Rapid response to selection, competitive release and increased transmission potential of artesunate-selected Plasmodium chabaudi malaria parasites

Assessing fitness costs in malaria parasites: a comprehensive review and implications for drug resistance management

Artemisinin-based combination therapy (ACT) remains a broadly effective anti-malarial drug combination, but the emergence of resistance is threatening its effectiveness. Limiting the spread of these drug-resistant parasites and delaying the emergence of resistance in new areas are of high priority. Understanding the evolution of resistance relies on discerning the fitness costs and benefits associated with resistance mutations. If the cost associated with resistance in an untreated host is sufficiently large relative to the benefit of resistance in a treated host, then the spread of resistance can be mitigated by ensuring sufficient hosts free from that active pharmaceutical ingredient. There is no straightforward way to measure these fitness costs, and each approach that has been used has its limitations. Here, the evidence of fitness costs as measured using field data, animal models, and in vitro models is reviewed for three of the main current or past first-line treatments for malaria: chloroquine (CQ), sulfadoxine-pyrimethamine (SP), and artemisinin derivatives (ART). Despite the difficulties of assessing fitness costs, there is a good amount of evidence of fitness costs in drug-resistant Plasmodium falciparum parasites. The most persuasive evidence comes from resistance reversal observed following the cessation of the use of chloroquine. Comparable evidence cannot be obtained for SP- and ART-resistant parasites, due to the absence of complete cessation of these drugs in the field. Data from in vitro and animal models are variable. While fitness costs are often observed, their presence is not universal across all resistant strains. The extent and nature of these fitness costs can vary greatly depending on the specific genetic factors involved and the ecological context in which the parasites evolve. As a result, it is essential to avoid making broad generalizations about the prevalence or impact of fitness costs in drug-resistant malaria parasites. Focusing on fitness costs as a vulnerability in resistant parasites can guide their evolutionary trajectory towards minimizing their fitness. By accurately predicting these costs, efforts to extend the effectiveness of anti-malarials can be enhanced, limiting resistance evolution and advancing malaria control and elimination goals.

Modeling resistance to the broadly neutralizing antibody PGT121 in people living with HIV-1

PGT121 is a broadly neutralizing antibody in clinical development for the treatment and prevention of HIV-1 infection via passive administration. PGT121 targets the HIV-1 V3-glycan and demonstrated potent antiviral activity in a phase I clinical trial. Resistance to PGT121 monotherapy rapidly occurred in the majority of participants in this trial with the sampled rebound viruses being entirely resistant to PGT121 mediated neutralization. However, two individuals experienced long-term ART-free viral suppression following antibody infusion and retained sensitivity to PGT121 upon viral rebound. Here, we develop mathematical models of the HIV-1 dynamics during this phase I clinical trial. We utilize these models to understand the dynamics leading to PGT121 resistance and to identify the mechanisms driving the observed long-term viral control. Our modeling highlights the importance of the relative fitness difference between PGT121 sensitive and resistant subpopulations prior to treatment. Specifically, by fitting our models to data, we identify the treatment-induced competitive advantage of previously existing or newly generated resistant population as a primary driver of resistance. Finally, our modeling emphasizes the high neutralization ability of PGT121 in both participants who exhibited long-term viral control.

Evolution-Informed Strategies for Combating Drug Resistance in Cancer

The ever-changing nature of cancer poses the most difficult challenge oncologists face today. Cancer's remarkable adaptability has inspired many to work toward understanding the evolutionary dynamics that underlie this disease in hopes of learning new ways to fight it. Eco-evolutionary dynamics of a tumor are not accounted for in most standard treatment regimens, but exploiting them would help us combat treatment-resistant effectively. Here, we outline several notable efforts to exploit these dynamics and circumvent drug resistance in cancer.

Targeting malaria parasites inside mosquitoes: ecoevolutionary consequences

Proof-of-concept studies demonstrate that antimalarial drugs designed for human treatment can also be applied to mosquitoes to interrupt malaria transmission. Deploying a new control tool is ideally undertaken within a stewardship programme that maximises a drug's lifespan by minimising the risk of resistance evolution and slowing its spread once emerged. We ask: what are the epidemiological and evolutionary consequences of targeting parasites within mosquitoes? Our synthesis argues that targeting parasites inside mosquitoes (i) can be modelled by readily expanding existing epidemiological frameworks; (ii) provides a functionally novel control method that has potential to be more robust to resistance evolution than targeting parasites in humans; and (iii) could extend the lifespan and clinical benefit of antimalarials used exclusively to treat humans.

