Exploiting evolutionary trade-offs for posttreatment management of drug-resistant populations

Distinguishing mutants that resist drugs via different mechanisms by examining fitness tradeoffs

There is growing interest in designing multidrug therapies that leverage tradeoffs to combat resistance. Tradeoffs are common in evolution and occur when, for example, resistance to one drug results in sensitivity to another. Major questions remain about the extent to which tradeoffs are reliable, specifically, whether the mutants that provide resistance to a given drug all suffer similar tradeoffs. This question is difficult because the drug-resistant mutants observed in the clinic, and even those evolved in controlled laboratory settings, are often biased towards those that provide large fitness benefits. Thus, the mutations (and mechanisms) that provide drug resistance may be more diverse than current data suggests. Here, we perform evolution experiments utilizing lineage-tracking to capture a fuller spectrum of mutations that give yeast cells a fitness advantage in fluconazole, a common antifungal drug. We then quantify fitness tradeoffs for each of 774 evolved mutants across 12 environments, finding these mutants group into classes with characteristically different tradeoffs. Their unique tradeoffs may imply that each group of mutants affects fitness through different underlying mechanisms. Some of the groupings we find are surprising. For example, we find some mutants that resist single drugs do not resist their combination, while others do. And some mutants to the same gene have different tradeoffs than others. These findings, on one hand, demonstrate the difficulty in relying on consistent or intuitive tradeoffs when designing multidrug treatments. On the other hand, by demonstrating that hundreds of adaptive mutations can be reduced to a few groups with characteristic tradeoffs, our findings may yet empower multidrug strategies that leverage tradeoffs to combat resistance. More generally speaking, by grouping mutants that likely affect fitness through similar underlying mechanisms, our work guides efforts to map the phenotypic effects of mutation.

Assessment of bacteriocin production by clinical Pseudomonas aeruginosa isolates and their potential as therapeutic agents

INTRODUCTION

Bacterial infections and the rising antimicrobial resistance pose a significant threat to public health. Pseudomonas aeruginosa produces bacteriocins like pyocins, especially S-type pyocins, which are promising for biological applications. This research focuses on clinical P. aeruginosa isolates to assess their bacteriocin production, inhibitory spectrum, chemical structure, antibacterial agents, and preservative potential.

METHODS

The identification of P. aeruginosa was conducted through both phenotypic and molecular approaches. The inhibitory spectrum and antibacterial potential of the isolates were assessed. The kinetics of antibacterial peptide production were investigated, and the activity of bacteriocin was quantified in arbitrary units (AU ml-1). Physico-chemical characterization of the antibacterial peptides was performed. Molecular weight estimation was carried out using SDS-PAGE. qRT-PCR analysis was employed to validate the expression of the selected candidate gene.

RESULT

The antibacterial activity of P. aeruginosa was attributed to the secretion of bacteriocin compounds, which belong to the S-type pyocin family. The use of mitomycin C led to a significant 65.74% increase in pyocin production by these isolates. These S-type pyocins exhibited the ability to inhibit the growth of both Gram-negative (P. mirabilis and P. vulgaris) and Gram-positive (S. aureus, S. epidermidis, E. hirae, S. pyogenes, and S. mutans) bacteria. The molecular weight of S-type pyocin was 66 kDa, and its gene expression was confirmed through qRT-PCR.

CONCLUSION

These findings suggest that S-type pyocin hold significant potential as therapeutic agents against pathogenic strains. The Physico-chemical resistance of S-type pyocin underscores its potential for broad applications in the pharmaceutical, hygiene, and food industries.

Distinguishing mutants that resist drugs via different mechanisms by examining fitness tradeoffs

There is growing interest in designing multidrug therapies that leverage tradeoffs to combat resistance. Tradeoffs are common in evolution and occur when, for example, resistance to one drug results in sensitivity to another. Major questions remain about the extent to which tradeoffs are reliable, specifically, whether the mutants that provide resistance to a given drug all suffer similar tradeoffs. This question is difficult because the drug-resistant mutants observed in the clinic, and even those evolved in controlled laboratory settings, are often biased towards those that provide large fitness benefits. Thus, the mutations (and mechanisms) that provide drug resistance may be more diverse than current data suggests. Here, we perform evolution experiments utilizing lineage-tracking to capture a fuller spectrum of mutations that give yeast cells a fitness advantage in fluconazole, a common antifungal drug. We then quantify fitness tradeoffs for each of 774 evolved mutants across 12 environments, finding these mutants group into 6 classes with characteristically different tradeoffs. Their unique tradeoffs may imply that each group of mutants affects fitness through different underlying mechanisms. Some of the groupings we find are surprising. For example, we find some mutants that resist single drugs do not resist their combination, while others do. And some mutants to the same gene have different tradeoffs than others. These findings, on one hand, demonstrate the difficulty in relying on consistent or intuitive tradeoffs when designing multidrug treatments. On the other hand, by demonstrating that hundreds of adaptive mutations can be reduced to a few groups with characteristic tradeoffs, our findings may yet empower multidrug strategies that leverage tradeoffs to combat resistance. More generally speaking, by grouping mutants that likely affect fitness through similar underlying mechanisms, our work guides efforts to map the phenotypic effects of mutation.

