Intracellular characterization of aerobic glucose metabolism in seven yeast species by 13C flux analysis and metabolomics

Enhancing Gastrodin Production in Yarrowia lipolytica by Metabolic Engineering

Gastrodin, 4-hydroxybenzyl alcohol-4-O-β-D-glucopyranoside, has been widely used in the treatment of neurogenic and cardiovascular diseases. Currently, gastrodin biosynthesis is being achieved in model microorganisms. However, the production levels are insufficient for industrial applications. In this study, we successfully engineered a Yarrowia lipolytica strain to overproduce gastrodin through metabolic engineering. Initially, the engineered strain expressing the heterologous gastrodin biosynthetic pathway, which comprises chorismate lyase, carboxylic acid reductase, phosphopantetheinyl transferase, endogenous alcohol dehydrogenases, and a UDP-glucosyltransferase, produced 1.05 g/L gastrodin from glucose in a shaking flask. Then, the production was further enhanced to 6.68 g/L with a productivity of 2.23 g/L/day by overexpressing the key node DAHP synthases of the shikimate pathway and alleviating the native tryptophan and phenylalanine biosynthetic pathways. Finally, the best strain, Gd07, produced 13.22 g/L gastrodin in a 5 L fermenter. This represents the highest reported production of gastrodin in an engineered microorganism to date, marking the first successful de novo production of gastrodin using Y. lipolytica.

Genome-scale model development and genomic sequencing of the oleaginous clade Lipomyces

The Lipomyces clade contains oleaginous yeast species with advantageous metabolic features for biochemical and biofuel production. Limited knowledge about the metabolic networks of the species and limited tools for genetic engineering have led to a relatively small amount of research on the microbes. Here, a genome-scale metabolic model (GSM) of Lipomyces starkeyi NRRL Y-11557 was built using orthologous protein mappings to model yeast species. Phenotypic growth assays were used to validate the GSM (66% accuracy) and indicated that NRRL Y-11557 utilized diverse carbohydrates but had more limited catabolism of organic acids. The final GSM contained 2,193 reactions, 1,909 metabolites, and 996 genes and was thus named iLst996. The model contained 96 of the annotated carbohydrate-active enzymes. iLst996 predicted a flux distribution in line with oleaginous yeast measurements and was utilized to predict theoretical lipid yields. Twenty-five other yeasts in the Lipomyces clade were then genome sequenced and annotated. Sixteen of the Lipomyces species had orthologs for more than 97% of the iLst996 genes, demonstrating the usefulness of iLst996 as a broad GSM for Lipomyces metabolism. Pathways that diverged from iLst996 mainly revolved around alternate carbon metabolism, with ortholog groups excluding NRRL Y-11557 annotated to be involved in transport, glycerolipid, and starch metabolism, among others. Overall, this study provides a useful modeling tool and data for analyzing and understanding Lipomyces species metabolism and will assist further engineering efforts in Lipomyces.

The metabolic domestication syndrome of budding yeast

Cellular metabolism evolves through changes in the structure and quantitative states of metabolic networks. Here, we explore the evolutionary dynamics of metabolic states by focusing on the collection of metabolite levels, the metabolome, which captures key aspects of cellular physiology. Using a phylogenetic framework, we profiled metabolites in 27 populations of nine budding yeast species, providing a graduated view of metabolic variation across multiple evolutionary time scales. Metabolite levels evolve more rapidly and independently of changes in the metabolic network's structure, providing complementary information to enzyme repertoire. Although metabolome variation accumulates mainly gradually over time, it is profoundly affected by domestication. We found pervasive signatures of convergent evolution in the metabolomes of independently domesticated clades of Saccharomyces cerevisiae. Such recurring metabolite differences between wild and domesticated populations affect a substantial part of the metabolome, including rewiring of the TCA cycle and several amino acids that influence aroma production, likely reflecting adaptation to human niches. Overall, our work reveals previously unrecognized diversity in central metabolism and the pervasive influence of human-driven selection on metabolite levels in yeasts.

Genetic inactivation of the Carnitine/Acetyl-Carnitine mitochondrial carrier of Yarrowia lipolytica leads to enhanced odd-chain fatty acid production

BACKGROUND

Mitochondrial carriers (MCs) can deeply affect the intracellular flux distribution of metabolic pathways. The manipulation of their expression level, to redirect the flux toward the production of a molecule of interest, is an attractive target for the metabolic engineering of eukaryotic microorganisms. The non-conventional yeast Yarrowia lipolytica is able to use a wide range of substrates. As oleaginous yeast, it directs most of the acetyl-CoA therefrom generated towards the synthesis of lipids, which occurs in the cytoplasm. Among them, the odd-chain fatty acids (OCFAs) are promising microbial-based compounds with several applications in the medical, cosmetic, chemical and agricultural industries.

RESULTS

In this study, we have identified the MC involved in the Carnitine/Acetyl-Carnitine shuttle in Y. lipolytica, YlCrc1. The Y. lipolytica Ylcrc1 knock-out strain failed to grow on ethanol, acetate and oleic acid, demonstrating the fundamental role of this MC in the transport of acetyl-CoA from peroxisomes and cytoplasm into mitochondria. A metabolic engineering strategy involving the deletion of YlCRC1, and the recombinant expression of propionyl-CoA transferase from Ralstonia eutropha (RePCT), improved propionate utilization and its conversion into OCFAs. These genetic modifications and a lipogenic medium supplemented with glucose and propionate as the sole carbon sources, led to enhanced accumulation of OCFAs in Y. lipolytica.

CONCLUSIONS

The Carnitine/Acetyl-Carnitine shuttle of Y. lipolytica involving YlCrc1, is the sole pathway for transporting peroxisomal or cytosolic acetyl-CoA to mitochondria. Manipulation of this carrier can be a promising target for metabolic engineering approaches involving cytosolic acetyl-CoA, as demonstrated by the effect of YlCRC1 deletion on OCFAs synthesis.

Enhancing precursor supply and modulating metabolism to achieve high-level production of β-farnesene in Yarrowia lipolytica

β-Farnesene is a sesquiterpene commonly found in essential oils of plants, with applications spanning from agricultural pest control and biofuels to industrial chemicals. The use of renewable substrates in microbial cell factories offers a sustainable approach to β-farnesene biosynthesis. In this study, malic enzyme from Mucor circinelloides was examined for NADPH regeneration, concomitant with the augmentation of cytosolic acetyl-CoA supply by expressing ATP-citrate lyase from Mus musculus and manipulating the citrate pathway via AMP deaminase and isocitrate dehydrogenase. Carbon flux was modulated through the elimination of native 6-phosphofructokinase, while the incorporation of an exogenous non-oxidative glycolysis pathway served to bridge the pentose phosphate pathway with the mevalonate pathway. The resulting orthogonal precursor supply pathway facilitated β-farnesene production, reaching 810 mg/L in shake-flask fermentation. Employing optimal fermentation conditions and feeding strategy, a titer of 28.9 g/L of β-farnesene was attained in a 2 L bioreactor.

