Immune selection suppresses the emergence of drug resistance in malaria parasites but facilitates its spread

Although drug resistance in Plasmodium falciparum typically evolves in regions of low transmission, resistance spreads readily following introduction to regions with a heavier disease burden. This suggests that the origin and the spread of resistance are governed by different processes, and that high transmission intensity specifically impedes the origin. Factors associated with high transmission, such as highly immune hosts and competition within genetically diverse infections, are associated with suppression of resistant lineages within hosts. However, interactions between these factors have rarely been investigated and the specific relationship between adaptive immunity and selection for resistance has not been explored. Here, we developed a multiscale, agent-based model of Plasmodium parasites, hosts, and vectors to examine how host and parasite dynamics shape the evolution of resistance in populations with different transmission intensities. We found that selection for antigenic novelty (“immune selection”) suppressed the evolution of resistance in high transmission settings. We show that high levels of population immunity increased the strength of immune selection relative to selection for resistance. As a result, immune selection delayed the evolution of resistance in high transmission populations by allowing novel, sensitive lineages to remain in circulation at the expense of the spread of a resistant lineage. In contrast, in low transmission settings, we observed that resistant strains were able to sweep to high population prevalence without interference. Additionally, we found that the relationship between immune selection and resistance changed when resistance was widespread. Once resistance was common enough to be found on many antigenic backgrounds, immune selection stably maintained resistant parasites in the population by allowing them to proliferate, even in untreated hosts, when resistance was linked to a novel epitope. Our results suggest that immune selection plays a role in the global pattern of resistance evolution.

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Immune selection suppresses the emergence of drug resistance in malaria parasites but facilitates its spread

10.1101/2020.12.15.422843 ◽

2020 ◽

Author(s):

Alexander O B Whitlock ◽

Jonathan J Juliano ◽

Nicole Mideo

Keyword(s):

Drug Resistance ◽

Immune Selection ◽

Agent Based ◽

Low Transmission ◽

Resistance Evolution ◽

High Transmission ◽

Population Immunity ◽

Evolution Of Resistance ◽

Selection For ◽

The Relationship

Although drug resistance in Plasmodium falciparum typically evolves in regions of low transmission, resistance spreads readily following introduction to regions with a heavier disease burden. This suggests that the origin and the spread of resistance are governed by different processes, and that high transmission intensity specifically impedes the origin. Factors associated with high transmission, such as highly immune hosts and competition within genetically diverse infections, are associated with suppression of resistant lineages within hosts. However, interactions between these factors have rarely been investigated and the specific relationship between adaptive immunity and selection for resistance has not been explored. Here, we developed a multiscale, agent-based model of Plasmodium parasites, hosts, and vectors to examine how host and parasite dynamics shape the evolution of resistance in populations with different transmission intensities. We found that selection for antigenic novelty (“immune selection”) and within-host competition both suppressed the evolution of resistance in high transmission settings. We show that high levels of population immunity increased the strength of immune selection relative to selection for resistance. As a result, immune selection delayed the evolution of resistance in high transmission populations by allowing novel, sensitive lineages to remain in circulation at the expense of common, resistant lineages. In contrast, in low transmission populations, we observed that common, resistant strains were able to sweep to high population prevalence without interference. Additionally, we found that the relationship between immune selection and resistance changed when resistance was widespread in the population. Once resistance was common enough to be found on many antigenic backgrounds, immune selection stably maintained resistance in the population because resistance was able to proliferate, even in untreated hosts, when it was linked to a novel epitope. The results of our simulations demonstrate that immune selection plays a major role in observed dynamics of resistance evolution.

