improved n retention through plant-microbe interactions

1
RESULTS REFERENCES (1) Davis et al. 2012. PLOS One 7: e47149. (2) Lundberg D. S. et al. 2012. Nature 488: 86-90. (3) Norton J. M. 2008. Nitrogen in agricultural systems. Madison, WI: American Society of Agronomy, Inc. (4) Hofmockel K. et al., 2014. Poster for NIWQP and AFRI PD Meeting. (5) Osterholz W. et al., 2015. PhD Thesis ISU. (6) Kozich J. J. et al. 2013. Applied and Environmental Microbiology 79: 5112-5120. (7) Caporaso J. G. et al. 2010. Nature Methods 7: 335-336. (8) Edgar R. C. 2013. Nature Methods 10: 996-998. (9) McMurdie P. J. & Holmes S. 2013. PLOS One 8: e61217. (10) Segata N. et al. 2011. Genome Biology 12: R60. (11) Deng Y. et al. 2012. BMC Bioinformatics 13: 113-132. (12) Quast C. et al. 2013. Nucleic Acids Research 41: D590-D596. Plant Pathology & Microbiology 1 and Ecology, Evolution & Organismal Biology 2 NIWQP and AFRI PD Meeting October 12-13, 2016 Guillaume Bay 1,* , Kirsten Hofmockel 2 , Chiliang Chen 1 and Larry Halverson 1 Improved Nitrogen Retention Through Plant-Microbe Interactions SUMMARY OF FINDINGS In this poster we highlight the soil and rhizosphere microbial community of the entire root system of 3-week old maize grown in soil obtained from a conventional 2-yr corn/soybean & diversified 4-yr corn/soybean/oats/alfalfa rotation Diversified cropping systems modify the structure (abundance and composition) of both the total resident and metabolically active microbial communities (Figures 3, 4 & 5) Maize strongly influences the structure of the rhizosphere community in a cropping system dependent manner (Figures 3, 4 & 5). Likewise the endosphere community reflect whether the plant was grown in soil from a specific cropping system (Figure 3 and data not shown). The richness and evenness of both total and metabolically active microbial communities increase as a result of crop diversification (Table 1) Crop diversification reduces the abundance of AOB in the soil and AOA & AOB in the rhizosphere (Figure 5) Crop diversification tends to increase the level of organization and complexity of both soil and rhizosphere microbial networks (Table 2 ) CONCLUSIONS Soils of diversified system exhibit richer, more even microbial communities whose structure differs from that of conventional system Crop diversification leads to a significant decrease in the AOA/AOB populations, which may contribute to lower N loss from the system Crop diversification may enhance substrate use via a better coupling of carbon and N cycles, thanks to a more organized microbial community with a greater potential for interactions Cropping System Diversification Alters Microbial Community Structure Each datum point represents the quality filtered (Q25) relative abundances of all the OTUs in that sample. OTUs were classified against Silva 111 database (12) at 97% similarity. These plots illustrate that although samples from a given environment (bulk soil /rhizosphere/endosphere) cluster together they are distinct (p 0.008 and p 0.018) by cropping system based on Adonis statistical analysis. β-diversity 1 community structure (i.e. relative abundance). 1 β-diversity: ratio between mean local and mean regional species richness. p = 0.008 p = 0.018 B A Conventional Diversified Rotation Bulk Soil Endosphere Rhizosphere Compartment Figure 3 | Weighted UniFrac distance PCoA plots showing the effects of cropping system on bulk soil, and maize rhizosphere and endosphere (A) total and (B) metabolically active bacterial communities Cropping System Diversification Influences Microbial Richness and Evenness We used 3 separate α-diversity indices to assess how cropping systems influence the composition of the total and metabolically active