Global metabolite analysis of yeast: evaluation of sample preparation methods

Metabolic engineering of a tyrosine-overproducing yeast platform using targeted metabolomics

Background

L-tyrosine is a common precursor for a wide range of valuable secondary metabolites, including benzylisoquinoline alkaloids (BIAs) and many polyketides. An industrially tractable yeast strain optimized for production of L-tyrosine could serve as a platform for the development of BIA and polyketide cell factories. This study applied a targeted metabolomics approach to evaluate metabolic engineering strategies to increase the availability of intracellular L-tyrosine in the yeast Saccharomyces cerevisiae CEN.PK. Our engineering strategies combined localized pathway engineering with global engineering of central metabolism, facilitated by genome-scale steady-state modelling.

Results

Addition of a tyrosine feedback resistant version of 3-deoxy-D-arabino-heptulosonate-7-phosphate synthase Aro4 from S. cerevisiae was combined with overexpression of either a tyrosine feedback resistant yeast chorismate mutase Aro7, the native pentafunctional arom protein Aro1, native prephenate dehydrogenase Tyr1 or cyclohexadienyl dehydrogenase TyrC from Zymomonas mobilis. Loss of aromatic carbon was limited by eliminating phenylpyruvate decarboxylase Aro10. The TAL gene from Rhodobacter sphaeroides was used to produce coumarate as a simple test case of a heterologous by-product of tyrosine. Additionally, multiple strategies for engineering global metabolism to promote tyrosine production were evaluated using metabolic modelling. The T21E mutant of pyruvate kinase Cdc19 was hypothesized to slow the conversion of phosphoenolpyruvate to pyruvate and accumulate the former as precursor to the shikimate pathway. The ZWF1 gene coding for glucose-6-phosphate dehydrogenase was deleted to create an NADPH deficiency designed to force the cell to couple its growth to tyrosine production via overexpressed NADP⁺-dependent prephenate dehydrogenase Tyr1. Our engineered Zwf1⁻ strain expressing TYRC ARO4^FBR and grown in the presence of methionine achieved an intracellular L-tyrosine accumulation up to 520 μmol/g DCW or 192 mM in the cytosol, but sustained flux through this pathway was found to depend on the complete elimination of feedback inhibition and degradation pathways.

Conclusions

Our targeted metabolomics approach confirmed a likely regulatory site at DAHP synthase and identified another possible cofactor limitation at prephenate dehydrogenase. Additionally, the genome-scale metabolic model identified design strategies that have the potential to improve availability of erythrose 4-phosphate for DAHP synthase and cofactor availability for prephenate dehydrogenase. We evaluated these strategies and provide recommendations for further improvement of aromatic amino acid biosynthesis in S. cerevisiae.

Electronic supplementary material

The online version of this article (doi:10.1186/s12934-015-0252-2) contains supplementary material, which is available to authorized users.

Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis

Kidney cancer [or renal cell carcinoma (RCC)] is known as "the internist's tumor" because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the Von Hippel-Lindau tumor suppressor, in characterizing higher-grade tumors, we found that the Warburg effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared with other metabolic pathways. Together, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC.

NMR analysis of budding yeast metabolomics: a rapid method for sample preparation

Here we propose the optimization of a rapid and reproducible protocol for intracellular metabolite extraction from yeast cells and their metabolic profiling by (1)H-NMR spectroscopy. The protocol reliability has been validated through comparison between the metabolome of cells in different phases of growth or with different genetic backgrounds.

Non-targeted metabolomic reveals the effect of salt stress on global metabolite of halotolerant yeast Candida versatilis and principal component analysis

As one of the major microbes in the soy sauce fermentation, Candida versatilis enriches the flavor and improves the quality of soy sauce. In this study, a combination of five different GC-MS and LC-MS-based metabolome analytical approaches was used to analyze the intracellular, extracellular and whole metabolites of C. versatilis. Our results found out that a total of 132, 244 and 267 different metabolites were detectable from the intracellular, extracellular and whole part, respectively. When exposed to 0. 9 and 18 % salt, respectively, 114, 123 and 129 different intracellular metabolites, 184, 200 and 178 extracellular metabolites and 177, 188 and 186 whole metabolites were detected, respectively. Our data showed that salt enhances the metabolic capacity of C. versatilis, especially its amino acid and enhances the synthesis and secretion of some metabolites of C. versatilis, especially the aldehydes and phenols, such as vanillin, guaiacol and 5-hydroxymethylfurfural. Our data also showed that special attention has to be paid to the generation of biogenic amines when C. versatilis was treated with salt.

