Metabolomic and (13)C-metabolic flux analysis of a xylose-consuming Saccharomyces cerevisiae strain expressing xylose isomerase

Chemobiosis reveals tardigrade tun formation is dependent on reversible cysteine oxidation

Tardigrades, commonly known as 'waterbears', are eight-legged microscopic invertebrates renowned for their ability to withstand extreme stressors, including high osmotic pressure, freezing temperatures, and complete desiccation. Limb retraction and substantial decreases to their internal water stores results in the tun state, greatly increasing their ability to survive. Emergence from the tun state and/or activity regain follows stress removal, where resumption of life cycle occurs as if stasis never occurred. However, the mechanism(s) through which tardigrades initiate tun formation is yet to be uncovered. Herein, we use chemobiosis to demonstrate that tardigrade tun formation is mediated by reactive oxygen species (ROS). We further reveal that tuns are dependent on reversible cysteine oxidation, and that this reversible cysteine oxidation is facilitated by the release of intracellular reactive oxygen species (ROS). We provide the first empirical evidence of chemobiosis and map the initiation and survival of tardigrades via osmobiosis, chemobiosis, and cryobiosis. In vivo electron paramagnetic spectrometry suggests an intracellular release of reactive oxygen species following stress induction; when this release is quenched through the application of exogenous antioxidants, the tardigrades can no longer survive osmotic stress. Together, this work suggests a conserved dependence of reversible cysteine oxidation across distinct tardigrade cryptobioses.

Construction of a xylose metabolic pathway in Trichosporonoides oedocephalis ATCC 16958 for the production of erythritol and xylitol

PURPOSE

Erythritol is a valuable compound as sweetener and chemical material however cannot be fermented from the abundant substrate xylose.

METHODS

The strain Trichosporonoides oedocephalis ATCC 16958 was employed to produce polyols including xylitol and erythritol by metabolic engineering approaches.

RESULTS

The introduction of a substrate-specific ribose-5-phosphate isomerase endowed T. oedocephalis with xylose-assimilation activity to produce xylitol, and eliminated glycerol production simultaneously. A more value-added product, erythritol was produced by further introducing a homologous xylulose kinase. The carbon flux was redirected from xylitol to erythritol by adding high osmotic pressure. The production of erythritol was improved to 46.5 g/L in flasks by fermentation adjustment, and the process was scaled up in a 5-L fermentor, with a 40 g/L erythritol production after 120 h, and a time-space yield of 0.56 g/L/h.

CONCLUSION

This study demonstrated the potential of T. oedocephalis in the synthesis of multiple useful products from xylose.

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.

D-xylose accelerated death of pentose metabolizing Saccharomyces cerevisiae

Rapid and effective consumption of D-xylose by Saccharomyces cerevisiae is essential for cost-efficient cellulosic bioethanol production. Hence, heterologous D-xylose metabolic pathways have been introduced into S. cerevisiae. An effective solution is based on a xylose isomerase in combination with the overexpression of the xylulose kinase (Xks1) and all genes of the non-oxidative branch of the pentose phosphate pathway. Although this strain is capable of consuming D-xylose, growth inhibition occurs at higher D-xylose concentrations, even abolishing growth completely at 8% D-xylose. The decreased growth rates are accompanied by significantly decreased ATP levels. A key ATP-utilizing step in D-xylose metabolism is the phosphorylation of D-xylulose by Xks1. Replacement of the constitutive promoter of XKS1 by the galactose tunable promoter Pgal10 allowed the controlled expression of this gene over a broad range. By decreasing the expression levels of XKS1, growth at high D-xylose concentrations could be restored concomitantly with increased ATP levels and high rates of xylose metabolism. These data show that in fermentations with high D-xylose concentrations, too high levels of Xks1 cause a major drain on the cellular ATP levels thereby reducing the growth rate, ultimately causing substrate accelerated death. Hence, expression levels of XKS1 in S. cerevisiae needs to be tailored for the specific growth conditions and robust D-xylose metabolism.

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.

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

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

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.

