Escherichia coli responds with a rapid and large change in growth rate upon a shift from glucose-limited to glucose-excess conditions

Fermentation Analytical Technology (FAT): Monitoring industrial E. coli fermentations using absolute quantitative 1H NMR spectroscopy

BACKGROUND

To perform fast, reproducible, and absolute quantitative measurements in an automated manner has become of paramount importance when monitoring industrial processes, including fermentations. Due to its numerous advantages - including its inherent quantitative nature - Proton Nuclear Magnetic Resonance (1H NMR) spectroscopy provides an ideal tool for the time-resolved monitoring of fermentations. However, analytical conditions, including non-automated sample preparation and long relaxation times (T1) of some metabolites, can significantly lengthen the experimental time and make implementation in an industrial set up unfeasible.

RESULTS

We present a high throughput method based on Standard Operating Procedures (SOPs) and 1H NMR, which lays the foundation for what we call Fermentation Analytical Technology (FAT). Our method was developed for the accurate absolute quantification of metabolites produced during Escherichia coli industrial fermentations. The method includes: (1) a stopped flow system for non-invasive sample collection followed by sample quenching, (2) automatic robot-assisted sample preparation, (3) fast 1H NMR measurements, (4) metabolites quantification using multivariate curve resolution (MCR), and (5) metabolites absolute quantitation using a novel correction factor (k) to compensate for the short recycle delay (D1) employed in the 1H NMR measurements. The quantification performance was tested using two sample types: buffer solutions of chemical standards and real fermentation samples. Five metabolites - glucose, acetate, alanine, phenylalanine and betaine - were quantified. Absolute quantitation ranged between 0.64 and 3.40 mM in pure buffer, and 0.71-7.76 mM in real samples.

SIGNIFICANCE

The proposed method is generic and can be straight forward implemented to other types of fermentations, such as lactic acid, ethanol and acetic acid fermentations. It provides a high throughput automated solution for monitoring fermentation processes and for quality control through absolute quantification of key metabolites in fermentation broth. It can be easily implemented in an at-line industrial setting, facilitating the optimization of the manufacturing process towards higher yields and more efficient and sustainable use of resources.

A comprehensive study of glucose and oxygen gradients in a scaled-down model of recombinant HuGM-CSF production in thermoinduced Escherichia coli fed-batch cultures

The effect of gradients of elevated glucose and low dissolved oxygen in the addition zone of fed-batch E. coli thermoinduced recombinant high cell density cultures can be evaluated through two-compartment scale-down models. Here, glucose was fed in the inlet of a plug flow bioreactor (PFB) connected to a stirred tank bioreactor (STB). E. coli cells diminished growth from 48.2 ± 2.2 g/L in the stage of RP production if compared to control (STB) with STB-PFB experiments, when residence time inside the PFB was 25 s (34.1 ± 3.5 g/L) and 40 s (25.6 ± 5.1 g/L), respectively. The recombinant granulocyte-macrophage colony-stimulating factor (rHuGM-CSF) production decreased from 34 ± 7% of RP in inclusion bodies (IB) in control cultures to 21 ± 8%, and 7 ± 4% during the thermoinduction production phase when increasing residence time inside the PFB to 25 s and 40 s, respectively. This, along with the accumulation of acetic and formic acid (up to 4 g/L), indicates metabolic redirection of central carbon routes through metabolic flow and mixed acid fermentation. Special care must be taken when producing a recombinant protein in heat-induced E. coli, because the yield and productivity of the protein decreases as the size of the bioreactors increases, especially if they are carried at high cell density.

A Unique Response Behavior in the Dissolved Oxygen Tension in E. coli Minibioreactor Cultivations with Intermittent Feeding

Intermittent bolus feeding for E. coli cultivations in minibioreactor systems (MBRs) profoundly affects the cell metabolism. Bolus feeding leads to temporal substrate surplus and transient oxygen limitation, which triggers the formation of inhibitory byproducts. Due to the high oxygen demand right after the injection of the substrate, the dissolved oxygen tension (DOT) signal exhibits a negative pulse. This contribution describes and analyzes this DOT response in E. coli minibioreactor cultivations. In addition to gaining information on culture conditions, a unique response behavior in the DOT signal was observed in the analysis. This response appeared only at a dilution ratio per biomass unit higher than a certain threshold. The analysis highlights a plausible relationship between a metabolic adaptation behavior and the newly observed DOT signal segment not reported in the literature. A hypothesis that links particular DOT segments to specific metabolic states is proposed. The quantitative analysis and mechanistic model simulations support this hypothesis and show the possibility of obtaining cell physiological and growth parameters from the DOT signal.

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.

