Modelling overflow metabolism in Escherichia coli with flux balance analysis incorporating differential proteomic efficiencies of energy pathways

Interplay of niche and respiratory network in shaping bacterial colonization

The human body is an intricate ensemble of prokaryotic and eukaryotic cells, and this coexistence relies on the interplay of many biotic and abiotic factors. The inhabiting microbial population has to maintain its physiological homeostasis under highly dynamic and often hostile host environments. While bacterial colonization primarily relies on the metabolic suitability for the niche, there are reports of active remodeling of niche microenvironments to create favorable habitats, especially in the context of pathogenic settlement. Such physiological plasticity requires a robust metabolic system, often dependent on an adaptable energy metabolism. This review focuses on the respiratory electron transport system and its adaptive consequences within the host environment. We provide an overview of respiratory chain plasticity, which allows pathogenic bacteria to niche-specify, niche-diversify, mitigate inflammatory stress, and outcompete the resident microbiota. We have reviewed existing and emerging knowledge about the role of respiratory chain components responsible for the entry and exit of electrons in influencing the pathogenic outcomes.

Enzyme-constrained Metabolic Model of Treponema pallidum Identified Glycerol-3-phosphate Dehydrogenase as an Alternate Electron Sink

Treponema pallidum, the causative agent of syphilis, poses a significant global health threat. Its strict intracellular lifestyle and challenges in in vitro cultivation have impeded detailed metabolic characterization. In this study, we present iTP251, the first genome-scale metabolic model of T. pallidum, reconstructed and extensively curated to capture its unique metabolic features. These refinements included the curation of key reactions such as pyrophosphate-dependent phosphorylation and pathways for nucleotide synthesis, amino acid synthesis, and cofactor metabolism. The model demonstrated high predictive accuracy, validated by a MEMOTE score of 92%. To further enhance its predictive capabilities, we developed ec-iTP251, an enzyme-constrained version of iTP251, incorporating enzyme turnover rate and molecular weight information for all reactions having gene-protein-reaction associations. Ec-iTP251 provides detailed insights into protein allocation across carbon sources, showing strong agreement with proteomics data (Pearson's correlation of 0.88) in the central carbon pathway. Moreover, the thermodynamic analysis revealed that lactate uptake serves as an additional ATP-generating strategy to utilize unused proteomes, albeit at the cost of reducing the driving force of the central carbon pathway by 27%. Subsequent analysis identified glycerol-3-phosphate dehydrogenase as an alternative electron sink, compensating for the absence of a conventional electron transport chain while maintaining cellular redox balance. These findings highlight T. pallidum's metabolic adaptations for survival and redox balance in intracellular environments, providing a foundation for future research into its unique bioenergetics.

Dynamic flux balance analysis of high cell density fed-batch culture of Escherichia coli BL21 (DE3) with mass spectrometry-based spent media analysis

Dynamic flux balance analysis (FBA) allows estimation of intracellular reaction rates using organism-specific genome-scale metabolic models (GSMM) and by assuming instantaneous pseudo-steady states for processes that are inherently dynamic. This technique is well-suited for industrial bioprocesses employing complex media characterized by a hierarchy of substrate uptake and product secretion. However, knowledge of exchange rates of many components of the media would be required to obtain meaningful results. Here, we performed spent media analysis using mass spectrometry coupled with liquid and gas chromatography for a fed-batch, high-cell density cultivation of Escherichia coli BL21(DE3) expressing a recombinant protein. Time course measurements thus obtained for 246 metabolites were converted to instantaneous exchange rates. These were then used as constraints for dynamic FBA using a previously reported GSMM, thus providing insights into how the flux map evolves through the process. Changes in tri-carboxylic acid cycle fluxes correlated with the increased demand for energy during recombinant protein production. The results show how amino acids act as hubs for the synthesis of other cellular metabolites. Our results provide a deeper understanding of an industrial bioprocess and will have implications in further optimizing the process.

