Profiling and source tracking of the microbial populations and resistome present in fish products

Abstract

Microorganisms in processing environments significantly impact the quality and safety of food products and can serve as potential reservoirs for antibiotic-resistant genes, contributing to public health concerns about antimicrobial resistance (AMR). Fish processing plants represent an understudied environment for microbiome mapping. This study investigated the microbial composition, prevalence of Listeria spp., and resistome structures in three catfish processing facilities in the southeastern United States. The 16S rRNA gene sequencing revealed that the observed richness and Shannon diversity index increased significantly from fish to fillet. Beta diversity analysis showed distinct clustering of microbial communities between fish, environment, and fillet samples. Fast expectation-maximization microbial source tracking (FEAST) algorithm demonstrated that the microbiota presents in the processing environment contributed 48.2 %, 62.4 %, and 53.7 % to the microbiota present on fillet in Facility 1 (F1), F2, and F3, respectively. Food contact surfaces made larger contributions compared to the non-food contact surfaces. The linear discriminant analysis of effect size (LEfSe) identified specific microbial genera (e.g., Plesiomohas, Brochothrix, Chryseobacterium and Cetobacterium) that significantly varied between Listeria spp. positive and negative samples in all three processing plants. The metagenomic sequencing results identified 212 antimicrobial resistance genes (ARGs) belonging to 72 groups from the raw fish and fish fillet samples collected from three processing plants. Although there was a significant decrease in the overall diversity of ARGs from fish to fillet samples, the total abundance of ARGs did not change significantly (P > 0.05). ARGs associated with resistance to macrolide-lincosamide-streptogramin (MLS), cationic antimicrobial peptides, aminoglycosides, and beta-lactams were found to be enriched in the fillet samples when compared to fish samples. Results of this study highlight the profound impact of processing environment on shaping the microbial populations present on the final fish product and the need for additional strategies to mitigate AMR in fish products.

Keywords: 16S rRNA; Antimicrobial resistance; Catfish; Listeria spp.; Metagenomic sequencing; Processing plant.