C. elegans protein interaction network analysis probes RNAi validated pro-longevity effect of nhr-6, a human homolog of tumor suppressor Nr4a1

Bashir A Akhoon,Nivedita Singh,Laxmi Rathor,Shailendra K Gupta,Rakesh Pandey,Aakanksha Pant,Shishir K Gupta,Thomas Dandekar,Sudeep Tiwari

doi:10.1038/s41598-019-51649-0

Abstract

Protein-protein interaction (PPI) studies are gaining momentum these days due to the plethora of various high-throughput experimental methods available for detecting PPIs. Proteins create complexes and networks by functioning in harmony with other proteins and here in silico network biology hold the promise to reveal new functionality of genes as it is very difficult and laborious to carry out experimental high-throughput genetic screens in living organisms. We demonstrate this approach by computationally screening C. elegans conserved homologs of already reported human tumor suppressor and aging associated genes. We select by this nhr-6, vab-3 and gst-23 as predicted longevity genes for RNAi screen. The RNAi results demonstrated the pro-longevity effect of these genes. Nuclear hormone receptor nhr-6 RNAi inhibition resulted in a C. elegans phenotype of 23.46% lifespan reduction. Moreover, we show that nhr-6 regulates oxidative stress resistance in worms and does not affect the feeding behavior of worms. These findings imply the potential of nhr-6 as a common therapeutic target for aging and cancer ailments, stressing the power of in silico PPI network analysis coupled with RNAi screens to describe gene function.

Highlights

Protein-protein interaction (PPI) studies are gaining momentum these days due to the plethora of various high-throughput experimental methods available for detecting protein-protein interactions (PPIs)
The inter-relationships between the implied proteins, rather than the individual mRNA knockout itself, determine the behavior of the various integrated processes in a biological system. Taking these considerations into account, we studied the protein-protein interactions (PPIs) of C. elegans using several computational approaches to predict genes that serve dual functions, behaving as tumor suppressor genes (TSG) and influencing the lifespan in C. elegans
Advances in the in silico network biology have made it possible to use protein-protein interaction networks for better understanding of cellular functions in both physiologic and pathologic conditions. These in silico omics methods can help us in making functional predictions based on the principle that a protein with unreported function may interact with previously characterized proteins and we can assign its function

Summary

Introduction

Protein-protein interaction (PPI) studies are gaining momentum these days due to the plethora of various high-throughput experimental methods available for detecting PPIs. To determine the PPIs associated with C. elegans TSG (tumor suppressor gene) homologs, we first identified 464 worm orthologs of 221 human TSG in 196 ortholog clusters, out of 716 human TSG present in the TSGene database (https://bioinfo.uth.edu/TSGene/) by the robust orthology detection pipeline OrthoMCL (http://orthomcl.org/orthomcl/).

Results

Conclusion