Changes in Oxygen Availability during Glucose-Limited Chemostat Cultivations of Penicillium chrysogenum Lead to Rapid Metabolite, Flux and Productivity Responses

Bioreactor scale-up from the laboratory scale to the industrial scale has always been a pivotal step in bioprocess development. However, the transition of a bioeconomy from innovation to commercialization is often hampered by performance loss in titer, rate and yield. These are often ascribed to temporal variations of substrate and dissolved oxygen (for instance) in the environment, experienced by microorganisms at the industrial scale. Oscillations in dissolved oxygen (DO) concentration are not uncommon. Furthermore, these fluctuations can be exacerbated with poor mixing and mass transfer limitations, especially in fermentations with filamentous fungus as the microbial cell factory. In this work, the response of glucose-limited chemostat cultures of an industrial Penicillium chrysogenum strain to different dissolved oxygen levels was assessed under both DO shift-down (60% → 20%, 10% and 5%) and DO ramp-down (60% → 0% in 24 h) conditions. Collectively, the results revealed that the penicillin productivity decreased as the DO level dropped down below 20%, while the byproducts, e.g., 6-oxopiperidine-2-carboxylic acid (OPC) and 6-aminopenicillanic acid (6APA), accumulated. Following DO ramp-down, penicillin productivity under DO shift-up experiments returned to its maximum value in 60 h when the DO was reset to 60%. The result showed that a higher cytosolic redox status, indicated by NADH/NAD+, was observed in the presence of insufficient oxygen supply. Consistent with this, flux balance analysis indicated that the flux through the glyoxylate shunt was increased by a factor of 50 at a DO value of 5% compared to the reference control, favoring the maintenance of redox status. Interestingly, it was observed that, in comparison with the reference control, the penicillin productivity was reduced by 25% at a DO value of 5% under steady state conditions. Only a 14% reduction in penicillin productivity was observed as the DO level was ramped down to 0. Furthermore, intracellular levels of amino acids were less sensitive to DO levels at DO shift-down relative to DO ramp-down conditions; this difference could be caused by different timescales between turnover rates of amino acid pools (tens of seconds to minutes) and DO switches (hours to days at steady state and minutes to hours at ramp-down). In summary, this study showed that changes in oxygen availability can lead to rapid metabolite, flux and productivity responses, and dynamic DO perturbations could provide insight into understanding of metabolic responses in large-scale bioreactors.

Cofactor Specificity of Glucose-6-Phosphate Dehydrogenase Isozymes in Pseudomonas putida Reveals a General Principle Underlying Glycolytic Strategies in Bacteria

Glucose-6-phosphate dehydrogenase (G6PDH) is widely distributed in nature and catalyzes the first committing step in the oxidative branch of the pentose phosphate (PP) pathway, feeding either the reductive PP or the Entner-Doudoroff pathway. Besides its role in central carbon metabolism, this dehydrogenase provides reduced cofactors, thereby affecting redox balance. Although G6PDH is typically considered to display specificity toward NADP⁺, some variants accept NAD⁺ similarly or even preferentially. Furthermore, the number of G6PDH isozymes encoded in bacterial genomes varies from none to more than four orthologues. On this background, we systematically analyzed the interplay of the three G6PDH isoforms of the soil bacterium Pseudomonas putida KT2440 from genomic, genetic, and biochemical perspectives. P. putida represents an ideal model to tackle this endeavor, as its genome harbors gene orthologues for most dehydrogenases in central carbon metabolism. We show that the three G6PDHs of strain KT2440 have different cofactor specificities and that the isoforms encoded by zwfA and zwfB carry most of the activity, acting as metabolic “gatekeepers” for carbon sources that enter at different nodes of the biochemical network. Moreover, we demonstrate how multiplication of G6PDH isoforms is a widespread strategy in bacteria, correlating with the presence of an incomplete Embden-Meyerhof-Parnas pathway. The abundance of G6PDH isoforms in these species goes hand in hand with low NADP⁺ affinity, at least in one isozyme. We propose that gene duplication and relaxation in cofactor specificity is an evolutionary strategy toward balancing the relative production of NADPH and NADH.

IMPORTANCE Protein families have likely arisen during evolution by gene duplication and divergence followed by neofunctionalization. While this phenomenon is well documented for catabolic activities (typical of environmental bacteria that colonize highly polluted niches), the coexistence of multiple isozymes in central carbon catabolism remains relatively unexplored. We have adopted the metabolically versatile soil bacterium Pseudomonas putida KT2440 as a model to interrogate the physiological and evolutionary significance of coexisting glucose-6-phosphate dehydrogenase (G6PDH) isozymes. Our results show that each of the three G6PDHs in this bacterium display distinct biochemical properties, especially at the level of cofactor preference, impacting bacterial physiology in a carbon source-dependent fashion. Furthermore, the presence of multiple G6PDHs differing in NAD⁺ or NADP⁺ specificity in bacterial species strongly correlates with their predominant metabolic lifestyle. Our findings support the notion that multiplication of genes encoding cofactor-dependent dehydrogenases is a general evolutionary strategy toward achieving redox balance according to the growth conditions.

Understanding gradients in industrial bioreactors

Gradients in industrial bioreactors have attracted substantial research attention since exposure to fluctuating environmental conditions has been shown to lead to changes in the metabolome, transcriptome as well as population heterogeneity in industrially relevant microorganisms. Such changes have also been found to impact key process parameters like the yield on substrate and the productivity. Hence, understanding gradients is important from both the academic and industrial perspectives. In this review the causes of gradients are outlined, along with their impact on microbial physiology. Quantifying the impact of gradients requires a detailed understanding of both fluid flow inside industrial equipment and microbial physiology. This review critically examines approaches used to investigate gradients including large-scale experimental work, computational methods and scale-down approaches. Avenues for future work have been highlighted, particularly the need for further coordinated development of both in silico and experimental tools which can be used to further the current understanding of gradients in industrial equipment.

