Publications by year
2021
Pradhan A, Ma Q, de Assis LJ, Leaves I, Larcombe DE, Rodriguez Rondon AV, Nev OA, Brown AJP (2021). Anticipatory Stress Responses and Immune Evasion in Fungal Pathogens.
Trends in Microbiology,
29(5), 416-427.
Abstract:
Anticipatory Stress Responses and Immune Evasion in Fungal Pathogens
In 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.
Abstract.
Nev O, Richard L, Jepson A, Butt L, Beardmore R, Gudelj I (2021). Data for the manuscript Predicting microbial growth dynamics in response to nutrient availability.
Abstract:
Data for the manuscript Predicting microbial growth dynamics in response to nutrient availability
Data for the manuscript Predicting microbial growth dynamics in response to nutrient availability
Abstract.
Nev OA, Lindsay RJ, Jepson A, Butt L, Beardmore RE, Gudelj I (2021). Predicting microbial growth dynamics in response to nutrient availability.
PLoS Comput Biol,
17(3).
Abstract:
Predicting microbial growth dynamics in response to nutrient availability.
Developing mathematical models to accurately predict microbial growth dynamics remains a key challenge in ecology, evolution, biotechnology, and public health. To reproduce and grow, microbes need to take up essential nutrients from the environment, and mathematical models classically assume that the nutrient uptake rate is a saturating function of the nutrient concentration. In nature, microbes experience different levels of nutrient availability at all environmental scales, yet parameters shaping the nutrient uptake function are commonly estimated for a single initial nutrient concentration. This hampers the models from accurately capturing microbial dynamics when the environmental conditions change. To address this problem, we conduct growth experiments for a range of micro-organisms, including human fungal pathogens, baker's yeast, and common coliform bacteria, and uncover the following patterns. We observed that the maximal nutrient uptake rate and biomass yield were both decreasing functions of initial nutrient concentration. While a functional form for the relationship between biomass yield and initial nutrient concentration has been previously derived from first metabolic principles, here we also derive the form of the relationship between maximal nutrient uptake rate and initial nutrient concentration. Incorporating these two functions into a model of microbial growth allows for variable growth parameters and enables us to substantially improve predictions for microbial dynamics in a range of initial nutrient concentrations, compared to keeping growth parameters fixed.
Abstract.
Author URL.
2020
Nev O, Jepson A, Beardmore R, Gudelj I (2020). Predicting community dynamics of antibiotic sensitive and resistant species in fluctuating environments (dataset). Journal of the Royal Society Interface
Nev OA, Jepson A, Beardmore RE, Gudelj I (2020). Predicting community dynamics of antibiotic-sensitive and -resistant species in fluctuating environments.
J R Soc Interface,
17(166).
Abstract:
Predicting community dynamics of antibiotic-sensitive and -resistant species in fluctuating environments.
Microbes 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.
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Author URL.
2018
Nev OA, van den Berg HA (2018). Holling Type I versus Holling Type II functional responses in Gram-negative bacteria. Transactions of Mathematics and its Applications, 2, 1-19.
Nev OA, van den Berg HA (2018). Microbial metabolism and growth under conditions of starvation modelled as the sliding mode of a differential inclusion.
Dynamical Systems,
33(1), 93-112.
Abstract:
Microbial metabolism and growth under conditions of starvation modelled as the sliding mode of a differential inclusion
We consider a model of bacterial growth with variable internal stores, extended with adaptive resource allocation and investigate the behaviour of this model under conditions of starvation, i.e. severe nutrient shortage, treating the behaviour under the starvation regime in terms of a differential inclusion, and derive Filippov solutions. This Filippov sliding mode representation appears to be simple but sound qualitative description of metabolic ‘shut down’ in response to starvation. We discuss a natural connection between biologically motivated modelling approaches to metabolic ‘shut down’ and numerical regularisation techniques to approximate Filippov solutions.
Abstract.
2017
Nev OA, van den Berg HA (2017). Erratum to: Variable-Internal-Stores models of microbial growth and metabolism with dynamic allocation of cellular resources (Journal of Mathematical Biology, (2017), 74, 1-2, (409-445), 10.1007/s00285-016-1030-4).
Journal of Mathematical Biology,
74(1-2).
Abstract:
Erratum to: Variable-Internal-Stores models of microbial growth and metabolism with dynamic allocation of cellular resources (Journal of Mathematical Biology, (2017), 74, 1-2, (409-445), 10.1007/s00285-016-1030-4)
In 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.
Abstract.
Nev OA, van Den Berg HA (2017). Mathematical models of microbial growth and metabolism: a whole-organism perspective.
Science Progress,
100(4), 343-362.
Abstract:
Mathematical models of microbial growth and metabolism: a whole-organism perspective
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.
Abstract.
Nev OA, Nev OA, van den Berg HA (2017). Optimal management of nutrient reserves in microorganisms under time-varying environmental conditions.
Journal of Theoretical Biology,
429, 124-141.
Abstract:
Optimal management of nutrient reserves in microorganisms under time-varying environmental conditions
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.
Abstract.
Nev OA, van den Berg HA (2017). Variable-Internal-Stores models of microbial growth and metabolism with dynamic allocation of cellular resources.
Journal of Mathematical Biology,
74(1-2), 409-445.
Abstract:
Variable-Internal-Stores models of microbial growth and metabolism with dynamic allocation of cellular resources
Variable-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.
Abstract.
2014
Krivulin NK, Nev OA (2014). Calculation of the asymptotic characteristics of a stochastic synchronized dynamic system.
Vestnik St. Petersburg University: Mathematics,
47(4), 145-153.
Abstract:
Calculation of the asymptotic characteristics of a stochastic synchronized dynamic system
This paper is concerned with the model of a stochastic dynamic system with synchronized events. The dynamics of the system is described by a generalized linear equation with a matrix involving one random entry on the diagonal; the remaining entries are nonnegative constants that are related by some conditions. The problem is to determine the mean asymptotic growth rate of the state vector (the Lyapunov exponent) of the system. The solution depends upon a change of variables, as a result of which new random variables are introduced instead of the random coordinates of the state vector. It is shown that in many cases by an appropriate choice of new variables one may reduce the problem to examining only one sequence of random variables given by a recurrence equation of a certain form, which depends only on two of three constants in the matrix of the system. The construction of such a system of random variables is followed by examination of its convergence. The Lyapunov exponent of a system is obtained as the mean value of the limit distribution of a sequence.
Abstract.