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Superinfection and the evolution of resistance to antimalarial drugs

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2012.1064 ◽

2012 ◽

Vol 279 (1743) ◽

pp. 3834-3842 ◽

Cited By ~ 21

Author(s):

Eili Y. Klein ◽

David L. Smith ◽

Ramanan Laxminarayan ◽

Simon Levin

Keyword(s):

Drug Resistance ◽

Plasmodium Falciparum ◽

General Theory ◽

Mathematical Models ◽

Random Sampling ◽

Transmission Rate ◽

Drug Resistant ◽

Antimalarial Drug Resistance ◽

Resistance Evolution ◽

Evolution Of Resistance

A major issue in the control of malaria is the evolution of drug resistance. Ecological theory has demonstrated that pathogen superinfection and the resulting within-host competition influences the evolution of specific traits. Individuals infected with Plasmodium falciparum are consistently infected by multiple parasites; however, while this probably alters the dynamics of resistance evolution, there are few robust mathematical models examining this issue. We developed a general theory for modelling the evolution of resistance with host superinfection and examine: (i) the effect of transmission intensity on the rate of resistance evolution; (ii) the importance of different biological costs of resistance; and (iii) the best measure of the frequency of resistance. We find that within-host competition retards the ability and slows the rate at which drug-resistant parasites invade, particularly as the transmission rate increases. We also find that biological costs of resistance that reduce transmission are less important than reductions in the duration of drug-resistant infections. Lastly, we find that random sampling of the population for resistant parasites is likely to significantly underestimate the frequency of resistance. Considering superinfection in mathematical models of antimalarial drug resistance may thus be important for generating accurate predictions of interventions to contain resistance.

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Evolution of drug resistance in HIV protease

BMC Bioinformatics ◽

10.1186/s12859-020-03825-7 ◽

2020 ◽

Vol 21 (S18) ◽

Author(s):

Dhara Shah ◽

Christopher Freas ◽

Irene T. Weber ◽

Robert W. Harrison

Keyword(s):

Drug Resistance ◽

Spanning Trees ◽

Experimental Studies ◽

Hiv Protease ◽

Computational Techniques ◽

Hiv Protease Inhibitors ◽

Phenotype Data ◽

The Face ◽

Evolution Of Resistance ◽

Selection For

Abstract Background Drug resistance is a critical problem limiting effective antiviral therapy for HIV/AIDS. Computational techniques for predicting drug resistance profiles from genomic data can accelerate the appropriate choice of therapy. These techniques can also be used to identify protease mutants for experimental studies of resistance and thereby assist in the development of next-generation therapies. Few studies, however, have assessed the evolution of resistance from genotype–phenotype data. Results The machine learning produced highly accurate and robust classification of resistance to HIV protease inhibitors. Genotype data were mapped to the enzyme structure and encoded using Delaunay triangulation. Estimates of evolutionary relationships, based on this encoding, and using Minimum Spanning Trees, showed clusters of mutations that closely resemble the wild type. These clusters appear to evolve uniquely to more resistant phenotypes. Conclusions Using the triangulation metric and spanning trees results in paths that are consistent with evolutionary theory. The majority of the paths show bifurcation, namely they switch once from non-resistant to resistant or from resistant to non-resistant. Paths that lose resistance almost uniformly have far lower levels of resistance than those which either gain resistance or are stable. This strongly suggests that selection for stability in the face of a rapid rate of mutation is as important as selection for resistance in retroviral systems.

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Challenging conventional wisdom on the evolution of resistance to multi-drug HIV treatment: Lessons from data and modeling

10.1101/807560 ◽

2019 ◽

Cited By ~ 3

Author(s):

Alison Feder ◽

Kristin Harper ◽

Pleuni S. Pennings

Keyword(s):

