Lost in transition: start-up of glycolysis yields subpopulations of nongrowing cells

The deubiquitinase Ubp3/Usp10 constrains glucose-mediated mitochondrial repression via phosphate budgeting

Many cells in high glucose repress mitochondrial respiration, as observed in the Crabtree and Warburg effects. Our understanding of biochemical constraints for mitochondrial activation is limited. Using a Saccharomyces cerevisiae screen, we identified the conserved deubiquitinase Ubp3 (Usp10), as necessary for mitochondrial repression. Ubp3 mutants have increased mitochondrial activity despite abundant glucose, along with decreased glycolytic enzymes, and a rewired glucose metabolic network with increased trehalose production. Utilizing ∆ubp3 cells, along with orthogonal approaches, we establish that the high glycolytic flux in glucose continuously consumes free Pi. This restricts mitochondrial access to inorganic phosphate (Pi), and prevents mitochondrial activation. Contrastingly, rewired glucose metabolism with enhanced trehalose production and reduced GAPDH (as in ∆ubp3 cells) restores Pi. This collectively results in increased mitochondrial Pi and derepression, while restricting mitochondrial Pi transport prevents activation. We therefore suggest that glycolytic flux-dependent intracellular Pi budgeting is a key constraint for mitochondrial repression.

Establishing cell suitability for high-level production of licorice triterpenoids in yeast

Yeast has been an indispensable host for synthesizing complex plant-derived natural compounds, yet the yields remained largely constrained. This limitation mainly arises from overlooking the importance of cell and pathway suitability during the optimization of enzymes and pathways. Herein, beyond conventional enzyme engineering, we dissected metabolic suitability with a framework for simultaneously augmenting cofactors and carbon flux to enhance the biosynthesis of heterogenous triterpenoids. We further developed phospholipid microenvironment engineering strategies, dramatically improving yeast's suitability for the high performance of endoplasmic reticulum (ER)-localized, rate-limiting plant P450s. Combining metabolic and microenvironment suitability by manipulating only three genes, NHMGR (NADH-dependent HMG-CoA reductase), SIP4 (a DNA-binding transcription factor)and GPP1 (Glycerol-1-phosphate phosphohydrolase 1), we enabled the high-level production of 4.92 g/L rare licorice triterpenoids derived from consecutive oxidation of β-amyrin by two P450 enzymes after fermentation optimization. This production holds substantial commercial value, highlighting the critical role of establishing cell suitability in enhancing triterpenoid biosynthesis and offering a versatile framework applicable to various plant natural product biosynthetic pathways.

The significance of upper glycolytic components in regulating retinal pigment epithelial cellular behavior

Cell adhesion to the extracellular matrix and its natural outcome of cell spreading, along with the maintenance of barrier activity, are essential behaviors of epithelial cells, including retinal pigment epithelium (RPE). Disruptions in these characteristics can result in severe vision-threatening diseases such as diabetic macular edema and age-related macular degeneration. However, the precise mechanisms underlying how RPE cells regulate their barrier integrity and cell spreading are not fully understood. This study aims to elucidate the relative importance of upper glycolytic components in governing these cellular behaviors of RPE cells. Electric Cell-Substrate Impedance Sensing (ECIS) technology was utilized to assess in real-time the effects of targeting various upper glycolytic enzymes on RPE barrier function and cell spreading by measuring cell resistance and capacitance, respectively. Specific inhibitors used included WZB117 for Glut1 inhibition, Lonidamine for Hexokinase inhibition, PFK158 for PFKFB3/PFK axis inhibition, and TDZD-8 for Aldolase inhibition. Additionally, the viability of RPE cells was evaluated using a lactate dehydrogenase (LDH) cytotoxicity assay. The most significant decrease in electrical resistance and increase in capacitance of RPE cells were observed due to dose-dependent inhibition of Glut1 using WZB117, as well as Aldolase inhibition with TDZD-8. LDH level analysis at 24-72 h post-treatment with WZB117 (1 and 10 μM) or TDZD-8 (1 μM) showed no significant difference compared to the control, indicating that the disruption of RPE functionality was not attributed to cell death. Lastly, inhibition of other upper glycolytic components, including PFKFB3/PFK with PFK158 or Hexokinase with Lonidamine, did not significantly affect RPE cell behavior. This study provides insights into the varied roles of upper glycolytic components in regulating the functionality of RPE cells. Specifically, it highlights the critical roles of Glut1 and Aldolase in preserving barrier integrity and promoting RPE cell adhesion and spreading. Such understanding will guide the development of safe interventions to treat RPE cell dysfunction in various retinal disorders.

The unusual kinetics of lactate dehydrogenase of Schistosoma mansoni and their role in the rapid metabolic switch after penetration of the mammalian host

Lactate dehydrogenase (LDH) from Schistosoma mansoni has peculiar properties for a eukaryotic LDH. Schistosomal LDH (SmLDH) isolated from schistosomes, and the recombinantly expressed protein, are strongly inhibited by ATP, which is neutralized by fructose-1,6-bisphosphate (FBP). In the conserved FBP/anion binding site we identified two residues in SmLDH (Val187 and Tyr190) that differ from the conserved residues in LDHs of other eukaryotes, but are identical to conserved residues in FBP-sensitive prokaryotic LDHs. Three-dimensional (3D) models were generated to compare the structure of SmLDH with other LDHs. These models indicated that residues Val187, and especially Tyr190, play a crucial role in the interaction of FBP with the anion pocket of SmLDH. These 3D models of SmLDH are also consistent with a competitive model of SmLDH inhibition in which ATP (inhibitor) and FBP (activator) compete for binding in a well-defined anion pocket. The model of bound ATP predicts a distortion of the nearby key catalytic residue His195, resulting in enzyme inhibition. To investigate a possible physiological role of this allosteric regulation of LDH in schistosomes we made a kinetic model in which the allosteric regulation of the glycolytic enzymes can be varied. The model showed that inhibition of LDH by ATP prevents fermentation to lactate in the free-living stages in water and ensures complete oxidation via the Krebs cycle of the endogenous glycogen reserves. This mechanism of allosteric inhibition by ATP prevents the untimely depletion of these glycogen reserves, the only fuel of the free-living cercariae. Neutralization by FBP of this ATP inhibition of LDH prevents accumulation of glycolytic intermediates when S. mansoni schistosomula are confronted with the sudden large increase in glucose availability upon penetration of the final host. It appears that the LDH of S. mansoni is special and well suited to deal with the variations in glucose availability the parasite encounters during its life cycle.

Understanding and computational design of genetic circuits of metabolic networks

The expression of metabolic proteins is controlled by genetic circuits, matching metabolic demands and changing environmental conditions. Ideally, this regulation brings about a competitive level of metabolic fitness. Understanding how cells can achieve a robust (close-to-optimal) functioning of metabolism by appropriate control of gene expression aids synthetic biology by providing design criteria of synthetic circuits for biotechnological purposes. It also extends our understanding of the designs of genetic circuitry found in nature such as metabolite control of transcription factor activity, promoter architectures and transcription factor dependencies, and operon composition (in bacteria). Here, we review, explain and illustrate an approach that allows for the inference and design of genetic circuitry that steers metabolic networks to achieve a maximal flux per unit invested protein across dynamic conditions. We discuss how this approach and its understanding can be used to rationalize Escherichia coli's strategy to regulate the expression of its ribosomes and infer the design of circuitry controlling gene expression of amino-acid biosynthesis enzymes. The inferred regulation indeed resembles E. coli's circuits, suggesting that these have evolved to maximize amino-acid production fluxes per unit invested protein. We end by an outlook of the use of this approach in metabolic engineering applications.

