DANIELE DE MARTINO

Date: Monday, January 27, 2020

Time: 12:30

Place: Institute of Integrative Systems Biology (I2SYSBIO) Seminar Room.

Organized by: Institute of Integrative Systems Biology I2SysBio (UV-CSIC).

Summary:

How much is the metabolic state of bacteria optimal for growth?
Optimality is a standard modeling assumption
(FBA or flux balance analysis, based on linear programming & exponential
growth takeover) but this contrasts with observed single cell growth rate
variability. In this seminar I will present a statistical mechanics approach to single cell metabolism based on maximum entropy modeling. The model, applied to the bacterium E coli, provides a better match to measured fluxes with respect to FBA and it makes a wide range of predictions: on flux variability, regulation, and correlations; on the relative importance of stoichiometry vs. optimization; on scaling relations for growth rate distributions, the latter being verified by single cell experiments. Why not optimal? Statistical mechanics approaches hint at minimum information costs to achieve a certain optimization and show a tradeoff between
optimization and adaptation  in the form of a fluctuation theorem.

Reference: De Martino, D. et al. (2018) Statistical mechanics for metabolic networks during steady state growth. Nature communications 9: 1-9.

Poster