Publications by year
In Press
Beardmore R, Gudelj I, Hewlett M, Pena-Miller R, Meyer J (In Press). Canonical host-pathogen tradeoffs subverted by mutations with dual benefits.
The American NaturalistAbstract:
Canonical host-pathogen tradeoffs subverted by mutations with dual benefits
Host-parasite coevolution is expected to drive the evolution of genetic diversity because the traits used in arms races, namely host range and parasite resistance, are hypothesized to tradeoff with traits used in resource competition. We therefore tested data for several tradeoffs among 93 isolates of bacteriophage λ and 51 Escherichia coli genotypes that coevolved during a labora- tory experiment. Surprisingly, we found multiple tradeups (positive trait correlations) but little evidence of several canonical tradeoffs. For example, some bacterial genotypes evaded a trade- off between phage resistance and absolute fitness, instead evolving simultaneous improvements in both traits. This was surprising because our experimental design was predicted to expose resistance-fitness tradeoffs by culturing E. coli in a medium where the phage receptor, LamB, is also used for nutrient acquisition. On reflection, LamB mediates not one but many tradeoffs, allowing for more complex trait interactions than just pairwise tradeoffs. Here, we report that mathematical reasoning and laboratory data highlight how tradeups should exist whenever an evolutionary system exhibits multiple interacting tradeoffs. Does this mean that coevolution should not promote genetic diversity? No, quite the contrary. We deduce that whenever posi- tive trait correlations are observed in multi-dimensional traits, other traits may trade off and so provide the right circumstances for diversity maintenance. Overall, this study reveals there are predictive limits when data only account for pairwise trait correlations and it argues that a wider range of circumstances than previously anticipated can promote genetic and species diversity.
Abstract.
Reding C, Hewlett M, Bergmiller T, Gudelj I, Beardmore R (In Press). Fluorescence photography of patterns and waves of bacterial adaptation at high antibiotic doses.
Abstract:
Fluorescence photography of patterns and waves of bacterial adaptation at high antibiotic doses
Fisher suggested advantageous genes would spread through populations as a wave so we sought genetic waves in evolving populations, as follows. By fusing a fluorescent marker to a drug efflux protein (AcrB) whose expression providesEscherichia coliwith resistance to some antibiotics, we quantified the evolution and spread of drug-resistantE. colithrough spacetime using image analysis and quantitative PCR. As is done in hospitals routinely, we exposed the bacterium to a gradient of antibiotic in a ‘disk diffusion’ drug susceptibility test that we videoed. The videos show complex spatio-genomic patterns redolent of, yet more complex than, Fisher’s predictions whereby a decelerating wave front of advantageous genes colonises towards the antibiotic source, forming bullseye patterns en route and leaving a wave back of bacterial sub-populations expressing AcrB at decreasing levels away from the drug source. qPCR data show thatE. colisited at rapidly-adapting spatial hotspots gain 2 additional copies ofacr, the operon that encodes AcrB, within 24h and imaging data show resistant sub-populations thrive most near the antibiotic source due to non-monotone relationships between inhibition due to antibiotic and distance from the source. In the spirit of Fisher, we provide an explicitly spatial nonlinear diffusion equation that exhibits these properties too. Finally, linear diffusion theory quantifies how the spatial extent of bacterial killing scales with increases in antibiotic dosage, predicting that microbes can survive chemotherapies that have been escalated to 250× the clinical dosage if the antibiotic is diffusion-limited.
Abstract.
Beardmore R, Gudelj I, Reding C, Wood E, Bergmiller T, Schulenberg H, Philip R, Catalan P (In Press). The Antibiotic Dosage of Fastest Resistance Evolution: gene amplifications underpinning the inverted-U. Molecular Biology and Evolution
2023
Ames R, Brown AJP, Gudelj I, Nev OA (2023). Analysis of Pneumocystis Transcription Factor Evolution and Implications for Biology and Lifestyle.
mBio,
14(1).
Abstract:
Analysis of Pneumocystis Transcription Factor Evolution and Implications for Biology and Lifestyle.
Pneumocystis jirovecii kills hundreds of thousands of immunocompromised patients each year. Yet many aspects of the biology of this obligate pathogen remain obscure because it is not possible to culture the fungus in vitro independently of its host. Consequently, our understanding of Pneumocystis pathobiology is heavily reliant upon bioinformatic inferences. We have exploited a powerful combination of genomic and phylogenetic approaches to examine the evolution of transcription factors in Pneumocystis species. We selected protein families (Pfam families) that correspond to transcriptional regulators and used bioinformatic approaches to compare these families in the seven Pneumocystis species that have been sequenced to date with those from other yeasts, other human and plant pathogens, and other obligate parasites. Some Pfam families of transcription factors have undergone significant reduction during their evolution in the Pneumocystis genus, and other Pfam families have been lost or appear to be in the process of being lost. Meanwhile, other transcription factor families have been retained in Pneumocystis species, and some even appear to have undergone expansion. On this basis, Pneumocystis species seem to have retained transcriptional regulators that control chromosome maintenance, ribosomal gene regulation, RNA processing and modification, and respiration. Meanwhile, regulators that promote the assimilation of alternative carbon sources, amino acid, lipid, and sterol biosynthesis, and iron sensing and homeostasis appear to have been lost. Our analyses of transcription factor retention, loss, and gain provide important insights into the biology and lifestyle of Pneumocystis. IMPORTANCE Pneumocystis jirovecii is a major fungal pathogen of humans that infects healthy individuals, colonizing the lungs of infants. In immunocompromised and transplant patients, this fungus causes life-threatening pneumonia, and these Pneumocystis infections remain among the most common and serious infections in HIV/AIDS patients. Yet we remain remarkably ignorant about the biology and epidemiology of Pneumocystis due to the inability to culture this fungus in vitro. Our analyses of transcription factor retentions, losses, and gains in sequenced Pneumocystis species provide valuable new views of their specialized biology, suggesting the retention of many metabolic and stress regulators and the loss of others that are essential in free-living fungi. Given the lack of in vitro culture methods for Pneumocystis, this powerful bioinformatic approach has advanced our understanding of the lifestyle of P. jirovecii and the nature of its dependence on the host for survival.
Abstract.
Author URL.
Nev OA, Zamaraeva E, De Oliveira R, Abou-Jaoudé W, Ouattara DA, Hoving JC, Gudelj I, Brown AJP (2023). METABOLIC MODELLING AS a POWERFUL TOOL TO IDENTIFY CRITICAL COMPONENTS OF THE PNEUMOCYSTIS GROWTH MEDIUM.
Lindsay RJ, Holder PJ, Talbot NJ, Gudelj I (2023). Metabolic efficiency reshapes the seminal relationship between pathogen growth rate and virulence.
Ecol Lett,
26(6), 896-907.
Abstract:
Metabolic efficiency reshapes the seminal relationship between pathogen growth rate and virulence.