The Imidazolium Ionic Liquids Toxicity is Due to Their Effect on the Plasma Membrane

Ionic liquids (ILs) are organic salts with a low melting point. This is due to the fact that their alkyl side chains, which are covalently connected to the ion, hinder the crystallization of ILs. The low melting point of ILs has led to their widespread use as relatively harmless solvents. However, ILs do have toxic properties, the mechanism of which is largely unknown, so identifying the cellular targets of ILs is of practical importance. In our work, we showed that imidazolium ILs are not able to penetrate model membranes without damaging them. We also found that inactivation of multidrug resistance (MDR) pumps in yeast cells does not increase their sensitivity to imidazolium ILs. The latter indicates that the target of toxicity of imidazolium ILs is not in the cytoplasm. Thus, it can be assumed that the disruption of the barrier properties of the plasma membrane is the main reason for the toxicity of low concentrations of imidazolium ILs. We also showed that supplementation with imidazolium ILs restores the growth of cells with kinetically blocked glycolysis. Apparently, a slight disruption of the plasma membrane caused by ILs can, in some cases, be beneficial for the cell.

Data integration strategies for whole-cell modeling

Data makes the world go round-and high quality data is a prerequisite for precise models, especially for whole-cell models (WCM). Data for WCM must be reusable, contain information about the exact experimental background, and should-in its entirety-cover all relevant processes in the cell. Here, we review basic requirements to data for WCM and strategies how to combine them. As a species-specific resource, we introduce the Yeast Cell Model Data Base (YCMDB) to illustrate requirements and solutions. We discuss recent standards for data as well as for computational models including the modeling process as data to be reported. We outline strategies for constructions of WCM despite their inherent complexity.

Upper glycolytic components contribute differently in controlling retinal vascular endothelial cellular behavior: Implications for endothelial-related retinal diseases

BACKGROUND

Retinal degenerative diseases such as diabetic retinopathy and diabetic macular edema are characterized by impaired retinal endothelial cells (RECs) functionality. While the role of glycolysis in glucose homeostasis is well-established, its contributions to REC barrier assembly and cell spreading remain poorly understood. This study aimed to investigate the importance of upper glycolytic components in regulating the behavior of human RECs (HRECs).

METHODS

Electric cell-substrate impedance sensing (ECIS) technology was employed to analyze the real-time impact of various upper glycolytic components on maintaining barrier functionality and cell spreading of HRECs by measuring cell resistance and capacitance, respectively. Specific inhibitors were used: WZB117 to inhibit Glut1/3, lonidamine to inhibit hexokinases, PFK158 to inhibit the PFKFB3-PFK axis, and TDZD-8 to inhibit aldolases. Additionally, the viability of HRECs was evaluated using the lactate dehydrogenase (LDH) cytotoxicity assay.

RESULTS

The most significant reduction in electrical resistance and increase in capacitance of HRECs resulted from the dose-dependent inhibition of PFKFB3/PFK using PFK158, followed by aldolase inhibition using TDZD-8. LDH level analysis at 24- and 48-hours post-treatment with PFK158 (1 μM) or TDZD-8 (1 and 10 μM) showed no significant difference compared to the control, indicating that the disruption of HRECs functionality was not attributed to cell death. Conversely, inhibiting Glut1/3 with WZB117 had minimal impact on HREC behavior, except at higher concentrations (10 μM) and prolonged exposure. Lastly, inhibiting hexokinase with lonidamine did not noticeably alter HREC cell behavior.

CONCLUSION

This study illustrates the unique impacts of components within upper glycolysis on HREC functionality, emphasizing the crucial role of the PFKFB3/PFK axis in regulating HREC behavior. Understanding the specific contributions of each glycolytic component in preserving normal REC functionality will facilitate the development of targeted interventions for treating endothelial cell dysfunction in retinal disorders while minimizing effects on healthy cells.

Disruption of trehalose periplasmic recycling dysregulates cAMP-CRP signaling in Escherichia coli during stationary phase

IMPORTANCE

Survival during starvation hinges on the ability to manage intracellular energy reserves and to initiate appropriate metabolic responses to perturbations of such reserves. How Escherichia coli manage carbon storage systems under starvation stress, as well as transpose changes in intracellular metabolite levels into regulatory signals, is not well understood. Endogenous trehalose metabolism may be at the center of these processes, coupling carbon storage with carbon starvation responses. The coupled transport to the periplasm and subsequent hydrolysis of trehalose back to glucose for transport to the cytoplasm may function as a crucial metabolic signaling pathway. Although trehalose has been characterized as a stress protectant in E. coli, the disaccharide also functions as both an energy storage compound and a regulator of carbohydrate metabolism in fungi, plants, and other bacteria. Our research explores the metabolic regulatory properties of trehalose in E. coli and a potential mechanism by which the intracellular carbon pool is interconnected with regulatory circuits, enabling long-term survival.

Improved 2,3-Butanediol Production Rate of Metabolically Engineered Saccharomyces cerevisiae by Deletion of RIM15 and Activation of Pyruvate Consumption Pathway

Saccharomyces cerevisiae is a promising host for the bioproduction of higher alcohols, such as 2,3-butanediol (2,3-BDO). Metabolically engineered S. cerevisiae strains that produce 2,3-BDO via glycolysis have been constructed. However, the specific 2,3-BDO production rates of engineered strains must be improved. To identify approaches to improving the 2,3-BDO production rate, we investigated the factors contributing to higher ethanol production rates in certain industrial strains of S. cerevisiae compared to laboratory strains. Sequence analysis of 11 industrial strains revealed the accumulation of many nonsynonymous substitutions in RIM15, a negative regulator of high fermentation capability. Comparative metabolome analysis suggested a positive correlation between the rate of ethanol production and the activity of the pyruvate-consuming pathway. Based on these findings, RIM15 was deleted, and the pyruvate-consuming pathway was activated in YHI030, a metabolically engineered S. cerevisiae strain that produces 2,3-BDO. The titer, specific production rate, and yield of 2,3-BDO in the test tube-scale culture using the YMS106 strain reached 66.4 ± 4.4 mM, 1.17 ± 0.017 mmol (g dry cell weight h)-1, and 0.70 ± 0.03 mol (mol glucose consumed)-1. These values were 2.14-, 2.92-, and 1.81-fold higher than those of the vector control, respectively. These results suggest that bioalcohol production via glycolysis can be enhanced in a metabolically engineered S. cerevisiae strain by deleting RIM15 and activating the pyruvate-consuming pathway.

Bacterial toxin-antitoxin systems: Novel insights on toxin activation across populations and experimental shortcomings

The alarming rise in hard-to-treat bacterial infections is of great concern to human health. Thus, the identification of molecular mechanisms that enable the survival and growth of pathogens is of utmost urgency for the development of more efficient antimicrobial therapies. In challenging environments, such as presence of antibiotics, or during host infection, metabolic adjustments are essential for microorganism survival and competitiveness. Toxin-antitoxin systems (TASs) consisting of a toxin with metabolic modulating activity and a cognate antitoxin that antagonizes that toxin are important elements in the arsenal of bacterial stress defense. However, the exact physiological function of TA systems is highly debatable and with the exception of stabilization of mobile genetic elements and phage inhibition, other proposed biological functions lack a broad consensus. This review aims at gaining new insights into the physiological effects of TASs in bacteria and exploring the experimental shortcomings that lead to discrepant results in TAS research. Distinct control mechanisms ensure that only subsets of cells within isogenic cultures transiently develop moderate levels of toxin activity. As a result, TASs cause phenotypic growth heterogeneity rather than cell stasis in the entire population. It is this feature that allows bacteria to thrive in diverse environments through the creation of subpopulations with different metabolic rates and stress tolerance programs.

