Aging is one of the more mysterious processes in biology. We don’t know, scientifically speaking, what exactly it is. We do know for sure when it ends. But what precipitates that endpoint is inscrutable, determined by factors that can often seem statistically random.
Researchers in the lab of Walter Fontana, an HMS professor of systems biology, have found patterns in this randomness, ones that provide clues to the biological basis of aging.
'Lifespan Machine' probes cause of aging, a video
The research team, led by Novartis Fellow Nicholas Stroustrup, found a surprising statistical regularity in how a variety of genetic and environmental factors affect the life span of the Caenorhabditis elegans worm. Their findings suggest that aging does not have a single discrete molecular cause but is rather a systemic process involving many components within a complex biological network. Perturb any node in the system, and you affect the whole thing.
The study, in the January 27, 2016, issue of Nature, offers an alternative to research that seeks to identify a specific master aging mechanism, such as protein homeostasis or DNA damage.
“There are many important molecular changes that occur with age, but it might not make sense to call all of them ‘causes of aging,’ per se,” says Stroustrup, the paper’s first author.
In order to study life span dynamics at the population level, Stroustrup constructed what his team calls a lifespan machine, a device comprising 50 off-the-shelf flatbed scanners. Each scanner was retooled to record 16 petri dishes every hour, totaling 800 dishes and 30,000 worms. The scanners capture images at 3,200 dots per inch, a resolution high enough to detect movements of eight micrometers, or about 12 percent of the width of an average C. elegans.
Stroustrup exposed the worms to interventions as diverse as temperature change, oxidative stress, change in diet, and genetic manipulation. The lifespan machine recorded how long it took the worms to die under each condition. Stroustrup then aggregated the data, generated life span distribution curves for each intervention and compared results.
The life span distributions provided considerably more information than just changes in average life span. The research team measured variations arising in ostensibly identical individuals, looking at how many worms died young versus how many made it to old age under each condition. This comprehensive view was important for capturing the dynamics and randomness in the aging process.
The researchers found an unexpected uniformity among the distribution curves. When all the bell curves were expanded or contracted along the X-axes (which in this study represented time), they became statistically indistinguishable.
The interventions seemed to affect life span in the same way across all individuals in the same population; no matter which genetic process or environmental factor the researchers targeted, all molecular causes of death seemed to be affected at once and to the same extent.
“Life span is a whole-organism property,” says Fontana, “and it is profoundly difficult to study it molecularly in real time. But by discovering this kind of statistical regularity about the endpoint of aging, we have learned something about the aging process that determines that endpoint.”
Most important, says Fontana, this regularity suggests a profound interdependence in the physiology of an organism so that changes in one physiological aspect affect all others to determine life span.