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Populations of genetically identical cells can display marked variation in phenotypic traits; such variation is termed phenotypic heterogeneity. Here, we investigate the effect of substrate and electron donor limitation on phenotypic heterogeneity in N2 and CO2 fixation in the green sulphur bacterium Chlorobium phaeobacteroides. We grew populations in chemostats and batch cultures and used stable isotope labelling combined with nanometer‐scale secondary ion mass spectrometry (NanoSIMS) to quantify phenotypic heterogeneity. Experiments in H2S (i.e. electron donor) limited chemostats show that varying levels of NH4+ limitation induce heterogeneity in N2 fixation. Comparison of phenotypic heterogeneity between chemostats and batch (unlimited for H2S) populations indicates that electron donor limitation drives heterogeneity in N2 and CO2 fixation. Our results demonstrate that phenotypic heterogeneity in a certain metabolic activity can be driven by different modes of limitation and that heterogeneity can emerge in different metabolic processes upon the same mode of limitation. In conclusion, our data suggest that limitation is a general driver of phenotypic heterogeneity in microbial populations.
A fundamental question in ecology is how biodiversity affects ecosystem function. Biodiversity is commonly estimated based on genetic variation. We investigated a new approach that defines and measures biodiversity in complex microbial communities. We used the variation in multiple functionally-relevant, phenotypic traits measured in parallel in single cells as a metric for microbial phenotypic diversity. We studied phenotypic diversity and ecosystem functioning throughout different photosynthetic layers dominated by divergent microbial communities in the gradient of Lago di Cadagno. We determined genetic diversity by 16S and 18S amplicon sequencing and bulk ecosystem functioning (photosynthesis). In addition, we determined phenotypic diversity using single-cell technologies such as nanometer-scale secondary ion mass spectrometry (NanoSIMS) correlated with confocal laser scanning microscopy (CLSM) and scanning flow-cytometry. We measured functional trait variation between individuals in 13CO2 fixation, 15NH4+ uptake, and variation in physio-morphological cell traits, such as cell size, shape, and auto-fluorescence for various pigments related to photosynthesis. We used the distances between individuals in a multidimensional trait space to derive phenotypic trait-based diversity indices, such as trait richness, trait evenness, and trait divergence. We find that phenotypic trait divergence associates with ecosystem functioning, whereas genetic diversity does not. Including activity-based, single-cell phenotypic measurements with NanoSIMS provided an additional accuracy to the trait-based diversity assessment and allowed us to formulate hypotheses on the mechanisms that shape the correlation between phenotypic diversity and eco-system function. Together, our results show that phenotypic diversity is a meaningful concept to measure microbial biodiversity and associate it with ecosystem functioning.
A fundamental question in ecology is how biodiversity affects ecosystem function. Biodiversity is commonly estimated based on genetic variation. We investigated a new approach that defines and measures biodiversity in complex microbial communities. We used the variation in multiple functionally-relevant, phenotypic traits measured in parallel in single cells as a metric for microbial phenotypic diversity. We studied phenotypic diversity and ecosystem functioning throughout different photosynthetic layers dominated by divergent microbial communities in the gradient of Lago di Cadagno. We determined genetic diversity by 16S and 18S amplicon sequencing and bulk ecosystem functioning (photosynthesis). In addition, we determined phenotypic diversity using single-cell technologies such as nanometer-scale secondary ion mass spectrometry (NanoSIMS) correlated with confocal laser scanning microscopy (CLSM) and scanning flow-cytometry. We measured functional trait variation between individuals in 13CO2 fixation, 15NH4+ uptake, and variation in physio-morphological cell traits, such as cell size, shape, and auto-fluorescence for various pigments related to photosynthesis. We used the distances between individuals in a multidimensional trait space to derive phenotypic trait-based diversity indices, such as trait richness, trait evenness, and trait divergence. We find that phenotypic trait divergence associates with ecosystem functioning, whereas genetic diversity does not. Including activity-based, single-cell phenotypic measurements with NanoSIMS provided an additional accuracy to the trait-based diversity assessment and allowed us to formulate hypotheses on the mechanisms that shape the correlation between phenotypic diversity and eco-system function. Together, our results show that phenotypic diversity is a meaningful concept to measure microbial biodiversity and associate it with ecosystem functioning.
A fundamental question in ecology is how biodiversity affects ecosystem function. Biodiversity is commonly estimated based on genetic variation. We investigated a new approach that defines and measures biodiversity in complex microbial communities. We used the variation in multiple functionally-relevant, phenotypic traits measured in parallel in single cells as a metric for microbial phenotypic diversity. We studied phenotypic diversity and ecosystem functioning throughout different photosynthetic layers dominated by divergent microbial communities in the gradient of Lago di Cadagno. We determined genetic diversity by 16S and 18S amplicon sequencing and bulk ecosystem functioning (photosynthesis). In addition, we determined phenotypic diversity using single-cell technologies such as nanometer-scale secondary ion mass spectrometry (NanoSIMS) correlated with confocal laser scanning microscopy (CLSM) and scanning flow-cytometry. We measured functional trait variation between individuals in 13CO2 fixation, 15NH4+ uptake, and variation in physio-morphological cell traits, such as cell size, shape, and auto-fluorescence for various pigments related to photosynthesis. We used the distances between individuals in a multidimensional trait space to derive phenotypic trait-based diversity indices, such as trait richness, trait evenness, and trait divergence. We find that phenotypic trait divergence associates with ecosystem functioning, whereas genetic diversity does not. Including activity-based, single-cell phenotypic measurements with NanoSIMS provided an additional accuracy to the trait-based diversity assessment and allowed us to formulate hypotheses on the mechanisms that shape the correlation between phenotypic diversity and eco-system function. Together, our results show that phenotypic diversity is a meaningful concept to measure microbial biodiversity and associate it with ecosystem functioning.