Metabolic engineering of glycolysis in Escherichia coli for efficient production of patchoulol and τ-cadinol

Glucose metabolism suppresses the microbial synthesis of sesquiterpenes with a syndrome of "too much of a good thing can be bad". Here, patchoulol production in Escherichia coli was increased 2.02 times by engineering patchoulol synthase to obtain an initial strain. Knocking out the synthetic pathway for cyclic adenosine monophosphate relieved glucose repression and improved patchoulol titer and yield by 27.7 % and 43.1 %, respectively. A glycolysis regulation device mediated by pyruvate sensing was constructed which effectively alleviated overflow metabolism in a high-glucose environment with 10.2 % greater patchoulol titer in strain 070QA. Without fine-tuning the glucose-feeding rate, patchoulol titer further increased to 1675.1 mg/L in a 5-L bioreactor experiment, which was the highest level reported in E. coli. Using strain 070QA as a chassis, the τ-cadinol titer reached 15.2 g/L, representing the first report for microbial production of τ-cadinol. These findings will aid in the industrial production of sesquiterpene.

Proteome efficiency of metabolic pathways in Escherichia coli increases along the nutrient flow

IMPORTANCE

Protein translation is the most expensive cellular process in fast-growing bacteria, and efficient proteome usage should thus be under strong natural selection. However, recent studies show that a considerable part of the proteome is unneeded for instantaneous cell growth in Escherichia coli. We still lack a systematic understanding of how this excess proteome is distributed across different pathways as a function of the growth conditions. We estimated the minimal required proteome across growth conditions in E. coli and compared the predictions with experimental data. We found that the proteome allocated to the most expensive internal pathways, including translation and the synthesis of amino acids and cofactors, is near the minimally required levels. In contrast, transporters and central carbon metabolism show much higher proteome levels than the predicted minimal abundance. Our analyses show that the proteome fraction unneeded for instantaneous cell growth decreases along the nutrient flow in E. coli.

Flux balance analysis-based metabolic modeling of microbial secondary metabolism: Current status and outlook

In microorganisms, different from primary metabolism for cellular growth, secondary metabolism is for ecological interactions and stress responses and an important source of natural products widely used in various areas such as pharmaceutics and food additives. With advancements of sequencing technologies and bioinformatics tools, a large number of biosynthetic gene clusters of secondary metabolites have been discovered from microbial genomes. However, due to challenges from the difficulty of genome-scale pathway reconstruction and the limitation of conventional flux balance analysis (FBA) on secondary metabolism, the quantitative modeling of secondary metabolism is poorly established, in contrast to that of primary metabolism. This review first discusses current efforts on the reconstruction of secondary metabolic pathways in genome-scale metabolic models (GSMMs), as well as related FBA-based modeling techniques. Additionally, potential extensions of FBA are suggested to improve the prediction accuracy of secondary metabolite production. As this review posits, biosynthetic pathway reconstruction for various secondary metabolites will become automated and a modeling framework capturing secondary metabolism onset will enhance the predictive power. Expectedly, an improved FBA-based modeling workflow will facilitate quantitative study of secondary metabolism and in silico design of engineering strategies for natural product production.

Sensitive real-time on-line estimator for oxygen transfer rates in fermenters

Recombinant Escherichia coli grown in large-scale fermenters are used extensively to produce plasmids and biopharmaceuticals. One method commonly used to control culture growth is predefined glucose feeding, often an exponential feeding profile. Predefined feeding profiles cannot adjust automatically to metabolic state changes, such as the metabolic burden associated with recombinant protein expression or high-cell density associated stresses. As the culture oxygen consumption rates indicates a culture's metabolic state, there exist several methods to estimate the oxygen uptake rate (OUR). These common OUR methods have limited application since these approaches either disrupt the oxygen supply, rely on empirical relationships, or are unable to account for latency and filtering effects. In this study, an oxygen transfer rate (OTR) estimator was developed to aid OUR prediction. This non-disruptive OTR estimator uses the dissolved oxygen and the off-gas oxygen concentration, in parallel. This new OTR estimator captures small variations in OTR due to physical and chemical manipulations of the fermenter, such as in stir speed variation, glucose feeding rate change, and recombinant protein expression. Due its sensitivity, this non-disruptive real-time OTR estimator could be integrated with feed control algorithms to maintain the metabolic state of a culture to a desired setpoint.

