334 research outputs found
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Trade-offs between drug toxicity and benefit in the multi-antibiotic resistance system underlie optimal growth of E. coli
Background: Efflux is a widespread mechanism of reversible drug resistance in bacteria that can be triggered by environmental stressors, including many classes of drugs. While such chemicals when used alone are typically toxic to the cell, they can also induce the efflux of a broad range of agents and may therefore prove beneficial to cells in the presence of multiple stressors. The cellular response to a combination of such chemical stressors may be governed by a trade-off between the fitness costs due to drug toxicity and benefits mediated by inducible systems. Unfortunately, disentangling the cost-benefit interplay using measurements of bacterial growth in response to the competing effects of the drugs is not possible without the support of a theoretical framework. Results: Here, we use the well-studied multiple antibiotic resistance (MAR) system in E. coli to experimentally characterize the trade-off between drug toxicity (ācostā) and drug-induced resistance (ābenefitā) mediated by efflux pumps. Specifically, we show that the combined effects of a MAR-inducing drug and an antibiotic are governed by a superposition of cost and benefit functions that govern these trade-offs. We find that this superposition holds for all drug concentrations, and it therefore allows us to describe the full doseāresponse diagram for a drug pair using simpler cost and benefit functions. Moreover, this framework predicts the existence of optimal growth at a non-trivial concentration of inducer. We demonstrate that optimal growth does not coincide with maximum induction of the mar promoter, but instead results from the interplay between drug toxicity and mar induction. Finally, we derived and experimentally validated a general phase diagram highlighting the role of these opposing effects in shaping the interaction between two drugs. Conclusions: Our analysis provides a quantitative description of the MAR system and highlights the trade-off between inducible resistance and the toxicity of the inducing agent in a multi-component environment. The results provide a predictive framework for the combined effects of drug toxicity and induction of the MAR system that are usually masked by bulk measurements of bacterial growth. The framework may also be useful for identifying optimal growth conditions in more general systems where combinations of environmental cues contribute to both transient resistance and toxicity.Engineering and Applied SciencesMolecular and Cellular Biolog
Uncovering Scaling Laws to Infer Multi-drug Response of Resistant Microbes and Cancer Cells
Drug resistance in bacterial infections and cancers constitutes a major threat to human health. Treatments often include several interacting drugs, but even potent therapies can become ineffective in resistant mutants. Here we simplify the picture of drug resistance by identifying scaling laws that unify the multi-drug responses of drug sensitive and drug resistant cells. Based on these scaling relationships, we are able to infer the two-drug response of resistant mutants in previously unsampled regions of dosage space in clinically relevant microbes such as E. coli, E. faecalis, S. aureus and S. cerevisiae, as well as in human non-small cell lung cancer, melanoma, and breast cancer stem cells. Importantly, we find that scaling relations also apply across evolutionarily close strains. Finally, scaling allows one to rapidly identify new drug combinations and predict potent dosage regimes for targeting resistant mutants without any prior mechanistic knowledge of the specific resistance mechanism.Molecular and Cellular Biolog
Gene expression noise in stress response as a survival strategy in fluctuating environments
Populations of cells live in uncertain environments, where they encounter large variations in nutrients, oxygen and toxic compounds. In the fluctuating environment, cells can sense their surroundings and express proteins to protect themselves against harmful substances. However, if the stressor appears infrequently or abruptly, sensing can be too costly or too slow, and cells cannot rely solely on it. To hedge against the sudden appearance of a stressor, cell populations can also rely on phenotypic diversification through bet-hedging. In bet-hedging, cells exploit noise in gene expression or use multistable genetic networks to produce an heterogeneous distribution of resistance-conferring protein levels. In this thesis, we analyze novel roles of noise in biological systems. Through a combination of modeling and stochastic simulations, we find that noise can coordinate multi-component stress response mechanisms in a subset of the population with no extra cost. In addition, we use evolutionary algorithms to analyze the conditions where the benefits provided by noise in gene expression are equivalent to those of a more complicated, bistable distribution of protein levels. Our results show that for cells living in noisy fluctuating environments, both noise in gene expression and bistability show similar growth rates, meaning that noise in gene expression can be an effective bet-hedging strategy
MarA, RamA, and SoxS as Mediators of the Stress Response:Survival at a Cost
