The emergence of metabolic heterogeneity and diverse growth responses in isogenic bacterial cells

Bioenergetic suppression by redox-active metabolites promotes antibiotic tolerance in Pseudomonas aeruginosa

The proton-motive force (PMF), consisting of a pH gradient and a membrane potential (ΔΨ) underpins many processes essential to bacterial growth and/or survival. Yet bacteria often enter a bioenergetically diminished state characterized by a low PMF. Consequently, they have increased tolerance for diverse stressors, including clinical antibiotics. Despite the ubiquity of low metabolic rates in the environment, the extent to which bacteria have agency over entry into such a low-bioenergetic state has received relatively little attention. Here, we tested the hypothesis that production of redox-active metabolites (RAMs) could drive such a physiological transition. Pseudomonas aeruginosa is an opportunistic pathogen that produces phenazines, model RAMs that are highly toxic in the presence of molecular oxygen (O2). Under oxic conditions, the phenazines pyocyanin and phenazine-1-carboximide, as well as toxoflavin-a RAM produced by Burkholderia species-suppress the ΔΨ in distinct ways across distributions of single cells, reduce the efficiency of proton pumping, and lower cellular adenosine-triphosphate (ATP) levels. In planktonic culture, the degree and rate by which each RAM lowers the ΔΨ correlates with the protection it confers against antibiotics that strongly impact cellular energy flux. This bioenergetic suppression requires the RAM's presence and corresponds to its cellular reduction rate and abiotic oxidation rate by O2; it can be reversed by increasing the ΔΨ with nigericin. RAMs similarly impact the bioenergetic state of cells in (hyp)oxic biofilm aggregates. Collectively, these findings demonstrate that bacteria can suppress their bioenergetic state by the production of endogenous toxins in a manner that bolsters stress resilience.

Plasmid-encoded phosphatase RapP enhances cell growth in non-domesticated Bacillus subtilis strains

The trade-off between rapid growth and other important physiological traits (e.g., survival and adaptability) poses a fundamental challenge for microbes to achieve fitness maximization. Studies on Bacillus subtilis biology often use strains derived after a process of lab 'domestication' from an ancestral strain known as Marburg strain. The domestication process led to loss of a large plasmid (pBS32) encoding a phosphatase (RapP) that dephosphorylates the Spo0F protein and thus regulates biofilm formation and sporulation. Here, we show that plasmid pBS32, and more specifically rapP, enhance growth rates by preventing premature expression of the Spo0F-Spo0A-mediated adaptive response during exponential phase. This results in reallocation of proteome resources towards biosynthetic, growth-promoting pathways without compromising long-term fitness during stationary phase. Thus, RapP helps B. subtilis to constrain physiological trade-offs and economize cellular resources for fitness improvement.

Shaping of microbial phenotypes by trade-offs

Growth rate maximization is an important fitness strategy for microbes. However, the wide distribution of slow-growing oligotrophic microbes in ecosystems suggests that rapid growth is often not favored across ecological environments. In many circumstances, there exist trade-offs between growth and other important traits (e.g., adaptability and survival) due to physiological and proteome constraints. Investments on alternative traits could compromise growth rate and microbes need to adopt bet-hedging strategies to improve fitness in fluctuating environments. Here we review the mechanistic role of trade-offs in controlling bacterial growth and further highlight its ecological implications in driving the emergences of many important ecological phenomena such as co-existence, population heterogeneity and oligotrophic/copiotrophic lifestyles.

Formation and emergent dynamics of spatially organized microbial systems

Spatial organization is the norm rather than the exception in the microbial world. While the study of microbial physiology has been dominated by studies in well-mixed cultures, there is now increasing interest in understanding the role of spatial organization in microbial physiology, coexistence and evolution. Where studied, spatial organization has been shown to influence all three of these aspects. In this mini review and perspective article, we emphasize that the dynamics within spatially organized microbial systems (SOMS) are governed by feedbacks between local physico-chemical conditions, cell physiology and movement, and evolution. These feedbacks can give rise to emergent dynamics, which need to be studied through a combination of spatio-temporal measurements and mathematical models. We highlight the initial formation of SOMS and their emergent dynamics as two open areas of investigation for future studies. These studies will benefit from the development of model systems that can mimic natural ones in terms of species composition and spatial structure.

