Institute for Systems Biology

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.

Phagocytosis and the Inflammatory Response

Abstract: Macrophages are a cornerstone of the innate immune system. They detect infectious organisms via a plethora of receptors, phagocytose them, and orchestrate an appropriate host response. Phagocytosis is extraordinarily complex: numerous receptors stimulate particle internalization, the cytoskeletal elements mediating internalization differ by receptor system and the nature of the pathogen being internalized, and the outcome can differ by bacterium. After generating a panel of 150 monoclonal antibodies that recognizes proteins recruited to the phagosome, analysis of novel phagocytic proteins was prioritized by focusing on those that behave differently during the internalization of virulent and avirulent bacteria. Several novel proteins that have roles in membrane extension were characterized. Although the inflammatory pathways leading to appropriate host response are reasonably well defined, it is not clear how macrophages define the threat precisely. Recent work indicates that Toll-like receptors play a key role in reading a bar code on invading microorganisms and in eliciting a specific immune response. The mechanisms and coupling to the phagocytic response are discussed.

High-resolution DNA analysis of human embryonic stem cell lines reveals culture-induced copy number changes and loss of heterozygosity.

Abstract: Prolonged culture of human embryonic stem cells (hESCs) can lead to adaptation and the acquisition of chromosomal abnormalities, underscoring the need for rigorous genetic analysis of these cells. Here we report the highest-resolution study of hESCs to date using an Affymetrix SNP 6.0 array containing 906,600 probes for single nucleotide polymorphisms (SNPs) and 946,000 probes for copy number variations (CNVs). Analysis of 17 different hESC lines maintained in different laboratories identified 843 CNVs of 50 kb-3 Mb in size. We identified, on average, 24% of the loss of heterozygosity (LOH) sites and 66% of the CNVs changed in culture between early and late passages of the same lines. Thirty percent of the genes detected within CNV sites had altered expression compared to samples with normal copy number states, of which >44% were functionally linked to cancer. Furthermore, LOH of the q arm of chromosome 16, which has not been observed previously in hESCs, was detected.

Integrated biclustering of heterogeneous genome-wide datasets for the inference of global regulatory networks.

Abstract: The learning of global genetic regulatory networks from expression data is a severely under-constrained problem that is aided by reducing the dimensionality of the search space by means of clustering genes into putatively co-regulated groups, as opposed to those that are simply co-expressed. Be cause genes may be co-regulated only across a subset of all observed experimental conditions, biclustering (clustering of genes and conditions) is more appropriate than standard clustering. Co-regulated genes are also often functionally (physically, spatially, genetically, and/or evolutionarily) associated, and such a priori known or pre-computed associations can provide support for appropriately grouping genes. One important association is the presence of one or more common cis-regulatory motifs. In organisms where these motifs are not known, their de novo detection, integrated into the clustering algorithm, can help to guide the process towards more biologically parsimonious solutions. We have developed an algorithm, cMonkey, that detects putative co-regulated gene groupings by integrating the biclustering of gene expression data and various functional associations with the de novo detection of sequence motifs. We have applied this procedure to the archaeon Halobacterium NRC-1, as part of our efforts to decipher its regulatory network. In addition, we used cMonkey on public data for three organisms in the other two domains of life: Helicobacter pylori, Saccharomyces cerevisiae, and Escherichia coli. The biclusters detected by cMonkey both recapitulated known biology and enabled novel predictions (some for Halobacterium were subsequently confirmed in the laboratory). For example, it identified the bacteriorhodopsin regulon, assigned additional genes to this regulon with apparently unrelated function, and detected its known promoter motif. We have performed a thorough comparison of cMonkey results against other clustering methods, and find that cMonkey biclusters are more parsimonious with all available evidence for co-regulation.

mTOR Signaling to Translation

Abstract: Over the past few years, the target of rapamycin (TOR) pathway has been implicated in the control of translation, both in yeast and in higher eukaryotes. In this review, we provide an overview of translation in eukaryotes, and discuss the mechanisms and advantages of the regulation of translation. We then describe how the TOR pathway can modulate translation in yeast and in mammals, through the modulation of the phosphorylation of key translation components, and the regulation of the abundance of ribosomes and translation factors.