Robust, linear correlations between growth rates and β-lactam-mediated lysis rates

Streptococcus suis regulates central carbon fluxes in response to environment to balance drug resistance and virulence

Streptococcus suis, a zoonotic pathogen, must adapt to the distinct nutritional environment of the host microhabitat during infection and the establishment of invasive disease, primarily by modulating its metabolic pathways. Metabolic plasticity endows S. suis with an enhanced capacity for environmental adaptation. Multidrug-resistant S. suis is increasingly prevalent due to the extensive use of antibiotics in swine production. In this study, an environment-dependent evolutionary model demonstrated that S. suis could modulate its metabolism in response to environmental changes, thereby altering its drug resistance and virulence. The central carbon flux regulated by pyruvate dehydrogenase (PDH) was identified as a pivotal node in balancing drug resistance and virulence in S. suis. Within the in vivo host environment, increased carbon flux through PDH enhances the production of capsular polysaccharide (CPS), thereby improving immune evasion. Conversely, in the antibiotic environment, reduced carbon flux through PDH downregulates the bacterial metabolic state, which diminishes the induction of toxic metabolites by antibiotics, thereby augmenting drug resistance. This concept provides a reasonable explanation for the puzzling phenomena observed with S. suis in clinical settings. For instance, antibiotic-resistant S. suis has a survival advantage in pig farms where antibiotics are frequently used but is less frequently associated with invasive infections. Furthermore, this study demonstrates that exogenous pyruvate can enhance the bactericidal effect of gentamicin against clinically multidrug-resistant S. suis, offering new insights and potential strategies for controlling clinical multidrug-resistant S. suis infections.

Antibiotic-mediated microbial community restructuring is dictated by variability in antibiotic-induced lysis rates and population interactions

It is widely known that faster-growing bacterial cells are more susceptible to many antibiotics. Given this notion, it appears intuitive that antibiotic treatment would enrich slower-growing cells in a clonal population or slower-growing populations in a microbial community, which has been commonly observed. However, experimental observations also show the enrichment of faster-growing subpopulations under certain conditions. Does this apparent discrepancy suggest the uniqueness about different growth environments or the role of additional confounding factors? If so, what could be the major determinant in antibiotic-mediated community restructuring? Combining modeling and quantitative measurements using a barcoded heterogeneous E. coli library, we show that the outcome of antibiotic-mediated community restructuring can be driven by two major factors. One is the variability among the clonal responses of different subpopulations to the antibiotic; the other is their interactions. Our results suggest the importance of quantitative measurements of antibiotic responses in individual clones in predicting community responses to antibiotics and addressing subpopulation interactions.

Deciphering population-level response under spatial drug heterogeneity on microhabitat structures

Bacteria and cancer cells live in a spatially heterogeneous environment, where migration shapes the microhabitat structures critical for colonization and metastasis. The interplay between growth, migration, and microhabitat structure complicates the prediction of population responses to drugs, such as clearance or sustained growth, posing a longstanding challenge. Here, we disentangle growth-migration dynamics and identify that population decline is determined by two decoupled terms: a spatial growth variation term and a microhabitat structure term. Notably, the microhabitat structure term can be interpreted as a dynamic-related centrality measure. For fixed spatial drug arrangements, we show that interpreting these centralities reveals how different network structures, even with identical edge densities, microhabitat numbers, and spatial heterogeneity, can lead to distinct population-level responses. Increasing edge density shifts the population response from growth to clearance, supporting an inversed centrality-connectivity relationship, and mirroring the effects of higher migration rates. Furthermore, we derive a sufficient condition for robust population decline across various spatial growth rate arrangements, regardless of spatial-temporal fluctuations induced by drugs. Additionally, we demonstrate that varying the maximum growth-to-death ratio, determined by drug-bacteria interactions, can lead to distinct population decline profiles and a minimal decline phase emerges. These findings address key challenges in predicting population-level responses and provide insights into divergent clinical outcomes under identical drug dosages. This work may offer a new method of interpreting treatment dynamics and potential approaches for optimizing spatially explicit drug dosing strategies.

Metabolic mutations reduce antibiotic susceptibility of E. coli by pathway-specific bottlenecks

Metabolic variation across pathogenic bacterial strains can impact their susceptibility to antibiotics and promote the evolution of antimicrobial resistance (AMR). However, little is known about how metabolic mutations influence metabolism and which pathways contribute to antibiotic susceptibility. Here, we measured the antibiotic susceptibility of 15,120 Escherichia coli mutants, each with a single amino acid change in one of 346 essential proteins. Across all mutants, we observed modest increases of the minimal inhibitory concentration (twofold to tenfold) without any cases of major resistance. Most mutants that showed reduced susceptibility to either of the two tested antibiotics carried mutations in metabolic genes. The effect of metabolic mutations on antibiotic susceptibility was antibiotic- and pathway-specific: mutations that reduced susceptibility against the β-lactam antibiotic carbenicillin converged on purine nucleotide biosynthesis, those against the aminoglycoside gentamicin converged on the respiratory chain. In addition, metabolic mutations conferred tolerance to carbenicillin by reducing growth rates. These results, along with evidence that metabolic bottlenecks are common among clinical E. coli isolates, highlight the contribution of metabolic mutations for AMR.

The role of bacterial metabolism in antimicrobial resistance

The relationship between bacterial metabolism and antibiotic treatment is complex. On the one hand, antibiotics leverage cell metabolism to function. On the other hand, increasing research has highlighted that the metabolic state of the cell also impacts all aspects of antibiotic biology, from drug efficacy to the evolution of antimicrobial resistance (AMR). Given that AMR is a growing threat to the current global antibiotic arsenal and ability to treat infectious diseases, understanding these relationships is key to improving both public and human health. However, quantifying the contribution of metabolism to antibiotic activity and subsequent bacterial evolution has often proven challenging. In this Review, we discuss the complex and often bidirectional relationships between metabolism and the various facets of antibiotic treatment and response. We first summarize how antibiotics leverage metabolism for their function. We then focus on the converse of this relationship by specifically delineating the unique contribution of metabolism to three distinct but related arms of antibiotic biology: antibiotic efficacy, AMR evolution and AMR mechanisms. Finally, we note the relevance of metabolism in clinical contexts and explore the future of metabolic-based strategies for personalized antimicrobial therapies. A deeper understanding of these connections is crucial for the broader scientific community to address the growing crisis of AMR and develop future effective therapeutics.

Genetic adaptation to amoxicillin in Escherichia coli: The limited role of dinB and katE

Bacteria can quickly adapt to sub-lethal concentrations of antibiotics. Several stress and DNA repair genes contribute to this adaptation process. However, the pathways leading to adaptation by acquisition of de novo mutations remain poorly understood. This study explored the roles of DNA polymerase IV (dinB) and catalase HP2 (katE) in E. coli's adaptation to amoxicillin. These genes are thought to play essential roles in beta-lactam resistance-dinB in increasing mutation rates and katE in managing oxidative stress. By comparing the adaptation rates, transcriptomic profiles, and genetic changes of wild-type and knockout strains, we aimed to clarify the contributions of these genes to beta-lactam resistance. While all strains exhibited similar adaptation rates and mutations in the frdD gene and ampC operon, several unique mutations were acquired in the ΔkatE and ΔdinB strains. Overall, this study distinguishes the contributions of general stress-related genes on the one hand, and dinB, and katE on the other hand, in development of beta-lactam resistance.

Habitat fragmentation enhances microbial collective defence

Microbes often inhabit complex, spatially partitioned environments such as host tissue or soil, but the effects of habitat fragmentation on microbial ecology and infection dynamics are poorly understood. Here, we investigate how habitat fragmentation impacts a prevalent microbial collective defence mechanism: enzymatic degradation of an environmental toxin. Using a theoretical model, we predict that habitat fragmentation can strongly enhance the collective benefits of enzymatic toxin degradation. For the example of [Formula: see text]-lactamase-producing bacteria that mount a collective defence by degrading a [Formula: see text]-lactam antibiotic, we find that realistic levels of habitat fragmentation can allow a population to survive antibiotic doses that greatly exceed those required to kill a non-fragmented population. This 'habitat-fragmentation rescue' is a stochastic effect that originates from variation in bacterial density among different subpopulations and demographic noise. We also study the contrasting case of collective enzymatic foraging, where enzyme activity releases nutrients from the environment; here we find that increasing habitat fragmentation decreases the lag time for population growth but does not change the ecological outcome. Taken together, this work predicts that stochastic effects arising from habitat fragmentation can greatly enhance the effectiveness of microbial collective defence via enzymatic toxin degradation.

