Metabolite profiling for analysis of yeast stress response during very high gravity ethanol fermentations

Quantifying microbial robustness in dynamic environments using microfluidic single-cell cultivation

BACKGROUND

Microorganisms must respond to changes in their environment. Analysing the robustness of functions (i.e. performance stability) to such dynamic perturbations is of great interest in both laboratory and industrial settings. Recently, a quantification method capable of assessing the robustness of various functions, such as specific growth rate or product yield, across different conditions, time frames, and populations has been developed for microorganisms grown in a 96-well plate. In micro-titer-plates, environmental change is slow and undefined. Dynamic microfluidic single-cell cultivation (dMSCC) enables the precise maintenance and manipulation of microenvironments, while tracking single cells over time using live-cell imaging. Here, we combined dMSCC and a robustness quantification method to a pipeline for assessing performance stability to changes occurring within seconds or minutes.

RESULTS

Saccharomyces cerevisiae CEN.PK113-7D, harbouring a biosensor for intracellular ATP levels, was exposed to glucose feast-starvation cycles, with each condition lasting from 1.5 to 48 min over a 20 h period. A semi-automated image and data analysis pipeline was developed and applied to assess the performance and robustness of various functions at population, subpopulation, and single-cell resolution. We observed a decrease in specific growth rate but an increase in intracellular ATP levels with longer oscillation intervals. Cells subjected to 48 min oscillations exhibited the highest average ATP content, but the lowest stability over time and the highest heterogeneity within the population.

CONCLUSION

The proposed pipeline enabled the investigation of function stability in dynamic environments, both over time and within populations. The strategy allows for parallelisation and automation, and is easily adaptable to new organisms, biosensors, cultivation conditions, and oscillation frequencies. Insights on the microbial response to changing environments will guide strain development and bioprocess optimisation.

Four ways of implementing robustness quantification in strain characterisation

BACKGROUND

In industrial bioprocesses, microorganisms are generally selected based on performance, whereas robustness, i.e., the ability of a system to maintain a stable performance, has been overlooked due to the challenges in its quantification and implementation into routine experimental procedures. This work presents four ways of implementing robustness quantification during strain characterisation. One Saccharomyces cerevisiae laboratory strain (CEN.PK113-7D) and two industrial strains (Ethanol Red and PE2) grown in seven different lignocellulosic hydrolysates were assessed for growth-related functions (specific growth rate, product yields, etc.) and eight intracellular parameters (using fluorescent biosensors).

RESULTS

Using flasks and high-throughput experimental setups, robustness was quantified in relation to: (i) stability of growth functions in response to the seven hydrolysates; (ii) stability of growth functions across different strains to establish the impact of perturbations on yeast metabolism; (iii) stability of intracellular parameters over time; (iv) stability of intracellular parameters within a cell population to indirectly quantify population heterogeneity. Ethanol Red was the best-performing strain under all tested conditions, achieving the highest growth function robustness. PE2 displayed the highest population heterogeneity. Moreover, the intracellular environment varied in response to non-woody or woody lignocellulosic hydrolysates, manifesting increased oxidative stress and unfolded protein response, respectively.

CONCLUSIONS

Robustness quantification is a powerful tool for strain characterisation as it offers novel information on physiological and biochemical parameters. Owing to the flexibility of the robustness quantification method, its implementation was successfully validated at single-cell as well as high-throughput levels, showcasing its versatility and potential for several applications.

Metabolomics analysis of the metabolic effects of citric acid on Issatchenkia terricola WJL-G4

In current research, yeast species Issatchenkia terricola WJL-G4 was shown to be capable of degrading citric acid, especially in the processing of fruit juice and wine. I. terricola WJL-G4 was able to use citric acid as a carbon source, but the metabolic effects of citric acid on yeast remained unclear. In this study, the metabolic effects of citric acid on I. terricola WJL-G4 were studied using liquid chromatography-mass spectrometry metabolomics technology, with glucose treatment as the control. Results showed that organic acid contents related to the extracellular tricarboxylic acid cycle (TCA) varied greatly. The metabolomics results indicated that I. terricola WJL-G4 might metabolize citric acid through the TCA pathway, and the glycolysis pathway might be inhibited; however, gluconeogenesis proceeded normally during citric acid treatment. Some fatty acids and phospholipids, along with the metabolic pathways of amino acids, vitamins, purines and nicotinamide in I. terricola WJL-G4 were also affected by the citric acid treatment. This work provided a theoretical basis for further study of the mechanism of yeast metabolism of citric acid.

