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Antimicrobials can exert specific physiological effects when used in combination that are different from those when applied alone. These effects include physiological effects (i.e. synergy, antagonism and suppression) as well as evolutionary effects on the selection of resistant strains (i.e. cross-resistance and collateral sensitivity). While combination effects have been extensively mapped for antibiotic-antibiotic combinations, the combination effects of antibiotics with antimicrobials used as biocides or antiseptics have not been systematically investigated.
Here, we investigated the physiological and evolutionary consequences of combinations of antibiotics (meropenem, gentamicin and ciprofloxacin) and substances used as biocides or antiseptics (octenidine, benzalkonium chloride, cetrimonium bromide, chlorhexidine, povidone-iodine, silver) on growth and selection of Pseudomonas aeruginosa. We find prevalent physiological combination effects with synergy occurring 6 times and antagonism occurring 10 times. The effects are specific to the antibiotic-biocide combination with meropenem showing a tendency for antagonism with biocides (6 of 7), while gentamicin has a tendency for synergy (5 of 7). A particular strong antagonism is apparent for the meropenem-chlorhexidine combination, for which we conducted an in-depth study on the underlying molecular mechanism using RNASeq. Moreover, we find widespread effects of the biocide-antibiotic combinations on selection of P. aeruginosa strains resistant to the antibiotics, including cross-resistance and collateral sensitivity.
In conclusion, antibiotics and biocides or antiseptics exert physiological and evolutionary combination effects on the pathogen P. aeruginosa. These effects have consequences for the efficacy of both types of substances and for the selection of antimicrobial resistant strains in clinical applications with combined exposure (e.g. wound care, coated biomaterials).
Biocides used as disinfectants are important to prevent the transmission of pathogens, especially during the current antibiotic resistance crisis. This crisis is exacerbated by phenotypically tolerant persister subpopulations which can survive transient antibiotic treatment and facilitate resistance evolution. Despite the transient nature of disinfection, knowledge concerning persistence to disinfectants and its link to resistance evolution is currently lacking. Here, we show that E. coli displays persistence against a widely used disinfectant benzalkonium chloride (BAC). Periodic, persister-mediated failure of disinfection rapidly selects for BAC tolerance. BAC tolerance is associated with reduced cell surface charge and mutations in the novel tolerance locus lpxM. Moreover, the fitness cost incurred by BAC tolerance turned into a fitness benefit in the presence of antibiotics, suggesting a selective advantage of BAC-tolerant mutants in antibiotic environments. Our findings provide a mechanistic underpinning for the faithful application of disinfectants to prevent multi-drug-resistance evolution and to steward the efficacy of biocides and antibiotics.
Biocides used as disinfectants are important to prevent the transmission of pathogens, especially during the current antibiotic resistance crisis. This crisis is exacerbated by phenotypically tolerant persister subpopulations which can survive transient antibiotic treatment and facilitate resistance evolution. Despite the transient nature of disinfection, knowledge concerning persistence to disinfectants and its link to resistance evolution is currently lacking. Here, we show that E. coli displays persistence against a widely used disinfectant benzalkonium chloride (BAC). Periodic, persister-mediated failure of disinfection rapidly selects for BAC tolerance. BAC tolerance is associated with reduced cell surface charge and mutations in the novel tolerance locus lpxM. Moreover, the fitness cost incurred by BAC tolerance turned into a fitness benefit in the presence of antibiotics, suggesting a selective advantage of BAC-tolerant mutants in antibiotic environments. Our findings provide a mechanistic underpinning for the faithful application of disinfectants to prevent multi-drug-resistance evolution and to steward the efficacy of biocides and antibiotics.
Biocides, including disinfectants and antimicrobial surfaces (AMCs), are important to prevent the spread of pathogens and antimicrobial resistant bacteria via surfaces. However, concerns have been raised about the evolution and selection of resistance against disinfectants and AMCs. In turn, resistance against disinfectants and AMCs can be associated to antibiotic resistance due to cross-resistance and co-resistance. We need to understand the mechanisms and risks of disinfectants and AMCs for resistance and cross-resistance evolution to optimize their application and safeguard their long-term efficacy. We used adaptive laboratory evolution (ALE) experiments based on repeated exposure of bacteria to disinfectants. Our results show that repeated disinfection of E. coli with benzalkonium chloride in suspension results in a 2000-fold increase in survival within 5 exposure cycles. Adaption is linked to the initial presence of persister cells highly tolerant to benzalkonium chloride. We used the same approach to develop standardizable ALE experiments to determine resistance evolution to AMCs. The results highlight rapid adaptation of E. coli and P. aeruginosa towards copper surfaces. Moreover, there are multiple situations in the clinic or in the environment in which biocides and antibiotics co-occur and in which combination effects can shape their antimicrobial activity or their selective effects. Our work with P. aeruginosa shows prevalent combination effects of biocides and antibiotics, ranging from synergy to antagonism and resulting in the selection for or against antibiotic resistant strains. The combination effects are dependent on the biofilm mode-of-growth, manifesting in apparent differences in the structural arrangement of antibiotic sensitive and resistant strains in biofilms exposed to combinations. Furthermore, biocides affect rates of mutation and horizontal gene transfer, thereby having a potential facilitating effect on resistance evolution. Taken together, our work shows that the role of biocides as potential drivers of resistance evolution and selection deserves further study and regulative action.