Data-driven in silico prediction of regulation heterogeneity and ATP demands of Escherichia coli in large-scale bioreactors

Escherichia coli exposed to industrial-scale heterogeneous mixing conditions respond to external stress by initiating short-term metabolic and long-term strategic transcriptional programs. In native habitats, long-term strategies allow survival in severe stress but are of limited use in large bioreactors, where microenvironmental conditions may change right after said programs are started. Related on/off switching of genes causes additional ATP burden that may reduce the cellular capacity for producing the desired product. Here, we present an agent-based data-driven model linked to computational fluid dynamics, finally allowing to predict additional ATP needs of Escherichia coli K12 W3110 exposed to realistic large-scale bioreactor conditions. The complex model describes transcriptional up- and downregulation dynamics of about 600 genes starting from subminute range covering 28 h. The data-based approach was extracted from comprehensive scale-down experiments. Simulating mixing and mass transfer conditions in a 54 m³ stirred bioreactor, 120,000 E. coli cells were tracked while fluctuating between different zones of glucose availability. It was found that cellular ATP demands rise between 30% and 45% of growth decoupled maintenance needs, which may limit the production of ATP-intensive product formation accordingly. Furthermore, spatial analysis of individual cell transcriptional patterns reveal very heterogeneous gene amplifications with hot spots of 50%-80% messenger RNA upregulation in the upper region of the bioreactor. The phenomenon reflects the time-delayed regulatory response of the cells that propagate through the stirred tank. After 4.2 h, cells adapt to environmental changes but still have to bear an additional 6% ATP demand.

Escherichia coli metabolism under short-term repetitive substrate dynamics: adaptation and trade-offs

Background

Microbial metabolism is highly dependent on the environmental conditions. Especially, the substrate concentration, as well as oxygen availability, determine the metabolic rates. In large-scale bioreactors, microorganisms encounter dynamic conditions in substrate and oxygen availability (mixing limitations), which influence their metabolism and subsequently their physiology. Earlier, single substrate pulse experiments were not able to explain the observed physiological changes generated under large-scale industrial fermentation conditions.

Results

In this study we applied a repetitive feast–famine regime in an aerobic Escherichia coli culture in a time-scale of seconds. The regime was applied for several generations, allowing cells to adapt to the (repetitive) dynamic environment. The observed response was highly reproducible over the cycles, indicating that cells were indeed fully adapted to the regime. We observed an increase of the specific substrate and oxygen consumption (average) rates during the feast–famine regime, compared to a steady-state (chemostat) reference environment. The increased rates at same (average) growth rate led to a reduced biomass yield (30% lower). Interestingly, this drop was not followed by increased by-product formation, pointing to the existence of energy-spilling reactions. During the feast–famine cycle, the cells rapidly increased their uptake rate. Within 10 s after the beginning of the feeding, the substrate uptake rate was higher (4.68 μmol/g_CDW/s) than reported during batch growth (3.3 μmol/g_CDW/s). The high uptake led to an accumulation of several intracellular metabolites, during the feast phase, accounting for up to 34% of the carbon supplied. Although the metabolite concentrations changed rapidly, the cellular energy charge remained unaffected, suggesting well-controlled balance between ATP producing and ATP consuming reactions.

Conclusions

The adaptation of the physiology and metabolism of E. coli under substrate dynamics, representative for large-scale fermenters, revealed the existence of several cellular mechanisms coping with stress. Changes in the substrate uptake system, storage potential and energy-spilling processes resulted to be of great importance. These metabolic strategies consist a meaningful step to further tackle reduced microbial performance, observed under large-scale cultivations.

Unveiling dynamic metabolic signatures in human induced pluripotent and neural stem cells

Metabolism plays an essential role in cell fate decisions. However, the methods used for metabolic characterization and for finding potential metabolic regulators are still based on characterizing cellular metabolic steady-state which is dependent on the extracellular environment. In this work, we hypothesized that the response dynamics of intracellular metabolic pools to extracellular stimuli is controlled in a cell type-specific manner. We applied principles of process dynamics and control to human induced pluripotent stem cells (hiPSC) and human neural stem cells (hNSC) subjected to a sudden extracellular glutamine step. The fold-changes of steady-states and the transient profiles of metabolic pools revealed that dynamic responses were reproducible and cell type-specific. Importantly, many amino acids had conserved dynamics and readjusted their steady state concentration in response to the increased glutamine influx. Overall, we propose a novel methodology for systematic metabolic characterization and identification of potential metabolic regulators.

