Price equation captures the role of drug interactions and collateral effects in the evolution of multidrug resistance.
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ABSTRACT:
SUBMITTER: Gjini E
PROVIDER: S-EPMC8331190 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The increasing incidence of drug resistance in Mycobacterium tuberculosis has diminished the efficacy of almost all available antibiotics, complicating efforts to combat the spread of this global health burden. Alongside the development of new drugs, optimised drug combinations are needed to improve treatment success and prevent the further spread of antibiotic resistance. Typically, antibiotic resistance leads to reduced sensitivity, yet in some cases the evolution of drug resistance can lead to enhanced sensitivity to unrelated drugs. This phenomenon of collateral sensitivity is largely unexplored in M. tuberculosis but has the potential to identify alternative therapeutic strategies to combat drug-resistant strains that are unresponsive to current treatments. Here, by using drug susceptibility profiling, genomics and evolutionary studies we provide evidence for the existence of collateral drug sensitivities in an isogenic collection M. tuberculosis drug-resistant strains. Furthermore, in proof-of-concept studies, we demonstrate how collateral drug phenotypes can be exploited to select against and prevent the emergence of drug-resistant strains. This study highlights that the evolution of drug resistance in M. tuberculosis leads to collateral drug responses that can be exploited to design improved drug regimens.
| S-EPMC10024696 | biostudies-literature
Project description:Antimicrobial treatments increasingly rely on multidrug combinations, in part because of the emergence and spread of antibiotic resistance. The continued effectiveness of combination treatments depends crucially on the frequency with which multidrug resistance arises. Yet, it is unknown how this propensity for resistance depends on cross-resistance and on epistatic interactions-ranging from synergy to antagonism-between the drugs. Here, we analyzed how interactions between pairs of drugs affect the spontaneous emergence of resistance in the medically important pathogen Staphylococcus aureus. Resistance is selected for within a window of drug concentrations high enough to inhibit wild-type growth but low enough for some resistant mutants to grow. Introducing an experimental method for high-throughput colony imaging, we counted resistant colonies arising across a two-dimensional matrix of drug concentrations for each of three drug pairs. Our data show that these different drug combinations have significantly different impacts on the size of the window of drug concentrations where resistance is selected for. We framed these results in a mathematical model in which the frequencies of resistance to single drugs, cross-resistance, and epistasis combine to determine the propensity for multidrug resistance. The theory suggests that drug pairs which interact synergistically, preferred for their immediate efficacy, may in fact favor the future evolution of resistance. This framework reveals the central role of drug epistasis in the evolution of resistance and points to new strategies for combating the emergence of drug-resistant bacteria.
| S-EPMC2567468 | biostudies-literature
Project description:A major challenge in the treatment of cancer is multidrug resistance (MDR) that develops during chemotherapy. Here we demonstrate that tiopronin (1), a thiol-substituted N-propanoylglycine derivative, was selectively toxic to a series of cell lines expressing the drug efflux pump P-glycoprotein (P-gp, ABCB1) and MRP1 (ABCC1). Treatment of MDR cells with 1 led to instability of the ABCB1 mRNA and consequently a reduction in P-gp protein, despite functional assays demonstrating that tiopronin does not interact with P-gp. Long-term exposure of P-gp-expressing cells to 1 sensitized them to doxorubicin and paclitaxel, both P-gp substrates. Treatment of MRP1-overexpressing cells with tiopronin led to a significant reduction in MRP1 protein. Synthesis and screening of analogues of tiopronin demonstrated that the thiol functional group was essential for collateral sensitivity while substitution of the amino acid backbone altered but did not destroy specificity, pointing to future development of targeted analogues.
| S-EPMC3208667 | biostudies-literature
Project description:Infections with rapidly evolving pathogens are often treated using combinations of drugs with different mechanisms of action. One of the major goal of combination therapy is to reduce the risk of drug resistance emerging during a patient's treatment. Although this strategy generally has significant benefits over monotherapy, it may also select for multidrug-resistant strains, particularly during long-term treatment for chronic infections. Infections with these strains present an important clinical and public health problem. Complicating this issue, for many antimicrobial treatment regimes, individual drugs have imperfect penetration throughout the body, so there may be regions where only one drug reaches an effective concentration. Here we propose that mismatched drug coverage can greatly speed up the evolution of multidrug resistance by allowing mutations to accumulate in a stepwise fashion. We develop a mathematical model of within-host pathogen evolution under spatially heterogeneous drug coverage and demonstrate that even very small single-drug compartments lead to dramatically higher resistance risk. We find that it is often better to use drug combinations with matched penetration profiles, although there may be a trade-off between preventing eventual treatment failure due to resistance in this way and temporarily reducing pathogen levels systemically. Our results show that drugs with the most extensive distribution are likely to be the most vulnerable to resistance. We conclude that optimal combination treatments should be designed to prevent this spatial effective monotherapy. These results are widely applicable to diverse microbial infections including viruses, bacteria, and parasites.
