Evaluation and Optimization of Metabolome Sample Preparation Methods for Saccharomyces cerevisiae

Evolution-aided improvement of the acid tolerance of Levilactobacillus brevis and its application in sourdough fermentation

Levilactobacillus brevis is crucial in food fermentation, particularly in sourdough production. However, the cultivation of L. brevis faces a challenge with accumulation of lactic acid, a major inhibitor. We aimed to increase the acid tolerance of L. brevis, an industrial strain for sourdough fermentation. We used the adaptive laboratory evolution (ALE) to obtain lactic acid tolerant strains. The evolved strain's fermentation and metabolite profiles, alongside sensory evaluation, were compared with the parental strain by using various analytical techniques. The ALE approach increased lactic acid tolerance in the evolved strain showing an increased growth rate by 1.1 and 1.9 times higher than the parental strain at pH 4.1 and 6.5, respectively. Comprehensive analyses demonstrated its potential application in sourdough fermentation, promising reduced downstream costs. The evolved strain, free from genetically modified organisms concerns, has great potential for industrial use by exhibiting enhanced growth in acidic conditions without affecting consumers' bread preferences.

A robust yeast chassis: comprehensive characterization of a fast-growing Saccharomyces cerevisiae

Robust chassis are critical to facilitate advances in synthetic biology. This study describes a comprehensive characterization of a new yeast isolate Saccharomyces cerevisiae XP that grows faster than commonly used research and industrial S. cerevisiae strains. The genomic, transcriptomic, and metabolomic analyses suggest that the fast growth rate is, in part, due to the efficient electron transport chain and key growth factor synthesis. A toolbox for genetic manipulation of the yeast was developed; we used it to construct l-lactic acid producers for high lactate production. The development of genetically malleable yeast strains that grow faster than currently used strains may significantly enhance the uses of S. cerevisiae in biotechnology.IMPORTANCEYeast is known as an outstanding starting strain for constructing microbial cell factories. However, its growth rate restricts its application. A yeast strain XP, which grows fast in high concentrations of sugar and acidic environments, is revealed to demonstrate the potential in industrial applications. A toolbox was also built for its genetic manipulation including gene insertion, deletion, and ploidy transformation. The knowledge of its metabolism, which could guide the designing of genetic experiments, was generated with multi-omics analyses. This novel strain along with its toolbox was then tested by constructing an l-lactic acid efficient producer, which is conducive to the development of degradable plastics. This study highlights the remarkable competence of nonconventional yeast for applications in biotechnology.

Biosynthesis of l-histidine from marine biomass-derived galactans in metabolically engineered Corynebacterium glutamicum

l-Histidine plays significant roles in the food and pharmaceutical industries, and its demand has been steadily increasing recently. As demand for l-histidine continues, the development of eco-friendly processes is required. To pursue this goal, D-galactose, a primary component of red algae, was employed as a carbon source for synthesizing l-histidine. To harness this marine biomass, κ-carrageenan was preferentially hydrolyzed to obtain D-galactose using κ-carrageenase (CgkA) and iduronate-2-sulfatase (IdsA3). Subsequently, l-histidine production was enhanced by modifying precursor pathways in Corynebacterium glutamicum. The resulting strain, TDPH6 exhibited a remarkable 2.15-fold increase in l-histidine production compared to TDP. Furthermore, a galactose utilization system was introduced and named TDPH6G2. During fermentation, this strain efficiently consumed 100 % of the D-galactose and synthesized 0.395 g/L of l-histidine. In conclusion, this study presents a sustainable approach to L-histidine synthesis by introducing a galactose utilization system into C. glutamicum.

Evaluation of amino acid profile by targeted metabolomics in the eukaryotic model under exposure of benzo[a]pyrene as the exclusive stressor

Amino acids (AAs) are a class of important metabolites in metabolomics methodology that investigates metabolite changes in a cell, tissue, or organism for early diagnosis of diseases. Benzo[a]pyrene (BaP) is considered a priority contaminant by different environmental control agencies because it is a proven carcinogenic compound for humans. Therefore, it is important to evaluate the BaP interference in the metabolism of amino acids. In this work, a new amino acid extraction procedure (derivatized with propyl chloroformate/propanol) using functionalized magnetic carbon nanotubes was developed and optimized. A hybrid nanotube was used followed by desorption without heating, and excellent extraction of analytes was obtained. After exposure of Saccharomyces cerevisiae, the BaP concentration of 25.0 μmol L-1 caused changes in cell viability, indicating metabolic changes. A fast and efficient GC/MS method using a Phenomenex ZB-AAA column was optimized, enabling the determination of 16 AAs in yeasts exposed or not to BaP. A comparison of AA concentrations obtained in the two experimental groups showed that glycine (Gly), serine (Ser), phenylalanine (Phe), proline (Pro), asparagine (Asn), aspartic acid (Asp), glutamic acid (Glu), tyrosine (Tyr), and leucine (Leu) statistically differentiated, after subsequent application of ANOVA with Bonferroni post-hoc test, with a confidence level of 95%. This amino acid pathway analysis confirmed previous studies that revealed the potential of these AAs as toxicity biomarker candidates.

Transcriptional and metabolomic responses of Methylococcus capsulatus Bath to nitrogen source and temperature downshift

Methanotrophs play a significant role in methane oxidation, because they are the only biological methane sink present in nature. The methane monooxygenase enzyme oxidizes methane or ammonia into methanol or hydroxylamine, respectively. While much is known about central carbon metabolism in methanotrophs, far less is known about nitrogen metabolism. In this study, we investigated how Methylococcus capsulatus Bath, a methane-oxidizing bacterium, responds to nitrogen source and temperature. Batch culture experiments were conducted using nitrate or ammonium as nitrogen sources at both 37°C and 42°C. While growth rates with nitrate and ammonium were comparable at 42°C, a significant growth advantage was observed with ammonium at 37°C. Utilization of nitrate was higher at 42°C than at 37°C, especially in the first 24 h. Use of ammonium remained constant between 42°C and 37°C; however, nitrite buildup and conversion to ammonia were found to be temperature-dependent processes. We performed RNA-seq to understand the underlying molecular mechanisms, and the results revealed complex transcriptional changes in response to varying conditions. Different gene expression patterns connected to respiration, nitrate and ammonia metabolism, methane oxidation, and amino acid biosynthesis were identified using gene ontology analysis. Notably, key pathways with variable expression profiles included oxidative phosphorylation and methane and methanol oxidation. Additionally, there were transcription levels that varied for genes related to nitrogen metabolism, particularly for ammonia oxidation, nitrate reduction, and transporters. Quantitative PCR was used to validate these transcriptional changes. Analyses of intracellular metabolites revealed changes in fatty acids, amino acids, central carbon intermediates, and nitrogen bases in response to various nitrogen sources and temperatures. Overall, our results offer improved understanding of the intricate interactions between nitrogen availability, temperature, and gene expression in M. capsulatus Bath. This study enhances our understanding of microbial adaptation strategies, offering potential applications in biotechnological and environmental contexts.

