Broad Institute

About: Broad Institute is a nonprofit organization based out in Cambridge, Massachusetts, United States. It is known for research contribution in the topics: Population & Genome-wide association study. The organization has 6584 authors who have published 11618 publications receiving 1522743 citations. The organization is also known as: Eli and Edythe L. Broad Institute of MIT and Harvard.

Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome

Abstract: Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities' metagenomes provides information complementary to organismal abundances from taxonomic markers, but the resulting data typically comprise short reads from hundreds of different organisms and are at best challenging to assemble comparably to single-organism genomes. Here, we describe an alternative approach to infer the functional and metabolic potential of a microbial community metagenome. We determined the gene families and pathways present or absent within a community, as well as their relative abundances, directly from short sequence reads. We validated this methodology using a collection of synthetic metagenomes, recovering the presence and abundance both of large pathways and of small functional modules with high accuracy. We subsequently applied this method, HUMAnN, to the microbial communities of 649 metagenomes drawn from seven primary body sites on 102 individuals as part of the Human Microbiome Project (HMP). This provided a means to compare functional diversity and organismal ecology in the human microbiome, and we determined a core of 24 ubiquitously present modules. Core pathways were often implemented by different enzyme families within different body sites, and 168 functional modules and 196 metabolic pathways varied in metagenomic abundance specifically to one or more niches within the microbiome. These included glycosaminoglycan degradation in the gut, as well as phosphate and amino acid transport linked to host phenotype (vaginal pH) in the posterior fornix. An implementation of our methodology is available at http://huttenhower.sph.harvard.edu/humann. This provides a means to accurately and efficiently characterize microbial metabolic pathways and functional modules directly from high-throughput sequencing reads, enabling the determination of community roles in the HMP cohort and in future metagenomic studies.

Gene expression elucidates functional impact of polygenic risk for schizophrenia

Abstract: Over 100 genetic loci harbor schizophrenia associated variants, yet how these variants confer liability is uncertain. The CommonMind Consortium sequenced RNA from dorsolateral prefrontal cortex of schizophrenia cases (N = 258) and control subjects (N = 279), creating a resource of gene expression and its genetic regulation. Using this resource, ~20% of schizophrenia loci have variants that could contribute to altered gene expression and liability. In five loci, only a single gene was involved: FURIN, TSNARE1, CNTN4, CLCN3, or SNAP91. Altering expression of FURIN, TSNARE1, or CNTN4 changes neurodevelopment in zebrafish; knockdown of FURIN in human neural progenitor cells yields abnormal migration. Of 693 genes showing significant case/control differential expression, their fold changes are ≤ 1.33, and an independent cohort yields similar results. Gene co-expression implicates a network relevant for schizophrenia. Our findings show schizophrenia is polygenic and highlight the utility of this resource for mechanistic interpretations of genetic liability for brain diseases.

Proteomic Mapping of Mitochondria in Living Cells via Spatially Restricted Enzymatic Tagging

Abstract: Microscopy and mass spectrometry (MS) are complementary techniques: The former provides spatiotemporal information in living cells, but only for a handful of recombinant proteins at a time, whereas the latter can detect thousands of endogenous proteins simultaneously, but only in lysed samples. Here, we introduce technology that combines these strengths by offering spatially and temporally resolved proteomic maps of endogenous proteins within living cells. Our method relies on a genetically targetable peroxidase enzyme that biotinylates nearby proteins, which are subsequently purified and identified by MS. We used this approach to identify 495 proteins within the human mitochondrial matrix, including 31 not previously linked to mitochondria. The labeling was exceptionally specific and distinguished between inner membrane proteins facing the matrix versus the intermembrane space (IMS). Several proteins previously thought to reside in the IMS or outer membrane, including protoporphyrinogen oxidase, were reassigned to the matrix by our proteomic data and confirmed by electron microscopy. The specificity of peroxidase-mediated proteomic mapping in live cells, combined with its ease of use, offers biologists a powerful tool for understanding the molecular composition of living cells.

Efficient proximity labeling in living cells and organisms with TurboID.

Abstract: Protein interaction networks and protein compartmentalization underlie all signaling and regulatory processes in cells. Enzyme-catalyzed proximity labeling (PL) has emerged as a new approach to study the spatial and interaction characteristics of proteins in living cells. However, current PL methods require over 18 h of labeling time or utilize chemicals with limited cell permeability or high toxicity. We used yeast display-based directed evolution to engineer two promiscuous mutants of biotin ligase, TurboID and miniTurbo, which catalyze PL with much greater efficiency than BioID or BioID2, and enable 10-min PL in cells with non-toxic and easily deliverable biotin. Furthermore, TurboID extends biotin-based PL to flies and worms.