Minnesota Corn Growers Association



Progress Report PROJECT TITLE: Hyper-Thermostable Enzyme (Lactonases) for use as Microbial Biocontrol Agents for Plant DiseasesPROJECT NUMBER: 4136-17SPREPORTING PERIOD: May. 1, 2019 – July. 31, 2019PRINCIPAL INVESTIGATOR: Michael Sadowsky and Mikael EliasORGANIZATION: University of MinnesotaPHONE NUMBER: 612-624-2706EMAIL: sadwosky@umn.eduClavibacter michiganensis subsp. nebraskensis (Cmn) Dose Response Assay for Corn LeavesInitial Field Testing ResultsIn these studies we investigated the dose-response relationship of Clavibacter michiganensis subsp. nebraskensis (Cmn) on corn leaves to determine the minimal concentration of cells required to cause visible infection. This is needed to then test the effective dose of SSpox Maize growthMaize cv Viking seed (40-30UP) were grown in Euro pots (diameter 8 inch) with sterilized soil mixture (50 standard soil/ 50 Germinating Mix) in a growth chamber under diurnal conditions with a 16 hour light at 22 ?C and 8 hour dark cycle at 18?C. Bacteria working solutionFirstly, Clavibacter michiganensis subsp. nebraskensis (causing Goss's bacterial wilt & leaf blight on Maize) was grown on NBY agar at room temperature (~5 days). Then, a single colony of Cmn was transferred into the fresh NBY plate. After three days, Cmn was centrifuged and suspended into 1X PBS to obtain working solution at OD540=0.1 ( about 108 cell/ml).Infection assays and resultsThe corn leaves were scraped with sterilized sand paper and inoculated serial diluted cells from 106, 105,104,103,102,10,0 cells on the scraped corn leaf, respectively. The effect of each concentration of Cmn on disease was evaluated using triplicate samples. After 18 days, Goss’s Wilt Symptoms were observed at two highest concentrations (106 and105) experiments. 106105104103102100Cmn++----- To better quantify the effect on plant disease, we adopted the use of bleaching (chlorosis) assay that non-destructively measures plant chlorophyll in control and diseased corn leaf tissue. ChlorophyllChlorophyll content in 6 replicates of corn with 106 cells CmmMeanDay 037.744.846.949.447.645.545.3Day 182.49.07.88.813.110.98.6 31783297757300953135132869003848100107950Day 18020000Day 18144018024130Day 0020000Day 0Results showed that dead/chlorotic leaves had 5-fold less chlorophyll than did controls. This assay will now be used on plants showing disease symptoms between these two extremes.We have now obtained a culture of Xanthomonas axonopodis pv. glycines causing bacterial pustule disease on soybean and we will test our enzymes against this pathogen. We also now have permission from APHIS to test Erwinia stewartii (Syn. Pantoea stewartii) causing Stewart's wilt (Stewart's disease, Stewart's bacterial wilt), Erwinia chrysanthemi pv zeae, and Dickeya zeae (bacterial stalk rot of maize) and we are trying to obtain these strain now to test on corn. To better assess the relationship between pathogen effects and quorum quenching lactonases we developed a system to measure this in a quantitative fashion. Here disease scale has 13 levels, representing 0-100% tissue necrosis/leaf.The test plant was maize and this is seen below.Quantification of Disease LevelsScale designation Level 1Level 2Level 3Level 4Level 5Level 6Level 7Level 8Level 9Level 10Level 11Level 12Level 13Percent of leaf with necrosis025102030405060708090100The assay appears to be useful for other pathogens as well. Below is the Corn Leaf Assay done using Clavibacter michiganensis subsp. nebraskensis (Cmn)TreatmentDisease levelsRep. ARep. BRep. CNegative control111Buffer needle111SsoPox only 111Cmn only999Cmn+SsoPox333Bacterial strains and quorum quenching lactonases. Eleven pathogenic strains that we are using in this study include Clavibacter michiganensis subsp. nebraskensis, Erwinia chrysanthemi pv. Zeae, Pantoea stewartii Mergaert, Erwinia aroideae 8066, Erwinia atroseptica 8064, Xanthomonas campestris pv. campestris, Pseudomonas syringae pv syringae, Pseudomonas syringae pv phaseolicola, Erwinia carotovora, Xanthomonas campestris pv. phaseoli, and Pectobacterium carotovorum. The strains were grown in selected medium at 25-30?C. There will be two kinds of the quorum quenching lactonases (SsoPox W2631, and GcL WT) used in this study. The characterizations of these lactonases were studied by Dr. Elias groups PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5SZW15PC9BdXRob3I+PFllYXI+MjAxNjwvWWVhcj48UmVj

