Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
134
datasets available to search
ShareScore release 0.9.0
Dataset results
134 results for “Salmonella enterica”
Genome assemblies and respective wg/cgMLST profiles of a diverse dataset comprising 1,434 Salmonella enterica isolates
<p><strong>Dataset</strong></p> <p>This dataset comprises the genome assemblies and respective 8,558-loci whole-genome (wg) Multiple Locus Sequence Type (MLST) profiles [INNUENDO schema (<a href="https://efsa.onlinelibrary.wiley.com/doi/epdf/10.2903/sp.efsa.2018.EN-1498">Llarena et al. 2018</a>) available in <a href="https://chewbbaca.online/species/8/schemas/1">chewie-NS</a> (<a href="https://academic.oup.com/nar/article/49/D1/D660/5929238">Mamede et al. 2022</a>)] of a final set of 1,434 <em>Salmonella enterica </em>samples selected among the Whole-Genome Sequencing (WGS) data publicly available in the European Nucleotide Archive (ENA) or in the <a href="https://www.ncbi.nlm.nih.gov/">National Center for Biotechnology Information</a> (NCBI) Sequence Read Archive (SRA) at the beginning of the analysis (November 2021). This set of samples was carefully selected to cover a wide genetic diversity (assessed in terms of serotype). In total, 125 different serotypes are represented in this dataset, with Typhimurium (including monophasic), Enteritidis and Infantis being the most represented ones and, together, corresponding to 56.2% of the dataset.</p> <p>File “Se_metadata.xlsx” contains metadata information for each isolate, including ENA/SRA accession number, BioProject and in-silico MLST ST and serotype.</p> <p>The directory “assemblies/” contains all the genome assemblies (.fasta format) of each isolate presented in the metadata file. </p> <p>The file “profiles/Se_profiles_wgMLST.tsv” corresponds to a tab separated file with the 8,558-loci wgMLST profiles of each isolate presented in the metadata file. The files “profiles/Se_profiles_cgMLST_95.tsv”, “profiles/Se_profiles_cgMLST_98.tsv” and “profiles/Se_profiles_cgMLST_100.tsv” correspond to a 3,261-loci, 3,179-loci and 874-loci cgMLST profiles of each isolate presented in the metadata file, respectively. These profiles were determined as explained below.</p> <p> </p> <p><strong>Dataset selection and curation</strong></p> <p>With the objective of creating a diverse dataset of <em>S. enterica</em> genome assemblies, we collected information about the genetic diversity (serotype) of the isolates available at <a href="https://enterobase.warwick.ac.uk/species/index/senterica">Enterobase</a> database in the beginning of this analysis (November 2021) and in other previous works. Based on this information, we selected an initial dataset comprising 1,779 samples associated with four BioProjects (<a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJEB16326">PRJEB16326</a>, <a href="https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJEB20997">PRJEB20997</a>, <a href="https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJEB30335">PRJEB30335</a> and <a href="https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJEB39988">PRJEB39988</a>). Their WGS data was downloaded from ENA/SRA with <a href="https://github.com/rpetit3/fastq-dl">fastq-dl</a> v1.0.6. Read quality control, trimming and assembly were performed with the Aquamis v1.3.9 (<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8145556/">Deneke et al. 2021</a>) using default parameters. Assembly quality control (QC), including contamination assessment, as well as MLST ST determination were performed with the same pipeline. All genome assemblies passing the QC were included in the final dataset. Among the others, we noticed that a considerable proportion of assemblies was flagged as “QC fail” exclusively due to the “NumContamSNVs” parameter, suggesting that this setting might have been too strict. After manual inspection of a random subset, assemblies for which the percentage of reads corresponding to the correct species was >98% were recovered and integrated in the final dataset (those samples are labeled in the Metadata file). In total, 1,434 isolates passed this curation step and were included in the final dataset. In-silico serotyping was performed with SeqSero2 v1.2.1 (<a href="https://pubmed.ncbi.nlm.nih.gov/31540993/">Zhang et al. 2019</a>). wgMLST profiles of each of these isolates were determined with chewBBACA v2.8.5 (<a href="https://pubmed.ncbi.nlm.nih.gov/29543149/">Silva et al. 2018</a>), using the 8,558-loci INNUENDO schema available in <a href="https://chewbbaca.online/species/8">chewie-NS</a> (<a href="https://efsa.onlinelibrary.wiley.com/doi/epdf/10.2903/sp.efsa.2018.EN-1498">Llarena et al. 2018</a>; <a href="https://academic.oup.com/nar/article/49/D1/D660/5929238">Mamede et al. 2022</a>) and downloaded on May 31<sup>st</sup>, 2022. Three cgMLST schemas were obtained with <a href="https://github.com/insapathogenomics/ReporTree">ReporTree</a> v1.0.0 (<a href="https://www.researchsquare.com/article/rs-1404655/v1">Mixão et al. 2022</a>) using the 8,558-loci wgMLST profiles of the 1,434 isolates as input and setting distinct “--site-inclusion” thresholds: 0.95, 0.98 and 1.0 (i.e., keep schema loci called in at least 95%, 98% and 100% of the samples, resulting in a 3,261-loci, 3,179-loci and 874-loci allelic matrices, respectively).</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>We thank the National Distributed Computing Infrastructure of Portugal (INCD) for providing the necessary resources to run the genome assemblies. INCD was funded by FCT and FEDER under the project 22153-01/SAICT/2016.</p>
Salmonella enterica serovar Derby isolated from eggs show genomic and phenotypic traits that may be linked to inability to produce human infection.