A cornerstone of classical virulence evolution theories is the assumption that pathogen growth rate is positively correlated with virulence, the amount of damage pathogens inflict on their hosts. Such theories are key for incorporating evolutionary principles into sustainable disease management strategies. Yet, empirical evidence raises doubts over this central assumption underpinning classical theories, thus undermining their generality and predictive power. In this paper, we identify a key component missing from current theories which redefines the growth-virulence relationship in a way that is consistent with data. By modifying the activity of a single metabolic gene, we engineered strains of Magnaporthe oryzae with different nutrient acquisition and growth rates. We conducted in planta infection studies and uncovered an unexpected non-monotonic relationship between growth rate and virulence that is jointly shaped by how growth rate and metabolic efficiency interact. This novel mechanistic framework paves the way for a much-needed new suite of virulence evolution theories.
Abstract.
Author URL.
Wood E, Schulenburg H, Rosenstiel P, Bergmiller T, Ankrett D, Gudelj I, Beardmore R (2023). Ribosome-binding antibiotics increase bacterial longevity and growth efficiency.
Proc Natl Acad Sci U S A,
120(40).
Abstract:
Ribosome-binding antibiotics increase bacterial longevity and growth efficiency.
Antibiotics, by definition, reduce bacterial growth rates in optimal culture conditions; however, the real-world environments bacteria inhabit see rapid growth punctuated by periods of low nutrient availability. How antibiotics mediate population decline during these periods is poorly understood. Bacteria cannot optimize for all environmental conditions because a growth-longevity tradeoff predicts faster growth results in faster population decline, and since bacteriostatic antibiotics slow growth, they should also mediate longevity. We quantify how antibiotics, their targets, and resistance mechanisms influence longevity using populations of Escherichia coli and, as the tradeoff predicts, populations are maintained for longer if they encounter ribosome-binding antibiotics doxycycline and erythromycin, a finding that is not observed using antibiotics with alternative cellular targets. This tradeoff also predicts resistance mechanisms that increase growth rates during antibiotic treatment could be detrimental during nutrient stresses, and indeed, we find resistance by ribosomal protection removes benefits to longevity provided by doxycycline. We therefore liken ribosomal protection to a "Trojan horse" because it provides protection from an antibiotic but, during nutrient stresses, it promotes the demise of the bacteria. Seeking mechanisms to support these observations, we show doxycycline promotes efficient metabolism and reduces the concentration of reactive oxygen species. Seeking generality, we sought another mechanism that affects longevity and we found the number of doxycycline targets, namely, the ribosomal RNA operons, mediates growth and longevity even without antibiotics. We conclude that slow growth, as observed during antibiotic treatment, can help bacteria overcome later periods of nutrient stress.
Abstract.
Author URL.
2022
Catalán P, Wood E, Blair JMA, Gudelj I, Iredell JR, Beardmore RE (2022). Seeking patterns of antibiotic resistance in ATLAS, an open, raw MIC database with patient metadata.
Nat Commun,
13(1).
Abstract:
Seeking patterns of antibiotic resistance in ATLAS, an open, raw MIC database with patient metadata.
Antibiotic resistance represents a growing medical concern where raw, clinical datasets are under-exploited as a means to track the scale of the problem. We therefore sought patterns of antibiotic resistance in the Antimicrobial Testing Leadership and Surveillance (ATLAS) database. ATLAS holds 6.5M minimal inhibitory concentrations (MICs) for 3,919 pathogen-antibiotic pairs isolated from 633k patients in 70 countries between 2004 and 2017. We show most pairs form coherent, although not stationary, timeseries whose frequencies of resistance are higher than other databases, although we identified no systematic bias towards including more resistant strains in ATLAS. We sought data anomalies whereby MICs could shift for methodological and not clinical or microbiological reasons and found artefacts in over 100 pathogen-antibiotic pairs. Using an information-optimal clustering methodology to classify pathogens into low and high antibiotic susceptibilities, we used ATLAS to predict changes in resistance. Dynamics of the latter exhibit complex patterns with MIC increases, and some decreases, whereby subpopulations' MICs can diverge. We also identify pathogens at risk of developing clinical resistance in the near future.
Abstract.
Author URL.
2021
Reding C, Catalán P, Jansen G, Bergmiller T, Wood E, Rosenstiel P, Schulenberg H, Philip R, Gudelj I, Beardmore R, et al (2021). Antibiotic dosages of fastest resistance evolution: gene amplifications underpinning the inverted U.
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.
Lindsay RJ, Jepson A, Butt L, Holder PJ, Smug BJ, Gudelj I (2021). Would that it were so simple: Interactions between multiple traits undermine classical single‐trait‐based predictions of microbial community function and evolution.
Ecology Letters,
24(12), 2775-2795.
Abstract:
Would that it were so simple: Interactions between multiple traits undermine classical single‐trait‐based predictions of microbial community function and evolution
AbstractUnderstanding how microbial traits affect the evolution and functioning of microbial communities is fundamental for improving the management of harmful microorganisms, while promoting those that are beneficial. Decades of evolutionary ecology research has focused on examining microbial cooperation, diversity, productivity and virulence but with one crucial limitation. The traits under consideration, such as public good production and resistance to antibiotics or predation, are often assumed to act in isolation. Yet, in reality, multiple traits frequently interact, which can lead to unexpected and undesired outcomes for the health of macroorganisms and ecosystem functioning. This is because many predictions generated in a single‐trait context aimed at promoting diversity, reducing virulence or controlling antibiotic resistance can fail for systems where multiple traits interact. Here, we provide a much needed discussion and synthesis of the most recent research to reveal the widespread and diverse nature of multi‐trait interactions and their consequences for predicting and controlling microbial community dynamics. Importantly, we argue that synthetic microbial communities and multi‐trait mathematical models are powerful tools for managing the beneficial and detrimental impacts of microbial communities, such that past mistakes, like those made regarding the stewardship of antimicrobials, are not repeated.
Abstract.
2020
Catalan P, Reding C, Blair J, Gudelj I, Iredell J, Beardmore R (2020). Clinical Antibiotic Resistance Patterns Across 70 Countries.
Duxbury SJN, Bates S, Beardmore RE, Gudelj I (2020). Evolution of drug-resistant and virulent small colonies in phenotypically diverse populations of the human fungal pathogen. <i>Candida glabrata</i>.
Proceedings of the Royal Society B: Biological Sciences,
287(1931), 20200761-20200761.
