Antibiotic export by efflux pumps affects growth of neighboring bacteria

Antibiotic resistance in bacterial communities

Bacteria are single-celled organisms, but the survival of microbial communities relies on complex dynamics at the molecular, cellular, and ecosystem scales. Antibiotic resistance, in particular, is not just a property of individual bacteria or even single-strain populations, but depends heavily on the community context. Collective community dynamics can lead to counterintuitive eco-evolutionary effects like survival of less resistant bacterial populations, slowing of resistance evolution, or population collapse, yet these surprising behaviors are often captured by simple mathematical models. In this review, we highlight recent progress - in many cases, advances driven by elegant combinations of quantitative experiments and theoretical models - in understanding how interactions between bacteria and with the environment affect antibiotic resistance, from single-species populations to multispecies communities embedded in an ecosystem.

Monitoring lineages of growing and dividing bacteria reveals an inducible memory of mar operon expression

In Gram negative bacteria, the multiple antibiotic resistance or mar operon, is known to control the expression of multi-drug efflux genes that protect bacteria from a wide range of drugs. As many different chemical compounds can induce this operon, identifying the parameters that govern the dynamics of its induction is crucial to better characterize the processes of tolerance and resistance. Most experiments have assumed that the properties of the mar transcriptional network can be inferred from population measurements. However, measurements from an asynchronous population of cells can mask underlying phenotypic variations of single cells. We monitored the activity of the mar promoter in single Escherichia coli cells in linear micro-colonies and established that the response to a steady level of inducer was most heterogeneous within individual colonies for an intermediate value of inducer. Specifically, sub-lineages defined by contiguous daughter-cells exhibited similar promoter activity, whereas activity was greatly variable between different sub-lineages. Specific sub-trees of uniform promoter activity persisted over several generations. Statistical analyses of the lineages suggest that the presence of these sub-trees is the signature of an inducible memory of the promoter state that is transmitted from mother to daughter cells. This single-cell study reveals that the degree of epigenetic inheritance changes as a function of inducer concentration, suggesting that phenotypic inheritance may be an inducible phenotype.

Efflux, Signaling and Warfare in a Polymicrobial World

The discovery void of antimicrobial development has occurred at a time when the world has seen a rapid emergence and spread of antimicrobial resistance, the 'perfect storm' as it has often been described. While the discovery and development of new antibiotics has continued in the research sphere, the pipeline to clinic has largely been fed by derivatives of existing classes of antibiotics, each prone to pre-existing resistance mechanisms. A novel approach to infection management has come from the ecological perspective whereby microbial networks and evolved communities already possess small molecular capabilities for pathogen control. The spatiotemporal nature of microbial interactions is such that mutualism and parasitism are often two ends of the same stick. Small molecule efflux inhibitors can directly target antibiotic efflux, a primary resistance mechanism adopted by many species of bacteria and fungi. However, a much broader anti-infective capability resides within the action of these inhibitors, borne from the role of efflux in key physiological and virulence processes, including biofilm formation, toxin efflux, and stress management. Understanding how these behaviors manifest within complex polymicrobial communities is key to unlocking the full potential of the advanced repertoires of efflux inhibitors.

Advances in linking single-cell bacterial stress response to population-level survival

Stress response mechanisms can allow bacteria to survive a myriad of challenges, including nutrient changes, antibiotic encounters, and antagonistic interactions with other microbes. Expression of these stress response pathways, in addition to other cell features such as growth rate and metabolic state, can be heterogeneous across cells and over time. Collectively, these single-cell-level phenotypes contribute to an overall population-level response to stress. These include diversifying actions, which can be used to enable bet-hedging, and coordinated actions, such as biofilm production, horizontal gene transfer, and cross-feeding. Here, we highlight recent results and emerging technologies focused on both single-cell and population-level responses to stressors, and we draw connections about the combined impact of these effects on survival of bacterial communities.

