Dataset Information

Salmonella enterica and Escherichia coli in Wheat Flour: Detection and Serotyping by a Quasimetagenomic Approach Assisted by Magnetic Capture, Multiple-Displacement Amplification, and Real-Time Sequencing.

ABSTRACT: Food safety is a new area for novel applications of metagenomics analysis, which not only can detect and subtype foodborne pathogens in a single workflow but may also produce additional information with in-depth analysis capabilities. In this study, we applied a quasimetagenomic approach by combining short-term enrichment, immunomagnetic separation (IMS), multiple-displacement amplification (MDA), and nanopore sequencing real-time analysis for simultaneous detection of Salmonella and Escherichia coli in wheat flour. Tryptic soy broth was selected for the 12-h enrichment of samples at 42°C. Enrichments were subjected to IMS using beads capable of capturing both Salmonella and E. coli MDA was performed on harvested beads, and amplified DNA fragments were subjected to DNA library preparation for sequencing. Sequencing was performed on a portable device with real-time basecalling adaptability, and resulting sequences were subjected to two parallel pipelines for further analysis. After 1 h of sequencing, the quasimetagenomic approach could detect all targets inoculated at approximately 1 CFU/g flour to the species level. Discriminatory power was determined by simultaneous detection of dual inoculums of Salmonella and E. coli, absence of detection in control samples, and consistency in microbial flora composition of the same flour samples over several rounds of experiments. The total turnaround time for detection was approximately 20 h. Longer sequencing for up to 15 h enabled serotyping for many of the samples with more than 99% genome coverage, which could be subjected to other appropriate genetic analysis pipelines in less than a total of 36 h.IMPORTANCE Enterohemorrhagic Escherichia coli (EHEC) and Salmonella are of serious concern in low-moisture foods, including wheat flour and its related products, causing illnesses, outbreaks, and recalls. The development of advanced detection methods based on molecular principles of analysis is essential to incorporate into interventions intended to reduce the risk from these pathogens. In this work, a quasimetagenomic method based on real-time sequencing analysis and assisted by magnetic capture and DNA amplification was developed. This protocol is capable of detecting multiple Salmonella and/or E. coli organisms in the sample within less than a day, and it can also generate sufficient whole-genome sequences of the target organisms suitable for subsequent bioinformatics analysis. Multiplex detection and identification were accomplished in less than 20 h and additional whole-genome analyses of different nature were attained within 36 h, in contrast to the several days required in previous sequencing pipelines.

SUBMITTER: Forghani F

PROVIDER: S-EPMC7301854 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Salmonella enterica and Escherichia coli in Wheat Flour: Detection and Serotyping by a Quasimetagenomic Approach Assisted by Magnetic Capture, Multiple-Displacement Amplification, and Real-Time Sequencing.

Forghani Fereidoun F Li Shaoting S Zhang Shaokang S Mann David A DA Deng Xiangyu X den Bakker Henk C HC Diez-Gonzalez Francisco F

Applied and environmental microbiology 20200617 13

Food safety is a new area for novel applications of metagenomics analysis, which not only can detect and subtype foodborne pathogens in a single workflow but may also produce additional information with in-depth analysis capabilities. In this study, we applied a quasimetagenomic approach by combining short-term enrichment, immunomagnetic separation (IMS), multiple-displacement amplification (MDA), and nanopore sequencing real-time analysis for simultaneous detection of <i>Salmonella</i> and <i>E ...[more]