Endo metabolomic profiling of flor and wine yeasts reveals a positive correlation between intracellular metabolite load and the specific glycolytic flux during wine fermentation

This study explored the intracellular metabolic variations between 17 strains of Saccharomyces cerevisiae belonging to two different genetic populations: flor and wine yeasts, in the context of alcoholic fermentation. These two populations are closely related as they share the same ecological niche but display distinct genetic characteristics. A protocol was developed for intracellular metabolites extraction and 1H-NMR analysis. This methodology allowed us to identify and quantify 21 intracellular metabolites at two different fermentation steps: the exponential and stationary phases. This work provided evidence of significant differences in the abundance of intracellular metabolites, which are strain- and time-dependent, thus revealing complex interactions. Moreover, the differences in abundance appeared to be correlated with life-history traits such as average cell size and specific glycolytic flux, which revealed unsuspected phenotypic correlations between metabolite load and fermentation activity.

Ethanol mediates the interaction between Caenorhabditis elegans and the nematophagous fungus Purpureocillium lavendulum

Accurately recognizing pathogens by the host is vital for initiating appropriate immune response against infecting microorganisms. Caenorhabditis elegans has no known receptor to recognize pathogen-associated molecular pattern. However, recent studies showed that nematodes have a strong specificity for transcriptomes infected by different pathogens, indicating that they can identify different pathogenic microorganisms. However, the mechanism(s) for such specificity remains largely unknown. In this study, we showed that the nematophagous fungus Purpureocillium lavendulum can infect the intestinal tract of the nematode C. elegans and the infection led to the accumulation of reactive oxygen species (ROS) in the infected intestinal tract, which suppressed fungal growth. Co-transcriptional analysis revealed that fungal genes related to anaerobic respiration and ethanol production were up-regulated during infection. Meanwhile, the ethanol dehydrogenase Sodh-1 in C. elegans was also up-regulated. Together, these results suggested that the infecting fungi encounter hypoxia stress in the nematode gut and that ethanol may play a role in the host-pathogen interaction. Ethanol production in vitro during fungal cultivation in hypoxia conditions was confirmed by gas chromatography-mass spectrometry. Direct treatment of C. elegans with ethanol elevated the sodh-1 expression and ROS accumulation while repressing a series of immunity genes that were also repressed during fungal infection. Mutation of sodh-1 in C. elegans blocked ROS accumulation and increased the nematode's susceptibility to fungal infection. Our study revealed a new recognition and antifungal mechanism in C. elegans. The novel mechanism of ethanol-mediated interaction between the fungus and nematode provides new insights into fungal pathogenesis and for developing alternative biocontrol of pathogenic nematodes by nematophagous fungi. IMPORTANCE Nematodes are among the most abundant animals on our planet. Many of them are parasites in animals and plants and cause human and animal health problems as well as agricultural losses. Studying the interaction of nematodes and their microbial pathogens is of great importance for the biocontrol of animal and plant parasitic nematodes. In this study, we found that the model nematode Caenorhabditis elegans can recognize its fungal pathogen, the nematophagous fungus Purpureocillium lavendulum, through fungal-produced ethanol. Then the nematode elevated the reactive oxygen species production in the gut to inhibit fungal growth in an ethanol dehydrogenase-dependent manner. With this mechanism, novel biocontrol strategies may be developed targeting the ethanol receptor or metabolic pathway of nematodes. Meanwhile, as a volatile organic compound, ethanol should be taken seriously as a vector molecule in the microbial-host interaction in nature.

Optimized Fast Filtration-Based Sampling and Extraction Enables Precise and Absolute Quantification of the Escherichia coli Central Carbon Metabolome

Precise and accurate quantification is a prerequisite for interpretation of targeted metabolomics data, but this task is challenged by the inherent instability of the analytes. The sampling, quenching, extraction, and sample purification conditions required to recover and stabilize metabolites in representative extracts have also been proven highly dependent on species-specific properties. For Escherichia coli, unspecific leakage has been demonstrated for conventional microbial metabolomics sampling protocols. We herein present a fast filtration-based sampling protocol for this widely applied model organism, focusing on pitfalls such as inefficient filtration, selective loss of biomass, matrix contamination, and membrane permeabilization and leakage. We evaluate the effect of and need for removal of extracellular components and demonstrate how residual salts can challenge analytical accuracy of hyphenated mass spectrometric analyses, even when sophisticated correction strategies are applied. Laborious extraction procedures are bypassed by direct extraction in cold acetonitrile:water:methanol (3:5:2, v/v%), ensuring compatibility with sample concentration and thus, any downstream analysis. By applying this protocol, we achieve and demonstrate high precision and low metabolite turnover, and, followingly, minimal perturbation of the inherent metabolic state. This allows us to herein report absolute intracellular concentrations in E. coli and explore its central carbon metabolome at several commonly applied cultivation conditions.

Metabolomics and modelling approaches for systems metabolic engineering

Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.

Evaluation and optimization of analytical procedure and sample preparation for polar Streptomyces albus J1074 metabolome profiling

Metabolomics is an essential discipline in omics technology that promotes research on the biology of microbial systems. Streptomyces albus J1074 is a model organism used in fundamental research and industrial microbiology. Nevertheless, a comprehensive and standardized method for analyzing the metabolome of S. albus J1074 is yet to be developed. Thus, we comprehensively evaluated and optimized the analytical procedure and sample preparation for profiling polar metabolites using hydrophilic interaction liquid chromatography (HILIC) coupled with high-resolution mass spectrometry (HRMS). We systematically examined the HILIC columns, quenching solutions, sample-to-quenching ratios, and extraction methods. Then, the optimal protocol was used to investigate the dynamic intracellular polar metabolite profile of the engineered S. albus J1074 strains during spinosad (spinosyn A and spinosyn D) fermentation. A total of 3648 compounds were detected, and 83 metabolites were matched to the standards. The intracellular metabolomic profiles of engineered S. albus J1074 strains (ADE-AP and OE3) were detected; furthermore, their metabolomes in different stages were analyzed to reveal the reasons for their differences in their spinosad production, as well as the current metabolic limitation of heterologous spinosad production in S. albus J1074. The HILIC-HRMS method is a valuable tool for investigating polar metabolomes, and provides a reference methodology to study other Streptomyces metabolomes.

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A HILIC-HRMS method was developed for polar metabolome profiling.

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Sample preparation protocol for Streptomyces albus J1074 intracellular metabolites was studied for the first time.

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This study revealed the possible reasons for different production of spinosad of engineered S. albus J1074 strains.

In-depth investigation of the mechanisms of Echinacea purpurea polysaccharide mitigating alcoholic liver injury in mice via gut microbiota informatics and liver metabolomics

Accumulating evidence suggests that the pathogenesis of alcoholic liver disease (ALD) is strongly correlated with abnormalities of the gut-liver axis. Echinacea purpurea polysaccharide (EPP) is a homogeneous polysaccharide, which has been shown to mitigate ALD. However, the effects of EPP on gut microbiome and consequently on hepatic metabolism have yet to be explored. In this study, the microbiome and metabolomics were combined to explore the effects of EPP on gut microbiota and hepatic metabolism, and the relationship between both was further revealed by Spearman correlation analysis. Results exhibited EPP reversed alcohol-induced disturbances in gut microbiota, evidenced by increased abundance of Muribaculaceae, Lactobacillus, and Bacteroides and decreased abundance of Escherichia_Shigella and Enterococcus. Besides, EPP promoted the production of n-butyric acid, a short-chain fatty acid that maintains the integrity of the intestinal barrier. Moreover, EPP improved alterations in hepatic metabolites, and characteristic metabolites such as Berberine and Ponasterone as well as key metabolic pathways, particularly Nitrogen metabolism, were identified. Furthermore, correlation analysis suggested significant associations between gut microbes and hepatic metabolites, which in turn confirmed EPP alleviated ALD via the gut-liver axis. Therefore, these findings elucidated in-depth mechanisms of EPP against ALD and provided a new target for intervention in alcohol-related diseases.