microbial community. Observed: count of OTUs in each system; Chao 1: metric for species richness, the count of OTUs in a habitat that does not take into account their abundance; Simpson: metric for assessing how close in numbers is each OTU in a habitat. Values are the average for bulk soil, rhizosphere, and endosphere samples for each cropping system. In all cases there was greater species richness in the diversified compared to the conventional cropping system. Observed Simpson 8820 9423 ± 53 0.9961 9153 9747 ± 45 0.9946 Diversified Total Community Chao 1 Conventional Observed Simpson 7551 8377 ± 0.9976 8948 9449 ± 32 0.9971 Conventional Diversified Active Community Chao 1 130 Table 1 | Bacterial Diversity Indices Cropping System Diversification Alters Microbial Community Structure We used linear discriminant analysis effect size (LEfSe) (10) to assess how cropping systems affect the composition of microbial communities. Taxa that are significantly different (p = 0.05) are mapped onto the cladogram at the taxonomic level they differ between cropping system. Nodes and branches correspond to discriminant taxon and are colored according to the highest-ranked group (i.e. conventional or diversified) for that taxon. When the relative abundance for a specific taxon is not significantly different, the cor-responding node is colored yellow. Circles represent phylogenetic levels from Kingdom to Family from the inside outwards. Taxa with known nitrifying/denitrifying members as well as phyla of interest are represented by a unique numerical identifier. Bulk Soil Rhizosphere Total Community Active Community 1 2 1a1b 3 4 5 6 7 8 9 1 10 1a 1c 3 4 5 6 14 9 11 12 13 15 1 2 1a 3 6 9 16 17 14 15 1a 1c 10 16 6 18 14 8 9 Conventiona l Diversified 1: α-Proteobacteria b 1a: Sphingomonadaceae d & Erythrobacteraceae d 1b: Burkholderiales c 1c: Rhizobiaceae d 2: β-Proteobacteria b 3: Pseudomonadales 4: Thaumarchaeota a 5: Actinobacteria a 6: Rubrobacteria b 7: Bacteroidetes a 8: Cyanobacteria a 9: Nitrospiraceae d 10: Nitrosomonadaceae d 11: δ-Proteobacteria b 12: Euryarchaeota a 13: Acidobacteria a 14: Elusimicrobia a 15: Planctomycetes a 16: Verrucomicrobia a 17: Holophagae b 18: Chloroflexi a where a : Phylum, b : Class, c : Order, d : Family. Figure 4 | Cladograms of cropping system effects on taxonomic enrichments in the total and metabolically active bulk soil and rhizosphere communities Diversified Cropping Systems Exhibit Distinct Microbial Community Networks The interactions among microbial communities were assessed using a random matrix theory-based approach implemented in the Molecular Ecological Network Analysis pipeline (11). Bold values indicate which cropping system possesses attributes for more resilient and more interactive networks. Table 2 | Major topological properties of the molecular ecological co-occurrence networks of microbial communities from conventional and diversified cropping systems R² of Network Total links Average Average Average Modularity power size (% pos/neg connectivity path length clustering (number of law interactions) coefficient modules) Total Community Bulk Soil Conventional 0.91 988 4127 (85/15) 8.354 5.31 0.288 0.579 (87) Diversified 0.85 863 6386 (82.5/17.5) 14.8 4.352 0.362 0.452 (60) Rhizosphere Conventional 0.90 737 1934 (96.5/3.5) 5.248 6.732 0.263 0.745 (78) Diversified 0.88 904 3540 (98.2/1.8) 7.832 6.803 0.357 0.713 (43) Active Community Bulk Soil Conventional 0.89 2176 6946 (77/23) 6.384 6.874 0.249 0.628 (142) Diversified 0.89 2331 9632 (77.4/22.6) 8.264 6.351 0.267 0.655 (121) Rhizosphere Conventional 0.72 1366 10566 (78.3/21.7) 15.47 5.23 0.41 0.598 (14) Diversified 0.52 854 9928 (99.4/0.6) 23.251 8.353 0.416 0.317 (58) We used qPCR to