Claudin-10 Expression and the Gene Expression Pattern of Thick Ascending Limb Cells.

Many genomic, anatomical and functional differences exist between the medullary (MTAL) and the cortical thick ascending limb of the loop of Henle (CTAL), including a higher expression of claudin-10 (CLDN10) in the MTAL than in the CTAL. Therefore, we assessed to what extent the Cldn10 gene expression is a determinant of differential gene expression between MTAL and CTAL. RNAs extracted from CTAL and MTAL microdissected from wild type (WT) and Cldn10 knock out mice (cKO) were analyzed by RNAseq. Differential and enrichment analyses (GSEA) were performed with interactive R Shiny software. Between WT and cKO MTAL, 637 genes were differentially expressed, whereas only 76 were differentially expressed between WT and cKO CTAL. Gene expression patterns and GSEA analyses in all replicates showed that WT MTAL did not cluster with the other replicates; no hierarchical clustering could be found between WT CTAL, cKO CTAL and cKO MTAL. Compared to WT replicates, cKO replicates were enriched in Cldn16, Cldn19, Pth1r, (parathyroid hormone receptor type 1), Casr (calcium sensing receptor) and Vdr (Vitamin D Receptor) mRNA in both the cortex and medulla. Cldn10 is associated with gene expression patterns, including genes specifically involved in divalent cations reabsorption in the TAL.

Polyphyly in widespread Salmonella enterica serovars and using genomic proximity to choose the best reference genome for bioinformatics analyses.

Salmonella is the most common cause of gastroenteritis in the world. Over the past 5 years, whole-genome analysis has led to the high-resolution characterization of clinical and foodborne Salmonella responsible for typhoid fever, foodborne illness or contamination of the agro-food chain. Whole-genome analyses are simplified by the availability of high-quality, complete genomes for mapping analysis and for calculating the pairwise distance between genomes, but unfortunately some difficulties may still remain. For some serovars, the complete genome is not available, or some serovars are polyphyletic and knowing the serovar alone is not sufficient for choosing the most appropriate reference genome. For these serovars, it is essential to identify the genetically closest complete genome to be able to carry out precise genome analyses. In this study, we explored the genomic proximity of 650 genomes of the 58 Salmonella enterica subsp. enterica serovars most frequently isolated in humans and from the food chain in the United States (US) and in Europe (EU), with a special focus on France. For each serovar, to take into account their genomic diversity, we included all the multilocus sequence type (MLST) profiles represented in EnteroBase with 10 or more genomes (on 19 July 2021). A phylogenetic analysis using both core- and pan-genome approaches was carried out to identify the genomic proximity of all the Salmonella studied and 20 polyphyletic serovars that have not yet been described in the literature. This study determined the genetic proximity between all 58 serovars studied and revealed polyphyletic serovars, their genomic lineages and MLST profiles. Finally, we enhanced the open-access databases with 73 new genomes and produced a list of high-quality complete reference genomes for 48 S. enterica subsp. enterica serovars among the most isolated in the US, EU, and France.

Salmonella enterica subsp. enterica Welikade: guideline for phylogenetic analysis of serovars rarely involved in foodborne outbreaks.

BACKGROUND: Salmonella spp. is a major foodborne pathogen with a wide variety of serovars associated with human cases and food sources. Nevertheless, in Europe a panel of ten serovars is responsible for up to 80% of confirmed human cases. Clustering studies by single nucleotide polymorphism (SNP) core-genome phylogenetic analysis of outbreaks due to these major serovars are simplified by the availability of many complete genomes in the free access databases. This is not the case for outbreaks due to less common serovars, such as Welikade, for which no reference genomes are available. In this study, we propose a method to solve this problem. We propose to perform a core genome MLST (cgMLST) analysis based on hierarchical clustering using the free-access EnteroBase to select the most suitable genome to use as a reference for SNP phylogenetic analysis. In this study, we applied this protocol to a retrospective analysis of a Salmonella enterica serovar Welikade (S. Welikade) foodborne outbreak that occurred in France in 2016. Finally, we compared the cgMLST and SNP analyses. SNP phylogenetic reconstruction was carried out considering the effect of recombination events identified by the ClonalFrameML tool. The accessory genome was also explored by phage content and virulome analyses. RESULTS: Our findings revealed high clustering concordance using cgMLST and SNP analyses. Nevertheless, SNP analysis allowed for better assessment of the genetic distance among strains. The results revealed epidemic clones of S. Welikade circulating within the poultry and dairy sectors in France, responsible for sporadic and non-sporadic human cases between 2012 and 2019. CONCLUSIONS: This study increases knowledge on this poorly described serovar and enriches public genome databases with 42 genomes from human and non-human S. Welikade strains, including the isolate collected in 1956 in Sri Lanka, which gave the name to this serovar. This is the first genomic analysis of an outbreak due to S. Welikade described to date.

