scholarly journals Eco-evolutionary control of pathogens

2020 ◽  
Vol 117 (33) ◽  
pp. 19694-19704 ◽  
Author(s):  
Michael Lässig ◽  
Ville Mustonen
Keyword(s):  
Population Size ◽  
Evolutionary Dynamics ◽  
Control Strategies ◽  
Optimal Dosage ◽  
Antigen Binding ◽  
General Systems ◽  
Fitness Parameters ◽  
Pathogen Control ◽  
Carry Over ◽  
Evolutionary Control

Control can alter the eco-evolutionary dynamics of a target pathogen in two ways, by changing its population size and by directed evolution of new functions. Here, we develop a payoff model of eco-evolutionary control based on strategies of evolution, regulation, and computational forecasting. We apply this model to pathogen control by molecular antibody–antigen binding with a tunable dosage of antibodies. By analytical solution, we obtain optimal dosage protocols and establish a phase diagram with an error threshold delineating parameter regimes of successful and compromised control. The solution identifies few independently measurable fitness parameters that predict the outcome of control. Our analysis shows how optimal control strategies depend on mutation rate and population size of the pathogen, and how monitoring and computational forecasting affect protocols and efficiency of control. We argue that these results carry over to more general systems and are elements of an emerging eco-evolutionary control theory.

scholarly journals Eco-evolutionary control of pathogens

2019 ◽  
Author(s):  
Michael Lässig ◽  
Ville Mustonen
Keyword(s):  
Optimal Control ◽  
Population Size ◽  
Evolutionary Dynamics ◽  
Control Strategies ◽  
General Systems ◽  
Fitness Parameters ◽  
Pathogen Control ◽  
Successful Control ◽  
Carry Over ◽  
Evolutionary Control

AbstractControl can alter the eco-evolutionary dynamics of a target pathogen in two ways, by changing its population size and by directed evolution of new functions. Here we develop a fitness model of eco-evolutionary control that specifies a minimum leverage for successful control against the intrinsic dynamics of the pathogen. We apply this model to pathogen control by molecular antibody-antigen binding with a tunable level of antibodies. By analytical solution, we obtain a phase diagram of optimal control and show that an error threshold separates regimes of successful and futile control. Our analysis identifies few, independently measurable fitness parameters that predict the outcome of control. We show that optimal control strategies depend on mutation rate and population size of the pathogen, and we discuss how monitoring and computational forecasting affect the efficiency of control. We argue that these results carry over to more general systems and are elements of an emerging eco-evolutionary control theory.

Changes in migration, carry-over effects, and migratory connectivity

2019 ◽  
pp. 93-107 ◽  
Author(s):  
Roberto Ambrosini ◽  
Andrea Romano ◽  
Nicola Saino
Keyword(s):  
Climate Change ◽  
Life Cycle ◽  
Population Size ◽  
Migratory Connectivity ◽  
Negative Effects ◽  
Annual Life Cycle ◽  
Northern Latitudes ◽  
Timing Of Migration ◽  
Tropical Areas ◽  
Carry Over

Studies of the timing (phenology) of bird migration provided some of the first evidence for the effects of climate change on organisms. Since the rate of climate change is uneven across the globe, with northern latitudes experiencing faster warming trends than tropical areas, animals moving across latitudes are subject to diverging trends of climate change at different stages of their annual life cycle, and, consequently, they can become mistimed with the local ecological conditions, with potentially negative effects on population size. This chapter reviews the modifications induced by climate change in different migration traits, like the timing of migration events, the distribution of organisms, and the direction and the speed of movements. It also considers the effects of ecological carry-over effects and migratory connectivity on the response of birds to climate change.

scholarly journals Transmission and evolutionary dynamics of human coronavirus OC43 strains in coastal Kenya investigated by partial spike sequence analysis, 2015–16

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Carol A Abidha ◽  
Joyce Nyiro ◽  
Everlyn Kamau ◽  
Osman Abdullahi ◽  
David James Nokes ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Evolutionary Dynamics ◽  
Control Strategies ◽  
Respiratory Illness ◽  
Respiratory Pathogen ◽  
Human Coronavirus ◽  
Spike Gene ◽  
Low Genetic Diversity ◽  
Coastal Kenya ◽  
Close Phylogenetic Relationship