Evaluating proteome allocation of Saccharomyces cerevisiae phenotypes with resource balance analysis

Saccharomyces cerevisiae is an important model organism and a workhorse in bioproduction. Here, we reconstructed a compact and tractable genome-scale resource balance analysis (RBA) model (i.e., named scRBA) to analyze metabolic fluxes and proteome allocation in a computationally efficient manner. Resource capacity models such as scRBA provide the quantitative means to identify bottlenecks in biosynthetic pathways due to enzyme, compartment size, and/or ribosome availability limitations. ATP maintenance rate and in vivo apparent turnover numbers (k_app) were regressed from metabolic flux and protein concentration data to capture observed physiological growth yield and proteome efficiency and allocation, respectively. Estimated parameter values were found to vary with oxygen and nutrient availability. Overall, this work (i) provides condition-specific model parameters to recapitulate phenotypes corresponding to different extracellular environments, (ii) alludes to the enhancing effect of substrate channeling and post-translational activation on in vivo enzyme efficiency in glycolysis and electron transport chain, and (iii) reveals that the Crabtree effect is underpinned by specific limitations in mitochondrial proteome capacity and secondarily ribosome availability rather than overall proteome capacity.

Comparative study of two Saccharomyces cerevisiae strains with kinetic models at genome-scale

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by ¹³C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

Engineering of Yarrowia lipolytica for terpenoid production

Terpenoids are a group of chemicals of great importance for human health and prosperity. Terpenoids can be used for human and animal nutrition, treating diseases, enhancing agricultural output, biofuels, fragrances, cosmetics, and flavouring. However, due to the rapid depletion of global natural resources and manufacturing practices relying on unsustainable petrochemical synthesis, there is a need for economic alternatives to supply the world's demand for these essential chemicals. Microbial biosynthesis offers the means to develop scalable and sustainable bioprocesses for terpenoid production. In particular, the non-conventional yeast Yarrowia lipolytica demonstrates excellent potential as a chassis for terpenoid production due to its amenability to industrial production scale-up, genetic engineering, and high accumulation of terpenoid precursors. This review aims to illustrate the scientific progress in developing Y. lipolytica terpenoid cell factories, focusing on metabolic engineering approaches for strain improvement and cultivation optimization.

Cryptic specialized metabolites drive Streptomyces exploration and provide a competitive advantage during growth with other microbes

Streptomyces bacteria have a complex life cycle that is intricately linked with their remarkable metabolic capabilities. Exploration is a recently discovered developmental innovation of these bacteria, that involves the rapid expansion of a structured colony on solid surfaces. Nutrient availability impacts exploration dynamics, and we have found that glycerol can dramatically increase exploration rates and alter the metabolic output of exploring colonies. We show here that glycerol-mediated growth acceleration is accompanied by distinct transcriptional signatures and by the activation of otherwise cryptic metabolites including the orange-pigmented coproporphyrin, the antibiotic chloramphenicol, and the uncommon, alternative siderophore foroxymithine. Exploring cultures are also known to produce the well-characterized desferrioxamine siderophore. Mutational studies of single and double siderophore mutants revealed functional redundancy when strains were cultured on their own; however, loss of the alternative foroxymithine siderophore imposed a more profound fitness penalty than loss of desferrioxamine during coculture with the yeast Saccharomyces cerevisiae. Notably, the two siderophores displayed distinct localization patterns, with desferrioxamine being confined within the colony area, and foroxymithine diffusing well beyond the colony boundary. The relative fitness advantage conferred by the alternative foroxymithine siderophore was abolished when the siderophore piracy capabilities of S. cerevisiae were eliminated (S. cerevisiae encodes a ferrioxamine-specific transporter). Our work suggests that exploring Streptomyces colonies can engage in nutrient-targeted metabolic arms races, deploying alternative siderophores that allow them to successfully outcompete other microbes for the limited bioavailable iron during coculture.

Enhancing Red Yeast Biomass Yield and Lipid Biosynthesis by Using Waste Nitrogen Source by Glucose Fed-Batch at Low Temperature

This work reports the effect of simple feeding strategies and temperature to obtain high-cell-density cultures of Rhodotorula glutinis var. rubescens LOCKR13 maximizing the de novo lipid productivity using deproteinated potato wastewater (DPW) as a basic medium. Feeding DPW with glucose enables a high yield of Rhodotorula glutinis var. rubescens LOCKR13 biomass (52 g d.w. L−1) to be obtained. The highest values of lipid accumulation (34.15%, w/w), production (14.68 g L−1) and yield coefficients (YL/S: 0.242 g g−1), and volumetric productivity (PL: 0.1 g L−1 h−1) were reached by the strain in the two-stage fed-batch process at 20 °C. The lipid of yeast biomass was rich in oleic acid (Δ9C18:1) and palmitic acid (C16:0), and the lower temperature of incubation significantly increased the MUFA (especially oleic acid) content. For the first time, a unique set of thermal analyses of the microbial oil was performed. The isotherms of the oxidation kinetics (PDSC) showed that lipids extracted from the biomass of red yeast had high oxidative stability. This feature of the yeast oil can be useful for long-shelf-life food products and can be promising for the production of biodiesel.

Deep learning-based kcat prediction enables improved enzyme-constrained model reconstruction

Enzyme turnover numbers (kcat) are key to understanding cellular metabolism, proteome allocation and physiological diversity, but experimentally measured kcat data are sparse and noisy. Here we provide a deep learning approach (DLKcat) for high-throughput kcat prediction for metabolic enzymes from any organism merely from substrate structures and protein sequences. DLKcat can capture kcat changes for mutated enzymes and identify amino acid residues with a strong impact on kcat values. We applied this approach to predict genome-scale kcat values for more than 300 yeast species. Additionally, we designed a Bayesian pipeline to parameterize enzyme-constrained genome-scale metabolic models from predicted kcat values. The resulting models outperformed the corresponding original enzyme-constrained genome-scale metabolic models from previous pipelines in predicting phenotypes and proteomes, and enabled us to explain phenotypic differences. DLKcat and the enzyme-constrained genome-scale metabolic model construction pipeline are valuable tools to uncover global trends of enzyme kinetics and physiological diversity, and to further elucidate cellular metabolism on a large scale.

Engineering of Yarrowia lipolytica for the production of plant triterpenoids: Asiatic, madecassic, and arjunolic acids

Several plant triterpenoids have valuable pharmaceutical properties, but their production and usage is limited since extraction from plants can burden natural resources, and result in low yields and purity. Here, we engineered oleaginous yeast Yarrowia lipolytica to produce three valuable plant triterpenoids (asiatic, madecassic, and arjunolic acids) by fermentation. First, we established the recombinant production of precursors, ursolic and oleanolic acids, by expressing plant enzymes in free or fused versions in a Y. lipolytica strain previously optimized for squalene production. Engineered strains produced up to 11.6 mg/g DCW ursolic acid or 10.2 mg/g DCW oleanolic acid. The biosynthetic pathway from ursolic acid was extended by expressing the Centella asiatica cytochrome P450 monoxygenases CaCYP716C11p, CaCYP714E19p, and CaCYP716E41p, resulting in the production of trace amounts of asiatic acid and 0.12 mg/g DCW madecassic acid. Expressing the same C. asiatica cytochromes P450 in oleanolic acid-producing strain resulted in the production of oleanane triterpenoids. Expression of CaCYP716C11p in the oleanolic acid-producing strain yielded 8.9 mg/g DCW maslinic acid. Further expression of a codon-optimized CaCYP714E19p resulted in 4.4 mg/g DCW arjunolic acid. Lastly, arjunolic acid production was increased to 9.1 mg/g DCW by swapping the N-terminal domain of CaCYP714E19p with the N-terminal domain from a Kalopanax septemlobus cytochrome P450. In summary, we have demonstrated the production of asiatic, madecassic, and arjunolic acids in a microbial cell factory. The strains and fermentation processes need to be further improved before the production of these molecules by fermentation can be industrialized.