Antimicrobial peptide LL37 is potent against non-growing Escherichia coli cells despite a slower action rate

Antimicrobial peptides (AMPs) have long been considered as potential agents against non-growing, dormant cells due to their membrane-targeted action, which is largely independent of the cell's growth state. However, the relationship between the action of AMPs and the physiological state of their target cells has been unclear, with recent reports offering conflicting views on the efficacy of AMPs against bacteria in a stationary phase. In this study, we employ single-cell approaches combined with population-level experiments to examine the action of human LL37 peptides against Escherichia coli cells in different growth phases. Time-lapse, single-cell data from our experiments reveal that LL37 peptides act faster on large, dividing cells than on small, newborn cells. We extend this investigation to non-growing E. coli cells in a stationary phase, where we observe that the action of LL37 peptides is slower on non-growing cells compared to exponentially growing cells. This slower action rate is, however, not mirrored in the minimum bactericidal concentration (MBC) measurements. Notably, we find that the MBC for non-growing cells is lower than for exponentially growing cells, indicating that, given sufficient time, LL37 peptides exhibit strong potency against non-growing cells. We propose that the enhanced potency of LL37 peptides against non-growing cells, despite their slower action, can be attributed to continuous absorption of AMPs on the cell membrane over time.

IMPORTANCE

Antibiotic treatments can fail because of the regrowth of a bacterial subpopulation that resumes proliferation once the treatment ceases. This resurgence is primarily driven by non-growing, dormant bacterial cells that withstand the action of antibiotics without developing resistance. In this study, we explore the potency of the human antimicrobial peptide LL37 against non-growing Escherichia coli cells. Our findings reveal that despite a slower initial action, LL37 peptides, given sufficient time, demonstrate strong efficacy against non-growing cells. These insights suggest a potential role of antimicrobial peptides in combating persistent bacterial infections by targeting the non-growing cells.

Pilin antigenic variants impact gonococcal lifestyle and antibiotic tolerance by modulating interbacterial forces

Type 4 pili (T4P) are multifunctional filaments involved in adhesion, surface motility, biofilm formation, and horizontal gene transfer. These extracellular polymers are surface-exposed and, therefore, act as antigens. The human pathogen Neisseria gonorrhoeae uses pilin antigenic variation to escape immune surveillance, yet it is unclear how antigenic variation impacts most other functions of T4P. Here, we addressed this question by replacing the major pilin of a laboratory strain with pilins from clinical isolates. We reveal that the resulting strains vary substantially in their attractive forces. Strongly interacting bacteria form microcolonies while weakly interacting bacteria retain a planktonic lifestyle. In mixed microcolonies, different variant strains segregate in agreement with the differential strength of adhesion hypothesis. By combining structural predictions and laser tweezers experiments, we show that the C-terminal region of the pilin is crucial for attraction. Lifestyle affects growth kinetics and antibiotic tolerance. In the presence of ceftriaxone or ciprofloxacin, the killing kinetics indicate strongly increased tolerance of aggregating strains. We propose that pilin antigenic variation produces a mixed population containing variants optimized for growth, colonization, or survivability under external stress. Different environments select different variants, ensuring the survival and reproduction of the population as a whole.

Rethinking dormancy: Antibiotic persisters are metabolically active, non-growing cells

OBJECTIVES

Bacterial persisters are a subpopulation of multidrug-tolerant cells capable of surviving and resuming activity after exposure to bactericidal antibiotic concentrations, contributing to relapsing infections and the development of antibiotic resistance. In this study, we challenge the conventional view that persisters are metabolically dormant by providing compelling evidence that an isogenic population of Escherichia coli remains metabolically active in persistence.

METHODS

Using transcriptomic analysis, we examined E. coli persisters at multiple time points following exposure to bactericidal concentrations of ampicillin (Amp). Some genes were consistently upregulated in Amp treated persisters compared to the untreated controls, a change that can only occur in metabolically active cells capable of increasing RNA levels.

RESULTS

Some of the identified genes have been previously linked to persister cells, while others have not been associated with them before. If persister cells were metabolically dormant, gene expression changes over time would be minimal during Amp treatment. However, network analysis revealed major shifts in gene network activity at various time points of antibiotic exposure.

CONCLUSIONS

These findings reveal that persisters are metabolically active, non-dividing cells, thereby challenging the traditional view that they are dormant.

Antibiotic tolerance among clinical isolates: mechanisms, detection, prevalence, and significance

SUMMARYAntibiotic treatment failures in the absence of resistance are not uncommon. Recently, attention has grown around the phenomenon of antibiotic tolerance, an underappreciated contributor to recalcitrant infections first detected in the 1970s. Tolerance describes the ability of a bacterial population to survive transient exposure to an otherwise lethal concentration of antibiotic without exhibiting resistance. With advances in genomics, we are gaining a better understanding of the molecular mechanisms behind tolerance, and several studies have sought to examine the clinical prevalence of tolerance. Attempts have also been made to assess the clinical significance of tolerance through in vivo infection models and prospective/retrospective clinical studies. Here, we review the data available on the molecular mechanisms, detection, prevalence, and clinical significance of genotypic tolerance that span ~50 years. We discuss the need for standardized methodology and interpretation criteria for tolerance detection and the impact that methodological inconsistencies have on our ability to accurately assess the scale of the problem. In terms of the clinical significance of tolerance, studies suggest that tolerance contributes to worse outcomes for patients (e.g., higher mortality, prolonged hospitalization), but historical data from animal models are varied. Furthermore, we lack the necessary information to effectively treat tolerant infections. Overall, while the tolerance field is gaining much-needed traction, the underlying clinical significance of tolerance that underpins all tolerance research is still far from clear and requires attention.

Linking spatial drug heterogeneity to microbial growth dynamics in theory and experiment

Diffusion and migration play pivotal roles in microbial communities - shaping, for example, colonization in new environments and the maintenance of spatial structures of biodiversity. While previous research has extensively studied free diffusion, such as range expansion, there remains a gap in understanding the effects of biologically or physically deleterious confined environments. In this study, we examine the interplay between migration and spatial drug heterogeneity within an experimental meta-community of E. faecalis, a Gram-positive opportunistic pathogen. When the community is confined to spatially-extended habitats ('islands') bordered by deleterious conditions, we find that the population level response depends on the trade-off between the growth rate within the island and the rate of transfer into regions with harsher conditions, a phenomenon we explore by modulating antibiotic concentration within the island. In heterogeneous islands, composed of spatially patterned patches that support varying levels of growth, the population's fate depends critically on the specific spatial arrangement of these patches - the same spatially averaged growth rate leads to diverging responses. These results are qualitatively captured by simple simulations, and analytical expressions which we derive using first-order perturbation approximations to reaction-diffusion models with explicit spatial dependence. Among all possible spatial arrangements, our theoretical and experimental findings reveal that the arrangement with the highest growth rates at the center most effectively mitigates population decline, while the arrangement with the lowest growth rates at the center is the least effective. Extending this approach to more complex experimental communities with varied spatial structures, such as a ring-structured community, further validates the impact of spatial drug arrangement. Our findings suggest new approaches to interpreting diverging clinical outcomes when applying identical drug doses and inform the possible optimization of spatially-explicit dosing strategies.

Correction of a widespread bias in pooled chemical genomics screens improves their interpretability

Chemical genomics is a powerful and increasingly accessible technique to probe gene function, gene-gene interactions, and antibiotic synergies and antagonisms. Indeed, multiple large-scale pooled datasets in diverse organisms have been published. Here, we identify an artifact arising from uncorrected differences in the number of cell doublings between experiments within such datasets. We demonstrate that this artifact is widespread, show how it causes spurious gene-gene and drug-drug correlations, and present a simple but effective post hoc method for removing its effects. Using several published datasets, we demonstrate that this correction removes spurious correlations between genes and conditions, improving data interpretability and revealing new biological insights. Finally, we determine experimental factors that predispose a dataset for this artifact and suggest a set of experimental and computational guidelines for performing pooled chemical genomics experiments that will maximize the potential of this powerful technique.

