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During adaptive laboratory evolution experiments, any unexpected interruption in data monitoring or control could lead to the loss of valuable experimental data and compromise the integrity of the entire experiment. Most homemade mini-bioreactors are built employing microcontrollers such as Arduino. Although affordable, these platforms lack the robustness of the programmable logic controller (PLC), which enhances the safety and robustness of the control process. Here, we describe the design and validation of a PLC-controlled morbidostat, an innovative automated continuous-culture mini-bioreactor specifically created to study the evolutionary pathways to drug resistance in microorganisms. This morbidostat includes several improvements, both at the hardware and software level, for better online monitoring and a more robust operation. The device was validated employing Escherichia coli, exploring its adaptive evolution in the presence of didecyldimethylammonium chloride (DDAC), a quaternary ammonium compound widely used for its antimicrobial properties. E. coli was subjected to increasing concentrations of DDAC over 3 days. Our results demonstrated a significant increase in DDAC susceptibility, with evolved populations exhibiting substantial changes in their growth after exposure. [ABSTRACT FROM AUTHOR]

In a conventional morbidostat, cell growth is monitored by measuring OD, and stress conditions are automatically adjusted using OD values. However, phenomena such as biofilm formation, agglomeration, and the presence of opaque substrates or products can result in inaccurate OD measurements of population size, causing morbidostat systems to fail to adjust stress conditions appropriately.This study offers a solution for circumstances where it is impractical to determine vital activity based on OD by developing a novel morbidostat system that adjusts stress conditions based on measurements of exhaust CO2. As a proof of concept, the adaptation of E. coli ATCC 47076 to 48 °C was performed with two morbidostats using this new strategy. Both populations evolved in the morbidostats were confirmed to grow at 48 °C, a temperature their ancestral strain cannot withstand.

During adaptive laboratory evolution experiments, any unexpected interruption in data monitoring or control could lead to the loss of valuable experimental data and compromise the integrity of the entire experiment. Most homemade mini-bioreactors are built employing microcontrollers such as Arduino. Although affordable, these platforms lack the robustness of the programmable logic controller (PLC), which enhances the safety and robustness of the control process. Here, we describe the design and validation of a PLC-controlled morbidostat, an innovative automated continuous-culture mini-bioreactor specifically created to study the evolutionary pathways to drug resistance in microorganisms. This morbidostat includes several improvements, both at the hardware and software level, for better online monitoring and a more robust operation. The device was validated employing Escherichia coli, exploring its adaptive evolution in the presence of didecyldimethylammonium chloride (DDAC), a quaternary ammonium compound widely used for its antimicrobial properties. E. coli was subjected to increasing concentrations of DDAC over 3 days. Our results demonstrated a significant increase in DDAC susceptibility, with evolved populations exhibiting substantial changes in their growth after exposure.

The morbidostat is a bacteria culture device that progressively increases antibiotic drug concentration. It is used to study the evolutionary pathway. In this article, we construct mathematical models for the morbidostat. First we consider the case of no mutations, we study limiting systems and obtain criteria for the large time behavior of the solutions. From the theoretical results and numerical simulations, we conclude that there are two competitive exclusion states of either wild type or mutant type as the threshold parameter $ U $ varies. There are three cases, wild type bacteria excludes all mutants; a mutant dominates in the competition; oscillation between the above two states. Next we study the systems of forward mutations and forward-backward mutations. Then we apply a result of pertubation for globally stable state.

Several studies have demonstrated that antimicrobial resistance (AMR) can result from natural mutations or the acquisition of foreign antimicrobial resistance genes. Many environmental parameters are known to affect AMR, including trace antibiotic concentrations in water, pH, hydraulic retention time, and nutrient concentration, among others. However, most analyses that investigate these parameters analyze them independently. This study investigated the development of natural resistance in Salmonella sp., and the horizontal transfer of resistance genes from an imipenem- resistant (IR) E. coli strain under varying environmental conditions. An automated continuous-culture device was employed to investigate the effect of external parameters of relevance to wastewater treatment plants and to conduct a multiparametric analysis to determine the relative importance of the different variables. In terms of mutation-driven resistance, hydraulic retention time, trace antibiotic concentration, and initial cell concentrations are the leading factors contributing to higher IR in Salmonella spp. In the case of acquired resistance, the initial trace antibiotic concentrations, and hydraulic retention times were also important, but pH, initial nutrient concentration, and, very importantly, the initial concentration of IR E. coli , were the leading factors contributing to IR in Salmonella spp. These results point out some important factors that need to be considered during the design and operation of wastewater treatment plants to minimize the appearance and transmission of antibiotic resistance. [Display omitted] • Used continuous-culture device for multiparametric study of AMR. • Mutation resistance is driven by HRT, trace antibiotic, and bacteria concentration. • Acquired resistance is driven by pH, trace antibiotic, and AMR gene donor. • Emphasized the importance of removing trace antibiotic concentrations in Wastewater. [ABSTRACT FROM AUTHOR]

