Quasimetagenomics-Based and Real-Time-Sequencing-AidedDetection and Subtyping of Salmonella enterica from FoodSamples

Ji-Yeon Hyeon,a Shaoting Li,a David A. Mann,a Shaokang Zhang,a Zhen Li,b Yi Chen,c Xiangyu Denga

aCenter for Food Safety, Department of Food Science and Technology, University of Georgia, Griffin, Georgia, USAbWashington State Department of Health, Public Health Laboratories, Shoreline, Washington, USAcCenter for Food Safety and Applied Nutrition, Food and Drug Administration, College Park, Maryland, USA

ABSTRACT Metagenomics analysis of food samples promises isolation-independentdetection and subtyping of foodborne bacterial pathogens in a single workflow. Theselective concentration of Salmonella genomic DNA by immunomagnetic separation(IMS) and multiple displacement amplification (MDA) shortened the time for cultureenrichment of Salmonella-spiked raw chicken breast samples by over 12 h while per-mitting serotyping and high-fidelity single nucleotide polymorphism (SNP) typing ofthe pathogen using short shotgun sequencing reads. The herein-termed quasimeta-genomics approach was evaluated on Salmonella-spiked lettuce and black pepper-corn samples as well as retail chicken parts naturally contaminated with different se-rotypes of Salmonella. Culture enrichment of between 8 and 24 h was required fordetecting and subtyping naturally occurring Salmonella from unspiked chicken partscompared with 4- to 12-h culture enrichment when Salmonella-spiked food sampleswere analyzed, indicating the likely need for longer culture enrichment to revive lowlevels of stressed or injured Salmonella cells in food. A further acceleration of theworkflow was achieved by real-time nanopore sequencing. After 1.5 h of analysis ona potable sequencer, sufficient data were generated from sequencing the IMS-MDAproducts of a cultured-enriched lettuce sample to enable serotyping and robustphylogenetic 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 detectionare widely available. Our study demonstrated a substantial acceleration of these pro-cesses by the use of immunomagnetic separation (IMS) with multiple displacement am-plification (MDA) and real-time nanopore sequencing. In one example, the combineduse of the two methods delivered a less than 24-h turnaround time from the collec-tion of a Salmonella-contaminated lettuce sample to the phylogenetic identificationof the pathogen. An improved efficiency such as this is important for further ex-panding the use of whole-genome and metagenomics sequencing in the microbialanalysis of food. Our results suggest the potential of the quasimetagenomics ap-proach in areas where rapid detection and subtyping of foodborne pathogens areimportant, such as for foodborne outbreak response and the precision tracking andmonitoring of foodborne pathogens in production environments and supply chains.

KEYWORDS Salmonella, detection, subtyping, metagenomics, MinION

The detection and subtyping of foodborne pathogens are typically separate. After apathogen is detected, further subtyping assays may ensue. According to the United

States Food and Drug Administration’s bacteriological analytical manual (BAM) (https://www.fda.gov/food/foodscienceresearch/laboratorymethods/ucm2006949.htm) and the

Received 24 October 2017 Accepted 28November 2017

Accepted manuscript posted online 1December 2017

Citation Hyeon J-Y, Li S, Mann DA, Zhang S, LiZ, Chen Y, Deng X. 2018. Quasimetagenomics-based and real-time-sequencing-aideddetection and subtyping of Salmonella entericafrom food samples. Appl Environ Microbiol84:e02340-17. https://doi.org/10.1128/AEM.02340-17.

Editor Charles M. Dozois, INRS—InstitutArmand-Frappier

Copyright © 2018 American Society forMicrobiology. All Rights Reserved.

Address correspondence to Xiangyu Deng,xdeng@uga.edu.

J.-Y.H. and S.L. contributed equally to thisarticle.

FOOD MICROBIOLOGY

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U.S. Department of Agriculture Food Safety and Inspection Service’s microbiologylaboratory guidebook (MLG) (https://www.fsis.usda.gov/wps/portal/fsis/topics/science/laboratories-and-procedures/guidebooks-and-methods/microbiology-laboratory-guidebook/microbiology-laboratory-guidebook), the confirmed detection of bacterialfoodborne pathogens from food and environmental samples requires a culture isola-tion of bacterial isolates and a confirmatory identification by biochemical or moleculartests. The isolation and identification of major bacterial foodborne pathogens take 5 to7 days or even longer using these isolate-centric workflows. Then, the isolates may befurther characterized by a variety of pheno- and genotyping methods (1), which canfurther increase the laboratory turnaround time.

Faster alternatives for the detection and subtyping of foodborne pathogens havebeen developed and implemented. A wide array of rapid detection methods, includingnucleic acid-based, immunology-based, and biosensor-based techniques, is commer-cially available for selected pathogens (2). While most of these methods still requireculture enrichment for 8 to 48 h, they typically enable a much faster presumptivedetection of specific pathogens in certain food matrices than culture-based detectionmethods. The routine use of whole-genome sequencing (WGS) promises a substantialreduction of the time and cost for public health laboratories by providing a one-stopplatform for various subtyping methods. Using WGS data, multiple subtyping analysescan be integrated into a single in silico workflow, including serotyping (3), singlenucleotide polymorphism (SNP) typing (4), multilocus sequence typing (MLST) (5, 6),and antimicrobial resistance profiling (7). However, most rapid detection methods donot yield bacterial isolates, which are required for current practices of WGS. In addition,standard laboratory procedures for WGS, which consist of regrowth of the pathogen,genomic DNA purification, and library preparation in addition to actual sequencing,take 5 to 7 days to complete. That means the entire process from the collection of acontaminated food sample to the determination of the pathogen genome sequencescan take up to 10 to 14 days.

Recent studies using metagenomics sequencing demonstrated isolation-independentdetection and subtyping of Shiga toxin-producing Escherichia coli (STEC) from spinach(8, 9). The direct capture and characterization of STEC genomic sequences was madepossible by sequencing the metagenomes derived from enrichment cultures of spinachsamples. Using this method, pathogen detection and subtyping can be effectivelycombined into a single workflow uninterrupted by culture isolation.

Such applications also underscored the importance of culture enrichment for ametagenomics analysis of pathogen analytes. In the aforementioned studies, bothnonselective preenrichment and selective enrichment with a variety of antibiotics wereperformed to effectively enrich for STEC (8, 9). In fact, metagenomics sequencinghas been used as a tool to evaluate and rationalize culture enrichment methods fordetecting STEC on fresh spinach (8), Listeria monocytogenes in ice cream (10), andSalmonella enterica from the tomato phyllosphere (11) and on cilantro (12). Thesestudies collectively suggest that the often low levels of pathogen cells in food samples,the presence of competitive or antagonist organisms against the analyte, and the foodprocessing and storage conditions detrimental to optimal growth of target pathogenscan all pose challenges for effective culture enrichment. Therefore, alternative methodsto partially replace culture enrichment are needed to improve the efficiency of analyteDNA concentration and to accelerate the workflow of metagenomics food testing.