Abstract:
Evolution of drug-resistant and virulent small colonies in phenotypically diverse populations of the human fungal pathogen. Candida glabrata
. Antimicrobial resistance frequently carries a fitness cost to a pathogen, measured as a reduction in growth rate compared to the sensitive wild-type, in the absence of antibiotics. Existing empirical evidence points to the following relationship between cost of resistance and virulence. If a resistant pathogen suffers a fitness cost in terms of reduced growth rate it commonly has lower virulence compared to the sensitive wild-type. If this cost is absent so is the reduction in virulence. Here we show, using experimental evolution of drug resistance in the fungal human pathogen
. Candida glabrata,
. that reduced growth rate of resistant strains need not result in reduced virulence. Phenotypically heterogeneous populations were evolved in parallel containing highly resistant sub-population small colony variants (SCVs) alongside sensitive sub-populations. Despite their low growth rate in the absence of an antifungal drug, the SCVs did not suffer a marked alteration in virulence compared with the wild-type ancestral strain, or their co-isolated sensitive strains. This contrasts with classical theory that assumes growth rate to positively correlate with virulence. Our work thus highlights the complexity of the relationship between resistance, basic life-history traits and virulence.
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Abstract.
Ahmed J (2020). Investigating the Effect of Temperature on Pump-Driven Antibiotic Resistance towards Erythromycin in Escherichia coli.
Abstract:
Investigating the Effect of Temperature on Pump-Driven Antibiotic Resistance towards Erythromycin in Escherichia coli
Antibiotic resistance is an inevitable by-product from treatment of bacterial (and fungal) infections, however the rate and intensity at which it is emerging is alarming. More and more drugs are being rendered ineffective, where poor treatment behaviours, such as overuse, are being held accountable. Coupled with a dry antibiotic pipeline, we are increasingly seeing ourselves approach a post-antibiotic era. As research is being conducted into discovering new antibiotics, we also need to find ways to preserve the ones we still have. Therefore it is equally important to identify and study potential selection pressures, both environmental and clinical, that contribute to the rise in resistance.
To provide a preliminary insight on temperature as a possible selection pressure, this research project aimed to investigate the effect of temperature on the susceptibility of Escherichia coli to the macrolide-class antibiotic erythromycin, and ultimately its effect on the expression of multidrug efflux pump AcrAB-TolC. This was done by exposing E. coli cells to a range of erythromycin concentrations during 24 hours of growth, establishing a minimum inhibitory concentration (MIC) at 30°C and seeing any shifts in the MIC at 37°C. It was found that as temperature increased from 30°C to 37°C, so did the MIC. Thus the cells were more resistant at the higher temperature.
Next, to see whether and how AcrAB-TolC was selected for as a result of temperature, the expression of protein AcrB was measured via fluorescence emitted from sfGFP (due to the sfGFP gene being physically fused to the acrB gene). It was found that the range of concentrations that select for pump expression, referred to as the “AcrB expression-selection window”, shifted positively with increasing temperature. This suggests a temperature-dependent nature of resistance selection, therefore this knowledge may help in choosing an effective dose for treatment based on thermal conditions.
The outcomes of this research project will help provide a foundation for looking further into temperature, and other selection pressures, and their effect on the rise in antibiotic resistance.
Abstract.
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.
Abstract.
Author URL.
Nev O, Jepson A, Butt L, Lindsay R, Beardmore R, Gudelj I (2020). Raw growth data for the manuscript Predicting microbial growth dynamics in changing environments.
2019
Beardmore R, Hewlett M, Peña-Miller R, Reding C, Gudelj I, Meyer JR (2019). Canonical host-pathogen tradeoffs subverted by mutations with dual benefits.
Reding C, Catalán P, Jansen G, Bergmiller T, Rosenstiel P, Schulenburg H, Gudelj I, Beardmore R (2019). Hotspot Dosages of Most Rapid Antibiotic Resistance Evolution.
Lindsay RJ, Pawlowska BJ, Gudelj I (2019). Privatisation of public goods can cause population decline (dataset). Nature Ecology and Evolution
Lindsay RJ, Pawlowska BJ, Gudelj I (2019). Privatization of public goods can cause population decline.
Nature Ecology and Evolution,
3(8), 1206-1216.
Abstract:
Privatization of public goods can cause population decline
Microbes commonly deploy a risky strategy to acquire nutrients from their environment, involving the production of costly public goods that can be exploited by neighbouring individuals. Why engage in such a strategy when an exploitation-free alternative is readily available whereby public goods are kept private? We address this by examining metabolism of Saccharomyces cerevisiae in its native form and by creating a new three-strain synthetic community deploying different strategies of sucrose metabolism. Public-metabolizers digest resources externally, private-metabolizers internalize resources before digestion, and cheats avoid the metabolic costs of digestion but exploit external products generated by competitors. A combination of mathematical modelling and ecological experiments reveal that private-metabolizers invade and take over an otherwise stable community of public-metabolizers and cheats. However, owing to the reduced growth rate of private-metabolizers and population bottlenecks that are frequently associated with microbial communities, privatizing public goods can become unsustainable, leading to population decline.
Abstract.
2018
Beardmore RE, Cook E, Nilsson S, Smith AR, Tillmann A, Esquivel BD, Haynes K, Gow NAR, Brown AJP, White TC, et al (2018). Drug-mediated metabolic tipping between antibiotic resistant states in a mixed-species community.
Nat Ecol Evol,
2(8), 1312-1320.
Abstract:
Drug-mediated metabolic tipping between antibiotic resistant states in a mixed-species community.
Microbes rarely exist in isolation, rather, they form intricate multi-species communities that colonize our bodies and inserted medical devices. However, the efficacy of antimicrobials is measured in clinical laboratories exclusively using microbial monocultures. Here, to determine how multi-species interactions mediate selection for resistance during antibiotic treatment, particularly following drug withdrawal, we study a laboratory community consisting of two microbial pathogens. Single-species dose responses are a poor predictor of community dynamics during treatment so, to better understand those dynamics, we introduce the concept of a dose-response mosaic, a multi-dimensional map that indicates how species' abundance is affected by changes in abiotic conditions. We study the dose-response mosaic of a two-species community with a 'Gene × Gene × Environment × Environment' ecological interaction whereby Candida glabrata, which is resistant to the antifungal drug fluconazole, competes for survival with Candida albicans, which is susceptible to fluconazole. The mosaic comprises several zones that delineate abiotic conditions where each species dominates. Zones are separated by loci of bifurcations and tipping points that identify what environmental changes can trigger the loss of either species. Observations of the laboratory communities corroborated theory, showing that changes in both antibiotic concentration and nutrient availability can push populations beyond tipping points, thus creating irreversible shifts in community composition from drug-sensitive to drug-resistant species. This has an important consequence: resistant species can increase in frequency even if an antibiotic is withdrawn because, unwittingly, a tipping point was passed during treatment.
Abstract.
Author URL.
Beardmore RE, Cook E, Nilsson S, Smith AR, Tillmann A, Esquivel BD, Haynes K, Gow NAR, Brown AJP, White TC, et al (2018). Erratum to: Drug-mediated metabolic tipping between antibiotic resistant states in a mixed-species community (Nature Ecology & Evolution, (2018), 2, 8, (1312-1320), 10.1038/s41559-018-0582-7).
Nature Ecology and Evolution,
2(11).