13C-Isotope-Assisted Assessment of Metabolic Quenching During Sample Collection from Suspension Cell Cultures

Metabolomics and fluxomics are core approaches to directly profile and interrogate cellular metabolism in response to various genetic or environmental perturbations. In order to accurately measure the abundance and isotope enrichment of intracellular metabolites, cell culture samples must be rapidly harvested and cold quenched to preserve the in vivo metabolic state of the cells at the time of sample collection. When dealing with suspension cultures, this process is complicated by the need to separate the liquid culture media from cellular biomass prior to metabolite extraction. Here, we examine the efficacy of several commonly used metabolic quenching methods, using the model cyanobacterium Synechocystis sp. PCC 6803 as an example. Multiple ¹³C-labeled compounds, including ¹³C-bicarbonate, ¹³C-glucose, and ¹³C-glutamine, were used as tracers during the sample collection and the cold-quenching process to assess the extent of metabolic turnover after cells were harvested from culture flasks. We show that the combination of rapid filtration followed by 100% cold (-80 °C) methanol quenching exhibits the highest quenching efficiency, while mixing cell samples with a partially frozen 30% methanol slurry (-24 °C) followed by centrifugation is slightly less effective at quenching metabolism but enables less laborious sample processing. By contrast, rapidly mixing the cells with a saline ice slurry (∼0 °C) is less effective, as indicated by high isotope-labeling rates after sample harvest, while mixing the cells with 60% cold methanol (-65 °C) prior to centrifugation causes significant metabolite loss. This study demonstrates a rigorous, quantitative, and broadly applicable method for assessing the metabolic quenching efficacy of protocols used for sample collection in metabolomics and fluxomics studies.

Saccharomyces cerevisiae does not undergo a quorum sensing-dependent switch of budding pattern

Saccharomyces cerevisiae can alter its morphology to a filamentous form associated with unipolar budding in response to environmental stressors. Induction of filamentous growth is suggested under nitrogen deficiency in response to alcoholic signalling molecules through quorum sensing. To investigate this further, we analysed the budding pattern of S. cerevisiae cells over time under low nitrogen conditions while concurrently measuring cell density and extracellular metabolite concentration. We found that the proportion of cells displaying unipolar budding increased between local cell densities of 4.8 × 10⁶ and 5.3 × 10⁷ cells/ml. This increase in unipolar budding was not reproduced with cells growing at the critical cell density and in conditioned media. Growth under high nitrogen conditions also resulted in increased unipolar budding between local cell densities of 5.2 × 10⁶ and 8.2 × 10⁷ cells/ml, but with differences in metabolite concentration compared to low nitrogen conditions. Neither cell density, metabolite concentration, nor nitrogen deficiency were therefore sufficient to increase unipolar budding. Therefore, by using the budding pattern as an early indicator of filamentous growth, our results suggest that quorum sensing may not control the switch of budding behaviour in S. cerevisiae. Only a high concentration of the putative signalling molecule, 2-phenylethanol, resulted in an increase in unipolar budding. However, this concentration was not physiologically relevant, suggesting toxicity rather than a known quorum sensing mechanism.

Towards Unbiased Evaluation of Ionization Performance in LC-HRMS Metabolomics Method Development

As metabolomics increasingly finds its way from basic science into applied and regulatory environments, analytical demands on nontargeted mass spectrometric detection methods continue to rise. In addition to improved chemical comprehensiveness, current developments aim at enhanced robustness and repeatability to allow long-term, inter-study, and meta-analyses. Comprehensive metabolomics relies on electrospray ionization (ESI) as the most versatile ionization technique, and recent liquid chromatography-high resolution mass spectrometry (LC-HRMS) instrumentation continues to overcome technical limitations that have hindered the adoption of ESI for applications in the past. Still, developing and standardizing nontargeted ESI methods and instrumental setups remains costly in terms of time and required chemicals, as large panels of metabolite standards are needed to reflect biochemical diversity. In this paper, we investigated in how far a nontargeted pilot experiment, consisting only of a few measurements of a test sample dilution series and comprehensive statistical analysis, can replace conventional targeted evaluation procedures. To examine this potential, two instrumental ESI ion source setups were compared, reflecting a common scenario in practical method development. Two types of feature evaluations were performed, (a) summary statistics solely involving feature intensity values, and (b) analyses additionally including chemical interpretation. Results were compared in detail to a targeted evaluation of a large metabolite standard panel. We reflect on the advantages and shortcomings of both strategies in the context of current harmonization initiatives in the metabolomics field.

Bacterial Metabolomics: Sample Preparation Methods

Metabolomics is a comprehensive analysis of metabolites existing in biological systems. As one of the important "omics" tools, the approach has been widely employed in various fields in helping to better understand the complex cellular metabolic states and changes. Bacterial metabolomics has gained a significant interest as bacteria serve to provide a better subject or model at systems level. The approach in metabolomics is categorized into untargeted and targeted which serves different paradigms of interest. Nevertheless, the bottleneck in metabolomics has been the sample or metabolite preparation method. A custom-made method and design for a particular species or strain of bacteria might be necessary as most studies generally refer to other bacteria or even yeast and fungi that may lead to unreliable analysis. The paramount aspect of metabolomics design comprises sample harvesting, quenching, and metabolite extraction procedures. Depending on the type of samples and research objective, each step must be at optimal conditions which are significantly important in determining the final output. To date, there are no standardized nor single designated protocols that have been established for a specific bacteria strain for untargeted and targeted approaches. In this paper, the existing and current developments of sample preparation methods of bacterial metabolomics used in both approaches are reviewed. The review also highlights previous literature of optimized conditions used to propose the most ideal methods for metabolite preparation, particularly for bacterial cells. Advantages and limitations of methods are discussed for future improvement of bacterial metabolomics.

l-Lactic Acid Production Using Engineered Saccharomyces cerevisiae with Improved Organic Acid Tolerance

Lactic acid is mainly used to produce bio-based, bio-degradable polylactic acid. For industrial production of lactic acid, engineered Saccharomyces cerevisiae can be used. To avoid cellular toxicity caused by lactic acid accumulation, pH-neutralizing agents are used, leading to increased production costs. In this study, lactic acid-producing S. cerevisiae BK01 was developed with improved lactic acid tolerance through adaptive laboratory evolution (ALE) on 8% lactic acid. The genetic basis of BK01 could not be determined, suggesting complex mechanisms associated with lactic acid tolerance. However, BK01 had distinctive metabolomic traits clearly separated from the parental strain, and lactic acid production was improved by 17% (from 102 g/L to 119 g/L). To the best of our knowledge, this is the highest lactic acid titer produced by engineered S. cerevisiae without the use of pH neutralizers. Moreover, cellulosic lactic acid production by BK01 was demonstrated using acetate-rich buckwheat husk hydrolysates. Particularly, BK01 revealed improved tolerance against acetic acid of the hydrolysates, a major fermentation inhibitor of lignocellulosic biomass. In short, ALE with a high concentration of lactic acid improved lactic acid production as well as acetic acid tolerance of BK01, suggesting a potential for economically viable cellulosic lactic acid production.

