Single cell kinetics of phenotypic switching in the arabinose utilization system of E. coli

Single cell technologies for monitoring protein secretion heterogeneity

Cell-to-cell heterogeneity presents challenges across various fields, from biomedicine to bioproduction, where precise cellular responses are vital. While single cell technologies have significantly enhanced our understanding of population heterogeneity, the predominant focus has been on monitoring intracellular compounds. Recognizing the added complexity introduced by the secretion system, in this review, we first provide a systematic overview of the distinct steps necessary for driving protein secretion. We discuss the various sources of noise acting from the synthesized preprotein to the secretory protein released based on a Gram-positive cellular system as a model. We next explore the applicability of single cell technologies for monitoring protein secretion throughout these functional stages. We also emphasize the importance of applying these single cell technologies for monitoring protein secretion during bioproduction.

Microfluidic approaches in microbial ecology

Microbial life is at the heart of many diverse environments and regulates most natural processes, from the functioning of animal organs to the cycling of global carbon. Yet, the study of microbial ecology is often limited by challenges in visualizing microbial processes and replicating the environmental conditions under which they unfold. Microfluidics operates at the characteristic scale at which microorganisms live and perform their functions, thus allowing for the observation and quantification of behaviors such as growth, motility, and responses to external cues, often with greater detail than classical techniques. By enabling a high degree of control in space and time of environmental conditions such as nutrient gradients, pH levels, and fluid flow patterns, microfluidics further provides the opportunity to study microbial processes in conditions that mimic the natural settings harboring microbial life. In this review, we describe how recent applications of microfluidic systems to microbial ecology have enriched our understanding of microbial life and microbial communities. We highlight discoveries enabled by microfluidic approaches ranging from single-cell behaviors to the functioning of multi-cellular communities, and we indicate potential future opportunities to use microfluidics to further advance our understanding of microbial processes and their implications.

A versatile regulatory toolkit of arabinose-inducible artificial transcription factors for Enterobacteriaceae

The Gram-negative bacteria Salmonella enterica and Escherichia coli are important model organisms, powerful prokaryotic expression platforms for biotechnological applications, and pathogenic strains constitute major public health threats. To facilitate new approaches for research and biotechnological applications, we here develop a set of arabinose-inducible artificial transcription factors (ATFs) using CRISPR/dCas9 and Arabidopsis-derived DNA-binding proteins to control gene expression in E. coli and Salmonella over a wide inducer concentration range. The transcriptional output of the different ATFs, in particular when expressed in Salmonella rewired for arabinose catabolism, varies over a wide spectrum (up to 35-fold gene activation). As a proof-of-concept, we use the developed ATFs to engineer a Salmonella two-input biosensor strain, SALSOR 0.2 (SALmonella biosenSOR 0.2), which detects and quantifies alkaloid drugs through a measurable fluorescent output. Moreover, we use plant-derived ATFs to regulate β-carotene biosynthesis in E. coli, resulting in ~2.1-fold higher β-carotene production compared to expression of the biosynthesis pathway using a strong constitutive promoter.

Switching off: The phenotypic transition to the uninduced state of the lactose uptake pathway

The lactose uptake pathway of E. coli is a paradigmatic example of multistability in gene regulatory circuits. In the induced state of the lac pathway, the genes comprising the lac operon are transcribed, leading to the production of proteins that import and metabolize lactose. In the uninduced state, a stable repressor-DNA loop frequently blocks the transcription of the lac genes. Transitions from one phenotypic state to the other are driven by fluctuations, which arise from the random timing of the binding of ligands and proteins. This stochasticity affects transcription and translation, and ultimately molecular copy numbers. Our aim is to understand the transition from the induced to the uninduced state of the lac operon. We use a detailed computational model to show that repressor-operator binding and unbinding, fluctuations in the total number of repressors, and inducer-repressor binding and unbinding all play a role in this transition. Based on the timescales on which these processes operate, we construct a minimal model of the transition to the uninduced state and compare the results with simulations and experimental observations. The induced state turns out to be very stable, with a transition rate to the uninduced state lower than 2×10^-9 per minute. In contrast to the transition to the induced state, the transition to the uninduced state is well described in terms of a 2D diffusive system crossing a barrier, with the diffusion rates emerging from a model of repressor unbinding.