Quantitative Flow Cytometry to Understand Population Heterogeneity in Response to Changes in Substrate Availability in Escherichia coli and Saccharomyces cerevisiae Chemostats

Microbial cells in bioprocesses are usually described with averaged parameters. But in fact, single cells within populations vary greatly in characteristics such as stress resistance, especially in response to carbon source gradients. Our aim was to introduce tools to quantify population heterogeneity in bioprocesses using a combination of reporter strains, flow cytometry, and easily comprehensible parameters. We calculated mean, mode, peak width, and coefficient of variance to describe distribution characteristics and temporal shifts in fluorescence intensity. The skewness and the slope of cumulative distribution function plots illustrated differences in distribution shape. These parameters are person-independent and precise. We demonstrated this by quantifying growth-related population heterogeneity of Saccharomyces cerevisiae and Escherichia coli reporter strains in steady-state of aerobic glucose-limited chemostat cultures at different dilution rates and in response to glucose pulses. Generally, slow-growing cells showed stronger responses to glucose excess than fast-growing cells. Cell robustness, measured as membrane integrity after exposure to freeze-thaw treatment, of fast-growing cells was strongly affected in subpopulations of low membrane robustness. Glucose pulses protected subpopulations of fast-growing but not slower-growing yeast cells against membrane damage. Our parameters could successfully describe population heterogeneity, thereby revealing physiological characteristics that might have been overlooked during traditional averaged analysis.

Dynamic metabolic response of Aspergillus niger to glucose perturbation: evidence of regulatory mechanism for reduced glucoamylase production

Environmental gradient is an important common issue during scale-up process for protein production. To address the dynamic regulatory mechanism of Aspergillus niger being exposed to inhomogeneous glucose concentrations, glucose perturbation were experimented on the steady state of A. niger chemostat culture, and dynamic profiles of the intracellular metabolites in central carbon metabolism were tracked in a time scale of seconds. The upper glycolysis and pentose phosphate pathway showed sharp variations after glucose perturbation, while the lower glycolysis, TCA cycle and amino acid pools represented a moderate and prolonged response due to the allosteric regulation of enzymes and buffering function of metabolites with large pool sizes. Improved glucose-6-phosphate enhanced the metabolic flux to PP pathway remarkably, which provided not only more redox cofactors (NADPH) for protein synthesis but also more precursors (phosphoribosyl pyrophosphate and ribose-5-phosphate) for cell growth. Moreover, reduction of the total adenine nucleotides and major precursor amino acids indicated the upregulated RNA synthesis was required to produce stress proteins, and partially explained the drop of glucoamylase production when A. niger experienced a fluctuated glucose concentration environment. These findings would be valuable for improving bioreactor operation, design, and scale-up from engineering or genetic aspects.

Advances in bio-based production of dicarboxylic acids longer than C4

Growing concerns of environmental pollution and fossil resource shortage are major driving forces for bio-based production of chemicals traditionally from petrochemical industry. Dicarboxylic acids (DCAs) are important platform chemicals with large market and wide applications, and here the recent advances in bio-based production of straight-chain DCAs longer than C4 from biological approaches, especially by synthetic biology, are reviewed. A couple of pathways were recently designed and demonstrated for producing DCAs, even those ranging from C5 to C15, by employing respective starting units, extending units, and appropriate enzymes. Furthermore, in order to achieve higher production of DCAs, enormous efforts were made in engineering microbial hosts that harbored the biosynthetic pathways and in improving properties of biocatalytic elements to enhance metabolic fluxes toward target DCAs. Here we summarize and discuss the current advantages and limitations of related pathways, and also provide perspectives on synthetic pathway design and optimization for hyper-production of DCAs.

RapidRIP quantifies the intracellular metabolome of 7 industrial strains of E. coli

Fast metabolite quantification methods are required for high throughput screening of microbial strains obtained by combinatorial or evolutionary engineering approaches. In this study, a rapid RIP-LC-MS/MS (RapidRIP) method for high-throughput quantitative metabolomics was developed and validated that was capable of quantifying 102 metabolites from central, amino acid, energy, nucleotide, and cofactor metabolism in less than 5 minutes. The method was shown to have comparable sensitivity and resolving capability as compared to a full length RIP-LC-MS/MS method (FullRIP). The RapidRIP method was used to quantify the metabolome of seven industrial strains of E. coli revealing significant differences in glycolytic, pentose phosphate, TCA cycle, amino acid, and energy and cofactor metabolites were found. These differences translated to statistically and biologically significant differences in thermodynamics of biochemical reactions between strains that could have implications when choosing a host for bioprocessing.

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.

Beyond topology: coevolution of structure and flux in metabolic networks

Interactions between the structure of a metabolic network and its functional properties underlie its evolutionary diversification, but the mechanism by which such interactions arise remains elusive. Particularly unclear is whether metabolic fluxes that determine the concentrations of compounds produced by a metabolic network, are causally linked to a network's structure or emerge independently of it. A direct empirical study of populations where both structural and functional properties vary among individuals' metabolic networks is required to establish whether changes in structure affect the distribution of metabolic flux. In a population of house finches (Haemorhous mexicanus), we reconstructed full carotenoid metabolic networks for 442 individuals and uncovered 11 structural variants of this network with different compounds and reactions. We examined the consequences of this structural diversity for the concentrations of plumage-bound carotenoids produced by flux in these networks. We found that concentrations of metabolically derived, but not dietary carotenoids, depended on network structure. Flux was partitioned similarly among compounds in individuals of the same network structure: within each network, compound concentrations were closely correlated. The highest among-individual variation in flux occurred in networks with the strongest among-compound correlations, suggesting that changes in the magnitude, but not the distribution of flux, underlie individual differences in compound concentrations on a static network structure. These findings indicate that the distribution of flux in carotenoid metabolism closely follows network structure. Thus, evolutionary diversification and local adaptations in carotenoid metabolism may depend more on the gain or loss of enzymatic reactions than on changes in flux within a network structure.