Drug Resistance ◽

Standard Of Care ◽

Compartment Model ◽

Antiretroviral Drugs ◽

Hiv Treatment ◽

Current Standard ◽

Hiv Drug Resistance ◽

Resistance Evolution ◽

Single Drug ◽

Evolution Of Resistance

AbstractUnder the current standard of care, individuals with HIV take three antiretroviral drugs simultaneously. Triple-drug combination therapies limit HIV drug resistance evolution, because viruses resistant to a subset of the cocktail are suppressed by the remainder of the drugs and should not complete replication and spread. Despite this, reanalysis of HIV genetic data shortly after triple drug therapies became available (1990s and 2000s) reveals ongoing drug resistance in patients on three-drug therapies. In disagreement with expected patterns of evolution in three-drug therapy-treated HIV populations, resistance usually evolves one mutation at a time in a semi-predictable order. We argue here that these surprising observations can be explained using a model that divides the human body into compartments (for example, the gut, lymph nodes and brain). If one drug reaches a compartment that the other two drugs cannot, this creates a single-drug compartment that can select for single-drug resistant viruses. Such viruses can potentially become resistant to additional drugs, if they migrate to another compartment where a second drug is present, and so on. In addition to a compartment model, for some drug combinations, an alternative model of time-heterogeneity due to short half-lives combined with sub-optimal adherence could also explain the observations. We discuss how these lessons from HIV drug resistance evolution may be useful for other systems.

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The path of least resistance: aggressive or moderate treatment?

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2014.0566 ◽

2014 ◽

Vol 281 (1794) ◽

pp. 20140566 ◽

Cited By ~ 54

Author(s):

Roger D. Kouyos ◽

C. Jessica E. Metcalf ◽

Ruthie Birger ◽

Eili Y. Klein ◽

Pia Abel zur Wiesch ◽

...

Keyword(s):

Drug Resistance ◽

Conceptual Framework ◽

Antimicrobial Chemotherapy ◽

Treatment Strategies ◽

Patient Treatment ◽

Drug Pressure ◽

Mortality And Morbidity ◽

High Drug ◽

Resistance Evolution ◽

Evolution Of Resistance

The evolution of resistance to antimicrobial chemotherapy is a major and growing cause of human mortality and morbidity. Comparatively little attention has been paid to how different patient treatment strategies shape the evolution of resistance. In particular, it is not clear whether treating individual patients aggressively with high drug dosages and long treatment durations, or moderately with low dosages and short durations can better prevent the evolution and spread of drug resistance. Here, we summarize the very limited available empirical evidence across different pathogens and provide a conceptual framework describing the information required to effectively manage drug pressure to minimize resistance evolution.

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The epidemiology and detectability of asymptomatic Plasmodium vivax and Plasmodium falciparum infections in low, moderate and high transmission settings in Ethiopia

Malaria Journal ◽

10.1186/s12936-021-03587-4 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Elifaged Hailemeskel ◽

Surafel K Tebeje ◽

Sinknesh W. Behaksra ◽

Girma Shumie ◽

Getasew Shitaye ◽

...

Keyword(s):

Plasmodium Falciparum ◽

Plasmodium Vivax ◽

Age Groups ◽

Diagnostic Tools ◽

Asymptomatic Malaria ◽

Rapid Diagnostics ◽

Cross Sectional ◽

Low Transmission ◽

High Transmission ◽

Study Sites

Abstract Background As countries move to malaria elimination, detecting and targeting asymptomatic malaria infections might be needed. Here, the epidemiology and detectability of asymptomatic Plasmodium falciparum and Plasmodium vivax infections were investigated in different transmission settings in Ethiopia. Method: A total of 1093 dried blood spot (DBS) samples were collected from afebrile and apparently healthy individuals across ten study sites in Ethiopia from 2016 to 2020. Of these, 862 were from community and 231 from school based cross-sectional surveys. Malaria infection status was determined by microscopy or rapid diagnostics tests (RDT) and 18S rRNA-based nested PCR (nPCR). The annual parasite index (API) was used to classify endemicity as low (API > 0 and < 5), moderate (API ≥ 5 and < 100) and high transmission (API ≥ 100) and detectability of infections was assessed in these settings. Results In community surveys, the overall prevalence of asymptomatic Plasmodium infections by microscopy/RDT, nPCR and all methods combined was 12.2% (105/860), 21.6% (183/846) and 24.1% (208/862), respectively. The proportion of nPCR positive infections that was detectable by microscopy/RDT was 48.7% (73/150) for P. falciparum and 4.6% (2/44) for P. vivax. Compared to low transmission settings, the likelihood of detecting infections by microscopy/RDT was increased in moderate (Adjusted odds ratio [AOR]: 3.4; 95% confidence interval [95% CI] 1.6–7.2, P = 0.002) and high endemic settings (AOR = 5.1; 95% CI 2.6–9.9, P < 0.001). After adjustment for site and correlation between observations from the same survey, the likelihood of detecting asymptomatic infections by microscopy/RDT (AOR per year increase = 0.95, 95% CI 0.9–1.0, P = 0.013) declined with age. Conclusions Conventional diagnostics missed nearly half of the asymptomatic Plasmodium reservoir detected by nPCR. The detectability of infections was particularly low in older age groups and low transmission settings. These findings highlight the need for sensitive diagnostic tools to detect the entire parasite reservoir and potential infection transmitters.

