Network identification and flux quantification in the central metabolism of Saccharomyces cerevisiae under different conditions of glucose repression

A hub for regulation of mitochondrial metabolism: Fatty acid and lipoic acid biosynthesis

Having evolved from a prokaryotic origin, mitochondria retain pathways required for the catabolism of energy-rich molecules and for the biosynthesis of molecules that aid catabolism and/or participate in other cellular processes essential for life of the cell. Reviewed here are details of the mitochondrial fatty acid biosynthetic pathway (FAS II) and its role in building both the octanoic acid precursor for lipoic acid biosynthesis (LAS) and longer-chain fatty acids functioning in chaperoning the assembly of mitochondrial multisubunit complexes. Also covered are the details of mitochondrial lipoic acid biosynthesis, which is distinct from that of prokaryotes, and the attachment of lipoic acid to subunits of pyruvate dehydrogenase, α-ketoglutarate dehydrogenase, and glycine cleavage system complexes. Special emphasis has been placed on presenting what is currently known about the interconnected paths and loops linking the FAS II-LAS pathway and two other mitochondrial realms, the organellar translation machinery and Fe-S cluster biosynthesis and function.

Reversing the directionality of reactions between non-oxidative pentose phosphate pathway and glycolytic pathway boosts mycosporine-like amino acid production in Saccharomyces cerevisiae

BACKGROUND

Mycosporine-like amino acids (MAAs) are a class of strongly UV-absorbing compounds produced by cyanobacteria, algae and corals and are promising candidates for natural sunscreen components. Low MAA yields from natural sources, coupled with difficulties in culturing its native producers, have catalyzed synthetic biology-guided approaches to produce MAAs in tractable microbial hosts like Escherichia coli, Saccharomyces cerevisiae and Corynebacterium glutamicum. However, the MAA titres obtained in these hosts are still low, necessitating a thorough understanding of cellular factors regulating MAA production.

RESULTS

To delineate factors that regulate MAA production, we constructed a shinorine (mycosporine-glycine-serine) producing yeast strain by expressing the four MAA biosynthetic enzymes from Nostoc punctiforme in Saccharomyces cerevisiae. We show that shinorine is produced from the pentose phosphate pathway intermediate sedoheptulose 7-phosphate (S7P), and not from the shikimate pathway intermediate 3-dehydroquinate (3DHQ) as previously suggested. Deletions of transaldolase (TAL1) and phosphofructokinase (PFK1/PFK2) genes boosted S7P/shinorine production via independent mechanisms. Unexpectedly, the enhanced S7P/shinorine production in the PFK mutants was not entirely due to increased flux towards the pentose phosphate pathway. We provide multiple lines of evidence in support of a reversed pathway between glycolysis and the non-oxidative pentose phosphate pathway (NOPPP) that boosts S7P/shinorine production in the phosphofructokinase mutant cells.

CONCLUSION

Reversing the direction of flux between glycolysis and the NOPPP offers a novel metabolic engineering strategy in Saccharomyces cerevisiae.

Mitochondrial Metabolism in the Spotlight: Maintaining Balanced RNAP III Activity Ensures Cellular Homeostasis

RNA polymerase III (RNAP III) holoenzyme activity and the processing of its products have been linked to several metabolic dysfunctions in lower and higher eukaryotes. Alterations in the activity of RNAP III-driven synthesis of non-coding RNA cause extensive changes in glucose metabolism. Increased RNAP III activity in the S. cerevisiae maf1Δ strain is lethal when grown on a non-fermentable carbon source. This lethal phenotype is suppressed by reducing tRNA synthesis. Neither the cause of the lack of growth nor the underlying molecular mechanism have been deciphered, and this area has been awaiting scientific explanation for a decade. Our previous proteomics data suggested mitochondrial dysfunction in the strain. Using model mutant strains maf1Δ (with increased tRNA abundance) and rpc128-1007 (with reduced tRNA abundance), we collected data showing major changes in the TCA cycle metabolism of the mutants that explain the phenotypic observations. Based on 13C flux data and analysis of TCA enzyme activities, the present study identifies the flux constraints in the mitochondrial metabolic network. The lack of growth is associated with a decrease in TCA cycle activity and downregulation of the flux towards glutamate, aspartate and phosphoenolpyruvate (PEP), the metabolic intermediate feeding the gluconeogenic pathway. rpc128-1007, the strain that is unable to increase tRNA synthesis due to a mutation in the C128 subunit, has increased TCA cycle activity under non-fermentable conditions. To summarize, cells with non-optimal activity of RNAP III undergo substantial adaptation to a new metabolic state, which makes them vulnerable under specific growth conditions. Our results strongly suggest that balanced, non-coding RNA synthesis that is coupled to glucose signaling is a fundamental requirement to sustain a cell's intracellular homeostasis and flexibility under changing growth conditions. The presented results provide insight into the possible role of RNAP III in the mitochondrial metabolism of other cell types.

High throughput 13C-metabolic flux analysis of 3-hydroxypropionic acid producing Pichia pastoris reveals limited availability of acetyl-CoA and ATP due to tight control of the glycolytic flux

BACKGROUND

Production of 3-hydroxypropionic acid (3-HP) through the malonyl-CoA pathway has yielded promising results in Pichia pastoris (Komagataella phaffii), demonstrating the potential of this cell factory to produce this platform chemical and other acetyl-CoA-derived products using glycerol as a carbon source. However, further metabolic engineering of the original P. pastoris 3-HP-producing strains resulted in unexpected outcomes, e.g., significantly lower product yield and/or growth rate. To gain an understanding on the metabolic constraints underlying these observations, the fluxome (metabolic flux phenotype) of ten 3-HP-producing P. pastoris strains has been characterized using a high throughput ¹³C-metabolic flux analysis platform. Such platform enabled the operation of an optimised workflow to obtain comprehensive maps of the carbon flux distribution in the central carbon metabolism in a parallel-automated manner, thereby accelerating the time-consuming strain characterization step in the design-build-test-learn cycle for metabolic engineering of P. pastoris.

RESULTS

We generated detailed maps of the carbon fluxes in the central carbon metabolism of the 3-HP producing strain series, revealing the metabolic consequences of different metabolic engineering strategies aimed at improving NADPH regeneration, enhancing conversion of pyruvate into cytosolic acetyl-CoA, or eliminating by-product (arabitol) formation. Results indicate that the expression of the POS5 NADH kinase leads to a reduction in the fluxes of the pentose phosphate pathway reactions, whereas an increase in the pentose phosphate pathway fluxes was observed when the cytosolic acetyl-CoA synthesis pathway was overexpressed. Results also show that the tight control of the glycolytic flux hampers cell growth due to limited acetyl-CoA biosynthesis. When the cytosolic acetyl-CoA synthesis pathway was overexpressed, the cell growth increased, but the product yield decreased due to higher growth-associated ATP costs. Finally, the six most relevant strains were also cultured at pH 3.5 to assess the effect of a lower pH on their fluxome. Notably, similar metabolic fluxes were observed at pH 3.5 compared to the reference condition at pH 5.

CONCLUSIONS

This study shows that existing fluoxomics workflows for high-throughput analyses of metabolic phenotypes can be adapted to investigate P. pastoris, providing valuable information on the impact of genetic manipulations on the metabolic phenotype of this yeast. Specifically, our results highlight the metabolic robustness of P. pastoris's central carbon metabolism when genetic modifications are made to increase the availability of NADPH and cytosolic acetyl-CoA. Such knowledge can guide further metabolic engineering of these strains. Moreover, insights into the metabolic adaptation of P. pastoris to an acidic pH have also been obtained, showing the capability of the fluoxomics workflow to assess the metabolic impact of environmental changes.

The Warburg effect and mitochondrial oxidative phosphorylation: Friends or foes?

