Allan Kuchinsky

Integration of biological networks and gene expression data using Cytoscape

Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.

The Synthetic Biology Open Language (SBOL) provides a community standard for communicating designs in synthetic biology

The re-use of previously validated designs is critical to the evolution of synthetic biology from a research discipline to an engineering practice. Here we describe the Synthetic Biology Open Language (SBOL), a proposed data standard for exchanging designs within the synthetic biology community. SBOL represents synthetic biology designs in a community-driven, formalized format for exchange between software tools, research groups and commercial service providers. The SBOL Developers Group has implemented SBOL as an XML/RDF serialization and provides software libraries and specification documentation to help developers implement SBOL in their own software. We describe early successes, including a demonstration of the utility of SBOL for information exchange between several different software tools and repositories from both academic and industrial partners. As a community-driven standard, SBOL will be updated as synthetic biology evolves to provide specific capabilities for different aspects of the synthetic biology workflow.

GLay: Community structure analysis of biological networks

Summary: GLay provides Cytoscape users an assorted collection of versatile community structure algorithms and graph layout functions for network clustering and structured visualization. High performance is achieved by dynamically linking highly optimized C functions to the Cytoscape JAVA program, which makes GLay especially suitable for decomposition, display and exploratory analysis of large biological networks. Availability: http://brainarray.mbni.med.umich.edu/glay/ Contact: sugang@umich.edu

Alternative Splicing in the Differentiation of Human Embryonic Stem Cells into Cardiac Precursors

The role of alternative splicing in self-renewal, pluripotency and tissue lineage specification of human embryonic stem cells (hESCs) is largely unknown. To better define these regulatory cues, we modified the H9 hESC line to allow selection of pluripotent hESCs by neomycin resistance and cardiac progenitors by puromycin resistance. Exon-level microarray expression data from undifferentiated hESCs and cardiac and neural precursors were used to identify splice isoforms with cardiac-restricted or common cardiac/neural differentiation expression patterns. Splice events for these groups corresponded to the pathways of cytoskeletal remodeling, RNA splicing, muscle specification, and cell cycle checkpoint control as well as genes with serine/threonine kinase and helicase activity. Using a new program named AltAnalyze (http://www.AltAnalyze.org), we identified novel changes in protein domain and microRNA binding site architecture that were predicted to affect protein function and expression. These included an enrichment of splice isoforms that oppose cell-cycle arrest in hESCs and that promote calcium signaling and cardiac development in cardiac precursors. By combining genome-wide predictions of alternative splicing with new functional annotations, our data suggest potential mechanisms that may influence lineage commitment and hESC maintenance at the level of specific splice isoforms and microRNA regulation.

Network Analysis of Human In-Stent Restenosis

Background— Recent successes in the treatment of in-stent restenosis (ISR) by drug-eluting stents belie the challenges still faced in certain lesions and patient groups. We analyzed human coronary atheroma in de novo and restenotic disease to identify targets of therapy that might avoid these limitations. Methods and Results— We recruited 89 patients who underwent coronary atherectomy for de novo atherosclerosis (n=55) or in-stent restenosis (ISR) of a bare metal stent (n=34). Samples were fixed for histology, and gene expression was assessed with a dual-dye 22 000 oligonucleotide microarray. Histological analysis revealed significantly greater cellularity and significantly fewer inflammatory infiltrates and lipid pools in the ISR group. Gene ontology analysis demonstrated the prominence of cell proliferation programs in ISR and inflammation/immune programs in de novo restenosis. Network analysis, which combines semantic mining of the published literature with the expression signature of ISR, revealed gene expression modules suggested as candidates for selective inhibition of restenotic disease. Two modules are presented in more detail, the procollagen type 1 &agr;2 gene and the ADAM17/tumor necrosis factor-&agr; converting enzyme gene. We tested our contention that this method is capable of identifying successful targets of therapy by comparing mean significance scores for networks generated from subsets of the published literature containing the terms “sirolimus” or “paclitaxel.” In addition, we generated 2 large networks with sirolimus and paclitaxel at their centers. Both analyses revealed higher mean values for sirolimus, suggesting that this agent has a broader suppressive action against ISR than paclitaxel. Conclusions— Comprehensive histological and gene network analysis of human ISR reveals potential targets for directed abrogation of restenotic disease and recapitulates the results of clinical trials of existing agents.