Hierarchical Bayesian models of transcriptional and translational regulation processes with delays

MOTIVATION

Simultaneous recordings of gene network dynamics across large populations have revealed that cell characteristics vary considerably even in clonal lines. Inferring the variability of parameters that determine gene dynamics is key to understanding cellular behavior. However, this is complicated by the fact that the outcomes and effects of many reactions are not observable directly. Unobserved reactions can be replaced with time delays to reduce model dimensionality and simplify inference. However, the resulting models are non-Markovian, and require the development of new inference techniques.

RESULTS

We propose a non-Markovian, hierarchical Bayesian inference framework for quantifying the variability of cellular processes within and across cells in a population. We illustrate our approach using a delayed birth-death process. In general, a distributed delay model, rather than a popular fixed delay model, is needed for inference, even if only mean reaction delays are of interest. Using in silico and experimental data we show that the proposed hierarchical framework is robust and leads to improved estimates compared to its non-hierarchical counterpart. We apply our method to data obtained using time-lapse microscopy and infer the parameters that describe the dynamics of protein production at the single cell and population level. The mean delays in protein production are larger than previously reported, have a coefficient of variation of around 0.2 across the population, and are not strongly correlated with protein production or growth rates.

AVAILABILITY AND IMPLEMENTATION

Accompanying code in Python is available at https://github.com/mvcortez/Bayesian-Inference.

CONTACT

kresimir.josic@gmail.com or jaekkim@kaist.ac.kr or cbskust@korea.ac.kr.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

The Marburg Collection: A Golden Gate DNA Assembly Framework for Synthetic Biology Applications in Vibrio natriegens

Vibrio natriegens is known as the world's fastest growing organism with a doubling time of less than 10 min. This incredible growth speed empowers V. natriegens as a chassis for synthetic and molecular biology, potentially replacing E. coli in many applications. While first genetic parts have been built and tested for V. natriegens, a comprehensive toolkit containing well-characterized and standardized parts did not exist. To close this gap, we created the Marburg Collection-a highly flexible Golden Gate cloning toolbox optimized for the emerging chassis organism V. natriegens, containing 191 genetic parts. The Marburg Collection overcomes the paradigm of plasmid construction-integrating inserts into a backbone-by enabling the de novo assembly of plasmids from basic genetic parts. This allows users to select the plasmid replication origin and resistance part independently, which is highly advantageous when limited knowledge about the behavior of those parts in the target organism is available. Additional design highlights of the Marburg Collection are novel connector parts, which facilitate modular circuit assembly and, optionally, the inversion of individual transcription units to reduce transcriptional crosstalk in multigene constructs. To quantitatively characterize the genetic parts contained in the Marburg Collection in V. natriegens, we developed a reliable microplate reader measurement workflow for reporter experiments and overcame organism-specific challenges. We think the Marburg Collection with its thoroughly characterized parts will provide a valuable resource for the growing V. natriegens community.

Escherichia coli AraJ boosts utilization of arabinose in metabolically engineered cyanobacterium Synechocystis sp. PCC 6803

Lignocellulosic biomass can serve as an inexpensive and renewable source of carbon for the biosynthesis of commercially important compounds. L-arabinose is the second most abundant pentose sugar present in the plant materials. Model cyanobacterium Synechocystis sp. PCC 6803 is incapable of catabolism of L-arabinose as a source of carbon and energy. In this study, all the heterologous genes expressed in Synechocystis were derived from Escherichia coli K-12. Initially we constructed four Synechocystis strains that expressed AraBAD enzymes involved in L-arabinose catabolism, either in combination with or without one of the three arabinose transporters, AraE, AraFGH or AraJ. Among the recombinants, the strain possessing AraJ transporter was observed to be the most efficient in terms of dry biomass production and L-arabinose consumption. Later, an additional strain was generated by the expression of AraJ in the AraE-possessing strain. The resultant strain was shown to be advantageous over its parent. This study demonstrates that AraJ, a protein with hitherto unknown function plays a role in the uptake of L-arabinose to boost its catabolism in the transgenic Synechocystis strains. The work also contributes to the current knowledge regarding metabolic engineering of cyanobacteria for the utilization of pentose sugars.