Abstract Human coronavirus OC43 (HCoV-OC43) is a major contributor to seasonal outbreaks of acute respiratory illness (ARI). The origins of locally circulating HCoV-OC43 strains and characteristics of their genetic diversity are unknown for most settings despite significance to effective HCoV control strategies. Between December 2015 and June 2016, we undertook ARI surveillance in coastal Kenya in nine outpatients and one inpatient health facility (HF). Ninety-two patient samples tested HCoV-OC43 positive and forty (43.5%) were successfully sequenced in spike (S) gene region (2,864 long, ∼70%). Phylogenetic analysis confirmed co-circulation of two distinct HCoV-OC43 clades that closely clustered with genotype G (n = 34, 85%) and genotype H (n = 6, 15%) reference strains. Local viruses within the same clade displayed low genetic diversity yielding identical sequences in multiple HF. Furthermore, the newly sequenced Kenyan viruses showed close phylogenetic relationship to other contemporaneous sampled strains (2015–16) including those originating from distant places (e.g. USA and China). Using a genetic similarity threshold of 99.1 per cent at nucleotide level, the HCoV-OC43 strains sampled globally between 1967 and 2019 fell into nine sequence clusters. Notably, some of these clusters appeared to have become extinct, or occurred only sporadically in a few geographical areas while others persisted globally for multiple years. In conclusion, we found that HCoV-OC43 strains spread rapidly both locally and across the globe with limited genetic evolution in the spike gene. Full-genome sequences that are spatio-temporally representative are required to advance understanding of the transmission pathways of this important human respiratory pathogen.

scholarly journals The population genetics of haplo-diploids and X-linked genes

1984 ◽  
Vol 44 (3) ◽  
pp. 321-341 ◽  
Author(s):  
P. J. Avery
Keyword(s):  
Population Genetics ◽  
Genetic Variability ◽  
Population Size ◽  
Effective Population Size ◽  
Disease Genes ◽  
Effective Population ◽  
Random Drift ◽  
Mutation Pressure ◽  
Electrophoretic Data ◽  
Fitness Parameters

SUMMARYFrom the available electrophoretic data, it is clear that haplodiploid insects have a much lower level of genetic variability than diploid insects, a difference that is only partially explained by the social structure of some haplodiploid species. The data comparing X-linked genes and autosomal genes in the same species is much more sparse and little can be inferred from it. This data is compared with theoretical analyses of X-linked genes and genes in haplodiploids. (The theoretical population genetics of X-linked genes and genes in haplodiploids are identical.) X-linked genes under directional selection will be lost or fixed more quickly than autosomal genes as selection acts more directly on X-linked genes and the effective population size is smaller. However, deleterious disease genes, maintained by mutation pressure, will give higher disease incidences at X-linked loci and hence rare mutants are easier to detect at X-linked loci. Considering the forces which can maintain balanced polymorphisms, there are much stronger restrictions on the fitness parameters at X-linked loci than at autosomal loci if genetic variability is to be maintained, and thus fewer polymorphic loci are to be expected on the X-chromosome and in haplodiploids. However, the mutation-random drift hypothesis also leads to the expectation of lower heterozygosity due to the decrease in effective population size. Thus the theoretical results fit in with the data but it is still subject to argument whether selection or mutation-random drift are maintaining most of the genetic variability at X-linked genes and genes in haplodiploids.

scholarly journals Testing the optimality properties of a dual antibiotic treatment in a two-locus, two-allele model

2014 ◽  
Vol 11 (96) ◽  
pp. 20131035 ◽  
Author(s):  
Rafael Peña-Miller ◽  
Ayari Fuentes-Hernandez ◽  
Carlos Reding ◽  
Ivana Gudelj ◽  
Robert Beardmore
Keyword(s):  
Evolutionary Dynamics ◽  
Control Strategies ◽  
Treatment Strategies ◽  
Heterogeneous Population ◽  
Antimicrobial Drugs ◽  
Population Structures ◽  
Optimality Properties ◽  
Allele Model ◽  
Antibiotic Combination

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.

scholarly journals How long do Red Queen dynamics survive under genetic drift? A comparative analysis of evolutionary and eco-evolutionary models

2018 ◽  
Author(s):  
Hanna Schenk ◽  
Hinrich Schulenburg ◽  
Arne Traulsen
Keyword(s):  
Population Size ◽  
Evolutionary Dynamics ◽  
Stochastic Dynamics ◽  
Extinction Time ◽  
Evolutionary Models ◽  
Red Queen ◽  
Fluctuating Selection ◽  
Ecological Dynamics ◽  
Theoretical Concepts ◽  
Fixed Population

