Search bioRxivSearch

Biology subjects

Bridges, D.

Publications and source records attributed to Bridges, D..

3 recordsLinked to original sources

The Signaling Pathways Project: an integrated ‘omics knowledgebase for mammalian cellular signaling pathways

Integrated mining of public transcriptomic and ChIP-Seq datasets has the potential to illuminate facets of mammalian cellular signaling pathways not yet explored in the research literature. Here, we designed a web knowledgebase, the Signaling Pathways Project (SPP), which incorporates stable community classifications of the four major categories of signaling pathway node (receptors, enzymes, transcription factors and co-nodes) and their cognate bioactive small molecules (BSMs). We then mapped over 10,000 public transcriptomic or cistromic experiments to their relevant signaling pathway node, BSM or biosample of study. To provide for prediction of pathway node-target transcriptional regulatory relationships, we generated consensus omics signatures, or consensomes, based on measures of significant differential expression of genomic targets across all underlying transcriptomic experiments. To expose the SPP knowledgebase to researchers, a web browser interface accommodates a variety of routine data mining strategies. Consensomes were validated using alignment with literature-based knowledge, gene target-level integration of transcriptomic and ChIP-Seq data points, and in bench experiments that confirmed previously uncharacterized node-gene target regulatory relationships. SPP is freely accessible at https://beta.signalingpathways.org.

bioinformatics

Use of a Neural Circuit Probe to Validate in silico Predictions of Inhibitory Connections

Understanding how neuronal signals propagate in local network is an important step in understanding information processing. As a result, spike trains recorded with Multi-electrode Arrays (MEAs) have been widely used to study behaviors of neural connections. Studying the dynamics of neuronal networks requires the identification of both excitatory and inhibitory connections. The detection of excitatory relationships can robustly be inferred by characterizing the statistical relationships of neural spike trains. However, the identification of inhibitory relationships is more difficult: distinguishing endogenous low firing rates from active inhibition is not obvious. In this paper, we propose an in silico interventional procedure that makes predictions about the effect of stimulating or inhibiting single neurons on other neurons, and thereby gives the ability to accurately identify inhibitory causal relationships. To experimentally test these predictions, we have developed a Neural Circuit Probe (NCP) that delivers drugs transiently and reversibly on individually identified neurons to assess their contributions to the neural circuit behavior. With the help of NCP, three inhibitory connections identified by our in silico modeling were validated through real interventional experiments. Together, these methods provide a basis for mapping complete neural circuits.

neuroscience

Glucocorticoid-Induced Metabolic Disturbances are Exacerbated in Obesity

Obesity and chronically elevated glucocorticoids result in similar co-morbidities, but the effect of a combination of these ailments on metabolic outcomes is unclear. Measures of glucose homeostasis and markers of hepatic lipid accumulation were assessed to determine whether obesity exaggerated the effects of dexamethasone-induced metabolic disturbances. The combination of obesity and glucocorticoids resulted in hepatic steatosis and synergistic impairments in insulin sensitivity and this was matched with synergistic elevations in markers of lipolysis. These findings suggest lipolysis may be a key player in glucocorticoid-induced insulin resistance and fatty liver in people with obesity.

physiology