Validated In Silico Population Model of Escherichia coli

Flux balance analysis (FBA) and ordinary differential equation models have been instrumental in depicting the metabolic functioning of a cell. Nevertheless, they demonstrate a population's average behavior (summation of individuals), thereby portraying homogeneity. However, living organisms such as Escherichia coli contain more biochemical reactions than engaging metabolites, making them an underdetermined and degenerate system. This results in a heterogeneous population with varying metabolic patterns. We have formulated a population systems biology model that predicts this degeneracy by emulating a diverse metabolic makeup with unique biochemical signatures. The model mimics the universally accepted experimental view that a subpopulation of bacteria, even under normal growth conditions, renders a unique biochemical state, leading to the synthesis of metabolites and persister progenitors of antibiotic resistance and biofilms. We validate the platform's predictions by producing commercially important heterologous (isobutanol) and homologous (shikimate) metabolites. The predicted fluxes are tested in vitro resulting in 32- and 42-fold increased product of isobutanol and shikimate, respectively. Moreover, we authenticate the platform by mimicking a bacterial population in the presence of glyphosate, a metabolic pathway inhibitor. Here, we observe a fraction of subsisting persisters despite inhibition, thus affirming the signature of a heterogeneous populace. The platform has multiple uses based on the disposition of the user.

Construction of Multiscale Genome-Scale Metabolic Models: Frameworks and Challenges

Genome-scale metabolic models (GEMs) are effective tools for metabolic engineering and have been widely used to guide cell metabolic regulation. However, the single gene–protein-reaction data type in GEMs limits the understanding of biological complexity. As a result, multiscale models that add constraints or integrate omics data based on GEMs have been developed to more accurately predict phenotype from genotype. This review summarized the recent advances in the development of multiscale GEMs, including multiconstraint, multiomic, and whole-cell models, and outlined machine learning applications in GEM construction. This review focused on the frameworks, toolkits, and algorithms for constructing multiscale GEMs. The challenges and perspectives of multiscale GEM development are also discussed.

Is energy excess the initial trigger of carbon overflow metabolism? Transcriptional network response of carbon-limited Escherichia coli to transient carbon excess

Background

Escherichia coli adapted to carbon-limiting conditions is generally geared for energy-efficient carbon utilization. This includes also the efficient utilization of glucose, which serves as a source for cellular building blocks as well as energy. Thus, catabolic and anabolic functions are balanced under these conditions to minimize wasteful carbon utilization. Exposure to glucose excess interferes with the fine-tuned coupling of anabolism and catabolism leading to the so-called carbon overflow metabolism noticeable through acetate formation and eventually growth inhibition.

Results

Cellular adaptations towards sudden but timely limited carbon excess conditions were analyzed by exposing slow-growing cells in steady state glucose-limited continuous culture to a single glucose pulse. Concentrations of metabolites as well as time-dependent transcriptome alterations were analyzed and a transcriptional network analysis performed to determine the most relevant transcription and sigma factor combinations which govern these adaptations. Down-regulation of genes related to carbon catabolism is observed mainly at the level of substrate uptake and downstream of pyruvate and not in between in the glycolytic pathway. It is mainly accomplished through the reduced activity of CRP-cAMP and through an increased influence of phosphorylated ArcA. The initiated transcriptomic change is directed towards down-regulation of genes, which contribute to active movement, carbon uptake and catabolic carbon processing, in particular to down-regulation of genes which contribute to efficient energy generation. Long-term changes persisting after glucose depletion and consumption of acetete encompassed reduced expression of genes related to active cell movement and enhanced expression of genes related to acid resistance, in particular acid resistance system 2 (GABA shunt) which can be also considered as an inefficient bypass of the TCA cycle.

