2023 FDA Science Forum
In-depth analysis of seafood resistome using shotgun metagenomics
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Contributing OfficeCenter for Veterinary Medicine
Abstract
Background:
Comprehensive profiling of antibiotic resistance genes in the farm to fork food supply chain is a goal of integrated surveillance programs. The distribution and relative abundances of antimicrobial resistance genes (ARGs) in seafood microbiomes are not well understood. High-throughput next generation sequencing technologies offer new approaches for antimicrobial resistance monitoring. In this study, we employed a shotgun metagenomics approach to catalogue and quantify resistance genes present in different seafood samples collected by the National Antimicrobial Resistance Monitoring System.
Methods:
A total of 122 seafood samples (41 salmon, 35 shrimp and 46 tilapia) were included in the study. Community DNA was extracted and sequenced on a HiSeq2500 sequencer using 2x125 bp paired-end sequencing. The presence and abundance of ARGs in the metagenomic dataset were determined using the Short, Better Representative Extract Dataset (ShortBRED) unique peptide markers generated from the AMRFinderPlus protein database. We used LDA Effect Size (LEfSe) to determine the resistance genes most likely to explain the difference between sources.
Results:
We identified 91 resistance genes representing 15 antimicrobial resistance classes including β-Lactam, aminoglycosides, tetracycline, quinolone, macrolide, and phenicol. We identified more than 31 β-Lactam resistance genes including blaOXA, blaIMP, blaCMY and blaFOX genes in our study. In addition, we detected fluoroquinolone resistance genes namely: qnrA, qnrB, qnrD, qnrS, qnrVC and oqxB genes. The distribution and relative abundance of ARGs observed varied by sample type. We found that salmon samples contained 73 ARGs, tilapia 74 ARGs and shrimp samples 60 ARGs. The three most common antimicrobial resistance genes observed in salmon microbiomes were aac(3)-VIIa (70.7%), blaLRA-1 (53.7%), emhC (46.3%) and tet(L) (46.3%) while aac(3)-VIIa (68.6%) was the most common AR gene in shrimp followed by emhC (51.4%) and blaOXA-548 family (48.6%). Among tilapia samples, aac(3)-VIIa (58.7%) and blaOXA-548 family (58.7%) were the most common ARGs followed by tet(L) (56.5%).
Conclusions:
Our study provides valuable insights into the diversity and identity of resistance genes present in seafood samples. This work helps characterize the resistome of seafood microbiome beyond what can be determined by culture-based methods alone. This information will help shed light on the potential of metagenomics as an auxiliary method for monitoring resistance in the food supply.