AbstractBackgroundRed Queen dynamics are defined as long term co-evolutionary dynamics, often with oscillations of genotype abundances driven by fluctuating selection in host-parasite systems. Much of our current understanding of these dynamics is based on theoretical concepts explored in mathematical models that are mostly (i) deterministic, inferring an infinite population size and (ii) evolutionary, thus ecological interactions that change population sizes are excluded. Here, we recall the different mathematical approaches used in the current literature on Red Queen dynamics. We then compare models from game theory (evo) and classical theoretical ecology models (eco-evo), that are all derived from individual interactions and are thus intrinsically stochastic. We assess the influence of this stochasticity through the time to the first loss of a genotype within a host or parasite population.ResultsThe time until the first genotype is lost (“extinction time”), is shorter when ecological dynamics, in the form of a changing population size, is considered. Furthermore, when individuals compete only locally with other individuals extinction is even faster. On the other hand, evolutionary models with a fixed population size and competition on the scale of the whole population prolong extinction and therefore stabilise the oscillations. The stabilising properties of intraspecific competitions become stronger when population size is increased and the deterministic part of the dynamics gain influence. In general, the loss of genotype diversity can be counteracted with mutations (or recombination), which then allow the populations to recurrently undergo negative frequency-dependent selection dynamics and selective sweeps.ConclusionAlthough the models we investigated are equal in their biological motivation and interpretation, they have diverging mathematical properties both in the derived deterministic dynamics and the derived stochastic dynamics. We find that models that do not consider intraspecific competition and that include ecological dynamics by letting the population size vary, lose genotypes – and thus Red Queen oscillations – faster than models with competition and a fixed population size.

scholarly journals Besides stem canker severity, oilseed rape host genotype matters for the production of Leptosphaeria maculans fruiting bodies

2020 ◽  
Author(s):  
Lydia Bousset ◽  
Patrick Vallée ◽  
Régine Delourme ◽  
Nicolas Parisey ◽  
Marcellino Palerme ◽  
...  
Keyword(s):  
Oilseed Rape ◽  
Control Strategies ◽  
Leptosphaeria Maculans ◽  
Stem Canker ◽  
Major Effect ◽  
Automated Image Analysis ◽  
Fruiting Bodies ◽  
Host Genotype ◽  
Carry Over ◽  
Body Production

SummaryFor fungal cyclic epidemics on annual crops, the pathogen carry-over is an important step in designing disease control strategies. However, it remains particularly difficult to estimate and predict. Plant resistance affects the pathogen development within the epidemics but we lack data on the inter-annual transmission of inoculum. We addressed this question by considering Leptosphaeria maculans on 15 oilseed rape genotypes in field during 4 growing seasons. Stem canker severity of host genotypes was visually scored at harvest while the number of fruiting bodies produced on incubated stubble was quantified using an automated image analysis framework. Our results confirm that higher severity at harvest leads to higher fruiting body production and is significantly affected by host genotype and Nitrogen supply. Most interestingly, we show that the production of fruiting bodies is significantly and substantially affected by host genotype, independently of severity at harvest. Tracking individual stems through incubation, we confirm for the first time that the oilseed rape genotype has a direct effect, not only through disease severity. While the genericity of this finding should be investigated on other fungi, this major effect of genotype on inoculum carry-over should be taken into account in models of varietal deployment strategies.

Nonlinear incidence Human immunodeficiency virus infection model with optimal control

2020 ◽  
Vol 34 (11) ◽  
pp. 2050100
Author(s):  
David Yaro ◽  
Aly R. Seadawy ◽  
Dianchen Lu
Keyword(s):  
Optimal Control ◽  
Human Immunodeficiency Virus ◽  
Evolutionary Dynamics ◽  
Control Strategies ◽  
Cellular Level ◽  
Infection Model ◽  
Hiv Model ◽  
Immunodeficiency Virus ◽  
Infected Cells ◽  
Horizontal Spread

Mathematical modeling plays a crucial role in understanding the dynamics of Human immunodeficiency virus (HIV) disease. Most models deal with the vertical and horizontal spread of disease, but few studies have focused on the evolutionary dynamics of HIV at the cellular level. In this paper, we present an HIV model to analyze the dynamics of HIV infection at the cellular level to produce more natural results. We present a detailed stability analysis of disease-free and viral-persistence equilibrium in the system. In addition, sensitivity analysis and optimal control strategies are used to analyze the role of antiretroviral drug therapy and dietary supplements in controlling the concentration of infected cells and viruses.

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