Conclusions

Our analysis revealed that the major part of the trancriptomic response towards the glucose pulse is not directed towards enhanced cell proliferation but towards protection against excessive intracellular accumulation of potentially harmful concentration of metabolites including among others energy rich compounds such as ATP. Thus, resources are mainly utilized to cope with “overfeeding” and not for growth including long-lasting changes which may compromise the cells future ability to perform optimally under carbon-limiting conditions (reduced motility and ineffective substrate utilization).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01787-4.

ECMpy, a Simplified Workflow for Constructing Enzymatic Constrained Metabolic Network Model

Genome-scale metabolic models (GEMs) have been widely used for the phenotypic prediction of microorganisms. However, the lack of other constraints in the stoichiometric model often leads to a large metabolic solution space being inaccessible. Inspired by previous studies that take an allocation of macromolecule resources into account, we developed a simplified Python-based workflow for constructing enzymatic constrained metabolic network model (ECMpy) and constructed an enzyme-constrained model for Escherichia coli (eciML1515) by directly adding a total enzyme amount constraint in the latest version of GEM for E. coli (iML1515), considering the protein subunit composition in the reaction, and automated calibration of enzyme kinetic parameters. Using eciML1515, we predicted the overflow metabolism of E. coli and revealed that redox balance was the key reason for the difference between E. coli and Saccharomyces cerevisiae in overflow metabolism. The growth rate predictions on 24 single-carbon sources were improved significantly when compared with other enzyme-constrained models of E. coli. Finally, we revealed the tradeoff between enzyme usage efficiency and biomass yield by exploring the metabolic behaviours under different substrate consumption rates. Enzyme-constrained models can improve simulation accuracy and thus can predict cellular phenotypes under various genetic perturbations more precisely, providing reliable guidance for metabolic engineering.

Vitreoscilla Haemoglobin: A Tool to Reduce Overflow Metabolism

Overflow metabolism is a phenomenon extended in nature, ranging from microbial to cancer cells. Accumulation of overflow metabolites pose a challenge for large-scale bioprocesses. Yet, the causes of overflow metabolism are not fully clarified. In this work, the underlying mechanisms, reasons and consequences of overflow metabolism in different organisms have been summarized. The reported effect of aerobic expression of Vitreoscilla haemoglobin (VHb) in different organisms are revised. The use of VHb to reduce overflow metabolism is proposed and studied through flux balance analysis in E. coli at a fixed maximum substrate and oxygen uptake rates. Simulations showed that the presence of VHb increases the growth rate, while decreasing acetate production, in line with the experimental measurements. Therefore, aerobic VHb expression is considered a potential tool to reduce overflow metabolism in cells.

Adaptive laboratory evolution of Escherichia coli W enhances gamma-aminobutyric acid production using glycerol as the carbon source

The microbial conversion of glycerol into value-added commodity products has emerged as an attractive means to meet the demands of biosustainability. However, glycerol is a non-preferential carbon source for productive fermentation because of its low energy density. We employed evolutionary and metabolic engineering in tandem to construct an Escherichia coli strain with improved GABA production using glycerol as the feedstock carbon. Adaptive evolution of E. coli W under glycerol-limited conditions for 1300 generations harnessed an adapted strain with a metabolic system optimized for glycerol utilization. Mutation profiling, enzyme kinetic assays, and transcriptome analysis of the adapted strain allowed us to decipher the basis of glycerol adaptation at the molecular level. Importantly, increased substrate influx mediated by the mutant glpK and modulation of intracellular cAMP levels were the key drivers of improved fitness in the glycerol-limited condition. Leveraging the enhanced capability of glycerol utilization in the strain, we constructed a GABA-producing E. coli W-derivative with superior GABA production compared to the wild-type. Furthermore, rationally designed inactivation of the non-essential metabolic genes, including ackA, mgsA, and gabT, in the glycerol-adapted strain improved the final GABA titer and specific productivity by 3.9- and 4.3-fold, respectively, compared with the wild-type.