Measuring competitive exclusion in non-small cell lung cancer

In this study, we experimentally measure the frequency-dependent interactions between a gefitinib-resistant non-small cell lung cancer population and its sensitive ancestor via the evolutionary game assay. We show that cost of resistance is insufficient to accurately predict competitive exclusion and that frequency-dependent growth rate measurements are required. Using frequency-dependent growth rate data, we then show that gefitinib treatment results in competitive exclusion of the ancestor, while the absence of treatment results in a likely, but not guaranteed, exclusion of the resistant strain. Then, using simulations, we demonstrate that incorporating ecological growth effects can influence the predicted extinction time. In addition, we show that higher drug concentrations may not lead to the optimal reduction in tumor burden. Together, these results highlight the potential importance of frequency-dependent growth rate data for understanding competing populations, both in the laboratory and as we translate adaptive therapy regimens to the clinic.

Malaria transmission blocking compounds: a patent review

INTRODUCTION

Despite substantial progress in the field, malaria remains a global health issue and currently available control strategies are not sufficient to achieve eradication. Agents able to prevent transmission are likely to have a strong impact on malaria control and have been prioritized as a primary objective to reduce the number of secondary infections. Therefore, there is an increased interest in finding novel drugs targeting sexual stages of Plasmodium and innovative methods to target malaria transmission from host to vector, and vice versa.

AREAS COVERED

This review covers innovative transmission-blocking inventions patented between 2015 and October 2021. The focus is on chemical interventions which could be used as "chemical vaccines" to prevent transmission (small molecules, carbohydrates, and polypeptides).

EXPERT OPINION

Even though the development of novel strategies to block transmission still requires fundamental additional research and a deeper understanding of parasite sexual stages biology, the research in this field has significantly accelerated. Among innovative inventions patented over the last six years, the surface-delivery of antimalarial drugs to kill transmission-stages parasites in mosquitoes holds the highest promise for success in malaria control strategies, opening completely new scenarios in malaria transmission-blocking drug discovery.

The Antimalaria Drug Artesunate Inhibits Porcine Reproductive and Respiratory Syndrome Virus Replication via Activating AMPK and Nrf2/HO-1 Signaling Pathways

Porcine Reproductive and Respiratory Syndrome virus (PRRSV) causes significant economic losses to the pork industry worldwide. Currently, vaccine strategies provide limited protection against PRRSV transmission, and no effective drug is commercially available. Therefore, there is an urgent need to develop novel antiviral strategies to prevent PRRSV pandemics. This study showed that artesunate (AS), one of the antimalarial drugs, potently suppressed PRRSV replication in Marc-145 cells and ex vivo primary porcine alveolar macrophages (PAMs) at micromolar concentrations. Furthermore, we demonstrated that this suppression was closely associated with AS-activated AMPK (energy homeostasis) and Nrf2/HO-1 (inflammation) signaling pathways. AS treatment promoted p-AMPK, Nrf2 and HO-1 expression, and thus inhibited PRRSV replication in Marc-145 and PAM cells in a time- and dose-dependent manner. These effects of AS were reversed when AMPK or HO-1 gene was silenced by siRNA. In addition, we demonstrated that AMPK works upstream of Nrf2/HO-1 as its activation by AS is AMPK-dependent. Adenosine phosphate analysis showed that AS activates AMPK via improving AMP/ADP:ATP ratio rather than direct interaction with AMPK. Altogether, our findings indicate that AS could be a promising novel therapeutics for controlling PRRSV and that its anti-PRRSV mechanism, which involves the functional link between energy homeostasis and inflammation suppression pathways, may provide opportunities for developing novel antiviral agents. Importance Porcine reproductive and respiratory syndrome virus (PRRSV) infections have been continuously threatened the pork industry worldwide. Vaccination strategies provide very limited protection against PRRSV infection, and no effective drug is commercially available. We show that artesunate (AS), one of the antimalarial drugs, is a potent inhibitor against PRRSV replication in Marc-145 cells and ex vivo primary porcine alveolar macrophages (PAMs). Furthermore, we demonstrate that AS inhibits PRRSV replication via activation of AMPK-dependent Nrf2/HO-1 signaling pathways, revealing a novel link between energy homeostasis (AMPK) and inflammation suppression (Nrf2/HO-1) during viral infection. Therefore, we believe that AS may be a promising novel therapeutics for controlling PRRSV, and its anti-PRRSV mechanism may provide a potential strategy to develop novel antiviral agents.

