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Microbiologically induced corrosion due to bacterial biofilms causes several problems in industrial systems, technical applications and in medicine. Prior to the formation of a biofilm on a substrate, planktonic cells attach on the surface. Hence, the properties of the surface play a key role in biofilm formation and are of great importance for the development of strategies to prevent bacterial attachment and biofilm formation.
This project aims at clarifying to which extent surface micro-/nanostructuring and chemical functionalization affects bacterial attachment and whether a synergistic combination of the two can be used to control bacterial adhesion. To answer these questions, model surfaces with regular patterns of 5-10 micrometers in size have been prepared, which provide distinct zones differing in terms of their chemistry or nano-roughness. This was achieved by micro contact printing of self-assembled monolayers with different functional groups and deposition of patterned ZnO nanorod arrays for studying the effect of surface chemistry and morphology, respectively. Typical contrasts studied were combinations of positively/negatively charged, hydrophobic/hydrophilic or flat/rough.
The attachment behavior of bacteria on tailored surfaces were studied in a flow chamber as a function of time. The strain Pseudomonas fluorescens SBW25 was chosen as a model organism. DNA-intercalating dyes such as Syto9 have a high affinity to adsorb on ZnO nanorods. To overcome this limitation a genetic modification was performed by introducing a gene which expresses a green fluorescent protein in P. fluorescens SBW25 enabling the quantitative evaluation of the flow chamber studies by means of fluorescence microscopy. Further analysis of the attachment behavior was performed by means of scanning electron microscopy.
The presentation will summarize the results of our systematic study on the role of individual parameters on bacterial attachment and highlight synergistic combinations, showing an inhibition or enhancing effect. As the investigations with model substrates enable a precise control of the surface parameters, this approach can be applied to different microorganisms and material systems to achieve a correlative description of bacterial adhesion on solid surfaces.
This 6 minute long MP4-video presents some key results of the European research project "BioCombs4Nanofibers" to the broader public. Inspired by nature, some concepts of certain types of spiders are transferred to technology in order to develop bacteria-repellent surfaces through laser surface nanostructuring.
Funding notice: This study was funded by the European Union's research and innovation program under the FET Open grant agreement No. 862016 (BioCombs4Nanofibers, http://biocombs4nanofibers.eu).
Biofilm formation on materials leads to high costs in industrial processes, as well as in medical applications. This fact has stimulated interest in the development of new materials with improved surfaces to reduce bacterial adhesion.
We present a flow chamber system to test and quantify bacterial adhesion on materials that are part of antifouling concepts. The adhesion process is standardized and can be adapted to different bacteria in subaquatic of subaerial environments. It is combined with a standardized evaluation procedure based on statistical evidence.
Assessing co-selection of biocide and antibiotic resistance in wastewater microbial communities
(2022)
Biocides are used for a wide range of purposes, including disinfectants or preservatives. Biocides play a major role in the prevention of microbial infections in healthcare and animal husbandry. The use of biocides often leads to the discharge of active biocidal substances into wastewater streams, causing the exposure of wastewater microbial communities to subinhibitory concentrations. In turn, it is known that wastewater treatment plants (WWTP) are hotspots for antibiotic resistant bacteria. Since similar mechanisms confer resistance to biocides and antibiotics, exposure to biocides can result in co-selection of antibiotic resistant bacteria in WWTP due to biocides. Here, we investigate the magnitude and the drivers of co-selection of antibiotic resistance in natural wastewater microbial communities upon biocide exposure. Microbial communities will be sampled at the WWTP Ruhleben in Berlin and characterized regarding their biocide and antibiotic resistance. Changes in the resistance level after exposure to different biocides will be determined by enumerating resistant and non-resistant E. coli and heterotrophic bacteria on selective plates with and without several biocides and antibiotics. Moreover, we are establishing a synthetic community comprising about 100 environmental E. coli isolates each with different antimicrobial resistance traits. Each isolate will be tagged with a unique DNA-barcode. All isolates will be pooled and exposed to different biocides at various concentrations. The barcode labeling enables us to determine the abundance of each isolate at the beginning and end of the experiment by transposon-tag sequencing. The project results will inform risk assessment of the effects of biocidal residues on antimicrobial resistance selection in WWTP.