Flux, toxicity, and expression costs generate complex genetic interactions in a metabolic pathway

Our ability to predict the impact of mutations on traits relevant for disease and evolution remains severely limited by the dependence of their effects on the genetic background and environment. Even when molecular interactions between genes are known, it is unclear how these translate to organism-level interactions between alleles. We therefore characterized the interplay of genetic and environmental dependencies in determining fitness by quantifying ~4000 fitness interactions between expression variants of two metabolic genes, starting from various environmentally modulated expression levels. We detect a remarkable variety of interactions dependent on initial expression levels and demonstrate that they can be quantitatively explained by a mechanistic model accounting for catabolic flux, metabolite toxicity, and expression costs. Complex fitness interactions between mutations can therefore be predicted simply from their simultaneous impact on a few connected molecular phenotypes.

Theoretical investigation of a genetic switch for metabolic adaptation

Membrane transporters carry key metabolites across the cell membrane and, from a resource standpoint, are hypothesized to be produced when necessary. The expression of membrane transporters in metabolic pathways is often upregulated by the transporter substrate. In E. coli, such systems include for example the lacY, araFGH, and xylFGH genes, which encode for lactose, arabinose, and xylose transporters, respectively. As a case study of a minimal system, we build a generalizable physical model of the xapABR genetic circuit, which features a regulatory feedback loop via membrane transport (positive feedback) and enzymatic degradation (negative feedback) of an inducer. Dynamical systems analysis and stochastic simulations show that the membrane transport makes the model system bistable in certain parameter regimes. Thus, it serves as a genetic “on-off” switch, enabling the cell to only produce a set of metabolic enzymes when the corresponding metabolite is present in large amounts. We find that the negative feedback from the degradation enzyme does not significantly disturb the positive feedback from the membrane transporter. We investigate hysteresis in the switching and discuss the role of cooperativity and multiple binding sites in the model circuit. Fundamentally, this work explores how a stable genetic switch for a set of enzymes is obtained from transcriptional auto-activation of a membrane transporter through its substrate.

Genome Insights of the Plant-Growth Promoting Bacterium Cronobacter muytjensii JZ38 With Volatile-Mediated Antagonistic Activity Against Phytophthora infestans

Salinity stress is a major challenge to agricultural productivity and global food security in light of a dramatic increase of human population and climate change. Plant growth promoting bacteria can be used as an additional solution to traditional crop breeding and genetic engineering. In the present work, the induction of plant salt tolerance by the desert plant endophyte Cronobacter sp. JZ38 was examined on the model plant Arabidopsis thaliana using different inoculation methods. JZ38 promoted plant growth under salinity stress via contact and emission of volatile compounds. Based on the 16S rRNA and whole genome phylogenetic analysis, fatty acid analysis and phenotypic identification, JZ38 was identified as Cronobacter muytjensii and clearly separated and differentiated from the pathogenic C. sakazakii. Full genome sequencing showed that JZ38 is composed of one chromosome and two plasmids. Bioinformatic analysis and bioassays revealed that JZ38 can grow under a range of abiotic stresses. JZ38 interaction with plants is correlated with an extensive set of genes involved in chemotaxis and motility. The presence of genes for plant nutrient acquisition and phytohormone production could explain the ability of JZ38 to colonize plants and sustain plant growth under stress conditions. Gas chromatography-mass spectrometry analysis of volatiles produced by JZ38 revealed the emission of indole and different sulfur volatile compounds that may play a role in contactless plant growth promotion and antagonistic activity against pathogenic microbes. Indeed, JZ38 was able to inhibit the growth of two strains of the phytopathogenic oomycete Phytophthora infestans via volatile emission. Genetic, transcriptomic and metabolomics analyses, combined with more in vitro assays will provide a better understanding the highlighted genes' involvement in JZ38's functional potential and its interaction with plants. Nevertheless, these results provide insight into the bioactivity of C. muytjensii JZ38 as a multi-stress tolerance promoting bacterium with a potential use in agriculture.

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.