Metabolomic analysis and pathway profiling of paramylon production in Euglena gracilis grown on different carbon sources

Paramylon (β-1,3-glucan) produced by Euglena gracilis displays antioxidant, antitumor, and hypolipidaemic functions. The biological properties of paramylon production by E. gracilis can be understood by elucidating the metabolic changes within the algae. In this study, the carbon sources in AF-6 medium were replaced with glucose, sodium acetate, glycerol, or ethanol, and the paramylon yield was measured. Adding 0.1260 g/L glucose to the culture medium resulted in the highest paramylon yield of 70.48 %. The changes in metabolic pathways in E. gracilis grown on glucose were assessed via non-targeted metabolomics analysis using ultra-high-performance liquid chromatography coupled to high-resolution quadrupole-Orbitrap mass spectrometry. We found that glucose, as a carbon source, regulated some differentially expressed metabolites, including l-glutamic acid, γ-aminobutyric acid (GABA), and l-aspartic acid. Pathway analysis using the Kyoto Encyclopedia of Genes and Genomes further showed that glucose regulated the carbon and nitrogen balance through the GABA shunt, which enhanced photosynthesis, regulated the flux of carbon and nitrogen into the tricarboxylic acid cycle, promoted glucose uptake, and increased the accumulation of paramylon. This study provides new insights into E. gracilis metabolism during paramylon synthesis.

Metabolome analysis of the response and tolerance mechanisms of Saccharomyces cerevisiae to formic acid stress

Various inhibitors are produced during the hydrolysis of lignocellulosic biomass that can interfere with the growth of yeast cells and the production of bioethanol. Formic acid is a common weak acid inhibitor present in lignocellulosic hydrolysate that has toxic effects on yeast cells. However, the mechanism of the response of Saccharomyces cerevisiae to formic acid is not fully understood. In this study, liquid chromatography-mass spectrometry (LC-MS) was used to investigate the effects of formic acid treatment on cell metabolites of S. cerevisiae. Treatment with different concentrations of formic acid significantly inhibited the growth of yeast cells, reduced the yield of ethanol, prolonged the cell fermentation cycle, and increased the content of malondialdehyde. Principal component analysis and orthogonal partial least squares discriminant analysis showed that 55 metabolites were significantly altered in S. cerevisiae after formic acid treatment. The metabolic relevance of these compounds in the response of S. cerevisiae to formic acid stress was investigated. Formic acid can cause oxidative stress, inhibit protein synthesis, and damage DNA in S. cerevisiae, and these are possible reasons for the inhibition of S. cerevisiae cell growth. In addition, the levels of several aromatic amino acids identified in the cells of formic acid-treated yeast were increased; the biosynthesis of nucleotides was slowed, and energy consumption was reduced. These mechanisms may help to improve the tolerance of yeast cells to formic acid. The results described herein highlight our current understanding of the molecular mechanism of the response of S. cerevisiae to formic acid. The study will provide a theoretical basis for research on the tolerance mechanisms of S. cerevisiae.

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

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

Robustness: linking strain design to viable bioprocesses

Microbial cell factories are becoming increasingly popular for the sustainable production of various chemicals. Metabolic engineering has led to the design of advanced cell factories; however, their long-term yield, titer, and productivity falter when scaled up and subjected to industrial conditions. This limitation arises from a lack of robustness - the ability to maintain a constant phenotype despite the perturbations of such processes. This review describes predictable and stochastic industrial perturbations as well as state-of-the-art technologies to counter process variability. Moreover, we distinguish robustness from tolerance and discuss the potential of single-cell studies for improving system robustness. Finally, we highlight ways of achieving consistent and comparable quantification of robustness that can guide the selection of strains for industrial bioprocesses.

Isobutanol tolerance and production of Saccharomyces cerevisiae can be improved by engineering its TATA-binding protein Spt15

Low isobutanol tolerance of Saccharomyces cerevisiae limits its application in isobutanol fermentation. Here, we used global transcription machinery engineering to screen mutants with higher isobutanol tolerance and elevated isobutanol titres. TATA-binding protein Spt15 was used as the target of global transcription machinery engineering for improvement of such complex phenotypes. A random mutagenesis library of S. cerevisiae TATA-binding protein Spt15 was constructed and subjected to screening under isobutanol stress. A mutant strain (denoted as spt15-3) with improved isobutanol tolerance was identified. There were three mutations of Spt15 in strain spt15-3, including deletion of A at position -132 nt upstream of initiation codon, insertion of G at position -65 nt upstream of initiation codon and a synonymous mutation at position 315 nt (T → C) downstream of initiation codon. We then metabolically engineered isobutanol synthesis in strains harbouring plasmids YCplac22 containing these Spt15 mutations. Delta integration was used to overexpress ILV3 gene, and 2μ plasmids carrying PGK1p-ILV2 and PGK1p-ARO10 were used to overexpress ILV2 and ARO10 genes. After 24-h micro-aerobic fermentation, Engi-3 produced 0·556 g l^-1 isobutanol, which was 404% and 25·3% greater than isobutanol produced by control Engi-1 and engineered Engi-2, respectively. After 28 h, Engi-4 produced 0·459 g l^-1 isobutanol, which was 315% and 3·2% greater than isobutanol produced Engi-1 and Engi-2, respectively. RNA-Seq-based transcriptome analysis shows that mutations of Spt15 in strain spt15-3 increased the expression of SPT15. Meanwhile, compared with strain Engi-3, the spt15-3 mutation downregulated the expression of genes involved in the TCA cycle and glyoxylic acid cycle, but increased the expression of genes related to cell stability. This work demonstrates that isobutanol tolerance and production of S. cerevisiae can be improved by engineering its TATA-binding protein Spt15. This study clarified the molecular mechanisms regulating isobutanol production and tolerance in S. cerevisiae.

