Search

Bacterial Toxin-Antitoxin systems (TAS) are involved in key biological functions including plasmid maintenance, defense against phages, persistence and virulence. They are found in nearly all phyla and classified into 6 different types based on the mode of inactivation of the toxin, with the type II TAS being the best characterized so far. We have herein developed a new in silico discovery pipeline named TASmania, which mines the >41K assemblies of the EnsemblBacteria database for known and uncharacterized protein components of type I to IV TAS loci. Our pipeline annotates the proteins based on a list of curated HMMs, which leads to >2.106 loci candidates, including orphan toxins and antitoxins, and organises the candidates in pseudo-operon structures in order to identify new TAS candidates based on a guilt-by-association strategy. In addition, we classify the two-component TAS with an unsupervised method on top of the pseudo-operon (pop) gene structures, leading to 1567 “popTA” models offering a more robust classification of the TAs families. These results give valuable clues in understanding the toxin/antitoxin modular structures and the TAS phylum specificities. Preliminary in vivo work confirmed six putative new hits in Mycobacterium tuberculosis as promising candidates. The TASmania database is available on the following server https://shiny.bioinformatics.unibe.ch/apps/tasmania/., Author summary TASmania offers an extensive annotation of TA loci in a very large database of bacterial genomes, which represents a resource of crucial importance for the microbiology community. TASmania supports i) the discovery of new TA families; ii) the design of a robust experimental strategy by taking into account potential interferences in trans; iii) the comparative analysis between TA loci content, phylogeny and/or phenotypes (pathogenicity, persistence, stress resistance, associated host types) by providing a vast repertoire of annotated assemblies. Our database contains TA annotations of a given strain not only mapped to its core genome but also to its plasmids, whenever applicable.

The genus Legionella comprises 65 species, among which Legionella pneumophila is a human pathogen causing severe pneumonia. To understand the evolution of an environmental to an accidental human pathogen, we have functionally analyzed 80 Legionella genomes spanning 58 species. Uniquely, an immense repository of 18,000 secreted proteins encoding 137 different eukaryotic-like domains and over 200 eukaryotic-like proteins is paired with a highly conserved type IV secretion system (T4SS). Specifically, we show that eukaryotic Rho- and Rab-GTPase domains are found nearly exclusively in eukaryotes and Legionella . Translocation assays for selected Rab-GTPase proteins revealed that they are indeed T4SS secreted substrates. Furthermore, F-box, U-box, and SET domains were present in >70% of all species, suggesting that manipulation of host signal transduction, protein turnover, and chromatin modification pathways are fundamental intracellular replication strategies for legionellae. In contrast, the Sec-7 domain was restricted to L. pneumophila and seven other species, indicating effector repertoire tailoring within different amoebae. Functional screening of 47 species revealed 60% were competent for intracellular replication in THP-1 cells, but interestingly, this phenotype was associated with diverse effector assemblages. These data, combined with evolutionary analysis, indicate that the capacity to infect eukaryotic cells has been acquired independently many times within the genus and that a highly conserved yet versatile T4SS secretes an exceptional number of different proteins shaped by interdomain gene transfer. Furthermore, we revealed the surprising extent to which legionellae have coopted genes and thus cellular functions from their eukaryotic hosts, providing an understanding of how dynamic reshuffling and gene acquisition have led to the emergence of major human pathogens.

International audience; A chronic inflammatory state to a large extent explains sickle cell disease (SCD) pathophysi-ology. Nonetheless, the principal dysregulated factors affecting this major pathway and their mechanisms of action still have to be fully identified and elucidated. Integrating gene expression and genome-wide association study (GWAS) data analysis represents a novel approach to refining the identification of key mediators and functions in complex diseases. Here, we performed gene expression meta-analysis of five independent publicly available microarray datasets related to homozygous SS patients with SCD to identify a consensus SCD transcriptomic profile. The meta-analysis conducted using the MetaDE R package based on combining p values (maxP approach) identified 335 differentially expressed genes (DEGs; 224 upregulated and 111 downregulated). Functional gene set enrichment revealed the importance of several metabolic pathways, of innate immune responses, erythrocyte development, and hemostasis pathways. Advanced analyses of GWAS data generated within the framework of this study by means of the atSNP R package and SIFT tool identified 60 regulatory single-nucleotide polymorphisms (rSNPs) occurring in the promoter of 20 DEGs and a deleterious SNP, affecting CAMKK2 protein function. This novel database of candidate genes, transcription factors, and rSNPs associated with SCD provides new markers that may help to identify new therapeutic targets.

