Gradient Descent Optimization in Gene Regulatory Pathways

BACKGROUND: Gene Regulatory Networks (GRNs) have become a major focus of interest in recent years. Elucidating the architecture and dynamics of large scale gene regulatory networks is an important goal in systems biology. The knowledge of the gene regulatory networks further gives insights about gene regulatory pathways. This information leads to many potential applications in medicine and molecular biology, examples of which are identification of metabolic pathways, complex genetic diseases, drug discovery and toxicology analysis. High-throughput technologies allow studying various aspects of gene regulatory networks on a genome-wide scale and we will discuss recent advances as well as limitations and future challenges for gene network modeling. Novel approaches are needed to both infer the causal genes and generate hypothesis on the underlying regulatory mechanisms. METHODOLOGY: In the present article, we introduce a new method for identifying a set of optimal gene regulatory pathways by using structural equations as a tool for modeling gene regulatory networks. The method, first of all, generates data on reaction flows in a pathway. A set of constraints is formulated incorporating weighting coefficients. Finally the gene regulatory pathways are obtained through optimization of an objective function with respect to these weighting coefficients. The effectiveness of the present method is successfully tested on ten gene regulatory networks existing in the literature. A comparative study with the existing extreme pathway analysis also forms a part of this investigation. The results compare favorably with earlier experimental results. The validated pathways point to a combination of previously documented and novel findings. CONCLUSIONS: We show that our method can correctly identify the causal genes and effectively output experimentally verified pathways. The present method has been successful in deriving the optimal regulatory pathways for all the regulatory networks considered. The biological significance and applicability of the optimal pathways has also been discussed. Finally the usefulness of the present method on genetic engineering is depicted with an example

Contribution of Zinc-Dependent Delayed Calcium Influx via TRPC5 in Oxidative Neuronal Death and its Prevention by Novel TRPC Antagonist

Oxidative stress is a key mediator of neuronal death in acute brain injuries, such as epilepsy, trauma, and stroke. Although it is accompanied by diverse cellular changes, increases in levels of intracellular zinc ion (Zn2+) and calcium ion (Ca2+) may play a critical causative role in oxidative neuronal death. However, the mechanistic link between Zn2+ and Ca2+ dyshomeostasis in neurons during oxidative stress is not well-understood. Here, we show that the exposure of cortical neurons to H2O2 led to a zinc-triggered calcium influx, which resulted in neuronal death. The cyclin-dependent kinase inhibitor, NU6027, inhibited H2O2-induced Ca2+ increases and subsequent cell death in cortical neurons, without affecting the early increase in Zn2+. Therefore, we attempted to identify the zinc-regulated Ca2+ pathway that was inhibited by NU6027. The expression profile in cortical neurons identified transient receptor potential cation channel 5 (TRPC5) as a candidate that is known to involve in the generation of epileptiform burst firing and epileptic neuronal death (Phelan KD et al. 2012a; Phelan KD et al. 2013b). NU6027 inhibited basal and zinc-augmented TRPC5 currents in TRPC5-overexpressing HEK293 cells. Consistently, cortical neurons from TRPC5 knockout mice were highly resistant to H2O2-induced death. Moreover, NU6027 is neuroprotective in kainate-treated epileptic rats. Our results demonstrate that TRPC5 is a novel therapeutic target against oxidative neuronal injury in prolonged seizures and that NU6027 is a potent inhibitor of TRPC5