LTP2 hypomorphs show genotype-by-environment interaction in early seedling traits in Arabidopsis thaliana

Isogenic individuals can display seemingly stochastic phenotypic differences, limiting the accuracy of genotype-to-phenotype predictions. The extent of this phenotypic variation depends in part on genetic background, raising questions about the genes involved in controlling stochastic phenotypic variation. Focusing on early seedling traits in Arabidopsis thaliana, we found that hypomorphs of the cuticle-related gene LTP2 greatly increased variation in seedling phenotypes, including hypocotyl length, gravitropism and cuticle permeability. Many ltp2 hypocotyls were significantly shorter than wild-type hypocotyls while others resembled the wild type. Differences in epidermal properties and gene expression between ltp2 seedlings with long and short hypocotyls suggest a loss of cuticle integrity as the primary determinant of the observed phenotypic variation. We identified environmental conditions that reveal or mask the increased variation in ltp2 hypomorphs, and found that increased expression of its closest paralog LTP1 is necessary for ltp2 phenotypes. Our results illustrate how decreased expression of a single gene can generate starkly increased phenotypic variation in isogenic individuals in response to an environmental challenge.

Disruption of GRR1 in Saccharomyces cerevisiae rescues tps1Δ growth on fermentable carbon sources

In Saccharomyces cerevisiae , trehalose-6-phosphate synthase (Tps1) catalyzes the formation of trehalose-6-phophate in trehalose synthesis. Deletion of the TPS1 gene is associated with phenotypes including inability to grow on fermentable carbon sources, survive at elevated temperatures, or sporulate. To further understand these pleiotropic phenotypes, we conducted a genetic suppressor screen and identified a novel suppressor, grr1 Δ, able to restore tps1 Δ growth on rapidly fermentable sugars. However, disruption of GRR1 did not rescue tps1 Δ thermosensitivity. These results support the model that trehalose metabolism has important roles in regulating glucose sensing and signaling in addition to regulating stress resistance.

The impact of metabolism on the adaptation of organisms to environmental change

Since Jacob and Monod's discovery of the lac operon ∼1960, the explanations offered for most metabolic adaptations have been genetic. The focus has been on the adaptive changes in gene expression that occur, which are often referred to as "metabolic reprogramming." The contributions metabolism makes to adaptation have been largely ignored. Here we point out that metabolic adaptations, including the associated changes in gene expression, are highly dependent on the metabolic state of an organism prior to the environmental change to which it is adapting, and on the plasticity of that state. In support of this hypothesis, we examine the paradigmatic example of a genetically driven adaptation, the adaptation of E. coli to growth on lactose, and the paradigmatic example of a metabolic driven adaptation, the Crabtree effect in yeast. Using a framework based on metabolic control analysis, we have reevaluated what is known about both adaptations, and conclude that knowledge of the metabolic properties of these organisms prior to environmental change is critical for understanding not only how they survive long enough to adapt, but also how the ensuing changes in gene expression occur, and their phenotypes post-adaptation. It would be useful if future explanations for metabolic adaptations acknowledged the contributions made to them by metabolism, and described the complex interplay between metabolic systems and genetic systems that make these adaptations possible.

Tumor heterogeneity: preclinical models, emerging technologies, and future applications

Heterogeneity describes the differences among cancer cells within and between tumors. It refers to cancer cells describing variations in morphology, transcriptional profiles, metabolism, and metastatic potential. More recently, the field has included the characterization of the tumor immune microenvironment and the depiction of the dynamics underlying the cellular interactions promoting the tumor ecosystem evolution. Heterogeneity has been found in most tumors representing one of the most challenging behaviors in cancer ecosystems. As one of the critical factors impairing the long-term efficacy of solid tumor therapy, heterogeneity leads to tumor resistance, more aggressive metastasizing, and recurrence. We review the role of the main models and the emerging single-cell and spatial genomic technologies in our understanding of tumor heterogeneity, its contribution to lethal cancer outcomes, and the physiological challenges to consider in designing cancer therapies. We highlight how tumor cells dynamically evolve because of the interactions within the tumor immune microenvironment and how to leverage this to unleash immune recognition through immunotherapy. A multidisciplinary approach grounded in novel bioinformatic and computational tools will allow reaching the integrated, multilayered knowledge of tumor heterogeneity required to implement personalized, more efficient therapies urgently required for cancer patients.

Kidney glycolysis serves as a mammalian phosphate sensor that maintains phosphate homeostasis

How phosphate levels are detected in mammals is unknown. The bone-derived hormone fibroblast growth factor 23 (FGF23) lowers blood phosphate levels by reducing kidney phosphate reabsorption and 1,25(OH)2D production, but phosphate does not directly stimulate bone FGF23 expression. Using PET scanning and LC-MS, we found that phosphate increases kidney-specific glycolysis and synthesis of glycerol-3-phosphate (G-3-P), which then circulates to bone to trigger FGF23 production. Further, we found that G-3-P dehydrogenase 1 (Gpd1), a cytosolic enzyme that synthesizes G-3-P and oxidizes NADH to NAD+, is required for phosphate-stimulated G-3-P and FGF23 production and prevention of hyperphosphatemia. In proximal tubule cells, we found that phosphate availability is substrate-limiting for glycolysis and G-3-P production and that increased glycolysis and Gpd1 activity are coupled through cytosolic NAD+ recycling. Finally, we show that the type II sodium-dependent phosphate cotransporter Npt2a, which is primarily expressed in the proximal tubule, conferred kidney specificity to phosphate-stimulated G-3-P production. Importantly, exogenous G-3-P stimulated FGF23 production when Npt2a or Gpd1 were absent, confirming that it was the key circulating factor downstream of glycolytic phosphate sensing in the kidney. Together, these findings place glycolysis at the nexus of mineral and energy metabolism and identify a kidney-bone feedback loop that controls phosphate homeostasis.

Elucidating yeast glycolytic dynamics at steady state growth and glucose pulses through kinetic metabolic modeling

Microbial cell factories face changing environments during industrial fermentations. Kinetic metabolic models enable the simulation of the dynamic metabolic response to these perturbations, but their development is challenging due to model complexity and experimental data requirements. An example of this is the well-established microbial cell factory Saccharomyces cerevisiae, for which no consensus kinetic model of central metabolism has been developed and implemented in industry. Here, we aim to bring the academic and industrial communities closer to this consensus model. We developed a physiology informed kinetic model of yeast glycolysis connected to central carbon metabolism by including the effect of anabolic reactions precursors, mitochondria and the trehalose cycle. To parametrize such a large model, a parameter estimation pipeline was developed, consisting of a divide and conquer approach, supplemented with regularization and global optimization. Additionally, we show how this first mechanistic description of a growing yeast cell captures experimental dynamics at different growth rates and under a strong glucose perturbation, is robust to parametric uncertainty and explains the contribution of the different pathways in the network. Such a comprehensive model could not have been developed without using steady state and glucose perturbation data sets. The resulting metabolic reconstruction and parameter estimation pipeline can be applied in the future to study other industrially-relevant scenarios. We show this by generating a hybrid CFD-metabolic model to explore intracellular glycolytic dynamics for the first time. The model suggests that all intracellular metabolites oscillate within a physiological range, except carbon storage metabolism, which is sensitive to the extracellular environment.

Dynamics of co-substrate pools can constrain and regulate metabolic fluxes

Cycling of co-substrates, whereby a metabolite is converted among alternate forms via different reactions, is ubiquitous in metabolism. Several cycled co-substrates are well known as energy and electron carriers (e.g. ATP and NAD(P)H), but there are also other metabolites that act as cycled co-substrates in different parts of central metabolism. Here, we develop a mathematical framework to analyse the effect of co-substrate cycling on metabolic flux. In the cases of a single reaction and linear pathways, we find that co-substrate cycling imposes an additional flux limit on a reaction, distinct to the limit imposed by the kinetics of the primary enzyme catalysing that reaction. Using analytical methods, we show that this additional limit is a function of the total pool size and turnover rate of the cycled co-substrate. Expanding from this insight and using simulations, we show that regulation of these two parameters can allow regulation of flux dynamics in branched and coupled pathways. To support these theoretical insights, we analysed existing flux measurements and enzyme levels from the central carbon metabolism and identified several reactions that could be limited by the dynamics of co-substrate cycling. We discuss how the limitations imposed by co-substrate cycling provide experimentally testable hypotheses on specific metabolic phenotypes. We conclude that measuring and controlling co-substrate dynamics is crucial for understanding and engineering metabolic fluxes in cells.

