Reporter algorithm integrates omics data with metabolic network and thereby identifies metabolic regulatory hotspots. M1 - metabolite; G1-5 - upregulated genes; purple/ green/blue circles & squares - transcription factors and corresponding binding motifs.
The Patil group uses a combination of modelling, bioinformatics, and experimental approaches to study metabolic networks and how they are controlled.
Previous and current research
Metabolism is a fundamental cellular process that provides molecular building blocks and energy for growth and maintenance. In order to optimise the use of resources and to maximise fitness, cells respond to environmental or genetic perturbations through a highly coordinated regulation of metabolism. The research in our group focuses on understanding the basic principles of operation and regulation of metabolic networks. We are particularly interested in developing models connecting genotype to the metabolic phenotype (metabolic fluxes and metabolite concentrations) in cell factories and in microbial communities.
With a foundation in genome-scale metabolic modelling, optimisation methods and statistics, we develop novel computational algorithms that are driven by mechanistic insights. For example, we have previously shown that the transcriptional changes in metabolic networks are organised around key metabolites that are crucial for responding to the underlying perturbations (see figure). We complement our computational analyses with experimental activities carried out within our group (microbial physiology and genetics) and in close collaboration with other groups at EMBL and elsewhere (high-throughput phenotyping, metabolomics, proteomics and more). This combination of computational and experimental approaches has previously enabled us to improve yeast cell factories producing vanillin – a popular flavouring agent. Currently we are developing novel tools, concepts and applications in the following research areas:
i) Metabolic interactions in microbial communities: Microbial communities are ubiquitous in nature and have a large impact on ecological processes and human health. A major focus of our current activities is the development of computational and experimental tools for mapping competitive and cooperative metabolic interactions in natural as well as in synthetic microbial communities. With the help of these tools, we aim at uncovering the role of inter-species interactions in shaping the diversity and stability of complex microbial communities.
ii) Computer-aided design of cell factories: Cell factories, such as yeast and CHO cells, are at the heart of biotechnological processes for sustainable production of various chemicals and pharmaceuticals. We are using modelling and bioinformatics tools to identify genetic redesign strategies towards improving the productivity of cell factories. These strategies guide our experimental implementation, which in turn help us to further improve the design algorithms in an iterative fashion.
Future Projects and Goals
We are keenly interested in expanding the scope of our computational and experimental models to gain mechanistic insight into following biological processes: i) xenobiotic metabolism in microbial communities; ii) crosstalk between metabolism and gene regulatory networks; and iii) metabolic changes during developmental processes. To this end, we are actively seeking collaborative projects within EMBL and elsewhere.