A paradox of parasite resistance: Disease-driven trophic cascades increase the cost of resistance, selecting for lower resistance with parasites than without them

Most evolutionary theory predicts that, during epidemics, hosts will evolve higher resistance to parasites that kill them. Here, we provide an alternative to that typical expectation, with an explanation centered on resource feedbacks. When resistance is costly, hosts evolve decreasing resistance without parasites, as expected. But with parasites, hosts can evolve lower resistance than they would in the absence of parasites. This outcome arises in an eco-evolutionary model when four conditions are met: first, resistance has a fecundity cost (here, via decreased foraging/exposure rate); second, resources increase during epidemics via trophic cascades; third, increased resources magnify the benefit of maintaining a fast foraging rate, thereby magnifying the cost of evolving a slower foraging/exposure rate (i.e., resistance); fourth, that amplification of the cost outweighs the benefit of resistance. When these conditions are met, hosts evolve lower resistance than without parasites. This phenomenon was previously observed in a mesocosm experiment with fungal parasites, zooplankton hosts, and algal resources. Re-analyzing this experiment produced evidence for our model's mechanism. Thus, both model and experiment indicate that, via resource feedbacks, parasites can counterintuitively select against resistance.

Market forces determine the distribution of a leaky function in a simple microbial community

Many biological functions are leaky, and organisms that perform them contribute some of their products to a community “marketplace” in which nonperforming individuals may compete for them. Leaky functions are partitioned unequally in microbial communities, and the evolutionary forces determining which species perform them and which become beneficiaries are poorly understood. Here, we demonstrate that the market principle of comparative advantage determines the distribution of a leaky antibiotic resistance gene in an environment occupied by two “species”—strains of Escherichia coli growing on mutually exclusive resources and thus occupying separate niches. Communities comprised of antibiotic-resistant cells were rapidly invaded by sensitive cells of both types. While the two phenotypes coexisted stably for 500 generations, in 15/18 replicates, antibiotic sensitivity became fixed in one species. Fixation always occurred in the same species despite both species being genetically identical except for their niche-defining mutation. In the absence of antibiotic, the fitness cost of resistance was identical in both species. However, the intrinsic resistance of the species that ultimately became the sole helper was significantly lower, and thus its reward for expressing the resistance gene was higher. Opportunity cost of resistance, not absolute cost or efficiency of antibiotic removal, determined which species became the helper, consistent with the economic theory of comparative advantage. We present a model that suggests that this market-like dynamic is a general property of Black Queen systems and, in communities dependent on multiple leaky functions, could lead to the spontaneous development of an equitable and efficient division of labor.

Fitness barriers to spread of colistin-resistant Klebsiella pneumoniae overcome by establishing niche in patient population with elevated colistin use

To combat antibiotic resistance, it is critical to improve our understanding of how new resistant strains emerge and spread. An antibiotic resistance threat of critical priority is the epidemic ST258 strain of carbapenem-resistant Klebsiella pneumoniae (CRKP). Here, we studied the spread of resistance among ST258 to an antibiotic of last resort, colistin, by tracking its evolution across 21 U.S. long-term acute care hospitals over the course of a year. Phylogenetic analysis suggested that a significant cost was associated with colistin resistance in most cases, as resistance emergence was common but resistance variants were rarely transmitted. The high cost of resistance was further supported by the observation that several of the resistance variants that were transmitted had acquired secondary variants that reverted the strain to colistin susceptibility. The exceptions to the general pattern of instability associated with colistin resistance were two large clusters of resistant strains in one ST258 clade II sublineage (clade IIB) present across 11 of the 12 sampled Southern California hospitals. Quantification of transmission fitness in the healthcare environment using time-scaled haplotypic density indicated that while resistant isolates from other clades were less fit than their susceptible counterparts, clade IIB resistant isolates were more fit. Overlaying patient clinical data suggested that the increased fitness of colistin-resistant clade IIB isolates is in part driven by a lineage defining variant that increased clade IIB's association with patient subpopulations who were more likely to be treated with colistin. These results show that a favorable genetic background and sustained selective pressure led to the emergence and spread of a colistin-resistant ST258 sublineage across a regional healthcare network. More broadly, these findings highlight the utility of integrating pathogen genomic and corresponding clinical data from regional healthcare networks to detect and understand the origin and dissemination of antibiotic resistance threats.

The competition dynamics of resistant and sensitive infections

Antimicrobial resistance is a major health problem with complex dynamics. Resistance may occur in an area because treated infections mutated and developed resistance, and the proportion of infections in a population may then increase. We developed a novel and flexible model that captures several features of resistance dynamics and competition. The model is able to account for many antimicrobials and thus can generally explore competition dynamics and their impact on pathogens and bacteria.Unlike simpler models, our nested model allows the population of resistant pathogen to smoothly increase or decrease. Time dependent dynamics are incorporated into difference equations which examines the effects of 12 parameters. This enables us to explicitly include three key competition dynamics: the transmission cost of resistance that occurs between hosts, the fitness cost of resistance that occurs within untreated hosts, and the release of this competition (from the fitness cost) that occurs once a host is treated. For malaria, our results suggest that without competitive release, drug resistance does not emerge. However, once emerged, competitive release has little effect, and the best way to mitigate the spread is to ensure that treatment is very effective.

