Growth resumption from stationary phase reveals memory in Escherichia coli cultures

Population-level control of two manganese oxidases expands the niche for bacterial manganese biomineralization

The enzymatic oxidation of aqueous divalent manganese (Mn) is a widespread microbial trait that produces reactive Mn(III, IV) oxide minerals. These biominerals drive carbon, nutrient, and trace metal cycles, thus playing important environmental and ecological roles. However, the regulatory mechanisms and physiological functions of Mn biomineralization are unknown. This challenge arises from the common occurrence of multiple Mn oxidases within the same organism and the use of Mn oxides as indicators of combined gene activity. Through the detection of gene activation in individual cells, we discover that expression of mnxG and mcoA, two Mn oxidase-encoding genes in Pseudomonas putida GB-1, is confined to subsets of cells within the population, with each gene showing distinct spatiotemporal patterns that reflect local microenvironments. These coordinated intra-population dynamics control Mn biomineralization and illuminate the strategies used by microbial communities to dictate the extent, location, and timing of biogeochemical transformations.

Nongenetic adaptation by collective migration

Cell populations must adjust their phenotypic composition to adapt to changing environments. One adaptation strategy is to maintain distinct phenotypic subsets within the population and to modulate their relative abundances via gene regulation. Another strategy involves genetic mutations, which can be augmented by stress-response pathways. Here, we studied how a migrating bacterial population regulates its phenotypic distribution to traverse diverse environments. We generated isogenic Escherichia coli populations with varying distributions of swimming behaviors and observed their phenotype distributions during migration in liquid and porous environments. We found that the migrating populations became enriched with high-performing swimming phenotypes in each environment, allowing the populations to adapt without requiring mutations or gene regulation. This adaptation is dynamic and rapid, reversing in a few doubling times when migration ceases. By measuring the chemoreceptor abundance distributions during migration toward different attractants, we demonstrated that adaptation acts on multiple chemotaxis-related traits simultaneously. These measurements are consistent with a general mechanism in which adaptation results from a balance between cell growth generating diversity and collective migration eliminating underperforming phenotypes. Thus, collective migration enables cell populations with continuous, multidimensional phenotypes to flexibly and rapidly adapt their phenotypic composition to diverse environmental conditions.

A genetically encoded fluorescent biosensor for visualization of acetyl-CoA in live cells

Acetyl-coenzyme A is a central metabolite that participates in many cellular pathways. Evidence suggests that acetyl-CoA metabolism is highly compartmentalized in mammalian cells. Yet methods to measure acetyl-CoA in living cells are lacking. Herein, we engineered an acetyl-CoA biosensor from the bacterial protein PanZ and circularly permuted green fluorescent protein (cpGFP). The sensor, "PancACe," has a maximum change of ∼2-fold and a response range of ∼10 μM-2 mM acetyl-CoA. We demonstrated that the sensor has a greater than 7-fold selectivity over coenzyme A, butyryl-CoA, malonyl-CoA, and succinyl-CoA, and a 2.3-fold selectivity over propionyl-CoA. We expressed the sensor in E. coli and showed that it enables detection of rapid changes in acetyl-CoA levels. By localizing the sensor to either the cytoplasm, nucleus, or mitochondria in human cells, we showed that it enables subcellular detection of changes in acetyl-CoA levels, the magnitudes of which agreed with an orthogonal PicoProbe assay.

Diversification of single-cell growth dynamics under starvation influences subsequent reproduction in a clonal bacterial population

Most of the microbes in nature infrequently receive nutrients and are thus in slow- or non-growing states. How quickly they can resume their growth upon an influx of new resources is crucial to occupy environmental niches. Isogenic microbial populations are known to harbor only a fraction of cells with rapid growth resumption, yet little is known about the physiological characteristics of those cells and their emergence in the population. Here, we tracked growth of individual Escherichia coli cells in populations under fluctuating nutrient conditions. We found that shifting from high- to low-nutrient conditions caused stalling of cell growth with few cells continuing to divide extremely slowly, a process which was dependent on lipid turnover. Resuming high-nutrient inflow after low-nutrient conditions resulted in cells resuming growth and division, but with different lag times and leading to varying progeny. The history of cell growth during low-nutrient but not high-nutrient conditions was determinant for resumption of growth, which cellular genealogy analysis suggested to originate from inherited physiological differences. Our results demonstrate that cellular growth dynamics become diverse by nutrient limitations, under which a fraction of cells experienced a particular growth history can reproduce progeny with new resources in the future.

Characterization of Escherichia coli Persisters from Biofilm Culture: Multiple Dormancy Levels and Multigenerational Memory in Formation

Persister cells (PCs), a subpopulation occurring within normal cells, exhibit a transient tolerance to antibiotics because of their dormant state. PCs are categorized into two types: type I PCs, which emerge during the stationary phase, and type II PCs, which emerge during the logarithmic phase. Using the conventional colony-forming method, we previously demonstrated that type I PCs of Escherichia coli form more frequently in air-solid biofilm culture than in liquid culture. In the current study, we modified a cell filamentation method as a more efficient and rapid alternative for quantifying PCs. This modified method yielded results consistent with those of the conventional method with 103-104 times higher sensitivity and less detection time, within several hours, and further revealed the existence of multiple levels of type I PCs, including a substantial number of deeply dormant cells. This study also discovered a potential epigenetic memory mechanism, spanning several generations (four or six cell divisions), which influences type II PC formation based on prior biofilm experience in E. coli.

The Impact of the Major Endoribonucleases RNase E and RNase III and of the sRNA StsR on Photosynthesis Gene Expression in Rhodobacter sphaeroides Is Growth-Phase-Dependent

Rhodobacter sphaeroides is a facultative phototrophic bacterium that performs aerobic respiration when oxygen is available. Only when oxygen is present at low concentrations or absent are pigment-protein complexes formed, and anoxygenic photosynthesis generates ATP. The regulation of photosynthesis genes in response to oxygen and light has been investigated for decades, with a focus on the regulation of transcription. However, many studies have also revealed the importance of regulated mRNA processing. This study analyzes the phenotypes of wild type and mutant strains and compares global RNA-seq datasets to elucidate the impact of ribonucleases and the small non-coding RNA StsR on photosynthesis gene expression in Rhodobacter. Most importantly, the results demonstrate that, in particular, the role of ribonuclease E in photosynthesis gene expression is strongly dependent on growth phase.

