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
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:This study compared the therapeutic effects of medium cut-off (MCO) and high flux (HF) dialyzers using metabolomics and proteomics. This was a single-center prospective trial of 20 patients receiving maintenance hemodialysis (HD). A consecutive dialyzer membrane was used for 15-week study periods as follows: 1st HF dialyzer, MCO dialyzer, 2nd HF dialyzer, for 5 weeks respectively. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis was used to identify proteins.
Project description:Plasma proteins were digested with trypsin and the resulting peptides were analyzed by nanoLC–MS/MS on an EASY-nLC 1200 system coupled to an Orbitrap Exploris 480 mass spectrometer. Peptides were loaded onto a self-packed C18 reversed-phase column (25 cm × 100 μm i.d.) and separated at 500 nL/min using a linear gradient with solvent A (0.1% formic acid, 2% acetonitrile in water) and solvent B (0.1% formic acid, 90% acetonitrile in water): 4–20% B (0–68 min), 20–32% B (68–82 min), 32–80% B (82–86 min), and 80% B wash (86–90 min). The MS was operated with FAIMS using compensation voltages of −70 V and −45 V. Full MS scans were acquired at 60,000 resolution over m/z 400–1,200, and MS/MS scans at 30,000 resolution (first mass m/z 110). The top 15 precursors were selected for HCD (NCE 27%) with 30 s dynamic exclusion; AGC target was 75%, intensity threshold 10,000 ions/s, and maximum injection time 100 ms. TurboTMT was disabled for label-free quantification. Raw data were processed in Proteome Discoverer v2.4.1.15 and searched against the Homo_sapiens_9606_PR_20201214.fasta database (75,777 entries) with a reverse decoy strategy. Trypsin was specified with up to two missed cleavages; minimum peptide length was 6 aa. Carbamidomethyl (C) was set as a fixed modification; oxidation (M), protein N-terminal acetylation, methionine loss, and methionine loss + acetylation were set as variable modifications (≤3 variable modifications per peptide). Precursor and fragment mass tolerances were 10 ppm and 0.02 Da, respectively. FDR was controlled at <1% at the PSM, peptide, and protein levels. For label-free quantification, peptide intensities were normalized by peptide-wise mean centering across samples followed by within-sample median normalization, and protein abundances were summarized as the median of normalized peptide values per protein for downstream analyses.