Phenotypic resistant single-cell characteristics under recurring ampicillin antibiotic exposure in Escherichia coli

Non-heritable, phenotypic drug resistance toward antibiotics challenges antibiotic therapies. Characteristics of such phenotypic resistance have implications for the evolution of heritable resistance. Diverse forms of phenotypic resistance have been described, but phenotypic resistance characteristics remain less explored than genetic resistance. Here, we add novel combinations of single-cell characteristics of phenotypic resistant E. coli cells and compare those to characteristics of susceptible cells of the parental population by exposure to different levels of recurrent ampicillin antibiotic. Contrasting expectations, we did not find commonly described characteristics of phenotypic resistant cells that arrest growth or near growth. We find that under ampicillin exposure, phenotypic resistant cells reduced their growth rate by about 50% compared to growth rates prior to antibiotic exposure. The growth reduction is a delayed alteration to antibiotic exposure, suggesting an induced response and not a stochastic switch or caused by a predetermined state as frequently described. Phenotypic resistant cells exhibiting constant slowed growth survived best under ampicillin exposure and, contrary to expectations, not only fast-growing cells suffered high mortality triggered by ampicillin but also growth-arrested cells. Our findings support diverse modes of phenotypic resistance, and we revealed resistant cell characteristics that have been associated with enhanced genetically fixed resistance evolution, which supports claims of an underappreciated role of phenotypic resistant cells toward genetic resistance evolution. A better understanding of phenotypic resistance will benefit combatting genetic resistance by developing and engulfing effective anti-phenotypic resistance strategies.

IMPORTANCE

Antibiotic resistance is a major challenge for modern medicine. Aside from genetic resistance to antibiotics, phenotypic resistance that is not heritable might play a crucial role for the evolution of antibiotic resistance. Using a highly controlled microfluidic system, we characterize single cells under recurrent exposure to antibiotics. Fluctuating antibiotic exposure is likely experienced under common antibiotic therapies. These phenotypic resistant cell characteristics differ from previously described phenotypic resistance, highlighting the diversity of modes of resistance. The phenotypic characteristics of resistant cells we identify also imply that such cells might provide a stepping stone toward genetic resistance, thereby causing treatment failure.

Scaling of stochastic growth and division dynamics: A comparative study of individual rod-shaped cells in the Mother Machine and SChemostat platforms

Microfluidic platforms enable long-term quantification of stochastic behaviors of individual bacterial cells under precisely controlled growth conditions. Yet, quantitative comparisons of physiological parameters and cell behaviors of different microorganisms in different experimental and device modalities is not available due to experiment-specific details affecting cell physiology. To rigorously assess the effects of mechanical confinement, we designed, engineered, and performed side-by-side experiments under otherwise identical conditions in the Mother Machine (with confinement) and the SChemostat (without confinement), using the latter as the ideal comparator. We established a protocol to cultivate a suitably engineered rod-shaped mutant of Caulobacter crescentus in the Mother Machine and benchmarked the differences in stochastic growth and division dynamics with respect to the SChemostat. While the single-cell growth rate distributions are remarkably similar, the mechanically confined cells in the Mother Machine experience a substantial increase in interdivision times. However, we find that the division ratio distribution precisely compensates for this increase, which in turn reflects identical emergent simplicities governing stochastic intergenerational homeostasis of cell sizes across device and experimental configurations, provided the cell sizes are appropriately mean-rescaled in each condition. Our results provide insights into the nature of the robustness of the bacterial growth and division machinery.

Synergistic and antagonistic effects of deterministic and stochastic cell-cell variations

By diversifying, cells in a clonal population can together overcome the limits of individuals. Diversity in single-cell growth rates allows the population to survive environmental stresses, such as antibiotics, and grow faster than the undiversified population. These functional cell-cell variations can arise stochastically, from noise in biochemical reactions, or deterministically, by asymmetrically distributing damaged components. While each of the mechanisms is well understood, the effect of the combined mechanisms is unclear. To evaluate the contribution of the deterministic component we developed a mathematical model by mapping the growing population to the Ising model. To analyze the combined effects of stochastic and deterministic contributions we introduced the analytical results of the Ising-mapping into an Euler-Lotka framework. Model results, confirmed by simulations and experimental data, show that deterministic cell-cell variations increase near-linearly with stress. As a consequence, we predict that the gain in population doubling time from cell-cell variations is primarily stochastic at low stress but may cross over to deterministic at higher stresses. Furthermore, we find that while the deterministic component minimizes population damage, stochastic variations antagonize this effect. Together our results may help identifying stress-tolerant pathogenic cells and thus inspire novel antibiotic strategies.

Deep model predictive control of gene expression in thousands of single cells

Gene expression is inherently dynamic, due to complex regulation and stochastic biochemical events. However, the effects of these dynamics on cell phenotypes can be difficult to determine. Researchers have historically been limited to passive observations of natural dynamics, which can preclude studies of elusive and noisy cellular events where large amounts of data are required to reveal statistically significant effects. Here, using recent advances in the fields of machine learning and control theory, we train a deep neural network to accurately predict the response of an optogenetic system in Escherichia coli cells. We then use the network in a deep model predictive control framework to impose arbitrary and cell-specific gene expression dynamics on thousands of single cells in real time, applying the framework to generate complex time-varying patterns. We also showcase the framework's ability to link expression patterns to dynamic functional outcomes by controlling expression of the tetA antibiotic resistance gene. This study highlights how deep learning-enabled feedback control can be used to tailor distributions of gene expression dynamics with high accuracy and throughput without expert knowledge of the biological system.

The macrophage-bacterium mismatch in persister formation

Many pathogens are hard to eradicate, even in the absence of genetically detectable antimicrobial resistance mechanisms and despite proven antibiotic susceptibility. The fraction of clonal bacteria that temporarily elude effective antibiotic treatments is commonly known as 'antibiotic persisters.' Over the past decade, there has been a growing body of research highlighting the pivotal role played by the cellular host in the development of persisters. In parallel, this research has also sought to elucidate the molecular mechanisms underlying the formation of intracellular antibiotic persisters and has demonstrated a prominent role for the bacterial stress response. However, questions remain regarding the conditions leading to the formation of stress-induced persisters among a clonal population of intracellular bacteria and despite an ostensibly uniform environment. In this opinion, following a brief review of the current state of knowledge regarding intracellular antibiotic persisters, we explore the ways in which macrophage functional heterogeneity and bacterial phenotypic heterogeneity may contribute to the emergence of these persisters. We propose that the degree of mismatch between the macrophage permissiveness and the bacterial preparedness to invade and thrive intracellularly may explain the formation of stress-induced nonreplicating intracellular persisters.

Metabolic and transcriptional activities underlie stationary-phase Pseudomonas aeruginosa sensitivity to Levofloxacin

IMPORTANCE

The bacterial pathogen Pseudomonas aeruginosa is responsible for a variety of chronic human infections. Even in the absence of identifiable resistance mutations, this pathogen can tolerate lethal antibiotic doses through phenotypic strategies like biofilm formation and metabolic quiescence. In this study, we determined that P. aeruginosa maintains greater metabolic activity in the stationary phase compared to the model organism, Escherichia coli, which has traditionally been used to study fluoroquinolone antibiotic tolerance. We demonstrate that hallmarks of E. coli fluoroquinolone tolerance are not conserved in P. aeruginosa, including the timing of cell death and necessity of the SOS DNA damage response for survival. The heightened sensitivity of stationary-phase P. aeruginosa to fluoroquinolones is attributed to maintained transcriptional and reductase activity. Our data suggest that perturbations that suppress transcription and respiration in P. aeruginosa may actually protect the pathogen against this important class of antibiotics.