Engineering orthogonal synthetic timer circuits based on extracytoplasmic function σ factors

The rational design of synthetic regulatory circuits critically hinges on the availability of orthogonal and well-characterized building blocks. Here, we focus on extracytoplasmic function (ECF) σ factors, which are the largest group of alternative σ factors and hold extensive potential as synthetic orthogonal regulators. By assembling multiple ECF σ factors into regulatory cascades of varying length, we benchmark the scalability of the approach, showing that these ‘autonomous timer circuits’ feature a tuneable time delay between inducer addition and target gene activation. The implementation of similar timers in Escherichia coli and Bacillus subtilis shows strikingly convergent circuit behavior, which can be rationalized by a computational model. These findings not only reveal ECF σ factors as powerful building blocks for a rational, multi-layered circuit design, but also suggest that ECF σ factors are universally applicable as orthogonal regulators in a variety of bacterial species.

Bayesian inference of distributed time delay in transcriptional and translational regulation

MOTIVATION

Advances in experimental and imaging techniques have allowed for unprecedented insights into the dynamical processes within individual cells. However, many facets of intracellular dynamics remain hidden, or can be measured only indirectly. This makes it challenging to reconstruct the regulatory networks that govern the biochemical processes underlying various cell functions. Current estimation techniques for inferring reaction rates frequently rely on marginalization over unobserved processes and states. Even in simple systems this approach can be computationally challenging, and can lead to large uncertainties and lack of robustness in parameter estimates. Therefore we will require alternative approaches to efficiently uncover the interactions in complex biochemical networks.

RESULTS

We propose a Bayesian inference framework based on replacing uninteresting or unobserved reactions with time delays. Although the resulting models are non-Markovian, recent results on stochastic systems with random delays allow us to rigorously obtain expressions for the likelihoods of model parameters. In turn, this allows us to extend MCMC methods to efficiently estimate reaction rates, and delay distribution parameters, from single-cell assays. We illustrate the advantages, and potential pitfalls, of the approach using a birth-death model with both synthetic and experimental data, and show that we can robustly infer model parameters using a relatively small number of measurements. We demonstrate how to do so even when only the relative molecule count within the cell is measured, as in the case of fluorescence microscopy.

AVAILABILITY AND IMPLEMENTATION

Accompanying code in R is available at https://github.com/cbskust/DDE_BD.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Expression of Escherichia coli araE and modified lacY genes in Campylobacter jejuni is not sufficient for arabinose transport

Introduction

Unlike Escherichia coli, Campylobacter jejuni is unable to import a range of sugars, including arabinose, which makes common expression vectors, such as pBAD33, non-functional in these bacteria.

Aim

The aim of this study was to investigate whether the E. coli transporters AraE and modified LacY (LacYA177C) would enable C. jejuni to uptake arabinose.

Methodology and Results

The respective genes of E. coli were constitutively expressed in C. jejuni strain 11168H after integration into the chromosome via homologous recombination. Vectors carrying these genes also contained a reporter gene, gfp, under the control of the arabinose-inducible promoter, pBAD. These constructs were verified in E. coli by demonstrating the induction of gfp in the presence of arabinose. Integration of the genes into one of the rRNA gene clusters was verified by PCR and genome sequencing. The latter also confirmed that the inserted gene clusters contained no mutations. Expression of the gfp gene in the presence of arabinose inducer was monitored using fluorescence microscopy of colonies and fluorimetry using both whole cells and lysates.

Conclusion

The results demonstrated the inability of C. jejuni to use arabinose transporters, which are fully functional in E. coli, suggesting a remarkable difference in the physiology of these bacteria.

Gene Expression Changes with Minor Effects on the Population Average Have Major Effects on the Occurrence of Cells with Extreme Protein Concentrations

The cell-to-cell heterogeneity in a bacterial population provides a rich response to environmental changes and robust survival of an isogenic population. Especially, the rare, extreme phenotypes can be important for survival under transient lethal conditions.

The cell-to-cell heterogeneity in a bacterial population provides a rich response to environmental changes and robust survival of an isogenic population. Especially, the rare, extreme phenotypes can be important for survival under transient lethal conditions. We analyze the probability of having an extremely high or low protein level in a stochastic model of gene expression. The fraction of rare state cells defined as the cells in the tails of distributions is found to be highly sensitive to small changes of the mean protein level. The result highlights the importance of relatively weak changes to the mean for the occurrence of rare phenotypes.

