Project description:Escherichia coli bloodstream infections are common and associated with high mortality. A key feature of E. coli is the lipopolysaccharide (LPS) O-antigen, which contributes to immune evasion during invasive infection. We analyzed serial E. coli isolates from patients with relapsed bacteremia and identified frequent disruption of O-antigen synthesis due to mutations in wbbL, resulting in a rough LPS (R-LPS) phenotype. E. coli with rough LPS isolates were more serum sensitive and less pathogenic in mice. Despite this apparent attenuation, 11 of 66 (18%) E. coli sequence type 131 bloodstream isolates in our cohort lacked O-antigen and were associated with significantly worse clinical outcomes, including septic shock and mortality. Using a recurrent bacteremia model, we show that R-LPS isolates partially evade protective immunity generated against smooth-LPS E. coli, highlighting the importance of host immune context in invasive disease.
2026-05-18 | GSE319702 | GEO
Project description:Characterization of Bacteria Causing Bloodstream Infection Through Whole Genome Sequencing
Project description:Tilapia Lake Virus (TiLV) poses a significant threat to global tilapia aquaculture, causing high mortality rates and severe economic losses. Despite its impact, the molecular mechanisms of TiLV-host interactions remain poorly understood. This study investigates the proteomic and phosphoproteomic changes in two piscine cell lines, E-11 and RHTiB, following TiLV infection.
Project description:Hantavirus infection causing zoonotic diseases with a high mortality rate in humans has long been a global public health concern. Over the past decades, accumulating evidences suggest that long noncoding RNAs (lncRNAs) play key regulatory roles in innate immunity. However, the involvement of host lncRNAs in hantaviral control remains uncharacterized. To explore the potential role of long non-coding RNAs in host innate immune responses, DGE analysis of HUVECs for whole genome profiling was performed at 24 hours post HTNV infection.
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.