Laboratory Evolution of Antimicrobial Resistance in Bacteria to Develop Rational Treatment Strategies

Laboratory evolution studies, particularly with Escherichia coli, have yielded invaluable insights into the mechanisms of antimicrobial resistance (AMR). Recent investigations have illuminated that, with repetitive antibiotic exposures, bacterial populations will adapt and eventually become tolerant and resistant to the drugs. Through intensive analyses, these inquiries have unveiled instances of convergent evolution across diverse antibiotics, the pleiotropic effects of resistance mutations, and the role played by loss-of-function mutations in the evolutionary landscape. Moreover, a quantitative analysis of multidrug combinations has shed light on collateral sensitivity, revealing specific drug combinations capable of suppressing the acquisition of resistance. This review article introduces the methodologies employed in the laboratory evolution of AMR in bacteria and presents recent discoveries concerning AMR mechanisms derived from laboratory evolution. Additionally, the review outlines the application of laboratory evolution in endeavors to formulate rational treatment strategies.

Trade-offs constrain adaptive pathways to the type VI secretion system survival

The Type VI Secretion System (T6SS) is a nano-harpoon used by many bacteria to inject toxins into neighboring cells. While much is understood about mechanisms of T6SS-mediated toxicity, less is known about the ways that competitors can defend themselves against this attack, especially in the absence of their own T6SS. Here we subjected eight replicate populations of Escherichia coli to T6SS attack by Vibrio cholerae. Over ∼500 generations of competition, isolates of the E. coli populations evolved to survive T6SS attack an average of 27-fold better, through two convergently evolved pathways: apaH was mutated in six of the eight replicate populations, while the other two populations each had mutations in both yejM and yjeP. However, the mutations we identified are pleiotropic, reducing cellular growth rates, and increasing susceptibility to antibiotics and elevated pH. These trade-offs help us understand how the T6SS shapes the evolution of bacterial interactions.

Evolution of E. coli in a mouse model of inflammatory bowel disease leads to a disease-specific bacterial genotype and trade-offs with clinical relevance

Inflammatory bowel disease (IBD) is a persistent inflammatory condition that affects the gastrointestinal tract and presents significant challenges in its management and treatment. Despite the knowledge that within-host bacterial evolution occurs in the intestine, the disease has rarely been studied from an evolutionary perspective. In this study, we aimed to investigate the evolution of resident bacteria during intestinal inflammation and whether- and how disease-related bacterial genetic changes may present trade-offs with potential therapeutic importance. Here, we perform an in vivo evolution experiment of E. coli in a gnotobiotic mouse model of IBD, followed by multiomic analyses to identify disease-specific genetic and phenotypic changes in bacteria that evolved in an inflamed versus a non-inflamed control environment. Our results demonstrate distinct evolutionary changes in E. coli specific to inflammation, including a single nucleotide variant that independently reached high frequency in all inflamed mice. Using ex vivo fitness assays, we find that these changes are associated with a higher fitness in an inflamed environment compared to isolates derived from non-inflamed mice. Further, using large-scale phenotypic assays, we show that bacterial adaptation to inflammation results in clinically relevant phenotypes, which intriguingly include collateral sensitivity to antibiotics. Bacterial evolution in an inflamed gut yields specific genetic and phenotypic signatures. These results may serve as a basis for developing novel evolution-informed treatment approaches for patients with intestinal inflammation.