Quantitative NMR metabolite profiling of methicillin-resistant and methicillin-susceptible Staphylococcus aureus discriminates between biofilm and planktonic phenotypes

Wound bioburden in the form of colonizing biofilms is a major contributor to nonhealing wounds. Staphylococcus aureus is a Gram-positive, facultative anaerobe commonly found in chronic wounds; however, much remains unknown about the basic physiology of this opportunistic pathogen, especially with regard to the biofilm phenotype. Transcriptomic and proteomic analysis of S. aureus biofilms have suggested that S. aureus biofilms exhibit an altered metabolic state relative to the planktonic phenotype. Herein, comparisons of extracellular and intracellular metabolite profiles detected by (1)H NMR were conducted for methicillin-resistant (MRSA) and methicillin-susceptible (MSSA) S. aureus strains grown as biofilm and planktonic cultures. Principal component analysis distinguished the biofilm phenotype from the planktonic phenotype, and factor loadings analysis identified metabolites that contributed to the statistical separation of the biofilm from the planktonic phenotype, suggesting that key features distinguishing biofilm from planktonic growth include selective amino acid uptake, lipid catabolism, butanediol fermentation, and a shift in metabolism from energy production to assembly of cell-wall components and matrix deposition. These metabolite profiles provide a basis for the development of metabolite biomarkers that distinguish between biofilm and planktonic phenotypes in S. aureus and have the potential for improved diagnostic and therapeutic use in chronic wounds.

Model-driven redox pathway manipulation for improved isobutanol production in Bacillus subtilis complemented with experimental validation and metabolic profiling analysis

To rationally guide the improvement of isobutanol production, metabolic network and metabolic profiling analysis were performed to provide global and profound insights into cell metabolism of isobutanol-producing Bacillus subtilis. The metabolic flux distribution of strains with different isobutanol production capacity (BSUL03, BSUL04 and BSUL05) drops a hint of the importance of NADPH on isobutanol biosynthesis. Therefore, the redox pathways were redesigned in this study. To increase NADPH concentration, glucose-6-phosphate isomerase was inactivated (BSUL06) and glucose-6-phosphate dehydrogenase was overexpressed (BSUL07) successively. As expected, NADPH pool size in BSUL07 was 4.4-fold higher than that in parental strain BSUL05. However, cell growth, isobutanol yield and production were decreased by 46%, 22%, and 80%, respectively. Metabolic profiling analysis suggested that the severely imbalanced redox status might be the primary reason. To solve this problem, gene udhA of Escherichia coli encoding transhydrogenase was further overexpressed (BSUL08), which not only well balanced the cellular ratio of NAD(P)H/NAD(P)⁺, but also increased NADH and ATP concentration. In addition, a straightforward engineering approach for improving NADPH concentrations was employed in BSUL05 by overexpressing exogenous gene pntAB and obtained BSUL09. The performance for isobutanol production by BSUL09 was poorer than BSUL08 but better than other engineered strains. Furthermore, in fed-batch fermentation the isobutanol production and yield of BSUL08 increased by 11% and 19%, up to the value of 6.12 g/L and 0.37 C-mol isobutanol/C-mol glucose (63% of the theoretical value), respectively, compared with parental strain BSUL05. These results demonstrated that model-driven complemented with metabolic profiling analysis could serve as a useful approach in the strain improvement for higher bio-productivity in further application.

Application of stable isotope-assisted metabolomics for cell metabolism studies

The applications of stable isotopes in metabolomics have facilitated the study of cell metabolisms. Stable isotope-assisted metabolomics requires: (1) properly designed tracer experiments; (2) stringent sampling and quenching protocols to minimize isotopic alternations; (3) efficient metabolite separations; (4) high resolution mass spectrometry to resolve overlapping peaks and background noises; and (5) data analysis methods and databases to decipher isotopic clusters over a broad m/z range (mass-to-charge ratio). This paper overviews mass spectrometry based techniques for precise determination of metabolites and their isotopologues. It also discusses applications of isotopic approaches to track substrate utilization, identify unknown metabolites and their chemical formulas, measure metabolite concentrations, determine putative metabolic pathways, and investigate microbial community populations and their carbon assimilation patterns. In addition, 13C-metabolite fingerprinting and metabolic models can be integrated to quantify carbon fluxes (enzyme reaction rates). The fluxome, in combination with other "omics" analyses, may give systems-level insights into regulatory mechanisms underlying gene functions. More importantly, 13C-tracer experiments significantly improve the potential of low-resolution gas chromatography-mass spectrometry (GC-MS) for broad-scope metabolism studies. We foresee the isotope-assisted metabolomics to be an indispensable tool in industrial biotechnology, environmental microbiology, and medical research.

Metabolomic analysis of three Mollicute species

We present a systematic study of three bacterial species that belong to the class Mollicutes, the smallest and simplest bacteria, Spiroplasma melliferum, Mycoplasma gallisepticum, and Acholeplasma laidlawii. To understand the difference in the basic principles of metabolism regulation and adaptation to environmental conditions in the three species, we analyzed the metabolome of these bacteria. Metabolic pathways were reconstructed using the proteogenomic annotation data provided by our lab. The results of metabolome, proteome and genome profiling suggest a fundamental difference in the adaptation of the three closely related Mollicute species to stress conditions. As the transaldolase is not annotated in Mollicutes, we propose variants of the pentose phosphate pathway catalyzed by annotated enzymes for three species. For metabolite detection we employed high performance liquid chromatography coupled with mass spectrometry. We used liquid chromatography method - hydrophilic interaction chromatography with silica column - as it effectively separates highly polar cellular metabolites prior to their detection by mass spectrometer.