Besides culture enrichment, sequencing itself is another time-consuming step fordetecting foodborne pathogens. A full sequencing run on an Illumina MiSeq platformtakes �24 to 56 h (150- to 300-bp paired-end reads), whereas rapid pathogen detectionmethods for the microbiological analysis of food generally involve assays that can becompleted within minutes and hours excluding culture enrichment (13). The advent ofnanopore sequencing on a portable device has enabled rapid and in-field detectionand analysis of clinical pathogens (14). This technology allows real-time analysis ofsequencing data as they are being generated, permitting a rapid identification of

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bacterial and viral pathogens by whole-genome sequencing (15) and metagenomicssequencing (16).

In this study, we aimed to improve and expedite metagenomics detection andsubtyping of foodborne pathogens through the selective concentration of analyte DNAand real-time nanopore sequencing of concentrated DNA samples. Using Salmonella-spiked chicken breast as a model system, we first investigated whether culture enrich-ment could be shortened via targeted cell capture by immunomagnetic separation(IMS) and whole-genome amplification by multiple displacement amplification (MDA).Unlike culture enrichment, which is intrinsically restricted in speed by the length of thecell cycle, MDA provides a rapid and highly efficient alternative to enriching analyteDNA for the molecular detection of bacteria. Using bacteriophage �29 DNA polymer-ase, MDA was reported to generate sufficient amounts of DNA from single E. coli cellsfor whole-genome sequencing (17). The �29 DNA polymerase has high processivity (18)and high proofreading activity (19). Its reaction can be performed isothermally at 30°Cwithout the need of a thermocycler. The IMS-MDA method enabled sequencing-basedculture-independent detection of Chlamydia trachomatis, an obligate intracellularpathogen, from clinical samples (20). We have recently shown that IMS-MDA led toreal-time PCR detection of low levels of Salmonella from raw chicken breast with no orshortened (4 h) culture enrichment (21). Unlike previous studies that were focused onoptimizing culture enrichment prior to metagenomics sequencing (8–12, 22), we aimedto reduce the need for culture enrichment via the alternative method of IMS-MDA. Todifferentiate it from conventional metagenomics sequencing without selective analyteconcentration, the shotgun sequencing of IMS-MDA products was termed quasimeta-genomics sequencing in this study. We further evaluated the method with Salmonella-spiked iceberg lettuce, black peppercorns, and peanut butter, as well as with naturallycontaminated retail chicken parts. Finally, we demonstrated the rapid detection andphylogenetic identification of Salmonella from a lettuce sample using quasimeta-genomics sequencing on a MinION device (Oxford Nanopore Technologies, Oxford, UK).

RESULTSComparison of culture enrichment methods. Both buffered peptone water (BPW)

(23) and Rappaport-Vassiliadis (RV) broth (24) have been used to enrich Salmonella fromchicken. The preenrichment in BPW followed by a selective enrichment in RV wasreported to increase the sensitivity of PCR detection of Salmonella in poultry (23). Eachmedium alone and the combination of both were evaluated to identify optimalconditions for increasing the abundance of S. enterica serotype Enteritidis relative tobackground flora on raw chicken breast. Real-time PCR threshold cycles (CTs) were usedto estimate the relative abundance of S. Enteritidis (21). The CT values were obtainedfrom real-time PCR assays using DNA extracted from enrichment cultures as the PCRtemplates. After enrichment, S. Enteritidis cells were enumerated on xylose-lysine-tergitol-4 (XLT) agar that is selective for Salmonella. The level of microorganisms afterenrichment, including both S. Enteritidis and background flora, was estimated ontryptic soy agar (TSA). As shown in Table S1 in the supplemental material, while BPWwas most effective in enriching S. Enteritidis by yielding the lowest CT value and thehighest S. Enteritidis count on XLT, it also resulted in the highest level of backgroundflora as measured by the difference between CFU counts on TSA and XLT. Thecombination of BPW and RV broth was least effective in enriching S. Enteritidis relativeto background flora as indicated by the highest CT value. Therefore, RV broth wasselected for S. Enteritidis enrichment prior to IMS and MDA because of its balancedperformance in enriching S. Enteritidis and in suppressing the excessive growth ofbackground flora.

Effects of IMS, MDA, and IMS-MDA on recovering the S. Enteritidis genome byshotgun sequencing. After culture enrichment, IMS was used to selectively capture S.Enteritidis cells, and MDA was used to generate DNA from captured cells for shotgunsequencing. Their individual and combined effects on improving the sequencing yieldof S. Enteritidis among chicken and microbial DNAs were assessed. When IMS was

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performed alone without MDA, the DNA extracted from cells that bound to immuno-magnetic beads was insufficient for sequencing (below the 10-pg/�g quantificationlimit of the Qubit HS dsDNA assay). When MDA was used, alone or in combination withIMS, all the resulting DNA samples enabled the construction of libraries for IlluminaMiSeq sequencing. The sequencing results were evaluated by multiple metrics asshown in Table 1. The raw reads from all the MDA and IMS-MDA samples enabled anaccurate serotype prediction using SeqSero (3). When MDA was used alone without IMSafter 12 h of RV broth enrichment, only an average of 4.74% of all sequencing readswere classified as Salmonella. In contrast, using IMS in conjunction with MDA afterenrichment substantially increased the percentage of Salmonella reads to an average of48.14%. The increased sequencing output of Salmonella by IMS-MDA led to substantialimprovements in the sequencing parameters for the S. Enteritidis genome. The se-quencing depth normalized by 100 million bases of sequencing data increased from1.01� by MDA to 9.82� by IMS-MDA. The N50 of a draft S. Enteritidis genome assemblyusing metagenomically classified Salmonella reads increased by 31-fold with the use ofIMS-MDA instead of just MDA after RV broth enrichment. The values of normalizedsequencing depth and N50 were equivalent to those obtained by WGS of S. Enteritidisgenomes prepared from pure cultures (25).