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ADDIN EN.CITE.DATA 1, 2.We previously reported successful protection of several plant species from bacterial diseases by using lactonase enzyme SsoPox. Here we described our initial assays on corn using Clavibacter michiganensis subsp. nebraskensis (Cmn). The goal was to determine if the presence of lactonase on the corn leaf surface (the phyllosphere) alters bacterial community structure, in addition to preventing disease.Variation of maize phyllosphere microbiome due to interaction of Cmn and SsoPoxNext-Generation SequencingThe V4 hypervariable region of 16S rRNA was amplified for bacteria and archaea by using primer set 515F (5’– GTG CCA GCM GCC GCG GTA A –3’) and 806R (5’– GGA CTA CHV GGG TWT CTA AT –3’). Sequencing was done by the University of Minnesota Genomics Center (Minneapolis, MN, USA) as previously describedPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Hb2hsPC9BdXRob3I+PFllYXI+MjAxNjwvWWVhcj48UmVj

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ADDIN EN.CITE.DATA 3. Briefly, samples were first amplified by using the following cycling conditions: 95?C for 5 min, followed by 25 cycles of 98?C for 20 s, 55?C for 15 s, and 72?C for 1 min. Adapters and barcodes were added by using an additional 10 cycles PCR. Amplicons were gel purified, pooled, and paired-end sequenced at a read length of 300 nt on the Illumina MiSeq platform (Illumnia, Inc., San Diego, CA, USA). BioinformaticsHighly quality sequence data for analyses were obtrained by submitting the raw sequencing data through the SHI7 pipeline for quantity control (QC) PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5BbC1HaGFsaXRoPC9BdXRob3I+PFllYXI+MjAxODwvWWVh

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ADDIN EN.CITE.DATA 6. UCHIME software was used to identify and remove the probable Chimeric sequence ADDIN EN.CITE <EndNote><Cite><Author>Edgar</Author><Year>2011</Year><RecNum>1014</RecNum><DisplayText><style face="superscript">7</style></DisplayText><record><rec-number>1014</rec-number><foreign-keys><key app="EN" db-id="fe2spz5eg2p5fee9tw8pzvpswxvxfxzwfsxd" timestamp="1529597623">1014</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Edgar, Robert C</author><author>Haas, Brian J</author><author>Clemente, Jose C</author><author>Quince, Christopher</author><author>Knight, Rob</author></authors></contributors><titles><title>UCHIME improves sensitivity and speed of chimera detection</title><secondary-title>Bioinformatics</secondary-title></titles><periodical><full-title>Bioinformatics</full-title></periodical><pages>2194-2200</pages><volume>27</volume><number>16</number><dates><year>2011</year></dates><isbn>1460-2059</isbn><urls></urls></record></Cite></EndNote>7. All sequence data was rarefied to 63,000 sequence reads per sample before sustainable statistical analysis. Raw sequencing data will eventually be deposited in the Sequence Read Archive (SRA) of NCBI ().Statistical analysisFor statistical analysis, Alpha diversity (average species diversity) indices, as well as Good’s coverage, were calculated using the Shannon index and abundance-based coverage estimate through mother program. Visualization of the taxonomic distribution of microbial communities was performed by using the “ggplot2” package in R (Al-Masaudi et al., 2017). Differences in beta diversity among samples was evaluated by using analysis of similarity (ANOSIM), which employs Bray-Curtis dissimilarity matrices (BC) ADDIN EN.CITE <EndNote><Cite><Author>Bray</Author><Year>1957</Year><RecNum>839</RecNum><DisplayText><style