Production of abscisic acid in the oleaginous yeast Yarrowia lipolytica

Abscisic acid (ABA) is a phytohormone with applications in agriculture and human health. ABA can be produced by Botrytis cinerea, a plant pathogenic filamentous fungus. However, the cultivation process is lengthy and strain improvement by genetic engineering is difficult. Therefore, we engineered the oleaginous yeast Yarrowia lipolytica as an alternative host for ABA production. First, we expressed five B. cinerea genes involved in ABA biosynthesis (BcABA1, BcABA2, BcABA3, BcABA4, and BcCPR1) in a Y. lipolytica chassis with optimized mevalonate flux. The strain produced 59.2 mg/L of ABA in small-scale cultivation. Next, we expressed an additional copy of each gene in the strain, but only expression of additional copy of BcABA1 gene increased the ABA titer to 168.5 mg/L. We then integrated additional copies of mevalonate pathway and ABA-biosynthesis encoding genes, and we expressed plant ABA-transporters resulting in an improved strain producing 263.5 mg/L and 9.1 mg/g DCW ABA. Bioreactor cultivation resulted in a specific yield of 12.8 mg/g DCW ABA, however, surprisingly, the biomass level obtained in bioreactors was only 10.5 g DCW/L, with a lower ABA titer of 133.6 mg/L. While further optimization is needed, this study confirms that Y. lipolytica as a potential alternative host for the abscisic acid production.

Exploratory Growth in Streptomyces venezuelae Involves a Unique Transcriptional Program, Enhanced Oxidative Stress Response, and Profound Acceleration in Response to Glycerol

Exploration is a recently discovered mode of growth and behavior exhibited by some Streptomyces species that is distinct from their classical sporulating life cycle. While much has been uncovered regarding initiating environmental conditions and phenotypic outcomes of exploratory growth, how this process is coordinated at a genetic level remains unclear. We used RNA sequencing to survey global changes in the transcriptional profile of exploring cultures over time in the model organism Streptomyces venezuelae. Transcriptomic analyses revealed widespread changes in gene expression impacting diverse cellular functions. Investigations into differentially expressed regulatory elements revealed specific groups of regulatory factors to be impacted, including the expression of several extracytoplasmic function (ECF) sigma factors, second messenger signaling pathways, and members of the whiB-like (wbl) family of transcription factors. Dramatic changes were observed among primary metabolic pathways, especially among respiration-associated genes and the oxidative stress response; enzyme assays confirmed that exploring cultures exhibit an enhanced oxidative stress response compared with classically growing cultures. Changes in the expression of the glycerol catabolic genes in S. venezuelae led to the discovery that glycerol supplementation of the growth medium promotes a dramatic acceleration of exploration. This effect appears to be unique to glycerol as an alternative carbon source, and this response is broadly conserved across other exploration-competent species. IMPORTANCE Exploration represents an alternative growth strategy for Streptomyces bacteria and is initiated in response to other microbes or specific environmental conditions. Here, we show that entry into exploration involves comprehensive transcriptional reprogramming, with an emphasis on changes in primary metabolism and regulatory/signaling functions. Intriguingly, a number of transcription factor classes were downregulated upon entry into exploration. In contrast, respiration-associated genes were strongly induced, and this was accompanied by an enhanced oxidative stress response. Notably, our transcriptional analyses suggested that glycerol may play a role in exploration, and we found that glycerol supplementation dramatically enhanced the exploration response in many streptomycetes. This work sheds new light on the regulatory and metabolic cues that influence a fascinating new microbial behavior.

Multi-Omics Analysis of Multiple Glucose-Sensing Receptor Systems in Yeast

The yeast Saccharomyces cerevisiae has long been used to produce alcohol from glucose and other sugars. While much is known about glucose metabolism, relatively little is known about the receptors and signaling pathways that indicate glucose availability. Here, we compare the two glucose receptor systems in S. cerevisiae. The first is a heterodimer of transporter-like proteins (transceptors), while the second is a seven-transmembrane receptor coupled to a large G protein (Gpa2) that acts in coordination with two small G proteins (Ras1 and Ras2). Through comprehensive measurements of glucose-dependent transcription and metabolism, we demonstrate that the two receptor systems have distinct roles in glucose signaling: the G-protein-coupled receptor directs carbohydrate and energy metabolism, while the transceptors regulate ancillary processes such as ribosome, amino acids, cofactor and vitamin metabolism. The large G-protein transmits the signal from its cognate receptor, while the small G-protein Ras2 (but not Ras1) integrates responses from both receptor pathways. Collectively, our analysis reveals the molecular basis for glucose detection and the earliest events of glucose-dependent signal transduction in yeast.

Recent Advances in the Biosynthesis of Farnesene Using Metabolic Engineering

Farnesene, as an important sesquiterpene isoprenoid polymer of acetyl-CoA, is a renewable feedstock for diesel fuel, polymers, and cosmetics. It has been widely applied in agriculture, medicine, energy, and other fields. In recent years, farnesene biosynthesis is considered a green and economical approach because of its mild reaction conditions, low environmental pollution, and sustainability. Metabolic engineering has been widely applied to construct cell factories for farnesene biosynthesis. In this paper, the research progress, common problems, and strategies of farnesene biosynthesis are reviewed. They are mainly described from the perspectives of the current status of farnesene biosynthesis in different host cells, optimization of the metabolic pathway for farnesene biosynthesis, and key enzymes for farnesene biosynthesis. Furthermore, the challenges and prospects for future farnesene biosynthesis are discussed.

Engineering ergothioneine production in Yarrowia lipolytica

Ergothioneine is a naturally occurring antioxidant that has shown potential in ameliorating neurodegenerative and cardiovascular diseases. In this study, we investigated the potential of the Crabtree‐negative, oleaginous yeast Yarrowia lipolytica as an alternative host for ergothioneine production. We expressed the biosynthetic enzymes EGT1 from Neurospora crassa and EGT2 from Claviceps purpurea to obtain 158 mg·L⁻¹ of ergothioneine in small‐scale cultivation, with an additional copy of each gene improving the titer to 205 mg·L⁻¹. The effect of phosphate limitation on ergothioneine production was studied, and finally, a phosphate‐limited fed‐batch fermentation in 1 L bioreactors yielded 1.63 ± 0.04 g·L⁻¹ ergothioneine in 220 h, corresponding to an overall volumetric productivity of 7.41 mg·L⁻¹·h⁻¹, showing that Y. lipolytica is a promising host for ergothioneine production.

