Evolution of transcriptional regulatory networks in prokaryotes.

It is becoming increasingly clear that molecular machineries of cellular life forms such as proteins, nucleic acids and metabolites, which have largely been studied in isolation or as part of individual pathways, are in fact tied together to form a large, interlinked, complex system in the cell, very much like a network. In order to gain a deeper understanding of how living organisms function, it is of fundamental importance to discern the organization of these biological networks and understand the evolutionary forces that shape them.

Our research focuses on investigating the properties of biological networks and developing methods to uncover general organizational principles that are otherwise not obvious.

Further, we integrate several kinds of experimental information such as sequence, structure, chromosomal location, phenotypic data, and gene expression data with molecular interaction networks to gain a better understanding of specific biological systems.

In particular, we are interested in understanding the evolution of the following fundamental regulatory processes at a systems level (i) cell size regulation, (ii) cell morphology and (iii) cell-to-cell communication. We are currently approaching these problems by integrating gene knockout data in bacteria, yeast, worm and fly with other large scale datasets such as genome sequence data, molecular interaction networks and gene expression data to discover novel members and identify evolutionary trends that govern these systems.

Structural organization of transcriptional regulatory networks. (a) The ‘basic unit’ comprises the transcription factor, its target gene with DNA recognition site and the regulatory interaction between them. (b) Units are often organised into network ‘motifs’, which comprise specific patterns of inter-regulation that are over-represented in networks. (c) Network motifs can be interconnected to form semi-independent ‘modules’, many of which have been identified by integrating regulatory interaction data with gene expression data, and imposing evolutionary conservation. (d) The entire assembly of regulatory interactions constitutes the ‘transcriptional regulatory network’, which provides the blueprint for regulation of gene expression in an organism.