Anaerobic bacteria in chronic wounds: Roles in disease, infection and treatment failure

Infection is among the most common factors that impede wound healing, yet standard treatments routinely fail to resolve chronic wound infections. The chronic wound environment is largely hypoxic/anoxic, and wounds are predominantly colonised by facultative and obligate anaerobic bacteria. Oxygen (O2) limitation is an underappreciated driver of microbiota composition and behaviour in chronic wounds. In this perspective article, we examine how anaerobic bacteria and their distinct physiologies support persistent, antibiotic-recalcitrant infections. We describe the anaerobic energy metabolisms bacteria rely on for long-term survival in the wound environment, and why many antibiotics become less effective under hypoxic conditions. We also discuss obligate anaerobes, which are among the most prevalent taxa to colonise chronic wounds, yet their potential roles in influencing the microbial community and wound healing have been overlooked. All of the most common obligate anaerobes found in chronic wounds are opportunistic pathogens. We consider how these organisms persist in the wound environment and interface with host physiology to hinder wound healing processes or promote chronic inflammation. Finally, we apply our understanding of anaerobic physiologies to evaluate current treatment practices and to propose new strategies for treating chronic wound infections.

Optogenetic patterning generates multi-strain biofilms with spatially distributed antibiotic resistance

Spatial organization of microbes in biofilms enables crucial community function such as division of labor. However, quantitative understanding of such emergent community properties remains limited due to a scarcity of tools for patterning heterogeneous biofilms. Here we develop a synthetic optogenetic toolkit 'Multipattern Biofilm Lithography' for rational engineering and orthogonal patterning of multi-strain biofilms, inspired by successive adhesion and phenotypic differentiation in natural biofilms. We apply this toolkit to profile the growth dynamics of heterogeneous biofilm communities, and observe the emergence of spatially modulated commensal relationships due to shared antibiotic protection against the beta-lactam ampicillin. Supported by biophysical modeling, these results yield in-vivo measurements of key parameters, e.g., molecular beta-lactamase production per cell and length scale of antibiotic zone of protection. Our toolbox and associated findings provide quantitative insights into the spatial organization and distributed antibiotic protection within biofilms, with direct implications for future biofilm research and engineering.

Purine and pyrimidine synthesis differently affect the strength of the inoculum effect for aminoglycoside and β-lactam antibiotics

The inoculum effect has been observed for nearly all antibiotics and bacterial species. However, explanations accounting for its occurrence and strength are lacking. Previous work found that the relationship between [ATP] and growth rate can account for the strength and occurrence of the inoculum effect for bactericidal antibiotics. However, the molecular pathway(s) underlying this relationship, and therefore determining the inoculum effect, remain undiscovered. Using a combination of flux balance analysis and experimentation, we show that nucleotide synthesis can determine the relationship between [ATP] and growth and thus the strength of inoculum effect in an antibiotic class-dependent manner. If the [ATP]/growth rate is sufficiently high as determined by exogenously supplied nitrogenous bases, the inoculum effect does not occur. This is consistent for both Escherichia coli and Pseudomonas aeruginosa. Interestingly, and separate from activity through the tricarboxylic acid cycle, we find that transcriptional activity of genes involved in purine and pyrimidine synthesis can predict the strength of the inoculum effect for β-lactam and aminoglycosides antibiotics, respectively. Our work highlights the antibiotic class-specific effect of purine and pyrimidine synthesis on the severity of the inoculum effect, which may pave the way for intervention strategies to reduce the inoculum effect in the clinic.

IMPORTANCE

If a bacterial population can grow and reach a sufficiently high density, routine doses of antibiotics can be ineffective. This phenomenon, called the inoculum effect, has been observed for nearly all antibiotics and bacterial species. It has also been reported to result in antibiotic failure in the clinic. Understanding how to reduce the inoculum effect can make high-density infections easier to treat. Here, we show that purine and pyrimidine synthesis affect the strength of the inoculum effect; as the transcriptional activity of pyrimidine synthesis increases, the strength of the inoculum effect for aminoglycosides decreases. Conversely, as the transcriptional activity of purine synthesis increases, the strength of the inoculum effect for β-lactam antibiotics decreases. Our work highlights the importance of nucleotide synthesis in determining the strength of the inoculum effect, which may lead to the identification of new ways to treat high-density infections in the clinic.

Synergistic effects of novel penicillin-binding protein 1A amino acid substitutions contribute to high-level amoxicillin resistance of Helicobacter pylori

The growing resistance to amoxicillin (AMX)-one of the main antibiotics used in Helicobacter pylori eradication therapy-is an increasing health concern. Several mutations of penicillin-binding protein 1A (PBP1A) are suspected of causing AMX resistance; however, only a limited set of these mutations have been experimentally explored. This study aimed to investigate four PBP1A mutations (i.e., T558S, N562H, T593A, and G595S) carried by strain KIN76, a high-level AMX-resistant clinical H. pylori isolate with an AMX minimal inhibition concentration (MIC) of 2 µg/mL. We transformed a recipient strain 26695 with the DNA containing one to four mutation allele combinations of the pbp1 gene from strain KIN76. Transformants were subjected to genomic exploration and antimicrobial susceptibility testing. The resistance was transformable, and the presence of two to four PBP1A mutations (T558S and N562H, or T593A and G595S), rather than separate single mutations, was necessary to synergistically increase the AMX MIC up to 16-fold compared with the wild-type (WT) strain 26695. An AMX binding assay of PBP1A was performed using these strains, and binding was visualized by chasing Bocillin, a fluorescent penicillin analog. This revealed that all four-mutation allele-transformed strains exhibited decreased affinity to AMX on PBP1A than the WT. Protein structure modeling indicated that functional modifications occur as a result of these amino acid substitutions. This study highlights a new synergistic AMX resistance mechanism and establishes new markers of AMX resistance in H. pylori.IMPORTANCEThe development of resistance to antibiotics, including amoxicillin, is hampering the eradication of Helicobacter pylori infection. The identification of mechanisms driving this resistance is crucial for the development of new therapeutic strategies. We have demonstrated in vitro the synergistic role of novel mutations in the pbp1 gene of H. pylori that is suspected to drive amoxicillin resistance. Also deepening our understanding of amoxicillin resistance mechanisms, this study establishes new molecular markers of amoxicillin resistance that may be useful in molecular-based antibiotic susceptibility testing approaches for clinical practice or epidemiologic investigations.

Coordinated regulation of osmotic imbalance by c-di-AMP shapes ß-lactam tolerance in Group B Streptococcus

Streptococcus agalactiae is among the few pathogens that have not developed resistance to ß-lactam antibiotics despite decades of clinical use. The molecular basis of this long-lasting susceptibility has not been investigated, and it is not known whether specific mechanisms constrain the emergence of resistance. In this study, we first report ß-lactam tolerance due to the inactivation of the c-di-AMP phosphodiesterase GdpP. Mechanistically, tolerance depends on antagonistic regulation by the repressor BusR, which is activated by c-di-AMP and negatively regulates ß-lactam susceptibility through the BusAB osmolyte transporter and the AmaP/Asp23/GlsB cell envelope stress complex. The BusR transcriptional response is synergistic with the simultaneous allosteric inhibition of potassium and osmolyte transporters by c-di-AMP, which individually contribute to low-level ß-lactam tolerance. Genome-wide transposon mutagenesis confirms the role of GdpP and highlights functional interactions between a lysozyme-like hydrolase, the KhpAB RNA chaperone and the protein S immunomodulator in the response of GBS to ß-lactam. Overall, we demonstrate that c-di-AMP acts as a turgor pressure rheostat, coordinating an integrated response at the transcriptional and post-translational levels to cell wall weakening caused by ß-lactam activity, and reveal additional mechanisms that could foster resistance.

Data-driven learning of structure augments quantitative prediction of biological responses

Multi-factor screenings are commonly used in diverse applications in medicine and bioengineering, including optimizing combination drug treatments and microbiome engineering. Despite the advances in high-throughput technologies, large-scale experiments typically remain prohibitively expensive. Here we introduce a machine learning platform, structure-augmented regression (SAR), that exploits the intrinsic structure of each biological system to learn a high-accuracy model with minimal data requirement. Under different environmental perturbations, each biological system exhibits a unique, structured phenotypic response. This structure can be learned based on limited data and once learned, can constrain subsequent quantitative predictions. We demonstrate that SAR requires significantly fewer data comparing to other existing machine-learning methods to achieve a high prediction accuracy, first on simulated data, then on experimental data of various systems and input dimensions. We then show how a learned structure can guide effective design of new experiments. Our approach has implications for predictive control of biological systems and an integration of machine learning prediction and experimental design.

