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Statistical mechanics of cell metabolism

  • January 15th, 2020
Statistical mechanics of cell metabolism

DANIELE DE MARTINO

Date: Monday, January 27th, 2020

Hour: 12:30

Venue: Institute for Integrative Systems Biolgy (I2SYSBIO), Seminars Room

Organizer: Institute for Integrative Systems Biology (I2SYSBIO) (UV-CSIC)

Abstract: 

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

 

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