Bandeau MISTIC

Integration of multi-omic data for analyzing the dynamics of microbial communities in plant health

PhD research project as part of the MISTIC project, supervised by INRAE.

  • Title: "Integration of multi-omic data for analyzing the dynamics of microbial communities in plant health" ; Inria.

Project summary:

Microorganisms play a crucial role in plant health: for example, they contribute to nutrient absorption and protect plants against infections by various pathogens. However, we still have a limited understanding of how these microbial communities assemble and interact. To better understand their dynamics, we have access to massive datasets, known as omic data, containing various information, such as the genomes of different microorganisms, their physiology (what they consume and produce), and the activation of their metabolic functions. To integrate these data at the community level, we are exploring the use of dynamic models. Currently, two types of models have been developed: population models, which are effective in representing interactions between microorganisms but ignore intra-cellular information, and genome-based models, which are much more comprehensive in terms of intra-cellular regulations but require significant computational resources and introduce numerous biases. The objective of this thesis is to create an intermediate modeling paradigm, allowing for a compact representation of community dynamics while remaining connected to metabolic functions and the entire set of omic data. This will involve overcoming modeling, computational, and inference challenges for dynamic models based on heterogeneous, high-dimensional data.

See also