measure the abundance of AOA and AOB. While there was no significant effect of cropping system on soil AOA abundance there were fewer AOB in soils from the diversified system (A). In contrast, there was a dramatic decrease in abundance of AOA and AOB on maize roots grown in soil from the diversified cropping system (B). Values are means ± SE; n = 8. Values within a compartment with different letters are statistically different. Cropping System Diversification Affects Ammonia-Oxidizers’ Abundance Figure 5 | Effect of diversification on AOA and AOB amoA gene abundance in (A) the bulk soil and (B) the rhizosphere p < 0.001 A B B A Microbial Type & Cropping System AOA Conventiona l Diversified Conventiona l Diversified AOB p = 0.02 p = 0.31 p < 0.001 B A A A B A Conventiona l Diversified AOA Microbial Type & Cropping System Conventiona l Diversified AOB amoA gene copy number g soil -1 (×10 6 ) amoA gene copy number cm root -2 (×10 6 ) 0 15 30 45 60 75 90 105 120 135 150 0 0.25 0.50 0.7 5 1 1.25 1.50 1.75 2 2.25 *contact: [email protected] CONTEXT Microbes play an essential role in soils, being able to shape plant development and nutrient availability (2). Ammonia-oxidizing bacteria (AOB) and archaea (AOA) mediate the rate-limiting step of nitrification, the conversion of NH 4 + to NO 3 - , contributing to eutrophication of water (3). Despite similar total %C and N contents and NH 4 + pool sizes, compared to conventional systems soil from diversified systems have lower NO 3 - pool sizes. Prior work at the Marsden site also demonstrated increased soil protease activity (4) but comparable NH 3 mineralization rates (5) in the diversified compared to conventional cropping system. Soil microbiome = soil microbes not directly influenced by plant roots Rhizosphere microbiome = microbes infuenced by rhizodeposits OBSERVATIONS At the Marsden long-term cropping system site, more diversified 4-year rotations (maize/soybean/oat/alfalfa) managed with lower inorganic nitrogen (N)-inputs and periodic application of composted manure (100 kg N ha -1 ) can yield comparably to conventionally managed 2-year rotations (maize-soybean) receiving normal rates of inorganic N-fertilizer, and result in lower N loss than conventional systems (1). APPROACH We used 16S amplicon sequencing and qPCR of ammonia oxidizers to assess the effect of cropping system on the soil total resident (DNA-based) and metabolically active (rRNA-based) community profiles and whether the maize root harbors distinct communities in a cropping system-specific manner. HYPOTHESIS As compared to simpler cropping systems, soils in diversified cropping systems foster different microbial assemblages resulting in tighter coupling of available N supply and demand, and smaller inorganic N pools. MATERIAL & METHODS 2. Plants Grown in Rhizotrons Figure 2 Twenty-one-day old maize plants growing in rhizotrons filled with soil from conventional and diversified cropping system plots. 1. Experimental Site 3. Sample Collection, Sequencing, qPCR & Data Analysis Figure 1 Marsden field site in Iowa, USA, established in 2002; randomized complete block (n-4) design where each phase of each rotation is present every year. Plots are 18 m × 85 m. 2. DNA & RNA extractions 3a. qPCR on ammonia mono-oxygenase (amoA) gene of AOA/AOB from soil and rhizosphere microbiomes Phyloseq in (9) MENAP (Molecular Ecological Network Analysis Pipeline) (11) LEfSe (Linear Discriminant Analysis Effect Size) (10) 1. Rhizotrons: - Bulk soil collection - Sampling of the microbial communities (washing of roots & sonication) (8) UPARSE OTU Clustering Pipeline Quantitative Insights Into Microbial Ecology (7) 3b. Illumina MiSeq sequencing on bulk soil and rhizosphere communities (6)

