Bao Li Similar Datasets
Project description:Label-free absolute quantitative proteomics is commonly used for absolute quantification of the proteome or specific proteins of interest in various biological samples. Current label-free absolute protein quantification (APQ) methods determine MS1 intensities, MS2 spectral counts or intensities to absolutely quantify protein concentrations from data obtained from data-dependent acquisition (DDA). In recent years, label-free data-independent acquisition (DIA) has seen increasing use as a powerful tool for relative protein quantification. Here we present a novel label-free DIA-based absolute protein quantification (DIA-APQ) method for the absolute quantification of protein expressions from DIA data. To validate this method, both DDA and DIA experiments were performed on 36 individual human liver microsome and S9 samples. The DIA-APQ assay was able to quantify approximately twice as many proteins as the DDA MS1-based APQ method whereas protein concentrations determined by the two methods were comparable. To evaluate the accuracy of the DIA-APQ method, we absolutely quantified carboxylesterase 1 concentrations in human liver samples using an established SILAC internal standard-based proteomic assay; the SILAC results were consistent with those obtained from DIA-APQ analysis. Finally, we employed a unique algorithm in DIA-APQ to distribute the MS signals from shared peptides to different protein isoforms and successfully applied the DIA-APQ method to the absolute quantification of several drug-metabolizing enzyme isoforms in human liver microsomes. This novel DIA-based APQ method not only provides a powerful approach for absolutely quantifying entire proteomes and specific candidate proteins, but also has with the capacity differentiating protein isoforms.
2019-03-20 | PXD010912 | Pride
Project description:Transcriptional profiling in liver of 48 pigs (132 days of age) originated from two lines divergently selected for residual feed intake (RFI) : low-RFI pigs (RFIneg), high-RFI pigs (RFIpl). Both lines were offered isocaloric and isoproteic diets with contrasted energy source and nutrients: low fat, low fiber (LF) diet or a high fat, high fiber (HF)diet during 10 weeks. Effects of RFI selection, diet and interaction between diet and line were investigated.
2017-03-14 | GSE84091 | GEO
Project description:Despite data-independent acquisition (DIA) has been increasingly used for relative protein quantification, DIA-based label-free absolute quantification method has not been fully established. Here we present a novel DIA method using the TPA algorithm (DIA-TPA) for the absolute quantification of protein expressions in human liver microsomal and S9 samples. To validate this method, both data-dependent acquisition (DDA) and DIA experiments were conducted on 36 individual human liver microsome and S9 samples. The MS2-based DIA-TPA was able to quantify approximately twice as many proteins as the MS1-based DDA-TPA method, whereas protein concentrations determined by the two approaches were comparable. To evaluate the accuracy of the DIA-TPA method, we absolutely quantified carboxylesterase 1 concentrations in human liver S9 fractions using an established SILAC internal standard-based proteomic assay; the SILAC results were consistent with those obtained from DIA-TPA analysis. Finally, we employed a unique algorithm in DIA-TPA to distribute the MS signals from shared peptides to individual proteins or isoforms and successfully applied the method to the absolute quantification of several drug-metabolizing enzymes in human liver microsomes. In sum, the DIA-TPA method not only can absolutely quantify entire proteomes and specific proteins, but also has the capability quantifying proteins with shared peptides. SIGNIFICANCE: Data independent acquisition (DIA) has emerged as a powerful approach for relative protein quantification at the whole proteome level. However, DIA-based label-free absolute protein quantification (APQ) method has not been fully established. In the present study, we present a novel DIA-based label-free APQ approach, named DIA-TPA, with the capability absolutely quantifying proteins with shared peptides. The method was validated by comparing the quantification results of DIA-TPA with that obtained from stable isotope-labeled internal standard-based proteomic assays.
| S-EPMC6533198 | biostudies-literature
Project description:The majority of large-scale proteomics quantification methods yield long lists of quantified proteins that are often difficult to interpret and poorly reproduced. Computational approaches are required to analyze such intricate quantitative proteomics data sets. We propose a statistical approach to computationally identify protein sets (e.g., Gene Ontology (GO) terms) that are significantly enriched with abundant proteins with reproducible quantification measurements across a set of replicates. To this end, we developed PSEA-Quant, a protein set enrichment analysis algorithm for label-free and label-based protein quantification data sets. It offers an alternative approach to classic GO analyses, models protein annotation biases, and allows the analysis of samples originating from a single condition, unlike analogous approaches such as GSEA and PSEA. We demonstrate that PSEA-Quant produces results complementary to GO analyses. We also show that PSEA-Quant provides valuable information about the biological processes involved in cystic fibrosis using label-free protein quantification of a cell line expressing a CFTR mutant. Finally, PSEA-Quant highlights the differences in the mechanisms taking place in the human, rat, and mouse brain frontal cortices based on tandem mass tag quantification. Our approach, which is available online, will thus improve the analysis of proteomics quantification data sets by providing meaningful biological insights.