Identification of antibiotic induced persister cells in Streptococcus agalactiae

Antibiotic persistence is a phenomenon, where a small fraction of a bacterial population expresses a phenotypic variation that allows them to survive antibiotic treatment, which is lethal to the rest of the population. These cells are called persisters cells, and their occurrence has been associated with recurrent disease. Streptococcus agalactiae is a human pathobiont, able to cause invasive infections, and recurrent infections have been reported to occur in both newborns and adults. In this study, we demonstrated that S. agalactiae NEM316 can form persister cells when exposed to antibiotics from different classes. The frequency of persister cell formation was dependent on bacterial growth phase and the class of antibiotics. The ability to form persister cells in response to penicillin was shown to be a general trait among different clinical S. agalactiae isolates, independent of sero- and sequence-type. Taken together, this study shows the existence of antibiotic tolerant S. agalactiae persister cells, which may explain why this bacterial species frequently persists after treatment of invasive infection and can be associated with recurrent disease.

UNRAVELING CRP/cAMP-MEDIATED METABOLIC REGULATION IN ESCHERICHIA COLI PERSISTER CELLS

A substantial gap persists in our comprehension of how bacterial metabolism undergoes rewiring during the transition to a persistent state. Also, it remains unclear which metabolic mechanisms become indispensable for persister cell survival. To address these questions, we directed our efforts towards persister cells in Escherichia coli that emerge during the late stationary phase. These cells have been recognized for their exceptional resilience and are commonly believed to be in a dormant state. Our results demonstrate that the global metabolic regulator Crp/cAMP redirects the metabolism of these antibiotic-tolerant cells from anabolism to oxidative phosphorylation. Although our data indicates that persisters exhibit a reduced metabolic rate compared to rapidly growing exponential-phase cells, their survival still relies on energy metabolism. Extensive genomic-level analyses of metabolomics, proteomics, and single-gene deletions consistently emphasize the critical role of energy metabolism, specifically the tricarboxylic acid (TCA) cycle, electron transport chain (ETC), and ATP synthase, in sustaining the viability of persisters. Altogether, this study provides much-needed clarification regarding the role of energy metabolism in antibiotic tolerance and highlights the importance of using a multipronged approach at the genomic level to obtain a broader picture of the metabolic state of persister cells.

Universal Transitions between Growth and Dormancy via Intermediate Complex Formation

A simple cell model consisting of a catalytic reaction network with intermediate complex formation is numerically studied. As nutrients are depleted, the transition from the exponential growth phase to the growth-arrested dormant phase occurs along with hysteresis and a lag time for growth recovery. This transition is caused by the accumulation of intermediate complexes, leading to the jamming of reactions and the diversification of components. These properties are generic in random reaction networks, as supported by dynamical systems analyses of corresponding mean-field models.

A genetically-encoded fluorescent biosensor for visualization of acetyl-CoA in live cells

Acetyl-coenzyme A is a central metabolite that participates in many cellular pathways. Evidence suggests that acetyl-CoA production and consumption are highly compartmentalized in mammalian cells. Yet methods to measure acetyl-CoA in living cells are lacking. In this work, we engineer an acetyl-CoA biosensor from the bacterial protein PanZ and circularly permuted green fluorescent protein (cpGFP). We biochemically characterize the sensor and demonstrate its selectivity for acetyl-CoA over other CoA species. We then deploy the biosensor in E. coli and HeLa cells to demonstrate its utility in living cells. In E. coli, we show that the biosensor enables detection of rapid changes in acetyl-CoA levels. In human cells, we show that the biosensor enables subcellular detection and reveals the compartmentalization of acetyl-CoA metabolism.

The protein carboxymethyltransferase-dependent aspartate salvage pathway plays a crucial role in the intricate metabolic network of Escherichia coli

Protein carboxymethyltransferase (Pcm) is a highly evolutionarily conserved enzyme that initiates the conversion of abnormal isoaspartate to aspartate residues. While it is commonly believed that Pcm facilitates the repair of damaged proteins, a number of observations suggest that it may have another role in cell functioning. We investigated whether Pcm provides a means for Escherichia coli to recycle aspartate, which is essential for protein synthesis and other cellular processes. We showed that Pcm is required for the energy production, the maintenance of cellular redox potential and of S-adenosylmethionine synthesis, which are critical for the proper functioning of many metabolic pathways. Pcm contributes to the full growth capacity both under aerobic and anaerobic conditions. Last, we showed that Pcm enhances the robustness of bacteria when exposed to sublethal antibiotic treatments and improves their fitness in the mammalian urinary tract. We propose that Pcm plays a crucial role in E. coli metabolism by ensuring a steady supply of aspartate.

Phage Paride can kill dormant, antibiotic-tolerant cells of Pseudomonas aeruginosa by direct lytic replication

Bacteriophages are ubiquitous viral predators that have primarily been studied using fast-growing laboratory cultures of their bacterial hosts. However, microbial life in nature is mostly in a slow- or non-growing, dormant state. Here, we show that diverse phages can infect deep-dormant bacteria and suspend their replication until the host resuscitates ("hibernation"). However, a newly isolated Pseudomonas aeruginosa phage, named Paride, can directly replicate and induce the lysis of deep-dormant hosts. While non-growing bacteria are notoriously tolerant to antibiotic drugs, the combination with Paride enables the carbapenem meropenem to eradicate deep-dormant cultures in vitro and to reduce a resilient bacterial infection of a tissue cage implant in mice. Our work might inspire new treatments for persistent bacterial infections and, more broadly, highlights two viral strategies to infect dormant bacteria (hibernation and direct replication) that will guide future studies on phage-host interactions.