Abstract:
Erratum to: Drug-mediated metabolic tipping between antibiotic resistant states in a mixed-species community (Nature Ecology & Evolution, (2018), 2, 8, (1312-1320), 10.1038/s41559-018-0582-7)
In the version of this Article originally published, the following sentence was missing from the Acknowledgements: “R.E.B. is an EPSRC Healthcare Technologies Impact Fellow EP/N033671/1; I.G. is funded by ERC Consolidator grant 647292 MathModExp; A.J.P.B. N.A.R.G. and A.T. were funded by BBSRC grant BB/F00513X/1; K.H. I.G. S.N. and E.C. were funded by BBSRC grant BB/F005210/2.” This text has now been added.
Abstract.
Lindsay RJ, Pawlowska BJ, Gudelj I (2018). When increasing population density can promote the evolution of metabolic cooperation.
ISME J,
12(3), 849-859.
Abstract:
When increasing population density can promote the evolution of metabolic cooperation.
Microbial cooperation drives ecological and epidemiological processes and is affected by the ecology and demography of populations. Population density influences the selection for cooperation, with spatial structure and the type of social dilemma, namely public-goods production or self-restraint, shaping the outcome. While existing theories predict that in spatially structured environments increasing population density can select either for or against cooperation, experimental studies with both public-goods production and self-restraint systems have only ever shown that increasing population density favours cheats. We suggest that the disparity between theory and empirical studies results from experimental procedures not capturing environmental conditions predicted by existing theories to influence the outcome. Our study resolves this issue and provides the first experimental evidence that high population density can favour cooperation in spatially structured environments for both self-restraint and public-goods production systems. Moreover, using a multi-trait mathematical model supported by laboratory experiments we extend this result to systems where the self-restraint and public-goods social dilemmas interact. We thus provide a systematic understanding of how the strength of interaction between the two social dilemmas and the degree of spatial structure within an environment affect selection for cooperation. These findings help to close the current gap between theory and experiments.
Abstract.
Author URL.
2017
Takano S, Pawlowska BJ, Gudelj I, Yomo T, Tsuru S (2017). Density-Dependent Recycling Promotes the Long-Term Survival of Bacterial Populations during Periods of Starvation.
mBio,
8(1).
Abstract:
Density-Dependent Recycling Promotes the Long-Term Survival of Bacterial Populations during Periods of Starvation.
UNLABELLED: the amount of natural resources in the Earth's environment is in flux, which can trigger catastrophic collapses of ecosystems. How populations survive under nutrient-poor conditions is a central question in ecology. Curiously, some bacteria persist for a long time in nutrient-poor environments. Although this survival may be accomplished through cell death and the recycling of dead cells, the importance of these processes and the mechanisms underlying the survival of the populations have not been quantitated. Here, we use microbial laboratory experiments and mathematical models to demonstrate that death and recycling are essential activities for the maintenance of cell survival. We also show that the behavior of the survivors is governed by population density feedback, wherein growth is limited not only by the available resources but also by the population density. The numerical simulations suggest that population density-dependent recycling could be an advantageous behavior under starvation conditions. IMPORTANCE: How organisms survive after exhaustion of resources is a central question in ecology. Starving Escherichia coli constitute a model system to understand survival mechanisms during long-term starvation. Although death and the recycling of dead cells might play a key role in the maintenance of long-term survival, their mechanisms and importance have not been quantitated. Here, we verified the significance of social recycling of dead cells for long-term survival. We also show that the survivors restrained their recycling and did not use all available nutrients released from dead cells, which may be advantageous under starvation conditions. These results indicate that not only the utilization of dead cells but also restrained recycling coordinate the effective utilization of limited resources for long-term survival under starvation.
Abstract.
Author URL.
Reding-Roman C, Hewlett M, Duxbury S, Gori F, Gudelj I, Beardmore R (2017). The unconstrained evolution of fast and efficient antibiotic-resistant bacterial genomes. Nature Ecology & Evolution, 1(3).
2016
Lindsay RJ, Kershaw MJ, Pawlowska BJ, Talbot NJ, Gudelj I (2016). Harbouring public good mutants within a pathogen population can increase both fitness and virulence.
Elife,
5Abstract:
Harbouring public good mutants within a pathogen population can increase both fitness and virulence.
Existing theory, empirical, clinical and field research all predict that reducing the virulence of individuals within a pathogen population will reduce the overall virulence, rendering disease less severe. Here, we show that this seemingly successful disease management strategy can fail with devastating consequences for infected hosts. We deploy cooperation theory and a novel synthetic system involving the rice blast fungus Magnaporthe oryzae. In vivo infections of rice demonstrate that M. oryzae virulence is enhanced, quite paradoxically, when a public good mutant is present in a population of high-virulence pathogens. We reason that during infection, the fungus engages in multiple cooperative acts to exploit host resources. We establish a multi-trait cooperation model which suggests that the observed failure of the virulence reduction strategy is caused by the interference between different social traits. Multi-trait cooperative interactions are widespread, so we caution against the indiscriminant application of anti-virulence therapy as a disease-management strategy.
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Author URL.
Rashkov P, Barrett IP, Beardmore RE, Bendtsen C, Gudelj I (2016). Kinase Inhibition Leads to Hormesis in a Dual Phosphorylation-Dephosphorylation Cycle.
PLoS Comput Biol,
12(11).
Abstract:
Kinase Inhibition Leads to Hormesis in a Dual Phosphorylation-Dephosphorylation Cycle.
Many antimicrobial and anti-tumour drugs elicit hormetic responses characterised by low-dose stimulation and high-dose inhibition. While this can have profound consequences for human health, with low drug concentrations actually stimulating pathogen or tumour growth, the mechanistic understanding behind such responses is still lacking. We propose a novel, simple but general mechanism that could give rise to hormesis in systems where an inhibitor acts on an enzyme. At its core is one of the basic building blocks in intracellular signalling, the dual phosphorylation-dephosphorylation motif, found in diverse regulatory processes including control of cell proliferation and programmed cell death. Our analytically-derived conditions for observing hormesis provide clues as to why this mechanism has not been previously identified. Current mathematical models regularly make simplifying assumptions that lack empirical support but inadvertently preclude the observation of hormesis. In addition, due to the inherent population heterogeneities, the presence of hormesis is likely to be masked in empirical population-level studies. Therefore, examining hormetic responses at single-cell level coupled with improved mathematical models could substantially enhance detection and mechanistic understanding of hormesis.
Abstract.
Author URL.
Gudelj I, Kinnersley M, Rashkov P, Schmidt K, Rosenzweig F (2016). Stability of Cross-Feeding Polymorphisms in Microbial Communities.
PLoS Computational Biology,
12(12).
