Two strings to the systems biology bow: co-extracting the metabolome and proteome of yeast

Experimental samples are valuable and can represent a significant investment in time and resources. It is highly desirable at times to obtain as much information as possible from a single sample. This is especially relevant for systems biology approaches in which several ‘omics platforms are studied simultaneously. Unfortunately, each platform has a particular extraction methodology which increases sample number and sample volume requirements when multiple ‘omics are analyzed. We evaluated the integration of a yeast extraction method; specifically we explored whether fractions from a single metabolite extraction could be apportioned to multiple downstream ‘omics analytical platforms. In addition, we examined how variations to a chloroform/methanol yeast metabolite extraction regime influence metabolite recoveries. We show that protein suitable for proteomic analysis can be recovered from a metabolite extraction and that recovery of lipids, while reproducible, are not wholly quantitative. Higher quenching solution temperatures (?30 °C) can be used without significant leakage of intracellular metabolites when lower fermentation temperatures (20 °C) are employed. However, extended residence time in quenching solution, in combination with vigorous washing of quenched cell pellets, leads to extensive leakage of intracellular metabolites. Finally, there is minimal difference in metabolite amounts obtained when metabolite extractions are performed at 4 °C compared to extractions at ?20 °C. The evaluated extraction method delivers material suitable for metabolomic and proteomic analyses from the same sample preparation.     

Trend analysis of metabonomics and systematic review of metabonomics-derived cancer marker metabolites

In this paper, trend analyses were performed to compare the different ‘omic’ technologies and the different analytical platforms and biological matrices exploited in metabonomic studies. While common and differential marker metabolites had been identified using various analytical platforms in metabonomics, little research was directed to review and consolidate marker metabolites in each disease state. A systematic review of metabonomics-derived marker metabolites in different cancers was performed to understand the significance of metabonomics in elucidating cancer biochemistry. The biological pathways associated with the cancer marker metabolites were further correlated to the pathology of cancers. Our trend analyses indicated that metabonomic publications increased exponentially in recent years, with nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography/mass spectrometry (LC/MS) being the most popular analytical platforms while blood, urine and tissue are the most commonly profiled biological matrices. Based on the consolidated cancer marker metabolites, it is reinforced that different cancers possess some common and yet distinct metabolic phenotypes, exhibiting numerous perturbed biochemical pathways related to their needs to support cell growth and proliferation and facilitate cancer cell survival.     

基于液质联用的莱茵衣藻极性甘油酯组定性定量分析

以模式藻株莱茵衣藻(Chlamydomonas reinhardtii)为材料, 基于液质联用技术对其极性甘油酯组进行定性定量分析。通过综合利用UPLC-ESI-Q-Trap/MS的一级质谱扫描(中性丢失或母离子扫描)及UPLC-ESI-Orbitrap/MS²的二级碎片信息扫描, 共鉴定出109种极性甘油酯分子; 再通过外标法利用UPLC-ESI-Q-Trap/MS在多级反应监测模式下对各分子进行靶向定量分析。结果表明, 莱茵衣藻的极性脂以糖脂MGDG、DGDG及甜菜碱脂DGTS为主, 所有极性脂的分子组成表明, DGDG、SQDG、DGTS及PI是C18脂肪酸的去饱和载体。该研究利用液质联用技术建立了莱茵衣藻极性甘油酯组的结构图谱及定量分析技术平台, 为微藻极性脂生物学功能及脂质代谢研究奠定了基础。     

GC/MS based metabolomics: development of a data mining system for metabolite identification by using soft independent modeling of class analogy (SIMCA)

Background  

The goal of metabolomics analyses is a comprehensive and systematic understanding of all metabolites in biological samples. Many useful platforms have been developed to achieve this goal. Gas chromatography coupled to mass spectrometry (GC/MS) is a well-established analytical method in metabolomics study, and 200 to 500 peaks are routinely observed with one biological sample. However, only ~100 metabolites can be identified, and the remaining peaks are left as "unknowns".     

Process for the integrated extraction, identification and quantification of metabolites, proteins and RNA to reveal their co-regulation in biochemical networks

A novel extraction protocol is described with which metabolites, proteins and RNA are sequentially extracted from the same sample, thereby providing a convenient procedure for the analysis of replicates as well as exploiting the inherent biological variation of independent samples for multivariate data analysis. A detection of 652 metabolites, 297 proteins and clear RNA bands in a single Arabidopsis thaliana leaf sample was validated by analysis with gas chromatography coupled to a time of flight mass spectrometer for metabolites, two-dimensional liquid chromatography coupled to mass spectrometry for proteins, and Northern blot analysis for RNA. A subset of the most abundant proteins and metabolites from replicate analysis of different Arabidopsis accessions was merged to form an integrative dataset allowing both classification of different genotypes and the unbiased analysis of the hierarchical organization of proteins and metabolites within a real biochemical network.     