Nutrient-supplemented propagation of Saccharomyces cerevisiae improves its lignocellulose fermentation ability

Propagation conditions have been shown to be of considerable importance for the fermentation ability of Saccharomyces cerevisiae. The limited tolerance of yeast to inhibitors present in lignocellulosic hydrolysates is a major challenge in second-generation bioethanol production. We have investigated the hypothesis that the addition of nutrients during propagation leads to yeast cultures with improved ability to subsequently ferment lignocellulosic materials. This hypothesis was tested with and without short-term adaptation to wheat straw or corn stover hydrolysates during propagation of the yeast. The study was performed using the industrial xylose-fermenting S. cerevisiae strain CR01. Adding a mixture of pyridoxine, thiamine, and biotin to unadapted propagation cultures improved cell growth and ethanol yields during fermentation in wheat straw hydrolysate from 0.04 g g⁻¹ to 0.19 g g⁻¹ and in corn stover hydrolysate from 0.02 g g⁻¹ to 0.08 g g⁻¹. The combination of short–term adaptation and supplementation with the vitamin mixture during propagation led to ethanol yields of 0.43 g g⁻¹ in wheat straw hydrolysate fermentation and 0.41 g g⁻¹ in corn stover hydrolysate fermentation. These ethanol yields were improved compared to ethanol yields from cultures that were solely short-term adapted (0.37 and 0.33 g g⁻¹). Supplementing the propagation medium with nutrients in combination with short-term adaptation was thus demonstrated to be a promising strategy to improve the efficiency of industrial lignocellulosic fermentation.

Compatible solutes adaptive alterations in Arthrobacter simplex during exposure to ethanol, and the effect of trehalose on the stress resistance and biotransformation performance

Ethanol-tolerant Arthrobacter simplex is desirable since ethanol facilitates hydrophobic substrates dissolution on an industrial scale. Herein, alterations in compatible solutes were investigated under ethanol stress. The results showed that the amount of trehalose and glycerol increased while that of glutamate and proline decreased. The trehalose protectant role was verified and its concentration was positively related to the degree of cell tolerance. otsA, otsB and treS, three trehalose biosynthesis genes in A. simplex, also enhanced Escherichia coli stress tolerance, but the increased tolerance was dependent on the type and level of the stress. A. simplex strains accumulating trehalose showed a higher productivity in systems containing more ethanol and substrate because of better viability. The underlying mechanisms of trehalose were involved in better cell integrity, higher membrane stability, stronger reactive oxygen species scavenging capacity and higher energy level. Therefore, trehalose was a general protectant and the upregulation of its biosynthesis by genetic modification enhanced cell stress tolerance, consequently promoted productivity.

Whole-genome sequencing of an acidophilic Rhodotorula sp. ZM1 and its phenol-degrading capability under acidic conditions

The goal of this work was to investigate the genetics of an acidophilic phenol-degrading yeast strain using whole-genome sequencing (WGS), characterize the growth of the strain and phenol degradation capability as well as degradation pathway under extremely acidic conditions. The result showed that the strain ZM1 isolated from an acid mine drainage (AMD) belongs to basidiomycetous yeast Rhodotorula sp., which possesses some unique genes compared to other four closely related Rhodotorula species. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis suggested that ZM1 possessed the degradation potentials for aromatic compounds. ZM1 was acidophilic with the optimum growth at the initial pH of 3.0. It could adjust pH to desired levels probably by acid production during the cultivation. Notably, at pH 3.0, the strain ZM1 showed a high phenol-degrading capability that almost completely degraded 1100 mg/L of phenol in 120 h with the highest degradation rate of 0.074 g/(g cell dry weight h). Under the same pH, the strain could completely degrade 500 mg/L phenol within 48 h at NaCl concentration up to 10 g/L. The identification of the gene catA by the KEGG analysis, together with the presence of metabolic intermediate of cis, cis-muconic acid detected by gas chromatography-mass spectrometry, confirmed that the strain ZM1 degraded phenol via ortho-cleavage pathway. These findings suggest that the indigenous yeasts strain ZM1 could be exploited as an important member for in-situ biodegradation of aromatic compounds in the extremely acidic environments.

Antioxidant activity changes of exopolysaccharides with different carbon sources from Lactobacillus plantarum LPC-1 and its metabolomic analysis

The effects of different carbon sources on the antioxidant activity changes of exopolysaccharides (EPSs) were determined for the strains Lactobacillus plantarum LPC-1 with glucose, sucrose and its mixture as carbon sources, respectively. Meanwhile, GC-MS datasets coupled with multivariate statistical methods were used to investigate metabolic changes of EPSs-producing L. plantarum cultured with different carbon source. Among carbon sources examined, both of glucose and sucrose were favorable for the cell growth, while the maximum EPSs yield was achieved when sucrose was employed. EPSs cultured with different carbon sources showed remarkable different antioxidant activities, and EPSs with sucrose or mixed sugar as carbon source exhibited a promising antioxidant activity, such as hydroxyl scavenging activity and DPPH radical scavenging activity. Results from rice cultivation showed a similar conclusion that there were also significant differences in the antioxidant activities of EPSs obtained from different carbon sources in inducing rice resistance to chromium stress, but addition of EPSs had no significant impact on the uptake of Cr metals. Principal component analysis showed clear differences in metabolites among different treatment, and the glycolysis and tricarboxylic acid cycle were decreased when sucrose or mixed sugar was used as carbon source, and the production of lactic acid was also reduced, which might be the main reasons for the overproduction of EPSs. Our results indicated that Lactobacillus strain, depending on the carbon source in the medium, could produce EPSs of different biological properties, and the metabolomic analysis findings provided the first omics view of cell growth and EPSs synthesis in L. plantarum, which would be a theoretical basis for further improving the production of EPSs.