IMS-MDA shortened culture enrichment for quasimetagenomics detection of S.Enteritidis. To evaluate how IMS-MDA could improve the selective concentration ofSalmonella in comparison to that by culture enrichment alone, we further sequenced (i)DNA samples prepared immediately after S. Enteritidis inoculation on chicken breast(�1 CFU/g) and after RV broth enrichment of the inoculated samples for 4, 8, 12, and24 h, and (ii) IMS-MDA products after RV broth enrichment for 4, 8, and 12 h. As shownin Fig. 1A and in Table 1, the percentage of Salmonella organisms in the chickenmicrobiome (i.e., Salmonella abundance) increased slowly in the first 12 h of RV brothenrichment and rose to only 18.00% after culturing for 24 h. In comparison, IMS-MDAtreatment after 4 h of enrichment increased Salmonella abundance to 31.49%. Further-more, RV broth enrichment alone for 12 h enabled only 11.04% of the target S.Enteritidis genome to be sequenced, while IMS-MDA was able to recover 21.61% of thegenome after only 4 h of enrichment and almost the entire genome (99.09%) after 12h of enrichment (Fig. 1B and Table 1). IMS-MDA also improved the overall Salmonellasequencing output among all sequencing reads, including those from chicken DNA.Forty-eight percent of all sequencing reads were classified as Salmonella after 12 h ofRV broth enrichment followed by IMS-MDA compared with 16.74% after 24 h of RV

TABLE 1 Effect of IMS and MDA on selective concentration of Salmonella

Sample prepna CT

Output(Mb)b

Coverage(%)c

Depthratiod N50

e SerotypeSalmonellareads (%)f

Salmonellaabundance (%)g

RV12-MDAh 20.12 725 96.26 1.01 5106 Enteritidis 4.74 96.37RV12-IMS-MDAh 17.25 606 99.09 9.82 156488 Enteritidis 48.14 99.35RV4-IMS-MDAh 22.67 546 21.61 0.12 N/A Enteritidis 0.59 31.49RV8-IMS-MDAh 24.21 607 67.60 0.78 2173 Enteritidis 3.83 54.63RV0 NAi 140 0.27 0.00 NA NA 0.02 0.05RV4 NA 307 0.37 0.00 NA NA 0.01 0.03RV8 NA 170 0.42 0.01 NA NA 0.03 0.18RV12h 25.55 162 11.04 0.10 576 NA 0.49 1.22RV24h 14.1 254 98.87 3.60 34048 Enteritidis 16.74 18.00aAll samples were inoculated with S. Enteritidis at �1 CFU/g; RV12, enrichment in RV broth for 12 h; RV12-IMS-MDA, IMS-MDA treatment after 12 h of RV brothenrichment.

bTotal output size (million bases) of raw reads per sample.cPercentage of S. Enteritidis reference genome (NCBI reference sequence NC_011294.1) that was mapped by sequencing reads.dAverage depth of sequencing was calculated as the ratio between the total size of Salmonella sequences per 100 million bases of sequencing data and the size ofthe S. Enteritidis reference genome.

eN50 was calculated from de novo assemblies of sequencing reads classified as Salmonella.fPercentage of Salmonella reads among all sequencing reads.gPercentage of Salmonella reads among all bacterial reads.hAverage of two replicate samples.iNA, no result was obtained. For serotyping, the result was recorded as NA unless both replicates were serotyped.

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broth enrichment alone (Fig. 1C and Table 1). These results showed that IMS-MDA, a 2-to 3-h process, could reduce culture enrichment by at least 12 h as evaluated bydifferent descriptive measures.

Detection and high-fidelity subtyping by shotgun sequencing following IMS-MDA. The ability of the quasimetagenomics approach to distinguish the spiked analytefrom other S. Enteritidis strains was evaluated using the Center for Food Safety andApplied Nutrition (CFSAN) SNP pipeline (26). In addition to the raw chicken breastsamples that were inoculated with the S. Enteritidis strain at �1 CFU/g as previouslydescribed, samples with additional inoculum levels at �0.1 and 10 CFU/g were pre-pared and analyzed. An uninoculated sample was enriched for 12 h before going

FIG 1 Comparison of quasimetagenomics sequencing performance using different sample preparation methods. (A) Percentages ofsequences from Salmonella and other individual genera among all microbial sequences generated by sequencing. Results from varioussample preparation methods were evaluated. RV_8h, enrichment by RV broth for 8 h; RV-IMS-MDA_4h, enrichment by RV broth for 4 hfollowed by IMS and MDA. (B) Percentages of the S. Enteritidis (SE) reference genome that were sequenced by the quasimetagenomicsapproach using DNA samples prepared from RV broth enrichment alone and RV broth enrichment followed by IMS-MDA. (C) Percentagesof Salmonella reads among all sequencing reads, including host/chicken DNA. DNA samples were prepared from RV broth enrichmentalone and RV broth enrichment followed by IMS-MDA. In all samples, �1 CFU/g of S. Enteritidis was inoculated in each 25-g aliquot ofraw chicken breast.

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through the entire IMS-MDA and shotgun sequencing process as a negative control.The sample was further confirmed to be Salmonella negative by culture enrichment(data not shown). The results from all the samples are summarized in Table 2.

An average of 569 Mb of sequences was generated from the inoculated samples byshotgun sequencing on an Illumina MiSeq instrument, which accounted for �5% of thetotal output of a MiSeq run (MiSeq reagent kit V3, according to the manufacturer’sspecifications).

Accurate serotype predictions using the sequencing reads were achieved for all theinoculated samples except when the lowest inoculation level (0.1 CFU/g) was coupledwith the shortest culture enrichment duration (4 h). The lowest sequencing coveragepermitting serotyping from Illumina reads was 21.61%. At least 10% of the reference S.Enteritidis genome was recovered by quasimetagenomics sequencing of the inoculatedsamples. The minimum sequencing coverage of an inoculated sample was 10.72%,which was obtained at the lowest inoculum level of 0.1 CFU/g with shortest cultureenrichment of 4 h. When 12 h of culture enrichment was performed, more than 90% ofthe S. Enteritidis genome was mapped by sequencing reads at all inoculation levels. Incontrast, 0.02% of the reference genome was mapped by the sequencing reads fromthe negative-control sample.