PMID: 32358002

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Project description:Salmonella enterica (S. enterica) is an important foodborne pathogen, causing food poisoning and human infection, and critically threatening food safety and public health. Salmonella typing is essential for bacterial identification, tracing, epidemiological investigation, and monitoring. Serotyping and multilocus sequence typing (MLST) analysis are standard bacterial typing methods despite the low resolution. Core genome MLST (cgMLST) is a high-resolution molecular typing method based on whole genomic sequencing for accurate bacterial tracing. We investigated 250 S. enterica isolates from poultry, livestock, food, and human sources in nine provinces of China from 2004 to 2019 using serotyping, MLST, and cgMLST analysis. All S. enterica isolates were divided into 36 serovars using slide agglutination. The major serovars in order were Enteritidis (31 isolates), Typhimurium (29 isolates), Mbandaka (23 isolates), and Indiana (22 isolates). All strains were assigned into 43 sequence types (STs) by MLST. Among them, ST11 (31 isolates) was the primary ST. Besides this, a novel ST, ST8016, was identified, and it was different from ST40 by position 317 C → T in dnaN. Furthermore, these 250 isolates were grouped into 185 cgMLST sequence types (cgSTs) by cgMLST. The major cgST was cgST235530 (11 isolates), and only three cgSTs contained isolates from human and other sources, indicating a possibility of cross-species infection. Phylogenetic analysis indicated that most of the same serovar strains were putatively homologous except Saintpaul and Derby due to their multilineage characteristics. In addition, serovar I 4,[5],12:i:- and Typhimurium isolates have similar genomic relatedness on the phylogenetic tree. In conclusion, we sorted out the phenotyping and genotyping diversity of S. enterica isolates in China during 2004-2019 and clarified the temporal and spatial distribution characteristics of Salmonella from different hosts in China in the recent 16 years. These results greatly supplement Salmonella strain resources, genetic information, and traceability typing data; facilitate the typing, traceability, identification, and genetic evolution analysis of Salmonella; and therefore, improve the level of analysis, monitoring, and controlling of foodborne microorganisms in China.

Project description:Until recently, traditional serology and the Kauffmann White Scheme (KWS) have been the gold standard for Salmonella serotyping. Whole Genome Sequencing (WGS) has now emerged as an alternative in this field. Serotype information remains a cornerstone in food safety and public health activities to reduce the burden of salmonellosis. At the same time, recent advances in WGS have improved the ability to perform advanced pathogen characterization while improving trace back investigations to determine the source of foodborne illness during outbreaks. Serovar prediction based on WGS can be performed using in silico data analysis tools. Three such tools have been developed: (a). Salmonella in silico Typing Resource (SISTR), (b). SeqSero, and (c). in silico 7-gene MLST ST (Multilocus Sequence Typing Sub-Typing) which was generated using the SISTR platform. Public health officials around the world are diligently working to validate these tools for replacing traditional surveillance methods to provide a more powerful approach for molecular epidemiology in support of public health investigations. In this study, we report a retrospective analysis of our laboratory inventory of 1,041 Salmonella isolates collected between 1999 and 2017. These isolates are of public health significance since they all came from either food, feed or environmental swabs. They were all serotyped by both traditional serology and WGS using an in silico SeqSero tool for serovar prediction. Both predicted identical Salmonella serotypes in 899 isolates (86.4% of the 1,041 Salmonella isolates). SeqSero assignments differed from traditional serological testing in 80 isolates (7.7%) and no serotype prediction was ascertained from 62 isolates (5.9%). This retrospective study is an excellent example of using WGS and SeqSero as a data analysis tool to predict Salmonella serotypes that can provide numerous advantages including molecular and genetic details regarding the characteristics of the Salmonella isolates compared to traditional KWS serotyping. In conclusion, it is evident that using WGS and in silico tools for Salmonella serotyping might someday replace traditional serotyping.

Dataset Information

Salmonella enterica and Escherichia coli in Wheat Flour: Detection and Serotyping by a Quasimetagenomic Approach Assisted by Magnetic Capture, Multiple-Displacement Amplification, and Real-Time Sequencing.

Publications

Salmonella enterica and Escherichia coli in Wheat Flour: Detection and Serotyping by a Quasimetagenomic Approach Assisted by Magnetic Capture, Multiple-Displacement Amplification, and Real-Time Sequencing.

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