (2.6%), and Pantoea agglomerans (2%) were presented higher frequency than in general view. On other hand, species such as Rothia dentocariosa, Rothia mucilaginosa, Streptomyces coelicoflavus, Chryseobacterium gleum, Exiguobacterium sp MH3 are absent from the subway car (Figure 9).Figure SEQ Figure \* ARABIC 9 – Main microorganism on subway’s cars surfaces.Identification of possible sources of microbial diversityThe microorganisms identified in the Lisbon subway system can have one or several sources. Using the HMP website and the several bibliographic references was possible to identify the possible sources for the microbial diversity found in the subway system. The main sources of the diversity of the microorganisms that constitute this particular microbiome were the environment (50.0%), humans (38%), and animal (12%) (Figure 10). Figure SEQ Figure \* ARABIC 10 – Possible sources of the microbial diversity found in the subway system.Amongst the environment-associated sources, the soil (34.6%) was the main contributor for microbial diversity, followed by the water (18.7%), and plants (13.1%). The minor were air (3%), sewage (3%), and ice (0.9%) (Figure 11).Figure SEQ Figure \* ARABIC 11 – Possible environment-associated sources for the microbial diversity identified in the subway system.Amongst the human-associated sources, the second most represented in the subway microbiome, have with the most significant source of microbial diversity was the normal flora of the gastrointestinal tract (29.3%), followed by the normal flora of the skin (20.7%), and the normal flora of the urogenital tract (19.5%) On another hand, the Lymph nodes (1.2%), were the source with less representability (Figure 12).Figure SEQ Figure \* ARABIC 12 – Possible human-associated sources the microbial diversity identified in the subway system.Finally, amongst the animal-associated sources, the most significant source of microbial diversity was food-associated (76%). In this group, were represented microorganism linked to the production or treatment of the alimentary products. The other sources are animal associated, which can find the microorganisms that are possible to find in the meets that are consumed (Figure 13). Figure SEQ Figure \* ARABIC 13 – Possible animal and food-associated product sources the microbial diversity identified in the subway systemFunctional pathways analysisIn the functional pathways analysis, the bacteria remained as the kingdom most frequently represented (49.9%), followed by Archaea (14.7%), and Fungi (8.8%). However, in this analysis, other Eukaryotic kingdoms, such as Plantae (14.7%) and Animalia (7,0%), were also detected in significant percentages (Figure 14).Figure SEQ Figure \* ARABIC 14 – Possible host organisms for the actives pathways identified in the subway system.Then, a research on MetaCyc database was performed to identify the superclass the pathways. Amino acids biosynthesis or degradation (13.5%), secondary metabolism biosynthesis or degradation (12.2%), and generation of precursor metabolites and energy (10.9%) were the functional pathways’ superclass more represented in this subway system. Interestingly, the Antibiotic biosynthesis or resistance superclass contributed with two percent to the main pathways identified (Figure 15 and Supplementary Table/Figure 5).Figure SEQ Figure \* ARABIC 15 – Main superclass’s from the actives pathways identified in the subway system.Discussion A total of 159 samples were collected in the Lisbon subway system. The majority of these samples presented a DNA concentration higher than 0.5 ?g for DNA, with the exception of six samples. In the subway station, the info button was the surface that most frequently presented this low DNA concentration. This might have happened due to the small interaction between commuters and this surface. Also, the info button is a vertical surface reducing the deposition of microorganisms. In the subway car, support posts (vertical and horizontal) were the surfaces that most frequently exhibit a DNA concentration lower than 0.5 ?g. Once more, this might be due to the structure (building material and spatial orientation) of the surface, to the place where the sampling was performed, or to the reduced sampling time. It should be noticed that the samples inside subways cars were limited by the duration of the travel between two adjacent stations. Contrarily to what has been described above, the surface in the subway’s car with higher DNA concentration (>600 ?g), was the horizontal support post. This discrepancy with previous values might be related to the interval between the interaction commuters-surfaces. Since this sample was collected during rush hour (18:30), is possible to postulate that commuters were using the horizontal support shortly before the sampling. In subway stations, turnstiles and the handrails presented the highest DNA concentrations. This can happen due to the timing of the collection, or because these surfaces are very used in the quotidian of the subway system. Regarding the design, these surfaces are very different being the handrail in the horizontal plane and made of metal, and the turnstile in the vertical plane and made of glass and rubber.Despite the large dispersion of values found, line B presented the highest DNA concentrations among the lines analyzed. This line that connects the Aeroporto (Airport) and S. Sebasti?o (in the center of Lisbon) stations frequently used by both workers and tourists. Line D presented the second highest DNA concentration. In the time of the year in which the collection took place, both workers and students that live outside the city commonly use this line, which serves the main University Campus in Lisbon (Cidade Universitária). In line A, including some of the oldest metro stations in the subways systems, the number of cars that circulates is lower (three instead four) when compared the remaining lines. Also, the architecture of the station in line A is clearly different from the remaining stations. These facts could account for the lower DNA concentrations detected. Finally, line C that connects Telheiras to Cais do Sodré presented the lowest values of DNA concentration. Lines A and C, have some of the most touristic places in the city, being the oldest lines in this subway system. Statistically significant differences were observed between Line A and Line B. Only the number of the commuters and the structure of the station may affect the concentration of DNA collected. Line B is the most recent line of the subway system and presents fewer commuters than Line A, at least in the month that the sampling took place. Line C also presented statistically significant differences with Line B. These two lines were collected in different time periods; line C was collected in the morning period while Line B was collected in the afternoon (Supplementary table 1). This indicates that the collection time may have an effect on the DNA concentration. Also, this differences may be related to the cleaning routines in this subway systems since all the cleanings are usually performed during the morning period. The analysis of more samples would allow understanding if these time periods have an influence in the diversity identified. Regarding the number of commuters in both lines, line B has a higher number when compared with line C. A correlation between DNA concentration and the sampled period was observed in the Hong Kong subway, where the afternoon period was found to present more diversity than the morning period ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/AEM.02244-14", "ISSN" : "10985336", "PMID" : "25172855", "abstract" : "Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on \u03b1- and \u03b2-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. 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The number of commuters did not appear to have an influence in the concentration of DNA collected; opposite trends were observed in New York ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1016/j.cels.2015.01.001", "ISBN" : "2405-4712", "ISSN" : "24054712", "PMID" : "26594662", "abstract" : "Summary The panoply of microorganisms and other species present in our environment influence human health and disease, especially in cities, but have not been profiled with metagenomics at a city-wide scale. We sequenced DNA from surfaces across the entire New York City (NYC) subway system, the Gowanus Canal, and public parks. Nearly half of the DNA (48%) does not match any known organism; identified organisms spanned 1,688 bacterial, viral, archaeal, and eukaryotic taxa, which were enriched for genera associated with skin (e.g., Acinetobacter). Predicted ancestry of human DNA left on subway surfaces can recapitulate U.S. Census demographic data, and bacterial signatures can match a station's history, such as marine-associated bacteria in a hurricane-flooded station. 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"formattedCitation" : "(Afshinnekoo et al. 2015)", "plainTextFormattedCitation" : "(Afshinnekoo et al. 2015)", "previouslyFormattedCitation" : "(Afshinnekoo et al. 2015)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Afshinnekoo et al. 2015), being possible to hypothesize that the architecture of the lines may influence the concentration of DNA collected. No statistically significant differences were found between the stations or the surfaces in subways stations (Figure 2 B and C) and cars (Figure 3 A and B), indicating that these parameters do not influence DNA concentration values. Until now, only the line presented influence in DNA concentration, since between the surfaces no difference was found (Figure 3 A and B). This can indicate that the material of the surface and the time of sampling did not influence the DNA concentration.To verify the effects of line, stations, surface and time, further testing needs to be conducted. For instance, it would be interesting to study the intradiurnal pattern of the DNA concentration. As such, samples should be collected in several stations along all lines, with two hours’ intervals.The shotgun sequencing provided information about the microbiome of the subway system. However, not all the samples have been sequenced. The sequenced samples were chosen to ensure the best coverage of the subway system, including both terminal and interchange stations. Microorganism represent the majority of the biomass in the world, it was expected that in the subway system this was not different. Bacteria was the kingdom most represented, followed by the Fungi, and Virus. This differences between the bacteria and virus can appear once the kit used to extract the DNA was not specific to extract only the DNA from virus or one taxa in particularly. So, once the genome from virus is considerably smaller than the genome of a bacteria, and exist more difficulty in extract DNA from virus, this differences between bacteria and virus may appear. Moraxellacea, Pseudomonadaceae and Sphigobacteriacea families were the most frequently found (Figure 6). In the subway of Boston, it was concluded that the each surface has a specific microbiome, meaning that the microbiome is deeply influenced by the surface/material ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/mSystems.00018-16", "ISSN" : "2379-5077", "abstract" : "Public transit systems are ideal for studying the urban microbiome and interindividual community transfer. In this study, we used 16S amplicon and shotgun metagenomic sequencing to profile microbial communities on multiple transit surfaces across train lines and stations in the Boston metropolitan transit system. The greatest determinant of microbial community structure was the transit surface type. In contrast, little variation was observed between geographically distinct train lines and stations serving different demographics. All surfaces were dominated by human skin and oral commensals such as Propionibacterium, Corynebacterium, Staphylococcus, and Streptococcus. The detected taxa not associated with humans included generalists from alphaproteobacteria, which were especially abundant on outdoor touchscreens. Shotgun metagenomics further identified viral and eukaryotic microbes, including Propionibacterium phage and Malassezia globosa. Functional profiling showed that Propionibacterium acnes pathways such as propionate production and porphyrin synthesis were enriched on train holding surfaces (holds), while electron transport chain components for aerobic respiration were enriched on touchscreens and seats. Lastly, the transit environment was not found to be a reservoir of antimicrobial resistance and virulence genes. Our results suggest that microbial communities on transit surfaces are maintained from a metapopulation of human skin commensals and environmental generalists, with enrichments corresponding to local interactions with the human body and environmental exposures.IMPORTANCE Mass transit environments, specifically, urban subways, are distinct microbial environments with high occupant densities, diversities, and turnovers, and they are thus especially relevant to public health. Despite this, only three culture-independent subway studies have been performed, all since 2013 and all with widely differing designs and conclusions. In this study, we profiled the Boston subway system, which provides 238 million trips per year overseen by the Massachusetts Bay Transportation Authority (MBTA). This yielded the first high-precision microbial survey of a variety of surfaces, ridership environments, and microbiological functions (including tests for potential pathogenicity) in a mass transit environment. Characterizing microbial profiles for multiple transit systems will become increasingly important for biosurveillance of antibiotic resistance genes or \u2026", "author" : [ { "dropping-particle" : "", "family" : "Hsu", "given" : "Tiffany", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Joice", "given" : "Regina", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Vallarino", "given" : "Jose", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Abu-Ali", "given" : "Galeb", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Hartmann", "given" : "Erica M", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Shafquat", "given" : "Afrah", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "DuLong", "given" : "Casey", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Baranowski", "given" : "Catherine", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Gevers", "given" : "Dirk", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Green", "given" : "Jessica L", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Morgan", "given" : "Xochitl C", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Spengler", "given" : "John D", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Huttenhower", "given" : "Curtis", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "mySystems", "id" : "ITEM-1", "issue" : "3", "issued" : { "date-parts" : [ [ "2016" ] ] }, "page" : "1-18", "title" : "Urban Transit System Microbial Communities Differ by Surface Type and Interaction with Humans and the Environment", "type" : "article-journal", "volume" : "1" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Hsu et al. 2016)", "plainTextFormattedCitation" : "(Hsu et al. 2016)", "previouslyFormattedCitation" : "(Hsu et al. 2016)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Hsu et al. 2016). The same was not observed in Lisbon, since no microbial signature was found for the surfaces. In this study, only 28 samples were sequenced and there was an uneven distribution of the samples - in some surfaces four samples were sequenced while in other surfaces only one sample was sequenced. The phylum Proteobacteria, remained as the phylum more represented such as in the New York and Hong Kong subway systems ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1016/j.cels.2015.01.001", "ISBN" : "2405-4712", "ISSN" : "24054712", "PMID" : "26594662", "abstract" : "Summary The panoply of microorganisms and other species present in our environment influence human health and disease, especially in cities, but have not been profiled with metagenomics at a city-wide scale. We sequenced DNA from surfaces across the entire New York City (NYC) subway system, the Gowanus Canal, and public parks. Nearly half of the DNA (48%) does not match any known organism; identified organisms spanned 1,688 bacterial, viral, archaeal, and eukaryotic taxa, which were enriched for genera associated with skin (e.g., Acinetobacter). Predicted ancestry of human DNA left on subway surfaces can recapitulate U.S. Census demographic data, and bacterial signatures can match a station's history, such as marine-associated bacteria in a hurricane-flooded station. 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"itemData" : { "DOI" : "10.1128/AEM.02244-14", "ISSN" : "10985336", "PMID" : "25172855", "abstract" : "Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on \u03b1- and \u03b2-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. This Hong Kong data set and communities from previous studies conducted in the United States formed distinct community clusters, indicating that additional work is required to unravel the mechanisms that shape subway microbiomes around the globe.", "author" : [ { "dropping-particle" : "", "family" : "Leung", "given" : "Marcus H Y", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wilkins", "given" : "David", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Li", "given" : "Ellen K T", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kong", "given" : "Fred K F", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Lee", "given" : "Patrick K H", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Applied and Environmental Microbiology", "id" : "ITEM-2", "issue" : "21", "issued" : { "date-parts" : [ [ "2014" ] ] }, "page" : "6760-6770", "title" : "Indoor-air microbiome in an urban subway network: Diversity and dynamics", "type" : "article-journal", "volume" : "80" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Afshinnekoo et al. 2015; Leung et al. 2014)", "plainTextFormattedCitation" : "(Afshinnekoo et al. 2015; Leung et al. 2014)", "previouslyFormattedCitation" : "(Afshinnekoo et al. 2015; Leung et al. 2014)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Afshinnekoo et al. 2015; Leung et al. 2014). More specifically, the order Pseudomonadales, including the species Acinetobacter Iwoffi and the genus Pseudomonas. The species more common in the subway surfaces was A. Iwoffi . This bacteria, present in the human body, is frequently found in the normal flora of the skin, airways or urogenital tract. Despite being harmless to immunonocompetent hosts, in immunocompromised patients this species is known as the etiological agent of diseases such as pneumonia, posthemorrhagic hydrocephalus among other (See Supplementary table 4). The high abundance of this bacteria, supports the fact that the microbiome is deeply influenced by the human microbiome. The same was observed in the others subways systems previously studied ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1016/j.cels.2015.01.001", "ISBN" : "2405-4712", "ISSN" : "24054712", "PMID" : "26594662", "abstract" : "Summary The panoply of microorganisms and other species present in our environment influence human health and disease, especially in cities, but have not been profiled with metagenomics at a city-wide scale. We sequenced DNA from surfaces across the entire New York City (NYC) subway system, the Gowanus Canal, and public parks. Nearly half of the DNA (48%) does not match any known organism; identified organisms spanned 1,688 bacterial, viral, archaeal, and eukaryotic taxa, which were enriched for genera associated with skin (e.g., Acinetobacter). Predicted ancestry of human DNA left on subway surfaces can recapitulate U.S. Census demographic data, and bacterial signatures can match a station's history, such as marine-associated bacteria in a hurricane-flooded station. 