Amplicon sequencing for the quantification of spoilage microbiota in complex foods including bacterial spores

Exploring the Feasibility of 16S rRNA Short Amplicon Sequencing-Based Microbiota Analysis for Microbiological Safety Assessment of Raw Oyster

16S rRNA short amplicon sequencing-based microbiota profiling has been thought of and suggested as a feasible method to assess food safety. However, even if a comprehensive microbial information can be obtained by microbiota profiling, it would not be necessarily sufficient for all circumstances. To prove this, the feasibility of the most widely used V3-V4 amplicon sequencing method for food safety assessment was examined here. We designed a pathogen (Vibrio parahaemolyticus) contamination and/or V. parahaemolyticus-specific phage treatment model of raw oysters under improper storage temperature and monitored their microbial structure changes. The samples stored at refrigerator temperature (negative control, NC) and those that were stored at room temperature without any treatment (no treatment, NT) were included as control groups. The profiling results revealed that no statistical difference exists between the NT group and the pathogen spiked- and/or phage treated-groups even when the bacterial composition was compared at the possible lowest-rank taxa, family/genus level. In the beta-diversity analysis, all the samples except the NC group formed one distinct cluster. Notably, the samples with pathogen and/or phage addition did not form each cluster even though the enumerated number of V. parahaemolyticus in those samples were extremely different. These discrepant results indicate that the feasibility of 16S rRNA short amplicon sequencing should not be overgeneralized in microbiological safety assessment of food samples, such as raw oyster.

Temporal variation of antibiotic resistome and pathogens in food waste during short-term storage

The massive food wastes pose a growing health concern for spreading of antibiotic resistance and pathogens due to food spoilage. However, little is known about these microbial hazards during collection, classification, and transportation before eventual treatment. Here, we profiled the temporal variations of antibiotic resistance genes (ARGs), pathogens, bacterial and fungal communities across four typical food wastes (vegetable, fish, meat, and rice) during storage at room temperature in summer (maximum 28-29 °C) of typical southeast city in China. A total of 171 ARGs and 32 mobile genetic elements were detected, and the absolute abundance of ARGs significantly increased by up to 126-fold with the storage time. Additionally, five bacterial pathogens containing virulence factor genes were detected, and Klebsiella pneumoniae was persistently detected throughout the storage time in all food types except rice. Moreover, fungal pathogens (e.g., Aspergillus, Penicillium, and Fusarium) were also frequently detected. Notably, animal food wastes were demonstrated to harbor higher abundance of ARGs and more types of pathogens, indicating a higher level of hazard. Mobile genetic elements and food types were demonstrated to mainly impact ARG profiles and pathogens, respectively. This work provides a comprehensive understanding of the microbial hazards associated with food waste recycling, and will contribute to optimize the food waste management to ensure biosecurity and benefit human health.

Model Selection Reveals the Butyrate-Producing Gut Bacterium Coprococcus eutactus as Predictor for Language Development in 3-Year-Old Rural Ugandan Children

Introduction

The metabolic activity of the gut microbiota plays a pivotal role in the gut-brain axis through the effects of bacterial metabolites on brain function and development. In this study we investigated the association of gut microbiota composition with language development of 3-year-old rural Ugandan children.

Methods

We studied the language ability in 139 children of 36 months in our controlled maternal education intervention trial to stimulate children’s growth and development. The dataset includes 1170 potential predictors, including anthropometric and cognitive parameters at 24 months, 542 composition parameters of the children’s gut microbiota at 24 months and 621 of these parameters at 36 months. We applied a novel computationally efficient version of the all-subsets regression methodology and identified predictors of language ability of 36-months-old children scored according to the Bayley Scales of Infant and Toddler Development (BSID-III).

Results

The best three-term model, selected from more than 266 million models, includes the predictors Coprococcus eutactus at 24 months of age, Bifidobacterium at 36 months of age, and language development at 24 months. The top 20 four-term models, selected from more than 77 billion models, consistently include C. eutactus abundance at 24 months, while 14 of these models include the other two predictors as well. Mann–Whitney U tests suggest that the abundance of gut bacteria in language non-impaired children (n = 78) differs from that in language impaired children (n = 61). While anaerobic butyrate-producers, including C. eutactus, Faecalibacterium prausnitzii, Holdemanella biformis, Roseburia hominis are less abundant, facultative anaerobic bacteria, including Granulicatella elegans, Escherichia/Shigella and Campylobacter coli, are more abundant in language impaired children. The overall predominance of oxygen tolerant species in the gut microbiota was slightly higher in the language impaired group than in the non-impaired group (P = 0.09).

Conclusion

Application of the all-subsets regression methodology to microbiota data established a correlation between the relative abundance of the anaerobic butyrate-producing gut bacterium C. eutactus and language development in Ugandan children. We propose that the gut redox potential and the overall bacterial butyrate-producing capacity in the gut are important factors for language development.