An improved extraction method enables the comprehensive analysis of lipids,proteins, metabolites and phytohormones from a single sample of leaf tissue under water‐deficit stress

Phytohormones play essential roles in the regulation of growth and development in plants. Plant hormone profiling is therefore essential to understand developmental processes and the adaptation of plants to biotic and/or abiotic stresses. Interestingly, commonly used hormone extraction and profiling methods do not adequately resolve other molecular entities, such as polar metabolites, lipids, starch and proteins, which would be required to comprehensively describe the continuing biological processes at a systematic level. In this article we introduce an updated version of a previously published liquid:liquid metabolite extraction protocol, which not only allows for the profiling of primary and secondary metabolites, lipids, starch and proteins, but also enables the quantitative analysis of the major plant hormone classes, including abscisic acid, auxins, cytokinins, jasmonates and salicylates, from a single sample aliquot. The optimization of the method, which uses the introduction of acidified water, enabling the complete purification of major plant hormones into the organic (methyl‐tert‐butyl‐ether) phase, eliminated the need for solid‐phase extraction for sample clean‐up, and therefore reduces both sampling time and cost. As a proof‐of‐concept analysis, Arabidopsis thaliana plants were subjected to water‐deficit stress, which were then profiled for hormonal, metabolic, lipidomic and proteomic changes. Surprisingly, we determined not only previously described molecular changes but also significant changes regarding the breakdown of specific galactolipids, followed by the substantial accumulation of unsaturated fatty‐acid derivatives and diverse jasmonates in the course of adaptation to water‐deficit stress.     

Comparison of 1D and 2D NMR spectroscopy for metabolic profiling

High-resolution, liquid state nuclear magnetic resonance (NMR) spectroscopy is a popular platform for metabolic profiling because the technique is nondestructive, quantitative, reproducible, and the spectra contain a wealth of biochemical information. Because of the large dynamic range of metabolite concentrations in biofluids, statistical analyses of one-dimensional (1D) proton NMR data tend to be biased toward selecting changes in more abundant metabolites. Although two-dimensional (2D) proton-proton experiments can alleviate spectral crowding, they have been mainly used for structural determination. In this study, 2D total correlation spectroscopy NMR was used to compare the global metabolic profiles of urine obtained from wild-type and Abcc6-knockout mice. The 2D data were compared to an improved 1D experiment in which signal contributions from macromolecules and the urea peak have been spectroscopically removed for more accurate quantitation of low-abundance metabolites. Although statistical models from both 1D and 2D data could differentiate samples acquired from the two groups of mice, only the 2D spectra allowed the characterization of statistically relevant changes in the low-abundance metabolites. While acquisition of the 2D data require more time, the data obtained resulted in a more meaningful and comprehensive metabolic profile, aided in metabolite identifications, and minimized ambiguities in peak assignments.     

Determination of oxalyl thiolesters, N-oxalylcysteine and N-oxalylcysteamine in biological materials

A convenient method is described for the quantitative analysis of oxalyl thiolesters (OTEs), a newly discovered class of mammalian metabolites, in biological samples. By this particular technique the total concentration of all OTEs in the sample is determined. The method involves first reacting the biological material with cysteamine (2-aminoethanethiol) or cysteine under conditions that convert OTEs quantitatively to N-oxalylcysteamine (or N-oxalylcysteine), followed by reaction with monobromobimane to give a highly fluorescent derivative that is analyzed by reversed-phase ion-pair chromatography, with tetrabutylammonium ion as the counterion and N-(2-mercaptopropionyl)glycine as an internal standard. The method is capable of detecting as little as 0.6 pmol of the bimane derivative of the N-oxalyl compound in a single HPLC injection. The application of this method has led to the discovery that not only OTEs but also N-oxalylcysteine and N-oxalylcysteamine are normal mammalian metabolites. In various rat tissues the OTE concentration ranges up to 65 nmol/g (wet wt), the N-oxalylcysteine concentration is approximately 10 nmol/g, and the N-oxalylcysteamine concentration is 0-3 nmol/g.     

A Strategy for Sensitive,Large Scale Quantitative Metabolomics

Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously.  Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases.     