Microbial life in slow and stopped lanes

Microbes in nature often lack nutrients and face extreme or widely fluctuating temperatures, unlike microbes in growth-optimized settings in laboratories that much of the literature examines. Slowed or suspended lives are the norm for microbes. Studying them is important for understanding the consequences of climate change and for addressing fundamental questions about life: are there limits to how slowly a cell's life can progress, and how long cells can remain viable without self-replicating? Recent studies began addressing these questions with single-cell-level measurements and mathematical models. Emerging principles that govern slowed or suspended lives of cells - including lives of dormant spores and microbes at extreme temperatures - are re-defining discrete cellular states as continuums and revealing intracellular dynamics at new timescales. Nearly inactive, lifeless-appearing microbes are transforming our understanding of life.

Mitochondrial response of glioma cells to temozolomide

Metabolic adaptations are central for carcinogenesis and response to therapy, but little is known about the contribution of mitochondrial dynamics to the response of glioma cells to the standard treatment with temozolomide (TMZ). Glioma cells responded to TMZ with mitochondrial mass increased and the production of round structures of dysfunctional mitochondria. At single-cell level, asymmetric mitosis contributed to the heterogeneity of mitochondrial levels. It affected the fitness of cells in control and treated condition, indicating that the mitochondrial levels are relevant for glioma cell fitness in the presence of TMZ.

A heritable iron memory enables decision-making in Escherichia coli

The importance of memory in bacterial decision-making is relatively unexplored. We show here that a prior experience of swarming is remembered when Escherichia coli encounters a new surface, improving its future swarming efficiency. We conducted >10,000 single-cell swarm assays to discover that cells store memory in the form of cellular iron levels. This "iron" memory preexists in planktonic cells, but the act of swarming reinforces it. A cell with low iron initiates swarming early and is a better swarmer, while the opposite is true for a cell with high iron. The swarming potential of a mother cell, which tracks with its iron memory, is passed down to its fourth-generation daughter cells. This memory is naturally lost by the seventh generation, but artificially manipulating iron levels allows it to persist much longer. A mathematical model with a time-delay component faithfully recreates the observed dynamic interconversions between different swarming potentials. We demonstrate that cellular iron levels also track with biofilm formation and antibiotic tolerance, suggesting that iron memory may impact other physiologies.

Accurate Prediction of Antimicrobial Susceptibility for Point-of-Care Testing of Urine in Less than 90 Minutes via iPRISM Cassettes

The extensive and improper use of antibiotics has led to a dramatic increase in the frequency of antibiotic resistance among human pathogens, complicating infectious disease treatments. In this work, a method for rapid antimicrobial susceptibility testing (AST) is presented using microstructured silicon diffraction gratings integrated into prototype devices, which enhance bacteria-surface interactions and promote bacterial colonization. The silicon microstructures act also as optical sensors for monitoring bacterial growth upon exposure to antibiotics in a real-time and label-free manner via intensity-based phase-shift reflectometric interference spectroscopic measurements (iPRISM). Rapid AST using clinical isolates of Escherichia coli (E. coli) from urine is established and the assay is applied directly on unprocessed urine samples from urinary tract infection patients. When coupled with a machine learning algorithm trained on clinical samples, the iPRISM AST is able to predict the resistance or susceptibility of a new clinical sample with an Area Under the Receiver Operating Characteristic curve (AUC) of ∼ 0.85 in 1 h, and AUC > 0.9 in 90 min, when compared to state-of-the-art automated AST methods used in the clinic while being an order of magnitude faster.

Collective behavior and self-organization in neural rosette morphogenesis

Neural rosettes develop from the self-organization of differentiating human pluripotent stem cells. This process mimics the emergence of the embryonic central nervous system primordium, i.e., the neural tube, whose formation is under close investigation as errors during such process result in severe diseases like spina bifida and anencephaly. While neural tube formation is recognized as an example of self-organization, we still do not understand the fundamental mechanisms guiding the process. Here, we discuss the different theoretical frameworks that have been proposed to explain self-organization in morphogenesis. We show that an explanation based exclusively on stem cell differentiation cannot describe the emergence of spatial organization, and an explanation based on patterning models cannot explain how different groups of cells can collectively migrate and produce the mechanical transformations required to generate the neural tube. We conclude that neural rosette development is a relevant experimental 2D in-vitro model of morphogenesis because it is a multi-scale self-organization process that involves both cell differentiation and tissue development. Ultimately, to understand rosette formation, we first need to fully understand the complex interplay between growth, migration, cytoarchitecture organization, and cell type evolution.

Nanoscale clustering by O-antigen-Secretory Immunoglobulin-A binding limits outer membrane diffusion by encaging individual Salmonella cells

Secreted immunoglobulins, predominantly SIgA, influence the colonization and pathogenicity of mucosal bacteria. While part of this effect can be explained by SIgA-mediated bacterial aggregation, we have an incomplete picture of how SIgA binding influences cells independently of aggregation. Here we show that akin to microscale crosslinking of cells, SIgA targeting the Salmonella Typhimurium O-antigen extensively crosslinks the O-antigens on the surface of individual bacterial cells at the nanoscale. This crosslinking results in an essentially immobilized bacterial outer membrane. Membrane immobilization, combined with Bam-complex mediated outer membrane protein insertion results in biased inheritance of IgA-bound O-antigen, concentrating SIgA-bound O-antigen at the oldest poles during cell growth. By combining empirical measurements and simulations, we show that this SIgA-driven biased inheritance increases the rate at which phase-varied daughter cells become IgA-free: a process that can accelerate IgA escape via phase-variation of O-antigen structure. Our results show that O-antigen-crosslinking by SIgA impacts workings of the bacterial outer membrane, helping to mechanistically explain how SIgA may exert aggregation-independent effects on individual microbes colonizing the mucosae.

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.

Iron Memory in E. coli

The importance of memory in bacterial decision-making is relatively unexplored. We show here that a prior experience of swarming is remembered when E. coli encounters a new surface, improving its future swarming efficiency. We conducted >10,000 single-cell swarm assays to discover that cells store memory in the form of cellular iron levels. This memory pre-exists in planktonic cells, but the act of swarming reinforces it. A cell with low iron initiates swarming early and is a better swarmer, while the opposite is true for a cell with high iron. The swarming potential of a mother cell, whether low or high, is passed down to its fourth-generation daughter cells. This memory is naturally lost by the seventh generation, but artificially manipulating iron levels allows it to persist much longer. A mathematical model with a time-delay component faithfully recreates the observed dynamic interconversions between different swarming potentials. We also demonstrate that iron memory can integrate multiple stimuli, impacting other bacterial behaviors such as biofilm formation and antibiotic tolerance.

High rifampicin peak plasma concentrations accelerate the slow phase of bacterial decline in tuberculosis patients: Evidence for heteroresistance

BACKGROUND

Antibiotic treatments are often associated with a late slowdown in bacterial killing. This separates the killing of bacteria into at least two distinct phases: a quick phase followed by a slower phase, the latter of which is linked to treatment success. Current mechanistic explanations for the in vitro slowdown are either antibiotic persistence or heteroresistance. Persistence is defined as the switching back and forth between susceptible and non-susceptible states, while heteroresistance is defined as the coexistence of bacteria with heterogeneous susceptibilities. Both are also thought to cause a slowdown in the decline of bacterial populations in patients and therefore complicate and prolong antibiotic treatments. Reduced bacterial death rates over time are also observed within tuberculosis patients, yet the mechanistic reasons for this are unknown and therefore the strategies to mitigate them are also unknown.