Species interactions drive the spread of ampicillin resistance in human-associated gut microbiota

Background and objectives

Slowing the spread of antimicrobial resistance is urgent if we are to continue treating infectious diseases successfully. There is increasing evidence microbial interactions between and within species are significant drivers of resistance. On one hand, cross-protection by resistant genotypes can shelter susceptible microbes from the adverse effects of antibiotics, reducing the advantage of resistance. On the other hand, antibiotic-mediated killing of susceptible genotypes can alleviate competition and allow resistant strains to thrive (competitive release). Here, by observing interactions both within and between species in microbial communities sampled from humans, we investigate the potential role for cross-protection and competitive release in driving the spread of ampicillin resistance in the ubiquitous gut commensal and opportunistic pathogen Escherichia coli.

Methodology

Using anaerobic gut microcosms comprising E.coli embedded within gut microbiota sampled from humans, we tested for cross-protection and competitive release both within and between species in response to the clinically important beta-lactam antibiotic ampicillin.

Results

While cross-protection gave an advantage to antibiotic-susceptible E.coli in standard laboratory conditions (well-mixed LB medium), competitive release instead drove the spread of antibiotic-resistant E.coli in gut microcosms (ampicillin boosted growth of resistant bacteria in the presence of susceptible strains).

Conclusions and implications

Competition between resistant strains and other members of the gut microbiota can restrict the spread of ampicillin resistance. If antibiotic therapy alleviates competition with resident microbes by killing susceptible strains, as here, microbiota-based interventions that restore competition could be a key for slowing the spread of resistance.

Lay Summary

Slowing the spread of global antibiotic resistance is an urgent task. In this paper, we ask how interactions between microbial species drive the spread of resistance. We show that antibiotic killing of susceptible microbes can free up resources for resistant microbes and allow them to thrive. Therefore, we should consider microbes in light of their social interactions to understand the spread of resistance.

Antibiotic Breakdown by Susceptible Bacteria Enhances the Establishment of β-Lactam Resistant Mutants

For a better understanding of the evolution of antibiotic resistance, it is imperative to study the factors that determine the initial establishment of mutant resistance alleles. In addition to the antibiotic concentration, the establishment of resistance alleles may be affected by interactions with the surrounding susceptible cells from which they derive, for instance via the release of nutrients or removal of the antibiotic. Here, we investigate the effects of social interactions with surrounding susceptible cells on the establishment of Escherichia coli mutants with increasing β-lactamase activity (i.e., the capacity to hydrolyze β-lactam antibiotics) from single cells under the exposure of the antibiotic cefotaxime (CTX) on agar plates. We find that relatively susceptible cells, expressing a β-lactamase with very low antibiotic-hydrolyzing activity, increase the probability of mutant cells to survive and outgrow into colonies due to the active breakdown of the antibiotic. However, the rate of breakdown by the susceptible strain is much higher than expected based on its low enzymatic activity. A detailed theoretical model suggests that this observation may be explained by cell filamentation causing delayed lysis. While susceptible cells may hamper the spread of higher-resistant β-lactamase mutants at relatively high frequencies, our findings show that they promote their initial establishment.

Antimalarial Drug Resistance and Implications for the WHO Global Technical Strategy

PURPOSE OF REVIEW

Five years have passed since the World Health Organization released its Global Technical Strategy for Malaria (GTS). In that time, progress against malaria has plateaued. This review focuses on the implications of antimalarial drug resistance for the GTS and how interim progress in parasite genomics and antimalarial pharmacology offer a bulwark against it.

