The overall project goal is to provide the agricultural community with an integrated, validated and highly discriminative method for tracking and source attribution of antimicrobial resistance in environmental systems, leveraging nucleotide-level variation within resistome data.The following objectives support this goal: 1) systematic review and evaluationof computational algorithms and statistical methods for generating nucleotide-level resistome fingerprints from metagenomic data; 2) evaluation of the applied benefit of resistome fingerprints utilizing both simulated and public metagenomic data from distantly and closely related samples; 3) validation of the high discriminative capacity of resistome fingerprints using experimentally generated data; and 4) sustainment of the method via an integrated outreach campaign.
Resistome Fingerprinting: Development of a highly discriminative method for tracking and source attribution of antimicrobial resistance in environmental systems
Objective
Investigators
Noyes, Noelle
Institution
University of Minnesota
Start date
2019
End date
2022
Funding Source
Project number
MINV62-058
Accession number
1018489