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.

MINERVA-a platform for visualization and curation of molecular interaction networks.

Abstract: Our growing knowledge about various molecular mechanisms is becoming increasingly more structured and accessible. Different repositories of molecular interactions and available literature enable construction of focused and high-quality molecular interaction networks. Novel tools for curation and exploration of such networks are needed, in order to foster the development of a systems biology environment. In particular, solutions for visualization, annotation and data cross-linking will facilitate usage of network-encoded knowledge in biomedical research. To this end we developed the MINERVA (Molecular Interaction NEtwoRks VisuAlization) platform, a standalone webservice supporting curation, annotation and visualization of molecular interaction networks in Systems Biology Graphical Notation (SBGN)-compliant format. MINERVA provides automated content annotation and verification for improved quality control. The end users can explore and interact with hosted networks, and provide direct feedback to content curators. MINERVA enables mapping drug targets or overlaying experimental data on the visualized networks. Extensive export functions enable downloading areas of the visualized networks as SBGN-compliant models for efficient reuse of hosted networks. The software is available under Affero GPL 3.0 as a Virtual Machine snapshot, Debian package and Docker instance at http://r3lab.uni.lu/web/minerva-website/ . We believe that MINERVA is an important contribution to systems biology community, as its architecture enables set-up of locally or globally accessible SBGN-oriented repositories of molecular interaction networks. Its functionalities allow overlay of multiple information layers, facilitating exploration of content and interpretation of data. Moreover, annotation and verification workflows of MINERVA improve the efficiency of curation of networks, allowing life-science researchers to better engage in development and use of biomedical knowledge repositories. A web platform that integrates data on biological networks can help scientists obtain deeper insights into the inner workings of the cell. Life is powered by the complex interplay between myriad 'pathways' composed of interacting proteins, DNA and other biomolecules. Biologists have accumulated vast troves of data on these processes, and now researchers led by Piotr Gawron at the University of Luxembourg have built software that can combine these disparate datasets into a more meaningful 'big picture'. The Molecular Interaction Networks Visualization (MINERVA) platform allows users to interact directly with graphical representations of biological pathways as a means to understand the broader cellular impacts of both diseases and the drugs intended to treat them. The resulting maps can then be manually curated, annotated and exported to other bioinformatics platforms for use by the broader research community.

Serologic analysis of ovarian tumor antigens reveals a bias toward antigens encoded on 17q.

Abstract: We utilized SEREX immunoscreening to identify a set of novel tumor antigens that are associated with human serous ovarian cancer and may prove useful for the early detection and treatment of this disease. Extensive screening with a panel of sera from 25 late-stage ovarian cancer patients against 3 independent cDNA libraries identified a set of 9 antigens that were immunogenic in more than 1 patient and not in a panel of 20-45 normal female serum donors. These antigens include p53, NY-ESO-1, UBQLN1, HOXB6, TOP2A, putative helicase-RUVBL (RUVBL), HMBA-inducible (HEXIM1), DDX5 and HDCMA. Ten of 25 ovarian cancer patients (40%) expressed serum IgG to at least 1 of these antigens, while 14% (4/25) had antibodies to 2 or more antigens. Unexpectedly, 4 antigens identified in this screen, DDX5, HEXIM1, TOP2A and HOXB6, are encoded within a region of 17q that also includes the genes for HER2/neu, Homeobox-B7 and BRCA1. Real-time RT-PCR analysis showed that mRNA for HER2/neu and 3 SEREX-defined antigens, TOP2A, HOXB6 and DDX5, was more abundant in ovarian tumors than most normal tissues, including normal and benign ovarian tissues, suggesting that elevated expression of genes encoded within this region of chromosome 17 is a common event in ovarian tumors. Thus, these abnormal expression patterns combined with the endogenous immune response suggests that these antigens represent potential targets for immunotherapy.

Genomic and genetic dissection of an archaeal regulon

Abstract: The extremely halophilic archaeon Halobacterium sp. NRC-1 can grow phototrophically by means of light-driven proton pumping by bacteriorhodopsin in the purple membrane. Here, we show by genetic analysis of the wild type, and insertion and double-frame shift mutants of Bat that this transcriptional regulator coordinates synthesis of a structural protein and a chromophore for purple membrane biogenesis in response to both light and oxygen. Analysis of the complete Halobacterium sp. NRC-1 genome sequence showed that the regulatory site, upstream activator sequence (UAS), the putative binding site for Bat upstream of the bacterio-opsin gene (bop), is also present upstream to the other Bat-regulated genes. The transcription regulator Bat contains a photoresponsive cGMP-binding (GAF) domain, and a bacterial AraC type helix–turn–helix DNA binding motif. We also provide evidence for involvement of the PAS/PAC domain of Bat in redox-sensing activity by genetic analysis of a purple membrane overproducer. Five additional Bat-like putative regulatory genes were found, which together are likely to be responsible for orchestrating the complex response of this archaeon to light and oxygen. Similarities of the bop-like UAS and transcription factors in diverse organisms, including a plant and a γ-proteobacterium, suggest an ancient origin for this regulon capable of coordinating light and oxygen responses in the three major branches of the evolutionary tree of life. Finally, sensitivity of four of five regulon genes to DNA supercoiling is demonstrated and correlated to presence of alternating purine–pyrimidine sequences (RY boxes) near the regulated promoters.

Identification of androgen-coregulated protein networks from the microsomes of human prostate cancer cells

Abstract: Background: Androgens play a critical role in the development of prostate cancer-dysregulation of androgen-regulated growth pathways can led to hormone-refractory prostate cancer. A comprehensive understanding of androgen-regulated cellular processes has not been achieved to date. To this end, we have applied a large-scale proteomic approach to define cellular processes that are responsive to androgen treatment in LNCaP prostate cancer cells. Results: Using isotope-coded affinity tags and mass spectrometry we identified and quantified the relative abundance levels of 1,064 proteins and found that distinct cellular processes were coregulated by androgen while others were essentially unaffected. Subsequent pharmacological perturbation of the cellular process for energy generation confirmed that androgen starvation had a profound effect on this pathway. Conclusions: Our results provide evidence for the role of androgenic hormones in coordinating the expression of critical components involved in distinct cellular processes and further establish a foundation for the comprehensive reconstruction of androgen-regulated protein networks and pathways in prostate cancer cells.

State of the Human Proteome in 2014/2015 As Viewed through PeptideAtlas: Enhancing Accuracy and Coverage through the AtlasProphet.

Abstract: The Human PeptideAtlas is a compendium of the highest quality peptide identifications from over 1000 shotgun mass spectrometry proteomics experiments collected from many different laboratories, all reanalyzed through a uniform processing pipeline. The latest 2015-03 build contains substantially more input data than past releases, is mapped to a recent version of our merged reference proteome, and uses improved informatics processing and the development of the AtlasProphet to provide the highest quality results. Within the set of ∼20,000 neXtProt primary entries, 14,070 (70%) are confidently detected in the latest build, 5% are ambiguous, 9% are redundant, leaving the total percentage of proteins for which there are no mapping detections at just 16% (3166), all derived from over 133 million peptide-spectrum matches identifying more than 1 million distinct peptides using AtlasProphet to characterize and classify the protein matches. Improved handling for detection and presentation of single amino-acid variants (SAAVs) reveals the detection of 5326 uniquely mapping SAAVs across 2794 proteins. With such a large amount of data, the control of false positives is a challenge. We present the methodology and results for maintaining rigorous quality along with a discussion of the implications of the remaining sources of errors in the build.