Bet-hedging during bacterial diauxic shift

When Phase Contrast Fails: ChainTracer and NucTracer, Two ImageJ Methods for Semi-Automated Single Cell Analysis Using Membrane or DNA Staining

Within bacterial populations, genetically identical cells often behave differently. Single-cell measurement methods are required to observe this heterogeneity. Flow cytometry and fluorescence light microscopy are the primary methods to do this. However, flow cytometry requires reasonably strong fluorescence signals and is impractical when bacteria grow in cell chains. Therefore fluorescence light microscopy is often used to measure population heterogeneity in bacteria. Automatic microscopy image analysis programs typically use phase contrast images to identify cells. However, many bacteria divide by forming a cross-wall that is not detectable by phase contrast. We have developed ‘ChainTracer’, a method based on the ImageJ plugin ObjectJ. It can automatically identify individual cells stained by fluorescent membrane dyes, and measure fluorescence intensity, chain length, cell length, and cell diameter. As a complementary analysis method we developed 'NucTracer', which uses DAPI stained nucleoids as a proxy for single cells. The latter method is especially useful when dealing with crowded images. The methods were tested with Bacillus subtilis and Lactococcus lactis cells expressing a GFP-reporter. In conclusion, ChainTracer and NucTracer are useful single cell measurement methods when bacterial cells are difficult to distinguish with phase contrast.

Divergent MLS1 Promoters Lie on a Fitness Plateau for Gene Expression

Qualitative patterns of gene activation and repression are often conserved despite an abundance of quantitative variation in expression levels within and between species. A major challenge to interpreting patterns of expression divergence is knowing which changes in gene expression affect fitness. To characterize the fitness effects of gene expression divergence, we placed orthologous promoters from eight yeast species upstream of malate synthase (MLS1) in Saccharomyces cerevisiae. As expected, we found these promoters varied in their expression level under activated and repressed conditions as well as in their dynamic response following loss of glucose repression. Despite these differences, only a single promoter driving near basal levels of expression caused a detectable loss of fitness. We conclude that the MLS1 promoter lies on a fitness plateau whereby even large changes in gene expression can be tolerated without a substantial loss of fitness.

A synthetic growth switch based on controlled expression of RNA polymerase

The ability to control growth is essential for fundamental studies of bacterial physiology and biotechnological applications. We have engineered an Escherichia coli strain in which the transcription of a key component of the gene expression machinery, RNA polymerase, is under the control of an inducible promoter. By changing the inducer concentration in the medium, we can adjust the RNA polymerase concentration and thereby switch bacterial growth between zero and the maximal growth rate supported by the medium. We show that our synthetic growth switch functions in a medium-independent and reversible way, and we provide evidence that the switching phenotype arises from the ultrasensitive response of the growth rate to the concentration of RNA polymerase. We present an application of the growth switch in which both the wild-type E. coli strain and our modified strain are endowed with the capacity to produce glycerol when growing on glucose. Cells in which growth has been switched off continue to be metabolically active and harness the energy gain to produce glycerol at a twofold higher yield than in cells with natural control of RNA polymerase expression. Remarkably, without any further optimization, the improved yield is close to the theoretical maximum computed from a flux balance model of E. coli metabolism. The proposed synthetic growth switch is a promising tool for gaining a better understanding of bacterial physiology and for applications in synthetic biology and biotechnology.

Rethinking the Hierarchy of Sugar Utilization in Bacteria

Bacteria are known to consume some sugars over others, although recent work reported by Koirala and colleagues in this issue of the Journal of Bacteriology (S. Koirala, X. Wang, and C. V. Rao, J Bacteriol 198:386-393, 2016, http://dx.doi.org/10.1128/JB.00709-15) revealed that individual cells do not necessarily follow this hierarchy. By studying the preferential consumption of l-arabinose over d-xylose in Escherichia coli, those authors found that subpopulations consume one, the other, or both sugars through cross-repression between utilization pathways. Their findings challenge classic assertions about established hierarchies and can guide efforts to engineer the simultaneous utilization of multiple sugars.