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.

The Timing of Transcriptional Regulation in Synthetic Gene Circuits

Transcription factors and their target promoters are central to synthetic biology. By arranging these components into novel gene regulatory circuits, synthetic biologists have been able to create a wide variety of phenotypes, including bistable switches, oscillators, and logic gates. However, transcription factors (TFs) do not instantaneously regulate downstream targets. After the gene encoding a TF is turned on, the gene must first be transcribed, the transcripts must be translated, and sufficient TF must accumulate in order to bind operator sites of the target promoter. The time to complete this process, here called the "signaling time," is a critical aspect in the design of dynamic regulatory networks, yet it remains poorly characterized. In this work, we measured the signaling time of two TFs in Escherichia coli commonly used in synthetic biology: the activator AraC and the repressor LacI. We found that signaling times can range from a few to tens of minutes, and are affected by the expression rate of the TF. Our single-cell data also show that the variability of the signaling time increases with its mean. To validate these signaling time measurements, we constructed a two-step genetic cascade, and showed that the signaling time of the full cascade can be predicted from those of its constituent steps. These results provide concrete estimates for the time scales of transcriptional regulation in living cells, which are important for understanding the dynamics of synthetic transcriptional gene circuits.

Tunable recombinant protein expression in E. coli: promoter systems and genetic constraints

Tuning of transcription is a promising strategy to overcome challenges associated with a non-suitable expression rate like outgrowth of segregants, inclusion body formation, metabolic burden and inefficient translocation. By adjusting the expression rate-even on line-to purposeful levels higher product titres and more cost-efficient production processes can be achieved by enabling culture long-term stability and constant product quality. Some tunable systems are registered for patents or already commercially available. Within this contribution, we discuss the induction mechanisms of various Escherichia coli inherent promoter systems with respect to their tunability and review studies using these systems for expression tuning. According to the current level of knowledge, some promoter systems were successfully used for expression tuning, and in some cases, analytical evidence on single-cell level is still pending. However, only a few studies using tunable strains apply a suitable process control strategy. So far, expression tuning has only gathered little attention, but we anticipate that expression tuning harbours great potential for enabling and optimizing the production of a broad spectrum of products in E. coli.

Comparative Single-Cell Analysis of Different E. coli Expression Systems during Microfluidic Cultivation

Recombinant protein production is mostly realized with large-scale cultivations and monitored at the level of the entire population. Detailed knowledge of cell-to-cell variations with respect to cellular growth and product formation is limited, even though phenotypic heterogeneity may distinctly hamper overall production yields, especially for toxic or difficult-to-express proteins. Unraveling phenotypic heterogeneity is thus a key aspect in understanding and optimizing recombinant protein production in biotechnology and synthetic biology. Here, microfluidic single-cell analysis serves as the method of choice to investigate and unmask population heterogeneities in a dynamic and spatiotemporal fashion. In this study, we report on comparative microfluidic single-cell analyses of commonly used E. coli expression systems to uncover system-inherent specifications in the synthetic M9CA growth medium. To this end, the PT7lac/LacI, the PBAD/AraC and the Pm/XylS system were systematically analyzed in order to gain detailed insights into variations of growth behavior and expression phenotypes and thus to uncover individual strengths and deficiencies at the single-cell level. Specifically, we evaluated the impact of different system-specific inducers, inducer concentrations as well as genetic modifications that affect inducer-uptake and regulation of target gene expression on responsiveness and phenotypic heterogeneity. Interestingly, the most frequently applied expression system based on E. coli strain BL21(DE3) clearly fell behind with respect to expression homogeneity and robustness of growth. Moreover, both the choice of inducer and the presence of inducer uptake systems proved crucial for phenotypic heterogeneity. Conclusively, microfluidic evaluation of different inducible E. coli expression systems and setups identified the modified lacY-deficient PT7lac/LacI as well as the Pm/XylS system with conventional m-toluic acid induction as key players for precise and robust triggering of bacterial gene expression in E. coli in a homogeneous fashion.