Development of bifunctional biosensors for sensing and dynamic control of glycolysis flux in metabolic engineering

Glycolysis is the primary metabolic pathway in all living organisms. Maintaining the balance of glycolysis flux and biosynthetic pathways is the crucial matter involved in the microbial cell factory. Few regulation systems can address the issue of metabolic flux imbalance in glycolysis. Here, we designed and constructed a bifunctional glycolysis flux biosensor that can dynamically regulate glycolysis flux for overproduction of desired biochemicals. A series of positive-and negative-response biosensors were created and modified for varied thresholds and dynamic ranges. These engineered glycolysis flux biosensors were verified to be able to characterize in vivo fructose-1,6-diphosphate concentration. Subsequently, the biosensors were applied for fine-tuning glycolysis flux to effectively balance the biosynthesis of two chemicals: mevalonate and N-acetylglucosamine. A glycolysis flux-dynamically controlled Escherichia coli strain achieved a 111.3 g/L mevalonate titer in a 1L fermenter.

Yeast metabolic innovations emerged via expanded metabolic network and gene positive selection

Yeasts are known to have versatile metabolic traits, while how these metabolic traits have evolved has not been elucidated systematically. We performed integrative evolution analysis to investigate how genomic evolution determines trait generation by reconstructing genome-scale metabolic models (GEMs) for 332 yeasts. These GEMs could comprehensively characterize trait diversity and predict enzyme functionality, thereby signifying that sequence-level evolution has shaped reaction networks towards new metabolic functions. Strikingly, using GEMs, we can mechanistically map different evolutionary events, e.g. horizontal gene transfer and gene duplication, onto relevant subpathways to explain metabolic plasticity. This demonstrates that gene family expansion and enzyme promiscuity are prominent mechanisms for metabolic trait gains, while GEM simulations reveal that additional factors, such as gene loss from distant pathways, contribute to trait losses. Furthermore, our analysis could pinpoint to specific genes and pathways that have been under positive selection and relevant for the formulation of complex metabolic traits, i.e. thermotolerance and the Crabtree effect. Our findings illustrate how multidimensional evolution in both metabolic network structure and individual enzymes drives phenotypic variations.

Large dependency of intracellular NAD and CoA pools on cultivation conditions in Saccharomyces cerevisiae

OBJECTIVE

The objective of this study was to investigate the variation of NAD and CoA metabolite pools in Saccharomyces cerevisiae cultivated under various cultivation conditions. This study complements a previous report on glycolytic, pentose phosphate pathway, tricarboxylic acid cycle, amino acids, and deoxy-/nucleoside phosphate pools determined under the same cultivation conditions.

RESULTS

S. cerevisiae pellets from batch (four carbohydrate sources) and chemostat (carbon-, nitrogen-, phosphate-limited and a range of dilution rates) bioreactor cultivations were extracted and analyzed with two recently established absolute quantitative liquid chromatography mass spectrometry (LC-MS/MS) methods for NAD and CoA metabolites. Both methods apply 13C internal standard dilution strategy for the enhanced analytical accuracy and precision. Individual metabolite pools were relatively constant for the different growth rates within the same mode of cultivation, but large differences were observed among some of the modes, i.e. NAD metabolites were 10 to 100-fold lower in nitrogen limited chemostats compared to the other modes, and phosphate limited chemostats were characterized with much lower CoA metabolite pools. The results complement the previous results and together provide a comprehensive insight into primary metabolite pools variations at a large range in growth and carbon source consumption rates.

mfapy: An open-source Python package for 13C-based metabolic flux analysis

¹³C-based metabolic flux analysis (¹³C-MFA) is an essential tool for estimating intracellular metabolic flux levels in metabolic engineering and biology. In ¹³C-MFA, a metabolic flux distribution that explains the observed isotope labeling data was computationally estimated using a non-linear optimization method. Herein, we report the development of mfapy, an open-source Python package developed for more flexibility and extensibility for ¹³C-MFA. mfapy compels users to write a customized Python code by describing each step in the data analysis procedures of the isotope labeling experiments. The flexibility and extensibility provided by mfapy can support trial-and-error performance in the routine estimation of metabolic flux distributions, experimental design by computer simulations of ¹³C-MFA experiments, and development of new data analysis techniques for stable isotope labeling experiments. mfapy is available to the public from the Github repository (https://github.com/fumiomatsuda/mfapy).

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An open-source Python package, mfapy, is developed for ¹³C-MFA.

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mfapy enables users to write Python codes for data analysis procedures of ¹³C-MFA.

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mfapy has a flexibility and extensibility to support various data analysis procedures.

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Computer simulations of ¹³C-MFA experiments is supported for experimental design.

Tailored biosynthesis of gibberellin plant hormones in yeast

The application of small amounts of natural plant growth hormones, such as gibberellins (GAs), can increase the productivity and quality of many vegetable and fruit crops. However, gibberellin growth hormones usage is limited by the high cost of their production, which is currently based on fermentation of a natural fungal producer Fusarium fujikuroi that produces a mix of several GAs. We explored the potential of the oleaginous yeast Yarrowia lipolytica to produce specific profiles of GAs. Firstly, the production of the GA-precursor ent-kaurenoic acid (KA) at 3.75 mg/L was achieved by expression of biosynthetic enzymes from the plant Arabidopsis thaliana and upregulation of the mevalonate (MVA) pathway.

We then built a GA₄-producing strain by extending the GA-biosynthetic pathway and upregulating the MVA-pathway further, resulting in 17.29 mg/L GA₄. Additional expression of the F. fujikoroi GA-biosynthetic enzymes resulted in the production of GA₇ (trace amounts) and GA₃ (2.93 mg/L). Lastly, through protein engineering and the expression of additional KA-biosynthetic genes, we increased the GA₃-production 4.4-fold resulting in 12.81 mg/L. The developed system presents a promising resource for the recombinant production of specific gibberellins, identifying bottlenecks in GA biosynthesis, and discovering new GA biosynthetic genes.

Classification

Biological Sciences, Applied Biological Sciences.

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A complete biosynthetic pathway towards gibberellins was reconstructed in a microbial host

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The pathway towards ent-kaurenoic acid consisted of Arabidopsis thaliana enzymes

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The pathway from ent-kaurenoic acid to gibberellins GA₃, GA₄ and GA₇ consisted of Fusarium fujikuroi enzymes

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Y. lipolytica expressed 14 heterologous genes for gibberellins biosynthesis and had 5 genome edits for improved mevalonate flux

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The strains produced up to 12 mg/L of GA₃ and up to 17 mg/L GA₄ in small-scale cultivations

Impact of the Whole Genome Duplication Event on PYK Activity and Effects of a PYK1 Mutation on Metabolism in S. cerevisiae

Background: Evolution of aerobic fermentation (crabtree effect) in yeast is associated with the whole genome duplication (WGD) event, suggesting that duplication of certain genes may have altered yeast metabolism. The pyruvate kinase (PYK) gene is associated with alterations in cell metabolism, and duplicated during the WGD, generating PYK1 and PYK2. Thus, the impact of WGD on PYK activity and role of PYK in yeast metabolism were explored. Methods: PYK activity in the presence or absence of fructose-1,6-bisphosphate (FBP) was compared between pre- and post-WGD yeast. Glucose consumption, ethanol production, and oxygen consumption were measured in wildtype yeast and yeast with a T403E point mutation, which alters FBP binding affinity. Results: FBP stimulated increased PYK activity in pre-WGD yeast and in the PYK1 isoforms of post-WGD yeast, but not in the PYK2 isoforms of post-WGD yeast. Compared to wildtype, T403E mutant yeast displayed reduced glucose consumption, reduced ethanol production, and increased mitochondrial metabolism. Conclusion: The WGD event impacted the sensitivity of PYK activity to FBP. Mutations in the FBP binding domain of PYK induce metabolic shifts that favor respiration and suppress fermentation.