Intercellular communication and social behaviors in mycobacteria

Cell-to-cell communication is a fundamental process of bacteria to exert communal behaviors. Sputum samples of patients with cystic fibrosis have often been observed with extensive mycobacterial genetic diversity. The emergence of heterogenic mycobacterial populations is observed due to subtle changes in their morphology, gene expression level, and distributive conjugal transfer (DCT). Since each subgroup of mycobacteria has different hetero-resistance, they are refractory against several antibiotics. Such genetically diverse mycobacteria have to communicate with each other to subvert the host immune system. However, it is still a mystery how such heterogeneous strains exhibit synchronous behaviors for the production of quorum sensing (QS) traits, such as biofilms, siderophores, and virulence proteins. Mycobacteria are characterized by division of labor, where distinct sub-clonal populations contribute to the production of QS traits while exchanging complimentary products at the community level. Thus, active mycobacterial cells ensure the persistence of other heterogenic clonal populations through cooperative behaviors. Additionally, mycobacteria are likely to establish communication with neighboring cells in a contact-independent manner through QS signals. Hence, this review is intended to discuss our current knowledge of mycobacterial communication. Understanding mycobacterial communication could provide a promising opportunity to develop drugs to target key pathways of mycobacteria.

Nutrient and salt depletion synergistically boosts glucose metabolism in individual Escherichia coli cells

The interaction between a cell and its environment shapes fundamental intracellular processes such as cellular metabolism. In most cases growth rate is treated as a proximal metric for understanding the cellular metabolic status. However, changes in growth rate might not reflect metabolic variations in individuals responding to environmental fluctuations. Here we use single-cell microfluidics-microscopy combined with transcriptomics, proteomics and mathematical modelling to quantify the accumulation of glucose within Escherichia coli cells. In contrast to the current consensus, we reveal that environmental conditions which are comparatively unfavourable for growth, where both nutrients and salinity are depleted, increase glucose accumulation rates in individual bacteria and population subsets. We find that these changes in metabolic function are underpinned by variations at the translational and posttranslational level but not at the transcriptional level and are not dictated by changes in cell size. The metabolic response-characteristics identified greatly advance our fundamental understanding of the interactions between bacteria and their environment and have important ramifications when investigating cellular processes where salinity plays an important role.

Elucidating heterogeneous iron biomineralization patterns in a denitrifying As(iii)-oxidizing bacterium: implications for arsenic immobilization

Anaerobic nitrate-dependent iron(ii) oxidation is a process common to many bacterial species, which promotes the formation of Fe(iii) minerals that can influence the fate of soil and groundwater pollutants, such as arsenic. Herein, we investigated simultaneous nitrate-dependent Fe(ii) and As(iii) oxidation by Acidovorax sp. strain ST3 with the aim of studying the Fe biominerals formed, their As immobilization capabilities and the metabolic effect on cells. X-ray powder diffraction (XRD) and scanning transmission electron microscopy (STEM) nanodiffraction were applied for biomineral characterization in bulk and at the nanoscale, respectively. NanoSIMS (nanoscale secondary ion mass spectrometry) was used to map the intra and extracellular As and Fe distribution at the single-cell level and to trace metabolically active cells, by incorporation of a ¹³C-labeled substrate (acetate). Metabolic heterogeneity among bacterial cells was detected, with periplasmic Fe mineral encrustation deleterious to cell metabolism. Interestingly, Fe and As were not co-localized in all cells, indicating delocalized sites of As(iii) and Fe(ii) oxidation. The Fe(iii) minerals lepidocrocite and goethite were identified in XRD, although only lepidocrocite was identified via STEM nanodiffraction. Extracellular amorphous nanoparticles were formed earlier and retained more As(iii/v) than crystalline "flakes" of lepidocrocite, indicating that longer incubation periods promote the formation of more crystalline minerals with lower As retention capabilities. Thus, the addition of nitrate promotes Fe(ii) oxidation and formation of Fe(iii) biominerals by ST3 cells which retain As(iii/v), and although this process was metabolically detrimental to some cells, it warrants further examination as a viable mechanism for As removal in anoxic environments by biostimulation with nitrate.

Multisite Enzymes as a Mechanism for Bistability in Reaction Networks

Here, we focus on a common class of enzymes that have multiple substrate binding sites (multisite enzymes) and analyze their capacity to generate bistable dynamics in the reaction networks that they are embedded in. These networks include both substrate-product-substrate cycles and substrate-to-product conversion with subsequent product consumption. Using mathematical techniques, we show that the inherent binding and catalysis reactions arising from multiple substrate-enzyme complexes create a potential for bistable dynamics in such reaction networks. We construct a generic model of an enzyme with n-substrate binding sites and derive an analytical solution for the steady-state concentration of all enzyme-substrate complexes. By studying these expressions, we obtain a mechanistic understanding of bistability, derive parameter combinations that guarantee bistability, and show how changing specific enzyme kinetic parameters and enzyme levels can lead to bistability in reaction networks involving multisite enzymes. Thus, the presented findings provide a biochemical and mathematical basis for predicting and engineering bistability in multisite enzymes.