Antimicrobial surfaces have broad use in multiple settings including touch surfaces in hospitals, implanted devices, or consumer products. Their aim is to support existing hygiene procedures, and to help combat the increasing threat of antimicrobial resistance. However, concerns have been raised over the potential selection pressure exerted by such surfaces, which might drive the evolution and spread of antimicrobial resistance. In my presentation, I will highlight the risks and knowledge gaps associated with resistance on antimicrobial surfaces by different processes including evolution by de novo mutations and horizontal gene transfer, and species sorting of inherently resistant bacteria dispersed onto antimicrobial surfaces. The latter process has the potential to select for antibiotic resistance via cross-resistance between traits that confer resistance to both the antimicrobial surface coating and antibiotics. Conditions in which antibiotics and antimicrobial coatings are present simultaneously (e.g. implants) will lead to more complex interactions that can either result in the selection for or against antibiotic resistance. We mapped these interactions between several antimicrobials and antibiotics on growth and selection of Pseudomonas aeruginosa. We find prevalent physiological (i.e. synergy and antagonism) and evolutionary (i.e. cross-resistance and collateral sensitivity) combination effects. Understanding these interactions opens the door to tailor therapeutic interventions to select against resistance. In additions, we need new methods and translational studies that investigate resistance development to antimicrobial surfaces under realistic conditions. Therefore, I will present recent developments in our lab on the development of such a method based on existing efficacy standards.
Antimicrobial touch surfaces have been introduced in healthcare settings with the aim of supporting existing hygiene procedures, and to help combat the increasing threat of antimicrobial resistance. However, concerns have been raised over the potential selection pressure exerted by such surfaces, which may drive the evolution and spread of antimicrobial resistance. This review highlights studies that indicate risks associated with resistance on antimicrobial surfaces by different processes, including evolution by de-novo mutation and horizontal gene transfer, and species sorting of inherently resistant bacteria dispersed on to antimicrobial surfaces. The review focuses on antimicrobial surfaces made of copper, silver and antimicrobial peptides because of the practical application of copper and silver, and the promising characteristics of antimicrobial peptides. The available data point to a potential for resistance selection and a subsequent increase in resistant strains via cross-resistance and co-resistance conferred by metal and antibiotic resistance traits. However, translational studies describing the development of resistance to antimicrobial touch surfaces in healthcare-related environments are rare, and will be needed to assess whether and how antimicrobial surfaces lead to resistance selection in These settings. Such studies will need to consider numerous variables, including the antimicrobial concentrations present in coatings, the occurrence of biofilms on surfaces, and the humidity relevant to dry-surface environments. On-site tests on the efficacy of antimicrobial Coatings should routinely evaluate the risk of selection associated with their use.
Pseudomonas aeruginosa biofilms exhibit an intrinsic resistance to antibiotics and constitute a considerable clinical threat. In cystic fibrosis, a common feature of biofilms formed by P. aeruginosa in the airway is the occurrence of mutants deficient in flagellar motility. This study investigates the impact of flagellum deletion on the structure and antibiotic tolerance of P. aeruginosa biofilms, and highlights a role for the flagellum in adaptation and cell survival during biofilm development. Mutations in the flagellar hook protein FlgE influence greatly P. aeruginosa biofilm structuring and antibiotic tolerance. Phenotypic analysis of the flgE knockout mutant compared to the wild type (WT) reveal increased fitness under planktonic conditions, reduced initial adhesion but enhanced formation of microcolony aggregates in a microfluidic environment, and decreased expression of genes involved in exopolysaccharide formation. Biofilm cells of the flgE knock-out mutant display enhanced tolerance towards multiple antibiotics, whereas its planktonic cells show similar resistance to the WT. Confocal microscopy of biofilms demonstrates that gentamicin does not affect the viability of cells located in the inner part of the flgE knock-out mutant biofilms due to reduced penetration. These findings suggest that deficiency in flagellar proteins like FlgE in biofilms and in cystic fibrosis infections represent phenotypic and evolutionary adaptations that alter the structure of P. aeruginosa biofilms conferring increased antibiotic tolerance.
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.