Improved Sample Preparation for Untargeted Metabolomics Profiling of Escherichia coli

Metabolomics is a powerful tool that can systematically describe global changes in the metabolome of microbes, thus improving our understanding of the mechanisms of action of antibiotics and facilitating the development of next-generation antibacterial therapies. However, current sample preparation methods are not efficient or reliable for studying the effects of antibiotics on microbes. In the present study, we reported a novel sample preparation approach using cold methanol/ethylene glycol for quenching Escherichia coli, thus overcoming the loss of intracellular metabolites caused by cell membrane damage. After evaluating the extraction efficiency of several extraction methods, we employed the optimized workflow to profile the metabolome of E. coli exposed to cephalexin. In doing so, we proved the utility of the proposed approach and provided insights into the comprehensive metabolic alterations associated with antibiotic treatment.

IMPORTANCE The emergence and global spread of multidrug-resistant bacteria and genes are a global problem. It is critical to understand the interactions between antibiotics and bacteria and find alternative treatments for infections when we are moving closer to a postantibiotic era. It has been demonstrated that the bacterial metabolic environment plays an important role in the modulation of antibiotic susceptibility and efficacy. In the present study, we proposed a novel metabolomic approach for intracellular metabolite profiling of E. coli, which can be used to investigate the metabolite alterations of bacteria caused by antibiotic treatment. Further understanding of antibiotic-induced perturbations of bacterial metabolism would facilitate the discovery of new therapeutic targets and pathways.

Metabolic engineering of the oleaginous yeast Yarrowia lipolytica PO1f for production of erythritol from glycerol

BACKGROUND

Sugar alcohols are widely used as low-calorie sweeteners in the food and pharmaceutical industries. They can also be transformed into platform chemicals. Yarrowia lipolytica, an oleaginous yeast, is a promising host for producing many sugar alcohols. In this work, we tested whether heterologous expression of a recently identified sugar alcohol phosphatase (PYP) from Saccharomyces cerevisiae would increase sugar alcohol production in Y. lipolytica.

RESULTS

Y. lipolytica was found natively to produce erythritol, mannitol, and arabitol during growth on glucose, fructose, mannose, and glycerol. Osmotic stress is known to increase sugar alcohol production, and was found to significantly increase erythritol production during growth on glycerol. To better understand erythritol production from glycerol, since it was the most promising sugar alcohol, we measured the expression of key genes and intracellular metabolites. Osmotic stress increased the expression of several key genes in the glycerol catabolic pathway and the pentose phosphate pathway. Analysis of intracellular metabolites revealed that amino acids, sugar alcohols, and polyamines are produced at higher levels in response to osmotic stress. Heterologous overexpression of the sugar alcohol phosphatase increased erythritol production and glycerol utilization in Y. lipolytica. We further increased erythritol production by increasing the expression of native glycerol kinase (GK), and transketolase (TKL). This strain was able to produce 27.5 ± 0.7 g/L erythritol from glycerol during batch growth and 58.8 ± 1.68 g/L erythritol during fed-batch growth in shake-flasks experiments. In addition, the glycerol utilization was increased by 2.5-fold. We were also able to demonstrate that this strain efficiently produces erythritol from crude glycerol, a major byproduct of the biodiesel production.

CONCLUSIONS

We demonstrated the application of a promising enzyme for increasing erythritol production in Y. lipolytica. We were further able to boost production by combining the expression of this enzyme with other approaches known to increase erythritol production in Y. lipolytica. This suggest that this new enzyme provides an orthogonal route for boosting production and can be stacked with existing designs known to increase sugar alcohol production in yeast such as Y. lipolytica. Collectively, this work establishes a new route for increasing sugar alcohol production and further develops Y. lipolytica as a promising host for erythritol production from cheap substrates such as glycerol.

Integrating transcriptomic and metabolomic analysis of the oleaginous yeast Rhodosporidium toruloides IFO0880 during growth under different carbon sources

Rhodosporidium toruloides is an oleaginous yeast capable of producing a variety of biofuels and bioproducts from diverse carbon sources. Despite numerous studies showing its promise as a platform microorganism, little is known about its metabolism and physiology. In this work, we investigated the central carbon metabolism in R. toruloides IFO0880 using transcriptomics and metabolomics during growth on glucose, xylose, acetate, or soybean oil. These substrates were chosen because they can be derived from plants. Significant changes in gene expression and metabolite concentrations were observed during growth on these four substrates. We mapped these changes onto the governing metabolic pathways to better understand how R. toruloides reprograms its metabolism to enable growth on these substrates. One notable finding concerns xylose metabolism, where poor expression of xylulokinase induces a bypass leading to arabitol production. Collectively, these results further our understanding of central carbon metabolism in R. toruloides during growth on different substrates. They may also help guide the metabolic engineering and development of better models of metabolism for R. toruloides.Key points• Gene expression and metabolite concentrations were significantly changed.• Reduced expression of xylulokinase induces a bypass leading to arabitol production.• R. toruloides reprograms its metabolism to allow growth on different substrates.

Glycolate production by a Chlamydomonas reinhardtii mutant lacking carbon-concentrating mechanism

The green alga Chlamydomonas reinhardtii serves as a model organism for plant and photosynthesis research due to many commonalities in metabolism and to the fast growth rate of C. reinhardtii which accelerates experimental turnaround time. In addition, C. reinhardtii is a focus of research efforts in metabolic engineering and synthetic biology for the potential production of biofuels and value-added chemicals. Here, we report that the C. reinhardtii cia5 mutant, which lacks a functional carbon-concentrating mechanism (CCM), can produce substantial amounts of glycolate, a high-value cosmetic ingredient, when the mutant is cultured under ambient air conditions. In order to reveal the metabolic basis of glycolate accumulation by the cia5 mutant, we investigated the metabolomes of the cia5 mutant and a wild type strain CC-125 (WT) through the global metabolic profiling of intracellular and extracellular fractions using gas chromatography and mass spectrometry. We observed the intracellular and extracellular metabolic profiles of the WT and the cia5 mutant were similar during the mixotrophic phase at 30 h. However, when the cells entered the photoautotrophic phase (i.e., 96 h and 120 h), both the intracellular and extracellular metabolic profiles of cia5 mutant differed significantly when compared to WT. In the cia5 mutant strain, a group of photorespiration pathway intermediates including glycolate, glyoxylate, glycine, and serine accumulated to significantly higher levels compared to WT. In the photorespiration pathway, glycolate is metabolized to glyoxylate and glycine leading to NH₃ and CO₂ generation during the mitochondrial conversion of glycine to serine. This result provides further evidence that the CIA5 mutation increased the photorespiration rate. Because the cia5 mutant lacks a CCM, and C. reinhardtii might harbor an inefficient or incomplete photorespiration pathway, glycolate may accumulate when the CCM is not functional. We envision that investigating photorespiration controls in C. reinhardtii provides tools for producers to use the cia5 mutant to produce glycolate as well as platform to engineer alternative pathways for glycolate metabolism.