Hospital-acquired infections (HAIs), including emerging multi-drug resistant organisms, threaten healthcare systems worldwide. Efficient containment measures of HAIs must mobilize the entire healthcare network. Thus, to best understand how to reduce the potential scale of HAI epidemic spread, we explore patient transfer patterns in the French healthcare system. Using an exhaustive database of all hospital discharge summaries in France in 2014, we construct and analyze three patient networks based on the following: transfers of patients with HAI (HAI-specific network); patients with suspected HAI (suspected-HAI network); and all patients (general network). All three networks have heterogeneous patient flow and demonstrate small-world and scale-free characteristics. Patient populations that comprise these networks are also heterogeneous in their movement patterns. Ranking of hospitals by centrality measures and comparing community clustering using community detection algorithms shows that despite the differences in patient population, the HAI-specific and suspected-HAI networks rely on the same underlying structure as that of the general network. As a result, the general network may be more reliable in studying potential spread of HAIs. Finally, we identify transfer patterns at both the French regional and departmental (county) levels that are important in the identification of key hospital centers, patient flow trajectories, and regional clusters that may serve as a basis for novel wide-scale infection control strategies., Author summary Hospital-acquired infections (HAIs), including emerging multi-drug resistant organisms, threaten healthcare systems worldwide. Efficient containment measures of HAIs must mobilize the entire healthcare network. Thus, to best understand how to reduce the scale of potential HAI epidemic spread, we explore patient transfer patterns in the French healthcare system. We construct and compare the characteristics of three different patient transfer networks based on data on transfers of patients with diagnosed HAIs, suspected HAIs, or of all patients. Our analyses show that these healthcare networks, the patient populations that comprise them and the patient movement patterns are heterogeneous and centralized. Despite the differences in patient populations, the HAI-specific and suspected-HAI healthcare networks have the same underlying structure as that of the general healthcare network. We identify key hospital centers, patient flow trajectories, at both the regional and department (county) level that may serve as a basis for proposing novel wide-scale infection control strategies.

UV irradiation is a major environmental factor causing skin dryness, aging and cancer. UVB in particular triggers cumulative DNA damage, oxidative stress and mitochondrial dysfunction. The objective of our study was to provide both qualitative and quantitative analysis of how mitochondria respond to UVB irradiation in normal human epidermal keratinocytes (NHEK) of healthy donors, with the rationale that monitoring mitochondrial shape will give an indication of cell population fitness and enable the screening of bioactive agents with UVB-protective properties. Our results show that NHEK undergo dose-dependent mitochondrial fragmentation after exposure to UVB. In order to obtain a quantitative measure of this phenomenon, we implemented a novel tool for automated quantification of mitochondrial morphology in live cells based on confocal microscopy and computational calculations of mitochondrial shape descriptors. This method was used to substantiate the effects on mitochondrial morphology of UVB irradiation and of knocking-down the mitochondrial fission-mediating GTPase Dynamin-related protein 1 (DRP1). Our data further indicate that all the major mitochondrial dynamic proteins are expressed in NHEK but that their level changes were stronger after mitochondrial uncoupler treatment than following UVB irradiation or DRP1 knock-down. Our system and procedures might be of interest for the identification of cosmetic or dermatologic UVB-protective agents.

Bovine coronaviruses (BCoVs) are widespread around the world and cause enteric or respiratory infections among cattle. The current study includes 13 samples from BCoVs collected in Normandy during an 11-year period (from 2003 to 2014), 16 French HCoV-OC43s, and 113 BCoVs or BCoVs-like sequence data derived from partial or complete genome sequences available on GenBank. According to a genotyping method developed previously for HCoV-OC43, BCoVs and BCoVs-like are distributed on three main sub-clusters named C1, C2, and C3. Sub-cluster C1 includes BCoVs and BCoVs-like from America and Asia. Sub-cluster C2 includes BCoVs from Europe. Sub-cluster C3 includes prototype, vaccine, or attenuated BCoV strains. The phylogenetic analyses revealed the monophyletic status of the BCoVs from France reported here for the first time. Moreover, BCoV exhibits a relative genetic stability when compared to HCoV-OC43 we previously described from the same region. The numerous recombination detected between HCoV-OC43 were much less frequent for BCoV. The analysis points thus to the influence of different evolutive constraints in these two close groups., Graphical abstract Image 1, Highlight • We develop a genotyping methodology for BCoVs. • We report first BCoV partial genomic data from France. • We observe a different evolutive patterns for the BCoV and HCoV-OC43. • We don't report the existence of recombinant variants among BCoVs. • We show a geographical distribution of BCoVs.