METHODS AND FINDINGS

We analyse a dose ranging trial for rifampicin in tuberculosis patients and show that there is a slowdown in the decline of bacteria. We show that the late phase of bacterial killing depends more on the peak drug concentrations than the total drug exposure. We compare these to pharmacokinetic-pharmacodynamic models of rifampicin heteroresistance and persistence. We find that the observation on the slow phase's dependence on pharmacokinetic measures, specifically peak concentrations are only compatible with models of heteroresistance and incompatible with models of persistence. The quantitative agreement between heteroresistance models and observations is very good ([Formula: see text]). To corroborate the importance of the slowdown, we validate our results by estimating the time to sputum culture conversion and compare the results to a different dose ranging trial.

CONCLUSIONS

Our findings indicate that higher doses, specifically higher peak concentrations may be used to optimize rifampicin treatments by accelerating bacterial killing in the slow phase. It adds to the growing body of literature supporting higher rifampicin doses for shortening tuberculosis treatments.

Resuscitation dynamics reveal persister partitioning after antibiotic treatment

Bacteria can survive antibiotics by forming dormant, drug-tolerant persisters. Persisters can resuscitate from dormancy after treatment and prolong infections. Resuscitation is thought to occur stochastically, but its transient, single-cell nature makes it difficult to investigate. We tracked the resuscitation of individual persisters by microscopy after ampicillin treatment and, by characterizing their dynamics, discovered that Escherichia coli and Salmonella enterica persisters resuscitate exponentially rather than stochastically. We demonstrated that the key parameters controlling resuscitation map to the ampicillin concentration during treatment and efflux during resuscitation. Consistently, we observed many persister progeny have structural defects and transcriptional responses indicative of cellular damage, for both β-lactam and quinolone antibiotics. During resuscitation, damaged persisters partition unevenly, generating both healthy daughter cells and defective ones. This persister partitioning phenomenon was observed in S. enterica, Klebsiella pneumoniae, Pseudomonas aeruginosa, and an E. coli urinary tract infection (UTI) isolate. It was also observed in the standard persister assay and after in situ treatment of a clinical UTI sample. This study reveals novel properties of resuscitation and indicates that persister partitioning may be a survival strategy in bacteria that lack genetic resistance.

Diverse mechanisms of bioproduction heterogeneity in fermentation and their control strategies

Microbial bioproduction often faces challenges related to populational heterogeneity, where cells exhibit varying biosynthesis capabilities. Bioproduction heterogeneity can stem from genetic and non-genetic factors, resulting in decreased titer, yield, stability, and reproducibility. Consequently, understanding and controlling bioproduction heterogeneity are crucial for enhancing the economic competitiveness of large-scale biomanufacturing. In this review, we provide a comprehensive overview of current understandings of the various mechanisms underlying bioproduction heterogeneity. Additionally, we examine common strategies for controlling bioproduction heterogeneity based on these mechanisms. By implementing more robust measures to mitigate heterogeneity, we anticipate substantial enhancements in the scalability and stability of bioproduction processes.

ONE-SENTENCE SUMMARY

This review summarizes current understandings of different mechanisms of bioproduction heterogeneity and common control strategies based on these mechanisms.

Single Cell Killing Kinetics Differentiate Phenotypic Bacterial Responses to Different Antibacterial Classes

With the spread of multidrug-resistant bacteria, there has been an increasing focus on molecular classes that have not yet yielded an antibiotic. A key capability for assessing and prescribing new antibacterial treatments is to compare the effects antibacterial agents have on bacterial growth at a phenotypic, single-cell level. Here, we combined time-lapse microscopy with microfluidics to investigate the concentration-dependent killing kinetics of stationary-phase Escherichia coli cells. We used antibacterial agents from three different molecular classes, β-lactams and fluoroquinolones, with the known antibiotics ampicillin and ciprofloxacin, respectively, and a new experimental class, protein Ψ-capsids. We found that bacterial cells elongated when treated with ampicillin and ciprofloxacin used at their minimum inhibitory concentration (MIC). This was in contrast to Ψ-capsids, which arrested bacterial elongation within the first two hours of treatment. At concentrations exceeding the MIC, all the antibacterial agents tested arrested bacterial growth within the first 2 h of treatment. Further, our single-cell experiments revealed differences in the modes of action of three different agents. At the MIC, ampicillin and ciprofloxacin caused the lysis of bacterial cells, whereas at higher concentrations, the mode of action shifted toward membrane disruption. The Ψ-capsids killed cells by disrupting their membranes at all concentrations tested. Finally, at increasing concentrations, ampicillin and Ψ-capsids reduced the fraction of the population that survived treatment in a viable but nonculturable state, whereas ciprofloxacin increased this fraction. This study introduces an effective capability to differentiate the killing kinetics of antibacterial agents from different molecular classes and offers a high content analysis of antibacterial mechanisms at the single-cell level. IMPORTANCE Antibiotics act against bacterial pathogens by inhibiting their growth or killing them directly. Different modes of action determine different antibacterial responses, whereas phenotypic differences in bacteria can challenge the efficacy of antibiotics. Therefore, it is important to be able to differentiate the concentration-dependent killing kinetics of antibacterial agents at a single-cell level, in particular for molecular classes which have not yielded an antibiotic before. Here, we measured single-cell responses using microfluidics-enabled imaging, revealing that a novel class of antibacterial agents, protein Ψ-capsids, arrests bacterial elongation at the onset of treatment, whereas elongation continues for cells treated with β-lactam and fluoroquinolone antibiotics. The study advances our current understanding of antibacterial function and offers an effective strategy for the comparative design of new antibacterial therapies, as well as clinical antibiotic susceptibility testing.

Resistance-resistant antibacterial treatment strategies

Antibiotic resistance is a major danger to public health that threatens to claim the lives of millions of people per year within the next few decades. Years of necessary administration and excessive application of antibiotics have selected for strains that are resistant to many of our currently available treatments. Due to the high costs and difficulty of developing new antibiotics, the emergence of resistant bacteria is outpacing the introduction of new drugs to fight them. To overcome this problem, many researchers are focusing on developing antibacterial therapeutic strategies that are "resistance-resistant"-regimens that slow or stall resistance development in the targeted pathogens. In this mini review, we outline major examples of novel resistance-resistant therapeutic strategies. We discuss the use of compounds that reduce mutagenesis and thereby decrease the likelihood of resistance emergence. Then, we examine the effectiveness of antibiotic cycling and evolutionary steering, in which a bacterial population is forced by one antibiotic toward susceptibility to another antibiotic. We also consider combination therapies that aim to sabotage defensive mechanisms and eliminate potentially resistant pathogens by combining two antibiotics or combining an antibiotic with other therapeutics, such as antibodies or phages. Finally, we highlight promising future directions in this field, including the potential of applying machine learning and personalized medicine to fight antibiotic resistance emergence and out-maneuver adaptive pathogens.