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"itemData" : { "DOI" : "10.1128/mSystems.00018-16", "ISSN" : "2379-5077", "abstract" : "Public transit systems are ideal for studying the urban microbiome and interindividual community transfer. In this study, we used 16S amplicon and shotgun metagenomic sequencing to profile microbial communities on multiple transit surfaces across train lines and stations in the Boston metropolitan transit system. The greatest determinant of microbial community structure was the transit surface type. In contrast, little variation was observed between geographically distinct train lines and stations serving different demographics. All surfaces were dominated by human skin and oral commensals such as Propionibacterium, Corynebacterium, Staphylococcus, and Streptococcus. The detected taxa not associated with humans included generalists from alphaproteobacteria, which were especially abundant on outdoor touchscreens. Shotgun metagenomics further identified viral and eukaryotic microbes, including Propionibacterium phage and Malassezia globosa. Functional profiling showed that Propionibacterium acnes pathways such as propionate production and porphyrin synthesis were enriched on train holding surfaces (holds), while electron transport chain components for aerobic respiration were enriched on touchscreens and seats. Lastly, the transit environment was not found to be a reservoir of antimicrobial resistance and virulence genes. Our results suggest that microbial communities on transit surfaces are maintained from a metapopulation of human skin commensals and environmental generalists, with enrichments corresponding to local interactions with the human body and environmental exposures.IMPORTANCE Mass transit environments, specifically, urban subways, are distinct microbial environments with high occupant densities, diversities, and turnovers, and they are thus especially relevant to public health. Despite this, only three culture-independent subway studies have been performed, all since 2013 and all with widely differing designs and conclusions. In this study, we profiled the Boston subway system, which provides 238 million trips per year overseen by the Massachusetts Bay Transportation Authority (MBTA). This yielded the first high-precision microbial survey of a variety of surfaces, ridership environments, and microbiological functions (including tests for potential pathogenicity) in a mass transit environment. Characterizing microbial profiles for multiple transit systems will become increasingly important for biosurveillance of antibiotic resistance genes or \u2026", "author" : [ { "dropping-particle" : "", "family" : "Hsu", "given" : "Tiffany", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Joice", "given" : "Regina", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Vallarino", "given" : "Jose", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Abu-Ali", "given" : "Galeb", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Hartmann", "given" : "Erica M", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Shafquat", "given" : "Afrah", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "DuLong", "given" : "Casey", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Baranowski", "given" : "Catherine", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Gevers", "given" : "Dirk", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Green", "given" : "Jessica L", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Morgan", "given" : "Xochitl C", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Spengler", "given" : "John D", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Huttenhower", "given" : "Curtis", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "mySystems", "id" : "ITEM-2", "issue" : "3", "issued" : { "date-parts" : [ [ "2016" ] ] }, "page" : "1-18", "title" : "Urban Transit System Microbial Communities Differ by Surface Type and Interaction with Humans and the Environment", "type" : "article-journal", "volume" : "1" }, "uris" : [ "" ] }, { "id" : "ITEM-3", "itemData" : { "DOI" : "10.1128/AEM.02244-14", "ISSN" : "10985336", "PMID" : "25172855", "abstract" : "Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on \u03b1- and \u03b2-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. This Hong Kong data set and communities from previous studies conducted in the United States formed distinct community clusters, indicating that additional work is required to unravel the mechanisms that shape subway microbiomes around the globe.", "author" : [ { "dropping-particle" : "", "family" : "Leung", "given" : "Marcus H Y", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wilkins", "given" : "David", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Li", "given" : "Ellen K T", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kong", "given" : "Fred K F", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Lee", "given" : "Patrick K H", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Applied and Environmental Microbiology", "id" : "ITEM-3", "issue" : "21", "issued" : { "date-parts" : [ [ "2014" ] ] }, "page" : "6760-6770", "title" : "Indoor-air microbiome in an urban subway network: Diversity and dynamics", "type" : "article-journal", "volume" : "80" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Afshinnekoo et al. 2015; Hsu et al. 2016; Leung et al. 2014)", "plainTextFormattedCitation" : "(Afshinnekoo et al. 2015; Hsu et al. 2016; Leung et al. 2014)", "previouslyFormattedCitation" : "(Afshinnekoo et al. 2015; Hsu et al. 2016; Leung et al. 2014)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Afshinnekoo et al. 2015; Hsu et al. 2016; Leung et al. 2014). However, due the limited number of sequenced samples was not possible to further analyzed the participation of the human body in the diversity of subway microbiome. Also, due the specific legislation applied was not possible to verify several other aspects, such as if the microbiome in a specific station or stations is influence according to the microbiome of a specify population group, as concluded in Hong kong, where Enhydrobacter was found in human skin, mostly from Chinese individuals ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/AEM.02244-14", "ISSN" : "10985336", "PMID" : "25172855", "abstract" : "Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on \u03b1- and \u03b2-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. 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In the New York subway, similar results were reported, being verified that the human DNA collected from the surfaces can recapitulate the geospatial demographics of the city in U.S. census data ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1016/j.cels.2015.01.001", "ISBN" : "2405-4712", "ISSN" : "24054712", "PMID" : "26594662", "abstract" : "Summary The panoply of microorganisms and other species present in our environment influence human health and disease, especially in cities, but have not been profiled with metagenomics at a city-wide scale. We sequenced DNA from surfaces across the entire New York City (NYC) subway system, the Gowanus Canal, and public parks. Nearly half of the DNA (48%) does not match any known organism; identified organisms spanned 1,688 bacterial, viral, archaeal, and eukaryotic taxa, which were enriched for genera associated with skin (e.g., Acinetobacter). Predicted ancestry of human DNA left on subway surfaces can recapitulate U.S. Census demographic data, and bacterial signatures can match a station's history, such as marine-associated bacteria in a hurricane-flooded station. 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Pseudomonas, were the second most frequent microorganism found in the subway microbiome. These are mostly environmental bacterias, such as Massilia and Pantoea (See Supplementary table 4). Pseudomonas did not present the same importance in the surfaces from the subway car, although these bacteria appeared in the general view of the subway. This can happen due to the difference that exists between the number of samples from the subway car and subway station, making that the samples from the subway car have much more influence on the general view of the subway. Therefore, is not a surprise that significant difference were not found between the general view and the subway car. Other species of bacteria that appeared with lower abundance were helpful to understand how the surrounding environment influences the subway microbiome. This was the case of bacteria such as Exiguobacterium sp MH3, Exiguobacterium sibirium, Psychrobacter Cryohalolentis, Psychrobacter aquaticus or Psychrobacter arcticus, among others. These species are frequently found in extreme environments (See supplementary table 4), mostly associated with water sources. Similar results were previously reported in the Hong Kong subway system ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/AEM.02244-14", "ISSN" : "10985336", "PMID" : "25172855", "abstract" : "Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on \u03b1- and \u03b2-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. This Hong Kong data set and communities from previous studies conducted in the United States formed distinct community clusters, indicating that additional work is required to unravel the mechanisms that shape subway microbiomes around the globe.", "author" : [ { "dropping-particle" : "", "family" : "Leung", "given" : "Marcus H Y", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wilkins", "given" : "David", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Li", "given" : "Ellen K T", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kong", "given" : "Fred K F", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Lee", "given" : "Patrick K H", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Applied and Environmental Microbiology", "id" : "ITEM-1", "issue" : "21", "issued" : { "date-parts" : [ [ "2014" ] ] }, "page" : "6760-6770", "title" : "Indoor-air microbiome in an urban subway network: Diversity and dynamics", "type" : "article-journal", "volume" : "80" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Leung et al. 2014)", "plainTextFormattedCitation" : "(Leung et al. 2014)", "previouslyFormattedCitation" : "(Leung et al. 2014)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Leung et al. 2014). In fact, both cities are surrounded by water. Other bacterias, such as Citrobacter freundii, Citrobacter, Acinetobacter towneri, Acinetobacter oleivorans or Comamonas testosteroni, are commonly associated with sewage (See supplementary table 4). The appearance of these bacterias in the subway system may be related to the industrial water treatment stations present inside of the tunnels of the subway. Lastly, other species are related with the oil and gas work-effluent, such as Acinetobacter guillowiase, Pseudomonas fulva, Pseudomonas alcaligenes and Delfia acidovorans (See supplementary table 4). The appearance of these bacterias may result for the proximity of some stations to Lisbon port (Porto de Lisboa) or even to the oils used in subways cars. Therefore, it has been proven that the external environment can deeply influence the subway system. However, once again, due the limited number of samples was not possible to conclude if the one particular station has its characteristic microbiome, or if there is an interaction between the stations, making the stations more similar between them, as in the Hong Kong subway, where an interaction between the lines has been reported ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/AEM.02244-14", "ISSN" : "10985336", "PMID" : "25172855", "abstract" : "Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on \u03b1- and \u03b2-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. 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A primally analyze in the HMP website gave the possible sources to some of the identified species. However, the HMP database only contains species human-associated sources, such as skin or gastrointestinal track. After, another research using bibliographic material. Gathering the information from both, environment-associated sources appeared as the major contributors for subway microbiome diversity, followed by human-associated sources, and food- and animal-associated. Amongst the environment-associated sources, the soil was the major contributor for subway microbiome diversity as previously reported in other subways systems (Afshinnekoo et al. 2015; Leung et al. 2014), followed by water that frequently found near to some subway stations. Several soil-associated bacteria have been frequently detected in others indoor environments (Leung et al. 2014). These results were also expected, since commuters carry these microorganisms in the sole of shoes from the outside to inside the subway system. Once inside of the subway system, this microorganism became airborne due to the ventilation system existing in the subway.The human body was the second largest source of subway microbiome diversity. Amongst the human-associated sources, the normal flora of the gastrointestinal track was the as the major contributors for subway microbiome diversity, followed the normal flora of the skin. In the analyzed samples, only one seat in the subway car and no bench in the subway station were sequenced. These results showed a possible transfer between the gastrointestinal tract and hands and later these microorganisms were transfer to subway surfaces. These results are consistent with previous reports from other subway systems, where for example, in New York the same sources are considered main human sources for the microbiome subway (Afshinnekoo et al. 2015).The third source largest source of subway microbiome diversity were food- and animal-associated sources. The food-associated microorganism are commonly found in the production or preservation of some aliments, such as cheese, yogurt, and meat curing brines. These microorganisms can be transfered from the alimentary product to the hand of the commuters and then to the subway surfaces. Animal-associated microorganisms are mainly those associated with Portuguese cuisines, such as cows, ducks or goats. However, other animals such pigeons are quite to found both outdoor using several buildings for the construction of the nests. Bacteria were the most predominant organisms contributing to the identified pathways, followed by several Eukaryotic kingdoms. Comparing the results from the functional pathways with those of the microbiome, a higher diversity of organisms was identified. The research showed that the amino acids biosynthesis or degradation, secondary metabolism biosynthesis or degradation, and generation of precursor metabolites and energy were the functional pathways’ superclass more represented. Once the microorganisms have to adapt and survive in the subway system, and the generation of the metabolites is one of the many strategies that adopted by the organisms to survive (The MetaSUB International Consortium 2016). The antibiotic biosynthesis or resistance superclass was another of the superclass detected. This is interesting, due to the recent reports of antibiotic-resistance microorganism in the subway systems ADDIN CSL_CITATION { "citationItems" : [ { "id" : "ITEM-1", "itemData" : { "DOI" : "10.1128/AEM.02244-14", "ISSN" : "10985336", "PMID" : "25172855", "abstract" : "Subway systems are indispensable for urban societies, but microbiological characteristics of subway aerosols are relatively unknown. Previous studies investigating microbial compositions in subways employed methodologies that underestimated the diversity of microbial exposure for commuters, with little focus on factors governing subway air microbiology, which may have public health implications. Here, a culture-independent approach unraveling the bacterial diversity within the urban subway network in Hong Kong is presented. Aerosol samples from multiple subway lines and outdoor locations were collected. Targeting the 16S rRNA gene V4 region, extensive taxonomic diversity was found, with the most common bacterial genera in the subway environment among those associated with skin. Overall, subway lines harbored different phylogenetic communities based on \u03b1- and \u03b2-diversity comparisons, and closer inspection suggests that each community within a line is dependent on architectural characteristics, nearby outdoor microbiomes, and connectedness with other lines. Microbial diversities and assemblages also varied depending on the day sampled, as well as the time of day, and changes in microbial communities between peak and nonpeak commuting hours were attributed largely to increases in skin-associated genera in peak samples. Microbial diversities within the subway were influenced by temperature and relative humidity, while carbon dioxide levels showed a positive correlation with abundances of commuter-associated genera. This Hong Kong data set and communities from previous studies conducted in the United States formed distinct community clusters, indicating that additional work is required to unravel the mechanisms that shape subway microbiomes around the globe.", "author" : [ { "dropping-particle" : "", "family" : "Leung", "given" : "Marcus H Y", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wilkins", "given" : "David", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Li", "given" : "Ellen K T", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Kong", "given" : "Fred K F", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Lee", "given" : "Patrick K H", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Applied and Environmental Microbiology", "id" : "ITEM-1", "issue" : "21", "issued" : { "date-parts" : [ [ "2014" ] ] }, "page" : "6760-6770", "title" : "Indoor-air microbiome in an urban subway network: Diversity and dynamics", "type" : "article-journal", "volume" : "80" }, "uris" : [ "" ] }, { "id" : "ITEM-2", "itemData" : { "DOI" : "10.3390/ijerph10062412", "ISSN" : "16617827", "PMID" : "23765189", "abstract" : "This study focused on the presence of antibiotic-resistant bacteria in a metro system as an example of a public transportation system. The molecular characteristics of Staphylococcus were investigated to discern which strains were isolated from metro stations in Shanghai. These were compared with strains isolated from hospital treatment rooms and parks. Airborne Staphylococcus samples in the metro were resistant to an average of 2.64 antibiotic types, and 58.0% of the strain samples were resistant to at least three antibiotics; this was a significantly higher rate than strains from the park, but was lower than those from hospitals. The presence of two antibiotic resistance genes of Staphylococcus strains, mecA (28.0%) and qac (40.0%), were also found at significantly higher levels in metro samples than park samples, but did not differ significantly from hospital samples. Furthermore, 22.0% of the metro Staphylococcus samples were found to be biofilm-positive. The high rate of antibiotic resistance found in Staphylococcus samples collected from metro stations, and the discovery of antibiotic-resistant genes, indicate that the closed indoor environment and crowded passengers may accelerate the spread of antibiotic resistant strains. More attention should be paid to the inspection and control of antibiotic resistant strains in public transportation systems.", "author" : [ { "dropping-particle" : "", "family" : "Zhou", "given" : "Feng", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Wang", "given" : "Yuyan", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "International Journal of Environmental Research and Public Health", "id" : "ITEM-2", "issue" : "6", "issued" : { "date-parts" : [ [ "2013" ] ] }, "page" : "2412-2426", "title" : "Characteristics of antibiotic resistance of airborne Staphylococcus isolated from metro stations", "type" : "article-journal", "volume" : "10" }, "uris" : [ "" ] }, { "id" : "ITEM-3", "itemData" : { "DOI" : "10.1128/AEM.07212-11", "ISSN" : "00992240", "PMID" : "22247150", "abstract" : "The reliable detection of airborne biological threat agents depends on several factors, including the performance criteria of the detector and its operational environment. One step in improving the detector's performance is to increase our knowledge of the biological aerosol background in potential operational environments. Subway stations are enclosed public environments, which may be regarded as potential targets for incidents involving biological threat agents. In