Project description:Parkinson disease (PD) is a neurodegenerative disease characterized by the accumulation of alpha-synuclein (SNCA) and other proteins in aggregates termed âLewy Bodiesâ within neurons. PD has both genetic and environmental risk factors, and while processes leading to aberrant protein aggregation are unknown, past work points to abnormal levels of SNCA and other proteins. Although several genome-wide studies have been performed for PD, these have focused on DNA sequence variants by genome-wide association studies (GWAS) and on RNA levels (microarray transcriptomics), while genome-wide proteomics analysis has been lacking. After appropriate filters, proteomics identified 3,558 unique proteins and 283 of these (7.9%) were significantly different between PD and controls (q-value<0.05). RNA-sequencing identified 17,580 protein-coding genes and 1,095 of these (6.2%) were significantly different (FDR p-value<0.05), but only 166 of the FDR significant protein-coding genes (0.94%) were present among the 3,558 proteins characterized. Of these 166, eight genes (4.8%) were significant in both studies, with the same direction of effect. Functional enrichment analysis of the proteomics results strongly supports mitochondrial-related pathways, while comparable analysis of the RNA-sequencing results implicates protein folding pathways and metallothioneins. Ten of the implicated genes or proteins co-localized to GWAS loci. Evidence implicating SNCA was stronger in proteomics than in RNA-sequencing analyses. Notably, differentially expressed protein-coding genes were more likely to not be characterized in the proteomics analysis, which lessens the ability to compare across platforms. Combining multiple genome-wide platforms offers novel insights into the pathological processes responsible for this disease by identifying pathways implicated across methodologies. The study consists of mRNA-Seq (29 PD, 44 neurologically normal controls) and three-stage Mass Spectrometry Tandem Mass Tag Proteomics (12 PD, 12 neurologically normal controls) performed in post-mortem BA9 brain tissue. The proteomics samples are a subset of the RNA-Seq samples.
Project description:Prokaryotes are, due to their moderate complexity, particularly amenable to the comprehensive identification of the protein repertoire expressed under different conditions. We applied a generic strategy to identify a complete expressed prokaryotic proteome, which is based on the analysis of RNA and proteins extracted from matched samples. Saturated transcriptome profiling by RNA-seq provided an endpoint estimate of the protein-coding genes expressed under two conditions which mimic the interaction of Bartonella henselae with its mammalian host. Directed shotgun proteomics experiments were carried out on four subcellular fractions. By specifically targeting proteins which are short, basic, low abundant and membrane localized, we could eliminate their initial under-representation compared to the estimated endpoint. A total of 1,250 proteins were identified with an estimated false discovery rate below 1%. This represents 85% of all distinct annotated proteins and around 90% of the expressed protein-coding genes. Genes, whose transcripts were detected, but not their corresponding protein products, were found highly enriched in several genomic islands. Additionally, genes that lacked an ortholog and a functional annotation were not detected at the protein level, and possibly include over-predicted genes in genome annotations. Furthermore, a dramatic membrane proteome re-organization was observed including differential regulation of autotransporters, adhesins and hemin binding proteins. Particularly noteworthy was the complete membrane proteome coverage which included expression of all members of the VirB/D4 type IV secretion system, a key virulence factor. Transcriptome and proteome analysis of B.henselae in two conditions and duplicates: uninduced and induced for host invasion.
Project description:Peripheral blood monocytes were differentiated into macrophages, starved for 24h hours, and treated for 3h with LPA 18:0, 20:4 or a mix of LPAs similar to the composition in ascites (1 µM 16:0 + 0.25 µm 18:0 + 0.5 µM 18:1 + 1.625 µM 18:2 + 1.625 µM 20:4). RNA expression was measured via QuantSeq.
Project description:blanc-08-01_2012_01_rnapaths_03 - rnapaths--3_02/2012 - Identify the transcript overlap and specificity between the PTGS and decapping/exoribonuclease pathways b identifying transcripts that are significantly changed in double mutants versus single mutants, and transcripts that are commonly changed among the single and double mutants compared to WT. - Identify transcripts that are significantly changed in double mutants (L1 vcs sgs2) (xrn4-5/sgs3-11) versus their respective single mutants (L1 vcs and L1 sgs2) (xrn4-5 and sgs3-11) , and identify transcripts that are changed among the single and double mutants compared to WT (Col) reference or to mutant L1 reference. 20 dye-swap - genotype comparaison