Project description:metabolite levels measured by general metabolomics (Boston, USA) (the data is raw abundance. Mapping was applied on log10 transformed data)
Project description:Full clinical data for a cohort of 199 individuals with acute coronary syndrome.
Untargeted serum metabolomics using the Metabolon platform for individuals with ACS (n=156).
Serum metabolomics using the Nightingale Health (NMR) platform for individuals with ACS and controls (ACS, n=191; controls, n=961).
Project description:This single cell RNA-seq experiment was performed to quantify DLL3 expression in circulating tumor cells in small cell lung cancer patients to predict response to tarlatamab treatment. CTCs enriched from the blood of three SCLC patients prior or post tarlatamab treatment using the CTC-iChip followed by magnetic depletion of RBCs were processed with the 10x Genomics Chromium platform (Chromium GEM-X Single Cell 3' Kit v4) and sequenced on a NextSeq 2000 system. Corresponding EGA study number: EGAS50000001401, EGA dataset number: EGAD50000002035
Project description:metabolite levels provided by UM platform (Creative Dynamics Inc, NY, USA) (the data is raw abundance. Mapping was applied on log10 transformed data)
Project description:Neurons and glia are distinct in their morphology, development, and function. They have unique transcriptomes and proteomes, but little is known about their metabolomes. The challenge of brain cell metabolic profiling is to obtain a large number of pure cells for reliable analysis. Here, we purify microglia, astrocytes, and neurons from the genetically labeled-brain. We identified >70 metabolites in them with targeted metabolomics and 9,854 metabolite features with untargeted metabolomics. We systematically characterized cell type–enriched metabolites and metabolic pathways. The enrichment of glutathione (GSH) metabolism in microglia was further validated in vivo. A significant decrease in GSH levels and GSH metabolism observed in microglia in aging and Alzheimer's disease (AD) models. Disrupting GSH metabolism in microglia results in aberrant morphogenesis, upregulation of mitophagy-related genes, and the deposition of β-Amyloid. Our results provide a valuable resource for metabolic studies related to aging, AD and other neurological diseases.
Project description:Changes in cellular metabolism contribute to the development and progression of tumors, and can render tumors vulnerable to interventions. However, studies of human cancer metabolism remain limited due to technical challenges of detecting and quantifying small molecules, the highly interconnected nature of metabolic pathways, and the lack of designated tools to analyze and integrate metabolomics with other âomics data. Our study generates the largest comprehensive metabolomics dataset on a single cancer type, and provides a significant advance in integration of metabolomics with sequencing data. Our results highlight the massive re-organization of cellular metabolism as tumors progress and acquire more aggressive features. The results of our work are made available through an interactive public data portal for cancer research community. 10 RNA samples from human ccRCC tumors analyzed from the high glutathione cluster
Project description:This dataset contains processed aptamer-based serum proteomics data from ME/CFS patients and healthy controls, analyzed using the 7k SomaScan assay (v4.1) platform. It includes log2-transformed intensities for 7326 aptamers (6494 protein targets), cohort metadata (age range, sex, BMI category, fasting status, SF-36 physical function score, metabotype), and aptamer annotations. The dataset supports the manuscript: Charting the Circulating Proteome in ME/CFS Using Cross System Profiling to Uncover Mechanistic Insights.
Project description:Embryonic genome activation (EGA), a pivotal transcriptional event during preimplantation development, is accompanied by post-transcriptional regulation of maternal mRNAs. Disentangling the transcriptional output of the newly activated embryonic genome from concomitant post-transcriptional processing is important for decoding EGA dynamics.Here, using optimized low-input SLAM-seq (thiol(SH)-linked alkylation for the metabolic sequencing) in mouse embryos, we delineates the temporal hierarchy of EGA nascent transcription during mouse preimplantation embryogenesis and uncovers a mechanistic link between EGA and the first lineage specification, providing new insights into the regulatory architecture of early mammalian development.