<p><em><span>Salmonella enterica</span></em><span> serovar Derby causes foodborne disease (FBD) outbreaks worldwide, mainly from contaminated pork but also from chickens. During a major epidemic of FBD in Uruguay due to <em>S</em>. Enteritidis from poultry, we conducted a large survey of commercially available eggs, where we isolated many <em>S.</em> Enteritidis strains but surprisingly also a much larger number (ratio 5:1) of <em>S</em>. Derby strains. No single case of <em>S</em>. Derby infection was detected in that period, suggesting that the <em>S</em>. Derby egg strains were impaired for human infection. We sequenced fourteen of these egg isolates, as well as fifteen isolates from pork or human infection that were isolated in Uruguay before and after that period, and all sequenced strains had the same sequence type <span>(ST40). Phylogenomic genomic analysis was conducted using more than 3500 genomes from the same sequence type (ST), revealing that Uruguayan isolates clustered into four distantly related lineages. Population structure analysis (BAPS) suggested the division of the analyzed genomes into nine different BAPS1 groups, with Uruguayan strains clustering within four of them. </span>All egg isolates clustered together as a monophyletic group and showed marked differences in gene content with the strains in the other clusters. <span>Differences included the absence of a C-terminal fragment of the <em>speF</em> gene, as well as variations in the composition of mobile genetic elements, such as plasmids, insertion sequences, transposons, and phages, between egg isolates and human/pork isolates.</span></span> <span>Egg isolates showed an acid susceptibility phenotype, reduced ability to reach the intestine after oral inoculation of mice, and reduced induction of SPI-2 <em>ssaG</em> gene, compared to human isolates from other monophyletic groups. Mice challenge experiments showed that mice infected intraperitoneally with human/pork isolates died between 1-7 days p.i., while all animals infected with the egg strain survived the challenge. Altogether, our results suggest that loss of gene functions and the absence of plasmids in egg isolates may explain why these <em>S</em>. Derby were not capable of producing human infection despite being at that time, the main serovar recovered from eggs countrywide.</span></p>
The OHEJP BeONE Project – Salmonella enterica genome assembly dataset
<p><strong>Dataset</strong></p> <p>This dataset comprises the genome assemblies of 1,540 <em>Salmonella enterica</em> samples collected by the BeONE Consortium on behalf of the One Health European Joint Programme “BeONE: Building Integrative Tools for One Health Surveillance” (<a href="https://onehealthejp.eu/jrp-beone/">https://onehealthejp.eu/jrp-beone/</a>). Additionally, a complementary dataset is also made available (<a href="https://zenodo.org/record/7119735">https://zenodo.org/record/7119735</a>), comprising genome assemblies of 1,434 <em>S. enterica</em> samples selected among the Whole-Genome Sequencing (WGS) data publicly available in the European Nucleotide Archive (ENA) or in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA).</p> <p>File “<strong>BeONE_Se_metadata.xls</strong>x” contains the genome assembly statistics for each isolate, including European Nucleotide Archive accession numbers, in-silico Multi Locus Sequence Type and Serotype, and information regarding year of sampling, country and source.</p> <p>The archive “<strong>BeONE_Se_assemblies.zi</strong>p” contains all the genome assemblies (.fasta format) of each isolate presented in the metadata file.</p> <p> </p> <p><strong>Dataset selection and curation</strong></p> <p>This anonymized dataset of <em>S. enterica</em> genome assemblies was generated using Next Generation Sequencing data collected within the BeONE Consortium available at the European Nucleotide Archive under BioProject Accession Number <a href="http://www.ebi.ac.uk/ena/browser/view/PRJEB57179">PRJEB57179</a>. Read quality control, trimming and assembly were performed with Aquamis v1.3.9 (<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8145556/">Deneke et al. 2021</a>) using default parameters. Assembly quality control (QC), including contamination assessment, as well as MLST ST determination were performed with the same pipeline. All genome assemblies passing the QC were included in the final dataset. Among the others, we noticed that a considerable proportion of assemblies was flagged as “QC fail” exclusively due to the “NumContamSNVs” parameter, suggesting that this setting might have been too strict. After manual inspection of a random subset, assemblies for which the percentage of reads corresponding to the correct species was >98% were recovered and integrated in the final dataset (those samples are labeled in the Metadata file). In total, 1,540 isolates passed the dataset curation step and were included in the final dataset. In-silico serotyping was performed with SeqSero2 v1.2.1 (<a href="https://pubmed.ncbi.nlm.nih.gov/31540993/">Zhang et al. 2019</a>).</p> <p> </p> <p><strong>Funding</strong></p> <p>This work was supported by funding from the European Union’s Horizon 2020 Research and Innovation programme under grant agreement No 773830: One Health European Joint Programme. </p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>We thank the National Distributed Computing Infrastructure of Portugal (INCD) for providing the necessary resources to run the genome assemblies. INCD was funded by FCT and FEDER under the project 22153-01/SAICT/2016.</p>