Engineering the Saccharomyces cerevisiae β-oxidation pathway to increase medium chain fatty acid production as potential biofuel

Fatty acid-derived biofuels and biochemicals can be produced in microbes using β-oxidation pathway engineering. In this study, the β-oxidation pathway of Saccharomyces cerevisiae was engineered to accumulate a higher ratio of medium chain fatty acids (MCFAs) when cells were grown on fatty acid-rich feedstock. For this purpose, the haploid deletion strain Δpox1 was obtained, in which the sole acyl-CoA oxidase encoded by POX1 was deleted. Next, the POX2 gene from Yarrowia lipolytica, which encodes an acyl-CoA oxidase with a preference for long chain acyl-CoAs, was expressed in the Δpox1 strain. The resulting Δpox1 [pox2+] strain exhibited a growth defect because the β-oxidation pathway was blocked in peroxisomes. To unblock the β-oxidation pathway, the gene CROT, which encodes carnitine O-octanoyltransferase, was expressed in the Δpox1 [pox2+] strain to transport the accumulated medium chain acyl-coAs out of the peroxisomes. The obtained Δpox1 [pox2+, crot+] strain grew at a normal rate. The effect of these genetic modifications on fatty acid accumulation and profile was investigated when the strains were grown on oleic acids-containing medium. It was determined that the engineered strains Δpox1 [pox2+] and Δpox1 [pox2+, crot+] had increased fatty acid accumulation and an increased ratio of MCFAs. Compared to the wild-type (WT) strain, the total fatty acid production of the strains Δpox1 [pox2+] and Δpox1 [pox2+, crot+] were increased 29.5% and 15.6%, respectively. The intracellular level of MCFAs in Δpox1 [pox2+] and Δpox1 [pox2+, crot+] increased 2.26- and 1.87-fold compared to the WT strain, respectively. In addition, MCFAs in the culture medium increased 3.29-fold and 3.34-fold compared to the WT strain. These results suggested that fatty acids with an increased MCFAs ratio accumulate in the engineered strains with a modified β-oxidation pathway. Our approach exhibits great potential for transforming low value fatty acid-rich feedstock into high value fatty acid-derived products.

Sampling and analysis of metabolomes in biological fluids

Metabolome analysis involves the study of small molecules that are involved in the metabolic responses that occur through patho-physiological changes caused by genetic stimuli or chemical agents.

Stable isotope-labeled tracers for metabolic pathway elucidation by GC-MS and FT-MS

Advances in analytical methodologies, principally nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS), over the last decade have made large-scale analysis of the human metabolome a reality. This is leading to the reawakening of the importance of metabolism in human diseases, particularly widespread metabolic diseases such as cancer, diabetes, and obesity. Emerging NMR and MS atom-tracking technologies and informatics are poised to revolutionize metabolomics-based research because they deliver the high information throughput (HIT) that is needed for deciphering systems biochemistry. In particular, stable isotope-resolved metabolomics (SIRM) enables unambiguous tracking of individual atoms through compartmentalized metabolic networks in a wide range of experimental systems, including human subjects. MS offers a wide range of instrumental capabilities involving different levels of initial capital outlay and operating costs, ranging from gas-chromatography (GC) MS that is affordable by many individual laboratories to the HIT-supporting Fourier-transform (FT) class of MS that rivals NMR in cost and infrastructure support. This chapter focuses on sample preparation, instrument, and data processing procedures for these two extremes of MS instrumentation used in SIRM.

Yeast metabolomics: sample preparation for a GC/MS-based analysis

Metabolome sample preparation is one of the key factors in metabolomics analyses. The quality of the metabolome data will depend on the suitability of the experimental procedures to the cellular system (e.g., yeast cells) and the analytical performance. Here, we summarize a protocol for metabolome analysis of yeast cells using gas chromatography-mass spectrometry (GC-MS). First, the main phases of a metabolomics analysis are identified: sample preparation, metabolite extraction, and analysis. We also provide an overview on different methods used to quench samples and extract intracellular metabolites from yeast cells. This protocol provides a detailed description of a GC-MS-based analysis of yeast metabolome, in particular for metabolites containing amino and/or carboxyl groups, which represent most of the compounds participating in the central carbon metabolism.

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.