Cancer cells display an altered energy metabolism, which was proposed to be the root of cancer. This early discovery was done by O. Warburg who conducted one of the first studies of tumor cell energy metabolism. Taking advantage of cancer cells that exhibited various growth rates, he showed that cancer cells display a decreased respiration and an increased glycolysis proportional to the increase in their growth rate, suggesting that they mainly depend on fermentative metabolism for ATP generation. Warburg's results and hypothesis generated controversies that are persistent to this day. It is thus of great importance to understand the mechanisms by which cancer cells can reversibly regulate the two pathways of their energy metabolism as well as the functioning of this metabolism in cell proliferation. In this review, we discuss of the origin of the decrease in cell respiratory rate, whether the Warburg effect is mandatory for an increased cell proliferation rate, the consequences of this effect on two major players of cell energy metabolism that are ATP and NADH, and the role of the microenvironment in the regulation of cellular respiration and metabolism both in cancer cell and in yeast.

Metabolic engineering of Kluyveromyces marxianus for biomass-based applications

Kluyveromyces marxianus ATCC 26,548 was cultivated in aerobic chemostats with [1-13C] and [U-13C] glucose as carbon source under three different growth conditions (0.10, 0.25, and 0.5 h-1) to evaluate metabolic fluxes. Carbon balances closed always within 97-102%. Growth was carbon limited, and the cell yield on glucose was the same. The extracellular side-product formation was very low, totaling 0.0008 C-mol C-mol-1 substrate at 0.5 h-1. The intracellular flux ratios did not show significant variation for metabolic flux analysis from labelling and biomass composition and metabolic flux ratio analysis from labelling. The observed strictly oxidative metabolism and the stability of the metabolism in terms of fluxes even at high growth rates, without triggering out the synthesis of by-products, is an extremely desired condition that underlines the potential of K. marxianus for biotechnological biomass-related applications and the comprehension of the metabolic pools and pathways is an important step to engineering this organism.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03324-x.

Monitoring Intracellular Metabolite Dynamics in Saccharomyces cerevisiae during Industrially Relevant Famine Stimuli

Carbon limitation is a common feeding strategy in bioprocesses to enable an efficient microbiological conversion of a substrate to a product. However, industrial settings inherently promote mixing insufficiencies, creating zones of famine conditions. Cells frequently traveling through such regions repeatedly experience substrate shortages and respond individually but often with a deteriorated production performance. A priori knowledge of the expected strain performance would enable targeted strain, process, and bioreactor engineering for minimizing performance loss. Today, computational fluid dynamics (CFD) coupled to data-driven kinetic models are a promising route for the in silico investigation of the impact of the dynamic environment in the large-scale bioreactor on microbial performance. However, profound wet-lab datasets are needed to cover relevant perturbations on realistic time scales. As a pioneering study, we quantified intracellular metabolome dynamics of Saccharomyces cerevisiae following an industrially relevant famine perturbation. Stimulus-response experiments were operated as chemostats with an intermittent feed and high-frequency sampling. Our results reveal that even mild glucose gradients in the range of 100 µmol·L−1 impose significant perturbations in adapted and non-adapted yeast cells, altering energy and redox homeostasis. Apparently, yeast sacrifices catabolic reduction charges for the sake of anabolic persistence under acute carbon starvation conditions. After repeated exposure to famine conditions, adapted cells show 2.7% increased maintenance demands.

Metabolic Footprinting of Microbial Systems Based on Comprehensive In Silico Predictions of MS/MS Relevant Data

Metabolic footprinting represents a holistic approach to gathering large-scale metabolomic information of a given biological system and is, therefore, a driving force for systems biology and bioprocess development. The ongoing development of automated cultivation platforms increases the need for a comprehensive and rapid profiling tool to cope with the cultivation throughput. In this study, we implemented a workflow to provide and select relevant metabolite information from a genome-scale model to automatically build an organism-specific comprehensive metabolome analysis method. Based on in-house literature and predicted metabolite information, the deduced metabolite set was distributed in stackable methods for a chromatography-free dilute and shoot flow-injection analysis multiple-reaction monitoring profiling approach. The workflow was used to create a method specific for Saccharomyces cerevisiae, covering 252 metabolites with 7 min/sample. The method was validated with a commercially available yeast metabolome standard, identifying up to 74.2% of the listed metabolites. As a first case study, three commercially available yeast extracts were screened with 118 metabolites passing quality control thresholds for statistical analysis, allowing to identify discriminating metabolites. The presented methodology provides metabolite screening in a time-optimised way by scaling analysis time to metabolite coverage and is open to other microbial systems simply starting from genome-scale model information.

Nutrient-depended metabolic switching during batch cultivation of Streptomyces coelicolor explored with absolute quantitative mass spectrometry-based metabolite profiling

The well-known secondary metabolite-producing bacterium Streptomyces coelicolor is a natural choice for the development of super-hosts optimized for the heterologous expression of antibiotic biosynthetic gene clusters (BGCs). In this study, we used S. coelicolor M145 and its derivative strain M1146 where all active BGCs have been deleted and generated high-resolution quantitative time series metabolite profiles under two cultivation conditions (phosphate and nitrogen limitation to cease growth and trigger secondary metabolism). Five targeted LC-MS/MS-based methods were used to quantify intracellular primary metabolites covering phosphorylated metabolites, amino acids, organic acids, (deoxy) nucleoside/sugar phosphates, Nicotinamide adenine dinucleotide (NAD), and Coenzyme A (CoA). The nitrogen limitation resulted in a sharp decline in respiration and an immediate drop in the cell mass concentration. Intracellularly, a reduction in the level of the metabolites next to α-ketoglutarate in the tricarboxylic acid cycle and a decrease in the NADH pool were among the most prominent adaptation to this nutrient limitation. Phosphate limitation evoked a different adaptation of the metabolite pools as most of the phosphorylated metabolite pools except 6-phosphogluconic acid (6PG) pool were downregulated. ¹³C-isotope-labeling experiments revealed the simultaneous activity of both glycolysis and gluconeogenesis during the co-utilization of glucose and glutamate. The S. coelicolor M1146 strain had similar time-series metabolite profile dynamics as the parent M145 strain, except for a visibly increased 6PG pool in the stationary phase. In general, the nutrient limitation had a larger effect on the metabolite pool levels than the absence of secondary metabolite production in M1146. This study provides new insight into the primary carbon metabolism and its link to the secondary metabolism which is needed for further optimization of both super-host genotype and cultivation conditions.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-022-03146-x.

Enzyme-constrained models predict the dynamics of Saccharomyces cerevisiae growth in continuous, batch and fed-batch bioreactors

Genome‐scale, constraint‐based models (GEM) and their derivatives are commonly used to model and gain insights into microbial metabolism. Often, however, their accuracy and predictive power are limited and enable only approximate designs. To improve their usefulness for strain and bioprocess design, we studied here their capacity to accurately predict metabolic changes in response to operational conditions in a bioreactor, as well as intracellular, active reactions. We used flux balance analysis (FBA) and dynamic FBA (dFBA) to predict growth dynamics of the model organism Saccharomyces cerevisiae under different industrially relevant conditions. We compared simulations with the latest developed GEM for this organism (Yeast8) and its enzyme‐constrained version (ecYeast8) herein described with experimental data and found that ecYeast8 outperforms Yeast8 in all the simulations. EcYeast8 was able to predict well‐known traits of yeast metabolism including the onset of the Crabtree effect, the order of substrate consumption during mixed carbon cultivation and production of a target metabolite. We showed how the combination of ecGEM and dFBA links reactor operation and genetic modifications to flux predictions, enabling the prediction of yields and productivities of different strains and (dynamic) production processes. Additionally, we present flux sampling as a tool to analyse flux predictions of ecGEM, of major importance for strain design applications. We showed that constraining protein availability substantially improves accuracy of the description of the metabolic state of the cell under dynamic conditions. This therefore enables more realistic and faithful designs of industrially relevant cell‐based processes and, thus, the usefulness of such models.