face="superscript">8, 9</style></DisplayText><record><rec-number>839</rec-number><foreign-keys><key app="EN" db-id="fe2spz5eg2p5fee9tw8pzvpswxvxfxzwfsxd" timestamp="1504735446">839</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Bray, J Roger</author><author>Curtis, John T</author></authors></contributors><titles><title>An ordination of the upland forest communities of southern Wisconsin</title><secondary-title>Ecological monographs</secondary-title></titles><periodical><full-title>Ecological monographs</full-title></periodical><pages>325-349</pages><volume>27</volume><number>4</number><dates><year>1957</year></dates><isbn>1557-7015</isbn><urls></urls></record></Cite><Cite><Author>Clarke</Author><Year>1993</Year><RecNum>32</RecNum><record><rec-number>32</rec-number><foreign-keys><key app="EN" db-id="fe2spz5eg2p5fee9tw8pzvpswxvxfxzwfsxd" timestamp="0">32</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Clarke, K.R.</author></authors></contributors><titles><title>Non-parametric multivariate analyses of changes in community structure</title><secondary-title>Australian Journal of Ecology</secondary-title></titles><periodical><full-title>Australian Journal of Ecology</full-title></periodical><pages>117-143</pages><volume>18</volume><dates><year>1993</year></dates><urls></urls></record></Cite></EndNote>8, 9. Principal coordinates analysis (PCoA) was used to analyze the differences in microbial community structure between various DNA extraction methods. Linear discriminant analysis (LDA) of effect size (LEfSe) was used to identify OTUs that differed significantly influencing of SsoPox on phyllosphere. Moreover, indicator OTUs association with influencing of SsoPox on phyllosphere was determined based on multipatt function using the indcespecies package in R. The association was further considered significant using a false discovery rate.Attended conferenceSummarized the results of project and prepared the poster. Presented the poster in MN AG EXPO on January 24, 2019. The results attracted a lot of attention. Lots of farmers were interested when the technology could be used in the field. We will continue to improve our technology and conduct the addition experiments in the field. Publications. This material is currently being written for submission to the journal of Molecular Plant-Microbe Interactions.Field Study Using Corn In order to better understand the capability of SsoPox to suppress disease on corn disease in the field, we conducted the field study in the past three months. We tested two diseases related to corns. The first disease is Bacterial Leaf Streak (BLS) causing by Xanthomonas vasicola pv. vasculorum (Xvv). We inoculated Xvv at 10^7 CFU/mL with the clapper, one upper leaf per plant. The second disease is Goss’s Wilt causing by Clavibacter michiganensis subsp. nebraskensis (Cmn). We inoculated Cmn at 10^8 CFU/mL with the clapper, one upper leaf per plant. In the treatment groups, we sprayed SsoPox on the surface of corn leaf, which had been inoculated Xvv or Cmn. In the control groups, we conducted the similar assays, but used BSA instead of SsoPox. We used the untreated corn plants as negative control groups. Each assay was performed in 3 block replications, and each block also performed 3 plants replications. 8650310915100162115528511500-3089123498900172466017716500ResultsComposition of microbial communities on maize phyllosphereResults in Table 1 show the mean coverage of all three treatment categories was greater than 99%, without significant difference between Cmn, Cmn+SsoPox, and control groups, respectively. The mean Shannon diversity indices for individual categories ranged from 1.04 to 1.64, and Shannon diversity differed significantly between Cmn groups to Cmn+SsoPox and the control. The ranking of diversity was as follows: Cmn+SsoPox > Control > Cmn. However, there was no significant differences between Cmn to Cmn+SsoPox in Chao1 and Sobs.Bacterial community analyses found that the Cmn group