Ontology highlight
ABSTRACT:
PROVIDER: PRJNA741062 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Streptococcus dysgalactiae subspecies equisimilis (SDSE) is a Gram-positive bacterial pathogen that infects humans and is closely related to group A streptococcus (GAS). Compared to GAS, far less is known about SDSE pathobiology. Increased rates of invasive SDSE infections have recently been reported in many countries. One SDSE emm type, stG62647, is known to cause severe diseases, including necrotizing soft-tissue infections, endocarditis, and osteoarticular infections. To increase our understanding of the molecular pathogenesis of stG62647 SDSE isolates causing human infections, we sequenced to closure the genomes of 120 stG62647 SDSE isolates. The genomes varied in size from 2.1 to 2.24 megabase pairs. Consistent with previous data, the great majority of stG62647 isolates had IS1548 integrated into the silB gene, thereby inactivating it. Regions of difference in gene content, including putative mobile genetic elements, were the largest source of genomic diversity. All 120 stG62647 isolates were assayed for virulence using a well-established mouse model of necrotizing myositis. An unexpectedly wide range of virulence was identified (20% to 95%), as assessed by near-mortality data. To explore the molecular mechanisms underlying virulence differences, we analyzed RNAseq transcriptome profiles for 38 stG62647 isolates (comprising the 19 least and most virulent) grown in vitro. Genetic polymorphisms were identified from whole-genome sequence data. Collectively, the results suggest that these SDSE isolates use multiple genetic pathways to achieve an altered virulence phenotype. Our study integrates genomic, mouse virulence, and RNAseq data to advance our understanding of SDSE pathobiology and its molecular pathogenesis.
2024-07-20 | GSE272047 | GEO
Project description:Streptococcus pyogenes (Group A Streptococcus: GAS) is a major human pathogen that causes streptococcal pharyngitis, skin and soft-tissue infections, and life-threatening conditions such as streptococcal toxic shock syndrome (STSS). A large number of virulence-related genes are encoded on GAS genomes, which are involved in host-pathogen interaction, colonization, immune invasion, and long-term survival within hosts, causing the diverse symptoms. Here, we investigated the interaction between GAS-derived extracellular vesicles and host cells in order to reveal pathogenicity mechanisms induced by GAS infection.
2021-05-17 | PXD026040 | JPOST Repository
Project description:Necrotizing soft-tissue infections (NSTIs) have multiple causes, risk factors, anatomical locations, and pathogenic mechanisms. In patients with NSTI, circulating metabolites may serve as substrate having impact on bacterial adaptation at the site of infection. Metabolic signatures associated with NSTI may reveal potential be useful as diagnostic and prognostic markers, as well as novel targets for therapy. This study used untargeted metabolomics analyses of plasma from NSTI patients (n=34) and healthy (non-infected) controls (n=24) to identify the metabolic signatures and connectivity patterns among metabolites associated with NSTI.
2019-10-28 | ST001270 | MetabolomicsWorkbench
Project description:Primary objectives: The primary objective is to investigate circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
Primary endpoints: circulating tumor DNA (ctDNA) via deep sequencing for mutation detection and by whole genome sequencing for copy number analyses before start (baseline) with regorafenib and at defined time points during administration of regorafenib for treatment efficacy in colorectal cancer patients in terms of overall survival (OS).
| 2533916 | ecrin-mdr-crc
Project description:Streptococcus pyogenes (group A streptococci; GAS) is the main causative pathogen of monomicrobial necrotizing soft tissue infections (NSTIs). To resist immuno-clearance, GAS adapt their genetic information and/or phenotype to the surrounding environment. Hyper-virulent streptococcal pyrogenic exotoxin B (SpeB) negative variants caused by covRS mutations are enriched during infection. A key driving force for this process is the bacterial Sda1 DNase. Here, we identify another strategy resulting in SpeB-negative variants, namely reversible abrogation of SpeB secretion triggered by neutrophil effector molecules. Analysis of NSTI patient tissue biopsies revealed that tissue inflammation, neutrophil influx, and degranulation positively correlate with increasing frequency of SpeB-negative GAS clones. Using single colony proteomics, we show that GAS isolated directly from tissue express but do not secrete SpeB. Once the tissue pressure is lifted, GAS regain SpeB secreting function. Neutrophils were identified as the main immune cells responsible for the observed phenotype. Subsequent analyses identified hydrogen peroxide and hypochlorous acid as reactive agents driving this phenotypic GAS adaptation to the tissue environment. SpeB-negative GAS show improved survival within neutrophils and induce increased degranulation. Our findings provide new information about GAS fitness and heterogeneity in the soft tissue milieu and provide new potential targets for therapeutic intervention in NSTIs.
2023-10-24 | PXD040160 | Pride
Project description:Extracellular matrix (ECM) elasticity is perceived by cells via focal adhesion structures, which transduce mechanical cues into chemical signaling to conform cell behavior. Although the contribution of ECM compliance to the control of cell migration or division has been extensively studied, little has been reported regarding whole proteome adaptation to changes of mechanical forces. Uropathogenic E. coli (UPEC) are responsible of 70-95% of the Urinary Tract Infections (UTIs), comprising cystitis, prostatitis and pyelonephritis. These are recurrent or chronic infections causing significant costs in public health. UPEC produce the Cytotoxic Necrotizing Factor1 (CNF1) toxin, targeting one of the major host mechano-sensor and -adaptor, namely the actin cytoskeleton. We have discovered that the CNF1 and integrin-dependent invasion of cells by UPEC is highly dependent on ECM stiffness. Here we aim to analyze primary human cells treated or not with CNF1 and cultured on a fibronectin ECM of variable stiffness by label free shotgun proteomics, to bring new concepts on the manipulation of host tissue mechanics by pathogens.
2022-10-25 | PXD035396 | Pride
Project description:Staphylococcus aureus is a high-priority pathogen causing severe infections with high morbidity and mortality worldwide. Many S. aureus strains are methicillin-resistant (MRSA) or even multi-drug resistant. It is one of the most successful and prominent modern pathogens. An effective fight against S. aureus infections requires novel targets for antimicrobial and antistaphylococcal therapies. Recent advances in whole-genome sequencing and high-throughput techniques facilitate the generation of genome-scale metabolic models (GEMs). Among the multiple applications of GEMs is drug-targeting in pathogens. Hence, comprehensive and predictive metabolic reconstructions of S. aureus could facilitate the identification of novel targets for antimicrobial therapies. This review aims at giving an overview of all available GEMs of multiple S. aureus strains. We downloaded all 114 available GEMs of S. aureus for further analysis. The scope of each model was evaluated, including the number of reactions, metabolites, and genes.Furthermore, all models were quality-controlled using Mᴇᴍᴏᴛᴇ, an open-source application with standardized metabolic tests. Growth capabilities and model similarities were examined. This review should lead as a guide for choosing the appropriate GEM for a given research question. With the information about the availability, the format, and the strengths and potentials of each model, one can either choose an existing model or combine several models to create models with even higher predictive values. This facilitates model-driven discoveries of novel antimicrobial targets to fight multi-drug resistant S. aureus strains.
2022-02-16 | MODEL2007150002 | BioModels