| S-EPMC4460514 | biostudies-literature
Project description:Polymorphisms in the Plasmodium falciparum multidrug resistance protein 1 (pfmdr1) gene and the Plasmodium falciparum chloroquine resistance transporter (pfcrt) gene alter the malaria parasite's susceptibility to most of the current antimalarial drugs. However, the precise mechanisms by which PfMDR1 contributes to multidrug resistance have not yet been fully elucidated, nor is it understood why polymorphisms in pfmdr1 and pfcrt that cause chloroquine resistance simultaneously increase the parasite's susceptibility to lumefantrine and mefloquine-a phenomenon known as collateral drug sensitivity. Here, we present a robust expression system for PfMDR1 in Xenopus oocytes that enables direct and high-resolution biochemical characterizations of the protein. We show that wild-type PfMDR1 transports diverse pharmacons, including lumefantrine, mefloquine, dihydroartemisinin, piperaquine, amodiaquine, methylene blue, and chloroquine (but not the antiviral drug amantadine). Field-derived mutant isoforms of PfMDR1 differ from the wild-type protein, and each other, in their capacities to transport these drugs, indicating that PfMDR1-induced changes in the distribution of drugs between the parasite's digestive vacuole (DV) and the cytosol are a key driver of both antimalarial resistance and the variability between multidrug resistance phenotypes. Of note, the PfMDR1 isoforms prevalent in chloroquine-resistant isolates exhibit reduced capacities for chloroquine, lumefantrine, and mefloquine transport. We observe the opposite relationship between chloroquine resistance-conferring mutations in PfCRT and drug transport activity. Using our established assays for characterizing PfCRT in the Xenopus oocyte system and in live parasite assays, we demonstrate that these PfCRT isoforms transport all 3 drugs, whereas wild-type PfCRT does not. We present a mechanistic model for collateral drug sensitivity in which mutant isoforms of PfMDR1 and PfCRT cause chloroquine, lumefantrine, and mefloquine to remain in the cytosol instead of sequestering within the DV. This change in drug distribution increases the access of lumefantrine and mefloquine to their primary targets (thought to be located outside of the DV), while simultaneously decreasing chloroquine's access to its target within the DV. The mechanistic insights presented here provide a basis for developing approaches that extend the useful life span of antimalarials by exploiting the opposing selection forces they exert upon PfCRT and PfMDR1.
| S-EPMC9067703 | biostudies-literature
Project description:Antibiotic cycling has been proposed as a promising approach to slow down resistance evolution against currently employed antibiotics. It remains unclear, however, to which extent the decreased resistance evolution is the result of collateral sensitivity, an evolutionary trade-off where resistance to one antibiotic enhances the sensitivity to the second, or due to additional effects of the evolved genetic background, in which mutations accumulated during treatment with a first antibiotic alter the emergence and spread of resistance against a second antibiotic via other mechanisms. Also, the influence of antibiotic exposure patterns on the outcome of drug cycling is unknown. Here, we systematically assessed the effects of the evolved genetic background by focusing on the first switch between two antibiotics against Salmonella Typhimurium, with cefotaxime fixed as the first and a broad variety of other drugs as the second antibiotic. By normalizing the antibiotic concentrations to eliminate the effects of collateral sensitivity, we demonstrated a clear contribution of the evolved genetic background beyond collateral sensitivity, which either enhanced or reduced the adaptive potential depending on the specific drug combination. We further demonstrated that the gradient strength with which cefotaxime was applied affected both cefotaxime resistance evolution and adaptation to second antibiotics, an effect that was associated with higher levels of clonal interference and reduced cost of resistance in populations evolved under weaker cefotaxime gradients. Overall, our work highlights that drug cycling can affect resistance evolution independently of collateral sensitivity, in a manner that is contingent on the antibiotic exposure pattern.