Data from: Assessing the contributions of intraspecific and environmental sources of infection in urban wildlife: Salmonella enterica and white ibis as a case study
Conversion of natural habitats into urban landscapes can expose wildlife to novel pathogens and alter pathogen transmission pathways. Because transmission is difficult to quantify for many wildlife pathogens, mathematical models paired with field observations can help select among competing transmission pathways that might operate in urban landscapes. Here we develop a mathematical model for the enteric bacteria Salmonella enterica in urban-foraging white ibis (Eudocimus albus) in south Florida as a case study to determine (i) the relative importance of contact-based versus environmental transmission among ibis and (ii) whether transmission can be supported by ibis alone or requires external sources of infection. We use biannual field prevalence data to restrict model outputs generated from a Latin hypercube sample of parameter space and select among competing transmission scenarios. We find the most support for transmission from environmental uptake rather than between-host contact and that ibis–ibis transmission alone could maintain low infection prevalence. Our analysis provides the first parameter estimates for Salmonella shedding and uptake in a wild bird and provides a key starting point for predicting how ibis response to urbanization alters their exposure to a multi-host zoonotic enteric pathogen. More broadly, our study provides an analytical roadmap to assess transmission pathways of multi-host wildlife pathogens in the face of scarce infection data.
The genomic and epidemiological virulence patterns of Salmonella enterica serovars in the United States
<p>The serovars of <i>Salmonella enterica </i>display dramatic differences in pathogenesis and host preferences. We developed a process (patent pending) for grouping <i>Salmonella</i> isolates and serovars by their public health risk. We collated a curated set of 12,337 <i>S. enterica</i> isolate genomes from human, beef, and bovine sources in the US. After annotating a virulence gene catalog for each isolate, we used unsupervised random forest methods to estimate the proximity (similarity) between isolates based upon the genomic presentation of putative virulence traits We then grouped isolates (virulence clusters) using hierarchical clustering (Ward's method), used non-parametric bootstrapping to assess cluster stability, and externally validated the clusters against epidemiological virulence measures from FoodNet, the National Outbreak Reporting System (NORS), and US federal sampling of beef products. We identified five stable virulence clusters of <i>S. enterica</i> serovars. Cluster 1 (higher virulence) serovars yielded an annual incidence rate of domestically acquired sporadic cases roughly one and a half times higher than the other four clusters combined (Clusters 2-5, lower virulence). Compared to other clusters, cluster 1 also had a higher proportion of infections leading to hospitalization and was implicated in more foodborne and beef-associated outbreaks, despite being isolated at a similar frequency from beef products as other clusters. We also identified subpopulations within 11 serovars. Remarkably, we found <i>S.</i> Infantis and<i> S.</i> Typhimurium subpopulations that significantly differed in genome length and clinical case presentation. Further, we found that the presence of the pESI plasmid accounted for the genome length differences between the <i>S. </i>Infantis subpopulations. Our results show that <i>S. enterica</i> strains associated with highest incidence of human infections share a common virulence repertoire. This work could be updated regularly and used in combination with foodborne surveillance information to prioritize serovars of public health concern. </p><p>Files contained in this repository will reproduce elements of figures 3,4,6, and 7 of the accompanying PLOS One manuscript. </p><p> </p>
EFSA cgMLST gene lists for Escherichia coli and Salmonella enterica chewieNS schema
<p>Annex A contains the list of cgMLST loci of <em>Escherichia coli</em> and <em>Salmonella enterica</em> used in the cgMLST analysis in the EFSA One Health WGS System.</p>
Salmonella Enterica Centrifuge DB
<p>Plascope DB for Salmonella Enterica. It can be used to perform binary classification of plasmid contigs.</p>
Global effects of deletion of the sdh genes, encoding succinate dehydrogenase, and of cobalt on protein abundance in stationary phase Salmonella enterica serovar Typhimurium.