Next-generation sequencing as a screening tool for foodborne pathogens in fresh produce

Next generation sequencing (NGS) approaches are increasingly applied to tracing microbial contaminants entering the food chain due to NGS' untargeted nature and ability to investigate non-culturable (and/or difficult to culture) organisms while yielding genomic information about the microbiota. So far, a plethora of microbes has been shown to be associated with fresh produce, but few studies have utilised NGS to identify contamination with human pathogens. This study aims to establish the limit of detection (LoD) for Salmonella and phage MS2 (a Norovirus surrogate) contamination of fresh produce employing NGS approaches on the Illumina MiSeq: 16S amplicon-sequencing, and RNA-seq, using ScriptSeq (Illumina) and NEBNext (New England BioLabs) kits. ScriptSeq proved the most sensitive approach; delivering an LoD of 10⁴ CFU reaction^-1 (Colony Forming Units) for Salmonella and 10⁵ PFU reaction^-1 (Plaque Forming Units) for phage MS2. Use of the NEBNext kit resulted in detection of Salmonella at 10⁶ CFU reaction^-1 and phage MS2 at 10⁷ PFU reaction^-1. 16S amplicon-sequencing yielded a similar LoD of 10⁵ CFU reaction^-1 for Salmonella but could not detect MS2. The tested NGS methodologies, in combination with bioinformatics approaches applied, proved less sensitive than conventional microbial detection approaches.

The use of next generation sequencing for improving food safety: Translation into practice

Next Generation Sequencing (NGS) combined with powerful bioinformatic approaches are revolutionising food microbiology. Whole genome sequencing (WGS) of single isolates allows the most detailed comparison possible hitherto of individual strains. The two principle approaches for strain discrimination, single nucleotide polymorphism (SNP) analysis and genomic multi-locus sequence typing (MLST) are showing concordant results for phylogenetic clustering and are complementary to each other. Metabarcoding and metagenomics, applied to total DNA isolated from either food materials or the production environment, allows the identification of complete microbial populations. Metagenomics identifies the entire gene content and when coupled to transcriptomics or proteomics, allows the identification of functional capacity and biochemical activity of microbial populations. The focus of this review is on the recent use and future potential of NGS in food microbiology and on current challenges. Guidance is provided for new users, such as public health departments and the food industry, on the implementation of NGS and how to critically interpret results and place them in a broader context. The review aims to promote the broader application of NGS technologies within the food industry as well as highlight knowledge gaps and novel applications of NGS with the aim of driving future research and increasing food safety outputs from its wider use.

Exploring Foodborne Pathogen Ecology and Antimicrobial Resistance in the Light of Shotgun Metagenomics

In this chapter, applications of shotgun metagenomics for taxonomic profiling and functional investigation of food microbial communities with a focus on antimicrobial resistance (AMR) were overviewed in the light of last data in the field. Potentialities of metagenomic approach, along with the challenges encountered for a wider and routinely use in food safety was discussed.

Next generation sequencing-based multigene panel for high throughput detection of food-borne pathogens

Contamination of food by chemicals or pathogenic bacteria may cause particular illnesses that are linked to food consumption, commonly referred to as foodborne diseases. Bacteria are present in/on various foods products, such as fruits, vegetables and ready-to-eat products. Bacteria that cause foodborne diseases are known as foodborne pathogens (FBPs). Accurate detection methods that are able to reveal the presence of FBPs in food matrices are in constant demand, in order to ensure safe foods with a minimal risk of causing foodborne diseases. Here, a multiplex PCR-based Illumina sequencing method for FBP detection in food matrices was developed. Starting from 25 bacterial targets and 49 selected PCR primer pairs, a primer collection called foodborne pathogen - panel (FPP) consisting of 12 oligonucleotide pairs was developed. The FPP allows a more rapid and reliable identification of FBPs compared to classical cultivation methods. Furthermore, FPP permits sensitive and specific FBP detection in about two days from food sample acquisition to bioinformatics-based identification. The FPP is able to simultaneously identify eight different bacterial pathogens, i.e. Listeria monocytogenes, Campylobacter jejuni, Campylobacter coli, Salmonella enterica subsp. enterica serovar enteritidis, Escherichia coli, Shigella sonnei, Staphylococcus aureus and Yersinia enterocolitica, in a given food matrix at a threshold contamination level of 10¹cell/g. Moreover, this novel detection method may represent an alternative and/or a complementary approach to PCR-based techniques, which are routinely used for FBP detection, and could be implemented in (parts of) the food chain as a quality check.

Characterization of specific spoilage organisms (SSOs) in vacuum-packed ham by culture-plating techniques and MiSeq next-generation sequencing technologies

BACKGROUND

Knowledge regarding microaerophilic and anaerobic specific spoilage organisms (SSOs) is crucial for an appropriate evaluation of vacuum-packed ham. The objective of this study was to characterize the SSO community in vacuum-packed ham by a culture-dependent technique and MiSeq next-generation sequencing (NGS) platform. The relation between changes among the SSO group in the ham and changes in sensory characteristics of the product was also assessed.