What makes Komagataella phaffii non-conventional?

The important industrial protein production host Komagataella phaffii (syn Pichia pastoris) is classified as a non-conventional yeast. But what exactly makes K. phaffii non-conventional? In this review, we set out to address the main differences to the 'conventional' yeast Saccharomyces cerevisiae, but also pinpoint differences to other non-conventional yeasts used in biotechnology. Apart from its methylotrophic lifestyle, K. phaffii is a Crabtree-negative yeast species. But even within the methylotrophs, K. phaffii possesses distinct regulatory features such as glycerol-repression of the methanol-utilization pathway or the lack of nitrate assimilation. Rewiring of the transcriptional networks regulating carbon (and nitrogen) source utilization clearly contributes to our understanding of genetic events occurring during evolution of yeast species. The mechanisms of mating-type switching and the triggers of morphogenic phenotypes represent further examples for how K. phaffii is distinguished from the model yeast S. cerevisiae. With respect to heterologous protein production, K. phaffii features high secretory capacity but secretes only low amounts of endogenous proteins. Different to S. cerevisiae, the Golgi apparatus of K. phaffii is stacked like in mammals. While it is tempting to speculate that Golgi architecture is correlated to the high secretion levels or the different N-glycan structures observed in K. phaffii, there is recent evidence against this. We conclude that K. phaffii is a yeast with unique features that has a lot of potential to explore both fundamental research questions and industrial applications.

De novo biosynthesis of bioactive isoflavonoids by engineered yeast cell factories

Isoflavonoids comprise a class of plant natural products with great nutraceutical, pharmaceutical and agricultural significance. Their low abundance in nature and structural complexity however hampers access to these phytochemicals through traditional crop-based manufacturing or chemical synthesis. Microbial bioproduction therefore represents an attractive alternative. Here, we engineer the metabolism of Saccharomyces cerevisiae to become a platform for efficient production of daidzein, a core chemical scaffold for isoflavonoid biosynthesis, and demonstrate its application towards producing bioactive glucosides from glucose, following the screening-reconstruction-application engineering framework. First, we rebuild daidzein biosynthesis in yeast and its production is then improved by 94-fold through screening biosynthetic enzymes, identifying rate-limiting steps, implementing dynamic control, engineering substrate trafficking and fine-tuning competing metabolic processes. The optimized strain produces up to 85.4 mg L^-1 of daidzein and introducing plant glycosyltransferases in this strain results in production of bioactive puerarin (72.8 mg L^-1) and daidzin (73.2 mg L^-1). Our work provides a promising step towards developing synthetic yeast cell factories for de novo biosynthesis of value-added isoflavonoids and the multi-phased framework may be extended to engineer pathways of complex natural products in other microbial hosts.

A comparative study at bioprocess and metabolite levels of superhost strain Streptomyces coelicolor M1152 and its derivative M1581 heterologously expressing chloramphenicol biosynthetic gene cluster

Microbial superhost strains should provide an ideal platform for the efficient homologous or heterologous phenotypic expression of biosynthetic gene clusters (BGCs) of new and novel bioactive molecules. Our aim in the current study was to perform a comparative study at the bioprocess and metabolite levels of the previously designed superhost strain Streptomyces coelicolor M1152 and its derivative strain S. coelicolor M1581 heterologously expressing chloramphenicol BGC. Parent strain M1152 was characterized by a higher specific growth rate, specific CO₂ evolution rate, and a higher specific l-glutamate consumption rate as compared with M1581. Intracellular primary central metabolites (nucleoside/sugar phosphates, amino acids, organic acids, and CoAs) were quantified using four targeted LC-MS/MS-based methods. The metabolite pathways in the nonantibiotic producing S. coelicolor host strain were flooded with carbon from both carbon sources, whereas in antibiotic-producing strain, the carbon of l-glutamate seems to be draining out through excreting synthesized antibiotic. The ¹³ C-isotope-labeling experiments revealed the bidirectionality in the glycolytic pathway and reversibility in the non-oxidative part of PPP even with continuous uptake of d-glucose. The change in the primary metabolites due to the insertion of BGC disclosed a clear linkage between the primary and secondary metabolites.

A genome-scale metabolic model of Saccharomyces cerevisiae that integrates expression constraints and reaction thermodynamics

Eukaryotic organisms play an important role in industrial biotechnology, from the production of fuels and commodity chemicals to therapeutic proteins. To optimize these industrial systems, a mathematical approach can be used to integrate the description of multiple biological networks into a single model for cell analysis and engineering. One of the most accurate models of biological systems include Expression and Thermodynamics FLux (ETFL), which efficiently integrates RNA and protein synthesis with traditional genome-scale metabolic models. However, ETFL is so far only applicable for E. coli. To adapt this model for Saccharomyces cerevisiae, we developed yETFL, in which we augmented the original formulation with additional considerations for biomass composition, the compartmentalized cellular expression system, and the energetic costs of biological processes. We demonstrated the ability of yETFL to predict maximum growth rate, essential genes, and the phenotype of overflow metabolism. We envision that the presented formulation can be extended to a wide range of eukaryotic organisms to the benefit of academic and industrial research.

A metabolic model of Lipomyces starkeyi for predicting lipogenesis potential from diverse low-cost substrates

BACKGROUND

Lipomyces starkeyi has been widely regarded as a promising oleaginous yeast with broad industrial application prospects because of its wide substrate spectrum, good adaption to fermentation inhibitors, excellent fatty acid composition for high-quality biodiesel, and negligible lipid remobilization. However, the currently low experimental lipid yield of L. starkeyi prohibits its commercial success. Metabolic model is extremely valuable to comprehend the complex biochemical processes and provide great guidance for strain modification to facilitate the lipid biosynthesis.

RESULTS

A small-scale metabolic model of L. starkeyi NRRL Y-11557 was constructed based on the genome annotation information. The theoretical lipid yields of glucose, cellobiose, xylose, glycerol, and acetic acid were calculated according to the flux balance analysis (FBA). The optimal flux distribution of the lipid synthesis showed that pentose phosphate pathway (PPP) independently met the necessity of NADPH for lipid synthesis, resulting in the relatively low lipid yields. Several targets (NADP-dependent oxidoreductases) beneficial for oleaginicity of L. starkeyi with significantly higher theoretical lipid yields were compared and elucidated. The combined utilization of acetic acid and other carbon sources and a hypothetical reverse β-oxidation (RBO) pathway showed outstanding potential for improving the theoretical lipid yield.

CONCLUSIONS

The lipid biosynthesis potential of L. starkeyi can be significantly improved through appropriate modification of metabolic network, as well as combined utilization of carbon sources according to the metabolic model. The prediction and analysis provide valuable guidance to improve lipid production from various low-cost substrates.

The Pentose Phosphate Pathway in Yeasts-More Than a Poor Cousin of Glycolysis

The pentose phosphate pathway (PPP) is a route that can work in parallel to glycolysis in glucose degradation in most living cells. It has a unidirectional oxidative part with glucose-6-phosphate dehydrogenase as a key enzyme generating NADPH, and a non-oxidative part involving the reversible transketolase and transaldolase reactions, which interchange PPP metabolites with glycolysis. While the oxidative branch is vital to cope with oxidative stress, the non-oxidative branch provides precursors for the synthesis of nucleic, fatty and aromatic amino acids. For glucose catabolism in the baker’s yeast Saccharomyces cerevisiae, where its components were first discovered and extensively studied, the PPP plays only a minor role. In contrast, PPP and glycolysis contribute almost equally to glucose degradation in other yeasts. We here summarize the data available for the PPP enzymes focusing on S. cerevisiae and Kluyveromyces lactis, and describe the phenotypes of gene deletions and the benefits of their overproduction and modification. Reference to other yeasts and to the importance of the PPP in their biotechnological and medical applications is briefly being included. We propose future studies on the PPP in K. lactis to be of special interest for basic science and as a host for the expression of human disease genes.