Machine learning applied for metabolic flux-based control of micro-aerated fermentations in bioreactors

Various bio-based processes depend on controlled micro-aerobic conditions to achieve a satisfactory product yield. However, the limiting oxygen concentration varies according to the micro-organism employed, while for industrial applications, there is no cost-effective way of measuring it at low levels. This study proposes a machine learning procedure within a metabolic flux-based control strategy (SUPERSYS_MCU) to address this issue. The control strategy used simulations of a genome-scale metabolic model to generate a surrogate model in the form of an artificial neural network, to be used in a micro-aerobic fermentation strategy (MF-ANN). The meta-model provided setpoints to the controller, allowing adjustment of the inlet air flow to control the oxygen uptake rate. The strategy was evaluated in micro-aerobic batch cultures employing industrial Saccharomyces cerevisiae yeast, with defined medium and glucose as the carbon source, as a case study. The performance of the proposed control scheme was compared with a conventional fermentation and with three previously reported micro-aeration strategies, including respiratory quotient-based control and constant air flow rate. Due to maintenance of the oxidative balance at the anaerobiosis threshold, the MF-ANN provided volumetric ethanol productivity of 4.16 g·L^-1 ·h^-1 and a yield of 0.48 g_ethanol .g_substrate ^-1 , which were higher than the values achieved for the other conditions studied (maximum of 3.4 g·L^-1 ·h^-1 and 0.35-0.40 g_ethanol ·g_substrate ^-1 , respectively). Due to its modular character, the MF-ANN strategy could be adapted to other micro-aerated bioprocesses.

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.

Structure-based directed evolution improves S. cerevisiae growth on xylose by influencing in vivo enzyme performance

BACKGROUND

Efficient bioethanol production from hemicellulose feedstocks by Saccharomyces cerevisiae requires xylose utilization. Whereas S. cerevisiae does not metabolize xylose, engineered strains that express xylose isomerase can metabolize xylose by converting it to xylulose. For this, the type II xylose isomerase from Piromyces (PirXI) is used but the in vivo activity is rather low and very high levels of the enzyme are needed for xylose metabolism. In this study, we explore the use of protein engineering and in vivo selection to improve the performance of PirXI. Recently solved crystal structures were used to focus mutagenesis efforts.

RESULTS

We constructed focused mutant libraries of Piromyces xylose isomerase by substitution of second shell residues around the substrate- and metal-binding sites. Following library transfer to S. cerevisiae and selection for enhanced xylose-supported growth under aerobic and anaerobic conditions, two novel xylose isomerase mutants were obtained, which were purified and subjected to biochemical and structural analysis. Apart from a small difference in response to metal availability, neither the new mutants nor mutants described earlier showed significant changes in catalytic performance under various in vitro assay conditions. Yet, in vivo performance was clearly improved. The enzymes appeared to function suboptimally in vivo due to enzyme loading with calcium, which gives poor xylose conversion kinetics. The results show that better in vivo enzyme performance is poorly reflected in kinetic parameters for xylose isomerization determined in vitro with a single type of added metal.

CONCLUSION

This study shows that in vivo selection can identify xylose isomerase mutants with only minor changes in catalytic properties measured under standard conditions. Metal loading of xylose isomerase expressed in yeast is suboptimal and strongly influences kinetic properties. Metal uptake, distribution and binding to xylose isomerase are highly relevant for rapid xylose conversion and may be an important target for optimizing yeast xylose metabolism.

Rewiring carbon metabolism in yeast for high level production of aromatic chemicals

The production of bioactive plant compounds using microbial hosts is considered a safe, cost-competitive and scalable approach to their production. However, microbial production of some compounds like aromatic amino acid (AAA)-derived chemicals, remains an outstanding metabolic engineering challenge. Here we present the construction of a Saccharomyces cerevisiae platform strain able to produce high levels of p-coumaric acid, an AAA-derived precursor for many commercially valuable chemicals. This is achieved through engineering the AAA biosynthesis pathway, introducing a phosphoketalose-based pathway to divert glycolytic flux towards erythrose 4-phosphate formation, and optimizing carbon distribution between glycolysis and the AAA biosynthesis pathway by replacing the promoters of several important genes at key nodes between these two pathways. This results in a maximum p-coumaric acid titer of 12.5 g L⁻¹ and a maximum yield on glucose of 154.9 mg g⁻¹.

Microbial production of aromatic amino acid (AAA)-derived chemicals remains an outstanding metabolic engineering challenge. Here, the authors engineer baker’s yeast for high levels p-coumaric acid production by rewiring the central carbon metabolism and channeling more flux to the AAA biosynthetic pathway.

Metabolic fluxes-oriented control of bioreactors: a novel approach to tune micro-aeration and substrate feeding in fermentations

Background

Fine-tuning the aeration for cultivations when oxygen-limited conditions are demanded (such as the production of vaccines, isobutanol, 2–3 butanediol, acetone, and bioethanol) is still a challenge in the area of bioreactor automation and advanced control. In this work, an innovative control strategy based on metabolic fluxes was implemented and evaluated in a case study: micro-aerated ethanol fermentation.

