AEM Accepted Manuscript Posted Online 1 December 2017 Appl. Environ. Microbiol. doi:10.1128/AEM.02340-17 Copyright © 2017 American Society for Microbiology. All Rights Reserved.
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Running title: Quasi-metagenomics sequencing of Salmonella from food
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Quasi-metagenomics and realtime sequencing aided detection and subtyping of Salmonella
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enterica from food samples
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Ji-Yeon Hyeon1#, Shaoting Li1#, David A. Mann1, Shaokang Zhang1, Zhen Li2, Yi Chen3,
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Xiangyu Deng1*
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Center for Food Safety, Department of Food Science and Technology, University of Georgia,
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1109 Experiment St, Griffin, Georgia, 30223, US
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98155, US
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MD 20740, US
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Key words: Salmonella, detection, subtyping, metagenomics, MinION
Washington State Department of Health, Public Health Laboratories, Shoreline, Washington,
Center for Food Safety and Applied Nutrition, Food and Drug Administration, College Park,
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#
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*Corresponding author
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Xiangyu Deng
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Center for Food Safety, Department of Food Science and Technology, University of Georgia,
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1109 Experiment St, Griffin, Georgia, 30223, US
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E-mail:
[email protected]
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Contributed equally
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Abstract
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Metagenomics analysis of food samples promises isolation-independent detection and subtyping
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of foodborne bacterial pathogens in a single workflow. Selective concentration of Salmonella
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genomic DNA through immunomagnetic separation (IMS) and multiple displacement
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amplification (MDA) were shown to shorten culture enrichment of Salmonella-spiked raw
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chicken breast samples by over 12 hours while permitting serotyping and high-fidelity single
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nucleotide polymorphisms (SNP) typing of the pathogen using short shotgun sequencing reads.
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The herein termed quasi-metagenomics approach was evaluated on Salmonella-spiked lettuce
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and black peppercorn samples as well as retail chicken parts naturally contaminated with
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different serotypes of Salmonella. Between 8 and 24 h culture enrichment was required for
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detecting and subtyping naturally occurring Salmonella from unspiked chicken parts compared
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with 4 to 12 h culture enrichment when Salmonella-spiked food samples were analyzed,
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indicating the likely need for longer culture enrichment to revive low levels of stressed or injured
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Salmonella cells in food. Further acceleration of the workflow was achieved by real-time
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nanopore sequencing. After 1.5 hours of analysis on a potable sequencer, sufficient data were
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generated from sequencing IMS-MDA product of a cultured-enriched lettuce sample to allow
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serotyping and robust phylogenetic placement of the inoculated isolate.
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Importance
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Both culture enrichment and next-generation sequencing remain to be time-consuming processes
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for food testing where rapid methods for pathogen detection are widely available. Our study
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demonstrated substantial acceleration of the respective process through IMS-MDA and real-time
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nanopore sequencing. In one example, the combined use of the two methods delivered a less than
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24 h turnaround time from a Salmonella-contaminated lettuce sample to phylogenetic
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identification of the pathogen. Improved efficiency like this is important for further expanding
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the use of whole genome and metagenomics sequencing in microbial analysis of food. Our
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results suggest the potential of the quasi-metagenomics approach in areas where rapid detection
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and subtyping of foodborne pathogens is important, such as foodborne outbreak response and
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precision tracking and monitoring of foodborne pathogens in production environments and
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supply chains.
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Introduction
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Detection and subtyping of foodborne pathogens are typically separated. After a pathogen is
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detected, further subtyping assays may ensue. According to the United States Food and Drug
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Administration’s Bacteriological Analytical Manual (BAM)
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(https://www.fda.gov/food/foodscienceresearch/ laboratorymethods/ucm2006949.htm) and
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U.S.Department of Agriculture Food Safety and Inspection Service’s Microbiology Laboratory
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Guidebook (MLG) (https://www.fsis.usda.gov/wps/portal/ fsis/topics/science/laboratories-and-
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procedures/guidebooks-and-methods/microbiology-laboratory-guidebook/microbiology-
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laboratory-guidebook), confirmed detection of bacterial foodborne pathogens from food and
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environmental samples requires culture isolation of bacterial isolates and confirmatory
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identification by biochemical or molecular tests. Isolation and identification of major bacterial
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foodborne pathogens takes 5-7 days or even longer using these isolate-centric workflows. Then
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the isolates may be further characterized by a variety of pheno-and genotyping methods (1),
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which can further increase the laboratory turnaround time.