Abstract:
Stability of Cross-Feeding Polymorphisms in Microbial Communities
Cross-feeding, a relationship wherein one organism consumes metabolites excreted by another, is a ubiquitous feature of natural and clinically-relevant microbial communities and could be a key factor promoting diversity in extreme and/or nutrient-poor environments. However, it remains unclear how readily cross-feeding interactions form, and therefore our ability to predict their emergence is limited. In this paper we developed a mathematical model parameterized using data from the biochemistry and ecology of an E. coli cross-feeding laboratory system. The model accurately captures short-term dynamics of the two competitors that have been observed empirically and we use it to systematically explore the stability of cross-feeding interactions for a range of environmental conditions. We find that our simple system can display complex dynamics including multi-stable behavior separated by a critical point. Therefore whether cross-feeding interactions form depends on the complex interplay between density and frequency of the competitors as well as on the concentration of resources in the environment. Moreover, we find that subtly different environmental conditions can lead to dramatically different results regarding the establishment of cross-feeding, which could explain the apparently unpredictable between-population differences in experimental outcomes. We argue that mathematical models are essential tools for disentangling the complexities of cross-feeding interactions.
Abstract.
2015
Meyer JR, Gudelj I, Beardmore R (2015). Biophysical mechanisms that maintain biodiversity through trade-offs.
Nat Commun,
6Abstract:
Biophysical mechanisms that maintain biodiversity through trade-offs.
Trade-offs are thought to arise from inevitable, biophysical limitations that prevent organisms from optimizing multiple traits simultaneously. A leading explanation for biodiversity maintenance is a theory that if the shape, or geometry, of a trade-off is right, then multiple species can coexist. Testing this theory, however, is difficult as trait data is usually too noisy to discern shape, or trade-offs necessary for the theory are not observed in vivo. To address this, we infer geometry directly from the biophysical mechanisms that cause trade-offs, deriving the geometry of two by studying nutrient uptake and metabolic properties common to all living cells. To test for their presence in vivo we isolated Escherichia coli mutants that vary in a nutrient transporter, LamB, and found evidence for both trade-offs. Consistent with data, population genetics models incorporating the trade-offs successfully predict the co-maintenance of three distinct genetic lineages, demonstrating that trade-off geometry can be deduced from fundamental principles of living cells and used to predict stable genetic polymorphisms.
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Author URL.
Fuentes-Hernandez A, Plucain J, Gori F, Pena-Miller R, Reding C, Jansen G, Schulenburg H, Gudelj I, Beardmore R (2015). Using a sequential regimen to eliminate bacteria at sublethal antibiotic dosages.
PLoS Biol,
13(4).
Abstract:
Using a sequential regimen to eliminate bacteria at sublethal antibiotic dosages.
We need to find ways of enhancing the potency of existing antibiotics, and, with this in mind, we begin with an unusual question: how low can antibiotic dosages be and yet bacterial clearance still be observed? Seeking to optimise the simultaneous use of two antibiotics, we use the minimal dose at which clearance is observed in an in vitro experimental model of antibiotic treatment as a criterion to distinguish the best and worst treatments of a bacterium, Escherichia coli. Our aim is to compare a combination treatment consisting of two synergistic antibiotics to so-called sequential treatments in which the choice of antibiotic to administer can change with each round of treatment. Using mathematical predictions validated by the E. coli treatment model, we show that clearance of the bacterium can be achieved using sequential treatments at antibiotic dosages so low that the equivalent two-drug combination treatments are ineffective. Seeking to treat the bacterium in testing circumstances, we purposefully study an E. coli strain that has a multidrug pump encoded in its chromosome that effluxes both antibiotics. Genomic amplifications that increase the number of pumps expressed per cell can cause the failure of high-dose combination treatments, yet, as we show, sequentially treated populations can still collapse. However, dual resistance due to the pump means that the antibiotics must be carefully deployed and not all sublethal sequential treatments succeed. A screen of 136 96-h-long sequential treatments determined five of these that could clear the bacterium at sublethal dosages in all replicate populations, even though none had done so by 24 h. These successes can be attributed to a collateral sensitivity whereby cross-resistance due to the duplicated pump proves insufficient to stop a reduction in E. coli growth rate following drug exchanges, a reduction that proves large enough for appropriately chosen drug switches to clear the bacterium.
Abstract.
Author URL.
2014
Sieber M, Robb M, Forde SE, Gudelj I (2014). Dispersal network structure and infection mechanism shape diversity in a coevolutionary bacteria-phage system.
ISME Journal,
8(3), 504-514.
Abstract:
Dispersal network structure and infection mechanism shape diversity in a coevolutionary bacteria-phage system
Resource availability, dispersal and infection genetics all have the potential to fundamentally alter the coevolutionary dynamics of bacteria-bacteriophage interactions. However, it remains unclear how these factors synergise to shape diversity within bacterial populations. We used a combination of laboratory experiments and mathematical modeling to test how the structure of a dispersal network affects host phenotypic diversity in a coevolving bacteria-phage system in communities of differential resource input. Unidirectional dispersal of bacteria and phage from high to low resources consistently increased host diversity compared with a no dispersal regime. Bidirectional dispersal, on the other hand, led to a marked decrease in host diversity. Our mathematical model predicted these opposing outcomes when we incorporated modified gene-for-gene infection genetics. To further test how host diversity depended on the genetic underpinnings of the bacteria-phage interaction, we expanded our mathematical model to include different infection mechanisms. We found that the direction of dispersal had very little impact on bacterial diversity when the bacteria-phage interaction was mediated by matching alleles, gene-for-gene or related infection mechanisms. Our experimental and theoretical results demonstrate that the effects of dispersal on diversity in coevolving host-parasite systems depend on an intricate interplay of the structure of the underlying dispersal network and the specifics of the host-parasite interaction. © 2014 International Society for Microbial Ecology. All rights reserved.
Abstract.
Sieber M, Gudelj I (2014). Do-or-die life cycles and diverse post-infection resistance mechanisms limit the evolution of parasite host ranges.
Ecology Letters,
17(4), 491-498.
Abstract:
Do-or-die life cycles and diverse post-infection resistance mechanisms limit the evolution of parasite host ranges
In light of the dynamic nature of parasite host ranges and documented potential for rapid host shifts, the observed high host specificity of most parasites remains an ecological paradox. Different variants of host-use trade-offs have become a mainstay of theoretical explanations of the prevalence of host specialism, but empirical evidence for such trade-offs is rare. We propose an alternative theory based on basic features of the parasite life cycle: host selection and subsequent intrahost replication. We introduce a new concept of effective burst size that accounts for the fact that successful host selection does not guarantee intrahost replication. Our theory makes a general prediction that a parasite will expand its host range if its effective burst size is positive. An in silico model of bacteria-phage coevolution verifies our predictions and demonstrates that the tendency for relatively narrow host ranges in parasites can be explained even in the absence of trade-offs. © 2014 John Wiley & Sons Ltd/CNRS.
Abstract.
Peña-Miller R, Fuentes-Hernandez A, Reding C, Gudelj I, Beardmore R (2014). Testing the optimality properties of a dual antibiotic treatment in a two-locus, two-allele model.
J R Soc Interface,
11(96).