To obtain a detailed picture of the dynamics of antibiotic resistance development in Neisseria gonorrhoeae, we built a morbidostat according to the protocol of Toprak et al., adjusted to the specific characteristics required for the growth of N. gonorrhoeae. In this article we describe the adaptations, specifications and the difficulties we encountered during the construction and optimization of the NG morbidostat. As a proof of concept, we conducted a morbidostat experiment by increasing concentrations of azithromycin in response to bacterial growth. We started the experiment with two N. gonorrhoeae reference strains WHO-F and WHO-X. These strains were grown in 12 mL GC Broth supplemented with IsoVitaleX™ (1%) and vancomycin, colistin, nystatin, trimethoprim (VCNT) selective supplement for 30 days in a 6% CO 2 environment at 36°C. Samples of the cultures were taken 2-3 times a week and minimal inhibitory concentrations (MICs) of azithromycin were determined using E-test. The initial MICs of WHO-F and WHO-X were 0.125 µg/mL and 0.25 µg/mL, respectively. In less than 30 days, we were able to induce high level azithromycin resistance in N. gonorrhoeae, with a 750 and 1000 fold increase in MIC for WHO-F and WHO-X, respectively.

In a conventional morbidostat, cell growth is monitored by measuring OD, and stress conditions are automatically adjusted using OD values. However, phenomena such as biofilm formation, agglomeration, and the presence of opaque substrates or products can result in inaccurate OD measurements of population size, causing morbidostat systems to fail to adjust stress conditions appropriately. This study offers a solution for circumstances where it is impractical to determine vital activity based on OD by developing a novel morbidostat system that adjusts stress conditions based on measurements of exhaust CO 2 . As a proof of concept, the adaptation of E. coli ATCC 47076 to 48 °C was performed with two morbidostats using this new strategy. Both populations evolved in the morbidostats were confirmed to grow at 48 °C, a temperature their ancestral strain cannot withstand., Competing Interests: I declare that I have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author. Published by Elsevier B.V.)

Microbial evolution experiments provide a powerful tool to unravel the molecular basis of adaptive evolution but their outcomes can be difficult to interpret, unless the selective forces that are applied during the experiment are carefully controlled. In this respect, experimental evolution in continuous cultures provides advantages over commonly used sequential batch‐culture protocols because continuous cultures allow for more accurate control over the induced selective environment. However, commercial continuous‐culture systems are large and expensive, while available DIY continuous‐culture systems are not versatile enough to allow for multiple sensors and rigorous stirring.We present a modular continuous‐culture system that adopts the commonly used GL45 glass laboratory bottle as a bioreactor vessel. Our design offers three advantages: first, it is equipped with a large head plate, fitting two sensors and seven input/output ports, enabling the customization of the system for many running modes (chemostat, auxostat, etc.). Second, the bioreactor is small (25–250 ml), which makes it feasible to run many replicates in parallel. Third, bioreactor modules can be coupled by uni‐ or bi‐directional flows to induce spatiotemporal variation in selection. These features result in a particularly flexible culturing platform that facilitates the investigation of a broad range of evolutionary and ecological questions.To illustrate the versatility of our culturing system, we outline two evolution experiments that impose a temporally or spatially variable regime of selection. The first experiment illustrates how controlled temporal variation in resource availability can be utilized to select for anticipatory switching. The second experiment illustrates a spatially structured morbidostat setup that is designed to probe epistatic interactions between adaptive mutations. Furthermore, we demonstrate how sensor data can be used to stabilize selection pressures or track evolutionary adaptation.Evolution experiments in which populations are exposed to controlled spatiotemporal variation, are essential to gain insight into the process of adaptation and the mechanisms that constrain evolution. Continuous‐culture systems, like the one presented here, offer control over key environmental parameters and establish a well‐defined regime of selection. As such, they create the opportunity to expose evolutionary constraints in the form of phenotypic trade‐offs, contributing to a mechanistic understanding of adaptive evolution. [ABSTRACT FROM AUTHOR]