Adaptation of central metabolite pools to variations in growth rate and cultivation conditions in Saccharomyces cerevisiae

Background

Saccharomyces cerevisiae is a well-known popular model system for basic biological studies and serves as a host organism for the heterologous production of commercially interesting small molecules and proteins. The central metabolism is at the core to provide building blocks and energy to support growth and survival in normal situations as well as during exogenous stresses and forced heterologous protein production. Here, we present a comprehensive study of intracellular central metabolite pool profiling when growing S. cerevisiae on different carbon sources in batch cultivations and at different growth rates in nutrient-limited glucose chemostats. The latest versions of absolute quantitative mass spectrometry-based metabolite profiling methodology were applied to cover glycolytic and pentose phosphate pathway metabolites, tricarboxylic acid cycle (TCA), complete amino acid, and deoxy-/nucleoside phosphate pools.

Results

Glutamate, glutamine, alanine, and citrate were the four most abundant metabolites for most conditions tested. The amino acid is the dominant metabolite class even though a marked relative reduction compared to the other metabolite classes was observed for nitrogen and phosphate limited chemostats. Interestingly, glycolytic and pentose phosphate pathway (PPP) metabolites display the largest variation among the cultivation conditions while the nucleoside phosphate pools are more stable and vary within a closer concentration window. The overall trends for glucose and nitrogen-limited chemostats were increased metabolite pools with the increasing growth rate. Next, comparing the chosen chemostat reference growth rate (0.12 h⁻¹, approximate one-fourth of maximal unlimited growth rate) illuminates an interesting pattern: almost all pools are lower in nitrogen and phosphate limited conditions compared to glucose limitation, except for the TCA metabolites citrate, isocitrate and α-ketoglutarate.

Conclusions

This study provides new knowledge-how the central metabolism is adapting to various cultivations conditions and growth rates which is essential for expanding our understanding of cellular metabolism and the development of improved phenotypes in metabolic engineering.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-021-01557-8.

Yeast-Based Biosynthesis of Natural Products From Xylose

Xylose is the second most abundant sugar in lignocellulosic hydrolysates. Transformation of xylose into valuable chemicals, such as plant natural products, is a feasible and sustainable route to industrializing biorefinery of biomass materials. Yeast strains, including Saccharomyces cerevisiae, Scheffersomyces stipitis, and Yarrowia lipolytica, display some paramount advantages in expressing heterologous enzymes and pathways from various sources and have been engineered extensively to produce natural products. In this review, we summarize the advances in the development of metabolically engineered yeasts to produce natural products from xylose, including aromatics, terpenoids, and flavonoids. The state-of-the-art metabolic engineering strategies and representative examples are reviewed. Future challenges and perspectives are also discussed on yeast engineering for commercial production of natural products using xylose as feedstocks.

Comparative metabolomics of Phialemonium curvatum as an omnipotent fungus cultivated on crude palm oil versus glucose

BACKGROUND

Sugars and triglycerides are common carbon sources for microorganisms. Nonetheless, a systematic comparative interpretation of metabolic changes upon vegetable oil or glucose as sole carbon source is still lacking. Selected fungi that can grow in acidic mineral salt media (MSM) with vegetable oil had been identified recently. Hence, this study aimed to investigate the overall metabolite changes of an omnipotent fungus and to reveal changes at central carbon metabolism corresponding to both carbon sources.

RESULTS

Targeted and non-targeted metabolomics for both polar and semi-polar metabolites of Phialemonium curvatum AWO2 (DSM 23903) cultivated in MSM with palm oil (MSM-P) or glucose (MSM-G) as carbon sources were obtained. Targeted metabolomics on central carbon metabolism of tricarboxylic acid (TCA) cycle and glyoxylate cycle were analysed using LC-MS/MS-TripleQ and GC-MS, while untargeted metabolite profiling was performed using LC-MS/MS-QTOF followed by multivariate analysis. Targeted metabolomics analysis showed that glyoxylate pathway and TCA cycle were recruited at central carbon metabolism for triglyceride and glucose catabolism, respectively. Significant differences in organic acids concentration of about 4- to 8-fold were observed for citric acid, succinic acid, malic acid, and oxaloacetic acid. Correlation of organic acids concentration and key enzymes involved in the central carbon metabolism was further determined by enzymatic assays. On the other hand, the untargeted profiling revealed seven metabolites undergoing significant changes between MSM-P and MSM-G cultures.

CONCLUSIONS

Overall, this study has provided insights on the understanding on the effect of triglycerides and sugar as carbon source in fungi global metabolic pathway, which might become important for future optimization of carbon flux engineering in fungi to improve organic acids production when vegetable oil is applied as the sole carbon source.

Mitochondrial HMG-Box Containing Proteins: From Biochemical Properties to the Roles in Human Diseases

Mitochondrial DNA (mtDNA) molecules are packaged into compact nucleo-protein structures called mitochondrial nucleoids (mt-nucleoids). Their compaction is mediated in part by high-mobility group (HMG)-box containing proteins (mtHMG proteins), whose additional roles include the protection of mtDNA against damage, the regulation of gene expression and the segregation of mtDNA into daughter organelles. The molecular mechanisms underlying these functions have been identified through extensive biochemical, genetic, and structural studies, particularly on yeast (Abf2) and mammalian mitochondrial transcription factor A (TFAM) mtHMG proteins. The aim of this paper is to provide a comprehensive overview of the biochemical properties of mtHMG proteins, the structural basis of their interaction with DNA, their roles in various mtDNA transactions, and the evolutionary trajectories leading to their rapid diversification. We also describe how defects in the maintenance of mtDNA in cells with dysfunctional mtHMG proteins lead to different pathologies at the cellular and organismal level.

Yarrowia lipolytica Strains Engineered for the Production of Terpenoids

Terpenoids are a diverse group of over 55,000 compounds with potential applications as advanced fuels, bulk and fine chemicals, pharmaceutical ingredients, agricultural chemicals, etc. To facilitate their bio-based production, there is a need for plug-and-play hosts, capable of high-level production of different terpenoids. Here we engineer Yarrowia lipolytica platform strains for the overproduction of mono-, sesqui-, di-, tri-, and tetraterpenoids. The monoterpene platform strain was evaluated by expressing Perilla frutescens limonene synthase, which resulted in limonene titer of 35.9 mg/L and was 100-fold higher than when the same enzyme was expressed in the strain without mevalonate pathway improvement. Expression of Callitropsis nootkatensis valencene synthase in the sesquiterpene platform strain resulted in 113.9 mg/L valencene, an 8.4-fold increase over the control strain. Platform strains for production of squalene, complex triterpenes, or diterpenes and carotenoids were also constructed and resulted in the production of 402.4 mg/L squalene, 22 mg/L 2,3-oxidosqualene, or 164 mg/L β-carotene, respectively. The presented terpenoid platform strains can facilitate the evaluation of terpenoid biosynthetic pathways and are a convenient starting point for constructing efficient cell factories for the production of various terpenoids. The platform strains and exemplary terpenoid strains can be obtained from Euroscarf.