this study, the airborne bacterial community at a subway station in Norway was characterized (concentration level, diversity, and virulence- and survival-associated properties). In addition, a SASS 3100 high-volume air sampler and a matrix-assisted laser desorption ionization-time of flight mass spectrometry-based isolate screening procedure was used for these studies. The daytime level of airborne bacteria at the station was higher than the nighttime and outdoor levels, and the relative bacterial spore number was higher in outdoor air than at the station. The bacterial content, particle concentration, and size distribution were stable within each environment throughout the study (May to September 2010). The majority of the airborne bacteria belonged to the genera Bacillus, Micrococcus, and Staphylococcus, but a total of 37 different genera were identified in the air. These results suggest that anthropogenic sources are major contributors to airborne bacteria at subway stations and that such airborne communities could harbor virulence- and survival-associated properties of potential relevance for biological detection and surveillance, as well as for public health. Our findings also contribute to the development of realistic testing and evaluation schemes for biological detection/surveillance systems by providing information that can be used to mimic real-life operational airborne environments in controlled aerosol test chambers.", "author" : [ { "dropping-particle" : "", "family" : "Dybwad", "given" : "Marius", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Granum", "given" : "Per Einar", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Bruheim", "given" : "P. Per", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" }, { "dropping-particle" : "", "family" : "Blatnya", "given" : "Janet Martha", "non-dropping-particle" : "", "parse-names" : false, "suffix" : "" } ], "container-title" : "Applied and Environmental Microbiology", "id" : "ITEM-3", "issue" : "6", "issued" : { "date-parts" : [ [ "2012" ] ] }, "page" : "1917-1929", "title" : "Characterization of airborne bacteria at an underground subway station", "type" : "article-journal", "volume" : "78" }, "uris" : [ "" ] } ], "mendeley" : { "formattedCitation" : "(Leung et al. 2014; Zhou & Wang 2013; Dybwad et al. 2012)", "plainTextFormattedCitation" : "(Leung et al. 2014; Zhou & Wang 2013; Dybwad et al. 2012)", "previouslyFormattedCitation" : "(Leung et al. 2014; Zhou & Wang 2013; Dybwad et al. 2012)" }, "properties" : { "noteIndex" : 0 }, "schema" : "" }(Leung et al. 2014; Zhou & Wang 2013; Dybwad et al. 2012). However, this is not a matter of concern due to the residual percentage that this superclass showed being the subway system considered as a safe transportation. Conclusion The characterization of the subway microbiome was performed using the high-throughput culturing-independent method, NGS, and though a limited number of the sample was analyzed, was possible to verify the high diversity present in the Lisbon’s subway system. Also, it was observed that the time and the architecture of the lines had an influence on the concentration of the DNA collect. However, with the present dataset was not possible to prove that specific groups etnias had an impact on the diversity of a particular line or station from the subway, such as a specific environment or that a surface has a specific microbiome. More samples are needed for these hypotheses be proven, and to understand if exist an interaction between the stations and lines, or if all lines and stations have its specific environment, with a possibility of having an exception when for example commuters carry with them a specimen that is characteristic from one station to another.Amongst the microorganisms and the functional pathways that found in this study, none represent an immediate threat to the public health. With the results herein presented is possible to secure that the subway continues to be a safe transportation to commuters. The environment and human-associated sources are the major contributors for the subway’s microbiome diversity, being possible to deduce that the results from more samples will increase the diversity found. Regarding forensic aspects, none of the species identified can be considerd as a threat, and the interaction station-line and line-line have to be clarified. However, results from previous studies showed that the antibiotic-resistant organisms are presente in the system, and although actually, the percentage is not alarming, active surveillance is required. The number of commuters per day is elevated and with the high interaction between the commuters-surfaces or commuters-commuters, the subway constitutes an ideal route for the transmission and transportation of harmful microorganism, as in the case of a bioterrorism attack or the new outbreak of a infectious disease. BibliographyAmies, C.R. 1967. A modified formula for the preparation of Stuart's transport. medium.Can J. Public Health 58:296-300.ADDIN Mendeley Bibliography CSL_BIBLIOGRAPHY Afshinnekoo, E. et al., 2015. Geospatial Resolution of Human and Bacterial Diversity with City-Scale Metagenomics. Cell Systems, 1(1), pp.72–87.Aspevall, O. et al., 2015. Global Antimicrobial Resistance Surveillance System: Manual for Early Implementation. World Health Organization, pp.1–36. 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International Journal of Environmental Research and Public Health, 10(6), pp.2412–2426.Attachments LINK Excel.Sheet.12 C:\\Users\\andre\\Dropbox\\Tese\\Excel\\FINAL.xlsx "LineA - summary!L1C1:L53C12" \a \f 4 \h \* MERGEFORMAT Sample NumberDateTimeSiteGPS coordinates (Latitude/Longitude)DescriptionPlaceMaterialSampling DurationCollectorQuant Yield (total ng)A0106.01.16?Amadora Este → Alfornelos ??Inside Metro Carriage Vertical Support PostMetal3minAF and MO28,00A0206.01.1615:26Amadora Este38°?45′?28″?N9°?13′?05″?WUnderground Metro StationTurnstileGlass and rubber3minAF and MO104,80A0306.01.1615:26Amadora EsteUnderground Metro StationElevatorMetal and glass3minAF and MO93,20A0406.01.16?Alfornelos → Pontinha??Inside Metro Carriage Bench SupportMetal1min20secAF and MO134,40A0506.01.1615:46Alfornelos38°?45′?37″?N9°?12′?18″?WUnderground Metro StationHandrailMetal3minAF and MO61,12A0606.01.1615:46AlfornelosUnderground Metro StationEscalatorRubber3minAF and MO54,08A0706.01.16?Pontinha → Carnide ??Inside Metro Carriage WindowGlass1min18secAF and MO35,68A0806.01.1616:05Pontinha38°?45′?41″?N9°?11′?48″?WUnderground Metro StationTicket Kiosk Metal and plastic3minAF and MO86,40A0906.01.1616:05Pontinha Underground Metro StationPayphoneMetal and plastic3minAF and MO76,80A1006.01.16?Carnide → Colégio Militar/Luz??Inside Metro Carriage Horizontal Support PostMetal1min42secAF and MO27,36A1106.01.1616:24Carnide 38°?45′?31″?N9°?11′?33″?WUnderground Metro StationTicket ValidationPlastic3minAF and MO82,40A1206.01.1616:24Carnide Underground Metro StationBenchwood3minAF and MO41,60A1306.01.16?Colégio Militar/Luz →Alto dos Moinhos ??Inside Metro Carriage SeatVelvet and plastic1min29secAF and MO32,16A1406.01.1616:36Colégio Militar/Luz38°?45′?09″?N9°?11′?19″?WUnderground Metro StationInfo PlacardAcrylic3minAF and MO147,20A1506.01.1616:36Colégio Militar/LuzUnderground Metro StationGarbage canMetal3minAF and MO43,68A1606.01.16?Alto dos Moinhos → Laranjeiras??Inside Metro Carriage Vertical Support PostMetal1min25secAF and MO152,00A1706.01.1616:48Alto dos Moinhos38°?44′?58″?N9°?10′?46″?WUnderground Metro StationInfo buttonMetal and plastic3minAF and MO?A1806.01.1616:48Alto dos MoinhosUnderground Metro StationTurnstileGlass and rubber3minAF and MO49,28A1906.01.16?Laranjeiras → Jardim Zoológico??Inside Metro Carriage Bench SupportMetal1min38secAF and MO42,08A2006.01.1617:08Laranjeiras38°?44′?53″?N9°?10′?19″?WUnderground Metro StationHandrailMetal3minAF and MO50,24A2106.01.1617:08LaranjeirasUnderground Metro StationPayphoneMetal and plastic3minAF and MO68,80A2206.01.16?Jardim Zoológico → Pra?a de Espanha ??Inside Metro Carriage WindowGlass1min47secAF and MO84,00A2306.01.1617:15Jardim Zoológico38°?44′?31″?N9°?10′?07″?WUnderground Metro StationTicket Kiosk Metal and plastic3minAF and MO122,40A2406.01.1617:15Jardim ZoológicoUnderground Metro StationBenchwood3minAF and MO37,76A2506.01.16?Pra?a de Espanha → S?o Sebasti?o??Inside Metro Carriage Horizontal Support PostMetal1min27secAF and MO3,50A2606.01.1617:30Pra?a de Espanha38°?44′?14″?N9°?09′?34″?WUnderground Metro StationTicket ValidationPlastic3minAF and MO38,24A2706.01.1617:30Pra?a de EspanhaUnderground Metro StationInfo PlacardAcrylic3minAF and MO40,48A2806.01.16?S?o Sebasti?o → Parque ??Inside Metro Carriage SeatVelvet and plastic1min15secAF and MO57,28A2906.01.1617:40S?o Sebasti?o38°?44′?04″?N9°?09′?16″?WUnderground Metro StationGarbage canMetal3minAF and MO36,48A3006.01.1617:40S?o Sebasti?oUnderground Metro StationInfo buttonMetal and plastic3minAF and MO28,80A3106.01.16?Parque → Marquês de Pombal??Inside Metro Carriage Vertical Support PostMetal1min14secAF and MO4,66A3206.01.1618:07Parque8°?43′?45″?N9°?09′?00″?WUnderground Metro StationPayphoneMetal and plastic3minAF and MO105,60A3306.01.1618:07ParqueUnderground Metro StationTurnstileGlass and rubber3minAF and MO23,20A3406.01.16?Marquês do Pombal → Avenida??Inside Metro Carriage Horizontal Support PostMetal1min20secAF and MO21,92A3506.01.1618:23Marquês do Pombal38°?43′?28″?N9°?09′?01″?WUnderground Metro StationHandrailMetal3minAF and MO70,88A3606.01.1618:23Marquês do PombalUnderground Metro StationVending machineAcrylic and Plastic 3minAF and MO53,92A3706.01.16?Avenida → Restauradores ??Inside Metro Carriage WindowGlass1minAF and MO100,00A3806.01.1618:36Avenida38°?43′?12″?N9°?08′?45″?WUnderground Metro StationEscalatorRubber3minAF and MO108,00A3906.01.1618:36AvenidaUnderground Metro StationTicket Kiosk Metal and plastic3minAF and MO63,68A4006.01.16?Restauradores → Baixa-Chiado??Inside Metro Carriage Horizontal Support PostMetal1min17secAF and MO408,00A4106.01.1618:49Restauradores38°?42′?54″?N9°?08′?29″?WUnderground Metro StationBenchwood3minAF and MO49,76A4206.01.1618:49RestauradoresUnderground Metro StationTicket ValidationPlastic3minAF and MO80,00A4306.01.16?Baixa-Chiado → Terreiro do Pa?o??Inside Metro Carriage SeatVelvet and plastic1min17secAF and MO34,08A4406.01.1619:03Baixa-Chiado38°?42′?38″?N9°?08′?21″?WUnderground Metro StationInfo PlacardAcrylic3minAF and MO57,92A4506.01.1619:03Baixa-ChiadoUnderground Metro StationGarbage canMetal3minAF and MO24,48A4606.01.16?Terreiro do Pa?o → Santa Apolónia ??Inside Metro Carriage Vertical Support PostMetal3minAF and MO28,00A4706.01.1619:22Terreiro do Pa?o38°?42′?23″?N9°?08′?07″?WUnderground Metro StationInfo buttonMetal and plastic3minAF and MO42,40A4806.01.1619:22Terreiro do Pa?oUnderground Metro StationTicket ValidationPlastic3minAF and MO74,56A4906.01.16Terreiro do Pa?o → Santa Apolónia Inside Metro Carriage Air conditionerMetal3minAF and MO87,20A5006.01.1619:40Santa Apolónia 38°?42′?45″?N9°?07′?24″?WUnderground Metro StationTurnstileGlass and rubber3minAF and MO98,40A5106.01.1619:40Santa Apolónia Underground Metro StationElevatorMetal and Glass3minAF and MO56,64Acontrol06.01.16?Amadora Este ??Underground Metro Station??0min30secAF and MO<0,50Supplementary table SEQ Supplementary_table \* ARABIC 1 - - Detailed description of the samples that took place in January of 2016 in Lisbon Subway. LineTime (hr)SiteDescriptionPlaceMaterialSampling Duration (minutes)Quant Yield (total ng)A15Amadora Este/AlfornelosSCVertical Support PostMetal328.0Amadora EsteSSTurnstileGlass and rubber3104.8Amadora EsteSSElevatorMetal and glass393.2Alfornelos/PontinhaSCBench SupportMetal1134.4AlfornelosSSHandrailMetal361.1AlfornelosSSEscalatorRubber354.116Pontinha/ Carnide SCWindowGlass135.7PontinhaSSTicket Kiosk Metal and plastic386.4Pontinha SSPayphoneMetal and plastic376.8Carnide/Colégio Militar/LuzSCHorizontal Support PostMetal127.4Carnide SSTicket ValidationPlastic382.4Carnide SSBenchwood341.6Colégio Militar/Luz/Alto dos Moinhos SCSeatVelvet and plastic132.2Colégio Militar/LuzSSInfo PlacardAcrylic3147.2Colégio Militar/LuzSSGarbage canMetal343.7Alto dos Moinhos/LaranjeirasSCVertical Support PostMetal1152.0Alto dos MoinhosSSTurnstileGlass and rubber349.317Laranjeiras/Jardim ZoológicoSCBench SupportMetal142.1LaranjeirasSSHandrailMetal350.2LaranjeirasSSPayphoneMetal and plastic368.8Jardim Zoológico/Pra?a de Espanha SCWindowGlass184.0Jardim ZoológicoSSTicket Kiosk Metal and plastic3122.4Jardim ZoológicoSSBenchwood337.8Pra?a de Espanha/S?o Sebasti?oSCHorizontal Support PostMetal13.5A17Pra?a de EspanhaSSTicket ValidationPlastic338.2Pra?a de EspanhaSSInfo PlacardAcrylic340.5S?o Sebasti?o/Parque SCSeatVelvet and plastic157.3S?o Sebasti?oSSGarbage canMetal336.5S?o Sebasti?oSSInfo buttonMetal and plastic328.818Parque/Marquês de PombalSCVertical Support PostMetal14.7ParqueSSPayphoneMetal and plastic3105.6ParqueSSTurnstileGlass and rubber323.2Marquês do Pombal/AvenidaSCHorizontal Support PostMetal121.9Marquês do PombalSSHandrailMetal370.9Marquês do PombalSSVending machineAcrylic and Plastic 353.9Avenida/Restauradores SCWindowGlass1100.0AvenidaSSEscalatorRubber3108.0AvenidaSSTicket Kiosk Metal and plastic363.7Restauradores/Baixa-ChiadoSCHorizontal Support PostMetal1408.0RestauradoresSSBenchwood349.8RestauradoresSSTicket ValidationPlastic380.019Baixa-Chiado/Terreiro do Pa?oSCSeatVelvet and plastic134.1Baixa-ChiadoSSInfo PlacardAcrylic357.9Baixa-ChiadoSSGarbage canMetal324.5Terreiro do Pa?o/Santa Apolónia SCVertical Support PostMetal328.0Terreiro do Pa?oSSInfo buttonMetal and plastic342.4Terreiro do Pa?oSSTicket ValidationPlastic374.6Terreiro do Pa?o/Santa Apolónia SCAir conditionerMetal387.2Santa Apolónia SSTurnstileGlass and rubber398.4Santa Apolónia SSElevatorMetal and Glass356.6B15Aeroporto/Encarna??oSCVertical Support PostMetal252.7B15AeroportoSSTurnstileGlass and rubber3168.3AeroportoSSElevatorMetal and glass3223.2Encarna??o/MoscavideSCBench SupportMetal2304.2Encarna??oSSHandrailMetal3304.2Encarna??oSSEscalatorRubber352.016Moscavide/Oriente SCWindowGlass1120.6MoscavideSSTicket Kiosk Metal and plastic3313.2MoscavideSSBenchWood3226.8Oriente/Cabo RuivoSCHorizontal Support PostMetal2113.4OrienteSSTicket ValidationPlastic3105.3OrienteSSInfo PlacardAcrylic3142.2Cabo Ruivo/Olivais SCSeatVelvet and plastic119.1Cabo RuivoSSGarbage canMetal326.5Cabo RuivoSSInfo buttonMetal and plastic322.1OlivaisSSTicket ValidationPlastic352.4OlivaisSSElevator Metal and glass345.717Chelas/Bela Vista SCBench SupportMetal118.4ChelasSSTurnstileGlass and rubber3216.0ChelasSSHandrailMetal3669.6Bela Vista/Olaias SCWindowGlass113.6Bela VistaSSEscalatorRubber 3318.6Bela VistaSSTicket Kiosk Metal and plastic3466.2OlaiasSSBenchWood 3177.3OlaiasSSInfo PlacardAcrylic349.713Alameda/Saldanha SCSeatVelvet and plastic3150.3Saldanha/S?o Sebasti?oSCVertical Support PostMetal2157.5Alameda/S?o Sebasti?oSCAir conditionerMetal2246.6C10Telheiras/Campo Grande SCVertical Support PostMetal25.5Telheiras SSTurnstileGlass and rubber32.5Telheiras SSElevatorMetal and glass32.6Campo Grande/AlvaladeSCBench SupportMetal211.3Alvalade/RomaSCWindowGlass12.5AlvaladeSSHandrailMetal 311.0AlvaladeSSTicket Kiosk Metal and plastic37.5Roma/AreeiroSCHorizontal Support PostMetal13.0RomaSSBench Wood 39.5RomaSSTicket ValidationPlastic37.6Areeiro/Alameda SCSeatVelvet and plastic14.3AreeiroSSInfo PlacardAcrylic37.9AreeiroSSGarbage canMetal35.211Alameda/ ArroiosSCVertical Support PostMetal16.9AlamedaSSInfo buttonMetal and plastic35.2AlamedaSSVending Machine Acrylic and Plastic 35.9Arroios/AnjosSCBench SupportMetal12.6ArroiosSSTurnstileGlass and rubber34.8ArroiosSSHandrailMetal33.7Anjos/IntendenteSCWindowGlass12.7AnjosSSEscalatorRubber 31.8AnjosSSTicket Kiosk Metal and plastic32.712Intendente/Martim MonizSCHorizontal Support PostMetal13.7IntendenteSSBenchWood 35.6IntendenteSSInfo PlacardAcrylic35.7Martim Moniz/RossioSCSeatVelvet and plastic14.1Martim MonizSSTicket ValidationPlastic35.3C12Martim MonizSSGarbage canMetal32.0Rossio/Baixa-ChiadoSCVertical Support PostMetal31.6RossioSSVending Machine Acrylic and Plastic 32.413Baixa-Chiado/Cais do SodréSCBench SupportMetal35.4Telheiras/Alvalade SCAir conditionerMetal23.2Cais do SodréSSElevatorMetal and Glass311.1Cais do SodréSSEscalatorRubber 32.4D10Odivelas/Senhor RoubadoSCBench SupportMetal364.5OdivelasSSTurnstileGlass and rubber339.8OdivelasSSElevatorMetal and glass343.2Senhor Roubado/AmeixoeiraSCVertical Support PostMetal233.0Senhor RoubadoSSHandrailMetal347.7Senhor RoubadoSSEscalatorRubber356.8Ameixoeira/LumiarSCWindowGlass1115.2AmeixoeiraSSTicket Kiosk Metal and plastic332.3AmeixoeiraSSBenchWood344.311Lumiar/Quinta das ConchasSCHorizontal Support PostMetal114.1LumiarSSTicket ValidationPlastic3347.2LumiarSSInfo PlacardAcrylic333.0Quinta das Conchas/Campo GrandeSCSeatVelvet and plastic1518.4Quinta das ConchasSSGarbage canMetal331.0Quinta das ConchasSSInfo buttonMetal and plastic3169.6Campo Grande/Cidade UniversitáriaSCVertical Support PostMetal234.9Campo GrandeSSVending Machine Acrylic and plastic 338.2Campo GrandeSSPayphone Metal and plastic338.6Cidade Universitária/Entre CamposSCBench SupportMetal264.2Cidade UniversitáriaSSTicket ValidationPlastic357.9D11Cidade UniversitáriaSSHandrailStone 367.012Entre Campos/ Campo PequenoSCWindowGlass11.4Entre CamposSSTurnstileGlass and rubber353.9Entre CamposSSTicket Kiosk Metal and plastic341.0Campo Pequeno/SaldanhaSCHorizontal Support PostMetal126.0Campo PequenoSSBenchWood 383.2Campo PequenoSSInfo PlacardAcrylic333.2Saldanha/PicoasSCSeatVelvet and plastic128.2SaldanhaSSGarbage canMetal321.6SaldanhaSSInfo buttonMetal and Plastic344.614Picoas/Marquês de PombalSCVertical Support PostMetal342.4PicoasSSTurnstileGlass and rubber3600.0PicoasSSHandrailMetal360.4Marquês de Pombal/RatoSCBench SupportMetal343.0RatoSSElevatorMetal and Glass347.6RatoSSEscalator Rubber 389.6Odivelas/Senhor RoubadoSCAir conditionerMetal356.8SaldanhaSSBathroom Diverse 38.7SaldanhaSSAir conditioner (Attending Box)Metal345.2Legend: SC – subway car; SS – Subway station.Supplementary table 2 - Statistical analyses performed to determine the influence of line (A), surface (B), material (C), sampling duration (D), and sampled period (E) on DNA concentration.ABCDEABCDESupplementary table 3 – Taxonomic representation of the microorganism identified in the subway system.DomainPhylumClassOrderFamilyGenusSpeciesBacteriaActinobacteriaActinobacteriaActinomycetalesDermabacteraceae?BrachybacteriumBrachybacterium sp.DermacoccaceaeDermacoccusDermacoccus sp Ellin185MicrococcaceaeKocuriaKocuria sp.?KocuriaK. rhizophilaMicrococcaceaeMicrococcusM. luteusRothiaRothia sp.R. dentocariosa??R. mucilaginosaPropionibacteriaceaePropionibacteriumP. acnes?StreptomycetaceaeStreptomycesS. coelicoflavusBifidobacterialesBifidobacteriaceaeBifidobacteriumB. animalisBacteroidetesFlavobacteriiaFlavobacterialesFlavobacteriaceaeChryseobacteriumChryseobacterium sp.C. gleumEmpedobacterE. brevis???RiemerellaRiemerella sp.SphingobacteriiaSphingobacterialesSphingobacteriaceaePedobacterPedobacter sp:SphingobacteriumSphingobacterium sp.????SphingobacteriumSphingobacterium sp IITKGP BTPF85Deinococcus ThermusDeinococciDeinococcalesDeinococcaceaeDeinococcusDeinococcus sp.FirmicutesBacilliBacillalesBacillaceaeBacillusB. nealsoniiLysinibacillusLysinibacillus sp.?L. sphaericusBacillales nonameExiguobacteriumExiguobacterium sp.Exiguobacterium sp MH3E. sibiricumStaphylococcaceaeMacrococcusM. caseolyticusStaphylococcusS. epidermidisS. equorumS. haemolyticus??S. saprophyticusLactobacillalesAerococcaceaeAerococcusA. viridansCarnobacteriaceaeCarnobacteriumCarnobacterium sp WN1359??C. maltaromaticumEnterococcaceaeEnterococcusE. casseliflavusE. duransE. faecalisE. faeciumE. hiraeE. italicusE. mundtii??E. sulfureusLactobacillaceaeLactobacillusL. delbrueckiiLeuconostocaceaeLeuconostocL. carnosumL. mesenteroidesL. pseudomesenteroides?WeissellaWeissella sp.StreptococcaceaeLactococcusL. lactis?StreptococcusS. thermophilusClostridiaClostridialesEubacteriaceaeEubacteriumE. rectaleLachnospiraceaeBlautiaR. torques???RuminococcaceaeSubdoligranulumSubdoligranulum sp.ProteobacteriaAlphaproteobacteriaCaulobacteralesCaulobacteraceaeAsticcacaulisAsticcacaulis sp.BrevundimonasBrevundimonas sp.?B. diminutaCaulobacterCaulobacter sp.C. vibrioidesRhizobialesBradyrhizobiaceaeRhodopseudomonasR. palustrisBrucellaceae??BrucellaBrucella