Gene Expression Variability Underlies Adaptive Resistance in Phenotypically Heterogeneous Bacterial Populations

The root cause of the antibiotic resistance crisis is the ability of bacteria to evolve resistance to a multitude of antibiotics and other environmental toxins. The regulation of adaptation is difficult to pinpoint due to extensive phenotypic heterogeneity arising during evolution. Here, we investigate the mechanisms underlying general bacterial adaptation by evolving wild-type Escherichia coli populations to dissimilar chemical toxins. We demonstrate the presence of extensive inter- and intrapopulation phenotypic heterogeneity across adapted populations in multiple traits, including minimum inhibitory concentration, growth rate, and lag time. To search for a common response across the heterogeneous adapted populations, we measured gene expression in three stress-response networks: the mar regulon, the general stress response, and the SOS response. While few genes were differentially expressed, clustering revealed that interpopulation gene expression variability in adapted populations was distinct from that of unadapted populations. Notably, we observed both increases and decreases in gene expression variability upon adaptation. Sequencing select genes revealed that the observed gene expression trends are not necessarily attributable to genetic changes. To further explore the connection between gene expression variability and adaptation, we propagated single-gene knockout and CRISPR (clustered regularly interspaced short palindromic repeats) interference strains and quantified impact on adaptation to antibiotics. We identified significant correlations that suggest genes with low expression variability have greater impact on adaptation. This study provides evidence that gene expression variability can be used as an indicator of bacterial adaptive resistance, even in the face of the pervasive phenotypic heterogeneity underlying adaptation.

[Randomness and cell fate]

Thermal fluctuations at the molecular scale cause random fluctuations of gene expression, which, in association with differentiation circuits, can lead to phenotypic diversification in cell populations. In this synthesis article, we detail the mechanisms that generate this diversification and illustrate their consequences in various organisms. In bacteria, random phenotypic diversification allows to anticipate environmental changes that are otherwise unpredictable, in particular during metabolic transitions and stress responses, for example inducing a transient form of antibiotic resistance. In multi-cellular organisms, similar mechanisms allow the maintenance of healthy tissues, such as intestinal crypts, epidermis and retina, but also seem to play a role in establishment and renewal of tumoral heterogeneity.

Integrating Kinetic Model of E. coli with Genome Scale Metabolic Fluxes Overcomes Its Open System Problem and Reveals Bistability in Central Metabolism

An understanding of the dynamics of the metabolic profile of a bacterial cell is sought from a dynamical systems analysis of kinetic models. This modelling formalism relies on a deterministic mathematical description of enzyme kinetics and their metabolite regulation. However, it is severely impeded by the lack of available kinetic information, limiting the size of the system that can be modelled. Furthermore, the subsystem of the metabolic network whose dynamics can be modelled is faced with three problems: how to parameterize the model with mostly incomplete steady state data, how to close what is now an inherently open system, and how to account for the impact on growth. In this study we address these challenges of kinetic modelling by capitalizing on multi-‘omics’ steady state data and a genome-scale metabolic network model. We use these to generate parameters that integrate knowledge embedded in the genome-scale metabolic network model, into the most comprehensive kinetic model of the central carbon metabolism of E. coli realized to date. As an application, we performed a dynamical systems analysis of the resulting enriched model. This revealed bistability of the central carbon metabolism and thus its potential to express two distinct metabolic states. Furthermore, since our model-informing technique ensures both stable states are constrained by the same thermodynamically feasible steady state growth rate, the ensuing bistability represents a temporal coexistence of the two states, and by extension, reveals the emergence of a phenotypically heterogeneous population.

Fluorescent Reporter Libraries as Useful Tools for Optimizing Microbial Cell Factories: A Review of the Current Methods and Applications

The use of genetically encoded fluorescent reporters allows speeding up the initial optimization steps of microbial bioprocesses. These reporters can be used for determining the expression level of a particular promoter, not only the synthesis of a specific protein but also the content of intracellular metabolites. The level of protein/metabolite is thus proportional to a fluorescence signal. By this way, mean expression profiles of protein/metabolites can be determined non-invasively at a high-throughput rate, allowing the rapid identification of the best producers. Actually, different kinds of reporter systems are available, as well as specific cultivation devices allowing the on-line recording of the fluorescent signal. Cell-to-cell variability is another important phenomenon that can be integrated into the screening procedures for the selection of more efficient microbial cell factories.