Retrieving Good-Quality Salmonella Genomes From the GenBank Database Using a Python Tool, SalmoDEST.

With the advent of next-generation whole-genome sequencing (WGS), the need for good-quality and well-characterised Salmonella genomes has increased over the past years. Good-quality complete genomes are often required for assembly reference mapping or phylogenetic single nucleotide polymorphism (SNP) analysis. Complete genomes or contigs from specific sources or serovars are also searched for clustering analysis or source attribution studies. Therefore, new bioinformatics tools are needed for the extraction of good-quality and well-characterised genomes from public databases. Here, we developed SalmoDEST, an open-source Python tool capable of extracting Salmonella genomes with a coverage higher than 50x and genome length over 4Mb from the GenBank database in the form of complete genomes or contigs, with verification of the serovar to which they belong and identification of the corresponding multi locus sequence type (MLST) profile. To validate the ability to SalmoDEST to screen for and retrieve genomes of good quality, we compared our results for S. Typhi complete genome with those available in the literature and extracted Salmonella genomes from bovine sources strains isolated worldwide. Finally, we provide in this study a list of 239 complete genomes for 123 serovars of Salmonella of high quality. SalmoDEST is a handy and easy-to-use open-source tool to extract complete genomes or contigs that can be routinely used in public health, food safety and research laboratories. SalmoDEST (SALMOnella Download gEnome Serotype sT) is available at https://github.com/I-Guy/SalmoDEST.

Closed Genome Sequence of a Salmonella enterica Serovar Bovismorbificans Strain Isolated from Dried Pork Sausage Associated with an Outbreak in France.

We report here the closed genome sequence of one Salmonella enterica subsp. enterica serovar Bovismorbificans strain isolated from dried pork sausage consumed by a patient suffering from salmonellosis.

The Spatiotemporal Dynamics and Microevolution Events That Favored the Success of the Highly Clonal Multidrug-Resistant Monophasic Salmonella Typhimurium Circulating in Europe.

The European epidemic monophasic variant of Salmonella enterica serovar Typhimurium (S. 1,4,[5],12:i:-) characterized by the multi locus sequence type ST34 and the antimicrobial resistance ASSuT profile has become one of the most common serovars in Europe (EU) and the United States (US). In this study, we reconstructed the time-scaled phylogeny and evolution of this Salmonella in Europe. The epidemic S. 1,4,[5],12:i:- ST34 emerged in the 1980s by an acquisition of the Salmonella Genomic Island (SGI)-4 at the 3' end of the phenylalanine phe tRNA locus conferring resistance to copper and arsenic toxicity. Subsequent integration of the Tn21 transposon into the fljAB locus gave resistance to mercury toxicity and several classes of antibiotics used in food-producing animals (ASSuT profile). The second step of the evolution occurred in the 1990s, with the integration of mTmV and mTmV-like prophages carrying the perC and/or sopE genes involved in the ability to reduce nitrates in intestinal contents and facilitate the disruption of the junctions of the host intestinal epithelial cells. Heavy metals are largely used as food supplements or pesticide for cultivation of seeds intended for animal feed so the expansion of the epidemic S. 1,4,[5],12:i:- ST34 was strongly related to the multiple-heavy metal resistance acquired by transposons, integrative and conjugative elements and facilitated by the escape until 2011 from the regulatory actions applied in the control of S. Typhimurium in Europe. The genomic plasticity of the epidemic S. 1,4,[5],12:i:- was demonstrated in our study by the analysis of the plasmidome. We were able to identify plasmids harboring genes mediating resistance to phenicols, colistin, and fluoroquinolone and also describe for the first time in six of the analyzed genomes the presence of two plasmids (pERR1744967-1 and pERR2174855-2) previously described only in strains of enterotoxigenic Escherichia coli and E. fergusonii.

