Surveillance of Foodborne Pathogens: Towards Diagnostic Metagenomics of Fecal Samples

Diagnostic metagenomics is a rapidly evolving laboratory tool for culture-independent tracing of foodborne pathogens. The method has the potential to become a generic platform for detection of most pathogens and many sample types. Today, however, it is still at an early and experimental stage. Studies show that metagenomic methods, from sample storage and DNA extraction to library preparation and shotgun sequencing, have a great influence on data output. To construct protocols that extract the complete metagenome but with minimal bias is an ongoing challenge. Many different software strategies for data analysis are being developed, and several studies applying diagnostic metagenomics to human clinical samples have been published, detecting, and sometimes, typing bacterial infections. It is possible to obtain a draft genome of the pathogen and to develop methods that can theoretically be applied in real-time. Finally, diagnostic metagenomics can theoretically be better geared than conventional methods to detect co-infections. The present review focuses on the current state of test development, as well as practical implementation of diagnostic metagenomics to trace foodborne bacterial infections in fecal samples from animals and humans.

[1]  J. May,et al.  PCR for enteric pathogens in high-prevalence settings. What does a positive signal tell us? , 2015, Infectious diseases.

[2]  S. Lonardi,et al.  CLARK: fast and accurate classification of metagenomic and genomic sequences using discriminative k-mers , 2015, BMC Genomics.

[3]  Robin Patel,et al.  Impact of Contaminating DNA in Whole-Genome Amplification Kits Used for Metagenomic Shotgun Sequencing for Infection Diagnosis , 2017, Journal of Clinical Microbiology.

[4]  D. Rapp.  DNA extraction from bovine faeces: current status and future trends , 2010, Journal of applied microbiology.

[5]  J. Choo,et al.  Sample storage conditions significantly influence faecal microbiome profiles , 2015, Scientific Reports.

[6]  Ole Lund,et al.  Benchmarking of Methods for Genomic Taxonomy , 2014, Journal of Clinical Microbiology.

[7]  Erik Kristiansson,et al.  Statistical evaluation of methods for identification of differentially abundant genes in comparative metagenomics , 2016, BMC Genomics.

[8]  Monzoorul Haque Mohammed,et al.  Classification of metagenomic sequences: methods and challenges , 2012, Briefings Bioinform..

[9]  L B Reller,et al.  Practice guidelines for the management of infectious diarrhea. , 2001, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[10]  L. Raskin,et al.  PCR Biases Distort Bacterial and Archaeal Community Structure in Pyrosequencing Datasets , 2012, PloS one.

[11]  M. Zaharia,et al.  A cloud-compatible bioinformatics pipeline for ultrarapid pathogen identification from next-generation sequencing of clinical samples , 2014, Genome Research.

[12]  R. Knight,et al.  The Human Microbiome Project , 2007, Nature.

[13]  Ahmed A. Metwally,et al.  Analysis of the microbiome: Advantages of whole genome shotgun versus 16S amplicon sequencing. , 2016, Biochemical and biophysical research communications.

[14]  C. Huttenhower,et al.  Metagenomic microbial community profiling using unique clade-specific marker genes , 2012, Nature Methods.

[15]  J. Venter,et al.  Library preparation methodology can influence genomic and functional predictions in human microbiome research , 2015, Proceedings of the National Academy of Sciences.

[16]  Sijung Yun,et al.  Masking as an effective quality control method for next-generation sequencing data analysis , 2014, BMC Bioinformatics.

[17]  Anders F. Andersson,et al.  Binning metagenomic contigs by coverage and composition , 2014, Nature Methods.

[18]  Sharon L. Grim,et al.  Analysis, Optimization and Verification of Illumina-Generated 16S rRNA Gene Amplicon Surveys , 2014, PloS one.

[19]  Katherine H. Huang,et al.  Detection of low-abundance bacterial strains in metagenomic datasets by eigengenome partitioning , 2015, Nature Biotechnology.

[20]  R. Knight,et al.  The human microbiome project: exploring the microbial part of ourselves in a changing world , 2022 .

[21]  J. Handelsman,et al.  Molecular biological access to the chemistry of unknown soil microbes: a new frontier for natural products. , 1998, Chemistry & biology.

[22]  J. Utzinger,et al.  Metagenomic diagnostics for the simultaneous detection of multiple pathogens in human stool specimens from Côte d'Ivoire: a proof-of-concept study. , 2016, Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases.

[23]  Paul Turner,et al.  Reagent and laboratory contamination can critically impact sequence-based microbiome analyses , 2014, BMC Biology.

[24]  M. Pallen.  Diagnostic metagenomics: potential applications to bacterial, viral and parasitic infections , 2014, Parasitology.

[25]  Umer Zeeshan Ijaz,et al.  Illumina error profiles: resolving fine-scale variation in metagenomic sequencing data , 2016, BMC Bioinformatics.

[26]  Yu-Chieh Liao,et al.  Accurate binning of metagenomic contigs via automated clustering sequences using information of genomic signatures and marker genes , 2016, Scientific Reports.