Capillary flow-based sample preparation system for metabolomic analysis of mammalian cells in suspension

Sample preparation methodology is critical to obtaining reliable data for studying endogenous metabolites. Dependable preparation techniques require separation of cells from culture media, quenching of enzymatic activity, and extraction of metabolites from the cells. Presented here is a simple, rapid, semi-automated metabolomic sample preparation technique for 20 μL samples of RAW 264.7 cells suspended in culture media. This method uses online filter-assisted electroporation-based cell lysis and chilled organic solvent extraction to prepare metabolomic samples from cells in suspension in 2 min. Experiments using an isotopically labeled adenosine triphosphate internal standard were carried out to ensure enzymatic quenching by monitoring the ratio of labeled adenosine diphosphate to adenosine triphosphate. Cells were metabolically labeled with ¹³C-glucose concurrent with sampling aliquots of the cell suspension over the course of 24 h. Incorporation of ¹³C into organic acid metabolites such as itaconate Cell lysates was analyzed by nano-reverse-phase liquid chromatography-mass spectrometry (nano-RP-LC-MS), showing incorporation of ¹³C into organic acid metabolites such as itaconate.

Extraction strategies for tackling complete hair metabolome using LC-HRMS-based analysis

Over recent years, metabolomics has been featured as the state-of-the-art technology that successfully opens the paths to understanding biological mechanisms and facilitating biomarker discovery. However, the inherent dynamic and sensitive nature of the metabolome have been challenging the accuracy of capturing the timepoints of interest while using biofluids such as urine and blood. Hair has thus emerged as a valuable analytical specimen for the long-term and retrospective determinations. Unfortunately, notwithstanding the apparent interest on global hair metabolomics, very few studies have engaged in the optimisation of the extraction strategy. In this study, we systemically investigated the extraction procedures for hair metabolome using a single factor experimental design. Three pH values (acidic, neutral, and basic) in aqueous solution, six extraction solvents (methanol, acetonitrile, acetone, phosphate-buffered saline, deionised water, and dichloromethane), different compositions of selected solvent mixtures and their sequential extraction, and a series of extraction times (15, 45, 60, 120, 240, and 480 min) were evaluated. The ideal condition for hair extraction is ultrasonic-assisted extraction with methanol:phosphate-buffered saline 50:50 (v/v) under +55 °C for 240 min. This strategy may secure the true composition of the metabolome, maximise the signal abundance, and guarantee a high coverage of wide-range metabolites in a straightforward approach. The optimised extraction strategy was then coupled with structure annotation tools for hair metabolome profiling. After a single RPLC-HRMS run, hair metabolite identification was achieved as the annotations of 171 probable structures and 853 tentative structures as well as the assignments of 414 unequivocal molecular formulae. In conclusion, we established an efficient extraction strategy for untargeted hair metabolomics, which the method is deliverable to any analytical laboratories and the sample can be directly profiled by means of a conventional RPLC-HRMS gradient.

GC-MS-Based Metabolomics for the Smut Fungus Ustilago maydis: A Comprehensive Method Optimization to Quantify Intracellular Metabolites

Ustilago maydis, a smut fungus, is an appealing model in fundamental research and an upcoming cell factory for industrial biotechnology. The genome of U. maydis has been sequenced and some synthesis pathways were biochemically described; however, the operation of the cellular metabolic network is not well-characterized. Thus, we conducted a comprehensive study to optimize the sample preparation procedure for metabolomics of U. maydis using GC-MS/MS. Due to the unique characteristics of U. maydis cell culture, two quenching solutions, different washing steps, eight extraction methods, and three derivatization conditions have been examined. The optimal method was then applied for stable isotope-assisted quantification of low molecular weight hydrophilic metabolites while U. maydis utilized different carbon sources including sucrose, glucose, and fructose. This study is the first report on a methodology for absolute quantification of intracellular metabolites in U. maydis central carbon metabolism such as sugars, sugar phosphates, organic acids, amino acids, and nucleotides. For biotechnological use, this method is crucial to exploit the full production potential of this fungus and can also be used to study other fungi of the family Ustilaginaceae.

Metabolic engineering considerations for the heterologous expression of xylose-catabolic pathways in Saccharomyces cerevisiae

Xylose, the second most abundant sugar in lignocellulosic biomass hydrolysates, can be fermented by Saccharomyces cerevisiae expressing one of two heterologous xylose pathways: a xylose oxidoreductase pathway and a xylose isomerase pathway. Depending on the type of the pathway, its optimization strategies and the fermentation efficiencies vary significantly. In the present study, we constructed two isogenic strains expressing either the oxidoreductase pathway (XYL123) or the isomerase pathway (XI-XYL3), and delved into simple and reproducible ways to improve the resulting strains. First, the strains were subjected to the deletion of PHO13, overexpression of TAL1, and adaptive evolution, but those individual approaches were only effective in the XYL123 strain but not in the XI-XYL3 strain. Among other optimization strategies of the XI-XYL3 strain, we found that increasing the copy number of the xylose isomerase gene (xylA) is the most promising but yet preliminary strategy for the improvement. These results suggest that the oxidoreductase pathway might provide a simpler metabolic engineering strategy than the isomerase pathway for the development of efficient xylose-fermenting strains under the conditions tested in the present study.

Comprehensive Vitamer Profiling of Folate Mono- and Polyglutamates in Baker's Yeast (Saccharomyces cerevisiae) as a Function of Different Sample Preparation Procedures

Folates are a group of B9 vitamins playing an important role in many metabolic processes such as methylation reactions, nucleotide synthesis or oxidation and reduction processes. However, humans are not able to synthesize folates de novo and thus rely on external sources thereof. Baker's yeast (Saccharomyces cerevisiae) has been shown to produce high amounts of this vitamin but extensive identification of its folate metabolism is still lacking. Therefore, we optimized and compared different sample preparation and purification procedures applying solid phase extraction (SPE). Strong anion exchange (SAX), C18 and hydrophilic-lipophilic-balanced (HLB) materials were tested for their applicability in future metabolomics studies. SAX turned out to be the preferred material for the quantitative purification of folates. Qualification of several folate vitamers was achieved by ultra-high pressure liquid chromatography quadrupole time of flight mass spectrometry (UHPLC-Q-ToF-MS) measurements and quantification was performed by liquid chromatography tandem mass spectrometry (LC-MS/MS) applying stable isotope dilution assays (SIDAs). The oxidation product s-pyrazino-triazine (MeFox) was included into the SIDA method for total folate determination and validation. Applying the best protocol (SAX) in regard to folate recovery, we analyzed 32 different vitamers in different polyglutamate states up to nonaglutamates, of which we could further identify 26 vitamers based on tandem-MS (MS2) spectra. Total folate quantification revealed differences in formyl folate contents depending on the cartridge chemistry used for purification. These are supposedly a result of interconversion reactions occurring during sample preparation due to variation in pH adjustments for the different purification protocols. The occurrence of interconversion and oxidation reactions should be taken into consideration in sample preparation procedures for metabolomics analyses with a focus on folates.

Harmonization of quality metrics and power calculation in multi-omic studies

Multi-omic studies combine measurements at different molecular levels to build comprehensive models of cellular systems. The success of a multi-omic data analysis strategy depends largely on the adoption of adequate experimental designs, and on the quality of the measurements provided by the different omic platforms. However, the field lacks a comparative description of performance parameters across omic technologies and a formulation for experimental design in multi-omic data scenarios. Here, we propose a set of harmonized Figures of Merit (FoM) as quality descriptors applicable to different omic data types. Employing this information, we formulate the MultiPower method to estimate and assess the optimal sample size in a multi-omics experiment. MultiPower supports different experimental settings, data types and sample sizes, and includes graphical for experimental design decision-making. MultiPower is complemented with MultiML, an algorithm to estimate sample size for machine learning classification problems based on multi-omic data.