The H2O2 inherently released by the mycobacterial minor subpopulation enhances the survival of the major kin subpopulation against rifampicin

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Stress survival of mycobacterial minor (SCs) and major (NCs) subpopulations.

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The SCs enhance survival of the NCs against rifampicin.

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H₂O₂ released by the SCs increased KatG levels in the NCs.

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Increased KatG levels neutralised the H₂O₂ formed during rifampicin exposure.

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The enhanced survival was not observed in the furA-katG/katG knockout mutants.

Exposure to antibiotics most often generates oxidative stress in bacteria. Oxidative stress survival mechanisms would facilitate the evolution of antibiotic resistance. As part of an effort to understand oxidative stress survival mechanisms in mycobacteria, here we show that the minor subpopulation (SCs; short-sized cells constituting 10% of the population) of Mycobacterium smegmatis significantly increased the survival of its major kin subpopulation (NCs; normal/long-sized cells constituting 90% of the population) in the mid-log-phase (MLP) cultures against the oxidative stress induced by rifampicin and exogenously added H₂O₂ (positive control). We had earlier shown that the SCs in the MLP cultures inherently and naturally release significantly high levels of H₂O₂ into the medium. Addition of the SCs’ culture supernatant, unlike the supernatant of the dimethylthiourea (H₂O₂ scavenger) exposed SCs, enhanced the survival of NCs. It indicated that NCs’ survival required the H₂O₂ present in the SCs’ supernatant. This H₂O₂ transcriptionally induced high levels of catalase-peroxidase (KatG) in the NCs. The naturally high KatG levels in the NCs significantly neutralised the endogenous H₂O₂ formed upon exposure to rifampicin or H₂O₂, thereby enhancing the survival of NCs against oxidative stress. The absence of such enhanced survival in the furA-katG and katG knockout (KO) mutants of NCs in the presence of wild-type SCs, confirmed the requirement of the H₂O₂ present in the SCs’ supernatant and NCs’ KatG for enhanced oxidative stress survival. The presence of SCs:NCs at 1:9 in the pulmonary tuberculosis patients’ sputum alludes to the clinical significance of the finding.

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

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

Pareto optimality between growth-rate and lag-time couples metabolic noise to phenotypic heterogeneity in Escherichia coli

Despite mounting evidence that in clonal bacterial populations, phenotypic variability originates from stochasticity in gene expression, little is known about noise-shaping evolutionary forces and how expression noise translates to phenotypic differences. Here we developed a high-throughput assay that uses a redox-sensitive dye to couple growth of thousands of bacterial colonies to their respiratory activity and show that in Escherichia coli, noisy regulation of lower glycolysis and citric acid cycle is responsible for large variations in respiratory metabolism. We found that these variations are Pareto optimal to maximization of growth rate and minimization of lag time, two objectives competing between fermentative and respiratory metabolism. Metabolome-based analysis revealed the role of respiratory metabolism in preventing the accumulation of toxic intermediates of branched chain amino acid biosynthesis, thereby supporting early onset of cell growth after carbon starvation. We propose that optimal metabolic tradeoffs play a key role in shaping and preserving phenotypic heterogeneity and adaptation to fluctuating environments.

Persistence of Intracellular Bacterial Pathogens-With a Focus on the Metabolic Perspective

Persistence has evolved as a potent survival strategy to overcome adverse environmental conditions. This capability is common to almost all bacteria, including all human bacterial pathogens and likely connected to chronic infections caused by some of these pathogens. Although the majority of a bacterial cell population will be killed by the particular stressors, like antibiotics, oxygen and nitrogen radicals, nutrient starvation and others, a varying subpopulation (termed persisters) will withstand the stress situation and will be able to revive once the stress is removed. Several factors and pathways have been identified in the past that apparently favor the formation of persistence, such as various toxin/antitoxin modules or stringent response together with the alarmone (p)ppGpp. However, persistence can occur stochastically in few cells even of stress-free bacterial populations. Growth of these cells could then be induced by the stress conditions. In this review, we focus on the persister formation of human intracellular bacterial pathogens, some of which belong to the most successful persister producers but lack some or even all of the assumed persistence-triggering factors and pathways. We propose a mechanism for the persister formation of these bacterial pathogens which is based on their specific intracellular bipartite metabolism. We postulate that this mode of metabolism ultimately leads, under certain starvation conditions, to the stalling of DNA replication initiation which may be causative for the persister state.