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Faster alternatives for the detection and subtyping of foodborne pathogens have been developed
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and implemented. A wide array of rapid detection methods, including nucleic acid-based,
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immunological-based and biosensor-based techniques, are commercially available for selected
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pathogens (2). While most of these methods still require culture enrichment for 8 – 48 h, they
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typically allow presumptive detection of specific pathogens in certain food matrices much faster
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than culture-based detection methods. Routine use of WGS promises substantial reduction of
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time and cost for public health laboratories by providing a one-stop platform for various
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subtyping methods. Using WGS data, multiple subtyping analyses can be integrated into a single
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in silico workflow, including serotyping (3), SNP typing (4), multilocus sequence typing (MLST)
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(5, 6) and antimicrobial resistance profiling (7). However, most rapid detection methods do not
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yield bacterial isolates, which are required by current practices of WGS. In addition, standard
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laboratory procedures of WGS, which consist of regrowth of the pathogen, genomic DNA
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purification and library preparation in addition to actual sequencing, take 5-7 days to complete.
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That means the entire process from contaminated food to pathogen genomes can take up to 10-14
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days.
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Recent studies using metagenomics sequencing demonstrated isolation-independent detection
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and subtyping of Shiga toxin-producing Escherichia coli (STEC) from spinach (8, 9). Direct
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capture and characterization of STEC genomic sequences was made possible by sequencing the
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metagenomes derived from enrichment cultures of spinach samples. Using this method, pathogen
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detection and subtyping can be effectively combined into a single workflow uninterrupted by
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culture isolation.
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Such applications also underscored the importance of culture enrichment for metagenomics
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analysis of pathogen analytes. In the aforementioned studies, both nonselective pre-enrichment
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and selective enrichment through a variety of antibiotics were performed to effectively enrich
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STEC (8, 9). In fact, metagenomics sequencing has been used as a tool to evaluate and
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rationalize culture enrichment methods for detecting STEC from fresh spinach (8), Listeria
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monocytogenes from ice cream (10), and Salmonella enterica from tomato phyllosphere (11) and
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cilantro (12). These studies collectively suggest that the often low levels of pathogen cells in
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food samples, presence of competitive or antagonist organisms against the analyte, and food
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processing and storage conditions detrimental to optimal growth of target pathogens can all pose
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challenges for effective culture enrichment. Therefore, alternative methods to partially replace
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culture enrichment are needed to improve the efficiency of analyte DNA concentration and
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accelerate the workflow of metagenomics food testing.
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Besides culture enrichment, sequencing itself is another time-consuming step for detecting
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foodborne pathogen. A full sequencing run on an Illumina MiSeq platform takes ~ 24 to 56 h
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(150 – 300 bp paired-end reads), whereas rapid pathogen detection methods for microbiological
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analysis of food generally refer to assays that can be completed within minutes and hours
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excluding culture enrichment (13). The advent of nanopore sequencing on a portable device has
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enabled rapid and in-field detection and analysis of clinical pathogens (14). This technology
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allows real-time analysis of sequencing data as they are being generated, permitting rapid
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identification of bacterial and viral pathogens thorough whole genome (15) and metagenomics
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sequencing (16).