Eco-evolutionary dynamics of experimental Pseudomonas aeruginosa populations under oxidative stress

Within-host environments are likely to present a challenging and stressful environment for opportunistic pathogenic bacteria colonizing from the external environment. How populations of pathogenic bacteria respond to such environmental challenges and how this varies between strains is not well understood. Oxidative stress is one of the defences adopted by the human immune system to confront invading bacteria. In this study, we show that strains of the opportunistic pathogenic bacterium Pseudomonas aeruginosa vary in their eco-evolutionary responses to hydrogen peroxide stress. By quantifying their 24 h growth kinetics across hydrogen peroxide gradients we show that a transmissible epidemic strain isolated from a chronic airway infection of a cystic fibrosis patient, LESB58, is much more susceptible to hydrogen peroxide than either of the reference strains, PA14 or PAO1, with PAO1 showing the lowest susceptibility. Using a 12 day serial passaging experiment combined with a mathematical model, we then show that short-term susceptibility controls the longer-term survival of populations exposed to subinhibitory levels of hydrogen peroxide, but that phenotypic evolutionary responses can delay population extinction. Our model further suggests that hydrogen peroxide driven extinctions are more likely with higher rates of population turnover. Together, these findings suggest that hydrogen peroxide is likely to be an effective defence in host niches where there is high population turnover, which may explain the counter-intuitively high susceptibility of a strain isolated from chronic lung infection, where such ecological dynamics may be slower.

Nothing makes sense in drug resistance except in the light of evolution

Our ability to fight infectious diseases is being increasingly compromised due to the emergence and spread of pathogens that become resistant to one or several drugs. This phenomenon is ubiquitous among pathogens and has parallels in cancer treatment. Given the urgency of the problem, there is a need for a paradigm shift in drug therapy toward one in which the objective to prevent the evolution of drug resistance is considered alongside the main objective of eliminating the infection or tumor. Here, I stress the importance of considering an evolutionary perspective to achieve this goal, and review recent advances in this direction, including therapies that exploit the fitness trade-offs of resistance.

Drug synergy discovery of tavaborole and aminoglycosides against Escherichia coli using high throughput screening

High incidences of urinary tract infection (UTI) of aminoglycosides-resistant E.coli causes a severe burden for public health. A new therapeutic strategy to ease this crisis is to repurpose non-antibacterial compounds to increase aminoglycosides sensibility against multidrug resistant E.coli pathogens. Based on high throughput screening technology, we profile the antimicrobial activity of tavaborole, a first antifungal benzoxaborole drug for onychomycosis treatment, and investigate the synergistic interaction between tavaborole and aminoglycosides, especially tobramycin and amikacin. Most importantly, by resistance accumulation assay, we found that, tavaborole not only slowed resistance occurrence of aminoglycosides, but also reduced invasiveness of E.coli in combination with tobramycin. Mechanistic studies preliminary explored that tavaborole and aminoglycosides lead to mistranslation, but would be still necessary to investigate more details for further research. In addition, tavaborole exhibited low systematic toxicity in vitro and in vivo, and enhanced aminoglycoside bactericidal activity in mice peritonitis model. Collectively, these results suggest the potential of tavaborole as a novel aminoglycosides adjuvant to tackle the clinically relevant drug resistant E. coli and encourages us to discover more benzoxaborole analogues for circumvention of recalcitrant infections.

Unblinding the watchmaker: cancer treatment and drug design in the face of evolutionary pressure

INTRODUCTION

Death due to cancer is mostly associated with therapy ineffectiveness, i.e. tumor cells no longer responding to treatment. The underlying dynamics that facilitate this mutational escape from selective pressure are well studied in several other fields and several interesting approaches exist to combat this phenomenon, for example in the context of antibiotic-resistance in bacteria.

AREAS COVERED

Ninety percent of all cancer-related deaths are associated with treatment failure. Here, we discuss the common treatment modalities and prior attempts to overcome acquired resistance to therapy. The underlying molecular mechanisms are discussed and the implications of emerging resistance in other systems, such as bacteria, are discussed in the context of cancer.

EXPERT OPINION

Reevaluating emerging therapy resistance in tumors as an evolutionary mechanism to survive in a rapidly and drastically altering fitness landscape leads to novel treatment strategies and distinct requirements for new drugs. Here, we propose a scheme of considerations that need to be applied prior to the discovery of novel therapeutic drugs.

Study of intestinal microbial flora of local chickens to investigate the effect of probiotics Bacillus subtilis and Bacillus coagulans on the expression of ctxM and luxS pathogenic genes in isolates of Escherichia coli

Background and objective: Antibiotics are widely used worldwide. However, due to the emergence of antibiotic resistance in a wide range of microorganisms, their use worldwide has failed. Probiotics are suggested as complementary and alternative medicine. The present study aimed to investigate the effects of probiotics isolated from local chickens on the expression of luxS and ctxM genes in resistant Escherichia coli.