Observing Bacterial Persistence at Single-Cell Resolution

Within a bacterial population, there can be a subpopulation of cells with an antibiotic-tolerant persister phenotype characterized by long lag phase. Their long lag phase necessitates long (hours or days) periods of single-cell observation to capture high-quality quantitative information about persistence. We describe a method of single-cell imaging using glass bottom dishes and a nutrient agarose pad that allows for long-term single-cell microscopy observation in a stable environment. We apply this method to characterize the lag phase and persistence of individual Escherichia coli cells.

Computation of Single-Cell Metabolite Distributions Using Mixture Models

Metabolic heterogeneity is widely recognized as the next challenge in our understanding of non-genetic variation. A growing body of evidence suggests that metabolic heterogeneity may result from the inherent stochasticity of intracellular events. However, metabolism has been traditionally viewed as a purely deterministic process, on the basis that highly abundant metabolites tend to filter out stochastic phenomena. Here we bridge this gap with a general method for prediction of metabolite distributions across single cells. By exploiting the separation of time scales between enzyme expression and enzyme kinetics, our method produces estimates for metabolite distributions without the lengthy stochastic simulations that would be typically required for large metabolic models. The metabolite distributions take the form of Gaussian mixture models that are directly computable from single-cell expression data and standard deterministic models for metabolic pathways. The proposed mixture models provide a systematic method to predict the impact of biochemical parameters on metabolite distributions. Our method lays the groundwork for identifying the molecular processes that shape metabolic heterogeneity and its functional implications in disease.

Microbial metabolic noise

From the time a cell was first placed under the microscope, it became apparent that identifying two clonal cells that "look" identical is extremely challenging. Since then, cell-to-cell differences in shape, size, and protein content have been carefully examined, informing us of the ultimate limits that hinder two cells from occupying an identical phenotypic state. Here, we present recent experimental and computational evidence that similar limits emerge also in cellular metabolism. These limits pertain to stochastic metabolic dynamics and, thus, cell-to-cell metabolic variability, including the resulting adapting benefits. We review these phenomena with a focus on microbial metabolism and conclude with a brief outlook on the potential relationship between metabolic noise and adaptive evolution. This article is categorized under: Metabolic Diseases > Computational Models Metabolic Diseases > Biomedical Engineering.

Fingerprinting Bacterial Metabolic Response to Erythromycin by Raman-Integrated Mid-Infrared Photothermal Microscopy

We report rapid and sensitive phenotyping of bacterial response to antibiotic treatment at single-cell resolution by a Raman-integrated optical mid-infrared photothermal (MIP) microscope. The MIP microscope successfully detected biochemical changes of bacteria in specific to the acting mechanism of erythromycin with 1 h incubation. Compared to Raman spectroscopy, MIP spectroscopy showed a much larger signal-to-noise ratio at the fingerprint region at an acquisition speed as fast as 1 s per spectrum. The high sensitivity of MIP enabled detection of metabolic changes at antibiotic concentrations below minimum inhibitory concentration (MIC). Meanwhile, the single-cell resolution of the technique allowed observation of heteroresistance within one bacterial population, which is of great clinical relevance. This study showcases characterizing antibiotic response as one of the many possibilities of applying MIP microscopy to single-cell biology.

Gene expression noise can promote the fixation of beneficial mutations in fluctuating environments

Nongenetic phenotypic variation can either speed up or slow down adaptive evolution. We show that it can speed up evolution in environments where available carbon and energy sources change over time. To this end, we use an experimentally validated model of Escherichia coli growth on two alternative carbon sources, glucose and acetate. On the superior carbon source (glucose), all cells achieve high growth rates, while on the inferior carbon source (acetate) only a small fraction of the population manages to initiate growth. Consequently, populations experience a bottleneck when the environment changes from the superior to the inferior carbon source. Growth on the inferior carbon source depends on a circuit under the control of a transcription factor that is repressed in the presence of the superior carbon source. We show that noise in the expression of this transcription factor can increase the probability that cells start growing on the inferior carbon source. In doing so, it can decrease the severity of the bottleneck and increase mean population fitness whenever this fitness is low. A modest amount of noise can also enhance the fitness effects of a beneficial allele that increases the fraction of a population initiating growth on acetate. Additionally, noise can protect this allele from extinction, accelerate its spread, and increase its likelihood of going to fixation. Central to the adaptation-enhancing principle we identify is the ability of noise to mitigate population bottlenecks, particularly in environments that fluctuate periodically. Because such bottlenecks are frequent in fluctuating environments, and because periodically fluctuating environments themselves are common, this principle may apply to a broad range of environments and organisms.