Metabolomic analysis of significant changes in Lactobacillus casei Zhang during culturing to generation 4,000 under conditions of glucose restriction

Lactic acid bacteria are being consumed more frequently as awareness of their health benefits has increased. The industrial production of lactic acid bacteria requires a comprehensive understanding of their survival stress, especially regarding changes in metabolic substances in a glucose-limited environment. In the present study, a metabolomic approach was applied to investigate Lactobacillus casei Zhang using cultures from a common ancestor that were permitted to evolve under conditions with normal or glucose-restricted media for up to 4,000 generations. Metabolomic analyses of intracellular and extracellular differential metabolites under De Man, Rogosa and Sharpe broth (2% vol/vol glucose; Oxoid Ltd., Basingstoke, UK) and glucose-restricted (0.02% vol/vol glucose in De Man, Rogosa and Sharpe broth) conditions were performed at generations 0, 2,000, and 4,000 and revealed 23 different metabolites. Myristic acid, ergothioneine, Lys-Thr, and palmitamide contents exhibited significant reductions between 0 and 4,000 generations, whereas nicotinate, histidine, palmitic acid, l-lysine, urocanate, thymine, and other substances increased. The dynamics of the pathways involved in AA metabolism, including glycine, serine, and threonine metabolism, histidine metabolism, lysine degradation, and arginine and proline metabolism, were also a focus of the present study. There were also changes in several other metabolic pathways, including vitamin B₆, thiamine, nicotinate, and nicotinamide, according to generation time. Additionally, in the present study we screened for key metabolites involved in the glucose-restricted response and provided a theoretical basis for comprehensively revealing the regulatory mechanisms associated with L. casei Zhang glucose restriction at the metabolic level. These findings also provide novel ideas and methods for analyzing the glucose-restricted stress response at the metabolic level.

The combination of NAD+-dependent deacetylase gene deletion and the interruption of gluconeogenesis causes increased glucose metabolism in budding yeast

Metabolic engineering focuses on rewriting the metabolism of cells to enhance native products or endow cells with the ability to produce new products. This engineering has the potential for wide-range application, including the production of fuels, chemicals, foods and pharmaceuticals. Glycolysis manages the levels of various secondary metabolites by controlling the supply of glycolytic metabolites. Metabolic reprogramming of glycolysis is expected to cause an increase in the secondary metabolites of interest. In this study, we constructed a budding yeast strain harboring the combination of triple sirtuin gene deletion (hst3∆ hst4∆ sir2∆) and interruption of gluconeogenesis by the deletion of the FBP1 gene encoding fructose-1,6-bisphosphatase (fbp1∆). hst3∆ hst4∆ sir2∆ fbp1∆ cells harbored active glycolysis with high glucose consumption and active ethanol productivity. Using capillary electrophoresis–time-of-flight mass spectrometry (CE–TOF/MS) analysis, hst3∆ hst4∆ sir2∆ fbp1∆ cells accumulated not only glycolytic metabolites but also secondary metabolites, including nucleotides that were synthesized throughout the pentose phosphate (PP) pathway, although various amino acids remained at low levels. Using the stable isotope labeling assay for metabolites, we confirmed that hst3∆ hst4∆ sir2∆ fbp1∆ cells directed the metabolic fluxes of glycolytic metabolites into the PP pathway. Thus, the deletion of three sirtuin genes (HST3, HST4 and SIR2) and the FBP1 gene can allow metabolic reprogramming to increase glycolytic metabolites and several secondary metabolites except for several amino acids.

Indentation with atomic force microscope, Saccharomyces cerevisiae cell gains elasticity under ethanol stress

During bioethanol fermentation process, Saccharomyces cerevisiae cell membrane is the first target to be attacked by the accumulated ethanol. In such a prominent position, S. cerevisiae cell membrane could reversely provide protection through changing fluidity or elasticity secondary to remodeled membrane components or structure during the fermentation process. However, there is yet to be a direct observation of the real effect of the membrane compositional change. In this study, atomic force microscope-based strategy was performed to determine Young's modulus of S. cerevisiae to directly clarify ethanol stress-associated changes and roles of S. cerevisiae cell membrane fluidity and elasticity. Cell survival rate decreased while the cell swelling rate and membrane permeability increased as ethanol concentration increased from 0% to 20% v/v. Young's modulus decreased continuously from 3.76MPa to 1.53MPa while ethanol stress increased from 0% to 20% v/v, indicating that ethanol stress induced the S. cerevisiae membrane fluidity and elasticity changes. Combined with the fact that membrane composition varies under ethanol stress, to some extent, this could be considered as a forced defensive act to the ethanol stress by S. cerevisiae cells. On the other hand, the ethanol stress induced loosening of cell membrane also caused S. cerevisiae cell to proactively remodel membrane to make cell membrane more agreeable to the increase of environmental threat. Increased ethanol stress made S. cerevisiae cell membrane more fluidized and elastic, and eventually further facilitated yeast cell's survival.