The Extent of Antimicrobial Resistance Due to Efflux Pump Regulation

A key mechanism driving antimicrobial resistance (AMR) stems from the ability of bacteria to up-regulate efflux pumps upon exposure to drugs. The resistance gained by this up-regulation is pliable because of the tight regulation of efflux pump levels. This leads to temporary enhancement in survivability of bacteria due to higher efflux pump levels in the presence of antibiotics, which can be reversed when the cells are no longer exposed to the drug. Knowledge of the extent of resistance thus gained would inform intervention strategies aimed at mitigating AMR. Here, we combine mathematical modeling and experiments to quantify the maximum extent of resistance that efflux pump up-regulation can confer via phenotypic induction in the presence of drugs and genotypic abrogation of regulation. Our model describes the dynamics of drug transport in and out of cells coupled with the associated regulation of efflux pump levels and predicts the increase in the minimum inhibitory concentration (MIC) of drugs due to such regulation. To test the model, we measured the uptake and efflux as well as the MIC of the compound ethidium bromide (EtBr), a substrate of the efflux pump LfrA, in wild-type Mycobacterium smegmatis mc²155, as well as in two laboratory-generated strains. Our model captured the observed EtBr levels and MIC fold-changes quantitatively. Further, the model identified key parameters associated with the resulting resistance, variations in which could underlie the extent to which such resistance arises across different drug-bacteria combinations, potentially offering tunable handles to optimize interventions aimed at minimizing AMR.

Unravelling microbial efflux through mathematical modelling

AbstractMathematical modelling is a useful tool that is increasingly used in the life sciences to understand and predict the behaviour of biological systems. This review looks at how this interdisciplinary approach has advanced our understanding of microbial efflux, the process by which microbes expel harmful substances. The discussion is largely in the context of antimicrobial resistance, but applications in synthetic biology are also touched upon. The goal of this paper is to spark further fruitful collaborations between modellers and experimentalists in the efflux community and beyond.

Calibrating spatiotemporal models of microbial communities to microscopy data: A review

Spatiotemporal models that account for heterogeneity within microbial communities rely on single-cell data for calibration and validation. Such data, commonly collected via microscopy and flow cytometry, have been made more accessible by recent advances in microfluidics platforms and data processing pipelines. However, validating models against such data poses significant challenges. Validation practices vary widely between modelling studies; systematic and rigorous methods have not been widely adopted. Similar challenges are faced by the (macrobial) ecology community, in which systematic calibration approaches are often employed to improve quantitative predictions from computational models. Here, we review single-cell observation techniques that are being applied to study microbial communities and the calibration strategies that are being employed for accompanying spatiotemporal models. To facilitate future calibration efforts, we have compiled a list of summary statistics relevant for quantifying spatiotemporal patterns in microbial communities. Finally, we highlight some recently developed techniques that hold promise for improved model calibration, including algorithmic guidance of summary statistic selection and machine learning approaches for efficient model simulation.

MDR Pumps as Crossroads of Resistance: Antibiotics and Bacteriophages

At present, antibiotic resistance represents a global problem in modern medicine. In the near future, humanity may face a situation where medicine will be powerless against resistant bacteria and a post-antibiotic era will come. The development of new antibiotics is either very expensive or ineffective due to rapidly developing bacterial resistance. The need to develop alternative approaches to the treatment of bacterial infections, such as phage therapy, is beyond doubt. The cornerstone of bacterial defense against antibiotics are multidrug resistance (MDR) pumps, which are involved in antibiotic resistance, toxin export, biofilm, and persister cell formation. MDR pumps are the primary non-specific defense of bacteria against antibiotics, while drug target modification, drug inactivation, target switching, and target sequestration are the second, specific line of their defense. All bacteria have MDR pumps, and bacteriophages have evolved along with them and use the bacteria’s need for MDR pumps to bind and penetrate into bacterial cells. The study and understanding of the mechanisms of the pumps and their contribution to the overall resistance and to the sensitivity to bacteriophages will allow us to either seriously delay the onset of the post-antibiotic era or even prevent it altogether due to phage-antibiotic synergy.