For each inoculated sample, a core genome SNP phylogeny was constructed toinclude the quasimetagenomics sample and a total of 52 S. Enteritidis isolates repre-senting 16 major outbreaks and 3 sporadic cases in the United States between 2001and 2012 (4). As shown in Fig. 2, tight clustering of the quasimetagenomics sample(target) and the WGS sample of the spiked strain (reference) was achieved in all the ninecombinations of inoculation levels and culture enrichment durations, indicating theequivalence of the two methods in supporting core-genome SNP typing. When spikedchicken samples were culture enriched for 12 h, a perfect match between each pair ofquasimetagenomics and WGS samples was observed with a 0-SNP distance in between(Fig. 2). Besides the clustering of the quasimetagenomics and WGS samples, the rest ofthe phylogenetic tree was congruent across all the trials. These results suggest thathigh-fidelity subtyping with phylogenetic discrimination can be achieved by the

TABLE 2 Quasimetagenomics sequencing of S. Enteritidis from raw chicken breast at different inoculation levels and after differentculture enrichment durations

Sample prepna

Inoculum(CFU/g) CT

Output(Mb)b

Coverage(%)c

Depthratiod N50

e SerotypeSalmonellareads (%)f

Salmonellaabundance (%)g

4-h enrichmentRV4-IMS-MDA 0.1 28.76 487 10.72 0.08 NAh NA 0.38 18.37RV4-IMS-MDA 1 22.67 546 21.61 0.12 NA Enteritidis 0.59 31.49RV4-IMS-MDA 10 20.08 480 72.66 0.64 1,461 Enteritidis 3.15 68.49

8-h enrichmentRV8-IMS-MDA 0.1 25.52 597 33.13 0.16 NA Enteritidis 0.77 39.95RV8-IMS-MDA 1 24.21 607 67.60 0.78 2,173 Enteritidis 3.83 54.63RV8-IMS-MDA 10 19.64 583 99.04 8.23 104,352 Enteritidis 39.8 99.46

12-h enrichmentRV12-IMS-MDA 0.1 19.73 515 92.92 4.48 71,749 Enteritidis 21.66 97.77RV12-IMS-MDA 1 17.25 606 99.09 9.82 156,488 Enteritidis 48.14 99.35RV12-IMS-MDA 10 16.83 783 99.10 11.46 337,433 Enteritidis 54.76 99.55

Negative control NA NA 833 0.02 0.00 NA NA 0.15 0.15aAll results (except for the negative control) are reported as the averages from two replicates.bTotal output size (million bases) of raw reads per sample.cPercentage of S. Enteritidis reference genome (NCBI reference sequence NC_011294.1) that was mapped by sequencing reads.dAverage depth of sequencing was calculated as the ratio between the total size of Salmonella sequences per 100 million bases of sequencing data and the size ofthe S. Enteritidis reference genome.

eN50 was calculated from de novo assemblies of sequencing reads classified as Salmonella.fPercentage of Salmonella reads among all sequencing reads.gPercentage of Salmonella reads among all bacterial reads.hNA, no result was obtained. For serotyping, the result was recorded as NA unless both replicates were serotyped.

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quasimetagenomics approach with culture enrichment for 12 h or shorter, even whenthe contamination level was low (�0.1 CFU/g).

Detection and subtyping of Salmonella from unspiked retail raw chicken meat.The performance of the quasimetagenomics approach was further assessed by analyz-ing naturally contaminated retail chicken samples. As opposed to spiked samples, thenaturally contaminated samples were retail products that had been contaminated bySalmonella during production. A total of 76 retail chicken part samples (25-g aliquots),including breasts (n � 24), wings (n � 27), thighs (n � 12), drumsticks (n � 9), groundchicken (n � 2), gizzards (n � 2), and hearts (n � 2), were screened for Salmonella byRV broth enrichment. In parallel, IMS-MDA real-time PCR was performed after 4, 8, 12,and 24 h of enrichment (21). Salmonella was isolated from three wing samples byculture enrichment. WGS of the isolated strains was performed, and their serotypeswere determined to be Enteritidis (sample A), Typhimurium (sample B), and Heidelberg(sample C) using WGS data (Table 3).

The same three samples were also determined to be Salmonella positive by IMS-MDA real-time PCR and were further analyzed using a three-tube most probablenumber (MPN) method (Table 3). Using IMS-MDA real-time PCR, Salmonella was firstdetected after 8 h of enrichment in sample A and after 24 h of enrichment in samples

FIG 2 Phylogenetic clustering of the spiked chicken breast samples sequenced by the quasimetagenomics method (target) on an Illumina MiSeq platform andthe genomes of recent outbreak and sporadic strains. The WGS of the spiked strain (reference) is also included. Each of the 9 dotted-line boxes shows thehighlighted part of the respective tree that includes the target and reference and corresponds to a specific combination of inoculum level (0.1, 1, or 10 CFU/g)and RV broth enrichment time (4, 8, or 12 h). Bars represent unit distances of 2, 5, or 50 SNPs.

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B and C. The longer enrichment time required by samples B and C was likely due to thelow level of Salmonella contamination (MPN of �3/g) compared with that in sample A(MPN of 43/g). Quasimetagenomics sequencing was performed on selected IMS-MDAproducts prepared from positive wing samples. As shown in Table 3 and Fig. S1, correctserotyping (Enteritidis and Typhimurium) and accurate phylogenetic placement wereachieved from sample A and sample B. Sample C had a low sequencing coverage of12.53%, which did not permit serotyping and strain-level phylogenetic placement (datanot shown). Instead, the genome distance between sample C and a set of 258 completeSalmonella reference genomes of 57 serotypes was estimated using Mash (27). Theeight closest genomes to sample C were all of serotype Heidelberg (see Table S2),supporting the detection and preliminary identification of a Heidelberg isolate fromthis sample.

Detection and subtyping of S. Enteritidis from other selected food samples. Inaddition to raw chicken parts, the IMS-MDA-shotgun sequencing method was furtherevaluated with other selected food samples, including lettuce, black peppercorn, andpeanut butter, all of which were linked to recent Salmonella outbreaks (28–30). With 12h of culture enrichment, strain-level high-fidelity subtyping was achieved in bothlettuce and peppercorn samples at all inoculation levels (�0.1, 1, and 10 CFU/g) asshown by the clustering of IMS-MDA shotgun sequencing and in WGS samples with a0- or 1-SNP distance (Table 4; see also Fig. S2). While IMS-MDA enabled a real-time PCR

TABLE 3 Quasimetagenomics detection and serotyping of Salmonella in unspiked raw chicken parts

Sample prepn MPN/g CT

Output(Mb)a

Coverage(%)b

Depthratioc N50

d SerotypeSalmonellareads (%)e

Salmonellaabundance (%)f

Sample ARV8-IMS-MDA 43 23.30 227 13.31 0.41 665 Enteritidis 1.74 9.87RV12-IMS-MDA 43 17.60 248 61.00 0.88 731 Enteritidis 4.08 8.31

Sample BRV24-IMS-MDA �3 22.20 245 89.25 1.74 2,121 Typhimurium 8.26 9.79

Sample CRV24-IMS-MDA �3 25.24 289 12.53 0.31 2,169 NAg 1.35 2.41

aTotal output size (million bases) of raw reads per sample.bPercentage of S. Enteritidis reference genome (NCBI reference sequence NC_011294.1) that was mapped by sequencing reads.cAverage depth of sequencing was calculated as the ratio between the total size of Salmonella sequences per 100 million bases of sequencing data and the size ofthe S. Enteritidis reference genome.

dN50 was calculated from de novo assemblies of sequencing reads classified as Salmonella.ePercentage of Salmonella reads among all sequencing reads.fPercentage of Salmonella reads among all bacterial reads.gNo result was obtained, but was determined as serotype Heidelberg by WGS.