Global LC/MS Metabolomics Profiling of Calcium Stressed and Immunosuppressant Drug Treated Saccharomyces cerevisiae

Previous studies have shown that calcium stressed Saccharomyces cerevisiae, challenged with immunosuppressant drugs FK506 and Cyclosporin A, responds with comprehensive gene expression changes and attenuation of the generalized calcium stress response. Here, we describe a global metabolomics workflow for investigating the utility of tracking corresponding phenotypic changes. This was achieved by efficiently analyzing relative abundance differences between intracellular metabolite pools from wild-type and calcium stressed cultures, with and without prior immunosuppressant drugs exposure. We used pathway database content from WikiPathways and YeastCyc to facilitate the projection of our metabolomics profiling results onto biological pathways. A key challenge was to increase the coverage of the detected metabolites. This was achieved by applying both reverse phase (RP) and aqueous normal phase (ANP) chromatographic separations, as well as electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI) sources for detection in both ion polarities. Unsupervised principle component analysis (PCA) and ANOVA results revealed differentiation between wild-type controls, calcium stressed and immunosuppressant/calcium challenged cells. Untargeted data mining resulted in 247 differentially expressed, annotated metabolites, across at least one pair of conditions. A separate, targeted data mining strategy identified 187 differential, annotated metabolites. All annotated metabolites were subsequently mapped onto curated pathways from YeastCyc and WikiPathways for interactive pathway analysis and visualization. Dozens of pathways showed differential responses to stress conditions based on one or more matches to the list of annotated metabolites or to metabolites that had been identified further by MS/MS. The purine salvage, pantothenate and sulfur amino acid pathways were flagged as being enriched, which is consistent with previously published literature for transcriptomics analysis. Thus, broad discovery-based data mining combined with targeted pathway projections can be an important asset for rapidly distilling, testing and evaluating a large amount of information for further investigation.

Mapping condition-dependent regulation of lipid metabolism in Saccharomyces cerevisiae

Lipids play a central role in cellular function as constituents of membranes, as signaling molecules, and as storage materials. Although much is known about the role of lipids in regulating specific steps of metabolism, comprehensive studies integrating genome-wide expression data, metabolite levels, and lipid levels are currently lacking. Here, we map condition-dependent regulation controlling lipid metabolism in Saccharomyces cerevisiae by measuring 5636 mRNAs, 50 metabolites, 97 lipids, and 57 (13)C-reaction fluxes in yeast using a three-factor full-factorial design. Correlation analysis across eight environmental conditions revealed 2279 gene expression level-metabolite/lipid relationships that characterize the extent of transcriptional regulation in lipid metabolism relative to major metabolic hubs within the cell. To query this network, we developed integrative methods for correlation of multi-omics datasets that elucidate global regulatory signatures. Our data highlight many characterized regulators of lipid metabolism and reveal that sterols are regulated more at the transcriptional level than are amino acids. Beyond providing insights into the systems-level organization of lipid metabolism, we anticipate that our dataset and approach can join an emerging number of studies to be widely used for interrogating cellular systems through the combination of mathematical modeling and experimental biology.

The potential of electrophoretic sample pretreatment techniques and new instrumentation for bioanalysis, with a focus on peptidomics and metabolomics

This Review highlights the potential of new electromigration-based sample pretreatment techniques for bioanalysis. Sample pretreatment is a challenging part of the analytical workflow, especially in the fields of peptidomics and metabolomics, where the analytes are very diverse, both in physicochemical properties and in endogenous concentration. Electromigration-based techniques have several strengths, such as fast selective analyte concentration and that complementary information on the content of a sample can be obtained when compared with more conventional (chromatography-based) techniques. In the past decade, various new electromigration-based sample pretreatment techniques have been developed, and importantly, new instrumental setups. In this Review, we provide an introduction on electromigration and its strengths. Then, selected examples of electromigration-based sample pretreatment techniques and instrumentation are discussed, namely free-flow electrophoresis, isoelectric focusing, isotachophoresis, electrodialysis, electromembrane extraction and electroextraction. Finally, the promising perspectives of electromigration-based sample pretreatment techniques are outlined.

Identification of intracellular Spiroplasma melliferum metabolites by the HPLC-MS method

In contrast to the abundance of systems-oriented approaches describing changes on the transcriptome or proteome level, relatively few studies have employed the metabolome. The goal of the presented research was to identify as many intracellular metabolites as possible in a Spiroplasma melliferum extract by flow injection time-of-flight mass spectrometry. The Mollicutes class bacterium S. melliferum is a member of a unique category of bacteria that have in common the absence of a cell wall, a reduced genome, and simplified metabolic pathways. Metabolite identification was confirmed by fragmentation of previously detected ions by target mass spectrometry. The selected liquid chromatography approach, hydrophilic interaction chromatography with amino and silica columns, effectively separates highly polar cellular metabolites prior to their detection on a high accuracy mass spectrometer in positive and negative acquisition mode for each column. Here we present reliable measurement of 76 metabolites, including components of sugar, amino acid, and nucleotide metabolism. We have identified about a third of the possible intracellular S. melliferum metabolites predicted by genome annotation.