Drug-tolerant persister cells in cancer: the cutting edges and future directions

Drug-tolerant persister (DTP) cell populations were originally discovered in antibiotic-resistant bacterial biofilms. Similar populations with comparable features have since been identified among cancer cells and have been linked with treatment resistance that lacks an underlying genomic alteration. Research over the past decade has improved our understanding of the biological roles of DTP cells in cancer, although clinical knowledge of the role of these cells in treatment resistance remains limited. Nonetheless, targeting this population is anticipated to provide new treatment opportunities. In this Perspective, we aim to provide a clear definition of the DTP phenotype, discuss the underlying characteristics of these cells, their biomarkers and vulnerabilities, and encourage further research on DTP cells that might improve our understanding and enable the development of more effective anticancer therapies.

Bacterial memory in antibiotic resistance evolution and nanotechnology in evolutionary biology

Bacterial memory refers to the phenomenon in which past experiences influence current behaviors in response to changing environments. It serves as a crucial process that enables adaptation and evolution. We first summarize the state-of-art approaches regarding history-dependent behaviors that impact growth dynamics and underlying mechanisms. Then, the phenotypic and genotypic origins of memory and how encoded memory modulates drug tolerance/resistance are reviewed. We also provide a summary of possible memory effects induced by antimicrobial nanoparticles. The regulatory networks and genetic underpinnings responsible for memory building partially overlap with nanoparticle and drug exposures, which may raise concerns about the impact of nanotechnology on adaptation. Finally, we provide a perspective on the use of nanotechnology to harness bacterial memory based on its unique mode of actions on information processing and transmission in bacteria. Exploring bacterial memory mechanisms provides valuable insights into acclimation, evolution, and the potential applications of nanotechnology in harnessing memory.

Microbial Growth under Limiting Conditions-Future Perspectives

Microorganisms rule the functioning of our planet and each one of the individual macroscopic living creature. Nevertheless, microbial activity and growth status have always been challenging tasks to determine both in situ and in vivo. Microbial activity is generally related to growth, and the growth rate is a result of the availability of nutrients under adequate or adverse conditions faced by microbial cells in a changing environment. Most studies on microorganisms have been carried out under optimum or near-optimum growth conditions, but scarce information is available about microorganisms at slow-growing states (i.e., near-zero growth and maintenance metabolism). This study aims to better understand microorganisms under growth-limiting conditions. This is expected to provide new perspectives on the functions and relevance of the microbial world. This is because (i) microorganisms in nature frequently face conditions of severe growth limitation, (ii) microorganisms activate singular pathways (mostly genes remaining to be functionally annotated), resulting in a broad range of secondary metabolites, and (iii) the response of microorganisms to slow-growth conditions remains to be understood, including persistence strategies, gene expression, and cell differentiation both within clonal populations and due to the complexity of the environment.

Dynamic proteome trade-offs regulate bacterial cell size and growth in fluctuating nutrient environments

Bacteria dynamically regulate cell size and growth to thrive in changing environments. While previous studies have characterized bacterial growth physiology at steady-state, a quantitative understanding of bacterial physiology in time-varying environments is lacking. Here we develop a quantitative theory connecting bacterial growth and division rates to proteome allocation in time-varying nutrient environments. In such environments, cell size and growth are regulated by trade-offs between prioritization of biomass accumulation or division, resulting in decoupling of single-cell growth rate from population growth rate. Specifically, bacteria transiently prioritize biomass accumulation over production of division machinery during nutrient upshifts, while prioritizing division over growth during downshifts. When subjected to pulsatile nutrient concentration, we find that bacteria exhibit a transient memory of previous metabolic states due to the slow dynamics of proteome reallocation. This allows for faster adaptation to previously seen environments and results in division control which is dependent on the time-profile of fluctuations.

Resuscitation dynamics reveal persister partitioning after antibiotic treatment

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

A Synthetic Polymicrobial Community Biofilm Model Demonstrates Spatial Partitioning, Tolerance to Antimicrobial Treatment, Reduced Metabolism, and Small Colony Variants Typical of Chronic Wound Biofilms

Understanding chronic wound infection is key for successful treatment and requires accurate laboratory models. We describe a modified biofilm flow device that effectively mimics the chronic wound environment, including simulated wound fluid, a collagen-based 3D biofilm matrix, and a five-species mixture of clinically relevant bacteria (Pseudomonas aeruginosa, Staphylococcus aureus, Escherichia coli, Enterococcus faecalis, and Citrobacter freundii). Mixed biofilms were cultured for between 3 and 14 days with consistent numbers of bacteria that exhibited reduced metabolic activity, which increased with a high dose of glucose. S. aureus was recovered from biofilms as a small colony variant, but as a normal colony variant if P. aeruginosa was excluded from the system. Bacteria within the biofilm did not co-aggregate but formed discrete, species-specific clusters. Biofilms demonstrated differential tolerance to the topical antimicrobials Neosporin and HOCl, consistent with protection due to the biofilm lifestyle. The characteristics exhibited within this model match those of real-world wound biofilms, reflecting the clinical scenario and yielding a powerful in vitro tool that is versatile, inexpensive, and pivotal for understanding chronic wound infection.

Navigating Environmental Transitions: the Role of Phenotypic Variation in Bacterial Responses

The ability of bacteria to respond to changes in their environment is critical to their survival, allowing them to withstand stress, form complex communities, and induce virulence responses during host infection. A remarkable feature of many of these bacterial responses is that they are often variable across individual cells, despite occurring in an isogenic population exposed to a homogeneous environmental change, a phenomenon known as phenotypic heterogeneity. Phenotypic heterogeneity can enable bet-hedging or division of labor strategies that allow bacteria to survive fluctuating conditions. Investigating the significance of phenotypic heterogeneity in environmental transitions requires dynamic, single-cell data. Technical advances in quantitative single-cell measurements, imaging, and microfluidics have led to a surge of publications on this topic. Here, we review recent discoveries on single-cell bacterial responses to environmental transitions of various origins and complexities, from simple diauxic shifts to community behaviors in biofilm formation to virulence regulation during infection. We describe how these studies firmly establish that this form of heterogeneity is prevalent and a conserved mechanism by which bacteria cope with fluctuating conditions. We end with an outline of current challenges and future directions for the field. While it remains challenging to predict how an individual bacterium will respond to a given environmental input, we anticipate that capturing the dynamics of the process will begin to resolve this and facilitate rational perturbation of environmental responses for therapeutic and bioengineering purposes.

