Recipient Organization
COLLEGE OF WILLIAM AND MARY
1314 S MOUNT VERNON AVE
WILLIAMSBURG,VA 23185
Performing Department
(N/A)
Non Technical Summary
The objectives of this project are to: 1) characterize soil microbiome community structures, focusing on viruses, bacteria, archaea, and fungi; 2) investigate the temporal effects and interaction of different agricultural management practices on soil microbiomes and crop production; 3) determine the impacts of viral predation on soil microbiome structure and function, including crop production; and 4) develop a conceptual model for how viruses impact soil microbiomes, respond to soil management practices, and ultimately impact system productivity. These objectives will be met through a combination of field studies and manipulative experiments using microcosm (greenhouse) approaches. Metagenomics and amplicon high-throughput sequencing will be applied to characterize soil microbial communities, quantify viral impacts, and ultimately integrate viruses as part of agriculture soil microbiomes. The proposed work will address program goals by: 1) characterizing molecular mechanisms involved in microbiome assembly and interactions in various environments and growth stages; and 2) functionally characterizing microbiomes, including viruses, and their role in optimization of environmental processes (i.e., nitrogen cycling, soil health, plant growth and productivity). We lack models that include the role of viruses in agricultural production systems, and characterization of the soil virome stands as a major challenge of the 21st Century. The proposed study will substantially improve our fundamental understanding of how viruses impact microbial community dynamics, soil health and crop productivity under different agricultural practices. Project outcomes will help us better design and target best management practices that can inform better decision making and sustain our next generation of agriculture.
Animal Health Component
10%
Research Effort Categories
Basic
90%
Applied
10%
Developmental
0%
Goals / Objectives
The overarching goal of this research is to assess how viruses function as part of agriculture soil microbiomes and how those functions impact soil health and crop productivity. This work will investigate the role of viruses within the soil microbiome (bacteria, archaea and fungi) under different farming practices (conventional, conservation, and organic, defined below) through field sampling and greenhouse experiments. To date, there has been very limited research on the soil virome regarding its composition, interactions with other soil microbes, and its potential impacts on agriculture. We hypothesize that the composition, distribution, and functions of the agriculture virome have important consequences for structuring soil microbiomes, manipulating the associated soil processes and functions, as well as for long term soil health and sustainable agriculture.Specific goals include:Objective 1: Characterize soil microbiome community structures, focusing on bacteria, archaea, fungi and viruses. DNA-based molecular techniques and high-throughput sequencing will be applied to characterize soil microbial communities and integrate viruses as part of the soil microbiome. Interaction networks, host prediction analyses, and characterization of virus-encoded auxiliary metabolic genes will be used to assess the role of viruses in soil microbiomes.Objective 2: Investigate the temporal effects and interaction of agricultural management practices on soil microbiomes and crop production. Physical and chemical properties of soil samples at two depths will be examined from fields with different management practices (conventional, conservation, organic) over two growing seasons. Management will be linked with soil properties (including bulk density, aggregate stability, pH, cation exchange capacity, extractable nutrients) as well as microbiome structure and function (e.g., nitrogen transformation potential, active carbon, and viral auxiliary metabolic genes).Objective 3: Determine the impacts of viral predation on soil microbiome structure and function, including crop production. Microcosm approaches will be used to assess the direct impacts of viral infection and lysis on soil microbiomes and ultimately plant growth and productivity over one growing season.Objective 4: Develop a conceptual model for how viruses impact soil microbiomes, respond to soil management practices, and ultimately impact system productivity. The collective data generated by these endeavors will be integrated into a conceptual model that accounts for the roles of viruses within agriculture soil microbiomes, including direct and indirect impacts on soil health and crop productivity.