Results

The experiments were carried out in fed-batch mode, using commercial Saccharomyces cerevisiae, defined medium, and glucose as carbon source. Simulations of a genome-scale metabolic model for Saccharomyces cerevisiae were used to identify the range of oxygen and substrate fluxes that would maximize ethanol fluxes. Oxygen supply and feed flow rate were manipulated to control oxygen and substrate fluxes, as well as the respiratory quotient (RQ). The performance of the controlled cultivation was compared to two other fermentation strategies: a conventional “Brazilian fuel-ethanol plant” fermentation and a strictly anaerobic fermentation (with ultra-pure nitrogen used as the inlet gas). The cultivation carried out under the proposed control strategy showed the best average volumetric ethanol productivity (7.0 g L⁻¹ h⁻¹), with a final ethanol concentration of 87 g L⁻¹ and yield of 0.46 g_ethanol g_substrate⁻¹. The other fermentation strategies showed lower yields (close to 0.40 g_ethanol g_substrate⁻¹) and ethanol productivity around 4.0 g L⁻¹ h⁻¹.

Conclusion

The control system based on fluxes was successfully implemented. The proposed approach could also be adapted to control several bioprocesses that require restrict aeration.

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.

Metabolic flux analysis for metabolome data validation of naturally xylose-fermenting yeasts

BACKGROUND

Efficient xylose fermentation still demands knowledge regarding xylose catabolism. In this study, metabolic flux analysis (MFA) and metabolomics were used to improve our understanding of xylose metabolism. Thus, a stoichiometric model was constructed to simulate the intracellular carbon flux and used to validate the metabolome data collected within xylose catabolic pathways of non-Saccharomyces xylose utilizing yeasts.

RESULTS

A metabolic flux model was constructed using xylose fermentation data from yeasts Scheffersomyces stipitis, Spathaspora arborariae, and Spathaspora passalidarum. In total, 39 intracellular metabolic reactions rates were utilized validating the measurements of 11 intracellular metabolites, acquired by mass spectrometry. Among them, 80% of total metabolites were confirmed with a correlation above 90% when compared to the stoichiometric model. Among the intracellular metabolites, fructose-6-phosphate, glucose-6-phosphate, ribulose-5-phosphate, and malate are validated in the three studied yeasts. However, the metabolites phosphoenolpyruvate and pyruvate could not be confirmed in any yeast. Finally, the three yeasts had the metabolic fluxes from xylose to ethanol compared. Xylose catabolism occurs at twice-higher flux rates in S. stipitis than S. passalidarum and S. arborariae. Besides, S. passalidarum present 1.5 times high flux rate in the xylose reductase reaction NADH-dependent than other two yeasts.

CONCLUSIONS

This study demonstrated a novel strategy for metabolome data validation and brought insights about naturally xylose-fermenting yeasts. S. stipitis and S. passalidarum showed respectively three and twice higher flux rates of XR with NADH cofactor, reducing the xylitol production when compared to S. arborariae. Besides then, the higher flux rates directed to pentose phosphate pathway (PPP) and glycolysis pathways resulted in better ethanol production in S. stipitis and S. passalidarum when compared to S. arborariae.

Heterologous phosphoketolase expression redirects flux towards acetate, perturbs sugar phosphate pools and increases respiratory demand in Saccharomyces cerevisiae

Introduction

Phosphoketolases (Xfpk) are a non-native group of enzymes in yeast, which can be expressed in combination with other metabolic enzymes to positively influence the yield of acetyl-CoA derived products by reducing carbon losses in the form of CO₂. In this study, a yeast strain expressing Xfpk from Bifidobacterium breve, which was previously found to have a growth defect and to increase acetate production, was characterized.

Results

Xfpk-expression was found to increase respiration and reduce biomass yield during glucose consumption in batch and chemostat cultivations. By cultivating yeast with or without Xfpk in bioreactors at different pHs, we show that certain aspects of the negative growth effects coupled with Xfpk-expression are likely to be explained by proton decoupling. At low pH, this manifests as a reduction in biomass yield and growth rate in the ethanol phase. Secondly, we show that intracellular sugar phosphate pools are significantly altered in the Xfpk-expressing strain. In particular a decrease of the substrates xylulose-5-phosphate and fructose-6-phosphate was detected (26% and 74% of control levels) together with an increase of the products glyceraldehyde-3-phosphate and erythrose-4-phosphate (208% and 542% of control levels), clearly verifying in vivo Xfpk enzymatic activity. Lastly, RNAseq analysis shows that Xfpk expression increases transcription of genes related to the glyoxylate cycle, the TCA cycle and respiration, while expression of genes related to ethanol and acetate formation is reduced. The physiological and transcriptional changes clearly demonstrate that a heterologous phosphoketolase flux in combination with endogenous hydrolysis of acetyl-phosphate to acetate increases the cellular demand for acetate assimilation and respiratory ATP-generation, leading to carbon losses.