Bacterial Resuscitation from Starvation-Induced Dormancy Results in Phenotypic Diversity Coupled with Translational Activity Depending on Carbon Substrate Availability

Dormancy is a survival strategy of stressed bacteria inhabiting a various environment. Frequent dormant-active transitions owing to environmental changes play an important role in functional redundancy. However, a proper understanding of the phenotypic changes in bacteria during these transitions remains to be clarified. In this study, orthogonal approaches, such as electron microscopy, flow cytometry, and Raman spectroscopy, which can evaluate phenotypic heterogeneity at the single-cell level, were used to observe morphological and molecular phenotypic changes in resuscitated cells, and RNA sequencing (RNASeq) was used to determine the genetic characteristics associated with phenotypes. Within 12 h of the resuscitation process, morphological (cell size and shape) and physiological (growth and viability) characteristics as well as molecular phenotypes (cellular components) were found to be recovered to the extent that they were similar to those in active cells. The recovery rate and detailed phenotypic properties of the resuscitated cells differed significantly depending on the type or concentration of carbon sources. RNASeq analysis revealed that genes related to translation were significantly upregulated under all resuscitation conditions. The simpler the carbon source (e.g., glucose), the higher the expression of genes involved in cellular repair, and the more complex the carbon source (e.g., beef extract), the higher the expression of genes associated with increased energy production associated with cellular aerobic respiration. This study of phenotypic plasticity of resuscitated cells provides fundamental insight into understanding the adaptive fine-tuning of the microbiome in response to environmental changes and the functional redundancy resulting from phenotype heterogeneity.

Digital models in biotechnology: Towards multi-scale integration and implementation

Industrial biotechnology encompasses a large area of multi-scale and multi-disciplinary research activities. With the recent megatrend of digitalization sweeping across all industries, there is an increased focus in the biotechnology industry on developing, integrating and applying digital models to improve all aspects of industrial biotechnology. Given the rapid development of this field, we systematically classify the state-of-art modelling concepts applied at different scales in industrial biotechnology and critically discuss their current usage, advantages and limitations. Further, we critically analyzed current strategies to couple cell models with computational fluid dynamics to study the performance of industrial microorganisms in large-scale bioprocesses, which is of crucial importance for the bio-based production industries. One of the most challenging aspects in this context is gathering intracellular data under industrially relevant conditions. Towards comprehensive models, we discuss how different scale-down concepts combined with appropriate analytical tools can capture intracellular states of single cells. We finally illustrated how the efforts could be used to develop digitals models suitable for both cell factory design and process optimization at industrial scales in the future.

Fast bacterial growth reduces antibiotic accumulation and efficacy

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

Predicting Metabolic Adaptation Under Dynamic Substrate Conditions Using a Resource-Dependent Kinetic Model: A Case Study Using Saccharomyces cerevisiae

Exposed to changes in their environment, microorganisms will adapt their phenotype, including metabolism, to ensure survival. To understand the adaptation principles, resource allocation-based approaches were successfully applied to predict an optimal proteome allocation under (quasi) steady-state conditions. Nevertheless, for a general, dynamic environment, enzyme kinetics will have to be taken into account which was not included in the linear resource allocation models. To this end, a resource-dependent kinetic model was developed and applied to the model organism Saccharomyces cerevisiae by combining published kinetic models and calibrating the model parameters to published proteomics and fluxomics datasets. Using this approach, we were able to predict specific proteomes at different dilution rates under chemostat conditions. Interestingly, the approach suggests that the occurrence of aerobic fermentation (Crabtree effect) in S. cerevisiae is not caused by space limitation in the total proteome but rather an effect of constraints on the mitochondria. When exposing the approach to repetitive, dynamic substrate conditions, the proteome space was allocated differently. Less space was predicted to be available for non-essential enzymes (reserve space). This could indicate that the perceived “overcapacity” present in experimentally measured proteomes may very likely serve a purpose in increasing the robustness of a cell to dynamic conditions, especially an increase of proteome space for the growth reaction as well as of the trehalose cycle that was shown to be essential in providing robustness upon stronger substrate perturbations. The model predictions of proteome adaptation to dynamic conditions were additionally evaluated against respective experimentally measured proteomes, which highlighted the model’s ability to accurately predict major proteome adaptation trends. This proof of principle for the approach can be extended to production organisms and applied for both understanding metabolic adaptation and improving industrial process design.

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.

Anti-persister strategies against stress induced bacterial persistence

The increase in antibiotic non-responsive bacteria is the leading concern in current research-oriented to eliminate pathogens. Nowadays, the excess use of antibiotics without specifically understanding the potentiality of killing pathogens and bacterial survival patterns has helped bacteria emerge indefatigably. Bacteria use various mechanisms such as resistance, persistence, and tolerance to ensure survival. Among these, persistence is a mechanism by which bacteria reside in their dormant state, bypassing the effects of treatments, making it crucial for bacterial survival. Persistent bacterial cells arise from the normal bacterial population as a slow-growing subset of bacteria with no metabolic flux. This behavior renders it to survive for a longer duration and at higher concentrations of antibiotics. They are one of the underlying causes of recurrence of bacterial infections. The present article explains the detailed molecular mechanisms and strategies of bacterial persistence, including the toxin-antitoxin modules, DNA damage, the formation of inactive ribosomal complexes, (p)ppGpp network, antibiotic-induced persistence, which are triggered by drug-induced stress. The article also comprehensively covers the epigenetic memory of persistence in bacteria, and anti-persistent therapeutics like antimicrobial molecules, synthetic peptides, acyldepsipeptide antibiotics, and endolysin therapy to reduce persister cell formation and control their frequency. These strategies could be utilized in combating the pathogenic bacteria undergoing persistence.