NAD-dependent lactate dehydrogenase catalyses the first step in respiratory utilization of lactate by Lactococcus lactis

Lactococcus lactis can undergo respiration when hemin is added to an aerobic culture. The most distinctive feature of lactococcal respiration is that lactate could be consumed in the stationary phase concomitantly with the rapid accumulation of diacetyl and acetoin. However, the enzyme responsible for lactate utilization in this process has not yet been identified. As genes for fermentative NAD-dependent l-lactate dehydrogenase (l-nLDH) and potential electron transport chain (ETC)-related NAD-independent l-LDH (l-iLDH) exist in L. lactis, the activities of these enzymes were measured in this study using crude cell extracts prepared from respiratory and fermentation cultures. Further studies were conducted with purified preparations of recombinant LDH homologous proteins. The results showed that l-iLDH activity was hardly detected in both crude cell extracts and purified l-iLDH homologous protein while l-nLDH activity was very significant. This suggested that l-iLDHs were inactive in lactate utilization. The results of kinetic analyses and the effects of activator, inhibitor, substrate and product concentrations on the reaction equilibrium showed that l-nLDH was much more prone to catalyze the pyruvate reduction reaction but could reverse its role provided that the concentrations of NADH and pyruvate were extremely low while NAD and lactate were abundant. Metabolite analysis in respiratory culture revealed that the cellular status in the stationary phase was beneficial for l-nLDH to catalyze lactate oxidation. The factors accounting for the respiration- and stationary phase-dependent lactate utilization in L. lactis are discussed here.

•

LutABC proteins do not participate in lactate oxidation in Lactococcus lactis

•

Lactococcus lactis has very low NAD-independent lactate dehydrogenase activity

•

Fructose-1,6-bisphosphate-dependent lactate dehydrogenase can work in reverse in vivo

•

Metabolite concentrations in the stationary phase are favorable for lactate oxidation

•

Respiratory metabolism is the basis for continual lactate oxidation in Lactococcus

Evaluation of extraction protocols for simultaneous polar and non-polar yeast metabolite analysis using multivariate projection methods

Metabolomic and lipidomic approaches aim to measure metabolites or lipids in the cell. Metabolite extraction is a key step in obtaining useful and reliable data for successful metabolite studies. Significant efforts have been made to identify the optimal extraction protocol for various platforms and biological systems, for both polar and non-polar metabolites. Here we report an approach utilizing chemoinformatics for systematic comparison of protocols to extract both from a single sample of the model yeast organism Saccharomyces cerevisiae. Three chloroform/methanol/water partitioning based extraction protocols found in literature were evaluated for their effectiveness at reproducibly extracting both polar and non-polar metabolites. Fatty acid methyl esters and methoxyamine/trimethylsilyl derivatized aqueous compounds were analyzed by gas chromatography mass spectrometry to evaluate non-polar or polar metabolite analysis. The comparative breadth and amount of recovered metabolites was evaluated using multivariate projection methods. This approach identified an optimal protocol consisting of 64 identified polar metabolites from 105 ion hits and 12 fatty acids recovered, and will potentially attenuate the error and variation associated with combining metabolite profiles from different samples for untargeted analysis with both polar and non-polar analytes. It also confirmed the value of using multivariate projection methods to compare established extraction protocols.

Methodological approaches to help unravel the intracellular metabolome of Bacillus subtilis

Background

Bacillus subtilis (B. subtilis) has become widely accepted as a model organism for studies on Gram-positive bacteria. A deeper insight into the physiology of this prokaryote requires advanced studies of its metabolism. To provide a reliable basis for metabolome investigations, a validated experimental protocol is needed since the quality of the analytical sample and the final data are strongly affected by the sampling steps. To ensure that the sample analyzed precisely reflects the biological condition of interest, outside biases have to be avoided during sample preparation.

Results

Procedures for sampling, quenching, extraction of metabolites, cell disruption, as well as metabolite leakage were tested and optimized for B. subtilis. In particular the energy status of the bacterial cell, characterized by the adenylate energy charge, was used to evaluate sampling accuracy. Moreover, the results of the present study demonstrate that the cultivation medium can affect the efficiency of the developed sampling procedure.

Conclusion

The final workflow presented here allows for the reproducible and reliable generation of physiological data. The method with the highest qualitative and quantitative metabolite yield was chosen, and when used together with complementary bioanalytical methods (i.e., GC-MS, LC-MS and ¹H-NMR) provides a solid basis to gather information on the metabolome of B. subtilis.

