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Action and power efficiency in self-organization: The case for growth efficiency as a cellular objective in escherichia coli

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publicationEvolution, Development and Complexity - Multiscale Evolutionary Models of Complex Adaptive Systems
EditorsClaudio L. Flores Martinez, Georgi Yordanov Georgiev, John M. Smart, Michael E. Price
PublisherSpringer
Pages229-244
Number of pages16
ISBN (Print)9783030000745
DOIs
Publication statusPublished - 2019
Publication typeA4 Article in a conference publication
EventConference on Complex Systems - Cancun, Mexico
Duration: 17 Sep 201722 Sep 2017

Publication series

NameSpringer Proceedings in Complexity
ISSN (Print)2213-8684
ISSN (Electronic)2213-8692

Conference

ConferenceConference on Complex Systems
CountryMexico
CityCancun
Period17/09/1722/09/17

Abstract

Complex systems of different nature self-organize using common mechanisms. One of those is increase of their efficiency. The level of organization of complex systems of different nature can be measured as increased efficiency of the product of time and energy for an event, which is the amount of physical action consumed by it. Here we apply a method developed in physics to study the efficiency of biological systems. The identification of cellular objectives is one of the central topics in the research of microbial metabolic networks. In particular, the information about a cellular objective is needed in flux balance analysis which is a commonly used constrained-based metabolic network analysis method for the prediction of cellular phenotypes. The cellular objective may vary depending on the organism and its growth conditions. It is probable that nutritionally scarce conditions are very common in the nature, and, in order to survive in those conditions, cells exhibit various highly efficient nutrient-processing systems like enzymes. In this study, we explore the efficiency of a metabolic network in transformation of substrates to new biomass, and we introduce a new objective function simulating growth efficiency. We are searching for general principles of self-organization across systems of different nature. The objective of increasing efficiency of physical action has been identified previously as driving systems toward higher levels of self-organization. The flow agents in those networks are driven toward their natural state of motion, which is governed by the principle of least action in physics. We connect this to a power efficiency principle. Systems structure themselves in a way to decrease the average amount of action or power per one event in the system. In this particular example, action efficiency is examined in the case of growth efficiency of E. coli. We derive the expression for growth efficiency as a special case of action (power) efficiency to justify it through first principles in physics. Growth efficiency as a cellular objective of E. coli coincides with previous research on complex systems and is justified by first principles in physics. It is expected and confirmed outcome of this work. We examined the properties of growth efficiency using a metabolic model for Escherichia coli. We found that the maximal growth efficiency is obtained at a finite nutrient uptake rate. The rate is substrate dependent and it typically does not exceed 20 mmol/h/gDW. We further examined whether the maximal growth efficiency could serve as a cellular objective function in metabolic network analysis and found that cellular growth in batch cultivation can be predicted reasonably well under this assumption. The fit to experimental data was found slightly better than with the commonly used objective function of maximal growth rate. Based on our results, we suggest that the maximal growth efficiency can be considered a plausible optimization criterion in metabolic modeling for E. coli. In the future, it would be interesting to study growth efficiency as an objective also in other cellular systems and under different cultivation conditions.

Keywords

  • Action efficiency, Constraint-based modeling, Metabolism, Microorganism, Principle of least action

Publication forum classification

Field of science, Statistics Finland