Inhibition of alternative respiration system of Scheffersomyces stipitis and effect on glucose or xylose fermentation

Scheffersomyces stipitis is a Crabtree-negative pentose fermenting yeast, which shows a complex respiratory system involving a cytochrome and an alternative salicylhydroxamic acid (SHAM)-sensitive respiration mechanism that is poorly understood. This work aimed to investigate the role of the antimycin A (AA) sensitive respiration and SHAM-sensitive respiration in the metabolism of xylose and glucose by S. stipitis, upon different agitation conditions. Inhibition of the SHAM-sensitive respiration caused a significant (P < 0.05) decrease in glycolytic flux and oxygen consumption when using glucose and xylose under agitation conditions, but without agitation, only a mild reduction was observed. The combination of SHAM and AA abolished respiration, depleting the glycolytic flux using both carbon sources tested, leading to increased ethanol production of 21.05 g/L at 250 rpm for 0.5 M glucose, and 8.3 g/L ethanol using xylose. In contrast, inhibition of only the AA-sensitive respiration, caused increased ethanol production to 30 g/L using 0.5 M glucose at 250 rpm, and 11.3 g/L from 0.5 M xylose without agitation. Results showed that ethanol production can be induced by respiration inhibition, but the active role of SHAM-sensitive respiration should be considered to investigate better conditions to increase and optimize yields.

Metabolic flux configuration determination using information entropy

Constraint-based models use steady-state mass balances to define a solution space of flux configurations, which can be narrowed down by measuring as many fluxes as possible. Due to loops and redundant pathways, this process typically yields multiple alternative solutions. To address this ambiguity, flux sampling can estimate the probability distribution of each flux, or a flux configuration can be singled out by further minimizing the sum of fluxes according to the assumption that cellular metabolism favors states where enzyme-related costs are economized. However, flux sampling is susceptible to artifacts introduced by thermodynamically infeasible cycles and is it not clear if the economy of fluxes assumption (EFA) is universally valid. Here, we formulated a constraint-based approach, MaxEnt, based on the principle of maximum entropy, which in this context states that if more than one flux configuration is consistent with a set of experimentally measured fluxes, then the one with the minimum amount of unwarranted assumptions corresponds to the best estimation of the non-observed fluxes. We compared MaxEnt predictions to Escherichia coli and Saccharomyces cerevisiae publicly available flux data. We found that the mean square error (MSE) between experimental and predicted fluxes by MaxEnt and EFA-based methods are three orders of magnitude lower than the median of 1,350,000 MSE values obtained using flux sampling. However, only MaxEnt and flux sampling correctly predicted flux through E. coli’s glyoxylate cycle, whereas EFA-based methods, in general, predict no flux cycles. We also tested MaxEnt predictions at increasing levels of overflow metabolism. We found that MaxEnt accuracy is not affected by overflow metabolism levels, whereas the EFA-based methods show a decreasing performance. These results suggest that MaxEnt is less sensitive than flux sampling to artifacts introduced by thermodynamically infeasible cycles and that its predictions are less susceptible to overfitting than EFA-based methods.

Mitochondrial respiration is required to provide amino acids during fermentative proliferation of fission yeast

When glucose is available, many organisms repress mitochondrial respiration in favour of aerobic glycolysis, or fermentation in yeast, that suffices for ATP production. Fission yeast cells, however, rely partially on respiration for rapid proliferation under fermentative conditions. Here, we determined the limiting factors that require respiratory function during fermentation. When inhibiting the electron transport chain, supplementation with arginine was necessary and sufficient to restore rapid proliferation. Accordingly, a systematic screen for mutants growing poorly without arginine identified mutants defective in mitochondrial oxidative metabolism. Genetic or pharmacological inhibition of respiration triggered a drop in intracellular levels of arginine and amino acids derived from the Krebs cycle metabolite alpha‐ketoglutarate: glutamine, lysine and glutamic acid. Conversion of arginine into these amino acids was required for rapid proliferation when blocking the respiratory chain. The respiratory block triggered an immediate gene expression response diagnostic of TOR inhibition, which was muted by arginine supplementation or without the AMPK‐activating kinase Ssp1. The TOR‐controlled proteins featured biased composition of amino acids reflecting their shortage after respiratory inhibition. We conclude that respiration supports rapid proliferation in fermenting fission yeast cells by boosting the supply of Krebs cycle‐derived amino acids.

Disruption in phosphate transport affects membrane lipid and lipid droplet homeostasis in Saccharomyces cerevisiae

Phosphate plays a crucial role in phospholipid metabolism and it is transported by the phosphate (Pi) transporters. Phospholipids are building blocks of the cell membrane, and essential for cell growth; however, the role of phosphate transporters in lipid metabolism remains elusive. The present study shows that the deletion of Pi transporters exhibited an increase in both phospholipid and neutral lipid levels when compared to wild type. The mRNA expressions of genes involved in phospholipid synthesis (CKI1, EKI1, CHO2, and OPI3) were increased due to de-repression of the transcription factors (INO2 and INO4). Neutral lipid levels (triacylglycerol and sterol ester) and their synthesizing genes (LRO1, ARE2, ACC1, and FAS1) were also increased, resulting in lipid droplet accumulation in Pi transporter mutants. Interestingly, phospholipase (PLC1) and histone acetyltransferase genes (ESA1, EAF1, YNG1, YNG2, and GCN5) were also found to be significantly increased, leading to dysregulation of lipid levels in Pi transporter mutants. In summary, our results suggest that the Pi transporters are involved in lipid droplet and membrane lipid homeostasis.

QTL mapping of modelled metabolic fluxes reveals gene variants impacting yeast central carbon metabolism

The yeast Saccharomyces cerevisiae is an attractive industrial microorganism for the production of foods and beverages as well as for various bulk and fine chemicals, such as biofuels or fragrances. Building blocks for these biosyntheses are intermediates of yeast central carbon metabolism (CCM), whose intracellular availability depends on balanced single reactions that form metabolic fluxes. Therefore, efficient product biosynthesis is influenced by the distribution of these fluxes. We recently demonstrated great variations in CCM fluxes between yeast strains of different origins. However, we have limited understanding of flux modulation and the genetic basis of flux variations. In this study, we investigated the potential of quantitative trait locus (QTL) mapping to elucidate genetic variations responsible for differences in metabolic flux distributions (fQTL). Intracellular metabolic fluxes were estimated by constraint-based modelling and used as quantitative phenotypes, and differences in fluxes were linked to genomic variations. Using this approach, we detected four fQTLs that influence metabolic pathways. The molecular dissection of these QTLs revealed two allelic gene variants, PDB1 and VID30, contributing to flux distribution. The elucidation of genetic determinants influencing metabolic fluxes, as reported here for the first time, creates new opportunities for the development of strains with optimized metabolite profiles for various applications.

Relevance and Regulation of Cell Density

Cell density shows very little variation within a given cell type. For example, in humans variability in cell density among cells of a given cell type is 100 times smaller than variation in cell mass. This tight control indicates that maintenance of a cell type-specific cell density is important for cell function. Indeed, pathological conditions such as cellular senescence are accompanied by changes in cell density. Despite the apparent importance of cell-type-specific density, we know little about how cell density affects cell function, how it is controlled, and how it sometimes changes as part of a developmental process or in response to changes in the environment. The recent development of new technologies to accurately measure the cell density of single cells in suspension and in tissues is likely to provide answers to these important questions.