To obtain a detailed picture of the dynamics of antibiotic resistance development in Neisseria gonorrhoeae, we built a morbidostat according to the protocol of Toprak et al., adjusted to the specific characteristics required for the growth of N. gonorrhoeae. In this article we describe the adaptations, specifications and the difficulties we encountered during the construction and optimization of the NG morbidostat. As a proof of concept, we conducted a morbidostat experiment by increasing concentrations of azithromycin in response to bacterial growth. We started the experiment with two N. gonorrhoeae reference strains WHO-F and WHO-X. These strains were grown in 12 mL GC Broth supplemented with IsoVitaleX™ (1%) and vancomycin, colistin, nystatin, trimethoprim (VCNT) selective supplement for 30 days in a 6% CO 2 environment at 36°C. Samples of the cultures were taken 2-3 times a week and minimal inhibitory concentrations (MICs) of azithromycin were determined using E-test. The initial MICs of WHO-F and WHO-X were 0.125 µg/mL and 0.25 µg/mL, respectively. In less than 30 days, we were able to induce high level azithromycin resistance in N. gonorrhoeae, with a 750 and 1000 fold increase in MIC for WHO-F and WHO-X, respectively.

A morbidostat is a bacteria culture device that maintains a nearly constant microbial population for the selection of drug-resistant mutants via a feedback algorithm. In this paper, the global dynamics of a microbial species undergoing sequential evolution are studied in detail to elucidate the operation of a morbidostat. The cultivation of the microbes is assumed to be under periodic dilution, and a simple threshold algorithm is used as feedback. We also prove the extinction and uniform persistence of all species with both forward and backward mutation in a sequential evolution scenario. Numerical simulations for the case of logistic growth and the Hill function for drug inhibition are also applied to verify our theoretical results. The theoretical framework elucidates the generic features of the operation of a morbidostat under drug-inhibitor-induced feedback and will provide a useful aid for the design of experiments. [ABSTRACT FROM AUTHOR]

Resistance to the broad-spectrum antibiotic ciprofloxacin is detected at high rates for a wide range of bacterial pathogens. To investigate the dynamics of ciprofloxacin resistance development, we applied a comparative resistomics workflow for three clinically relevant species of Gram-negative bacteria: Escherichia coli, Acinetobacter baumannii, and Pseudomonas aeruginosa. We combined experimental evolution in a morbidostat with deep sequencing of evolving bacterial populations in time series to reveal both shared and unique aspects of evolutionary trajectories. Representative clone characterization by sequencing and MIC measurements enabled direct assessment of the impact of mutations on the extent of acquired drug resistance. In all three species, we observed a two-stage evolution: (i) early ciprofloxacin resistance reaching 4- to 16-fold the MIC for the wild type, commonly as a result of single mutations in DNA gyrase target genes ( gyrA or gyrB ), and (ii) additional genetic alterations affecting the transcriptional control of the drug efflux machinery or secondary target genes (DNA topoisomerase parC or parE ). IMPORTANCE The challenge of spreading antibiotic resistance calls for systematic efforts to develop more "irresistible" drugs based on a deeper understanding of dynamics and mechanisms of antibiotic resistance acquisition. To address this challenge, we have established a comparative resistomics approach which combines experimental evolution in a continuous-culturing device, the morbidostat, with ultradeep sequencing of evolving microbial populations to identify evolutionary trajectories (mutations and genome rearrangements) leading to antibiotic resistance over a range of target pathogens. Here, we report the comparative resistomics study of three Gram-negative bacteria (Escherichia coli, Acinetobacter baumannii, and Pseudomonas aeruginosa), which revealed shared and species-specific aspects of the evolutionary landscape leading to robust resistance against the clinically important antibiotic ciprofloxacin. Despite some differences between morbidostat-deduced mutation profiles and those observed in clinical isolates of individual species, a cross-species comparative resistomics approach allowed us to recapitulate all types of clinically relevant ciprofloxacin resistance mechanisms. This observation supports the anticipated utility of this approach in guiding rational optimization of treatment regimens for current antibiotics and the development of novel antibiotics with minimized resistance propensities.