RECENT FINDINGS

For the first time, drug resistance-conferring genes have been identified and validated before their global expansion in malaria parasite populations. More efficient methods for their detection and elaboration have been developed, although low-density infections and polyclonality remain a nuisance to be solved. Clinical trials of alternative regimens for multidrug-resistant malaria have delivered promising results. New agents continue down the development pipeline, while a nascent infrastructure in sub-Saharan Africa for conducting phase I trials and trials of transmission-blocking agents has come to fruition after years of preparation.

SUMMARY

These and other developments can help inform the GTS as the world looks ahead to the next two decades of its implementation. To remain ahead of the threat that drug resistance poses, wider application of genomic-based surveillance and optimization of existing and forthcoming antimalarial drugs are essential.

Effect of drug dose and timing of treatment on the emergence of drug resistance in vivo in a malaria model

BACKGROUND AND OBJECTIVES

There is a significant interest in identifying clinically effective drug treatment regimens that minimize the de novo evolution of antimicrobial resistance in pathogen populations. However, in vivo studies that vary treatment regimens and directly measure drug resistance evolution are rare. Here, we experimentally investigate the role of drug dose and treatment timing on resistance evolution in an animal model.

METHODOLOGY

In a series of experiments, we measured the emergence of atovaquone-resistant mutants of Plasmodium chabaudi in laboratory mice, as a function of dose or timing of treatment (day post-infection) with the antimalarial drug atovaquone.

RESULTS

The likelihood of high-level resistance emergence increased with atovaquone dose. When varying the timing of treatment, treating either very early or late in infection reduced the risk of resistance. When we varied starting inoculum, resistance was more likely at intermediate inoculum sizes, which correlated with the largest population sizes at time of treatment.

CONCLUSIONS AND IMPLICATIONS

(i) Higher doses do not always minimize resistance emergence and can promote the emergence of high-level resistance. (ii) Altering treatment timing affects the risk of resistance emergence, likely due to the size of the population at the time of treatment, although we did not test the effect of immunity whose influence may have been important in the case of late treatment. (iii) Finding the 'right' dose and 'right' time to maximize clinical gains and limit resistance emergence can vary depending on biological context and was non-trivial even in our simplified experiments.

LAY SUMMARY

In a mouse model of malaria, higher drug doses led to increases in drug resistance. The timing of drug treatment also impacted resistance emergence, likely due to the size of the population at the time of treatment.

Antibiotics can be used to contain drug-resistant bacteria by maintaining sufficiently large sensitive populations

Standard infectious disease practice calls for aggressive drug treatment that rapidly eliminates the pathogen population before resistance can emerge. When resistance is absent, this elimination strategy can lead to complete cure. However, when resistance is already present, removing drug-sensitive cells as quickly as possible removes competitive barriers that may slow the growth of resistant cells. In contrast to the elimination strategy, a containment strategy aims to maintain the maximum tolerable number of pathogens, exploiting competitive suppression to achieve chronic control. Here, we combine in vitro experiments in computer-controlled bioreactors with mathematical modeling to investigate whether containment strategies can delay failure of antibiotic treatment regimens. To do so, we measured the "escape time" required for drug-resistant Escherichia coli populations to eclipse a threshold density maintained by adaptive antibiotic dosing. Populations containing only resistant cells rapidly escape the threshold density, but we found that matched resistant populations that also contain the maximum possible number of sensitive cells could be contained for significantly longer. The increase in escape time occurs only when the threshold density-the acceptable bacterial burden-is sufficiently high, an effect that mathematical models attribute to increased competition. The findings provide decisive experimental confirmation that maintaining the maximum number of sensitive cells can be used to contain resistance when the size of the population is sufficiently large.

Pairwise growth competitions identify relative fitness relationships among artemisinin resistant Plasmodium falciparum field isolates

Background

Competitive outcomes between co-infecting malaria parasite lines can reveal fitness disparities in blood stage growth. Blood stage fitness costs often accompany the evolution of drug resistance, with the expectation that relatively fitter parasites will be more likely to spread in populations. With the recent emergence of artemisinin resistance, it is important to understand the relative competitive fitness of the metabolically active asexual blood stage parasites. Genetically distinct drug resistant parasite clones with independently evolved sets of mutations are likely to vary in asexual proliferation rate, contributing to their chance of transmission to the mosquito vector.