Screening of an Escherichia coli promoter library for a phenylalanine biosensor

In recent years, the application of transcription factor-based biosensors for the engineering of microbial production strains opened up new opportunities for industrial biotechnology. However, the design of synthetic regulatory circuits depends on the selection of suitable transcription factor-promoter pairs to convert the concentration of effector molecules into a measureable output. Here, we present an efficient strategy to screen promoter libraries for appropriate parts for biosensor design. To this end, we pooled the strains of the Alon library containing about 2000 different Escherichia coli promoter-gfpmut2 fusions, and enriched galactose- and L-phenylalanine-responsive promoters by toggled rounds of positive and negative selection using fluorescence-activated cell sorting (FACS). For both effectors, responsive promoters were isolated and verified by cultivation in microtiter plates. The promoter of mtr, encoding an L-tryptophan-specific transporter, was identified as suitable part for the construction of an L-phenylalanine biosensor. In the following, we performed a comparative analysis of different biosensor constructs based on the mtr promoter. The obtained data revealed a strong influence of the biosensor architecture on the performance characteristics. For proof-of-principle, the mtr sensor was applied in a FACS high-throughput screening of an E. coli MG1655 mutant library for the isolation of L-phenylalanine producers. These results emphasize the developed screening approach as a convenient strategy for the identification of effector-responsive promoters for the design of novel biosensors.

Tunable recombinant protein expression in E. coli: enabler for continuous processing?

Tuning of transcription is a powerful process technological tool for efficient recombinant protein production in Escherichia coli. Many challenges such as product toxicity, formation of inclusion bodies, cell death, and metabolic burden are associated with non-suitable (too high or too low) levels of recombinant protein expression. Tunable expression systems allow adjusting the recombinant protein expression using process technological means. This enables to exploit the cell's metabolic capacities to a maximum. Within this article, we review genetic and process technological aspects of tunable expression systems in E. coli, providing a roadmap for the industrial exploitation of the reviewed technologies. We attempt to differentiate the term "expression tuning" from its inflationary use by providing a concise definition and highlight interesting fields of application for this versatile new technology. Dependent on the type of inducer (metabolizable or non-metabolizable), different process strategies are required in order to achieve tuning. To fully profit from the benefits of tunable systems, an independent control of growth rate and expression rate is indispensable. Being able to tackle problems such as long-term culture stability and constant product quality expression tuning is a promising enabler for continuous processing in biopharmaceutical production.

Single-cell characterization of metabolic switching in the sugar phosphotransferase system of Escherichia coli

The utilization of several sugars in Escherichia coli is regulated by the Phosphotransferase System (PTS), in which diverse sugar utilization modules compete for phosphoryl flux from the general PTS proteins. Existing theoretical work predicts a winner-take-all outcome when this flux limits carbon uptake. To date, no experimental work has interrogated competing PTS uptake modules with single-cell resolution. Using time-lapse microscopy in perfused microchannels, we analyzed the competition between N-acetyl-glucosamine and sorbitol, as representative PTS sugars, by measuring both the expression of their utilization systems and the concomitant impact of sugar utilization on growth rates. We find two distinct regimes: hierarchical usage of the carbohydrates, and co-expression of the genes for both systems. Simulations of a mathematical model incorporating asymmetric sugar quality reproduce our metabolic phase diagram, indicating that under conditions of nonlimiting phosphate flux, co-expression is due to uncoupling of both sugar utilization systems. Our model reproduces hierarchical winner-take-all behaviour and stochastic co-expression, and predicts the switching between both strategies as a function of available phosphate flux. Hence, experiments and theory both suggest that PTS sugar utilization involves not only switching between the sugars utilized but also switching of utilization strategies to accommodate prevailing environmental conditions.