Metabolic regulation is sufficient for global and robust coordination of glucose uptake, catabolism, energy production and growth in Escherichia coli

The metabolism of microorganisms is regulated through two main mechanisms: changes of enzyme capacities as a consequence of gene expression modulation (“hierarchical control”) and changes of enzyme activities through metabolite-enzyme interactions. An increasing body of evidence indicates that hierarchical control is insufficient to explain metabolic behaviors, but the system-wide impact of metabolic regulation remains largely uncharacterized. To clarify its role, we developed and validated a detailed kinetic model of Escherichia coli central metabolism that links growth to environment. Metabolic control analyses confirm that the control is widely distributed across the network and highlight strong interconnections between all the pathways. Exploration of the model solution space reveals that several robust properties emerge from metabolic regulation, from the molecular level (e.g. homeostasis of total metabolite pool) to the overall cellular physiology (e.g. coordination of carbon uptake, catabolism, energy and redox production, and growth), while allowing a large degree of flexibility at most individual metabolic steps. These properties have important physiological implications for E. coli and significantly expand the self-regulating capacities of its metabolism.

Metabolism is a fundamental biochemical process that enables cells to operate and grow by converting nutrients into ‘building blocks’ and energy. Metabolism happens through the work of enzymes, which are encoded by genes. Thus, genes and their regulation are often thought of controlling metabolism, somewhat at the top of a hierarchical control system. However, an increasing body of evidence indicates that metabolism plays an active role in the control of its own operation via a dense network of metabolite-enzyme interactions. The system-wide role of metabolic regulation is hard to dissect and so far remains largely uncharacterized. To better understand its role, we constructed a detailed kinetic model of the carbon and energy metabolism of the bacterium Escherichia coli, a model organism in Systems and Synthetic biology. Model simulations indicate that kinetic considerations of metabolism alone can explain data from hundreds of experiments, without needing to invoke regulation of gene expression. In particular, metabolic regulation is sufficient to coordinate carbon utilization, redox and energy production, and growth, while maintaining local flexibility at individual metabolic steps. These findings indicate that the self-regulating capacities of E. coli metabolism are far more significant than previously expected, and improve our understanding on how cells work.

Analysis of intracellular metabolites of Corynebacterium glutamicum at high cell density with automated sampling and filtration and assessment of engineered enzymes for effective l-lysine production

Engineering of enzymes and pathways is generally required for the development of efficient strains for bioproduction processes. To this end, quantitative and reliable data of intracellular metabolites are highly desired, but often not available, especially for conditions more close to industrial applications, i.e. at high cell density and product concentration. Here, we investigated the intracellular metabolite profiles of an engineered l-lysine-producing Corynebacterium glutamicum strain and the corresponding wild-type strain to assess the impacts of deregulation of product inhibition of the key enzymes aspartate kinase and phosphoenolpyruvate carboxylase and to identify potentials for their further improvement. A bioreactor system with automated fast-sampling, filtration and on-filter quenching of the metabolism was used for a more reliable determination of intracellular metabolites in batch cultures with optical cell density (OD₆₆₀) up to 40. The l-lysine-producing strain showed substantially different metabolite profiles in the amino acid metabolism, including increased intracellular pool sizes in the l-lysine-, l-homoserine- and l-threonine pathways and decreased intracellular pool sizes for all other determined amino acids. By comparing data of in vitro inhibition of the engineered enzymes and determined intracellular concentrations of the inhibitors it was found that the inferred in vivo activities of these enzymes are still significantly below their in vitro maximums. This work demonstrates the usefulness of metabolic analysis for assessing the impact of engineered enzymes and identifying targets for further strain development.

The Landscape of Evolution: Reconciling Structural and Dynamic Properties of Metabolic Networks in Adaptive Diversifications

The network of the interactions among genes, proteins, and metabolites delineates a range of potential phenotypic diversifications in a lineage, and realized phenotypic changes are the result of differences in the dynamics of the expression of the elements and interactions in this deterministic network. Regulatory mechanisms, such as hormones, mediate the relationship between the structural and dynamic properties of networks by determining how and when the elements are expressed and form a functional unit or state. Changes in regulatory mechanisms lead to variable expression of functional states of a network within and among generations. Functional properties of network elements, and the magnitude and direction of evolutionary change they determine, depend on their location within a network. Here, we examine the relationship between network structure and the dynamic mechanisms that regulate flux through a metabolic network. We review the mechanisms that control metabolic flux in enzymatic reactions and examine structural properties of the network locations that are targets of flux control. We aim to establish a predictive framework to test the contributions of structural and dynamic properties of deterministic networks to evolutionary diversifications.

Bacterial metabolism in immediate response to nutritional perturbation with temporal and network view of metabolites

In this study, the initial propagation of metabolic perturbation in Escherichia coli was visualized to understand the dynamic characteristics of the metabolic pathways without the association of transcription alterations. E. coli cells were exposed to the sudden relief of glucose starvation, and time-dependent variances in metabolite balances were traced in the second scale. The acquired time-course data were represented by structural variations of the metabolite-metabolite correlation network. The initial correlation structure was altered immediately by the glucose pulse, followed by further structural variations within a few minutes. It was demonstrated that one metabolite temporally correlated with distinct metabolites with different timings, and such a behavior could imply a regulatory role for the metabolite in the metabolic network. Centrality analysis of the networks and partial correlation analysis indicated that preparation for growth and oxidative stress could be coupled as a structural property of the metabolic pathways.