Methods

An optimized in vitro 96-well plate-based protocol was used to quantitatively measure-head-to-head competitive fitness during blood stage development between seven genetically distinct field isolates from a hotspot of emerging artemisinin resistance and the laboratory strain, NF54. These field isolates were isolated from patients in Southeast Asia carrying different alleles of kelch13 and included both artemisinin-sensitive and artemisinin-resistant isolates. Fluorescent labeled microsatellite markers were used to track the relative densities of each parasite throughout the co-growth period of 14–60 days. All-on-all competitions were conducted for the panel of eight parasite lines (28 pairwise competitions) to determine their quantitative competitive fitness relationships.

Results

Twenty-eight pairwise competitive growth outcomes allowed for an unambiguous ranking among a set of seven genetically distinct parasite lines isolated from patients in Southeast Asia displaying a range of both kelch13 alleles and clinical clearance times and a laboratory strain, NF54. This comprehensive series of assays established the growth relationships among the eight parasite lines. Interestingly, a clinically artemisinin resistant parasite line that carries the wild-type form of kelch13 outcompeted all other parasites in this study. Furthermore, a kelch13 mutant line (E252Q) was competitively more fit without drug than lines with other resistance-associated kelch13 alleles, including the C580Y allele that has expanded to high frequencies under drug pressure in Southeast Asian resistant populations.

Conclusions

This optimized competitive growth assay can be employed for assessment of relative growth as an index of fitness during the asexual blood stage growth between natural lines carrying different genetic variants associated with artemisinin resistance. Improved understanding of the fitness costs of different parasites proliferating in human blood and the role different resistance mutations play in the context of specific genetic backgrounds will contribute to an understanding of the potential for specific mutations to spread in populations, with the potential to inform targeted strategies for malaria therapy.

Aggressive or moderate drug therapy for infectious diseases? Trade-offs between different treatment goals at the individual and population levels

Antimicrobial resistance is one of the major public health threats of the 21st century. There is a pressing need to adopt more efficient treatment strategies in order to prevent the emergence and spread of resistant strains. The common approach is to treat patients with high drug doses, both to clear the infection quickly and to reduce the risk of de novo resistance. Recently, several studies have argued that, at least in some cases, low-dose treatments could be more suitable to reduce the within-host emergence of antimicrobial resistance. However, the choice of a drug dose may have consequences at the population level, which has received little attention so far. Here, we study the influence of the drug dose on resistance and disease management at the host and population levels. We develop a nested two-strain model and unravel trade-offs in treatment benefits between an individual and the community. We use several measures to evaluate the benefits of any dose choice. Two measures focus on the emergence of resistance, at the host level and at the population level. The other two focus on the overall treatment success: the outbreak probability and the disease burden. We find that different measures can suggest different dosing strategies. In particular, we identify situations where low doses minimize the risk of emergence of resistance at the individual level, while high or intermediate doses prove most beneficial to improve the treatment efficiency or even to reduce the risk of resistance in the population.

Community interactions and spatial structure shape selection on antibiotic resistant lineages

Polymicrobial interactions play an important role in shaping the outcome of antibiotic treatment, yet how multispecies communities respond to antibiotic assault is still little understood. Here we use an individual-based simulation model of microbial biofilms to investigate how competitive and mutualistic interactions between an antibiotic-resistant and a susceptible strain (or species) influence the two-lineage community response to antibiotic exposure. Our model predicts that while increasing competition and antibiotics leads to increasing competitive release of the antibiotic-resistant strain, hitting a mutualistic community of cross-feeding species with antibiotics leads to a mutualistic suppression effect where both susceptible and resistant species are harmed. We next show that the impact of antibiotics is further governed by emergent spatial feedbacks within communities. Mutualistic cross-feeding communities can rescue susceptible members by subsidizing their growth inside the biofilm despite lack of access to the nutrient-rich and high-antibiotic growing front. Moreover, we show that antibiotic detoxification by resistant cells can protect nearby susceptible cells, but such cross-protection is more effective in mutualistic communities because mutualism drives mixing of resistant and susceptible cells. In contrast, competition leads to segregation, which ultimately prevents susceptible cells to profit from detoxification. Understanding how the interplay between microbial metabolic interactions and community spatial structuring shapes the outcome of antibiotic treatment can be key to effectively leverage the power of antibiotics and promote microbiome health.