Dispersive solid phase extraction combined with ion-pair ultra high-performance liquid chromatography tandem mass spectrometry for quantification of nucleotides in Lactococcus lactis

Analysis of intracellular metabolites in bacteria is of utmost importance for systems biology and at the same time analytically challenging due to the large difference in concentrations, multiple negative charges, and high polarity of these compounds. To challenge this, a method based on dispersive solid phase extraction with charcoal and subsequent analysis with ion-pair liquid chromatography coupled with electrospray ionization tandem mass spectrometry was established for quantification of intracellular pools of the 28 most important nucleotides. The method can handle extracts where cells leak during the quenching. Using a Phenyl-Hexyl column and tributylamine as volatile ion-pair reagent, sufficient retention and separation was achieved for mono-, di-, and triphosphorylated nucleotides. Stable isotope labeled nucleotides were used as internal standards for some analytes. The method was validated by determination of the recovery, matrix effects, accuracy, linearity, and limit of detection based on spiking of medium blank as well as standard addition to quenched Lactococcus lactis samples. For standard addition experiments, the isotope-labeled standards needed to be added in similar or higher concentrations as the analytes. L. lactis samples had an energy charge of 0.97 ± 0.001 which was consistent with literature, whereas some differences were observed compared with legacy data based on ³³P labeling.

Data Analysis and Interpretation in Metabolomics

Metabolomics represents the new ‘omics’ approach of the functional genomics era. It consists in the identification and quantification of all small molecules, namely metabolites, in a given biological system. While metabolomics refers to the analysis of any possible biological system, metabonomics is specifically applied to disease and physiopathological situations. The data collected within these approaches is highly integrative of the other higher levels and is hence amenable to be explored with a top-down systems biology point of view. The aim of this chapter is to give a global view of the state of the art in metabolomics describing the two analytical techniques usually used to give rise to this kind of data, nuclear magnetic resonance, NMR, and mass spectrometry. In addition, the author will focus on the different data analysis tools that can be applied to such studies to extract information with special interest at the attempts to integrate metabolomics with other ‘omics’ approaches and its relevance in systems biology modeling.

Quantitative quenching evaluation and direct intracellular metabolite analysis in Penicillium chrysogenum

Sustained progress in metabolic engineering methodologies has stimulated new efforts toward optimizing fungal production strains such as through metabolite analysis of Penicillium chrysogenum industrial-scale processes. Accurate intracellular metabolite quantification requires sampling procedures that rapidly stop metabolism (quenching) and avoid metabolite loss via the cell membrane (leakage). When sampling protocols are validated, the quenching efficiency is generally not quantitatively assessed. For fungal metabolomics, quantitative biomass separation using centrifugation is a further challenge. In this study, P. chrysogenum intracellular metabolites were quantified directly from biomass extracts using automated sampling and fast filtration. A master/slave bioreactor concept was applied to provide industrial production conditions. Metabolic activity during sampling was monitored by 13C tracing. Enzyme activities were efficiently stopped and metabolite leakage was absent. This work provides a reliable method for P. chrysogenum metabolomics and will be an essential base for metabolic engineering of industrial processes.

Extraction, derivatization, and determination of metabolome in human macrophages

A GC/TOF-MS was applied to the determination of metabolites in human macrophages. The extraction conditions and quenching conditions were investigated and optimized. The results indicated that 0.9% w/v sodium chloride at 4°C was the most favorable condition to quench macrophage, 1 mL 50% ACN for 2 min in ice bath was the optimal condition to extract 5 × 10(6) cells. Two hundred six peaks could be detectable with peak area over 50 using this method. Among these peaks, 45 peaks with the similarity over 700 were identified using standard compounds for endogenous metabolites. Thirty-seven out of 45 metabolites could be quantified directly by this method. Twenty metabolites were selected randomly, and 15 amino acids were used for method validation. The correlation coefficients (r) ranging from 0.9902 to 0.9977 were obtained for 15 amino acids in the range of 2.35-150.20 μg/mL. The intraday and interday precisions were lower than 19.90% for the randomly selected 20 endogenous metabolites. Using this development method and multivariate statistical technique, several potential biomarkers were found from human macrophages infected by different Mycobacterium tuberculosis (M. tuberculosis) strains. The results suggest that the method could be applied to the investigation of the pathogenicity of tuberculosis.

Detection of polar metabolites through the use of gas chromatography-mass spectrometry

Gas chromatography-mass spectrometry (GC-MS) is a highly reproducible and sensitive analytical technique that has had significant use in the area of metabolite profiling. GC-MS is able to detect a wide variety of metabolites, with highly differing chemistries. In general, extracted biological samples are volatilized prior to separation on a capillary column with a stationary phase suited to the analysis of the compounds of interest. Separated compounds are eluted into a mass spectrometer equipped with an electron impact ionization source, thereby generating a quantifiable mass spectral fingerprint. This chapter describes a method for the trimethylsilyl derivatization of polar metabolites, followed by detection and relative quantification using a gas chromatograph coupled to a single quadrupole mass spectrometer. Using this method will enable the profiling of the greatest range of polar metabolites.

NMR Metabolomics Analysis of Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative disease, which is characterized by progressive death of dopaminergic neurons in the substantia nigra pars compacta. Although mitochondrial dysfunction and oxidative stress are linked to PD pathogenesis, its etiology and pathology remain to be elucidated. Metabolomics investigates metabolite changes in biofluids, cell lysates, tissues and tumors in order to correlate these metabolomic changes to a disease state. Thus, the application of metabolomics to investigate PD provides a systematic approach to understand the pathology of PD, to identify disease biomarkers, and to complement genomics, transcriptomics and proteomics studies. This review will examine current research into PD mechanisms with a focus on mitochondrial dysfunction and oxidative stress. Neurotoxin-based PD animal models and the rationale for metabolomics studies in PD will also be discussed. The review will also explore the potential of NMR metabolomics to address important issues related to PD treatment and diagnosis.