Parallel isotope differential modeling for instationary 13C fluxomics at the genome scale

BACKGROUND

A precise map of the metabolic fluxome, the closest surrogate to the physiological phenotype, is becoming progressively more important in the metabolic engineering of photosynthetic organisms for biofuel and biomass production. For photosynthetic organisms, the state-of-the-art method for this purpose is instationary 13C fluxomics, which has arisen as a sibling of transcriptomics or proteomics. Instationary 13C data processing requires solving high-dimensional nonlinear differential equations and leads to large computational and time costs when its scope is expanded to a genome-scale metabolic network.

RESULT

Here, we present a parallelized method to model instationary 13C labeling data. The elementary metabolite unit (EMU) framework is reorganized to allow treating individual mass isotopomers and breaking up of their networks into strongly connected components (SCCs). A variable domain parallel algorithm is introduced to process ordinary differential equations in a parallel way. 15-fold acceleration is achieved for constant-step-size modeling and ~ fivefold acceleration for adaptive-step-size modeling.

CONCLUSION

This algorithm is universally applicable to isotope granules such as EMUs and cumomers and can substantially accelerate instationary 13C fluxomics modeling. It thus has great potential to be widely adopted in any instationary 13C fluxomics modeling.

Pyruvate kinase variant of fission yeast tunes carbon metabolism, cell regulation, growth and stress resistance

Cells balance glycolysis with respiration to support their metabolic needs in different environmental or physiological contexts. With abundant glucose, many cells prefer to grow by aerobic glycolysis or fermentation. Using 161 natural isolates of fission yeast, we investigated the genetic basis and phenotypic effects of the fermentation-respiration balance. The laboratory and a few other strains depended more on respiration. This trait was associated with a single nucleotide polymorphism in a conserved region of Pyk1, the sole pyruvate kinase in fission yeast. This variant reduced Pyk1 activity and glycolytic flux. Replacing the "low-activity" pyk1 allele in the laboratory strain with the "high-activity" allele was sufficient to increase fermentation and decrease respiration. This metabolic rebalancing triggered systems-level adjustments in the transcriptome and proteome and in cellular traits, including increased growth and chronological lifespan but decreased resistance to oxidative stress. Thus, low Pyk1 activity does not lead to a growth advantage but to stress tolerance. The genetic tuning of glycolytic flux may reflect an adaptive trade-off in a species lacking pyruvate kinase isoforms.

Revisiting the Warburg Effect: Diet-Based Strategies for Cancer Prevention

It is widely acknowledged that cancer cell energy metabolism relies mainly on anaerobic glycolysis; this phenomenon is described as the Warburg effect. However, whether the Warburg effect is caused by genetic dysregulation in cancer or is the cause of cancer remains unknown. The exact reasons and physiology of this abnormal metabolism are unclear; therefore, many researchers have attempted to reduce malignant cell growth in tumors in preclinical and clinical studies. Anticancer strategies based on the Warburg effect have involved the use of drug compounds and dietary changes. We recently reviewed applications of the Warburg effect to understand the benefits of this unusual cancer-related metabolism. In the current article, we summarize diet strategies for cancer treatment based on the Warburg effect.

Tracing metabolic flux through time and space with isotope labeling experiments

Metabolism is dynamic and must function in context-specific ways to adjust to changes in the surrounding cellular and ecological environment. When isotopic tracers are used, metabolite flow (i.e. metabolic flux) can be quantified through biochemical networks to assess metabolic pathway operation. The cellular activities considered across multiple tissues and organs result in the observed phenotype and can be analyzed to discover emergent, whole-system properties of biology and elucidate misconceptions about network operation. However, temporal and spatial challenges remain significant hurdles and require novel approaches and creative solutions. We survey current investigations in higher plant and animal systems focused on dynamic isotope labeling experiments, spatially resolved measurement strategies, and observations from re-analysis of our own studies that suggest prospects for future work. Related discoveries will be necessary to push the frontier of our understanding of metabolism to suggest novel solutions to cure disease and feed a growing future world population.

Measuring glycolytic flux in single yeast cells with an orthogonal synthetic biosensor

Metabolic heterogeneity between individual cells of a population harbors significant challenges for fundamental and applied research. Identifying metabolic heterogeneity and investigating its emergence require tools to zoom into metabolism of individual cells. While methods exist to measure metabolite levels in single cells, we lack capability to measure metabolic flux, i.e., the ultimate functional output of metabolic activity, on the single-cell level. Here, combining promoter engineering, computational protein design, biochemical methods, proteomics, and metabolomics, we developed a biosensor to measure glycolytic flux in single yeast cells. Therefore, drawing on the robust cell-intrinsic correlation between glycolytic flux and levels of fructose-1,6-bisphosphate (FBP), we transplanted the B. subtilis FBP-binding transcription factor CggR into yeast. With the developed biosensor, we robustly identified cell subpopulations with different FBP levels in mixed cultures, when subjected to flow cytometry and microscopy. Employing microfluidics, we were also able to assess the temporal FBP/glycolytic flux dynamics during the cell cycle. We anticipate that our biosensor will become a valuable tool to identify and study metabolic heterogeneity in cell populations.

Comparison of metabolic profiles of yeasts based on the difference of the Crabtree positive and negative

The Crabtree effect involves energy management in which yeasts utilize glycolysis as the terminal electron acceptor instead of oxygen, despite the presence of sufficient dissolved oxygen, when oxygen concentrations exceed a certain limit. The Crabtree effect is detrimental to bakery yeast production, because it results in lower cellular glucose yields. Batch culture of Saccharomyces cerevisiae, a Crabtree positive yeast, decreased the cell yield of glucose and produced large amounts of ethanol despite a high specific glucose consumption rate compared to Candida utilis, a Crabtree negative yeast. This study investigated the effect of these characteristics on metabolite levels. We performed metabolome analysis of both yeasts during each growth phase of batch culture using liquid chromatography-tandem mass spectrometry and gas chromatography-mass spectrometry. Principle component analysis of metabolome data indicated that the Crabtree effect affected metabolites related to NADH synthesis in central metabolism. The amount of these metabolites in S. cerevisiae was lower than that in C. utilis. However, to maintain the specific glucose consumption rate at high levels, yeasts must avoid depletion of NAD⁺, which is essential for glucose utilization. Our results indicated that NADH was oxidized by converting acetaldehyde to ethanol in S. cerevisiae, which is in accordance with previous reports. Therefore, the specific NADH production rates of S. cerevisiae and C. utilis did not show a difference. This study suggested that NAD⁺/NADH ratio is disrupted by the Crabtree effect, which in turn influenced central metabolism and that S. cerevisiae maintained the NAD⁺/NADH ratio by producing ethanol.