TABLE 4 Quasimetagenomics detection and serotyping of S. Enteritidis on inoculated black pepper and lettuce samples

Sample andinoculum (CFU/g) CT

Output(Mb)a

Coverage(%)b

Depthratioc N50

d SerotypeSalmonellareads (%)e

Salmonellaabundance (%)f

Black pepper0.1 17.30 199 99.06 20.63 226,848 Enteritidis 97.58 99.831 18.70 343 99.10 20.52 117,116 Enteritidis 96.28 99.2710 18.70 385 99.11 20.62 7,544 Enteritidis 96.22 99.57

Lettuce0.1 19.70 345 98.76 8.21 49,289 Enteritidis 38.33 99.121 16.20 332 99.06 19.40 70,588 Enteritidis 90.49 99.9110 15.50 354 99.08 20.65 175,495 Enteritidis 96.49 99.93

aTotal output size (million bases) of raw reads per sample.bPercentage of S. Enteritidis reference genome (NCBI reference sequence NC_011294.1) that was mapped by sequencing reads.cAverage depth of sequencing was calculated as the ratio between the total size of Salmonella sequences per 100 million bases of sequencing data and the size ofthe S. Enteritidis reference genome.

dN50 was calculated from de novo assemblies of sequencing reads classified as Salmonella.ePercentage of Salmonella reads among all sequencing reads.fPercentage of Salmonella reads among all bacterial reads.

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detection of S. Enteritidis from peanut butter samples at all inoculation levels after 12h of culture enrichment (data not shown), the CT values were 25 or higher, andinsufficient DNA samples were obtained for shotgun sequencing. The high fat contentin peanut butter likely compromised the effective capture of S. Enteritidis by IMS beads.

Rapid quasimetagenomics detection and subtyping of S. Enteritidis from let-tuce using MinION sequencing. IMS-MDA products prepared after 12 h of cultureenrichment from a spiked lettuce sample (1 CFU/g) were sequenced on a MinIONdevice. Sequencing data were collected hourly until the full run finished after 48.5 h.The same sample had been sequenced on a MiSeq platform (Table 4). After 1.5 h ofsequencing, a total of 14,760 one direction (1D) and two direction (2D) reads with anaverage length of 2,362 bp were generated. These reads covered 65.19% of the S.Enteritidis reference genome and enabled an accurate prediction of its serotype asEnteritidis (see Table S3). Using core-genome SNP typing, the MinION quasimeta-genomics sample was accurately placed on the phylogenetic tree that included 52previously described outbreak and clinical S. Enteritidis isolates. As shown in Fig. 3, the1.5-h MinION sample clustered closely with the WGS reference of the inoculated isolate.Similar results were obtained using MinION data after 48.5 h of sequencing (Fig. 3),which contained 197,070 1D and 2D reads with an average length of 2,388 bp. The SNPdistances between the quasimetagenomics sample and the WGS reference were 70 and65 after 1.5 h and 48.5 h of MinION sequencing, respectively.

Correlation between CT value and sequencing coverage. Prior to shotgun se-quencing on an Illumina MiSeq instrument, all the IMS-MDA processed samples (n �

28) in this study were analyzed by real-time PCR. The resulting CT values displayed apositive correlation with shotgun sequencing coverage (R2 � 0.76) (Fig. 4). Thisobservation suggests that the CT value is a useful indicator of target genome output byshotgun sequencing. When CT values were lower than 25, the majority (�50%) of theS. Enteritidis genome was likely to be sequenced. Serotype prediction from rawsequencing reads was successful in every sample tested in the study when the CT valuewas below 26. Therefore, CT values can be used as a performance parameter fordeveloping and optimizing the quasimetagenomics method or as a quality checkbefore committing to sequencing.

DISCUSSION

The conventional metagenomics approach relies on deep sequencing to identifylow-abundant microbial species directly from environmental samples. This strategy canbe impractical, if not ineffective, for detecting low levels of bacterial pathogen con-

FIG 3 Phylogenetic clustering of a spiked lettuce sample sequenced by the quasimetagenomics methodon a MinION device after 1.5 h (target_1.5 h) and 48 h (target_48.5 h) of sequencing. The WGS of thespiked strain (reference) is also included. Bars represent a unit distance of 100 SNPs on the tree.

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taminants in food samples. As shown by previous studies (8–12), an adequate concen-tration of pathogen analytes prior to sequencing is critical for metagenomics identifi-cation of the pathogen sequences. Culture enrichment alone was used in these studiesto concentrate target pathogen cells. Given sufficient time, when the analyte rose tobecome a dominant species in the enrichment culture, nearly full recovery of theanalyte genome could be achieved from sequencing enriched samples. This enabled avariety of subtyping analyses to be performed on shotgun metagenomics data, gen-erating rich information about the analyte in addition to its detection. In this study, weimproved and accelerated the isolation-independent shotgun sequencing-based de-tection and subtyping of Salmonella from selected food samples using selective en-richment of the analyte genomic DNA by IMS-MDA real-time nanopore sequencing byMinION and streamlined bioinformatics analysis of sequencing data.

First, culture enrichment time was substantially shortened by IMS-MDA. Whilenecessary and effective in the microbial analysis of food samples, culture enrichmentalone can be time consuming, especially when low levels of pathogen contaminantsare present in food samples together with competing flora and, in some cases,antimicrobial substances. With an approximate detection sensitivity of �103 CFU/g(13), IMS enabled the selective capture of Salmonella cells before they reached highabundances in the enrichment culture. Subsequent MDA generated sufficient genomicDNA for shotgun sequencing from small amounts of captured cells. This methoddiffered from those of previous studies that focused on optimized media to shortentarget pathogen enrichment. For example, it was recently reported that nonselectivepreenrichment could reduce the levels of inoculated competitive bacteria, enabling anearly Salmonella recovery (22). The shorter enrichment time enabled by IMS-MDA alsohelped address culture enrichment biases unfavorable for Salmonella detection, such asthe microbiota shift from Proteobacteria, which includes Salmonella, to Firmicutes afterextended (24 h) culturing (11, 12, 31). As shown in Fig. 1A and B, when using RV brothenrichment alone, sharp increases of both sequencing coverage and percentage ofSalmonella reads occurred between 12 h and 24 h of culturing, indicating the start andcontinuation of the exponential phase of the Salmonella growth cycle. IMS-MDAenabled strain-level phylogenetic placement of the spiked isolate after only 4 h ofenrichment (Fig. 2), likely before the majority of S. Enteritidis cells entered the expo-nential phase. After 12 h of enrichment when the S. Enteritidis population appeared tobe at the beginning or at an early stage of exponential phase, IMS-MDA led to 99.09%

FIG 4 Positive correlation between percentages of the target genome sequenced by the quasimetag-enomics approach (x axis) and the CT values from real-time PCR analysis of the IMS-MDA products (y axis).A total of 28 samples were analyzed.

