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1 PROGRESS REPORT PROJECT TITLE: Hyper-Thermostable Enzyme (Lactonases) for use as Microbial Biocontrol Agents for Plant Diseases PROJECT NUMBER: 4136-17SP REPORTING PERIOD: May. 1, 2019 July. 31, 2019 PRINCIPAL INVESTIGATOR: Michael Sadowsky and Mikael Elias ORGANIZATION: University of Minnesota PHONE NUMBER: 612-624-2706 EMAIL: [email protected] Clavibacter michiganensis subsp. nebraskensis (Cmn) Dose Response Assay for Corn Leaves Maize growth Maize cv Viking seed (40-30UP) were grown in Euro pots (diameter 8 inch) with a sterilized soil mixture (50 standard soil/ 50 Germinating Mix) in a plant growth chamber under diurnal conditions with a 16 hour light at 22 ˚C and 8 hour dark cycle at 18˚C. Bacteria working solution Firstly, Clavibacter michiganensis subsp. nebraskensis (causing Goss's bacterial wilt & leaf blight on Maize) was grown on NBY agar at room temperature ( for ~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 10 8 cell/ml). Infection assays and results The corn leaves were scraped with sterilized sand paper and inoculated serial diluted cells from 10 6 , 10 5 ,10 4 ,10 3 ,10 2 ,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 (10 6 and10 5 ) experiments. 10 6 10 5 10 4 10 3 10 2 10 0 Cmn + + - - - - -
Transcript

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PROGRESS REPORT

PROJECT TITLE: Hyper-Thermostable Enzyme (Lactonases) for use as Microbial Biocontrol Agents for

Plant Diseases

PROJECT NUMBER: 4136-17SP

REPORTING PERIOD: May. 1, 2019 – July. 31, 2019

PRINCIPAL INVESTIGATOR: Michael Sadowsky and Mikael Elias

ORGANIZATION: University of Minnesota

PHONE NUMBER: 612-624-2706

EMAIL: [email protected]

Clavibacter michiganensis subsp. nebraskensis (Cmn) Dose Response Assay for Corn Leaves

Maize growth

Maize cv Viking seed (40-30UP) were grown in Euro pots (diameter 8 inch) with a sterilized soil

mixture (50 standard soil/ 50 Germinating Mix) in a plant growth chamber under diurnal

conditions with a 16 hour light at 22 ˚C and 8 hour dark cycle at 18˚C.

Bacteria working solution

Firstly, Clavibacter michiganensis subsp. nebraskensis (causing Goss's bacterial wilt & leaf

blight on Maize) was grown on NBY agar at room temperature ( for ~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 results

The 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.

106 105 104 103 102 10 0

Cmn + + - - - - -

2

To better quantify the effect on plant disease, we adopted the use of chlorosis assay that non-

destructively measures plant chlorophyll in control and diseased corn leaf tissue.

Chlorophyll

Results 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 Levels

Scale designation Level

1

Level

2

Level

3

Level

4

Level

5

Level

6

Level

7

Level

8

Level

9

Level

10

Level

11

Level

12

Level

13

Percent of

leaf with

necrosis

0 2 5 10 20 30 40 50 60 70 80 90 100

Chlorophyll content in 6 replicates of corn with 106 cells Cmm Mean

Day 0 37.7 44.8 46.9 49.4 47.6 45.5 45.3

Day 18 2.4 9.0 7.8 8.8 13.1 10.9 8.6

Day 0 Day 18

3

The assay appears to be useful for other pathogens as well. Below is the Corn Leaf Assay done

using Clavibacter michiganensis subsp. nebraskensis (Cmn)

Treatment

Disease levels

Rep. A Rep. B Rep. C

Negative control 1 1 1

Buffer needle 1 1 1

SsoPox only 1 1 1

Cmn only 9 9 9

Cmn+SsoPox 3 3 3

Bacterial 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 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

4

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 SsoPox

Next-Generation Sequencing The 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 described3. 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).

Bioinformatics

Highly quality sequence data for analyses were obtrained by submitting the raw sequencing data

through the SHI7 pipeline for quantity control (QC) 4, 5. In brief, sequencing adaptors were

removed, the two paired-end reads were merged, and residual adaptors were further trimmed.

Low quality reads were removed to keep QC values > 31 and highly quality reads were

converted into the FASTA format and aligned on the basis of the Greengenes ver. 13.86.

UCHIME software was used to identify and remove the probable Chimeric sequence7. 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 (https://www.ncbi.nlm.nih.gov/sra).

Statistical analysis

For 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)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 conference

Summarized 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

5

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.

Corn field Study

In order to further understand the capability of SsoPox on corn disease in the field, we conducted

the corn 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 using 3

replications, and each block was also performed using 3 plants replications.

Results

Composition of microbial communities in the maize phyllosphere

Results 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. 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 control.