Alleviated Antibiotic-Resistant Genes in the Rhizosphere of Agricultural Soils with Low Antibiotic Concentration

The influence of the rhizosphere on the abundance and diversity of antibiotic resistance genes (ARGs) has been recognized but there is a lack of consensus because of broad ranges of plant species and antibiotic concentrations across different habitats and the elusive underlying mechanisms. Here, we profiled antibiotic concentrations and resistomes in the rhizosphere and bulk soils by cultivating 10 types of crops in manure-amended agricultural soils. Rhizosphere effects altered the antibiotic resistome structure, significantly increased the absolute abundance of the antibiotic resistome, and decreased their relative abundance, contrasting previous studies. Such plantation-driven variation in ARGs resulted from the boost of bacterial lineages with negative relationships with ARGs and the constraint of the potential ARG-hosts in the rhizosphere of plants cultivated in soils with low antibiotic concentrations as the selective pressure. This mechanism is not reported previously and deepens our understanding about the rhizosphere effects on ARGs.

Quantitation and Comparison of Phenotypic Heterogeneity Among Single Cells of Monoclonal Microbial Populations

Phenotypic heterogeneity within microbial populations arises even when the cells are exposed to putatively constant and homogeneous conditions. The outcome of this phenomenon can affect the whole function of the population, resulting in, for example, new "adapted" metabolic strategies and impacting its fitness at given environmental conditions. Accounting for phenotypic heterogeneity becomes thus necessary, due to its relevance in medical and applied microbiology as well as in environmental processes. Still, a comprehensive evaluation of this phenomenon requires a common and unique method of quantitation, which allows for the comparison between different studies carried out with different approaches. Consequently, in this study, two widely applicable indices for quantitation of heterogeneity were developed. The heterogeneity coefficient (HC) is valid when the population follows unimodal activity, while the differentiation tendency index (DTI) accounts for heterogeneity implying outbreak of subpopulations and multimodal activity. We demonstrated the applicability of HC and DTI for heterogeneity quantitation on stable isotope probing with nanoscale secondary ion mass spectrometry (SIP-nanoSIMS), flow cytometry, and optical microscopy datasets. The HC was found to provide a more accurate and precise measure of heterogeneity, being at the same time consistent with the coefficient of variation (CV) applied so far. The DTI is able to describe the differentiation in single-cell activity within monoclonal populations resolving subpopulations with low cell abundance, individual cells with similar phenotypic features (e.g., isotopic content close to natural abundance, as detected with nanoSIMS). The developed quantitation approach allows for a better understanding on the impact and the implications of phenotypic heterogeneity in environmental, medical and applied microbiology, microbial ecology, cell biology, and biotechnology.

Deciphering Metabolic Heterogeneity by Single-Cell Analysis

Single-cell analysis provides insights into cellular heterogeneity and dynamics of individual cells. This Feature highlights recent developments in key analytical techniques suited for single-cell metabolic analysis with a special focus on mass spectrometry-based analytical platforms and RNA-seq as well as imaging techniques that reveal stochasticity in metabolism.

Selection of Bacterial Mutants in Late Infections: When Vector Transmission Trades Off against Growth Advantage in Stationary Phase