Reciprocal Regulation of l-Arabinose and d-Xylose Metabolism in Escherichia coli

Glucose is known to inhibit the transport and metabolism of many sugars in Escherichia coli. This mechanism leads to its preferential consumption. Far less is known about the preferential utilization of nonglucose sugars in E. coli. Two exceptions are l-arabinose and d-xylose. Previous studies have shown that l-arabinose inhibits d-xylose metabolism in Escherichia coli. This repression results from l-arabinose-bound AraC binding to the promoter of the d-xylose metabolic genes and inhibiting their expression. This mechanism, however, has not been explored in single cells. Both the l-arabinose and d-xylose utilization systems are known to exhibit a bimodal induction response to their cognate sugar, where mixed populations of cells either expressing the metabolic genes or not are observed at intermediate sugar concentrations. This suggests that l-arabinose can only inhibit d-xylose metabolism in l-arabinose-induced cells. To understand how cross talk between these systems affects their response, we investigated E. coli during growth on mixtures of l-arabinose and d-xylose at single-cell resolution. Our results showed that mixed, multimodal populations of l-arabinose- and d-xylose-induced cells occurred at intermediate sugar concentrations. We also found that d-xylose inhibited the expression of the l-arabinose metabolic genes and that this repression was due to XylR. These results demonstrate that a strict hierarchy does not exist between l-arabinose and d-xylose as previously thought. The results may also aid in the design of E. coli strains capable of simultaneous sugar consumption.

IMPORTANCE

Glucose, d-xylose, and l-arabinose are the most abundant sugars in plant biomass. Developing efficient fermentation processes that convert these sugars into chemicals and fuels will require strains capable of coutilizing these sugars. Glucose has long been known to repress the expression of the l-arabinose and d-xylose metabolic genes in Escherichia coli. Recent studies found that l-arabinose also represses the expression of the d-xylose metabolic genes. In the present study, we found that d-xylose also represses the expression of the l-arabinose metabolic genes, leading to mixed populations of cells capable of utilizing l-arabinose and d-xylose. These results further our understanding of mixed-sugar utilization and may aid in strain design.

AraR, an l-Arabinose-Responsive Transcriptional Regulator in Corynebacterium glutamicum ATCC 31831, Exerts Different Degrees of Repression Depending on the Location of Its Binding Sites within the Three Target Promoter Regions

In Corynebacterium glutamicum ATCC 31831, a LacI-type transcriptional regulator AraR, represses the expression of l-arabinose catabolism (araBDA), uptake (araE), and the regulator (araR) genes clustered on the chromosome. AraR binds to three sites: one (BSB) between the divergent operons (araBDA and galM-araR) and two (BSE1 and BSE2) upstream of araE. L-Arabinose acts as an inducer of the AraR-mediated regulation. Here, we examined the roles of these AraR-binding sites in the expression of the AraR regulon. BSB mutation resulted in derepression of both araBDA and galM-araR operons. The effects of BSE1 and/or BSE2 mutation on araE expression revealed that the two sites independently function as the cis elements, but BSE1 plays the primary role. However, AraR was shown to bind to these sites with almost the same affinity in vitro. Taken together, the expression of araBDA and araE is strongly repressed by binding of AraR to a single site immediately downstream of the respective transcriptional start sites, whereas the binding site overlapping the -10 or -35 region of the galM-araR and araE promoters is less effective in repression. Furthermore, downregulation of araBDA and araE dependent on l-arabinose catabolism observed in the BSB mutant and the AraR-independent araR promoter identified within galM-araR add complexity to regulation of the AraR regulon derepressed by L-arabinose.

IMPORTANCE

Corynebacterium glutamicum has a long history as an industrial workhorse for large-scale production of amino acids. An important aspect of industrial microorganisms is the utilization of the broad range of sugars for cell growth and production process. Most C. glutamicum strains are unable to use a pentose sugar L-arabinose as a carbon source. However, genes for L-arabinose utilization and its regulation have been recently identified in C. glutamicum ATCC 31831. This study elucidates the roles of the multiple binding sites of the transcriptional repressor AraR in the derepression by L-arabinose and thereby highlights the complex regulatory feedback loops in combination with l-arabinose catabolism-dependent repression of the AraR regulon in an AraR-independent manner.

