Genotyping of Salmonella with lineage-specific genes: correlation with serotyping

Zhou, Qinghua; Li, Ren-Qing; Liu, Guirong; Liu, Shulin

doi:10.1016/j.ijid.2016.05.029

Cited by 21 publications

(22 citation statements)

References 31 publications

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“…In addition to these methods, several studies have further investigated the utility of lineage-specific gene markers for the identification of polyphyletic serovars [142][143][144]. However, we are not aware of any currently publicly available program that implements the findings from these studies.…”

Section: Serotyping Predictionmentioning

confidence: 99%

Typing methods based on whole genome sequencing data

et al. 2020

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Whole genome sequencing (WGS) of foodborne pathogens has become an effective method for investigating the information contained in the genome sequence of bacterial pathogens. In addition, its highly discriminative power enables the comparison of genetic relatedness between bacteria even on a sub-species level. For this reason, WGS is being implemented worldwide and across sectors (human, veterinary, food, and environment) for the investigation of disease outbreaks, source attribution, and improved risk characterization models. In order to extract relevant information from the large quantity and complex data produced by WGS, a host of bioinformatics tools has been developed, allowing users to analyze and interpret sequencing data, starting from simple gene-searches to complex phylogenetic studies. Depending on the research question, the complexity of the dataset and their bioinformatics skill set, users can choose between a great variety of tools for the analysis of WGS data. In this review, we describe the relevant approaches for phylogenomic studies for outbreak studies and give an overview of selected tools for the characterization of foodborne pathogens based on WGS data. Despite the efforts of the last years, harmonization and standardization of typing tools are still urgently needed to allow for an easy comparison of data between laboratories, moving towards a one health worldwide surveillance system for foodborne pathogens.

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Section: Serotyping Predictionmentioning

confidence: 99%

Typing methods based on whole genome sequencing data

et al. 2020

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“…Furthermore, genomics can be used as a gold standard to validate or refute user‐friendly typing schemes that are commonly used. A recent study devised a new MLST typing method for Salmonella and validated this method against a core genome phylogeny to demonstrate its utility in distinguishing strains …”

Section: Clinical Diagnosticsmentioning

confidence: 99%

“…A recent study devised a new MLST typing method for Salmonella and validated this method against a core genome phylogeny to demonstrate its utility in distinguishing strains. 166 Despite advances in genomic diagnostics, there is so far only one example in the literature of a patient outcome being improved by genomics in real time. 167 High-risk and time-sensitive infections, such as those in immune-compromised patients or sepsis, could benefit immensely from this technology, but moving real-time genomic diagnostics into clinics and public health laboratories will require overcoming several additional hurdles.…”

Section: Clinical Diagnosticsmentioning

confidence: 99%

Genomic epidemiology of multidrug‐resistant Gram‐negative organisms

Hawken

Snitkin

2018

Annals of the New York Academy of Sciences

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The emergence and spread of antibiotic-resistant Gram-negative bacteria (rGNB) across global healthcare networks presents a significant threat to public health. As the number of effective antibiotics available to treat these resistant organisms dwindles, it is essential that we devise more effective strategies for controlling their proliferation. Recently, whole-genome sequencing has emerged as a disruptive technology that has transformed our understanding of the evolution and epidemiology of diverse rGNB species, and it has the potential to guide strategies for controlling the evolution and spread of resistance. Here, we review specific areas in which genomics has already made a significant impact, including outbreak investigations, regional epidemiology, clinical diagnostics, resistance evolution, and the study of epidemic lineages. While highlighting early successes, we also point to the next steps needed to translate this technology into strategies to improve public health and clinical medicine.

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“…Among the tools implementing this method are Metric Oriented Sequence Typer (MOST) (8), which infers serovars from MLST, and SISTR (5), which can predict serovars based on phylogenetic clustering of core genome MLST (cgMLST) or based on a k-mer reference search (mash). Several studies have further investigated the utility of lineage-specific gene markers for the identification of polyphyletic serovars (9)(10)(11). However, we are not aware of any currently publicly available program that implements the findings from these studies.…”

mentioning

confidence: 99%

Performance and Accuracy of Four Open-Source Tools for In Silico Serotyping of Salmonella spp. Based on Whole-Genome Short-Read Sequencing Data

Uelze

Blettner

Deneke

et al. 2020

Appl Environ Microbiol

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We compared the performance of four open-source in silico Salmonella typing tools (SeqSero, SeqSero2, Salmonella In Silico Typing Resource [SISTR], and Metric Oriented Sequence Typer [MOST]) to assess their potential for replacing laboratory serological testing with serovar predictions from whole-genome sequencing data. We conducted a retrospective analysis of 1,624 Salmonella isolates of 72 serovars submitted to the German National Salmonella Reference Laboratory between 1999 and 2019. All isolates are derived from animal and foodstuff origins. We conducted Illumina short-read sequencing and compared the in silico serovar prediction results with the results of routine laboratory serotyping. We found the best-performing in silico serovar prediction tool to be SISTR, with 94% correctly typed isolates, followed by SeqSero2 (87%), SeqSero (81%), and MOST (79%). Furthermore, we found that mapping-based tools like SeqSero and SeqSero2 (allele mode) were more reliable for the prediction of monophasic variants, while sequence type and cluster-based methods like MOST and SISTR (core-genome multilocus sequence type [cgMLST]), showed greater resilience when confronted with GC-biased sequencing data. We showed that the choice of library preparation kit could substantially affect O antigen detection, due to the low GC content of the wzx and wzy genes. Although the accuracy of computational serovar predictions is still not quite on par with traditional serotyping by Salmonella reference laboratories, the command-line tools investigated in this study perform a rapid, efficient, inexpensive, and reproducible analysis, which can be integrated into in-house characterization pipelines. Based on our results, we find SISTR most suitable for automated, routine serotyping for public health surveillance of Salmonella. IMPORTANCE Salmonella spp. are important foodborne pathogens. To reduce the number of infected patients, it is essential to understand which subtypes of the bacteria cause disease outbreaks. Traditionally, characterization of Salmonella requires serological testing, a laboratory method by which Salmonella isolates can be classified into over 2,600 distinct subtypes, called serovars. Due to recent advances in whole-genome sequencing, many tools have been developed to replace traditional testing methods with computational analysis of genome sequences. It is crucial to validate that these tools, many already in use for routine surveillance, deliver accurate and reliable serovar information. In this study, we set out to compare which of the currently available open-source command-line tools is most suitable to replace serological testing. A thorough evaluation of the differing computational approaches is highly important to ensure the backward compatibility of serotyping data and to maintain comparability between laboratories.

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Genotyping of Salmonella with lineage-specific genes: correlation with serotyping

Abstract: Individual Salmonella lineages each have specific genes that can be used to differentiate Salmonella isolates on a phylogenetic basis.

Cited by 21 publications

References 31 publications

Typing methods based on whole genome sequencing data

Typing methods based on whole genome sequencing data

Genomic epidemiology of multidrug‐resistant Gram‐negative organisms

Performance and Accuracy of Four Open-Source Tools for In Silico Serotyping of Salmonella spp. Based on Whole-Genome Short-Read Sequencing Data

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