Expression of RCK2 MAPKAP (MAPK-activated protein kinase) rescues yeast cells sensitivity to osmotic stress

Background

Saccharomyces cerevisiae is the micro-organism of choice for the conversion of fermentable sugars during beverage or bioethanol fermentations. These fermentations are characterised by high osmotic stress on a yeast cell, with selected brewing fermentations beginning at 20–25% fermentable sugars and bioethanol fermentations at 13% fermentable sugars.

Results

RCK2 encodes for a MAPKAP (MAPK-activated protein kinase) enzyme and was identified on a locus by QTL analysis in yeast cells under osmotic stress, RCK2 expression was placed under a tetracycline regulatable vector and rescued glucose, sorbitol or glycerol induced osmotic stress in an rck2 null strain. A strain overexpressing RCK2 had significantly faster fermentation rates when compared with the empty vector control strain.

Conclusions

Presence of RCK2 increased rates of glucose utilisation (~40 g glucose in first 8 h) during a 15% glucose fermentation and concurrent production of ethanol when compared with empty vector controls. Tolerance to osmotic stress using the tetracycline regulatable vectors could be turned off with the addition of tetracycline returning a rck2 null strain back to osmotic sensitivity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12934-015-0276-7) contains supplementary material, which is available to authorized users.

A comparison of whole cell directed evolution approaches in breeding of industrial strain of Saccharomyces cerevisiae

OBJECTIVE

To reduce the fermentation cost in very high gravity fermentations of ethanol using Saccharomyces cerevisiae, whole cell directed evolution approaches were carried out.

RESULTS

The methods used included cell ploidy manipulation, global transcription machinery engineering and genome shuffling. Ethanol production by the four methods was improved compared with the control. Notably, the ethanol yield of a strain constructed by genome shuffling was enhanced by up to 11 % more than the control reaching 120 g ethanol/l in 35 h using a very high gravity fermentation with 300 g glucose/l.

CONCLUSION

Genome shuffling can create strains with improved fermentation characteristics in very high gravity fermentations.

Metabolic network discovery by top-down and bottom-up approaches and paths for reconciliation

The primary focus in the network-centric analysis of cellular metabolism by systems biology approaches is to identify the active metabolic network for the condition of interest. Two major approaches are available for the discovery of the condition-specific metabolic networks. One approach starts from genome-scale metabolic networks, which cover all possible reactions known to occur in the related organism in a condition-independent manner, and applies methods such as the optimization-based Flux-Balance Analysis to elucidate the active network. The other approach starts from the condition-specific metabolome data, and processes the data with statistical or optimization-based methods to extract information content of the data such that the active network is inferred. These approaches, termed bottom-up and top-down, respectively, are currently employed independently. However, considering that both approaches have the same goal, they can both benefit from each other paving the way for the novel integrative analysis methods of metabolome data- and flux-analysis approaches in the post-genomic era. This study reviews the strengths of constraint-based analysis and network inference methods reported in the metabolic systems biology field; then elaborates on the potential paths to reconcile the two approaches to shed better light on how the metabolism functions.

Metabolomic studies of human gastric cancer: Review

Metabolomics is a field of study in systems biology that involves the identification and quantification of metabolites present in a biological system. Analyzing metabolic differences between unperturbed and perturbed networks, such as cancerous and non-cancerous samples, can provide insight into underlying disease pathology, disease prognosis and diagnosis. Despite the large number of review articles concerning metabolomics and its application in cancer research, biomarker and drug discovery, these reviews do not focus on a specific type of cancer. Metabolomics may provide biomarkers useful for identification of early stage gastric cancer, potentially addressing an important clinical need. Here, we present a short review on metabolomics as a tool for biomarker discovery in human gastric cancer, with a primary focus on its use as a predictor of anticancer drug chemosensitivity, diagnosis, prognosis, and metastasis.

Extraction for metabolomics: access to the metabolome

INTRODUCTION

The value of information obtained from a metabolomic study depends on how much of the metabolome is present in analysed samples. Thus, only a comprehensive and reproducible extraction method will provide reliable data because the metabolites that will be measured are those that were extracted and all conclusions will be built around this information.

OBJECTIVE

To discuss the efficiency and reliability of available sample pre-treatment methods and their application in different fields of metabolomics.

METHODS

The review has three sections: the first deals with pre-extraction techniques, the second discusses the choice of extraction solvents and their main features and the third includes a brief description of the most used extraction techniques: microwave-assisted extraction, solid-phase extraction, supercritical fluid extraction, Soxhlet and a new method developed in our laboratory--the comprehensive extraction method.