Protein network prediction and topological analysis in Leishmania major as a tool for drug target selection

BackgroundLeishmaniasis is a virulent parasitic infection that causes a worldwide disease burden. Most treatments have toxic side-effects and efficacy has decreased due to the emergence of resistant strains. The outlook is worsened by the absence of promising drug targets for this disease. We have taken a computational approach to the detection of new drug targets, which may become an effective strategy for the discovery of new drugs for this tropical disease.ResultsWe have predicted the protein interaction network of Leishmania major by using three validated methods: PSIMAP, PEIMAP, and iPfam. Combining the results from these methods, we calculated a high confidence network (confidence score > 0.70) with 1,366 nodes and 33,861 interactions. We were able to predict the biological process for 263 interacting proteins by doing enrichment analysis of the clusters detected. Analyzing the topology of the network with metrics such as connectivity and betweenness centrality, we detected 142 potential drug targets after homology filtering with the human proteome. Further experiments can be done to validate these targets.ConclusionWe have constructed the first protein interaction network of the Leishmania major parasite by using a computational approach. The topological analysis of the protein network enabled us to identify a set of candidate proteins that may be both (1) essential for parasite survival and (2) without human orthologs. These potential targets are promising for further experimental validation. This strategy, if validated, may augment established drug discovery methodologies, for this and possibly other tropical diseases, with a relatively low additional investment of time and resources.

Exploring Biological Networks with Cytoscape Software

Cytoscape is a free software package for visualizing, modeling, and analyzing molecular and genetic interaction networks. As a key feature, Cytoscape enables biologists to determine and analyze the interconnectivity of a list of genes or proteins. This unit explains how to use Cytoscape to load and navigate biological network information and view mRNA expression profiles and other functional genomics and proteomics data in the context of the network obtained for genes of interest. Additional analyses that can be performed with Cytoscape are also discussed. Curr. Protoc. Bioinform. 23:8.13.1‐8.13.20.

Biological storytelling: a software tool for biological information organization based upon narrative structure

The main task of molecular biologists seeking to understand the molecular basis of disease is identifying and interpreting the relationships of genes, proteins, and pathways in living organisms. While emerging technologies have provided powerful analysis tools to this end, they have also produced an explosion of data, which biologists need to make sense of. We have built software tools to support the synthesis activities of molecular biologists, in particular the activities of organizing, retrieving, using, sharing, and reusing diverse biological information. A key aspect of our approach, based upon the findings of user studies, is the use of narrative structure as a conceptual framework for developing and representing the story of how genes, proteins, and other molecules interact in biological processes. Biological stories are represented both textually and graphically within a simple conceptual model of items, collections, and stories.

VistaClara: an expression browser plug-in for Cytoscape

Summary: VistaClara is a plug-in for Cytoscape which provides a more flexible means to visualize gene and protein expression within a network context. An extended attribute browser is provided in the form of a graphical and interactive permutation matrix that resembles the heat map displays popular in gene-expression analysis. This extended browser permits a variety of display options and interactions not currently available in Cytoscape. Availability: http://chianti.ucsd.edu/cyto_web/plugins/index.php Contact: robert_kincaid@agilent.com

Oxido-reductive regulation of vascular remodeling by receptor tyrosine kinase ROS1

Angioplasty and stenting is the primary treatment for flow-limiting atherosclerosis; however, this strategy is limited by pathological vascular remodeling. Using a systems approach, we identified a role for the network hub gene glutathione peroxidase-1 (GPX1) in pathological remodeling following human blood vessel stenting. Constitutive deletion of Gpx1 in atherosclerotic mice recapitulated this phenotype of increased vascular smooth muscle cell (VSMC) proliferation and plaque formation. In an independent patient cohort, gene variant pair analysis identified an interaction of GPX1 with the orphan protooncogene receptor tyrosine kinase ROS1. A meta-analysis of the only genome-wide association studies of human neointima-induced in-stent stenosis confirmed the association of the ROS1 variant with pathological remodeling. Decreased GPX1 expression in atherosclerotic mice led to reductive stress via a time-dependent increase in glutathione, corresponding to phosphorylation of the ROS1 kinase activation site Y2274. Loss of GPX1 function was associated with both oxidative and reductive stress, the latter driving ROS1 activity via s-glutathiolation of critical residues of the ROS1 tyrosine phosphatase SHP-2. ROS1 inhibition with crizotinib and deglutathiolation of SHP-2 abolished GPX1-mediated increases in VSMC proliferation while leaving endothelialization intact. Our results indicate that GPX1-dependent alterations in oxido-reductive stress promote ROS1 activation and mediate vascular remodeling.