Redox metabolism for improving whole-cell P450-catalysed terpenoid biosynthesis

The growing preference for producing cytochrome P450-mediated natural products in microbial systems stems from the challenging nature of the organic chemistry approaches. The P450 enzymes are redox-dependent proteins, through which they source electrons from reducing cofactors to drive their activities. Widely researched in biochemistry, most of the previous studies have extensively utilised expensive cell-free assays to reveal mechanistic insights into P450 functionalities in presence of commercial redox partners. However, in the context of microbial bioproduction, the synergic activity of P450- reductase proteins in microbial systems have not been largely investigated. This is mainly due to limited knowledge about their mutual interactions in the context of complex systems. Hence, manipulating the redox potential for natural product synthesis in microbial chassis has been limited. As the potential of redox state as crucial regulator of P450 biocatalysis has been greatly underestimated by the scientific community, in this review, we re-emphasize their pivotal role in modulating the in vivo P450 activity through affecting the product profile and yield. Particularly, we discuss the applications of widely used in vivo redox engineering methodologies for natural product synthesis to provide further suggestions for patterning on P450-based terpenoids production in microbial platforms.

A Review of Using Mathematical Modeling to Improve Our Understanding of Bacteriophage, Bacteria, and Eukaryotic Interactions

Phage therapy, the therapeutic usage of viruses to treat bacterial infections, has many theoretical benefits in the ‘post antibiotic era.’ Nevertheless, there are currently no approved mainstream phage therapies. One reason for this is a lack of understanding of the complex interactions between bacteriophage, bacteria and eukaryotic hosts. These three-component interactions are complex, with non-linear or synergistic relationships, anatomical barriers and genetic or phenotypic heterogeneity all leading to disparity between performance and efficacy in in vivo versus in vitro environments. Realistic computer or mathematical models of these complex environments are a potential route to improve the predictive power of in vitro studies for the in vivo environment, and to streamline lab work. Here, we introduce and review the current status of mathematical modeling and highlight that data on genetic heterogeneity and mutational stochasticity, time delays and population densities could be critical in the development of realistic phage therapy models in the future. With this in mind, we aim to inform and encourage the collaboration and sharing of knowledge and expertise between microbiologists and theoretical modelers, synergising skills and smoothing the road to regulatory approval and widespread use of phage therapy.

Understanding and mathematical modelling of cellular resource allocation in microorganisms: a comparative synthesis

BACKGROUND

The rising consensus that the cell can dynamically allocate its resources provides an interesting angle for discovering the governing principles of cell growth and metabolism. Extensive efforts have been made in the past decade to elucidate the relationship between resource allocation and phenotypic patterns of microorganisms. Despite these exciting developments, there is still a lack of explicit comparison between potentially competing propositions and a lack of synthesis of inter-related proposals and findings.

RESULTS

In this work, we have reviewed resource allocation-derived principles, hypotheses and mathematical models to recapitulate important achievements in this area. In particular, the emergence of resource allocation phenomena is deciphered by the putative tug of war between the cellular objectives, demands and the supply capability. Competing hypotheses for explaining the most-studied phenomenon arising from resource allocation, i.e. the overflow metabolism, have been re-examined towards uncovering the potential physiological root cause. The possible link between proteome fractions and the partition of the ribosomal machinery has been analysed through mathematical derivations. Finally, open questions are highlighted and an outlook on the practical applications is provided. It is the authors' intention that this review contributes to a clearer understanding of the role of resource allocation in resolving bacterial growth strategies, one of the central questions in microbiology.

CONCLUSIONS

We have shown the importance of resource allocation in understanding various aspects of cellular systems. Several important questions such as the physiological root cause of overflow metabolism and the correct interpretation of 'protein costs' are shown to remain open. As the understanding of the mechanisms and utility of resource application in cellular systems further develops, we anticipate that mathematical modelling tools incorporating resource allocation will facilitate the circuit-host design in synthetic biology.