sp.?B. ovisRhizobiaceaeAgrobacteriumAgrobacterium sp.A. tumefaciens?RhizobiumR. lupini?Rhodobiaceae??RhodobacteralesRhodobacteraceaeParacoccusParacoccus sp.??P. denitrificansSphingomonadalesSphingomonadaceaeNovosphingobiumN. lindaniclasticumSphingobiumSphingobium sp.S. yanoikuyaeBetaproteobacteriaBurkholderialesAlcaligenaceaeAchromobacterA. piechaudiiBordetellaBordetella sp.BurkholderiaceaeCupriavidusCupriavidus sp.BurkholderiaceaeRalstoniaRalstonia sp.Burkholderiales nonameThiomonasThiomonas amonadaceaeComamonasComamonas amonas sp B 9C. testosteroniDelftiaDelftia?sp.D. acidovorans?PolaromonasPolaromonas sp.OxalobacteraceaeDuganellaD. zoogloeoidesHerbaspirillumHerbaspirillum sp.JanthinobacteriumJanthinobacterium sp.MassiliaMassilia sp.?M. timonae?GallionellalesGallionellaceae??GammaproteobacteriaChromatialesChromatiaceaeRheinheimeraRheinheimera sp.EnterobacterialesEnterobacteriaceaeCitrobacterCitrobacter sp.Citrobacter freundiiEnterobacterEnterobacter cloacae?Enterobacter hormaecheiErwiniaErwinia billingiaeEscherichiaEscherichia sp.E. coli?E. hermanniiKlebsiellaKlebsiella sp.Klebsiella oxytoca?Klebsiella pneumoniaePantoeaPantoea sp.P. agglomeransP. dispersa?P. vagansPasteurellalesPasteurellaceaeHaemophilusH. influenzaePseudomonadalesMoraxellaceaeAcinetobacterAcinetobacter sp.Acinetobacter sp ATCC 27244A. baumanniiA. bereziniaeA. bouvetiiA. guillouiaeA. haemolyticusA. indicusA. johnsoniiA. juniiA. lwoffiiA. oleivoransA. parvusA. pittii calcoaceticus nosocomialisA. radioresistensA. radioresistensA. schindleriA. towneriA. ursingiiEnhydrobacterE. aerosaccusPsychrobacterPsychrobacter sp 1501 2011P. aquaticusP. arcticus??P. cryohalolentisPseudomonadaceaePseudomonas?Pseudomonas sp.PseudomonasPseudomonas sp 313Pseudomonas sp HPB0071P. alcaligenesP. chloritidismutansP. fragiP. fulvaP. luteolaP. mandeliiP. mendocinaP. psychrophilaP. psychrotoleransP. putidaP. stutzeriP. synxanthaP. syringae?P. taiwanensisXanthomonadalesXanthomonadaceaePseudoxanthomonasPseudoxanthomonas sp.StenotrophomonasStenotrophomonas sp.?S. maltophilia???Xanthomonadaceae nonamePseudomonas geniculataTenericutesMollicutesMycoplasmatalesMycoplasmataceaeMycoplasmaM. wenyoniiFungiAscomycotaEurotiomycetesEurotialesAspergillaceae??SaccharomycetesSaccharomycetalesDebaryomycetaceaeDebaryomycesD. hansenii??SaccharomycetaceaeTorulasporaT. delbrueckiiSordariomycetesHypocrealesNectriaceaeFusariumFusarium sp.????F. graminearumVirusViruses nonameViruses nonameCaudoviralesPodoviridaeEpsilon15-like virus??P22-like virus?SiphoviridaeSiphoviridae_nonamePropionibacterium phage PHL060L00??????Staphylococcus phageSupplementary table 4 – Possible source for the microbial diversity observed in the Lisbon Subway.Species Relative Abundance (average %)Type of organism Possible sources to microorganism A. lwoffii39.81Gram -Normal flora of the airways, skin, and urogenital tract Pseudomonas unclassified 10.08Gram -nd Massilia unclassified 7.48Gram -Environmental (air and water)Pantoea unclassified 7.43Gram -nd A. ursingii6.51Gram -EnvironmentalNormal flora of the skin and mouth M. timonae5.19Gram -nd E. aerosaccus3.79Gram -Environmental Normal flora of the skinA. johnsonii2.23Gram -Normal flora of the skin and gastrointestinal tract P. stutzeri1.45Gram -Environmental (soil and water )Sphingobacterium sp IITKGP BTPF851.42Gram -nd S. maltophilia1.13Gram -Environmental (plants, soil, and water)A. unclassified 1.07Gram -nd A. radioresistens1.00Gram -EnvironmentalNormal flora of the skin and gastrointestinal tract A. pittii calcoaceticus nosocomialis0.95Gram -nd P. putida0.91Gram -Environmental (soil)P.agglomerans0.74Gram -Environmental (air, plants, soil, and water)Normal flora of the gastrointestinal tract and urogentital tract Sphingobacterium unclassified 0.60Gram -nd E.billingiae0.54Gram -Environmental (plants)E. brevis0.50Gram -nd Cupriavidus unclassified 0.49Gram -Environmental (soil)B. nealsonii0.43Gram +nd E. cloacae0.42Gram -Normal flora of the gastrointestinal tractPsychrobacter sp 1501 20110.42Gram -nd P. dispersa0.34Gram -nd Janthinobacterium unclassified 0.33Gram -nd Brevundimonas unclassified 0.29Gram -nd Escherichia unclassified 0.28Gram -Normal flora of the gastrointestinal tractChryseobacterium unclassified 0.28Gram -nd Stenotrophomonas unclassified 0.27Gram -Environmental (soil)Normal flora of the gastrointestinal tractK. pneumoniae0.26Gram -Environmental (plants, soil, and water )Normal flora of the arways, skin, gastrointestinal tract, and urogentital tract P. psychrotolerans0.23Gram -nd Agrobacterium unclassified 0.22Gram -nd Comamonas sp B 90.17Gram -nd B. diminuta0.16Gram -Environmental Normal flora of the mouthA. tumefaciens0.13Gram -Environmental (plants and soil)M. wenyonii0.12?nd R. lupini0.12Gram -Environmental (plants and soil)A. bereziniae0.09Gram -Environmental Normal flora of the skinP. luteola0.09Gram -EnvironmentalKlebsiella unclassified 0.09Gram -nd K. oxytoca0.08Gram -Normal flora of the gastrointestinal tractA. baumannii0.07Gram -Normal flora of the skin and urogenital tract E.hermannii0.07Gram -Normal flora of the blood and urogenital tractS. saprophyticus0.07Gram +Normal flora of the skin and gastrointestinal tract and urogenital tract Pedobacter unclassified 0.07Gram -Environmental (Sludge and soil)Sphingobium unclassified 0.06Gram -Environmental (soil)Citrobacter unclassified 0.06Gram -Environmental (sewage, soil, and water)Normal flora of the gastrointestinal tractA. schindleri0.06Gram -nd E. casseliflavus0.05Gram +Normal flora of the mouthL. lactis0.05Gram +Environmental (plants)Food associatedA. viridans0.05Gram +Normal flora of the urogenital tractFood associatedCarnobacterium sp WN13590.04Gram +Food associatedEnvironmental (water)Comamonas unclassified 0.03Gram -nd Acinetobacter sp ATCC 272440.03Gram -Normal flora of the skinE. faecalis0.03Gram +Normal flora of the blood, gastrointestinal tract, urogenital tract, and lymph nodes Riemerella unclassified 0.03Gram -Animal associatedP. mandelii0.03Gram -Environmental (water)Exiguobacterium sp MH30.03Gram +Environmental (ice and soil)L. mesenteroides0.02Gram +Normal flora of the gastrointestinal tractAsticcacaulis unclassified 0.02Gram -Environmental (soil and water)E. mundtii0.02Gram +Animal associatedEnvironmental (plants and soil)P22likevirus unclassified 0.02?nd S. yanoikuyae0.02Gram -Environmental (soil)C. maltaromaticum0.02Gram +EnvironmentalFood associatedP. geniculata0.01Gram -Environmental (water)A. haemolyticus0.01Gram -Normal flora of the airwaysM. luteus0.01Gram +Environmental (air and water)Animal associatedNormal flora of the skin and gastrointestinal tract S. thermophilus0.01Gram +Food associatedE.sulfureus0.01Gram +Food associatedP. psychrophila0.01Gram -Food associatedE. hirae0.01Gram +nd Pseudomonas sp HPB00710.01Gram -nd A. guillouiae0.01Gram -Environmental (oil)Pseudomonas sp 3130.01Gram -nd Paracoccus unclassified 0.01Gram -nd P. fragi0.01Gram -Food associatedP. vagans0.01Gram -Environmental (plants)Propionibacterium phage PHL060L000.01?Normal flora of the skinDermacoccus sp Ellin1850.01Gram +Normal flora of the skinP. acnes0.01Gram +Normal flora of the skin Rheinheimera unclassified 0.00?nd E. coli0.00Gram -Normal flora of the gastrointestinal tract and urogentital tract Ralstonia unclassified 0.00Gram -nd K. rhizophila0.00Gram +Environmental (soil)L. pseudomesenteroides0.00Gram +Environmental (plants)Food associatedP. fulva0.00Gram -Environmental (plants and oil)Thiomonas unclassified 0.00Gram -EnvironmentalKocuria unclassified 0.00Gram +Normal flora of the skin and gastrointestinal tractDelftia unclassified 0.00Gram -nd Caulobacter unclassified 0.00Gram -nd P. synxantha0.00Gram -nd P. mendocina0.00Gram -Environmental (soil and water )P. chloritidismutans0.00Gram -nd Epsilon15likevirus unclassified 0.00?nd A. piechaudii0.00Gram -Environmental (soil)Normal flora of the airways and blood C. testosteroni0.00Gram -Environmental (sludge)A. towneri0.00Gram -Environmental (sludge)Staphylococcus phage PVL0.00?nd D. acidovorans0.00Environmental (oil, sludge, soil, and water)Herbaspirillum unclassified 0.00Gram -Environmental (plants and soil)E. sibiricum0.00Gram +EnvironmentalE. faecium0.00Gram +Normal flora of the blood, gastrointestinal tract, and urogentital tract Exiguobacterium unclassified 0.00Gram +Environmental D. zoogloeoides0.00Gram -Environmental (sludge and water)A. oleivorans0.00Gram -Environmental (sludge, soil, and water)P alcaligenes0.00Gram -Environmental (oil, sludge and soil)P. cryohalolentis0.00Gram -Environmental (soil)C. gleum0.00Gram -Normal flora of the urogenital tractEnvironmental (soil and water)P. aquaticus0.00Gram -Environmental (water)M. caseolyticus0.00Gram +Food associatedWeissella unclassified 0.00Gram +EnvironmentalNormal flora of the gastrointestinal tractFood associatedN. lindaniclasticum0.00Gram -Environmental (soil) P. arcticus0.00Gram -Environmental (soil)A. indicus0.00Gram -Environmental (soil) S. equorum0.00Gram +Animal and Food associatedR. torques0.00Gram +Normal flora of the gastrointestinal tractBrachybacterium unclassified 0.00Gram +EnvironmentalFood associatedLysinibacillus unclassified 0.00Gram +Environmental (soil)P. syringae0.00?Environmental (plants)A. bouvetii0.00?Environmental (sludge)Deinococcus unclassified 0.00Gram +Environmental (soil) Bordetella unclassified 0.00Gram -Animal associatedB. ovis0.00Gram -Food associatedE. italicus0.00Gram +Food associatedNormal flora of the mouthS. coelicoflavus0.00Gram +Environmental (soil)A. parvus0.00Gram -Animal associatedFusarium unclassified 0.00Fungind E. durans0.00Gram +Food associatedNormal flora of the gastrointestinal tract and urogentital tract S. haemolyticus0.00Gram +Normal flora of the skin and urogenital tract L. carnosum0.00Gram +Food associatedC. vibrioides0.00Gram -EnvironmentalP. denitrificans0.00Gram -Environmental (sewage, sludge, and soil)R. dentocariosa0.00Gram +Normal flora of the airway, blood, and mouth A. junii0.00Gram -Normal flora of the arways, blood, and gastrointestinal tractSubdoligranulum unclassified 0.00Gram -Normal flora of the gastrointestinal tractH. influenzae0.00Gram -Normal flora of the arways and bloodL. delbrueckii0.00Gram +Normal flora of the gastrointestinal tract and urogentital tract B. animalis0.00Gram +nd P. taiwanensis0.00Gram -Environmental (soil)R. palustris0.00Gram -EnvironmentalL. sphaericus0.00Gram +Environmental (sludge, soil, and water)F. graminearum0.00FungiEnvironmental (plants and soil)E. rectale0.00Gram +Normal flora of the gastrointestinal tractPseudoxanthomonas unclassified 0.00Gram -Environmental (soil)T. delbrueckii0.00FungiFood associatedRothia unclassified 0.00Gram +Normal flora of the gastrointestinal tract and mouthPolaromonas unclassified 0.00Gram -Environmental (soil and water)E. hormaechei0.00Gram -Normal flora of the blood, mouth and urogenital tract S. epidermidis0.00Gram +Normal flora of the skin and urogenital tract R. mucilaginosa0.00Gram +Normal flora of the arways and mouthD. hansenii0.00YeastFood associatedSupplementary table 5 – Description of the sources and Superclass’s of active pathways. Active PathwaysExpected Taxonomic RangeSuperclasses12DICHLORETHDEG-PWY: 1,2-dichloroethane degradationBacteriaDegradation/Utilization/Assimilation?→?Chlorinated Compounds Degradation3-HYDROXYPHENYLACETATE-DEGRADATION-PWY: 4-hydroxyphenylacetate degradationProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation4-HYDROXYMANDELATE-DEGRADATION-PWY: 4-hydroxymandelate degradationBacteria; Fungi Degradation/Utilization/Assimilation?→?Aromatic Compounds Degradation4TOLCARBDEG-PWY: 4-toluenecarboxylate degradationProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds DegradationAEROBACTINSYN-PWY: aerobactin biosynthesisProteobacteriaBiosynthesis?→?Siderophore BiosynthesisALLANTOINDEG-PWY: superpathway of allantoin degradation in yeastYeastsDegradation/Utilization/Assimilation?→?Amines and Polyamines Degradation?→?Allantoin DegradationANAEROFRUCAT-PWY: homolactic fermentationArchaea; Bacteria; Eukaryota Generation of Precursor Metabolites and Energy?→?FermentationANAGLYCOLYSIS-PWY: glycolysis III (from glucose)Bacteria; Eukaryota Generation of Precursor Metabolites and Energy?→?GlycolysisARG+POLYAMINE-SYN: superpathway of arginine and polyamine biosynthesisBacteriaBiosynthesis?→?Amines and Polyamines BiosynthesisARGDEG-IV-PWY: arginine degradation VIII (arginine oxidase pathway)ProteobacteriaDegradation/Utilization/Assimilation?→?Amino Acids Degradation→?Proteinogenic Amino Acids Degradation?→?L-arginine DegradationARGDEG-PWY: superpathway of arginine, putrescine, and 4-aminobutyrate degradationBacteriaDegradation/Utilization/Assimilation?→?Amino Acids Degradation→?Proteinogenic Amino Acids Degradation?→?L-arginine DegradationARGININE-SYN4-PWY: ornithine de novo biosynthesisMetazoaBiosynthesis?→?Amino Acids Biosynthesis?→?Other Amino Acid Biosynthesis?→?L-Ornithine BiosynthesisARGSYN-PWY: arginine biosynthesis I (via L-ornithine)Archaea; Bacteria; ViridiplantaeBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-arginine BiosynthesisARGSYNBSUB-PWY: arginine biosynthesis II (acetyl cycle)Archaea; Bacteria; Fungi; ViridiplantaeBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-arginine BiosynthesisARO-PWY: chorismate biosynthesis IBacteria; Eukaryota Biosynthesis?→?Aromatic Compounds Biosynthesis?→?Chorismate BiosynthesisSuperpathwaysASPASN-PWY: superpathway of aspartate and asparagine biosynthesis; interconversion of aspartate and asparagineBacteriaBiosynthesis?→?Amino Acids BiosynthesisAST-PWY: arginine degradation II (AST pathway)ProteobacteriaDegradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Proteinogenic Amino Acids Degradation?→?L-arginine DegradationBIOTIN-BIOSYNTHESIS-PWY: biotin biosynthesis IBacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Vitamins Biosynthesis?→?Biotin BiosynthesisCALVIN-PWY: Calvin-Benson-Bassham cycleBacteria; Eukaryota Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis; Degradation/Utilization/Assimilation → C1 Compounds Utilization and Assimilation → CO2 Fixation → Autotrophic CO2 Fixation; Generation of Precursor Metabolites and Energy → PhotosynthesisCARNMET-PWY: L-carnitine degradation IProteobacteriaDegradation/Utilization/Assimilation?→?Amines and Polyamines Degradation?→?Carnitine DegradationCATECHOL-ORTHO-CLEAVAGE-PWY: catechol degradation to &β-ketoadipateProteobacteria; Actinobacteria Degradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Catechol DegradationCENTBENZCOA-PWY: benzoyl-CoA degradation II (anaerobic)BacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Benzoyl-CoA DegradationCENTFERM-PWY: pyruvate fermentation to butanoateProteobacteria; Firmicutes Generation of Precursor Metabolites and Energy?→?Fermentation?→?Pyruvate FermentationCITRULBIO-PWY: citrulline biosynthesisMammaliaBiosynthesis?→?Amino Acids Biosynthesis?→?Other Amino Acid Biosynthesis?→?L-citrulline BiosynthesisCOA-PWY: coenzyme A biosynthesisArchaea; Bacteria; Eukaryota Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Coenzyme A BiosynthesisCOBALSYN-PWY: adenosylcobalamin salvage from cobinamide IProteobacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Vitamins Biosynthesis?→?Cobalamin Biosynthesis?→?Adenosylcobalamin Biosynthesis?→Adenosylcobalamin Salvage from CobinamideCOLANSYN-PWY: colanic acid building blocks biosynthesisProteobacteriaBiosynthesis?→?Carbohydrates BiosynthesisSuperpathwaysCRNFORCAT-PWY: creatinine degradation IBacteriaDegradation/Utilization/Assimilation?→?Amines and Polyamines Degradation?→?Creatinine DegradationDAPLYSINESYN-PWY: lysine biosynthesis IBacteriaBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-lysine BiosynthesisDENITRIFICATION-PWY: nitrate reduction I (denitrification)Archaea; Bacteria; FungiDegradation/Utilization/Assimilation?→?Inorganic Nutrients Metabolism?→?Nitrogen Compounds Metabolism?→?Denitrification; Degradation/Utilization/Assimilation → Inorganic Nutrients Metabolism → Nitrogen Compounds Metabolism → Nitrate Reduction; Generation of Precursor Metabolites and Energy → Respiration → Anaerobic RespirationDENOVOPURINE2-PWY: superpathway of purine nucleotides de novo biosynthesis IIBacteriaBiosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Purine Nucleotide Biosynthesis?→Purine Nucleotides De Novo BiosynthesisDTDPRHAMSYN-PWY: dTDP-L-rhamnose biosynthesis IArchaea; Bacteria Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar Biosynthesis?→?dTDP-L-Rhamnose-Biosynthesis; Biosynthesis → Cell Structures Biosynthesis → Lipopolysaccharide Biosynthesis → O-Antigen BiosynthesisECASYN-PWY: enterobacterial common antigen biosynthesisProteobacteriaBiosynthesis?→?Cell Structures BiosynthesisSuperpathwaysENTBACSYN-PWY: enterobactin biosynthesisProteobacteriaBiosynthesis?→?Siderophore Biosynthesis SuperpathwaysFAO-PWY: fatty acid &β-oxidation IBacteria; Eukaryota Degradation/Utilization/Assimilation?→?Fatty Acid and Lipids Degradation?→?Fatty Acids DegradationFASYN-ELONG-PWY: fatty acid elongation -- saturatedBacteria; ViridiplantaeBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid BiosynthesisFASYN-INITIAL-PWY: superpathway of fatty acid biosynthesis initiation (E. coli)Bacteria; Eukaryota Biosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid BiosynthesisFERMENTATION-PWY: mixed acid fermentationBacteria; Fungi Generation of Precursor Metabolites and Energy?→?FermentationFOLSYN-PWY: superpathway of tetrahydrofolate biosynthesis and salvageBacteria; Fungi Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Vitamins Biosynthesis?→Folate BiosynthesisFUCCAT-PWY: fucose degradationBacteriaDegradation/Utilization/Assimilation?→?Carbohydrates Degradation→?Sugars DegradationGALACTARDEG-PWY: D-galactarate degradation IBacteriaDegradation/Utilization/Assimilation?→?Carboxylates Degradation?→?Sugar Acids Degradation?→?D-Galactarate Degradation; Degradation/Utilization/Assimilation → Secondary Metabolites Degradation → Sugar Derivatives Degradation → Sugar Acids Degradation → D-Galactarate DegradationGALACTUROCAT-PWY: D-galacturonate degradation IBacteriaDegradation/Utilization/Assimilation?→?Carboxylates Degradation?→?Sugar Acids Degradation?→?D-Galactarate Degradation; Degradation/Utilization/Assimilation → Secondary Metabolites Degradation → Sugar Derivatives Degradation → Sugar Acids Degradation → D-Galactarate DegradationGALLATE-DEGRADATION-I-PWY: gallate degradation IIBacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Gallate DegradationGALLATE-DEGRADATION-II-PWY: gallate degradation IBacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Gallate DegradationGLCMANNANAUT-PWY: superpathway of N-acetylglucosamine, N-acetylmannosamine and N-acetylneuraminate degradationBacteriaDegradation/Utilization/Assimilation?→?Amines and Polyamines DegradationGLUCARDEG-PWY: D-glucarate degradation IBacteriaDegradation/Utilization/Assimilation?→?Carboxylates Degradation?→?Sugar Acids Degradation?→?D-Glucarate Degradation; Degradation/Utilization/Assimilation → Secondary Metabolites Degradation → Sugar Derivatives Degradation → Sugar Acids Degradation → D-Glucarate DegradationGLUCARGALACTSUPER-PWY: superpathway of D-glucarate and D-galactarate degradationBacteriaSuperpathwaysGLUCONEO-PWY: gluconeogenesis IArchaea; Bacteria; Fungi; ViridiplantaeBiosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?GluconeogenesisGLUCOSE1PMETAB-PWY: glucose and glucose-1-phosphate degradationBacteriaDegradation/Utilization/Assimilation?→?Carbohydrates Degradation→?Sugars DegradationGLUDEG-I-PWY: GABA shuntMetazoaDegradation/Utilization/Assimilation?→?Amines and Polyamines Degradation?→?4-Aminobutanoate Degradation; Degradation/Utilization/Assimilation → Amino Acids Degradation → Proteinogenic Amino Acids Degradation → L-glutamate DegradationGLUTORN-PWY: ornithine biosynthesisArchaea; BacteriaBiosynthesis?→?Amino Acids Biosynthesis?→?Other Amino Acid Biosynthesis?→?L-Ornithine BiosynthesisGLYCOCAT-PWY: glycogen degradation IBacteriaBiosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis; Degradation/Utilization/Assimilation → Carbohydrates Degradation → Polysaccharides Degradation → Glycogen Degradation; Degradation/Utilization/Assimilation → Polymeric Compounds Degradation → Polysaccharides Degradation → Glycogen DegradationGLYCOGENSYNTH-PWY: glycogen biosynthesis I (from ADP-D-Glucose)BacteriaBiosynthesis?→?Carbohydrates Biosynthesis?→?Polysaccharides Biosynthesis?