Proteome reallocation in Escherichia coli with increasing specific growth rate

Cells usually respond to changing growth conditions with a change in the specific growth rate (μ) and adjustment of their proteome to adapt and maintain metabolic efficiency. Description of the principles behind proteome resource allocation is important for understanding metabolic regulation in response to changing μ. Thus, we analysed the proteome resource allocation dynamics of Escherichia coli into different metabolic processes in response to changing μ. E. coli was grown on minimal and defined rich media in steady state continuous cultures at different μ and characterised combining two LC-MS/MS-based proteomics methods: stable isotope labelling by amino acids in cell culture (SILAC) and intensity based label-free absolute quantification. We detected slowly growing cells investing more proteome resources in energy generation and carbohydrate transport and metabolism whereas for achieving faster growth cells needed to devote most resources to translation and processes closely related to the protein synthesis pipeline. Furthermore, down-regulation of energy generation and carbohydrate metabolism proteins with faster growth displayed very similar expression dynamics with the global transcriptional regulator CRP (cyclic AMP receptor protein), pointing to a dominant protein resource allocating role of this protein. Our data also suggest that acetate overflow may be the result of global proteome resource optimisation as cells saved proteome resources by switching from fully respiratory to respiro-fermentative growth. The presented results give a quantitative overview of how E. coli adjusts its proteome to achieve faster growth and in future could contribute to the design of more efficient cell factories through proteome optimisation.

Comparative fluxome and metabolome analysis for overproduction of succinate in Escherichia coli

An aerobic succinate-producing Escherichia coli mutant was compared to its wild-type by quantitatively analyzing both the metabolome and fluxome, during glucose-limited steady-state and succinate excess dynamic conditions, in order to identify targets for further strain engineering towards more efficient succinate production. The mutant had four functional mutations under the conditions investigated: increased expression of a succinate exporter (DcuC), deletion of a succinate importer (Dct), deletion of succinate dehydrogenase (SUCDH) and expression of a PEP carboxylase (PPC) with increased capacity due to a point mutation. The steady-state and dynamic patterns of the intracellular metabolite levels and fluxes in response to changes were used to locate the quantitative differences in the physiology/metabolism of the mutant strain. Unexpectedly the mutant had a higher energy efficiency, indicated by a much lower rate of oxygen consumption, under glucose-limited conditions, caused by the deletion of the transcription factors IclR and ArcA. Furthermore the mutant had a much lower uptake capacity for succinate (26-fold) and oxygen (17-fold under succinate excess) compared to the wild-type strain. The mutant strain produced 7.9 mmol.CmolX(-1).h(-1) succinate during chemostat cultivation, showing that the choice of the applied genetic modifications was a successful strategy. Furthermore, the applied genetic modifications resulted in multiple large changes in metabolite levels (FBP, pyruvate, 6PG, NAD(+) /NADH ratio, α-ketogluarate) corresponding to large changes in fluxes. Compared to the wild-type a considerable flux shift occurred from the tricarboxylic acid (TCA) cycle to the oxidative part of the pentose phosphate pathway, including an inversion of the pyruvate kinase flux. The mutant responded very differently to excess of succinate, with a remarkable possible reversal of the TCA cycle. The mutant and the wild-type both showed homeostatic behaviour with respect to the energy charge. In contrast, large changes in redox ratios (NAD(+) /NADH) occurred in the wild-type, while the mutant showed even larger changes. This large redox change can be associated to the reversal of flux directions. The observed large flexibility in the central metabolism following genetic (deletions) and environmental (substrate excess) perturbations of the mutant, indicates that introducing a more efficient succinate exporter could result in an even higher succinate production rate.

Perturbation Experiments: Approaches for Metabolic Pathway Analysis in Bioreactors

In the last decades, targeted metabolic engineering of microbial cells has become one of the major tools in bioprocess design and optimization. For successful application, a detailed knowledge is necessary about the relevant metabolic pathways and their regulation inside the cells. Since in vitro experiments cannot display process conditions and behavior properly, process data about the cells' metabolic state have to be collected in vivo. For this purpose, special techniques and methods are necessary. Therefore, most techniques enabling in vivo characterization of metabolic pathways rely on perturbation experiments, which can be divided into dynamic and steady-state approaches. To avoid any process disturbance, approaches which enable perturbation of cell metabolism in parallel to the continuing production process are reasonable. Furthermore, the fast dynamics of microbial production processes amplifies the need of parallelized data generation. These points motivate the development of a parallelized approach for multiple metabolic perturbation experiments outside the operating production reactor. An appropriate approach for in vivo characterization of metabolic pathways is presented and applied exemplarily to a microbial L-phenylalanine production process on a 15 L-scale.