A Simple and Robust Statistical Method to Define Genetic Relatedness of Samples Related to Outbreaks at the Genomic Scale - Application to Retrospective Salmonella Foodborne Outbreak Investigations.

The investigation of foodborne outbreaks (FBOs) from genomic data typically relies on inspecting the relatedness of samples through a phylogenomic tree computed on either SNPs, genes, kmers, or alleles (i.e., cgMLST and wgMLST). The phylogenomic reconstruction is often time-consuming, computation-intensive and depends on hidden assumptions, pipelines implementation and their parameterization. In the context of FBO investigations, robust links between isolates are required in a timely manner to trigger appropriate management actions. Here, we propose a non-parametric statistical method to assert the relatedness of samples (i.e., outbreak cases) or whether to reject them (i.e., non-outbreak cases). With typical computation running within minutes on a desktop computer, we benchmarked the ability of three non-parametric statistical tests (i.e., Wilcoxon rank-sum, Kolmogorov-Smirnov and Kruskal-Wallis) on six different genomic features (i.e., SNPs, SNPs excluding recombination events, genes, kmers, cgMLST alleles, and wgMLST alleles) to discriminate outbreak cases (i.e., positive control: C+) from non-outbreak cases (i.e., negative control: C-). We leveraged four well-characterized and retrospectively investigated FBOs of Salmonella Typhimurium and its monophasic variant S. 1,4,[5],12:i:- from France, setting positive and negative controls in all the assays. We show that the approaches relying on pairwise SNP differences distinguished all four considered outbreaks in contrast to the other tested genomic features (i.e., genes, kmers, cgMLST alleles, and wgMLST alleles). The freely available non-parametric method written in R has been designed to be independent of both the phylogenomic reconstruction and the detection methods of genomic features (i.e., SNPs, genes, kmers, or alleles), making it widely and easily usable to anybody working on genomic data from suspected samples.

First Draft Genome Sequences of Three Strains of Francisella tularensis subsp. holarctica, Isolated from Hares and a Tick in France.

Here, we report the complete genome sequences of three strains of Francisella tularensis subsp. holarctica (11-789-5S, 11-935-13S, and 11-930-9S), isolated from brown hares and a tick during a tularemia outbreak in France, where tularemia is endemic.

MLVA for Salmonella enterica subsp. enterica Serovar Dublin: Development of a Method Suitable for Inter-Laboratory Surveillance and Application in the Context of a Raw Milk Cheese Outbreak in France in 2012.

Salmonella enterica subspecies enterica serovar Dublin (S. Dublin) figures among the most frequently isolated Salmonella strains in humans in France. This serovar may affect production and animal health mainly in cattle herds with corresponding high economic losses. Given that the current gold standard method, pulsed-field gel electrophoresis (PFGE), provides insufficient discrimination for epidemiological investigations, we propose a standard operating procedure in this study for multiple-locus variable number tandem repeat analysis (MLVA) of S. Dublin, suitable for inter-laboratory surveillance. An in silico analysis on the genome of S. Dublin strains CT_02021853 was performed to identify appropriate microsatellite regions. Of 21 VNTR loci screened, six were selected and 401 epidemiologically unrelated and related strains, isolated from humans, food and animals were analyzed to assess performance criteria such as typeability, discriminatory power and epidemiological concordance. The MLVA scheme developed was applied to an outbreak involving Saint-Nectaire cheese for which investigations were conducted in France in 2012, making it possible to discriminate between epidemiologically related strains and sporadic case strains, while PFGE assigned only a single profile. The six loci selected were sequenced on a large set of strains to determine the sequence of the repeated units and flanking regions, and their stability was evaluated in vivo through the analysis of the strains investigated from humans, food and the farm environment during the outbreak. The six VNTR selected were found to be stable and the discriminatory power of the MLVA method developed was calculated to be 0.954 compared with that for PFGE, which was only 0.625. Twenty-four reference strains were selected from the 401 examined strains in order to represent most of the allele diversity observed for each locus. This reference set can be used to harmonize MLVA results and allow data exchange between laboratories. This original MLVA protocol could be used easily and routinely for monitoring of serovar Dublin isolates and for conducting outbreak investigations.