Variability in Adaptive Resistance of Salmonella Typhimurium to Sublethal Levels of Antibiotics

This study was designed to evaluate the adaptive resistance of Salmonella Typhimurium under continuous sublethal selective pressure. Salmonella Typhimurium ATCC 19585 (STATCC) and S. Typhimurium CCARM 8009 (STCCARM) were sequentially cultured for 3 days at 37 °C in trypticase soy broth containing 1/2 × MICs of cefotaxime (CEF1/2), chloramphenicol (CHL1/2), gentamicin (GEN1/2), and polymyxin B (POL1/2). The STATCC and STCCARM exposed to CEF1/2, CHL1/2, GEN1/2, and POL1/2 were evaluated using antibiotic susceptibility, cross-resistance, and relative fitness. The susceptibilities of STATCC exposed to GEN1/2 and POL1/2 were increased by a 2-fold (gentamicin) and 8-fold (polymyxin B) increase in minimum inhibitory concentration (MIC) values, respectively. The MIC values of STCCARM exposed to CEF1/2, CHL1/2, GEN1/2, and POL1/2 were increased by 4-fold (cefotaxime), 2-fold (chloramphenicol), 2-fold (gentamicin), and 8-fold (polymyxin B). The highest heterogeneous fractions were observed for the STATCC exposed to CEF1/2 (38%) and POL1/2 (82%). The STCCARM exposed to GEN1/2 was cross-resistant to cefotaxime (p < 0.05), chloramphenicol (p < 0.01), and polymyxin B (p < 0.05). The highest relative fitness levels were 0.92 and 0.96, respectively, in STATCC exposed to CEF1/2 and STCCARM exposed to POL1/2. This study provides new insight into the fate of persistent cells and also guidance for antibiotic use.

A fluorescently labelled quaternary ammonium compound (NBD-DDA) to study resistance mechanisms in bacteria

Quaternary ammonium compounds (QACs) are widely used as active agents in disinfectants, antiseptics, and preservatives. Despite being in use since the 1940s, there remain multiple open questions regarding their detailed mode-of-action and the mechanisms, including phenotypic heterogeneity, that can make bacteria less susceptible to QACs. To facilitate studies on resistance mechanisms towards QACs, we synthesized a fluorescent quaternary ammonium compound, namely N-dodecyl-N,N-dimethyl-[2-[(4-nitro-2,1,3-benzoxadiazol-7-yl)amino]ethyl]azanium-iodide (NBD-DDA). NBD-DDA is readily detected by flow cytometry and fluorescence microscopy with standard GFP/FITC-settings, making it suitable for molecular and single-cell studies. As a proof-of-concept, NBD-DDA was then used to investigate resistance mechanisms which can be heterogeneous among individual bacterial cells. Our results reveal that the antimicrobial activity of NBD-DDA against Escherichia coli, Staphylococcus aureus and Pseudomonas aeruginosa is comparable to that of benzalkonium chloride (BAC), a widely used QAC, and benzyl-dimethyl-dodecylammonium chloride (BAC₁₂), a mono-constituent BAC with alkyl-chain length of 12 and high structural similarity to NBD-DDA. Characteristic time-kill kinetics and increased tolerance of a BAC tolerant E. coli strain against NBD-DDA suggest that the mode of action of NBD-DDA is similar to that of BAC. As revealed by confocal laser scanning microscopy (CLSM), NBD-DDA is preferentially localized to the cell envelope of E. coli, which is a primary target of BAC and other QACs. Leveraging these findings and NBD-DDA's fluorescent properties, we show that reduced cellular accumulation is responsible for the evolved BAC tolerance in the BAC tolerant E. coli strain and that NBD-DDA is subject to efflux mediated by TolC. Overall, NBD-DDA's antimicrobial activity, its fluorescent properties, and its ease of detection render it a powerful tool to study resistance mechanisms of QACs in bacteria and highlight its potential to gain detailed insights into its mode-of-action.

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.

Intercellular interaction mechanisms promote diversity in intracellular ATP concentration in Escherichia coli populations

In fluctuating environments, many microorganisms acquire phenotypic heterogeneity as a survival tactic to increase the likelihood of survival of the overall population. One example of this interindividual heterogeneity is the diversity of ATP concentration among members of Escherichia coli populations under glucose deprivation. Despite the importance of such environmentally driven phenotypic heterogeneity, how the differences in intracellular ATP concentration emerge among individual E. coli organisms is unknown. In this study, we focused on the mechanism through which individual E. coli achieve high intracellular ATP concentrations. First, we measured the ATP retained by E. coli over time when cultured at low (0.1 mM) and control (22.2 mM) concentrations of glucose and obtained the chronological change in ATP concentrations. Then, by comparing these chronological change of ATP concentrations and analyzing whether stochastic state transitions, periodic oscillations, cellular age, and intercellular communication-which have been reported as molecular biological mechanisms for generating interindividual heterogeneity-are involved, we showed that the appearance of high ATP-holding individuals observed among E. coli can be explained only by intercellular transmission. By performing metabolomic analysis of post-culture medium, we revealed a significant increase in the ATP, especially at low glucose, and that the number of E. coli that retain significantly higher ATP can be controlled by adding large amounts of ATP to the medium, even in populations cultured under control glucose concentrations. These results reveal for the first time that ATP-mediated intercellular transmission enables some individuals in E. coli populations grown at low glucose to retain large amounts of ATP.

Microfluidics for long-term single-cell time-lapse microscopy: Advances and applications

Cells are inherently dynamic, whether they are responding to environmental conditions or simply at equilibrium, with biomolecules constantly being made and destroyed. Due to their small volumes, the chemical reactions inside cells are stochastic, such that genetically identical cells display heterogeneous behaviors and gene expression profiles. Studying these dynamic processes is challenging, but the development of microfluidic methods enabling the tracking of individual prokaryotic cells with microscopy over long time periods under controlled growth conditions has led to many discoveries. This review focuses on the recent developments of one such microfluidic device nicknamed the mother machine. We overview the original device design, experimental setup, and challenges associated with this platform. We then describe recent methods for analyzing experiments using automated image segmentation and tracking. We further discuss modifications to the experimental setup that allow for time-varying environmental control, replicating batch culture conditions, cell screening based on their dynamic behaviors, and to accommodate a variety of microbial species. Finally, this review highlights the discoveries enabled by this technology in diverse fields, such as cell-size control, genetic mutations, cellular aging, and synthetic biology.

Microfluidics for antibiotic susceptibility testing

The rise of antibiotic resistance is a threat to global health. Rapid and comprehensive analysis of infectious strains is critical to reducing the global use of antibiotics, as informed antibiotic use could slow down the emergence of resistant strains worldwide. Multiple platforms for antibiotic susceptibility testing (AST) have been developed with the use of microfluidic solutions. Here we describe microfluidic systems that have been proposed to aid AST. We identify the key contributions in overcoming outstanding challenges associated with the required degree of multiplexing, reduction of detection time, scalability, ease of use, and capacity for commercialization. We introduce the reader to microfluidics in general, and we analyze the challenges and opportunities related to the field of microfluidic AST.

Genetic, physiological, and cellular heterogeneities of bacterial pathogens in food matrices: Consequences for food safety

In complex food systems, bacteria live in heterogeneous microstructures, and the population displays phenotypic heterogeneities at the single-cell level. This review provides an overview of spatiotemporal drivers of phenotypic heterogeneity of bacterial pathogens in food matrices at three levels. The first level is the genotypic heterogeneity due to the possibility for various strains of a given species to contaminate food, each of them having specific genetic features. Then, physiological heterogeneities are induced within the same strain, due to specific microenvironments and heterogeneous adaptative responses to the food microstructure. The third level of phenotypic heterogeneity is related to cellular heterogeneity of the same strain in a specific microenvironment. Finally, we consider how these phenotypic heterogeneities at the single-cell level could be implemented in mathematical models to predict bacterial behavior and help ensure microbiological food safety.