Most microorganisms live in environments where nutrients are limited and fluctuate over time. Cells respond to nutrient fluctuations by sensing and adapting their physiological state. Recent studies suggest phenotypic heterogeneity in isogenic populations as an alternative strategy in fluctuating environments, where a subpopulation of cells express a function that allows growth under conditions that might arise in the future. It is unknown how environmental factors such as nutrient limitation shape phenotypic heterogeneity in metabolism and whether this allows cells to respond to nutrient fluctuations. Here, we show that substrate limitation increases phenotypic heterogeneity in metabolism, and this heterogeneity allows cells to cope with substrate fluctuations. We subjected the N2-fixing bacterium Klebsiella oxytoca to different levels of substrate limitation and substrate shifts, and obtained time-resolved single-cell measurements of metabolic activities using nanometre-scale secondary ion mass spectrometry (NanoSIMS). We found that the level of NH4+ limitation shapes phenotypic heterogeneity in N2 fixation. In turn, the N2 fixation rate of single cells during NH4+ limitation correlates positively with their growth rate after a shift to NH4+ depletion, experimentally demonstrating the benefit of heterogeneity. The results indicate that phenotypic heterogeneity is a general solution to two important ecological challenges - nutrient limitation and fluctuations - that many microorganisms face. Currently, we use NanoSIMS to develop a new approach that defines functionally-relevant, phenotypic biodiversity in microbial systems.
Populations of genetically identical cells that share the same environment can differ markedly in their phenotypes. This phenomenon has been termed phenotypic heterogeneity. While a few molecular mechanisms that lead to heterogeneity in gene expression have been elucidated, it remains unclear how heterogeneity in gene expression is transmitted to heterogeneity in activity; especially in metabolism. Metabolic activity of single bacterial cells can be quantified by labeling the substrate with stable isotopes and by measuring label uptake with nanometer-scale secondary ion mass spectrometry (NanoSIMS). Here we combined NanoSIMS with single-molecule mRNA fluorescence in situ hybridization (smFISH) to link heterogeneity in gene expression and metabolism in nitrogen fixing bacteria. We find that gene expression and metabolic activity are decoupled in single cells. However, heterogeneity in gene expression is correlated with heterogeneity in metabolic activity on the population level. Gene expression kinetics can provide insights into the molecular mechanisms that lead to heterogeneity in metabolism.
Populations of genetically identical cells that share the same environment can differ markedly in their phenotypes. This phenomenon has been termed phenotypic heterogeneity. While a few molecular mechanisms that lead to heterogeneity in gene expression have been elucidated, it remains unclear how heterogeneity in gene expression is transmitted to heterogeneity in activity; especially in metabolism. Metabolic activity of single bacterial cells can be quantified by labeling the substrate with stable isotopes and by measuring label uptake with nanometer-scale secondary ion mass spectrometry (NanoSIMS). Here we combined NanoSIMS with single-molecule mRNA fluorescence in situ hybridization (smFISH) to link heterogeneity in gene expression and metabolism in nitrogen fixing bacteria. We find that gene expression and metabolic activity are decoupled in single cells. However, heterogeneity in gene expression is correlated with heterogeneity in metabolic activity on the population level. Gene expression kinetics can provide insights into the molecular mechanisms that lead to heterogeneity in metabolism.
Most microorganisms live in environments where nutrients are limited and fluctuate over time. Cells respond to nutrient fluctuations by sensing and adapting their physiological state. Recent studies suggest phenotypic heterogeneity in isogenic populations as an alternative strategy in fluctuating environments, where a subpopulation of cells express a function that allows growth under conditions that might arise in the future. It is unknown how environmental factors such as nutrient limitation shape phenotypic heterogeneity in metabolism and whether this allows cells to respond to nutrient fluctuations. Here, we show that substrate limitation increases phenotypic heterogeneity in metabolism, and this heterogeneity allows cells to cope with substrate fluctuations. We subjected the N2-fixing bacterium Klebsiella oxytoca to different levels of substrate limitation and substrate shifts, and obtained time-resolved single-cell measurements of metabolic activities using nanometre-scale secondary ion mass spectrometry (NanoSIMS). We found that the level of NH4+ limitation shapes phenotypic heterogeneity in N2 fixation. In turn, the N2 fixation rate of single cells during NH4+ limitation correlates positively with their growth rate after a shift to NH4+ depletion, experimentally demonstrating the benefit of heterogeneity. The results indicate that phenotypic heterogeneity is a general solution to two important ecological challenges - nutrient limitation and fluctuations - that many microorganisms face. Currently, we use NanoSIMS to develop a new approach that defines functionally-relevant, phenotypic biodiversity in microbial systems. In the last part of my presentation, I will highlight why the concept of phenotypic diversity is relevant for the understanding of antimicrobial resistance.