Collateral sensitivity (CS), which arises when resistance to one antibiotic increases sensitivity toward other antibiotics, offers treatment opportunities to constrain or reverse the evolution of... Show moreCollateral sensitivity (CS), which arises when resistance to one antibiotic increases sensitivity toward other antibiotics, offers treatment opportunities to constrain or reverse the evolution of antibiotic resistance. The applicability of CS-informed treatments remains uncertain, in part because we lack an understanding of the generality of CS effects for different resistance mutations, singly or in combination. Here, we address this issue in the gram-positive pathogen Streptococcus pneumoniae by measuring collateral and fitness effects of clinically relevant gyrA and parC alleles and their combinations that confer resistance to fluoroquinolones. We integrated these results in a mathematical model that allowed us to evaluate how different in silico combination treatments impact the dynamics of resistance evolution. We identified common and conserved CS effects of different gyrA and parC alleles; however, the spectrum of collateral effects was unique for each allele or allelic pair. This indicated that allelic identity can impact the evolutionary dynamics of resistance evolution during monotreatment and combination treatment. Our model simulations, which included the experimentally derived antibiotic susceptibilities and fitness effects, and antibiotic-specific pharmacodynamics revealed that both collateral and fitness effects impact the population dynamics of resistance evolution. Overall, we provide evidence that allelic identity and interactions can have a pronounced impact on collateral effects to different antibiotics and suggest that these need to be considered in models examining CS-based therapies. Show less
Background\Objectives\Methods\Results\Conclusions\Collateral effects of antibiotic resistance occur when resistance to one antibiotic agent leads to increased resistance or increased sensitivity to... Show moreBackground\Objectives\Methods\Results\Conclusions\Collateral 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.\nTo develop a methodology to quantify collateral effect directionality and effect size from large-scale antimicrobial resistance population surveillance data. We 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. We 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. Our 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. Show less
Collateral sensitivity (CS)-based antibiotic treatments, where increased resistance to one antibiotic leads to increased sensitivity to a second antibiotic, may have the potential to limit the... Show moreCollateral sensitivity (CS)-based antibiotic treatments, where increased resistance to one antibiotic leads to increased sensitivity to a second antibiotic, may have the potential to limit the emergence of antimicrobial resistance. However, it remains unclear how to best design CS-based treatment schedules. To address this problem, we use mathematical modelling to study the effects of pathogen- and drug-specific characteristics for different treatment designs on bacterial population dynamics and resistance evolution. We confirm that simultaneous and one-day cycling treatments could supress resistance in the presence of CS. We show that the efficacy of CS-based cycling therapies depends critically on the order of drug administration. Finally, we find that reciprocal CS is not essential to suppress resistance, a result that significantly broadens treatment options given the ubiquity of one-way CS in pathogens. Overall, our analyses identify key design principles of CS-based treatment strategies and provide guidance to develop treatment schedules to suppress resistance. Show less
Aulin, L.B.S.; Koumans, C.I.M.; Haakman, Y.; Os, W. van; Kraakman, M.E.M.; Gooskens, J.; ... ; Hasselt, J.G.C. van 2021
One of the hallmark behaviors of social groups is division of labor, where different group members become specialized to carry out complementary tasks. By dividing labor, cooperative groups... Show moreOne of the hallmark behaviors of social groups is division of labor, where different group members become specialized to carry out complementary tasks. By dividing labor, cooperative groups increase efficiency, thereby raising group fitness even if these behaviors reduce individual fitness. We find that antibiotic production in colonies of Streptomyces coelicolor is coordinated by a division of labor. We show that S. coelicolor colonies are genetically heterogeneous because of amplifications and deletions to the chromosome. Cells with chromosomal changes produce diversified secondary metabolites and secrete more antibiotics; however, these changes reduced individual fitness, providing evidence for a trade-off between antibiotic production and fitness. Last, we show that colonies containing mixtures of mutants and their parents produce significantly more antibiotics, while colony-wide spore production remains unchanged. By generating specialized mutants that hyper-produce antibiotics, streptomycetes reduce the fitness costs of secreted secondary metabolites while maximizing the yield and diversity of these products. Show less
Liakopoulos, A.; Bunt, G. van den; Geurts, Y.; Bootsma, M.C.J.; Toleman, M.; Ceccarelli, D.; ... ; Mevius, D.J. 2018
In recent years, ESBL/AmpC-producing Escherichia coli (ESBL/AmpC-EC) have been isolated with increasing frequency from animals, food, environmental sources and humans. With incomplete and scattered... Show moreIn recent years, ESBL/AmpC-producing Escherichia coli (ESBL/AmpC-EC) have been isolated with increasing frequency from animals, food, environmental sources and humans. With incomplete and scattered evidence, the contribution to the human carriage burden from these reservoirs remains unclear.Pooled data on ESBL/AmpC-EC isolates were recovered from 35 studies in the Netherlands comprising >27 000 samples, mostly obtained between 2005 and 2015. Frequency distributions of ESBL/AmpC genes from 5808 isolates and replicons of ESBL/AmpC-carrying plasmids from 812 isolates were compared across 22 reservoirs through proportional similarity indices (PSIs) and principal component analyses (PCAs).To quantify molecular similarities between different reservoirs as a first step towards risk attribution.Our 'One Health' approach provides an integrated evaluation of the molecular relatedness of ESBL/AmpC-EC from numerous sources. The analysis showed distinguishable ESBL/AmpC-EC transmission cycles in different hosts and failed to demonstrate a close epidemiological linkage of ESBL/AmpC genes and plasmid replicon types between livestock farms and people in the general population.Predominant ESBL/AmpC genes were identified in each reservoir. PCAs and PSIs revealed close human-animal ESBL/AmpC gene similarity between human farming communities and their animals (broilers and pigs) (PSIs from 0.8 to 0.9). Isolates from people in the general population had higher similarities to those from human clinical settings, surface and sewage water and wild birds (0.7-0.8), while similarities to livestock or food reservoirs were lower (0.3-0.6). Based on rarefaction curves, people in the general population had more diversity in ESBL/AmpC genes and plasmid replicon types than those in other reservoirs.BackgroundMethodsObjectivesConclusionsResults Show less
Abdul Momin, M.H.; Liakopoulos, A.; Wareham, D.W. 2017