Pathogens -microorganisms that make us sick- often live within dynamic and complex multispecies communities, where they may not only compete for limiting resources but also exchange beneficial resources or services with other resident species. While antibiotics are commonly used to get rid of such harmful microbes, the community-wide effects of antibiotic treatment and its consequences for antibiotic resistance are still not well understood. How do competitive or mutually beneficial interactions between antibiotic resistant and susceptible species influence community resistance to antibiotics? Here we investigate this question using a computational model. We find that antibiotic exposure favours the resistant lineage when resistant and susceptible strains are competitors but harms both types when they are mutualists. With antibiotic-detoxifying resistant cells, cross-protection of susceptible cells is more effective in mutualistic communities because mutualism drives mixing of susceptible and resistant cells. In contrast, competition leads to their segregation, precluding susceptible cells to profit from their competitor’s local detoxification. Our findings highlight that knowing not only what species are present but also how they interact with each other and arrange themselves in space is central to understanding antibiotic resistance and to informing the development of strategies that promote microbiome health.

A nutrient mediates intraspecific competition between rodent malaria parasites in vivo

Hosts are often infected with multiple strains of a single parasite species. Within-host competition between parasite strains can be intense and has implications for the evolution of traits that impact patient health, such as drug resistance and virulence. Yet the mechanistic basis of within-host competition is poorly understood. Here, we demonstrate that a parasite nutrient, para-aminobenzoic acid (pABA), mediates competition between a drug resistant and drug susceptible strain of the malaria parasite, Plasmodium chabaudi. We further show that increasing pABA supply to hosts infected with the resistant strain worsens disease and changes the relationship between parasite burden and pathology. Our experiments demonstrate that, even when there is profound top-down regulation (immunity), bottom-up regulation of pathogen populations can occur and that its importance may vary during an infection. The identification of resources that can be experimentally controlled opens up the opportunity to manipulate competitive interactions between parasites and hence their evolution.

Fitness estimates from experimental infections predict the long-term strain structure of a vector-borne pathogen in the field

The populations of many pathogen species consist of a collection of common and rare strains but the factors underlying this strain-specific variation in frequency are often unknown. Understanding frequency variation among strains is particularly challenging for vector-borne pathogens where the strain-specific fitness depends on the performance in both the vertebrate host and the arthropod vector. Two sympatric multiple-strain tick-borne pathogens, Borrelia afzelii and B. garinii, that use the same tick vector, Ixodes ricinus, but different vertebrate hosts were studied. 454-sequencing of the polymorphic ospC gene was used to characterize the community of Borrelia strains in a local population of I. ricinus ticks over a period of 11 years. Estimates of the reproduction number (R0), a measure of fitness, were obtained for six strains of B. afzelii from a previous laboratory study. There was substantial variation in prevalence among strains and some strains were consistently common whereas other strains were consistently rare. In B. afzelii, the strain-specific estimates of R0 in laboratory mice explained over 70% of the variation in the prevalences of the strains in our local population of ticks. Our study shows that laboratory estimates of fitness can predict the community structure of multiple-strain pathogens in the field.

Facilitation through altered resource availability in a mixed-species rodent malaria infection

A major challenge in disease ecology is to understand how co-infecting parasite species interact. We manipulate in vivo resources and immunity to explain interactions between two rodent malaria parasites, Plasmodium chabaudi and P. yoelii. These species have analogous resource-use strategies to the human parasites Plasmodium falciparum and P. vivax: P. chabaudi and P. falciparum infect red blood cells (RBC) of all ages (RBC generalist); P. yoelii and P. vivax preferentially infect young RBCs (RBC specialist). We find that: (1) recent infection with the RBC generalist facilitates the RBC specialist (P. yoelii density is enhanced ~10 fold). This occurs because the RBC generalist increases availability of the RBC specialist's preferred resource; (2) co-infections with the RBC generalist and RBC specialist are highly virulent; (3) and the presence of an RBC generalist in a host population can increase the prevalence of an RBC specialist. Thus, we show that resources shape how parasite species interact and have epidemiological consequences.