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.

Antimicrobial effects of blue light therapy against cutibacterium acnes: optimal dosing and impact of serial treatments

Background

Blue light therapy (BLT) is a Food and Drug Administration cleared modality used in dermatology as an effective treatment of acne. The primary purpose of this study is to determine if there are dose-dependent antimicrobial effects of BLT against Cutibacterium acnes (C. acnes).

Methods

A known strain of C. acnes was grown on chocolate agar in a controlled laboratory environment under anaerobic conditions for 1 week. After 1 week, 2-3 colonies of C. acnes were isolated and transferred to broth medium to incubate for 2 or 7 days. Broth vials (treatment arm) then underwent 1 of 6 different blue light dosing treatment regimens and a duplicate broth vial served as a control left open to the same environment. The BLT regimens were a single treatment of 25 J/cm2, 50 J/cm2, 75 J/cm2, 100 J/cm2, 2 serial treatments of 50 J/cm2 separated by 24 hours, or 2 serial treatments of 75 J/cm2 separated by 24 hours. The Omnilux Blue device (415 nm wavelength) was used for all BLT treatments and delivered, on average, 1.68 ± 0.004 J/min. Following treatment, the control and treatment broth samples were plated on chocolate agar and allowed to grow for 7 days. After 7 days, plates were counted and colony forming units (CFUs) were calculated. Six trials were completed for each BLT dosing regimen based on an a priori power analysis of 6 individual 2-sided t-tests. Comparisons in the primary outcome were made via mixed-effects analysis of variance with replicate as a random effect.

Results

All BLT treatment regimens resulted in significantly fewer CFUs than their aggregate control plate CFUs (P < .05 for all). Furthermore, in 2-way comparison of CFUs between BLT treatment groups, a single treatment of 75 J/cm2 did lead to significantly less growth than 25 J/cm2 (P = .017) and 50 J/cm2 (P = .017). There were no improved antimicrobial effects with serial treatments when comparing 2 doses of 50 J/cm2 with a single dose of 100J/cm2, nor were 2 doses of 75 J/cm2 more efficacious than 100 J/cm2. Using the Omnilux Blue device, it took 44.8 minutes to deliver a 75 J/cm2 dose.

Conclusion

BLT is an effective antimicrobial agent against this single virulent strain of C. acnes. Treatment dosing of 75 J/cm2 was identified to be the most effective dose per unit time. Serial treatments did not lead to superior antimicrobial effects over a single, high-dose treatment.

Essential gene knockdowns reveal genetic vulnerabilities and antibiotic sensitivities in Acinetobacter baumannii

The emergence of multidrug-resistant Gram-negative bacteria underscores the need to define genetic vulnerabilities that can be therapeutically exploited. The Gram-negative pathogen, Acinetobacter baumannii, is considered an urgent threat due to its propensity to evade antibiotic treatments. Essential cellular processes are the target of existing antibiotics and a likely source of new vulnerabilities. Although A. baumannii essential genes have been identified by transposon sequencing, they have not been prioritized by sensitivity to knockdown or antibiotics. Here, we take a systems biology approach to comprehensively characterize A. baumannii essential genes using CRISPR interference (CRISPRi). We show that certain essential genes and pathways are acutely sensitive to knockdown, providing a set of vulnerable targets for future therapeutic investigation. Screening our CRISPRi library against last-resort antibiotics uncovered genes and pathways that modulate beta-lactam sensitivity, an unexpected link between NADH dehydrogenase activity and growth inhibition by polymyxins, and anticorrelated phenotypes that may explain synergy between polymyxins and rifamycins. Our study demonstrates the power of systematic genetic approaches to identify vulnerabilities in Gram-negative pathogens and uncovers antibiotic-essential gene interactions that better inform combination therapies.IMPORTANCEAcinetobacter baumannii is a hospital-acquired pathogen that is resistant to many common antibiotic treatments. To combat resistant A. baumannii infections, we need to identify promising therapeutic targets and effective antibiotic combinations. In this study, we comprehensively characterize the genes and pathways that are critical for A. baumannii viability. We show that genes involved in aerobic metabolism are central to A. baumannii physiology and may represent appealing drug targets. We also find antibiotic-gene interactions that may impact the efficacy of carbapenems, rifamycins, and polymyxins, providing a new window into how these antibiotics function in mono- and combination therapies. Our studies offer a useful approach for characterizing interactions between drugs and essential genes in pathogens to inform future therapies.

Tradeoffs in bacterial physiology determine the efficiency of antibiotic killing

Antibiotic effectiveness depends on a variety of factors. While many mechanistic details of antibiotic action are known, the connection between death rate and bacterial physiology is poorly understood. A common observation is that death rate in antibiotics rises linearly with growth rate; however, it remains unclear how other factors, such as environmental conditions and whole-cell physiological properties, affect bactericidal activity. To address this, we developed a high-throughput assay to precisely measure antibiotic-mediated death. We found that death rate is linear in growth rate, but the slope depends on environmental conditions. Growth under stress lowers death rate compared to nonstressed environments with similar growth rate. To understand stress's role, we developed a mathematical model of bacterial death based on resource allocation that includes a stress-response sector; we identify this sector using RNA-seq. Our model accurately predicts the minimal inhibitory concentration (MIC) with zero free parameters across a wide range of growth conditions. The model also quantitatively predicts death and MIC when sectors are experimentally modulated using cyclic adenosine monophosphate (cAMP), including protection from death at very low cAMP levels. The present study shows that different conditions with equal growth rate can have different death rates and establishes a quantitative relation between growth, death, and MIC that suggests approaches to improve antibiotic efficacy.

Ribosome-binding antibiotics increase bacterial longevity and growth efficiency

Antibiotics, by definition, reduce bacterial growth rates in optimal culture conditions; however, the real-world environments bacteria inhabit see rapid growth punctuated by periods of low nutrient availability. How antibiotics mediate population decline during these periods is poorly understood. Bacteria cannot optimize for all environmental conditions because a growth-longevity tradeoff predicts faster growth results in faster population decline, and since bacteriostatic antibiotics slow growth, they should also mediate longevity. We quantify how antibiotics, their targets, and resistance mechanisms influence longevity using populations of Escherichia coli and, as the tradeoff predicts, populations are maintained for longer if they encounter ribosome-binding antibiotics doxycycline and erythromycin, a finding that is not observed using antibiotics with alternative cellular targets. This tradeoff also predicts resistance mechanisms that increase growth rates during antibiotic treatment could be detrimental during nutrient stresses, and indeed, we find resistance by ribosomal protection removes benefits to longevity provided by doxycycline. We therefore liken ribosomal protection to a "Trojan horse" because it provides protection from an antibiotic but, during nutrient stresses, it promotes the demise of the bacteria. Seeking mechanisms to support these observations, we show doxycycline promotes efficient metabolism and reduces the concentration of reactive oxygen species. Seeking generality, we sought another mechanism that affects longevity and we found the number of doxycycline targets, namely, the ribosomal RNA operons, mediates growth and longevity even without antibiotics. We conclude that slow growth, as observed during antibiotic treatment, can help bacteria overcome later periods of nutrient stress.

Short-Term Dietary Intervention with Whole Oats Protects from Antibiotic-Induced Dysbiosis

Antibiotic-induced gut microbiome dysbiosis (AID) is known to be influenced by host dietary composition. However, how and when diet modulates gut dysbiosis remains poorly characterized. Thus, here, we utilize a multi-omics approach to characterize how a diet supplemented with oats, a rich source of microbiota-accessible carbohydrates, or dextrose impacts amoxicillin-induced changes to gut microbiome structure and transcriptional activity. We demonstrate that oat administration during amoxicillin challenge provides greater protection from AID than the always oats or recovery oats diet groups. In particular, the group in which oats were provided at the time of antibiotic exposure induced the greatest protection against AID while the other oat diets saw greater effects after amoxicillin challenge. The oat diets likewise reduced amoxicillin-driven elimination of Firmicutes compared to the dextrose diet. Functionally, gut communities fed dextrose were carbohydrate starved and favored respiratory metabolism and consequent metabolic stress management while oat-fed communities shifted their transcriptomic profile and emphasized antibiotic stress management. The metabolic trends were exemplified when assessing transcriptional activity of the following two common gut commensal bacteria: Akkermansia muciniphila and Bacteroides thetaiotaomicron. These findings demonstrate that while host diet is important in shaping how antibiotics effect the gut microbiome composition and function, diet timing may play an even greater role in dietary intervention-based therapeutics. IMPORTANCE We utilize a multi-omics approach to demonstrate that diets supplemented with oats, a rich source of microbiota-accessible carbohydrates, are able to confer protection against antibiotic-induced dysbiosis (AID). Our findings affirm that not only is host diet important in shaping antibiotics effects on gut microbiome composition and function but also that the timing of these diets may play an even greater role in managing AID. This work provides a nuanced perspective on dietary intervention against AID and may be informative on preventing AID during routine antibiotic treatment.

