Vamsi K. Mootha

Bio: Vamsi K. Mootha is an academic researcher from Broad Institute. The author has contributed to research in topics: Mitochondrion & Mitochondrial DNA. The author has an hindex of 85, co-authored 227 publications receiving 73860 citations. Previous affiliations of Vamsi K. Mootha include Harvard University & Beth Israel Deaconess Medical Center.

Mitochondrial clearance of Ca2+ controls insulin secretion

Abstract: SUMMARY Transport of Ca2+ from the cytosol to the mitochondrial matrix of insulin-secreting pancreatic β-cells facilitates nutrient-mediated insulin secretion. However, the underlying mechanism is unclear. The establishment of the molecular identity of the mitochondrial Ca2+ uniporter (MCU) and associated proteins has allowed mitochondrial Ca2+ transport to be modified in intact cells. We examined the consequences of deficiency of the accessory protein, MICU2, in rat and human insulin-secreting cell lines as well as in mouse islets. Glucose-induced mitochondrial Ca2+ elevation and inner membrane hyperpolarization were reduced, together with cytosolic ATP/ADP-ratios and insulin secretion. Insulin secretion in Micu2 knock out mice was attenuated in vitro as well as in vivo. While KCl-evoked sub-plasmalemmal Ca2+ increases were more pronounced, the global cytosolic Ca2+ response was, surprisingly, diminished in MICU2-deficient cells. These findings were supported by selective inhibition of mitochondrial Ca2+ uptake by mitochondrial depolarization. It is concluded that mitochondrial Ca2+ transport plays an additional and hitherto unrecognized role in stimulated β-cells by regulating net Ca2+ entry across the plasma membrane. This is likely accounted for by clearing of sub-plasmalemmal Ca2+ levels by mitochondria located near the plasma membrane.

Salvage of ribose from uridine or RNA supports glycolysis in nutrient-limited conditions

Abstract: Glucose is vital for life, serving as both a source of energy and carbon building block for growth. When glucose is limiting, alternative nutrients must be harnessed. To identify mechanisms by which cells can tolerate complete loss of glucose, we performed nutrient-sensitized genome-wide genetic screens and a PRISM growth assay across 482 cancer cell lines. We report that catabolism of uridine from the medium enables the growth of cells in the complete absence of glucose. While previous studies have shown that uridine can be salvaged to support pyrimidine synthesis in the setting of mitochondrial oxidative phosphorylation deficiency1, our work demonstrates that the ribose moiety of uridine or RNA can be salvaged to fulfil energy requirements via a pathway based on: (1) the phosphorylytic cleavage of uridine by uridine phosphorylase UPP1/UPP2 into uracil and ribose-1-phosphate (R1P), (2) the conversion of uridine-derived R1P into fructose-6-P and glyceraldehyde-3-P by the non-oxidative branch of the pentose phosphate pathway and (3) their glycolytic utilization to fuel ATP production, biosynthesis and gluconeogenesis. Capacity for glycolysis from uridine-derived ribose appears widespread, and we confirm its activity in cancer lineages, primary macrophages and mice in vivo. An interesting property of this pathway is that R1P enters downstream of the initial, highly regulated steps of glucose transport and upper glycolysis. We anticipate that 'uridine bypass' of upper glycolysis could be important in the context of disease and even exploited for therapeutic purposes.

Effectors enabling adaptation to mitochondrial complex I loss in Hürthle cell carcinoma

Abstract: Oncocytic (Hürthle cell) carcinoma of the thyroid (HCC) is genetically characterized by complex I mitochondrial DNA mutations and widespread chromosomal losses. Here, we utilize RNA-seq and metabolomics to identify candidate molecular effectors activated by these genetic drivers. We find glutathione biosynthesis, amino acid metabolism, mitochondrial unfolded protein response, and lipid peroxide scavenging, a safeguard against ferroptosis, to be increased in HCC. A CRISPR-Cas9 knockout screen in a new HCC model reveals which pathways are key for fitness, and highlights loss of GPX4, a defense against ferroptosis, as a strong liability. Rescuing complex I redox activity with the yeast NADH dehydrogenase (NDI1) in HCC cells diminishes ferroptosis sensitivity, while inhibiting complex I in normal thyroid cells augments ferroptosis induction. Our work demonstrates unmitigated lipid peroxide stress to be an HCC vulnerability that is mechanistically coupled to the genetic loss of mitochondrial complex I activity. Significance Oncocytic (Hürthle cell) carcinoma of the thyroid (HCC) is a unique tumor with a remarkable accumulation of mitochondria. HCC harbors unique genetic alterations, including mitochondrial DNA (mtDNA) mutations in complex I genes and widespread loss-of-heterozygosity in the nuclear DNA. With less favorable clinical outcomes, new therapies for HCC are needed, especially since these tumors show intrinsic resistance to radioactive iodine, which is one of the main treatments for metastatic well-differentiated thyroid cancer. An absence of authentic HCC cell lines and animal models has hindered the mechanistic understanding of this disease and slowed therapeutic progress. In this study, we describe the transcriptomic and metabolomic landscape of HCC and present new HCC models that recapitulate key mtDNA and nuclear DNA alterations. A targeted CRISPR-Cas9 knockout screen in an HCC cell line highlights the molecular programs nominated by our -omics profiling that are required for cell fitness. This screen suggests that lipid peroxide scavenging, a defense system against an iron-dependent form of cell death known as ferroptosis, is a vulnerability in HCC that is coupled to complex I loss, and that targeting this pathway may help patients with HCC.

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

Abstract: DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.

limma powers differential expression analyses for RNA-sequencing and microarray studies

Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。