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coverage and a 9.82� average sequencing depth of the S. Enteritidis genome (Table 1).In comparison, an only 3.60� average sequencing depth was obtained by sequencingthe metagenome of the 24-h enrichment culture without IMS-MDA (Table 1). Besidesthe demonstrated efficiency in selective concentration of Salmonella genomic DNA,both IMS and MDA are mature techniques featuring acceptable costs, rapid turnaround,and straightforward procedures. IMS is included in the Food Safety and InspectionService (FSIS) MLG method for the selective capture of E. coli O157:H7 and non-O157Shiga toxin-producing E. coli. MDA has been widely used to isothermally amplify lowconcentration DNA samples for metagenomics sequencing (8).

As shown in Fig. 2, the SNP distance between the quasimetagenomics sample(target) and the WGS of the inoculated strain (reference) was dependent upon inocu-lation level and enrichment time. A perfect match (i.e., 0-SNP distance) between thetarget and the reference was observed when 12-h enrichment was performed regard-less of the inoculation level and when 8-h enrichment was performed with a 10 CFU/ginoculum (Fig. 2). In such cases, the genome coverage by quasimetagenomics sequenc-ing was above 90% (Table 2). Therefore, we recommend the use of genome coverageas an empirical quality metric to interpret quasimetagenomics sequencing data, espe-cially when high-fidelity SNP typing is needed, such as during outbreak investigations.Our results suggested that when over 90% of genome coverage was achieved, thequasimetagenomics sequencing data were equivalent to those of WGS of pure culturesfor genome-wide SNP typing. Totals of 5 (8-h enrichment/0.1 CFU/g inoculum), 6 (8-henrichment/1 CFU/g inoculum), and 7 (4-h enrichment/10 CFU/g inoculum) SNPs wereidentified between the target and the reference (Fig. 2) when the genome coverageranged from 33% to 73% (Table 2). While a SNP distance smaller than 10 SNPs wascommonly used in surveillance and outbreak investigations to determine epidemio-logically related isolates (32, 33), caution should be taken when evaluating the SNPdistance obtained from quasimetagenomics data when the genome coverage is lessoptimal. When low inoculation levels (0.1 and 1 CFU/g) were combined with theshortest enrichment duration of 4 h, only a fraction of the S. Enteritidis genome wasrecovered (11% and 22%, respectively) (Table 2). SNP distances obtained from such lowgenome coverages may not be used as a reliable quantitative measure of geneticrelatedness. Despite this, the target and the reference still clustered among sampledoutbreak and sporadic isolates (Fig. 2), suggesting that enough SNPs were captured toreconstruct the phylogeny of the analyzed isolates. This finding is consistent with aprevious report showing that partial SNP genotypes obtained from low-coveragegenome data sets enabled an accurate phylogenetic placement of bacterial strains (34).Similar results were obtained when analyzing naturally contaminated chicken samples.Robust genome-wide SNP typing was possible when 12- and 24-h enrichment wasperformed (Fig. S1), leading to 61% and 89% genome coverage, respectively (Table 3).

By concentrating Salmonella cells and amplifying the target genomic DNA, theIMS-MDA technique significantly changed the taxonomic composition of the foodmetagenome (Fig. 1A). Shotgun sequencing after IMS-MDA was hence termedquasimetagenomics sequencing to reflect the much reduced microbial diversity due tothe IMS-MDA treatment.

The quasimetagenomics approach was shown to be effective in detecting andsubtyping naturally occurring Salmonella of three serotypes in retail chicken samples.For two positive samples, an extended culture enrichment up to 24 h was needed forphylogenetic placement using quasimetagenomics sequencing data. Salmonella con-tamination levels in both samples were determined to be low at an MPN of �3/g (MLGappendix 2.05). For the third positive sample with an MPN of 43/g, 8 h of enrichmentwas sufficient to enable both serotyping and phylogenetic placement of the Salmonellacontaminant. These results stressed the importance of culture enrichment. Key perfor-mance parameters of quasimetagenomics sequencing, such as the limit of detectionand coverage of the analyte genome, were affected by the effectiveness of cultureenrichment, which increased with enrichment duration. The duration of culture enrich-ment required to achieve a certain limit of detection depends on multiple factors, such

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as the food microbiome composition, the type of food matrix, the length of the lagphase, and the growth dynamics of the target pathogen (10). Therefore, optimizationsof culture enrichment and sample preparation methods are needed for specific foodsamples and pathogens.

Second, further acceleration of the quasimetagenomics analysis was achieved byusing nanopore real-time sequencing on a MinION device. The total turnaround timefrom the collection of the spiked lettuce sample to the phylogenetic placement of theinoculated strain was less than 24 h, including 12 h for culture enrichment, 3 h forIMS-MDA, 4 h for sequencing library preparation, and 1.5 h for sequencing. Notably,extending MinION sequencing to a complete run for 48.5 h resulted in only a minorimprovement in core SNP typing accuracy, with the SNP distance between thequasimetagenomics sample and the WGS of the inoculated strain reduced from 70 to65. The error rate of MinION long reads was still substantially higher than that ofIllumina short reads. The same quasimetagenomics sample sequenced on a MiSeqplatform had a 0-SNP distance compared with the WGS reference (Fig. S2). Despitethese errors, the MinION reads acquired after only 1.5 h of quasimetagenomics se-quencing supported a robust phylogenetic identification of the spiked strain, indicatingMinION=s potential as a rapid and nimble alternative to Illumina platforms for thescreening of Salmonella from food samples. In comparison, a full Illumina MiSeq runtakes �39 h to complete and generates an output of �8 Gb (250-bp paired-end reads,according to the manufacturer’s specifications), which is enough to accommodate �14quasimetagenomics samples based on the average size of the MiSeq sequencedsamples (569 Mb) in this study. Therefore, sequencing on Illumina platforms is cost andtime effective when operated in a high-throughput manner.