Structured population balances to support microalgae-based processes: Review of the state-of-art and perspectives analysis

Design and optimization of microalgae processes have traditionally relied on the application of unsegregated mathematical models, thus neglecting the impact of cell-to-cell heterogeneity. However, there is experimental evidence that the latter one, including but not limited to variation in mass/size, internal composition and cell cycle phase, can play a crucial role in both cultivation and downstream processes. Population balance equations (PBEs) represent a powerful approach to develop mathematical models describing the effect of cell-to-cell heterogeneity. In this work, the potential of PBEs for the analysis and design of microalgae processes are discussed. A detailed review of PBE applications to microalgae cultivation, harvesting and disruption is reported. The review is largely focused on the application of the univariate size/mass structured PBE, where the size/mass is the only internal variable used to identify the cell state. Nonetheless, the need, addressed by few studies, for additional or alternative internal variables to identify the cell cycle phase and/or provide information about the internal composition is discussed. Through the review, the limitations of previous studies are described, and areas are identified where the development of more reliable PBE models, driven by the increasing availability of single-cell experimental data, could support the understanding and purposeful exploitation of the mechanisms determining cell-to-cell heterogeneity.

Using Kinetic Modelling to Infer Adaptations in Saccharomyces cerevisiae Carbohydrate Storage Metabolism to Dynamic Substrate Conditions

Microbial metabolism is strongly dependent on the environmental conditions. While these can be well controlled under laboratory conditions, large-scale bioreactors are characterized by inhomogeneities and consequently dynamic conditions for the organisms. How Saccharomyces cerevisiae response to frequent perturbations in industrial bioreactors is still not understood mechanistically. To study the adjustments to prolonged dynamic conditions, we used published repeated substrate perturbation regime experimental data, extended it with proteomic measurements and used both for modelling approaches. Multiple types of data were combined; including quantitative metabolome, ¹³C enrichment and flux quantification data. Kinetic metabolic modelling was applied to study the relevant intracellular metabolic response dynamics. An existing model of yeast central carbon metabolism was extended, and different subsets of enzymatic kinetic constants were estimated. A novel parameter estimation pipeline based on combinatorial enzyme selection supplemented by regularization was developed to identify and predict the minimum enzyme and parameter adjustments from steady-state to dynamic substrate conditions. This approach predicted proteomic changes in hexose transport and phosphorylation reactions, which were additionally confirmed by proteome measurements. Nevertheless, the modelling also hints at a yet unknown kinetic or regulation phenomenon. Some intracellular fluxes could not be reproduced by mechanistic rate laws, including hexose transport and intracellular trehalase activity during substrate perturbation cycles.

Characterizing phenotypic diversity of trehalose biosynthesis mutants in multiple wild strains of Saccharomyces cerevisiae

In the yeast Saccharomyces cerevisiae, trehalose-6-phospahte synthase (Tps1) and trehalose-6-phosphate phosphatase (Tps2) are the main proteins catalyzing intracellular trehalose production. In addition to Tps1 and Tps2, 2 putative regulatory proteins with less clearly defined roles also appear to be involved with trehalose production, Tps3 and Tsl1. While this pathway has been extensively studied in laboratory strains of S. cerevisiae, we sought to examine the phenotypic consequences of disrupting these genes in wild strains. Here we deleted the TPS1, TPS2, TPS3, and TSL1 genes in 4 wild strains and 1 laboratory strain for comparison. Although some tested phenotypes were not shared between all strains, deletion of TPS1 abolished intracellular trehalose, caused inability to grow on fermentable carbon sources and resulted in severe sporulation deficiency for all 5 strains. After examining tps1 mutant strains expressing catalytically inactive variants of Tps1, our results indicate that Tps1, independent of trehalose production, is a key component for yeast survival in response to heat stress, for regulating sporulation, and growth on fermentable sugars. All tps2Δ mutants exhibited growth impairment on nonfermentable carbon sources, whereas variations were observed in trehalose synthesis, thermosensitivity and sporulation efficiency. tps3Δ and tsl1Δ mutants exhibited mild or no phenotypic disparity from their isogenic wild type although double mutants tps3Δ tsl1Δ decreased the amount of intracellular trehalose production in all 5 strains by 17-45%. Altogether, we evaluated, confirmed, and expanded the phenotypic characteristics associated trehalose biosynthesis mutants. We also identified natural phenotypic variants in multiple strains that could be used to genetically dissect the basis of these traits and then develop mechanistic models connecting trehalose metabolism to diverse cellular processes.

pH dependencies of glycolytic enzymes of yeast under in vivo-like assay conditions

Under carbon source transitions, the intracellular pH of Saccharomyces cerevisiae is subject to change. Dynamics in pH modulate the activity of the glycolytic enzymes, resulting in a change in glycolytic flux and ultimately cell growth. To understand how pH affects the global behavior of glycolysis and ethanol fermentation, we measured the activity of the glycolytic and fermentative enzymes in S. cerevisiae under in vivo-like conditions at different pH. We demonstrate that glycolytic enzymes exhibit differential pH dependencies, and optima, in the pH range observed during carbon source transitions. The forward reaction of GAPDH shows the highest decrease in activity, 83%, during a simulated feast/famine regime upon glucose removal (cytosolic pH drop from 7.1 to 6.4). We complement our biochemical characterization of the glycolytic enzymes by fitting the V_max to the progression curves of product formation or decay over time. The fitting analysis shows that the observed changes in enzyme activities require changes in V_max , but changes in K_m cannot be excluded. Our study highlights the relevance of pH as a key player in metabolic regulation and provides a large set of quantitative data that can be explored to improve our understanding of metabolism in dynamic environments.

13C metabolic flux analysis: Classification and characterization from the perspective of mathematical modeling and application in physiological research of neural cell

¹³C metabolic flux analysis (¹³C-MFA) has emerged as a forceful tool for quantifying in vivo metabolic pathway activity of different biological systems. This technology plays an important role in understanding intracellular metabolism and revealing patho-physiology mechanism. Recently, it has evolved into a method family with great diversity in experiments, analytics, and mathematics. In this review, we classify and characterize the various branch of ¹³C-MFA from a unified perspective of mathematical modeling. By linking different parts in the model to each step of its workflow, the specific technologies of ¹³C-MFA are put into discussion, including the isotope labeling model (ILM), isotope pattern measuring technique, optimization algorithm and statistical method. Its application in physiological research in neural cell has also been reviewed.

Trehalose biosynthetic pathway regulates filamentation response in Saccharomyces cerevisiae

BACKGROUND

Diploid cells of Saccharomyces cerevisiae undergo either pseudohyphal differentiation or sporulation in response to depletion of carbon and nitrogen sources. Distinct signaling pathways regulate filamentation and sporulation in response to nutrient limitation. How these pathways are coordinated for implementing distinct cell fate decisions in response to similar nutritional cues is an enigma. Although the role of trehalose pathway in sporulation has been extensively studied, it's possible role in pseudohyphal differentiation has been unexplored.

METHODS AND RESULTS

Briefly, tps1 and tps2 mutants were tested for their ability to form pseudohyphae independently as well as in the background of GPR1 and RAS2 mutations. Here, we demonstrate that disruption of TPS1 but not TPS2 inhibits pseudohyphae formation. Interestingly, deletion of GPR1 suppresses the above defect. Further genetic analysis revealed that TPS1 and TPS2 exert opposing effects in triggering filamentation.

