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Gregor Mendel Institute

How are proteins in the cells of a flowering plant similar to social networks on Twitter or Facebook? And how might both of those be related to the way pathogens make plants or people sick?


Shahid Mukhtar, Ph.D., and colleagues at the University of Alabama at Birmingham address these questions in a collaborative study with Youssef Belkhadir at the Gregor Mendel Institute of the Austrian Academy of Sciences. Using systems biology, they successfully identified previously unknown protein targets of plant pathogens in the flowering plant Arabidopsis thaliana by employing some of the same methods used to analyze social networks. Their theoretical framework, they say, could help analyze other interactions between species to reveal pathogen contact points.



As part of the international Fascination of Plants Day, the GMI once again teamed up with the Vienna Open Lab to offer a two hour program to school classes to introduce them to the fascinating world of plants.




To combat pathogen infection in both animals and plants, it is important to know which genes in the pathogen are important for successfully infecting their host. Traditionally, identifying such genes has been laborious and time consuming. Researchers would mutate genes thought to be involved in infection, infect these mutants into their host one at a time, and then determine whether the mutant is as infectious as the non-mutated pathogen. In work published today in PLoS Biology from the Gregor Mendel Institute for Molecular Plant Biology of the Austrian Academy of Sciences and the Center for Integrative Bioinformatics Vienna at the Max F. Perutz Laboratories , both located at the Vienna BioCenter, PhD student Simon Uhse in the group of Armin Djamei describes a method that dramatically increases the speed for identifying genes critical for infection.


Magnus Nordborg has been awarded a €2.5M ERC Advanced Grant to study the causes of epigenetic variation in the global Arabidopsis population and its evolutionary significance. This is Magnus' second ERC Advanced Grant.


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