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Page 1: Improved N Retention Through Plant-Microbe Interactions

RESULTS

REFERENCES(1) Davis et al. 2012. PLOS One 7: e47149.(2) Lundberg D. S. et al. 2012. Nature 488: 86-90.(3) Norton J. M. 2008. Nitrogen in agricultural systems. Madison,WI: American Society of Agronomy, Inc.(4) Hofmockel K. et al., 2014. Poster for NIWQP and AFRI PDMeeting.(5) Osterholz W. et al., 2015. PhD Thesis ISU.(6) Kozich J. J. et al. 2013. Applied and EnvironmentalMicrobiology 79: 5112-5120.(7) Caporaso J. G. et al. 2010. Nature Methods 7: 335-336.

(8) Edgar R. C. 2013. Nature Methods 10: 996-998.(9) McMurdie P. J. & Holmes S. 2013. PLOS One 8: e61217.(10) Segata N. et al. 2011. Genome Biology 12: R60.(11) Deng Y. et al. 2012. BMC Bioinformatics 13: 113-132.(12) Quast C. et al. 2013. Nucleic Acids Research 41: D590-D596.

Plant Pathology & Microbiology1 and Ecology, Evolution & Organismal Biology2

NIWQP and AFRI PD MeetingOctober 12-13, 2016

Guillaume Bay1,*, Kirsten Hofmockel2, Chiliang Chen1 and Larry Halverson1

Improved Nitrogen Retention Through Plant-Microbe Interactions

SUMMARY OF FINDINGS• In this poster we highlight the soil and rhizosphere microbial community of the

entire root system of 3-week old maize grown in soil obtained from a conventional2-yr corn/soybean & diversified 4-yr corn/soybean/oats/alfalfa rotation

• Diversified cropping systems modify the structure (abundance and composition)of both the total resident and metabolically active microbial communities (Figures3, 4 & 5)

• Maize strongly influences the structure of the rhizosphere community in acropping system dependent manner (Figures 3, 4 & 5). Likewise the endospherecommunity reflect whether the plant was grown in soil from a specific croppingsystem (Figure 3 and data not shown).

• The richness and evenness of both total and metabolically active microbialcommunities increase as a result of crop diversification (Table 1)

• Crop diversification reduces the abundance of AOB in the soil and AOA & AOBin the rhizosphere (Figure 5)

• Crop diversification tends to increase the level of organization and complexity ofboth soil and rhizosphere microbial networks (Table 2 )

CONCLUSIONS• Soils of diversified system exhibit richer, more even microbial communities whose

structure differs from that of conventional system

• Crop diversification leads to a significant decrease in the AOA/AOB populations,which may contribute to lower N loss from the system

• Crop diversification may enhance substrate use via a better coupling of carbonand N cycles, thanks to a more organized microbial community with a greaterpotential for interactions

• Cropping System Diversification Alters Microbial Community StructureEach datum point represents the qualityfiltered (Q25) relative abundances of allthe OTUs in that sample. OTUs wereclassified against Silva 111 database (12)at 97% similarity. These plots illustratethat although samples from a givenenvironment (bulk soil/rhizosphere/endosphere) clustertogether they are distinct (p ≤ 0.008 andp ≤ 0.018) by cropping system based onAdonis statistical analysis. β-diversity1

community structure (i.e. relativeabundance).1β-diversity: ratio between mean localand mean regional species richness.

p = 0.008 p = 0.018

BA

Conventional DiversifiedRotation Bulk Soil

EndosphereRhizosphereCompartment

Figure 3 | Weighted UniFrac distance PCoA plots showing the effects ofcropping system on bulk soil, and maize rhizosphere and endosphere(A) total and (B) metabolically active bacterial communities

• Cropping System Diversification Influences Microbial Richness and EvennessWe used 3 separate α-diversity indices to assess how croppingsystems influence the composition of the total andmetabolically active microbial community. Observed: countof OTUs in each system; Chao 1: metric for species richness,the count of OTUs in a habitat that does not take into accounttheir abundance; Simpson: metric for assessing how close innumbers is each OTU in a habitat. Values are the average forbulk soil, rhizosphere, and endosphere samples for eachcropping system. In all cases there was greater speciesrichness in the diversified compared to the conventionalcropping system.