Abstract:
Testing the optimality properties of a dual antibiotic treatment in a two-locus, two-allele model.
Mathematically speaking, it is self-evident that the optimal control of complex, dynamical systems with many interacting components cannot be achieved with 'non-responsive' control strategies that are constant through time. Although there are notable exceptions, this is usually how we design treatments with antimicrobial drugs when we give the same dose and the same antibiotic combination each day. Here, we use a frequency- and density-dependent pharmacogenetics mathematical model based on a standard, two-locus, two-allele representation of how bacteria resist antibiotics to probe the question of whether optimal antibiotic treatments might, in fact, be constant through time. The model describes the ecological and evolutionary dynamics of different sub-populations of the bacterium Escherichia coli that compete for a single limiting resource in a two-drug environment. We use in vitro evolutionary experiments to calibrate and test the model and show that antibiotic environments can support dynamically changing and heterogeneous population structures. We then demonstrate, theoretically and empirically, that the best treatment strategies should adapt through time and constant strategies are not optimal.
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Author URL.
2013
Maharjan R, Nilsson S, Sung J, Haynes K, Beardmore RE, Hurst LD, Ferenci T, Gudelj I (2013). The form of a trade-off determines the response to competition. Ecology Letters, 16(10), 1267-1276.
Maharjan R, Nilsson S, Sung J, Haynes K, Beardmore RE, Hurst LD, Ferenci T, Gudelj I (2013). The form of a trade-off determines the response to competition.
Ecol Lett,
16(10), 1267-1276.
Abstract:
The form of a trade-off determines the response to competition.
Understanding how populations and communities respond to competition is a central concern of ecology. A seminal theoretical solution first formalised by Levins (and re-derived in multiple fields) showed that, in theory, the form of a trade-off should determine the outcome of competition. While this has become a central postulate in ecology it has evaded experimental verification, not least because of substantial technical obstacles. We here solve the experimental problems by employing synthetic ecology. We engineer strains of Escherichia coli with fixed resource allocations enabling accurate measurement of trade-off shapes between bacterial survival and multiplication in multiple environments. A mathematical chemostat model predicts different, and experimentally verified, trajectories of gene frequency changes as a function of condition-specific trade-offs. The results support Levins' postulate and demonstrates that otherwise paradoxical alternative outcomes witnessed in subtly different conditions are predictable.
Abstract.
Author URL.
2011
Levert M, Zamfir O, Clermont O, Bouvet O, Lespinats S, Hipeaux MC, Branger C, Picard B, Saint-Ruf C, Norel F, et al (2011). Correction: Molecular and Evolutionary Bases of Within-Patient Genotypic and Phenotypic Diversity in Escherichia coli Extraintestinal Infections.
PLoS Pathog,
7(6).
Abstract:
Correction: Molecular and Evolutionary Bases of Within-Patient Genotypic and Phenotypic Diversity in Escherichia coli Extraintestinal Infections.
[This corrects the article on p. e1001125 in vol. 6.].
Abstract.
Beardmore RE, Gudelj I, Lipson DA, Hurst LD (2011). Metabolic trade-offs and the maintenance of the fittest and the flattest.
Nature,
472(7343), 342-346.
Abstract:
Metabolic trade-offs and the maintenance of the fittest and the flattest.
How is diversity maintained? Environmental heterogeneity is considered to be important, yet diversity in seemingly homogeneous environments is nonetheless observed. This, it is assumed, must either be owing to weak selection, mutational input or a fitness advantage to genotypes when rare. Here we demonstrate the possibility of a new general mechanism of stable diversity maintenance, one that stems from metabolic and physiological trade-offs. The model requires that such trade-offs translate into a fitness landscape in which the most fit has unfit near-mutational neighbours, and a lower fitness peak also exists that is more mutationally robust. The 'survival of the fittest' applies at low mutation rates, giving way to 'survival of the flattest' at high mutation rates. However, as a consequence of quasispecies-level negative frequency-dependent selection and differences in mutational robustness we observe a transition zone in which both fittest and flattest coexist. Although diversity maintenance is possible for simple organisms in simple environments, the more trade-offs there are, the wider the maintenance zone becomes. The principle may be applied to lineages within a species or species within a community, potentially explaining why competitive exclusion need not be observed in homogeneous environments. This principle predicts the enigmatic richness of metabolic strategies in clonal bacteria and questions the safety of lethal mutagenesis as an antimicrobial treatment.
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Author URL.
2010
MaClean RC, Fuentes-Hernandez A, Greig D, Hurst LD, Gudelj I (2010). A mixture of "cheats" and "co-operators" can enable maximal group benefit.
PLoS Biol,
8(9).
Abstract:
A mixture of "cheats" and "co-operators" can enable maximal group benefit.
Is a group best off if everyone co-operates? Theory often considers this to be so (e.g. the "conspiracy of doves"), this understanding underpinning social and economic policy. We observe, however, that after competition between "cheat" and "co-operator" strains of yeast, population fitness is maximized under co-existence. To address whether this might just be a peculiarity of our experimental system or a result with broader applicability, we assemble, benchmark, dissect, and test a systems model. This reveals the conditions necessary to recover the unexpected result. These are 3-fold: (a) that resources are used inefficiently when they are abundant, (b) that the amount of co-operation needed cannot be accurately assessed, and (c) the population is structured, such that co-operators receive more of the resource than the cheats. Relaxing any of the assumptions can lead to population fitness being maximized when cheats are absent, which we experimentally demonstrate. These three conditions will often be relevant, and hence in order to understand the trajectory of social interactions, understanding the dynamics of the efficiency of resource utilization and accuracy of information will be necessary.
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Gudelj I, Weitz JS, Ferenci T, Claire Horner-Devine M, Marx CJ, Meyer JR, Forde SE (2010). An integrative approach to understanding microbial diversity: from intracellular mechanisms to community structure.
Ecol Lett,
13(9), 1073-1084.
Abstract:
An integrative approach to understanding microbial diversity: from intracellular mechanisms to community structure.
Trade-offs have been put forward as essential to the generation and maintenance of diversity. However, variation in trade-offs is often determined at the molecular level, outside the scope of conventional ecological inquiry. In this study, we propose that understanding the intracellular basis for trade-offs in microbial systems can aid in predicting and interpreting patterns of diversity. First, we show how laboratory experiments and mathematical models have unveiled the hidden intracellular mechanisms underlying trade-offs key to microbial diversity: (i) metabolic and regulatory trade-offs in bacteria and yeast; (ii) life-history trade-offs in bacterial viruses. Next, we examine recent studies of marine microbes that have taken steps toward reconciling the molecular and the ecological views of trade-offs, despite the challenges in doing so in natural settings. Finally, we suggest avenues for research where mathematical modelling, experiments and studies of natural microbial communities provide a unique opportunity to integrate studies of diversity across multiple scales.
Abstract.
Author URL.
Estrela S, Gudelj I (2010). Evolution of cooperative cross-feeding could be less challenging than originally thought.
