Enrichment dynamics of Listeria monocytogenes and the associated microbiome from naturally contaminated ice cream linked to a listeriosis outbreak

Botulinum Neurotoxin Detection Methods for Public Health Response and Surveillance

Botulism outbreak due to consumption of food contaminated with botulinum neurotoxins (BoNTs) is a public health emergency. The threat of bioterrorism through deliberate distribution in food sources and/or aerosolization of BoNTs raises global public health and security concerns due to the potential for high mortality and morbidity. Rapid and reliable detection methods are necessary to support clinical diagnosis and surveillance for identifying the source of contamination, performing epidemiological analysis of the outbreak, preventing and responding to botulism outbreaks. This review considers the applicability of various BoNT detection methods and examines their fitness-for-purpose in safeguarding the public health and security goals.

Culture-independent Profiling of the Fecal Microbiome to Identify Microbial Species Associated with a Diarrheal Outbreak in Immunocompromised Mice

Immunocompromised mice are used frequently in biomedical research, in part because they accommodate the engraftment and study of primary human cells within a mouse model; however, these animals are susceptible to opportunistic infections and require special husbandry considerations. In 2015, an outbreak marked by high morbidity but low mortality swept through a colony of immunocompromised mice; this outbreak rapidly affected 75% of the colony and ultimately required complete depopulation of the barrier suite. Conventional microbiologic and molecular diagnostics were unsuccessful in determining the cause; therefore, we explored culture-independent methods to broadly profile the microbial community in the feces of affected animals. This approach identified 4 bacterial taxa- Candidatus Arthromitus, Clostridium celatum, Clostridiales bacterium VE202-01, and Bifidobacterium pseudolongum strain PV8-2- that were significantly enriched in the affected mice. Based on these results, specific changes were made to the animal husbandry procedures for immunocompromised mice. This case report highlights the utility of culture-independent methods in laboratory animal diagnostics.

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.

Listeria monocytogenes in Foods

Listeria monocytogenes causes listeriosis, a rare foodborne disease with a mortality rate of 20%-30%. The elderly and immunocompromised are particularly susceptible to listeriosis. L. monocytogenes is ubiquitous in nature and can contaminate food-processing environments, posing a threat to the food chain. This is particularly important for ready-to-eat foods as there is no heat treatment or other antimicrobial step between production and consumption. Thus, occurrence and control of L. monocytogenes are important for industry and public health. Advances in whole-genome sequence technology are facilitating the investigation of disease outbreaks, linking sporadic cases to outbreaks, and linking outbreaks internationally. Novel control methods, such as bacteriophage and bacteriocins, can contribute to a reduction in the occurrence of L. monocytogenes in the food-processing environment, thereby reducing the risk of food contamination and contributing to a reduction in public health issues.

Quasimetagenomics-Based and Real-Time-Sequencing-Aided Detection and Subtyping of Salmonella enterica from Food Samples

Metagenomics analysis of food samples promises isolation-independent detection and subtyping of foodborne bacterial pathogens in a single workflow. The selective concentration of Salmonella genomic DNA by immunomagnetic separation (IMS) and multiple displacement amplification (MDA) shortened the time for culture enrichment of Salmonella-spiked raw chicken breast samples by over 12 h while permitting serotyping and high-fidelity single nucleotide polymorphism (SNP) typing of the pathogen using short shotgun sequencing reads. The herein-termed quasimetagenomics approach was evaluated on Salmonella-spiked lettuce and black peppercorn samples as well as retail chicken parts naturally contaminated with different serotypes of Salmonella Culture enrichment of between 8 and 24 h was required for detecting and subtyping naturally occurring Salmonella from unspiked chicken parts compared with 4- to 12-h culture enrichment when Salmonella-spiked food samples were analyzed, indicating the likely need for longer culture enrichment to revive low levels of stressed or injured Salmonella cells in food. A further acceleration of the workflow was achieved by real-time nanopore sequencing. After 1.5 h of analysis on a potable sequencer, sufficient data were generated from sequencing the IMS-MDA products of a cultured-enriched lettuce sample to enable serotyping and robust phylogenetic placement of the inoculated isolate.IMPORTANCE Both culture enrichment and next-generation sequencing remain time-consuming processes for food testing, whereas rapid methods for pathogen detection are widely available. Our study demonstrated a substantial acceleration of these processes by the use of immunomagnetic separation (IMS) with multiple displacement amplification (MDA) and real-time nanopore sequencing. In one example, the combined use of the two methods delivered a less than 24-h turnaround time from the collection of a Salmonella-contaminated lettuce sample to the phylogenetic identification of the pathogen. An improved efficiency such as this is important for further expanding the use of whole-genome and metagenomics sequencing in the microbial analysis of food. Our results suggest the potential of the quasimetagenomics approach in areas where rapid detection and subtyping of foodborne pathogens are important, such as for foodborne outbreak response and the precision tracking and monitoring of foodborne pathogens in production environments and supply chains.

