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Improved N Retention Through Plant-Microbe Interactions


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Improved N Retention Through Plant-Microbe Interactions

  1. 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 & Microbiology1 and Ecology, Evolution & Organismal Biology2 NIWQP and AFRI PD Meeting October 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 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-diversity1 community structure (i.e. relative abundance). 1β-diversity: ratio between mean local and mean regional species richness. p = 0.008 p = 0.018 BA Conventional Diversified Rotation Bulk Soil EndosphereRhizosphere 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 0.9946Diversified 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 TotalCommunityActiveCommunity 1 2 1a1b 3 4 5 67 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-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 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 = 0.02p = 0.31 p < 0.001 B A A A BA Conventiona l Diversified AOA Microbial Type & Cropping System Conventiona l Diversified AOB amoAgenecopynumbergsoil-1(×106) amoAgenecopynumbercmroot-2(×106) 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: 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 conventional systems 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 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)