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.

CLYBL is a polymorphic human enzyme with malate synthase and β-methylmalate synthase activity

Abstract: CLYBL is a human mitochondrial enzyme of unknown function that is found in multiple eukaryotic taxa and conserved to bacteria. The protein is expressed in the mitochondria of all mammalian organs, with highest expression in brown fat and kidney. Approximately 5% of all humans harbor a premature stop polymorphism in CLYBL that has been associated with reduced levels of circulating vitamin B12. Using comparative genomics, we now show that CLYBL is strongly co-expressed with and co-evolved specifically with other components of the mitochondrial B12 pathway. We confirm that the premature stop polymorphism in CLYBL leads to a loss of protein expression. To elucidate the molecular function of CLYBL, we used comparative operon analysis, structural modeling and enzyme kinetics. We report that CLYBL encodes a malate/β-methylmalate synthase, converting glyoxylate and acetyl-CoA to malate, or glyoxylate and propionyl-CoA to β-methylmalate. Malate synthases are best known for their established role in the glyoxylate shunt of plants and lower organisms and are traditionally described as not occurring in humans. The broader role of a malate/β-methylmalate synthase in human physiology and its mechanistic link to vitamin B12 metabolism remain unknown.

Proteomic Mapping of the Human Mitochondrial Intermembrane Space in Live Cells via Ratiometric APEX Tagging

Abstract: Obtaining complete protein inventories for subcellular regions is a challenge that often limits our understanding of cellular function, especially for regions that are impossible to purify and are therefore inaccessible to traditional proteomic analysis. We recently developed a method to map proteomes in living cells with an engineered peroxidase (APEX) that bypasses the need for organellar purification when applied to membrane-bound compartments; however, it was insufficiently specific when applied to unbounded regions that allow APEX-generated radicals to escape. Here, we combine APEX technology with a SILAC-based ratiometric tagging strategy to substantially reduce unwanted background and achieve nanometer spatial resolution. This is applied to map the proteome of the mitochondrial intermembrane space (IMS), which can freely exchange small molecules with the cytosol. Our IMS proteome of 127 proteins has >94% specificity and includes nine newly discovered mitochondrial proteins. This approach will enable scientists to map proteomes of cellular regions that were previously inaccessible.

Buffering mitochondrial DNA variation.

Abstract: Reactive oxygen species (ROS) are traditionally viewed as the toxic by-product of cellular respiration. A new study suggests a homeostatic role for ROS in maintaining stable respiratory phenotypes across genetic variants of the mitochondrial genome.

Associations between plasma branched-chain amino acids, β-aminoisobutyric acid and body composition.

Abstract: Plasma branched-chain amino acids (BCAA) are elevated in obesity and associated with increased cardiometabolic risk. β-Aminoisobutyric acid (B-AIBA), a recently identified small molecule metabolite, is associated with decreased cardiometabolic risk. Therefore, we investigated the association of BCAA and B-AIBA with each other and with detailed body composition parameters, including abdominal visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). A cross-sectional study was carried out with lean (n 15) and obese (n 33) men and women. Detailed metabolic evaluations, including measures of body composition, insulin sensitivity and plasma metabolomics were completed. Plasma BCAA were higher (1·6 (se 0·08) (×107) v. 1·3 (se 0·06) (×107) arbitrary units; P = 0·005) in obese v. lean subjects. BCAA were positively associated with VAT (R 0·49; P = 0·0006) and trended to an association with SAT (R 0·29; P = 0·052). The association between BCAA and VAT, but not SAT, remained significant after controlling for age, sex and race on multivariate modelling (P 0·05). Plasma B-AIBA was associated with parameters of insulin sensitivity (Matsuda index R 0·36, P = 0·01; glucose AUC: R −0·30, P = 0·04). Plasma BCAA levels were positively correlated with VAT and markers of insulin resistance. The results suggest a possible complex role of adipose tissue in BCAA homeostasis and insulin resistance.

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。