Escherichia coli achieves faster growth by increasing catalytic and translation rates of proteins

Regulation levels of the gene expression cascade controlling protein levels and metabolic fluxes for cells to achieve faster growth have not been elaborated in acceptable detail. Furthermore, there is need for specific growth rate (μ) dependent absolute quantitative transcriptome and proteome data to understand the molecular relationships for enabling cells to modify μ. We address these questions, for the first time, by presenting regulatory strategies for more efficient metabolism of Escherichia coli at higher μ by statistical covariance analysis of genome-wide intracellular mRNA and protein concentrations coupled to metabolic flux analysis in the steady state range of μ = 0.11-0.49 h(-1). Our analyses show dominating post-transcriptional control of protein abundances and post-translational control of flux rates. On average, E. coli achieved five-times faster growth through 3.7-fold increase of apparent catalytic rates of enzymes (kapp) and 2.5-fold increased translation rates, demonstrating the relevance of post-translational regulation for increasing flux throughput. Interestingly, pathways carrying the highest flux showed both high protein abundance and kapp values. Furthermore, co-regulation analysis of enzymatic capacities revealed tightly coupled regulatory dependencies of protein synthesis and RNA precursor synthesis, substrate utilization, biosynthetic and energy generation pathways carrying the highest flux. We also observed metabolic pathway and COG specific protein and metabolic flux control levels, protein expression costs and genome-wide principles for translation efficiency and transcription unit polarity. This work contributes to the much needed quantitative understanding of coordinated gene expression regulation and metabolic flux control. Our findings will also advance modeling and metabolic engineering of industrial strains.

A model-driven quantitative metabolomics analysis of aerobic and anaerobic metabolism in E. coli K-12 MG1655 that is biochemically and thermodynamically consistent

The advent of model-enabled workflows in systems biology allows for the integration of experimental data types with genome-scale models to discover new features of biology. This work demonstrates such a workflow, aimed at establishing a metabolomics platform applied to study the differences in metabolomes between anaerobic and aerobic growth of Escherichia coli. Constraint-based modeling was utilized to deduce a target list of compounds for downstream method development. An analytical and experimental methodology was developed and tailored to the compound chemistry and growth conditions of interest. This included the construction of a rapid sampling apparatus for use with anaerobic cultures. The resulting genome-scale data sets for anaerobic and aerobic growth were validated by comparison to previous small-scale studies comparing growth of E. coli under the same conditions. The metabolomics data were then integrated with the E. coli genome-scale metabolic model (GEM) via a sensitivity analysis that utilized reaction thermodynamics to reconcile simulated growth rates and reaction directionalities. This analysis highlighted several optimal network usage inconsistencies, including the incorrect use of the beta-oxidation pathway for synthesis of fatty acids. This analysis also identified enzyme promiscuity for the pykA gene, that is critical for anaerobic growth, and which has not been previously incorporated into metabolic models of E coli.

Flux imbalance analysis and the sensitivity of cellular growth to changes in metabolite pools

Stoichiometric models of metabolism, such as flux balance analysis (FBA), are classically applied to predicting steady state rates - or fluxes - of metabolic reactions in genome-scale metabolic networks. Here we revisit the central assumption of FBA, i.e. that intracellular metabolites are at steady state, and show that deviations from flux balance (i.e. flux imbalances) are informative of some features of in vivo metabolite concentrations. Mathematically, the sensitivity of FBA to these flux imbalances is captured by a native feature of linear optimization, the dual problem, and its corresponding variables, known as shadow prices. First, using recently published data on chemostat growth of Saccharomyces cerevisae under different nutrient limitations, we show that shadow prices anticorrelate with experimentally measured degrees of growth limitation of intracellular metabolites. We next hypothesize that metabolites which are limiting for growth (and thus have very negative shadow price) cannot vary dramatically in an uncontrolled way, and must respond rapidly to perturbations. Using a collection of published datasets monitoring the time-dependent metabolomic response of Escherichia coli to carbon and nitrogen perturbations, we test this hypothesis and find that metabolites with negative shadow price indeed show lower temporal variation following a perturbation than metabolites with zero shadow price. Finally, we illustrate the broader applicability of flux imbalance analysis to other constraint-based methods. In particular, we explore the biological significance of shadow prices in a constraint-based method for integrating gene expression data with a stoichiometric model. In this case, shadow prices point to metabolites that should rise or drop in concentration in order to increase consistency between flux predictions and gene expression data. In general, these results suggest that the sensitivity of metabolic optima to violations of the steady state constraints carries biologically significant information on the processes that control intracellular metabolites in the cell.

Metabolic responses of Saccharomyces cerevisiae to valine and ammonium pulses during four-stage continuous wine fermentations

Nitrogen supplementation, which is widely used in winemaking to improve fermentation kinetics, also affects the products of fermentation, including volatile compounds. However, the mechanisms underlying the metabolic response of yeast to nitrogen additions remain unclear. We studied the consequences for Saccharomyces cerevisiae metabolism of valine and ammonium pulses during the stationary phase of four-stage continuous fermentation (FSCF). This culture technique provides cells at steady state similar to that of the stationary phase of batch wine fermentation. Thus, the FSCF device is an appropriate and reliable tool for individual analysis of the metabolic rerouting associated with nutrient additions, in isolation from the continuous evolution of the environment in batch processes. Nitrogen additions, irrespective of the nitrogen-containing compound added, substantially modified the formation of fermentation metabolites, including glycerol, succinate, isoamyl alcohol, propanol, and ethyl esters. This flux redistribution, fulfilling the requirements for precursors of amino acids, was consistent with increased protein synthesis resulting from increased nitrogen availability. Valine pulses, less efficient than ammonium addition in increasing the fermentation rate, were followed by a massive conversion of this amino acid in isobutanol and isobutyl acetate through the Ehrlich pathway. However, additional routes were involved in valine assimilation when added in stationary phase. Overall, we found that particular metabolic changes may be triggered according to the nature of the amino acid supplied, in addition to the common response. Both these shared and specific modifications should be considered when designing strategies to modulate the production of volatile compounds, a current challenge for winemakers.

