Want A Long Lifespan? You Need Stable Gene Networks

Credit: Andrei Seluanov and Vera Gorbunova, University of Rochester

Organisms like the naked mole rat and the giant red sea urchin exhibit a feature called negligible senescence – which essentially means they show very little signs of aging at all. How do they accomplish this? New research suggests one reason is that these organisms all possess stable gene networks.

What does a ‘stable gene network’ mean?

These organisms show consistent gene expression which manages to avoid the dysregulation afflicting other aging organisms and maintains a similar organisation. Using mathematical modeling, researchers established that in order to preserve this stability, these organisms would need a better gene network repair system and low connectivity. They also worked out the particular parameters involved which were: effective gene network connectivity, effective genome size, proteome turnover, and DNA repair rate. In simple terms – their genomes were more efficient, proteins were processed more smoothly and DNA was repaired more effectively. 

“If the repair rates are sufficiently high or the connectivity of the gene network is sufficiently low, then the regulatory network is very stable and mortality is time-independent in a manner similar to that observed in negligibly senescent animals. Should the repair systems display inadequate efficiency, a dynamic instability emerges, with exponential accumulation of genome-regulation errors, functional declines and a rapid aging process accompanied by an exponential increase in mortality.”

What was really interesting was that these innate networks were more important than genotoxic stress levels the organisms were exposed to – meaning that these genetically programmed features had a far greater effect on lifespan than oxidative stress exposure for example. As these models are confirmed and tested on suitable organisms, target genes could emerge for future treatments like gene therapy, which might boost lifespan and health. 

Read more about it in Maria Konovalenko’s article at IEET

And Genetic Engineering News