Antibiotics and ECMO in the Adult Population-Persistent Challenges and Practical Guides

Extracorporeal membrane oxygenation (ECMO) is an emerging treatment modality associated with a high frequency of antibiotic use. However, several covariables emerge during ECMO implementation, potentially jeopardizing the success of antimicrobial therapy. These variables include but are not limited to: the increased volume of distribution, altered clearance, and adsorption into circuit components, in addition to complex interactions of antibiotics in critical care illness. Furthermore, ECMO complicates the assessment of antibiotic effectiveness as fever, or other signs may not be easily detected, the immunogenicity of the circuit affects procalcitonin levels and other inflammatory markers while disrupting the immune system. We provided a review of pharmacokinetics and pharmacodynamics during ECMO, emphasizing practical application and review of patient-, illness-, and ECMO hardware-related factors.

DeLTA 2.0: A deep learning pipeline for quantifying single-cell spatial and temporal dynamics

Improvements in microscopy software and hardware have dramatically increased the pace of image acquisition, making analysis a major bottleneck in generating quantitative, single-cell data. Although tools for segmenting and tracking bacteria within time-lapse images exist, most require human input, are specialized to the experimental set up, or lack accuracy. Here, we introduce DeLTA 2.0, a purely Python workflow that can rapidly and accurately analyze images of single cells on two-dimensional surfaces to quantify gene expression and cell growth. The algorithm uses deep convolutional neural networks to extract single-cell information from time-lapse images, requiring no human input after training. DeLTA 2.0 retains all the functionality of the original version, which was optimized for bacteria growing in the mother machine microfluidic device, but extends results to two-dimensional growth environments. Two-dimensional environments represent an important class of data because they are more straightforward to implement experimentally, they offer the potential for studies using co-cultures of cells, and they can be used to quantify spatial effects and multi-generational phenomena. However, segmentation and tracking are significantly more challenging tasks in two-dimensions due to exponential increases in the number of cells. To showcase this new functionality, we analyze mixed populations of antibiotic resistant and susceptible cells, and also track pole age and growth rate across generations. In addition to the two-dimensional capabilities, we also introduce several major improvements to the code that increase accessibility, including the ability to accept many standard microscopy file formats as inputs and the introduction of a Google Colab notebook so users can try the software without installing the code on their local machine. DeLTA 2.0 is rapid, with run times of less than 10 minutes for complete movies with hundreds of cells, and is highly accurate, with error rates around 1%, making it a powerful tool for analyzing time-lapse microscopy data.

Multidrug Resistance Pumps as a Keystone of Bacterial Resistance

Antibiotic resistance is a global problem of modern medicine. A harbinger of the onset of the postantibiotic era is the complexity and high cost of developing new antibiotics as well as their inefficiency due to the rapidly developing resistance of bacteria. Multidrug resistance (MDR) pumps, involved in the formation of resistance to xenobiotics, the export of toxins, the maintenance of cellular homeostasis, and the formation of biofilms and persistent cells, are the keystone of bacterial protection against antibiotics. MDR pumps are the basis for the nonspecific protection of bacteria, while modification of the drug target, inactivation of the drug, and switching of the target or sequestration of the target is the second specific line of their protection. Thus, the nonspecific protection of bacteria formed by MDR pumps is a barrier that prevents the penetration of antibacterial substances into the cell, which is the main factor determining the resistance of bacteria. Understanding the mechanisms of MDR pumps and a balanced assessment of their contribution to total resistance, as well as to antibiotic sensitivity, will either seriously delay the onset of the postantibiotic era or prevent its onset in the foreseeable future.

Effects of Incubation Time and Inoculation Level on the Stabilities of Bacteriostatic and Bactericidal Antibiotics against Salmonella Typhimurium

