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

Lineage-dependent variations in single-cell antibiotic susceptibility reveal the selective inheritance of phenotypic resistance in bacteria

Genetically identical bacterial cells often exhibit heterogeneous responses to antibiotics - some survive, others die. Here, we show that this heterogeneity propagates across generations to give rise to phenotypic resistance. Using real-time single-cell tracking, we exposed Escherichia coli to the β-lactam cefsulodin at its clinical breakpoint concentration and analyzed cell fate within genealogical trees statistically. Cell survival was strongly correlated among family members, driving the selective enrichment of robust lineages within an otherwise susceptible population. Our genealogical population model identified heritable phenotypic resistance as a key factor underlying this enrichment, which was validated experimentally. Comparing enrichment dynamics between the wild-type and a tolC knock-out strain, deficient in multidrug efflux, uncovered nuanced changes that increased the intergenerational memory of phenotypic resistance. Our findings provide evidence for heritable phenotypic resistance and demonstrate how its propagation through cell-to-cell heterogeneity enables the survival of minority cells within isogenic populations.

Paradox of the Sub-Plankton: Plausible Mechanisms and Open Problems Underlying Strain-Level Diversity in Microbial Communities

Microbial communities are often complex and highly diverse, typically with dozens of species sharing spatially-restricted environments. Within these species, genetic and ecological variation often exists at a much finer scale, with closely related strains coexisting and competing. While the coexistence of strains in communities has been heavily explored over the past two decades, we have no self-consistent theory of how this diversity is maintained. This question challenges our conventional understanding of ecological coexistence, typically framed around species with clear phenotypic and ecological differences. In this review, we synthesise plausible mechanisms underlying strain-level diversity (termed microdiversity), focusing on niche-based mechanisms such as nutrient competition, neutral mechanisms such as migration, and evolutionary mechanisms such as horizontal gene transfer. We critically assess the strengths and caveats of these mechanisms, acknowledging key gaps that persist in linking genetic similarity to ecological divergence. Finally, we highlight how the origin and maintenance of microdiversity could pose a major challenge to conventional ecological thinking. We articulate a call-to-arms for a dialogue between well-designed experiments and new theoretical frameworks to address this grand conceptual challenge in understanding microbial biodiversity.

Persistent glucose consumption under antibiotic treatment protects bacterial community

Antibiotics typically induce major physiological changes in bacteria. However, their effect on nutrient consumption remains unclear. Here we found that Escherichia coli communities can sustain normal levels of glucose consumption under a broad range of antibiotics. The community-living resulted in a low membrane potential in the bacteria, allowing slow antibiotic accumulation on treatment and better adaptation. Through multi-omics analysis, we identified a prevalent adaptive response characterized by the upregulation of lipid synthesis, which substantially contributes to sustained glucose consumption. The consumption was maintained by the periphery region of the community, thereby restricting glucose penetration into the community interior. The resulting spatial heterogeneity in glucose availability protected the interior from antibiotic accumulation in a membrane potential-dependent manner, ensuring rapid recovery of the community postantibiotic treatment. Our findings unveiled a community-level antibiotic response through spatial regulation of metabolism and suggested new strategies for antibiotic therapies.

Chloramphenicol and gentamicin reduce the evolution of resistance to phage ΦX174 by suppressing a subset of E. coli LPS mutants

Bacteriophages infect gram-negative bacteria by attaching to molecules present on the bacterial surface, often lipopolysaccharides (LPS). Modification of LPS can lead to resistance to phage infection. In addition, LPS modifications can impact antibiotic susceptibility, allowing for phage-antibiotic synergism. The evolutionary mechanism(s) behind such synergistic interactions remain largely unclear. Here, we show that the presence of antibiotics can affect the evolution of resistance to phage infection, using phage ΦX174 and Escherichia coli C. We use a collection of 34 E. coli C LPS strains, each of which is resistant to ΦX174, and has either a "rough" or "deep rough" LPS phenotype. Growth of the bacterial strains with the deep rough phenotype is inhibited at low concentrations of chloramphenicol and, to a much lesser degree, gentamicin. Treating E. coli C wild type with ΦX174 and chloramphenicol eliminates the emergence of mutants with the deep rough phenotype, and thereby slows the evolution of resistance to phage infection. At slightly lower chloramphenicol concentrations, phage resistance rates are similar to those observed at high concentrations; yet, we show that the diversity of possible mutants is much larger than at higher chloramphenicol concentrations. These data suggest that specific antibiotic concentrations can lead to synergistic phage-antibiotic interactions that disappear at higher antibiotic concentrations. Overall, we show that the change in survival of various ΦX174-resistant E. coli C mutants in the presence of antibiotics can explain the observed phage-antibiotic synergism.