Methicillin Resistant Staphylococci Isolated from Goats and Their Farm Environments in Saudi Arabia Genotypically Linked to Known Human Clinical Isolates: a Pilot Study

We conducted a pilot whole genome sequencing (WGS) study to characterize the genotypes of nine methicillin resistant staphylococci (MRS) isolates recovered from goats and their farm environments in Eastern Province, Saudi Arabia, between November 2019 to August 2020. Seven out of nine isolates were methicillin resistant Staphylococcus aureus (MRSA), and two were methicillin resistant Staphylococcus epidermidis (MRSE). All MRSA isolates possessed genotypes previously identified to infect humans, including isolates harboring ST6-SCCmec IV-t304 (n = 4), ST5-SCCmec VI- t688 (n = 2) and ST5-SCCmec V-t311 (n = 1). 2 MRSA isolates possessed plasmids that were genetically similar to those identified in S. aureus isolates recovered from humans and poultry. In contrast, plasmids found in three MRSA isolates and one MRSE isolate were genetically similar to those recovered from humans. All MRSA isolates harbored the host innate modulate genes sak and scn previously associated with human infections. The genotypes of MRSE isolates were determined as ST35, a well-known zoonotic sequence type and ST153, which has been associated with humans. However, the MRSE isolates were untypeable due to extra ccr complexes identified in their SCCmec elements. Moreover, we identified in ST153 isolate SCCmec element also harbored the Arginine Catabolic Mobile Element (ACME) IV. All MRS isolates were phenotypically resistant to trimethoprim-sulfamethoxazole, an antibiotic for the decolonization of MRS. Three isolates carried antibiotic resistance genes in their SCCmec elements that were not previously described, including those encoding fusidic acid resistance (fusC) and trimethoprim resistance (dfrC) incorporated in the MRSA SCCmec VI. IMPORTANCE Our findings demonstrate a possible cross-transmission of methicillin resistant staphylococci between goats and their local environments and between goats and humans. Due to ever increasing resistance to multiple antibiotics, the burden of MRS has a significant impact on livestock farming, public health, and the economy worldwide. This study highlights that implementing a holistic approach to whole genome sequencing surveillance in livestock and farm environments would aid our understanding of the transmission of methicillin resistant staphylococci and, most importantly, allow us to implement appropriate infection control and hygiene practices.

Methods to monitor bacterial growth and replicative rates at the single-cell level

The heterogeneity of bacterial growth and replicative rates within a population was proposed a century ago notably to explain the presence of bacterial persisters. The term "growth rate" at the single-cell level corresponds to the increase in size or mass of an individual bacterium while the "replicative rate" refers to its division capacity within a defined temporality. After a decades long hiatus, recent technical innovative approaches allow population growth and replicative rates heterogeneity monitoring at the single-cell level resuming in earnest. Among these techniques, the oldest and widely used is time-lapse microscopy, most recently combined with microfluidics. We also discuss recent fluorescence dilution methods informing only on replicative rates and best suited. Some new elegant single cell methods so far only sporadically used such as buoyant mass measurement and stable isotope probing have emerged. Overall, such tools are widely used to investigate and compare the growth and replicative rates of bacteria displaying drug-persistent behaviors to that of bacteria growing in specific ecological niches or collected from patients. In this review, we describe the current methods available, discussing both the type of queries these have been used to answer and the specific strengths and limitations of each method.

Stress-Induced Mutagenesis, Gambler Cells, and Stealth Targeting Antibiotic-Induced Evolution

Mechanisms of evolution and evolution of antibiotic resistance are both fundamental and world health problems. Stress-induced mutagenesis defines mechanisms of mutagenesis upregulated by stress responses, which drive adaptation when cells are maladapted to their environments—when stressed. Work in mutagenesis induced by antibiotics had produced tantalizing clues but not coherent mechanisms. We review recent advances in antibiotic-induced mutagenesis that integrate how reactive oxygen species (ROS), the SOS and general stress responses, and multichromosome cells orchestrate a stress response-induced switch from high-fidelity to mutagenic repair of DNA breaks. Moreover, while sibling cells stay stable, a mutable “gambler” cell subpopulation is induced by differentially generated ROS, which signal the general stress response. We discuss other evolvable subpopulations and consider diverse evolution-promoting molecules as potential targets for drugs to slow evolution of antibiotic resistance, cross-resistance, and immune evasion. An FDA-approved drug exemplifies “stealth” evolution-slowing drugs that avoid selecting resistance to themselves or antibiotics.

Fast bacterial growth reduces antibiotic accumulation and efficacy

Phenotypic variations between individual microbial cells play a key role in the resistance of microbial pathogens to pharmacotherapies. Nevertheless, little is known about cell individuality in antibiotic accumulation. Here, we hypothesise that phenotypic diversification can be driven by fundamental cell-to-cell differences in drug transport rates. To test this hypothesis, we employed microfluidics-based single-cell microscopy, libraries of fluorescent antibiotic probes and mathematical modelling. This approach allowed us to rapidly identify phenotypic variants that avoid antibiotic accumulation within populations of Escherichia coli, Pseudomonas aeruginosa, Burkholderia cenocepacia, and Staphylococcus aureus. Crucially, we found that fast growing phenotypic variants avoid macrolide accumulation and survive treatment without genetic mutations. These findings are in contrast with the current consensus that cellular dormancy and slow metabolism underlie bacterial survival to antibiotics. Our results also show that fast growing variants display significantly higher expression of ribosomal promoters before drug treatment compared to slow growing variants. Drug-free active ribosomes facilitate essential cellular processes in these fast-growing variants, including efflux that can reduce macrolide accumulation. We used this new knowledge to eradicate variants that displayed low antibiotic accumulation through the chemical manipulation of their outer membrane inspiring new avenues to overcome current antibiotic treatment failures.

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.

Quantifying heterologous gene expression during ectopic MazF production in Escherichia coli

Objective

MazF is a sequence-specific endoribonuclease-toxin of the MazEF toxin–antitoxin system. MazF cleaves single-stranded ribonucleic acid (RNA) regions at adenine–cytosine–adenine (ACA) sequences in the bacterium Escherichia coli. The MazEF system has been used in various biotechnology and synthetic biology applications. In this study, we infer how ectopic mazF overexpression affects production of heterologous proteins. To this end, we quantified the levels of fluorescent proteins expressed in E. coli from reporters translated from the ACA-containing or ACA-less messenger RNAs (mRNAs). Additionally, we addressed the impact of the 5′-untranslated region of these reporter mRNAs under the same conditions by comparing expression from mRNAs that comprise (canonical mRNA) or lack this region (leaderless mRNA).

Results

Flow cytometry analysis indicates that during mazF overexpression, fluorescent proteins are translated from the canonical as well as leaderless mRNAs. Our analysis further indicates that longer mazF overexpression generally increases the concentration of fluorescent proteins translated from ACA-less mRNAs, however it also substantially increases bacterial population heterogeneity. Finally, our results suggest that the strength and duration of mazF overexpression should be optimized for each experimental setup, to maximize the heterologous protein production and minimize the amount of phenotypic heterogeneity in bacterial populations, which is unfavorable in biotechnological processes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-022-06061-9.

