A special master’s degree program for the study of veterinarian public health is being launched by the Hebrew University in Jerusalem. It was regarded as a necessary, as raising animals and eating meat and poultry can affect human health, whether one has pets, lives or works about animals in farms or zoos or just consumes animal products. The program, to be organized jointly by the HU-Hadassah Braun School for Public Health and Community Medicine and the HU Koret School of Veterinary Medicine of the Robert H. Smith Faculty of Agriculture, Food and Environment, will begin in the coming academic year. Among the topics to be studied are food hygiene and safety, infectious diseases, toxicology and pharmacology, agricultural economy, public health services and more.
Prof. Eyal Klement, an expert in epidemiology and public health at the Koret School, explained: “While in Europe and the US, curricula that train veterinarians in public health have existed for several years, in Israel that have not been any. This has resulted in a serious shortage of veterinarians with expertise in this field. The new program will make it possible to prepare professionals for this and significantly help protect human health. Graduates will have a very good chance of being employed.”
The graduate program will take place at the Ein Kerem campus of the Braun school during its first year and during the second year at the Smith Faculty campus in Rehovot.
ALGORITHM IDENTIFIES AGING GENES
Limiting calorie consumption is one of the few proven ways to combat aging.
Although the underlying mechanism is unknown, eating much less has been shown to prolong lifespan in yeast, worms, flies, monkeys, and, in some studies, humans.
Now Keren Yizhak, a doctoral student in Prof. Eytan Ruppin’s laboratory at Tel Aviv University’s Blavatnik School of Computer Science, and colleagues at Bar-Ilan University (BIU) in Ramat Gan, have developed a computer algorithm that predicts which genes can be “turned off” to create the same anti-aging effect as calorie restriction. The findings, reported in Nature Communications, could lead to the development of new drugs to treat aging. “Most algorithms try to find drug targets that kill cells to treat cancer or bacterial infections,” said Yizhak. “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.”
Ruppin’s lab is a leader in the growing field of genome-scale metabolic modeling or GSMMs. Using mathematical equations and computers, GSMMs describe the metabolism, or life-sustaining, processes of living cells. Once built, the individual models serve as digital laboratories, allowing formerly labor-intensive tests to be conducted with the click of a mouse. Yizhak’s algorithm, which she calls a “metabolic transformation algorithm (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 process by which information from a gene is used in the synthesis of a functional gene product, which often is a protein. Genes can be “turned off” in various ways to prevent them from being expressed in the cell. In the study, Yizhak applied MTA to the genetics of aging.
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 at a BIU lab. Researchers there 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 percent 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.”
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% of the differences between the old and young information from four different studies. Next, Yizhak will study whether turning off the genes predicted by MTA prolongs the lifespan of genetically engineered mice. One day, drugs could be developed to target genes in humans, potentially allowing us to live longer.
MTA could also be applied to finding drug targets for disorders where metabolism plays a role, including obesity, diabetes, neurodegenerative disorders and cancer.