Surveillance of Listeria monocytogenes: Early Detection, Population Dynamics, and Quasimetagenomic Sequencing during Selective Enrichment

A mica filter enables bacterial enrichment from large volumes of natural water for sensitive monitoring of pathogens by nanopore sequencing

Nanopore sequencing is extremely promising for the high-throughput detection of pathogenic bacteria in natural water; these bacteria may be transmitted to humans and cause waterborne infectious diseases. However, the concentration of pathogenic bacteria in natural water is too low to be detected directly by nanopore sequencing. Herein, we developed a mica filter to enrich over 85% of bacteria from > 10 L of natural water in 100 min, which led to a 102-fold improvement in the assay limits of the MinION sequencer for assessing pathogenic bacteria. Correspondingly, the sequencing time of S. Typhi detection at a concentration as low as 105 CFU/L was reduced from traditional 48 h to 3 h. The bacterial adsorption followed pseudo-first-order kinetics and the successful adsorption of bacteria to the mica filter was confirmed by scanning electron microscopy and Fourier infrared spectroscopy et al. The mica filter remained applicable to a range of water samples whose quality parameters were within the EPA standard limits for freshwater water. The mica filter is thus an effective tool for the sensitive and rapid monitoring of pathogenic bacteria by nanopore sequencing, which can provide timely alerts for waterborne transmission events.

A metagenomics-based workflow for the detection and genomic characterization of GBS in raw freshwater fish

The unexpected foodborne outbreak in Singapore in 2015 has accentuated Group B Streptococcus (GBS, Streptococcus agalactiae) sequence type 283 as an emerging foodborne pathogen transmitted via the consumption of contaminated raw freshwater fish. Isolation-based workflows utilizing conventional microbiological and whole-genome sequencing methods are commonly used to support biosurveillance efforts critical for the control management of this emerging foodborne pathogen. However, these isolation-based workflows tend to have relatively long turnaround times that hamper a timely response for implementing risk mitigation. To address this gap, we have developed a metagenomics-based workflow for the simultaneous detection and genomic characterization of GBS in raw freshwater fish. Notably, our validation results showed that this metagenomics-based workflow could achieve comparable accuracy and potentially better detection limits while halving the turnaround time (from 2 weeks to 5 days) relative to an isolation-based workflow. The metagenomics-based workflow was also successfully adapted for use on a portable long-read nanopore sequencer, demonstrating its potential applicability for real-time point-of-need testing. Using GBS in freshwater fish as an example, this work represents a proof-of-concept study that supports the feasibility and validity of metagenomics as a rapid and accurate test methodology for the detection and genomic characterization of foodborne pathogens in complex food matrices.

IMPORTANCE

The need for a rapid and accurate food microbiological testing method is apparent for a timely and effective foodborne outbreak response. This is particularly relevant for emerging foodborne pathogens such as Group B Streptococcus (GBS) whose associated food safety risk might be undercharacterized. By using GBS in raw freshwater fish as a case example, this study describes the development of a metagenomics-based workflow for rapid food microbiological safety testing and surveillance. This study can inform as a working model for various foodborne pathogens in other complex food matrices, paving the way for future methodological development of metagenomics for food microbiological safety testing.

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.

Use of a taxon-specific reference database for accurate metagenomics-based pathogen detection of Listeria monocytogenes in turkey deli meat and spinach

BACKGROUND

The reliability of culture-independent pathogen detection in foods using metagenomics is contingent on the quality and composition of the reference database. The inclusion of microbial sequences from a diverse representation of taxonomies in universal reference databases is recommended to maximize classification precision for pathogen detection. However, these sizable databases have high memory requirements that may be out of reach for some users. In this study, we aimed to assess the performance of a foodborne pathogen (FBP)-specific reference database (taxon-specific) relative to a universal reference database (taxon-agnostic). We tested our FBP-specific reference database's performance for detecting Listeria monocytogenes in two complex food matrices-ready-to-eat (RTE) turkey deli meat and prepackaged spinach-using three popular read-based DNA-to-DNA metagenomic classifiers: Centrifuge, Kraken 2 and KrakenUniq.

RESULTS

In silico host sequence removal led to substantially fewer false positive (FP) classifications and higher classification precision in RTE turkey deli meat datasets using the FBP-specific reference database. No considerable improvement in classification precision was observed following host filtering for prepackaged spinach datasets and was likely a consequence of a higher microbe-to-host sequence ratio. All datasets classified with Centrifuge using the FBP-specific reference database had the lowest classification precision compared to Kraken 2 or KrakenUniq. When a confidence-scoring threshold was applied, a nearly equivalent precision to the universal reference database was achieved for Kraken 2 and KrakenUniq. Recall was high for both reference databases across all datasets and classifiers. Substantially fewer computational resources were required for metagenomics-based detection of L. monocytogenes using the FBP-specific reference database, especially when combined with Kraken 2.

CONCLUSIONS

A universal (taxon-agnostic) reference database is not essential for accurate and reliable metagenomics-based pathogen detection of L. monocytogenes in complex food matrices. Equivalent classification performance can be achieved using a taxon-specific reference database when the appropriate quality control measures, classification software, and analysis parameters are applied. This approach is less computationally demanding and more attainable for the broader scientific and food safety communities.