International audience; BackgroundDespite the absence of internal membranes, the nucleus of eukaryotic cells is spatially organized, with chromosomes and individual loci occupying dynamic, but nonrandom, spatial positions relative to nuclear landmarks and to each other. These positional preferences correlate with gene expression and DNA repair, recombination, and replication. Yet the principles that govern nuclear organization remain poorly understood and detailed predictive models are lacking.ResultsWe present a computational model of dynamic chromosome configurations in the interphase yeast nucleus that is based on first principles and is able to statistically predict the positioning of any locus in nuclear space. Despite its simplicity, the model agrees with extensive previous and new measurements on locus positioning and with genome-wide DNA contact frequencies. Notably, our model recapitulates the position and morphology of the nucleolus, the observed variations in locus positions, and variations in contact frequencies within and across chromosomes, as well as subchromosomal contact features. The model is also able to correctly predict nuclear reorganization accompanying a reduction in ribosomal DNA transcription, and sites of chromosomal rearrangements tend to occur where the model predicted high contact frequencies.ConclusionsOur results suggest that large-scale yeast nuclear architecture can be largely understood as a consequence of generic properties of crowded polymers rather than of specific DNA-binding factors and that configurations of chromosomes and DNA contacts are dictated mainly by genomic location and chromosome lengths. Our model provides a quantitative framework to understand and predict large-scale spatial genome organization and its interplay with functional processes.

Background Complex malaria infections are defined as those containing more than one genetically distinct lineage of Plasmodium parasite. Complexity of infection (COI) is a useful parameter to estimate from patient blood samples because it is associated with clinical outcome, epidemiology and disease transmission rate. This manuscript describes a method for estimating COI using likelihood, called COIL, from a panel of bi-allelic genotyping assays. Methods COIL assumes that distinct parasite lineages in complex infections are unrelated and that genotyped loci do not exhibit significant linkage disequilibrium. Using the population minor allele frequency (MAF) of the genotyped loci, COIL uses the binomial distribution to estimate the likelihood of a COI level given the prevalence of observed monomorphic or polymorphic genotypes within each sample. Results COIL reliably estimates COI up to a level of three or five with at least 24 or 96 unlinked genotyped loci, respectively, as determined by in silico simulation and empirical validation. Evaluation of COI levels greater than five in patient samples may require a very large collection of genotype data, making sequencing a more cost-effective approach for evaluating COI under conditions when disease transmission is extremely high. Performance of the method is positively correlated with the MAF of the genotyped loci. COI estimates from existing SNP genotype datasets create a more detailed portrait of disease than analyses based simply on the number of polymorphic genotypes observed within samples. Conclusions The capacity to reliably estimate COI from a genome-wide panel of SNP genotypes provides a potentially more accurate alternative to methods relying on PCR amplification of a small number of loci for estimating COI. This approach will also increase the number of applications of SNP genotype data, providing additional motivation to employ SNP barcodes for studies of disease epidemiology or control measure efficacy. The COIL program is available for download from GitHub, and users may also upload their SNP genotype data to a web interface for simple and efficient determination of sample COI. Electronic supplementary material The online version of this article (doi:10.1186/1475-2875-14-4) contains supplementary material, which is available to authorized users.

International audience; COV2HTML is an interactive web interface, which is addressed to biologists, and allows performing both coverage visualization and analysis of NGS alignments performed on prokaryotic organisms (bacteria and phages). It combines two processes: a tool that converts the huge NGS mapping or coverage files into light specific coverage files containing information on genetic elements; and a visualization interface allowing a real-time analysis of data with optional integration of statistical results. To demonstrate the scope of COV2HTML, the program was tested with data from two published studies. The first data were from RNA-seq analysis of Campylobacter jejuni, based on comparison of two conditions with two replicates. We were able to recover 26 out of 27 genes highlighted in the publication using COV2HTML. The second data comprised of stranded TSS and RNA-seq data sets on the Archaea Sulfolobus solfataricus. COV2HTML was able to highlight most of the TSSs from the article and allows biologists to visualize both TSS and RNA-seq on the same screen. The strength of the COV2HTML interface is making possible NGS data analysis without software installation, login, or a long training period. A web version is accessible at https://mmonot.eu/COV2HTML/. This website is free and open to users without any login requirement.