ABSTRACT: Biopsies were acquired from human donors and analyzed with deep proteomics using diaPASEF on a TIMSTOF Flex. I'll update the rest of the description if I can get the files to accession.
Project description:Data independent acquisition (DIA or DIA/SWATH ) mass spectrometry has emerged as a primary measurement strategy in the field of quantitative proteomics. diaPASEF is a recent adaptation that leverages trapped ion mobility spectrometry (TIMS) to improve selectivity and increase sensitivity. The complex fragmentation spectra generated by co-isolation of peptides in DIA mode are most typically analyzed with reference to prior knowledge in the form of spectral libraries. The best established method for generating libraries uses data dependent acquisition (DDA) mode, or DIA mode if appropriately deconvoluted, often including offline fractionation to increase depth of coverage,to create spectral libraries. More recently strategies for spectral library generation based on gas phase fractionation (GPF), where a representative sample is injected serially using narrow window DIA methods designed to cover different slices of the precursor space, have been introduced and performed comparably to deep offline fractionation-based libraries for DIA data analysis. Here, we investigated whether an analogous GPF-based library building approach that accounts for the ion mobility (IM) dimension is useful for the analysis of diaPASEF data and can remove the need for offline fractionation. To enable a rapid library development approach for diaPASEF we designed a GPF acquisition scheme covering the majority of multiply charged precursors in the m/z vs 1/K0 space requiring 7 injections of a representative sample and compared this with libraries generated by direct deconvolution-based analysis of diaPASEF data or by deep offline fractionation and ddaPASEF. . We found that the GPF based library outperformed library generation by direct deconvolution of the diaPASEF data, and performed comparably to deep offline fractionation libraries, when analysing diaPASEF data acquired from 200ng of commercial HeLa digest. With the ion mobility integrated GPF scheme we establish a pragmatic approach to rapid and comprehensive library generation for the analysis of diaPASEF data.
Project description:Data independent acquisition (DIA or DIA/SWATH ) mass spectrometry has emerged as a primary measurement strategy in the field of quantitative proteomics. diaPASEF is a recent adaptation that leverages trapped ion mobility spectrometry (TIMS) to improve selectivity and increase sensitivity. The complex fragmentation spectra generated by co-isolation of peptides in DIA mode are most typically analyzed with reference to prior knowledge in the form of spectral libraries. The best established method for generating libraries uses data dependent acquisition (DDA) mode, or DIA mode if appropriately deconvoluted, often including offline fractionation to increase depth of coverage,to create spectral libraries. More recently strategies for spectral library generation based on gas phase fractionation (GPF), where a representative sample is injected serially using narrow window DIA methods designed to cover different slices of the precursor space, have been introduced and performed comparably to deep offline fractionation-based libraries for DIA data analysis. Here, we investigated whether an analogous GPF-based library building approach that accounts for the ion mobility (IM) dimension is useful for the analysis of diaPASEF data and can remove the need for offline fractionation. To enable a rapid library development approach for diaPASEF we designed a GPF acquisition scheme covering the majority of multiply charged precursors in the m/z vs 1/K0 space requiring 7 injections of a representative sample and compared this with libraries generated by direct deconvolution-based analysis of diaPASEF data or by deep offline fractionation and ddaPASEF. . We found that the GPF based library outperformed library generation by direct deconvolution of the diaPASEF data, and performed comparably to deep offline fractionation libraries, when analysing diaPASEF data acquired from 200ng of commercial HeLa digest. With the ion mobility integrated GPF scheme we establish a pragmatic approach to rapid and comprehensive library generation for the analysis of diaPASEF data.
Project description:This study optimized identification rate and reproducibility of an untargeted diaPASEF approach for quantitative peptide profiling of hydrolyzed infant formula. For this, the impact of variable window widths as well as major acquisition parameters, such as the precursor coverage, number of diaPASEF scans, number of ion mobility windows and the resulting cycle time were evaluated.
Project description:We optimized the parameters of CCS range, polygon scan region, ramp time, and isolation window width to achieve high-depth proteome analysis using the timsTOF HT. As a result, we developed Thin-diaPASEF, which was optimized with a CCS range of 0.7–1.3, a ramp time of 150 ms, an isolation window width of 26 Th (with an overlap width of 1 Th), and a polygon area focused on regions where precursors accumulate. Thin-diaPASEF was then compared with existing methods, including py-diAID PASEF, slice-PASEF, and synchro-PASEF. The results demonstrated that Thin-diaPASEF achieved superior protein identification.
Performance evaluation of Thin-diaPASEF revealed the identification of approximately 9,400 proteins with a sample injection of 500 ng and an analysis time of 100 min. Finally, we applied Thin-diaPASEF to plasma proteome analysis. We compared three sample preparation methods: an improved LEL method based on our previously reported plasma and serum preparation approach, Seer’s nanoparticle-based method, and the conventional Top14 column-based method. As a result, the improved LEL method successfully identified 5,378 proteins at an analysis throughput of 24 samples per day.
Project description:Transcriptional profiling of colon epithelial biopsies from ulcerative colitis patients and healthy control donors. Study aims to survey and analyze variation from disease in different GI regions. Keywords: disease state analysis
Project description:Genome-wide transcriptional profiling of colonic biopsies endoscopically acquired from the rectosigmoid area of healthy donors and UC patients.
Project description:In the present study 23 participants completed three months of supervised aerobic exercise training of one leg (training period 1) followed by 9 months of rest before 12 of the participants completed a second exercise training period (training period 2) of three months of both legs. Skeletal muscle biopsies have been collected before and after the training periods. We have compared trained leg with untrained leg and studied gene and isoform expression. Additional samples included in this study has been previously submitted (GEO accession number GSE58387 and GSE60590).
Project description:ADRs (adverse drug reactions) are one of the main reasons for treatment discontinuation or alterations in dose regimens in clinical settings. Chemotherapy-induced ADRs are common, especially gastrointestinal-induced ones. Within TransQST (transqst.org), one of the main goal is to improve the in vitro-in vivo translation in toxicological studies, as well as translation between non-clinical species (such as rat and mouse) and humans. This experimental setup therefore aimed to investigate the effects of capecitabine, which is activated into 5-FU in the body, on advanced breast cancer patients. Healthy colon tissue was collected from the patients before and after the first cycle of the monotherapy, which consists of 2 weeks treatment followed by 1 week rest. Each patient was their own control sample. Transcriptomic data collected from the colon biopsies was compared with previous data collected from colon organoids to verify for the translatability of the in vitro model to humans. This dataset is part of the TransQST collaboration.
Project description:Sedentary lifestyle, chronic disease or microgravity can cause muscle deconditioning that then has an impact on other physiological systems. An example is the nervous system, which is adversely affected by decreased physical activity resulting in increased incidence of neurological problems such as chronic pain. We sought to better understand how this might occur by conducting RNA sequencing experiments on muscle biopsies from human volunteers in a 5-week bed-rest study with an exercise intervention arm. We also used a computational method for examining ligand-receptor interactions between muscle and human dorsal root ganglion (DRG) neurons, the latter of which play a key role in nociception and are generators of signals responsible for chronic pain. We identified 1352 differentially expressed genes (DEGs) in bed rest subjects without an exercise intervention but only 132 DEGs in subjects with the intervention. Thirty-six genes were shared between the exercise and no intervention groups. Among 591 upregulated muscle genes in the no intervention arm, 26 of these were ligands that have receptors that are expressed by human DRG neurons.