<p>A common strategy that bacteria utilize to increase their survival under stressful conditions in their natural environments, including antibiotic treatment, is the entry into quiescence, a state of reversible cell growth arrest that offers protection against many environmental insults. Understanding quiescence is an important fundamental question, with relevance in the medical and environmental fields. Little is known about the molecular and physiological determinants that orchestrate survival during this temporary arrest of proliferation, or those that allow a rapid transition back to the proliferating state when conditions again become favorable. In the wide host-range pathogen <em>Salmonella enterica</em> serovar Typhimurium (S. Typhimurium) and other Gram-negative bacteria, this temporary arrest of proliferation induces the expression of the alternative sigma subunit of RNA polymerase, σS/RpoS, which remodels global gene expression to reshape the cell physiology and ensure survival under starvation and various stress conditions (<em>i.e</em>., the general stress response). One important aspect of persistence is the phenotypic differentiation of quiescent populations into sub-population(s) of "persisters" that survive in the presence of lethal concentrations of antibiotics. This phenomenon is worsening the worldwide antibiotic crisis, by causing therapy failure and chronic infections and potentially favoring the development of antibiotic resistance. Understanding mechanisms governing bacterial persisters is thus an important topic and a key issue for drug developments. However, despites many studies, the physiological and molecular mechanisms controlling the formation of persisters are poorly understood and controversial.</p> <p>We have recently discovered an unexpected functional interaction between σS and succinate dehydrogenase (Sdh) in the formation of persisters. Succinate dehydrogenase (Sdh), a membrane bound complex that connects the TCA cycle and respiratory chain, is one major target down regulated by σS (Levi-Meyrueis <em>et al</em>. 2014, 2015, Lago <em>et al.</em> 2017). Stationary-phase <em>Salmonella</em> grown in LB rich medium form persisters with a higher frequency than actively growing bacteria, after transfer to fresh LB medium in the presence of lethal concentrations of ampicillin and ciprofloxacin, but not significant effect of the Δ<em>rpoS</em> mutation on this phenomenon was observed. Surprisingly however, the Δ<em>rpoS</em> mutation suppressed the defect in persister formation of a Δ<em>sdh </em>mutant. It is very likely that the Δ<em>rpoS</em> mutation compensates for a metabolic perturbation provoked by the Δ<em>sdh </em>mutation, and key for persister formation.</p> <p>To get further insights into the synthetic rescue process involved in persisters formation, we used a mass spectrometry-based proteomics approach to compare the proteome of the wild-type, Δ<em>rpoS</em>, Δ<em>sdh</em> and Δ<em>sdh</em>Δ<em>rpoS</em> strains grown to late stationary phase in nutrient-rich LB medium. Cells were also grown in LB supplemented with cobalt to pinpoint major changes induced by cobalt on the <em>Salmonella</em> proteome. Indeed, the synthetic rescue process involved in persisters formation in the presence of ampicillin was abolished when the inoculum has been grown in the presence of a non-lethal dose of cobalt (100 μM).</p> <p><strong>Accession number</strong>.The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier <strong>PXD043726.</strong></p> <p><strong>See also:</strong></p> <p>NOREL, F., & MONTEIL, V. (2023). Unraveling a synthetic rescue process involved in persisters formation [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10277562</p> <p>Phégnon, L., Uttenweiler-Joseph, S., & Létisse, F. (2024). <span>Key physiological and metabolic characteristics for the differentiation of quiescent Salmonella's cells into persisters [Data set]. </span>Zenodo. <a href="https://doi.org/10.5281/zenodo.10885905" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10885905</a></p> <p><strong>This work was supported by the French National Research Agency (ANR-19-CE44-0005-01, PERIOMET project).</strong></p> <p><strong>References</strong></p> <p>Levi-Meyrueis C, Monteil V, Sismeiro O, Dillies MA, Monot M, Jagla B<em>, et al. </em>Expanding the RpoS/sigmaS-network by RNA sequencing and identification of sigmaS-controlled small RNAs in <em>Salmonella</em>. PloS one. 2014;9(5):e96918.</p> <p>Levi-Meyrueis C, Monteil V, Sismeiro O, Dillies M-A, Kolb A, Monot M <em>et al</em>. Repressor activity of the RpoS/sigmaS-dependent RNA polymerase requires DNA binding. Nucleic Acids Res 2015 43, 1456–1468.</p> <p>Lago M, Monteil V, Douche T, Guglielmini J, Criscuolo A, Maufrais C, <em>et al</em>. Proteome remodelling by the stress sigma factor RpoS/sigma(S) in <em>Salmonella</em>: identification of small proteins and evidence for post-transcriptional regulation. Scientific reports. 2017;7(1):2127.</p> <p> </p>
Data from: Assessing the contributions of intraspecific and environmental sources of infection in urban wildlife: Salmonella enterica and white ibis as a case study
Open the record for dataset details and reuse information.