Essential Gene Knockdowns Reveal Genetic Vulnerabilities and Antibiotic Sensitivities in Acinetobacter baumannii

The emergence of multidrug-resistant Gram-negative bacteria underscores the need to define genetic vulnerabilities that can be therapeutically exploited. The Gram-negative pathogen, Acinetobacter baumannii, is considered an urgent threat due to its propensity to evade antibiotic treatments. Essential cellular processes are the target of existing antibiotics and a likely source of new vulnerabilities. Although A. baumannii essential genes have been identified by transposon sequencing (Tn-seq), they have not been prioritized by sensitivity to knockdown or antibiotics. Here, we take a systems biology approach to comprehensively characterize A. baumannii essential genes using CRISPR interference (CRISPRi). We show that certain essential genes and pathways are acutely sensitive to knockdown, providing a set of vulnerable targets for future therapeutic investigation. Screening our CRISPRi library against last-resort antibiotics uncovered genes and pathways that modulate beta-lactam sensitivity, an unexpected link between NADH dehydrogenase activity and growth inhibition by polymyxins, and anticorrelated phenotypes that underpin synergy between polymyxins and rifamycins. Our study demonstrates the power of systematic genetic approaches to identify vulnerabilities in Gram-negative pathogens and uncovers antibiotic-essential gene interactions that better inform combination therapies.

Lipopolysaccharide transport regulates bacterial sensitivity to a cell wall-degrading intermicrobial toxin

Gram-negative bacteria can antagonize neighboring microbes using a type VI secretion system (T6SS) to deliver toxins that target different essential cellular features. Despite the conserved nature of these targets, T6SS potency can vary across recipient species. To understand the functional basis of intrinsic T6SS susceptibility, we screened for essential Escherichia coli (Eco) genes that affect its survival when antagonized by a cell wall-degrading T6SS toxin from Pseudomonas aeruginosa, Tae1. We revealed genes associated with both the cell wall and a separate layer of the cell envelope, lipopolysaccharide, that modulate Tae1 toxicity in vivo. Disruption of genes in early lipopolysaccharide biosynthesis provided Eco with novel resistance to Tae1, despite significant cell wall degradation. These data suggest that Tae1 toxicity is determined not only by direct substrate damage, but also by indirect cell envelope homeostasis activities. We also found that Tae1-resistant Eco exhibited reduced cell wall synthesis and overall slowed growth, suggesting that reactive cell envelope maintenance pathways could promote, not prevent, self-lysis. Together, our study reveals the complex functional underpinnings of susceptibility to Tae1 and T6SS which regulate the impact of toxin-substrate interactions in vivo.

Mapping single‐cell responses to population‐level dynamics during antibiotic treatment

Treatment of sensitive bacteria with beta‐lactam antibiotics often leads to two salient population‐level features: a transient increase in total population biomass before a subsequent decline, and a linear correlation between growth and killing rates. However, it remains unclear how these population‐level responses emerge from collective single‐cell responses. During beta‐lactam treatment, it is well‐recognized that individual cells often exhibit varying degrees of filamentation before lysis. We show that the cumulative probability of cell lysis increases sigmoidally with the extent of filamentation and that this dependence is characterized by unique parameters that are specific to bacterial strain, antibiotic dose, and growth condition. Modeling demonstrates how the single‐cell lysis probabilities can give rise to population‐level biomass dynamics, which were experimentally validated. This mapping provides insights into how the population biomass time‐kill curve emerges from single cells and allows the representation of both single‐ and population‐level responses with universal parameters.

Lipopolysaccharide integrity primes bacterial sensitivity to a cell wall-degrading intermicrobial toxin

Gram-negative bacteria can antagonize neighboring microbes using a type VI secretion system (T6SS) to deliver toxins that target different essential cellular features. Despite the conserved nature of these targets, T6SS potency can vary across recipient species. To understand the molecular basis of intrinsic T6SS susceptibility, we screened for essential Escherichia coli genes that affect its survival when antagonized by a cell wall-degrading T6SS toxin from Pseudomonas aeruginosa , Tae1. We revealed genes associated with both the cell wall and a separate layer of the cell envelope, surface lipopolysaccharide, that modulate Tae1 toxicity in vivo . Disruption of lipopolysaccharide synthesis provided Escherichia coli (Eco) with novel resistance to Tae1, despite significant cell wall degradation. These data suggest that Tae1 toxicity is determined not only by direct substrate damage, but also by indirect cell envelope homeostasis activities. We also found that Tae1-resistant Eco exhibited reduced cell wall synthesis and overall slowed growth, suggesting that reactive cell envelope maintenance pathways could promote, not prevent, self-lysis. Together, our study highlights the consequences of co-regulating essential pathways on recipient fitness during interbacterial competition, and how antibacterial toxins leverage cellular vulnerabilities that are both direct and indirect to their specific targets in vivo .

Survival of Escherichia coli after high-antibiotic stress is dependent on both the pregrown physiological state and incubation conditions

Introduction

The survival of bacterial cells exposed to antibiotics depends on the mode of action, the antibiotics concentration, and the duration of treatment. However, it also depends on the physiological state of the cells and the environmental conditions. In addition, bacterial cultures contain sub-populations that can survive high antibiotic concentrations, so-called persisters. Research on persisters is challenging due to multiple mechanisms for their formation and low fractions, down to and below one millionth of the total cell population. Here, we present an improved version of the persister assay used to enumerate the amount of persisters in a cell population.

Methods

The persister assay with high antibiotic stress exposure was performed at both growth supporting and non-supporting conditions. Escherichia coli cells were pregrown to various growth stages in shake flasks and bench-top bioreactors. In addition, the physiological state of E. coli before antibiotic treatment was determined by quantitative mass spectrometry-based metabolite profiling.

Results

Survival of E. coli strongly depended on whether the persister assay medium supported growth or not. The results were also highly dependent on the type of antibiotic and pregrown physiological state of the cells. Therefore, applying the same conditions is critical for consistent and comparable results. No direct connection was observed between antibiotic efficacy to the metabolic state. This also includes the energetic state (i.e., the intracellular concentration of ATP and the adenylate energy charge), which has earlier been hypothesized to be decisive for persister formation.

Discussion

The study provides guides and suggestions for the design of future experimentation in the research fields of persisters and antibiotic tolerance.

Collective polarization dynamics in bacterial colonies signify the occurrence of distinct subpopulations

Membrane potential in bacterial systems has been shown to be dynamic and tightly related to survivability at the single-cell level. However, little is known about spatiotemporal patterns of membrane potential in bacterial colonies and biofilms. Here, we discovered a transition from uncorrelated to collective dynamics within colonies formed by the human pathogen Neisseria gonorrhoeae. In freshly assembled colonies, polarization is heterogeneous with instances of transient and uncorrelated hyper- or depolarization of individual cells. As colonies reach a critical size, the polarization behavior transitions to collective dynamics: A hyperpolarized shell forms at the center, travels radially outward, and halts several micrometers from the colony periphery. Once the shell has passed, we detect an influx of potassium correlated with depolarization. Transient hyperpolarization also demarks the transition from volume to surface growth. By combining simulations and the use of an alternative electron acceptor for the respiratory chain, we provide strong evidence that local oxygen gradients shape the collective polarization dynamics. Finally, we show that within the hyperpolarized shell, tolerance against aminoglycoside antibiotics increases. These findings highlight that the polarization pattern can signify the differentiation into distinct subpopulations with different growth rates and antibiotic tolerance.