Finally, standard bioinformatics tools and pipelines were used for sequencing dataanalyses. Regardless of the sequencing platforms, taxonomic identification was per-formed on raw sequencing reads using Kraken (35), Salmonella serotyping was per-formed using SeqSero (3), and strain-level subtyping was performed using the CFSANSNP pipeline (26). After the extraction of Salmonella reads according to the taxonomiclabels assigned by Kraken, the analytical workflow largely overlaps with that of WGS-based subtyping of Salmonella, an increasingly routine practice for Salmonella surveil-lance. In fact, the selective concentration of Salmonella genomic DNA by IMS-MDAreduced the microbial diversity of the quasimetagenome to facilitate bioinformaticsanalysis using the aforementioned tools.

As a limitation of this study, we did not test a sample that had been cocontaminatedby different strains, as in the case of a recent papaya outbreak that involved Salmonellastrains of multiple serotypes (https://www.cdc.gov/salmonella/kiambu-07-17/index.html). The potential and limits of subtyping multiple strains in the same sample usinga metagenomics approach need to be investigated in future studies.

MATERIALS AND METHODSMicroorganism. A S. Enteritidis strain (CFS039) was isolated from a poultry source in Georgia and

used throughout the study. Cultures of the S. Enteritidis strain isolated from a poultry source wereprepared by growing the stock culture in tryptic soy broth ([TSB] Difco Laboratories, Detroit, MI)overnight at 37°C before inoculation. To obtain viable Salmonella counts, 10-fold serial dilutions ofovernight cultures were made in phosphate-buffered saline ([PBS] pH 7.2; Amresco, Cleveland, OH), and100 �l of the dilutions was plated on TSA (Difco Laboratories). The plates were incubated at 37°Covernight, and then single colonies were enumerated from the appropriate dilutions.

Inoculation of S. Enteritidis to chicken breast, lettuce, black peppercorns, and peanut butterand sample preparation. Raw chicken breast, iceberg lettuce, black peppercorns, and peanut butterwere purchased from grocery stores in Athens, Georgia, on 22 May 2017. According to MLG 4.09, 25-gportions of food samples were aseptically placed in sterile Whirl-pak filter bags (Nasco, Fort Atkinson, WI)and then inoculated with 2 ml of S. Enteritidis inocula of different concentrations. Inocula were preparedfrom 10-fold serial dilutions of overnight 37°C tryptic soy broth cultures in PBS. Each 2-ml inoculum wasevenly placed on the surface of each food sample in approximately 5 drops. Then, the inoculated foodsample within the Whirl-pak bag was hand massaged for 1 min to enable homogenous distribution ofthe inoculum. Uninoculated food samples were also prepared by adding 2 ml of PBS as negative controls.

Culture enrichment. To compare culture enrichment methods, chicken samples (25 g each) wereinoculated with S. Enteritidis at the level of �1 CFU/g of chicken. The samples were divided into threegroups according to different enrichment methods: (i) enrichment in 225 ml of buffered peptone water

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([BPW] Difco Laboratories) at 37°C for 12 h, (ii) enrichment in 225 ml of Rappaport-Vassiliadis (RV) broth(Oxoid, Basingstoke, Hampshire, UK) at 42°C for 12 h, and (iii) enrichment in 225 ml of BPW at 37°C for6 h followed by the transferring of 1 ml of enriched BPW culture to 10 ml of RV broth and incubating at42°C for 6 h. The samples were homogenized by hand massage for 30 s in 225 ml of BPW or RV broth.After incubating, enriched media were 10-fold serially diluted in PBS, and 100 �l of each of the dilutionswas plated on XLT and TSA. In addition, DNA was extracted from 1 ml of enriched medium using aDNeasy blood and tissue kit (Qiagen, Valencia, CA), and real-time PCR was performed for the relativequantification of Salmonella as previously described (18).

For sequencing, all food samples, including raw chicken breast, lettuce, black peppercorns, andpeanut butter (25 g each), inoculated with S. Enteritidis at the level of ca. 0.1, 1, and 10 CFU/g werehomogenized by hand massage for 30 s in 225 ml RV broth and incubated at 42°C for 12 h. Homogenatesof 50-ml aliquots were collected after 4, 8, and 12 h of enrichment.

IMS-MDA. Before IMS-MDA, the 50-ml homogenates were centrifuged at 100 � g for 10 min toremove solid debris. Then, each supernatant was carefully recovered and centrifuged at 3,000 � g for 10min to harvest the cell pellet. The pellet was resuspended in 5 ml of BPW.

IMS and MDA were performed using anti-Salmonella Dynabeads (2.5-�m diameter; Thermo FisherScientific, Waltham, MA, USA) and an Illustra GenomiPhi V2 DNA amplification kit (GE Healthcare LifeSciences, Piscataway, NJ, USA), respectively, as previously described (18). For IMS, 1 ml of the resus-pended cell pellet in BPW was incubated with 20 �l of beads at room temperature using a rotating mixer(Thermo Fisher Scientific) for 30 min. After incubating, the bead-Salmonella complexes were magneticallyseparated from the suspension using a magnetic particle concentrator (Thermo Fisher Scientific) for 3min, and then washed three times with 1 ml of PBS containing 0.05% (vol/vol) Tween 20 (Thermo FisherScientific) to remove nonspecifically binding bacteria from the complex.

The bead-Salmonella complexes from IMS were resuspended in 9 �l of sample buffer and incubatedat 95°C for 3 min for denaturation for MDA. After cooling to 4°C on ice, 9 �l of reaction buffer and 1 �lof enzyme mix were added to each sample on ice to enable annealing of random hexamer primers. Thesample buffer, reaction buffer, and enzyme mix were supplied by the Illustra GenomiPhi V2 DNAamplification kit (GE Healthcare Life Sciences). After incubating at 30°C for 2 h for amplification, thesamples were heated to 65°C for 10 min to inactivate the �29 DNA polymerase and cooled to 4°C on ice.Then, the final products (approximately 20 �l) were stored at �20°C until they were used for real-timePCR and whole-genome sequencing.

Real-time PCR. For real-time PCRs, MDA product (2 �l) was added to 18 �l of a PCR mixture. Themixture contained TaqMan Universal PCR master mix (10 �l; Thermo Fisher Scientific), forward primer (2�l, 900 nM), reverse primer (2 �l, 900 nM), probe (2.5 �l, 250 nM), and distilled water (2 �l). Thesequences for the Salmonella-specific oligonucleotide primers and probe were designed to amplify a94-bp segment of the ttr gene (GenBank accession no. AF_282268) (27). An optimized real-time PCRprotocol was used that specified two holding periods, one at 50°C for 2 min and another at 95°C for 10min, followed by 40 cycles of 95°C for 15 s and 60°C for 60 s. The threshold cycle (CT), which is theintersection between each fluorescence curve and a threshold line, was calculated using StepOnereal-time PCR software version 2.0 (Thermo Fisher Scientific). Negative results corresponded to CT values�40 or samples with CT values higher than that of negative control.