1263 Salmonella enterica draft genomes assembled from Bioproject PRJEB31846
<p>We assembled 1263 Salmonella enterica draft genomes (raw data available from PRJEB31846).</p> <p> </p> <ul> <li>The dataset comprises diverse Salmonella enterica serovars collected between the years 1999 and 2019 and sequenced by the National Reference Laboratory for Salmonella on Illumina MiSeq and NextSeq technology. The data was described in more detail in 10.1128/AEM.02265-19.</li> </ul> <ul> <li>Data were trimmed (with fastp, version 0.19.5) and assembled (with shovil-spades, version 1.1.0) using the AQUAMIS pipeline (https://gitlab.com/bfr_bioinformatics/AQUAMIS, version v1.2.0). All samples passed basic quality checks, such as sufficient base quality, coverage depth, genome length and contig number. Furthermore, no evidence for sample contamination was detected.</li> <li>The assemblies are input to a validation of chewieSnake (https://gitlab.com/bfr_bioinformatics/chewieSnake).</li> <li>The cgMLST analysis is available in https://bfr_bioinformatics.gitlab.io/chewiesnake_publicationdata/</li> </ul> <p> </p>
INNUENDO whole genome and core genome MLST schemas and datasets for Salmonella enterica
<p><strong>Dataset</strong></p> <p>As reference dataset, 4,307 public available draft or complete genome assemblies and available metadata of <em>Salmonella enterica</em> have been downloaded from public repositories (i.e. <a href="https://enterobase.warwick.ac.uk/">EnteroBase</a>, <a href="https://www.ncbi.nlm.nih.gov/">National Center for Biotechnology Information NCBI</a>and <a href="https://www.ebi.ac.uk/">The European Bioinformatics Institute EMBL-EBI</a>; accessed April 2017). The collection includes 1,465 <em>S.</em> Enteritidis, 2,442 <em>S.</em>Typhimurium, and 400 of other frequently isolated serovars in Europe. The dataset includes also 153 <em>S.</em>Typhimurium variant 4,[5],12:i:- collected from different Italian regions between 2012 and 2014 during a surveillance study and 129 <em>S.</em> Enteritidis belonging to the INNUENDO sequence dataset (<a href="https://www.ebi.ac.uk/ena/data/view/PRJEB27020">PRJEB27020</a>). The 282 additional genomes were assembled using <a href="https://github.com/B-UMMI/INNUca">INNUca v3.1</a>.</p> <p>File 'Metadata/Senterica_metadata.txt' contains metadata information for each strain including source classification, host taxa, year and country of isolation, serotype, classical pubMLST 7 genes ST classification, and source/method of the assembly. </p> <p>The directory 'Genomes' contains all the 4,589 assemblies of the strains listed in 'Metadata/Senterica_metadata.txt'. Please note that genomes marked as 'Enterobase' have been downloaded from Enterobase webpage http://enterobase.warwick.ac.uk.</p> <p><strong>Schema creation and validation</strong></p> <p>The wgMLST schema from <a href="https://enterobase.warwick.ac.uk/species/senterica/download_data">EnteroBase</a> have been downloaded and curated using <a href="https://github.com/B-UMMI/chewBBACA/wiki/1.-Schema-Creation"><em>chewBBACA AutoAlleleCDSCuration</em></a> for removing all alleles that are not coding sequences (CDS). The quality of the remain loci have been assessed using <a href="https://github.com/B-UMMI/chewBBACA/wiki/1.-Schema-Creation"><em>chewBBACA Schema Evaluation</em></a> and loci with single alleles, those with high length variability (i.e. if more than 1 allele is outside the mode +/- 0.05 size) and those present in less than 0.5% of the <em>Salmonella</em> genomes in <a href="https://enterobase.warwick.ac.uk/species/index/senterica">EnteroBase</a> at the date of the analysis (April 2017) have been removed. The wgMLST schema have been further curated, excluding all those loci detected as “Repeated Loci” and loci annotated as “non-informative paralogous hit (NIPH/ NIPHEM)” or “Allele Larger/ Smaller than length mode (ALM/ ASM)” by the <a href="https://github.com/B-UMMI/chewBBACA/wiki/2.-Allele-Calling"><em>chewBBACA Allele Calling</em></a> engine in more than 1% of a dataset composed by 4,589 <em>Salmonella</em> genomes.</p> <p>File 'Schemas/Senterica_wgMLST_ 8558_schema.tar.gz' contains the wgMLST schema formatted for chewBBACA and includes a total of 8,558 loci.</p> <p>File 'Schemas/Senterica_cgMLST_ 3255_listGenes.txt' contains the list of genes from the wgMLST schema which defines the cgMLST schema. The cgMLST schema consists of 3,255 loci and has been defined as the loci present in at least the 99% of the 4,589 <em>Salmonella</em> genomes. Genomes have no more than 2% of missing loci.</p> <p>File 'Allele_Profles/Senterica_wgMLST_alleleProfiles.tsv' contains the wgMLST allelic profile of the 4,589 <em>Salmonella</em> genomes of the dataset. Please note that missing loci follow the annotation of chewBBACA Allele Calling software.