Changes in substrate availability in Escherichia coli lead to rapid metabolite, flux and growth rate responses

The interactions between the intracellular metabolome, fluxome and growth rate of Escherichia coli after sudden glycolytic/gluconeogenic substrate shifts are studied based on pulses of different substrates to an aerobic glucose-limited steady-state (dilution rate=0.1h(-1)). After each added glycolytic (glucose) and gluconeogenic (pyruvate and succinate) substrate pulse, no by-products were secreted and a pseudo steady state in flux and metabolites was achieved in about 30-40s. In the pulse experiments a large oxygen uptake capacity of the cells was observed. The in vivo dynamic responses showed massive reorganization and flexibility (1/100-14-fold change) of extra/intracellular metabolic fluxes, matching with large changes in the concentrations of intracellular metabolites, including reversal of reaction rate for pseudo/near equilibrium reactions. The coupling of metabolome and fluxome could be described by Q-linear kinetics. Remarkably, the three different substrate pulses resulted in a very similar increase in growth rate (0.13-0.3h(-1)). Data analysis showed that there must exist as yet unknown mechanisms which couple the protein synthesis rate to changes in central metabolites.

Systematic applications of metabolomics in metabolic engineering

The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis of extracellular or intracellular levels of the target compound (or a few closely related molecules) to drive metabolic engineering is quite common. However, there is surprisingly little systematic use of metabolomics datasets, which simultaneously measure hundreds of metabolites rather than just a few, for that same purpose. Here, we review the most common systematic approaches to integrating metabolite data with metabolic engineering, with emphasis on existing efforts to use whole-metabolome datasets. We then review some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, and discuss current computational approaches that explicitly use metabolomics data. We conclude with discussion of the broader potential of computational approaches that systematically use metabolomics data to drive metabolic engineering.

Comparison of the transient responses of Escherichia coli to a glucose pulse of various intensities

Dynamic stimulus-responses of Escherichia coli DPD2085, yciG::LuxCDABE reporter strain, to glucose pulses of different intensities (0.08, 0.4 and 1 g L(-1)) were compared using glucose-limited chemostat cultures at dilution rate close to 0.15 h(-1). After at least five residence times, the steady-state cultures were disturbed by a pulse of glucose, engendering conditions of glucose excess with concomitant oxygen limitation. In all conditions, glucose consumption, acetate and formate accumulations followed a linear relationship with time. The resulting specific uptake and production rates as well as respiratory rates were rapidly increased within the first seconds, which revealed a high ability of E. coli strain to modulate its metabolism to a new environment. For transition from glucose-excess to glucose-limited conditions, the cells rapidly re-established its pseudo-steady state. The dynamics of transient responses at the macroscopic viewpoint were shown to be independent on the glucose pulse intensity in the tested range. On the contrary, the E. coli biosensor yciG::luxCDABE revealed a transcriptional induction of yciG gene promoter depending on the quantities of the glucose added, through in situ and online monitoring of the bioluminescence emitted by the cells. Despite many studies describing the dynamics of the transient response of E. coli to glucose perturbations, it is the first time that a direct comparison is reported, using the same experimental design (strain, medium and experimental set up), to study the impact of the glucose pulse intensity on the dynamics of microbial behaviour regarding growth, respiration and metabolite productions.

Real-time monitoring of metabolic shift and transcriptional induction of yciG::luxCDABE E. coli reporter strain to a glucose pulse of different concentrations

Ineffective mixing entailing heterogeneity issue within industrial bioreactors has been reported to affect microbial physiology and consequently bioprocess performances. Alteration of these performances results from microorganism ability to modulate their physiology at metabolic and/or transcriptional levels in order to survive in a given environment. Until now, dynamics of both metabolic and transcriptional microbial response to external stimuli have been investigated using mainly ex situ measurements with sampling and/or quenching constraints. This work showed an in situ bioluminescence approach for real-time monitoring of characteristic stress responses of Escherichia coli containing yciG::luxCDABE reporter to glucose pulses in well-controlled steady-state chemostat cultures. Reproducibility of in situ bioluminescence profiles was assessed. A dramatic transient increase in the bioluminescence intensity (sharp peak) was observed for a complete depletion of sugars and for a sudden decrease in the dilution rate. This response was connected to a sudden change of the metabolic activity. On the contrary a bell curve of bioluminescence intensity, dose-dependent, was related to an induction of transcriptional activity. Real-time monitoring of the bioluminescence signal with time-span less than a second gave access to the characteristic times of the metabolic shift and transcriptional induction of the stress response.