Dairy Products and Dairy-Processing Environments as a Reservoir of Antibiotic Resistance and Quorum-Quenching Determinants as Revealed through Functional Metagenomics.

Here, the role of the dairy-processing chain as a reservoir of antimicrobial resistance (AR) determinants and a source of novel biocontrol quorum-sensing inhibitors is assessed through a functional metagenomics approach. A metagenomic library comprising ∼22,000 recombinant clones was built from DNA isolated from raw milk, raw milk cheeses, and cheese-processing environment swab samples. The high-throughput sequencing of 9,216 recombinant clones showed that lactic acid bacteria (LAB) dominated the microbial communities of raw milk cheese, while Gram-negative microorganisms of animal or soil origin dominated the microbiota of raw milk and cheese-processing environments. Although functional screening of the metagenomic library did not recover potential quorum-sensing inhibitors, in silico analysis using an in-house database built specifically for this study identified homologues to several genes encoding proteins with predicted quorum-quenching activity, among which, the QsdH hydrolase was the most abundant. In silico screening of the library identified LAB, and especially Lactococcus lactis, as a relevant reservoir of AR determinants in cheese. Functional screening of the library allowed the isolation of 13 recombinant clones showing an increased resistance toward ampicillin, which in all cases was accompanied by a reduced susceptibility to a wide range of ß-lactam antibiotics. This study shows that the dairy-processing environment is a rich reservoir of AR determinants, which vary by sample source, and suggests that combining next-generation sequencing with functional metagenomics can be of use in overcoming the limitations of both approaches.IMPORTANCE The study shows the potential of functional metagenomics analyses to uncover the diversity of functions in microbial communities prevailing in dairy products and their processing environments, evidencing that lactic acid bacteria (LAB) dominate the cheese microbiota, whereas Gram-negative microorganisms of animal or soil origin dominate the microbiota of milk and cheese-processing environments. The functional and in silico screening of the library allowed the identification of LAB, and especially Lactococcus lactis, as a relevant reservoir of antimicrobial resistance (AR) determinants in cheese. Quorum-quenching (QQ) determinants were not recovered through the execution of wet-lab function-based screenings but were detected through in silico sequencing-based analyses.

Correction: Oniciuc, E. A.; et al. The Present and Future of Whole Genome Sequencing (WGS) and Whole Metagenome Sequencing (WMS) for Surveillance of Antimicrobial Resistant Microorganisms and Antimicrobial Resistance Genes across the Food Chain. Genes 2018, 9, 268.

The authors wish to make the following changes to their paper [1]. Due to an undetected mistake in the references management, certain errors appeared in the reference list and a reference was duplicated in Table 1[...].

The Present and Future of Whole Genome Sequencing (WGS) and Whole Metagenome Sequencing (WMS) for Surveillance of Antimicrobial Resistant Microorganisms and Antimicrobial Resistance Genes across the Food Chain.

Antimicrobial resistance (AMR) surveillance is a critical step within risk assessment schemes, as it is the basis for informing global strategies, monitoring the effectiveness of public health interventions, and detecting new trends and emerging threats linked to food. Surveillance of AMR is currently based on the isolation of indicator microorganisms and the phenotypic characterization of clinical, environmental and food strains isolated. However, this approach provides very limited information on the mechanisms driving AMR or on the presence or spread of AMR genes throughout the food chain. Whole-genome sequencing (WGS) of bacterial pathogens has shown potential for epidemiological surveillance, outbreak detection, and infection control. In addition, whole metagenome sequencing (WMS) allows for the culture-independent analysis of complex microbial communities, providing useful information on AMR genes occurrence. Both technologies can assist the tracking of AMR genes and mobile genetic elements, providing the necessary information for the implementation of quantitative risk assessments and allowing for the identification of hotspots and routes of transmission of AMR across the food chain. This review article summarizes the information currently available on the use of WGS and WMS for surveillance of AMR in foodborne pathogenic bacteria and food-related samples and discusses future needs that will have to be considered for the routine implementation of these next-generation sequencing methodologies with this aim. In particular, methodological constraints that impede the use at a global scale of these high-throughput sequencing (HTS) technologies are identified, and the standardization of methods and protocols is suggested as a measure to upgrade HTS-based AMR surveillance schemes.