</p> <p>File 'Allele_Profles/Senterica_cgMLST_alleleProfiles.tsv' contains the cgMLST allelic profile of the 4,589 <em>Salmonella</em> genomes of the dataset. Please note that missing loci are indicated with a zero.</p> <p><strong>Additional citations</strong></p> <p>The schema are prepared to be used with <a href="https://github.com/B-UMMI/chewBBACA/wiki"><strong>chewBBACA</strong></a>. When using the schema in this repository please cite also:</p> <blockquote> <p>Silva M, Machado M, Silva D, Rossi M, Moran-Gilad J, Santos S, Ramirez M, Carriço J. chewBBACA: A complete suite for gene-by-gene schema creation and strain identification. 15/03/2018. M Gen 4(3): doi:10.1099/mgen.0.000166 <a href="http://mgen.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000166">http://mgen.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000166</a></p> </blockquote> <p><em>Salmonella enterica</em> schema is a derivation of EnteroBase <em>Salmonella </em><a href="http://enterobase.warwick.ac.uk/">EnteroBase</a> wgMLST schema. When using the schema in this repository please cite also:</p> <blockquote> <p>Alikhan N-F, Zhou Z, Sergeant MJ, Achtman M (2018) A genomic overview of the population structure of <em>Salmonella</em>. PLoS Genet 14 (4):e1007261. <a href="https://doi.org/10.1371/journal.pgen.1007261">https://doi.org/10.1371/journal.pgen.1007261</a></p> </blockquote>
In-vitro selection of lactic acid bacteria to combat Salmonella enterica and Campylobacter jejuni in broiler chickens
<p><em><span>In-vitro</span></em><span> selection of LAB strains for antimicrobial applications in livestock production required specific focus on certain LAB strains. Accordingly, six commercial LAB strains (homofermentative, obligatory heterofermentative and facultative heterofermentative) belonging to different genera, were chosen for screening against strains of <em>Salmonella </em>and <em>Campylobacter jejuni </em>under <em>in-vitro </em>conditions.</span></p> <p> </p>
Supplementary Material to the Publication: Clonal relation between Salmonella enterica subspecies enterica serovar Dublin strains of bovine and food origin in Germany
<p>OHEJP Project: BeOne</p> <p><em>Salmonella enterica </em>serovar Dublin (<em>S</em>. Dublin) is a host-adapted serovar that causes enteritis and/or systemic diseases in cattle. Because the serovar is not host-specific, it can infect other species, including human beings, causing severe disease and a higher mortality rate than other non-typhoidal serovars. Given that human illnesses are primarily caused by contaminated milk, milk products, and beef, data on the genetic connection between <em>S</em>. Dublin strains from livestock and food should be analyzed. </p> <p>Whole genome sequencing (WGS) was performed on 144 <em>S</em>. Dublin strains from cattle and 30 strains from food. Multilocus sequence typing (MLST) found that the majority of livestock and food isolates were of the sequence type ST-10. As discovered by core-genome Single-Nucleotide Polymorphisms Typing and core-genome MLST, 14 of 30 strains from food origin were clonally related to at least one strain from cattle. Without outliers, the remaining 16 food-borne strains fit into the genomic structure of <em>S</em>. Dublin in Germany. WGS demonstrated to be an effective method not only for learning about the epidemiology of Salmonella strains, but also for detecting clonal relationships between organisms isolated at different stages of production. This study discovered a strong genetic link between <em>S</em>. Dublin strains from cattle and food, and thus the potential to cause human infections. <em>S</em>. Dublin strains from both origins have a nearly comparable collection of virulence factors, emphasizing their ability to produce severe clinical symptoms in animals as well as humans, emphasizing the importance of effective <em>S</em>. Dublin management in a farm to fork strategy.</p>
Salmonella enterica serovar Enteritidis EN1660 proteome spectral data
<p>H-NS is a nucleoid structuring protein and global repressor of virulence and horizontally-acquired genes in bacteria. H-NS can interact with itself or with homologous proteins, but protein family diversity and regulatory network overlap remain poorly defined. Here we present a comprehensive phylogenetic analysis that revealed deep-branching clades, dispelling the presumption that H-NS is the progenitor of varied molecular backups. With few exceptions, clades are either entirely chromosomal or entirely plasmid-encoded proteins. On chromosomes, StpA and newly discovered HlpP are core genes in specific genera, whereas Hfp and newly discovered HlpC are sporadically distributed. Six clades of <u>H</u>-NS <u>p</u>lasmid <u>p</u>roteins (Hpp) exhibit ancient and dedicated associations with plasmids, including three clades with fidelity for plasmid incompatibility groups H, F, or X. A proliferation of H-NS homologs in Erwiniaceae includes the first observation of potentially co-dependent H-NS forms. Conversely, the observed diversification of oligomerization domains may facilitate stable co-existence of divergent homologs in a genome. Transcriptomic and proteomic analysis of regulatory crosstalk in <i>Salmonella </i>revealed networked and hierarchical control of H-NS homologs. We also discovered that H-NS is both a repressor and activator of <i>Salmonella</i> Pathogenicity Island 1 gene expression, and both modes are restored by Sfh (HppH) in the absence of H-NS.</p>