To survive and adapt to changing environments, bacteria have evolved mechanisms to express appropriate genes at appropriate times. Exposure to antimicrobials triggers a global stress response in Enterobacteriaceae, underpinned by activation of a family of transcriptional regulators, including MarA, RamA, and SoxS. These control a program of altered gene expression allowing a rapid and measured response to improve fitness in the presence of toxic drugs. Increased expression of marA, ramA, and soxS up regulates efflux activity to allow detoxification of the cell. However, this also results in trade-offs in other phenotypes, such as impaired growth rates, biofilm formation and virulence. Here, we review the current knowledge regarding the trade-offs that exist between drug survival and other phenotypes that result from induction of marA, ramA, and soxS. Additionally, we present some new findings linking expression of these regulators and biofilm formation in Enterobacteriaceae, thereby demonstrating the interconnected nature of regulatory networks within the cell and explaining how trade-offs can exist between important phenotypes. This has important implications for our understanding of how bacterial virulence and biofilms can be influenced by exposure to antimicrobials
Over-expressed CmbT multidrug resistance transporter improves the fitness of Lactococcus lactis
U ovom radu je izuÄavan uticaj poveÄane ekspresije cmbT gena, odgovornog za sintezu CmbT MDR transportera, na rast Lactococcus lactis. L. lactis pripada grupi bakterija mleÄne kiseline (BMK) i ima veliku primenu u prehrambenoj industriji kao starter kultura. CmbT transporter je nedavno okarakterisan MDR protein soja L. lactis, koji doprinosi rezistenciji na razliÄite toksiÄne agense kao i na neke kliniÄki znaÄajne antibiotike. U ovom radu je cmbT gen viÅ”estruko eksprimiran u soju L. lactis NZ9000 dodavanjem nizina kao inducera. PoveÄana ekspresija cmbT gena je praÄena metodom reverzne transkripcije (RT-PCR). Pokazano je da se nakon dodatka subinhibitornih koncentracija nizina u medijum za rast poveÄava koliÄina sintetisane informacione RNK specifiÄne za cmbT gen. Rast soja L. lactis NZ9000/pCT50, u kome je viÅ”estruko eksprimiran cmbT gen i L. lactis NZ9000 kontrolnog soja praÄen je u bogatom i hemijski definisanom medijumu u prisustvu samo metionina (0.084 mM) ili kombinacije metionina i cisteina (8.4 mM i 8.2 mM). PraÄene su krive rasta oba soja, a nakon izraÄunavanja odgovarajuÄih vremena generacije, rezultati su pokazali da L. lactis NZ9000/pCT50, brže raste u odnosu na kontrolni soj. UoÄena razlika je najverovatnije posledica aktivnosti CmbT transportera koji doprinosi izbacivanju toksiÄnih agenasa iz Äelije i na taj naÄin poboljÅ”ava adaptivne sposobnosti bakterije koja ga eksprimira i daje joj selektivnu prednost.The influence of the over-expression of CmbT multidrug resistance transporter on the growth rate of Lactococcus lactis NZ9000 was studied. L. lactis is a lactic acid bacteria (LAB) widely used as a starter culture in dairy industry. Recently characterized CmbT MDR transporter in L. lactis confers resistance to a wide variety of toxic compounds as well as to some clinically relevant antibiotics. In this study, the cmbT gene was over-expressed in the strain L. lactis NZ9000 in the presence of nisin inducer. Over-expression of the cmbT gene in L. lactis NZ9000 was followed by RT-PCR. The obtained results showed that the cmbT gene was successfully over-expressed by addition of sub-inhibitory amounts of nisin. Growth curves of L. lactis NZ9000/pCT50 over-expressing the cmbT gene and L. lactis NZ9000 control strain were followed in the rich medium as well as in the chemically defined medium in the presence solely of methionine (0.084 mM) or mix of methionine and cysteine (8.4 mM and 8.2 mM, respectively). Resulting doubling times revealed that L. lactis NZ9000/pCT50 had higher growth rate comparing to the control strain. This could be a consequence of the CmbT efflux activity, which improves the fitness of the host bacterium through the elimination of toxic compounds from the cell
Understanding and improving microbial biofuel tolerance as a result of efflux pump expression through genetic engineering and mathematical modeling
Recent advances in synthetic biology have enabled the construction of non-native metabolic pathways for production of next-generation biofuels in microbes. One such biofuel is the jet-fuel precursor Ī±-pinene, which can be processed into high-energy pinene dimers. However, accumulation of toxic biofuels in the growth medium limits the possible fuel yield. Overexpression of transporter proteins such as efflux pumps can increase tolerance to biofuels by pumping them out of the cell, thus improving fuel yields. However, too many efflux pumps can compromise the cell as well, creating a trade-off between biofuel toxicity and pump toxicity. In this work we improve the conditions of this trade-off in order to increase pinene tolerance in E. coli. We do so by constructing strains incorporating multiple efflux pumps from a variety of organisms and then testing them for tolerance in growth assay experiments. Previous research has suggested that certain combinations of efflux pumps can confer additional tolerance compared to the individual pumps themselves. However, the functional form of the combination of the tolerance provided by each pump and the toxicity due to their simultaneous activity is unknown. Using differential equations, we developed a growth model incorporating the trade-offs between toxicity of Ī±-pinene