In Vitro Investigation of the Impact of Bacterial-Fungal Interaction on Carbapenem-Resistant Klebsiella pneumoniae

Fungal-bacterial co-culturing is a potential technique for the production of secondary metabolites with antibacterial activity. Twenty-nine fungal species were screened in a co-culture with carbapenem-resistant Klebsiella pneumoniae at different temperatures. A temperature of 37 ° showed inhibition of bacterial growth. Antimicrobial susceptibility testing for K. pneumoniae was conducted to compare antibiotic resistance patterns before and after the co-culture. Genotypic comparison of the K. pneumonia was performed using next generation sequencing (NGS). It was shown that two out of five K. pneumoniae, with sequence type ST 101 isolates, lost bla-_OXA48, bla-_CTX-M-14, tir, strA and strB genes after the co-culture with Scopulariopsis brevicaulis fungus. The other three isolates (ST 383 and 147) were inhibited in the co-culture but did not show any changes in resistance. The total ethyl acetate extract of the fungal-bacterial co-culture was tested against K. pneumoniae using a disc diffusion method. The concentration of the crude extract was 0.97 mg/µL which resulted in total inhibition of the bacteria. Using chromatographic techniques, the purified compounds were identified as 11-octadecenoic acid, 2,4-Di-tert-butylphenol, 2,3-Butanediol and 9-octadecenamide. These were tested against K. pneumoniae using the well diffusion method at a concentration of 85 µg/µL which resulted in total inhibition of bacteria. The co-culture results indicated that bacteria under chemical stress showed variable responses and induced fungal secondary metabolites with antibacterial activities.

Dynamic gene expression and growth underlie cell-to-cell heterogeneity in Escherichia coli stress response

Individual bacteria that share identical genomes and growth environments can display substantial cell-to-cell differences in expression of stress-response genes and single-cell growth rates. This phenotypic heterogeneity can impact the survival of single cells facing sudden stress. However, the windows of time that cells spend in vulnerable or tolerant states are often unknown. We quantify the temporal expression of a suite of stress-response reporters, while simultaneously monitoring growth. We observe pulsatile expression across genes with a range of stress-response functions, finding that single-cell growth rates are often anticorrelated with reporter levels. These dynamic phenotypic differences have a concrete link to function, in which individual cells undergoing a pulse of elevated expression and slow growth are predisposed to survive antibiotic exposure.

Cell-to-cell heterogeneity in gene expression and growth can have critical functional consequences, such as determining whether individual bacteria survive or die following stress. Although phenotypic variability is well documented, the dynamics that underlie it are often unknown. This information is important because dramatically different outcomes can arise from gradual versus rapid changes in expression and growth. Using single-cell time-lapse microscopy, we measured the temporal expression of a suite of stress-response reporters in Escherichia coli, while simultaneously monitoring growth rate. In conditions without stress, we found several examples of pulsatile expression. Single-cell growth rates were often anticorrelated with reporter levels, with changes in growth preceding changes in expression. These dynamics have functional consequences, which we demonstrate by measuring survival after challenging cells with the antibiotic ciprofloxacin. Our results suggest that fluctuations in both gene expression and growth dynamics in stress-response networks have direct consequences on survival.

The Critical Role of Environmental Synergies in the Creation of Bionanohybrid Microbes

A wide range of bacteria can synthesize surface-associated nanoparticles (SANs) through exogenous metal ions reacting with sulfide produced via cysteine metabolism, resulting in the emergence of a biological-nanoparticle hybrid (bionanohybrid). The attached nanoparticles may couple to extracellular electron transfer, facilitating de novo photoelectrochemical processes. While SAN-cell coupling in hybrid organisms is opening a range of biotechnological possibilities, observation of bionanohybrids in nature is not commonly reported and their lab-based behavior remains difficult to control. We describe the critical role environmental synergy (microbial growth stage, cell densities, cysteine, and exogenous metal concentrations) plays in controlling the form and occurrence of Escherichia coli and Moorella thermoacetica bionanohybrids. SAN development depends on an appropriate cell density to metal ratio, with too few cells resulting in nanoparticle suppression through cytotoxicity or inhibition of cysteine conversion, and with too many cells diluting the number and size of particles produced. This cell number is governed by the concentration of cysteine present, which acts to protect the cells from metal ion toxicity. Exposing cells to metal and cysteine during the lag phase leads to SAN development, whereas cells in the exponential growth phase predominantly produce dispersed nanoparticles. Applying these principles more broadly, E. coli is shown to biosynthesize composite Bi/Cu sulfide SANs, and Clostridioides difficile can be coaxed into a bionanohybrid lifestyle by fine-tuning the cysteine dosage. Bionanohybrids maintain a remarkable ability for binary fission and sustained growth, opening doors to the production of SANs tailored to specific technological functions. IMPORTANCE Some bacteria can produce nanoscale-sized particles, which remain attached to the surface of the organism. The surface association of these nanoparticles creates a new mode of interaction between the microbe's environment and its internal cellular function, giving rise to a new hybrid lifeform, a biological nanoparticle hybrid (bionanohybrid). These hybrid organisms gain new or enhanced biological functions, and thus their creation opens a wide range of biotechnological possibilities. Despite this potential, the fundamental controls on bionanohybrid formation and occurrence remain poorly constrained. In this study, Escherichia coli K-12, Moorella thermoacetica, and Clostridioides difficile were used to test the combined influences of the growth phase, cell density, cysteine dose, and metal concentration in determining single and composite metal sulfide surface-associated nanoparticle production. The significance of this study is that it defined the critical synergies controlling nanoparticle formation on bacterial cell surfaces, unlocking the potential for bionanohybrid applications in a range of organisms.

The physiology and genetics of bacterial responses to antibiotic combinations

Several promising strategies based on combining or cycling different antibiotics have been proposed to increase efficacy and counteract resistance evolution, but we still lack a deep understanding of the physiological responses and genetic mechanisms that underlie antibiotic interactions and the clinical applicability of these strategies. In antibiotic-exposed bacteria, the combined effects of physiological stress responses and emerging resistance mutations (occurring at different time scales) generate complex and often unpredictable dynamics. In this Review, we present our current understanding of bacterial cell physiology and genetics of responses to antibiotics. We emphasize recently discovered mechanisms of synergistic and antagonistic drug interactions, hysteresis in temporal interactions between antibiotics that arise from microbial physiology and interactions between antibiotics and resistance mutations that can cause collateral sensitivity or cross-resistance. We discuss possible connections between the different phenomena and indicate relevant research directions. A better and more unified understanding of drug and genetic interactions is likely to advance antibiotic therapy.

Dynamic Boolean modelling reveals the influence of energy supply on bacterial efflux pump expression

Antimicrobial resistance (AMR) is a global health issue. One key factor contributing to AMR is the ability of bacteria to export drugs through efflux pumps, which relies on the ATP-dependent expression and interaction of several controlling genes. Recent studies have shown that significant cell-to-cell ATP variability exists within clonal bacterial populations, but the contribution of intrinsic cell-to-cell ATP heterogeneity is generally overlooked in understanding efflux pumps. Here, we consider how ATP variability influences gene regulatory networks controlling expression of efflux pump genes in two bacterial species. We develop and apply a generalizable Boolean modelling framework, developed to incorporate the dependence of gene expression dynamics on available cellular energy supply. Theoretical results show that differences in energy availability can cause pronounced downstream heterogeneity in efflux gene expression. Cells with higher energy availability have a superior response to stressors. Furthermore, in the absence of stress, model bacteria develop heterogeneous pulses of efflux pump gene expression which contribute to a sustained sub-population of cells with increased efflux expression activity, potentially conferring a continuous pool of intrinsically resistant bacteria. This modelling approach thus reveals an important source of heterogeneity in cell responses to antimicrobials and sheds light on potentially targetable aspects of efflux pump-related antimicrobial resistance.

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.

