Reputation-based collaborative network biology.

A pilot reputation-based collaborative network biology platform, Bionet, was developed for use in the sbv IMPROVER Network Verification Challenge to verify and enhance previously developed networks describing key aspects of lung biology. Bionet was successful in capturing a more comprehensive view of the biology associated with each network using the collective intelligence and knowledge of the crowd. One key learning point from the pilot was that using a standardized biological knowledge representation language such as BEL is critical to the success of a collaborative network biology platform. Overall, Bionet demonstrated that this approach to collaborative network biology is highly viable. Improving this platform for de novo creation of biological networks and network curation with the suggested enhancements for scalability will serve both academic and industry systems biology communities.

A vascular biology network model focused on inflammatory processes to investigate atherogenesis and plaque instability.

BACKGROUND: Numerous inflammation-related pathways have been shown to play important roles in atherogenesis. Rapid and efficient assessment of the relative influence of each of those pathways is a challenge in the era of "omics" data generation. The aim of the present work was to develop a network model of inflammation-related molecular pathways underlying vascular disease to assess the degree of translatability of preclinical molecular data to the human clinical setting. METHODS: We constructed and evaluated the Vascular Inflammatory Processes Network (V-IPN), a model representing a collection of vascular processes modulated by inflammatory stimuli that lead to the development of atherosclerosis. RESULTS: Utilizing the V-IPN as a platform for biological discovery, we have identified key vascular processes and mechanisms captured by gene expression profiling data from four independent datasets from human endothelial cells (ECs) and human and murine intact vessels. Primary ECs in culture from multiple donors revealed a richer mapping of mechanisms identified by the V-IPN compared to an immortalized EC line. Furthermore, an evaluation of gene expression datasets from aortas of old ApoE-/- mice (78 weeks) and human coronary arteries with advanced atherosclerotic lesions identified significant commonalities in the two species, as well as several mechanisms specific to human arteries that are consistent with the development of unstable atherosclerotic plaques. CONCLUSIONS: We have generated a new biological network model of atherogenic processes that demonstrates the power of network analysis to advance integrative, systems biology-based knowledge of cross-species translatability, plaque development and potential mechanisms leading to plaque instability.

Differential effects of Gq alpha, G14 alpha, and G15 alpha on vascular smooth muscle cell survival and gene expression profiles.

Gqalpha family members (Gqalpha, G11alpha, G14alpha, and G15/16alpha) stimulate phospholipase Cbeta (PLCbeta) and inositol lipid signaling but differ markedly in amino acid sequence and tissue distribution predicting unappreciated functional diversity. To examine functional differences, we compared the signaling properties of Gqalpha, G14alpha, and G15alpha and their cellular responses in vascular smooth muscle cells (VSMC). Constitutively active forms of Gqalpha, G14alpha, or G15alpha elicit markedly different responses when introduced to VSMC. Whereas each Galpha stimulated PLCbeta to similar extents when expressed at equal protein levels, Gqalpha and G14alpha but not G15alpha initiated profound cell death within 48 h. This response was the result of activation of apoptotic pathways, because Gqalpha and G14alpha, but not G15alpha, stimulated caspase-3 activation and did not alter phospho-Akt, a regulator of cell survival pathways. Gqalpha and G14alpha stimulate nuclear factor of activated T cell (NFAT) activation in VSMC, but Galpha-induced cell death seems independent of PKC, InsP(3)/Ca(2+), and NFAT, in that pharmacological inhibitors of these pathways did not block cell death. Gene expression analysis indicates that Gqalpha, G14alpha, and G15alpha each elicit markedly different profiles of altered gene sets in VSMC after 24 h. Whereas all three Galpha stimulated changes (> or =2-fold) in 50 shared mRNA, Gqalpha and G14alpha (but not G15alpha) stimulated changes in 221 shared mRNA, many of which are reported to be pro-apoptotic and/or involved with TNF-alpha signaling. We were surprised to find that each Galpha also stimulated changes in nonoverlapping Galpha-specific gene sets. These findings demonstrate that Gqalpha family members activate both overlapping and distinct signaling pathways and are more functionally diverse than previously thought.