Multi-Omics Analysis of Fatty Alcohol Production in Engineered Yeasts Saccharomyces cerevisiae and Yarrowia lipolytica

Fatty alcohols are widely used in various applications within a diverse set of industries, such as the soap and detergent industry, the personal care, and cosmetics industry, as well as the food industry. The total world production of fatty alcohols is over 2 million tons with approximately equal parts derived from fossil oil and from plant oils or animal fats. Due to the environmental impact of these production methods, there is an interest in alternative methods for fatty alcohol production via microbial fermentation using cheap renewable feedstocks. In this study, we aimed to obtain a better understanding of how fatty alcohol biosynthesis impacts the host organism, baker’s yeast Saccharomyces cerevisiae or oleaginous yeast Yarrowia lipolytica. Producing and non-producing strains were compared in growth and nitrogen-depletion cultivation phases. The multi-omics analysis included physiological characterization, transcriptome analysis by RNAseq, ¹³Cmetabolic flux analysis, and intracellular metabolomics. Both species accumulated fatty alcohols under nitrogen-depletion conditions but not during growth. The fatty alcohol–producing Y. lipolytica strain had a higher fatty alcohol production rate than an analogous S. cerevisiae strain. Nitrogen-depletion phase was associated with lower glucose uptake rates and a decrease in the intracellular concentration of acetyl–CoA in both yeast species, as well as increased organic acid secretion rates in Y. lipolytica. Expression of the fatty alcohol–producing enzyme fatty acyl–CoA reductase alleviated the growth defect caused by deletion of hexadecenal dehydrogenase encoding genes (HFD1 and HFD4) in Y. lipolytica. RNAseq analysis showed that fatty alcohol production triggered a cell wall stress response in S. cerevisiae. RNAseq analysis also showed that both nitrogen-depletion and fatty alcohol production have substantial effects on the expression of transporter encoding genes in Y. lipolytica. In conclusion, through this multi-omics study, we uncovered some effects of fatty alcohol production on the host metabolism. This knowledge can be used as guidance for further strain improvement towards the production of fatty alcohols.

Reserve Flux Capacity in the Pentose Phosphate Pathway by NADPH Binding Is Conserved across Kingdoms

All organisms evolved defense mechanisms to counteract oxidative stress and buildup of reactive oxygen species (ROS). To test whether a potentially conserved mechanism exists for the rapid response, we investigated immediate metabolic dynamics of Escherichia coli, yeast, and human dermal fibroblasts to oxidative stress that we found to be conserved between species. To elucidate the regulatory mechanisms that implement this metabolic response, we developed mechanistic kinetic models for each organism's central metabolism and systematically tested activation and inactivation of each irreversible reaction by each metabolite. This ensemble modeling predicts in vivo relevant metabolite-enzyme interactions based on their ability to quantitatively describe metabolite dynamics. All three species appear to inhibit their oxidative pentose phosphate pathway during normal growth by the redox cofactor NADPH and relieve this inhibition to increase the pathway flux for detoxification of ROS during stress, with the sole exception of yeast when exposed to high levels of stress.

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Characterization of immediate metabolic response to oxidative stress

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The metabolic response in glycolysis and PP pathway depends on stress severity

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Identification of NADPH feedback inhibition on G6PDH as key regulatory interaction

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The identified oxidative stress regulatory interaction is conserved across kingdoms

AYbRAH: a curated ortholog database for yeasts and fungi spanning 600 million years of evolution

Budding yeasts inhabit a range of environments by exploiting various metabolic traits. The genetic bases for these traits are mostly unknown, preventing their addition or removal in a chassis organism for metabolic engineering. Insight into the evolution of orthologs, paralogs and xenologs in the yeast pan-genome can help bridge these genotypes; however, existing phylogenomic databases do not span diverse yeasts, and sometimes cannot distinguish between these homologs. To help understand the molecular evolution of these traits in yeasts, we created Analyzing Yeasts by Reconstructing Ancestry of Homologs (AYbRAH), an open-source database of predicted and manually curated ortholog groups for 33 diverse fungi and yeasts in Dikarya, spanning 600 million years of evolution. OrthoMCL and OrthoDB were used to cluster protein sequence into ortholog and homolog groups, respectively; MAFFT and PhyML reconstructed the phylogeny of all homolog groups. Ortholog assignments for enzymes and small metabolite transporters were compared to their phylogenetic reconstruction, and curated to resolve any discrepancies. Information on homolog and ortholog groups can be viewed in the AYbRAH web portal (https://lmse.github.io/aybrah/), including functional annotations, predictions for mitochondrial localization and transmembrane domains, literature references and phylogenetic reconstructions. Ortholog assignments in AYbRAH were compared to HOGENOM, KEGG Orthology, OMA, eggNOG and PANTHER. PANTHER and OMA had the most congruent ortholog groups with AYbRAH, while the other phylogenomic databases had greater amounts of under-clustering, over-clustering or no ortholog annotations for proteins. Future plans are discussed for AYbRAH, and recommendations are made for other research communities seeking to create curated ortholog databases.

Elevated temperatures do not trigger a conserved metabolic network response among thermotolerant yeasts

BACKGROUND

Thermotolerance is a highly desirable trait of microbial cell factories and has been the focus of extensive research. Yeast usually tolerate only a narrow temperature range and just two species, Kluyveromyces marxianus and Ogataea polymorpha have been described to grow at reasonable rates above 40 °C. However, the complex mechanisms of thermotolerance in yeast impede its full comprehension and the rare physiological data at elevated temperatures has so far not been matched with corresponding metabolic analyses.

RESULTS

To elaborate on the metabolic network response to increased fermentation temperatures of up to 49 °C, comprehensive physiological datasets of several Kluyveromyces and Ogataea strains were generated and used for 13C-metabolic flux analyses. While the maximum growth temperature was very similar in all investigated strains, the metabolic network response to elevated temperatures was not conserved among the different species. In fact, metabolic flux distributions were remarkably irresponsive to increasing temperatures in O. polymorpha, while the K. marxianus strains exhibited extensive flux rerouting at elevated temperatures.

CONCLUSIONS

While a clear mechanism of thermotolerance is not deducible from the fluxome level alone, the generated data can be valued as a knowledge repository for using temperature to modulate the metabolic activity towards engineering goals.

Saccharomyces cerevisiae goes through distinct metabolic phases during its replicative lifespan

A comprehensive description of the phenotypic changes during cellular aging is key towards unraveling its causal forces. Previously, we mapped age-related changes in the proteome and transcriptome (Janssens et al., 2015). Here, employing the same experimental procedure and model-based inference, we generate a comprehensive account of metabolic changes during the replicative life of Saccharomyces cerevisiae. With age, we found decreasing metabolite levels, decreasing growth and substrate uptake rates accompanied by a switch from aerobic fermentation to respiration, with glycerol and acetate production. The identified metabolic fluxes revealed an increase in redox cofactor turnover, likely to combat increased production of reactive oxygen species. The metabolic changes are possibly a result of the age-associated decrease in surface area per cell volume. With metabolism being an important factor of the cellular phenotype, this work complements our recent mapping of the transcriptomic and proteomic changes towards a holistic description of the cellular phenotype during aging.

Combining 26s rDNA and the Cre-loxP System for Iterative Gene Integration and Efficient Marker Curation in Yarrowia lipolytica

Conventional plasmid-based gene expression tends to introduce genetic instability and gene copy number variations that lead to degenerated production. The limited number of auxotrophic markers in Yarrowia lipolytica also restricts our ability to perform iterative genetic modifications and manipulate long gene clusters. To overcome these limitations, we combined the high recombination efficiency of the Cre-loxP system and the high integration rate of 26s rDNA, and developed a versatile framework to iteratively integrate multicopy metabolic pathways in Y. lipolytica. We demonstrated the efficient genome integration of a plant-derived flavonoid pathway at random sites with multiple copies. Transient expression of Cre recombinase enabled efficient marker removal and allowed for the next round of genome integration. Investigating the recombination events demonstrated that the iterative integration is happening at sufficiently high rates (more than 80%) without disrupting the previous integration. Both the flavonoid precursor pathway and the plant-derived cytochrome c P450 enzymes were functionally integrated to improve flavonoid and hydroxylated flavonoid production. The engineered strains produced 71.2 mg/L naringenin, 54.2 mg/L eriodyctiol, and 48.1 mg/L taxifolin. The reported work provides a versatile platform to iteratively integrate functional gene clusters at high copy numbers. This work may streamline and expand our capability to build efficient microbial cell factories for high-value natural products and commodity chemical production in Y. lipolytica.