Conclusion

Our study shows that expression of Xfpk in yeast diverts a relatively small part of its glycolytic flux towards acetate formation, which has a significant impact on intracellular sugar phosphate levels and on cell energetics. The elevated acetate flux increases the ATP-requirement for ion homeostasis and need for respiratory assimilation, which leads to an increased production of CO₂. A majority of the negative growth effects coupled to Xfpk expression could likely be counteracted by preventing acetate accumulation via direct channeling of acetyl-phosphate towards acetyl-CoA.

Electronic supplementary material

The online version of this article (10.1186/s12934-019-1072-6) contains supplementary material, which is available to authorized users.

Established and Upcoming Yeast Expression Systems

Yeast was the first microorganism used by mankind for biotransformation of feedstock that laid the foundations of industrial biotechnology. Long historical use, vast amount of data, and experience paved the way for Saccharomyces cerevisiae as a first yeast cell factory, and still it is an important expression platform as being the production host for several large volume products. Continuing special needs of each targeted product and different requirements of bioprocess operations have led to identification of different yeast expression systems. Modern bioprocess engineering and advances in omics technology, i.e., genomics, transcriptomics, proteomics, secretomics, and interactomics, allow the design of novel genetic tools with fine-tuned characteristics to be used for research and industrial applications. This chapter focuses on established and upcoming yeast expression platforms that have exceptional characteristics, such as the ability to utilize a broad range of carbon sources or remarkable resistance to various stress conditions. Besides the conventional yeast S. cerevisiae, established yeast expression systems including the methylotrophic yeasts Pichia pastoris and Hansenula polymorpha, the dimorphic yeasts Arxula adeninivorans and Yarrowia lipolytica, the lactose-utilizing yeast Kluyveromyces lactis, the fission yeast Schizosaccharomyces pombe, and upcoming yeast platforms, namely, Kluyveromyces marxianus, Candida utilis, and Zygosaccharomyces bailii, are compiled with special emphasis on their genetic toolbox for recombinant protein production.

Pentose Metabolism in Saccharomyces cerevisiae: The Need to Engineer Global Regulatory Systems

Extending the host substrate range of industrially relevant microbes, such as Saccharomyces cerevisiae, has been a highly-active area of research since the conception of metabolic engineering. Yet, rational strategies that enable non-native substrate utilization in this yeast without the need for combinatorial and/or evolutionary techniques are underdeveloped. Herein, this review focuses on pentose metabolism in S. cerevisiae as a case study to highlight the challenges in this field. In the last three decades, work has focused on expressing exogenous pentose metabolizing enzymes as well as endogenous enzymes for effective pentose assimilation, growth, and biofuel production. The engineering strategies that are employed for pentose assimilation in this yeast are reviewed, and compared with metabolism and regulation of native sugar, galactose. In the case of galactose metabolism, multiple signals regulate and aid growth in the presence of the sugar. However, for pentoses that are non-native, it is unclear if similar growth and regulatory signals are activated. Such a comparative analysis aids in identifying missing links in xylose and arabinose utilization. While research on pentose metabolism have mostly concentrated on pathway level optimization, recent transcriptomics analyses highlight the need to consider more global regulatory, structural, and signaling components.

Production of biofuels and chemicals from xylose using native and engineered yeast strains

Numerous metabolic engineering strategies have allowed yeasts to efficiently assimilate xylose, the second most abundant sugar component of lignocellulosic biomass. During the investigation of xylose utilization by yeasts, a global rewiring of metabolic networks upon xylose cultivation has been captured, as opposed to a pattern of glucose repression. A clear understanding of the xylose-induced metabolic reprogramming in yeast would shed light on the optimization of yeast-based bioprocesses to produce biofuels and chemicals using xylose. In this review, we delved into the characteristics of yeast xylose metabolism, and potential benefits of using xylose as a carbon source to produce various biochemicals with examples. Transcriptomic and metabolomic patterns of xylose-grown yeast cells were distinct from those on glucose-a conventional sugar of industrial biotechnology-and the gap might lead to opportunities to produce biochemicals efficiently. Indeed, limited glycolytic metabolic fluxes during xylose utilization could result in enhanced production of metabolites whose biosynthetic pathways compete for precursors with ethanol fermentation. Also, alleviation of glucose repression on cytosolic acetyl coenzyme A (acetyl-CoA) synthesis, and respiratory energy metabolism during xylose utilization enhanced production of acetyl-CoA derivatives. Consideration of singular properties of xylose metabolism, such as redox cofactor imbalance between xylose reductase and xylitol dehydrogenase, is necessary to maximize these positive xylose effects. This review argues the importance and benefits of xylose utilization as not only a way of expanding a substrate range, but also an effective environmental perturbation for the efficient production of advanced biofuels and chemicals in yeasts.

