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.

Low-dose rapamycin extends lifespan in a mouse model of mtDNA depletion syndrome.

Abstract: Mitochondrial disorders affecting oxidative phosphorylation (OxPhos) are caused by mutations in both the nuclear and mitochondrial genomes. One promising candidate for treatment is the drug rapamycin, which has been shown to extend lifespan in multiple animal models, and which was previously shown to ameliorate mitochondrial disease in a knock-out mouse model lacking a nuclear-encoded gene specifying an OxPhos structural subunit (Ndufs4). In that model, relatively high-dose intraperitoneal rapamycin extended lifespan and improved markers of neurological disease, via an unknown mechanism. Here, we administered low-dose oral rapamycin to a knock-in (KI) mouse model of authentic mtDNA disease, specifically, progressive mtDNA depletion syndrome, resulting from a mutation in the mitochondrial nucleotide salvage enzyme thymidine kinase 2 (TK2). Importantly, low-dose oral rapamycin was sufficient to extend Tk2KI/KI mouse lifespan significantly, and did so in the absence of detectable improvements in mitochondrial dysfunction. We found no evidence that rapamycin increased survival by acting through canonical pathways, including mitochondrial autophagy. However, transcriptomics and metabolomics analyses uncovered systemic metabolic changes pointing to a potential 'rapamycin metabolic signature.' These changes also implied that rapamycin may have enabled the Tk2KI/KI mice to utilize alternative energy reserves, and possibly triggered indirect signaling events that modified mortality through developmental reprogramming. From a therapeutic standpoint, our results support the possibility that low-dose rapamycin, while not targeting the underlying mtDNA defect, could represent a crucial therapy for the treatment of mtDNA-driven, and some nuclear DNA-driven, mitochondrial diseases.

Itaconyl-CoA forms a stable biradical in methylmalonyl-CoA mutase and derails its activity and repair

Abstract: Itaconate is an immunometabolite with both anti-inflammatory and bactericidal effects. Its coenzyme A (CoA) derivative, itaconyl-CoA, inhibits B12-dependent methylmalonyl-CoA mutase (MCM) by an unknown mechanism. We demonstrate that itaconyl-CoA is a suicide inactivator of human and Mycobacterium tuberculosis MCM, which forms a markedly air-stable biradical adduct with the 5′-deoxyadenosyl moiety of the B12 coenzyme. Termination of the catalytic cycle in this way impairs communication between MCM and its auxiliary repair proteins. Crystallography and spectroscopy of the inhibited enzyme are consistent with a metal-centered cobalt radical ~6 angstroms away from the tertiary carbon-centered radical and suggest a means of controlling radical trajectories during MCM catalysis. Mycobacterial MCM thus joins enzymes in the glyoxylate shunt and the methylcitrate cycle as targets of itaconate in pathogen propionate metabolism.

Natural underlying mtDNA heteroplasmy as a potential source of intra‐person hiPSC variability

Abstract: Functional variability among human clones of induced pluripotent stem cells (hiPSCs) remains a limitation in assembling high-quality biorepositories. Beyond inter-person variability, the root cause of intra-person variability remains unknown. Mitochondria guide the required transition from oxidative to glycolytic metabolism in nuclear reprogramming. Moreover, mitochondria have their own genome (mitochondrial DNA [mtDNA]). Herein, we performed mtDNA next-generation sequencing (NGS) on 84 hiPSC clones derived from a cohort of 19 individuals, including mitochondrial and non-mitochondrial patients. The analysis of mtDNA variants showed that low levels of potentially pathogenic mutations in the original fibroblasts are revealed through nuclear reprogramming, generating mutant hiPSCs with a detrimental effect in their differentiated progeny. Specifically, hiPSC-derived cardiomyocytes with expanded mtDNA mutations non-related with any described human disease, showed impaired mitochondrial respiration, being a potential cause of intra-person hiPSC variability. We propose mtDNA NGS as a new selection criterion to ensure hiPSC quality for drug discovery and regenerative medicine.

Structural insights into the Ca2+-dependent gating of the human mitochondrial calcium uniporter

Abstract: Mitochondrial Ca2+ uptake is mediated by an inner mitochondrial membrane protein called the mitochondrial calcium uniporter. In humans, the uniporter functions as a holocomplex consisting of MCU, EMRE, MICU1 and MICU2, among which MCU and EMRE form a subcomplex and function as the conductive channel while MICU1 and MICU2 are EF-hand proteins that regulate the channel activity in a Ca2+-dependent manner. Here, we present the EM structures of the human mitochondrial calcium uniporter holocomplex (uniplex) in the presence and absence of Ca2+, revealing distinct Ca2+ dependent assembly of the uniplex. Our structural observations suggest that Ca2+ changes the dimerization interaction between MICU1 and MICU2, which in turn determines how the MICU1-MICU2 subcomplex interacts with the MCU-EMRE channel and, consequently, changes the distribution of the uniplex assemblies between the blocked and unblocked states.

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。