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In this study, we aimed to improve and expedite metagenomics detection and subtyping of
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foodborne pathogens through selective concentration of analyte DNA and real-time nanopore
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sequencing of concentrated DNA samples. Using Salmonella-spiked chicken breast as a model
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system, we first investigated whether culture enrichment could be shortened through targeted cell
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capture by immunomagnetic separation (IMS) and whole genome amplification by multiple
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displacement amplification (MDA). Unlike culture enrichment, which is intrinsically restricted in
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speed by the length of cell cycle, MDA provides a rapid and highly efficient alternative to
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enriching analyte DNA for molecular detection of bacteria. Using bacteriophage ɸ29 DNA
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polymerase, MDA was reported to generate sufficient amounts of DNA from single E. coli cells
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for whole genome sequencing (17). The ɸ29 DNA polymerase has high processivity (18) and
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high proofreading activity (19). Its reaction can be performed isothermally at 30ºC without the
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need of a thermocycler. The IMS-MDA method had allowed sequencing-based, culture-
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independent detection of Chlamydia trachomatis, an obligate intracellular pathogen, from
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clinical samples (20). We have recently shown that IMS-MDA led to real-time PCR detection of
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low levels of Salmonella from raw chicken breast with no or shortened (4 h) culture enrichment
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(21). Unlike previous studies that were focused on optimizing culture enrichment prior to
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metagenomics sequencing (8-12, 22), we aimed to reduce the need for culture enrichment
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through the alternative of IMS-MDA. To differentiate it from conventional metagenomics
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sequencing without selective analyte concentration, shotgun sequencing of IMS-MDA products
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was termed as quasi-metagenomics sequencing in this study. We further evaluated the method
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with Salmonella-spiked iceberg lettuce, black peppercorns, peanut butter as well as naturally-
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contaminated retail chicken parts. Finally, we demonstrated rapid detection and phylogenetic
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identification of Salmonella from a lettuce sample using quasi-metagenomics sequencing on a
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MinION device (Oxford Nanopore Technologies, Oxford, UK).
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Results
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Comparison of culture enrichment methods. Both buffered peptone water (BPW) (23) and
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Rappaport Vassiliadis (RV) broth (24) have been used to enrich Salmonella from chicken. Pre-
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enrichment in BPW followed by selective enrichment in RV was reported to increase the
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sensitivity of PCR detection of Salmonella in poultry (23).Each medium alone and the
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combination of both were evaluated to identify optimal conditions to increase the abundance of S.
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enterica serotype Enteritidis (SE) relative to background flora on raw chicken breast. Real-time
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PCR threshold cycles (i.e., Ct values) were used to estimate relative abundance of SE (21). The
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Ct values were obtained from real-time PCR assays using DNA extracted from enrichment
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cultures as PCR templates. SE cells after enrichment were enumerated on xylose-lysine-tergitol-
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4 (XLT) agar that is selective for Salmonella. The level of microorganisms after enrichment,
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including both SE and background flora, was estimated on trypticase soy agar (TSA). As shown
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in Table S1, while BPW was most effective in enriching SE by yielding the lowest Ct value and
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the highest SE count on XLT, it also resulted in the highest level of background flora measured
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by the difference between CFU counts on TSA and XLT. The combination of BPW and RV was
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least effective in enriching SE relative to background flora as indicated by the highest Ct value.
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Therefore, RV was selected for SE enrichment prior to IMS and MDA because of its balanced
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performance in enriching SE and suppressing excessive growth of background flora.
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Effects of IMS, MDA and IMS-MDA on recovering SE genome by shotgun sequencing.
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After culture enrichment, IMS was used to selectively capture SE cells and MDA was used to
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generate DNA from captured cells for shotgun sequencing. Their individual and combined
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effects on improving sequencing yield of SE among chicken and microbial DNA were assessed.
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When IMS was performed alone without MDA, DNA extracted from cells bound to
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immunomagnetic beads was insufficient for sequencing (below 10 pg/µg quantification limit of
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Qubit HS dsDNA assay). When MDA was used, alone or in combination with IMS, all the
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resulting DNA samples allowed construction of libraries for Illumina MiSeq sequencing.