Project Methods
Sampling the soil of corn fields: Soil samples will be collected in three 6 x 92 m replicate corn fields at RI-FST. For this proposed study, samples will be collected at two different timepoints relating to plant growth (cover crop and cash crop) and across two years. To account for spatial heterogeneity in the field samples, a total of 30 separate surface soil cores (0-15 cm depth per the soil health assessment protocol, and 15-30 cm depth) will be taken randomly from each of 3 replicate plots at RI-FST, across the length of the field. Soil cores will be collected using a 2.5 cm diameter stainless steel soil corer, and cores from each depth increment (0-15 cm and 15-30 cm) will be homogenized within each field to generate two composite samples. By sampling surface soil up to 30 cm, our study will focus on the highly active zone in closest proximity to cash crops (corn in this case). We propose to perform this sampling regime at all fields across the 3 farming practices. This protocol will generate 72 soil samples across 3 farming practices for two time points over two years. To determine temporal patterns during the year, samples will be collected 1) prior to cover crop termination and cash crop planting in spring, and 2) at the end of the growing season in late summer during steady state corn growth (at stage V3). Soil sampling will occur once at least 50% of plants reach the target growth stage.Greenhouse (microcosm) experiments: To address Q3, greenhouse (microcosm) experiments will be conducted that directly link soil viruses to changes in microbiome structure and function, including crop performance. Such microcosm approaches have proven particularly valuable in revealing direct impacts of viruses on soil nitrogen (Braga et al. 2020) and carbon cycling. Microcosms (18 total) will consist of 12"x12" pots filled with non-sterile field soil from one FST plot and planted to corn. Viruses will be extracted and concentrated from: a) soil from the same plot used to establish the microcosms, and b) soil from a different management regime. Final decisions will be made regarding the specific field soils to be used in greenhouse experiments pending results from Y1 and Y2 analyses. Microcosms will be split across treatments according to Figure 6. In two concurrent experiments: 3 replicates will receive no virus (buffer control); 3 replicates will receive live viral concentrate added at 2X ambient viral concentration; and 3 replicates will receive heat-killed viral concentrate to control for effects of non-viral components in the viral concentrate (e.g., nutrients). Integrated soil samples will be collected from each microcosm at three timepoints over the course of plant growth (initial, at growth stage V3, and at crop maturity). This protocol will generate 54 soil samples (3 replicates x 3 treatments x 3 timepoints x 1 soil x 2 sources of virus). The response variables to be measured as a result of viral manipulations include plant shoot and root biomass and ratio, relative contributions of assembly processes in microbial community composition, and predicted microbial functions.Monitoring of soil health and crop production: A soil health score will be determined for each field at each sampling time using the Cornell Assessment of Soil Health (CASH). The following attributes will be included in the score: soil pH, organic matter content, extractable phosphorus, potassium, micronutrients, soil texture, active carbon (e.g., permanganate oxidizable carbon), wet aggregate stability, soil respiration, total carbon, and total nitrogen. In addition to inclusion in determining an overall soil health score, individual metrics derived from the CASH will contribute to assessment of nitrogen and carbon cycling dynamics. Fresh soil samples will be stored at 4oC and transferred to the Cornell CASH lab as soon as possible after each collection; this will include 72 from the field study and 18 (final samples only) from greenhouse experiments. Crop productivity will be measured by Rodale farm operation team, either by a plot combine harvester together with a harvest master, or by hand for both field sampling and greenhouse experiments (see Table 3).Microbial analysis of soils: Microbes, including fungi, bacteria and archaea can promote plant growth by decomposing organic substances, serving as symbiotic partners (e.g., Rhizobacteria), and acting as antagonists against plant. Viruses may play important roles in nutrient cycling and controlling host community composition and abundance. These potential impacts are hypothesized but not well characterized for viruses in soils. Determining soil microbial characteristics (e.g., biodiversity, community structure, functional gene quantification) will: (i) help develop a more comprehensive understanding of farming practices and soil health relationships; (ii) provide a cost effective, relevant measure of ecosystem health (i.e., microbial biodiversity); and (iii) quantify relevant functional genes as a metric for indicating the soil's capacity for important nutrient transformations (e.g., nitrogen fixation, mineralization, nitrification and denitrification) that differ between agricultural practices.To characterize the microbial community structure at each experimental plot in the field studies (72 samples) and in replicate microcosms in the greenhouse (microcosm) study (54 samples), subsamples of soil will be stored at -80ºC until nucleic acid/virus particle extraction. See Table 3 for summary approaches. Viruses: Virus particles will be extracted from homogenized soil samples, concentrated using tangential flow filtration, and purified using standardized approaches for viral metagenomics. Viromes will be sequenced using Nextera XT v2 kits in conjunction with Illumina sequencing (Novaseq S4 6000). Viral metagenomic sequence data will be assembled using meta SPAdes and annotated using the MG-RAST and VIBRANT pipelines. Viral abundance will be estimated using epifluorescence microscopy. Bacteria, Archaea and Fungi: DNA will be extracted with Qiagen DNeasy PowerSoil kits, and 16S rRNA and ITS genes will be amplified as described below. Detailed bacterial, archaeal, and fungal biodiversity and community structure will be characterized by a high throughput sequencing platform (Illumina) at University of Georgia's core facility. Benefiting from the recent improvement of yielding longer sequences with paired-end reads from the same amplicon, we will amplify the hypervariable V3-V4 regions of the 16S rRNA gene, which is a standard protocol for microbial community analysis. For fungi the focus will be ITS, which is also commonly used in surveys. Regions will be targeted using protocols from the Earth Microbiome Project (EMP). For Bacteria and Archaea, EMP uses primers 515FB and 806RB that improve previous primer sets by capturing Crenarachaeota/Thaumarchaeota and Alphaproteobacterial clade SAR11, respectively. For fungi, EMP uses ITS1f and ITS2. Like other high-throughput techniques, with proper sequencing depth Illumina can detect rare members of the microbial community while providing millions of sequences with sufficient length to accurately identify consortia members and evaluate detailed community structures. Prokaryotic abundances will be estimated using epifluorescence microscopy.Nitrogen transformation potentials will be quantified by real-time PCR (qPCR) focusing on N2 fixation, nitrification and denitrification genes: 1) nitrogen-fixing bacteria: nifH gene; 2) ammonia-oxidizing Archaea (AOA) and Bacteria (AOB): amoA gene, amoA-beta, amoA-gamma; 3) denitrifying bacteria: nirS or nirK, and nosZ. Per fungi:bacteria ratio, we will determine the abundance of fungi ITS copies vs. bacteria 16S rRNA gene copies with the same primer sets mentioned above, and quantified in each sample by using qPCR.