and efflux pump activity to describe the dynamics of bacterial growth under these conditions. By analyzing biofuel toxicity and the effects of each efflux pump independently through a series of experiments and mathematical models, we propose a functional form for their combined effect on growth rate. We model the mean exponential growth rate as a function of pump induction and biofuel concentration and compare these results to experimental data. We also apply this technique to modeling toxicity of ionic liquids, a class of corrosive salts that has emerged as and effective chemical for pretreatment of biofuel production feedstock. We compare a model for a variety of ionic liquid responsive efflux pump controllers to that of an IPTG inducible controller and show agreement with experimental data, supporting the model\u27s utility to test control schemes before conducting experiments. The overall goal of this project is to use modeling to guide design of tolerance mechanisms to improve overall biofuel yield
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Drug-induced resistance evolution necessitates less aggressive treatment
Increasing body of experimental evidence suggests that anticancer and antimicrobial therapies may themselves promote the acquisition of drug resistance by increasing mutability. The successful control of evolving populations requires that such biological costs of control are identified, quantified and included to the evolutionarily informed treatment protocol. Here we identify, characterise and exploit a trade-off between decreasing the target population size and generating a surplus of treatment-induced rescue mutations. We show that the probability of cure is maximized at an intermediate dosage, below the drug concentration yielding maximal population decay, suggesting that treatment outcomes may in some cases be substantially improved by less aggressive treatment strategies. We also provide a general analytical relationship that implicitly links growth rate, pharmacodynamics and dose-dependent mutation rate to an optimal control law. Our results highlight the important, but often neglected, role of fundamental eco-evolutionary costs of control. These costs can often lead to situations, where decreasing the cumulative drug dosage may be preferable even when the objective of the treatment is elimination, and not containment. Taken together, our results thus add to the ongoing criticism of the standard practice of administering aggressive, high-dose therapies and motivate further experimental and clinical investigation of the mutagenicity and other hidden collateral costs of therapies. Author summary Evolution of drug resistance to anticancer and antimicrobial therapies is widespread among cancer and pathogen cell populations. Classical theory posits strictly that genetic and phenotypic variation is generated in evolving populations independently of the selection pressure. However, recent experimental findings among antimicrobial agents, traditional cytotoxic chemotherapies and targeted cancer therapies suggest that treatment not only imposes selection but can also affect the rate of adaptation by increasing mutability. Here we analyse a model with drug-induced increase in mutation rate and explore its consequences for treatment optimisation. We argue that the true biological cost of treatment is not limited to the harmful side-effects, but instead realises even more profoundly by fundamentally changing the underlying eco-evolutionary dynamics within the microenvironment. Using the concept of evolutionary rescue, we formulate the treatment as an optimal control problem and solve the optimal elimination strategy, which minimises the probability of evolutionary rescue. We show that aggressive elimination strategies, which aim at eradication as fast as possible and which represent the current standard of care, can be detrimental even with modest drug-induced increases (fold changePeer reviewe
Uticaj poveÄane ekspresije CmbT MDR transportera na rast Lactococcus lactis
The influence of the over-expression of CmbT multidrug resistance transporter on the growth rate of Lactococcus lactis NZ9000 was studied. L. lactis is a lactic acid bacteria (LAB) widely used as a starter culture in dairy industry. Recently characterized CmbT MDR transporter in L. lactis confers resistance to a wide variety of toxic compounds as well as to some clinically relevant antibiotics. In this study, the cmbT gene was over-expressed in the strain L. lactis NZ9000 in the presence of nisin inducer. Over-expression of the cmbT gene in L. lactis NZ9000 was followed by RT-PCR. The obtained results showed that the cmbT gene was successfully over-expressed by addition of sub-inhibitory amounts of nisin. Growth curves of L. lactis NZ9000/pCT50 over-expressing the cmbT gene and L. lactis NZ9000 control strain were followed in the rich medium as well as in the chemically defined medium in the presence solely of methionine (0.084 mM) or mix of methionine and cysteine (8.4 mM and 8.2 mM, respectively). Resulting doubling times revealed that L. lactis NZ9000/pCT50 had higher growth rate comparing to the control strain. This could be a consequence of the CmbT efflux activity, which improves the fitness of the host bacterium through the elimination of toxic compounds from the cell.U ovom radu je izuÄavan uticaj poveÄane ekspresije cmbT gena, odgovornog za sintezu CmbT MDR transportera, na rast Lactococcus lactis. L. lactis