Bruce W. Birren

Bio: Bruce W. Birren is an academic researcher from Broad Institute. The author has contributed to research in topics: Genome & Gene. The author has an hindex of 103, co-authored 205 publications receiving 113491 citations. Previous affiliations of Bruce W. Birren include Massachusetts Institute of Technology & California Institute of Technology.

Molecular linkage of the mouse CD5 and CD6 genes.

Abstract: CD5 and CD6 are both lymphocyte cell surface glycoproteins that appear to play a role in T-cell activation. In humans, CD6 is a 105000/130000 Mr monomer expressed at high levels by peripheral blood T cells and medullary thymocytes, and also by a small fraction of peripheral blood B cells (Kamoun et al. 1981; Reinherz et al. 1982a, b; Morimoto et al. 1988; Endres et al. 1989; Swack et al. 1989; Cardenas et al. 1990; Aruffo et al. 1991; Swack et al. 1991). The mouse homologue has recently been shown to be a 130000Mr glycoprotein expressed on the surface of thymocytes and T cells in lymph node and spleen (Robinson et al. 1995). Monoclonal antibody (mAb) crosslinking studies have shown that CD6 ligation in combination with costimulatory signals provided by accessory cells, PMA or anti-CD2/CD3 mAbs can induce proliferation of human T cells (Walker et al. 1987; Morimoto et al. 1988; Gangemi et al. 1989; Swack et al. 1989; Bott et al. 1993; Osorio et al. 1994). CD5 is a 67000Mr monomeric glycoprotein expressed on all mature T cells, most thymocytes, and a subset of mature B cells (Ledbetter et al. 1980; Wang et al. 1980; Caligaris-Cappio et al. 1982; Hayakawa et al. 1985; Jones et al. 1986; Huang et al. 1987a). Like CD6, CD5 also seems to play an important role in T-cell activation both in humans and mice, as crosslinking of CD5 by mAbs enhances T-cell proliferation either in a monocyte-dependent manner or in response to mitogens, alloantigens, or CD3-specific mAbs (Hollander et al. 1981; Ledbetter et al. 1985; Ceuppens and Baroja 1986; Nishimura et al. 1988; Spertini et al. 1991; Vandenberghe and Ceuppens 1991; Alberola-Ila et al. 1992). Furthermore, CD5 is physically associated with the Tcr/CD3 complex on T cells (Burgess et al. 1992; Osman et al. 1992). In addition to their similar tissue distribution and costimulatory activity in T cells, CD5 and CD6 are also structurally related molecules: they both belong to the scavenger receptor cysteine rich (SRCR) protein superfamily defined by the cysteine-rich domain of the type I macrophage scavenger receptor (Freeman et al. 1990; Aruffo et al. 1991, Robinson et al. 1995; Whitney et al. 1995). This domain includes a 100 amino acid stretch with six positionally conserved cysteine residues (Freeman et al. 1990). CD5 and CD6 are particularly close homologues, since they are so far the only members of this family possessing three SRCR domains, and they additionally share two cysteine residues and 31 conserved residues in their SRCR domains that are not found in other members of the SRCR family (Aruffo et al. 1991). Furthermore, the human CD5 and CD6 genes have both been mapped to chromosome 11 (Tsuge et al. 1985; Hecht et al. 1989). In mouse, theCD5 gene has been mapped to chromosome 19 (Tada et al. 1982). Because the CD5 and CD6 genes are related and map to the same chromosome in human, the present study was undertaken to look for a possible linkage between the mouse CD5 andCD6 genes. To address this question, we performed pulse field gel electrophoresis (PFGE) experiments using DNA from the mouse CD4+ T-cell line C6VL (obtained from J. Allison, University of Berkeley, CA), which expresses both CD5 ndCD6. Cells were grown in RPMI 1640 (GIBCO, Grand Island, NY) supplemented with 1 mM sodium pyruvate, 10 mM Hepes (Applied Scientific, San Francisco, CA), penicillin (100 units/ml), streptomycin (100 μg/ml; Flow Laboratories, McLean, VA), and 10% heat-inactivated fetal calf serum (Gemini Bio Products, Calabasas, CA). Cells were washed twice and resuspended in 1 × PBS at a concentration of 2× 107 cells/ml, and mixed with an equal volume of 1.5% low-melting temperature agarose (InCert Agarose; FMC BioProducts, Rockland, ME) prepared in 20 mM Tris pH 7.5/50 mM ethylenediaminetetraacetate (EDTA). The agarose/cell plugs were then incuO. Lecomte? J. B. Bock? J. R. Parnes ( ) Department of Medicine, Division of Immunology and Rheumatology, MSLS Building, Room P306, Stanford University School of Medicine, Stanford, CA 94305-5487, USA