RESULTS

Examination of over 200 studies showed that sample collection, homogenisation, grinding and storage could affect the yield and reproducibility of results. They also revealed that apart from the solvent used for extraction, the extraction techniques have a decisive role on the metabolites available for analysis.

CONCLUSION

It is essential to evaluate efficacy and reproducibility of sample pre-treatment as a first step to ensure the reliability of a metabolomic study. Among the reviewed methods, the comprehensive extraction method appears to provide a promising approach for extracting diverse types of metabolites.

Fermentation performance and physiology of two strains of Saccharomyces cerevisiae during growth in high gravity spruce hydrolysate and spent sulphite liquor

BACKGROUND

Lignocellulosic materials are a diverse group of substrates that are generally scarce in nutrients, which compromises the tolerance and fermentation performance of the fermenting organism. The problem is exacerbated by harsh pre-treatment, which introduces sugars and substances inhibitory to yeast metabolism. This study compares the fermentation behaviours of two yeast strains using different types of lignocellulosic substrates; high gravity dilute acid spruce hydrolysate (SH) and spent sulphite liquor (SSL), in the absence and presence of yeast extract. To this end, the fermentation performance, energy status and fermentation capacity of the strains were measured under different growth conditions.

RESULTS

Nutrient supplementation with yeast extract increased sugar uptake, cell growth and ethanol production in all tested fermentation conditions, but had little or no effect on the energy status, irrespective of media. Nutrient-supplemented medium enhanced the fermentation capacity of harvested cells, indicating that cell viability and reusability was increased by nutrient addition.

CONCLUSIONS

Although both substrates belong to the lignocellulosic spruce hydrolysates, their differences offer specific challenges and the overall yields and productivities largely depend on choice of fermenting strain.

Dosage Effects of Salt and pH Stresses on Saccharomyces cerevisiae as Monitored via Metabolites by Using Two Dimensional NMR Spectroscopy

Saccharomyces cerevisiae, which is a common species of yeast, is by far the most extensively studied model of a eukaryote because although it is one of the simplest eukaryotes, its basic cellular processes resemble those of higher organisms. In addition, yeast is a commercially valuable organism for ethanol production. Since the yeast data can be extrapolated to the important aspects of higher organisms, many researchers have studied yeast metabolism under various conditions. In this report, we analyzed and compared metabolites of Saccharomyces cerevisiae under salt and pH stresses of various strengths by using two-dimensional NMR spectroscopy. A total of 31 metabolites were identified for most of the samples. The levels of many identified metabolites showed gradual or drastic increases or decreases depending on the severity of the stresses involved. The statistical analysis produced a holistic outline: pH stresses were clustered together, but salt stresses were spread out depending on the severity. This work could provide a link between the metabolite profiles and mRNA or protein profiles under representative and well studied stress conditions.

Impact of osmotic stress and ethanol inhibition in yeast cells on process oscillation associated with continuous very-high-gravity ethanol fermentation

BACKGROUND

VHG fermentation is a promising process engineering strategy aiming at improving ethanol titer, and thus saving energy consumption for ethanol distillation and distillage treatment. However, sustained process oscillation was observed during continuous VHG ethanol fermentation, which significantly affected ethanol fermentation performance of the system.

RESULTS

Sustained process oscillation was investigated in continuous VHG ethanol fermentation, and stresses exerted on yeast cells by osmotic pressure from unfermented sugars and ethanol inhibition developed within the fermentation system were postulated to be major factors triggering this phenomenon. In this article, steady state was established for continuous ethanol fermentation with LG medium containing 120 g/L glucose, and then 160 g/L non-fermentable xylose was supplemented into the LG medium to simulate the osmotic stress on yeast cells under the VHG fermentation condition, but the fermentation process was still at steady state, indicating that the impact of osmotic stress on yeast cells was not the main reason for the process oscillation. However, when 30 g/L ethanol was supplemented into the LG medium to simulate the ethanol inhibition in yeast cells under the VHG fermentation condition, process oscillation was triggered, which was augmented with extended oscillation period and exaggerated oscillation amplitude as ethanol supplementation was increased to 50 g/L, but the process oscillation was gradually attenuated when the ethanol supplementations were stopped, and the steady state was restored. Furthermore, gas stripping was incorporated into the continuous VHG fermentation system to in situ remove ethanol produced by Saccharomyces cerevisiae, and the process oscillation was also attenuated, but restored after the gas stripping was interrupted.

CONCLUSIONS

Experimental results indicated that ethanol inhibition rather than osmotic stress on yeast cells is one of the main factors triggering the process oscillation under the VHG fermentation condition, and in the meantime gas stripping was validated to be an effective strategy for attenuating the process oscillation.

Comparative analysis of salt-tolerant gene HOG1 in a Zygosaccharomyces rouxii mutant strain and its parent strain

BACKGROUND

A higher-salt-tolerant mutant strain Zygosaccharomyces rouxii 3-2 (strain S3-2) that could be used for improving the flavour of high-salt liquid state soy sauce was previously constructed from parent strain Z. rouxii (strain S) by genome shuffling. However, whether the mutations in this strain affect HOG1 encoding MAPK Hog1p and improve intracellular glycerol production remains to be elucidated.

