Project description:Adult cardiac progenitor/stem cells (CPC/CSC) are multipotent resident populations involved in cardiac homeostasis and heart repair. Assisted by complementary RNAseq analysis, we defined the proteome fraction associable to specific CPC functions by comparison with human mesenchymal stem cells (MSC), the reference population for cell therapy. Label-free proteomics analysis identified 526 proteins expressed differentially in CPC. Quantitative iTRAQ analysis confirmed differential expression of a substantial proportion of these proteins expressed specifically in CPC relative to MSC. Systems biology analysis defined a clear overrepresentation of several categories related to enhanced angiogenic potential. The CPC plasma membrane compartment is comprised by 1595 proteins including a minimal signature of 167 proteins expressed preferentially in CPC. Of these core CPC functions, we selected a panel of 15 predicted cell surface markers and validated high differential expression of CDH5, CD200 and F11R in CPC.
Project description:Using mass spectrometry-based label-free quantitative (LFQ) proteomics analysis of in vitro differentiated murine Th17 and induced T regulatory (iTreg) cells. More than 4000 proteins covering almost all subcellular compartments were detected. Quantitative comparison of the protein expression profiles resulted in the identification of proteins specifically expressed in the Th17 and iTreg cells. Importantly, our combined analysis of proteome and gene expression data revealed protein expression changes that were not associated with changes at the transcriptional level.
Project description:This dataset includes raw label-free mass spectrometry proteomics data of different sinonasal tumor entities as well as normal sinonasal tissue. 72 samples were processed on a Q Exactive HF-X instrument coupled to an easy nanoLC 1200 system using one microgram of peptides and an 110 minutes gradient.
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:Using Mycoplasma pneumoniae as a model organism, we conditionally depleted the two essential ATP-dependent proteases (Lon and FtsH) of this bacterium, by engineering three strains carrying a Lon and/or FtsH inducible expression locus. An integrative comparative study combining label-free shotgun proteomics and RNA-seq allowed us to decipher the global cellular response to Lon and FtsH depletion and to define protease substrates in this genome-reduced organism.
Project description:Intra-tumour heterogeneity caused by clonal evolution is a major problem in cancer treatment stratification. To address this problem, we performed label-free quantitative proteomics on primary acute myeloid leukemia (AML) samples. We identified 50 leukemia-enriched plasma membrane (PM) proteins enabling the prospective isolation of genetically distinct subclones from individual AML patients. Subclones differed in their regulatory phenotype, drug sensitivity, growth and engraftment behavior, as determined by RNA sequencing, DNaseI hypersensitive site mapping, transcription factor occupancy analysis, in vitro culture and xenograft transplantation. Finally, we show that these markers can be used to identify and longitudinally track distinct leukemic clones in patients in routine diagnostics. Our study describes a strategy for a major improvement in stratifying cancer diagnosis and treatment.
Project description:CD4+ T cells play a key role in the adaptive immune system. Their subset, Th17 cells contribute to pathogenesis of inflammatory and autoimmune diseases and cancer. To reveal the Th17 cell-specific proteomic signature regulating Th17 cell differentiation and function in human we used a label-free mass spectrometry-based approach. To determine the degree of similarities and differences between the transcript and the protein levels, we performed a comprehensive analysis of the transcript-protein relationships. Comparison of the proteomics and RNA-sequencing data generated in this study during human Th17 differentiation revealed a high degree of overlap between the datasets. However, we found very limited overlap between the proteins differentially regulated in response to Th17 differentiation in human and mouse. Of the 758 and 397 proteins differentially regulated at 72h during Th17 specification in human and in mouse, respectively, only 33 were detected as differentially regulated in a similar fashion in both species. We validated a panel of selected proteins with known and unknown functions. Finally, using RNA interference (RNAi), we showed that SATB1 negatively regulates of human Th17 cell differentiation. To our knowledge, this study is the first to illustrate a comprehensive picture of the global protein landscape during early human Th17 cell differentiation. Poor overlap with recently reported mouse data underlines the importance of human studies for translational research.
Project description:Arabidopsis seedlings were grown for 1 week in Aradishes and then subjected to 5 min to 10 h of simulated microgravity using a 2D clinostat. RNA; proteins and metabolites were extracted and analyzed by RNA.seq and label free quantitative MS.