Doctoral student Keren Yizhak and her team at Tel Aviv University in collaboration with researchers from Bari-Ilan University have developed a computer algorithm that identifies which genes can be transformed, or ‘turned off’ to stop the aging process. This is the first technique able to achieve such results aside from restricting calorie consumption.
Yizhak’s ‘metabolic transformation algorithm’ uses genome-scale metabolic modelling (GSMMs) to understand the genetics of aging. Her team has largely conducted experiments on yeast, the DNA of which is very similar to human DNA, to understand how changes in gene expression extend or shorten the lifespan of living cells. MTA so far has successfully predicted a number of genes that, when ‘switched off’, have extended the lifespan of the yeast.
Yizhak is looking to apply MTA predictions to genetically engineered mice in her next series of experiments. She has put forward the idea that MTA could also be applied to “finding drug targets for conditions and diseases where metabolism plays a significant role, including obesity, diabetes, neurodegenerative disorders, and some types of cancer” (Leichman 2014).
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