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

Identification and functional validation of PNAs that inhibit murine CD40 expression by redirection of splicing

Cognate recognition between the CD40 receptor and its ligand, CD154, is thought to play a central role in the initiation and propagation of immune responses. We describe the specific down regulation of cell surface associated CD40 protein expression by use of a peptide nucleic acid (PNA) antisense inhibitor, ISIS 208529, that is designed to bind to the 3′ end of the exon 6 splice junction within the primary CD40 transcript. Binding of ISIS 208529 was found to alter constitutive splicing, leading to the accumulation of a transcript lacking exon 6. The resulting protein product lacks the transmembrane domain. ISIS 208529-mediated CD40 protein depletion was found to be sequence specific and dose dependent, and was dependent on the length of the PNA oligomer. CD40-dependent induction of IL-12 in primary murine macrophages was attenuated in cells treated with ISIS 208529. Oligolysine conjugation to the PNA inhibitor produced an inhibitor, ISIS 278647, which maintained its specificity and displayed efficacy in BCL(1) cells and in primary murine macrophages in the absence of delivery agents. These results demonstrate that PNA oligomers can be effective inhibitors of CD40 expression and hence may be useful as novel immuno-modulatory agents

An Endogenous TNF-α Antagonist Induced by Splice-switching Oligonucleotides Reduces Inflammation in Hepatitis and Arthritis Mouse Models

Tumor necrosis factor-α (TNF-α) is a key mediator of inflammatory diseases, including rheumatoid arthritis (RA), and anti–TNF-α drugs such as etanercept are effective treatments. Splice-switching oligonucleotides (SSOs) are a new class of drugs designed to induce therapeutically favorable splice variants of targeted genes. In this work, we used locked nucleic acid (LNA)–based SSOs to modulate splicing of TNF receptor 2 (TNFR2) pre-mRNA. The SSO induced skipping of TNFR2 exon 7, which codes the transmembrane domain (TM), switching endogenous expression from the membrane-bound, functional form to a soluble, secreted form (Δ7TNFR2). This decoy receptor protein accumulated in the circulation of treated mice, antagonized TNF-α, and altered disease in two mouse models: TNF-α-induced hepatitis and collagen-induced arthritis (CIA). This is the first report of upregulation of the endogenous, circulating TNF-α antagonist by oligonucleotide-induced splicing modulation