Open AccessBiologically anchored knowledge expansion approach uncovers KLF4 as a novel insulin signaling regulator
Author(s) -
Annamalai Muthiah,
Morgan S. Angulo,
Natalie N. Walker,
Susanna R. Keller,
Jae K. Lee
Publication year - 2018
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0204100
Subject(s) - insulin receptor , computational biology , klf4 , irs1 , regulator , transcription factor , biology , insulin resistance , biological pathway , insulin , irs2 , bioinformatics , computer science , genetics , gene expression , gene , sox2 , microbiology and biotechnology
One of the biggest challenges in analyzing high throughput omics data in biological studies is extracting information that is relevant to specific biological mechanisms of interest while simultaneously restricting the number of false positive findings. Due to random chances with numerous candidate targets and mechanisms, computational approaches often yield a large number of false positives that cannot easily be discerned from relevant biological findings without costly, and often infeasible, biological experiments. We here introduce and apply an integrative bioinformatics approach, Biologically Anchored Knowledge Expansion (BAKE), which uses sequential statistical analysis and literature mining to identify highly relevant network genes and effectively removes false positive findings. Applying BAKE to genomic expression data collected from mouse ( Mus musculus ) adipocytes during insulin resistance progression, we uncovered the transcription factor Krueppel-like Factor 4 (KLF4) as a regulator of early insulin signaling. We experimentally confirmed that KLF4 controls the expression of two key insulin signaling molecules, the Insulin Receptor Substrate 2 (IRS2) and Tuberous Sclerosis Complex 2 (TSC2).