Molecular-level tradeoffs and metabolic adaptation to simultaneous stressors

doi:10.1016/j.copbio.2010.05.011

Current Opinion in Biotechnology

Volume 21, Issue 5, October 2010, Pages 670-676

https://doi.org/10.1016/j.copbio.2010.05.011 Get rights and content

Life is a dynamic process driven by the complex interplay between physical constraints and selection pressures, ranging from nutrient limitation to inhibitory substances to predators. These stressors are not mutually exclusive; microbes have faced concurrent challenges for eons. Genome-enabled systems biology approaches are adapting economic and ecological concepts like tradeoff curves and strategic resource allocation theory to analyze metabolic adaptations to simultaneous stressors. These methodologies can accurately describe and predict metabolic adaptations to concurrent stresses by considering the tradeoff between investment of limiting resources into enzymatic machinery and the resulting cellular function. The approaches represent promising links between computational biology and well-established economic and ecological methodologies for analyzing the interplay between physical constraints and microbial fitness.

Section snippets

Mathematical modeling of microbial responses to environment

Microbes are complex systems; mathematical expressions have been used to predict and interpret these dynamic systems for more than a century (e.g. [1, 2, 3]). Microbial growth expressions were soon combined into systems of differential equations to consider a multitude of stressors including combinations of limiting substrates, competitors, predators, and the presence of inhibitors [4, 5]. Unfortunately, kinetic models are parameter heavy, in terms of both number and sensitivity. Literature

Stoichiometric analysis of single stress adaptations

The functional properties of metabolic systems are the product of evolutionary processes and are competitive given the organism's life history. Therefore, assumptions about competitive cellular behavior are used to select solutions to stoichiometry-based models. A widely utilized criterion presumes that microorganisms maximize biomass yield (microbe production from a fixed quantity of substrate). This criterion is convenient, simple, and successfully describes microbial behavior under certain

Economic considerations and metabolic strategies

Resource availability limits growth in most environments and is an important component of animal immune systems, commonly referred to as nutritional immunity [22••, 23]. This has driven microbial evolution toward strategies that allocate limiting resources to different metabolic isozymes and alternative pathways in a manner that favors fitness [24^•]. Standard economics approaches such as resource allocation theory and tradeoff analysis can be used to quantitatively compare the huge number of

Resource allocations and simultaneous stresses

Life is inherently competitive and stressors are not mutually exclusive. Microbes cope simultaneously with an assortment of constraints [37]. Economic and ecological theory provides a framework for predicting and interpreting microbial adaptations to multiple stresses [28, 38•, 39]. When subjected to multiple pressures, cells must allocate finite resources to different subsystems in a proportion that improves fitness; the systems biology challenge is to determine how these allocations respond

Stress adaptations and opportunity costs

Microbial responses to a variety of stressors can be quantified using the economic concept of opportunity costs. As an example of opportunity costs, E. coli shifts from the phosphotransferase system (K_m ∼ 5 μm) to a higher affinity ABC transporter (K_m < 1 μm) coupled with glucose kinase under glucose-scarce conditions [42]. The high affinity system requires more resources to assemble and operate (Figure 3); however, these costs are offset by improved glucose uptake at low external concentrations. The

Biodiversity, network robustness, and the Darwinian demon

All life faces physical, physiological, energetic, and temporal constraints. Resources allocated to one capacity cannot be allocated elsewhere. The resulting tradeoffs have been used to explain biodiversity on both an evolutionary and a dynamic basis [43, 44•]. Ecologists often invoke a thought experiment to test the null hypothesis of free specialization. The exercise proposes the existence of a ‘superspecies’, termed a Darwinian demon, unconstrained by tradeoffs: living long, reproducing

Conclusions

Decades of economic and ecological studies have highlighted the importance of strategic resource allocation and the associated constraints on competitive functionality. These concepts are relevant at all biological scales, from individual microbes to ecosystems, and appear to play key roles in the composition, organization, and functioning of molecular-level metabolic systems. The large body of theoretical and applied work in these fields provides a firm foundation for systems approaches to

References and recommended reading

Papers of particular interest, published within the period of review, have been highlighted as:

• of special interest
•• of outstanding interest

Acknowledgement

This work was supported by financial support from National Institutes of Health (EB006532 and P20 RR024237).

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View full text

Molecular-level tradeoffs and metabolic adaptation to simultaneous stressors

Section snippets

Mathematical modeling of microbial responses to environment

Stoichiometric analysis of single stress adaptations

Economic considerations and metabolic strategies

Resource allocations and simultaneous stresses

Stress adaptations and opportunity costs

Biodiversity, network robustness, and the Darwinian demon

Conclusions

References and recommended reading

Acknowledgement

Appl Microbiol Biotechnol

BioSystems

Microbiol Rev

Science

Ann NY Acad Sci

Analysis of double-substrate limited growth

Biotechnol Bioeng

Optima and limiting factors

Ann Bot

The growth of bacterial cultures

Annu Rev Microbiol

Dynamics of microbial propagation: models considering inhibitors and variable cell composition

Biotechnol Bioeng

Growth kinetics of suspended microbial cells: from single-substrate-controlled growth to mixed-substrate kinetics

Microbiol Mol Biol Rev

Prediction of enzyme kinetic parameters based on statistical learning

Genome Inform

Inferring dynamic properties of biochemical reaction networks from structural knowledge

Genome Inform

Something from nothing—bridging the gap between constraint-based and kinetic modeling

FEBS J

Towards a genome-scale kinetic model of cellular metabolism

BMC Syst Biol

Ensemble modeling of metabolic networks

Biophys J

Metabolic flux distributions: genetic information, computational predictions, and experimental validation

Appl Microbiol Biotechnol

Thirteen years of building constraint-based in silico models of Escherichia coli

J Bacteriol

Metabolic pathway analysis: basic concepts and scientific applications in the post-genomic era

Biotechnol Prog

Dynamic flux balance analysis of diauxic growth in Escherichia coli

Biophys J

Application of dynamic flux balance analysis to an industrial Escherichia coli fermentation

Metab Eng

Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type Escherichia coli W3110

Appl Environ Microbiol

Systematic evaluation of objective functions for predicting intracellular fluxes in Escherichia coli

Mol Syst Biol

Is maximization of molar yield in metabolic networks favoured by evolution?

J Theor Biol

Ecological Stoichiometry: The Biology of Elements from Molecules to the Biosphere

A cybernetic view of microbial growth: modeling of cells as optimal strategists

Biotechnol Bioeng

Metabolic systems cost-benefit analysis for interpreting network structure and regulation

Bioinformatics