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Asymptomatic malaria and anaemia among pregnant women during high and low malaria transmission seasons in Burkina Faso: household-based cross-sectional surveys in Burkina Faso, 2013 and 2017

Malaria Journal ◽

10.1186/s12936-021-03703-4 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Toussaint Rouamba ◽

Sékou Samadoulougou ◽

Mady Ouédraogo ◽

Hervé Hien ◽

Halidou Tinto ◽

...

Keyword(s):

Burkina Faso ◽

Pregnant Women ◽

Malaria Transmission ◽

Asymptomatic Malaria ◽

Cross Sectional ◽

Transmission Season ◽

Low Transmission ◽

High Transmission ◽

Asymptomatic Carriage ◽

Low Malaria Transmission

Abstract Background Malaria in endemic countries is often asymptomatic during pregnancy, but it has substantial consequences for both the mother and her unborn baby. During pregnancy, anaemia is an important consequence of malaria infection. In Burkina Faso, the intensity of malaria varies according to the season, albeit the prevalence of malaria and anaemia as well as their risk factors, during high and low malaria transmission seasons is underexplored at the household level. Methods Data of 1751 pregnant women from October 2013 to March 2014 and 1931 pregnant women from April 2017 to June 2017 were drawn from two cross-sectional household surveys conducted in 24 health districts of Burkina Faso. Pregnant women were tested for malaria in their household after consenting. Asymptomatic carriage was defined as a positive result from malaria rapid diagnostic tests in the absence of clinical symptoms of malaria. Anaemia was defined as haemoglobin level less than 11 g/dL in the first and third trimester and less than 10.5 g/dL in the second trimester of pregnancy. Results Prevalence of asymptomatic malaria in pregnancy was estimated at 23.9% (95% CI 20.2–28.0) during the high transmission season (October–November) in 2013. During the low transmission season, it was 12.7% (95% CI 10.9–14.7) between December and March in 2013–2014 and halved (6.4%; 95% CI 5.3–7.6) between April and June 2017. Anaemia prevalence was estimated at 59.4% (95% CI 54.8–63.8) during the high transmission season in 2013. During the low transmission season, it was 50.6% (95% CI 47.7–53.4) between December and March 2013–2014 and 65.0% (95% CI 62.8–67.2) between April and June, 2017. Conclusion This study revealed that the prevalence of malaria asymptomatic carriage and anaemia among pregnant women at the community level remain high throughout the year. Thus, more efforts are needed to increase prevention measures such as IPTp–SP coverage in order to reduce anaemia and contribute to preventing low birth weight and poor pregnancy outcomes.

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The population genetics of drug resistance evolution in natural populations of viral, bacterial and eukaryotic pathogens

Molecular Ecology ◽

10.1111/mec.13474 ◽

2015 ◽

Vol 25 (1) ◽

pp. 42-66 ◽

Cited By ~ 24

Author(s):

Benjamin A. Wilson ◽

Nandita R. Garud ◽

Alison F. Feder ◽

Zoe J. Assaf ◽

Pleuni S. Pennings

Keyword(s):

Drug Resistance ◽

Population Genetics ◽

Natural Populations ◽

Resistance Evolution

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The role of masks in reducing the risk of new waves of COVID-19 in low transmission settings: a modeling study

10.1101/2020.09.02.20186742 ◽

2020 ◽

Cited By ~ 2

Author(s):

Robyn M Stuart ◽

Romesh G Abeysuriya ◽

Cliff C Kerr ◽

Dina Mistry ◽

Daniel J Klein ◽

...

