Project description:Investigating the evolution of Escherichia coli in microgravity offers valuable insights into microbial adaptation to extreme environments. Here the effects of simulated microgravity (SµG) on gene expression of E. coli REL606, a strain evolved terrestrially for 35 years is explored. We evaluated the transcriptomic changes for glucose-limited and glucose-replete conditions over 24 hours which illustrate that SµG increased the expression of stress response and cell membrane-related genes, particularly under glucose-limited conditions. A machine learning model predicted that glucose-limited SµG impacts the cellular membrane, while glucose-replete SµG also inhibits protein synthesis at stationary phase. These findings highlight the transcriptomic and physiological adaptations of E. coli to short term microgravity, offering a foundation for future research into the long-term effects of space conditions on bacterial evolution.
Project description:Comparative genomic hybridization between Escherichia coli strains to determine core and pan genome content of clinical and environmental isolates Two color experiment, Escherichia coli Sakai (reference), clinical and environmental Escherichia coli strains (testers): At least two replicates including a single dye swap for each reference-tester comparison
Project description:Comparative genomic hybridization between Escherichia coli strains to determine core and pan genome content of clinical and environmental isolates
Project description:Understanding constraints which shape antibiotic resistance is key for predicting and controlling drug resistance. Here, we performed high-throughput laboratory evolution of Escherichia coli. The transcriptome, resistance, and genomic profiles for the evolved strains in 48 environments were quantitatively analyzed. By analyzing the quantitative datasets through interpretable machine learning techniques, the emergence of low dimensional phenotypic states within the 192 strains was observed. Further analysis revealed the underlying biological processes responsible for the distinct states. We also report a novel constraint which leads to decelerated evolution. These findings bridge the genotypic, gene expression, and drug resistance space, and lead to a comprehensive understanding of constraints for antibiotic resistance.
2020-10-12 | GSE137348 | GEO
Project description:A novel clinical mNGS-based machine learning model for rapid antimicrobial susceptibility testing of Acinetobacter baumannii
Project description:Primary objectives: The study investigates whether a Escherichia coli Nissle-suspenison has a (preventive) antidiarrheal effect in patients with tumors who are treated with chemotherapeutic schemes which are associated with increased occurances of diarrhea. Diarrhea caused by treatment are thought to be reduced in intensity and/or frequency by the treatment with Escherichia coli Nissle-Suspension.
Primary endpoints: Common toxicity criteria (CTC) for diarrhea
Project description:To investigate the relationship between RNA polymerase binding and transcription ChIP-seq on the common house-keeping SigmaD and RNA polymerase beta subunit were coupled with RNA-seq at various growth phases of Escherichia coli in rich media.