Within-host competition and drug resistance in the human malaria parasite Plasmodium falciparum

Infections with the malaria parasite Plasmodium falciparum typically comprise multiple strains, especially in high-transmission areas where infectious mosquito bites occur frequently. However, little is known about the dynamics of mixed-strain infections, particularly whether strains sharing a host compete or grow independently. Competition between drug-sensitive and drug-resistant strains, if it occurs, could be a crucial determinant of the spread of resistance. We analysed 1341 P. falciparum infections in children from Angola, Ghana and Tanzania and found compelling evidence for competition in mixed-strain infections: overall parasite density did not increase with additional strains, and densities of individual chloroquine-sensitive (CQS) and chloroquine-resistant (CQR) strains were reduced in the presence of competitors. We also found that CQR strains exhibited low densities compared with CQS strains (in the absence of chloroquine), which may underlie observed declines of chloroquine resistance in many countries following retirement of chloroquine as a first-line therapy. Our observations support a key role for within-host competition in the evolution of drug-resistant malaria. Malaria control and resistance-management efforts in high-transmission regions may be significantly aided or hindered by the effects of competition in mixed-strain infections. Consideration of within-host dynamics may spur development of novel strategies to minimize resistance while maximizing the benefits of control measures.

Does High-Dose Antimicrobial Chemotherapy Prevent the Evolution of Resistance?

High-dose chemotherapy has long been advocated as a means of controlling drug resistance in infectious diseases but recent empirical studies have begun to challenge this view. We develop a very general framework for modeling and understanding resistance emergence based on principles from evolutionary biology. We use this framework to show how high-dose chemotherapy engenders opposing evolutionary processes involving the mutational input of resistant strains and their release from ecological competition. Whether such therapy provides the best approach for controlling resistance therefore depends on the relative strengths of these processes. These opposing processes typically lead to a unimodal relationship between drug pressure and resistance emergence. As a result, the optimal drug dose lies at either end of the therapeutic window of clinically acceptable concentrations. We illustrate our findings with a simple model that shows how a seemingly minor change in parameter values can alter the outcome from one where high-dose chemotherapy is optimal to one where using the smallest clinically effective dose is best. A review of the available empirical evidence provides broad support for these general conclusions. Our analysis opens up treatment options not currently considered as resistance management strategies, and it also simplifies the experiments required to determine the drug doses which best retard resistance emergence in patients.

The evolution of antimicrobial resistant pathogens threatens much of modern medicine. For over one hundred years, the advice has been to ‘hit hard’, in the belief that high doses of antimicrobials best contain resistance evolution. We argue that nothing in evolutionary theory supports this as a good rule of thumb in the situations that challenge medicine. We show instead that the only generality is to either use the highest tolerable drug dose or the lowest clinically effective dose; that is, one of the two edges of the therapeutic window. This approach suggests treatment options not currently considered, and simplifies the experiments required to identify the dose that best retards resistance evolution.

How competition governs whether moderate or aggressive treatment minimizes antibiotic resistance

Understanding how our use of antimicrobial drugs shapes future levels of drug resistance is crucial. Recently, there has been debate over whether an aggressive (i.e., high dose) or more moderate (i.e., lower dose) treatment of individuals will most limit the emergence and spread of resistant bacteria. In this study, we demonstrate how one can understand and resolve these apparently contradictory conclusions. We show that a key determinant of which treatment strategy will perform best at the individual level is the extent of effective competition between resistant and sensitive pathogens within a host. We extend our analysis to the community level, exploring the spectrum between strict inter-strain competition and strain independence. From this perspective as well, we find that the magnitude of effective competition between resistant and sensitive strains determines whether an aggressive approach or moderate approach minimizes the burden of resistance in the population.

DOI:http://dx.doi.org/10.7554/eLife.10559.001

Antibiotics are chemical compounds used to treat bacterial infections. The discovery of antibiotics, starting with penicillin in 1929, revolutionized medicine, making it possible to cure or prevent life-threatening infections such as tetanus and pneumonia. However, many bacteria have become resistant to one or more antibiotics and so can no longer be killed by these drugs.

The emergence of antibiotic resistance reflects an evolutionary process that occurs during antibiotic treatment. While the antibiotic will kill most bacteria, some bacteria may naturally have a feature or genetic mutation that allows them to survive in the presence of the antibiotic. These bacteria then reproduce and pass on their resistant traits, eventually leading to the emergence of a new antibiotic-resistant strain of bacteria. Once a resistant strain exists it may be able to spread from one person to another.