This study was designed to evaluate the stability of chloramphenicol, erythromycin, tetracycline, cephalothin, ciprofloxacin, and tobramycin against antibiotic-sensitive Salmonella Typhimurium (ASST) and antibiotic-resistant S. Typhimurium (ARST) during the broth microdilution assay. The antimicrobial activity in association with antibiotic stability was measured by using antibiotic susceptibility, time-delayed inoculation, time-extended incubation, and inoculum effect assays. The loss of the antimicrobial activity of cephalothin against ASST exposed to 1 MIC was observed for the 10 h delayed inoculation. The antimicrobial activities of tetracycline and ciprofloxacin against ASST and ARST exposed to ½ MIC were significantly decreased after the 10 h delayed inoculation. All antibiotics used in this study, except for ciprofloxacin, showed the considerable losses of antimicrobial activities against ASST and ARST after 40 h of incubation at 37 °C when compared to the 20 h of incubation during AST. Compared to the standard inoculum level (6 log CFU/mL), the MIC0.1 values of bactericidal antibiotics, ciprofloxacin and tobramycin against ASST were increased by more than 4-fold at the high inoculum level of 9 log CFU/mL. This would provide practical information for better understanding the clinical efficacy of the currently used antibiotics by considering the antibiotic stability during incubation time at different inoculum levels.

Cholic acid: a novel steroidal uncompetitive inhibitor against β-lactamase produced by multidrug-resistant isolates

β-lactam antibiotics are the most frequently prescribed class of drugs worldwide, due to its efficacy and good safety profile. However, the emergence of β-lactamase producing bacterial strains eliminated the use of β-lactam antibiotics as a chemotherapeutic choice. To restore their usability, a non-antibiotic adjuvant in conjunction with β-lactam antibiotics is now being utilised. Cholic acid potentially acts as an adjuvant since it can blunt the pro-inflammatory activity in human. Our main objective is to scrutinise the inhibition of β-lactamase-producing bacteria by adjuvant cholic acid, synergism of the test drugs and the primary mechanism of enzymatic reaction. Antibacterial effect of the cholic acid-ampicillin (CA-AMP) on 7 β-lactamase positive isolates were evaluated accordingly to disc diffusion assay, antibiotic susceptibility test, as well as checkerboard analysis. Then, all activities were compared with ampicillin alone, penicillin alone, cholic acid alone and cholic acid-penicillin combination. The CA-AMP displayed notable antibiotic activity on all test bacteria and depicted synergistic influence by representing low fractional inhibitory concentration index (FIC ≤ 0.5). According to kinetic analyses, CA-AMP behaved as an uncompetitive inhibitor against beta lactamase, with reducing values of Michaelis constant (K_m) and maximal velocity (V_max) recorded. The inhibitor constant (Ki) of CA-AMP was equal to 4.98 ± 0.3 µM, which slightly lower than ampicillin (5.00 ± 0.1 µM).

Microscopic Approach to Intrinsic Antibiotic Resistance

The emergence of multidrug resistance in Gram-negative pathogens is critically determined by the interplay between efflux pumps activity and low permeation outer membrane. Although phenotypic heterogeneity in isogenic cells is recognized as a key factor of treatment failure, a mathematical framework able to integrate growth dynamics and single-cell heterogeneity in antimicrobial resistance, remains absent. Here we provide such framework that bridges single-cell and colony scales in the context of bacterial survival and efficacy against drugs. Using experimental inputs, our approach produces testable outputs and reveals nontrivial collective effects with key implications for fitness and survival of the colony. This framework provides a mathematical tool to test stress response strategies in organisms that can potentially guide experiments in natural and synthetic cellular systems.

Design and structural optimization of novel 2H-benzo[h]chromene derivatives that target AcrB and reverse bacterial multidrug resistance

Drug efflux pumps have emerged as a new drug targets for the treatment of bacterial infections in view of its critical role in promoting multidrug resistance. Herein, novel chromanone and 2H-benzo[h]chromene derivatives were designed by means of integrated molecular design and structure-based pharmacophore modeling in an attempt to identify improved efflux pump inhibitors that target Escherichia coli AcrB. The compounds were tested for their efflux inhibitory activity, ability to inhibit efflux, and the effect on bacterial outer and inner membranes. Twenty-three novel structures were identified that synergized with antibacterials tested, inhibited Nile Red efflux, and acted specifically on the AcrB. Among them, WK2, WL7 and WL10 exhibiting broad-spectrum and high-efficiency efflux inhibitory activity were identified as potential ideal AcrB inhibitors. Molecular modeling further revealed that the strong π-π stacking interactions and hydrogen bond networks were the major contributors to tight binding of AcrB.