High-resolution profiling of the gut microbiome reveals the extent of Clostridium difficile burden

Microbiome profiling through 16S rRNA gene sequence analysis has proven to be a useful research tool in the study of C. difficile infection (CDI); however, CDI microbiome studies typically report results at the genus level or higher, thus precluding identification of this pathogen relative to other members of the gut microbiota. Accurate identification of C. difficile relative to the overall gut microbiome may be useful in assessments of colonization in research studies or as a prognostic indicator for patients with CDI. To investigate the burden of C. difficile at the species level relative to the overall gut microbiome, we applied a high-resolution method for 16S rRNA sequence assignment to previously published gut microbiome studies of CDI and other patient populations. We identified C. difficile in 131 of 156 index cases of CDI (average abundance 1.78%), and 18 of 211 healthy controls (average abundance 0.008%). We further detected substantial levels of C. difficile in a subset of infants that persisted over the first two to 12 months of life. Correlation analysis of C. difficile burden compared to other detected species demonstrated consistent negative associations with C. scindens and multiple Blautia species. These analyses contribute insight into the relative burden of C. difficile in the gut microbiome for multiple patient populations, and indicate that high-resolution 16S rRNA gene sequence analysis may prove useful in the development and evaluation of new therapies for CDI.

High-resolution bacterial 16S rRNA gene profile meta-analysis and biofilm status reveal common colorectal cancer consortia

Colorectal cancer (CRC) remains the third most common cancer worldwide, with a growing incidence among young adults. Multiple studies have presented associations between the gut microbiome and CRC, suggesting a link with cancer risk. Although CRC microbiome studies continue to profile larger patient cohorts with increasingly economical and rapid DNA sequencing platforms, few common associations with CRC have been identified, in part due to limitations in taxonomic resolution and differences in analysis methodologies. Complementing these taxonomic studies is the newly recognized phenomenon that bacterial organization into biofilm structures in the mucus layer of the gut is a consistent feature of right-sided (proximal), but not left-sided (distal) colorectal cancer. In the present study, we performed 16S rRNA gene amplicon sequencing and biofilm quantification in a new cohort of patients from Malaysia, followed by a meta-analysis of eleven additional publicly available data sets on stool and tissue-based CRC microbiota using Resphera Insight, a high-resolution analytical tool for species-level characterization. Results from the Malaysian cohort and the expanded meta-analysis confirm that CRC tissues are enriched for invasive biofilms (particularly on right-sided tumors), a symbiont with capacity for tumorigenesis (Bacteroides fragilis), and oral pathogens including Fusobacterium nucleatum, Parvimonas micra, and Peptostreptococcus stomatis. Considered in aggregate, species from the Human Oral Microbiome Database are highly enriched in CRC. Although no detected microbial feature was universally present, their substantial overlap and combined prevalence supports a role for the gut microbiota in a significant percentage (>80%) of CRC cases.