Contribution of the infection ecosystem and biogeography to antibiotic failure in vivo

The acquisition of antibiotic resistance in bacteria, though a deeply concerning international issue, is reasonably well-understood at a mechanistic level. Less well-understood is why bacteria that are sensitive in vitro to well-established and widely-used antibiotics sometimes fail to respond to these agents in vivo. This is a particularly common problem in chronic, polymicrobial infection scenarios. Here, we discuss this in vitro-in vivo disconnect from the perspective of the bacterium, focusing in particular on how infection micro/macro-environment, biogeography, and the presence of co-habiting species affect the response to antibiotics. Using selected exemplars, we also consider interventions that might improve treatment outcomes, as well as ecologically 'eubiotic' approaches that have less of an impact on the patient's commensal microflora. In our view, the accrued data strongly suggest that we need a more comprehensive understanding of the in situ microbiology at infection sites.

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.

Effects of water environmental factors and antibiotics on bacterial community in urban landscape lakes

The presence of antibiotics can affect the natural microbial community and exert selective pressure on the environment's microorganisms. This study focused on three types of urban landscape lakes in Xi'an that were closely related to human activities. By combining basic water quality indicators, antibiotic occurrence status, bacterial communities and their potential metabolic functions, Spearman correlation coefficient and redundancy analysis were used to explore the relationship between them, and further explore the impact mechanism of environmental factors and antibiotics on bacterial community structure. The results showed that ofloxacin, erythromycin, and roxithromycin were the main types of antibiotics in the three landscape lakes, with low ecological risks, and there was a clear clustering of antibiotic occurrence. Proteobacteria was the most abundant bacterial phylum, and each lake had its own unique dominant bacteria, which indicates that they are influenced by varying water sources, pollution, and other nearby environments. Statistical analysis showed that pH and nitrogen nutrients were the most critical environmental factors affecting bacterial communities (P<0.01), while tetracyclines and lincomycins were the antibiotics that had a significant impact on bacterial communities (P<0.05). Antibiotics mainly promote defense- and signal transduction-related functions, and inhibit the metabolic activity of bacterial communities. However, the impact of antibiotics on bacterial diversity, community structure, and potential metabolic function in the three urban lakes was less than that of environmental factors. These results help to clarify the mechanism and degree of impact of different interference factors (environmental factors, conventional pollutants, and antibiotics) on bacterial communities in the water environment and are important for the management of urban landscape lake water environments.

Multi-scale models of whole cells: progress and challenges

Whole-cell modeling is "the ultimate goal" of computational systems biology and "a grand challenge for 21st century" (Tomita, Trends in Biotechnology, 2001, 19(6), 205-10). These complex, highly detailed models account for the activity of every molecule in a cell and serve as comprehensive knowledgebases for the modeled system. Their scope and utility far surpass those of other systems models. In fact, whole-cell models (WCMs) are an amalgam of several types of "system" models. The models are simulated using a hybrid modeling method where the appropriate mathematical methods for each biological process are used to simulate their behavior. Given the complexity of the models, the process of developing and curating these models is labor-intensive and to date only a handful of these models have been developed. While whole-cell models provide valuable and novel biological insights, and to date have identified some novel biological phenomena, their most important contribution has been to highlight the discrepancy between available data and observations that are used for the parametrization and validation of complex biological models. Another realization has been that current whole-cell modeling simulators are slow and to run models that mimic more complex (e.g., multi-cellular) biosystems, those need to be executed in an accelerated fashion on high-performance computing platforms. In this manuscript, we review the progress of whole-cell modeling to date and discuss some of the ways that they can be improved.

Quantifying stochastic establishment of mutants in microbial adaptation

Studies of microbial evolution, especially in applied contexts, have focused on the role of selection in shaping predictable, adaptive responses to the environment. However, chance events - the appearance of novel genetic variants and their establishment, i.e. outgrowth from a single cell to a sizeable population - also play critical initiating roles in adaptation. Stochasticity in establishment has received little attention in microbiology, potentially due to lack of awareness as well as practical challenges in quantification. However, methods for high-replicate culturing, mutant labelling and detection, and statistical inference now make it feasible to experimentally quantify the establishment probability of specific adaptive genotypes. I review methods that have emerged over the past decade, including experimental design and mathematical formulas to estimate establishment probability from data. Quantifying establishment in further biological settings and comparing empirical estimates to theoretical predictions represent exciting future directions. More broadly, recognition that adaptive genotypes may be stochastically lost while rare is significant both for interpreting common lab assays and for designing interventions to promote or inhibit microbial evolution.

