Overview
I obtained a `specialist’ diploma with honours (comparable to MMath) in Applied Mathematics and Computer Science at Nizhniy Novgorod State University in 2006. I subsequently worked as a Teaching Fellow at the Nizhniy Novgorod State University and at the St. Petersburg University of Economics, and then as a Research Assistant on the project Asymptotic properties of stochastic dynamical systems at St. Petersburg State University from 2011 to 2014.
In 2017, I obtained a PhD degree in Analytical Sciences at Warwick University, where I worked on a project which overall objective was to characterize how bacterial cells respond to changing environmental conditions by adjusting the expression levels of the transport systems and enzymes supporting various metabolic pathways.
In 2018 I joined Prof Ivana Gudelj’s group at Exeter University as a Postdoctoral Research Fellow, where I used mathematical approaches to study the evolution of drug resistance in mixed-species microbial communities using Candida species as model organisms.
From April 2020 I have been working as an MRC Skills Development Fellow in Prof Al Brown's group at the MRC Medical Mycology Centre at Exeter University. The goal of my research project is to overcome the main obstacle in the study of a major fungal pathogen of humans – Pneumocystis. This pathogen kills hundreds of thousands of immunocompromised patients each year, and yet only a few groups are studying this pathogen because, currently, it is not possible to culture it in vitro independently of its host. My goal is to develop an in silico metabolic model of Pneumocystis growth and metabolism based on recently published new genomic data and to use this model to design in vitro growth conditions.
Qualifications
2015 - 2017: PhD in Mathematical Biology, University of Warwick
2010 - 2012: MSc in Mathematical Methods of Economic Analysis, St. Petersburg branch of High School of Economics
2004 - 2008: BSc in Enterprise Economics and Management, Nizhniy Novgorod State University
2001 - 2006: BSc in Applied Mathematics and Informatics, Nizhniy Novgorod State University
Career
2020 - current: MRC Skills Development Fellow, University of Exeter
2018 - 2020: Postdoctoral Research Fellow, University of Exeter, Living Systems Institute
2011 - 2014: Research Assistant at the St. Petersburg State University, Mathematics and Mechanics
Research
Research interests
My immediate career focus is to develop and establish myself as an independent, interdisciplinary scientist, bringing non-trivial mathematical insights and techniques to Life and Medical Sciences. I am highly interested in applying my quantitative knowledge to a broad range of biomedical and clinical problems.
Research projects
From April 2020 I have been working as an MRC Skills Development Fellow in Prof Al Brown's group at the MRC Medical Mycology Centre at Exeter University. The goal of my research project is to overcome the main obstacle in the study of a major fungal pathogen of humans – Pneumocystis. This pathogen kills hundreds of thousands of immunocompromised patients each year, and yet only a few groups are studying this pathogen because, currently, it is not possible to culture it in vitro independently of its host. My goal is to release this major experimental bottleneck by developing an in silico metabolic model of Pneumocystis growth and metabolism based on recently published new genomic data and to use this model to design in vitro growth conditions.
Grants/Funding
2015 – 2017: FP7 Marie Curie Actions funded PhD student
2018 – 2020: ERC funded Postdoctoral Research Fellow
2020 – current: MRC Skills Development Fellow
Publications
Key publications | Publications by category | Publications by year
Publications by category
Journal articles
Pradhan A, Ma Q, de Assis LJ, Leaves I, Larcombe DE, Rodriguez Rondon AV, Nev OA, Brown AJP (2020). Anticipatory Stress Responses and Immune Evasion in Fungal Pathogens.
Trends in MicrobiologyAbstract:
Anticipatory Stress Responses and Immune Evasion in Fungal Pathogens
© 2020 the Authors 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.
Full text.
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.
Abstract.
Author URL.
Full text.
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.
Full text.
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
© 2017 Informa UK Limited, trading as Taylor. &. Francis Group. 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.
Full text.
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)
© 2016, Springer-Verlag Berlin Heidelberg. 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.
Full text.
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
© 2017, Science Reviews 2000 Ltd. All rights reserved. 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.
Full text.
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
© 2017 Elsevier Ltd 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.
Full text.
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
© 2016, the Author(s). 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.
Full text.
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
© 2014, Allerton Press, Inc. 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.
Publications by year
2020
Pradhan A, Ma Q, de Assis LJ, Leaves I, Larcombe DE, Rodriguez Rondon AV, Nev OA, Brown AJP (2020). Anticipatory Stress Responses and Immune Evasion in Fungal Pathogens.
Trends in MicrobiologyAbstract:
Anticipatory Stress Responses and Immune Evasion in Fungal Pathogens
© 2020 the Authors 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.
Full text.
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 Full text.
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.
Abstract.
Author URL.
Full text.
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.
Full text.
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
© 2017 Informa UK Limited, trading as Taylor. &. Francis Group. 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.
Full text.
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)
© 2016, Springer-Verlag Berlin Heidelberg. 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.
Full text.
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
© 2017, Science Reviews 2000 Ltd. All rights reserved. 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.
Full text.
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
© 2017 Elsevier Ltd 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.
Full text.
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
© 2016, the Author(s). 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.
Full text.
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
© 2014, Allerton Press, Inc. 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.
Refresh publications
Teaching
2007 - 2008: Nizhniy Novgorod State University, faculty of Economics, department of Information Technologies
Leading workshops and lab classes for students (Advanced Mathematics, Methods of Optimization)
2012 - 2013: St. Petersburg University of Economics, faculty of Information Systems in Economics and Management, department of Advanced Mathematics
Leading workshops for students (Advanced Mathematics)
2015 – 2017: University of Warwick, Mathematics Institute
Undergraduate teaching support
2018: Postgraduate Award in Teaching and Learning in Higher Education, University of Warwick