[27]  H. Drummond,et al.  The Impact of Different DNA Extraction Kits and Laboratories upon the Assessment of Human Gut Microbiota Composition by 16S rRNA Gene Sequencing , 2014, PloS one.

[28]  Paul P. Gardner,et al.  An evaluation of the accuracy and speed of metagenome analysis tools , 2015, Scientific Reports.

[29]  J. Gilbert,et al.  Recovering complete and draft population genomes from metagenome datasets , 2016, Microbiome.

[30]  G. Dubourg,et al.  Epidemiologic studies need asymptomatic controls. , 2015, Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases.

[31]  R. Guerrant,et al.  Evaluation and diagnosis of acute infectious diarrhea. , 1985, The American journal of medicine.

[32]  Jens Roat Kultima,et al.  Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes , 2014, Nature Biotechnology.

[33]  Jun Kawai,et al.  Metagenomic Diagnosis of Bacterial Infections , 2008, Emerging infectious diseases.

[34]  K. Kupkova,et al.  Bioinformatics strategies for taxonomy independent binning and visualization of sequences in shotgun metagenomics , 2016, Computational and structural biotechnology journal.

[35]  Susan P. Holmes,et al.  Waste Not , Want Not : Why Rarefying Microbiome Data is Inadmissible . October 1 , 2013 , 2013 .

[36]  S. C. Andersen,et al.  Gene-Based Pathogen Detection: Can We Use qPCR to Predict the Outcome of Diagnostic Metagenomics? , 2017, Genes.

[37]  M. Josefsen,et al.  Microbial food safety: Potential of DNA extraction methods for use in diagnostic metagenomics. , 2015, Journal of microbiological methods.

[38]  Karsten Kristiansen,et al.  Choice of bacterial DNA extraction method from fecal material influences community structure as evaluated by metagenomic analysis , 2014, Microbiome.

[39]  Ole Lund,et al.  MGmapper: Reference based mapping and taxonomy annotation of metagenomics sequence reads , 2017, PloS one.

[40]  A. Mitchell,et al.  Diarrhea in American Infants and Young Children in the Community Setting: Incidence, Clinical Presentation and Microbiology , 2006, The Pediatric infectious disease journal.

[41]  Luis Pedro Coelho,et al.  Towards standards for human fecal sample processing in metagenomic studies , 2017, Nature Biotechnology.

[42]  Ruth Timme,et al.  Practical Value of Food Pathogen Traceability through Building a Whole-Genome Sequencing Network and Database , 2016, Journal of Clinical Microbiology.

[43]  Timothy L. Tickle,et al.  Computational meta'omics for microbial community studies , 2013, Molecular systems biology.

[44]  R. Kaas,et al.  Erratum to: Evaluating next-generation sequencing for direct clinical diagnostics in diarrhoeal disease , 2017, European Journal of Clinical Microbiology & Infectious Diseases.

[45]  F. Aarestrup,et al.  Impact of Sample Type and DNA Isolation Procedure on Genomic Inference of Microbiome Composition , 2016, mSystems.

[46]  D. Raoult,et al.  MALDI-TOF Identification of the Human Gut Microbiome in People with and without Diarrhea in Senegal , 2014, PloS one.

[47]  C. Thermes,et al.  Library preparation methods for next-generation sequencing: tone down the bias. , 2014, Experimental cell research.

[48]  Cheryl L. Tarr,et al.  Metagenomics of Two Severe Foodborne Outbreaks Provides Diagnostic Signatures and Signs of Coinfection Not Attainable by Traditional Methods , 2016, Applied and Environmental Microbiology.

[49]  Derrick E. Wood,et al.  Kraken: ultrafast metagenomic sequence classification using exact alignments , 2014, Genome Biology.

[50]  F. Aarestrup,et al.  Sharing Data for Global Infectious Disease Surveillance and Outbreak Detection. , 2016, Trends in microbiology.

[51]  Anders Krogh,et al.  Fast and sensitive taxonomic classification for metagenomics with Kaiju , 2016, Nature Communications.

[52]  P. Hugenholtz,et al.  Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes , 2013, Nature Biotechnology.

[53]  Ole Lund,et al.  Rapid Whole-Genome Sequencing for Detection and Characterization of Microorganisms Directly from Clinical Samples , 2013, Journal of Clinical Microbiology.

[54]  S. Persson,et al.  Towards diagnostic metagenomics of Campylobacter in fecal samples , 2017, BMC Microbiology.

[55]  J. Coulibaly,et al.  Combined stool-based multiplex PCR and microscopy for enhanced pathogen detection in patients with persistent diarrhoea and asymptomatic controls from Côte d'Ivoire. , 2015, Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases.

[56]  T. R. Licht,et al.  Freezing fecal samples prior to DNA extraction affects the Firmicutes to Bacteroidetes ratio determined by downstream quantitative PCR analysis. , 2012, FEMS microbiology letters.

[57]  N. Loman,et al.  A culture-independent sequence-based metagenomics approach to the investigation of an outbreak of Shiga-toxigenic Escherichia coli O104:H4. , 2013, JAMA.

[58]  Luis M Rodriguez-R,et al.  Estimating coverage in metagenomic data sets and why it matters , 2014, The ISME Journal.