Control and regulation of acetate overflow in Escherichia coli

Overflow metabolism refers to the production of seemingly wasteful by-products by cells during growth on glucose even when oxygen is abundant. Two theories have been proposed to explain acetate overflow in Escherichia coli – global control of the central metabolism and local control of the acetate pathway – but neither accounts for all observations. Here, we develop a kinetic model of E. coli metabolism that quantitatively accounts for observed behaviours and successfully predicts the response of E. coli to new perturbations. We reconcile these theories and clarify the origin, control, and regulation of the acetate flux. We also find that, in turns, acetate regulates glucose metabolism by coordinating the expression of glycolytic and TCA genes. Acetate should not be considered a wasteful end-product since it is also a co-substrate and a global regulator of glucose metabolism in E. coli. This has broad implications for our understanding of overflow metabolism.

Microbial inefficient substrate use through the perspective of resource allocation models

Microorganisms extract energy from substrates following strategies that may seem suboptimal at first glance. Beyond the so-called yield-rate trade-off, resource allocation models, which focus on assigning different functional roles to the limited number of enzymes that a cell can support, offer a framework to interpret the inefficient substrate use by microorganisms. We review here relevant examples of substrate conversions where a significant part of the available energy is not utilised and how resource allocation models offer a mechanistic interpretation thereof, notably for open mixed cultures. Future developments are identified, in particular, the challenge of considering metabolic flexibility towards uncertain environmental changes instead of strict fixed optimality objectives, with the final goal of increasing the prediction capabilities of resource allocation models. Finally, we highlight the relevance of resource allocation to understand and enable a promising biorefinery platform revolving around lactate, which would increase the flexibility of waste-to-chemical biorefinery schemes.

Microbial Upgrading of Acetate into Value-Added Products-Examining Microbial Diversity, Bioenergetic Constraints and Metabolic Engineering Approaches

Ecological concerns have recently led to the increasing trend to upgrade carbon contained in waste streams into valuable chemicals. One of these components is acetate. Its microbial upgrading is possible in various species, with Escherichia coli being the best-studied. Several chemicals derived from acetate have already been successfully produced in E. coli on a laboratory scale, including acetone, itaconic acid, mevalonate, and tyrosine. As acetate is a carbon source with a low energy content compared to glucose or glycerol, energy- and redox-balancing plays an important role in acetate-based growth and production. In addition to the energetic challenges, acetate has an inhibitory effect on microorganisms, reducing growth rates, and limiting product concentrations. Moreover, extensive metabolic engineering is necessary to obtain a broad range of acetate-based products. In this review, we illustrate some of the necessary energetic considerations to establish robust production processes by presenting calculations of maximum theoretical product and carbon yields. Moreover, different strategies to deal with energetic and metabolic challenges are presented. Finally, we summarize ways to alleviate acetate toxicity and give an overview of process engineering measures that enable sustainable acetate-based production of value-added chemicals.

Resource allocation explains lactic acid production in mixed-culture anaerobic fermentations

Lactate production in anaerobic carbohydrate fermentations with mixed cultures of microorganisms is generally observed only in very specific conditions: the reactor should be run discontinuously and peptides and B vitamins must be present in the culture medium as lactic acid bacteria (LAB) are typically auxotrophic for amino acids. State-of-the-art anaerobic fermentation models assume that microorganisms optimise the adenosine triphosphate (ATP) yield on substrate and therefore they do not predict the less ATP efficient lactate production, which limits their application for designing lactate production in mixed-culture fermentations. In this study, a metabolic model taking into account cellular resource allocation and limitation is proposed to predict and analyse under which conditions lactate production from glucose can be beneficial for microorganisms. The model uses a flux balances analysis approach incorporating additional constraints from the resource allocation theory and simulates glucose fermentation in a continuous reactor. This approach predicts lactate production is predicted at high dilution rates, provided that amino acids are in the culture medium. In minimal medium and lower dilution rates, mostly butyrate and no lactate is predicted. Auxotrophy for amino acids of LAB is identified to provide a competitive advantage in rich media because less resources need to be allocated for anabolic machinery and higher specific growth rates can be achieved. The Matlab™ codes required for performing the simulations presented in this study are available at https://doi.org/10.5281/zenodo.4031144.

