Recipient Organization
PENNSYLVANIA STATE UNIVERSITY
408 Old Main
UNIVERSITY PARK,PA 16802-1505
Performing Department
Ecosystem Science and Manageme
Non Technical Summary
Soil health, which is inherently dependent on processes carried out by soil microorganisms, is crucial to sustainable agriculture. Researchers' poor understanding of how soil microbiomes and microbiome functionatliy relate to soil health creates challenges in communicating with farmers, land owners, and extension educators about management impacts on soil health and microbiomes. This proposal describes an Integrated pre-doctoral project led by Mara Cloutier, a Ph.D. candidate in Soil Science and Biogeochemistry at The Pennsylvania State University (PSU). Dr. Mary Ann Bruns and Dr. Kristy Borelli will service as Primary Mentors for Research and Extension. The research objective is to identify relationships between soil health, microbial assemblages, and microbiol functionality to determine how management practices impact these relationships. The extension objectivve is to develop ways to more effectively community soil microbiome data as an aspect of soil health to farmers and agricultural service providers through survey-based information compilation and a training workshop. The basic and applied contributions of this project address the USDA NIFA AFRI Farm Bill Priority areas "Agricultural Systems and Technology", and "Bioenergy, Natural Resources, and Environment". Relevance of this project to goals of the pre-doctoral program will be development of the PD's skills to perform innovative research and education pertinent to soil health and sustainable agriculture. This project is relevant to goals of the EWD program bcause if will increase the knowledge of relationships between soil health, microbiomes, and their functions.
Animal Health Component
20%
Research Effort Categories
Basic
80%
Applied
20%
Developmental
(N/A)
Goals / Objectives
The overarching research goals of this study are to conduct a qualitative and exploratory survey that will engage farmers by showing them how their local undisturbed soils microbiomes compare to upland and lowland soils on their farms and to compare MPs between farms. This strategy is intended to provide insights on how -omics data relates to soil microbial functions that are of interest to farmers and to identify organisms, genes, or interactions between the two that could be used as SH indicators.My overall extension goal is to identify ways to more effectively communicate soil microbial function as an aspect of SH to ASPs, other scientists, and farmers, while also determining the limitations and strengths of using -omic data to identify how MPs impact soil microbiomes.
Project Methods
Approach: Research Objectives: To identify relationships between -omics data, microbial functions and SH, I will conduct a survey of soils from six farms from central Pennsylvania, three in no-till and three in tillage to include an upland site, a lowland site, and a 'native' soil for 16S rRNA and meta-transcriptomic sequencing, enzyme assays, and SH testing. Each treatment combination will be represented at three sites.Soil Sampling and Analyses: Bulk soil cores (2.5 cm diameter) will be sampled at 10 locations across each field and taken at a depth of 10 cm. Samples will be placed into a bag and homogenized to create 1 composite sample from each field. Soil collected from each of the fields will be analyzed for SH, which will be assessed at Cornell University, Ithaca, NY, USA. Apart from the SH test, a range of enzyme assays.Molecular Techniques: 16S rRNA sequencing- Soil DNA and RNA will be extracted using the Qiagen kits, DNeasy PowerSoil Kit and RNeasy PowerSoil Kit. Following DNA extraction and sequencing preparation, Illumina amplicon sequencing will be performed by amplifying the 16S rRNA DNA sequences at the Genomics Core Facility at PSU. Meta-transcriptomic sequencing- Following RNA extraction and depletion, samples will be prepped for sequencing and sequenced by the Genomics Core Facility.Bioinformatics: 16S rRNA sequencing- Following sequencing, reads will be processed using QIIME supported commands to include operational taxonomic unit classification, chimeric sequence removal, and taxonomic classification (Caporaso et al, 2010). Meta-transcriptomic sequencing- Generate libraries of approximately 150 bp from Illumina shotgun sequencing. After reads are trimmed and filtered using trimmomatic, two separate analyses will be performed to 1) annotate short reads and perform differential abundance analyses and 2) to assemble reads into contigs, annotate, and perform differential analyses. Short reads will be filtered to remove the rRNA and the remaining reads will be queried against the BLASTx non-rRNA NCBI nr database. Annotation will be performed with MEGAN using cluster of orthologous groups (COG), Kyoto Encyclopedia of Genes and Genomes (KEGG), and SEED databases. Abundances of each transcript will be attained and subsequent bioinformatic analyses performed. Trinity will be used to