Acetate Exposure Determines the Diauxic Behavior of Escherichia coli during the Glucose-Acetate Transition

Growth of Escherichia coli on glucose in batch culture is accompanied by the excretion of acetate, which is consumed by the cells when glucose is exhausted. This glucose-acetate transition is classically described as a diauxie (two successive growth stages). Here, we investigated the physiological and metabolic properties of cells after glucose exhaustion through the analysis of growth parameters and gene expression. We found that E. coli cells grown on glucose in batch culture produce acetate and consume it after glucose exhaustion but do not grow on acetate. Acetate is catabolized, but key anabolic genes--such as the genes encoding enzymes of the glyoxylate shunt--are not upregulated, hence preventing growth. Both the induction of the latter anabolic genes and growth were observed only after prolonged exposure to low concentrations of acetate and could be accelerated by high acetate concentrations. We postulate that such decoupling between acetate catabolism and acetate anabolism might be an advantage for the survival of E. coli in the ever-changing environment of the intestine.

IMPORTANCE

The glucose-acetate transition is a valuable experimental model for comprehensive investigations of metabolic adaptation and a current paradigm for developing modeling approaches in systems microbiology. Yet, the work reported in our paper demonstrates that the metabolic behavior of Escherichia coli during the glucose-acetate transition is much more complex than what has been reported so far. A decoupling between acetate catabolism and acetate anabolism was observed after glucose exhaustion, which has not been reported previously. This phenomenon could represent a strategy for optimal utilization of carbon resources during colonization and persistence of E. coli in the gut and is also of significant interest for biotechnological applications.

Timing and Variability of Galactose Metabolic Gene Activation Depend on the Rate of Environmental Change

Modulation of gene network activity allows cells to respond to changes in environmental conditions. For example, the galactose utilization network in Saccharomyces cerevisiae is activated by the presence of galactose but repressed by glucose. If both sugars are present, the yeast will first metabolize glucose, depleting it from the extracellular environment. Upon depletion of glucose, the genes encoding galactose metabolic proteins will activate. Here, we show that the rate at which glucose levels are depleted determines the timing and variability of galactose gene activation. Paradoxically, we find that Gal1p, an enzyme needed for galactose metabolism, accumulates more quickly if glucose is depleted slowly rather than taken away quickly. Furthermore, the variability of induction times in individual cells depends non-monotonically on the rate of glucose depletion and exhibits a minimum at intermediate depletion rates. Our mathematical modeling suggests that the dynamics of the metabolic transition from glucose to galactose are responsible for the variability in galactose gene activation. These findings demonstrate that environmental dynamics can determine the phenotypic outcome at both the single-cell and population levels.

Understanding how cells respond to environmental changes is a fundamental question in biology. Such responses are governed by interactions between genes, proteins and other cellular machinery. However, even the responses of genetically identical cells are not identical. Our aim was to examine the origins of this variability using the galactose metabolic network in the baker yeast Saccharomyces cerevisiae. This metabolic network allows yeast to consume galactose once its preferred carbon source, glucose, is depleted. We used microfluidic devices and time-lapse fluorescence microscopy to observe how individual cells respond as glucose is removed from their environment at different rates. We found that the activation of the galactose metabolic network depends on the rate of depletion. Surprisingly, cells start to consume galactose faster when glucose is depleted slowly rather than removed quickly. Furthermore, genetically identical cells can exhibit remarkably different rates of galactose consumption. We provide a simple mathematical model that explains these different observations. These results suggest that dynamic changes of environmental conditions can affect the behavior of both individual cells and the whole population.

Posttranslational regulation of microbial metabolism

Fluxes in microbial metabolism are controlled by various regulatory layers that alter abundance or activity of metabolic enzymes. Recent studies suggest a division of labor between these layers: transcriptional regulation mostly controls the allocation of protein resources, passive flux regulation by enzyme saturation and thermodynamics allows rapid responses at the expense of higher protein cost, and posttranslational regulation is utilized by cells to directly take control of metabolic decisions. We present recent advances in elucidating the role of these regulatory layers, focusing on posttranslational modifications and allosteric interactions. As the systematic mapping of posttranslational regulatory events has now become possible, the next challenge is to identify those regulatory events that are functionally relevant under a given condition.