Horizontal gene transfer is the main driver of antimicrobial resistance in broiler chicks infected with Salmonella enterica serovar Heidelberg
<p>Overuse and misuse of antibiotics in clinical settings and in food production have been linked to the increased prevalence and spread of antimicrobial resistance (AR). Consequently, public health and consumer concerns have resulted in a remarkable reduction in antibiotics used for food animal production. However, there are no data on the effectiveness of antibiotic removal in reducing AR shared through horizontal gene transfer (HGT). In this study, we used neonatal broiler chicks and Salmonella enterica serovar Heidelberg (SH), a model food pathogen, to test if chicks raised antibiotic-free harbor transferable AR. We challenged chicks with an antibiotic susceptible SH strain using various routes of inoculation and determined if SH isolates recovered carried plasmids conferring AR. We used antimicrobial susceptibility testing and whole genome sequencing (WGS) to show that chicks grown without antibiotics harbored antimicrobial resistant SH population 14 days after challenge and chicks challenged orally acquired AR at a higher rate than chicks inoculated via the cloaca. Using 16S rRNA gene sequencing we found that SH infection perturbed the microbiota of broiler chicks and used metagenomics and WGS to confirm commensal Escherichia coli population as the main reservoir of IncI1 plasmid acquired by SH. The carriage of this IncI1 plasmid posed no fitness cost to SH but increased its fitness when exposed to acidic pH in vitro. These results suggest that HGT of plasmids carrying AR shaped the evolution of SH and that antibiotic use reduction alone is insufficient to limit antibiotic resistance transfer from commensal bacteria to Salmonella.</p>
Survival of Salmonella enterica serovar Heidelberg in pine shavings used as broiler litter
<p>Wood shavings is the most common bedding material used around the world to raise broiler. Therefore, wood shavings can be a vehicle for the transmission of pathogens to live birds. In this study, we performed an in-depth genomic characterization of three <em>Salmonella enterica </em>serovar Heidelberg (<em>S</em>. Heidelberg) strains recovered after their inoculation into fresh pine shaving. The three strains used for the microcosm study were previously isolated from broiler feces (SH-AAFC), broiler carcass (SH-ARS) and chicken thigh (SH-FSIS) and differed one from another by 46 - 94 single nucleotide variants. The SH-AAFC strain harbored an antimicrobial resistant gene (ARG) (<em>bla</em><sub>CMY-2</sub>) on an IncI1 plasmid while the SH-FSIS strain harbored multiple ARGs (<em>floR, cmlA1, tet(A), bla</em><sub>TEM-1B</sub><em>, ant(2'')-Ia, aph(6)-Id, aph(3'')-Ib </em>and<em> sul2</em>) on an IncC plasmid. The SH-ARS isolate was pan susceptible to several antibiotics evaluated. We determined the abundance of <em>Salmonella </em>at days 0, 1, 7, 14 and 21 and performed antibiotic susceptibility testing and whole genome sequencing (on 77 randomly selected <em>S</em>. Heidelberg isolates. After 21 days of incubation, <em>Salmonella </em>abundance decreased by 4.4 logs. <em>Salmonella</em> with high minimum inhibitory concentrations (MICs) against ampicillin showed a significantly higher abundance and survival rate compared to <em>Salmonella</em> with high MIC against gentamicin (<em>P</em>< 0.05). Clonal SH-AAFC was the most prevalent strain in the microcosms (48/77), followed by the strain SH-ARS (25/77). Only 4/77 isolates were determined to be clones of SH-FSIS. We identified recombination events and plasmid copy number changes that were associated with the fitness of <em>S</em>. Heidelberg strain carrying IncI1 and Col plasmids. Lastly, we found that litter physicochemical variables including water activity could explain up to 85% of the variability in our data.</p>
Global effects of deletions of the sitABCD, mntH, cbiMNQO and corA genes, encoding transporters for manganese, cobalt and magnesium on protein abundance in Salmonella enterica serovar Typhimurium grown to stationary phase in LB.