Antimicrobials can exert specific physiological effects when used in combination that are different from those when applied alone. 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 effects of combinations of antibiotics (meropenem, gentamicin, and ciprofloxacin) and substances used as biocides or antiseptics [octenidine, benzalkonium chloride, cetrimonium bromide, chlorhexidine, Povidone-iodine, silver nitrate (AgNO3), and Ag-nanoparticles] on the planktonic growth rate of Pseudomonas aeruginosa. Combination effects were investigated in growth experiments in microtiter plates at different concentrations and the Bliss interaction scores were calculated. Among the 21 screened combinations, we find prevalent combination effects with synergy occurring six 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). In conclusion, antibiotics and biocides or antiseptics exert physiological combination effects on the pathogen P. aeruginosa. These effects have consequences for the efficacy of both types of substances and potentially for the selection of antimicrobial resistant strains in clinical applications with combined exposure (e.g., wound care and coated biomaterials).
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).
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).
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.
Disinfectants are important to prevent the transmission of pathogens, especially in the face of the current antibiotic resistance crisis. The crisis is further exacerbated by phenotypically tolerant persister subpopulations that can survive transient antibiotic treatment and facilitate resistance evolution. Despite the transient nature of disinfectant application, persistence to disinfectants and its role for the evolution of tolerance and cross-resistance to antibiotics has not been studied. Our work shows that E. coli displays persistence against several widely used disinfectants, including benzalkonium chloride (BAC), didecyldimethylammoniumchlorid (DDAC) and isopropanol. The molecular mechanism of BAC persistence is triggered in stationary phase and affected by several antibiotic persister genes (hipA, tisB, tolC, relA, spoT). Experimental evolution and population dynamic modeling show that repeated failure of disinfection due to persisters rapidly selects for BAC tolerance underpinned by reduced cell surface charge due to mutations in genes related to lipid A acylation (lpxML). Furthermore, evolved BAC tolerance affects the susceptibility to antibiotics, leading to positive selection of disinfectant tolerant strains at environmentally relevant antibiotic concentrations and variations in evolvability of antibiotic resistance due to epistatic effects. These results highlight the need for faithful application of disinfectants to steward their efficacy and the efficacy of antibiotics. A better understanding of the bacterial response to disinfectants is crucial to understand and avert the ongoing antimicrobial resistance crisis.
Background:
One cornerstone to prevent the spread of antibiotic resistant bacteria in clinical settings is the application of disinfectants. However, bacteria can evolve resistance to disinfectants, which in turn can confer cross-resistance to antibiotics. Additionally, clonal bacterial populations can display phenotypic heterogeneity with respect to the tolerance of antibiotic stress leading to a prolonged survival of a sub-population; this phenomenon is termed persistence. Persistence to antibiotics is an evolvable trait and can serve as a stepping stone for the evolution of genetically encoded resistance. Until now, there is a lack of systematic studies that investigate if bacterial populations establish persister subpopulations that tolerate disinfectant stress longer than most of the population.
Objectives:
Our objective is to investigate if persistence is a bacterial survival strategy against disinfectants. Furthermore, we investigate the mechanisms of disinfectant persistence and if persistence can evolve in the face of fluctuating exposure to disinfectants. Lastly, we test if the evolved mechanisms of disinfectant tolerance lead to disinfectant resistance and if they confer cross-tolerance and cross-resistance against antibiotics.
Methods:
We use time-kill assays in the presence of disinfectants and experimental evolution combined to whole-genome sequencing in the model organism E. coli.
Results:
We find persister sub-populations against chlorhexidine and quaternary ammonium compounds, but not to alcohols, aldehydes and oxidative compounds. We will present the relationship of mechanisms known to underlie antibiotic persister formation to the formation of persisters against disinfectants. In addition, we will present data from an ongoing evolution experiment for persistence against disinfectants.
Question:
One cornerstone to prevent the spread of bacteria in clinical and industrial settings is the application of biocides including disinfectants and preservatives. However, bacteria can evolve resistance to biocides, which in turn can confer cross-resistance to antibiotics. Additionally, clonal bacterial populations can display phenotypic heterogeneity with respect to the tolerance of antibiotic stress leading to a prolonged survival of a sub-population; this phenomenon is termed persistence. Persistence to antibiotics is an evolvable trait and can serve as a stepping stone for the evolution of genetically encoded resistance. Until now, there is a lack of systematic studies that investigate if bacterial populations establish persister subpopulations that tolerate disinfectant stress longer than most of the population. Our objective is to investigate if persistence is a bacterial survival strategy against biocides. Furthermore, we investigate the mechanisms of biocide persistence and if persistence can evolve in the face of fluctuating exposure to biocides. Lastly, we test if the evolved mechanisms of biocide tolerance lead to biocide resistance and if they confer cross-tolerance and cross-resistance against antibiotics.
Methods:
We use time-kill assays in the presence of biocides and experimental evolution combined to whole-genome sequencing in the model organism E. coli.
Results:
We find persister sub-populations against chlorhexidine and quaternary ammonium compounds, but not to alcohols, aldehydes and oxidative compounds. We will present the relationship of mechanisms known to underlie antibiotic persister formation to the formation of persisters against biocides. In addition, we will present data from an ongoing evolution experiment for persistence against biocides.
Conclusion
There is a link between antibiotic and biocide persistence with possible implications for antibiotic resistance evolution and spread.