Concurrent isotope-assisted metabolic flux analysis and transcriptome profiling reveal responses of poplar cells to altered nitrogen and carbon supply

Reduced nitrogen is indispensable to plants. However, its limited availability in soil combined with the energetic and environmental impacts of nitrogen fertilizers motivates research into molecular mechanisms toward improving plant nitrogen use efficiency (NUE). We performed a systems-level investigation of this problem by employing multiple 'omics methodologies on cell suspensions of hybrid poplar (Populus tremula × Populus alba). Acclimation and growth of the cell suspensions in four nutrient regimes ranging from abundant to deficient supplies of carbon and nitrogen revealed that cell growth under low-nitrogen levels was associated with substantially higher NUE. To investigate the underlying metabolic and molecular mechanisms, we concurrently performed steady-state ¹³ C metabolic flux analysis with multiple isotope labels and transcriptomic profiling with cDNA microarrays. The ¹³ C flux analysis revealed that the absolute flux through the oxidative pentose phosphate pathway (oxPPP) was substantially lower (~threefold) under low-nitrogen conditions. Additionally, the flux partitioning ratio between the tricarboxylic acid cycle and anaplerotic pathways varied from 84%:16% under abundant carbon and nitrogen to 55%:45% under deficient carbon and nitrogen. Gene expression data, together with the flux results, suggested a plastidic localization of the oxPPP as well as transcriptional regulation of certain metabolic branchpoints, including those between glycolysis and the oxPPP. The transcriptome data also indicated that NUE-improving mechanisms may involve a redirection of excess carbon to aromatic metabolic pathways and extensive downregulation of potentially redundant genes (in these heterotrophic cells) that encode photosynthetic and light-harvesting proteins, suggesting the recruitment of these proteins as nitrogen sinks in nitrogen-abundant conditions.

Quantitative metabolomics of a xylose-utilizing Saccharomyces cerevisiae strain expressing the Bacteroides thetaiotaomicron xylose isomerase on glucose and xylose

The yeast Saccharomyces cerevisiae cannot utilize xylose, but the introduction of a xylose isomerase that functions well in yeast will help overcome the limitations of the fungal oxido-reductive pathway. In this study, a diploid S. cerevisiae S288c[2n YMX12] strain was constructed expressing the Bacteroides thetaiotaomicron xylA (XI) and the Scheffersomyces stipitis xyl3 (XK) and the changes in the metabolite pools monitored over time. Cultivation on xylose generally resulted in gradual changes in metabolite pool size over time, whereas more dramatic fluctuations were observed with cultivation on glucose due to the diauxic growth pattern. The low G6P and F1,6P levels observed with cultivation on xylose resulted in the incomplete activation of the Crabtree effect, whereas the high PEP levels is indicative of carbon starvation. The high UDP-D-glucose levels with cultivation on xylose indicated that the carbon was channeled toward biomass production. The adenylate and guanylate energy charges were tightly regulated by the cultures, while the catabolic and anabolic reduction charges fluctuated between metabolic states. This study helped elucidate the metabolite distribution that takes place under Crabtree-positive and Crabtree-negative conditions when cultivating S. cerevisiae on glucose and xylose, respectively.

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.

Rerouting of carbon flux in a glycogen mutant of cyanobacteria assessed via isotopically non-stationary 13 C metabolic flux analysis

Cyanobacteria, which constitute a quantitatively dominant phylum, have attracted attention in biofuel applications due to favorable physiological characteristics, high photosynthetic efficiency and amenability to genetic manipulations. However, quantitative aspects of cyanobacterial metabolism have received limited attention. In the present study, we have performed isotopically non-stationary ¹³ C metabolic flux analysis (INST-¹³ C-MFA) to analyze rerouting of carbon in a glycogen synthase deficient mutant strain (glgA-I glgA-II) of the model cyanobacterium Synechococcus sp. PCC 7002. During balanced photoautotrophic growth, 10-20% of the fixed carbon is stored in the form of glycogen via a pathway that is conserved across the cyanobacterial phylum. Our results show that deletion of glycogen synthase gene orchestrates cascading effects on carbon distribution in various parts of the metabolic network. Carbon that was originally destined to be incorporated into glycogen gets partially diverted toward alternate storage molecules such as glucosylglycerol and sucrose. The rest is partitioned within the metabolic network, primarily via glycolysis and tricarboxylic acid cycle. A lowered flux toward carbohydrate synthesis and an altered distribution at the glucose-1-phosphate node indicate flexibility in the network. Further, reversibility of glycogen biosynthesis reactions points toward the presence of futile cycles. Similar redistribution of carbon was also predicted by Flux Balance Analysis. The results are significant to metabolic engineering efforts with cyanobacteria where fixed carbon needs to be re-routed to products of interest. Biotechnol. Bioeng. 2017;114: 2298-2308. © 2017 Wiley Periodicals, Inc.

Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

The increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed "unsteady-state flux balance analysis" (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBA predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through ¹³C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.

Synergizing 13C Metabolic Flux Analysis and Metabolic Engineering for Biochemical Production

Metabolic engineering of industrial microorganisms to produce chemicals, fuels, and drugs has attracted increasing interest as it provides an environment-friendly and renewable route that does not depend on depleting petroleum sources. However, the microbial metabolism is so complex that metabolic engineering efforts often have difficulty in achieving a satisfactory yield, titer, or productivity of the target chemical. To overcome this challenge, ¹³C Metabolic Flux Analysis (¹³C-MFA) has been developed to investigate rigorously the cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, ¹³C-MFA has been widely used in academic labs and the biotechnology industry to pinpoint the key issues related to microbial-based chemical production and to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this chapter we introduce the basics of ¹³C-MFA and illustrate how ¹³C-MFA has been applied to synergize with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production.

Transcriptomes of a xylose-utilizing industrial flocculating Saccharomyces cerevisiae strain cultured in media containing different sugar sources

Lignocellulosic hydrolysates used for bioethanol production contain a mixture of sugars, with xylose being the second most abundant after glucose. Since xylose is not a natural substrate for Saccharomyces cerevisiae, recombinant S. cerevisiae strongly prefers glucose over xylose, and the fermentation rate and ethanol yield with xylose are both lower than those with glucose. To determine the molecular basis for glucose and xylose fermentation, we used microarrays to investigate the transcriptional difference of a xylose-utilizing industrial strain cultured in both single sugar media and a mixed sugar medium of glucose and xylose. The transcriptomes were nearly identical between glucose metabolizing cells in the glucose alone medium and those in the glucose fermentation phase in the mixed-sugar medium. Whereas the transcriptomes highly differed between the xylose metabolizing cells in the xylose alone medium and those in the xylose fermentation phase in the mixed sugar medium, and the differences mainly involved sulfur metabolism. When the transcriptional profiles were compared between glucose fermentation state and xylose fermentation state, we found the expression patterns of hexose transporters and glucose signaling pathway differed in response to different sugar sources, and the expression levels of the genes involved in gluconeogenesis, the glyoxylate and tricarboxylic acid cycles and respiration increased with xylose, indicating that the xylose-metabolizing cells had high requirements for maintenance energy and lacked the carbon catabolite repression capability. The effect of carbon catabolite repression by glucose lasted after glucose depletion for specific genes to different extents.

Functional expression and evaluation of heterologous phosphoketolases in Saccharomyces cerevisiae

Phosphoketolases catalyze an energy- and redox-independent cleavage of certain sugar phosphates. Hereby, the two-carbon (C2) compound acetyl-phosphate is formed, which enzymatically can be converted into acetyl-CoA—a key precursor in central carbon metabolism. Saccharomyces cerevisiae does not demonstrate efficient phosphoketolase activity naturally. In this study, we aimed to compare and identify efficient heterologous phosphoketolase enzyme candidates that in yeast have the potential to reduce carbon loss compared to the native acetyl-CoA producing pathway by redirecting carbon flux directly from C5 and C6 sugars towards C2-synthesis. Nine phosphoketolase candidates were expressed in S. cerevisiae of which seven produced significant amounts of acetyl-phosphate after provision of sugar phosphate substrates in vitro. The candidates showed differing substrate specificities, and some demonstrated activity levels significantly exceeding those of candidates previously expressed in yeast. The conducted studies also revealed that S. cerevisiae contains endogenous enzymes capable of breaking down acetyl-phosphate, likely into acetate, and that removal of the phosphatases Gpp1 and Gpp2 could largely prevent this breakdown. An evaluation of in vivo function of a subset of phosphoketolases was conducted by monitoring acetate levels during growth, confirming that candidates showing high activity in vitro indeed showed increased acetate accumulation, but expression also decreased cellular fitness. The study shows that expression of several bacterial phosphoketolase candidates in S. cerevisiae can efficiently divert intracellular carbon flux toward C2-synthesis, thus showing potential to be used in metabolic engineering strategies aimed to increase yields of acetyl-CoA derived compounds.