was primarily composed of members of the phyla Actinobacteria (>60%), Cyanobacteria (>20%), and Proteobacteria (>5%). The composition in Cmn+SsoPox groups ranked from Proteobacteria (mean 57.4%) > Actinobacteria (mean 30.8%) > Cyanobacteria (11.7%). This compared with the dominant Cyanobacteria (>50%) and Proteobacteria in the control groups (Figure 1A). Microbacteriaceae, which is the family level for Clavibacter michiganensis subsp. nebraskensis, was found as the major composition (mean 64.8%) in the Cmn group, but decreased significantly to 30.6% in the Cmn+SsoPox group (Kruskal-Wallis test, P<0.001), and rarely presented (ca. 0.2%) in control groups (Figure 1B). Notably, in control group, PBS treatment communities were characterized by greater relative abundance of taxa within unclassified family levels under Cyanobacteria and Alphaproteobacteria (Figure 2). In contrast, SsoPox treatment communities had greater relative abundance of Weeksellaceae, Moraxellaceae, Enterobacteriaceae, and Rhodocyclaceae. Moreover, microbial indicator analysis showed that Acetobacteraceae (delta R=0.931, p=0.022) could be used to as an indicator for PBS treatment, although its relative abundance was very low (0.005%). Contrasting, Corynebacteriaceae, Methylocytaceae, and Clostridiaceae could be used to indicator SsoPox treatment, and their delta R is 0.816, 0.816, and 0.784, respectively. Interestingly, these three taxa also had very low relative abundance (<0.01%).Shifts in bacterial community composition following treatments.Ordination analyses via PCoA (Figure 2) showed the separation of samples by three categories, and these clusters were significantly different by ANOSIM (P<0.001) and AMOVA (P<0.001). Inoculation with Cmn significantly shifted the bacterial community (beta diversity) from control groups to the treatment groups. For example, significant differences were observed in control v.s. Cmn (R=0.98, P<0.001) and control v.s. Cmn+SsoPox (R=0.93, P<0.001), respectively. Among samples treated with Cmn, difference in beta diversity, evaluated by ANOSIM and AMOVA were also significantly different between Cmn and Cmn+SsoPox (R=0.74, P<0.001). Notably, in the control group, PBS and SsoPox were not significantly different (P>0.05). Similarly, Cmn and Cmn+HEPES communities did not significantly differ (P>0.05) from each other. Reduction of Clavibacter and Clavibacter michiganensis subsp. nebraskensis Analysis of Clavibacter from abundance data at the genus level revealed that Clavibacter had a mean value less than 0.3 % in all of treatments, which was ranking as follows: Cmn (0.18%±0.02%) > Cmn+HEPES (0.17 %±0.02%) > Cmn+SsoPox (0.06%±0.02%) > SsoPox = PBS (0%), respectively (Figure 4). In the Cmn Groups, the relative abundance of Clavibacter was not significantly different between Cmn and Cmn+HEPES treatments (ANOVA, P>0.05). However, with treatment with the lactonase SsoPox, Clavibacter was significantly reduced in the Cmn+SsoPox groups (ANOVA, P<0.05). Notably, the similar trend was also quantified by qPCR through CMN_1184 gene (Figure 5). The quantification of Clavibacter michiganensis subsp. nebraskensis followed from 3.91, 3.63, and 3.38 1og10 (copies/?L DNA) for Cmn, Cmn+HEPES, and Cmn+SsoPox, respectively. The highest concentration of Clavibacter michiganensis subsp. nebraskensis was observed in the Cmn Groups, while Cmn treatment did not signify with Cmn+HEPES treatment ((ANOVA, P>0.05). However, significantly reduced quantification of Clavibacter michiganensis subsp. nebraskensis was observed in Cmn+SsoPox groups (ANOVA, P<0.05).Influence of SsoPox on the growth capability of CmnFrom the Figure 6, it clearly elucidated that SsoPox did not stress the grow capability of Cmn in the NBY broth. In comparison to only growing in NBY broth (Cmn treatment), the Cmn+SsoPox treatment group and the Cmn+BSA treatment group were grew much fast, particularly due to SsoPox and BSA as protein providing the additional nutrient in the cultural broth. The results indicated that the SsoPox was indirectly regulating the disease of Gross’s wilt on the corn leaf. TABLE 1 Coverage and alpha diversity of bacterial communities on the maize phyllospere within various treatments.TreatmentNo. samplesCoverage (%)Sobs?ShannonindexChao1Cmn999.80±0.05A43±11A1.04±0.16A112±38ACmn+SsoPox699.71±0.09A68±20AB1.69±0.25B167±72AControl599.70±0.10A73±30B1.44±0.29B138±49A? Sobs: number of OTUs observed at 97% similarity.