CONCLUSION

We provide new insights into the role of an otherwise well-known pathway of trehalose biosynthesis in pseudohyphal differentiation. Based on additional data we propose that downstream signaling, mediated by cAMP may be modulated by nutrient mediated differential regulation of RAS2 by TPS1 and TPS2.

Full humanization of the glycolytic pathway in Saccharomyces cerevisiae

Although transplantation of single genes in yeast plays a key role in elucidating gene functionality in metazoans, technical challenges hamper humanization of full pathways and processes. Empowered by advances in synthetic biology, this study demonstrates the feasibility and implementation of full humanization of glycolysis in yeast. Single gene and full pathway transplantation revealed the remarkable conservation of glycolytic and moonlighting functions and, combined with evolutionary strategies, brought to light context-dependent responses. Human hexokinase 1 and 2, but not 4, required mutations in their catalytic or allosteric sites for functionality in yeast, whereas hexokinase 3 was unable to complement its yeast ortholog. Comparison with human tissues cultures showed preservation of turnover numbers of human glycolytic enzymes in yeast and human cell cultures. This demonstration of transplantation of an entire essential pathway paves the way for establishment of species-, tissue-, and disease-specific metazoan models.

Trade-offs predicted by metabolic network structure give rise to evolutionary specialization and phenotypic diversification

Mitigating trade-offs between different resource-utilization functions is key to an organism's ecological and evolutionary success. These trade-offs often reflect metabolic constraints with a complex molecular underpinning; therefore, their consequences for evolutionary processes have remained elusive. Here, we investigate how metabolic architecture induces resource utilization constraints and how these constraints, in turn, elicit evolutionary specialization and diversification. Guided by the metabolic network structure of the bacterium Lactococcus cremoris, we selected two carbon sources (fructose and galactose) with predicted co-utilization constraints. By evolving L. cremoris on either fructose, galactose or a mix of both sugars, we imposed selection favoring divergent metabolic specializations or co-utilization of both resources, respectively. Phenotypic characterization revealed the evolution of either fructose or galactose specialists in the single-sugar treatments. In the mixed sugar regime, we observed adaptive diversification: both specialists coexisted, and no generalist evolved. Divergence from the ancestral phenotype occurred at key pathway junctions in the central carbon metabolism. Fructose specialists evolved mutations in the fbp and pfk genes that appear to balance anabolic and catabolic carbon fluxes. Galactose specialists evolved increased expression of pgmA (the primary metabolic bottleneck of galactose metabolism) and silencing of ptnABCD (the main glucose transporter) and ldh (regulator/enzyme of downstream carbon metabolism). Overall, our study shows how metabolic network architecture and historical contingency serve to predict targets of selection and inform the functional interpretation of evolved mutations. The elucidation of the relationship between molecular constraints and phenotypic trade-offs contributes to an integrative understanding of evolutionary specialization and diversification.

Fermentation of Dairy-Relevant Sugars by Saccharomyces, Kluyveromyces, and Brettanomyces: An Exploratory Study with Implications for the Utilization of Acid Whey, Part II

In Greek-style yogurt production, every kilogram of product yields 2 to 3 kg of acid whey (YAW); this coproduct’s composition and low pH pose challenges for its proper valorization and reinsertion into the food supply chain. However, 240 mL of YAW contains over 9 g of lactose and represents a good source of minerals; these traits can be leveraged to develop nutritious fermented beverages. The purpose of this study is to investigate the aerobic fermentation of dairy sugars by different yeasts by characterizing these processes and their products. This will determine whether such methods provide viable options for the production of acetic-acid-containing beverages from YAW. To achieve this, yeast nitrogen base was used to prepare four growth media formulations, each supplemented with lactose, glucose, galactose, or a 1:1 mix of glucose and galactose (GLU:GAL), and each adjusted to a pH of 4.20. Fermentations were performed by pure cultures of S. cerevisiae, K. marxianus, B. claussenii, or B. bruxellensis, and were held at 25 °C with agitation at 185 rpm. For each treatment, density, pH, and microbial enumeration were measured over time to obtain process profiles, while ethanol, organic acids, and sugars were analyzed at the beginning and the end of each fermentation via HPLC, to determine resulting products. ANOVA and Tukey’s honest significant difference test at a significance level of 0.05 were used to compare residual sugars and fermentation products. Variable rates of sugar consumption were observed for each species. In GLU:GAL, B. claussenii consumed all of the glucose, left behind most of the galactose, and produced a high concentration of acetic acid. These results suggest the potential to develop versatile processes that target glucose for acetic acid production, while leaving available galactose to confer products with prebiotic properties. The development of processes for the conversion of YAW into beverages with organic acids and other healthful components not only aligns with consumers’ demands for better-for-you products, but also promotes the valorization of this otherwise underutilized dairy coproduct.

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

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

Multisite Enzymes as a Mechanism for Bistability in Reaction Networks

Here, we focus on a common class of enzymes that have multiple substrate binding sites (multisite enzymes) and analyze their capacity to generate bistable dynamics in the reaction networks that they are embedded in. These networks include both substrate-product-substrate cycles and substrate-to-product conversion with subsequent product consumption. Using mathematical techniques, we show that the inherent binding and catalysis reactions arising from multiple substrate-enzyme complexes create a potential for bistable dynamics in such reaction networks. We construct a generic model of an enzyme with n-substrate binding sites and derive an analytical solution for the steady-state concentration of all enzyme-substrate complexes. By studying these expressions, we obtain a mechanistic understanding of bistability, derive parameter combinations that guarantee bistability, and show how changing specific enzyme kinetic parameters and enzyme levels can lead to bistability in reaction networks involving multisite enzymes. Thus, the presented findings provide a biochemical and mathematical basis for predicting and engineering bistability in multisite enzymes.

Kinetic Modeling of Saccharomyces cerevisiae Central Carbon Metabolism: Achievements, Limitations, and Opportunities

Central carbon metabolism comprises the metabolic pathways in the cell that process nutrients into energy, building blocks and byproducts. To unravel the regulation of this network upon glucose perturbation, several metabolic models have been developed for the microorganism Saccharomyces cerevisiae. These dynamic representations have focused on glycolysis and answered multiple research questions, but no commonly applicable model has been presented. This review systematically evaluates the literature to describe the current advances, limitations, and opportunities. Different kinetic models have unraveled key kinetic glycolytic mechanisms. Nevertheless, some uncertainties regarding model topology and parameter values still limit the application to specific cases. Progressive improvements in experimental measurement technologies as well as advances in computational tools create new opportunities to further extend the model scale. Notably, models need to be made more complex to consider the multiple layers of glycolytic regulation and external physiological variables regulating the bioprocess, opening new possibilities for extrapolation and validation. Finally, the onset of new data representative of individual cells will cause these models to evolve from depicting an average cell in an industrial fermenter, to characterizing the heterogeneity of the population, opening new and unseen possibilities for industrial fermentation improvement.

Exploring dynamic metabolomics data with multiway data analysis: a simulation study

BACKGROUND

Analysis of dynamic metabolomics data holds the promise to improve our understanding of underlying mechanisms in metabolism. For example, it may detect changes in metabolism due to the onset of a disease. Dynamic or time-resolved metabolomics data can be arranged as a three-way array with entries organized according to a subjects mode, a metabolites mode and a time mode. While such time-evolving multiway data sets are increasingly collected, revealing the underlying mechanisms and their dynamics from such data remains challenging. For such data, one of the complexities is the presence of a superposition of several sources of variation: induced variation (due to experimental conditions or inborn errors), individual variation, and measurement error. Multiway data analysis (also known as tensor factorizations) has been successfully used in data mining to find the underlying patterns in multiway data. To explore the performance of multiway data analysis methods in terms of revealing the underlying mechanisms in dynamic metabolomics data, simulated data with known ground truth can be studied.