Bacterial infections are often composed of cells with distinct phenotypes that can be produced by genetic or epigenetic mechanisms. This phenotypic heterogeneity has proved to be important in many pathogens, because it can alter both pathogenicity and transmission. We studied how and why it can emerge during infection in the bacterium Xenorhabdus nematophila, a pathogen that kills insects and multiplies in the cadaver before being transmitted by the soil nematode vector Steinernema carpocapsae We found that phenotypic variants cluster in three groups, one of which is composed of lrp defective mutants. These mutants, together with variants of another group, have in common that they maintain high survival during late stationary phase. This probably explains why they increase in frequency: variants of X. nematophila with a growth advantage in stationary phase (GASP) are under strong positive selection both in prolonged culture and in late infections. We also found that the within-host advantage of these variants seems to trade off against transmission by nematode vectors: the variants that reach the highest load in insects are those that are the least transmitted.IMPORTANCE Pathogens can evolve inside their host, and the importance of this mutation-fueled process is increasingly recognized. A disease outcome may indeed depend in part on pathogen adaptations that emerge during infection. It is therefore important to document these adaptations and the conditions that drive them. In our study, we took advantage of the possibility to monitor within-host evolution in the insect pathogen X. nematophila We demonstrated that selection occurring in aged infection favors lrp defective mutants, because these metabolic mutants benefit from a growth advantage in stationary phase (GASP). We also demonstrated that these mutants have reduced virulence and impaired transmission, modifying the infection outcome. Beyond the specific case of X. nematophila, we propose that metabolic mutants are to be found in other bacterial pathogens that stay for many generations inside their host.

Power-law tail in lag time distribution underlies bacterial persistence

Genetically identical microbial cells respond to stress heterogeneously, and this phenotypic heterogeneity contributes to population survival. Quantitative analysis of phenotypic heterogeneity can reveal dynamic features of stochastic mechanisms that generate heterogeneity. Additionally, it can enable a priori prediction of population dynamics, elucidating microbial survival strategies. Here, we quantitatively analyzed the persistence of an Escherichia coli population. When a population is confronted with antibiotics, a majority of cells is killed but a subpopulation called persisters survives the treatment. Previous studies have found that persisters survive antibiotic treatment by maintaining a long period of lag phase. When we quantified the lag time distribution of E. coli cells in a large dynamic range, we found that normal cells rejuvenated with a lag time distribution that is well captured by an exponential decay [exp(-kt)], agreeing with previous studies. This exponential decay indicates that their rejuvenation is governed by a single rate constant kinetics (i.e., k is constant). Interestingly, the lag time distribution of persisters exhibited a long tail captured by a power-law decay. Using a simple quantitative argument, we demonstrated that this power-law decay can be explained by a wide variation of the rate constant k Additionally, by developing a mathematical model based on this biphasic lag time distribution, we quantitatively explained the complex population dynamics of persistence without any ad hoc parameters. The quantitative features of persistence demonstrated in our work shed insights into molecular mechanisms of persistence and advance our knowledge of how a microbial population evades antibiotic treatment.

Spontaneous mutations in a regulatory gene induce phenotypic heterogeneity and adaptation of Ralstonia solanacearum to changing environments

An evolution experiment with the bacterial plant pathogen Ralstonia solanacearum revealed that several adaptive mutations conferring enhanced fitness in plants arose in the efpR gene encoding a regulator of virulence and metabolic functions. In this study, we found that an efpR mutant systematically displays colonies with two morphotypes: the type S ('smooth', similar to the wild type) and the type EV ('efpR variant'). We demonstrated that the efpH gene, a homologue of efpR, plays a key role in the control of phenotypic heterogeneity, the ΔefpR-ΔefpH double mutant being stably locked into the EV type. Using mixed infection assays, we demonstrated that the type EV is metabolically more proficient than the type S and displays fitness gain in specific environments, whereas the type S has a better fitness into the plant environment. We provide evidence that this efpR-dependent phenotypic heterogeneity is a general feature of strains of the R. solanacearum species complex and could occur in natural conditions. This study highlights the potential role of phenotypic heterogeneity in this plant pathogen as an adaptive trait to changing environments.

Light-dependent single-cell heterogeneity in the chloroplast redox state regulates cell fate in a marine diatom

Diatoms are photosynthetic microorganisms of great ecological and biogeochemical importance, forming vast blooms in aquatic ecosystems. However, we are still lacking fundamental understanding of how individual cells sense and respond to diverse stress conditions, and what acclimation strategies are employed during bloom dynamics. We investigated cellular responses to environmental stress at the single-cell level using the redox sensor roGFP targeted to various organelles in the diatom Phaeodactylum tricornutum. We detected cell-to-cell variability using flow cytometry cell sorting and a microfluidics system for live imaging of oxidation dynamics. Chloroplast-targeted roGFP exhibited a light-dependent, bi-stable oxidation pattern in response to H₂O₂ and high light, revealing distinct subpopulations of sensitive oxidized cells and resilient reduced cells. Early oxidation in the chloroplast preceded commitment to cell death, and can be used for sensing stress cues and regulating cell fate. We propose that light-dependent metabolic heterogeneity regulates diatoms’ sensitivity to environmental stressors in the ocean.