Preparation of unspiked retail chicken part samples. A total of 76 chicken parts, including breasts(n � 24), wings (n � 27), thighs (n � 12), drumsticks (n � 9), ground chicken meats (n � 2), and gizzardsand hearts (n � 2), were purchased from grocery stores in Athens, Georgia, between 29 March and 23April 2017. Each sample (25 g) was homogenized in 225 ml of RV broth and incubated at 42°C for 24 h.Then, 50 ml from each of the homogenates was collected after 4, 8, 12, and 24 h of enrichment and usedfor IMS-MDA.

MPN and culture-based detection of Salmonella from unspiked chicken samples. A 3-tube MPNassay using 0.1, 0.01, and 0.001 ml was performed to estimate the Salmonella contamination levels ofthree Salmonella-positive wing samples according to the MPN procedure of the MLG with the modifi-cation of using 225 ml RV broth instead of BPW to rinse the samples, as RV broth was used as theenrichment broth in this study. Salmonella organisms were isolated by culture enrichment according toMLG 4.09 with the modification that preenrichment was carried out in RV broth at 42°C instead of in BPWat 37°C. After a 24-h preenrichment, aliquots of 0.1 ml RV broth cultures were transferred to 10 ml ofRappaport-Vassiliadis soya (RVS) broth (Oxoid, Basingstoke, Hampshire, UK) and Muller–Kauffmanntetrathionate–novobiocin (MKTTn) broth (Oxoid) and incubated for 24 h at 42°C. After the selectiveenrichment, a loopful of each enriched sample was streaked on differential media, XLT and Brilliant greensulfa agar ([BGS] contains 0.1% sodium sulfapyridine; Oxoid). The presumptive Salmonella colonies fromthe selective agar were plated on TSA, followed by confirmation using real-time PCR.

Shotgun sequencing on MiSeq. Sample DNA concentrations were determined using a Qubit BRdsDNA assay kit (Invitrogen). Concentrations were diluted to 0.2 ng/�l and libraries were preparedfollowing the Illumina Nextera XT DNA library prep kit reference guide with the following exceptions.Forty microliters of PCR product was transferred to a new MIDI plate, and 20 �l of AMPure XP beads(Beckman Coulter) was added to each well and incubated at room temperature for 5 min withoutshaking. After 80% ethanol washes, beads were allowed to air dry for 12 min. Then, the beads wereresuspended in 53 �l of reticulocyte standard buffer (RSB) and incubated at room temperature for 2 minwithout shaking.

The concentrations of sample libraries were determined using the Qubit dsDNA HS assay kit(Invitrogen), and libraries were diluted to a 2 nM concentration and combined in equal volumes to formthe pooled library. The pooled library was denatured to obtain a 10 pM final library according to the

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Illumina denature and dilute libraries guide protocol A. Six hundred microliters of the denatured 10 pMlibrary was loaded into the MiSeq reagent cartridge.

Shotgun sequencing on MinION. The DNA library was prepared according to the 2D low-inputgenomic DNA protocol for MinION (SQK-LSK208; Oxford Nanopore Technologies). Briefly, each IMS-MDAproduct was sheared using a Covaris g-tube (Covaris) to obtain 8-kb fragments. Fragments were endrepaired using an NEBNext Ultra II end-repair kit (New England BioLabs) and cleaned using AMPure XPbeads and two 70% ethanol washes. End-prepped DNA was mixed with a blunt/TA ligase master mix andPCR adapters, and then incubated at room temperature for 10 min. Samples were cleaned again withAMPure beads and two 70% ethanol washes. The adapted DNA was mixed with 2� LongAmp Taq mastermix (New England BioLabs) and a PCR was run for 18 cycles. The above-described cleaning steps and endrepair were performed on the resulting PCR products. A ligation reaction was performed using TA ligasemaster mix (New England BioLabs). Cleanup was performed using washed MyOne C1 beads (Invitrogen).Beads were pelleted on a magnetic rack and washed with BBB solution from the MinION SQK-LS208 kit.Finally, the library was eluted from the beads with the elution buffer supplied in the kit and quantifiedusing a Qubit fluorimeter.

The MinION flow cell was primed, and the DNA library was mixed with run buffer and library loadingbeads from the kit. The prepared library was added to the flow cell, and a 48-h sequencing run wasstarted in the MinKnow software. Once the sequencing run started, the reads were uploaded to theMetrichor analysis platform (Metrichor Ltd.) for base calling. The base-called reads were downloaded toa local database.

Sequencing read trimming, filtering, and classification. Trimmomatic (27) was used to removelow-quality reads. The leading three and the trailing three nucleotides were removed from the reads, anda 4-nucleotide sliding window was used to remove nucleotides from the 3= ends when the average Phredscore dropped below 20. Additionally, reads shorter than 50 bp were discarded after trimming. Trimmedand filtered reads were taxonomically classified using Kraken (35). Reads classified as Salmonella wereextracted for further analysis.

De novo assembly and serotyping. The extracted Salmonella reads were assembled using SPAdes(29) with the “– careful” option. QUAST (30) was used to evaluate the quality of the draft genomeassemblies and to determine the N50 value for each assembly. SeqSero (3) was used to predict Salmonellaserotype from the extracted Salmonella reads.

SNP detection and phylogenetic analysis. Core-genome SNPs were identified using the CFSAN SNPpipeline v0.8.0 with default quality filters (22). Specifically, the minimum base quality was 20, theminimum mapping quality was 15, and the minimum fraction of reads for SNP calls was 0.6. The genomesof S. Enteritidis strain P125109 (NCBI reference sequence NC_011294.1) and S. enterica serotype Typhi-murium strain SL1344 (NCBI accession FQ312003.1) were used as reference genomes for read mapping.Default pipeline settings were used for MiSeq reads. For MinION reads, read mapping was performedusing BWA-MEM (35) with the “-x ont2d=” option. A SNP matrix and alignment concatenated SNPs wereproduced with custom Python scripts from each quasimetagenomics or WGS sample processed by theCFSAN SNP pipeline. Finally, maximum likelihood (ML) phylogenetic trees were constructed using PhyML(33).

Accession number(s). Quasimetagenomics sequencing data from this study are available in the NCBISequence Read Archive (SRA) under accession number PRJNA404022.

SUPPLEMENTAL MATERIAL

Supplemental material for this article may be found at https://doi.org/10.1128/AEM.02340-17.

SUPPLEMENTAL FILE 1, PDF file, 0.6 MB.

ACKNOWLEDGMENTThis work was supported in part by the USDA National Institute of Food and

Agriculture Hatch project no. 1006141.

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