Yu Fang Similar Datasets
Project description:There was significant difference in protein composition between cell wax and queen cell wax in honeybee colonies
2022-09-19 | PXD036838 |
Project description:Fatal COVID-19 is often complicated by hypoxemic respiratory failure and acute respiratory distress syndrome (ARDS). Mechanisms governing lung injury and repair in ARDS remain poorly understood because there are no biomarker-targeted therapeutics for patients with ARDS. We hypothesized that plasma proteomics may uncover unique biomarkers that correlate with disease severity in COVID-19 ARDS. We analyzed the circulating plasma proteome from 32 patients with ARDS and COVID-19 using an aptamer-based platform, which measures 7289 proteins, and correlated protein measurements with sequential organ failure assessment (SOFA) scores at 2 time points (Days 1 and 7 following ICU admission). We compared differential protein abundance and SOFA scores at each individual time point and identified 119 proteins at Day 1 and 46 proteins at Day 7 that correlated with patient SOFA scores. We modeled the relationship between dynamic protein abundance and changes in SOFA score between Days 1 and 7 and identified 39 proteins that significantly correlated with changes in SOFA score. Using Ingenuity Pathway Analysis, we identified increased ephrin signaling and acute phase response signaling correlated with increased SOFA scores over time, while pathways related to pulmonary fibrosis signaling and wound healing had an inverse relationship with SOFA scores between Days 1 and 7. These findings suggest that persistent inflammation may drive worsened disease severity, while repair processes correlate with improvements in organ dysfunction over time. This approach is generalizable to more diverse ARDS cohorts for identification of protein biomarkers and disease mechanisms as we strive towards targeted therapies in ARDS.
2025-04-09 | GSE283501 | GEO
Project description:Background: Macrophage-based immune dysregulation plays a critical role in development of delayed gastric emptying in animal models of diabetes. Human studies have also revealed loss of anti-inflammatory macrophages and increased expression of genes associated with pro-inflammatory macrophages in full thickness gastric biopsies from gastroparesis patients. Aim: We aimed to determine broader protein expression (proteomics) and protein-based signaling pathways in full thickness gastric biopsies of diabetic (DG) and idiopathic gastroparesis (IG) patients. Additionally, we determined correlations between protein expressions, gastric emptying and symptoms. Methods: Full-thickness gastric antrum biopsies were obtained from nine DG, seven IG patients and five non-diabetic controls. Aptamer-based SomaLogic tissue scan that quantitatively identifies 1300 human proteins was used. Protein fold changes were computed, and differential expressions were calculated using Limma. Ingenuity Pathway Analysis and correlations were carried out. Multiple-testing corrected p-values <0.05 were considered statistically significant. Results: 73 proteins were differentially expressed in DG, 132 proteins in IG and 40 proteins were common to DG and IG. In both DG and IG, “Role of Macrophages, Fibroblasts and Endothelial Cells” was the most statistically significant altered pathway (DG FDR: 7.9x10-9; IG FDR: 6.3x10-12). In DG, properdin expression correlated with GCSI-bloating (r: -0.99, FDR: 0.02) and expressions of prostaglandin G/H synthase 2, protein kinase C zeta type and complement C2 correlated with 4 hr gastric retention (r: -0.97, FDR: 0.03 for all). No correlations were found between proteins and symptoms or gastric emptying in IG. Conclusions: Protein expression changes suggest a central role of macrophage-driven immune dysregulation and complement activation in gastroparesis.
2019-09-15 | GSE130672 | GEO
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.
2018-12-14 | GSE118974 | GEO
Project description:The recent development within high-throughput technologies for expression profiling has allowed for parallel analysis of transcriptomes and proteomes in biological systems such as comparative analysis of transcript and protein levels of tissue regulated genes. Until now, such studies of have only included microarray or short length sequence tags for transcript profiling. Furthermore, most comparisons of transcript and protein levels have been based on absolute expression values from within the same tissue and not relative expression values based on tissue ratios. Presented here is a novel study of two porcine tissues based on integrative analysis of data from expression profiling of identical samples using cDNA microarray, 454-sequencing and iTRAQ-based proteomics. Sequence homology identified 2.541 unique transcripts that are detectable by both microarray hybridizations and 454-sequencing of 1.2 million cDNA tags. Both transcript-based technologies showed high reproducibility between sample replicates of the same tissue, but the correlation across these two technologies was modest. Thousands of genes being differentially expressed were identified with microarray. Out of the 306 differentially expressed genes, identified by 454-sequencing, 198 (65 %) were also found by microarray. The relationship between the regulation of transcript and protein levels was analyzed by integrating iTRAQ-based proteomics data. Protein expression ratios were determined for 354 genes, of which 148 could be mapped to both microarray and 454-sequencing data. A comparison of the expression ratios from the three technologies revealed that differences in transcript and protein levels across heart and muscle tissues are positively correlated. We show that the reproducibility within cDNA microarray and 454-sequencing is high, but that the agreement across these two technologies is modest. We demonstrate that the regulation of transcript and protein levels across identical tissue samples is positively correlated when the tissue expression ratios are used for comparison. The results presented are of interest in systems biology research in terms of integration and analysis of high-throughput expression data from mammalian tissues. Keywords: tissue comparison, platform comparison