Microscopic algae, such as diatoms, are widely spread throughout the oceans, and are responsible for half of the oxygen we breathe. At certain times of the year these algae grow very rapidly to form large “blooms” that can be detected by satellites in space. These blooms are generally short-lived because the algae are either eaten by other marine organisms, run out of nutrients, or die as a result of being infected by viruses or bacteria. However, some diatom cells survive the end of the bloom and go on to generate new blooms in the future, but it is still not clear how.

As the bloom collapses, diatoms experience many stressful conditions which can cause active molecules known as reactive oxygen species, or ROS for short, to accumulate inside cells. Normally growing cells also produce low amounts of ROS, which regulate various processes that are important for maintaining a cell’s health. However, high amounts of ROS can cause damage, which may lead to a cell’s death. Now, Mizrachi et al. investigated why some algae survive while others die in response to stressful conditions, focusing on the amount of ROS that accumulates within the diatom Phaeodactylum tricornutum.

Laboratory experiments showed that individual cells of P. tricornutum respond differently to environmental stress, forming two distinct groups of either sensitive or resilient cells. Sensitive cells accumulated high levels of ROS within a cell compartment known as the chloroplast and eventually died. Whereas resilient cells were able to maintain low levels of ROS in the chloroplast and survived long after the other cells perished. Populations of genetically identical diatom cells also formed distinct groups of sensitive and resilient cells, demonstrating that these two opposing reactions to stress are not caused by genetic differences between cells.

Lastly, Mizrachi et al. showed that how diatoms acclimate to stress depends on the amount of light they are exposed to. When in the dark, all cells became sensitive to oxidative stress, without forming distinct groups. But, when exposed to strong light that mimics the ocean surface, cells formed distinct groups within the population. This suggests that light regulates how susceptible these microscopic algae are to environmental stress.

The different responses within a population may serve as a “bet-hedging” strategy, enabling at least some of the cells to survive unpredicted stressful conditions. The next challenge will be to find out whether algae growing in the oceans also use the same strategy and investigate what impact this has on diatom blooms.

Stochastic modelling reveals mechanisms of metabolic heterogeneity

Phenotypic variation is a hallmark of cellular physiology. Metabolic heterogeneity, in particular, underpins single-cell phenomena such as microbial drug tolerance and growth variability. Much research has focussed on transcriptomic and proteomic heterogeneity, yet it remains unclear if such variation permeates to the metabolic state of a cell. Here we propose a stochastic model to show that complex forms of metabolic heterogeneity emerge from fluctuations in enzyme expression and catalysis. The analysis predicts clonal populations to split into two or more metabolically distinct subpopulations. We reveal mechanisms not seen in deterministic models, in which enzymes with unimodal expression distributions lead to metabolites with a bimodal or multimodal distribution across the population. Based on published data, the results suggest that metabolite heterogeneity may be more pervasive than previously thought. Our work casts light on links between gene expression and metabolism, and provides a theory to probe the sources of metabolite heterogeneity.

The presence of in situ sulphamethoxazole degraders and their interactions with other microbes in activated sludge as revealed by DNA stable isotope probing and molecular ecological network analysis

Wastewater treatment plants (WWTPs) are the main hotspots for the release of antibiotics, including the widely used sulphonamides. Microbes play important roles in eliminating sulphonamides in WWTPs, and knowledge about these degraders and their interactions within the microbial community is crucial for operating and optimising WWTPs. In the present study, stable isotope probing (SIP) coupled with high-throughput sequencing as culture-independent approach revealed four operational taxonomic units (OTUs) involved in sulphamethoxazole (SMX) degradation in activated sludge. Except for the OTU affiliated with Gammaproteobacteria, the others have not been previously reported to possess the ability to metabolise SMX. The isolated SMX degrader by culture-dependent method did not participate in SMX biodegradation in situ according to the SIP analysis, and showed weak correlations with other members in the activated sludge. The complex interactions between in situ active SMX degraders and non-degrading microbes might explain our failure to isolate these degraders. In addition, sul1 genes associated with SMX resistance were also labelled with ¹³C, suggesting that they might benefit from SMX degradation and/or originate from the active SMX degraders. These findings broaden our understanding of the diversity of SMX-degrading microbes and their associated characteristics in WWTPs.