Many studies have found a link between gut microbes and bowel cancer, the third most common cancer worldwide. The details of the association, however, have remained elusive. Researchers in the USA and Malaysia, led by Dr. Cynthia Sears at John Hopkins School of Medicine in Maryland, examined mucosal biofilm status by fluorescence microscopy and performed a meta-analysis of bacterial genetic associations in stool and colon tissues to clarify the connection. They found that bowel cancers were enriched in invasive bacterial biofilms as well as several specific gut and oral species, including one - Fusobacterium nucleatum - known to promote tumorigenesis in mouse models. Analyzing gut microbial populations might help assess bowel cancer risk. Further research is needed, however, to determine if these  bacteria directly contribute to disease causality.

High Throughput Sequencing for Detection of Foodborne Pathogens

High-throughput sequencing (HTS) is becoming the state-of-the-art technology for typing of microbial isolates, especially in clinical samples. Yet, its application is still in its infancy for monitoring and outbreak investigations of foods. Here we review the published literature, covering not only bacterial but also viral and Eukaryote food pathogens, to assess the status and potential of HTS implementation to inform stakeholders, improve food safety and reduce outbreak impacts. The developments in sequencing technology and bioinformatics have outpaced the capacity to analyze and interpret the sequence data. The influence of sample processing, nucleic acid extraction and purification, harmonized protocols for generation and interpretation of data, and properly annotated and curated reference databases including non-pathogenic "natural" strains are other major obstacles to the realization of the full potential of HTS in analytical food surveillance, epidemiological and outbreak investigations, and in complementing preventive approaches for the control and management of foodborne pathogens. Despite significant obstacles, the achieved progress in capacity and broadening of the application range over the last decade is impressive and unprecedented, as illustrated with the chosen examples from the literature. Large consortia, often with broad international participation, are making coordinated efforts to cope with many of the mentioned obstacles. Further rapid progress can therefore be prospected for the next decade.

A Review on the Applications of Next Generation Sequencing Technologies as Applied to Food-Related Microbiome Studies

The development of next generation sequencing (NGS) techniques has enabled researchers to study and understand the world of microorganisms from broader and deeper perspectives. The contemporary advances in DNA sequencing technologies have not only enabled finer characterization of bacterial genomes but also provided deeper taxonomic identification of complex microbiomes which in its genomic essence is the combined genetic material of the microorganisms inhabiting an environment, whether the environment be a particular body econiche (e.g., human intestinal contents) or a food manufacturing facility econiche (e.g., floor drain). To date, 16S rDNA sequencing, metagenomics and metatranscriptomics are the three basic sequencing strategies used in the taxonomic identification and characterization of food-related microbiomes. These sequencing strategies have used different NGS platforms for DNA and RNA sequence identification. Traditionally, 16S rDNA sequencing has played a key role in understanding the taxonomic composition of a food-related microbiome. Recently, metagenomic approaches have resulted in improved understanding of a microbiome by providing a species-level/strain-level characterization. Further, metatranscriptomic approaches have contributed to the functional characterization of the complex interactions between different microbial communities within a single microbiome. Many studies have highlighted the use of NGS techniques in investigating the microbiome of fermented foods. However, the utilization of NGS techniques in studying the microbiome of non-fermented foods are limited. This review provides a brief overview of the advances in DNA sequencing chemistries as the technology progressed from first, next and third generations and highlights how NGS provided a deeper understanding of food-related microbiomes with special focus on non-fermented foods.

High-resolution microbiome profiling uncovers Fusobacterium nucleatum, Lactobacillus gasseri/johnsonii, and Lactobacillus vaginalis associated to oral and oropharyngeal cancer in saliva from HPV positive and HPV negative patients treated with surgery and chemo-radiation

Microbiome studies show altered microbiota in head and neck squamous cell carcinoma (HNSCC), both in terms of taxonomic composition and metabolic capacity. These studies utilized a traditional bioinformatics methodology, which allows for accurate taxonomic assignment down to the genus level, but cannot accurately resolve species level membership. We applied Resphera Insight, a high-resolution methodology for 16S rRNA taxonomic assignment that is able to provide species-level context in its assignments of 16S rRNA next generation sequencing (NGS) data.