Cellular Memory of HipA-Induced Growth Arrest: The Length of Cell Growth Arrest Becomes Shorter for Each Successive Induction

Toxin-antitoxin (TA) systems are genetic modules found commonly in bacterial genomes. HipA is a toxin protein encoded from the hipBA TA system in the genome of Escherichia coli. Ectopic expression of hipA induces cell growth arrest. Unlike the cell growth arrest caused by other TA toxins, cells resume growth from the HipA-induced cell growth arrest phase after a defined period of time. In this article, we describe the change in the length of growth arrest while cells undergo repeated cycles of hipA induction, growth arrest and regrowth phases. In the multiple conditions tested, we observed that the length of growth arrest became successively shorter for each round of induction. We verified that this was not due to the appearance of HipA-resistant mutants. Additionally, we identified conditions, such as the growth phase of the starting culture and growth vessels, that alter the length of growth arrest. Our results showed that the length of HipA-induced growth arrest was dependent on environmental factors-in particular, the past growth environment of cells, such as a previous hipA induction. These effects lasted even after multiple rounds of cell divisions, indicating the presence of cellular "memory" that impacts cells' response to HipA-induced toxicity.

Bovine serum promotes the formation and phenotype memory retention of persister cells in Escherichia coli liquid cultures

Persister cells, or persisters, are a fraction of bacterial cells that have become temporarily tolerant to antibiotics despite their lack of typical antibiotic-resistant genes. In a previous study, we found that colony-biofilm culture (i.e., biofilm formed at an air-solid interface) promoted the formation and phenotype memory retention of persisters of Escherichia coli and other bacteria. To assess whether these same effects are caused by other types of stimuli that bacterial cells encounter in the environment, we examined the effects of bovine serum on the formation and phenotype retention of ampicillin-tolerant persisters in E. coli liquid culture. Bovine serum did indeed exert these effects significantly, and its effects were negated by heat treatment. Similar effects were observed with bovine serum albumin, albeit weaker than those of BS. Given that serum is a component of blood and lymph and is thus a general substance within animal and human bodies, our findings suggest that bacteria encountering these body fluids may enhance their abilities for persister formation and phenotype memory retention to allow their longer survival in antibiotic-containing environments.

Tracking bacterial lineages in complex and dynamic environments with applications for growth control and persistence

As bacteria transition from exponential to stationary phase, they change substantially in size, morphology, growth and expression profiles. These responses also vary between individual cells, but it has proved difficult to track cell lineages along the growth curve to determine the progression of events or correlations between how individual cells enter and exit dormancy. Here, we developed a platform for tracking more than 10⁵ parallel cell lineages in dense and changing cultures, independently validating that the imaged cells closely track batch populations. Initial applications show that for both Escherichia coli and Bacillus subtilis, growth changes from an 'adder' mode in exponential phase to mixed 'adder-timers' entering stationary phase, and then a near-perfect 'sizer' upon exit-creating broadly distributed cell sizes in stationary phase but rapidly returning to narrowly distributed sizes upon exit. Furthermore, cells that undergo more divisions when entering stationary phase suffer reduced survival after long periods of dormancy but are the only cells observed that persist following antibiotic treatment.

Transcriptome-Wide Analysis of Stationary Phase Small ncRNAs in E. coli

Almost two-thirds of the microbiome's biomass has been predicted to be in a non-proliferating, and thus dormant, growth state. It is assumed that dormancy goes hand in hand with global downregulation of gene expression. However, it remains largely unknown how bacteria manage to establish this resting phenotype at the molecular level. Recently small non-protein-coding RNAs (sRNAs or ncRNAs) have been suggested to be involved in establishing the non-proliferating state in bacteria. Here, we have deep sequenced the small transcriptome of Escherichia coli in the exponential and stationary phases and analyzed the resulting reads by a novel biocomputational pipeline STARPA (Stable RNA Processing Product Analyzer). Our analysis reveals over 12,000 small transcripts enriched during both growth stages. Differential expression analysis reveals distinct sRNAs enriched in the stationary phase that originate from various genomic regions, including transfer RNA (tRNA) fragments. Furthermore, expression profiling by Northern blot and RT-qPCR analyses confirms the growth phase-dependent expression of several enriched sRNAs. Our study adds to the existing repertoire of bacterial sRNAs and suggests a role for some of these small molecules in establishing and maintaining stationary phase as well as the bacterial stress response. Functional characterization of these detected sRNAs has the potential of unraveling novel regulatory networks central for stationary phase biology.

Synthetic biology in biofilms: Tools, challenges, and opportunities

The field of synthetic biology seeks to program living cells to perform novel functions with applications ranging from environmental biosensing to smart cell-based therapeutics. Bacteria are an especially attractive chassis organism due to their rapid growth, ease of genetic manipulation, and ability to persist across many environmental niches. Despite significant progress in bacterial synthetic biology, programming bacteria to perform novel functions outside the well-controlled laboratory context remains challenging. In contrast to planktonic laboratory growth, bacteria in nature predominately reside in the context of densely packed communities known as biofilms. While biofilms have historically been considered environmental and biomedical hazards, their physiology and emergent behaviors could be leveraged for synthetic biology to engineer more capable and robust bacteria. Specifically, bacteria within biofilms participate in complex emergent behaviors such as collective organization, cell-to-cell signaling, and division of labor. Understanding and utilizing these properties can enable the effective deployment of engineered bacteria into natural target environments. Toward this goal, this review summarizes the current state of synthetic biology in biofilms by highlighting new molecular tools and remaining biological challenges. Looking to future opportunities, advancing synthetic biology in biofilms will enable the next generation of smart cell-based technologies for use in medicine, biomanufacturing, and environmental remediation.

Epigenetic Memories: The Hidden Drivers of Bacterial Persistence?

Epigenetic modifications, including DNA methylation, stably alter gene expression without modifying genomic sequences. Recent evidence suggests that epigenetic regulation coupled with a long-term 'memory' effect plays a major role within bacterial persistence formation. Today, emerging high-resolution, single-molecule sequencing technologies allow an increased focus on DNA modifications as regulatory epigenetic marks, which presents a unique opportunity to identify possible epigenetic drivers of bacterial persistence.