PLoS One,
5(11).
Abstract:
Evolution of cooperative cross-feeding could be less challenging than originally thought.
The act of cross-feeding whereby unrelated species exchange nutrients is a common feature of microbial interactions and could be considered a form of reciprocal altruism or reciprocal cooperation. Past theoretical work suggests that the evolution of cooperative cross-feeding in nature may be more challenging than for other types of cooperation. Here we re-evaluate a mathematical model used previously to study persistence of cross-feeding and conclude that the maintenance of cross-feeding interactions could be favoured for a larger parameter ranges than formerly observed. Strikingly, we also find that large populations of cross-feeders are not necessarily vulnerable to extinction from an initially small number of cheats who receive the benefit of cross-feeding but do not reciprocate in this cooperative interaction. This could explain the widespread cooperative cross-feeding observed in natural populations.
Abstract.
Author URL.
Levert M, Zamfir O, Clermont O, Bouvet O, Lespinats S, Hipeaux MC, Branger C, Picard B, Saint-Ruf C, Norel F, et al (2010). Molecular and evolutionary bases of within-patient genotypic and phenotypic diversity in Escherichia coli extraintestinal infections.
PLoS Pathog,
6(9).
Abstract:
Molecular and evolutionary bases of within-patient genotypic and phenotypic diversity in Escherichia coli extraintestinal infections.
Although polymicrobial infections, caused by combinations of viruses, bacteria, fungi and parasites, are being recognised with increasing frequency, little is known about the occurrence of within-species diversity in bacterial infections and the molecular and evolutionary bases of this diversity. We used multiple approaches to study the genomic and phenotypic diversity among 226 Escherichia coli isolates from deep and closed visceral infections occurring in 19 patients. We observed genomic variability among isolates from the same site within 11 patients. This diversity was of two types, as patients were infected either by several distinct E. coli clones (4 patients) or by members of a single clone that exhibit micro-heterogeneity (11 patients); both types of diversity were present in 4 patients. A surprisingly wide continuum of antibiotic resistance, outer membrane permeability, growth rate, stress resistance, red dry and rough morphotype characteristics and virulence properties were present within the isolates of single clones in 8 of the 11 patients showing genomic micro-heterogeneity. Many of the observed phenotypic differences within clones affected the trade-off between self-preservation and nutritional competence (SPANC). We showed in 3 patients that this phenotypic variability was associated with distinct levels of RpoS in co-existing isolates. Genome mutational analysis and global proteomic comparisons in isolates from a patient revealed a star-like relationship of changes amongst clonally diverging isolates. A mathematical model demonstrated that multiple genotypes with distinct RpoS levels can co-exist as a result of the SPANC trade-off. In the cases involving infection by a single clone, we present several lines of evidence to suggest diversification during the infectious process rather than an infection by multiple isolates exhibiting a micro-heterogeneity. Our results suggest that bacteria are subject to trade-offs during an infectious process and that the observed diversity resembled results obtained in experimental evolution studies. Whatever the mechanisms leading to diversity, our results have strong medical implications in terms of the need for more extensive isolate testing before deciding on antibiotic therapies.
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Author URL.
2008
Forde SE, Beardmore RE, Gudelj I, Arkin SS, Thompson JN, Hurst LD (2008). Understanding the limits to generalizability of experimental evolutionary models.
Nature,
455(7210), 220-223.
Abstract:
Understanding the limits to generalizability of experimental evolutionary models.
Given the difficulty of testing evolutionary and ecological theory in situ, in vitro model systems are attractive alternatives; however, can we appraise whether an experimental result is particular to the in vitro model, and, if so, characterize the systems likely to behave differently and understand why? Here we examine these issues using the relationship between phenotypic diversity and resource input in the T7-Escherichia coli co-evolving system as a case history. We establish a mathematical model of this interaction, framed as one instance of a super-class of host-parasite co-evolutionary models, and show that it captures experimental results. By tuning this model, we then ask how diversity as a function of resource input could behave for alternative co-evolving partners (for example, E. coli with lambda bacteriophages). In contrast to populations lacking bacteriophages, variation in diversity with differences in resources is always found for co-evolving populations, supporting the geographic mosaic theory of co-evolution. The form of this variation is not, however, universal. Details of infectivity are pivotal: in T7-E. coli with a modified gene-for-gene interaction, diversity is low at high resource input, whereas, for matching-allele interactions, maximal diversity is found at high resource input. A combination of in vitro systems and appropriately configured mathematical models is an effective means to isolate results particular to the in vitro system, to characterize systems likely to behave differently and to understand the biology underpinning those alternatives.
Abstract.
Author URL.
2007
Gudelj I, Beardmore RE, Arkin SS, MacLean RC (2007). Constraints on microbial metabolism drive evolutionary diversification in homogeneous environments.
J Evol Biol,
20(5), 1882-1889.
Abstract:
Constraints on microbial metabolism drive evolutionary diversification in homogeneous environments.
Understanding the evolution of microbial diversity is an important and current problem in evolutionary ecology. In this paper, we investigated the role of two established biochemical trade-offs in microbial diversification using a model that connects ecological and evolutionary processes with fundamental aspects of biochemistry. The trade-offs that we investigated are as follows:(1) a trade-off between the rate and affinity of substrate transport; and (2) a trade-off between the rate and yield of ATP production. Our model shows that these biochemical trade-offs can drive evolutionary diversification under the simplest possible ecological conditions: a homogeneous environment containing a single limiting resource. We argue that the results of a number of microbial selection experiments are consistent with the predictions of our model.
Abstract.
Author URL.
2006
Gudelj I, Coman CD, Beardmore RE (2006). Classifying the role of trade-offs in the evolutionary diversity of pathogens.
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences,
462(2065), 97-116.
Abstract:
Classifying the role of trade-offs in the evolutionary diversity of pathogens
In this paper we use a system of non-local reaction-diffusion equations to study the effect of host heterogeneity on the phenotypic evolution of a pathogen population. The evolving phenotype is taken to be the transmission rate of the pathogen on the different hosts, and in our system there are two host populations present. The central feature of our model is a trade-off relationship between the transmission rates on these hosts, which means that an increase in the pathogen transmission on one host will lead to a decrease in the pathogen transmission on the other. The purpose of the paper is to develop a classification of phenotypic diversity as a function of the shape of the trade-off relationship and this is achieved by determining the maximum number of phenotypes a pathogen population can support in the long term, for a given form of the trade-off. Our findings are then compared with results obtained by applying classical theory from evolutionary ecology and the more recent adaptive dynamics method to the same host-pathogen system. We find our work to be in good agreement with these two approaches. © 2005 the Royal Society.
Abstract.
MacLean RC, Gudelj I (2006). Resource competition and social conflict in experimental populations of yeast.
Nature,
441(7092), 498-501.
Abstract:
Resource competition and social conflict in experimental populations of yeast.