Recent applications of metabolomics to advance microbial biofuel production

Biofuel production from plant biomass is a promising source of renewable energy [1]. However, efficient biofuel production involves the complex task of engineering high-performance microorganisms, which requires detailed knowledge of metabolic function and regulation. This review highlights the potential of mass-spectrometry-based metabolomic analysis to guide rational engineering of biofuel-producing microbes. We discuss recent studies that apply knowledge gained from metabolomic analyses to increase the productivity of engineered pathways, characterize the metabolism of emerging biofuel producers, generate novel bioproducts, enable utilization of lignocellulosic feedstock, and improve the stress tolerance of biofuel producers.

Comprehensive analysis of glucose and xylose metabolism in Escherichia coli under aerobic and anaerobic conditions by 13C metabolic flux analysis

Glucose and xylose are the two most abundant sugars derived from the breakdown of lignocellulosic biomass. While aerobic glucose metabolism is relatively well understood in E. coli, until now there have been only a handful of studies focused on anaerobic glucose metabolism and no ¹³C-flux studies on xylose metabolism. In the absence of experimentally validated flux maps, constraint-based approaches such as MOMA and RELATCH cannot be used to guide new metabolic engineering designs. In this work, we have addressed this critical gap in current understanding by performing comprehensive characterizations of glucose and xylose metabolism under aerobic and anaerobic conditions, using recent state-of-the-art techniques in ¹³C metabolic flux analysis (¹³C-MFA). Specifically, we quantified precise metabolic fluxes for each condition by performing parallel labeling experiments and analyzing the data through integrated ¹³C-MFA using the optimal tracers [1,2-¹³C]glucose, [1,6-¹³C]glucose, [1,2-¹³C]xylose and [5-¹³C]xylose. We also quantified changes in biomass composition and confirmed turnover of macromolecules by applying [U-¹³C]glucose and [U-¹³C]xylose tracers. We demonstrated that under anaerobic growth conditions there is significant turnover of lipids and that a significant portion of CO₂ originates from biomass turnover. Using knockout strains, we also demonstrated that β-oxidation is critical for anaerobic growth on xylose. Quantitative analysis of co-factor balances (NADH/FADH₂, NADPH, and ATP) for different growth conditions provided new insights regarding the interplay of energy and redox metabolism and the impact on E. coli cell physiology.

Combined 13C-assisted metabolomics and metabolic flux analysis reveals the impacts of glutamate on the central metabolism of high β-galactosidase-producing Pichia pastoris

Background

Pichia pastoris is a popular recombinant protein expression system for its accessibility of efficient gene manipulation and high protein production. Sufficient supply of precursors, energy, and redox cofactors is crucial for high recombinant protein production. In our present work, we found that the addition of glutamate improved the recombinant β-galactosidase (β-gal) production by P. pastoris G1HL.

Methods

To elucidate the impacts of glutamate on the central metabolism in detail, a combined ¹³C-assisted metabolomics and ¹³C metabolic flux analysis was conducted based on LC–MS/MS and GC–MS data.

Results

The pool sizes of intracellular amino acids were obviously higher on glucose/glutamate (Glc/Glu). The fluxes in EMP entry reaction and in downstream TCA cycle were 50 and 67% higher on Glc/Glu than on Glc, respectively. While the fluxes in upstream TCA cycle kept almost unaltered, the fluxes in PPP oxidative branch decreased.

Conclusion

The addition of glutamate leads to a remarkable change on the central metabolism of high β-galactosidase-producing P. pastoris G1HL. To meet the increased demands of redox cofactors and energy for higher β-galactosidase production on Glc/Glu, P. pastoris G1HL redistributes the fluxes in central metabolism through the inhibitions and/or activation of the enzymes in key nodes together with the energy and redox status.

Electronic supplementary material

The online version of this article (doi:10.1186/s40643-016-0124-6) contains supplementary material, which is available to authorized users.

Metabolic profiles of planktonic and biofilm cells of Candida orthopsilosis

AIM

This study aims to understand which Candida orthopsilosis protein aids fungus adaptation upon its switching from planktonic growth to biofilm.

MATERIALS & METHODS

Ion mobility separation within mass spectrometry analysis combination were used.

RESULTS

Proteins mapped for different biosynthetic pathways showed that selective ribosome autophagy might occur in biofilms. Glucose, used as a carbon source in the glycolytic flux, changed to glycogen and trehalose.

CONCLUSION

Candida orthopsilosis expresses proteins that combine a variety of mechanisms to provide yeasts with the means to adjust the catalytic properties of enzymes. Adjustment of the enzymes helps modulate the biosynthesis/degradation rates of the available nutrients, in order to control and coordinate the metabolic pathways that enable cells to express an adequate response to nutrient availability.