Metabolomic Alterations Do Not Induce Metabolic Burden in the Industrial Yeast M2n[pBKD2-Pccbgl1]-C1 Engineered by Multiple δ-Integration of a Fungal β-Glucosidase Gene

In the lignocellulosic yeast development, metabolic burden relates to redirection of resources from regular cellular activities toward the needs created by recombinant protein production. As a result, growth parameters may be greatly affected. Noteworthy, Saccharomyces cerevisiae M2n[pBKD2-Pccbgl1]-C1, previously developed by multiple δ-integration of the β-glucosidase BGL3, did not show any detectable metabolic burden. This work aims to test the hypothesis that the metabolic burden and the metabolomic perturbation induced by the δ-integration of a yeast strain, could differ significantly. The engineered strain was evaluated in terms of metabolic performances and metabolomic alterations in different conditions typical of the bioethanol industry. Results indicate that the multiple δ-integration did not affect the ability of the engineered strain to grow on different carbon sources and to tolerate increasing concentrations of ethanol and inhibitory compounds. Conversely, metabolomic profiles were significantly altered both under growing and stressing conditions, indicating a large extent of metabolic reshuffling involved in the maintenance of the metabolic homeostasis. Considering that four copies of BGL3 gene have been integrated without affecting any parental genes or promoter sequences, deeper studies are needed to unveil the mechanisms implied in these metabolomic changes, thus supporting the optimization of protein production in engineered strains.

Effects of overexpression of STB5 in Saccharomyces cerevisiae on fatty acid biosynthesis, physiology and transcriptome

Microbial conversion of biomass to fatty acids (FA) and products derived thereof is an attractive alternative to the traditional oleochemical production route from animal and plant lipids. This study examined if NADPH-costly FA biosynthesis could be enhanced by overexpressing the transcription factor Stb5 in Saccharomyces cerevisiae. Stb5 activates expression of multiple genes encoding enzymes within the pentose phosphate pathway (PPP) and other NADPH-producing reactions. Overexpression of STB5 led to a decreased growth rate and an increased free fatty acid (FFA) production during growth on glucose. The improved FFA synthetic ability in the glucose phase was shown to be independent of flux through the oxidative PPP. RNAseq analysis revealed that STB5 overexpression had wide-ranging effects on the transcriptome in the batch phase, and appeared to cause a counterintuitive phenotype with reduced flux through the oxidative PPP. During glucose limitation, when an increased NADPH supply is likely less harmful, an overall induction of the proposed target genes of Stb5 (eg. GND1/2, TAL1, ALD6, YEF1) was observed. Taken together, the strategy of utilizing STB5 overexpression to increase NADPH supply for reductive biosynthesis is suggested to have potential in strains engineered to have strong ability to consume excess NADPH, alleviating a potential redox imbalance.

Redirection of the Glycolytic Flux Enhances Isoprenoid Production in Saccharomyces cerevisiae

Sufficient supply of reduced nicotinamide adenine dinucleotide phosphate (NADPH) is a prerequisite of the overproduction of isoprenoids and related bioproducts in Saccharomyces cerevisiae. Although S. cerevisiae highly depends on the oxidative pentose phosphate (PP) pathway to produce NADPH, its metabolic flux toward the oxidative PP pathway is limited due to the rigid glycolysis flux. To maximize NADPH supply for the isoprenoid production in yeast, upper glycolytic metabolic fluxes are reduced by introducing mutations into phosphofructokinase (PFK) along with overexpression of ZWF1 encoding glucose-6-phosphate (G6P) dehydrogenase. The PFK mutations (Pfk1 S724D and Pfk2 S718D) result in less glycerol production and more accumulation of G6P, which is a gateway metabolite toward the oxidative PP pathway. When combined with the PFK mutations, overexpression of ZWF1 caused substantial increases of [NADPH]/[NADP⁺ ] ratios whereas the effect of ZWF1 overexpression alone in the wild-type strain is not noticeable. Also, the introduction of ZWF1 overexpression and the PFK mutations into engineered yeast overexpressing acetyl-CoA C-acetyltransferase (ERG10), truncated HMG-CoA reductase isozyme 1 (tHMG1), and amorphadiene synthase (ADS) leads to a titer of 497 mg L^-1 of amorphadiene (3.7-fold over the parental strain). These results suggest that perturbation of upper glycolytic fluxes, in addition to ZWF1 overexpression, is necessary for efficient NADPH supply through the oxidative PP pathway and enhanced production of isoprenoids by engineered S. cerevisiae.

Revisiting the Crabtree/Warburg effect in a dynamic perspective: a fitness advantage against sugar-induced cell death

The mechanisms behind the Warburg effect in mammalian cells, as well as for the similar Crabtree effect in the yeast Saccharomyces cerevisiae, are still a matter of debate: why do cells shift from the energy-efficient respiration to the energy-inefficient fermentation at high sugar concentration?

This review reports on the strong similarities of these phenomena in both cell types, discusses the current ideas, and provides a novel interpretation of their common functional mechanism in a dynamic perspective. This is achieved by analysing another phenomenon, the sugar-induced-cell-death (SICD) occurring in yeast at high sugar concentration, to highlight the link between ATP depletion and cell death.

The integration between SICD and the dynamic functioning of the glycolytic process, suggests that the Crabtree/Warburg effect may be interpreted as the avoidance of ATP depletion in those conditions where glucose uptake is higher than the downstream processing capability of the second phase of glycolysis. It follows that the down-regulation of respiration is strategic for cell survival allowing the allocation of more resources to the fermentation pathway, thus maintaining the cell energetic homeostasis.

Energy metabolism controls phenotypes by protein efficiency and allocation

Cells require energy for growth and maintenance and have evolved to have multiple pathways to produce energy in response to varying conditions. A basic question in this context is how cells organize energy metabolism, which is, however, challenging to elucidate due to its complexity, i.e., the energy-producing pathways overlap with each other and even intertwine with biomass formation pathways. Here, we propose a modeling concept that decomposes energy metabolism into biomass formation and ATP-producing pathways. The latter can be further decomposed into a high-yield and a low-yield pathway. This enables independent estimation of protein efficiency for each pathway. With this concept, we modeled energy metabolism for Escherichia coli and Saccharomyces cerevisiae and found that the high-yield pathway shows lower protein efficiency than the low-yield pathway. Taken together with a fixed protein constraint, we predict overflow metabolism in E. coli and the Crabtree effect in S. cerevisiae, meaning that energy metabolism is sufficient to explain the metabolic switches. The static protein constraint is supported by the findings that protein mass of energy metabolism is conserved across conditions based on absolute proteomics data. This also suggests that enzymes may have decreased saturation or activity at low glucose uptake rates. Finally, our analyses point out three ways to improve growth, i.e., increasing protein allocation to energy metabolism, decreasing ATP demand, or increasing activity for key enzymes.

Position-Specific Metabolic Probing and Metagenomics of Microbial Communities Reveal Conserved Central Carbon Metabolic Network Activities at High Temperatures

Temperature is a primary driver of microbial community composition and taxonomic diversity; however, it is unclear to what extent temperature affects characteristics of central carbon metabolic pathways (CCMPs) at the community level. In this study, 16S rRNA gene amplicon and metagenome sequencing were combined with ¹³C-labeled metabolite probing of the CCMPs to assess community carbon metabolism along a temperature gradient (60–95°C) in Great Boiling Spring, NV. 16S rRNA gene amplicon diversity was inversely proportional to temperature, and Archaea were dominant at higher temperatures. KO richness and diversity were also inversely proportional to temperature, yet CCMP genes were similarly represented across the temperature gradient and many individual metagenome-assembled genomes had complete pathways. In contrast, genes encoding cellulosomes and many genes involved in plant matter degradation and photosynthesis were absent at higher temperatures. In situ¹³C-CO₂ production from labeled isotopomer pairs of glucose, pyruvate, and acetate suggested lower relative oxidative pentose phosphate pathway activity and/or fermentation at 60°C, and a stable or decreased maintenance energy demand at higher temperatures. Catabolism of ¹³C-labeled citrate, succinate, L-alanine, L-serine, and L-cysteine was observed at 85°C, demonstrating broad heterotrophic activity and confirming functioning of the TCA cycle. Together, these results suggest that temperature-driven losses in biodiversity and gene content in geothermal systems may not alter CCMP function or maintenance energy demands at a community level.