Observed Simpson

8820 9423 ± 53 0.99619153 9747 ± 45 0.9946Diversified

Total Community Chao 1

Conventional

Observed Simpson

7551 8377 ± 0.99768948 9449 ± 32 0.9971

ConventionalDiversified

Active Community Chao 1

130

Table 1 | Bacterial Diversity Indices

• Cropping System Diversification Alters Microbial Community StructureWe used linear discriminant analysis effect size(LEfSe) (10) to assess how cropping systemsaffect the composition of microbial communities.Taxa that are significantly different (p = 0.05)are mapped onto the cladogram at the taxonomiclevel they differ between cropping system. Nodesand branches correspond to discriminant taxonand are colored according to the highest-rankedgroup (i.e. conventional or diversified) for thattaxon. When the relative abundance for aspecific taxon is not significantly different, thecor-responding node is colored yellow. Circlesrepresent phylogenetic levels from Kingdom toFamily from the inside outwards. Taxa withknown nitrifying/denitrifying members as well asphyla of interest are represented by a uniquenumerical identifier.

Bulk Soil Rhizosphere

Tota

l Com

mun

ityAc

tive

Com

mun

ity

1 21a1b

3

4

5

67

8

9

1 101a

1c3

4

5

6

14

9

11

12

13

15

1 21a

3

6

9

16

17

14

151a

1c

10

16

6

18

14

8

9

ConventionalDiversified

1: α-Proteobacteriab

1a: Sphingomonadaceaed

& Erythrobacteraceaed

1b: Burkholderialesc

1c: Rhizobiaceaed

2: β-Proteobacteriab

3: Pseudomonadales 4: Thaumarchaeotaa

5: Actinobacteriaa

6: Rubrobacteriab

7: Bacteroidetesa

8: Cyanobacteriaa

9: Nitrospiraceaed

10: Nitrosomonadaceaed

11: δ-Proteobacteriab

12: Euryarchaeotaa

13: Acidobacteriaa

14: Elusimicrobiaa

15: Planctomycetesa

16: Verrucomicrobiaa

17: Holophagaeb

18: Chloroflexia

where a: Phylum, b: Class,c: Order, d: Family.

Figure 4 | Cladograms of cropping system effects ontaxonomic enrichments in the total and metabolicallyactive bulk soil and rhizosphere communities

• Diversified Cropping Systems Exhibit Distinct Microbial Community Networks

The interactions amongmicrobial communities wereassessed using a randommatrix theory-based approachimplemented in the MolecularEcological Network Analysispipeline (11). Bold valuesindicate which croppingsystem possesses attributes formore resilient and moreinteractive networks.

Table 2 | Major topological properties of the molecular ecological co-occurrence networksof microbial communities from conventional and diversified cropping systems

R² of Network Total links Average Average Average Modularitypower size (% pos/neg connectivity path length clustering (number of

law interactions) coefficient modules)

Total CommunityBulk Soil

Conventional 0.91 988 4127 (85/15) 8.354 5.31 0.288 0.579 (87)Diversified 0.85 863 6386 (82.5/17.5) 14.8 4.352 0.362 0.452 (60)

RhizosphereConventional 0.90 737 1934 (96.5/3.5) 5.248 6.732 0.263 0.745 (78)Diversified 0.88 904 3540 (98.2/1.8) 7.832 6.803 0.357 0.713 (43)

Active CommunityBulk Soil

Conventional 0.89 2176 6946 (77/23) 6.384 6.874 0.249 0.628 (142)Diversified 0.89 2331 9632 (77.4/22.6) 8.264 6.351 0.267 0.655 (121)

RhizosphereConventional 0.72 1366 10566 (78.3/21.7) 15.47 5.23 0.41 0.598 (14)Diversified 0.52 854 9928 (99.4/0.6) 23.251 8.353 0.416 0.317 (58)

We used qPCR to measure the abundance ofAOA and AOB. While there was no significanteffect of cropping system on soil AOAabundance there were fewer AOB in soilsfrom the diversified system (A). In contrast,there was a dramatic decrease in abundanceof AOA and AOB on maize roots grown in soilfrom the diversified cropping system (B).Values are means ± SE; n = 8. Values within acompartment with different letters arestatistically different.

