Is selection relevant in the evolutionary emergence of drug resistance?

Suppressive drug combinations and their potential to combat antibiotic resistance

Antibiotic effectiveness often changes when two or more such drugs are administered simultaneously and unearthing antibiotic combinations with enhanced efficacy (synergy) has been a longstanding clinical goal. However, antibiotic resistance, which undermines individual drugs, threatens such combined treatments. Remarkably, it has emerged that antibiotic combinations whose combined effect is lower than that of at least one of the individual drugs can slow or even reverse the evolution of resistance. We synthesize and review studies of such so-called 'suppressive interactions' in the literature. We examine why these interactions have been largely disregarded in the past, the strategies used to identify them, their mechanistic basis, demonstrations of their potential to reverse the evolution of resistance and arguments for and against using them in clinical treatment. We suggest future directions for research on these interactions, aiming to expand the basic body of knowledge on suppression and to determine the applicability of suppressive interactions in the clinic.

Phagocytes, Antibiotics, and Self-Limiting Bacterial Infections

Most antibiotic use in humans is to reduce the magnitude and term of morbidity of acute, community-acquired infections in immune competent patients, rather than to save lives. Thanks to phagocytic leucocytes and other host defenses, the vast majority of these infections are self-limiting. Nevertheless, there has been a negligible amount of consideration of the contribution of phagocytosis and other host defenses in the research for, and the design of, antibiotic treatment regimens, which hyper-emphasizes antibiotics as if they were the sole mechanism responsible for the clearance of infections. Here, we critically review this approach and its limitations. With the aid of a heuristic mathematical model, we postulate that if the rate of phagocytosis is great enough, for acute, normally self-limiting infections, then (i) antibiotics with different pharmacodynamic properties would be similarly effective, (ii) low doses of antibiotics can be as effective as high doses, and (iii) neither phenotypic nor inherited antibiotic resistance generated during therapy are likely to lead to treatment failure.

How to Use a Chemotherapeutic Agent When Resistance to It Threatens the Patient

When resistance to anticancer or antimicrobial drugs evolves in a patient, highly effective chemotherapy can fail, threatening patient health and lifespan. Standard practice is to treat aggressively, effectively eliminating drug-sensitive target cells as quickly as possible. This prevents sensitive cells from acquiring resistance de novo but also eliminates populations that can competitively suppress resistant populations. Here we analyse that evolutionary trade-off and consider recent suggestions that treatment regimens aimed at containing rather than eliminating tumours or infections might more effectively delay the emergence of resistance. Our general mathematical analysis shows that there are situations in which regimens aimed at containment will outperform standard practice even if there is no fitness cost of resistance, and, in those cases, the time to treatment failure can be more than doubled. But, there are also situations in which containment will make a bad prognosis worse. Our analysis identifies thresholds that define these situations and thus can guide treatment decisions. The analysis also suggests a variety of interventions that could be used in conjunction with cytotoxic drugs to inhibit the emergence of resistance. Fundamental principles determine, across a wide range of disease settings, the circumstances under which standard practice best delays resistance emergence-and when it can be bettered.

Harnessing Intra-Host Strain Competition to Limit Antibiotic Resistance: Mathematical Model Results

Antibiotic overuse has promoted the spread of antibiotic resistance. To compound the issue, treating individuals dually infected with antibiotic-resistant and antibiotic-vulnerable strains can make their infections completely resistant through competitive release. We formulate mathematical models of transmission dynamics accounting for dual infections and extensions accounting for lag times between infection and treatment or between cure and ending treatment. Analysis using the Next-Generation Matrix reveals how competition within hosts and the costs of resistance determine whether vulnerable and resistant strains persist, coexist, or drive each other to extinction. Invasion analysis predicts that treatment of dually infected cases will promote resistance. By varying antibiotic strength, the models suggest that physicians have two ways to achieve a particular resistance target: prescribe relatively weak antibiotics to everyone infected with an antibiotic-vulnerable strain or give more potent prescriptions to only those patients singly infected with the vulnerable strain after ruling out the possibility of them being dually infected with resistance. Through selectivity and moderation in antibiotic prescription, resistance might be limited.

The application of evolutionary medicine principles for sustainable malaria control: a scoping study

Background

Current interventions against malaria have significantly reduced the number of people infected and the number of deaths. Concerns about emerging resistance of both mosquitoes and parasites to intervention have been raised, and questions remain about how best to generate wider knowledge of the underlying evolutionary processes. The pedagogical and research principles of evolutionary medicine may provide an answer to this problem.

Methods

Eight programme managers and five academic researchers were interviewed by telephone or videoconference to elicit their first-hand views and experiences of malaria control given that evolution is a constant threat to sustainable control. Interviewees were asked about their views on the relationship between practit groups and academics and for their thoughts on whether or not evolutionary medicine may provide a solution to reported tensions.

Results

There was broad agreement that evolution of both parasites and vectors presents an obstacle to sustainable control. It was also widely agreed that through more efficient monitoring, evolution could be widely monitored. Interviewees also expressed the view that even well planned interventions may fail if the evolutionary biology of the disease is not considered, potentially making current tools redundant.

Conclusions

This scoping study suggests that it is important to make research, including evolutionary principles, available and easily applicable for programme managers and key decision-makers, including donors and politicians. The main conclusion is that sharing knowledge through the educational and research processes embedded within evolutionary medicine has potential to relieve tensions and facilitate sustainable control of malaria and other parasitic infections.