Availability of the Molecular Switch XylR Controls Phenotypic Heterogeneity and Lag Duration during Escherichia coli Adaptation from Glucose to Xylose

The glucose-xylose metabolic transition is of growing interest as a model to explore cellular adaption since these molecules are the main substrates resulting from the deconstruction of lignocellulosic biomass. Here, we investigated the role of the XylR transcription factor in the length of the lag phases when the bacterium Escherichia coli needs to adapt from glucose- to xylose-based growth. First, a variety of lag times were observed when different strains of E. coli were switched from glucose to xylose. These lag times were shown to be controlled by XylR availability in the cells with no further effect on the growth rate on xylose. XylR titration provoked long lag times demonstrated to result from phenotypic heterogeneity during the switch from glucose to xylose, with a subpopulation unable to resume exponential growth, whereas the other subpopulation grew exponentially on xylose. A stochastic model was then constructed based on the assumption that XylR availability influences the probability of individual cells to switch to xylose growth. The model was used to understand how XylR behaves as a molecular switch determining the bistability set-up. This work shows that the length of lag phases in E. coli is controllable and reinforces the role of stochastic mechanism in cellular adaptation, paving the way for new strategies for the better use of sustainable carbon sources in bioeconomy.

Bacterial Vivisection: How Fluorescence-Based Imaging Techniques Shed a Light on the Inner Workings of Bacteria

The rise in fluorescence-based imaging techniques over the past 3 decades has improved the ability of researchers to scrutinize live cell biology at increased spatial and temporal resolution. In microbiology, these real-time vivisections structurally changed the view on the bacterial cell away from the "watery bag of enzymes" paradigm toward the perspective that these organisms are as complex as their eukaryotic counterparts. Capitalizing on the enormous potential of (time-lapse) fluorescence microscopy and the ever-extending pallet of corresponding probes, initial breakthroughs were made in unraveling the localization of proteins and monitoring real-time gene expression. However, later it became clear that the potential of this technique extends much further, paving the way for a focus-shift from observing single events within bacterial cells or populations to obtaining a more global picture at the intra- and intercellular level. In this review, we outline the current state of the art in fluorescence-based vivisection of bacteria and provide an overview of important case studies to exemplify how to use or combine different strategies to gain detailed information on the cell's physiology. The manuscript therefore consists of two separate (but interconnected) parts that can be read and consulted individually. The first part focuses on the fluorescent probe pallet and provides a perspective on modern methodologies for microscopy using these tools. The second section of the review takes the reader on a tour through the bacterial cell from cytoplasm to outer shell, describing strategies and methods to highlight architectural features and overall dynamics within cells.

In Vitro Studies of Persister Cells

Many bacterial pathogens can permanently colonize their host and establish either chronic or recurrent infections that the immune system and antimicrobial therapies fail to eradicate. Antibiotic persisters (persister cells) are believed to be among the factors that make these infections challenging. Persisters are subpopulations of bacteria which survive treatment with bactericidal antibiotics in otherwise antibiotic-sensitive cultures and were extensively studied in a hope to discover the mechanisms that cause treatment failures in chronically infected patients; however, most of these studies were conducted in the test tube. Research into antibiotic persistence has uncovered large intrapopulation heterogeneity of bacterial growth and regrowth but has not identified essential, dedicated molecular mechanisms of antibiotic persistence. Diverse factors and stresses that inhibit bacterial growth reduce killing of the bulk population and may also increase the persister subpopulation, implying that an array of mechanisms are present. Hopefully, further studies under conditions that simulate the key aspects of persistent infections will lead to identifying target mechanisms for effective therapeutic solutions.

Escherichia coli with a Tunable Point Mutation Rate for Evolution Experiments

The mutation rate and mutations' effects on fitness are crucial to evolution. Mutation rates are under selection due to linkage between mutation rate modifiers and mutations' effects on fitness. The linkage between a higher mutation rate and more beneficial mutations selects for higher mutation rates, while the linkage between a higher mutation rate and more deleterious mutations selects for lower mutation rates. The net direction of selection on mutations rates depends on the fitness landscape, and a great deal of work has elucidated the fitness landscapes of mutations. However, tests of the effect of varying a mutation rate on evolution in a single organism in a single environment have been difficult. This has been studied using strains of antimutators and mutators, but these strains may differ in additional ways and typically do not allow for continuous variation of the mutation rate. To help investigate the effects of the mutation rate on evolution, we have genetically engineered a strain of Escherichia coli with a point mutation rate that can be smoothly varied over two orders of magnitude. We did this by engineering a strain with inducible control of the mismatch repair proteins MutH and MutL. We used this strain in an approximately 350 generation evolution experiment with controlled variation of the mutation rate. We confirmed the construct and the mutation rate were stable over this time. Sequencing evolved strains revealed a higher number of single nucleotide polymorphisms at higher mutations rates, likely due to either the beneficial effects of these mutations or their linkage to beneficial mutations.

Dividing subpopulation of Escherichia coli in stationary phase

The bacterial growth cycle contains different phases: after the growth substrate is exhausted or the toxic waste products accumulate the growth stops. In this non-growing culture the number of colony forming bacteria remains constant or starts to decrease. It has been shown that during prolonged incubation there is constant growth and death of bacteria and certain mutant populations take over the culture. Here we show that the dynamic cell division and death balance can be obtained even before the appearance of mutants. The possible presence of different subpopulation should be considered when analyzing physiological states of bacterial cultures.

Muropeptides Stimulate Growth Resumption from Stationary Phase in Escherichia coli

When nutrients run out, bacteria enter a dormant metabolic state. This low or undetectable metabolic activity helps bacteria to preserve their scant reserves for the future needs, yet it also diminishes their ability to scan the environment for new growth-promoting substrates. However, neighboring microbial growth is a reliable indicator of a favorable environment and can thus serve as a cue for exiting dormancy. Here we report that for Escherichia coli and Pseudomonas aeruginosa this cue is provided by the basic peptidoglycan unit (i.e. muropeptide). We show that several forms of muropeptides from a variety of bacterial species can stimulate growth resumption of dormant cells and the sugar – peptide bond is crucial for this activity. These results, together with previous research that identifies muropeptides as a germination signal for bacterial spores, and their detection by mammalian immune cells, show that muropeptides are a universal cue for bacterial growth.