Tissue compartmentalization enables Salmonella persistence during chemotherapy

Antimicrobial chemotherapy can fail to eradicate the pathogen, even in the absence of antimicrobial resistance. Persisting pathogens can subsequently cause relapsing diseases. In vitro studies suggest various mechanisms of antibiotic persistence, but their in vivo relevance remains unclear because of the difficulty of studying scarce pathogen survivors in complex host tissues. Here, we localized and characterized rare surviving Salmonella in mouse spleen using high-resolution whole-organ tomography. Chemotherapy cleared >99.5% of the Salmonella but was inefficient against a small Salmonella subset in the white pulp. Previous models could not explain these findings: drug exposure was adequate, Salmonella continued to replicate, and host stresses induced only limited Salmonella drug tolerance. Instead, antimicrobial clearance required support of Salmonella-killing neutrophils and monocytes, and the density of such cells was lower in the white pulp than in other spleen compartments containing higher Salmonella loads. Neutrophil densities declined further during treatment in response to receding Salmonella loads, resulting in insufficient support for Salmonella clearance from the white pulp and eradication failure. However, adjunctive therapies sustaining inflammatory support enabled effective clearance. These results identify uneven Salmonella tissue colonization and spatiotemporal inflammation dynamics as main causes of Salmonella persistence and establish a powerful approach to investigate scarce but impactful pathogen subsets in complex host environments.

Quantification and surface localization of the hemolysin A type 1 secretion system at the endogenous level and under conditions of overexpression

Secretion systems are essential for Gram-negative bacteria as these nanomachineries allow a communication with the outside world by exporting proteins into the extracellular space or directly into the cytosol of a host cell. For example, type one secretion systems (T1SS) secrete a broad range of substrates across both membranes into the extracellular space. One well-known example is the hemolysin A (HlyA) T1SS from Escherichia coli (E. coli), which consists of an ABC transporter (HlyB), a membrane fusion protein (HlyD), the outer membrane protein TolC and the substrate HlyA, a member of the family of RTX (repeats in toxins) toxins. Here, we determined the amount of TolC at the endogenous level (parental strain, UTI89) and under conditions of overexpression (T7 expression system, BL21(DE3)-BD). The overall amount of TolC was not influenced by the overexpression of the HlyBD complex. Moving one step further, we determined the localization of the HlyA T1SS by super-resolution microscopy. In contrast to other bacterial secretion systems, no polarization was observed with respect to endogenous or overexpression levels. Additionally, the cell growth and division cycle did not influence the polarization. Most importantly, the size of the observed T1SS clusters did not correlate with the recently proposed outer membrane islands. These data indicate that T1SS cluster at the outer membrane generating domains of so far not described identity. Importance Uropathogenic Escherichia coli (UPEC) strains cause about 110 million urinary tract infections each year worldwide representing a global burden to the healthcare system. UPEC secrete many virulence factors among these the TX toxin hemolysin A via a cognate T1SS into the extracellular space. In this study, we determined the endogenous copy number of the HlyA T1SS in UTI89 and analyzed the surface localization in BL21(DE3)-BD and UTI89, respectively. With approximately 800 copies of the T1SS in UTI89, this is one of the highest expressed bacterial secretion systems. Furthermore and in clear contrast to other secretion systems, no polarized surface localization was detected. Finally, quantitative analysis of the super-resolution data revealed that clusters of the HlyA T1SS are not related to the recently identified outer membrane protein islands. These data provide insights into the quantitative molecular architecture of the HlyA T1SS.

Persistence against benzalkonium chloride promotes rapid evolution of tolerance during periodic disinfection

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 that can survive transient antibiotic treatment and facilitate resistance evolution. 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, which is associated with reduced cell surface charge and mutations in the lpxM locus, encoding an enzyme for lipid A biosynthesis. Moreover, the fitness cost incurred by BAC tolerance turns into a fitness benefit in the presence of antibiotics, suggesting a selective advantage of BAC-tolerant mutants in antibiotic environments. Our findings highlight the links between persistence to disinfectants and resistance evolution to antimicrobials.

Single-Cell Technologies to Study Phenotypic Heterogeneity and Bacterial Persisters

Antibiotic persistence is a phenomenon in which rare cells of a clonal bacterial population can survive antibiotic doses that kill their kin, even though the entire population is genetically susceptible. With antibiotic treatment failure on the rise, there is growing interest in understanding the molecular mechanisms underlying bacterial phenotypic heterogeneity and antibiotic persistence. However, elucidating these rare cell states can be technically challenging. The advent of single-cell techniques has enabled us to observe and quantitatively investigate individual cells in complex, phenotypically heterogeneous populations. In this review, we will discuss current technologies for studying persister phenotypes, including fluorescent tags and biosensors used to elucidate cellular processes; advances in flow cytometry, mass spectrometry, Raman spectroscopy, and microfluidics that contribute high-throughput and high-content information; and next-generation sequencing for powerful insights into genetic and transcriptomic programs. We will further discuss existing knowledge gaps, cutting-edge technologies that can address them, and how advances in single-cell microbiology can potentially improve infectious disease treatment outcomes.

Quantitative biology of survival under antibiotic treatments

The mathematical formulation for the dynamics of growth reduction and/or killing under antibiotic treatments has a long history. Even before the extensive use of antibiotics, attempts to model the killing dynamics of biocides were made [1]. Here, we review relatively simple quantitative formulations of the two main modes of survival under antibiotics, resistance and tolerance, as well as their heterogeneity in bacterial populations. We focus on the two main types of heterogeneity that have been described: heteroresistance and antibiotic persistence, each linked to the variation in a different parameter of the antibiotic response dynamics. Finally, we review the effects on survival of combining resistance and tolerance mutations as well as on the mode and tempo of evolution under antibiotic treatments.

Efflux Impacts Intracellular Accumulation Only in Actively Growing Bacterial Cells

For antibiotics with intracellular targets, effective treatment of bacterial infections requires the drug to accumulate to a high concentration inside cells. Bacteria produce a complex cell envelope and possess drug export efflux pumps to limit drug accumulation inside cells. Decreasing cell envelope permeability and increasing efflux pump activity can reduce intracellular accumulation of antibiotics and are commonly seen in antibiotic-resistant strains. Here, we show that the balance between influx and efflux differs depending on bacterial growth phase in Gram-negative bacteria. Accumulation of the fluorescent compound ethidium bromide (EtBr) was measured in Salmonella enterica serovar Typhimurium SL1344 (wild type) and efflux deficient (ΔacrB) strains during growth. In SL1344, EtBr accumulation remained low, regardless of growth phase, and did not correlate with acrAB transcription. EtBr accumulation in the ΔacrB strains was high in exponential phase but dropped sharply later in growth, with no significant difference from that in SL1344 in stationary phase. Low EtBr accumulation in stationary phase was not due to the upregulation of other efflux pumps but instead was due to decreased permeability of the envelope in stationary phase. Transcriptome sequencing (RNA-seq) identified changes in expression of several pathways that remodel the envelope in stationary phase, leading to lower permeability.

Memory shapes microbial populations

Correct decision making is fundamental for all living organisms to thrive under environmental changes. The patterns of environmental variation and the quality of available information define the most favourable strategy among multiple options, from randomly adopting a phenotypic state to sensing and reacting to environmental cues. Cellular memory—the ability to track and condition the time to switch to a different phenotypic state—can help withstand environmental fluctuations. How does memory manifest itself in unicellular organisms? We describe the population-wide consequences of phenotypic memory in microbes through a combination of deterministic modelling and stochastic simulations. Moving beyond binary switching models, our work highlights the need to consider a broader range of switching behaviours when describing microbial adaptive strategies. We show that memory in individual cells generates patterns at the population level coherent with overshoots and non-exponential lag times distributions experimentally observed in phenotypically heterogeneous populations. We emphasise the implications of our work in understanding antibiotic tolerance and, in general, bacterial survival under fluctuating environments.