RESULTS

We focus on simulated data arising from different dynamic models of increasing complexity, i.e., a simple linear system, a yeast glycolysis model, and a human cholesterol model. We generate data with induced variation as well as individual variation. Systematic experiments are performed to demonstrate the advantages and limitations of multiway data analysis in analyzing such dynamic metabolomics data and their capacity to disentangle the different sources of variations. We choose to use simulations since we want to understand the capability of multiway data analysis methods which is facilitated by knowing the ground truth.

CONCLUSION

Our numerical experiments demonstrate that despite the increasing complexity of the studied dynamic metabolic models, tensor factorization methods CANDECOMP/PARAFAC(CP) and Parallel Profiles with Linear Dependences (Paralind) can disentangle the sources of variations and thereby reveal the underlying mechanisms and their dynamics.

Feedback regulation and coordination of the main metabolism for bacterial growth and metabolic engineering for amino acid fermentation

Living organisms such as bacteria are often exposed to continuous changes in the nutrient availability in nature. Therefore, bacteria must constantly monitor the environmental condition, and adjust the metabolism quickly adapting to the change in the growth condition. For this, bacteria must orchestrate (coordinate and integrate) the complex and dynamically changing information on the environmental condition. In particular, the central carbon metabolism (CCM), monomer synthesis, and macromolecular synthesis must be coordinately regulated for the efficient growth. It is a grand challenge in bioscience, biotechnology, and synthetic biology to understand how living organisms coordinate the metabolic regulation systems. Here, we consider the integrated sensing of carbon sources by the phosphotransferase system (PTS), and the feed-forward/feedback regulation systems incorporated in the CCM in relation to the pool sizes of flux-sensing metabolites and αketoacids. We also consider the metabolic regulation of amino acid biosynthesis (as well as purine and pyrimidine biosyntheses) paying attention to the feedback control systems consisting of (fast) enzyme level regulation with (slow) transcriptional regulation. The metabolic engineering for the efficient amino acid production by bacteria such as Escherichia coli and Corynebacterium glutamicum is also discussed (in relation to the regulation mechanisms). The amino acid synthesis is important for determining the rate of ribosome biosynthesis. Thus, the growth rate control (growth law) is further discussed on the relationship between (p)ppGpp level and the ribosomal protein synthesis.

D-Xylose Sensing in Saccharomyces cerevisiae: Insights from D-Glucose Signaling and Native D-Xylose Utilizers

Extension of the substrate range is among one of the metabolic engineering goals for microorganisms used in biotechnological processes because it enables the use of a wide range of raw materials as substrates. One of the most prominent examples is the engineering of baker's yeast Saccharomyces cerevisiae for the utilization of d-xylose, a five-carbon sugar found in high abundance in lignocellulosic biomass and a key substrate to achieve good process economy in chemical production from renewable and non-edible plant feedstocks. Despite many excellent engineering strategies that have allowed recombinant S. cerevisiae to ferment d-xylose to ethanol at high yields, the consumption rate of d-xylose is still significantly lower than that of its preferred sugar d-glucose. In mixed d-glucose/d-xylose cultivations, d-xylose is only utilized after d-glucose depletion, which leads to prolonged process times and added costs. Due to this limitation, the response on d-xylose in the native sugar signaling pathways has emerged as a promising next-level engineering target. Here we review the current status of the knowledge of the response of S. cerevisiae signaling pathways to d-xylose. To do this, we first summarize the response of the native sensing and signaling pathways in S. cerevisiae to d-glucose (the preferred sugar of the yeast). Using the d-glucose case as a point of reference, we then proceed to discuss the known signaling response to d-xylose in S. cerevisiae and current attempts of improving the response by signaling engineering using native targets and synthetic (non-native) regulatory circuits.

The phosphate language of fungi

Phosphate is an essential macronutrient for fungal proliferation as well as a key mediator of antagonistic, beneficial, and pathogenic interactions between fungi and other organisms. In this review, we summarize recent insights into the integration of phosphate metabolism with mechanisms of fungal adaptation that support growth and survival. In particular, we highlight aspects of phosphate sensing important for responses to stress and regulation of cell-surface changes with an impact on fungal pathogenesis, host immune responses, and disease outcomes. Additionally, new studies provide insights into the influence of phosphate availability on cooperative or antagonistic interactions between fungi and other microbes, the associations of mycorrhizal and endophytic fungi with plants, and connections with plant immunity. Overall, phosphate homeostasis is emerging as an integral part of fungal metabolism and communication to support diverse lifestyles.

Evolution and function of carbohydrate reserve biosynthesis in parasitic protists

Nearly all eukaryotic cells synthesize carbohydrate reserves, such as glycogen, starch, or low-molecular-weight oligosaccharides. However, a number of parasitic protists have lost this capacity while others have lost, and subsequently evolved, entirely new pathways. Recent studies suggest that retention, loss, or acquisition of these pathways in different protists is intimately linked to their lifestyle. In particular, parasites with carbohydrate reserves often establish long-lived chronic infections and/or produce environmental cysts, whereas loss of these pathways is associated with parasites that have highly proliferative and metabolically active life-cycle stages. The evolution of mannogen biosynthesis in Leishmania and related parasites indicates that these pathways have played a role in defining the host range and niches occupied by some protists.

A yeast FRET biosensor enlightens cAMP signaling

The cAMP-PKA signaling cascade in budding yeast regulates adaptation to changing environments. We developed yEPAC, a FRET-based biosensor for cAMP measurements in yeast. We used this sensor with flow cytometry for high-throughput single cell-level quantification during dynamic changes in response to sudden nutrient transitions. We found that the characteristic cAMP peak differentiates between different carbon source transitions and is rather homogenous among single cells, especially for transitions to glucose. The peaks are mediated by a combination of extracellular sensing and intracellular metabolism. Moreover, the cAMP peak follows the Weber-Fechner law; its height scales with the relative, and not the absolute, change in glucose. Last, our results suggest that the cAMP peak height conveys information about prospective growth rates. In conclusion, our yEPAC-sensor makes possible new avenues for understanding yeast physiology, signaling, and metabolic adaptation.

Gene expression regulates metabolite homeostasis during the Crabtree effect: Implications for the adaptation and evolution of Metabolism

A key issue in both molecular and evolutionary biology has been to define the roles of genes and phenotypes in the adaptation of organisms to environmental changes. The dominant view has been that an organism's metabolic adaptations are driven by gene expression and that gene mutations, independent of the starting phenotype, are responsible for the evolution of new metabolic phenotypes. We propose an alternate hypothesis, in which the phenotype and genotype together determine metabolic adaptation both in the lifetime of the organism and in the evolutionary selection of adaptive metabolic traits. We tested this hypothesis by flux-balance and metabolic-control analysis of the relative roles of the starting phenotype and gene expression in regulating the metabolic adaptations during the Crabtree effect in yeast, when they are switched from a low- to high-glucose environment. Critical for successful short-term adaptation was the ability of the glycogen/trehalose shunt to balance the glycolytic pathway. The role of later gene expression of new isoforms of glycolytic enzymes, rather than flux control, was to provide additional homeostatic mechanisms allowing an increase in the amount and efficiency of adenosine triphosphate and product formation while maintaining glycolytic balance. We further showed that homeostatic mechanisms, by allowing increased phenotypic plasticity, could have played an important role in guiding the evolution of the Crabtree effect. Although our findings are specific to Crabtree yeast, they are likely to be broadly found because of the well-recognized similarities in glucose metabolism across kingdoms and phyla from yeast to humans.