RESULTS

Although two mutations in the ORF and one in the promoter of the HOG1 gene sequence of strain S3-2 occurred compared with that of strain S, there was no significant difference in secondary and tertiary structures between S3-2Hog1p and SHog1p. It was found that the expression level of S3-2HOG1 was higher than that of SHOG1 in YPDN medium with high salt concentration. Furthermore, overexpression of S3-2HOG1 in Saccharomyces cerevisiae W303-1A could improve the salt tolerance and osmotolerance of engineered yeast compared with that of SHOG1.

CONCLUSION

Enhancement of the transcription level of HOG1 induced by mutation in the promoter region may be one of the main reasons for the improved salt tolerance of strain S3-2 compared with that of strain S. Considering food security, the conservation of S3-2HOG1 would be beneficial for application of strain S3-2 in the fermentation of soy sauce.

Spectral deconvolution for gas chromatography mass spectrometry-based metabolomics: current status and future perspectives

Mass spectrometry coupled to gas chromatography (GC-MS) has been widely applied in the field of metabolomics. Success of this application has benefited greatly from computational workflows that process the complex raw mass spectrometry data and extract the qualitative and quantitative information of metabolites. Among the computational algorithms within a workflow, deconvolution is critical since it reconstructs a pure mass spectrum for each component that the mass spectrometer observes. Based on the pure spectrum, the corresponding component can be eventually identified and quantified. Deconvolution is challenging due to the existence of co-elution. In this review, we focus on progress that has been made in the development of deconvolution algorithms and provide thoughts on future developments that will expand the application of GC-MS in metabolomics.

GABA transaminases from Saccharomyces cerevisiae and Arabidopsis thaliana complement function in cytosol and mitochondria

GABA transaminase (GABA-T) catalyses the conversion of GABA to succinate semialdehyde (SSA) in the GABA shunt pathway. The GABA-T from Saccharomyces cerevisiae (ScGABA-TKG) is an α-ketoglutarate-dependent enzyme encoded by the UGA1 gene, while higher plant GABA-T is a pyruvate/glyoxylate-dependent enzyme encoded by POP2 in Arabidopsis thaliana (AtGABA-T). The GABA-T from A. thaliana is localized in mitochondria and mediated by an 18-amino acid N-terminal mitochondrial targeting peptide predicated by both web-based utilities TargetP 1.1 and PSORT. Yeast UGA1 appears to lack a mitochondrial targeting peptide and is localized in the cytosol. To verify this bioinformatic analysis and examine the significance of ScGABA-TKG and AtGABA-T compartmentation and substrate specificity on physiological function, expression vectors were constructed to modify both ScGABA-TKG and AtGABA-T, so that they express in yeast mitochondria and cytosol. Physiological function was evaluated by complementing yeast ScGABA-TKG deletion mutant Δuga1 with AtGABA-T or ScGABA-TKG targeted to the cytosol or mitochondria for the phenotypes of GABA growth defect, thermosensitivity and heat-induced production of reactive oxygen species (ROS). This study demonstrates that AtGABA-T is functionally interchangeable with ScGABA-TKG for GABA growth, thermotolerance and limiting production of ROS, regardless of location in mitochondria or cytosol of yeast cells, but AtGABA-T is about half as efficient in doing so as ScGABA-TKG. These results are consistent with the hypothesis that pyruvate/glyoxylate-limited production of NADPH mediates the effect of the GABA shunt in moderating heat stress in Saccharomyces.

Rational medium optimization based on comparative metabolic profiling analysis to improve fumaric acid production

To rationally guide fumaric acid production improvement, metabolic profiling approach was performed to analyze metabolite changes of Rhizopus oryzae FM19 under different fermentation conditions. A correlation between the metabolic profiling and fumaric acid production was revealed by principal component analysis as well as partial least squares. Citric acid, oxaloacetic acid, 2-oxoglutarate, lactic acid, proline, alanine, valine, leucine were identified to be mainly responsible for the metabolism difference, which were involved in the Embden-Meyerhof-Parnas, tricarboxylic acid cycle, amino acid metabolism and fatty acid metabolism. Through the further analysis of metabolites changes together with the above pathways, exogenous addition strategies were developed, which resulted in 14% increase of fumaric acid (up to 56.5 g/L) and less by-products. These results demonstrated that metabolic profiling analysis could be successfully applied to the rational guidance of medium optimization and the productivity improvement of value-added compounds.