Metabolomic studies of amino acid analysis in Saccharomyces cells exposed to selenium and gamma irradiation

Metabolomic studies are essential to identify and quantify key metabolites in biological systems. Analysis of amino acids (AA) is very important in target metabolomics studies. Chromatographic methods are used to support metabolite determinations. Therefore, this work presents analysis of 17 AA in Saccharomyces cerevisiae cells (a useful model in the study of cancer metabolism) exposed to sodium selenite and gamma radiation. An improved GC/MS method using propyl chloroformate/propanol as derivatizing reagent was applied to AA determinations. The method exhibited good linearity in the range of 0.08-600.00 mg L^-1; limits of determination from 0.04 to 1.60 mg L^-1; limits of quantification from 0.08 to 2.76 mg L^-1; repeatability ranging from 1.9 to 11.4 %; and precision ranging from 2.8 to 13.8 %. The correlations between selenite/gamma radiation with AA profile was investigated to establish candidates for cancer biomarkers. The analyses of yeast cultures found high concentrations of amino acids, such as Alanine, Serine, Glutamate, and Lysine, which might be associated with the development of metabolic adaptations of cancer based on its high demand for biomass and energy, found both in this model and neoplastic cells.

Systematic re-evaluation of the long-used standard protocol of urease-dependent metabolome sample preparation

In the urinary metabolomics for finding biomarkers in urine, owing to high concentrations of urea, for chromatography-based metabolomic analysis, urea needed to be degraded by urease. This urease pretreatment has been the key step of sample preparation for standard urinary metabolomics until today even for mass spectrometry-based analysis. The urease pretreatment involving incubation of urine with urease contradicts the concept of metabolome sampling, which should immediately arrest metabolic reactions to prevent alterations of a metabolite profile. Nonetheless, the impact of urease pretreatment has not been clearly elucidated yet. We found that activities of urease and endogenous urinary enzymes and metabolite contaminants from the urease preparations introduce artefacts into metabolite profiles, thus leading to misinterpretation.

Metabolomics analysis of Actinosynnema pretiosum with improved AP-3 production by enhancing UDP-glucose biosynthesis

Ansamitocin P-3 (AP-3) shows strong anticancer effects and has used as a payload for antibody-drug conjugates. Our previous study have shown that although genetically engineered Actinosynnema pretiosum strains with enhanced UDP-glucose (UDPG) biosynthesis displayed improved AP-3 production compared to the wild-type strain, the increase in yield was far from meeting the industrial demand. In this study, comparative metabolomics analysis complemented with quantitative real-time PCR analysis was performed for the wild-type strain and two mutants (OpgmOugp, ΔzwfΔgnd) to identify possible metabolic bottlenecks and non-intuitive targets for further enhancement of AP-3 production. We observed that enhancing intracellular UDPG availability facilitated the accumulation of intracellular N-demethyl-AP-3 and AP-3, where the transporting of them outside the cell still needs to be developed. We also found that the UDPG biosynthesis was closely associated with the availability of fructose in the medium and a suitable fructose feeding strategy could promote the further improvement of AP-3 titer. In addition, pathway abundance analysis revealed that undesired fatty acid accumulation and down-regulation of amino acid metabolism may be unfavorable for ansamitocin biosynthesis in later stage of production. These results indicate that genetic modification of the UDPG biosynthetic pathways may have pleiotropic effects on AP-3 production. Efforts must be made to eliminate these newly identified metabolic bottlenecks to boost AP-3 production in A. pretiosum.

Metabolomic change and pathway profiling reveal enhanced ansamitocin P-3 production in Actinosynnema pretiosum with low organic nitrogen availability in culture medium

Ansamitocin P-3 (AP-3), a 19-membered polyketide macrocyclic lactam, has potent antitumor activity. Our previous study showed that a relatively low organic nitrogen concentration in culture medium could significantly improve AP-3 production of Actinosynnema pretiosum. In the present study, we aimed to reveal the possible reasons for this improvement through metabolomic and gene transcriptional analytical methods. At the same time, a metabolic pathway profile based on metabolome data and pathway correlation information was performed to obtain a systematic view of the metabolic network modulations of A. pretiosum. Orthogonal partial least squares discriminant analysis showed that nine and eleven key metabolites directly associated with AP-3 production at growth phase and ansamitocin production phase, respectively. In-depth pathway analysis results highlighted that low organic nitrogen availability had significant impacts on central carbon metabolism and amino acid metabolic pathways of A. pretiosum and these metabolic responses were found to be beneficial to precursor supply and ansamitocin biosynthesis. Furthermore, real-time PCR results showed that the transcription of genes involved in precursor and ansamitocin biosynthetic pathways were remarkably upregulated under low organic nitrogen condition thus directing increased carbon flux toward ansamitocin biosynthesis. More importantly, the metabolic pathway analysis demonstrated a competitive relationship between fatty acid and AP-3 biosynthesis could significantly affect the accumulation of AP-3. Our findings provided new knowledge on the organic nitrogen metabolism and ansamitocin biosynthetic precursor in A. pretiosum and identified several important rate-limiting steps involved in ansamitocin biosynthesis thus providing a theoretical basis of further improvement in AP-3 production.

Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses

Metabolomics aims to address what and how regulatory mechanisms are coordinated to achieve flux optimality, different metabolic objectives as well as appropriate adaptations to dynamic nutrient availability. Recent decades have witnessed that the integration of metabolomics and fluxomics within the goal of synthetic biology has arrived at generating the desired bioproducts with improved bioconversion efficiency. Absolute metabolite quantification by isotope dilution mass spectrometry represents a functional readout of cellular biochemistry and contributes to the establishment of metabolic (structured) models required in systems metabolic engineering. In industrial practices, population heterogeneity arising from fluctuating nutrient availability frequently leads to performance losses, that is reduced commercial metrics (titer, rate, and yield). Hence, the development of more stable producers and more predictable bioprocesses can benefit from a quantitative understanding of spatial and temporal cell-to-cell heterogeneity within industrial bioprocesses. Quantitative metabolomics analysis and metabolic modeling applied in computational fluid dynamics (CFD)-assisted scale-down simulators that mimic industrial heterogeneity such as fluctuations in nutrients, dissolved gases, and other stresses can procure informative clues for coping with issues during bioprocessing scale-up. In previous studies, only limited insights into the hydrodynamic conditions inside the industrial-scale bioreactor have been obtained, which makes case-by-case scale-up far from straightforward. Tracking the flow paths of cells circulating in large-scale bioreactors is a highly valuable tool for evaluating cellular performance in production tanks. The "lifelines" or "trajectories" of cells in industrial-scale bioreactors can be captured using Euler-Lagrange CFD simulation. This novel methodology can be further coupled with metabolic (structured) models to provide not only a statistical analysis of cell lifelines triggered by the environmental fluctuations but also a global assessment of the metabolic response to heterogeneity inside an industrial bioreactor. For the future, the industrial design should be dependent on the computational framework, and this integration work will allow bioprocess scale-up to the industrial scale with an end in mind.