RESULTS

In the study, conventional microbiological analyses were employed in order to establish the participation of several groups of microorganisms in the deterioration of vacuum-packed ham. The diversity of the SSO group in the product was further assessed with the use of MiSeq NGS technology. The bacteria identified in sliced cooked ham belonged mostly to four phyla, namely Actinobacteria, Proteobacteria, Firmicutes and Bacteroidetes. A temperature of 4 °C favoured the development of mesophilic and psychrophilic/psychrotrophic flora, mainly Lactobacillaceae, Enterobacteriaceae and Micrococcaceae families. A high ratio of Brochothrix thermosphacta species and new, cold-tolerant Clostridium spp. was also observed. The growth of these microorganisms facilitated changes in the pH value and organoleptic characteristics of the product.

CONCLUSION

This study confirms that the combination of culturing and MiSeq NGS technology improves the microbial evaluation of food. © 2016 Society of Chemical Industry.

Flow Cytometric and 16S Sequencing Methodologies for Monitoring the Physiological Status of the Microbiome in Powdered Infant Formula Production

The aim of this study was to develop appropriate protocols for flow cytometric (FCM) and 16S rDNA sequencing investigation of the microbiome in a powdered infant formula (PIF) production facility. Twenty swabs were collected from each of the three care zones of a PIF production facility and used for preparing composite samples. For FCM studies, the swabs were washed in 200 mL phosphate buffer saline (PBS). The cells were harvested by three-step centrifugation followed by a single stage filtration. Cells were dispersed in fresh PBS and analyzed with a flow cytometer for membrane integrity, metabolic activity, respiratory activity and Gram characteristics of the microbiome using various fluorophores. The samples were also plated on agar plates to determine the number of culturable cells. For 16S rDNA sequencing studies, the cells were harvested by centrifugation only. Genomic DNA was extracted using a chloroform-based method and used for 16S rDNA sequencing studies. Compared to the dry low and high care zones, the wet medium care zone contained a greater number of viable, culturable, and metabolically active cells. Viable but non-culturable cells were also detected in dry-care zones. In total, 243 genera were detected in the facility of which 42 were found in all three care zones. The greatest diversity in the microbiome was observed in low care. The genera present in low, medium and high care were mostly associated with soil, water, and humans, respectively. The most prevalent genera in low, medium and high care were Pseudomonas, Acinetobacter, and Streptococcus, respectively. The integration of FCM and metagenomic data provided further information on the density of different species in the facility.

Mitigation of Biofilm Formation on Corrugated Cardboard Fresh Produce Packaging Surfaces Using a Novel Thiazolidinedione Derivative Integrated in Acrylic Emulsion Polymers

Various surfaces associated with the storage and packing of food are known to harbor distinct bacterial pathogens. Conspicuously absent among the plethora of studies implicating food packaging materials and machinery is the study of corrugated cardboard packaging, the worldwide medium for transporting fresh produce. In this study, we observed the microbial communities of three different store-bought fruits and vegetables, along with their analog cardboard packaging using high throughput sequencing technology. We further developed an anti-biofilm polymer meant to coat corrugated cardboard surfaces and mediate bacterial biofilm growth on said surfaces. Integration of a novel thiazolidinedione derivative into the acrylic emulsion polymers was assessed using Energy Dispersive X-ray Spectrometry (EDS) analysis and surface topography was visualized and quantified on corrugated cardboard surfaces. Biofilm growth was measured using q-PCR targeting the gene encoding 16s rRNA. Additionally, architectural structure of the biofilm was observed using SEM. The uniform integration of the thiazolidinedione derivative TZD-6 was confirmed, and it was determined via q-PCR to reduce biofilm growth by ~80% on tested surfaces. A novel and effective method for reducing microbial load and preventing contamination on food packaging is thereby proposed.

A benchmark study on error-correction by read-pairing and tag-clustering in amplicon-based deep sequencing

Background

The high error rate of next generation sequencing (NGS) restricts some of its applications, such as monitoring virus mutations and detecting rare mutations in tumors. There are two commonly employed sequencing library preparation strategies to improve sequencing accuracy by correcting sequencing errors: read-pairing method and tag-clustering method (i.e. primer ID or UID). Here, we constructed a homogeneous library from a single clone, and compared the variant calling accuracy of these error-correction methods.

Result

We comprehensively described the strengths and pitfalls of these methods. We found that both read-pairing and tag-clustering methods significantly decreased sequencing error rate. While the read-pairing method was more effective than the tag-clustering method at correcting insertion and deletion errors, it was not as effective as the tag-clustering method at correcting substitution errors. In addition, we observed that when the read quality was poor, the tag-clustering method led to huge coverage loss. We also tested the effect of applying quality score filtering to the error-correction methods and demonstrated that quality score filtering was able to impose a minor, yet statistically significant improvement to the error-correction methods tested in this study.

Conclusion

Our study provides a benchmark for researchers to select suitable error-correction methods based on the goal of the experiment by balancing the trade-off between sequencing cost (i.e. sequencing coverage requirement) and detection sensitivity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2388-9) contains supplementary material, which is available to authorized users.