→?Glycogen and Starch BiosynthesisGLYCOLATEMET-PWY: glycolate and glyoxylate degradation IBacteriaDegradation/Utilization/Assimilation?→?Carboxylates Degradation→?Glycolate DegradationGLYCOLYSIS-E-D: superpathway of glycolysis and Entner-DoudoroffBacteria; Eukaryota Generation of Precursor Metabolites and Energy SuperpathwaysGLYCOLYSIS-TCA-GLYOX-BYPASS: superpathway of glycolysis, pyruvate dehydrogenase, TCA, and glyoxylate bypassBacteriaGeneration of Precursor Metabolites and EnergySuperpathwaysGLYCOLYSIS: glycolysis I (from glucose-6P)Archaea; Bacteria; Eukaryota Generation of Precursor Metabolites and Energy?→?GlycolysisGLYOXYLATE-BYPASS: glyoxylate cycleArchaea; Bacteria; Eukaryota Generation of Precursor Metabolites and EnergyGOLPDLCAT-PWY: superpathway of glycerol degradation to 1,3-propanediolFirmicutes; Proteobacteria Degradation/Utilization/Assimilation?→?Alcohols Degradation?→Glycerol DegradationHCAMHPDEG-PWY: 3-phenylpropanoate and 3-(3-hydroxyphenyl)propanoate degradation to 2-oxopent-4-enoateProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Phenolic Compounds DegradationHEME-BIOSYNTHESIS-II: heme biosynthesis from uroporphyrinogen-III I (aerobic)BacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Porphyrin Compounds Biosynthesis?→?Heme BiosynthesisHEMESYN2-PWY: heme biosynthesis from uroporphyrinogen-III II (anaerobic)Bacteria; Fungi; Alveolata Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Porphyrin Compounds Biosynthesis?→?Heme BiosynthesisHISDEG-PWY: histidine degradation IBacteriaDegradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Proteinogenic Amino Acids Degradation?→?L-histidine DegradationHISHP-PWY: histidine degradation VIMammaliaDegradation/Utilization/Assimilation?→?Amino Acids Degradation→?Proteinogenic Amino Acids Degradation?→?L-histidine DegradationHOMOSER-METSYN-PWY: methionine biosynthesis IBacteriaBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-methionine Biosynthesis?→?L-methionine De Novo BiosynthesisILEUDEG-PWY: isoleucine degradation IArchaea; Bacteria; Eukaryota Degradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Proteinogenic Amino Acids Degradation?→?L-isoleucine DegradationKETOGLUCONMET-PWY: ketogluconate metabolismBacteriaDegradation/Utilization/Assimilation?→?Carboxylates Degradation?→?Sugar Acids Degradation; Degradation/Utilization/Assimilation?→?Secondary Metabolites Degradation?→?Sugar Derivatives Degradation?→?Sugar Acids DegradationLACTOSECAT-PWY: lactose and galactose degradation IFirmicutesDegradation/Utilization/Assimilation?→?Carbohydrates Degradation→?Sugars Degradation?→?Galactose Degradation; Degradation/Utilization/Assimilation → Carbohydrates Degradation → Sugars Degradation → Lactose DegradationLEU-DEG2-PWY: leucine degradation IBacteria; Eukaryota Degradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Proteinogenic Amino Acids Degradation?→?L-leucine DegradationLIPASYN-PWY: phospholipasesArchaea; Bacteria; Eukaryota Degradation/Utilization/Assimilation?→?Fatty Acid and Lipids DegradationLYSDEGII-PWY: lysine degradation IIIFungiDegradation/Utilization/Assimilation?→?Amino Acids Degradation→?Proteinogenic Amino Acids Degradation?→?L-lysine DegradationLYSINE-AMINOAD-PWY: lysine biosynthesis IVEuflenozoa; FungiBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-lysine BiosynthesisLYXMET-PWY: L-lyxose degradationBacteriaDegradation/Utilization/Assimilation?→?Carbohydrates Degradation→?Sugars DegradationM-CRESOL-DEGRADATION-PWY: m-cresol degradationProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds DegradationMANNOSYL-CHITO-DOLICHOL-BIOSYNTHESIS: dolichyl-diphosphooligosaccharide biosynthesisEukaryotaBiosynthesis?→?Carbohydrates Biosynthesis?→?Oligosaccharides Biosynthesis; Macromolecule Modification?→?Protein Modification?→?Protein GlycosylationMET-SAM-PWY: superpathway of S-adenosyl-L-methionine biosynthesisBacteriaBiosynthesis?→?Amino Acids Biosynthesis?→?Individual Amino Acids Biosynthesis?→?Methionine BiosynthesisMETH-ACETATE-PWY: methanogenesis from acetateArchaeaGeneration of Precursor Metabolites and Energy?→?Respiration?→?Anaerobic Respiration?→MethanogenesisMETHYLGALLATE-DEGRADATION-PWY: methylgallate degradationBacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds DegradationMETSYN-PWY: homoserine and methionine biosynthesisBacteriaBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-methionine Biosynthesis?→?L-methionine De Novo BiosynthesisNAD-BIOSYNTHESIS-II: NAD salvage pathway IIBacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?NAD Metabolism?→NAD BiosynthesisNONMEVIPP-PWY: methylerythritol phosphate pathwayBacteriaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Terpenoids Biosynthesis?→?Hemiterpenes Biosynthesis?→?Isopentenyl Diphosphate BiosynthesisNONOXIPENT-PWY: pentose phosphate pathway (non-oxidative branch)Bacteria; Eukaryota Generation of Precursor Metabolites and Energy?→?Pentose Phosphate PathwaysOANTIGEN-PWY: O-antigen building blocks biosynthesis (E. coli)BacteriaBiosynthesis?→?Cell Structures Biosynthesis?→?Lipopolysaccharide Biosynthesis?→?O-Antigen BiosynthesisORNARGDEG-PWY: superpathway of arginine and ornithine degradationBacteriaDegradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Arginine DegradationOXIDATIVEPENT-PWY: pentose phosphate pathway (oxidative branch) IBacteria; Eukaryota Generation of Precursor Metabolites and Energy?→?Pentose Phosphate PathwaysP101-PWY: ectoine biosynthesisBacteriaBiosynthesis?→?Amines and Polyamines BiosynthesisP105-PWY: TCA cycle IV (2-oxoglutarate decarboxylase)Proteobacteria; Actinobacteria; Cyanobacteria; Euglenida Generation of Precursor Metabolites and Energy?→?TCA cycleP108-PWY: pyruvate fermentation to propionate IBacteriaGeneration of Precursor Metabolites and Energy?→?Fermentation?→?Pyruvate FermentationP124-PWY: Bifidobacterium shuntActinobacteriaDegradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Sugars DegradationGeneration of Precursor Metabolites and Energy?→?FermentationP161-PWY: acetylene degradationBacteriaDegradation/Utilization/Assimilation?→Degradation/Utilization/Assimilation - Other; Generation of Precursor Metabolites and Energy → FermentationP162-PWY: glutamate degradation V (via hydroxyglutarate)Firmicutes; FusobacteriaDegradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Proteinogenic Amino Acids Degradation?→?L-glutamate Degradation; Generation of Precursor Metabolites and Energy → FermentationP163-PWY: lysine fermentation to acetate and butyrateBacteriaDegradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Proteinogenic Amino Acids Degradation?→?L-lysine Degradation; Generation of Precursor Metabolites and Energy → FermentationP184-PWY: protocatechuate degradation I (meta-cleavage pathway)ProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Protocatechuate DegradationP185-PWY: formaldehyde assimilation III (dihydroxyacetone cycle)FungiDegradation/Utilization/Assimilation?→?C1 Compounds Utilization and Assimilation?→?Formaldehyde AssimilationP221-PWY: octane oxidationBacteria; FungiDegradation/Utilization/Assimilation?→?Degradation/Utilization/Assimilation - OtherP23-PWY: reductive TCA cycle IArchaea; Bacteria; Proteobacteria Degradation/Utilization/Assimilation?→?C1 Compounds Utilization and Assimilation?→?CO2 Fixation?→Autotrophic CO2 Fixation?→?Reductive TCA CyclesP4-PWY: superpathway of lysine, threonine and methionine biosynthesis IBacteriaBiosynthesis?→?Amino Acids Biosynthesis SuperpathwaysP41-PWY: pyruvate fermentation to acetate and lactate IBacteriaGeneration of Precursor Metabolites and Energy?→?Fermentation?→?Pyruvate FermentationSuperpathwaysP42-PWY: incomplete reductive TCA cycleArchaeaDegradation/Utilization/Assimilation?→?C1 Compounds Utilization and Assimilation?→?CO2 Fixation?→?Autotrophic CO2 Fixation?→Reductive TCA CyclesP441-PWY: superpathway of N-acetylneuraminate degradationBacteriaDegradation/Utilization/Assimilation?→?Carboxylates DegradationSuperpathwaysP562-PWY: myo-inositol degradation IBacteria; Fungi Degradation/Utilization/Assimilation?→?Secondary Metabolites Degradation?→?Sugar Derivatives Degradation?→?Sugar Alcohols DegradationP601-PWY: (+)-camphor degradationProteobacteriaDegradation/Utilization/Assimilation?→?Secondary Metabolites Degradation?→?Terpenoids Degradation→?Camphor DegradationPANTO-PWY: phosphopantothenate biosynthesis IBacteria; Fungi; ViridiplantaeBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Vitamins Biosynthesis?→Pantothenate BiosynthesisPANTOSYN-PWY: pantothenate and coenzyme A biosynthesis IBacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Coenzyme A Biosynthesis; Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Vitamins BiosynthesisPENTOSE-P-PWY: pentose phosphate pathwayBacteria; Eukaryota Generation of Precursor Metabolites and Energy?→?Pentose Phosphate PathwaysSuperpathwaysPEPTIDOGLYCANSYN-PWY: peptidoglycan biosynthesis I (meso-diaminopimelate containing)BacteriaBiosynthesis?→?Cell Structures Biosynthesis?→?Cell Wall Biosynthesis?→?Peptidoglycan BiosynthesisSuperpathwaysPHOTOALL-PWY: oxygenic photosynthesisBacteria; ViridiplantaeGeneration of Precursor Metabolites and Energy?→?Photosynthesis SuperpathwaysPOLYAMINSYN3-PWY: superpathway of polyamine biosynthesis IIBacteria; Eukaryota Biosynthesis?→?Amines and Polyamines BiosynthesisSuperpathwaysPOLYAMSYN-PWY: superpathway of polyamine biosynthesis IBacteriaBiosynthesis?→?Amines and Polyamines BiosynthesisSuperpathwaysPOLYISOPRENSYN-PWY: polyisoprenoid biosynthesis (E. coli)Archaea; Bacteria ; Eukaryota Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Polyprenyl BiosynthesisSuperpathwaysPPGPPMET-PWY: ppGpp biosynthesisBacteriaBiosynthesis?→?Metabolic Regulators BiosynthesisPROPFERM-PWY: L-alanine fermentation to propionate and acetateFirmicutesGeneration of Precursor Metabolites and Energy?→?FermentationSuperpathwaysPROTOCATECHUATE-ORTHO-CLEAVAGE-PWY: protocatechuate degradation II (ortho-cleavage pathway)BacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Protocatechuate DegradationPWY-101: photosynthesis light reactionsBacteria; Eukaryota Generation of Precursor Metabolites and Energy?→?Electron Transfer Generation of Precursor Metabolites and Energy?→?PhotosynthesisPWY-1042: glycolysis IV (plant cytosol)ViridiplantaeGeneration of Precursor Metabolites and Energy?→?GlycolysisPWY-1269: CMP-KDO biosynthesis IBacteria; Proteobacteria; Viridiplantae Biosynthesis?→?Carbohydrates Biosynthesis?→?Polysaccharides Biosynthesis?→?CMP-3-deoxy-D-manno-octulosonate Biosynthesis; Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?CMP-sugar BiosynthesisPWY-1501: mandelate degradation IProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Mandelates DegradationPWY-1622: formaldehyde assimilation I (serine pathway)BacteriaDegradation/Utilization/Assimilation?→?C1 Compounds Utilization and Assimilation?→?Formaldehyde AssimilationPWY-181: photorespirationBacteria; Eukaryota; ViridiplantaeGeneration of Precursor Metabolites and Energy?→?PhotosynthesisPWY-1861: formaldehyde assimilation II (RuMP Cycle)BacteriaDegradation/Utilization/Assimilation?→?C1 Compounds Utilization and Assimilation?→?Formaldehyde AssimilationPWY-1882: superpathway of C1 compounds oxidation to CO2BacteriaDegradation/Utilization/Assimilation?→?C1 Compounds Utilization and AssimilationPWY-2083: isoflavonoid biosynthesis IIGunneridaeBiosynthesis?→?Secondary Metabolites Biosynthesis?→Phenylpropanoid Derivatives Biosynthesis?→?Flavonoids Biosynthesis?→?Isoflavonoids Biosynthesis; Biosynthesis?→?Secondary Metabolites Biosynthesis?→Phytoalexins Biosynthesis?→?Isoflavonoid Phytoalexins BiosynthesisPWY-241: C4 photosynthetic carbon assimilation cycle, NADP-ME typeEmbryophytaGeneration of Precursor Metabolites and Energy?→?PhotosynthesisPWY-2504: superpathway of aromatic compound degradation via 3-oxoadipateBacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds DegradationPWY-2723: trehalose degradation VFungiDegradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Sugars Degradation?→?Trehalose DegradationPWY-282: cuticular wax biosynthesisViridiplantaeBiosynthesis?→?Cell Structures Biosynthesis?→?Plant Cell Structures?→?Epidermal Structures; Biosynthesis?→?Fatty Acids and Lipids BiosynthesisPWY-2941: lysine biosynthesis IIFirmicutesBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-lysine BiosynthesisPWY-2942: lysine biosynthesis IIIBacteriaBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-lysine BiosynthesisPWY-3041: monoterpene biosynthesisTracheophytaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Terpenoids Biosynthesis?→?Monoterpenoids Biosynthesis; Generation of Precursor Metabolites and EnergyPWY-3101: flavonol biosynthesisSpermatophytaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→Flavonoids Biosynthesis?→?Flavonols BiosynthesisPWY-3301: sinapate ester biosynthesisBrassicaceaeBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→Cinnamates BiosynthesisPWY-3481: superpathway of phenylalanine and tyrosine biosynthesisViridiplantaeBiosynthesis?→?Amino Acids BiosynthesisPWY-361: phenylpropanoid biosynthesisSpermatophytaBiosynthesis?→?Cell Structures Biosynthesis?→?Plant Cell Structures?→?Secondary Cell Wall; Biosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→Lignins BiosynthesisPWY-3661: glycine betaine degradation IArchaea; Bacteria; Eukaryota Degradation/Utilization/Assimilation?→?Amines and Polyamines Degradation?→?Glycine Betaine DegradationPWY-3781: aerobic respiration (cytochrome c)Bacteria; Eukaryota Generation of Precursor Metabolites and Energy?→?Electron Transfer; Generation of Precursor Metabolites and Energy?→?Respiration?→?Aerobic RespirationPWY-3801: sucrose degradation II (sucrose synthase)Cyanobacteria; Viridiplantae Degradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Sugars Degradation?→?Sucrose DegradationPWY-3841: folate transformations IIViridiplantaeBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Vitamins Biosynthesis→?Folate Biosynthesis?→?Folate TransformationsPWY-3941: β-alanine biosynthesis IIBacteria; ViridiplantaeBiosynthesis?→?Amino Acids Biosynthesis?→?Other Amino Acid Biosynthesis?→?βAlanine BiosynthesisPWY-4041: &gamma;-glutamyl cycleFungi; Metazoa Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Reductants BiosynthesisPWY-4202: arsenate detoxification I (glutaredoxin)MammaliaDetoxification?→?Arsenate DetoxificationPWY-4221: pantothenate and coenzyme A biosynthesis IIViridiplantaeBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Coenzyme A BiosynthesisPWY-4321: glutamate degradation IVViridiplantaeDegradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Proteinogenic Amino Acids Degradation?→?L-glutamate DegradationPWY-4361: methionine salvage I (bacteria and plants)Archaea; Bacteria; Embryophyta; Metazoa Biosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-methionine Biosynthesis?→?L-methionine Salvage?→?S-methyl-5-thio-α-D-ribose 1-phosphate degradation; Degradation/Utilization/Assimilation?→?Nucleosides and Nucleotides Degradation?→?S-methyl-5-thio-α-D-ribose 1-phosphate degradationPWY-4984: urea cycleBacteria; Eukaryota Degradation/Utilization/Assimilation?→?Inorganic Nutrients Metabolism?→?Nitrogen Compounds MetabolismPWY-5004: superpathway of citrulline metabolismMetazoa; ViridiplantaeBiosynthesis?→?Amino Acids Biosynthesis?→?Other Amino Acid Biosynthesis?→?L-citrulline Biosynthesis SuperpathwaysPWY-5005: biotin biosynthesis IIBacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Vitamins Biosynthesis→?Biotin BiosynthesisPWY-5022: 4-aminobutyrate degradation VFirmicutesDegradation/Utilization/Assimilation?→?Amines and Polyamines Degradation?→?4-Aminobutanoate DegradationPWY-5030: histidine degradation IIIMammaliaDegradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Proteinogenic Amino Acids Degradation?→?L-histidine DegradationPWY-5041: S-adenosyl-L-methionine cycle IIBacteria; Eukaryota Biosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-methionine Biosynthesis?→?L-methionine Salvage?→?S-adenosyl-L-methionine cyclePWY-5079: phenylalanine degradation IIIFungiDegradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Proteinogenic Amino Acids Degradation?→?L-phenylalanine DegradationPWY-5080: very long chain fatty acid biosynthesis IBacteria; Eukaryota Biosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid BiosynthesisPWY-5083: NAD/NADH phosphorylation and dephosphorylationFungi; Viridiplantae Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?NAD MetabolismPWY-5097: lysine biosynthesis VIArchaea; Bacteria; Magnoliophyta Biosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-lysine BiosynthesisPWY-5100: pyruvate fermentation to acetate and lactate IIBacteriaGeneration of Precursor Metabolites and Energy?→?Fermentation→?Pyruvate FermentationPWY-5103: isoleucine biosynthesis IIIProteobacteriaBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-isoleucine BiosynthesisPWY-5104: isoleucine biosynthesis IVArchaea; Bacteria Biosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-isoleucine BiosynthesisPWY-5121: superpathway of geranylgeranyl diphosphate biosynthesis II (via MEP)Bacteria; ViridiplantaeBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Polyprenyl Biosynthesis?→?Geranylgeranyl Diphosphate Biosynthesis; Biosynthesis?→?Secondary Metabolites Biosynthesis?→Terpenoids Biosynthesis?→?Diterpenoids BiosynthesisPWY-5129: sphingolipid biosynthesis (plants)ViridiplantaeBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Sphingolipid BiosynthesisPWY-5135: xanthohumol biosynthesisCannabaceaeBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→Flavonoids Biosynthesis?→?Prenylflavonoids BiosynthesisPWY-5136: fatty acid &β-oxidation II (peroxisome)ViridiplantaeDegradation/Utilization/Assimilation?→?Fatty Acid and Lipids Degradation?→?Fatty Acids DegradationPWY-5138: unsaturated, even numbered fatty acid &β-oxidationViridiplantaeDegradation/Utilization/Assimilation?→?Fatty Acid and Lipids Degradation?→?Fatty Acids DegradationPWY-5139: pelargonidin conjugates biosynthesisMagnoliophytaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→Flavonoids Biosynthesis?→?Anthocyanins BiosynthesisPWY-5154: arginine biosynthesis III (via N-acetyl-L-citrulline)BacteriaBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-arginine BiosynthesisPWY-5156: superpathway of fatty acid biosynthesis II (plant)ViridiplantaeBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid Biosynthesis SuperpathwaysPWY-5163: p-cumate degradation to 2-oxopent-4-enoateProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds DegradationPWY-5168: ferulate and sinapate biosynthesisSpermatophytaBiosynthesis?→?Secondary Metabolites Biosynthesis?→Phenylpropanoid Derivatives Biosynthesis?→?Cinnamates BiosynthesisPWY-5173: superpathway of acetyl-CoA biosynthesisMagnoliophytaGeneration of Precursor Metabolites and Energy?→?Acetyl-CoA BiosynthesisPWY-5178: toluene degradation IV (aerobic) (via catechol)ProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Toluenes Degradation SuperpathwaysPWY-5182: toluene degradation II (aerobic) (via 4-methylcatechol)ProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Toluenes Degradation SuperpathwaysPWY-5188: tetrapyrrole biosynthesis I (from glutamate)Archaea; Bacteria; Proteobacteria; Magnoliophyta Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Tetrapyrrole BiosynthesisPWY-5189: tetrapyrrole biosynthesis II (from glycine)Actinobacteria; Proteobacteria; Fungi; EuglenozoaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Tetrapyrrole BiosynthesisPWY-5265: peptidoglycan biosynthesis II (staphylococci)Actinobacteria; Firmicutes Biosynthesis?→?Cell Structures Biosynthesis?→?Cell Wall Biosynthesis?→?Peptidoglycan BiosynthesisPWY-5283: lysine degradation VBacteriaDegradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Proteinogenic Amino Acids Degradation?→?L-lysine DegradationPWY-5307: gentiodelphin biosynthesisMagnoliophytaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→Flavonoids Biosynthesis?→?Anthocyanins BiosynthesisPWY-5320: kaempferol glycoside biosynthesis (Arabidopsis)BrassicaceaeBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→Flavonoids Biosynthesis?→?Flavonols BiosynthesisPWY-5345: superpathway of methionine biosynthesis (by sulfhydrylation)Bacteria; FungiBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-methionine Biosynthesis?