Accurate quantification of the redox-sensitive GSH/GSSG ratios in the yeast Pichia pastoris by HILIC-MS/MS

A novel method for the simultaneous quantification of both glutathione (GSH) and its oxidized form glutathione disulfide (GSSG) by hydrophilic interaction chromatography-MS/MS has been developed and is critically discussed. Internal standardization based on isotopically labeled standards for both analytes is an absolute prerequisite for accurate quantification of this redox pair. Hence, a highly efficient and selective miniaturized procedure for the synthesis of isotopically labeled GSSG from commercially available glutathione-(glycine-(13)C(2),(15)N) was established using H(2)O(2) as oxidant and NaI as catalyst. Moreover, a tool is presented to monitor and hence uncover artifactual GSSG formation due to oxidation of GSH during sample preparation, which is the main source of systematic error in GSSG analysis. For this purpose, we propose to monitor the oxidation product formed by reaction of naturally occurring GSH with the isotopically labeled GSH used as internal standard. For the determination of GSH/GSSG ratios in yeast, different extraction methods based on (1) hot extraction with aqueous, acidic, or organic solvents, (2) mechanical cell lysis, and (3) extraction at subambient temperature were investigated in terms of recovery, extraction efficiency, and artifactual formation of GSSG. Total combined uncertainties of as low as 25-30 % (coverage factor=2) for the determination of GSH/GSSG ratios without derivatization were made possible by the addition of the internal standards early in the analytical procedure (before extraction) and immediate analysis of the analytes.

Progress toward single cell metabolomics

The metabolome refers to the entire set of small molecules, or metabolites, within a biological sample. These molecules are involved in many fundamental intracellular functions and reflect the cell's physiological condition. The ability to detect and identify metabolites and determine and monitor their amounts at the single cell level enables an exciting range of studies of biological variation and functional heterogeneity between cells, even within a presumably homogenous cell population. Significant progress has been made in the development and application of bioanalytical tools for single cell metabolomics based on mass spectrometry, microfluidics, and capillary separations. Remarkable improvements in the sensitivity, specificity, and throughput of these approaches enable investigation of multiple metabolites simultaneously in a range of individual cell samples.

Error propagation analysis for quantitative intracellular metabolomics

Model-based analyses have become an integral part of modern metabolic engineering and systems biology in order to gain knowledge about complex and not directly observable cellular processes. For quantitative analyses, not only experimental data, but also measurement errors, play a crucial role. The total measurement error of any analytical protocol is the result of an accumulation of single errors introduced by several processing steps. Here, we present a framework for the quantification of intracellular metabolites, including error propagation during metabolome sample processing. Focusing on one specific protocol, we comprehensively investigate all currently known and accessible factors that ultimately impact the accuracy of intracellular metabolite concentration data. All intermediate steps are modeled, and their uncertainty with respect to the final concentration data is rigorously quantified. Finally, on the basis of a comprehensive metabolome dataset of Corynebacterium glutamicum, an integrated error propagation analysis for all parts of the model is conducted, and the most critical steps for intracellular metabolite quantification are detected.

Metabolic engineering of the purine biosynthetic pathway in Corynebacterium glutamicum results in increased intracellular pool sizes of IMP and hypoxanthine

Background

Purine nucleotides exhibit various functions in cellular metabolism. Besides serving as building blocks for nucleic acid synthesis, they participate in signaling pathways and energy metabolism. Further, IMP and GMP represent industrially relevant biotechnological products used as flavor enhancing additives in food industry. Therefore, this work aimed towards the accumulation of IMP applying targeted genetic engineering of Corynebacterium glutamicum.

Results

Blocking of the degrading reactions towards AMP and GMP lead to a 45-fold increased intracellular IMP pool of 22 μmol g_CDW^-1. Deletion of the pgi gene encoding glucose 6-phosphate isomerase in combination with the deactivated AMP and GMP generating reactions, however, resulted in significantly decreased IMP pools (13 μmol g_CDW^-1). Targeted metabolite profiling of the purine biosynthetic pathway further revealed a metabolite shift towards the formation of the corresponding nucleobase hypoxanthine (102 μmol g_CDW^-1) derived from IMP degradation.

Conclusions

The purine biosynthetic pathway is strongly interconnected with various parts of the central metabolism and therefore tightly controlled. However, deleting degrading reactions from IMP to AMP and GMP significantly increased intracellular IMP levels. Due to the complexity of this pathway further degradation from IMP to the corresponding nucleobase drastically increased suggesting additional targets for future strain optimization.