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Sequencing results were evaluated by multiple metrics as shown in Table 1. Raw reads from all
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the MDA and IMS-MDA samples allowed accurate serotype prediction using SeqSero (3). When
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MDA was used alone without IMS after 12 h of RV enrichment, only an average of 4.74% of all
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sequencing reads were classified as Salmonella. By contrast, using IMS in conjunction with
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MDA after enrichment substantially increased the percentage Salmonella reads to an average of
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48.14%. The increased sequencing output of Salmonella by IMS-MDA led to substantial
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improvements of sequencing parameters of the SE genome. Sequencing depth normalized by 100
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million bases of sequencing data increased from 1.01x by MDA to 9.82x by IMS-MDA. The
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N50 of draft SE genome assembly using metagenomically classified Salmonella reads increased
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by 31 folds through IMS-MDA instead of just MDA after RV enrichment. The values of
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normalized sequencing depth and N50 were equivalent to those obtained by WGS of SE
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genomes prepared from pure cultures (25).
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IMS-MDA shortened culture enrichment for quasi-metagenomics detection of SE. To
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evaluate how IMS-MDA could improve selective concentration of Salmonella in comparison to
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culture enrichment alone, we further sequenced 1) DNA samples prepared immediately after SE
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inoculation on chicken breast (~1 CFU/g) and after RV enrichment of the inoculated samples for
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4, 8, 12 and 24 h; and 2) IMS-MDA products after RV enrichment for 4, 8 and 12 h. As shown
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in Figure 1A and Table 1, the percentage of Salmonella in chicken microbiome (i.e., Salmonella
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abundance) increased slowly in the first 12 h of RV enrichment and rose to only 18.00% after
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culturing for 24 h. In comparison, IMS-MDA treatment after 4 h of enrichment increased
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Salmonella abundance to 31.49%. Furthermore, RV enrichment alone for 12 h only allowed
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11.04% of the target SE genome to be sequenced, while IMS-MDA was able to recover 21.61%
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of the genome after only 4 h enrichment, and almost the entire genome (99.09%) after 12 h
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enrichment (Figure 1B and Table 1). IMS-MDA also improved overall Salmonella sequencing
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output among all sequencing reads including chicken DNA. Forty-eight percent of all sequencing
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reads were classified as Salmonella after 12 h of RV enrichment followed by IMS-MDA,
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compared with 16.74% after 24 h of RV enrichment alone (Figure 1C and Table 1). These results
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showed that IMS-MDA, a 2-3 h process, could reduce culture enrichment by at least 12 h as
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evaluated by different descriptive measures.
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Detection and high fidelity subtyping by shotgun sequencing following IMS-MDA. The
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ability of the quasi-metagenomics approach to distinguish the spiked analyte from other SE
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strains was evaluated using the CFSAN SNP pipeline (26). In addition to the raw chicken breast
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samples that were inoculated with the SE strain at ~ 1 CFU/g as previously described, samples
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with additional inoculum levels at ~ 0.1 and 10 CFU/g were prepared and analyzed. An
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uninoculated sample was enriched for 12 h before going through the entire IMS-MDA and
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shotgun sequencing process as a negative control. The sample was further confirmed to be
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Salmonella negative by culture enrichment (data not shown). Results from all the samples were
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summarized in Table 2.
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An average of 569 Mb of sequences were generated from inoculated samples by shotgun
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sequencing on an Illumina MiSeq instrument, which accounted for ~5% of the total output of a
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MiSeq run (MiSeq Reagent Kit V3, according to manufacturer’s specification).
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Accurate serotype prediction using sequencing reads was achieved from all the inoculated
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samples except when lowest inoculation level (0.1 CFU/g) was coupled with the shortest culture
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enrichment duration (4 h). The lowest sequencing coverage permitting serotyping from Illumina
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reads was 21.61%. At least 10% of the reference SE genome was recovered by quasi-
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metagenomics sequencing of inoculated samples. The minimum sequencing coverage of an
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inoculated sample was 10.72%, which was obtained at the lowest inoculum level of 0.1 CFU/g
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with shortest culture enrichment for 4 h. When 12 h of culture enrichment was performed, more
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than 90% of the SE genome was mapped by sequencing reads at all inoculation levels. By
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contrast, 0.02% of the reference genome was mapped by sequencing reads from the negative
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control sample.