The closure issue related to liquid-cell mass transfer and substrate uptake dynamics in biological systems

An original dynamic model for substrate uptake under transient conditions is established and used to simulate a variety of biological responses to external perturbations. The actual uptake and growth rates, treated as cell properties, are part of the model variables as well as the substrate concentration at the cell-liquid interface. Several regulatory loops inspired by the structure of the glycolytic chain are considered to establish a set of ordinary differential equations. The uptake rate evolves so as to reach an equilibrium between the cell demand and the environmental supply. This model does not contain any of the usual algebraic closure laws relating to the instantaneous uptake, growth rates, and the substrate concentration, nor does it enforce the continuity of mass fluxes at the liquid-cell interface. However, these relationships are found in the steady-state solution. Previously unexplained experimental observations are well reproduced by this model. Also, the model structure is suitable for further coupling with flux-based metabolic models and fluid-flow equations.

Single-cell metabolic imaging reveals a SLC2A3-dependent glycolytic burst in motile endothelial cells

Single-cell motility is spatially heterogeneous and driven by metabolic energy. Directly linking cell motility to cell metabolism is technically challenging but biologically important. Here, we use single-cell metabolic imaging to measure glycolysis in individual endothelial cells with genetically encoded biosensors capable of deciphering metabolic heterogeneity at subcellular resolution. We show that cellular glycolysis fuels endothelial activation, migration and contraction and that sites of high lactate production colocalize with active cytoskeletal remodelling within an endothelial cell. Mechanistically, RhoA induces endothelial glycolysis for the phosphorylation of cofilin and myosin light chain in order to reorganize the cytoskeleton and thus control cell motility; RhoA activation triggers a glycolytic burst through the translocation of the glucose transporter SLC2A3/GLUT3 to fuel the cellular contractile machinery, as demonstrated across multiple endothelial cell types. Our data indicate that Rho-GTPase signalling coordinates energy metabolism with cytoskeleton remodelling to regulate endothelial cell motility.

Phosphoproteome Study of Escherichia coli Devoid of Ser/Thr Kinase YeaG During the Metabolic Shift From Glucose to Malate

Understanding phosphorylation-mediated regulation of metabolic enzymes, pathways, and cell phenotypes under metabolic shifts represents a major challenge. The kinases associated with most phosphorylation sites and the link between phosphorylation and enzyme activity remain unknown. In this study, we performed stable isotope labeling by amino acids in cell culture (SILAC)-based proteome and phosphoproteome analysis of Escherichia coli ΔyeaG, a strain lacking a poorly characterized serine/threonine kinase YeaG, to decipher kinase-substrate interactions and the effects on metabolic phenotype during shifts from glucose to malate. The starting point of our analysis was the identification of physiological conditions under which ΔyeaG exhibits a clear phenotype. By metabolic profiling, we discovered that ΔyeaG strain has a significantly shorter lag phase than the wild type during metabolic shift from glucose to malate. Under those conditions, our SILAC analysis revealed several proteins that were differentially phosphorylated in the ΔyeaG strain. By focusing on metabolic enzymes potentially involved in central carbon metabolism, we narrowed down our search for putative YeaG substrates and identified isocitrate lyase AceA as the direct substrate of YeaG. YeaG was capable of phosphorylating AceA in vitro only in the presence of malate, suggesting that this phosphorylation event is indeed relevant for glucose to malate shift. There is currently not enough evidence to firmly establish the exact mechanism of this newly observed regulatory phenomenon. However, our study clearly exemplifies the usefulness of SILAC-based approaches in identifying proteins kinase substrates, when applied in physiological conditions relevant for the activity of the protein kinase in question.

Global coordination of metabolic pathways in Escherichia coli by active and passive regulation

Microorganisms adjust metabolic activity to cope with diverse environments. While many studies have provided insights into how individual pathways are regulated, the mechanisms that give rise to coordinated metabolic responses are poorly understood. Here, we identify the regulatory mechanisms that coordinate catabolism and anabolism in Escherichia coli. Integrating protein, metabolite, and flux changes in genetically implemented catabolic or anabolic limitations, we show that combined global and local mechanisms coordinate the response to metabolic limitations. To allocate proteomic resources between catabolism and anabolism, E. coli uses a simple global gene regulatory program. Surprisingly, this program is largely implemented by a single transcription factor, Crp, which directly activates the expression of catabolic enzymes and indirectly reduces the expression of anabolic enzymes by passively sequestering cellular resources needed for their synthesis. However, metabolic fluxes are not controlled by this regulatory program alone; instead, fluxes are adjusted mostly through passive changes in the local metabolite concentrations. These mechanisms constitute a simple but effective global regulatory program that coarsely partitions resources between different parts of metabolism while ensuring robust coordination of individual metabolic reactions.

Cycles, sources, and sinks: Conceptualizing how phosphate balance modulates carbon flux using yeast metabolic networks

Phosphates are ubiquitous molecules that enable critical intracellular biochemical reactions. Therefore, cells have elaborate responses to phosphate limitation. Our understanding of long-term transcriptional responses to phosphate limitation is extensive. Contrastingly, a systems-level perspective presenting unifying biochemical concepts to interpret how phosphate balance is critically coupled to (and controls) metabolic information flow is missing. To conceptualize such processes, utilizing yeast metabolic networks we categorize phosphates utilized in metabolism into cycles, sources and sinks. Through this, we identify metabolic reactions leading to putative phosphate sources or sinks. With this conceptualization, we illustrate how mass action driven flux towards sources and sinks enable cells to manage phosphate availability during transient/immediate phosphate limitations. We thereby identify how intracellular phosphate availability will predictably alter specific nodes in carbon metabolism, and determine signature cellular metabolic states. Finally, we identify a need to understand intracellular phosphate pools, in order to address mechanisms of phosphate regulation and restoration.

Insights on the Control of Yeast Single-Cell Growth Variability by Members of the Trehalose Phosphate Synthase (TPS) Complex

Single-cell variability of growth is a biological phenomenon that has attracted growing interest in recent years. Important progress has been made in the knowledge of the origin of cell-to-cell heterogeneity of growth, especially in microbial cells. To better understand the origins of such heterogeneity at the single-cell level, we developed a new methodological pipeline that coupled cytometry-based cell sorting with automatized microscopy and image analysis to score the growth rate of thousands of single cells. This allowed investigating the influence of the initial amount of proteins of interest on the subsequent growth of the microcolony. As a preliminary step to validate this experimental setup, we referred to previous findings in yeast where the expression level of Tsl1, a member of the Trehalose Phosphate Synthase (TPS) complex, negatively correlated with cell division rate. We unfortunately could not find any influence of the initial TSL1 expression level on the growth rate of the microcolonies. We also analyzed the effect of the natural variations of trehalose-6-phosphate synthase (TPS1) expression on cell-to-cell growth heterogeneity, but we did not find any correlation. However, due to the already known altered growth of the tps1Δ mutants, we tested this strain at the single-cell level on a permissive carbon source. This mutant showed an outstanding lack of reproducibility of growth rate distributions as compared to the wild-type strain, with variable proportions of non-growing cells between cultivations and more heterogeneous microcolonies in terms of individual growth rates. Interestingly, this variable behavior at the single-cell level was reminiscent to the high variability that is also stochastically suffered at the population level when cultivating this tps1Δ strain, even when using controlled bioreactors.

Model reduction of genome-scale metabolic models as a basis for targeted kinetic models

Constraint-based, genome-scale metabolic models are an essential tool to guide metabolic engineering. However, they lack the detail and time dimension that kinetic models with enzyme dynamics offer. Model reduction can be used to bridge the gap between the two methods and allow for the integration of kinetic models into the Design-Built-Test-Learn cycle. Here we show that these reduced size models can be representative of the dynamics of the original model and demonstrate the automated generation and parameterisation of such models. Using these minimal models of metabolism could allow for further exploration of dynamic responses in metabolic networks.