Materials and methods: 300 fecal samples were taken from patients referring to Imam Khomeini Hospital in Tehran during May–September 2016 and Escherichia coli samples were isolated using specific culture media and biochemical tests and then the presence of luxS and ctxM genes were identified using PCR with specific primers. In order to extract the probiotics forming spores, the intestinal contents of 10 poultry that had not used any antibiotics and probiotics were cultured, isolated, and identified using biochemical and PCR methods. Commercial strains of Bacillus subtilis and Bacillus coagulans were purchased to compare their effects with native bacteria. These strains were then co-cultured with resistant Escherichia coli strains containing ctxM and luxS genes. Real-time PCR was used to evaluate the effect of these probiotics on gene expression

Results: The results indicated that 40 isolates (7.5%) of Escherichia coli were obtained from the 300 fecal samples. Thirteen samples (32.5%) were outpatients and 27 (67.5%) were inpatients. All isolates were isolated from men and women aged 21–62. Four Escherichia coli strains were isolated from patients carrying ctxM and luxS genes. Isolation of Bacillus coagulans and Bacillus subtilis from samples was confirmed by biochemical and molecular experiments. The commercial and native strains of Bacillus coagulans reduced the expression of the luxS and ctxM genes by 3.60, 3.30, 1.58, and 2.70 times respectively. Also, the commercial and native strains of Bacillus subtilis decreased the expression of the luxS and ctxM genes by 1.37, 1.10, 2.20, and 2.80 times respectively. The results of statistical analysis showed a significant relationship between the presence of native and commercial probiotics in culture and reduced expression of ctxM and luxS genes.

Conclusion: According to the results, supplements of Bacillus coagulans and Bacillus subtilis increase the effect of antibiotics resistance in Escherichia coli by reducing the expression of resistance genes.

Spatial structure impacts adaptive therapy by shaping intra-tumoral competition

Background

Adaptive therapy aims to tackle cancer drug resistance by leveraging resource competition between drug-sensitive and resistant cells. Here, we present a theoretical study of intra-tumoral competition during adaptive therapy, to investigate under which circumstances it will be superior to aggressive treatment.

Methods

We develop and analyse a simple, 2-D, on-lattice, agent-based tumour model in which cells are classified as fully drug-sensitive or resistant. Subsequently, we compare this model to its corresponding non-spatial ordinary differential equation model, and fit it to longitudinal prostate-specific antigen data from 65 prostate cancer patients undergoing intermittent androgen deprivation therapy following biochemical recurrence.

Results

Leveraging the individual-based nature of our model, we explicitly demonstrate competitive suppression of resistance during adaptive therapy, and examine how different factors, such as the initial resistance fraction or resistance costs, alter competition. This not only corroborates our theoretical understanding of adaptive therapy, but also reveals that competition of resistant cells with each other may play a more important role in adaptive therapy in solid tumours than was previously thought. To conclude, we present two case studies, which demonstrate the implications of our work for: (i) mathematical modelling of adaptive therapy, and (ii) the intra-tumoral dynamics in prostate cancer patients during intermittent androgen deprivation treatment, a precursor of adaptive therapy.

Conclusion

Our work shows that the tumour’s spatial architecture is an important factor in adaptive therapy and provides insights into how adaptive therapy leverages both inter- and intra-specific competition to control resistance.

Cancer therapy traditionally focuses on maximising tumour cell kill with the aim of achieving a cure, but such aggressive treatment can open up space for drug-resistant cells to grow. In contrast, adaptive therapy aims to leverage competition between drug-sensitive and resistant cells by adjusting treatment to maintain the tumour at a tolerable size, whilst preserving drug-sensitive cells. This approach is being tested in trials but is not yet widely used as deeper understanding of cell-cell competition is required. Here, we used a mathematical model to investigate how strongly, and with whom, resistant cells compete during continuous and adaptive therapy, and applied our insights to hormone therapy in prostate cancer where adaptive therapy has recently been successfully trialed. Our results provide new insights into how adaptive therapy works and show that, by shaping cell competition, the tumour’s spatial architecture is important in determining therapy response.

Strobl et al. develop an agent-based spatial model of drug resistance in tumour cells under adaptive therapy. Using this model, they investigate how the tumour’s spatial architecture impacts intratumoural competitive dynamics of drug-sensitive vs. -resistant clones in response to therapy.

Conditional prediction of consecutive tumor evolution using cancer progression models: What genotype comes next?