assemble a de novo transcriptome. Bowtie2 will be used to align the reads back to the de novo transcriptome. Reads in low abundance across the sample libraries will be filtered out. Transcript abundances will be estimated via RSEM and differential abundance analyses will be performed in R. Reads will also be assembled and contig quality will be analyzed using Trinity. TransDecoder and Trinotate will be used to annotate assembled contigs to identify open reading frame peptides. Protein function will be assigned using the Swiss-Prot database. Protein domains will be identified using Hmmer and PFAM, which will then be queried against the BLAST x database. For transcripts that do not assemble using available packages, reads will be queried against the NCBI non-redundant protein database using BLASTX. Reads will be functionally annotated via the COG, KEGG and SEED databases.StatisticalAnalyses:Following sequence processing, analyses that will be performed include differential abundance based on tillage treatment, landscape position, and cultivation, as well as with continuous variables from enzyme assays and soil health tests. Additional analyses will include PERMANOVAs to determine if there are differences in the transcriptomes between tillage treatments, landscape position, and cultivation. Canonical correspondence analyses will be used to determine if enzyme assays or soil health metrics predict sample functionality. Network analyses will be used to determine if there are correlations between the abundances of transcripts.Extension Objectives: Surveys will be conducted with farmer cooperators to assess their current knowledge and change in knowledge of soil microbiomes, microbiome functionality, and SH at the start and completion of this project. Surveys will also be conducted at extension-based conferences and workshops such as those hosted by PASA and the NTA to determine the challenges and needs of extension-based workers and other ASPs in communicating microbiome research to farmers and other land owners. To better understand these challenges and needs, a workshop for ASPs will be conducted to educate, train, and discuss agricultural soil microbiomes and their relation to SH. Surveys will be conducted pre/post workshop to assess the change in knowledge of soil microbiomes. Finally, a website will be created and updated regularly to document my journey of communicating microbiome research and results to a broader audience.Project Pitfalls and limitations: Variation in soil properties such as soil texture are expected and can impact the organisms that are found and the genes that are expressed. I will minimize these effects by sampling the same soil type in the lowland sites and a similar soil type in the upland sites. Additionally, I will include these parameters in my analyses to determine the impact that the soil edaphic properties have on microbiomes and their functions and SH.Hazard Statement: Hazards that are associated with this study are similar to other field based ecological research programs. Clear communication with landowners about possible risks to data collection personnel will be performed.Progress monitoring: Career progress throughout my PhD program will be documented on my LinkedIn profile, as well as my person website.Project impacts: This research will contribute to the fundamental understanding of how SH, the soil microbiome and the respective functionality of the microbiome are related. The extension portion of this project will identify how to better communicate microbiome research to farmers, extension specialists, and other ASPs. Through effective dissemination of results, farmers will have a better understanding of how MPs impact SH and soil microbiomes and can assist farmers in making informed decisions that advance sustainable agriculture and build SH.Social networking: My work is described on the Bruns lab website (http://sites.psu.edu/soilmicro biology/), as well as my own website (https://maralcloutier.weebly.com), my public Google Scholar (https://scholar.google.com/citations?user=sx8HmkIAAAAJ&hl=en), and ResearchGate (https://www.researchgate.net/profile/Mara_Cloutier) profiles and will continually be updated to document my career development during and after graduate school.Evaluation Plan and Timeline: The advisory panel will include PD Cloutier and all project mentors, as well as individuals representing different stakeholders and will be involved in the project development and identification of opportunities to further increase the impact of this project. The advisory board will discuss survey results and workshop objectives. Measurable outcomes and impacts of both the research and extension component of this project are discussed in detail in the Management Plan. To evaluate the progress of the research, extension and personal objectives listed above, this plan has been developed and progress toward meeting these objectives will be assessed biannually by my PhD committee and annually by the advisory panel (discussed in the Management Plan).