Project description:Background: Previous studies comparing quantitative proteomics and microarray data have generally found poor correspondence between the two. We hypothesised that this might in part be because the different assays were targeting different parts of the expressed genome and might therefore be subjected to confounding effects from processes such as alternative splicing. Results: Using a genome database as a platform for integration, we combined quantitative protein mass spectrometry with Affymetrix Exon array data at the level of individual exons. We found significantly higher degrees of correlation than have been previously observed (r=0.808). The study was performed using cell lines in equilibrium in order to reduce a major potential source of biological variation, thus allowing the analysis to focus on the data integration methods in order to establish their performance. Conclusion: We conclude that much of the variation observed when integrating microarray and proteomics data may occur as a consequence both of the data analysis and of the high granularity to which studies have until recently been limited. The approach opens up the possibility for the first time of considering combined microarray and proteomics datasets at the level of individual exons and isoforms, important given the high proportion of alternative splicing observed in the human genome.
Project description:We report the characterization of the major regulator of virulence gene expression (CovR) in Group B Streptococcus. The ChIP-seq experiments define the binding of CovR on the chromosome of the BM110 strain, a representative of the hypervirulent GBS lineage responsible of neonatal meningitis. Regulatory evolution of CovR signaling was investigated by comparing ChIP-seq done in parallel in a second GBS clinical isolate (NEM316) not belonging to the hypervirulent lineage.
Project description:The aim of this study was to investigate the response of human brain endothelial cells to bacterial (group B streptococcus, GBS) infection. Results: GBS WT strain infection results in a specific gene induction pattern that is different from the pilA mutant, but not other mutants such as pilB and srr-1. Conclusion: These findings suggest that the GBS PilA protein contributes to gene induction in brain endothelium.
Project description:Microproteins, as hidden players in the proteomic club, are encoded by small open reading frames (sORFs) and have garnered increasing attention in recent years. T cells play a critical role in the immune system's response to cancer, however, the exploration of novel microproteins in T cells remains an unexplored area. In this study, we employed an integrated approach combined nascent protein profiling and quantitative global proteomics to identify novel microproteins in human T cells.
Project description:Methanococcus maripaludis is a methanogenic archaeon. Within its genome, there are two operons for membrane associated hydrogenases, eha and ehb. To investigate the regulation of ehb on the cell, an S40 mutant was constructed in such a way that a portion of the ehb operon was replaced by pac cassette in the wild type parental strain S2 (done by Whitman's group at the University of Georgia). The S40 and S2 strains were grown in 14N and 15N media with acetate separately. A biological replicate was made by switching the media. Mass spectrometry based quantitative proteomics were done on the mixtures to investigate the differences in expression patterns between S40 and S2. Keywords: isotope labeling mass spectrometry, quantitative proteomics
Project description:To identify the role of the endolysosomal (EL) protein network in atrial fibrillation (AF), we applied a newly developed organelle isolation method to the AF goat model. To accomplish the goal, we used proteomics, transcriptomics, integrated analysis, enzyme assays, electron tomography, and western blotting and identified several regulating EL proteins, related protein networks and pathways.
Project description:Delirium is a common postoperative complication among older patients with many adverse outcomes. Due to lack of validated biomarkers, prediction and monitoring of delirium by biological testing is not currently feasible. Circulating proteins in cerebrospinal fluid (CSF) may reflect biological processes causing delirium. Our goal was to discover and investigate candidate protein biomarkers in preoperative CSF that were associated with development of postoperative delirium in older surgical patients. We employed a nested case–control study design coupled with high multiplex affinity proteomics analysis to measure 1305 proteins in preoperative CSF. Twenty-four matched delirium cases and non-delirium controls were selected from the Healthier Postoperative Recovery (HiPOR) cohort and the associations between preoperative protein levels and postoperative delirium were assessed using t-test statistics with further analysis by systems biology to elucidate delirium pathophysiology. Proteomics analysis identified 32 proteins in preoperative CSF that significantly associate with delirium (t-test p<0.05). Due to the limited sample size these proteins did not remain significant by multiple hypothesis testing using the Benjamini-Hochberg correction and q-value method. Three algorithms were applied to separate delirium cases from non-delirium controls. Hierarchical clustering classified 40/48 case-control samples correctly, principal components analysis separated 43/48. The receiver operating characteristic curve yielded an area under the curve [95% confidence interval] of 0.91 [0.80-0.97]. Systems biology analysis identified several key pathways associated with risk of delirium: inflammation, immune cell migration, apoptosis, angiogenesis, synaptic depression and neuronal cell death. Proteomics analysis of preoperative CSF identifies 32 proteins that might discriminate individuals who subsequently develop postoperative delirium from matched control samples. These proteins are potential candidate biomarkers for delirium and may play a role in its pathophysiology.
Project description:We used Illumina NGS to measure mRNA levels and perform subsequent differential expression analysis between wild type and RM system deficient strains of Streptococcus pyogenes