Phenotypic heterogeneity in metabolic traits among single cells of a rare bacterial species in its natural environment quantified with a combination of flow cell sorting and NanoSIMS

Populations of genetically identical microorganisms residing in the same environment can display marked variability in their phenotypic traits; this phenomenon is termed phenotypic heterogeneity. The relevance of such heterogeneity in natural habitats is unknown, because phenotypic characterization of a sufficient number of single cells of the same species in complex microbial communities is technically difficult. We report a procedure that allows to measure phenotypic heterogeneity in bacterial populations from natural environments, and use it to analyze N₂ and CO₂ fixation of single cells of the green sulfur bacterium Chlorobium phaeobacteroides from the meromictic lake Lago di Cadagno. We incubated lake water with ¹⁵N₂ and ¹³CO₂ under in situ conditions with and without NH₄⁺. Subsequently, we used flow cell sorting with auto-fluorescence gating based on a pure culture isolate to concentrate C. phaeobacteroides from its natural abundance of 0.2% to now 26.5% of total bacteria. C. phaeobacteroides cells were identified using catalyzed-reporter deposition fluorescence in situ hybridization (CARD-FISH) targeting the 16S rRNA in the sorted population with a species-specific probe. In a last step, we used nanometer-scale secondary ion mass spectrometry to measure the incorporation ¹⁵N and ¹³C stable isotopes in more than 252 cells. We found that C. phaeobacteroides fixes N₂ in the absence of NH₄⁺, but not in the presence of NH₄⁺ as has previously been suggested. N₂ and CO₂ fixation were heterogeneous among cells and positively correlated indicating that N₂ and CO₂ fixation activity interact and positively facilitate each other in individual cells. However, because CARD-FISH identification cannot detect genetic variability among cells of the same species, we cannot exclude genetic variability as a source for phenotypic heterogeneity in this natural population. Our study demonstrates the technical feasibility of measuring phenotypic heterogeneity in a rare bacterial species in its natural habitat, thus opening the door to study the occurrence and relevance of phenotypic heterogeneity in nature.

(p)ppGpp, a Small Nucleotide Regulator, Directs the Metabolic Fate of Glucose in Vibrio cholerae

When V. cholerae encounters nutritional stress, it activates (p)ppGpp-mediated stringent response. The genes relA and relV are involved in the production of (p)ppGpp, whereas the spoT gene encodes an enzyme that hydrolyzes it. Herein, we show that the bacterial capability to produce (p)ppGpp plays an essential role in glucose metabolism. The V. cholerae mutants defective in (p)ppGpp production (i.e. ΔrelAΔrelV and ΔrelAΔrelVΔspoT mutants) lost their viability because of uncontrolled production of organic acids, when grown with extra glucose. In contrast, the ΔrelAΔspoT mutant, a (p)ppGpp overproducer strain, exhibited better growth in the presence of the same glucose concentration. An RNA sequencing analysis demonstrated that transcriptions of genes consisting of an operon for acetoin biosynthesis were markedly elevated in N16961, a seventh pandemic O1 strain, but not in its (p)ppGpp(0) mutant during glucose-stimulated growth. Transposon insertion in acetoin biosynthesis gene cluster resulted in glucose-induced loss of viability of the ΔrelAΔspoT mutant, further suggesting the crucial role of acetoin production in balanced growth under glucose-rich environments. Additional deletion of the aphA gene, encoding a negative regulator for acetoin production, failed to rescue the (p)ppGpp(0) mutant from the defective glucose-mediated growth, suggesting that (p)ppGpp-mediated acetoin production occurs independent of the presence of AphA. Overall, our results reveal that (p)ppGpp, in addition to its well known role as a stringent response mediator, positively regulates acetoin production that contributes to the successful glucose metabolism and consequently the proliferation of V. cholerae cells under a glucose-rich environment, a condition that may mimic the human intestine.

The glycerol-dependent metabolic persistence of Pseudomonas putida KT2440 reflects the regulatory logic of the GlpR repressor

The growth of the soil bacterium Pseudomonas putida KT2440 on glycerol as the sole carbon source is characterized by a prolonged lag phase, not observed with other carbon substrates. We examined the bacterial growth in glycerol cultures while monitoring the metabolic activity of individual cells. Fluorescence microscopy and flow cytometry, as well as the analysis of the temporal start of growth in single-cell cultures, revealed that adoption of a glycerol-metabolizing regime was not the result of a gradual change in the whole population but rather reflected a time-dependent bimodal switch between metabolically inactive (i.e., nongrowing) and fully active (i.e., growing) bacteria. A transcriptional Φ(glpD-gfp) fusion (a proxy of the glycerol-3-phosphate [G3P] dehydrogenase activity) linked the macroscopic phenotype to the expression of the glp genes. Either deleting glpR (encoding the G3P-responsive transcriptional repressor that controls the expression of the glpFKRD gene cluster) or altering G3P formation (by overexpressing glpK, encoding glycerol kinase) abolished the bimodal glpD expression. These manipulations eliminated the stochastic growth start by shortening the otherwise long lag phase. Provision of glpR in trans restored the phenotypes lost in the ΔglpR mutant. The prolonged nongrowth regime of P. putida on glycerol could thus be traced to the regulatory device controlling the transcription of the glp genes. Since the physiological agonist of GlpR is G3P, the arrangement of metabolic and regulatory components at this checkpoint merges a positive feedback loop with a nonlinear transcriptional response, a layout fostering the observed time-dependent shift between two alternative physiological states.