Investigation of useful carbon tracers for 13C-metabolic flux analysis of Escherichia coli by considering five experimentally determined flux distributions

The ¹³C-MFA experiments require an optimal design since the precision or confidence intervals of the estimated flux levels depends on factors such as the composition of ¹³C-labeled carbon sources, as well as the metabolic flux distribution of interest. In this study, useful compositions of ¹³C-labeled glucose for ¹³C-metabolic flux analysis (¹³C-MFA) of Escherichia coli are investigated using a computer simulation of the stable isotope labeling experiment. Following the generation of artificial mass spectra datasets of amino acid fragments using five literature-reported flux distributions of E. coli, the best fitted flux distribution and the 95% confidence interval were estimated by the ¹³C-MFA procedure. A comparison of the precision scores showed that [1, 2-¹³C]glucose and a mixture of [1-¹³C] and [U-¹³C]glucose at 8:2 are one of the best carbon sources for a precise estimation of flux levels of the pentose phosphate pathway, glycolysis and the TCA cycle. Although the precision scores of the anaplerotic and glyoxylate pathway reactions were affected by both the carbon source and flux distribution, it was also shown that the mixture of non-labeled, [1-¹³C], and [U-¹³C]glucose at 4:1:5 was specifically effective for the flux estimation of the glyoxylate pathway reaction. These findings were confirmed by wet ¹³C-MFA experiments.

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Useful compositions of ¹³C-labeled glucose are investigated for ¹³C-MFA of E. coli.

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Computer simulations revealed that [1,2-¹³C] was one of the best first choices.

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Mixture of non-labeled, [1-¹³C] and [U-¹³C] at 0:8:2 was also suitable for ¹³C-MFA.

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Mixture at 4:1:5 was specifically effective for estimation of glyoxylate pathway.

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The wet ¹³C-MFA experiments of E. coli confirmed the findings.

Disruption of PHO13 improves ethanol production via the xylose isomerase pathway

Xylose is the second most abundant sugar in lignocellulosic materials and can be converted to ethanol by recombinant Saccharomyces cerevisiae yeast strains expressing heterologous genes involved in xylose assimilation pathways. Recent research demonstrated that disruption of the alkaline phosphatase gene, PHO13, enhances ethanol production from xylose by a strain expressing the xylose reductase (XR) and xylitol dehydrogenase (XDH) genes; however, the yield of ethanol is poor. In this study, PHO13 was disrupted in a recombinant strain harboring multiple copies of the xylose isomerase (XI) gene derived from Orpinomyces sp., coupled with overexpression of the endogenous xylulokinase (XK) gene and disruption of GRE3, which encodes aldose reductase. The resulting YΔGP/XK/XI strain consumed 2.08 g/L/h of xylose and produced 0.88 g/L/h of volumetric ethanol, for an 86.8 % theoretical ethanol yield, and only YΔGP/XK/XI demonstrated increase in cell concentration. Transcriptome analysis indicated that expression of genes involved in the pentose phosphate pathway (GND1, SOL3, TAL1, RKI1, and TKL1) and TCA cycle and respiratory chain (NDE1, ACO1, ACO2, SDH2, IDH1, IDH2, ATP7, ATP19, SDH4, SDH3, CMC2, and ATP15) was upregulated in the YΔGP/XK/XI strain. And the expression levels of 125 cell cycle genes were changed by deletion of PHO13.

The role of a xylose isomerase pathway in the conversion of xylose to lipid in Mucor circinelloides

The xylose isomerase (XI) pathway, which converts xylose in lignocellulosic materials into intermediate metabolites, is characterized for the first time in M. circinelloides.

13C-Metabolic Flux Analysis: An Accurate Approach to Demystify Microbial Metabolism for Biochemical Production

Metabolic engineering of various industrial microorganisms to produce chemicals, fuels, and drugs has raised interest since it is environmentally friendly, sustainable, and independent of nonrenewable resources. However, microbial metabolism is so complex that only a few metabolic engineering efforts have been able to achieve a satisfactory yield, titer or productivity of the target chemicals for industrial commercialization. In order to overcome this challenge, ¹³C Metabolic Flux Analysis (¹³C-MFA) has been continuously developed and widely applied to rigorously investigate cell metabolism and quantify the carbon flux distribution in central metabolic pathways. In the past decade, many ¹³C-MFA studies have been performed in academic labs and biotechnology industries to pinpoint key issues related to microbe-based chemical production. Insightful information about the metabolic rewiring has been provided to guide the development of the appropriate metabolic engineering strategies for improving the biochemical production. In this review, we will introduce the basics of ¹³C-MFA and illustrate how ¹³C-MFA has been applied via integration with metabolic engineering to identify and tackle the rate-limiting steps in biochemical production for various host microorganisms