| S-EPMC9778841 | biostudies-literature
Project description:BackgroundMultidrug resistant Klebsiella pneumoniae have caused major therapeutic problems worldwide due to the emergence of the extended-spectrum β-lactamase producing strains. Although there are >10 major facilitator super family (MFS) efflux pumps annotated in the genome sequence of the K. pneumoniae bacillus, apparently less is known about their physiological relevance.Principal findingsInsertional inactivation of kpnGH resulting in increased susceptibility to antibiotics such as azithromycin, ceftazidime, ciprofloxacin, ertapenem, erythromycin, gentamicin, imipenem, ticarcillin, norfloxacin, polymyxin-B, piperacillin, spectinomycin, tobramycin and streptomycin, including dyes and detergents such as ethidium bromide, acriflavine, deoxycholate, sodium dodecyl sulphate, and disinfectants benzalkonium chloride, chlorhexidine and triclosan signifies the wide substrate specificity of the transporter in K. pneumoniae. Growth inactivation and direct fluorimetric efflux assays provide evidence that kpnGH mediates antimicrobial resistance by active extrusion in K. pneumoniae. The kpnGH isogenic mutant displayed decreased tolerance to cell envelope stressors emphasizing its added role in K. pneumoniae physiology.Conclusions and significanceThe MFS efflux pump KpnGH involves in crucial physiological functions besides being an intrinsic resistance determinant in K. pneumoniae.
| S-EPMC4019481 | biostudies-literature
Project description:The emergence of resistance during multidrug chemotherapy impedes the treatment of many human diseases, including malaria, TB, HIV, and cancer. Although certain combination therapies have long been known to be more effective in curing patients than single drugs, the impact of such treatments on the evolution of drug resistance is unclear. In particular, very little is known about how the evolution of resistance is affected by the nature of the interactions--synergy or antagonism--between drugs. Here we directly measure the effect of various inhibitory and subinhibitory drug combinations on the rate of adaptation. We develop an automated assay for monitoring the parallel evolution of hundreds of Escherichia coli populations in a two-dimensional grid of drug gradients over many generations. We find a correlation between synergy and the rate of adaptation, whereby evolution in more synergistic drug combinations, typically preferred in clinical settings, is faster than evolution in antagonistic combinations. We also find that resistance to some synergistic combinations evolves faster than resistance to individual drugs. The accelerated evolution may be due to a larger selective advantage for resistance mutations in synergistic treatments. We describe a simple geometric model in which mutations conferring resistance to one drug of a synergistic pair prevent not only the inhibitory effect of that drug but also its enhancing effect on the other drug. Future study of the profound impact that synergy and other drug-pair properties can have on the rate of adaptation may suggest new treatment strategies for combating the spread of antibiotic resistance.
| S-EPMC2544564 | biostudies-literature
Project description:Antibiotic resistance is a major challenge to global public health. Discovery of new antibiotics is slow and to ensure proper treatment of bacterial infections new strategies are needed. One way to curb the development of antibiotic resistance is to design drug combinations where the development of resistance against one drug leads to collateral sensitivity to the other drug. Here we study collateral sensitivity patterns of the globally distributed extended-spectrum ?-lactamase CTX-M-15, and find three non-synonymous mutations with increased resistance against mecillinam or piperacillin-tazobactam that simultaneously confer full susceptibility to several cephalosporin drugs. We show in vitro and in mice that a combination of mecillinam and cefotaxime eliminates both wild-type and resistant CTX-M-15. Our results indicate that mecillinam and cefotaxime in combination constrain resistance evolution of CTX-M-15, and illustrate how drug combinations can be rationally designed to limit the resistance evolution of horizontally transferred genes by exploiting collateral sensitivity patterns.
| S-EPMC6365502 | biostudies-literature
Project description:BackgroundCollateral effects of antibiotic resistance occur when resistance to one antibiotic agent leads to increased resistance or increased sensitivity to a second agent, known respectively as collateral resistance (CR) and collateral sensitivity (CS). Collateral effects are relevant to limit impact of antibiotic resistance in design of antibiotic treatments. However, methods to detect antibiotic collateral effects in clinical population surveillance data of antibiotic resistance are lacking.ObjectivesTo develop a methodology to quantify collateral effect directionality and effect size from large-scale antimicrobial resistance population surveillance data.MethodsWe propose a methodology to quantify and test collateral effects in clinical surveillance data based on a conditional t-test. Our methodology was evaluated using MIC data for 419 Escherichia coli strains, containing MIC data for 20 antibiotics, which were obtained from the Pathosystems Resource Integration Center (PATRIC) database.ResultsWe demonstrate that the proposed approach identifies several antibiotic combinations that show symmetrical or non-symmetrical CR and CS. For several of these combinations, collateral effects were previously confirmed in experimental studies. We furthermore provide insight into the power of our method for multiple collateral effect sizes and MIC distributions.ConclusionsOur proposed approach is of relevance as a tool for analysis of large-scale population surveillance studies to provide broad systematic identification of collateral effects related to antibiotic resistance, and is made available to the community as an R package. This method can help mapping CS and CR, which could guide combination therapy and prescribing in the future.
| S-EPMC8633787 | biostudies-literature