Understanding the conditions that promote the maintenance of cooperation is a classic problem in evolutionary biology. The essence of this dilemma is captured by the 'tragedy of the commons': how can a group of individuals that exploit resources in a cooperative manner resist invasion by 'cheaters' who selfishly use common resources to maximize their individual reproduction at the expense of the group? Here, we investigate this conflict through experimental competitions between isogenic cheater and cooperator strains of yeast with alternative pathways of glucose metabolism, and by using mathematical models of microbial biochemistry. We show that both coexistence and competitive exclusion are possible outcomes of this conflict, depending on the spatial and temporal structure of the environment. Both of these outcomes are driven by trade-offs between the rate and efficiency of conversion of resources into offspring that are mediated by metabolic intermediates.
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Author URL.
2004
Gudelj I, Fitt BDL, van den Bosch F (2004). Evolution of sibling fungal plant pathogens in relation to host specialization.
Phytopathology,
94(7), 789-795.
Abstract:
Evolution of sibling fungal plant pathogens in relation to host specialization.
ABSTRACT Sibling plant pathogens can be grouped according to their host rangesthe following groups: group 1, sibling pathogens with nonoverlapping host ranges; group 2, sibling pathogens with both overlapping and nonoverlapping host ranges; and group 3, sibling pathogens with overlapping host ranges. Using the adaptive dynamics methodology, we investigated the evolution of sibling pathogens in relation to host specialization for groups 1 to 3. In particular, we focused on the role of multiple host niches and a trade-off in infectivity of pathogens to these hosts on the evolutionary outcome. We have shown that this ecological mechanism can explain only the evolution of sibling pathogens in group 1 and that other ecological and epidemiological mechanisms must be responsible for the evolution of sibling pathogens in the other two groups.
Abstract.
Author URL.
Gudelj I, White KAJ (2004). Spatial heterogeneity, social structure and disease dynamics of animal populations.
Theor Popul Biol,
66(2), 139-149.
Abstract:
Spatial heterogeneity, social structure and disease dynamics of animal populations.
Social groupings, population dynamics and population movements of animals all give rise to spatio-temporal variations in population levels. These variations may be of crucial importance when considering the spread of infectious diseases since infection levels do not increase unless there is a sufficient pool of susceptible individuals. This paper explores the impact of social groupings on the potential for an endemic disease to develop in a spatially explicit model system. Analysis of the model demonstrates that the explicit inclusion of space allows asymmetry between groups to arise when this was not possible in the equivalent spatially homogeneous system. Moreover, differences in movement behaviours for susceptible and infected individuals gives rise to different spatial profiles for the populations. These profiles were not observed in previous work on an epidemic system. The results are discussed in an ecological context with reference to furious and dumb strains of infectious diseases.
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Author URL.
Gudelj I, White KAJ, Britton NF (2004). The effects of spatial movement and group interactions on disease dynamics of social animals.
Bull Math Biol,
66(1), 91-108.
Abstract:
The effects of spatial movement and group interactions on disease dynamics of social animals.
The effects of spatial movements of infected and susceptible individuals on disease dynamics is not well understood. Empirical studies on the spatial spread of disease and behaviour of infected individuals are few and theoretical studies may be useful to explore different scenarios. Hence due to lack of detail in empirical studies, theoretical models have become necessary tools in investigating the disease influence in host-pathogen systems. In this paper we developed and analysed a spatially explicit model of two interacting social groups of animals of the same species. We investigated how the movement scenarios of susceptible and infected individuals together with the between-group contact parameter affect the survival rate of susceptible individuals in each group. This work can easily be applied to various host-pathogen systems. We define bounds on the number of susceptibles which avoid infection once the disease has died out as a function of the initial conditions and other model parameters. For example, once disease has passed through the populations, a larger diffusion coefficient for each group can result in higher population levels when there is no between-group interaction but in lower levels when there is between-group interaction. Numerical simulations are used to demonstrate these bounds and behaviours and to describe the different outcomes in ecological terms.
Abstract.
Author URL.
Gudelj I, van den Bosch F, Gilligan CA (2004). Transmission rates and adaptive evolution of pathogens in sympatric heterogeneous plant populations.
Proc Biol Sci,
271(1553), 2187-2194.
Abstract:
Transmission rates and adaptive evolution of pathogens in sympatric heterogeneous plant populations.
Diversification in agricultural cropping patterns is widely practised to delay the build-up of virulent races that can overcome host resistance in pathogen populations. This can lead to balanced polymorphism, but the long-term consequences of this strategy for the evolution of crop pathogen populations are still unclear. The widespread occurrence of sibling species and reproductively isolated sub-species among fungal and oomycete plant pathogens suggests that evolutionary divergence is common. This paper develops a mathematical model of host-pathogen interactions using a simple framework of two hosts to analyse the influences of sympatric host heterogeneity on the long-term evolutionary behaviour of plant pathogens. Using adaptive dynamics, which assumes that sequential mutations induce small changes in pathogen fitness, we show that evolutionary outcomes strongly depend on the shape of the trade-off curve between pathogen transmission on sympatric hosts. In particular, we determine the conditions under which the evolutionary branching of a monomorphic into a dimorphic population occurs, as well as the conditions that lead to the evolution of specialist (single host range) or generalist (multiple host range) pathogen populations.
Abstract.
Author URL.
2003
Beardmore I, Beardmore R (2003). The global structure of a spatial model of infectious disease.
Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences,
459(2034), 1427-1448.
Abstract:
The global structure of a spatial model of infectious disease
In this paper we study an SI model of infectious diseases that takes into account spatial inhomogeneities, resulting in a system of reaction-convection- diffusion equations on a bounded domain. The convection process is included to account for social interaction, as modelled by the location of a focal point or den where the population will tend to aggregate. We show that a vertical bifurcation of steady-state solutions occurs in this model when birth rate is taken as the bifurcation parameter, from which emanates a global secondary branch, which then bifurcates at infinity. Subsequently, we use singular perturbation techniques to give a description of the limiting spatial structure along this branch in large and small parameter limits. Finally, the results are illustrated numerically on some biologically relevant cases.
Abstract.
2001
Beardmore I, White KA (2001). Spreading disease through social groupings in competition.
J Theor Biol,
212(2), 253-269.
Abstract:
Spreading disease through social groupings in competition.
Many animal populations live in social groups which avoid contact with other conspecific groups for at least part of the year. This may give rise to competition between groups for items such as shelter, land and mates. We couple intra-specific group competition with disease dynamics to investigate how infectious diseases may spread through population subgroups, particularly with reference to the contact rates between groups. Our model uses a nonlinear systems of ODEs for which steady-state analysis is carried out in the simplest two-group system. This indicates that coexistence of social groups is possible with the disease or that competitive exclusion occurs with one group dying out whilst the other retains disease. Moreover, we show that in certain circumstances the model can exhibit multistability and we discuss the ecological implications of this result in relation to contact between social groups.
Abstract.
Author URL.