Heterogeneous Timing of Gene Induction as a Regulation Strategy

In response to environmental changes, cells often adapt by up-regulating genes to synthesize proteins that generate a benefit in the new environment. Several such cases of gene induction have been reported where the timing was heterogeneous, with some cells responding early and others responding late, although the microbial population was genetically homogeneous and the environment was well mixed. Here, we explore under which conditions heterogeneous timing of gene induction could be advantageous for the population as a whole. We base our study on a mathematical model that accounts for the cost of protein synthesis in terms of resources, which cells must provide immediately, whereas the associated benefit accumulates only slowly over the protein lifetime. Due to this delayed benefit, gene induction can be a risky investment, if resources are scarce and the environment fluctuates rapidly and unpredictably. Unprofitable gene induction then depletes the remaining limiting resource needed for maintenance of cell viability. We show that whenever gene induction is associated with a transient risk but beneficial in the long run, the stochastic timing of gene induction maximizes the reproductive success of a population. In particular, in an environment of stochastic periods of famine and feast, an optimum emerges from a trade-off between short-term growth, favoring rapid and homogeneous responses, and long-term survival, favoring a broadly heterogeneous response. Our analysis suggests that the optimal variability of induction times is just as large as the time required for the amortization of the initial investment into protein synthesis.

Comparison of Starvation-Induced Persister Cells with Antibiotic-Induced Persister Cells

The phenotypic heterogeneity in a large population arises because of fluctuation in microenvironments and stochastic gene expressions. In this report, we isolated two types of persistent sub-populations of Vibrio cholerae, one triggered by starvation and another by antibiotics. We characterised starvation-induced (E-cells) and antibiotic-induced (P-cell) persister cells for stress tolerance, colony morphology and toxin gene expressions. Both the sub-populations differ with respect to morphology, temperature tolerance and oxidative stress tolerance. The E-cells were smaller than the P-cells and formed tiny colonies (1-2 mm). The E-cells were more sensitive to heat and oxidative stress compared with P-cells. The up-regulated genes of P-cells include, genes of antioxidant enzymes (>5 fold), cholera toxin (>26 fold) and toxin: antitoxin protein hipA (>100 fold). Upon nutrient up-shift, the E-cells recovered after lag time of 6 h. However, such lag extension was not visible during P-cell recovery, suggesting that P-cell physiology is more akin to normal cells than E-cells. This is the first comparative report on the two different persister sub-populations of V. cholerae. The E-cells and P-cells are similar regarding antibiotic tolerance. However, the sub-populations differ significantly in stress tolerance and other phenotypes studied.

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.

Ribosome Provisioning Activates a Bistable Switch Coupled to Fast Exit from Stationary Phase

Observations of bacteria at the single-cell level have revealed many instances of phenotypic heterogeneity within otherwise clonal populations, but the selective causes, molecular bases, and broader ecological relevance remain poorly understood. In an earlier experiment in which the bacterium Pseudomonas fluorescens SBW25 was propagated under a selective regime that mimicked the host immune response, a genotype evolved that stochastically switched between capsulation states. The genetic cause was a mutation in carB that decreased the pyrimidine pool (and growth rate), lowering the activation threshold of a preexisting but hitherto unrecognized phenotypic switch. Genetic components surrounding bifurcation of UTP flux toward DNA/RNA or UDP-glucose (a precursor of colanic acid forming the capsules) were implicated as key components. Extending these molecular analyses-and based on a combination of genetics, transcriptomics, biochemistry, and mathematical modeling-we show that pyrimidine limitation triggers an increase in ribosome biosynthesis and that switching is caused by competition between ribosomes and CsrA/RsmA proteins for the mRNA transcript of a positively autoregulated activator of colanic acid biosynthesis. We additionally show that in the ancestral bacterium the switch is part of a program that determines stochastic entry into a semiquiescent capsulated state, ensures that such cells are provisioned with excess ribosomes, and enables provisioned cells to exit rapidly from stationary phase under permissive conditions.

Single-cell imaging and characterization of Escherichia coli persister cells to ofloxacin in exponential cultures

Bacterial persistence refers to the capacity of small subpopulations within clonal populations to tolerate antibiotics. Persisters are thought to originate from dormant cells in which antibiotic targets are less active and cannot be corrupted. Here, we report that in exponentially growing cultures, ofloxacin persisters originate from metabolically active cells: These cells are dividing before the addition of ofloxacin and do endure DNA damages during the treatment, similar to their nonpersister siblings. We observed that growth rate, DNA content, and SOS induction vary among persisters, as in the bulk of the population and therefore do not constitute predictive markers for persistence. Persister cells typically form long polynucleoid filaments and reach maximum SOS induction after removal of ofloxacin. Eventually, cell division resumes, giving rise to a new population. Our findings highlight the heterogeneity of persister cells and therefore the need to analyze these low-frequency phenotypic variants on a case-by-case basis at the single-cell level.

Klebsiella and Providencia emerge as lone survivors following long-term starvation of oral microbiota

It is well-understood that many bacteria have evolved to survive catastrophic events using a variety of mechanisms, which include expression of stress-response genes, quiescence, necrotrophy, and metabolic advantages obtained through mutation. However, the dynamics of individuals leveraging these abilities to gain a competitive advantage in an ecologically complex setting remain unstudied. In this study, we observed the saliva microbiome throughout the ecological perturbation of long-term starvation, allowing only the species best equipped to access and use the limited resources to survive. During the first several days, the community underwent a death phase that resulted in a ∼50-100-fold reduction in the number of viable cells. Interestingly, after this death phase, only three species, Klebsiella pneumoniae, Klebsiella oxytoca, and Providencia alcalifaciens, all members of the family Enterobacteriaceae, appeared to be transcriptionally active and recoverable. Klebsiella are significant human pathogens, frequently resistant to multiple antibiotics, and recently, ectopic colonization of the gut by oral Klebsiella was documented to induce dysbiosis and inflammation. MetaOmics analyses provided several leads for further investigation regarding the ecological success of the Enterobacteriaceae. The isolates accumulated single nucleotide polymorphisms in known growth advantage in stationary phase alleles and produced natural products closely resembling antimicrobial cyclic depsipeptides. The results presented in this study suggest that pathogenic Enterobacteriaceae persist much longer than their more benign neighbors in the salivary microbiome when faced with starvation. This is particularly significant, given that hospital surfaces contaminated with oral fluids, especially sinks and drains, are well-established sources of outbreaks of drug-resistant Enterobacteriaceae.