Physiologic and metabolic characterization of Saccharomyces cerevisiae reveals limitations in the synthesis of the triterpene squalene

Heterologous synthesis of triterpenoids in Saccharomyces cerevisiae from its native metabolite squalene has been reported to offer an alternative to chemical synthesis and extraction from plant material if productivities can be increased.Here, we physiologically characterized a squalene overproducing S. cerevisiae CEN.PK strain to elucidate the effect of cultivation conditions on the production of this central triterpenoid precursor. The maximum achievable squalene concentration was substantially influenced by nutritional conditions, medium composition and cultivation mode. Batch growth on glucose resulted in minimal squalene accumulation, while squalene only significantly accumulated during ethanol consumption (up to 59 mg/gCDW), probably due to increased acetyl-CoA supply on this carbon source. Likewise, low squalene concentrations were observed in glucose-limited chemostat cultivations and improved up to 8-fold upon increasing the ethanol fraction in the feed. In those experiments, a constant, growth-rate-independent specific squalene accumulation rate (2.2 mg/gCDW/h) was recorded resulting in a maximal squalene loading of 30 mg/gCDW at low dilution rates with longer residence times. Coenzyme A availability was identified as possible bottleneck as increased vitamin concentrations, including the Coenzyme A precursor pantothenate, improved squalene titers in batch and chemostat cultivations. This analysis demonstrates that thorough physiologic characterization of production strains is valuable for the identification of bottlenecks already in early stages of strain development and for guiding further optimization efforts.

Cocoa's Residual Honey: Physicochemical Characterization and Potential as a Fermentative Substrate by Saccharomyces cerevisiae AWRI726

This study aims to characterize the physicochemical properties of cocoa's residual honey and evaluate its fermentative capacity as a substrate, using Saccharomyces cerevisiae AWRI726 as the starter culture for alcoholic fermentation. The research hypothesis was that cocoa's residual honey can be used for the production of fermented beverages. Cocoa's honey has 14.14 g.100 mL⁻¹ of dry material, containing 11.80 g.100 mL⁻¹ of carbohydrates and 1.20% crude protein, in addition to other minor components, such as pectin, lipids, and Fe, Mn, Na, and Zn, with a carbon-to-nitrogen (C/N) ratio (9.8) most suitable for fermentation. Fermentation at 20°C for 240 hours produced a liquid with 16% v/v ethanol (14 g.L⁻¹ in 144 h). However, 24 hours of fermentation produced the maximum ethanol yield (0.373 g.g⁻¹) and volumetric productivity (0.168 g.L⁻¹.h⁻¹), which were associated with a significant increase in the specific cell growth rate. Saccharomyces cerevisiae AWR1726 performed satisfactorily in the alcoholic fermentation of cocoa's residual honey, similar to that observed in other fruit beverages, thus suggesting the suitability of cocoa's residual honey for future commercial applications.

An upper limit on Gibbs energy dissipation governs cellular metabolism

The principles governing cellular metabolic operation are poorly understood. Because diverse organisms show similar metabolic flux patterns, we hypothesized that a fundamental thermodynamic constraint might shape cellular metabolism. Here, we develop a constraint-based model for Saccharomyces cerevisiae with a comprehensive description of biochemical thermodynamics including a Gibbs energy balance. Non-linear regression analyses of quantitative metabolome and physiology data reveal the existence of an upper rate limit for cellular Gibbs energy dissipation. By applying this limit in flux balance analyses with growth maximization as the objective function, our model correctly predicts the physiology and intracellular metabolic fluxes for different glucose uptake rates as well as the maximal growth rate. We find that cells arrange their intracellular metabolic fluxes in such a way that, with increasing glucose uptake rates, they can accomplish optimal growth rates but stay below the critical rate limit on Gibbs energy dissipation. Once all possibilities for intracellular flux redistribution are exhausted, cells reach their maximal growth rate. This principle also holds for Escherichia coli and different carbon sources. Our work proposes that metabolic reaction stoichiometry, a limit on the cellular Gibbs energy dissipation rate, and the objective of growth maximization shape metabolism across organisms and conditions.

Production efficiency of the bacterial non-ribosomal peptide indigoidine relies on the respiratory metabolic state in S. cerevisiae

BACKGROUND

Beyond pathway engineering, the metabolic state of the production host is critical in maintaining the efficiency of cellular production. The biotechnologically important yeast Saccharomyces cerevisiae adjusts its energy metabolism based on the availability of oxygen and carbon sources. This transition between respiratory and non-respiratory metabolic state is accompanied by substantial modifications of central carbon metabolism, which impact the efficiency of metabolic pathways and the corresponding final product titers. Non-ribosomal peptide synthetases (NRPS) are an important class of biocatalysts that provide access to a wide array of secondary metabolites. Indigoidine, a blue pigment, is a representative NRP that is valuable by itself as a renewably produced pigment.

RESULTS

Saccharomyces cerevisiae was engineered to express a bacterial NRPS that converts glutamine to indigoidine. We characterize carbon source use and production dynamics, and demonstrate that indigoidine is solely produced during respiratory cell growth. Production of indigoidine is abolished during non-respiratory growth even under aerobic conditions. By promoting respiratory conditions via controlled feeding, we scaled the production to a 2 L bioreactor scale, reaching a maximum titer of 980 mg/L.

CONCLUSIONS

This study represents the first use of the Streptomyces lavendulae NRPS (BpsA) in a fungal host and its scale-up. The final product indigoidine is linked to the activity of the TCA cycle and serves as a reporter for the respiratory state of S. cerevisiae. Our approach can be broadly applied to investigate diversion of flux from central carbon metabolism for NRPS and other heterologous pathway engineering, or to follow a population switch between respiratory and non-respiratory modes.

Lipids modulate acetic acid and thiol final concentrations in wine during fermentation by Saccharomyces cerevisiae × Saccharomyces kudriavzevii hybrids

Saccharomyces cerevisiae × Saccharomyces kudriavzevii hybrids are typically used for white wine fermentation because of their cryotolerance. One group of these hybrids presents a unique ability to release thiol varietal aroma products as well as excessive amounts of acetic acid under specific conditions, which is detrimental for wine organoleptic quality. The aim of this work is to better assess the effects of lipids, sugar concentrations and temperature on the production of acetic acid and thiols during wine fermentation. To this end, we used a Box–Behnken experimental design and response surface modeling on the production of acetic acid and thiols in S. cerevisiae × S. kudriavzevii hybrids from the Eg8 family during fermentation of a synthetic must. We showed that these hybrids produced lower levels of acetic acid when the initial lipid concentration was increased, whereas they produced greater levels when the initial sugar concentration was high. Moreover, we found that lipids had a positive impact on the final concentrations of 4-methyl-4-mercaptopentan-2-one and 3-mercaptohexan-1-ol (3MH), giving box tree and citrus flavors, respectively. The increase of 3MH was concomitant with a decrease of 3-mercaptohexyl acetate (3MHA) characterized by a passion fruit aroma, indicating that lipid addition reduces the rate of 3MH acetylation into 3MHA. These results highlight the key role of lipid management in acetic acid metabolism and thiol release by S. cerevisiae × S. kudriavzevii hybrids and underline its technological interest in alcoholic fermentation to avoid the overproduction of volatile acidity while favoring the release of volatile thiols.