pripada grupi bakterija mleÄne kiseline (BMK) i ima veliku primenu u prehrambenoj industriji kao starter kultura. CmbT transporter je nedavno okarakterisan MDR protein soja L. lactis, koji doprinosi rezistenciji na razliÄite toksiÄne agense kao i na neke kliniÄki znaÄajne antibiotike. U ovom radu je cmbT gen viÅ”estruko eksprimiran u soju L. lactis NZ9000 dodavanjem nizina kao inducera. PoveÄana ekspresija cmbT gena je praÄena metodom reverzne transkripcije (RT-PCR). Pokazano je da se nakon dodatka subinhibitornih koncentracija nizina u medijum za rast poveÄava koliÄina sintetisane informacione RNK specifiÄne za cmbT gen. Rast soja L. lactis NZ9000/pCT50, u kome je viÅ”estruko eksprimiran cmbT gen i L. lactis NZ9000 kontrolnog soja praÄen je u bogatom i hemijski definisanom medijumu u prisustvu samo metionina (0.084 mM) ili kombinacije metionina i cisteina (8.4 mM i 8.2 mM). PraÄene su krive rasta oba soja, a nakon izraÄunavanja odgovarajuÄih vremena generacije, rezultati su pokazali da L. lactis NZ9000/pCT50, brže raste u odnosu na kontrolni soj. UoÄena razlika je najverovatnije posledica aktivnosti CmbT transportera koji doprinosi izbacivanju toksiÄnih agenasa iz Äelije i na taj naÄin poboljÅ”ava adaptivne sposobnosti bakterije koja ga eksprimira i daje joj selektivnu prednost
The future of evolutionary medicine: sparking innovation in biomedicine and public health
Evolutionary medicine - i.e. the application of insights from evolution and ecology to biomedicine - has tremendous untapped potential to spark transformational innovation in biomedical research, clinical care and public health. Fundamentally, a systematic mapping across the full diversity of life is required to identify animal model systems for disease vulnerability, resistance, and counter-resistance that could lead to novel clinical treatments. Evolutionary dynamics should guide novel therapeutic approaches that target the development of treatment resistance in cancers (e.g., via adaptive or extinction therapy) and antimicrobial resistance (e.g., via innovations in chemistry, antimicrobial usage, and phage therapy). With respect to public health, the insight that many modern human pathologies (e.g., obesity) result from mismatches between the ecologies in which we evolved and our modern environments has important implications for disease prevention. Life-history evolution can also shed important light on patterns of disease burden, for example in reproductive health. Experience during the COVID-19 (SARS-CoV-2) pandemic has underlined the critical role of evolutionary dynamics (e.g., with respect to virulence and transmissibility) in predicting and managing this and future pandemics, and in using evolutionary principles to understand and address aspects of human behavior that impede biomedical innovation and public health (e.g., unhealthy behaviors and vaccine hesitancy). In conclusion, greater interdisciplinary collaboration is vital to systematically leverage the insight-generating power of evolutionary medicine to better understand, prevent, and treat existing and emerging threats to human, animal, and planetary health
Dynamics and evolution of efflux pump-mediated antibiotic resistance
Antibiotic resistance is a worldwide health threat, as bacteria continue to evade antibiotic treatment. In order to survive, bacteria utilize a number of resistance mechanisms, including efflux pumps, which efficiently export antibiotics outside of the cell to reduce intracellular damage. While such mechanisms are well known, there remains a significant gap in knowledge regarding how different environmental dynamics, such as the rate of antibiotic introduction or the diversity within a microbial community, play a role in resistance. In this work, we used the AcrAB-TolC efflux pump as a case study to explore how such complex dynamics promote antibiotic resistance and its evolution. First, through a combined effort using experiments and mathematical modeling, we discovered that the rate of antibiotic introduction impacts the fraction of resistant bacteria in a population. We then explored the impact of mixed populations on survival following antibiotic treatment. In mixed microcolonies, we found that resistant cells can harm their susceptible neighbors by exporting antibiotics to increase the local concentrations of these drugs. Next, we aimed to understand how these environmental effects may impact longer-term survival of an antibiotic treatment, focusing on the evolution of resistance over ~72 hours. Through a series of adaptive evolution experiments, we identified that near-MIC treatments were the most likely to promote antibiotic resistance, regardless of whether the strains contained the AcrAB-TolC pump at wild type or overexpressed levels, or whether the strains lacked the pump altogether. In studying antibiotic introduction rates on evolution, we found that slower introduction rates facilitated the evolution of high levels of resistance with a minimal fitness cost. Meanwhile, mixed populations demonstrated limited evolvability after rapid antibiotic introductions. This work provides important insights into the impacts of environmental factors, such as the rate of antibiotic introduction and the homogeneity of populations, on the promotion and evolution of antibiotic resistance. These lessons may help inform future policies on antibiotic use and mitigate the continued pattern of resistance evolution
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