Phenotypic variation is a widespread attribute of prokaryotes that leads, inter alia, to the emergence of persistent bacteria, i.e., live but nongrowing members within a genetically clonal population. Persistence allows a fraction of cells to avoid the killing caused by conditions or agents that destroy most growing bacteria (e.g., some antibiotics). Known molecular mechanisms underlying the phenomenon include genetic changes, epigenetic variations, and feedback-based multistability. We show that a prolonged nongrowing state of the bacterial population can be brought about by a distinct regulatory architecture of metabolic genes when cells face specific nutrients (e.g., glycerol). Pseudomonas putida may have adopted the resulting carbon source-dependent metabolic bet hedging as an advantageous trait for exploring new chemical and nutritional landscapes. Defeating such naturally occurring adaptive features of environmental bacteria is instrumental in improving the performance of these microorganisms as whole-cell catalysts in a bioreactor setup.

Stochasticity enhances the gaining of bet-hedging strategies in contact-process-like dynamics

In biology and ecology, individuals or communities of individuals living in unpredictable environments often alternate between different evolutionary strategies to spread and reduce risks. Such behavior is commonly referred to as "bet-hedging." Long-term survival probabilities and population sizes can be much enhanced by exploiting such hybrid strategies. Here, we study the simplest possible birth-death stochastic model in which individuals can choose among a poor but safe strategy, a better but risky alternative, or a combination of both. We show analytically and computationally that the benefits derived from bet-hedging strategies are much stronger for higher environmental variabilities (large external noise) and/or for small spatial dimensions (large intrinsic noise). These circumstances are typically encountered by living systems, thus providing us with a possible justification for the ubiquitousness of bet-hedging in nature.

Shifting sugars and shifting paradigms

No organism lives in a constant environment. Based on classical studies in molecular biology, many have viewed microbes as following strict rules for shifting their metabolic activities when prevailing conditions change. For example, students learn that the bacterium Escherichia coli makes proteins for digesting lactose only when lactose is available and glucose, a better sugar, is not. However, recent studies, including three PLOS Biology papers examining sugar utilization in the budding yeast Saccharomyces cerevisiae, show that considerable heterogeneity in response to complex environments exists within and between populations. These results join similar recent results in other organisms that suggest that microbial populations anticipate predictable environmental changes and hedge their bets against unpredictable ones. The classical view therefore represents but one special case in a range of evolutionary adaptations to environmental changes that all organisms face.

This Primer explores three recent PLOS Biology papers that increase our understanding of how microbes respond optimally to the changing availability of nutrients in their environment. Read the Research Articles.

Microbial individuality: how single-cell heterogeneity enables population level strategies

Much of our knowledge of microbial life is only a description of average population behaviours, but modern technologies provide a more inclusive view and reveal that microbes also have individuality. It is now acknowledged that isogenic cell-to-cell heterogeneity is common across organisms and across different biological processes. This heterogeneity can be regulated and functional, rather than just reflecting tolerance to noisy biochemistry. Here, we review recent advances in our understanding of microbial heterogeneity, with an emphasis on the pervasiveness of heterogeneity, the mechanisms that sustain it, and how heterogeneity enables collective function.

Classification of phenotypic subpopulations in isogenic bacterial cultures by triple promoter probing at single cell level