<p>The RpoS/σS sigma subunit of RNA polymerase is the master regulator of the general stress response in many Gram-negative bacteria.</p><p>We have shown that in <i>Salmonella enterica </i>serovar Typhimurium, RpoS activates transcription of the <i>sitABCD</i> and <i>mntH </i> genes, involved in iron and manganese transport, and that of <i>corA</i> encoding the main magnesium transporter (Levi-Meyrueis <i>et al</i>. 2014, Metaane <i>et al</i>. 2022, Metaane <i>et al. </i>2023). In addition, RpoS represses expression of the CbiO protein produced from the <i>cbiMNQO</i> operon encoding a high affinity cobalt uptake system (Lago <i>et al.</i> 2017, Metaane <i>et al</i>. 2022, Metaane <i>et al. </i>2023). Moreover, Inductively coupled plasma mass spectrometry analyses have revealed that the Δ<i>rpoS</i> mutation reduces the cellular concentration of manganese and magnesium and increases the concentration of cobalt of stationary phase <i>Salmonella </i>(Metaane <i>et al. </i>2022). These findings suggested that a tight control of uptake and availability of manganese, magnesium and cobalt might be critical for quiescent bacteria. Consistent with this hypothesis, our recent findings unraveled the importance of RpoS and magnesium in the regrowth potential of quiescent <i>Salmonella</i> cells (Metaane <i>et al</i>. 2022).</p><p>Unexpectedly, our recent work revealed that, under magnesium proficient environmental conditions, the absence of the housekeeping Mg2+ transporter CorA is sensed by the cell which induces compensatory mechanisms to minimize the impact of a Δ<i>corA</i> mutation on protein content, magnesium homeostasis, growth, and motility of <i>Salmonella </i>(Metaane <i>et al. </i>2023). In this study, we used a mass spectrometry-based proteomics approach to address the physiological impact of the SitABCD, MntH and CbiMNQO transporters on quiescent <i>Salmonella. </i>A comprehensive quantitative proteomic analysis was performed using wild-type and Δ<i>rpoS </i>strains of <i>Salmonella</i> ATCC14028 carrying deletions of these genes and grown to late stationary phase in nutrient-rich LB medium, <i>i.e</i>. the growth conditions previously used to characterize the RpoS- transcriptome, proteome and ionome (Levi-Meyrueis <i>et al.</i> 2014, Lago <i>et al. </i>2017, Metaane <i>et al. </i>2022). Since CorA can also import cobalt, a Δ<i>corA</i> mutation was included and combined with the Δ<i>cbiMNQO</i> mutation. </p><p><strong>Accession number</strong>.The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier <strong>PXD043760</strong>.</p><p><strong>This work was supported by the French National Research Agency (ANR-19-CE44-0005-01, PERIOMET project).</strong></p><p><strong>References</strong></p><p>Levi-Meyrueis C, Monteil V, Sismeiro O, Dillies MA, Monot M, Jagla B, Coppée J-Y, Dupuy B, Norel F. Expanding the RpoS/sigmaS-network by RNA sequencing and identification of sigmaS-controlled small RNAs in <i>Salmonella</i>. PloS one. 2014;9(5):e96918.</p><p>Lago M, Monteil V, Douche T, Guglielmini J, Criscuolo A, Maufrais C, Matondo M, Norel F. Proteome remodelling by the stress sigma factor RpoS/sigma(S) in <i>Salmonella</i>: identification of small proteins and evidence for post-transcriptional regulation. Scientific reports. 2017;7(1):2127.</p><p>Metaane S, Monteil V, Ayrault S, Bordier L, Levi-Meyreuis C, Norel F. The stress sigma factor sigmaS/RpoS counteracts Fur repression of genes involved in iron and manganese metabolism and modulates the ionome of <i>Salmonella enterica </i>serovar Typhimurium. PLoS one. 2022;17(3):e0265511.</p><p>Metaane S, Monteil V, Douché T, Giai Gianetto Q, Matondo M, Maufrais C, Norel F. Loss of CorA, the primary magnesium transporter of <i>Salmonella, </i>is alleviated by MgtA and PhoP-dependent compensatory mechanisms. PloS one 2023;18(9):e0291736.</p><p>NOREL, & MONTEIL. (2023). Ionome analysis of Salmonella mutants by Inductively coupled plasma mass spectrometry (ICP-MS) (Version v1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.8085835</p><p> </p><p> </p>
Horizontal gene transfer is the main driver of antimicrobial resistance in broiler chicks infected with Salmonella enterica serovar Heidelberg
Open the record for dataset details and reuse information.
Salmonella enterica serovar Enteritidis EN1660 proteome spectral data
Open the record for dataset details and reuse information.
Supplementary material 1 from: Prigot-Maurice C, Depeux C, Paulhac H, Braquart-Varnier C, Beltran-Bech S (2022) Immune priming in Armadillidium vulgare against Salmonella enterica: direct or indirect costs on life history traits? In: De Smedt P, Taiti S, Sfenthourakis S, Campos-Filho IS (Eds) Facets of terrestrial isopod biology. ZooKeys 1101: 131-158. https://doi.org/10.3897/zookeys.1101.77216
Tables S1–S4, Figures S1–S3
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.