13C-metabolic flux analysis of ethanol-assimilating Saccharomyces cerevisiae for S-adenosyl-L-methionine production

BACKGROUND

Saccharomyces cerevisiae is a host for the industrial production of S-adenosyl-L-methionine (SAM), which has been widely used in pharmaceutical and nutritional supplement industries. It has been reported that the intracellular SAM content in S. cerevisiae can be improved by the addition of ethanol during cultivation. However, the metabolic state in ethanol-assimilating S. cerevisiae remains unclear. In this study, ¹³C-metabolic flux analysis (¹³C-MFA) was conducted to investigate the metabolic regulation responsible for the high SAM production from ethanol.

RESULTS

The comparison between the metabolic flux distributions of central carbon metabolism showed that the metabolic flux levels of the tricarboxylic acid cycle and glyoxylate shunt in the ethanol culture were significantly higher than that of glucose. Estimates of the ATP balance from the ¹³C-MFA data suggested that larger amounts of excess ATP was produced from ethanol via increased oxidative phosphorylation. The finding was confirmed by the intracellular ATP level under ethanol-assimilating condition being similarly higher than glucose.

CONCLUSIONS

These results suggest that the enhanced ATP regeneration due to ethanol assimilation was critical for the high SAM accumulation.

Metabolic engineering of Pichia pastoris

Besides its use for efficient production of recombinant proteins the methylotrophic yeast Pichia pastoris (syn. Komagataella spp.) has been increasingly employed as a platform to produce metabolites of varying origin. We summarize here the impressive methodological developments of the last years to model and analyze the metabolism of P. pastoris, and to engineer its genome and metabolic pathways. Efficient methods to insert, modify or delete genes via homologous recombination and CRISPR/Cas9, supported by modular cloning techniques, have been reported. An outstanding early example of metabolic engineering in P. pastoris was the humanization of protein glycosylation. More recently the cell metabolism was engineered also to enhance the productivity of heterologous proteins. The last few years have seen an increased number of metabolic pathway design and engineering in P. pastoris, mainly towards the production of complex (secondary) metabolites. In this review, we discuss the potential role of P. pastoris as a platform for metabolic engineering, its strengths, and major requirements for future developments of chassis strains based on synthetic biology principles.

Metabolic engineering to enhance heterologous production of hyaluronic acid in Bacillus subtilis

Hyaluronic acid (HA) is a high-value biopolymer that is produced in large scales using attenuated strains ofgroup C streptococci. However, due to the pathogenicity and fastidious nature of these bacteria, the development of bioprocesses for HA production centered on robust 'Generally Recognized as Safe (GRAS)' organisms, such as Bacillus subtilis, is of increased interest. Here, we report metabolic engineering of novel B. subtilis strains in which the carbon flux has been partially diverted from central metabolism, i.e. the pentose phosphate pathway (PPP) and glycolysis, into HA biosynthesis. First, an improved base strain of B. subtilis was engineered for more effective HA production with less susceptibility to catabolite repression when expressing genes from a xylose-inducible promoter. Subsequently, Clustered Regularly Interspaced Palindromic Repeats interference (CRISPRi) was applied to reduce the expression of individual pfkA or zwf in the base strain, leading to substantial improvements to the HA titer with a concomitant decrease in the molecular weight (MW). On the other hand, multiplexed repression of both pfkA and zwf expression resulted in increases to the HA titer of up to 108% and enhancements to the MW, compared to the base strain. Moreover, the addition of exogenous HA monomers, i.e. glucuronic acid (GlcUA) and N-acetyl-glucosamine (GlcNAc), to B. subtilis cultures markedly improved the HA MW but decreased the HA titer, providing insights into the mechanism of HA biosynthesis by streptococcal hyaluronan synthase (SeHAS) in B. subtilis. Our study demonstrates the successful application of metabolic engineering strategies to establish B. subtilis as an effective platform for high-level HA production.

Workflow Based on the Combination of Isotopic Tracer Experiments to Investigate Microbial Metabolism of Multiple Nutrient Sources

Studies in the field of microbiology rely on the implementation of a wide range of methodologies. In particular, the development of appropriate methods substantially contributes to providing extensive knowledge of the metabolism of microorganisms growing in chemically defined media containing unique nitrogen and carbon sources. In contrast, the management through metabolism of multiple nutrient sources, despite their broad presence in natural or industrial environments, remains virtually unexplored. This situation is mainly due to the lack of suitable methodologies, which hinders investigations. We report an experimental strategy to quantitatively and comprehensively explore how metabolism operates when a nutrient is provided as a mixture of different molecules, i.e., a complex resource. Here, we describe its application for assessing the partitioning of multiple nitrogen sources through the yeast metabolic network. The workflow combines information obtained during stable isotope tracer experiments using selected ¹³C- or ¹⁵N-labeled substrates. It first consists of parallel and reproducible fermentations in the same medium, which includes a mixture of N-containing molecules; however,a selected nitrogen source is labeled each time. A combination of analytical procedures (HPLC, GC-MS) is implemented to assess the labeling patterns of targeted compounds and to quantify the consumption and recovery of substrates in other metabolites. An integrated analysis of the complete dataset provides an overview of the fate of consumed substrates within cells. This approach requires an accurate protocol for the collection of samples-facilitated by a robot-assisted system for online monitoring of fermentations-and the achievement of numerous time-consuming analyses. Despite these constraints, it allowed understanding, for the first time, the partitioning of multiple nitrogen sources throughout the yeast metabolic network. We elucidated the redistribution of nitrogen from more abundant sources toward other N-compounds and determined the metabolic origins of volatile molecules and proteinogenic amino acids.

High Substrate Uptake Rates Empower Vibrio natriegens as Production Host for Industrial Biotechnology

The productivity of industrial fermentation processes is essentially limited by the biomass-specific substrate consumption rate (qS ) of the applied microbial production system. Since qS depends on the growth rate (μ), we highlight the potential of the fastest-growing nonpathogenic bacterium, Vibrio natriegens, as a novel candidate for future biotechnological processes. V. natriegens grows rapidly in BHIN complex medium with a μ of up to 4.43 h-1 (doubling time of 9.4 min) as well as in minimal medium supplemented with various industrially relevant substrates. Bioreactor cultivations in minimal medium with glucose showed that V. natriegens possesses an exceptionally high qS under aerobic (3.90 ± 0.08 g g-1 h-1) and anaerobic (7.81 ± 0.71 g g-1 h-1) conditions. Fermentations with resting cells of genetically engineered V. natriegens under anaerobic conditions yielded an overall volumetric productivity of 0.56 ± 0.10 g alanine liter-1 min-1 (i.e., 34 g liter-1 h-1). These inherent properties render V. natriegens a promising new microbial platform for future industrial fermentation processes operating with high productivity.IMPORTANCE Low conversion rates are one major challenge to realizing microbial fermentation processes for the production of commodities operating competitively with existing petrochemical approaches. For this reason, we screened for a novel platform organism possessing characteristics superior to those of traditionally employed microbial systems. We identified the fast-growing V. natriegens, which exhibits a versatile metabolism and shows striking growth and conversion rates, as a solid candidate to reach outstanding productivities. Due to these inherent characteristics, V. natriegens can speed up common laboratory routines, is suitable for already existing production procedures, and forms an excellent foundation for engineering next-generation bioprocesses.