Application of MinION sequencing as a tool for the rapid detection and characterization of Listeria monocytogenes in smoked salmon

Microbial pathogens may be present in different types of foods, and hence the development of novel methods to assure consumers' safeness is of great interest. Molecular methods are known to provide sensitive and rapid results; however, they are typically targeted approaches. In recent years, the advent of non-targeted approaches based on next-generation sequencing (NGS) has emerged as a rational way to proceed. This technology allows for the detection of several pathogens simultaneously. Furthermore, with the same set of data, it is possible to characterize the microorganisms in terms of serotype, virulence, and/ or resistance genes, among other molecular features. In the current study, a novel method for the detection of Listeria monocytogenes based on the "quasimetagenomics" approach was developed. Different enrichment media and immunomagnetic separation (IMS) strategies were compared to determine the best approach in terms of L. monocytogenes sequences generated from smoked salmon samples. Finally, the data generated were analyzed with a user-friendly workflow that simultaneously provided the species identification, serotype, and antimicrobial resistance genes. The new method was thoroughly evaluated against a culture-based approach, using smoked salmon inoculated with L. monocytogenes as the matrix of choice. The sequencing method reached a very low limit of detection (LOD50, 1.2 CFU/ 25 g) along with high diagnostic sensitivity and specificity (100%), and a perfect correlation with the culture-based method (Cohen's k = 1.00). Overall, the proposed method overcomes all the major limitations reported for the implementation of NGS as a routine food testing technology and paves the way for future developments taking its advantage into consideration.

Research progress on detection techniques for point-of-care testing of foodborne pathogens

The global burden of foodborne disease is enormous and foodborne pathogens are the leading cause of human illnesses. The detection of foodborne pathogenic bacteria has become a research hotspot in recent years. Rapid detection methods based on immunoassay, molecular biology, microfluidic chip, metabolism, biosensor, and mass spectrometry have developed rapidly and become the main methods for the detection of foodborne pathogens. This study reviewed a variety of rapid detection methods in recent years. The research advances are introduced based on the above technical methods for the rapid detection of foodborne pathogenic bacteria. The study also discusses the limitations of existing methods and their advantages and future development direction, to form an overall understanding of the detection methods, and for point-of-care testing (POCT) applications to accurately and rapidly diagnose and control diseases.

Prevalence and Clonal Diversity of over 1,200 Listeria monocytogenes Isolates Collected from Public Access Waters near Produce Production Areas on the Central California Coast during 2011 to 2016

A 5-year survey of public access surface waters in an agricultural region of the Central California Coast was done to assess the prevalence of the foodborne pathogen Listeria monocytogenes. In nature, L. monocytogenes lives as a saprophyte in soil and water, which are reservoirs for contamination of preharvest produce. Moore swabs were deployed biweekly in lakes, ponds, streams, and rivers during 2011 to 2016. L. monocytogenes was recovered in 1,224 of 2,922 samples, resulting in 41.9% prevalence. Multiple subtypes were isolated from 97 samples, resulting in 1,323 L. monocytogenes isolates. Prevalence was higher in winter and spring and after rain events in some waterways. Over 84% of the isolates were serotype 4b. Whole-genome sequencing was done on 1,248 isolates, and in silico multilocus sequence typing revealed 74 different sequence types (STs) and 39 clonal complexes (CCs). The clones most isolated, CC639, CC183, and CC1, made up 27%, 19%, and 13%, respectively, of the sequenced isolates. Other types were CC663, CC6, CC842, CC4, CC2, CC5, and CC217. All sequenced isolates contained intact copies of core L. monocytogenes virulence genes, and pathogenicity islands LIPI-3 and LIPI-4 were identified in 73% and 63%, respectively, of the sequenced isolates. The virulence factor internalin A was predicted to be intact in all but four isolates, while genes important for sanitizer and heavy metal resistance were found in <5% of the isolates. These waters are not used for crop irrigation directly, but they are available to wildlife and can flood fields during heavy rains. IMPORTANCE Listeria monocytogenes serotype 4b and 1/2a strains are implicated in most listeriosis, and hypervirulent listeriosis stems from strains containing pathogenicity islands LIPI-3 and LIPI-4. The waters and sediments in the Central California Coast agricultural region contain widespread and diverse L. monocytogenes populations, and all the isolates contain intact virulence genes. Emerging clones CC183 and CC639 were the most abundant clones, and major clones CC1, CC4, and CC6 were well represented. CC183 was responsible for three produce-related outbreaks in the last 7 years. Most of the isolates in the survey differ from those of lesser virulence that are often isolated from foods and food processing plants because they contain genes encoding an intact virulence factor, internalin A, and most did not contain genes for sanitizer and heavy metal resistance. This isolate collection is important for understanding L. monocytogenes populations in agricultural and natural regions.

The Saprophytic Lifestyle of Listeria monocytogenes and Entry Into the Food-Processing Environment

Listeria monocytogenes is an environmentally adapted saprophyte that can change into a human and animal bacterial pathogen with zoonotic potential through several regulatory systems. In this review, the focus is on the occurrence of Listeria sensu stricto and sensu lato in different ecological niches, the detection methods, and their analytical limitations. It also highlights the occurrence of L. monocytogenes genotypes in the environment (soil, water, and wildlife), reflects on the molecular determinants of L. monocytogenes for the saprophytic lifestyle and the potential for antibiotic resistance. In particular, the strain-specific properties with which some genotypes circulate in wastewater, surface water, soil, wildlife, and agricultural environments are of particular interest for the continuously updating risk analysis.