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

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.

Impact of DNA extraction and sampling methods on bacterial communities monitored by 16S rDNA metabarcoding in cold-smoked salmon and processing plant surfaces

Amplicon sequencing approaches have been widely used in food bacterial ecology. However, choices regarding the methodology can bias results. In this study, bacterial communities associated with cold-smoked salmon products and their processing plant surfaces were monitored via sequencing of the V3-V4 region of the 16S rRNA gene. The impact of DNA extraction protocols, sampling methods (swabbing or sponging) and surface materials on bacterial communities were investigated. α and β diversity analyses revealed that DNA extraction methods mainly influence the observed cold-smoked salmon microbiota composition. Moreover, different DNA extraction methods revealed significant differences in observed community richness and evenness. β-Proteobacteria: Photobacterium, Serratia and Firmicutes: Brochothrix, Carnobacterium and Staphylococcus were identified as the dominant genera. Surface microbiota richness, diversity and composition were mainly affected by cleaning and disinfection procedures but not by DNA extraction methods. Surface community richness and evenness appeared higher when sampled by sponging compared to swabbing. β-diversity analyses highlighted that surface topology, cleaning and disinfection and sampling devices seemed to affect the bacterial community composition. The dominant surface bacteria identified were mainly Flavobacteriaceae, β-Proteobacteria and γ-Proteobacteria described as fish spoilers such as Acinetobacter, Pseudomonas and Shewanella. DNA extraction and sampling methods can have an impact on sequencing results and the ecological analysis of bacterial community structures. This study confirmed the importance of methodology standardization and the need for analytical validation before 16S rDNA metabarcoding surveys.

Presence of viral haemorrhagic septicaemia virus (VHSV) in the environment of virus-contaminated fish farms and processing plants

After the first outbreak of viral haemorrhagic septicaemia virus (VHSV) in Finnish brackish water rainbow trout Oncorhynchus mykiss farms, infection spread rapidly between the farms. The infrastructure of fish farming did not take into account spreading of infectious fish diseases. To show the presence of VHSV in the environment, we tested seawater, sediment and wild blue mussels Mytilus edulis from VHSV-infected fish farms, and liquid waste from a processing plant that handled infected rainbow trout. Additionally, blue mussels were bath-challenged with VHSV (exposed to cultivated virus or naturally infected rainbow trout). To detect VHSV, virus isolation in cell culture and real-time reverse transcriptase polymerase chain reaction (qRT-PCR) were used. The virus or viral RNA was detected in sea water and in liquid waste from processing plants during wintertime when water temperature is close to 0°C and sunlight is sparse. VHSV did not appear to replicate in blue mussels in our study. Therefore, blue mussels were not considered relevant carriers of VHSV. However, traces of viral RNA were detected up to 29 d post challenge in mussels. Contact with water from processing plants handling VHSV-infected fish populations increases the risk of the disease spreading to susceptible fish populations, especially during cold and dark times of the year.