Electronic supplementary material

The online version of this article (doi:10.1186/s12936-016-1446-8) contains supplementary material, which is available to authorized users.

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.

Diversity and Evolution of the Tn5801-tet(M)-Like Integrative and Conjugative Elements among Enterococcus, Streptococcus, and Staphylococcus

This work describes the diversity and evolution of Tn5801 among enterococci, staphylococci, and streptococci based on analysis of the 5,073 genomes of these bacterial groups available in gene databases. We also examined 610 isolates of Enterococcus (from 10 countries, 1987 to 2010) for the presence of this and other known CTn-tet(M) elements due to the scarcity of data about Tn5801 among enterococci. Genome location (by ICeu-I-pulsed-field gel electrophoresis [PFGE] hybridization/integration site identification), conjugation and fitness (by standard methods), Tn5801 characterization (by long-PCR mapping/sequencing), and clonality (by PFGE/multilocus sequence typing [MLST]) were studied. Twenty-three Tn5801 variants (17 unpublished) clustered in two groups, designated "A" (25 kb; n = 14; predominant in Staphylococcus aureus) and "B" (20 kb; n = 9; predominant in Streptococcus agalactiae). The percent GC content of the common backbone suggests a streptococcal origin of Tn5801 group B, with further acquisition of a 5-kb fragment that resulted in group A. Deep sequence analysis allowed identification of variants associated with clonal lineages of S. aureus (clonal complex 8 [CC8], sequence type 239 [ST239]), S. agalactiae (CC17), Enterococcus faecium (ST17/ST18), or Enterococcus faecalis (ST8), local variants, or variants located in different species and geographical areas. All Tn5801 elements were chromosomally located upstream of the guaA gene, which serves as an integration hot spot. Transferability was demonstrated only for Tn5801 type B among E. faecalis clonal backgrounds, which eventually harbored another Tn5801 copy. The study documents early acquisition of Tn5801 by Enterococcus, Staphylococcus, and Streptococcus. Clonal waves of these pathogens seem to have contributed to the geographical spread and local evolution of the transposon. Horizontal transfer, also demonstrated, could explain the variability observed, with the isolates often containing sequences of different origins.

Combination Effects of Antimicrobial Peptides

Antimicrobial peptides (AMPs) are ancient and conserved across the tree of life. Their efficacy over evolutionary time has been largely attributed to their mechanisms of killing. Yet, the understanding of their pharmacodynamics both in vivo and in vitro is very limited. This is, however, crucial for applications of AMPs as drugs and also informs the understanding of the action of AMPs in natural immune systems. Here, we selected six different AMPs from different organisms to test their individual and combined effects in vitro. We analyzed their pharmacodynamics based on the Hill function and evaluated the interaction of combinations of two and three AMPs. Interactions of AMPs in our study were mostly synergistic, and three-AMP combinations displayed stronger synergism than two-AMP combinations. This suggests synergism to be a common phenomenon in AMP interaction. Additionally, AMPs displayed a sharp increase in killing within a narrow dose range, contrasting with those of antibiotics. We suggest that our results could lead a way toward better evaluation of AMP application in practice and shed some light on the evolutionary consequences of antimicrobial peptide interactions within the immune system of organisms.

Endless Resistance. Endless Antibiotics?

The practice of medicine was profoundly transformed by the introduction of the antibiotics (compounds isolated from Nature) and the antibacterials (compounds prepared by synthesis) for the control of bacterial infection. As a result of the extraordinary success of these compounds over decades of time, a timeless biological activity for these compounds has been presumed. This presumption is no longer. The inexorable acquisition of resistance mechanisms by bacteria is retransforming medical practice. Credible answers to this dilemma are far better recognized than they are being implemented. In this perspective we examine (and in key respects, reiterate) the chemical and biological strategies being used to address the challenge of bacterial resistance.

How Porin Heterogeneity and Trade-Offs Affect the Antibiotic Susceptibility of Gram-Negative Bacteria

Variations in porin proteins are common in Gram-negative pathogens. Altered or absent porins reduce access of polar antibiotics across the outer membrane and can thus contribute to antibiotic resistance. Reduced permeability has a cost however, in lowering access to nutrients. This trade-off between permeability and nutritional competence is the source of considerable natural variation in porin gate-keeping. Mutational changes in this trade-off are frequently selected, so susceptibility to detergents and antibiotics is polymorphic in environmental isolates as well as pathogens. Understanding the mechanism, costs and heterogeneity of antibiotic exclusion by porins will be crucial in combating Gram negative infections.

The role of models in translating within-host dynamics to parasite evolution

Mathematical modelling provides an effective way to challenge conventional wisdom about parasite evolution and investigate why parasites ‘do what they do’ within the host. Models can reveal when intuition cannot explain observed patterns, when more complicated biology must be considered, and when experimental and statistical methods are likely to mislead. We describe how models of within-host infection dynamics can refine experimental design, and focus on the case study of malaria to highlight how integration between models and data can guide understanding of parasite fitness in three areas: (1) the adaptive significance of chronic infections; (2) the potential for tradeoffs between virulence and transmission; and (3) the implications of within-vector dynamics. We emphasize that models are often useful when they highlight unexpected patterns in parasite evolution, revealing instead why intuition yields the wrong answer and what combination of theory and data are needed to advance understanding.