Project description:<p>Droplet-based single-cell RNA-seq has emerged as a powerful technique for massively parallel cellular profiling. While these approaches offer the exciting promise to deconvolute cellular heterogeneity in diseased tissues, the lack of cost-effective, reliable, and user-friendly instrumentation has hindered widespread adoption of droplet microfluidic techniques. To address this, we have developed a microfluidic control instrument that can be easily assembled from 3D printed parts and commercially available components costing approximately $575. We adapted this instrument for massively parallel scRNA-seq and deployed it in a clinical environment to perform single-cell transcriptome profiling of disaggregated synovial tissue from 5 rheumatoid arthritis patients. We sequenced 20,387 single cells from synovectomies, revealing 13 transcriptomically distinct clusters. These encompass a comprehensive and unbiased characterization of the autoimmune infiltrate, including inflammatory T and NK subsets that contribute to disease biology. Additionally, we identified fibroblast subpopulations that are demarcated via THY1 (CD90) and CD55 expression. Further experiments confirm that these represent synovial fibroblasts residing within the synovial intimal lining and subintimal lining, respectively, each under the influence of differing microenvironments. We envision that this instrument will have broad utility in basic and clinical settings, enabling low-cost and routine application of microfluidic techniques, and in particular single-cell transcriptome profiling.</p> <p>Reprinted from [Stephenson et al., Nature Communications, 2018], with permission from the Nature Publishing Group.</p>
Project description:<p>We performed comprehensive molecular profiling of germ cell tumors, including whole exome sequencing and transcriptome sequencing, derived from patient samples. This project additionally explores mechanisms of chemosensivity in these patients, as well as mechanisms of tumor evolution in the context of treatment.</p>
Project description:epigenome profiling in tumor tissues and paired normal tissues of LUAD patients and transcriptome profiling in tumor tissues of LUAD patients.
Project description:The primary objective of this prospective observational study is to characterize the gut and oral microbiome as well as the whole blood transcriptome in gastrointestinal cancer patients and correlate these findings with cancer type, treatment efficacy and toxicity. Participants will be recruited from existing clinical sites only, no additional clinical sites are needed.
Project description:We combined multi-omics approaches including de novo transcriptome assembly, ribosome profiling and MS-based peptidomics to study the global role of mRNA translation and small ORFs (sORFs) in rice herbicide resistant mutant.
Project description:131 patient-derived xenograft models were generated for non-small cell lung carcinoma and were profiled at the genome, transcriptome and proteome level by analysis of gene copy number variation, whole exome sequencing, DNA methylation, transcriptome, proteome and phospho(Tyr)-proteome. At the proteome level, the human tumor and murine stroma were discernible. Tumor proteome profiling resolved the known major histological subtypes and revealed 3 proteome subtypes (proteotypes) among adenocarcinoma and 2 in squamous cell carcinoma that were associated with distinct protein-phosphotyrosine signatures and patient survival. Stromal proteomes were similar between histological subtypes, but two adenocarcinoma proteotypes had distinct stromal proteomes. Proteotypes comprise tumor and stromal signatures of targetable biological pathways suggesting that patient stratification by proteome profiling may be an actionable approach to precisely diagnose and treat cancer.
Project description:SARS-CoV-2 causes the COVID-19 pandemic. It is urgent to develop disease models to dissect mechanisms regulating SARS-CoV-2 infection. Here, we derive airway organoids from human pluripotent stem cells (hPSC-AOs). The hPSC-AOs, particularly ciliated-like cells, are permissive to SARS-CoV-2 infection. Using this platform, we perform a high content screen and identify GW6471, which blocks SARS-CoV-2 infection. GW6471 can also block infection of the B.1.351 SARS-CoV-2 variant. RNA-seq analysis suggests that GW6471 blocks SARS-CoV-2 infection at least in part by inhibiting HIF1α, which is further validated by chemical inhibitor and genetic perturbation targeting HIF1α. Metabolic profiling identifies decreased rates of glycolysis upon GW6471 treatment, consistent with transcriptome profiling. Finally, xanthohumol, 5-(Tetradecyloxy)-2-furoic acid, and ND-646, three compounds that suppress fatty acid biosynthesis, also block SARS-CoV-2 infection. Together, a high content screen coupled with transcriptome and metabolic profiling reveals a key role of the HIF1α-glycolysis axis in mediating SARS-CoV-2 infection of human airway epithelium.