2009-01-22 | GSE10122 | GEO
Project description:In this study, we evaluated the utility of proteomics to identify plasma proteins in healthy participants from a phase I clinical trial with IFNβ-1a and pegIFNβ-1a biologics to identify potential pharmacodynamic (PD) biomarkers. Using a linear mixed-effects model with repeated measurement for product-time interaction, we found that 248 and 528 analytes detected by the SOMAscan® assay were differentially expressed (p-value < 6.86E-06) between therapeutic doses of IFNβ-1a or pegIFNβ-1a, and placebo, respectively. We further prioritized signals based on peak change, area under the effect curve over the study duration, and overlap in signals from the two products. Analysis of prioritized datasets indicated activation of IFNB1 signaling and an IFNB signaling node with IL-6 as upstream regulators of the plasma protein patterns from both products. Increased TNF, IL-1B, IFNG, and IFNA signaling also occurred early in response to each product suggesting a direct link between each product and these upstream regulators. In summary, we identified longitudinal global PD changes in a large array of new and previously reported circulating proteins in healthy participants treated with IFNβ-1a and pegIFNβ-1a that may help identify novel single proteomic PD biomarkers and/or composite PD biomarker signatures as well as provide insight into the mechanism of action of these products. Independent replication is needed to confirm present proteomic results and to support further investigation of the identified candidate PD biomarkers for biosimilar product development.
2023-10-31 | GSE207945 | GEO
Project description:The recent development within high-throughput technologies for expression profiling has allowed for parallel analysis of transcriptomes and proteomes in biological systems such as comparative analysis of transcript and protein levels of tissue regulated genes. Until now, such studies of have only included microarray or short length sequence tags for transcript profiling. Furthermore, most comparisons of transcript and protein levels have been based on absolute expression values from within the same tissue and not relative expression values based on tissue ratios. Presented here is a novel study of two porcine tissues based on integrative analysis of data from expression profiling of identical samples using cDNA microarray, 454-sequencing and iTRAQ-based proteomics. Sequence homology identified 2.541 unique transcripts that are detectable by both microarray hybridizations and 454-sequencing of 1.2 million cDNA tags. Both transcript-based technologies showed high reproducibility between sample replicates of the same tissue, but the correlation across these two technologies was modest. Thousands of genes being differentially expressed were identified with microarray. Out of the 306 differentially expressed genes, identified by 454-sequencing, 198 (65 %) were also found by microarray. The relationship between the regulation of transcript and protein levels was analyzed by integrating iTRAQ-based proteomics data. Protein expression ratios were determined for 354 genes, of which 148 could be mapped to both microarray and 454-sequencing data. A comparison of the expression ratios from the three technologies revealed that differences in transcript and protein levels across heart and muscle tissues are positively correlated. We show that the reproducibility within cDNA microarray and 454-sequencing is high, but that the agreement across these two technologies is modest. We demonstrate that the regulation of transcript and protein levels across identical tissue samples is positively correlated when the tissue expression ratios are used for comparison. The results presented are of interest in systems biology research in terms of integration and analysis of high-throughput expression data from mammalian tissues. Keywords: tissue comparison, platform comparison Tissue samples of heart (HEA) and Longissimus dorsi (LDO) were prepared by pooling from five healthy Hampshire gilts at age four to six months and division into six sub-samples, three for each tissue named HEA1, HEA2, HEA3, LDO1, LDO2 and LDO3. The exact same six tissue samples were used for subsequent expression profiling with cDNA microarray, 454-sequencing and iTRAQ-based proteomics. A reference sample for the cDNA microarray experiment and iTRAQ-based proteomics was constructed by combining the six samples. In the microarray experiment, three cDNA microarray slides were used per sample.
2009-01-22 | E-GEOD-10122 | biostudies-arrayexpress
Project description:proteomics reveals changes in protein expression of SIRT6KD、SIRT6KDNC、SIRT6OE、SIRT6OENC endothelial cells
2022-07-15 | OEX00019975 | NODE
Project description:PURPOSE:To clarify the mechanism of the wax deficiency, the wax-less flowering Chinese cabbage doubled-haploid (DH) line ‘CX001’ and Chinese cabbage DH line ‘FT’, obtained from isolated microspore culture, were used in the experiments. Transcriptome analysis indicated that BraA09g066480.3C was expressed in ‘FT’ but not in ‘CX001’.The work presented herein demonstrated that BraA09g066480.3C was the causal gene for wax-less flowering Chinese cabbage ‘CX001’
2022-12-29 | GSE221778 | GEO
Project description:Label-free proteomics of human brain FFPE archival tissue. Comparison of proteome composition between epilepsy and controls across 3 brain regions.
2020-05-31 | MSV000085517 | MassIVE