→?L-methionine De Novo BiosynthesisPWY-5347: superpathway of methionine biosynthesis (transsulfuration)BacteriaBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-methionine Biosynthesis?→?L-methionine De Novo BiosynthesisPWY-5353: arachidonate biosynthesisFungi; Bryophyta; Clorophyta Biosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid Biosynthesis?→?Unsaturated Fatty Acid Biosynthesis?→?Polyunsaturated Fatty Acid Biosynthesis?→?Arachidonate BiosynthesisPWY-5381: pyridine nucleotide cycling (plants)ViridiplantaeBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?NAD MetabolismPWY-5384: sucrose degradation IV (sucrose phosphorylase)ActinobacteriaDegradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Sugars Degradation?→?Sucrose DegradationPWY-5391: syringetin biosynthesisSpermatophytaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→Flavonoids Biosynthesis?→?Flavonols BiosynthesisPWY-5415: catechol degradation I (meta-cleavage pathway)Actinobacteria; ProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Catechol DegradationSuperpathwaysPWY-5417: catechol degradation III (ortho-cleavage pathway)Proteobacteria; FungiDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Catechol Degradation SuperpathwaysPWY-5419: catechol degradation to 2-oxopent-4-enoate IIActinobacteria; Proteobacteria Degradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Catechol DegradationPWY-5420: catechol degradation II (meta-cleavage pathway)Actinobacteria; Proteobacteria Degradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Catechol Degradation SuperpathwaysPWY-5423: oleoresin monoterpene volatiles biosynthesisPinidaeBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Terpenoids Biosynthesis?→?Monoterpenoids?PWY-5424: superpathway of oleoresin turpentine biosynthesisPinidaeBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Terpenoids Biosynthesis SuperpathwaysPWY-5425: oleoresin sesquiterpene volatiles biosynthesisPinidaeBiosynthesis?→?Secondary Metabolites Biosynthesis?→Terpenoids Biosynthesis?→?Sesquiterpenoids BiosynthesisPWY-5427: naphthalene degradation (aerobic)BacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Naphthalene DegradationPWY-5430: meta cleavage pathway of aromatic compoundsBacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Benzoate Degradation SuperpathwaysPWY-5431: aromatic compounds degradation via &β-ketoadipateProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Catechol Degradation SuperpathwaysPWY-5451: acetone degradation I (to methylglyoxal)MammaliaDegradation/Utilization/Assimilation?→?Fatty Acid and Lipids Degradation?→?Acetone DegradationPWY-5464: superpathway of cytosolic glycolysis (plants), pyruvate dehydrogenase and TCA cycleViridiplantaeGeneration of Precursor Metabolites and Energy SuperpathwaysPWY-5484: glycolysis II (from fructose-6P)Archaea; Bacteria; Eukaryota Generation of Precursor Metabolites and Energy?→?GlycolysisPWY-5487: 4-nitrophenol degradation IProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Nitroaromatic Compounds Degradation?→?Nitrophenol Degradation?→?4-Nitrophenol Degradation; Degradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Phenolic Compounds Degradation?→?Nitrophenol Degradation?→?4-Nitrophenol DegradationPWY-5488: 4-nitrophenol degradation IIBacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Nitroaromatic Compounds Degradation?→?Nitrophenol Degradation?→?4-Nitrophenol Degradation; Degradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Phenolic Compounds Degradation?→?Nitrophenol Degradation?→?4-Nitrophenol DegradationPWY-5494: pyruvate fermentation to propionate II (acrylate pathway)BacteriaGeneration of Precursor Metabolites and Energy?→?Fermentation→?Pyruvate FermentationPWY-5499: vitamin B6 degradationProteobacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers BiosynthesisPWY-5505: glutamate and glutamine biosynthesisArchaea; Bacteria; Eukaryota Biosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-glutamate Biosynthesis; Biosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-glutamine BiosynthesisPWY-5514: UDP-N-acetyl-D-galactosamine biosynthesis IIGiardiinaeBiosynthesis?→?Amines and Polyamines Biosynthesis?→?UDP-N-acetyl-D-galactosamine Biosynthesis; Biosynthesis?→?Cell Structures Biosynthesis?→?Cell Wall BiosynthesisPWY-5532: adenosine nucleotides degradation IVArchaeaDegradation/Utilization/Assimilation?→?Nucleosides and Nucleotides Degradation?→?Purine Nucleotides Degradation?→Adenosine Nucleotides DegradationPWY-561: superpathway of glyoxylate cycle and fatty acid degradationViridiplantaeGeneration of Precursor Metabolites and Energy SuperpathwaysPWY-5651: tryptophan degradation to 2-amino-3-carboxymuconate semialdehydeBacteria; Fungi; Metazoa Degradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Proteinogenic Amino Acids Degradation?→?L-tryptophan DegradationPWY-5654: 2-amino-3-carboxymuconate semialdehyde degradation to 2-oxopentenoateBacteriaDegradation/Utilization/Assimilation?→?Carboxylates DegradationPWY-5659: GDP-mannose biosynthesisArchaea; Bacteria; Eukaryota Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?GDP-sugar BiosynthesisPWY-5667: CDP-diacylglycerol biosynthesis IBacteria; Eukaryota Biosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Phospholipid Biosynthesis?→?CDP-diacylglycerol BiosynthesisPWY-5675: nitrate reduction V (assimilatory)Bacteria; Fungi Degradation/Utilization/Assimilation?→?Inorganic Nutrients Metabolism?→?Nitrogen Compounds Metabolism?→?Nitrate ReductionPWY-5686: UMP biosynthesisArchaea; Bacteria; Eukaryota Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Pyrimidine Nucleotide Biosynthesis?→Pyrimidine Nucleotides De Novo Biosynthesis?→?Pyrimidine Ribonucleotides De Novo BiosynthesisPWY-5690: TCA cycle II (plants and fungi)Fungi; Viridiplantae Generation of Precursor Metabolites and Energy?→?TCA cyclePWY-5692: allantoin degradation to glyoxylate IIViridiplantaeDegradation/Utilization/Assimilation?→?Amines and Polyamines Degradation?→?Allantoin DegradationPWY-5695: urate biosynthesis/inosine 5'-phosphate degradationBacteria; Fabaceae; Metazoa Biosynthesis?→?Amines and Polyamines Biosynthesis; Degradation/Utilization/Assimilation?→?Nucleosides and Nucleotides Degradation?→?Purine Nucleotides DegradationPWY-5705: allantoin degradation to glyoxylate IIIBacteria; ViridiplantaeDegradation/Utilization/Assimilation?→?Amines and Polyamines Degradation?→?Allantoin DegradationPWY-5723: Rubisco shuntSpermatophytaGeneration of Precursor Metabolites and EnergyPWY-5724: superpathway of atrazine degradationBacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?s-Triazine Degredation?→?Atrazine DegradationPWY-5743: 3-hydroxypropanoate cycleChloroflexi (Bacteria)Degradation/Utilization/Assimilation?→?C1 Compounds Utilization and Assimilation?→?CO2 Fixation?→Autotrophic CO2 FixationPWY-5744: glyoxylate assimilationThermoprotei (Archaea); Chloroflexi (Bacteria)Degradation/Utilization/Assimilation?→?C1 Compounds Utilization and Assimilation?→?CO2 Fixation?→Autotrophic CO2 Fixation; Degradation/Utilization/Assimilation?→?Degradation/Utilization/Assimilation - OtherPWY-5747: 2-methylcitrate cycle IIBacteriaDegradation/Utilization/Assimilation?→?Carboxylates Degradation?→?Propanoate Degradation?→?2-Methylcitrate CyclePWY-5749: itaconate degradationBacteria; Opisthokonta Degradation/Utilization/Assimilation?→?Carboxylates DegradationPWY-5751: phenylethanol biosynthesisCellular Organisms; Viridiplantae Biosynthesis?→?Aromatic Compounds Biosynthesis; Biosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives BiosynthesisPWY-5767: glycogen degradation IIIFungi; GracilarialDegradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Polysaccharides Degradation?→?Glycogen Degradation / Degradation/Utilization/Assimilation?→?Polymeric Compounds Degradation?→?Polysaccharides Degradation?→?Glycogen DegradationPWY-5791: 1,4-dihydroxy-2-naphthoate biosynthesis II (plants)ViridiplantaeBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?1,4-Dihydroxy-2-Naphthoate BiosynthesisPWY-5837: 1,4-dihydroxy-2-naphthoate biosynthesis IBacteria; ViridiplantaeBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?1,4-Dihydroxy-2-Naphthoate BiosynthesisPWY-5838: superpathway of menaquinol-8 biosynthesis IBacteria; Halobacteria Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Menaquinol BiosynthesisPWY-5840: superpathway of menaquinol-7 biosynthesisArchaea; Bacteria Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Menaquinol BiosynthesisPWY-5845: superpathway of menaquinol-9 biosynthesisBacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Menaquinol BiosynthesisPWY-5850: superpathway of menaquinol-6 biosynthesis IBacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Menaquinol BiosynthesisPWY-5855: ubiquinol-7 biosynthesis (prokaryotic)BacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Ubiquinol BiosynthesisPWY-5856: ubiquinol-9 biosynthesis (prokaryotic)BacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Ubiquinol BiosynthesisPWY-5857: ubiquinol-10 biosynthesis (prokaryotic)ProteobacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Ubiquinol BiosynthesisPWY-5860: superpathway of demethylmenaquinol-6 biosynthesis IHaemophilusBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→Demethylmenaquinol Biosynthesis?→?Demethylmenaquinol-6 BiosynthesisPWY-5861: superpathway of demethylmenaquinol-8 biosynthesisBacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→Demethylmenaquinol Biosynthesis?→?Demethylmenaquinol-8 BiosynthesisPWY-5862: superpathway of demethylmenaquinol-9 biosynthesisBacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Demethylmenaquinol BiosynthesisPWY-5870: ubiquinol-8 biosynthesis (eukaryotic)AscomycotaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Ubiquinol BiosynthesisPWY-5872: ubiquinol-10 biosynthesis (eukaryotic)EukaryotaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Ubiquinol BiosynthesisPWY-5873: ubiquinol-7 biosynthesis (eukaryotic)BacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Ubiquinol BiosynthesisPWY-5896: superpathway of menaquinol-10 biosynthesisActinobacteria; Bacteroidetes Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Menaquinol BiosynthesisPWY-5897: superpathway of menaquinol-11 biosynthesisBacteroides; Micrococcales; Prevotella Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Menaquinol BiosynthesisPWY-5898: superpathway of menaquinol-12 biosynthesisAgromyces; Microbacterium; Prevotella Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Menaquinol BiosynthesisPWY-5899: superpathway of menaquinol-13 biosynthesisMicrobacterium; Prevotella Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Menaquinol BiosynthesisPWY-5910: superpathway of geranylgeranyldiphosphate biosynthesis I (via mevalonate)Bacteria; Eukaryota Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Polyprenyl Biosynthesis?→?Geranylgeranyl Diphosphate Biosynthesis; Biosynthesis?→?Secondary Metabolites Biosynthesis?→Terpenoids Biosynthesis?→?Diterpenoids BiosynthesisPWY-5913: TCA cycle VI (obligate autotrophs)Proteobacteria; Cyanobacteria Generation of Precursor Metabolites and Energy?→?TCA cyclePWY-5918: superpathay of heme biosynthesis from glutamateArchaea; Proteobacteria; Euglenozoa; Magnoliophyta Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Porphyrin Compounds Biosynthesis?→?Heme BiosynthesisPWY-5920: superpathway of heme biosynthesis from glycineProteobacteria; Fungi; Euglenozoa; Metazoa Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Porphyrin Compounds Biosynthesis?→?Heme BiosynthesisPWY-5922: (4R)-carveol and (4R)-dihydrocarveol degradationBacteriaDegradation/Utilization/Assimilation?→?Secondary Metabolites Degradation?→?Terpenoids Degradation→?Carveol DegradationPWY-5941: glycogen degradation IIArchaea; Bacteria; Opisthokonta Degradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Polysaccharides Degradation?→Glycogen Degradation; Degradation/Utilization/Assimilation?→?Polymeric Compounds Degradation?→?Polysaccharides Degradation?→?Glycogen DegradationPWY-5958: acridone alkaloid biosynthesisPiperaceae; RutaceaeBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Nitrogen-Containing Secondary Compounds Biosynthesis?→?Alkaloids BiosynthesisPWY-5971: palmitate biosynthesis II (bacteria and plants)Bacteria; ViridiplantaeBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid Biosynthesis?→?Palmitate BiosynthesisPWY-5972: stearate biosynthesis I (animals)Bacteria; Opisthokonta Biosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid Biosynthesis?→?Stearate BiosynthesisPWY-5973: cis-vaccenate biosynthesisBacteria; Magnoliophyta Biosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid Biosynthesis?→?Unsaturated Fatty Acid BiosynthesisPWY-5981: CDP-diacylglycerol biosynthesis IIIBacteriaBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→Phospholipid Biosynthesis?→?CDP-diacylglycerol BiosynthesisPWY-5989: stearate biosynthesis II (bacteria and plants)Bacteria; ViridiplantaeBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid Biosynthesis?→?Stearate BiosynthesisPWY-5994: palmitate biosynthesis I (animals and fungi)OpisthokontaBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid Biosynthesis?→?Palmitate BiosynthesisPWY-6060: malonate degradation II (biotin-dependent)BacteriaDegradation/Utilization/Assimilation?→?Carboxylates Degradation→?Malonate DegradationPWY-6061: bile acid biosynthesis, neutral pathwayVertebrataBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Sterol BiosynthesisPWY-6098: diploterol and cycloartenol biosynthesisPteridaceaeBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Terpenoids Biosynthesis?→?Triterpenoids BiosynthesisPWY-6109: mangrove triterpenoid biosynthesisRhizophoraceaeBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Terpenoids Biosynthesis?→?Triterpenoids BiosynthesisPWY-6113: superpathway of mycolate biosynthesisMycobacteriaceaeBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid Biosynthesis / SuperpathwaysPWY-6121: 5-aminoimidazole ribonucleotide biosynthesis IBacteria; EukaryotaBiosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Purine Nucleotide Biosynthesis?→?5-Aminoimidazole Ribonucleotide BiosynthesisPWY-6122: 5-aminoimidazole ribonucleotide biosynthesis IIArchaea; Bacteria Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Purine Nucleotide Biosynthesis?→?5-Aminoimidazole Ribonucleotide BiosynthesisPWY-6123: inosine-5'-phosphate biosynthesis IBacteriaBiosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Purine Nucleotide Biosynthesis?→?Purine Nucleotides De Novo Biosynthesis?→?Purine Riboucleotides De Novo Biosynthesis?→?Inosine-5'-phosphate BiosynthesisPWY-6124: inosine-5'-phosphate biosynthesis IIEukaryotaBiosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Purine Nucleotide Biosynthesis?→?Purine Nucleotides De Novo Biosynthesis?→?Purine Riboucleotides De Novo Biosynthesis?→?Inosine-5'-phosphate BiosynthesisPWY-6125: superpathway of guanosine nucleotides de novo biosynthesis IIBacteriaBiosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→Purine Nucleotide Biosynthesis?→?Purine Nucleotides De Novo BiosynthesisPWY-6126: superpathway of adenosine nucleotides de novo biosynthesis IIArchaea; Bacteria; Eukaryota Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→Purine Nucleotide Biosynthesis?→?Purine Nucleotides De Novo BiosynthesisPWY-6147: 6-hydroxymethyl-dihydropterin diphosphate biosynthesis IBacteria; Fungi; ViridiplantaeBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Vitamins Biosynthesis?→?Folate Biosynthesis?→6-Hydroxymethyl-Dihydropterin Diphosphate BiosynthesisPWY-6151: S-adenosyl-L-methionine cycle IArchaea; Bacteria Biosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-methionine Biosynthesis?→?L-methionine Salvage?→?S-adenosyl-L-methionine cyclePWY-6163: chorismate biosynthesis from 3-dehydroquinateArchaea; Bacteria; Fungi; Algaea Biosynthesis?→?Aromatic Compounds Biosynthesis?→?Chorismate BiosynthesisPWY-6182: superpathway of salicylate degradationBacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds DegradationPWY-6190: 2,4-dichlorotoluene degradationBacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Chloroaromatic Compounds Degradation?→Chlorotoluene Degradation?→?Dichlorotoluene Degradation; Degradation/Utilization/Assimilation?→?Chlorinated Compounds Degradation?→?Chloroaromatic Compounds Degradation?→Chlorotoluene Degradation?→?Dichlorotoluene DegradationPWY-6210: 2-aminophenol degradationBacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds DegradationPWY-6215: 4-chlorobenzoate degradationBacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Chloroaromatic Compounds Degradation?→Chlorobenzoate Degradation; Degradation/Utilization/Assimilation?→?Chlorinated Compounds Degradation?→?Chloroaromatic Compounds Degradation?→Chlorobenzoate DegradationPWY-621: sucrose degradation III (sucrose invertase)Archaea; Bacteria; Eukaryota Degradation/Utilization/Assimilation?→?Carbohydrates Degradation→?Sugars Degradation?→?Sucrose DegradationPWY-622: starch biosynthesisCyanobacteria; Rhodophyta; ViridiplantaeBiosynthesis?→?Carbohydrates Biosynthesis?→?Polysaccharides Biosynthesis?→?Glycogen and Starch BiosynthesisPWY-6270: isoprene biosynthesis IEmbryophytaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Terpenoids Biosynthesis?→?Hemiterpenes BiosynthesisPWY-6277: superpathway of 5-aminoimidazole ribonucleotide biosynthesisBacteriaBiosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Purine Nucleotide Biosynthesis?→?5-Aminoimidazole Ribonucleotide BiosynthesisPWY-6282: palmitoleate biosynthesis IBacteriaBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid Biosynthesis?→?Unsaturated Fatty Acid Biosynthesis?→Palmitoleate BiosynthesisPWY-6286: spheroidene and spheroidenone biosynthesisBacteriaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Terpenoids Biosynthesis?→?Carotenoids Biosynthesis; Biosynthesis?→?Secondary Metabolites Biosynthesis?→?Terpenoids Biosynthesis?→?Tetraterpenoids BiosynthesisPWY-6305: putrescine biosynthesis IVViridiplantaeBiosynthesis?→?Amines and Polyamines Biosynthesis?→?Putrescine BiosynthesisPWY-6307: tryptophan degradation X (mammalian, via tryptamine)MammaliaDegradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Proteinogenic Amino Acids Degradation?→?L-tryptophan DegradationPWY-6313: serotonin degradationMetazoaDegradation/Utilization/Assimilation?→?Hormones DegradationPWY-6317: galactose degradation I (Leloir pathway)Bacteria; Fungi; Embryophyta Degradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Sugars Degradation?→?Galactose DegradationPWY-6318: phenylalanine degradation IV (mammalian, via side chain)MetazoaDegradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Proteinogenic Amino Acids Degradation?→?L-phenylalanine DegradationPWY-6338: superpathway of vanillin and vanillate degradationBacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Vanillin DegradationPWY-6339: syringate degradationBacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds DegradationPWY-6342: noradrenaline and adrenaline degradationBacteriaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Sugar Derivatives Biosynthesis?→?Cyclitols BiosynthesisPWY-6351: D-myo-inositol (1,4,5)-trisphosphate biosynthesisEukaryotaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Sugar Derivatives Biosynthesis?→?Cyclitols BiosynthesisPWY-6352: 3-phosphoinositide biosynthesisEukaryotaBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Phospholipid BiosynthesisPWY-6353: purine nucleotides degradation II (aerobic)Archaea; Bacteria; Opisthokonta Degradation/Utilization/Assimilation?→?Nucleosides and Nucleotides Degradation?→?Purine Nucleotides DegradationPWY-6367: D-myo-inositol-5-phosphate metabolismEukaryotaBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Phospholipid Biosynthesis; Biosynthesis?→?Secondary Metabolites Biosynthesis?→?Sugar Derivatives Biosynthesis?→?Cyclitols BiosynthesisPWY-6368: 3-phosphoinositide degradationEukaryotaDegradation/Utilization/Assimilation?→?Fatty Acid and Lipids DegradationPWY-6369: inositol pyrophosphates biosynthesisEukaryotaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Sugar Derivatives Biosynthesis?→?Cyclitols BiosynthesisPWY-6383: mono-trans, poly-cis decaprenyl phosphate biosynthesisMycobacteriaceaeBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Polyprenyl BiosynthesisPWY-6385: peptidoglycan biosynthesis III (mycobacteria)MycobacteriaceaeBiosynthesis?