Quasi-metagenomic Analysis of Salmonella from Food and Environmental Samples

Approaching toxigenic Clostridia from a One Health perspective

Spore-forming pathogens have a unique capacity to thrive in diverse environments, and with temporal persistence afforded through their ability to sporulate. Their prevalence in diverse ecosystems requires a One Health approach to identify critical reservoirs and outbreak-associated transmission chains, given their capacity to freely move across soils, waterways, foodstuffs and as commensals or infecting pathogens in human and animal populations. Among anaerobic spore-formers, genomic resources for pathogens including C. botulinum, C. difficile, and C. perfringens enable our capacity to identify common and unique factors that support their persistence in diverse reservoirs and capacity to cause disease. Publicly available genomic resources for spore-forming pathogens at NCBI's Pathogen Detection program aid outbreak investigations and longitudinal monitoring in national and international programs in public health and food safety, as well as for local healthcare systems. These tools also enable research to derive new knowledge regarding disease pathogenesis, and to inform strategies in disease prevention and treatment. As global community resources, the continued sharing of strain genomic data and phenotypes further enhances international resources and means to develop impactful applications. We present examples showing use of these resources in surveillance, including capacity to assess linkages among clinical, environmental, and foodborne reservoirs and to further research investigations into factors promoting their persistence and virulence in different settings.

Approaching pathogenic Clostridia from a One Health perspective

Spore-forming pathogens have a unique capacity to thrive in diverse environments, and with temporal persistence afforded through their ability to sporulate. These behaviors require a One Health approach to identify critical reservoirs and outbreak-associated transmission chains, given their capacity to freely move across soils, waterways, foodstuffs, and as commensals or infecting pathogens in human and veterinary populations. Among anaerobic spore-formers, genomic resources for pathogens including C. botulinum, C. difficile, and C. perfringens enable our capacity to identify common and unique factors that support their persistence in diverse reservoirs and capacity to cause disease. Publicly available genomic resources for spore-forming pathogens at NCBI's Pathogen Detection program aid outbreak investigations and longitudinal monitoring in national and international programs in public health and food safety, as well as for local healthcare systems. These tools also enable research to derive new knowledge regarding disease pathogenesis, and to inform strategies in disease prevention and treatment. As global community resources, the continued sharing of strain genomic data and phenotypes further enhances international resources and means to develop impactful applications. We present examples showing use of these resources in surveillance, including capacity to assess linkages among clinical, environmental, and foodborne reservoirs and to further research investigations into factors promoting their persistence and virulence in different settings.

Application of quasimetagenomics methods to define microbial diversity and subtype Listeria monocytogenes in dairy and seafood production facilities

IMPORTANCE

In developed countries, the human diet is predominated by food commodities, which have been manufactured, processed, and stored in a food production facility. Little is known about the application of metagenomic sequencing approaches for detecting foodborne pathogens, such as L. monocytogenes, and characterizing microbial diversity in food production ecosystems. In this work, we investigated the utility of 16S rRNA amplicon and quasimetagenomic sequencing for the taxonomic and phylogenetic classification of Listeria culture enrichments of environmental swabs collected from dairy and seafood production facilities. We demonstrated that single-nucleotide polymorphism (SNP) analyses of L. monocytogenes metagenome-assembled genomes (MAGs) from quasimetagenomic data sets can achieve similar resolution as culture isolate whole-genome sequencing. To further understand the impact of genome coverage on MAG SNP cluster resolution, an in silico downsampling approach was employed to reduce the percentage of target pathogen sequence reads, providing an initial estimate of required MAG coverage for subtyping resolution of L. monocytogenes.