While being genetically the same, a population of cells can show phenotypic variability even under homogeneous environments. Often advantageous under heterogeneous environments, this phenotypic heterogeneity is highly relevant in the studies of antibiotic resistance evolution and cancer resurgence. Numerous theoretical models exist applying a simple model of phenotypic switching. Experimental measurements on phenotypic heterogeneity have increased in precision over the past decade, and the simple models are inadequate to explain the new observations. In this paper, we explore the role of cellular memory as a crucial component of phenotypic switching. We see that memory helps account for the hitherto unexplained observations and fundamentally extend our understanding of phenotypic heterogeneity.

Nonrandom segregation of sister chromosomes by Escherichia coli MukBEF

Circular chromosomes in rod-shaped bacteria exist inside a cell in two distinct configurations, “transverse” and “longitudinal,” relative to the long cell axis, with chromosomal loci occupying specific cellular locations in both cases. Bacteria with longitudinal chromosome organization (e.g., Caulobacter crescentus) typically tether their origins of replication to the cell membrane and do not undergo overlapping rounds of replication. In contrast, bacteria with transverse organization (e.g., Escherichia coli) orient their chromosomes by an unknown mechanism and have lifestyles compatible with overlapping rounds of replication. Here, we address the relative roles of two major players in chromosome organization–segregation and propose a model of how E. coli maintains chromosome conformation and orientation inside cells and how this organization is propagated over generations.

Structural maintenance of chromosomes (SMC) complexes contribute to chromosome organization in all domains of life. In Escherichia coli, MukBEF, the functional SMC homolog, promotes spatiotemporal chromosome organization and faithful chromosome segregation. Here, we address the relative contributions of MukBEF and the replication terminus (ter) binding protein, MatP, to chromosome organization–segregation. We show that MukBEF, but not MatP, is required for the normal localization of the origin of replication to midcell and for the establishment of translational symmetry between newly replicated sister chromosomes. Overall, chromosome orientation is normally maintained through division from one generation to the next. Analysis of loci flanking the replication termination region (ter), which demark the ends of the linearly organized portion of the nucleoid, demonstrates that MatP is required for maintenance of chromosome orientation. We show that DNA-bound β₂-processivity clamps, which mark the lagging strands at DNA replication forks, localize to the cell center, independent of replisome location but dependent on MukBEF action, and consistent with translational symmetry of sister chromosomes. Finally, we directly show that the older (“immortal”) template DNA strand, propagated from previous generations, is preferentially inherited by the cell forming at the old pole, dependent on MukBEF and MatP. The work further implicates MukBEF and MatP as central players in chromosome organization, segregation, and nonrandom inheritance of genetic material and suggests a general framework for understanding how chromosome conformation and dynamics shape subcellular organization.

Multiform antimicrobial resistance from a metabolic mutation

A critical challenge for microbiology and medicine is how to cure infections by bacteria that survive antibiotic treatment by persistence or tolerance. Seeking mechanisms behind such high survival, we developed a forward-genetic method for efficient isolation of high-survival mutants in any culturable bacterial species. We found that perturbation of an essential biosynthetic pathway (arginine biosynthesis) in a mycobacterium generated three distinct forms of resistance to diverse antibiotics, each mediated by induction of WhiB7: high persistence and tolerance to kanamycin, high survival upon exposure to rifampicin, and minimum inhibitory concentration-shifted resistance to clarithromycin. As little as one base change in a gene that encodes, a metabolic pathway component conferred multiple forms of resistance to multiple antibiotics with different targets. This extraordinary resilience may help explain how substerilizing exposure to one antibiotic in a regimen can induce resistance to others and invites development of drugs targeting the mediator of multiform resistance, WhiB7.

Stochastic response of bacterial cells to antibiotics: its mechanisms and implications for population and evolutionary dynamics

The effectiveness of antibiotics against bacterial infections has been declining due to the emergence of resistance. Precisely understanding the response of bacteria to antibiotics is critical to maximizing antibiotic-induced bacterial eradication while minimizing the emergence of antibiotic resistance. Cell-to-cell heterogeneity in antibiotic susceptibility is observed across various bacterial species for a wide range of antibiotics. Heterogeneity in antibiotic susceptibility is not always due to the genetic differences. Rather, it can be caused by non-genetic mechanisms such as stochastic gene expression and biased partitioning upon cell division. Heterogeneous susceptibility leads to the stochastic growth and death of individual cells and stochastic fluctuations in population size. These fluctuations have important implications for the eradication of bacterial populations and the emergence of genotypic resistance.

Persister Escherichia coli Cells Have a Lower Intracellular pH than Susceptible Cells but Maintain Their pH in Response to Antibiotic Treatment

Persister and viable but non-culturable (VBNC) cells are two clonal subpopulations that can survive multidrug exposure via a plethora of putative molecular mechanisms. Here, we combine microfluidics, time-lapse microscopy, and a plasmid-encoded fluorescent pH reporter to measure the dynamics of the intracellular pH of individual persister, VBNC, and susceptible Escherichia coli cells in response to ampicillin treatment. We found that even before antibiotic exposure, persisters have a lower intracellular pH than those of VBNC and susceptible cells. We then investigated the molecular mechanisms underlying the observed differential pH regulation in persister E. coli cells and found that this is linked to the activity of the enzyme tryptophanase, which is encoded by tnaA. In fact, in a ΔtnaA strain, we found no difference in intracellular pH between persister, VBNC, and susceptible E. coli cells. Whole-genome transcriptomic analysis revealed that, besides downregulating tryptophan metabolism, the ΔtnaA strain downregulated key pH homeostasis pathways, including the response to pH, oxidation reduction, and several carboxylic acid catabolism processes, compared to levels of expression in the parental strain. Our study sheds light on pH homeostasis, proving that the regulation of intracellular pH is not homogeneous within a clonal population, with a subset of cells displaying a differential pH regulation to perform dedicated functions, including survival after antibiotic treatment. IMPORTANCE Persister and VBNC cells can phenotypically survive environmental stressors, such as antibiotic treatment, limitation of nutrients, and acid stress, and have been linked to chronic infections and antimicrobial resistance. It has recently been suggested that pH regulation might play a role in an organism's phenotypic survival to antibiotics; however, this hypothesis remains to be tested. Here, we demonstrate that even before antibiotic treatment, cells that will become persisters have a more acidic intracellular pH than clonal cells that will be either susceptible or VBNC upon antibiotic treatment. Moreover, after antibiotic treatment, persisters become more alkaline than VBNC and susceptible E. coli cells. This newly found phenotypic feature is remarkable because it distinguishes persister and VBNC cells that have often been thought to display the same dormant phenotype. We then show that this differential pH regulation is abolished in the absence of the enzyme tryptophanase via a major remodeling of bacterial metabolism and pH homeostasis. These new whole-genome transcriptome data should be taken into account when modeling bacterial metabolism at the crucial transition from exponential to stationary phase. Overall, our findings indicate that the manipulation of the intracellular pH represents a bacterial strategy for surviving antibiotic treatment. In turn, this suggests a strategy for developing persister-targeting antibiotics by interfering with cellular components, such as tryptophanase, that play a major role in pH homeostasis.