Project description:understanding the biology of methicillin resistant staphylococcus aureus (MRSA) is crucialto unlocking insights for new targets in the fight against this pathogen, there is howeverlimited reports of methadological approaches for carrying proteomic and metabolomic profiling in S.aureus. Therefore, we describe the use of a dual-functionality methanol extraction method for the concurrent extraction of protein and metabolites from S.aureus and reporton the comparative analysis of the proteomic and metabolomic profiles of MRSA versus methicillin sensitive S. aureus (MSSA). Using a reference strain from MRSA and MSSA, we first compared the MRSA proteome extracted using the methanol method to the one from the traditionally used urea method. Then using the methanol extraction method, we compared the proteome and metabolome of MRSA versus MSSA. Through this study, we demonstrated the effectivnessof the methanol-based-dual-extraction method, providing simultaneous insights into the proteomic and metabolomic landscapes of S.aureus strains, demonstrating the utility of proteomic and metabolomic profiling for elucidating the biological basis of antimicrobial resistance
Project description:The raw proteomics data in the manuscript “Single-cell RNA-sequence reveals that the switching of the transcriptional profiles of cysteine-related genes alter the virulence of Entamoeba histolytica”
Project description:We report the transcriptome profiles (RNA seq) of three different co-isolates of S.aureus that have been identified and isolated in both laboratory and infective scenarios. The transcriptome profiles were generated by deep sequencing and transcript levels assessed. For this the raw reads underwent quality-trimming (using the FastX suite), polyA-clipping, size filtering, mapping to the reference genome, coverage calculation, gene wise expression quantification followed by differential gene expression analysis (all done by the tool "READemption" (Förstner et al., unpublished) using "segemehl" (Hoffmann et al., 2009) and "DESeq" (Anders et al., 2010). RT-PCR as well as phenotypical assays were further used to validate the data. Differential gene expression between the isolates was observed in 4% (116 of 2774 genes). This had a significant impact on the physiology of each strain. RNA profiles of 3 different subpopulations of S.aureus generated by deep sequencing
Project description:Staphylococcus aureus is the most common cause of hospital-acquired infection. In healthy hosts outside of the health care setting, S.aureus is a frequent colonizer of the human nose but rarely causes severe invasive infection such as bacteremia, endocarditis, or osteomyelitis. To identify genes associated with community-acquired invasive isolates, regions of genomic variability, and the S.aureus population structure, we compared 61 community-acquired invasive isolates of S.aureus and 100 nasal carriage isolates from healthy donors using a microarray spotted with PCR products representing every gene from the seven S.aureus sequencing projects. The core genes common to all strains were identified, and 10 dominant lineages of S.aureus were clearly discriminated. Each lineage carried a unique combination of hundreds of core variable (CV) genes scattered throughout the chromosome, suggesting a common ancestor but early evolutionary divergence. Many CV genes are regulators of virulence genes or known or predicted to be expressed on the bacterial surface and to interact with the host during nasal colonization and infection. Within each lineage, isolates showed substantial variation in the carriage of mobile genetic elements and their associated virulence and resistance genes, indicating frequent horizontal transfer. However, we were unable to identify any association between lineage or gene and invasive isolates. We suggest that the S.aureus gene combinations necessary for invasive disease may also be necessary for nasal colonization and that community-acquired invasive disease is strongly dependent on host factors. Data is also available from http://bugs.sgul.ac.uk/E-BUGS-33