Accurate prediction of tumor progression is key for adaptive therapy and precision medicine. Cancer progression models (CPMs) can be used to infer dependencies in mutation accumulation from cross-sectional data and provide predictions of tumor progression paths. However, their performance when predicting complete evolutionary trajectories is limited by violations of assumptions and the size of available data sets. Instead of predicting full tumor progression paths, here we focus on short-term predictions, more relevant for diagnostic and therapeutic purposes. We examine whether five distinct CPMs can be used to answer the question "Given that a genotype with n mutations has been observed, what genotype with n + 1 mutations is next in the path of tumor progression?" or, shortly, "What genotype comes next?". Using simulated data we find that under specific combinations of genotype and fitness landscape characteristics CPMs can provide predictions of short-term evolution that closely match the true probabilities, and that some genotype characteristics can be much more relevant than global features. Application of these methods to 25 cancer data sets shows that their use is hampered by a lack of information needed to make principled decisions about method choice. Fruitful use of these methods for short-term predictions requires adapting method's use to local genotype characteristics and obtaining reliable indicators of performance; it will also be necessary to clarify the interpretation of the method's results when key assumptions do not hold.

Efficacy of epetraborole against Mycobacterium abscessus is increased with norvaline

Mycobacterium abscessus is the most common rapidly growing non-tuberculous mycobacteria to cause pulmonary disease in patients with impaired lung function such as cystic fibrosis. M. abscessus displays high intrinsic resistance to common antibiotics and inducible resistance to macrolides like clarithromycin. As such, M. abscessus is clinically resistant to the entire regimen of front-line M. tuberculosis drugs, and treatment with antibiotics that do inhibit M. abscessus in the lab results in cure rates of 50% or less. Here, we identified epetraborole (EPT) from the MMV pandemic response box as an inhibitor against the essential protein leucyl-tRNA synthetase (LeuRS) in M. abscessus. EPT protected zebrafish from lethal M. abscessus infection and did not induce self-resistance nor against clarithromycin. Contrary to most antimycobacterials, the whole-cell activity of EPT was greater against M. abscessus than M. tuberculosis, but crystallographic and equilibrium binding data showed that EPT binds LeuRS_Mabs and LeuRS_Mtb with similar residues and dissociation constants. Since EPT-resistant M. abscessus mutants lost LeuRS editing activity, these mutants became susceptible to misaminoacylation with leucine mimics like the non-proteinogenic amino acid norvaline. Proteomic analysis revealed that when M. abscessus LeuRS mutants were fed norvaline, leucine residues in proteins were replaced by norvaline, inducing the unfolded protein response with temporal changes in expression of GroEL chaperonins and Clp proteases. This supports our in vitro data that supplementation of media with norvaline reduced the emergence of EPT mutants in both M. abscessus and M. tuberculosis. Furthermore, the combination of EPT and norvaline had improved in vivo efficacy compared to EPT in a murine model of M. abscessus infection. Our results emphasize the effectiveness of EPT against the clinically relevant cystic fibrosis pathogen M. abscessus, and these findings also suggest norvaline adjunct therapy with EPT could be beneficial for M. abscessus and other mycobacterial infections like tuberculosis.

Current antimycobacterial drugs are inadequate to handle the increasing number of non-tuberculous mycobacteria infections that eclipse tuberculosis infections in many developed countries. Of particular importance for cystic fibrosis patients, Mycobacterium abscessus is notoriously difficult to treat where patients spend extended time on antibiotics with cure rates comparable to extreme drug resistant M. tuberculosis. Here, we identified epetraborole (EPT) with in vitro and in vivo activities against M. abscessus. We showed that EPT targets the editing domain of the leucyl-tRNA synthetase (LeuRS) and that escape mutants lost LeuRS editing activity, making these mutants susceptible to misaminoacylation with leucine mimics. Most importantly, combination therapy of EPT and norvaline limited the rate of EPT resistance in both M. abscessus and M. tuberculosis, and this was the first study to demonstrate improved in vivo efficacy of EPT and norvaline compared to EPT in a murine model of M. abscessus pulmonary infection. The demonstration of norvaline adjunct therapy with EPT for M. abscessus infections is promising for cystic fibrosis patients and could translate to other mycobacterial infections, such as tuberculosis.

In Vitro Resistance and Evolution of Resistance to Tavaborole in Trichophyton rubrum

Tavaborole is currently used in the topical treatment of onychomycosis. In this study, we analyzed the in vitro emergence/evolution of resistance against tavaborole in Trichophyton rubrum When T. rubrum strains were propagated on media containing the MIC of tavaborole, spontaneous resistant mutants were isolated at a frequency of 10^-8 The frequency was almost 100-fold higher following fungal growth in the presence of a subinhibitory tavaborole concentration (0.5-fold the MIC) for 10 transfers. All collected mutants showed similar 4- to 8-fold increases in the drug MIC. No cross-resistance to other antifungals was evident.