Development of novel parameters for pathogen identification in clinical metagenomic next-generation sequencing

Introduction: Metagenomic next-generation sequencing (mNGS) has emerged as a powerful tool for rapid pathogen identification in clinical practice. However, the parameters used to interpret mNGS data, such as read count, genus rank, and coverage, lack explicit performance evaluation. In this study, the developed indicators as well as novel parameters were assessed for their performance in bacterium detection. Methods: We developed several relevant parameters, including 10M normalized reads, double-discard reads, Genus Rank Ratio, King Genus Rank Ratio, Genus Rank Ratio*Genus Rank, and King Genus Rank Ratio*Genus Rank. These parameters, together with frequently used read indicators including raw reads, reads per million mapped reads (RPM), transcript per kilobase per million mapped reads (TPM), Genus Rank, and coverage were analyzed for their diagnostic efficiency in bronchoalveolar lavage fluid (BALF), a common source for detecting eight bacterium pathogens: Acinetobacter baumannii, Klebsiella pneumoniae, Streptococcus pneumoniae, Staphylococcus aureus, Hemophilus influenzae, Stenotrophomonas maltophilia, Pseudomonas aeruginosa, and Aspergillus fumigatus. Results: The results demonstrated that these indicators exhibited good diagnostic efficacy for the eight pathogens. The AUC values of all indicators were almost greater than 0.9, and the corresponding sensitivity and specificity values were almost greater than 0.8, excepted coverage. The negative predictive value of all indicators was greater than 0.9. The results showed that the use of double-discarded reads, Genus Rank Ratio*Genus Rank, and King Genus Rank Ratio*Genus Rank exhibited better diagnostic efficiency than that of raw reads, RPM, TPM, and in Genus Rank. These parameters can serve as a reference for interpreting mNGS data of BALF. Moreover, precision filters integrating our novel parameters were built to detect the eight bacterium pathogens in BALF samples through machine learning. Summary: In this study, we developed a set of novel parameters for pathogen identification in clinical mNGS based on reads and ranking. These parameters were found to be more effective in diagnosing pathogens than traditional approaches. The findings provide valuable insights for improving the interpretation of mNGS reports in clinical settings, specifically in BALF analysis.

Metagenomics Approaches for Improving Food Safety: A Review

ABSTRACT

Advancements in next-generation sequencing technology have dramatically reduced the cost and increased the ease of microbial whole genome sequencing. This approach is revolutionizing the identification and analysis of foodborne microbial pathogens, facilitating expedited detection and mitigation of foodborne outbreaks, improving public health outcomes, and limiting costly recalls. However, next-generation sequencing is still anchored in the traditional laboratory practice of the selection and culture of a single isolate. Metagenomic-based approaches, including metabarcoding and shotgun and long-read metagenomics, are part of the next disruptive revolution in food safety diagnostics and offer the potential to directly identify entire microbial communities in a single food, ingredient, or environmental sample. In this review, metagenomic-based approaches are introduced and placed within the context of conventional detection and diagnostic techniques, and essential considerations for undertaking metagenomic assays and data analysis are described. Recent applications of the use of metagenomics for food safety are discussed alongside current limitations and knowledge gaps and new opportunities arising from the use of this technology.

HIGHLIGHTS

Salmonella Genomics in Public Health and Food Safety

The species Salmonella enterica comprises over 2,600 serovars, many of which are known to be intracellular pathogens of mammals, birds, and reptiles. It is now apparent that Salmonella is a highly adapted environmental microbe and can readily persist in a number of environmental niches, including water, soil, and various plant (including produce) species. Much of what is known about the evolution and diversity of nontyphoidal Salmonella serovars (NTS) in the environment is the result of the rise of the genomics era in enteric microbiology. There are over 340,000 Salmonella genomes available in public databases. This extraordinary breadth of genomic diversity now available for the species, coupled with widespread availability and affordability of whole-genome sequencing (WGS) instrumentation, has transformed the way in which we detect, differentiate, and characterize Salmonella enterica strains in a timely way. Not only have WGS data afforded a detailed and global examination of the molecular epidemiological movement of Salmonella from diverse environmental reservoirs into human and animal hosts, but they have also allowed considerable consolidation of the diagnostic effort required to test for various phenotypes important to the characterization of Salmonella. For example, drug resistance, serovar, virulence determinants, and other genome-based attributes can all be discerned using a genome sequence. Finally, genomic analysis, in conjunction with functional and phenotypic approaches, is beginning to provide new insights into the precise adaptive changes that permit persistence of NTS in so many diverse and challenging environmental niches.