Characterization of GCY1 in Saccharomyces cerevisiae by metabolic profiling

AIMS

The analytical study of intracellular (IC) metabolites has developed with advances in chromatography-linked mass spectrometry and fast sampling procedures. We applied the IC metabolite analysis to characterize the role of GCY1 in the glycerol (GLY) catabolic pathway in Saccharomyces cerevisiae.

METHODS AND RESULTS

Strains with disrupted or overexpressing GLY catabolic genes such as GCY1, DAK1 and DAK2 were constructed. The strains were cultivated under different aeration conditions and quickly quenched using a novel rapid sampling port. IC concentrations of GLY, dihydroxyacetone (DHA), glycerol 3-phosphate and dihydroxyacetone phosphate were analysed in the strains by gas chromatography/mass spectrometry. DHA was not detected in the gcy1 gene-disrupted strain but accumulated 225.91 μmol g DCW(-1) in a DHA kinase gene-deficient strain under micro-aerobic conditions. Additionally, a 16.1% increase in DHA occurred by overexpressing GCY1 in the DHA kinase-deficient strain.

CONCLUSIONS

Metabolic profiling showed that the GCY1 gene product functions as a GLY dehydrogenase in S. cerevisiae, particularly under micro-aerobic conditions.

SIGNIFICANCE AND IMPACT OF THE STUDY

Metabolic profiling of the GLY dissimilation pathway was successfully demonstrated in S. cerevisiae, and the function of GCY1 was explained by the results.

Scheffersomyces stipitis: a comparative systems biology study with the Crabtree positive yeast Saccharomyces cerevisiae

BACKGROUND

Scheffersomyces stipitis is a Crabtree negative yeast, commonly known for its capacity to ferment pentose sugars. Differently from Crabtree positive yeasts such as Saccharomyces cerevisiae, the onset of fermentation in S. stipitis is not dependent on the sugar concentration, but is regulated by a decrease in oxygen levels. Even though S. stipitis has been extensively studied due to its potential application in pentoses fermentation, a limited amount of information is available about its metabolism during aerobic growth on glucose. Here, we provide a systems biology based comparison between the two yeasts, uncovering the metabolism of S. stipitis during aerobic growth on glucose under batch and chemostat cultivations.

RESULTS

Starting from the analysis of physiological data, we confirmed through 13C-based flux analysis the fully respiratory metabolism of S. stipitis when growing both under glucose limited or glucose excess conditions. The patterns observed showed similarity to the fully respiratory metabolism observed for S. cerevisiae under chemostat cultivations however, intracellular metabolome analysis uncovered the presence of several differences in metabolite patterns. To describe gene expression levels under the two conditions, we performed RNA sequencing and the results were used to quantify transcript abundances of genes from the central carbon metabolism and compared with those obtained with S. cerevisiae. Interestingly, genes involved in central pathways showed different patterns of expression, suggesting different regulatory networks between the two yeasts. Efforts were focused on identifying shared and unique families of transcription factors between the two yeasts through in silico transcription factors analysis, suggesting a different regulation of glycolytic and glucoenogenic pathways.

CONCLUSIONS

The work presented addresses the impact of high-throughput methods in describing and comparing the physiology of Crabtree positive and Crabtree negative yeasts. Based on physiological data and flux analysis we identified the presence of one metabolic condition for S. stipitis under aerobic batch and chemostat cultivations, which shows similarities to the oxidative metabolism observed for S. cerevisiae under chemostat cultivations. Through metabolome analysis and genome-wide transcriptomic analysis several differences were identified. Interestingly, in silico analysis of transciption factors was useful to address a different regulation of mRNAs of genes involved in the central carbon metabolism. To our knowledge, this is the first time that the metabolism of S. stiptis is investigated in details and is compared to S. cerevisiae. Our study provides useful results and allows for the possibility to incorporate these data into recently developed genome-scaled metabolic, thus contributing to improve future industrial applications of S. stipitis as cell factory.

'Domino' systems biology and the 'A' of ATP

We develop a strategic 'domino' approach that starts with one key feature of cell function and the main process providing for it, and then adds additional processes and components only as necessary to explain provoked experimental observations. The approach is here applied to the energy metabolism of yeast in a glucose limited chemostat, subjected to a sudden increase in glucose. The puzzles addressed include (i) the lack of increase in adenosine triphosphate (ATP) upon glucose addition, (ii) the lack of increase in adenosine diphosphate (ADP) when ATP is hydrolyzed, and (iii) the rapid disappearance of the 'A' (adenine) moiety of ATP. Neither the incorporation of nucleotides into new biomass, nor steady de novo synthesis of adenosine monophosphate (AMP) explains. Cycling of the 'A' moiety accelerates when the cell's energy state is endangered, another essential domino among the seven required for understanding of the experimental observations. This new domino analysis shows how strategic experimental design and observations in tandem with theory and modeling may identify and resolve important paradoxes. It also highlights the hitherto unexpected role of the 'A' component of ATP.