Abstract
BackgroundMetagenomics is gaining attention as a powerful tool for identifying how agricultural management practices influence human and animal health, especially in terms of potential to contribute to the spread of antibiotic resistance. However, the ability to compare the distribution and prevalence of antibiotic resistance genes (ARGs) across multiple studies and environments is currently impossible without a complete re-analysis of published datasets. This challenge must be addressed for metagenomics to realize its potential for helping guide effective policy and practice measures relevant to agricultural ecosystems, for example, identifying critical control points for mitigating the spread of antibiotic resistance.ResultsHere we introduce AgroSeek, a centralized web-based system that provides computational tools for analysis and comparison of metagenomic data sets tailored specifically to researchers and other users in the agricultural sector interested in tracking and mitigating the spread of ARGs. AgroSeek draws from rich, user-provided metagenomic data and metadata to facilitate analysis, comparison, and prediction in a user-friendly fashion. Further, AgroSeek draws from publicly-contributed data sets to provide a point of comparison and context for data analysis. To incorporate metadata into our analysis and comparison procedures, we provide flexible metadata templates, including user-customized metadata attributes to facilitate data sharing, while maintaining the metadata in a comparable fashion for the broader user community and to support large-scale comparative and predictive analysis.ConclusionAgroSeek provides an easy-to-use tool for environmental metagenomic analysis and comparison, based on both gene annotations and associated metadata, with this initial demonstration focusing on control of antibiotic resistance in agricultural ecosystems. Agroseek creates a space for metagenomic data sharing and collaboration to assist policy makers, stakeholders, and the public in decision-making. AgroSeek is publicly-available at https://agroseek.cs.vt.edu/.
Highlights
Metagenomics is gaining attention as a powerful tool for identifying how agricultural management practices influence human and animal health, especially in terms of potential to contribute to the spread of antibiotic resistance
AgroSeek presents many advantages as a centralized platform tailored to the study of antibiotic resistance in agricultural environments, with a corresponding mechanism to gather relevant metadata in a user-friendly and comprehensive fashion. Gathering such metadata is crucial to the ability to share data across the wider research community, allowing researchers to obtain a general sense of the ranges and distributions of various metagenomic measurements of interest for a given sample or environment type
Analysis tools We have demonstrated the functionality of all three metagenomic data analysis tools currently incorporated in AgroSeek using both real environmental sequencing data and synthetic data randomly generated by a Python script
Summary
Analysis tools We have demonstrated the functionality of all three metagenomic data analysis tools currently incorporated in AgroSeek using both real environmental sequencing data and synthetic data randomly generated by a Python script. These test runs demonstrate that AgroSeek is capable of handling arbitrary metadata attributes, performing analysis on selected data tables, and retrieving analysis results whenever the user desires to revisit them. Handled on the platform Some need to be handled None side on user side in the agriculture sector focused on antibiotic resistance, it is anticipated that additional data analysis tools will be incorporated into future versions, along with means for users to tap into a growing database of publicly-available user-provided metadata to expand the capacity of research questions and comparisons that can be made. The default metadata attributes and pipeline are fine-tuned with respect to the topic and audience of interest, namely antibiotic resistance in agricultural ecosystems, to conveniently obtain relevant analysis with the first pass
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