Optimal management of nutrient reserves in microorganisms under time-varying environmental conditions

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Intracellular reserves are a conspicuous feature of many bacteria; such internal stores are often present in the form of inclusions in which polymeric storage compounds are accumulated. Such reserves tend to increase in times of plenty and be used up in times of scarcity. Mathematical models that describe the dynamical nature of reserve build-up and use are known as “cell quota,” “dynamic energy/nutrient budget,” or “variable-internal-stores” models. Here we present a stoichiometrically consistent macro-chemical model that accounts for variable stores as well as adaptive allocation of building blocks to various types of catalytic machinery. The model posits feedback loops linking expression of assimilatory machinery to reserve density. The precise form of the “regulatory law” at the heart of such a loop expresses how the cell manages internal stores. We demonstrate how this “regulatory law” can be recovered from experimental data using several empirical data sets. We find that stores should be expected to be negligibly small in stable growth-sustaining environments, but prominent in environments characterised by marked fluctuations on time scales commensurate with the inherent dynamic time scale of the organismal system.OAN was funded through EU Research Framework programme 7 Marie Curie Actions, grant 316630 Centre for Analytical Science – Innovative Doctoral Programme (CAS-IDP)

Mathematical models of microbial growth and metabolism: A whole-organism perspective

This is the author accepted manuscript. The final version is available from Science Reviews 2000 via the DOI in this record.We review the principles underpinning the development of mathematical models of the metabolic activities of micro-organisms. Such models are important to understand and chart the substantial contributions made by micro-organisms to geochemical cycles, and also to optimise the performance of bioreactors that exploit the biochemical capabilities of these organisms. We advocate an approach based on the principle of dynamic allocation. We survey the biological background that motivates this approach, including nutrient assimilation, the regulation of gene expression, and the principles of microbial growth. In addition, we discuss the classic models of microbial growth as well as contemporary approaches. The dynamic allocation theory generalises these classic models in a natural manner and is readily amenable to the additional information provided by transcriptomics and proteomics approaches. Finally, we touch upon these organising principles in the context of the transition from the free-living unicellular mode of life to multicellularity.Olga Nev was funded through EU Research Framework programme 7 Marie Curie Actions, grant 316630 Centre for Analytical Science – Innovative Doctoral Programme (CAS-IDP)

Variable-Internal-Stores models of microbial growth and metabolism with dynamic allocation of cellular resources.

This is the final version of the article. Available from Springer via the DOI in this record.An erratum to this article is available at http://dx.doi.org/10.1007/s00285-016-1044-y and in ORE at http://hdl.handle.net/10871/31444Variable-Internal-Stores models of microbial metabolism and growth have proven to be invaluable in accounting for changes in cellular composition as microbial cells adapt to varying conditions of nutrient availability. Here, such a model is extended with explicit allocation of molecular building blocks among various types of catalytic machinery. Such an extension allows a reconstruction of the regulatory rules employed by the cell as it adapts its physiology to changing environmental conditions. Moreover, the extension proposed here creates a link between classic models of microbial growth and analyses based on detailed transcriptomics and proteomics data sets. We ascertain the compatibility between the extended Variable-Internal-Stores model and the classic models, demonstrate its behaviour by means of simulations, and provide a detailed treatment of the uniqueness and the stability of its equilibrium point as a function of the availabilities of the various nutrients.OAN was funded through EU Research Framework programme 7 Marie Curie Actions, grant 316630 Centre for Analytical Science – Innovative Doctoral Programme (CAS-IDP)

Erratum to: Variable-Internal-Stores models of microbial growth and metabolism with dynamic allocation of cellular resources

This is the final version of the article. Available from Springer via the DOI in this record. The online version of the original article can be found under doi: 10.1007/s00285-016-1030-4In the original publication of the article the symbol Phi ‘φ’ should be changed to symbol Psi ‘φ’in Table 1 under the section “Unscaled stoichiometric coefficients”,line 2, column 1.The original article has been updated to reflect the above change

Predicting community dynamics of antibiotic-sensitive and -resistant species in fluctuating environments (article)

This is the author accepted manuscript. The final version is available from the Royal Society via the DOI in this recordThe dataset associated with this article is available in ORE: https://doi.org/10.24378/exe.2323Microbes occupy almost every niche within and on their human hosts. Whether colonizing the gut, mouth or bloodstream, microorganisms face temporal fluctuations in resources and stressors within their niche but we still know little of how environmental fluctuations mediate certain microbial phenotypes, notably antimicrobial-resistant ones. For instance, do rapid or slow fluctuations in nutrient and antimicrobial concentrations select for, or against, resistance? We tackle this question using an ecological approach by studying the dynamics of a synthetic and pathogenic microbial community containing two species, one sensitive and the other resistant to an antibiotic drug where the community is exposed to different rates of environmental fluctuation. We provide mathematical models, supported by experimental data, to demonstrate that simple community outcomes, such as competitive exclusion, can shift to coexistence and ecosystem bistability as fluctuation rates vary. Theory gives mechanistic insight into how these dynamical regimes are related. Importantly, our approach highlights a fundamental difference between resistance in single-species populations, the context in which it is usually assayed, and that in communities. While fast environmental changes are known to select against resistance in single-species populations, here we show that they can promote the resistant species in mixed-species communities. Our theoretical observations are verified empirically using a two-species Candida community.European Research Council (ERC)Engineering and Physical Sciences Research Council (EPSRC

Anticipatory Stress Responses and Immune Evasion in Fungal Pathogens

This is the final version. Available on open access from Cell Press via the DOI in this recordIn certain niches, microbes encounter environmental challenges that are temporally linked. In such cases, microbial fitness is enhanced by the evolution of anticipatory responses where the initial challenge simultaneously activates pre-emptive protection against the second impending challenge. The accumulation of anticipatory responses in domesticated yeasts, which have been termed 'adaptive prediction', has led to the emergence of 'core stress responses' that provide stress cross-protection. Protective anticipatory responses also seem to be common in fungal pathogens of humans. These responses reflect the selective pressures that these fungi have faced relatively recently in their evolutionary history. Consequently, some pathogens have evolved 'core environmental responses' which exploit host signals to trigger immune evasion strategies that protect them against imminent immune attack.Medical Research Council (MRC)University of AberdeenUniversity of Exete