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For each inoculated sample, a core genome SNP phylogeny was constructed to include the quasi-
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metagenomics sample and a total of 52 SE isolates representing 16 major outbreaks and 3
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sporadic cases in the US between 2001 and 2012 (4). As shown in Figure 2, tight clustering of
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the quasi-metagenomics sample (Target) and the WGS sample of the spiked strain (Reference)
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was achieved in all the nine combinations of inoculation levels and culture enrichment durations,
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indicating equivalence of the two methods in supporting core genome SNP typing. When spiked
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chicken samples were culture enriched for 12 h, perfect match between each pair of quasi-
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metagenomics and WGS samples was observed with 0 SNP distance in between (Figure 2).
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Besides the clustering of the quasi-metagenomics and WGS samples, the rest of the phylogenetic
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tree was congruent across all the trials. These results suggest that high-fidelity subtyping with
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phylogenetic discrimination can be achieved by the quasi-metagenomics approach with culture
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enrichment for 12 h or shorter even when the contamination level was low (~ 0.1 CFU/g).
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Detection and subtyping of Salmonella from unspiked retail raw chicken meat. The
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performance of the quasi-metagenomics approach was further assessed by analyzing naturally
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contaminated retail chicken samples. As opposed to spiked samples, naturally contaminated
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samples referred to retail products that had been contaminated by Salmonella during production.
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A total of 76 retail chicken part samples (25 g aliquots), including breasts (n=24), wings (n=27),
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thighs (n=12), drumsticks (n=9), ground chicken (n=2), gizzards (n=2) and hearts (n=2) were
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screened for Salmonella by RV enrichment. In parallel, IMS-MDA-real-time PCR was
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performed after 4, 8, 12 and 24 h of enrichment (21). Salmonella was isolated from three wing
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samples by culture enrichment. WGS of the isolated strains was performed and their serotypes
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were determined to be Enteritidis (Sample A), Typhimurium (Sample B) and Heidelberg
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(Sample C) using WGS data (Table 3).
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The same three samples were also determined to be Salmonella positive by IMS-MDA-real-time
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PCR and further analyzed using a three-tube most probable number (MPN) method (Table 3).
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Using IMS-MDA-real-time PCR, Salmonella was first detected after 8 h of enrichment in
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Sample A and 24 h of enrichment in Samples B and C. The longer enrichment time required by
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Samples B and C was likely due to the low level of Salmonella contamination (< 3 MPN/g)
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compared with Sample A (43 MPN/g). Quasi-metagenomics sequencing was performed on
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selected IMS-MDA products prepared from positive wing samples. As shown in Table 3 and
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Figure S1, correct serotyping (Enteritidis and Typhimurium) and accurate phylogenetic
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placement were achieved from Sample A and Sample B. Sample C had a low sequencing
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coverage of 12.53%, which did not permit serotyping and strain-level phylogenetic placement
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(data now shown). Instead, genome distance between Sample C and a set of 258 complete
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Salmonella reference genomes of 57 serotypes was estimated using Mash (27). The eight closest
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genomes to Sample C were all of serotype Heidelberg (Table S2), supporting the detection and
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preliminary identification of a Heidelberg isolate from this sample.
