Professor

Department of Chemical Engineering & Laboratory of Network Biology

Technion, Israel Institute of Technology

 

 

The capacity of cells and organisms to respond to challenging conditions is limited by a finite repertoire of repeatable adaptive responses. Beyond this capacity, novel and unforeseen challenges may elicit exploratory dynamics, improvisational in nature, potentially providing adaptation to a much broader array of conditions. Exploratory adaptation, its dynamics and convergence properties are not well understood. I will describe experiments demonstrating adaptation to unforeseen challenge, and showing they involve a stochastic high-dimensional exploration in gene-expression space. A random network model of gene regulation shows the feasibility of such adaptation based on purely stochastic dynamics and stress sensing. Convergence in high-dimensional gene expression space is non-universal and depends on network properties: Successfully adapting network ensembles are heterogeneous and have outgoing hubs – “master regulators”, a known feature of gene networks. These findings establish a biologically plausible mechanism of adaptation by exploratory dynamics, and suggest a deep connection between cellular networks and learning theory.