Project description:Infection with SARS-CoV-2 has highly variable clinical manifestations, ranging from asymptomatic infection through to life-threatening disease. Host whole blood transcriptomics can offer unique insights into the biological processes underpinning infection and disease, as well as severity. We performed whole blood RNA-Sequencing of individuals with varying degrees of COVID-19 severity. We used differential expression analysis and pathway enrichment analysis to explore how the blood transcriptome differs between individuals with mild, moderate, and severe COVID-19, performing pairwise comparisons between groups.
Project description:The function of mucosal-associated invariant T (MAIT) highly depends on the mode of activation, either by recognition of bacterial metabolites via their T cell receptor (TCR) or in a TCR-independent manner via cytokines. The underlying molecular mechanisms are not entirely understood. To define the activation of MAIT cells on the molecular level, we applied a multi-omics approach with untargeted transcriptomics, proteomics and metabolomics. Transcriptomic analysis of E.coli- and TCR-activated MAIT cells showed a distinct transcriptional reprogramming, including altered pathways, transcription factors and effector molecules. We validated the consequences of this reprogramming on the phenotype by proteomics and metabolomics. Thus, and to distinguish between TCR-dependent and -independent activation, MAIT cells were stimulated with IL12/IL18, anti-CD3/CD28 or both. Only a combination of both led to full activation of MAIT cells, comparable to activation by E.coli. Using an integrated network-based approach, we identified key drivers of the distinct modes of activation, including cytokines and transcription factors, as well as negative feedback regulators like TWIST1 or LAG3. Taken together, we present novel insights into the biological function of MAIT cells, which may represent a basis for therapeutic approaches to target MAIT cells in pathological conditions.
Project description:12 Holstein dairy heifers were limit-fed with high or low forage diets, and integrative hepatic metabolomics and proteomics were used to reveal insights into the mechanism of different feed efficiency behind that.
Project description:Using RNA-seq and high-resolution mass spectrometry we performed a comprehensive systems analysis on 128 plasma and leukocyte samples from hospitalized patients with or without COVID-19 (n=102 and 26 respectively) and with differing degrees of disease severity. We generated abundance measurements for over 17,000 transcripts, proteins, metabolites, and lipids and compiled them with clinical data into a curated relational database. This resource offers the unique opportunity to perform systems analysis and cross-ome correlations to both molecules and patient outcomes. In total 219 molecular features were mapped with high significance to COVID-19 status and severity, including those involved in processes such as complement system activation, dysregulated lipid transport, and B cell activation. In one example, we detected a trio of covarying molecules – citrate, plasmenyl-phosphatidylcholines, and gelsolin (GSN) – that offer both pathophysiological insight and potential novel therapeutic targets. Further, our data revealed in some cases, and supported in others, that several biological processes were dysregulated in COVID-19 patients including vessel damage, platelet activation and degranulation, blood coagulation, and acute phase response. For example, we observed that the coagulation-related protein, cellular fibronectin (cFN), was highly increased within COVID-19 patients and provide new evidence that the upregulated proteoform stems from endothelial cells, consistent with endothelial injury as a major activator of the coagulation cascade. The abundance of prothrombin, which is cleaved to form thrombin during clotting, was significantly reduced and correlated with severity and might help to explain the hyper coagulative environment of SARS-CoV-2 infection. From transcriptomic analysis of leukocytes, we concluded that COVID-19 patients with acute respiratory distress syndrome (ARDS) demonstrated a phenotype that overlapped with, but was distinct from, that found in patients with non-COVID-19-ARDS. To aid in the global efforts toward elucidation of disease pathophysiology and therapeutic development, we created a web-based tool with interactive visualizations allowing for easy navigation of this systems-level compendium of biomolecule abundance in relation to COVID-19 status and severity. Finally, we leveraged these multi-omic data to predict COVID-19 patient outcomes with machine learning, which highlighted the predictive power of these expansive molecular measurements beyond the standardized clinical estimate of 10-year survival Charlson score.
Project description:Genome-wide DNA methylation analysis of COVID-19 severity using the Illumina HumanMethylationEPIC microarray platform to analyze over 850,000 methylation sites, comparing COVID-19 patients with patients presenting with respiratory symptoms, but negative for COVID-19, using whole blood tissue.
Project description:To understand the relationship between protein expression and mRNA translation during primary hepatocytes dedifferentiation, we have employed transcriptome microarrayas a discovery platform. Rat primary hepatocytes were isolated by the method of two-step enzymes perfusion and then cultured on mono-layer in vitro. Samples at 0h( just after perfusion, before planking) , 6h, 12h ,24h and 48h were collected. Integrative analysis of transcriptome and whole cell proteomics (WCP) leaded us to realize the poor correlation of them. This discovery made us realize that targeting mRNA was far from enough in illustrating this process. It would provide new insights from the aspects of post-translational modifications(PTMs).Post-translational modifications play important role in numorous biological and pathological process, but a few reports are related to primary hepatocytes dedifferentiation process, and there is still no integrative proteomics analysis in this field yet. In this study, we perform ubiquitinome phosphorylated proteome, whole cell proteome and transcriptome simultaneously during the five different time points of dedifferentiation in vitro quantified over 6000 modified sites mapping to over 2000 proteins. And comprehensive analysis of these datasets provides novel insight in this field.
Project description:We used total RNA of nasopharyngeal swabs from COVID-19 patients to identify their gene expression profile. Multiple biological process were significantly enriched in either asymptomatic or mildly symptomatic patients. These significantly expressed genes were suggested to contribute to the severity of the disease. We also performed metagenomics analysis to identify differences in the microbiome profile of the two groups of patients.