There is conflicting evidence about how best to prevent antibiotic-resistant bacteria from evolving and spreading. The results of some experiments suggest that treating bacteria with large doses of antibiotics early in an infection is the most effective way to optimize treatment and minimize the risk of an antibiotic-resistant strain developing. However, other studies suggest that exposing bacteria to high levels of antibiotics more efficiently selects for resistance; in this case a more moderate approach should be used when treating bacterial infections.

Here, Colijn and Cohen present a mathematical model that suggests that the natural competition between the antibiotic-resistant and antibiotic-sensitive strains of bacteria influence which treatment strategy should be taken. Strains were modeled both within individual hosts and spreading in a community of individuals. In the models, aggressive antibiotic treatment is most effective (in that it minimizes antibiotic resistance) when the antibiotic-resistant strain either does not experience strong competition from the non-resistant strains of bacteria or is not fit enough to be a good competitor. However, a more moderate treatment is appropriate when the two strains are competing and the antibiotic-resistant strain is a fit competitor. Competition may mean that moderate treatment is best to avoid resistance at the community level, even in situations when aggressive treatment is likely best for individuals.

Two important future challenges are to better understand the diversity of strains in bacterial infections, and to develop tools to measure to what extent strains are effectively competing with each other.

DOI:http://dx.doi.org/10.7554/eLife.10559.002

Existing Infection Facilitates Establishment and Density of Malaria Parasites in Their Mosquito Vector

Very little is known about how vector-borne pathogens interact within their vector and how this impacts transmission. Here we show that mosquitoes can accumulate mixed strain malaria infections after feeding on multiple hosts. We found that parasites have a greater chance of establishing and reach higher densities if another strain is already present in a mosquito. Mixed infections contained more parasites but these larger populations did not have a detectable impact on vector survival. Together these results suggest that mosquitoes taking multiple infective bites may disproportionally contribute to malaria transmission. This will increase rates of mixed infections in vertebrate hosts, with implications for the evolution of parasite virulence and the spread of drug-resistant strains. Moreover, control measures that reduce parasite prevalence in vertebrate hosts will reduce the likelihood of mosquitoes taking multiple infective feeds, and thus disproportionally reduce transmission. More generally, our study shows that the types of strain interactions detected in vertebrate hosts cannot necessarily be extrapolated to vectors.

The potential impact of coinfection on antimicrobial chemotherapy and drug resistance

Across a range of pathogens, resistance to chemotherapy is a growing problem in both public health and animal health. Despite the ubiquity of coinfection, and its potential effects on within-host biology, the role played by coinfecting pathogens on the evolution of resistance and efficacy of antimicrobial chemotherapy is rarely considered. In this review, we provide an overview of the mechanisms of interaction of coinfecting pathogens, ranging from immune modulation and resource modulation, to drug interactions. We discuss their potential implications for the evolution of resistance, providing evidence in the rare cases where it is available. Overall, our review indicates that the impact of coinfection has the potential to be considerable, suggesting that this should be taken into account when designing antimicrobial drug treatments.

Understanding genetic variation in in vivo tolerance to artesunate: implications for treatment efficacy and resistance monitoring

Artemisinin-based drugs are the front-line weapon in the treatment of human malaria cases, but there is concern that recent reports of slow clearing infections may signal developing resistance to treatment. In the absence of molecular markers for resistance, current efforts to monitor drug efficacy are based on the rate at which parasites are cleared from infections. However, some knowledge of the standing variation in parasite susceptibility is needed to identify a meaningful increase in infection half-life. Here, we show that five previously unexposed genotypes of the rodent malaria parasite Plasmodium chabaudi differ substantially in their in vivo response to treatment. Slower clearance rates were not linked to parasite virulence or growth rate, going against the suggestion that drug treatment will drive the evolution of virulence in this system. The level of variation observed here in a relatively small number of genotypes suggests existing ‘resistant’ parasites could be present in the population and therefore, increased parasite clearance rates could represent selection on pre-existing variation rather than de novo resistance events. This has implications for resistance monitoring as susceptibility may depend on evolved traits unrelated to drug exposure.