Selection for rapid uptake of scarce or fluctuating resource explains vulnerability of glycolysis to imbalance

Glycolysis is a conserved central pathway in energy metabolism that converts glucose to pyruvate with net production of two ATP molecules. Because ATP is produced only in the lower part of glycolysis (LG), preceded by an initial investment of ATP in the upper glycolysis (UG), achieving robust start-up of the pathway upon activation presents a challenge: a sudden increase in glucose concentration can throw a cell into a self-sustaining imbalanced state in which UG outpaces LG, glycolytic intermediates accumulate and the cell is unable to maintain high ATP concentration needed to support cellular functions. Such metabolic imbalance can result in "substrate-accelerated death", a phenomenon observed in prokaryotes and eukaryotes when cells are exposed to an excess of substrate that previously limited growth. Here, we address why evolution has apparently not eliminated such a costly vulnerability and propose that it is a manifestation of an evolutionary trade-off, whereby the glycolysis pathway is adapted to quickly secure scarce or fluctuating resource at the expense of vulnerability in an environment with ample resource. To corroborate this idea, we perform individual-based eco-evolutionary simulations of a simplified yeast glycolysis pathway consisting of UG, LG, phosphate transport between a vacuole and a cytosol, and a general ATP demand reaction. The pathway is evolved in constant or fluctuating resource environments by allowing mutations that affect the (maximum) reaction rate constants, reflecting changing expression levels of different glycolytic enzymes. We demonstrate that under limited constant resource, populations evolve to a genotype that exhibits balanced dynamics in the environment it evolved in, but strongly imbalanced dynamics under ample resource conditions. Furthermore, when resource availability is fluctuating, imbalanced dynamics confers a fitness advantage over balanced dynamics: when glucose is abundant, imbalanced pathways can quickly accumulate the glycolytic intermediate FBP as intracellular storage that is used during periods of starvation to maintain high ATP concentration needed for growth. Our model further predicts that in fluctuating environments, competition for glucose can result in stable coexistence of balanced and imbalanced cells, as well as repeated cycles of population crashes and recoveries that depend on such polymorphism. Overall, we demonstrate the importance of ecological and evolutionary arguments for understanding seemingly maladaptive aspects of cellular metabolism.

Regulation of trehalase activity by multi-site phosphorylation and 14-3-3 interaction

Protein phosphorylation enables a rapid adjustment of cellular activities to diverse intracellular and environmental stimuli. Many phosphoproteins are targeted on more than one site, which allows the integration of multiple signals and the implementation of complex responses. However, the hierarchy and interplay between multiple phospho-sites are often unknown. Here, we study multi‐site phosphorylation using the yeast trehalase Nth1 and its activator, the 14-3-3 protein Bmh1, as a model. Nth1 is known to be phosphorylated by the metabolic kinase PKA on four serine residues and by the cell cycle kinase CDK on one residue. However, how these five phospho-sites adjust Nth1 activity remains unclear. Using a novel reporter construct, we investigated the contribution of the individual sites for the regulation of the trehalase and its 14-3-3 interactor. In contrast to the constitutively phosphorylated S20 and S83, the weaker sites S21 and S60 are only phosphorylated by increased PKA activity. For binding Bmh1, S83 functions as the high‐affinity “gatekeeper” site, but successful binding of the Bmh1 dimer and thus Nth1 activation requires S60 as a secondary site. Under nutrient-poor conditions with low PKA activity, S60 is not efficiently phosphorylated and the cell cycle dependent phosphorylation of S66 by Cdk1 contributes to Nth1 activity, likely by providing an alternative Bmh1 binding site. Additionally, the PKA sites S20 and S21 modulate the dephosphorylation of Nth1 on downstream Bmh1 sites. In summary, our results expand our molecular understanding of Nth1 regulation and provide a new aspect of the interaction of 14-3-3 proteins with their targets.

Exploring the effect of network topology, mRNA and protein dynamics on gene regulatory network stability

Homeostasis of protein concentrations in cells is crucial for their proper functioning, requiring steady-state concentrations to be stable to fluctuations. Since gene expression is regulated by proteins such as transcription factors (TFs), the full set of proteins within the cell constitutes a large system of interacting components, which can become unstable. We explore factors affecting stability by coupling the dynamics of mRNAs and proteins in a growing cell. We find that mRNA degradation rate does not affect stability, contrary to previous claims. However, global structural features of the network can dramatically enhance stability. Importantly, a network resembling a bipartite graph with a lower fraction of interactions that target TFs has a higher chance of being stable. Scrambling the E. coli transcription network, we find that the biological network is significantly more stable than its randomized counterpart, suggesting that stability constraints may have shaped network structure during the course of evolution.

Impact of Altered Trehalose Metabolism on Physiological Response of Penicillium chrysogenum Chemostat Cultures during Industrially Relevant Rapid Feast/Famine Conditions

Due to insufficient mass transfer and mixing issues, cells in the industrial-scale bioreactor are often forced to experience glucose feast/famine cycles, mostly resulting in reduced commercial metrics (titer, yield and productivity). Trehalose cycling has been confirmed as a double-edged sword in the Penicillium chrysogenum strain, which facilitates the maintenance of a metabolically balanced state, but it consumes extra amounts of the ATP responsible for the repeated breakdown and formation of trehalose molecules in response to extracellular glucose perturbations. This loss of ATP would be in competition with the high ATP-demanding penicillin biosynthesis. In this work, the role of trehalose metabolism was further explored under industrially relevant conditions by cultivating a high-yielding Penicillium chrysogenum strain, and the derived trehalose-null strains in the glucose-limited chemostat system where the glucose feast/famine condition was imposed. This dynamic feast/famine regime with a block-wise feed/no feed regime (36 s on, 324 s off) allows one to generate repetitive cycles of moderate changes in glucose availability. The results obtained using quantitative metabolomics and stoichiometric analysis revealed that the intact trehalose metabolism is vitally important for maintaining penicillin production capacity in the Penicillium chrysogenum strain under both steady state and dynamic conditions. Additionally, cells lacking such a key metabolic regulator would become more sensitive to industrially relevant conditions, and are more able to sustain metabolic rearrangements, which manifests in the shrinkage of the central metabolite pool size and the formation of ATP-consuming futile cycles.

Serial propagation in water-in-oil emulsions selects for Saccharomyces cerevisiae strains with a reduced cell size or an increased biomass yield on glucose

In S. cerevisiae and many other micro-organisms an increase in metabolic efficiency (i.e. ATP yield on carbon) is accompanied by a decrease in growth rate. From a fundamental point of view, studying these yield-rate trade-offs provides insight in for example microbial evolution and cellular regulation. From a biotechnological point of view, increasing the ATP yield on carbon might increase the yield of anabolic products. We here aimed to select S. cerevisiae mutants with an increased biomass yield. Serial propagation of individual cells in water-in-oil emulsions previously enabled the selection of lactococci with increased biomass yields, and adapting this protocol for yeast allowed us to enrich an engineered Crabtree-negative S. cerevisiae strain with a high biomass yield on glucose. When we started the selection with an S. cerevisiae deletion collection, serial propagation in emulsion enriched hxk2Δ and reg1Δ strains with an increased biomass yield on glucose. Surprisingly, a tps1Δ strain was highly abundant in both emulsion- and suspension-propagated populations. In a separate experiment we propagated a chemically mutagenized S. cerevisiae population in emulsion, which resulted in mutants with a higher cell number yield on glucose, but no significantly changed biomass yield. Genome analyses indicate that genes involved in glucose repression and cell cycle processes play a role in the selected phenotypes. The repeated identification of mutations in genes involved in glucose-repression indicates that serial propagation in emulsion is a valuable tool to study metabolic efficiency in S. cerevisiae.