Xylose assimilation enhances the production of isobutanol in engineered Saccharomyces cerevisiae

Bioconversion of xylose-the second most abundant sugar in nature-into high-value fuels and chemicals by engineered Saccharomyces cerevisiae has been a long-term goal of the metabolic engineering community. Although most efforts have heavily focused on the production of ethanol by engineered S. cerevisiae, yields and productivities of ethanol produced from xylose have remained inferior as compared with ethanol produced from glucose. However, this entrenched focus on ethanol has concealed the fact that many aspects of xylose metabolism favor the production of nonethanol products. Through reduced overall metabolic flux, a more respiratory nature of consumption, and evading glucose signaling pathways, the bioconversion of xylose can be more amenable to redirecting flux away from ethanol towards the desired target product. In this report, we show that coupling xylose consumption via the oxidoreductive pathway with a mitochondrially-targeted isobutanol biosynthesis pathway leads to enhanced product yields and titers as compared to cultures utilizing glucose or galactose as a carbon source. Through the optimization of culture conditions, we achieve 2.6 g/L of isobutanol in the fed-batch flask and bioreactor fermentations. These results suggest that there may be synergistic benefits of coupling xylose assimilation with the production of nonethanol value-added products.

Redirection of the Glycolytic Flux Enhances Isoprenoid Production in Saccharomyces cerevisiae

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

Enhanced production of 3-hydroxypropionic acid from glucose and xylose by alleviation of metabolic congestion due to glycerol flux in engineered Escherichia coli

Among platform chemicals obtained from renewable biomass, 3-hydroxypropionic acid (3-HP) has attracted considerable attention. A GC/TOF-MS study revealed that the intracellular metabolites of the TCA cycle and fatty acid synthesis increased in JHS01302, a galP-overexpressing strain of Escherichia coli, during glucose and xylose co-fermentation. Decreased intracellular glycerol levels and increased intracellular biosynthesis of 3-HP were also detected in the strain. Based on these results, the yeast GPD1 gene was replaced with the endogenous gpsA gene to modulate the rate of glycerol metabolism. In flask cultures, JHS01304 containing the gpsA gene displayed 43% lower glycerol accumulation and 52% higher 3-HP production than the control. JHS01304 produced 37.6 g/L 3-HP with a productivity rate of 0.63 g/L/h and yield of 0.17 g/g in the fed-batch fermentation. The metabolome analysis provided valuable information for alleviating the metabolic burden of glycerol flux to improve the production of 3-HP during glucose and xylose co-fermentation.

Multiple-Omics Techniques Reveal the Role of Glycerophospholipid Metabolic Pathway in the Response of Saccharomyces cerevisiae Against Hypoxic Stress

Although the biological processes of organism under hypoxic stress had been elucidated, the whole physiological changes of Saccharomyces cerevisiae are still unclear. In this work, we investigated the changes of biological process of S. cerevisiae under hypoxia by the methods of transcriptomics, proteomics, metabolomics, and bioinformatics. The results showed that the expression of a total of 1017 mRNA in transcriptome, 213 proteins in proteome, and 51 metabolites in metabolome had been significantly changed between the hypoxia and normoxia conditions. Moreover, based on the integration of system-omics data, we found that the carbohydrate, amino acids, fatty acid biosynthesis, lipid metabolic pathway, and oxidative phosphorylation were significantly changed in hypoxic stress. Among these pathways, the glycerophospholipid metabolic pathway was remarkably up-regulated from the mRNA, protein, and metabolites levels under hypoxic stress, and the expression of relevant mRNA was also confirmed by the qPCR. The metabolites of glycerophospholipid pathway such as phosphatidylcholine, phosphatidylethanolamine, phosphoinositide, and phosphatidic acids probably maintained the stability of cell membranes against hypoxic stress to relieve the cell injury, and kept S. cerevisiae survive with energy production. These findings in the hypoxic omics and integrated networks provide very useful information for further exploring the molecular mechanism of hypoxic stress.

Extraction of Extracellular Matrix in Static and Dynamic Candida Biofilms Using Cation Exchange Resin and Untargeted Analysis of Matrix Metabolites by Ultra-High-Performance Liquid Chromatography-Tandem Quadrupole Time-of-Flight Mass Spectrometry (UPLC-Q-TOF-MS)

Fungal infections caused by Candida albicans poses a great threat to human health. The ability of biofilm formation is believed to be associated with resistance-related Candida infections. Currently, knowledge on extracellular matrix (EM) of C. albicans biofilm is limited. In this study, we introduced ion exchange resin, i.e., cation exchange resin (CER) and anion exchange resin (AER), in EM extraction of C. albicans biofilm as well as several non-albicans Candida (NAC) biofilms under static and dynamic states in combination with vortexing and ultrasonication (VU). The metabolites extracted from the dynamic C. albicans biofilm matrix using the CER-VU and VU were identified with ultra-high-performance liquid chromatography-tandem quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) via untargeted filtration. Compared with other physical and chemical extraction methods, CER-VU was demonstrated to be an ideal approach with high-yield acquisitions of EM constituents including proteins, triglycerides and carbohydrates and low-level damages on fungal cell viability and integrity. The untargeted MS analysis further showed the high efficacy of CER-VU, as a large quantity of metabolites (217 versus 198) was matched comprising a great number of lipids, carbohydrates, amino acids, nucleic acids and their derivatives together with a high involvement of signaling pathways compared with the VU alone. However, combining the results from both the CER-VU and VU methods could generate more metabolites. In summary, the EM analysis of the dynamic C. albicans biofilm expands our understanding upon a comprehensive depiction of matrix components and provides another effective approach for EM extraction.

Metabolomic and Transcriptomic Analyses of Escherichia coli for Efficient Fermentation of L-Fucose

L-Fucose, one of the major monomeric sugars in brown algae, possesses high potential for use in the large-scale production of bio-based products. Although fucose catabolic pathways have been enzymatically evaluated, the effects of fucose as a carbon source on intracellular metabolism in industrial microorganisms such as Escherichia coli are still not identified. To elucidate the effects of fucose on cellular metabolism and to find clues for efficient conversion of fucose into bio-based products, comparative metabolomic and transcriptomic analyses were performed on E. coli on L-fucose and on D-glucose as a control. When fucose was the carbon source for E. coli, integration of the two omics analyses revealed that excess gluconeogenesis and quorum sensing led to severe depletion of ATP, resulting in accumulation and export of fucose extracellularly. Therefore, metabolic engineering and optimization are needed for E. coil to more efficiently ferment fucose. This is the first multi-omics study investigating the effects of fucose on cellular metabolism in E. coli. These omics data and their biological interpretation could be used to assist metabolic engineering of E. coli producing bio-based products using fucose-containing brown macroalgae.

Production of galactitol from galactose by the oleaginous yeast Rhodosporidium toruloides IFO0880

BACKGROUND

Sugar alcohols are commonly used as low-calorie sweeteners and can serve as potential building blocks for bio-based chemicals. Previous work has shown that the oleaginous yeast Rhodosporidium toruloides IFO0880 can natively produce arabitol from xylose at relatively high titers, suggesting that it may be a useful host for sugar alcohol production. In this work, we explored whether R. toruloides can produce additional sugar alcohols.

RESULTS

Rhodosporidium toruloides is able to produce galactitol from galactose. During growth in nitrogen-rich medium, R. toruloides produced 3.2 ± 0.6 g/L, and 8.4 ± 0.8 g/L galactitol from 20 to 40 g/L galactose, respectively. In addition, R. toruloides was able to produce galactitol from galactose at reduced titers during growth in nitrogen-poor medium, which also induces lipid production. These results suggest that R. toruloides can potentially be used for the co-production of lipids and galactitol from galactose. We further characterized the mechanism for galactitol production, including identifying and biochemically characterizing the critical aldose reductase. Intracellular metabolite analysis was also performed to further understand galactose metabolism.