Resphera Insight applied to saliva samples from HNSCC patients and healthy controls led to the discovery that a subset of HNSCC saliva samples is significantly enriched with commensal species from the vaginal flora, including Lactobacillus gasseri/johnsonii (710x higher in saliva) and Lactobacillus vaginalis (52x higher in saliva). These species were not observed in normal saliva from Johns Hopkins patients, nor in 16S rRNA NGS saliva samples from the Human Microbiome Project (HMP). Interestingly, both species were only observed in saliva from Human Papilloma Virus (HPV) positive and HPV negative oropharyngeal cancer patients. We confirmed the representation of both species in HMP data obtained from mid-vagina (n=128) and vaginal introitus (n=121) samples.

Resphera Insight also led to the discovery that Fusobacterium nucleatum, an oral cavity flora commensal bacterium linked to colon cancer, is enriched (600x higher) in saliva from a subset of HNSCC patients with advanced tumors stages.

Together, these high-resolution analyses on 583 samples suggest a possible role for bacterial species in the therapeutic outcome of HPV positive and HPV negative HNSCC patients.

High-Resolution Microbiome Profiling for Detection and Tracking of Salmonella enterica

16S rRNA community profiling continues to be a useful tool to study microbiome composition and dynamics, in part due to advances in next generation sequencing technology that translate into reductions in cost. Reliable taxonomic identification to the species-level, however, remains difficult, especially for short-read sequencing platforms, due to incomplete coverage of the 16S rRNA gene. This is especially true for Salmonella enterica, which is often found as a low abundant member of the microbial community, and is often found in combination with several other closely related enteric species. Here, we report on the evaluation and application of Resphera Insight, an ultra-high resolution taxonomic assignment algorithm for 16S rRNA sequences to the species level. The analytical pipeline achieved 99.7% sensitivity to correctly identify S. enterica from WGS datasets extracted from the FDA GenomeTrakr Bioproject, while demonstrating 99.9% specificity over other Enterobacteriaceae members. From low-diversity and low-complexity samples, namely ice cream, the algorithm achieved 100% specificity and sensitivity for Salmonella detection. As demonstrated using cilantro and chili powder, for highly complex and diverse samples, especially those that contain closely related species, the detection threshold will likely have to be adjusted higher to account for misidentifications. We also demonstrate the utility of this approach to detect Salmonella in the clinical setting, in this case, bloodborne infections.

Metagenomics: The Next Culture-Independent Game Changer

A trend towards the abandonment of obtaining pure culture isolates in frontline laboratories is at a crossroads with the ability of public health agencies to perform their basic mandate of foodborne disease surveillance and response. The implementation of culture-independent diagnostic tests (CIDTs) including nucleic acid and antigen-based assays for acute gastroenteritis is leaving public health agencies without laboratory evidence to link clinical cases to each other and to food or environmental substances. This limits the efficacy of public health epidemiology and surveillance as well as outbreak detection and investigation. Foodborne outbreaks have the potential to remain undetected or have insufficient evidence to support source attribution and may inadvertently increase the incidence of foodborne diseases. Next-generation sequencing of pure culture isolates in clinical microbiology laboratories has the potential to revolutionize the fields of food safety and public health. Metagenomics and other 'omics' disciplines could provide the solution to a cultureless future in clinical microbiology, food safety and public health. Data mining of information obtained from metagenomics assays can be particularly useful for the identification of clinical causative agents or foodborne contamination, detection of AMR and/or virulence factors, in addition to providing high-resolution subtyping data. Thus, metagenomics assays may provide a universal test for clinical diagnostics, foodborne pathogen detection, subtyping and investigation. This information has the potential to reform the field of enteric disease diagnostics and surveillance and also infectious diseases as a whole. The aim of this review will be to present the current state of CIDTs in diagnostic and public health laboratories as they relate to foodborne illness and food safety. Moreover, we will also discuss the diagnostic and subtyping utility and concomitant bias limitations of metagenomics and comparable detection techniques in clinical microbiology, food and public health laboratories. Early advances in the discipline of metagenomics, however, have indicated noteworthy challenges. Through forthcoming improvements in sequencing technology and analytical pipelines among others, we anticipate that within the next decade, detection and characterization of pathogens via metagenomics-based workflows will be implemented in routine usage in diagnostic and public health laboratories.