Recombinant protein production-associated metabolic burden reflects anabolic constraints and reveals similarities to a carbon overfeeding response

A comparison of the metabolic response of Escherichia coli BL21 (DE3) towards the production of human basic fibroblast growth factor (hFGF-2) or towards carbon overfeeding revealed similarities which point to constraints in anabolic pathways. Contrary to expectations, neither energy generation (e.g., ATP) nor provision of precursor molecules for nucleotides (e.g., uracil) and amino acids (e.g., pyruvate, glutamate) limit host cell and plasmid-encoded functions. Growth inhibition is assumed to occur when hampered anabolic capacities do not match with the ongoing and overwhelming carbon catabolism. Excessive carbon uptake leads to by-product secretion, for example, pyruvate, acetate, glutamate, and energy spillage, for example, accumulation and degradation of adenine nucleotides with concomitant accumulation of extracellular hypoxanthine. The cellular response towards compromised anabolic capacities involves downregulation of cAMP formation, presumably responsible for subsequently better-controlled glucose uptake and resultant accumulation of glucose in the culture medium. Growth inhibition is neglectable under conditions of reduced carbon availability when hampered anabolic capacities also match with catabolic carbon processing. The growth inhibitory effect with accompanying energy spillage, respectively, hypoxanthine secretion and cessation of cAMP formation is not unique to the production of hFGF-2 but observed during the production of other proteins and also during overexpression of genes without transcript translation.

Bridging substrate intake kinetics and bacterial growth phenotypes with flux balance analysis incorporating proteome allocation

Empirical kinetic models such as the Monod equation have been widely applied to relate the cell growth with substrate availability. The Monod equation shares a similar form with the mechanistically-based Michaelis-Menten kinetics for enzymatic processes, which has provoked long-standing and un-concluded conjectures on their relationship. In this work, we integrated proteome allocation principles into a Flux Balance Analysis (FBA) model of Escherichia coli, which quantitatively revealed potential mechanisms that underpin the phenomenological Monod parameters: the maximum specific growth rate could be dictated by the abundance of growth-controlling proteome and growth-pertinent proteome cost; more importantly, the Monod constant (K_s) was shown to relate to the Michaelis constant for substrate transport (K_m,g), with the link being dependent on the cell's metabolic strategy. Besides, the proposed model was able to predict glucose uptake rate at given external glucose concentration through the size of available proteome resource for substrate transport and its enzymatic cost, while growth rate and acetate overflow were accurately simulated for two E. coli strains. Bridging the enzymatic kinetics of substrate intake and overall growth phenotypes, this work offers a mechanistic interpretation to the empirical Monod law, and demonstrates the potential of coupling local and global cellular constrains in predictive modelling.

New insights into transport capability of sugars and its impact on growth from novel mutants of Escherichia coli

The fast-growing capability of Escherichia coli strains used to produce industrially relevant metabolites relies on their capability to transport efficiently glucose or potential industrial feedstocks such as sucrose or xylose as carbon sources. E. coli imports extracellular glucose into the periplasmic space across the outer membrane porins: OmpC, OmpF, and LamB. As the internal membrane is an impermeable barrier for sugars, the cell employs several primary and secondary active transport systems, and the phosphoenolpyruvate (PEP)-sugar phosphotransferase (PTS) system for glucose transport. PTS:glucose is the preferred system by E. coli to transport and phosphorylate the periplasmic glucose; nevertheless, PTS imposes a strict metabolic control mechanism on the preferential consumption of glucose over other carbon sources in sugar mixtures such as glucose and xylose resulting from the hydrolysis of lignocellulosic biomass, by the carbon catabolite repression. In this contribution, we summarize the major sugar transport systems for glucose and disaccharide transport, the exhibited substrate plasticity, and their impact on the growth of E. coli, highlighting the relevance of PTS in the control of the expression of genes for the transport and catabolism of other sugars as xylose. We discuss the strategies developed by evolved mutants of E. coli during adaptive laboratory evolution experiments to overcome the nutritional stress condition imposed by inactivation of PTS as a strategy for the selection of fast-growing derivatives in glucose, xylose, or mixtures of glucose:xylose. This approach results in the recruitment of other primary and secondary active transporters, demonstrating relevant sugar plasticity in derivative-evolved mutants. Elucidation of the molecular and biochemical basis of sugar-transport substrate plasticity represents a consistent approach for sugar-transport system engineering for the design of efficient E. coli derivative strains with improved substrate assimilation for biotechnological purposes.

