Evidence map›Paper›PMID 38884907›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

In Silico Typing and Identification Confirmation of Isolates.

Matheus de O Costa, Nahuel Fittipaldi

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Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Matheus de O CostaLarge Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK, Canada. matheus.costa@usask.ca.
Nahuel FittipaldiDépartement de pathologie et microbiologie, Faculté de médecine vétérinaire, Université de Montreal, Montreal, QC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Streptococcus suis is an important zoonotic pathogen causing severe infections in pigs and humans. Serotyping of S. suis strains is crucial for epidemiological surveillance, outbreak investigations, and understanding the pathogenesis of this bacterium. Here, we describe a step-by-step approach that enhances a previously developed pipeline by utilizing a computational script for efficient and accurate typing of S. suis strains. The pipeline is implemented in Perl programming language and leverages the Short Read Sequence Typing for Bacterial Pathogens (SRST2) tool. It integrates various bioinformatics techniques and utilizes multiple databases, including a serotype database, cpsH confirmation database, multi-locus sequence typing (MLST) database, recN species-specific gene database, and virulence gene database. These databases contain comprehensive information on S. suis serotypes, genetic markers, and virulence factors. The script can utilize paired-end or single-end fastq files as input and first confirms the species by sequence read data aligning to the recN gene, ensuring the accurate identification of S. suis strains. The pipeline next performs MLST typing and virulence factor identification using SRST2 while in a parallel processes it performs in silico serotyping of the strains. The pipeline offers a streamlined and semiautomated approach to serotyping S. suis strains, facilitating large-scale studies and reducing the manual effort required for data analysis.

Indexed as

Computational BiologyMultilocus Sequence TypingSoftwareStreptococcus suisAnimalsBacterial Typing TechniquesComputer SimulationDatabases, GeneticHumansSerotypingStreptococcal InfectionsSwineVirulence FactorsVirulence FactorsBioinformaticsGenomic analysisHigh-throughput pipelineMLSTSerotypingSRST2Streptococcus suisVirulence factors

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.