Community interactions drive the evolution of antibiotic tolerance in bacteria

The emergence of antibiotic tolerance (prolonged survival against exposure) in natural bacterial populations is a major concern. Since it has been studied primarily in isogenic populations, we do not yet understand how ecological interactions in a diverse community impact the evolution of tolerance. To address this, we studied the evolutionary dynamics of a synthetic bacterial community composed of two interacting strains. In this community, an antibiotic-resistant strain protected the other, susceptible strain by degrading the antibiotic ampicillin in the medium. Surprisingly, we found that in the presence of antibiotics, the susceptible strain evolved tolerance. Tolerance was typified by an increase in survival as well as an accompanying decrease in the growth rate, highlighting a trade-off between the two. A simple mathematical model explained that the observed decrease in the death rate, even when coupled with a decreased growth rate, is beneficial in a community with weak protective interactions. In the presence of strong interactions, the model predicted that the trade-off would instead be detrimental, and tolerance would not emerge, which we experimentally verified. By whole genome sequencing the evolved tolerant isolates, we identified two genetic hot spots which accumulated mutations in parallel lines, suggesting their association with tolerance. Our work highlights that ecological interactions can promote antibiotic tolerance in bacterial communities, which has remained understudied.

Genome-Wide Transposon Mutagenesis Screens Identify Group A Streptococcus Genes Affecting Susceptibility to β-Lactam Antibiotics

Group A streptococcus (GAS) is a Gram-positive human bacterial pathogen responsible for more than 700 million infections annually worldwide. Beta-lactam antibiotics are the primary agents used to treat GAS infections. Naturally occurring GAS clinical isolates with decreased susceptibility to beta-lactam antibiotics attributed to mutations in PBP2X have recently been documented. This prompted us to perform a genome-wide screen to identify GAS genes that alter beta-lactam susceptibility in vitro. Using saturated transposon mutagenesis, we screened for GAS gene mutations conferring altered in vitro susceptibility to penicillin G and/or ceftriaxone, two beta-lactam antibiotics commonly used to treat GAS infections. In the aggregate, we found that inactivating mutations in 150 GAS genes are associated with altered susceptibility to penicillin G and/or ceftriaxone. Many of the genes identified were previously not known to alter beta-lactam susceptibility or affect cell wall biosynthesis. Using isogenic mutant strains, we confirmed that inactivation of clpX (Clp protease ATP-binding subunit) or cppA (CppA proteinase) resulted in decreased in vitro susceptibility to penicillin G and ceftriaxone. Deletion of murA1 (UDP-N-acetylglucosamine 1-carboxyvinyltransferase) conferred increased susceptibility to ceftriaxone. Our results provide new information about the GAS genes affecting susceptibility to beta-lactam antibiotics. IMPORTANCE Beta-lactam antibiotics are the primary drugs prescribed to treat infections caused by group A streptococcus (GAS), an important human pathogen. However, the molecular mechanisms of GAS interactions with beta-lactam antibiotics are not fully understood. In this study, we performed a genome-wide mutagenesis screen to identify GAS mutations conferring altered susceptibility to beta-lactam antibiotics. In the aggregate, we discovered that mutations in 150 GAS genes were associated with altered beta-lactam susceptibility. Many identified genes were previously not known to alter beta-lactam susceptibility or affect cell wall biosynthesis. Our results provide new information about the molecular mechanisms of GAS interaction with beta-lactam antibiotics.

Growth productivity as a determinant of the inoculum effect for bactericidal antibiotics

Understanding the mechanisms by which populations of bacteria resist antibiotics has implications in evolution, microbial ecology, and public health. The inoculum effect (IE), where antibiotic efficacy declines as the density of a bacterial population increases, has been observed for multiple bacterial species and antibiotics. Several mechanisms to account for IE have been proposed, but most lack experimental evidence or cannot explain IE for multiple antibiotics. We show that growth productivity, the combined effect of growth and metabolism, can account for IE for multiple bactericidal antibiotics and bacterial species. Guided by flux balance analysis and whole-genome modeling, we show that the carbon source supplied in the growth medium determines growth productivity. If growth productivity is sufficiently high, IE is eliminated. Our results may lead to approaches to reduce IE in the clinic, help standardize the analysis of antibiotics, and further our understanding of how bacteria evolve resistance.

Investigating the origins of bacterial SERS responses to antibiotics observed in the extracellular matrix liquid

Surface-enhanced Raman spectroscopy (SERS) has been applied to analyze bacterial cells and their responses to antibiotic exposure. However, significant knowledge gaps remain regarding the origins of specific antibiotic response patterns and the necessary experimental steps required to see them clearly in the SERS spectra, particularly involving SERS responses observed in the extracellular matrix liquid of bacterial samples. In this study, a variety of experimental parameters were tested to assess the antibiotic response patterns seen in liquid samples from E. coli under different conditions. These include testing the impact of washing the cells with water after incubating them with antibiotics, as well as the effect of using different types of liquids with varying characteristics for incubating the bacteria with the antibiotics. It was found that the experimental procedure has a significant impact on the resulting SERS signals, and the target patterns could only be observed in specific conditions. In particular, the step of washing the bacteria with water is necessary for observing the antibiotic response patterns, and incubating the bacteria and antibiotics in a nutrient-rich growth medium is preferable to incubating the cells in a buffer or in distilled water. These findings can be used to improve existing methods for testing antibiotic responses with SERS, and could potentially help to further develop and optimize SERS-based procedures for assessing antibiotic sensitivity.

Variability of Mycobacterium avium Complex Isolates Drug Susceptibility Testing by Broth Microdilution

Non-tuberculous mycobacteria are widely distributed in environments and are capable of infecting humans, particularly those with a compromised immune system. The most prevalent species that cause nontuberculous mycobacterial lung diseases are slow-growing bacteria from the Mycobacterium avium complex (MAC), mainly M. avium or M. intracellulare. The key treatment of MAC infections includes macrolides, ethambutol, and rifampicin; however, the therapy outcomes are unsatisfactory. Phenotypic drug susceptibility testing is a conditional recommendation prior to treatment, and critical concentrations for clarithromycin, amikacin, moxifloxacin, and linezolid have been established. In this review, data from studies on the determination of MIC of clinical isolates using the broth microdilution method were summarized. A significant variation in the MIC distributions from different studies was found. The main reasons could impact the findings: insufficient reproducibility of the phenotypic testing and variation in species lineages identified in different laboratories, which could have various intrinsic susceptibility to drugs. For most of the drugs analyzed, the MICs are too high, which could undermine the treatment efficiency. Further improvement of treatment outcomes demands the validation of microbiological resistance criteria together with the identification of molecular mechanisms of resistance.

Examining the impact of zinc on horizontal gene transfer in Enterobacterales

Antimicrobial resistance is one of the main international health concerns for humans, animals, and the environment, and substantial efforts have focused on reducing its development and spread. While there is evidence for correlations between antimicrobial usage and antimicrobial resistance development, specific information on the effect of heavy metal/antimicrobial usage on bacterial conjugation is more limited. The aim of this study was to investigate the effects of zinc and antimicrobials in different concentrations on horizontal gene transfer of an ampicillin resistance gene, using a multi-drug resistant Escherichia coli donor strain and three different Salmonella enterica serovars as recipient strains. Differences in conjugation frequencies for the different Salmonella recipients were observed, independent of the presence of zinc or the antimicrobials. Selective pressure on the recipient strains, in the form of ampicillin, resulted in a decrease in conjugation frequencies, while, the presence of rifampicin resulted in increases. Zinc exposure affected conjugation frequencies of only one of the three recipient strains, thus the effect of zinc on conjugation frequencies seemed to be concentration and strain dependent. Furthermore, differences in growth rates due to plasmid carriage were observed for one of the Salmonella strains.

Ring-fused 2-pyridones effective against multidrug-resistant Gram-positive pathogens and synergistic with standard-of-care antibiotics

The alarming rise of multidrug-resistant Gram-positive bacteria has precipitated a healthcare crisis, necessitating the development of new antimicrobial therapies. Here we describe a new class of antibiotics based on a ring-fused 2-pyridone backbone, which are active against vancomycin-resistant enterococci (VRE), a serious threat as classified by the Centers for Disease Control and Prevention, and other multidrug-resistant Gram-positive bacteria. Ring-fused 2-pyridone antibiotics have bacteriostatic activity against actively dividing exponential phase enterococcal cells and bactericidal activity against nondividing stationary phase enterococcal cells. The molecular mechanism of drug-induced killing of stationary phase cells mimics aspects of fratricide observed in enterococcal biofilms, where both are mediated by the Atn autolysin and the GelE protease. In addition, combinations of sublethal concentrations of ring-fused 2-pyridones and standard-of-care antibiotics, such as vancomycin, were found to synergize to kill clinical strains of VRE. Furthermore, a broad range of antibiotic resistant Gram-positive pathogens, including those responsible for the increasing incidence of antibiotic resistant healthcare-associated infections, are susceptible to this new class of 2-pyridone antibiotics. Given the broad antibacterial activities of ring-fused 2-pyridone compounds against Gram-positive (GmP) bacteria we term these compounds GmPcides, which hold promise in combating the rising tide of antibiotic resistant Gram-positive pathogens.