Phenotypic heterogeneity, defined as the unequal behavior of individuals in an isogenic population, is prevalent in microorganisms. It has a significant impact both on industrial bioprocesses and microbial ecology. We introduce a new versatile reporter system designed for simultaneous monitoring of the activities of three different promoters, where each promoter is fused to a dedicated fluorescent reporter gene (cerulean, mCherry, and mVenus). The compact 3.1 kb triple reporter cassette can either be carried on a replicating plasmid or integrated into the genome avoiding artifacts associated with variation in copy number of plasmid-borne reporter constructs. This construct was applied to monitor promoter activities related to quorum sensing (sinI promoter) and biosynthesis of the exopolysaccharide galactoglucan (wgeA promoter) at single cell level in colonies of the symbiotic nitrogen-fixing alpha-proteobacterium Sinorhizobium meliloti growing in a microfluidics system. The T5-promoter served as a constitutive and homogeneously active control promoter indicating cell viability. wgeA promoter activity was heterogeneous over the whole period of colony development, whereas sinI promoter activity passed through a phase of heterogeneity before becoming homogeneous at late stages. Although quorum sensing-dependent regulation is a major factor activating galactoglucan production, activities of both promoters did not correlate at single cell level. We developed a novel mathematical strategy for classification of the gene expression status in cell populations based on the increase in fluorescence over time in each individual. With respect to galactoglucan biosynthesis, cells in the population were classified into non-contributors, weak contributors, and strong contributors.

Natural variation in preparation for nutrient depletion reveals a cost-benefit tradeoff

Yeast can anticipate the depletion of a preferred nutrient by preemptively activating genes for alternative nutrients; the degree of this preparation varies across natural strains and is subject to a fitness tradeoff.

Maximizing growth and survival in the face of a complex, time-varying environment is a common problem for single-celled organisms in the wild. When offered two different sugars as carbon sources, microorganisms first consume the preferred sugar, then undergo a transient growth delay, the “diauxic lag,” while inducing genes to metabolize the less preferred sugar. This delay is commonly assumed to be an inevitable consequence of selection to maximize use of the preferred sugar. Contrary to this view, we found that many natural isolates of Saccharomyces cerevisiae display short or nonexistent diauxic lags when grown in mixtures of glucose (preferred) and galactose. These strains induce galactose utilization (GAL) genes hours before glucose exhaustion, thereby “preparing” for the transition from glucose to galactose metabolism. The extent of preparation varies across strains, and seems to be determined by the steady-state response of GAL genes to mixtures of glucose and galactose rather than by induction kinetics. Although early GAL gene induction gives strains a competitive advantage once glucose runs out, it comes at a cost while glucose is still present. Costs and benefits correlate with the degree of preparation: strains with higher expression of GAL genes prior to glucose exhaustion experience a larger upfront growth cost but also a shorter diauxic lag. Our results show that classical diauxic growth is only one extreme on a continuum of growth strategies constrained by a cost–benefit tradeoff. This type of continuum is likely to be common in nature, as similar tradeoffs can arise whenever cells evolve to use mixtures of nutrients.

When microorganisms encounter multiple sugars, they often consume a preferred sugar (such as glucose) before consuming alternative sugars (such as galactose). In experiments on laboratory strains of yeast, cells typically stop growing when the preferred sugar runs out, and start growing again only after taking time to turn on genes for alternative sugar utilization. This pause in growth, the “diauxic lag,” is a classic example of the ability of cells to make decisions based on environmental signals. Here we find, however, that when different natural yeast strains are grown in a mix of glucose and galactose, some strains do not exhibit a diauxic lag, or have a very short one. These “short lag” strains are able to turn on galactose utilization—or GAL—genes up to four hours before the glucose runs out, in effect preparing for the transition to galactose consumption. Although such preparation helps strains avoid the diauxic lag, it causes them to grow slower before glucose runs out, presumably because of the metabolic burden of expressing GAL genes. These observations suggest that microbes in nature may commonly face a tradeoff between growing efficiently on their preferred nutrient and being ready to consume alternative nutrients should the preferred nutrient run out.

Phenotypic bistability in Escherichia coli's central carbon metabolism

Fluctuations in intracellular molecule abundance can lead to distinct, coexisting phenotypes in isogenic populations. Although metabolism continuously adapts to unpredictable environmental changes, and although bistability was found in certain substrate-uptake pathways, central carbon metabolism is thought to operate deterministically. Here, we combine experiment and theory to demonstrate that a clonal Escherichia coli population splits into two stochastically generated phenotypic subpopulations after glucose-gluconeogenic substrate shifts. Most cells refrain from growth, entering a dormant persister state that manifests as a lag phase in the population growth curve. The subpopulation-generating mechanism resides at the metabolic core, overarches the metabolic and transcriptional networks, and only allows the growth of cells initially achieving sufficiently high gluconeogenic flux. Thus, central metabolism does not ensure the gluconeogenic growth of individual cells, but uses a population-level adaptation resulting in responsive diversification upon nutrient changes.