The ranking of diversity was as follows: Cmn+SsoPox > Control > Cmn. However, there was no

significant different between Cmn to Cmn+SsoPox in Chao1 and Sobs.

6

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 vs. 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/µL 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

7

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 Cmn

From 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.

Influence of SsoPox on corn disease at the Rosemount filed station

Bacterial leaf streak (BLS) symptom developed to only low severity levels at the Rosemount

study field. We will continue to examine BLS symptom next season. Therefore, we focused on

Goss’s Wilt caused by Cmn. From our study (Figure 7), SsoPox successfully suppressed the

Cmn (Figure 7D) compared with the Cmn-only treatment (Figure 7B) and Cmn+BSA treatment

(Figure7A). These exciting results were consistent and repeated in three different corn blocks at

the Rosemount field site. Based on these results, we are planning to test whether Goss’s Wilt can

be suppressed by SsoPox on different varieties of corn in the next season and at different

locations. Moreover, we will also test other corn disease, for example, diseases caused by

Xanthomonas vasicola pv. vasculorum (Xvv) (bacteria) and Exserohilum turcicum (Et) (fungus).

Outreach, writing a manuscript and preparing the conference

The manuscript related to our initial corn studies is under preparation now. We plan to submit it

for publication in the next month or so.

Qian Zhang will also make an oral presentation at the ASA/CSSA/SSA conference in San

Antonio, TX next month (Nov. 10-13, 2019).

8

TABLE 1 Coverage and alpha diversity of bacterial communities on the maize phyllospere

within various treatments.

Treatment No. samples Coverage (%) Sobs†

Shannon

index Chao1

Cmn 9 99.80±0.05A 43±11A 1.04±0.16A 112±38A

Cmn+SsoPox 6 99.71±0.09A 68±20AB 1.69±0.25B 167±72A

Control 5 99.70±0.10A 73±30B 1.44±0.29B 138±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.

9

Figure 1. Distribution of microbial composition at (A) phylum level and (B) family level on the

maize phyllosphere under influencing of Cmn and SsoPox.

0

10

20

30

40

50

60

70

80

90

100

Cmn Cmn+HEPS Cmn+SsoPox SsoPox PBS

Rel

ati

ve

ab

un

da

nce

(%

)

Tenericutes

Spirochaetes

Fusobacteria

Armatimonadetes

Fibrobacteres

FBP

Gemmatimonadetes

Acidobacteria

Crenarchaeota

Planctomycetes

Verrucomicrobia

Firmicutes

Bacteroidetes

Proteobacteria

Cyanobacteria

Actinobacteria

A

Treated by Cmn ControlTreated by.SsoPox

Cmn Cmn+HEPES SsoPoxCmn+SsoPox PBS

0

10

20

30

40

50

60

70

80

90

100

Cmn Cmn+HEPS Cmn+SsoPox SsoPox PBS

Rel

ati

ve

ab

un

dan

ce (

%)

Less abundance

Comamonadaceae

Sphingomonadaceae

Moraxellaceae

mitochondria

Pseudomonadaceae

Enterobacteriaceae

Microbacteriaceae

unclassified

B

Treated by Cmn ControlTreated by.SsoPox

Cmn Cmn+HEPES SsoPoxCmn+SsoPox PBS

10

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).

0

10

20

30

40

50

60

70

80

90

100

SsoPox PBS

Rel

ativ

e a

bu

nd

ance

(%)

unclassified(Alphaproteobacteria)

unclassified(Cyanobacteria)

Weeksellaceae

Moraxellaceae

Enterobacteriaceae

Rhodocyclaceae

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

-0.4 -0.2 0 0.2 0.4 0.6 0.8

PC

oA

2(3

4.0

1%

)

PCoA 1(36.44%)

Cm n

Cm nHEPS

Cm nSSO

SsoPox

PBS

R=0.93,(p

<0.001

R=0.98,(p<0.001

R=0.74,(p<0.001

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

-0.4 -0.2 0 0.2 0.4 0.6 0.8

PC

oA

2(3

4.0

1%

)

PCoA 1(36.44%)

Cm n

Cm nHEPS

Cm nSSO

SsoPox

PBS

Cmn

Cmn+HEPES

Cmn+SsoPox

SsoPox

PBS

11

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.

Cm

n

Cm

n+H

EPE

S

Cm

n+S

soP

oX

PB

S

Sso

Po

x0

0.05

0.1

0.15

0.2

0.25R

ela

tiv

e a

bu

nd

an

ce o

f C

lavib

acte

r (

%)

A

B

A

12

Figure 6. Influence of SsoPox on the growth capability of Cmn.

Figure 7. Influence of SsoPox on Goss’s wilt in Rosemount corn field

Negative Control

Cmn-only Treatment

A

B

B

Cmn+BSATreatment

C

C

Cmn+SsoPoxTreatment

D

D

13

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