Whole genome sequencing analyses of Listeria monocytogenes that persisted in a milkshake machine for a year and caused illnesses in Washington State

Background

In 2015, in addition to a United States multistate outbreak linked to contaminated ice cream, another outbreak linked to ice cream was reported in the Pacific Northwest of the United States. It was a hospital-acquired outbreak linked to milkshakes, made from contaminated ice cream mixes and milkshake maker, served to patients. Here we performed multiple analyses on isolates associated with this outbreak: pulsed-field gel electrophoresis (PFGE), whole genome single nucleotide polymorphism (SNP) analysis, species-specific core genome multilocus sequence typing (cgMLST), lineage-specific cgMLST and whole genome-specific MLST (wgsMLST)/outbreak-specific cgMLST. We also analyzed the prophages and virulence genes.

Results

The outbreak isolates belonged to sequence type 1038, clonal complex 101, genetic lineage II. There were no pre-mature stop codons in inlA. Isolates contained Listeria Pathogenicity Island 1 and multiple internalins. PFGE and multiple whole genome sequencing (WGS) analyses all clustered together food, environmental and clinical isolates when compared to outgroup from the same clonal complex, which supported the finding that L. monocytogenes likely persisted in the soft serve ice cream/milkshake maker from November 2014 to November 2015 and caused 3 illnesses, and that the outbreak strain was transmitted between two ice cream production facilities. The whole genome SNP analysis, one of the two species-specific cgMLST, the lineage II-specific cgMLST and the wgsMLST/outbreak-specific cgMLST showed that L. monocytogenes cells persistent in the milkshake maker for a year formed a unique clade inside the outbreak cluster. This clustering was consistent with the cleaning practice after the outbreak was initially recognized in late 2014 and early 2015. Putative prophages were conserved among prophage-containing isolates. The loss of a putative prophage in two isolates resulted in the loss of the AscI restriction site in the prophage, which contributed to their AscI-PFGE banding pattern differences from other isolates.

Conclusions

The high resolution of WGS analyses allowed the differentiation of epidemiologically unrelated isolates, as well as the elucidation of the microevolution and persistence of isolates within the scope of one outbreak. We applied a wgsMLST scheme which is essentially the outbreak-specific cgMLST. This scheme can be combined with lineage-specific cgMLST and species-specific cgMLST to maximize the resolution of WGS.

SYN-004 (ribaxamase), an oral beta-lactamase, mitigates antibiotic-mediated dysbiosis in a porcine gut microbiome model

AIM

To evaluate an antibiotic inactivation strategy to protect the gut microbiome from antibiotic-mediated damage.

METHODS AND RESULTS

SYN-004 (ribaxamase) is an orally delivered beta-lactamase intended to degrade penicillins and cephalosporins within the gastrointestinal tract to protect the microbiome. Pigs (20 kg, n = 10) were treated with ceftriaxone (CRO) (IV, 50 mg kg^-1 , SID) for 7 days and a cohort (n = 5) received ribaxamase (PO, 75 mg, QID) for 9 days beginning the day before antibiotic administration. Ceftriaxone serum levels were not statistically different in the antibiotic-alone and antibiotic + ribaxamase groups, indicating ribaxamase did not alter systemic antibiotic levels. Whole-genome metagenomic analyses of pig faecal DNA revealed that CRO caused significant changes to the gut microbiome and an increased frequency of antibiotic resistance genes. With ribaxamase, the gut microbiomes were not significantly different from pretreatment and antibiotic resistance gene frequency was not increased.

CONCLUSION

Ribaxamase mitigated CRO-mediated gut microbiome dysbiosis and attenuated propagation of the antibiotic resistance genes in pigs.

SIGNIFICANCE AND IMPACT OF THE STUDY

Damage of the microbiome can lead to overgrowth of pathogenic organisms and antibiotic exposure can promote selection for antibiotic-resistant micro-organisms. Ribaxamase has the potential to become the first therapy designed to protect the gut microbiome from antibiotic-mediated dysbiosis and reduce emergence of antibiotic resistance.