Understanding the dynamics and mechanisms of acquired drug resistance across major classes of antibiotics and bacterial pathogens is of critical importance for the optimization of current anti-infective therapies and the development of novel ones. To systematically address this challenge, we developed a workflow combining experimental evolution in a morbidostat continuous culturing device with deep genomic sequencing of population samples collected in time series. This approach was applied to the experimental evolution of six populations of Escherichia coli BW25113 towards acquiring resistance to triclosan (TCS), an antibacterial agent in various consumer products. This study revealed the rapid emergence and expansion (up to 100% in each culture within 4 days) of missense mutations in the fabI gene, encoding enoyl-acyl carrier protein reductase, the known TCS molecular target. A follow-up analysis of isolated clones showed that distinct amino acid substitutions increased the drug IC 90 in a 3-16-fold range, reflecting their proximity to the TCS-binding site. In contrast to other antibiotics, efflux-upregulating mutations occurred only rarely and with low abundance. Mutations in several other genes were detected at an earlier stage of evolution. Most notably, three distinct amino acid substitutions were mapped in the C-terminal periplasmic domain of CadC protein, an acid stress-responsive transcriptional regulator. While these mutations do not confer robust TCS resistance, they appear to play a certain, yet unknown, role in adaptation to relatively low drug pressure. Overall, the observed evolutionary trajectories suggest that the FabI enzyme is the sole target of TCS (at least up to the ~50 µm level), and amino acid substitutions in the TCS-binding site represent the main mechanism of robust TCS resistance in E. coli . This model study illustrates the potential utility of the established morbidostat-based approach for uncovering resistance mechanisms and target identification for novel drug candidates with yet unknown mechanisms of action.

To obtain a detailed picture of the dynamics of antibiotic resistance development in Neisseria gonorrhoeae , we built a morbidostat according to the protocol of Toprak et al ., adjusted to the specific characteristics required for the growth of N. gonorrhoeae . In this article we describe the adaptations, specifications and the difficulties we encountered during the construction and optimization of the NG morbidostat. As a proof of concept, we conducted a morbidostat experiment by increasing concentrations of azithromycin in response to bacterial growth. We started the experiment with two N. gonorrhoeae reference strains WHO-F and WHO-X. These strains were grown in 12 mL GC Broth supplemented with IsoVitaleX™ (1%) and vancomycin, colistin, nystatin, trimethoprim (VCNT) selective supplement for 30 days in a 6% CO 2 environment at 36°C. Samples of the cultures were taken 2-3 times a week and minimal inhibitory concentrations (MICs) of azithromycin were determined using E-test. The initial MICs of WHO-F and WHO-X were 0.125 µg/mL and 0.25 µg/mL, respectively. In less than 30 days, we were able to induce high level azithromycin resistance in N. gonorrhoeae , with a 750 and 1000 fold increase in MIC for WHO-F and WHO-X, respectively., Competing Interests: No competing interests were disclosed., (Copyright: © 2019 Verhoeven E et al.)

Colistin is a last-resort antibiotic commonly used against multidrug-resistant strains of Pseudomonas aeruginosa To investigate the potential for in situ evolution of resistance against colistin and to map the molecular targets of colistin resistance, we exposed two P. aeruginosa isolates to colistin using a continuous-culture device known as a morbidostat. As a result, colistin resistance reproducibly increased 10-fold within 10 days and 100-fold within 20 days, along with highly stereotypic yet strain-specific mutation patterns. The majority of mutations hit the pmrAB two-component signaling system and genes involved in lipopolysaccharide (LPS) synthesis, including lpxC , pmrE , and migA We tracked the frequencies of all arising mutations by whole-genome deep sequencing every 3 to 4 days to obtain a detailed picture of the dynamics of resistance evolution, including competition and displacement among multiple resistant subpopulations. In 7 out of 18 cultures, we observed mutations in mutS along with a mutator phenotype that seemed to facilitate resistance evolution., (Copyright © 2017 American Society for Microbiology.)