| S-EPMC4258137 | biostudies-literature
Project description:Plant-based protein sources play an important role in aquaculture by dwindling fish meal to sustainable levels. However, the use of such feedstuffs requires nutrient supplementation to fulfil fish nutritional requirements. This work addressed the response in the liver of farmed fish to dietary methionine (Met), assessing at the same time the growth performance. Fish were fed at suboptimal levels of dietary Met (0.77% w/w; M0.65 diet), within (1% w/w Met; M0.85 diet)and above(1.36 % w/w Met (M1.25 diet); 1.66% w/w Met(M1.5 diet)) the estimated requirement for this species, in a total of four tested conditions. The impact of dietary methionine supplementation in seabass juvenile’s performance was assessed through 85 days of trial, between May and August of 2018. Fish were reared in triplicate tanks and three liver samples/tank (9 per treatment) were collected for liver proteome analysis at the beginning and at the end of the trial i.e., after 18 and 85 days offeeding, correspondingly. This dataset refers to the 18th day of sampling.
2020-12-02 | PXD019610 | Pride
Project description:Liver development and metabolic adaptation are well-orchestrated by a series of signaling pathways and genes. Chromatin architecture is known to influence gene expression, yet its role in controlling liver development and metabolism remains unclear. We performed high-throughput chromatin conformation capture sequencing (HiC-seq) and integrated RNA sequencing (RNA-seq) and chromatin immunoprecipitation sequencing (ChIP-seq) on liver tissue that were collected from six key developmental stages (embryonic day 38 [E38] – 2 years [2y]) and a high fat diet (HFD) feeding group. Our data revealed global three-dimensional (3D) reorganization during liver development from the scales of compartment, topologically associated domain (TAD) and promoter-enhancer interaction (PEI), which consistently affects the expression level of genes known to be important for liver development and function. Comparison of 3D genome and gene expression profiles between pig liver development and human hepatocellular carcinoma (HCC) revealed similarities between fatal liver and HCC and provided potential explanation for the aberrant expression in HCC from the perspective of chromatin architecture. Moreover, the similar genome architecture and expression of genes related to lipid metabolism between nomally and HFD feeding pigs, along with the thicker back fat in HFD feeding pigs compared to normally feeding pigs, supported that pigs are resistant to nonalcoholic fatty liver disease (NAFLD). Together, our results provide a global view of dynamic chromatin interactions during liver development and metabolic adaptation induced by HFD feeding, which may open new avenues for liver research and HCC therapeutic interventions.
2022-03-15 | GSE176387 | GEO
Project description:Female and male pigs were studied. Half of the pigs were exposed to immune activation from virally-infected mothers, and half were not exposed. At 17 days of age half the pigs were injected with morphine for 4 days and the remainder with saline.
2025-03-05 | GSE209907 | GEO
Project description:In order to gain insight into hepatic metabolic pathways and key transcripts affecting traits related to body composition we aimed to compare samples of pigs of two breeds, the “obese” German Landrace (DL) and the “lean” Pietrain (Pi) obtained at prenatal stages (35, 63, and 91 days post conceptionem) and at adult age (180 days). In terms of number of genes regulated the most striking differences between DL and Pi were found at adult age with upregulation of key genes of lipid biosynthesis/metabolism pathways (FASN, ACSS2, ACACA) in obese DL pigs on the one hand and upregulation of genes of cell growth and/or maintenance, protein syntheses as well as cell proliferation pathways (PPARD, POU1F1, IGF2R) in lean Pi pigs on the other hand. Time course analysis of expression profiles of breed differences from foetal to adult stage and functional cluster analysis of the biological processes confirmed the trend of differences between genetically different obese and lean breeds. The highlighted classes of genes showed common breed-typical expression throughout prenatal development and at adult age. The transcriptional differences between obese and lean pigs involving lipid pathways and cell activity are already initiated during early prenatal development. The information about genetic differences between obese and lean pigs reveals a number of functional candidate genes for traits related to obesity and leaness. Keywords: pig, oligo-microarray, prenatal liver expression, adult liver expression, obesity, leaness
2007-07-27 | GSE5399 | GEO
Project description:Female and male 21 days of age pigs were studied. Half of the pigs were prenatally exposed to immune activation from virally-infected gilts, and half were not exposed.
2025-02-19 | GSE250318 | GEO
Project description:Female and male pigs were studied. Half of the pigs were exposed to immune activation from virally-infected mothers, and half were not exposed. At 21 days of age half the pigs were weaned and the remainder remained with the sow.
2025-02-19 | GSE227725 | GEO