• Cropping System Diversification Affects Ammonia-Oxidizers’ Abundance

Figure 5 | Effect of diversification on AOA and AOB amoAgene abundance in (A) the bulk soil and (B) the rhizosphere

p < 0.001

AB

B

A

Microbial Type & Cropping SystemAOA

Conventional

Diversified Conventional

DiversifiedAOB

p = 0.02p = 0.31 p < 0.001

B

AA

A

BA

Conventional

DiversifiedAOA

Microbial Type & Cropping System

Conventional

DiversifiedAOB

amoA

gene

cop

y nu

mbe

r g s

oil-1

(×10

6 )

amoA

gene

cop

y nu

mbe

r cm

root

-2(×

106 )

0

15

30

45

60

75

90

105

120

135

150

0

0.25

0.50

0.75

1

1.25

1.50

1.75

2

2.25

*contact: [email protected]

CONTEXT• Microbes play an essential role in soils, being able to shape plant development and nutrient

availability (2).• Ammonia-oxidizing bacteria (AOB) and archaea (AOA) mediate the rate-limiting step of

nitrification, the conversion of NH4+ to NO3

-, contributing to eutrophication of water (3).• Despite similar total %C and N contents and NH4

+ pool sizes, compared to conventionalsystems soil from diversified systems have lower NO3

- pool sizes.• Prior work at the Marsden site also demonstrated increased soil protease activity (4) but

comparable NH3 mineralization rates (5) in the diversified compared to conventionalcropping system.

• Soil microbiome = soil microbes not directly influenced by plant rootsRhizosphere microbiome = microbes infuenced by rhizodeposits

OBSERVATIONSAt the Marsden long-term cropping system site, more diversified 4-year rotations(maize/soybean/oat/alfalfa) managed with lower inorganic nitrogen (N)-inputs and periodicapplication of composted manure (≈ 100 kg N ha-1) can yield comparably to conventionallymanaged 2-year rotations (maize-soybean) receiving normal rates of inorganic N-fertilizer,and result in lower N loss than conventional systems (1).

APPROACHWe used 16S amplicon sequencing and qPCR of ammonia oxidizers to assess the effect ofcropping system on the soil total resident (DNA-based) and metabolically active (rRNA-based)community profiles and whether the maize root harbors distinct communities in a croppingsystem-specific manner.

HYPOTHESISAs compared to simpler cropping systems, soils in diversified cropping systems foster differentmicrobial assemblages resulting in tighter coupling of available N supply and demand, andsmaller inorganic N pools.

MATERIAL & METHODS2. Plants Grown in Rhizotrons

Figure 2 Twenty-one-day old maize plants growing in rhizotrons filledwith soil from conventional and diversified cropping system plots.

1. Experimental Site

3. Sample Collection, Sequencing, qPCR & Data Analysis

Figure 1 Marsden field site in Iowa, USA, established in 2002;randomized complete block (n-4) design where each phase ofeach rotation is present every year. Plots are 18 m × 85 m.

2. DNA & RNA extractions

3a. qPCR on ammonia mono-oxygenase (amoA) gene of AOA/AOB from soil and rhizosphere microbiomes

Phyloseq in (9)

MENAP (Molecular Ecological Network Analysis Pipeline)

(11)

LEfSe (Linear Discriminant Analysis Effect Size)

(10)

1. Rhizotrons:- Bulk soil collection- Sampling of the microbial

communities (washing of roots & sonication) (8)UPARSE

OTU Clustering Pipeline

Quantitative Insights Into Microbial Ecology

(7)

3b. Illumina MiSeq sequencing on bulk soil

and rhizosphere communities (6)