→?Cell Structures Biosynthesis?→?Cell Wall Biosynthesis?→?Peptidoglycan BiosynthesisPWY-6386: UDP-N-acetylmuramoyl-pentapeptide biosynthesis II (lysine-containing)Actinobacteria; Firmicutes Biosynthesis?→?Cell Structures Biosynthesis?→?Cell Wall Biosynthesis?→?UDP-N-Acetylmuramoyl-Pentapeptide BiosynthesisPWY-6387: UDP-N-acetylmuramoyl-pentapeptide biosynthesis I (meso-DAP-containing)BacteriaBiosynthesis?→?Cell Structures Biosynthesis?→?Cell Wall Biosynthesis?→?UDP-N-Acetylmuramoyl-Pentapeptide BiosynthesisPWY-6396: superpathway of 2,3-butanediol biosynthesisBacteria; Fungi Generation of Precursor Metabolites and Energy?→?Fermentation?→?Butanediol Biosynthesis SuperpathwaysPWY-6433: hydroxylated fatty acid biosynthesis (plants)ViridiplantaeBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid Biosynthesis?→?Hydroxylated Fatty Acids BiosynthesisPWY-6435: 4-hydroxybenzoate biosynthesis VViridiplantaeBiosynthesis?→?Aromatic Compounds Biosynthesis?→?4-Hydroxybenzoate BiosynthesisPWY-6467: Kdo transfer to lipid IVA II (Chlamydia)Chlamydiae/Verrucomicrobia groupBiosynthesis?→?Cell Structures Biosynthesis?→?Lipopolysaccharide Biosynthesis / Biosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Kdo Transfer to Lipid IVA \ SuperpathwaysPWY-6470: peptidoglycan biosynthesis V (&β-lactam resistance)Actinobacteria; Firmicutes Biosynthesis?→?Cell Structures Biosynthesis?→?Cell Wall Biosynthesis?→?Peptidoglycan Biosynthesis / Detoxification?→?Antibiotic Resistance / SuperpathwaysPWY-6471: peptidoglycan biosynthesis IV (Enterococcus faecium)?LactobacillalesBiosynthesis?→?Cell Structures Biosynthesis?→?Cell Wall Biosynthesis?→?Peptidoglycan Biosynthesis / Detoxification?→?Antibiotic Resistance / SuperpathwaysPWY-6478: GDP-D-glycero-&α;-D-manno-heptose biosynthesisBacteria Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?GDP-sugar BiosynthesisPWY-6491: D-galacturonate degradation IIIFungiDegradation/Utilization/Assimilation?→?Carboxylates Degradation?→?Sugar Acids Degradation?→?D-Galacturonate Degradation / Degradation/Utilization/Assimilation?→?Secondary Metabolites Degradation?→?Sugar Derivatives Degradation?→?Sugar Acids Degradation?→?D-Galacturonate DegradationPWY-6507: 5-dehydro-4-deoxy-D-glucuronate degradationBacteria Degradation/Utilization/Assimilation?→?Secondary Metabolites Degradation?→?Sugar Derivatives DegradationPWY-6519: 8-amino-7-oxononanoate biosynthesis IBacteria Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Vitamins Biosynthesis?→?Biotin Biosynthesis?→?7-Keto,8-aminopelargonate BiosynthesisPWY-6525: stellariose and mediose biosynthesisCaryophyllaceaeBiosynthesis?→?Carbohydrates Biosynthesis?→?Oligosaccharides BiosynthesisPWY-6527: stachyose degradationViridiplantaeDegradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Sugars DegradationPWY-6531: mannitol cycleApicomplexa; PhaeophyceaeDegradation/Utilization/Assimilation?→?Secondary Metabolites Degradation?→?Sugar Derivatives Degradation?→?Sugar Alcohols DegradationPWY-6538: caffeine degradation III (bacteria, via demethylation)Bacteria Degradation/Utilization/Assimilation?→?Secondary Metabolites Degradation?→?Nitrogen Containing Secondary Compounds Degradation?→?Alkaloids Degradation?→?Caffeine DegradationPWY-6545: pyrimidine deoxyribonucleotides de novo biosynthesis IIIArchaea; Bacteria; Dictyostelium; Viruses Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?2'-Deoxyribonucleotides Biosynthesis?→?Pyrimidine Deoxyribonucleotides De Novo Biosynthesis / Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Pyrimidine Nucleotide Biosynthesis?→?Pyrimidine Nucleotides De Novo Biosynthesis?→?Pyrimidine Deoxyribonucleotides De Novo Biosynthesis / Metabolic ClustersPWY-6559: spermidine biosynthesis IIBacteria Biosynthesis?→?Amines and Polyamines Biosynthesis?→?Spermidine BiosynthesisPWY-6562: norspermidine biosynthesisVibrionaceaeBiosynthesis?→?Amines and Polyamines BiosynthesisPWY-6565: superpathway of polyamine biosynthesis IIIVibrionaceaeBiosynthesis?→?Amines and Polyamines Biosynthesis / SuperpathwaysPWY-6567: chondroitin sulfate biosynthesis (late stages)MetazoaBiosynthesis?→?Carbohydrates Biosynthesis?→?Polysaccharides Biosynthesis?→?Glycosaminoglycans BiosynthesisPWY-6568: dermatan sulfate biosynthesis (late stages)MetazoaBiosynthesis?→?Carbohydrates Biosynthesis?→?Polysaccharides Biosynthesis?→?Glycosaminoglycans BiosynthesisPWY-6581: spirilloxanthin and 2,2'-diketo-spirilloxanthin biosynthesisBacteria Biosynthesis?→?Secondary Metabolites Biosynthesis?→?Terpenoids Biosynthesis?→?Carotenoids Biosynthesis / Biosynthesis?→?Secondary Metabolites Biosynthesis?→?Terpenoids Biosynthesis?→?Tetraterpenoids BiosynthesisPWY-6588: pyruvate fermentation to acetoneBacteria Generation of Precursor Metabolites and Energy?→?Fermentation?→?Pyruvate FermentationPWY-6590: superpathway of Clostridium acetobutylicum acidogenic fermentationFirmicutesGeneration of Precursor Metabolites and Energy?→?Fermentation?→?Pyruvate Fermentation / SuperpathwaysPWY-6608: guanosine nucleotides degradation IIIBacteria; MetazoaDegradation/Utilization/Assimilation?→?Nucleosides and Nucleotides Degradation?→?Purine Nucleotides Degradation?→?Guanosine Nucleotides DegradationPWY-6612: superpathway of tetrahydrofolate biosynthesisBacteria; Fungi; ViridiplantaeBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Vitamins Biosynthesis?→?Folate Biosynthesis / SuperpathwaysPWY-6628: superpathway of phenylalanine biosynthesisBacteria Biosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-phenylalanine Biosynthesis / SuperpathwaysPWY-6630: superpathway of tyrosine biosynthesisBacteria Biosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-tyrosine Biosynthesis / SuperpathwaysPWY-6633: caffeine degradation V (bacteria, via trimethylurate)Bacteria Degradation/Utilization/Assimilation?→?Secondary Metabolites Degradation?→?Nitrogen Containing Secondary Compounds Degradation?→?Alkaloids Degradation?→?Caffeine DegradationPWY-6637: sulfolactate degradation IIBacteria Degradation/Utilization/Assimilation?→?Inorganic Nutrients Metabolism?→?Sulfur Compounds Metabolism?→?Sulfolactate DegradationPWY-6660: 2-heptyl-3-hydroxy-4(1H)-quinolone biosynthesisBacteria Biosynthesis?→?Secondary Metabolites BiosynthesisPWY-6662: superpathway of quinolone and alkylquinolone biosynthesisBacteria Biosynthesis?→?Secondary Metabolites Biosynthesis / SuperpathwaysPWY-6682: dehydrophos biosynthesisStreptomycesBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Antibiotic BiosynthesisPWY-6703: preQ0 biosynthesisBacteria Biosynthesis?→?Secondary Metabolites BiosynthesisPWY-6708: ubiquinol-8 biosynthesis (prokaryotic)Bacteria Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Ubiquinol BiosynthesisPWY-6724: starch degradation IIViridiplantaeBiosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis / Degradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Polysaccharides Degradation?→?Starch Degradation / Degradation/Utilization/Assimilation?→?Polymeric Compounds Degradation?→?Polysaccharides Degradation?→?Starch DegradationPWY-6728: methylaspartate cycleHalobacteria Generation of Precursor Metabolites and EnergyPWY-6731: starch degradation IIIArchaeaDegradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Polysaccharides Degradation?→?Starch Degradation / Degradation/Utilization/Assimilation?→?Polymeric Compounds Degradation?→?Polysaccharides Degradation?→?Starch DegradationPWY-6737: starch degradation VArchaeaDegradation/Utilization/Assimilation → Carbohydrates Degradation → Polysaccharides Degradation → Starch Degradation / Degradation/Utilization/Assimilation?→?Polymeric Compounds Degradation?→?Polysaccharides Degradation?→?Starch DegradationPWY-6749: CMP-legionaminate biosynthesis IBacteria Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?CMP-sugar Biosynthesis?→?CMP-legionaminate biosynthesisPWY-6755: S-methyl-5-thio-&α;-D-ribose 1-phosphate degradation IBacteria Biosynthesis → Amino Acids Biosynthesis → Proteinogenic Amino Acids Biosynthesis → L-methionine Biosynthesis → L-methionine Salvage → S-methyl-5-thio-α-D-ribose 1-phosphate degradation / Degradation/Utilization/Assimilation?→?Nucleosides and Nucleotides Degradation?→?S-methyl-5-thio-α-D-ribose 1-phosphate degradationPWY-6760: xylose degradation IIIArchaea; Bacteria Degradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Sugars Degradation?→?Xylose DegradationPWY-6763: salicortin biosynthesisPopulus; SalixBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→?Benzenoids Biosynthesis?→?Benzoate BiosynthesisPWY-6785: hydrogen production VIIIChlorophyta; Cyanobacteria Generation of Precursor Metabolites and Energy?→?Hydrogen ProductionPWY-6803: phosphatidylcholine acyl editingSpermatophytaBiosynthesis?→?Fatty Acid and Lipid BiosynthesisPWY-6823: molybdenum cofactor biosynthesisArchaea; Bacteria; Eukaryota Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Molybdenum Cofactor BiosynthesisPWY-6834: spermidine biosynthesis IIIArchaea; Bacteria Biosynthesis?→?Amines and Polyamines Biosynthesis?→?Spermidine BiosynthesisPWY-6837: fatty acid beta-oxidation V (unsaturated, odd number, di-isomerase-dependent)Opisthokonta; Viridiplantae Degradation/Utilization/Assimilation?→?Fatty Acid and Lipids Degradation?→?Fatty Acids DegradationPWY-6842: glutathione-mediated detoxification IIViridiplantaeDetoxificationPWY-6855: chitin degradation I (archaea)ArchaeaDegradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Polysaccharides Degradation?→?Chitin Degradation / Degradation/Utilization/Assimilation?→?Polymeric Compounds Degradation?→?Polysaccharides Degradation?→?Chitin DegradationPWY-6897: thiamin salvage IIBacteriaBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Vitamins Biosynthesis?→?Thiamine Biosynthesis?→?Thiamine Salvage / SuperpathwaysPWY-6901: superpathway of glucose and xylose degradationBacteria Degradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Sugars Degradation / SuperpathwaysPWY-6906: chitin derivatives degradationVibrionaceaeDegradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Polysaccharides Degradation?→?Chitin Degradation / Degradation/Utilization/Assimilation?→?Polymeric Compounds Degradation?→?Polysaccharides Degradation?→?Chitin DegradationPWY-6936: seleno-amino acid biosynthesisViridiplantaeBiosynthesis?→?Amino Acids Biosynthesis?→?Other Amino Acid BiosynthesisPWY-6940: eicosapentaenoate biosynthesis III (fungi)OpisthokontaBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid Biosynthesis?→?Unsaturated Fatty Acid Biosynthesis?→?Polyunsaturated Fatty Acid Biosynthesis?→Icosapentaenoate Biosynthesis / SuperpathwaysPWY-6942: dTDP-D-desosamine biosynthesisBacteria Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar BiosynthesisPWY-6945: cholesterol degradation to androstenedione I (cholesterol oxidase)Bacteria Degradation/Utilization/Assimilation?→?Steroids Degradation?→?Cholesterol DegradationPWY-6946: cholesterol degradation to androstenedione II (cholesterol dehydrogenase)Bacteria Degradation/Utilization/Assimilation?→?Steroids Degradation?→?Cholesterol DegradationPWY-6953: dTDP-3-acetamido-3,6-dideoxy-&α;-D-galactose biosynthesisBacteria Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar Biosynthesis / Biosynthesis?→?Cell Structures Biosynthesis?→?Lipopolysaccharide BiosynthesisPWY-6956: naphthalene degradation to acetyl-CoABacteria Degradation/Utilization/Assimilation?→?Aromatic Compounds Degradation / SuperpathwaysPWY-6957: mandelate degradation to acetyl-CoAProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Mandelates Degradation / SuperpathwaysPWY-6969: TCA cycle V (2-oxoglutarate:ferredoxin oxidoreductase)Actinobacteria; Cyanobacteris; Euglenida; Proteobacteria Generation of Precursor Metabolites and Energy?→?TCA cyclePWY-6971: oleandomycin biosynthesisBacteria Biosynthesis?→?Secondary Metabolites Biosynthesis?→?Antibiotic Biosynthesis?→?Macrolide Antibiotics BiosynthesisPWY-6973: dTDP-D-olivose, dTDP-D-oliose and dTDP-D-mycarose biosynthesisBacteria Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar BiosynthesisPWY-6974: dTDP-L-olivose biosynthesisBacteria Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar BiosynthesisPWY-6976: dTDP-L-mycarose biosynthesisBacteria Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar BiosynthesisPWY-6981: chitin biosynthesisArthropoda; Cnidaria; Entamoeba; FungiBiosynthesis?→?Carbohydrates Biosynthesis?→?Polysaccharides Biosynthesis / SuperpathwaysPWY-7000: kanamycin biosynthesisActinobacteria Biosynthesis?→?Secondary Metabolites Biosynthesis?→?Antibiotic Biosynthesis / SuperpathwaysPWY-7002: 4-hydroxyacetophenone degradationBacteria Degradation/Utilization/Assimilation?→?Aromatic Compounds DegradationPWY-7006: 4-amino-3-hydroxybenzoate degradationBacteria Degradation/Utilization/Assimilation?→?Aromatic Compounds DegradationPWY-7007: methyl ketone biosynthesisSolanum Biosynthesis?→?Secondary Metabolites Biosynthesis / Generation of Precursor Metabolites and Energy / Metabolic ClustersPWY-7013: L-1,2-propanediol degradationBacteria Degradation/Utilization/Assimilation?→?Alcohols DegradationPWY-7014: paromamine biosynthesis IActinobacteria Biosynthesis?→?Secondary Metabolites Biosynthesis?→?Antibiotic Biosynthesis?→?Paromamine BiosynthesisPWY-7024: superpathway of the 3-hydroxypropionate cycleChloroflexiDegradation/Utilization/Assimilation?→?C1 Compounds Utilization and Assimilation?→?CO2 Fixation?→?Autotrophic CO2 Fixation / SuperpathwaysPWY-702: methionine biosynthesis IIEmbryophytaBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-methionine Biosynthesis?→?L-methionine De Novo BiosynthesisPWY-7031: undecaprenyl diphosphate-linked heptasaccharide biosynthesisCampylobacterBiosynthesis?→?Carbohydrates Biosynthesis?→?Oligosaccharides Biosynthesis / Macromolecule Modification?→?Protein Modification?→?Protein GlycosylationPWY-7036: very long chain fatty acid biosynthesis IIBacteria; Eukaryota Biosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid BiosynthesisPWY-7039: phosphatidate metabolism, as a signaling moleculeViridiplantaeBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Phospholipid BiosynthesisPWY-7046: 4-coumarate degradation (anaerobic)Bacteria Degradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Phenolic Compounds DegradationPWY-7055: daphnetin modificationSpermatophytaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→?Coumarins BiosynthesisPWY-7077: N-acetyl-D-galactosamine degradationProteobacteriaDegradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Sugars DegradationPWY-7090: UDP-2,3-diacetamido-2,3-dideoxy-&α;-D-mannuronate biosynthesisBacteria Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?UDP-sugar Biosynthesis / Biosynthesis?→?Cell Structures Biosynthesis?→?Lipopolysaccharide Biosynthesis?→?O-Antigen BiosynthesisPWY-7094: fatty acid salvageBacteria Biosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid BiosynthesisPWY-7097: vanillin and vanillate degradation IBacteria Degradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Vanillin DegradationPWY-7098: vanillin and vanillate degradation IIBacteria Degradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Vanillin DegradationPWY-7102: bisabolene biosynthesisBacteria; Eukaryota Generation of Precursor Metabolites and EnergyPWY-7104: dTDP-L-megosamine biosynthesisBacteriaBiosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar BiosynthesisPWY-7115: C4 photosynthetic carbon assimilation cycle, NAD-ME typeViridiplantaeGeneration of Precursor Metabolites and Energy?→?PhotosynthesisPWY-7117: C4 photosynthetic carbon assimilation cycle, PEPCK typeMagnoliophyta; Poacea Generation of Precursor Metabolites and Energy?→?PhotosynthesisPWY-7118: chitin degradation to ethanolOpisthokontaGeneration of Precursor Metabolites and EnergyPWY-7136: &β myrcene degradationProteobacteriaBiosynthesis?→?Secondary Metabolites BiosynthesisPWY-7153: grixazone biosynthesisActinobacteria Biosynthesis?→?Secondary Metabolites BiosynthesisPWY-7157: eupatolitin 3-O-glucoside biosynthesisGunneridaeBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→?Flavonoids Biosynthesis?→?Flavonols BiosynthesisPWY-7161: polymethylated quercetin biosynthesisGunneridaeBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→?Flavonoids Biosynthesis?→?Flavones BiosynthesisPWY-7174: S-methyl-5-thio-&α;-D-ribose 1-phosphate degradation IIBacteria Biosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-methionine Biosynthesis?→?L-methionine Salvage?→?S-methyl-5-thio-α-D-ribose 1-phosphate degradation / Degradation/Utilization/Assimilation?→?Nucleosides and Nucleotides Degradation?→?S-methyl-5-thio-α-D-ribose 1-phosphate degradationPWY-7184: pyrimidine deoxyribonucleotides de novo biosynthesis IArchaea; Bacteria; Eukaryota Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?2'-Deoxyribonucleotides Biosynthesis?→?Pyrimidine Deoxyribonucleotides De Novo Biosynthesis / Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Pyrimidine Nucleotide Biosynthesis?→?Pyrimidine Nucleotides De Novo Biosynthesis?→?Pyrimidine Deoxyribonucleotides De Novo Biosynthesis / Metabolic ClustersPWY-7185: UTP and CTP dephosphorylation IArchaea; Bacteria; Eukaryota Degradation/Utilization/Assimilation?→?Nucleosides and Nucleotides Degradation?→?Pyrimidine Nucleotides Degradation?→?Pyrimidine Ribonucleosides Degradation?→?UTP and CTP DephosphorylationPWY-7187: pyrimidine deoxyribonucleotides de novo biosynthesis IIArchaea; Bacteria Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?2'-Deoxyribonucleotides Biosynthesis?→?Pyrimidine Deoxyribonucleotides De Novo Biosynthesis / Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Pyrimidine Nucleotide Biosynthesis?→?Pyrimidine Nucleotides De Novo Biosynthesis?→?Pyrimidine Deoxyribonucleotides De Novo BiosynthesisPWY-7196: superpathway of pyrimidine ribonucleosides salvageArchaea; Bacteria; Fungi; ViridiplantaeBiosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Pyrimidine Nucleotide Biosynthesis?→?Pyrimidine Nucleotides Salvage / SuperpathwaysPWY-7198: pyrimidine deoxyribonucleotides de novo biosynthesis IVArchaeaBiosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?2'-Deoxyribonucleotides Biosynthesis?→?Pyrimidine Deoxyribonucleotides De Novo Biosynthesis / Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Pyrimidine Nucleotide Biosynthesis?→?Pyrimidine Nucleotides De Novo Biosynthesis?→?Pyrimidine Deoxyribonucleotides De Novo Biosynthesis / Metabolic ClustersPWY-7199: pyrimidine deoxyribonucleosides salvage?Amoebozoa; Archaea; Bacteria; Metazoa Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Pyrimidine Nucleotide Biosynthesis?→?Pyrimidine Nucleotides SalvagePWY-7200: superpathway of pyrimidine deoxyribonucleoside salvageArchaea; Bacteria; Eukaryota Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Pyrimidine Nucleotide Biosynthesis?→?Pyrimidine Nucleotides Salvage / SuperpathwaysPWY-7204: pyridoxal 5'-phosphate salvage II (plants)ViridiplantaeBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Vitamins Biosynthesis?→?Vitamin B6 BiosynthesisPWY-7208: superpathway of pyrimidine nucleobases salvageArchaea; Bacteria; Fungi; ViridiplantaeBiosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Pyrimidine Nucleotide Biosynthesis?→?Pyrimidine Nucleotides Salvage / SuperpathwaysPWY-7209: superpathway of pyrimidine ribonucleosides degradationArchaea; Bacteria; MetazoaDegradation/Utilization/Assimilation?→?Nucleosides and Nucleotides Degradation?→?Pyrimidine Nucleotides Degradation?→?Pyrimidine Nucleobases Degradation / Degradation/Utilization/Assimilation?→?Nucleosides and Nucleotides Degradation?→?Pyrimidine Nucleotides Degradation?→?Pyrimidine Ribonucleosides Degradation / SuperpathwaysPWY-7210: pyrimidine deoxyribonucleotides biosynthesis from CTPActinobacteria; Firmicutes; Fungi; MetazoaBiosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Pyrimidine Nucleotide Biosynthesis?→?Pyrimidine Nucleotides Salvage / Metabolic ClustersPWY-7211: superpathway of pyrimidine deoxyribonucleotides de novo biosynthesisArchaea; Bacteria; Eukaryota Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?2'-Deoxyribonucleotides Biosynthesis?→?Pyrimidine Deoxyribonucleotides De Novo Biosynthesis /Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Pyrimidine Nucleotide Biosynthesis?→?Pyrimidine Nucleotides De Novo Biosynthesis?