The effect of acetate on population heterogeneity in different cellular characteristics of Escherichia coli in aerobic batch cultures

Acetate as the major by-product in industrial-scale bioprocesses with Escherichia coli is found to decrease process efficiency as well as to be toxic to cells, which has several effects like a significant induction of cellular stress responses. However, the underlying phenomena are poorly explored. Therefore, we studied time-resolved population heterogeneity of the E. coli growth reporter strain MG1655/pGS20PrrnBGFPAAV expressing destabilized green fluorescent protein during batch growth on acetate and glucose as sole carbon sources. Additionally, we applied five fluorescent stains targeting different cellular properties (viability as well as metabolic and respiratory activity). Quantitative analysis of flow cytometry data verified that bacterial populations in the bioreactor are more heterogeneous in growth as well as stronger metabolically challenged during growth on acetate as sole carbon source, compared to growth on glucose or acetate after diauxic shift. Interestingly, with acetate as sole carbon source, significant subpopulations were found with some cells that seem to be more robust than the rest of the population. In conclusion, following batch cultures population heterogeneity was evident in all measured parameters. Our approach enabled a deeper study of heterogeneity during growth on the favored substrate glucose as well as on the toxic by-product acetate. Using a combination of activity fluorescent dyes proved to be an accurate and fast alternative as well as a supplement to the use of a reporter strain. However, the choice of combination of stains should be well considered depending on which population traits to aim for.

Induction of Escherichia coli Into a VBNC State by Continuous-Flow UVC and Subsequent Changes in Metabolic Activity at the Single-Cell Level

A viable but non-culturable (VBNC) state of bacteria induced by disinfection in water treatment poses serious health risks because of possible resuscitation of VBNC cells during transportation. In this study, a setup using continuous-flow ultraviolet (UVC) irradiation ranging from 0 to 172.2 mJ cm^-2 was designed to simulate real-world disinfection in both drinking water (SDW) and reclaimed water (SRW) treatment plants. A systematic investigation of UVC-induced VBNC bacteria, including occurrence, resuscitation, and time-dependent recovery of metabolic activity during post-incubation, was conducted. Different techniques including two new ones of “single cell culture” and D₂O-labeled single-cell Raman spectroscopy were employed to gain comprehensive insights into VBNC cells. Heterotrophic plate counts (HPC) and 5-cyano-2,3-ditoyl tetrazolium chloride flow cytometry (CTC-FCM) assay demonstrated that exposure to continuous-flow UVC can induce E. coli into a VBNC state. Membranes integrity and 16S rRNA transcription level of VBNC bacteria were demonstrated to be unaffected by UVC exposure even at a high dose of 172.2 mJ cm^-2. Resuscitation of VBNC bacteria was identified in a more accurate way based on “single cell culture.” Finally, time-dependent evolution of metabolic activity of UVC-treated cells during post-incubation was examined by D₂O-labeled Raman spectroscopy at a high-resolution of single-cell level. C-D Raman bands resulting from incorporation of D₂O-derived D into bacterial biomass were used as a sensitive and quantitative indicator of bacterial metabolic activity. A lower UVC dose, longer post-incubation time, and higher initial number of bacteria were demonstrated to result in a faster recovery of metabolic activity. Heterogeneous metabolic activity and subpopulation with higher metabolic activity were also revealed by single-cell Raman, even for UVC-treated cells losing cultivability. The comprehensive assessment of VBNC bacteria in UVC-disinfected drinking and reclaimed water points out treatment deficiencies of UVC and the necessity to develop more effective strategies to eliminate VBNC cells.

The Culture Environment Influences Both Gene Regulation and Phenotypic Heterogeneity in Escherichia coli

Microorganisms shape the composition of the medium they are growing in, which in turn has profound consequences on the reprogramming of the population gene-expression profile. In this paper, we investigate the progressive changes in pH and sugar availability in the medium of a growing Escherichia coli (E. coli) culture. We show how these changes have an effect on both the cellular heterogeneity within the microbial community and the gene-expression profile of the microbial population. We measure the changes in gene-expression as E. coli moves from lag, to exponential, and finally into stationary phase. We found that pathways linked to the changes in the medium composition such as ribosomal, tricarboxylic acid cycle (TCA), transport, and metabolism pathways are strongly regulated during the different growth phases. In order to quantify the corresponding temporal changes in the population heterogeneity, we measure the fraction of E. coli persisters surviving different antibiotic treatments during the various phases of growth. We show that the composition of the medium in which β-lactams or quinolones, but not aminoglycosides, are dissolved strongly affects the measured phenotypic heterogeneity within the culture. Our findings contribute to a better understanding on how the composition of the culture medium influences both the reprogramming in the population gene-expression and the emergence of phenotypic variants.