Evolutionary rescue in a fluctuating environment: periodic versus quasi-periodic environmental changes

No environment is constant over time, and environmental fluctuations impact the outcome of evolutionary dynamics. Survival of a population not adapted to some environmental conditions is threatened unless, for example, a mutation rescues it, an eco-evolutionary process termed evolutionary rescue. We here investigate evolutionary rescue in an environment that fluctuates between a favourable state, in which the population grows, and a harsh state, in which the population declines. We develop a stochastic model that includes both population dynamics and genetics. We derive analytical predictions for the mean extinction time of a non-adapted population given that it is not rescued, the probability of rescue by a mutation, and the mean appearance time of a rescue mutant, which we validate using numerical simulations. We find that stochastic environmental fluctuations, resulting in quasi-periodic environmental changes, accelerate extinction and hinder evolutionary rescue compared with deterministic environmental fluctuations, resulting in periodic environmental changes. We demonstrate that high equilibrium population sizes and per capita growth rates maximize the chances of evolutionary rescue. We show that an imperfectly harsh environment, which does not fully prevent births but makes the death rate to birth rate ratio much greater than unity, has almost the same rescue probability as a perfectly harsh environment, which fully prevents births. Finally, we put our results in the context of antimicrobial resistance and conservation biology.

Bacterial envelope stress responses: Essential adaptors and attractive targets

Millions of deaths a year across the globe are linked to antimicrobial resistant infections. The need to develop new treatments and repurpose of existing antibiotics grows more pressing as the growing antimicrobial resistance pandemic advances. In this review article, we propose that envelope stress responses, the signaling pathways bacteria use to recognize and adapt to damage to the most vulnerable outer compartments of the microbial cell, are attractive targets. Envelope stress responses (ESRs) support colonization and infection by responding to a plethora of toxic envelope stresses encountered throughout the body; they have been co-opted into virulence networks where they work like global positioning systems to coordinate adhesion, invasion, microbial warfare, and biofilm formation. We highlight progress in the development of therapeutic strategies that target ESR signaling proteins and adaptive networks and posit that further characterization of the molecular mechanisms governing these essential niche adaptation machineries will be important for sparking new therapeutic approaches aimed at short-circuiting bacterial adaptation.

Methylene Blue/Carbon Dots Composite with Photothermal and Photodynamic Properties: Synthesis, Characterization, and Antibacterial Application

Photodynamic therapy and photothermal therapy provide new ways to combat antibiotic resistance. In this research, methylene blue (MB) as an effective photosensitizer was conjugated with carbon quantum dots (CQDs), the composite product not only possessed good antibacterial properties against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) due to excellent singlet oxygen (1 O2 ) production rate and light heat transfer performance, but also showed good biocompatibility. Combined with 808 nm and 660 nm laser irradiation, the minimum bactericidal concentration of CQDs-MB towards S. aureus and E. coli was 5 μm. Therefore, this study provides a potential candidate material based on CQDs for clinical applications.

Highly Enhanced Photocatalytic Performances of Composites Consisting of Silver Phosphate and N-Doped Carbon Nanomesh for Oxytetracycline Degradation

Photocatalytic technology based on silver phosphate (Ag₃PO₄) has excellent potential in removing antibiotic pollutants, but the low separation rate of photogenerated hole-electron pairs restricts the application of the photocatalyst. In this study, it was found that the combination of nitrogen-doped carbon (NDC) with carbon defects and Ag₃PO₄ can significantly enhance the photocatalytic ability of Ag₃PO₄. After it was exposed to visible light for 5 min, the photocatalytic degradation efficiency of oxytetracycline (OTC) by the composite photocatalyst Ag₃PO₄@NDC could reach 100%. In addition, the structure of NDC, Ag₃PO_4, and Ag₃PO₄@NDC was systematically characterized by SEM, TEM, XRD, Raman, and EPR. The XPS results revealed intense interface interaction between Ag₃PO₄ and NDC, and electrons would transfer from Ag₃PO₄ to the NDC surface. A possible mechanism for enhancing the photocatalytic reaction of the Ag₃PO₄@NDC composite catalyst was proposed. This study provides a highly efficient visible light catalytic material, which can be a valuable reference for designing and developing a new highly efficient visible light catalyst.