Evolutionary causes and consequences of metabolic division of labour: why anaerobes do and aerobes don't

Metabolic division of the labour of organic matter decomposition into several steps carried out by different types of microbes is typical for many anoxic - but not oxic environments. An explanation of this well-known pattern is proposed based on the combination of three key insights: (i) well-studied anoxic environments are high flux environments: they are only anoxic because their high organic matter influx leads to oxygen depletion; (ii) shorter, incomplete catabolic pathways provide the capacity for higher flux, but this capacity is only advantageous in high flux environments; (iii) longer, complete catabolic pathways have energetic happy ends but only with high redox potential electron acceptors. Thus, aerobic environments favour longer pathways. Bioreactors, in contrast, are high flux environments and therefore favour division of catabolic labour even if aeration keeps them aerobic; therefore, host strains and feeding strategies must be carefully engineered to resist this pull.

Metabolic perturbations in mutants of glucose transporters and their applications in metabolite production in Escherichia coli

BACKGROUND

Most microorganisms have evolved to maximize growth rate, with rapid consumption of carbon sources from the surroundings. However, fast growing phenotypes usually feature secretion of organic compounds. For example, E. coli mainly produced acetate in fast growing condition such as glucose rich and aerobic condition, which is troublesome for metabolic engineering because acetate causes acidification of surroundings, growth inhibition and decline of production yield. The overflow metabolism can be alleviated by reducing glucose uptake rate.

RESULTS

As glucose transporters or their subunits were knocked out in E. coli, the growth and glucose uptake rates decreased and biomass yield was improved. Alteration of intracellular metabolism caused by the mutations was investigated with transcriptome analysis and 13C metabolic flux analysis (13C MFA). Various transcriptional and metabolic perturbations were identified in the sugar transporter mutants. Transcription of genes related to glycolysis, chemotaxis, and flagella synthesis was downregulated, and that of gluconeogenesis, Krebs cycle, alternative transporters, quorum sensing, and stress induced proteins was upregulated in the sugar transporter mutants. The specific production yields of value-added compounds (enhanced green fluorescent protein, γ-aminobutyrate, lycopene) were improved significantly in the sugar transporter mutants.

CONCLUSIONS

The elimination of sugar transporter resulted in alteration of global gene expression and redirection of carbon flux distribution, which was purposed to increase energy yield and recycle carbon sources. When the pathways for several valuable compounds were introduced to mutant strains, specific yield of them were highly improved. These results showed that controlling the sugar uptake rate is a good strategy for ameliorating metabolite production.

Acetate formation during recombinant protein production in Escherichia coli K-12 with an elevated NAD(H) pool

Acetate formation is a disadvantage in the use of Escherichia coli for recombinant protein production, and many studies have focused on optimizing fermentation processes or altering metabolism to eliminate acetate accumulation. In this study, E. coli MEC697 (MG1655 nadR nudC mazG) maintained a larger pool of NAD(H) compared to the wild-type control, and also accumulated lower concentrations of acetate when grown in batch culture on glucose. In steady-state cultures, the elevated total NAD(H) found in MEC697 delayed the threshold dilution rate for acetate formation to a growth rate of 0.27 h^-1. Batch and fed-batch processes using MEC697 were examined for the production of β-galactosidase as a model recombinant protein. Fed-batch culture of MEC697/pTrc99A-lacZ compared to MG1655/pTrc99A-lacZ at a growth rate of 0.22 h^-1 showed only a modest increase of protein formation. However, 1 L batch growth of MEC697/pTrc99A-lacZ resulted in 50% lower acetate formation compared to MG1655/pTrc99A-lacZ and a two-fold increase in recombinant protein production.