Quantitative 1H-NMR-metabolomics reveals extensive metabolic reprogramming and the effect of the aquaglyceroporin FPS1 in ethanol-stressed yeast cells

A metabolomic analysis using high resolution ¹H NMR spectroscopy coupled with multivariate statistical analysis was used to characterize the alterations in the endo- and exo-metabolome of S. cerevisiae BY4741 during the exponential phase of growth in minimal medium supplemented with different ethanol concentrations (0, 2, 4 and 6% v/v). This study provides evidence that supports the notion that ethanol stress induces reductive stress in yeast cells, which, in turn, appears to be counteracted by the increase in the rate of NAD⁺ regenerating bioreactions. Metabolomics data also shows increased intra- and extra-cellular accumulation of most amino acids and TCA cycle intermediates in yeast cells growing under ethanol stress suggesting a state of overflow metabolism in turn of the pyruvate branch-point. Given its previous implication in ethanol stress resistance in yeast, this study also focused on the effect of the expression of the aquaglyceroporin encoded by FPS1 in the yeast metabolome, in the absence or presence of ethanol stress. The metabolomics data collected herein shows that the deletion of the FPS1 gene in the absence of ethanol stress partially mimics the effect of ethanol stress in the parental strain. Moreover, the results obtained suggest that the reported action of Fps1 in mediating the passive diffusion of glycerol is a key factor in the maintenance of redox balance, an important feature for ethanol stress resistance, and may interfere with the ability of the yeast cell to accumulate trehalose. Overall, the obtained results corroborate the idea that metabolomic approaches may be crucial tools to understand the function and/or the effect of membrane transporters/porins, such as Fps1, and may be an important tool for the clear-cut design of improved process conditions and more robust yeast strains aiming to optimize industrial fermentation performance.

Systematic applications of metabolomics in metabolic engineering

The goals of metabolic engineering are well-served by the biological information provided by metabolomics: information on how the cell is currently using its biochemical resources is perhaps one of the best ways to inform strategies to engineer a cell to produce a target compound. Using the analysis of extracellular or intracellular levels of the target compound (or a few closely related molecules) to drive metabolic engineering is quite common. However, there is surprisingly little systematic use of metabolomics datasets, which simultaneously measure hundreds of metabolites rather than just a few, for that same purpose. Here, we review the most common systematic approaches to integrating metabolite data with metabolic engineering, with emphasis on existing efforts to use whole-metabolome datasets. We then review some of the most common approaches for computational modeling of cell-wide metabolism, including constraint-based models, and discuss current computational approaches that explicitly use metabolomics data. We conclude with discussion of the broader potential of computational approaches that systematically use metabolomics data to drive metabolic engineering.

Stress adaptation of Saccharomyces cerevisiae as monitored via metabolites using two-dimensional NMR spectroscopy

Many studies on yeast metabolism are focused on its response to specific stress conditions because the results can be extended to the human medical issues. Most of those works have been accomplished through functional genomics studies. However, these changes may not show a linear correlation with protein or metabolite levels. For many organisms including yeast, the number of metabolites is far fewer than that of genes or gene products. Thus, metabolic profiling can provide a simpler yet efficient snapshot of the system's physiology. Metabolites of Saccharomyces cerevisiae under various stresses were analyzed and compared with those under the normal, unstressed growth conditions by two-dimensional NMR spectroscopy. At least 31 metabolites were identified for most of the samples. The levels of many identified metabolites showed significant increase or decrease depending on the nature of the stress. The statistical analysis produced a holistic view: different stresses were clustered and isolated from one another with the exception of high pH, heat, and oxidative stresses. This work could provide a link between the metabolite profiles and mRNA or protein profiles under representative and well-studied stress conditions.

Yeast toxicogenomics: genome-wide responses to chemical stresses with impact in environmental health, pharmacology, and biotechnology

The emerging transdisciplinary field of Toxicogenomics aims to study the cell response to a given toxicant at the genome, transcriptome, proteome, and metabolome levels. This approach is expected to provide earlier and more sensitive biomarkers of toxicological responses and help in the delineation of regulatory risk assessment. The use of model organisms to gather such genomic information, through the exploitation of Omics and Bioinformatics approaches and tools, together with more focused molecular and cellular biology studies are rapidly increasing our understanding and providing an integrative view on how cells interact with their environment. The use of the model eukaryote Saccharomyces cerevisiae in the field of Toxicogenomics is discussed in this review. Despite the limitations intrinsic to the use of such a simple single cell experimental model, S. cerevisiae appears to be very useful as a first screening tool, limiting the use of animal models. Moreover, it is also one of the most interesting systems to obtain a truly global understanding of the toxicological response and resistance mechanisms, being in the frontline of systems biology research and developments. The impact of the knowledge gathered in the yeast model, through the use of Toxicogenomics approaches, is highlighted here by its use in prediction of toxicological outcomes of exposure to pesticides and pharmaceutical drugs, but also by its impact in biotechnology, namely in the development of more robust crops and in the improvement of yeast strains as cell factories.

Plasmid-mediate transfer of FLO1 into industrial Saccharomyces cerevisiae PE-2 strain creates a strain useful for repeat-batch fermentations involving flocculation-sedimentation

The flocculation gene FLO1 was transferred into the robust industrial strain Saccharomyces cerevisiae PE-2 by the lithium acetate method. The recombinant strain showed a fermentation performance similar to that of the parental strain. In 10 repeat-batch cultivations in VHG medium with 345 g glucose/L and cell recycling by flocculation-sedimentation, an average final ethanol concentration of 142 g/L and an ethanol productivity of 2.86 g/L/h were achieved. Due to the flocculent nature of the recombinant strain it is possible to reduce the ethanol production cost because of lower centrifugation and distillation costs.