The project is part of the BIOCIDE consortium funded within the call on Aquatic pollutants by JPI-AMR, JPI-OCEANS and JPI-WATER.
Biocides are used for a wide range of purposes, including disinfectants or preservatives. They play a major role in the prevention of microbial infections in healthcare and animal husbandry. The use of biocides often leads to the discharge of active biocidal substances into wastewater streams, causing the exposure of wastewater microbial communities to subinhibitory concentrations. In turn, it is known that wastewater treatment plants (WWTP) are hotspots for antibiotic resistant bacteria. Since similar mechanisms confer resistance to biocides and antibiotics, exposure to biocides can result in co-selection of antibiotic resistant bacteria in WWTP Here, we want to investigate co-selection processes of antibiotic resistance in natural WWTP microbial communities upon biocide exposure. Microbial communities were sampled at the WWTP Ruhleben in Berlin and characterized regarding their susceptibility against different clinically relevant antibiotics. To investigate the link between biocide exposure and antibiotic resistance, changes in the susceptibility level after exposure to environmentally relevant concentrations of the commonly used biocide didecyldimethylammonium chloride (DDAC) will be determined by enumerating resistant and non-resistant E. coli on selective plates with and without antibiotics and DDAC. In case of antibiotics, clinical breakpoint concentrations according to EUCAST will be used to discriminate between susceptible and resistant strains. In case of DDAC (and biocides in general), clinical breakpoints do not exist. Therefore, we determined a cut-off concentration at which the majority of naturally-occurring E. coli strains cannot grow anymore based on (I) the MIC (minimal inhibitory concentration) distribution, and (II) by plating wastewater communities onto selective indicator agar plates loaded with increasing DDAC concentration. Additionally, antibiotic cross-resistance will be determined by spotting single colonies, isolated from DDAC-selective plates onto antibiotic plates. The results of our experiments will help to determine selective concentrations and to estimate the risk of antibiotic co-selection and cross-resistance in microbial WWTP communities upon biocide exposure.
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.
Antimicrobial resistance (AMR) is a global health problem with the environment being an important compartment for the evolution, selection and transmission of AMR. These processes are impacted by pollution with antibiotics. However, biocides used as disinfectants and material preservatives are major pollutants by far excceding the market for antibiotics in terms of mass. Our work shows that biocides have the potential to affect evolutionary processes towards AMR by increasing the rates of de-novo mutation and conjugation. These effects depend on the species and biocidal substance. Importantly, chlorhexidine and quaternary ammonium compounds (QACs) affect rates of mutation and conjugation at environmentally relevant concentrations in E. coli. Moreover, our results show a connection between the RpoS-mediated general stress and the RecA-linked SOS response with increased rates of mutation and conjugation, but not for all biocides. Furthermore, our work highlights the potential of biocides to contribute to selection and transmission of AMR. We show that the application of biocides, especially QAC disinfectants, leads to the rapid evolution of tolerance (i.e. increased survival) in adaptive laboratory evolution (ALE) experiments. The evolved tolerant strains have a selective advantage in the presence of environmentally-relevant concentrations of antibiotics, which could lead to the stabilization of biocide tolerance in environments where biocides and antibiotics co-occur (e.g. wastewater, animal stables). ALE experiments with biocide tolerant strains indicate a decreased evolvability of resistance to antibiotics. Taken together, our work shows the importance of assessing the contribution of biocides on evolution, selection and transmission of AMR in the environment.
BIOCIDE
(2022)
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.
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, 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. In the last part of my presentation, I will highlight why the concept of phenotypic diversity is relevant for the understanding of antimicrobial resistance.
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.