Indole Pulse Signalling Regulates the Cytoplasmic pH of E. coli in a Memory-Like Manner

Bacterial cells are critically dependent upon pH regulation. Here we demonstrate that indole plays a critical role in the regulation of the cytoplasmic pH of Escherichia coli. Indole is an aromatic molecule with diverse signalling roles. Two modes of indole signalling have been described: persistent and pulse signalling. The latter is illustrated by the brief but intense elevation of intracellular indole during stationary phase entry. We show that under conditions permitting indole production, cells maintain their cytoplasmic pH at 7.2. In contrast, under conditions where no indole is produced, the cytoplasmic pH is near 7.8. We demonstrate that pH regulation results from pulse, rather than persistent, indole signalling. Furthermore, we illustrate that the relevant property of indole in this context is its ability to conduct protons across the cytoplasmic membrane. Additionally, we show that the effect of the indole pulse that occurs normally during stationary phase entry in rich medium remains as a "memory" to maintain the cytoplasmic pH until entry into the next stationary phase. The indole-mediated reduction in cytoplasmic pH may explain why indole provides E. coli with a degree of protection against stresses, including some bactericidal antibiotics.

Medium chain unsaturated fatty acid ethyl esters inhibit persister formation of Escherichia coli via antitoxin HipB

Persisters represent a small bacterial population that is dormant and that survives under antibiotic treatment without experiencing genetic adaptation. Persisters are also considered one of the major reasons for recalcitrant chronic bacterial infections. Although several mechanisms of persister formation have been proposed, it is not clear how cells enter the dormant state in the presence of antibiotics or how persister cell formation can be effectively controlled. A fatty acid compound, cis-2-decenoic acid, was reported to decrease persister formation as well as revert the dormant cells to a metabolically active state. We reasoned that some fatty acid compounds may be effective in controlling bacterial persistence because they are known to benefit host immune systems. This study investigated persister cell formation by pathogens that were exposed to nine fatty acid compounds during antibiotic treatment. We found that three medium chain unsaturated fatty acid ethyl esters (ethyl trans-2-decenoate, ethyl trans-2-octenoate, and ethyl cis-4-decenoate) decreased the level of Escherichia coli persister formation up to 110-fold when cells were exposed to ciprofloxacin or ampicillin antibiotics. RNA sequencing analysis and gene deletion persister studies elucidated that these fatty acids inhibit bacterial persistence by regulating antitoxin HipB. A similar persister cell reduction was observed for pathogenic E. coli EDL933, Pseudomonas aeruginosa PAO1, and Serratia marcescens ICU2-4 strains. This study demonstrates that fatty acid ethyl esters can be used to disrupt bacterial dormancy to combat persistent infectious diseases.

A Dynamic Model of Resource Allocation in Response to the Presence of a Synthetic Construct

Introducing synthetic constructs into bacteria often carries a burden that leads to reduced fitness and selective pressure for organisms to mutate their constructs and hence to a reduced functional lifetime. Understanding burden requires suitable methods for accurate measurement and quantification. We develop a dynamic growth model from physiologically relevant first-principles that allows parameters relevant to burden to be extracted from standard growth curves. We test several possibilities for the response of a bacterium to a new environment in terms of resource allocation. We find that burden manifests in the time taken to respond to new conditions as well as the rate of growth in exponential phase. Furthermore, we see that the presence of a synthetic construct hastens the reduction of ribosomes when approaching stationary phase, altering memory effects from previous periods of growth.

Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations

The MazF toxin sequence-specifically cleaves single-stranded RNA upon various stressful conditions, and it is activated as a part of the mazEF toxin-antitoxin module in Escherichia coli. Although autoregulation of mazEF expression through the MazE antitoxin-dependent transcriptional repression has been biochemically characterized, less is known about post-transcriptional autoregulation, as well as how both of these autoregulatory features affect growth of single cells during conditions that promote MazF production. Here, we demonstrate post-transcriptional autoregulation of mazF expression dynamics by MazF cleaving its own transcript. Single-cell analyses of bacterial populations during ectopic MazF production indicated that two-level autoregulation of mazEF expression influences cell-to-cell growth rate heterogeneity. The increase in growth rate heterogeneity is governed by the MazE antitoxin, and tuned by the MazF-dependent mazF mRNA cleavage. Also, both autoregulatory features grant rapid exit from the stress caused by mazF overexpression. Time-lapse microscopy revealed that MazF-mediated cleavage of mazF mRNA leads to increased temporal variability in length of individual cells during ectopic mazF overexpression, as explained by a stochastic model indicating that mazEF mRNA cleavage underlies temporal fluctuations in MazF levels during stress.

Population heterogeneity in microbial bioprocesses: origin, analysis, mechanisms, and future perspectives

Population heterogeneity is omnipresent in all bioprocesses even in homogenous environments. Its origin, however, is only so well understood that potential strategies like bet-hedging, noise in gene expression and division of labour that lead to population heterogeneity can be derived from experimental studies simulating the dynamics in industrial scale bioprocesses. This review aims at summarizing the current state of the different parts of single cell studies in bioprocesses. This includes setups to visualize different phenotypes of single cells, computational approaches connecting single cell physiology with environmental influence and special cultivation setups like scale-down reactors that have been proven to be useful to simulate large-scale conditions. A step in between investigation of populations and single cells is studying subpopulations with distinct properties that differ from the rest of the population with sub-omics methods which are also presented here. Moreover, the current knowledge about population heterogeneity in bioprocesses is summarized for relevant industrial production hosts and mixed cultures, as they provide the unique opportunity to distribute metabolic burden and optimize production processes in a way that is impossible in traditional monocultures. In the end, approaches to explain the underlying mechanism of population heterogeneity and the evidences found to support each hypothesis are presented. For instance, population heterogeneity serving as a bet-hedging strategy that is used as coordinated action against bioprocess-related stresses while at the same time spreading the risk between individual cells as it ensures the survival of least a part of the population in any environment the cells encounter.