STRUCTURE, DYNAMICS AND EVOLUTION OF THE GENETIC NETWORKS DRIVING YEAST ADAPTATION TO THE ENVIRONMENT – STRUDYEV
Evolution of genome response to environmental stress in yeasts
High-throughtput approaches and in silico modelling to decipher the nevolution of stress responses in yeasts
Systems biology and gene expression regulatory networks
Living cells are complex systems made of thousands of genes whose products are involved in a dynamic network of functional interactions. The amazing advances in molecular genomics allow us to deal with this complexity. It is now possible to measure the expression of the whole genome in a single experimen and thus to address the way these genes coordonate their activity to face varying environments. These information are too much for human brain. We need mathematical and informatical modelling to use it. This new way of studying living organisms is called systems biology. Its implications in terms of fundamental knowledge or biomedial applications are huge. The present project aims at combining experimental approaches and in silico modelling to understand how a simple cell, baker's yeast, adapt its genome expression to the presence of toxic compounds in its environment. We will then enlarge our analyses to 8 other yeast species, having different gene contents and ecological niches, in order to understand how evolved the stress adaptation systems. The potential applications of this work are in environmental toxicology and fight against pathogenic yeasts.
This project has three parts.
The first one consists in genome-wide analyses of stress response in different yeast species. We will use DNA microarrays to measure the expression of all genes in response of stress and chromatine immunoprecipitaiton to determine which regulatory proteins are involved in the regulaiton of this response.
The second one will use fluorescent cell imaging to measure the dynamic of stress response in individual cells.
The third one consists in developping in silico methods to integrate all these experimental data in a model of stress response dynamics and evolution.
Up to know we described the stress repsonse of 8 yeast species and we developped an in silico approahc for the comparative analyses of these responses.
We get data on the regulatory network associated to about 20 regulatory factors involved in stress response. hence, we focused on two fo these regulators (Yap5 and Yap7) which down-regulate genes involved in the virulence of the human pathogen C. glabrata. Interestingly enough, The two factors up-regulate the expression of the same genes in the non-pathogenic yeast S. cerevisiae (baker yeast).
We are analysing the basis of the divergence in the properties of Yap5 and Yap7 along the phylogenetic tree of yeasts. More generally, we are using our transcriptome data of 8 yeast species to reconstruct the evolution of stress response over 500 million years of evolution.
Goudot C, Etchebest C, Devaux F, Lelandais G. (2011) Condition specific transcriptional modules provides new insights in the evolution of yeast AP-1 proteins. Plos One 6(6):e20924. This scientific article presents the methology developed to compare stress responses in different organisms.
Lelandais G, Goudot C, Devaux F. (2011) The evolution of gene expression regulatory networks in yeast. CR Biol. 334(8-9):655-61. This review exposes the goals and methods of the genome-wide analyses of gene network evolution.
The global analysis of the genetic networks which control the cellular processes is a rapidly growing field. The project detailed below aims at using the adaptation of genomic expression to deleterious environmental changes in yeasts as a model to describe and understand the structure, the dynamic and the evolution of the regulatory networks. Our project can be summarized in three major tasks: the acquisition of accurate transcriptome expression data at different times and in different environmental conditions; the use of recent methods for the in silico modeling of the structure and the dynamic of genetic networks, and, finally, the experimental analysis of several yeast species, spanning an evolutionary range larger than that of the phylum of Chordates, combined with comparative functional genomics approaches to get an evolutionary perspective of gene networks. The main strengths of the project are: 1- a tight collaboration between the experimental and the in silico parts, 2- the use of cutting-edge technologies for the analysis of gene expression dynamics in several related species, 3- our experience in the field, attested by more than ten publications dealing with yeast genetics networks during the last five years and 4- in 2010 our team will join FRE3214 "microorganims genomics" (CNRS/UPMC), which aims at putting together people and skills from different disciplines and which will be a stimulating environment for our project to grow. We expect from this work better knowledge on the functioning, the evolution and the biodiversity of gene networks and accurate and efficient methodologies for the modeling and the analysis of these networks in microorganisms.
Project coordination
Frederic DEVAUX (UNIVERSITE PARIS VI [PIERRE ET MARIE CURIE]) – devaux@biologie.ens.fr
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
Partner
FRE3214 UNIVERSITE PARIS VI [PIERRE ET MARIE CURIE]
Help of the ANR 327,550 euros
Beginning and duration of the scientific project:
- 36 Months