Keyword(s):

Initial Conditions ◽

High Mobility ◽

Baseline Scenario ◽

New Wave ◽

Policy Environment ◽

Agent Based ◽

Low Transmission ◽

South Wales ◽

Community Transmission

Objectives: To evaluate the risk of a new wave of coronavirus disease 2019 (COVID-19) in a setting with ongoing low transmission, high mobility, and an effective test-and-trace system, under different assumptions about mask uptake. Design: We used a stochastic agent-based microsimulation model to create multiple simulations of possible epidemic trajectories that could eventuate over a five-week period following prolonged low levels of community transmission. Setting: We calibrated the model to the epidemiological and policy environment in New South Wales, Australia, at the end of August 2020. Participants: None Intervention: From September 1, 2020, we ran the stochastic model with the same initial conditions (i.e., those prevailing at August 31, 2020), and analyzed the outputs of the model to determine the probability of exceeding a given number of new diagnoses and active cases within five weeks, under three assumptions about future mask usage: a baseline scenario of 30% uptake, a scenario assuming no mask usage, and a scenario assuming mandatory mask usage with near-universal uptake (95%). Main outcome measure: Probability of exceeding a given number of new diagnoses and active cases within five weeks. Results: The policy environment at the end of August is sufficient to slow the rate of epidemic growth, but may not stop the epidemic from growing: we estimate a 20% chance that NSW will be diagnosing at least 50 new cases per day within five weeks from the date of this analysis. Mandatory mask usage would reduce this to 6-9%. Conclusions: Mandating the use of masks in community settings would significantly reduce the risk of epidemic resurgence.

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Agrichemicals boost the effects of antibiotics on antibiotic resistance evolution

10.7287/peerj.preprints.26925 ◽

2018 ◽

Author(s):

Brigitta Kurenbach ◽

Amy M Hill ◽

William Godsoe ◽

Sophie van Hamelsveld ◽

Jack A Heinemann

Keyword(s):

Antibiotic Resistance ◽

Acquired Resistance ◽

Genotypic Diversity ◽

Microbial Populations ◽

Phenotypic Variance ◽

Short Term ◽

Resistance Evolution ◽

Term Evolution ◽

Comprehensive Test ◽

Selection For

Antibiotic resistance is medicine’s climate change: caused by human activity, and resulting in more extreme outcomes. Resistance emerges in microbial populations when antibiotics act on phenotypic variance within the population. This can arise from either genotypic diversity (resulting from a mutation or horizontal gene transfer), or from ‘adaptive’ differences in gene expression due to environmental variation. Adaptive changes can increase fitness allowing bacteria to survive at higher concentrations of the antibiotic. They can also decrease fitness, potentially leading to selection for antibiotic resistance at lower concentrations. There are opportunities for other environmental stressors to promote antibiotic resistance in ways that are hard to predict using conventional assays. Exploiting our observation that commonly used herbicides can increase or decrease the minimum inhibitory concentration (MIC) of different antibiotics, we provide the first comprehensive test of the hypothesis that the rate of antibiotic resistance evolution under specified conditions can increase, regardless of whether a herbicide increases or decreases the antibiotic MIC. Short term evolution experiments were used for various herbicide and antibiotic combinations. We found conditions where acquired resistance arises more frequently regardless of whether the exogenous non-antibiotic agent increased or decreased antibiotic effectiveness. This “damned if you do/damned if you don’t” outcome suggests that the emergence of antibiotic resistance is exacerbated by additional environmental factors that influence competition between bacteria. Our work demonstrates that bacteria may acquire antibiotic resistance in the environment at rates substantially faster than predicted from laboratory conditions.

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