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Detection and subtyping of SE from other selected food samples. In addition to raw chicken
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parts, the IMS-MDA-shotgun sequencing method was further evaluated with other selected food
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samples including lettuce, black peppercorn and peanut butter, all of which were linked to recent
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Salmonella outbreaks (28-30). With 12 h of culture enrichment, strain-level, high-fidelity
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subtyping was achieved in both lettuce and peppercorn samples at all inoculation levels (~0.1, 1
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and 10 CFU/g) as shown by the clustering of IMS-MDA-shotgun sequencing and WGS samples
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with 0 or 1 SNP distance (Table 4 and Figure S2). While IMS-MDA allowed real-time PCR
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detection of SE from peanut butter samples at all inoculation levels after 12 h of culture
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enrichment (data now shown), the Ct values were 25 or higher and insufficient DNA samples
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were obtained for shotgun sequencing. The high fat contents in peanut butter likely compromised
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the effective capture of SE by IMS beads.
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Rapid quasi-metagenomics detection and subtyping of SE from lettuce using MinION
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sequencing. IMS-MDA product prepared after 12 h of culture enrichment of a spiked lettuce
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sample (1 CFU/g) was sequenced on a MinION device. Sequencing data were collected hourly
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until the full run finished after 48.5 h. The same sample had been sequenced on a MiSeq
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platform (Table 4). After 1.5 h of sequencing, a total of 14,760 1D and 2D reads with an average
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length of 2,362 bp were generated. These reads covered 65.19% of the SE reference genome and
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allowed accurate prediction of its serotype as Enteritidis (Table S3). Using core genome SNP
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typing, the MinION quasi-metagenomics sample was accurately placed on the phylogenetic tree
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that included 52 previously described outbreak and clinical SE isolates. As shown in Figure 3,
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the 1.5 h MinION sample clustered closely with the WGS reference of the inoculated isolate.
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Similar results were obtained using MinION data after 48.5 h of sequencing (Figure 3), which
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contained 197,070 1D and 2D reads with an average length of 2,388 bp. SNP distance between
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the quasi-metagenomics sample and the WGS reference was 70 and 65 after 1.5 h and 48.5 h of
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MinION sequencing, respectively.
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Correlation between Ct value and sequencing coverage. Prior to shotgun sequencing on an
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Illumina MiSeq instrument, all the IMS-MDA processed samples (n=28) in this study were
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analyzed by real-time PCR. The resulting Ct values displayed a positive correlation with shotgun
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sequencing coverage (R2 = 0.76, Figure 4). This observation suggests that Ct value is a useful
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indicator of target genome output by shotgun sequencing. When Ct values were lower than 25,
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the majority (>50%) of the SE genome was likely to be sequenced. Serotype prediction from raw
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sequencing reads was successful in every sample tested in the study when the Ct value was
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below 26. Therefore, Ct values can be used as a performance parameter for developing and
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optimizing the quasi-metagenomics method or as a quality check before committing to
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sequencing.
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Discussion
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Conventional metagenomics approach relies on deep sequencing to identify low abundant
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microbial species directly from environmental samples. This strategy can be impractical, if not
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ineffective, for detecting low levels of bacterial pathogen contaminants in food samples. As
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shown by previous studies (8-12), adequate concentration of pathogen analytes prior to
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sequencing is critical for metagenomics identification of pathogen sequences. Culture
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enrichment alone was used in these studies to concentrate target pathogen cells. Given sufficient
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time, when the analyte rose to become a dominant species in the enrichment culture, nearly full
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recovery of the analyte genome could be achieved from sequencing enriched samples. This
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allowed a variety of subtyping analyses to be performed on shotgun metagenomics data,
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generating rich information about the analyte in addition to its detection. In this study, we
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improved and accelerated the isolation-independent, shotgun sequencing-based detection and
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subtyping of Salmonella from selected food samples using selective enrichment of the analyte
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genomic DNA by IMS-MDA, real-time nanopore sequencing by MinION and streamlined
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bioinformatics analysis of sequencing data.
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Firstly, culture enrichment was substantially shortened by IMS-MDA. While necessary and
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effective in microbial analysis of food samples, culture enrichment alone can be time-consuming,
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especially when low levels of pathogen contaminants are present in food samples together with
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competing flora and, in some cases, antimicrobial substances. With approximate detection
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sensitivity at