A computational model for microbial colonization of an antifouling surface

Biofouling of marine surfaces such as ship hulls is a major industrial problem. Antifouling (AF) paints delay the onset of biofouling by releasing biocidal chemicals. We present a computational model for microbial colonization of a biocide-releasing AF surface. Our model accounts for random arrival from the ocean of microorganisms with different biocide resistance levels, biocide-dependent proliferation or killing, and a transition to a biofilm state. Our computer simulations support a picture in which biocide-resistant microorganisms initially form a loosely attached layer that eventually transitions to a growing biofilm. Once the growing biofilm is established, immigrating microorganisms are shielded from the biocide, allowing more biocide-susceptible strains to proliferate. In our model, colonization of the AF surface is highly stochastic. The waiting time before the biofilm establishes is exponentially distributed, suggesting a Poisson process. The waiting time depends exponentially on both the concentration of biocide at the surface and the rate of arrival of resistant microorganisms from the ocean. Taken together our results suggest that biofouling of AF surfaces may be intrinsically stochastic and hence unpredictable, but immigration of more biocide-resistant species, as well as the biological transition to biofilm physiology, may be important factors controlling the time to biofilm establishment.

A whole-genome assay identifies four principal gene functions that confer tolerance of meropenem stress upon Escherichia coli

We report here the identification of four gene functions of principal importance for the tolerance of meropenem stress in Escherichia coli: cell division, cell envelope synthesis and maintenance, ATP metabolism, and transcription regulation. The primary mechanism of β-lactam antibiotics such as meropenem is inhibition of penicillin binding proteins, thus interfering with peptidoglycan crosslinking, weakening the cell envelope, and promoting cell lysis. However, recent systems biology approaches have revealed numerous downstream effects that are triggered by cell envelope damage and involve diverse cell processes. Subpopulations of persister cells can also arise, which can survive elevated concentrations of meropenem despite the absence of a specific resistance factor. We used Transposon-Directed Insertion Sequencing with inducible gene expression to simultaneously assay the effects of upregulation, downregulation, and disruption of every gene in a model E. coli strain on survival of exposure to four concentrations of meropenem. Automated Gene Functional Classification and manual categorization highlighted the importance at all meropenem concentrations of genes involved in peptidoglycan remodeling during cell division, suggesting that cell division is the primary function affected by meropenem. Genes involved in cell envelope synthesis and maintenance, ATP metabolism, and transcriptional regulation were generally important at higher meropenem concentrations, suggesting that these three functions are therefore secondary or downstream targets. Our analysis revealed the importance of multiple two-component signal transduction mechanisms, suggesting an as-yet unexplored coordinated transcriptional response to meropenem stress. The inclusion of an inducible, transposon-encoded promoter allowed sensitive detection of genes involved in proton transport, ATP production and tRNA synthesis, for which modulation of expression affects survival in the presence of meropenem: a finding that would not be possible with other technologies. We were also able to suggest new targets for future antibiotic development or for synergistic effects between gene or protein inhibitors and existing antibiotics. Overall, in a single massively parallel assay we were able to recapitulate many of the findings from decades of research into β-lactam antibiotics, add to the list of genes known to be important for meropenem tolerance, and categorize the four principal gene functions involved.

Growth-mediated negative feedback shapes quantitative antibiotic response

Dose-response relationships are a general concept for quantitatively describing biological systems across multiple scales, from the molecular to the whole-cell level. A clinically relevant example is the bacterial growth response to antibiotics, which is routinely characterized by dose-response curves. The shape of the dose-response curve varies drastically between antibiotics and plays a key role in treatment, drug interactions, and resistance evolution. However, the mechanisms shaping the dose-response curve remain largely unclear. Here, we show in Escherichia coli that the distinctively shallow dose-response curve of the antibiotic trimethoprim is caused by a negative growth-mediated feedback loop: Trimethoprim slows growth, which in turn weakens the effect of this antibiotic. At the molecular level, this feedback is caused by the upregulation of the drug target dihydrofolate reductase (FolA/DHFR). We show that this upregulation is not a specific response to trimethoprim but follows a universal trend line that depends primarily on the growth rate, irrespective of its cause. Rewiring the feedback loop alters the dose-response curve in a predictable manner, which we corroborate using a mathematical model of cellular resource allocation and growth. Our results indicate that growth-mediated feedback loops may shape drug responses more generally and could be exploited to design evolutionary traps that enable selection against drug resistance.

Gigavalent Display of Proteins on Monodisperse Polyacrylamide Hydrogels as a Versatile Modular Platform for Functional Assays and Protein Engineering

The assembly of robust, modular biological components into complex functional systems is central to synthetic biology. Here, we apply modular "plug and play" design principles to a solid-phase protein display system that facilitates protein purification and functional assays. Specifically, we capture proteins on polyacrylamide hydrogel display beads (PHD beads) made in microfluidic droplet generators. These monodisperse PHD beads are decorated with predefined amounts of anchors, methacrylate-PEG-benzylguanine (BG) and methacrylate-PEG-chloroalkane (CA), that react covalently with SNAP-/Halo-tag fusion proteins, respectively, in a specific, orthogonal, and stable fashion. Anchors, and thus proteins, are distributed throughout the entire bead volume, allowing attachment of ∼10⁹ protein molecules per bead (⌀ 20 μm) -a higher density than achievable with commercial surface-modified beads. We showcase a diverse array of protein modules that enable the secondary capture of proteins, either noncovalently (IgG and SUMO-tag) or covalently (SpyCatcher, SpyTag, SnpCatcher, and SnpTag), in mono- and multivalent display formats. Solid-phase protein binding and enzymatic assays are carried out, and incorporating the photocleavable protein PhoCl enables the controlled release of modules via visible-light irradiation for functional assays in solution. We utilize photocleavage for valency engineering of an anti-TRAIL-R1 scFv, enhancing its apoptosis-inducing potency ∼50-fold through pentamerization.

Optimal dose of lactoferrin reduces the resilience of in vitro Staphylococcus aureus colonies

The rise in antibiotic resistance has stimulated research into adjuvants that can improve the efficacy of broad-spectrum antibiotics. Lactoferrin is a candidate adjuvant; it is a multifunctional iron-binding protein with antimicrobial properties. It is known to show dose-dependent antimicrobial activity against Staphylococcus aureus through iron sequestration and repression of β-lactamase expression. However, S. aureus can extract iron from lactoferrin through siderophores for their growth, which confounds the resolution of lactoferrin's method of action. We measured the minimum inhibitory concentration (MIC) for a range of lactoferrin/ β-lactam antibiotic dose combinations and observed that at low doses (< 0.39 μM), lactoferrin contributes to increased S. aureus growth, but at higher doses (> 6.25 μM), iron-depleted native lactoferrin reduced bacterial growth and reduced the MIC of the β-lactam-antibiotic cefazolin. This differential behaviour points to a bacterial population response to the lactoferrin/ β-lactam dose combination. Here, with the aid of a mathematical model, we show that lactoferrin stratifies the bacterial population, and the resulting population heterogeneity is at the basis of the dose dependent response seen. Further, lactoferrin disables a sub-population from β-lactam-induced production of β-lactamase, which when sufficiently large reduces the population's ability to recover after being treated by an antibiotic. Our analysis shows that an optimal dose of lactoferrin acts as a suitable adjuvant to eliminate S. aureus colonies using β-lactams, but sub-inhibitory doses of lactoferrin reduces the efficacy of β-lactams.