Engineering two species of yeast as cell factories for 2'-fucosyllactose

Oligosaccharides present in human breast milk have been linked to beneficial effects on infant health. Inclusion of these human milk oligosaccharides (HMOs) in infant formula can recapitulate these health benefits. As a result, there is substantial commercial interest in a cost-effective source of HMOs as infant formula ingredients. Here we demonstrate that the yeast species Saccharomyces cerevisiae and Yarrowia lipolytica both can be engineered to produce 2'-fucosyllactose (2'FL), which is the most abundant oligosaccharide in human breast milk, at high titer and productivity. Both yeast species were modified to enable uptake of lactose and synthesis of GDP-fucose - the two precursors of 2'FL - by installing a lactose transporter and enzymes that convert GDP-mannose to GDP-fucose. Production of 2'FL was then enabled by expression of α-1,2-fucosyltransferases from various organisms. By screening candidate transporters from a variety of sources, we identified transporters capable of exporting 2'FL from yeast, which is a key consideration for any biocatalyst for 2'FL production. In particular, we identified CDT2 from Neurospora crassa as a promising target for further engineering to improve 2'FL efflux. Finally, we demonstrated production of 2'FL in fermenters at rates and titers that indicate the potential of engineered S. cerevisiae and Y. lipolytica strains for commercial 2'FL production.

Regulation of glycolytic flux and overflow metabolism depending on the source of energy generation for energy demand

Overflow metabolism is a common phenomenon observed at higher glycolytic flux in many bacteria, yeast (known as Crabtree effect), and mammalian cells including cancer cells (known as Warburg effect). This phenomenon has recently been characterized as the trade-offs between protein costs and enzyme efficiencies based on coarse-graining approaches. Moreover, it has been recognized that the glycolytic flux increases as the source of energy generation changes from energetically efficient respiration to inefficient respiro-fermentative or fermentative metabolism causing overflow metabolism. It is highly desired to clarify the metabolic regulation mechanisms behind such phenomena. Metabolic fluxes are located on top of the hierarchical regulation systems, and represent the outcome of the integrated response of all levels of cellular regulation systems. In the present article, we discuss about the different levels of regulation systems for the modulation of fluxes depending on the growth rate, growth condition such as oxygen limitation that alters the metabolism towards fermentation, and genetic perturbation affecting the source of energy generation from respiration to respiro-fermentative metabolism in relation to overflow metabolism. The intracellular metabolite of the upper glycolysis such as fructose 1,6-bisphosphate (FBP) plays an important role not only for flux sensing, but also for the regulation of the respiratory activity either directly or indirectly (via transcription factors) at higher growth rate. The glycolytic flux regulation is backed up (enhanced) by unphosphorylated EIIA and HPr of the phosphotransferase system (PTS) components, together with the sugar-phosphate stress regulation, where the transcriptional regulation is further modulated by post-transcriptional regulation via the degradation of mRNA (stability of mRNA) in Escherichia coli. Moreover, the channeling may also play some role in modulating the glycolytic cascade reactions.

Metabolic engineering in the host Yarrowia lipolytica

The nonconventional, oleaginous yeast, Yarrowia lipolytica is rapidly emerging as a valuable host for the production of a variety of both lipid and nonlipid chemical products. While the unique genetics of this organism pose some challenges, many new metabolic engineering tools have emerged to facilitate improved genetic manipulation in this host. This review establishes a case for Y. lipolytica as a premier metabolic engineering host based on innate metabolic capacity, emerging synthetic tools, and engineering examples. The metabolism underlying the lipid accumulation phenotype of this yeast as well as high flux through acyl-CoA precursors and the TCA cycle provide a favorable metabolic environment for expression of relevant heterologous pathways. These properties allow Y. lipolytica to be successfully engineered for the production of both native and nonnative lipid, organic acid, sugar and acetyl-CoA derived products. Finally, this host has unique metabolic pathways enabling growth on a wide range of carbon sources, including waste products. The expansion of carbon sources, together with the improvement of tools as highlighted here, have allowed this nonconventional organism to act as a cellular factory for valuable chemicals and fuels.

Optimizing anaerobic growth rate and fermentation kinetics in Saccharomyces cerevisiae strains expressing Calvin-cycle enzymes for improved ethanol yield

BACKGROUND

Reduction or elimination of by-product formation is of immediate economic relevance in fermentation processes for industrial bioethanol production with the yeast Saccharomyces cerevisiae. Anaerobic cultures of wild-type S. cerevisiae require formation of glycerol to maintain the intracellular NADH/NAD+ balance. Previously, functional expression of the Calvin-cycle enzymes ribulose-1,5-bisphosphate carboxylase (RuBisCO) and phosphoribulokinase (PRK) in S. cerevisiae was shown to enable reoxidation of NADH with CO2 as electron acceptor. In slow-growing cultures, this engineering strategy strongly decreased the glycerol yield, while increasing the ethanol yield on sugar. The present study explores engineering strategies to improve rates of growth and alcoholic fermentation in yeast strains that functionally express RuBisCO and PRK, while maximizing the positive impact on the ethanol yield.

RESULTS

Multi-copy integration of a bacterial-RuBisCO expression cassette was combined with expression of the Escherichia coli GroEL/GroES chaperones and expression of PRK from the anaerobically inducible DAN1 promoter. In anaerobic, glucose-grown bioreactor batch cultures, the resulting S. cerevisiae strain showed a 31% lower glycerol yield and a 31% lower specific growth rate than a non-engineered reference strain. Growth of the engineered strain in anaerobic, glucose-limited chemostat cultures revealed a negative correlation between its specific growth rate and the contribution of the Calvin-cycle enzymes to redox homeostasis. Additional deletion of GPD2, which encodes an isoenzyme of NAD+-dependent glycerol-3-phosphate dehydrogenase, combined with overexpression of the structural genes for enzymes of the non-oxidative pentose-phosphate pathway, yielded a CO2-reducing strain that grew at the same rate as a non-engineered reference strain in anaerobic bioreactor batch cultures, while exhibiting a 86% lower glycerol yield and a 15% higher ethanol yield.

CONCLUSIONS

The metabolic engineering strategy presented here enables an almost complete elimination of glycerol production in anaerobic, glucose-grown batch cultures of S. cerevisiae, with an associated increase in ethanol yield, while retaining near wild-type growth rates and a capacity for glycerol formation under osmotic stress. Using current genome-editing techniques, the required genetic modifications can be introduced in one or a few transformations. Evaluation of this concept in industrial strains and conditions is therefore a realistic next step towards its implementation for improving the efficiency of first- and second-generation bioethanol production.