CONCLUSIONS

Rhodosporidium toruloides has traditionally been used for the production of lipids and lipid-based chemicals. Our work demonstrates that R. toruloides can also produce galactitol, which can be used to produce polymers with applications in medicine and as a precursor for anti-cancer drugs. Collectively, our results further establish that R. toruloides can produce multiple value-added chemicals from a wide range of sugars.

Influence of Metabolite Extraction Methods on 1H-NMR-Based Metabolomic Profiling of Enteropathogenic Yersinia

Metabolite extraction is one of the critical steps in microbial metabolome analysis. It affects both the observed metabolite content and biological interpretation of the data. Several methods exist for metabolite extraction of microbes, but the literature is not consistent regarding the sample model, adequacy, and performance of each method. In this study, an optimal extraction protocol for Yersinia intracellular metabolites was investigated. The effect of five extraction protocols consisting of different extraction solvent systems (60% methanol, 100% methanol, acetonitrile/methanol/water (2:2:1), chloroform/methanol/water (2:1:1), and 60% ethanol) on Yersinia metabolic profiles were compared. The number of detected peaks, sample-to-sample variation, and metabolite yield were used as criteria. Extracted metabolites were analyzed by ¹H-NMR and principal component analysis (PCA), as well as partial least squares discriminant analysis (PLS-DA) multivariate statistics. The extraction protocol using 100% methanol as the extraction solvent provided the highest number of detected peaks for both Yersinia species analyzed, yielding more spectral information. Together with the reproducibility and spectrum quality, 100% methanol extraction was suitable for intracellular metabolite extraction from both species. However, depending on the metabolites of interest, other solvents might be more suitable for future studies, as distinct profiles were observed amongst the extraction methods.

Combined transcriptomics-metabolomics profiling of the heat shock response in the hyperthermophilic archaeon Pyrococcus furiosus

Pyrococcus furiosus is a remarkable archaeon able to grow at temperatures around 100 °C. To gain insight into how this model hyperthermophile copes with heat stress, we compared transcriptomic and metabolomic data of cells subjected to a temperature shift from 90 °C to 97 °C. In this study, we used RNA-sequencing to characterize the global variation in gene expression levels, while nuclear magnetic resonance (NMR) and targeted ion exchange liquid chromatography-mass spectrometry (LC-MS) were used to determine changes in metabolite levels. Of the 552 differentially expressed genes in response to heat shock conditions, 257 were upregulated and 295 were downregulated. In particular, there was a significant downregulation of genes for synthesis and transport of amino acids. At the metabolite level, 37 compounds were quantified. The level of di-myo-inositol phosphate, a canonical heat stress solute among marine hyperthermophiles, increased considerably (5.4-fold) at elevated temperature. Also, the levels of mannosylglycerate, UDP-N-acetylglucosamine (UDPGlcNac) and UDP-N-acetylgalactosamine were enhanced. The increase in the pool of UDPGlcNac was concurrent with an increase in the transcript levels of the respective biosynthetic genes. This work provides the first metabolomic analysis of the heat shock response of a hyperthermophile.

Quenching for Microalgal Metabolomics: A Case Study on the Unicellular Eukaryotic Green Alga Chlamydomonas reinhardtii

Capturing a valid snapshot of the metabolome requires rapid quenching of enzyme activities. This is a crucial step in order to halt the constant flux of metabolism and high turnover rate of metabolites. Quenching with cold aqueous methanol is treated as a gold standard so far, however, reliability of metabolomics data obtained is in question due to potential problems connected to leakage of intracellular metabolites. Therefore, we investigated the influence of various parameters such as quenching solvents, methanol concentration, inclusion of buffer additives, quenching time and solvent to sample ratio on intracellular metabolite leakage from Chlamydomonas reinhardtii. We measured the recovery of twelve metabolite classes using gas chromatography mass spectrometry (GC-MS) in all possible fractions and established mass balance to trace the fate of metabolites during quenching treatments. Our data demonstrate significant loss of intracellular metabolites with the use of the conventional 60% methanol, and that an increase in methanol concentration or quenching time also resulted in higher leakage. Inclusion of various buffer additives showed 70 mM HEPES (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid) to be suitable. In summary, we recommend quenching with 60% aqueous methanol supplemented with 70 mM HEPES (−40 °C) at 1:1 sample to quenching solvent ratio, as it resulted in higher recoveries for intracellular metabolites with subsequent reduction in the metabolite leakage for all metabolite classes.

Bioformation of Volatile and Nonvolatile Metabolites by Saccharomycopsis fibuligera KJJ81 Cultivated under Different Conditions-Carbon Sources and Cultivation Times

Saccharomycopsis fibuligera KJJ81 isolated from nuruk is an amylolytic yeast that is widely used as a microbial starter in various fermented foods. Volatile and nonvolatile metabolites of S. fibuligera KJJ81 were investigated according to different carbon sources and cultivation times using a nontargeted metabolomic approach. Partial-least-squares discriminant analysis was applied to determine the major metabolites, which were found to be closely related to the clustering and discrimination of S. fibuligera KJJ81 samples. Some volatile metabolites derived from phenylalanine, such as 2-phenylethanol, 2-phenylethyl acetate, and ethyl phenylacetate, were predominantly found in cultivation medium containing glucose (YPD medium). In addition, the level of 2-phenylethanol increased continuously with the cultivation time. In terms of nonvolatile metabolites, carbohydrates (mannose, arabitol, and mannitol), fatty acids (palmitic acid and stearic acid), organic acids (oxalic acid and succinic acid), and amino acids (isoleucine, serine, alanine, glutamic acid, glycine, proline, phenylalanine, and threonine) were the main contributors to S. fibuligera KJJ81 samples cultivated in YPD medium according to cultivation time. These results show that the formation of volatile and nonvolatile metabolites of S. fibuligera KJJ81 can be significantly affected by both the carbon sources and the cultivation time.

Balancing metabolome coverage and reproducibility for untargeted NMR-based metabolic profiling in tissue samples through mixture design methods

Untargeted metabolomics attempts to acquire a comprehensive and reproducible set of small-molecule metabolites in biological systems. However, metabolite extraction method significantly affects the quality of metabolomics data. In the present study, we calculated the number of peaks (NP) and coefficient of variation (CV) to reflect metabolome coverage and reproducibility in untargeted NMR-based metabolic profiling of tissue samples in rats under different methanol/chloroform/water (MCW) extraction conditions. Different MCW extractions expectedly generated diverse characteristics of metabolome. Moreover, the classic MCW method revealed tissue-specific differences in the NP and CV values. To obtain high-quality metabolomics data, therefore, we used mixture design methods to optimize the MCW extraction strategy by maximizing the NP value and minimizing the CV value in each tissue sample. Results show that the optimal formulations of MCW extraction were 2:2:8 (ml/mg tissue) for brain sample, 2:4:6 (ml/mg tissue) for heart sample, 1.3:2:8.7 (ml/mg tissue) for liver sample, 4:2:6 (ml/mg tissue) for kidney sample, 2:3:7 (ml/mg tissue) for muscle sample, and 2:4:6 (ml/mg tissue) for pancreas sample. Therefore, these findings demonstrate that different tissue samples need a specific optimal extraction condition for balancing metabolome coverage and reproducibility in the untargeted metabolomics study. Mixture design method is an effective tool to optimize metabolite extraction strategy for tissue samples. Graphical abstract ᅟ.