Idiosyncratic variation in the fitness costs of tetracycline-resistance mutations in Escherichia coli

A bacterium’s fitness relative to its competitors, both in the presence and absence of antibiotics, plays a key role in its ecological success and clinical impact. In this study, we examine whether tetracycline-resistant mutants are less fit in the absence of the drug than their sensitive parents, and whether the fitness cost of resistance is constant or variable across independently derived lines. Tetracycline-resistant lines suffered, on average, a reduction in fitness of almost 8%. There was substantial among-line variation in the fitness cost. This variation was not associated with the level of phenotypic resistance conferred by the mutations, nor did it vary significantly across several different genetic backgrounds. The two resistant lines with the most extreme fitness costs involved functionally unrelated mutations on different genetic backgrounds. However, there was also significant variation in the fitness costs for mutations affecting the same pathway and even different alleles of the same gene. Our findings demonstrate that the fitness costs of antibiotic resistance do not always correlate with the phenotypic level of resistance or the underlying genetic changes. Instead, these costs reflect the idiosyncratic effects of particular resistance mutations and the genetic backgrounds in which they occur.

Evolution of drug-resistant and virulent small colonies in phenotypically diverse populations of the human fungal pathogen Candida glabrata

Antimicrobial resistance frequently carries a fitness cost to a pathogen, measured as a reduction in growth rate compared to the sensitive wild-type, in the absence of antibiotics. Existing empirical evidence points to the following relationship between cost of resistance and virulence. If a resistant pathogen suffers a fitness cost in terms of reduced growth rate it commonly has lower virulence compared to the sensitive wild-type. If this cost is absent so is the reduction in virulence. Here we show, using experimental evolution of drug resistance in the fungal human pathogen Candida glabrata, that reduced growth rate of resistant strains need not result in reduced virulence. Phenotypically heterogeneous populations were evolved in parallel containing highly resistant sub-population small colony variants (SCVs) alongside sensitive sub-populations. Despite their low growth rate in the absence of an antifungal drug, the SCVs did not suffer a marked alteration in virulence compared with the wild-type ancestral strain, or their co-isolated sensitive strains. This contrasts with classical theory that assumes growth rate to positively correlate with virulence. Our work thus highlights the complexity of the relationship between resistance, basic life-history traits and virulence.

Functional Identification of Px-fringe and Px-engrailed Genes under Heat Stress in Chlorpyrifos-Resistant and -Susceptible Plutela xylostella (Lepidoptera: Plutellidae)

In our previous research, the fitness cost of resistance of the diamondback moth (DBM), Plutella xylostella found in insecticide-resistant DBM (Rc-DBM) under heat stress was based on heavier damage to wing veins when compared to insecticide-susceptible DBM (Sm-DBM). To investigate the molecular mechanism of the damage to the veins between Rc- and Sm-DBM, the full-length sequences of two related genes involved in the development of wing veins, fringe (Px-fng) and engrailed (Px-en) of DBM were cloned, and the mRNA expressions of both Px-fng and Px-en were studied. The Px-fng and Px-en cDNA contained 1038 bp and 1152 bp of open reading frames (ORFs), respectively, which encoded a putative protein comprising 345 and 383 amino acids with a calculated molecular weight of 39.59 kDa and 42.69 kDa. Significantly down regulated expressions of Px-fng and Px-en under heat stress were found in pupae and adults of Rc-DBM compared to Sm-DBM, and a result of higher damage to wing veins in Rc-DBM under heat stress. Based on RNAi experiments, significant inhibitions on expressions of Px-fng and Px-en in both Sm-DBM and Rc-DBM were found when the pupae were infected by dsFng or dsEn. Corresponding to these, infections of dsFng or dsEn resulted in significant decrease of eclosion rate and increase malformation rate of DBM. Our results suggest that the higher damage of wing veins in DBM might be related to the heavier inhibitions of Px-fng and Px-en expression, and the Px-fng and Px-en are involved in the development of wings and veins.

The logic of containing tumors

Challenging the paradigm of the maximum tolerated dose, recent studies have shown that a strategy aiming for containment, not elimination, can control tumor burden more effectively in vitro, in mouse models, and in the clinic. These outcomes are consistent with the hypothesis that emergence of resistance to cancer therapy may be prevented or delayed by exploiting competitive ecological interactions between drug-sensitive and resistant tumor cell subpopulations. However, although various mathematical and computational models have been proposed to explain the superiority of particular containment strategies, this evolutionary approach to cancer therapy lacks a rigorous theoretical foundation. Here we combine extensive mathematical analysis and numerical simulations to establish general conditions under which a containment strategy is expected to control tumor burden more effectively than applying the maximum tolerated dose. We show that when resistant cells are present, an idealized strategy of containing a tumor at a maximum tolerable size maximizes time to treatment failure (that is, the time at which tumor burden becomes intolerable). These results are very general and do not depend on any fitness cost of resistance. We further provide formulas for predicting the clinical benefits attributable to containment strategies in a wide range of scenarios, and we compare outcomes of theoretically optimal treatments with those of more practical protocols. Our results strengthen the rationale for clinical trials of evolutionarily-informed cancer therapy.