Increased heme synthesis in yeast induces a metabolic switch from fermentation to respiration even under conditions of glucose repression

Regulation of mitochondrial biogenesis and respiration is a complex process that involves several signaling pathways and transcription factors as well as communication between the nuclear and mitochondrial genomes. Under aerobic conditions, the budding yeast Saccharomyces cerevisiae metabolizes glucose predominantly by glycolysis and fermentation. We have recently shown that altered chromatin structure in yeast induces respiration by a mechanism that requires transport and metabolism of pyruvate in mitochondria. However, how pyruvate controls the transcriptional responses underlying the metabolic switch from fermentation to respiration is unknown. Here, we report that this pyruvate effect involves heme. We found that heme induces transcription of HAP4, the transcriptional activation subunit of the Hap2/3/4/5p complex, required for growth on nonfermentable carbon sources, in a Hap1p- and Hap2/3/4/5p-dependent manner. Increasing cellular heme levels by inactivating ROX1, which encodes a repressor of many hypoxic genes, or by overexpressing HEM3 or HEM12 induced respiration and elevated ATP levels. Increased heme synthesis, even under conditions of glucose repression, activated Hap1p and the Hap2/3/4/5p complex and induced transcription of HAP4 and genes required for the tricarboxylic acid (TCA) cycle, electron transport chain, and oxidative phosphorylation, leading to a switch from fermentation to respiration. Conversely, inhibiting metabolic flux into the TCA cycle reduced cellular heme levels and HAP4 transcription. Together, our results indicate that the glucose-mediated repression of respiration in budding yeast is at least partly due to the low cellular heme level.

lumpGEM: Systematic generation of subnetworks and elementally balanced lumped reactions for the biosynthesis of target metabolites

In the post-genomic era, Genome-scale metabolic networks (GEMs) have emerged as invaluable tools to understand metabolic capabilities of organisms. Different parts of these metabolic networks are defined as subsystems/pathways, which are sets of functional roles to implement a specific biological process or structural complex, such as glycolysis and TCA cycle. Subsystem/pathway definition is also employed to delineate the biosynthetic routes that produce biomass building blocks. In databases, such as MetaCyc and SEED, these representations are composed of linear routes from precursors to target biomass building blocks. However, this approach cannot capture the nested, complex nature of GEMs. Here we implemented an algorithm, lumpGEM, which generates biosynthetic subnetworks composed of reactions that can synthesize a target metabolite from a set of defined core precursor metabolites. lumpGEM captures balanced subnetworks, which account for the fate of all metabolites along the synthesis routes, thus encapsulating reactions from various subsystems/pathways to balance these metabolites in the metabolic network. Moreover, lumpGEM collapses these subnetworks into elementally balanced lumped reactions that specify the cost of all precursor metabolites and cofactors. It also generates alternative subnetworks and lumped reactions for the same metabolite, accounting for the flexibility of organisms. lumpGEM is applicable to any GEM and any target metabolite defined in the network. Lumped reactions generated by lumpGEM can be also used to generate properly balanced reduced core metabolic models.

Stoichiometric models have been used in the area of metabolic engineering and systems biology for many decades. The early examples of these models include simplified ad hoc built metabolic pathways, and biomass compositions. The development of genome scale models (GEMs) brought a standard to metabolic network modeling. However, the vast amount of detailed biochemistry in GEMs makes it necessary to develop methods to manage the complexity in them. In this study, we developed lumpGEM, a tool that can systematically identify subnetworks from metabolic networks that can perform certain tasks, such as biosynthesis of a biomass building block and any other target metabolite. By generating alternative subnetworks, lumpGEM also accounts for the redundancy in metabolic networks. We applied lumpGEM on latest E. coli GEM iJO1366 and identified subnetworks/lumped reactions for every biomass building block defined in its biomass formulation. We also compared the results from lumpGEM with existing knowledge in the literature. The lumped reactions generated by lumpGEM can be used to generate consistently reduced metabolic network models.

A comprehensive evaluation of constraining amino acid biosynthesis in compartmented models for metabolic flux analysis

Recent advances in the availability and applicability of genetic tools for non-conventional yeasts have raised high hopes regarding the industrial applications of such yeasts; however, quantitative physiological data on these yeasts, including intracellular flux distributions, are scarce and have rarely aided in the development of novel yeast applications. The compartmentation of eukaryotic cells adds to model complexity. Model constraints are ideally based on biochemical evidence, which is rarely available for non-conventional yeast and eukaryotic cells. A small-scale model for ¹³C-based metabolic flux analysis of central yeast carbon metabolism was developed that is universally valid and does not depend on localization information regarding amino acid anabolism. The variable compartmental origin of traced metabolites is a feature that allows application of the model to yeasts with uncertain genomic and transcriptional backgrounds. The presented test case includes the baker's yeast Saccharomyces cerevisiae and the methylotrophic yeast Hansenula polymorpha. Highly similar flux solutions were computed using either a model with undefined pathway localization or a model with constraints based on curated (S. cerevisiae) or computationally predicted (H. polymorpha) localization information, while false solutions were found with incorrect localization constraints. These results indicate a potentially adverse effect of universally assuming Saccharomyces-like constraints on amino acid biosynthesis for non-conventional yeasts and verify the validity of neglecting compartmentation constraints using a small-scale metabolic model. The model was specifically designed to investigate the intracellular metabolism of wild-type yeasts under various growth conditions but is also expected to be useful for computing fluxes of other eukaryotic cells.

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Compartmentation influences computed intracellular fluxes.

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Improper localization constraints potentially produce false flux solutions.

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Minimal compartmentation constraints result in high-quality flux computations.

Flux-Enabled Exploration of the Role of Sip1 in Galactose Yeast Metabolism

¹³C metabolic flux analysis (¹³C MFA) is an important systems biology technique that has been used to investigate microbial metabolism for decades. The heterotrimer Snf1 kinase complex plays a key role in the preference Saccharomyces cerevisiae exhibits for glucose over galactose, a phenomenon known as glucose repression or carbon catabolite repression. The SIP1 gene, encoding a part of this complex, has received little attention, presumably, because its knockout lacks a growth phenotype. We present a fluxomic investigation of the relative effects of the presence of galactose in classically glucose-repressing media and/or knockout of SIP1 using a multi-scale variant of ¹³C MFA known as 2-Scale ¹³C metabolic flux analysis (2S-¹³C MFA). In this study, all strains have the galactose metabolism deactivated (gal1Δ background) so as to be able to separate the metabolic effects purely related to glucose repression from those arising from galactose metabolism. The resulting flux profiles reveal that the presence of galactose in classically glucose-repressing conditions, for a CEN.PK113-7D gal1Δ background, results in a substantial decrease in pentose phosphate pathway (PPP) flux and increased flow from cytosolic pyruvate and malate through the mitochondria toward cytosolic branched-chain amino acid biosynthesis. These fluxomic redistributions are accompanied by a higher maximum specific growth rate, both seemingly in violation of glucose repression. Deletion of SIP1 in the CEN.PK113-7D gal1Δ cells grown in mixed glucose/galactose medium results in a further increase. Knockout of this gene in cells grown in glucose-only medium results in no change in growth rate and a corresponding decrease in glucose and ethanol exchange fluxes and flux through pathways involved in aspartate/threonine biosynthesis. Glucose repression appears to be violated at a 1/10 ratio of galactose-to-glucose. Based on the scientific literature, we may have conducted our experiments near a critical sugar ratio that is known to allow galactose to enter the cell. Additionally, we report a number of fluxomic changes associated with these growth rate increases and unexpected flux profile redistributions resulting from deletion of SIP1 in glucose-only medium.

Model-based biotechnological potential analysis of Kluyveromyces marxianus central metabolism

The non-conventional yeast Kluyveromyces marxianus is an emerging industrial producer for many biotechnological processes. Here, we show the application of a biomass-linked stoichiometric model of central metabolism that is experimentally validated, and mass and charge balanced for assessing the carbon conversion efficiency of wild type and modified K. marxianus. Pairs of substrates (lactose, glucose, inulin, xylose) and products (ethanol, acetate, lactate, glycerol, ethyl acetate, succinate, glutamate, phenylethanol and phenylalanine) are examined by various modelling and optimisation methods. Our model reveals the organism's potential for industrial application and metabolic engineering. Modelling results imply that the aeration regime can be used as a tool to optimise product yield and flux distribution in K. marxianus. Also rebalancing NADH and NADPH utilisation can be used to improve the efficiency of substrate conversion. Xylose is identified as a biotechnologically promising substrate for K. marxianus.