In silico genome-scale metabolic modeling and in vitro static time-kill studies of exogenous metabolites alone and with polymyxin B against Klebsiella pneumoniae

Multidrug-resistant (MDR) Klebsiella pneumoniae is a top-prioritized Gram-negative pathogen with a high incidence in hospital-acquired infections. Polymyxins have resurged as a last-line therapy to combat Gram-negative “superbugs”, including MDR K. pneumoniae. However, the emergence of polymyxin resistance has increasingly been reported over the past decades when used as monotherapy, and thus combination therapy with non-antibiotics (e.g., metabolites) becomes a promising approach owing to the lower risk of resistance development. Genome-scale metabolic models (GSMMs) were constructed to delineate the altered metabolism of New Delhi metallo-β-lactamase- or extended spectrum β-lactamase-producing K. pneumoniae strains upon addition of exogenous metabolites in media. The metabolites that caused significant metabolic perturbations were then selected to examine their adjuvant effects using in vitro static time–kill studies. Metabolic network simulation shows that feeding of 3-phosphoglycerate and ribose 5-phosphate would lead to enhanced central carbon metabolism, ATP demand, and energy consumption, which is converged with metabolic disruptions by polymyxin treatment. Further static time–kill studies demonstrated enhanced antimicrobial killing of 10 mM 3-phosphoglycerate (1.26 and 1.82 log₁₀ CFU/ml) and 10 mM ribose 5-phosphate (0.53 and 0.91 log₁₀ CFU/ml) combination with 2 mg/L polymyxin B against K. pneumoniae strains. Overall, exogenous metabolite feeding could possibly improve polymyxin B activity via metabolic modulation and hence offers an attractive approach to enhance polymyxin B efficacy. With the application of GSMM in bridging the metabolic analysis and time–kill assay, biological insights into metabolite feeding can be inferred from comparative analyses of both results. Taken together, a systematic framework has been developed to facilitate the clinical translation of antibiotic-resistant infection management.

Molecular Basis of the Slow Growth of Mycoplasma hominis on Different Energy Sources

Mycoplasma hominis is an opportunistic urogenital pathogen in vertebrates. It is a non-glycolytic species that produces energy via arginine degradation. Among genital mycoplasmas, M. hominis is the most commonly reported to play a role in systemic infections and can persist in the host for a long time. However, it is unclear how M. hominis proceeds under arginine limitation. The recent metabolic reconstruction of M. hominis has demonstrated its ability to catabolize deoxyribose phosphate to produce ATP. In this study, we cultivated M. hominis on two different energy sources (arginine and thymidine) and demonstrated the differences in growth rate, antibiotic sensitivity, and biofilm formation. Using label-free quantitative proteomics, we compared the proteome of M. hominis under these conditions. A total of 466 proteins were identified from M. hominis, representing approximately 85% of the predicted proteome, while the levels of 94 proteins changed significantly. As expected, we observed changes in the levels of metabolic enzymes. The energy source strongly affects the synthesis of enzymes related to RNA modifications and ribosome assembly. The translocation of lipoproteins and other membrane-associated proteins was also impaired. Our study, the first global characterization of the proteomic switching of M. hominis in arginine-deficiency media, illustrates energy source-dependent control of pathogenicity factors and can help to determine the mechanisms underlying the interaction between the growth rate and fitness of genome-reduced bacteria.

Peptidoglycan Recycling Promotes Outer Membrane Integrity and Carbapenem Tolerance in Acinetobacter baumannii

β-Lactam antibiotics exploit the essentiality of the bacterial cell envelope by perturbing the peptidoglycan layer, typically resulting in rapid lysis and death. Many Gram-negative bacteria do not lyse but instead exhibit "tolerance," the ability to sustain viability in the presence of bactericidal antibiotics for extended periods. Antibiotic tolerance has been implicated in treatment failure and is a stepping-stone in the acquisition of true resistance, and the molecular factors that promote intrinsic tolerance are not well understood. Acinetobacter baumannii is a critical-threat nosocomial pathogen notorious for its ability to rapidly develop multidrug resistance. Carbapenem β-lactam antibiotics (i.e., meropenem) are first-line prescriptions to treat A. baumannii infections, but treatment failure is increasingly prevalent. Meropenem tolerance in Gram-negative pathogens is characterized by morphologically distinct populations of spheroplasts, but the impact of spheroplast formation is not fully understood. Here, we show that susceptible A. baumannii clinical isolates demonstrate tolerance to high-level meropenem treatment, form spheroplasts upon exposure to the antibiotic, and revert to normal growth after antibiotic removal. Using transcriptomics and genetic screens, we show that several genes associated with outer membrane integrity maintenance and efflux promote tolerance, likely by limiting entry into the periplasm. Genes associated with peptidoglycan homeostasis in the periplasm and cytoplasm also answered our screen, and their disruption compromised cell envelope barrier function. Finally, we defined the enzymatic activity of the tolerance determinants penicillin-binding protein 7 (PBP7) and ElsL (a cytoplasmic ld-carboxypeptidase). These data show that outer membrane integrity and peptidoglycan recycling are tightly linked in their contribution to A. baumannii meropenem tolerance. IMPORTANCE Carbapenem treatment failure associated with "superbug" infections has rapidly increased in prevalence, highlighting the urgent need to develop new therapeutic strategies. Antibiotic tolerance can directly lead to treatment failure but has also been shown to promote the acquisition of true resistance within a population. While some studies have addressed mechanisms that promote tolerance, factors that underlie Gram-negative bacterial survival during carbapenem treatment are not well understood. Here, we characterized the role of peptidoglycan recycling in outer membrane integrity maintenance and meropenem tolerance in A. baumannii. These studies suggest that the pathogen limits antibiotic concentrations in the periplasm and highlight physiological processes that could be targeted to improve antimicrobial treatment.

Enhancing bioreactor arrays for automated measurements and reactive control with ReacSight

Small-scale, low-cost bioreactors provide exquisite control of environmental parameters of microbial cultures over long durations. Their use is gaining popularity in quantitative systems and synthetic biology. However, existing setups are limited in their measurement capabilities. Here, we present ReacSight, a strategy to enhance bioreactor arrays for automated measurements and reactive experiment control. ReacSight leverages low-cost pipetting robots for sample collection, handling and loading, and provides a flexible instrument control architecture. We showcase ReacSight capabilities on three applications in yeast. First, we demonstrate real-time optogenetic control of gene expression. Second, we explore the impact of nutrient scarcity on fitness and cellular stress using competition assays. Third, we perform dynamic control of the composition of a two-strain consortium. We combine custom or chi.bio reactors with automated cytometry. To further illustrate ReacSight's genericity, we use it to enhance plate-readers with pipetting capabilities and perform repeated antibiotic treatments on a bacterial clinical isolate.

Streptozotocin-Induced Hyperglycemia Is Associated with Unique Microbiome Metabolomic Signatures in Response to Ciprofloxacin Treatment

It is well recognized that the microbiome plays key roles in human health, and that damage to this system by, for example, antibiotic administration has detrimental effects. With this, there is collective recognition that off-target antibiotic susceptibility within the microbiome is a particularly troublesome side effect that has serious impacts on host well-being. Thus, a pressing area of research is the characterization of antibiotic susceptibility determinants within the microbiome, as understanding these mechanisms may inform the development of microbiome-protective therapeutic strategies. In particular, metabolic environment is known to play a key role in the different responses of this microbial community to antibiotics. Here, we explore the role of host dysglycemia on ciprofloxacin susceptibility in the murine cecum. We used a combination of 16S rRNA sequencing and untargeted metabolomics to characterize changes in both microbiome taxonomy and environment. We found that dysglycemia minimally impacted ciprofloxacin-associated changes in microbiome structure. However, from a metabolic perspective, host hyperglycemia was associated with significant changes in respiration, central carbon metabolism, and nucleotide synthesis-related metabolites. Together, these data suggest that host glycemia may influence microbiome function during antibiotic challenge.

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.

Population genetics, biofilm recalcitrance, and antibiotic resistance evolution

Biofilms are communities of bacteria forming high-density sessile colonies. Such a lifestyle comes associated with costs and benefits: while the growth rate of biofilms is often lower than that of their free-living counterparts, this cost is readily repaid once the colony is subjected to antibiotics. Biofilms can grow in antibiotic concentrations a thousand times higher than planktonic bacteria. While numerous mechanisms have been proposed to explain biofilm recalcitrance towards antibiotics, little is yet known about their effect on the evolution of resistance. We synthesize the current understanding of biofilm recalcitrance from a pharmacodynamic and a population genetics perspective. Using the pharmacodynamic framework, we discuss the effects of various mechanisms and show that biofilms can either promote or impede resistance evolution.