→?Pyrimidine Deoxyribonucleotides De Novo Biosynthesis / SuperpathwaysPWY-7212: baicalein metabolismViridiplantaeBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→?Flavonoids Biosynthesis?→?Flavones BiosynthesisPWY-7219: adenosine ribonucleotides de novo biosynthesisArchaea; Bacteria; Eukaryota Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Purine Nucleotide Biosynthesis?→?Purine Nucleotides De Novo Biosynthesis?→?Purine Riboucleotides De Novo BiosynthesisPWY-7221: guanosine ribonucleotides de novo biosynthesisBacteria Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Purine Nucleotide Biosynthesis?→?Purine Nucleotides De Novo Biosynthesis?→?Purine Riboucleotides De Novo BiosynthesisPWY-7228: superpathway of guanosine nucleotides de novo biosynthesis IArchaea; Bacteria; Eukaryota Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Purine Nucleotide Biosynthesis?→?Purine Nucleotides De Novo Biosynthesis / superpathways PWY-7229: superpathway of adenosine nucleotides de novo biosynthesis IArchaea; Bacteria; Eukaryota Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Purine Nucleotide Biosynthesis?→?Purine Nucleotides De Novo Biosynthesis / superpathways PWY-722: nicotinate degradation IProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Nicotinate DegradationPWY-7230: ubiquinol-6 biosynthesis from 4-aminobenzoate (eukaryotic)Fungi Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Ubiquinol BiosynthesisPWY-7233: ubiquinol-6 bypass biosynthesis (eukaryotic)FungiBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Ubiquinol BiosynthesisPWY-7234: inosine-5'-phosphate biosynthesis IIIArchaeaBiosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Purine Nucleotide Biosynthesis?→?Purine Nucleotides De Novo Biosynthesis?→?Purine Riboucleotides De Novo /Biosynthesis?→?Inosine-5'-phosphate BiosynthesisPWY-7235: superpathway of ubiquinol-6 biosynthesis (eukaryotic)Fungi Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Ubiquinol Biosynthesis / SuperpathwaysPWY-7237: myo-, chiro- and scillo-inositol degradationBacteriaDegradation/Utilization/Assimilation?→?Secondary Metabolites Degradation?→?Sugar Derivatives Degradation?→?Sugar Alcohols Degradation / SuperpathwaysPWY-7238: sucrose biosynthesis IIViridiplantaeBiosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sucrose BiosynthesisPWY-7242: D-fructuronate degradationBacteria Degradation/Utilization/Assimilation?→?Carboxylates Degradation?→?Sugar Acids Degradation / Degradation/Utilization/Assimilation?→?Secondary Metabolites Degradation?→?Sugar Derivatives Degradation?→?Sugar Acids DegradationPWY-7245: superpathway NAD/NADP - NADH/NADPH interconversion (yeast)Fungi Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?NAD Metabolism / SuperpathwaysPWY-724: superpathway of lysine, threonine and methionine biosynthesis IIViridiplantaeBiosynthesis?→?Amino Acids Biosynthesis / SuperpathwaysPWY-7251: pentacyclic triterpene biosynthesisViridiplantaeBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Terpenoids Biosynthesis?→?Triterpenoids Biosynthesis / Metabolic ClustersPWY-7254: TCA cycle VII (acetate-producers)Bacteria Generation of Precursor Metabolites and Energy?→?TCA cyclePWY-7268: NAD/NADP-NADH/NADPH cytosolic interconversion (yeast)FungiBiosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?NAD MetabolismPWY-7269: NAD/NADP-NADH/NADPH mitochondrial interconversion (yeast)Fungi Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?NAD MetabolismPWY-7274: D-cycloserine biosynthesisStreptomycetaceaeBiosynthesis?→?Amino Acids Biosynthesis?→?Other Amino Acid Biosynthesis / Biosynthesis?→?Secondary Metabolites Biosynthesis?→?Antibiotic BiosynthesisPWY-7279: aerobic respiration (cytochrome c) (yeast)FungiGeneration of Precursor Metabolites and Energy?→?Electron Transfer / Generation of Precursor Metabolites and Energy?→?Respiration?→?Aerobic RespirationPWY-7283: wybutosine biosynthesisEukaryotaBiosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Nucleic Acid Processing / SuperpathwaysPWY-7286: 7-(3-amino-3-carboxypropyl)-wyosine biosynthesisEukaryotaBiosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Nucleic Acid ProcessingPWY-7288: fatty acid &β-oxidation (peroxisome, yeast)Fungi Degradation/Utilization/Assimilation?→?Fatty Acid and Lipids Degradation?→?Fatty Acids DegradationPWY-7289: L-cysteine biosynthesis VBacteria Biosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-cysteine BiosynthesisPWY-7300: ecdysone and 20-hydroxyecdysone biosynthesisArthropodaBiosynthesis?→?Hormones BiosynthesisPWY-7301: dTDP-&β-L-noviose biosynthesisActinobacteriaBiosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar BiosynthesisPWY-7312: dTDP-D-&β-fucofuranose biosynthesisEnterobacteriaceaeBiosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar Biosynthesis / Biosynthesis?→?Cell Structures Biosynthesis?→?Lipopolysaccharide Biosynthesis?→?O-Antigen BiosynthesisPWY-7315: dTDP-N-acetylthomosamine biosynthesisProteobacteriaBiosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar Biosynthesis / Biosynthesis?→?Cell Structures Biosynthesis?→?Lipopolysaccharide Biosynthesis?→?O-Antigen BiosynthesisPWY-7316: dTDP-N-acetylviosamine biosynthesisBacteria Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar Biosynthesis / Biosynthesis?→?Cell Structures Biosynthesis?→?Lipopolysaccharide Biosynthesis?→?O-Antigen BiosynthesisPWY-7317: superpathway of dTDP-glucose-derived O-antigen building blocks biosynthesisBacteria Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar Biosynthesis / Biosynthesis?→?Cell Structures Biosynthesis?→?Lipopolysaccharide Biosynthesis?→?O-Antigen Biosynthesis / SuperpathwaysPWY-7318: dTDP-3-acetamido-3,6-dideoxy-&α;-D-glucose biosynthesisBacteria Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar Biosynthesis / Biosynthesis?→?Cell Structures Biosynthesis?→?Lipopolysaccharide Biosynthesis?→?O-Antigen BiosynthesisPWY-7328: superpathway of UDP-glucose-derived O-antigen building blocks biosynthesisBacteria Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?UDP-sugar Biosynthesis / Biosynthesis?→?Cell Structures Biosynthesis?→?Lipopolysaccharide Biosynthesis?→?O-Antigen Biosynthesis / superpathways PWY-7345: superpathway of anaerobic sucrose degradationViridiplantaeDegradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Sugars Degradation?→?Sucrose Degradation / superpathwaysPWY-7347: sucrose biosynthesis IIIMethylobacter; Methylomicrobium; Methylophaga; MethylophilaceaeBiosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sucrose BiosynthesisPWY-7371: 1,4-dihydroxy-6-naphthoate biosynthesis IIBacteria Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?1,4-dihydroxy-6-naphthoate biosynthesisPWY-7374: 1,4-dihydroxy-6-naphthoate biosynthesis IBacteria Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?1,4-dihydroxy-6-naphthoate biosynthesisPWY-7379: mRNA capping IIMetazoa; VirusesBiosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Nucleic Acid Processing / SuperpathwaysPWY-7383: anaerobic energy metabolism (invertebrates, cytosol)Annelida; Mollusca; Nematoda; Platyhelminthes Generation of Precursor Metabolites and Energy?→?FermentationPWY-7384: anaerobic energy metabolism (invertebrates, mitochondrial)Annelida; Mollusca; Nematoda; Platyhelminthes Generation of Precursor Metabolites and Energy?→?Fermentation / SuperpathwaysPWY-7389: superpathway of anaerobic energy metabolism (invertebrates)Annelida; Mollusca; Nematoda; Platyhelminthes Generation of Precursor Metabolites and Energy?→?Fermentation / SuperpathwaysPWY-7391: isoprene biosynthesis II (engineered)?Biosynthesis?→?Secondary Metabolites Biosynthesis?→?Terpenoids Biosynthesis?→?Hemiterpenes BiosynthesisPWY-7400: arginine biosynthesis IV (archaebacteria)Archaea; Bacteria Biosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-arginine BiosynthesisPWY-7405: aurachin RE biosynthesisBacteria Biosynthesis?→?Secondary Metabolites Biosynthesis?→?Antibiotic Biosynthesis?→?Aurachin BiosynthesisPWY-7409: phospholipid remodeling (phosphatidylethanolamine, yeast)EukaryotaBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Phospholipid Biosynthesis?→?Phosphatidylethanolamine BiosynthesisPWY-7411: superpathway phosphatidate biosynthesis (yeast)EukaryotaSuperpathwaysPWY-7412: mycinamicin biosynthesisActinobacteria Biosynthesis?→?Secondary Metabolites Biosynthesis?→?Antibiotic Biosynthesis?→?Macrolide Antibiotics BiosynthesisPWY-7413: dTDP-6-deoxy-&α;-D-allose biosynthesisBacteria Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar BiosynthesisPWY-7432: phenylalanine biosynthesis (cytosolic, plants)ViridiplantaeBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-phenylalanine BiosynthesisPWY-7434: terminal O-glycans residues modificationEukaryotaMacromolecule Modification?→?Protein Modification?→?Protein GlycosylationPWY-7440: dTDP-&β-L-4-epi-vancosamine biosynthesisActinomycetales Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?dTDP-sugar BiosynthesisPWY-7446: sulfoglycolysisBacteria Degradation/Utilization/Assimilation?→?Secondary Metabolites Degradation?→?Sugar Derivatives Degradation?→?Sulfoquinovose DegradationPWY-7450: anthocyanidin modification (Arabidopsis)MagnoliophytaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→?Flavonoids Biosynthesis?→?Anthocyanins BiosynthesisPWY-7478: oryzalexin D and E biosynthesisMagnoliophytaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phytoalexins Biosynthesis?→?Terpenoid Phytoalexins BiosynthesisPWY-822: fructan biosynthesisBacteria; EmbryophytaBiosynthesis?→?Carbohydrates Biosynthesis?→?Polysaccharides BiosynthesisPWY-841: superpathway of purine nucleotides de novo biosynthesis IArchaea; Bacteria; Eukaryota Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Purine Nucleotide Biosynthesis?→?Purine Nucleotides De Novo Biosynthesis / SuperpathwaysPWY-842: starch degradation IPoaceaeDegradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Polysaccharides Degradation?→?Glycans Degradation / Degradation/Utilization/Assimilation → Carbohydrates Degradation → Polysaccharides Degradation → Starch Degradation / Degradation/Utilization/Assimilation → Polymeric Compounds Degradation → Polysaccharides Degradation → Glycans Degradation / Degradation/Utilization/Assimilation → Polymeric Compounds Degradation → Polysaccharides Degradation → Starch DegradationPWY-922: mevalonate pathway IArchaea; Bacteria; Fungi; Metazoa Biosynthesis?→?Secondary Metabolites Biosynthesis?→?Terpenoids Biosynthesis?→?Hemiterpenes Biosynthesis?→?Isopentenyl Diphosphate BiosynthesisPWY0-1061: superpathway of alanine biosynthesisBacteria Biosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-alanine Biosynthesis / SuperpathwaysPWY0-1241: ADP-L-glycero-&β-D-manno-heptose biosynthesisProteobacteriaBiosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sugar Nucleotides Biosynthesis?→?ADP-sugar BiosynthesisPWY0-1261: anhydromuropeptides recyclingBacteria Degradation/Utilization/Assimilation?→?Secondary Metabolites Degradation?→?Sugar Derivatives DegradationPWY0-1296: purine ribonucleosides degradationArchaea; Bacteria; Opisthokonta Degradation/Utilization/Assimilation?→?Nucleosides and Nucleotides Degradation?→?Purine Nucleotides DegradationPWY0-1297: superpathway of purine deoxyribonucleosides degradationBacteria Degradation/Utilization/Assimilation?→?Nucleosides and Nucleotides Degradation / Superpatways PWY0-1298: superpathway of pyrimidine deoxyribonucleosides degradationBacteriaDegradation/Utilization/Assimilation?→?Nucleosides and Nucleotides Degradation?→?Pyrimidine Nucleotides Degradation / SuperpathwaysPWY0-1319: CDP-diacylglycerol biosynthesis IIProteobacteria; Viridiplantae Biosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Phospholipid Biosynthesis?→?CDP-diacylglycerol BiosynthesisPWY0-1415: superpathway of heme biosynthesis from uroporphyrinogen-IIIBacteria Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Porphyrin Compounds Biosynthesis?→?Heme Biosynthesis / SuperpathwaysPWY0-1479: tRNA processingBacteria Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Nucleic Acid ProcessingPWY0-1533: methylphosphonate degradation IBacteria Degradation/Utilization/Assimilation?→?Inorganic Nutrients Metabolism?→?Phosphorus Compounds Metabolism?→?Methylphosphonate DegradationPWY0-162: superpathway of pyrimidine ribonucleotides de novo biosynthesisBacteria; Eukaryota Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Pyrimidine Nucleotide Biosynthesis?→?Pyrimidine Nucleotides De Novo Biosynthesis?→?Pyrimidine Ribonucleotides De Novo Biosynthesis / SuperpathwaysPWY0-166: superpathway of pyrimidine deoxyribonucleotides de novo biosynthesis (E. coli)Archaea; Bacteria Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?2'-Deoxyribonucleotides Biosynthesis?→?Pyrimidine Deoxyribonucleotides De Novo Biosynthesis / Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Pyrimidine Nucleotide Biosynthesis?→?Pyrimidine Nucleotides De Novo Biosynthesis?→?Pyrimidine Deoxyribonucleotides De Novo Biosynthesis / Superpathways PWY0-301: L-ascorbate degradation I (bacterial, anaerobic)Bacteria Degradation/Utilization/Assimilation?→?Carboxylates Degradation?→?L-Ascorbate DegradationPWY0-42: 2-methylcitrate cycle IBacteria; FungiDegradation/Utilization/Assimilation?→?Carboxylates Degradation?→?Propanoate Degradation?→?2-Methylcitrate CyclePWY0-781: aspartate superpathwayBacteria SuperpathwaysPWY1F-FLAVSYN: flavonoid biosynthesisSpermatophytaBiosynthesis?→?Secondary Metabolites Biosynthesis?→?Phenylpropanoid Derivatives Biosynthesis?→?Flavonoids BiosynthesisPWY3O-19: ubiquinol-6 biosynthesis from 4-hydroxybenzoate (eukaryotic)Fungi Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Ubiquinol BiosynthesisPWY3O-355: stearate biosynthesis III (fungi)Fungi Biosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid Biosynthesis?→?Stearate BiosynthesisPWY4FS-4: phosphatidylcholine biosynthesis IVViridiplantaeBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Phospholipid Biosynthesis?→?Phosphatidylcholine BiosynthesisPWY4FS-7: phosphatidylglycerol biosynthesis I (plastidic)Bacteria; Eukaryota Biosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Phospholipid Biosynthesis?→?Phosphatidylglycerol Biosynthesis / SuperpathwaysPWY4FS-8: phosphatidylglycerol biosynthesis II (non-plastidic)Bacteria; Eukaryota Biosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Phospholipid Biosynthesis?→?Phosphatidylglycerol Biosynthesis / SuperpathwaysPWY4LZ-257: superpathway of fermentation (Chlamydomonas reinhardtii)ViridiplantaeGeneration of Precursor Metabolites and Energy?→?Fermentation?→?Pyruvate Fermentation / SuperpathwaysPWY5F9-12: biphenyl degradationBacteria Degradation/Utilization/Assimilation?→?Aromatic Compounds DegradationPWY66-367: ketogenesisChordata Generation of Precursor Metabolites and Energy?→?OtherPWY66-373: sucrose degradation V (sucrose &α;-glucosidase)MammaliaDegradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Sugars Degradation?→?Sucrose DegradationPWY66-374: C20 prostanoid biosynthesisMammaliaBiosynthesis?→?Hormones BiosynthesisPWY66-378: androgen biosynthesisVertebrataBiosynthesis?→?Hormones BiosynthesisPWY66-387: fatty acid &α;-oxidation IIMetazoaDegradation/Utilization/Assimilation?→?Fatty Acid and Lipids Degradation?→?Fatty Acids DegradationPWY66-388: fatty acid &α;-oxidation IIIMetazoaDegradation/Utilization/Assimilation?→?Fatty Acid and Lipids Degradation?→?Fatty Acids DegradationPWY66-389: phytol degradationMammaliaDegradation/Utilization/Assimilation?→?Alcohols DegradationPWY66-391: fatty acid &β-oxidation VI (peroxisome)VertebrataDegradation/Utilization/Assimilation?→?Fatty Acid and Lipids Degradation?→?Fatty Acids DegradationPWY66-399: gluconeogenesis IIIMetazoaBiosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?GluconeogenesisPWY66-409: superpathway of purine nucleotide salvageEukaryota; Mammalia Biosynthesis?→?Nucleosides and Nucleotides Biosynthesis?→?Purine Nucleotide Biosynthesis?→?Purine Nucleotide Salvage / SuperpathwaysPWY66-422: D-galactose degradation V (Leloir pathway)EukaryotaDegradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Sugars Degradation?→?Galactose DegradationPWY6666-2: dopamine degradationMetazoaDegradation/Utilization/Assimilation?→?Amines and Polyamines DegradationPWYG-321: mycolate biosynthesisMycobacteriaceaeBiosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Fatty Acid BiosynthesisPYRIDNUCSAL-PWY: NAD salvage pathway IBacteria; Fungi Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?NAD Metabolism?→?NAD BiosynthesisPYRIDNUCSYN-PWY: NAD biosynthesis I (from aspartate)Bacteria; Eukaryota Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?NAD Metabolism?→?NAD BiosynthesisREDCITCYC: TCA cycle III (helicobacter)Bacteria Generation of Precursor Metabolites and Energy?→?TCA cycleRHAMCAT-PWY: L-rhamnose degradation IBacteria Degradation/Utilization/Assimilation?→?Carbohydrates Degradation?→?Sugars Degradation?→?L-rhamnose DegradationRUMP-PWY: formaldehyde oxidation IBacteria Degradation/Utilization/Assimilation → C1 Compounds Utilization and Assimilation → Formaldehyde Oxidation / Generation of Precursor Metabolites and EnergySALVADEHYPOX-PWY: adenosine nucleotides degradation IIArchaea; Bacteria; Eukaryota Degradation/Utilization/Assimilation?→?Nucleosides and Nucleotides Degradation?→?Purine Nucleotides Degradation?→?Adenosine Nucleotides DegradationSER-GLYSYN-PWY: superpathway of serine and glycine biosynthesis IArchaea; Bacteria; Eukaryota Biosynthesis?→?Amino Acids Biosynthesis / SuperpathwaysSO4ASSIM-PWY: sulfate reduction I (assimilatory)Bacteria; FungiDegradation/Utilization/Assimilation?→?Inorganic Nutrients Metabolism?→?Sulfur Compounds Metabolism?→?Sulfate Reduction / SuperpathwaysSPHINGOLIPID-SYN-PWY: sphingolipid biosynthesis (yeast)Fungi Biosynthesis?→?Fatty Acid and Lipid Biosynthesis?→?Sphingolipid BiosynthesisSUCSYN-PWY: sucrose biosynthesis I (from photosynthesis)Cyanobacteria; Viridiplantae Biosynthesis?→?Carbohydrates Biosynthesis?→?Sugars Biosynthesis?→?Sucrose Biosynthesis / SuperpathwaysSULFATE-CYS-PWY: superpathway of sulfate assimilation and cysteine biosynthesisBacteria SuperpathwaysTCA-GLYOX-BYPASS: superpathway of glyoxylate bypass and TCAArchaea; Bacteria Generation of Precursor Metabolites and Energy?→?TCA cycle / SuperpathwaysTCA: TCA cycle I (prokaryotic)Archaea; Bacteria Generation of Precursor Metabolites and Energy?→?TCA cycleTEICHOICACID-PWY: teichoic acid (poly-glycerol) biosynthesisFirmicutesBiosynthesis?→?Cell Structures Biosynthesis?→?Cell Wall Biosynthesis?→?Teichoic Acids BiosynthesisTHRESYN-PWY: threonine biosynthesisArchaea; Bacteria; Fungi; ViridiplantaeBiosynthesis?→?Amino Acids Biosynthesis?→?Proteinogenic Amino Acids Biosynthesis?→?L-threonine BiosynthesisTOLUENE-DEG-DIOL-PWY: toluene degradation to 2-oxopent-4-enoate (via toluene-cis-diol)ProteobacteriaDegradation/Utilization/Assimilation?→?Aromatic Compounds Degradation?→?Toluenes DegradationTRIGLSYN-PWY: triacylglycerol biosynthesisEukaryotaBiosynthesis?→?Fatty Acid and Lipid BiosynthesisTRNA-CHARGING-PWY: tRNA chargingArchaea; Bacteria; Eukaryota Biosynthesis?→?Aminoacyl-tRNA Charging / Metabolic ClustersTYRFUMCAT-PWY: tyrosine degradation IFungi; Mammalia; Proteobacteria Degradation/Utilization/Assimilation?→?Amino Acids Degradation?→?Proteinogenic Amino Acids Degradation?→?L-tyrosine DegradationUBISYN-PWY: superpathway of ubiquinol-8 biosynthesis (prokaryotic)Bacteria Biosynthesis?→?Cofactors, Prosthetic Groups, Electron Carriers Biosynthesis?→?Quinol and Quinone Biosynthesis?→?Ubiquinol Biosynthesis / SuperpathwaysUDPNACETYLGALSYN-PWY: UDP-N-acetyl-D-glucosamine biosynthesis IIEukaryotaBiosynthesis?→?Amines and Polyamines Biosynthesis?→?UDP-N-acetyl-D-glucosamine BiosynthesisUDPNAGSYN-PWY: UDP-N-acetyl-D-glucosamine biosynthesis IArchaea; Bacteria; Opisthokonta Biosynthesis?→?Amines and Polyamines Biosynthesis?→?UDP-N-acetyl-D-glucosamine Biosynthesis / Biosynthesis?→?Cell Structures Biosynthesis?→?Lipopolysaccharide Biosynthesis?→?O-Antigen BiosynthesisURDEGR-PWY: superpathway of allantoin degradation in plantsViridiplantaeDegradation/Utilization/Assimilation?→?Amines and Polyamines Degradation?→?Allantoin Degradation / SuperpathwaysURSIN-PWY: ureide biosynthesisFabaceaeBiosynthesis?→?Amines and Polyamines Biosynthesis / Superpathways ................
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