Phenotypic Heterogeneity, a Phenomenon That May Explain Why Quorum Sensing Does Not Always Result in Truly Homogenous Cell Behavior

Phenotypic heterogeneity describes the occurrence of "nonconformist" cells within an isogenic population. The nonconformists show an expression profile partially different from that of the remainder of the population. Phenotypic heterogeneity affects many aspects of the different bacterial lifestyles, and it is assumed that it increases bacterial fitness and the chances for survival of the whole population or smaller subpopulations in unfavorable environments. Well-known examples for phenotypic heterogeneity have been associated with antibiotic resistance and frequently occurring persister cells. Other examples include heterogeneous behavior within biofilms, DNA uptake and bacterial competence, motility (i.e., the synthesis of additional flagella), onset of spore formation, lysis of phages within a small subpopulation, and others. Interestingly, phenotypic heterogeneity was recently also observed with respect to quorum-sensing (QS)-dependent processes, and the expression of autoinducer (AI) synthase genes and other QS-dependent genes was found to be highly heterogeneous at a single-cell level. This phenomenon was observed in several Gram-negative bacteria affiliated with the genera Vibrio, Dinoroseobacter, Pseudomonas, Sinorhizobium, and Mesorhizobium. A similar observation was made for the Gram-positive bacterium Listeria monocytogenes. Since AI molecules have historically been thought to be the keys to homogeneous behavior within isogenic populations, the observation of heterogeneous expression is quite intriguing and adds a new level of complexity to the QS-dependent regulatory networks. All together, the many examples of phenotypic heterogeneity imply that we may have to partially revise the concept of homogeneous and coordinated gene expression in isogenic bacterial populations.

Kinetics of the cellular intake of a gene expression inducer at high concentrations

From in vivo single-event measurements of the transient and steady-state transcription activity of a single-copy lac-ara-1 promoter in Escherichia coli, we characterize the intake kinetics of its inducer (IPTG) from the media. We show that the empirical data are well-fit by a model of intake assuming a bilayer membrane, with the passage through the second layer being rate-limiting, coupled to a stochastic, sub-Poissonian, multi-step transcription process. Using this model, we show that for a wide range of extracellular inducer levels (up to 1.25 mM) the intake process is diffusive-like, suggesting unsaturated membrane permeability. Inducer molecules travel from the periplasm to the cytoplasm in, on average, 31.7 minutes, strongly affecting cells' response time. The novel methodology followed here should aid the study of cellular intake mechanisms at the single-event level.

Phenotypic Heterogeneity, a Phenomenon That May Explain Why Quorum Sensing Does Not Always Result in Truly Homogenous Cell Behavior

Phenotypic heterogeneity describes the occurrence of "nonconformist" cells within an isogenic population. The nonconformists show an expression profile partially different from that of the remainder of the population. Phenotypic heterogeneity affects many aspects of the different bacterial lifestyles, and it is assumed that it increases bacterial fitness and the chances for survival of the whole population or smaller subpopulations in unfavorable environments. Well-known examples for phenotypic heterogeneity have been associated with antibiotic resistance and frequently occurring persister cells. Other examples include heterogeneous behavior within biofilms, DNA uptake and bacterial competence, motility (i.e., the synthesis of additional flagella), onset of spore formation, lysis of phages within a small subpopulation, and others. Interestingly, phenotypic heterogeneity was recently also observed with respect to quorum-sensing (QS)-dependent processes, and the expression of autoinducer (AI) synthase genes and other QS-dependent genes was found to be highly heterogeneous at a single-cell level. This phenomenon was observed in several Gram-negative bacteria affiliated with the genera Vibrio, Dinoroseobacter, Pseudomonas, Sinorhizobium, and Mesorhizobium. A similar observation was made for the Gram-positive bacterium Listeria monocytogenes. Since AI molecules have historically been thought to be the keys to homogeneous behavior within isogenic populations, the observation of heterogeneous expression is quite intriguing and adds a new level of complexity to the QS-dependent regulatory networks. All together, the many examples of phenotypic heterogeneity imply that we may have to partially revise the concept of homogeneous and coordinated gene expression in isogenic bacterial populations.

Cooperativity leads to temporally-correlated fluctuations in the bacteriophage lambda genetic switch

Cooperative interactions are widespread in biochemical networks, providing the nonlinear response that underlies behavior such as ultrasensitivity and robust switching. We introduce a temporal correlation function-the conditional activity-to study the behavior of these phenomena. Applying it to the bistable genetic switch in bacteriophage lambda, we find that cooperative binding between binding sites on the prophage DNA lead to non-Markovian behavior, as quantified by the conditional activity. Previously, the conditional activity has been used to predict allosteric pathways in proteins; here, we show that it identifies the rare unbinding events which underlie induction from lysogeny to lysis.

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.