* Sample groups sharing the same letter did not vary significantly (P ≤ 0.05) by ANOVA followed by Tukey’s post-hoc test.Figure 1. Distribution of microbial composition at (A) phylum level and (B) family level on the maize phyllosphere under influencing of Cmn and SsoPox. Figure 2. Family-level classification and mean relative abundances of OTUs that differed significantly in relative abundances between SsoPox and PBS treatment by LEfSe. A minimum LDA score of 2.8 was used for this analysis. Figure 3. Principal coordinate analysis of maize phyllosphere among three categories treatments: control (SsoPox and PBS), Cmn treatment (Cmm and Cmn+HEPES), influence of SsoPox (Cmn+SsoPox). The relationship between the ordination plot and the distance matrix had a r2 value of 0.93. Analysis of similarities (ANOSIM) described the differences of beta diversity among three treatments (the threshold of p value is 0.017 on the basis of Bonferroni pairwise comparison). Figure 4. Distribution of Clavibacter from NGS under difference treatments. Sample groups sharing the same letter did not vary significantly (P ≤ 0.05) by ANOVA followed by Tukey’s post-hoc test.Figure 5. Quantification of Clavibacter michiganensis subsp. nebraskensis under difference treatments by using qPCR through CMN_1184. Sample groups sharing the same letter did not vary significantly (P ≤ 0.05) by ANOVA followed by Tukey’s post-hoc test.Figure 6. Influence of SsoPox on the growth capability of Cmn.References: ADDIN EN.REFLIST 1.Remy, B.; Plener, L.; Poirier, L.; Elias, M.; Daude, D.; Chabriere, E., Harnessing hyperthermostable lactonase from Sulfolobus solfataricus for biotechnological applications. Scientific reports 2016, 6, 37780.2.Bergonzi, C.; Schwab, M.; Elias, M., The quorum-quenching lactonase from Geobacillus caldoxylosilyticus: purification, characterization, crystallization and crystallographic analysis. Acta Crystallogr F Struct Biol Commun 2016, 72, (Pt 9), 681-6.3.Gohl, D. M.; Vangay, P.; Garbe, J.; MacLean, A.; Hauge, A.; Becker, A.; Gould, T. J.; Clayton, J. B.; Johnson, T. J.; Hunter, R.; Knights, D.; Beckman, K. B., Systematic improvement of amplicon marker gene methods for increased accuracy in microbiome studies. Nat Biotechnol 2016, 34, (9), 942-9.4.Al-Ghalith, G. A.; Hillmann, B.; Ang, K.; Shields-Cutler, R.; Knights, D., SHI7 Is a Self-Learning Pipeline for Multipurpose Short-Read DNA Quality Control. Msystems 2018, 3, (3).5.Zhang, Q.; Al-Ghalith, G. A.; Kobayashi, M.; Segawa, T.; Maeda, M.; Okabe, S.; Knights, D.; Ishii, S., High-Throughput flaA Short Variable Region Sequencing to Assess Campylobacter Diversity in Fecal Samples From Birds. Front Microbiol 2018, 9.6.McDonald, D.; Price, M. N.; Goodrich, J.; Nawrocki, E. P.; DeSantis, T. Z.; Probst, A.; Andersen, G. L.; Knight, R.; Hugenholtz, P., An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. Isme J 2012, 6, (3), 610-618.7.Edgar, R. C.; Haas, B. J.; Clemente, J. C.; Quince, C.; Knight, R., UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 2011, 27, (16), 2194-2200.8.Bray, J. R.; Curtis, J. T., An ordination of the upland forest communities of southern Wisconsin. Ecological monographs 1957, 27, (4), 325-349.9.Clarke, K. R., Non-parametric multivariate analyses of changes in community structure. Australian Journal of Ecology 1993, 18, 117-143.10.Chen, H.; Boutros, P. C., VennDiagram: a package for the generation of highly-customizable Venn and Euler diagrams in R. BMC bioinformatics 2011, 12, (1), 35. ................
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