New algorithm identifies 'ageing genes' that can be turned off

Scientists have developed a new computer algorithm that predicts which genes can be "turned off" to create an anti-aging effect.
The anti-ageing effect would be the same as experienced in calorie restriction, researchers said. Restricting calorie consumption is one of the few proven ways to combat ageing.
"Most algorithms try to find drug targets that kill cells to treat cancer or bacterial infections," said Keren Yizhak, a doctoral student in Professor Eytan Ruppin's laboratory at Tel Aviv University.
"Our algorithm is the first in our field to look for drug targets not to kill cells, but to transform them from a diseased state into a healthy one," said Yizhak.

Yizhak's algorithm, called "metabolic transformation algorithm," or MTA, can take information about any two metabolic states and predict the environmental or genetic changes required to go from one state to the other.
"Gene expression" is the measurement of the expression level of individual genes in a cell, and genes can be "turned off" in various ways to prevent them from being expressed in the cell, researchers said.

Yizhak applied MTA to the genetics of ageing. After using her custom-designed MTA to confirm previous laboratory findings, she used it to predict genes that can be turned off to make the gene expression of old yeast look like that of young yeast.

Yeast is the most widely used genetic model because much of its DNA is preserved in humans.
Some of the genes that the MTA identified were already known to extend the lifespan of yeast when turned off. Of the other genes she found, Yizhak sent seven to be tested.
Researchers found that turning off two of the genes, GRE3 and ADH2, in actual, non-digital yeast significantly extends the yeast's lifespan.
"You would expect about three per cent of yeast's genes to be lifespan-extending," said Yizhak.
"So achieving a 10-fold increase over this expected frequency, as we did, is very encouraging," Yizhak said.

Since MTA provides a systemic view of cell metabolism, it can also shed light on how the genes it identifies contribute to changes in genetic expression.
In the case of GRE3 and ADH2, MTA showed that turning off the genes increased oxidative stress levels in yeast, thus possibly inducing a mild stress similar to that produced by calorie restriction.
As a final test, Yizhak applied MTA to human metabolic information. MTA was able to identify a set of genes that can transform 40-to-70 per cent of the differences between the old and young information from four different studies.
The study was published in the journal Nature Communications.