Gene-targeted metagenomic analysis of glucan-branching enzyme gene profiles among human and animal fecal microbiota

Abstract: Glycoside hydrolases (GHs), the enzymes that breakdown complex carbohydrates, are a highly diversified class of key enzymes associated with the gut microbiota and its metabolic functions To learn more about the diversity of GHs and their potential role in a variety of gut microbiomes, we used a combination of 16S, metagenomic and targeted amplicon sequencing data to study one of these enzyme families in detail Specifically, we employed a functional gene-targeted metagenomic approach to the 1-4-α-glucan-branching enzyme (gBE) gene in the gut microbiomes of four host species (human, chicken, cow and pig) The characteristics of operational taxonomic units (OTUs) and operational glucan-branching units (OGBUs) were distinctive in each of hosts Human and pig were most similar in OTUs profiles while maintaining distinct OGBU profiles Interestingly, the phylogenetic profiles identified from 16S and gBE gene sequences differed, suggesting the presence of different gBE genes in the same OTU across different vertebrate hosts Our data suggest that gene-targeted metagenomic analysis is useful for an in-depth understanding of the diversity of a particular gene of interest Specific carbohydrate metabolic genes appear to be carried by distinct OTUs in different individual hosts and among different vertebrate species' microbiomes, the characteristics of which differ according to host genetic background and/or diet

16S rRNA gene survey of microbial communities in Winogradsky columns.

Abstract: A Winogradsky column is a clear glass or plastic column filled with enriched sediment. Over time, microbial communities in the sediment grow in a stratified ecosystem with an oxic top layer and anoxic sub-surface layers. Winogradsky columns have been used extensively to demonstrate microbial nutrient cycling and metabolic diversity in undergraduate microbiology labs. In this study, we used high-throughput 16s rRNA gene sequencing to investigate the microbial diversity of Winogradsky columns. Specifically, we tested the impact of sediment source, supplemental cellulose source, and depth within the column, on microbial community structure. We found that the Winogradsky columns were highly diverse communities but are dominated by three phyla: Proteobacteria, Bacteroidetes, and Firmicutes. The community is structured by a founding population dependent on the source of sediment used to prepare the columns and is differentiated by depth within the column. Numerous biomarkers were identified distinguishing sample depth, including Cyanobacteria, Alphaproteobacteria, and Betaproteobacteria as biomarkers of the soil-water interface, and Clostridia as a biomarker of the deepest depth. Supplemental cellulose source impacted community structure but less strongly than depth and sediment source. In columns dominated by Firmicutes, the family Peptococcaceae was the most abundant sulfate reducer, while in columns abundant in Proteobacteria, several Deltaproteobacteria families, including Desulfobacteraceae, were found, showing that different taxonomic groups carry out sulfur cycling in different columns. This study brings this historical method for enrichment culture of chemolithotrophs and other soil bacteria into the modern era of microbiology and demonstrates the potential of the Winogradsky column as a model system for investigating the effect of environmental variables on soil microbial communities.

Initial sequencing and analysis of the human genome.

Abstract: The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data

Abstract: Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS—the 1000 Genome pilot alone includes nearly five terabases—make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.

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。

SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V−SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online (http://bioinf.spbau.ru/spades). It is distributed as open source software.

Full-length transcriptome assembly from RNA-Seq data without a reference genome.

Abstract: Massively parallel sequencing of cDNA has enabled deep and efficient probing of transcriptomes. Current approaches for transcript reconstruction from such data often rely on aligning reads to a reference genome, and are thus unsuitable for samples with a partial or missing reference genome. Here we present the Trinity method for de novo assembly of full-length transcripts and evaluate it on samples from fission yeast, mouse and whitefly, whose reference genome is not yet available. By efficiently constructing and analyzing sets of de Bruijn graphs, Trinity fully reconstructs a large fraction of transcripts, including alternatively spliced isoforms and transcripts from recently duplicated genes. Compared with other de novo transcriptome assemblers, Trinity recovers more full-length transcripts across a broad range of expression levels, with a sensitivity similar to methods that rely on genome alignments. Our approach provides a unified solution for transcriptome reconstruction in any sample, especially in the absence of a reference genome.