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Institute for Systems Biology

NonprofitSeattle, Washington, United States
About: Institute for Systems Biology is a nonprofit organization based out in Seattle, Washington, United States. It is known for research contribution in the topics: Population & Proteomics. The organization has 1277 authors who have published 2777 publications receiving 353165 citations.


Papers
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Journal ArticleDOI
TL;DR: A robust and general method is presented for the identification and relative quantification of phosphorylation sites in complex protein mixtures based on a new chemical derivatization strategy using a dendrimer as a soluble polymer support and tandem mass spectrometry (MS/MS).
Abstract: We present a robust and general method for the identification and relative quantification of phosphorylation sites in complex protein mixtures. It is based on a new chemical derivatization strategy using a dendrimer as a soluble polymer support and tandem mass spectrometry (MS/MS). In a single step, phosphorylated peptides are covalently conjugated to a dendrimer in a reaction catalyzed by carbodiimide and imidazole. Modified phosphopeptides are released from the dendrimer via acid hydrolysis and analyzed by MS/MS. When coupled with an initial antiphosphotyrosine protein immunoprecipitation step and stable-isotope labeling, in a single experiment, we identified all known tyrosine phosphorylation sites within the immunoreceptor tyrosine-based activation motifs (ITAM) of the T-cell receptor (TCR) CD3 chains, and previously unknown phosphorylation sites on total 97 tyrosine phosphoproteins and their interacting partners in human T cells. The dynamic changes in phosphorylation were quantified in these proteins.

299 citations

Journal ArticleDOI
TL;DR: In this paper, the authors have identified and characterized an alternative RFC complex RFC(CTF18p, CTF8p, Dcc1p) that is required for sister chromatid cohesion and faithful chromosome transmission.

298 citations

Journal ArticleDOI
TL;DR: By uncovering the interrelationships between host diet and lifestyle factors, clinical blood markers, and the human gut microbiome at the population-scale, the results serve as a roadmap for future studies on host-microbe interactions and interventions.
Abstract: Variation in the human gut microbiome can reflect host lifestyle and behaviors and influence disease biomarker levels in the blood. Understanding the relationships between gut microbes and host phenotypes are critical for understanding wellness and disease. Here, we examine associations between the gut microbiota and ~150 host phenotypic features across ~3,400 individuals. We identify major axes of taxonomic variance in the gut and a putative diversity maximum along the Firmicutes-to-Bacteroidetes axis. Our analyses reveal both known and unknown associations between microbiome composition and host clinical markers and lifestyle factors, including host-microbe associations that are composition-specific. These results suggest potential opportunities for targeted interventions that alter the composition of the microbiome to improve host health. By uncovering the interrelationships between host diet and lifestyle factors, clinical blood markers, and the human gut microbiome at the population-scale, our results serve as a roadmap for future studies on host-microbe interactions and interventions.

298 citations

Journal ArticleDOI
TL;DR: It is shown how the functions of several GRNs can be considered in mathematical terms, and the resolution of GRNs by both "top down" and "bottom up" approaches are discussed.
Abstract: Summary Developmental processes in complex animals are directed by a hardwired genomic regulatory code, the ultimate function of which is to set up a progression of transcriptional regulatory states in space and time. The code specifies the gene regulatory networks (GRNs) that underlie allmajor developmentalevents.Modelsof GRNs are required for analysis, for experimental manipulation and, most fundamentally, for comprehension of how GRNs work. To model GRNs requires knowledge of both their overall structure, which depends upon linkage amongst regulatory genes, and the modular building blocksofwhichGRNsareheirarchicallyconstructed.The building blocks consist of basic transcriptional control processes executed by one or a few functionally linked genes. We show how the functions of several such buildingblockscanbeconsideredinmathematicalterms, and discuss resolution of GRNs by both ‘‘top down’’ and ‘‘bottom up’’ approaches. BioEssays 24:1118–1129, 2002. 2002 Wiley Periodicals, Inc.

297 citations

Journal ArticleDOI
TL;DR: It is demonstrated here that Pseudomonas aeruginosa activates caspase 1 and induces IL-1β secretion in infected macrophages and that Ipaf-dependent detection of cytosolic flagellin is a conserved mechanism by which macrophage detect the presence of pathogens that use T3SS.
Abstract: The innate immune system encodes cytosolic Nod-like receptors (NLRs), several of which activate caspase 1 processing and IL-1β and IL-18 secretion. Macrophages respond to Salmonella typhimurium infection by activating caspase 1 through the NLR Ipaf. This activation is mediated by cytosolic flagellin through the activity of the virulence-associated type III secretion system (T3SS). We demonstrate here that Pseudomonas aeruginosa activates caspase 1 and induces IL-1β secretion in infected macrophages. While live, virulent P. aeruginosa activate IL-1β secretion through caspase 1 and Ipaf, strains that have mutations in the T3SS or in flagellin did not. Ipaf-dependent caspase 1 activation could be recapitulated by delivering P. aeruginosa flagellin to the macrophage cytosol. We examined the role of Naip5 in P. aeruginosa-induced caspase 1 activation by using A/J (Naip5-deficient) compared with C57BL/6 and BALB/c (Naip5-sufficient) macrophages and observed that A/J macrophages secrete IL-1β in response to P. aeruginosa, S. typhimurium, and Listeria monocytogenes infection, as well as in response to cytosolic flagellin, but at slightly reduced levels. Thus, Ipaf-dependent detection of cytosolic flagellin is a conserved mechanism by which macrophages detect the presence of pathogens that use T3SS.

297 citations


Authors

Showing all 1292 results

NameH-indexPapersCitations
Younan Xia216943175757
Ruedi Aebersold182879141881
David Haussler172488224960
Steven P. Gygi172704129173
Nahum Sonenberg167647104053
Leroy Hood158853128452
Mark H. Ellisman11763755289
Wei Zhang112118993641
John Ralph10944239238
Eric H. Davidson10645447058
James R. Heath10342558548
Alan Aderem9924646682
Anne-Claude Gingras9733640714
Trey Ideker9730672276
Michael H. Gelb9450634714
Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20233
202260
2021216
2020204
2019188
2018168