Differential mobility analysis-mass spectrometry coupled to XCMS algorithm as a novel analytical platform for metabolic profiling

The development of additional analytical instruments is of great interest to expand metabolome coverage. Differential mobility analyzers (DMAs) are a type of ion mobility spectrometers that can be straightforwardly interfaced with commercial mass spectrometers. In this pilot study, we explored the capabilities of an ion mobility-mass spectrometry platform, based on interfacing a Differential Mobility Analyzer with a commercial quadrupole time of-flight mass spectrometer (DMA-QTOF), to phenotype the metabolic urinary fingerprint of a cohort of prostate cancer patients (n = 8) and a group of healthy counterparts (n = 20). The resolving power of the DMA and the QTOF was ～55 and ～6,500, respectively. The transmission efficiency of the DMA was 50%. We illustrate the benefits of incorporating the DMA through the separation of isobaric species according to their electrical mobility, which were not fully resolved by the high resolution QTOF. In addition, we show that the bidimensional electrical mobility-mass spectra obtained can be successfully processed with the XCMS routine, extending its potential to ion mobility-mass spectrometry-based platforms. Data mining with XCMS revealed seven features significantly down-regulated in cancer patients (P < 0.05). These peaks were the input of principal component analysis, showing a clear separation tendency from prostate cancer patients and healthy controls. NIST MS search algorithm was used to classify the samples according to their class, with a resulting 75% sensitivity and 80% specificity. We pursued further fragmentation experiments for structural elucidation of the most discriminant metabolites, thereby illustrating the full potential of this analytical platform for the task. In summary, DMA-MS/MS provides an additional level of separation as compared to traditional mass spectrometry-based methods, thereby increasing the array of multi-analytical platforms available to global metabolite profiling and metabolite identification.     

On-line sample extraction and enrichment of non-steroidal anti-inflammatory drugs by pre-column in capillary liquid chromatography mass spectrometry

A rapid and sensitive analytical method has been developed for the simultaneous determination of 16 non-steroidal anti-inflammatory drugs (NSAIDs) in human plasma by capillary liquid chromatography (LC) and quadrupole mass spectrometry with electrospray ionization operated in the negative ion mode. The sample clean-up and enrichment on a pre-column were accomplished on-line to improve the sensitivity. This method greatly reduced sample preparation time and sample volume compared with off-line sample extraction methods and conventional LC methods, respectively. The recoveries of NSAIDs from human plasma were 56.7-96.9%. The total analytical time for a single analytical run was approximately 15 min. The detection limits of NSAIDs were 0.001-0.075 microg ml(-1) using a selected ion monitoring mode.     

Multistep mass tagging coupled with 2D LC-MS--an approach to increasing the number of identified proteins.

Identification of large numbers of proteins from complex biological samples is a continuing challenge in the area of quantitative proteomics. We introduce here a simple and reliable multistep mass tagging technique using our recently developed solid phase mass tagging reagents. When coupled with two-dimensional liquid chromatography/nano-electrospray ionization ion trap mass spectrometry (2D-LC/nano-ESI-MS), this method allows enhanced protein identification when tested on samples from prokaryotic and eukaryotic sources. The proteome of Escherichia coli D21 grown to either mid-exponential or stationary phase, and the membrane proteome from established breast cancer cell lines BT474 and MCF7 were used as model systems in these experiments. In both experiments, the numbers of total identified proteins are at least twice the numbers identified from a single tagging cycle. The sample complexity can be effectively reduced with corresponding increases in protein identification using the multistep method. The strategy described here represents a potentially powerful technique for large-scale qualitative and quantitative proteome research.     

Chromatographic and capillary electrophoretic methods for the analysis of nicotinic acid and its metabolites

Methods for the assay of nicotinic acid (NiAc) and its metabolites in biological fluids using high-performance liquid chromatography (HPLC) and capillary electrophoresis (CE) are reviewed. Most of the references cited in this review concern HPLC methods. A few CE methods that have been recently reported are also included. As these compounds are relatively polar and have a wide range of physico-chemical properties, the sample pre-treatment or clean-up process prior to analysis is included. Most HPLC methods using an isocratic elution system allow determination of a single or few metabolites, but gradient HPLC methods enable simultaneous determination of five to eight compounds. Simultaneous determination of NiAc including many metabolites in a single run can be achieved by CE. We also discuss the pharmacokinetics of NiAc and some of its metabolites.     

Mass-spectrometric profiling of porphyrins in complex biological samples with fundamental,toxicological, and pharmacological applications

Rapid, high-throughput, and quantitative evaluations of biological metabolites in complex milieu are increasingly required for biochemical, toxicological, pharmacological, and environmental analyses. They are also essential for the development, testing, and improvement of new commercial chemical products. We demonstrate the application of ultra-high performance liquid chromatography-mass spectrometry (uHPLC-MS), employing an electrospray ionization source and a high accuracy quadrupole time-of-flight mass analyzer, for the identification and quantification of a series of porphyrin derivatives in liver: a matrix of particular relevance in toxicological or pharmacological testing. Exact mass is used to identify and quantify the metabolites. Chromatography enhances sensitivity and alleviates potential saturation issues by fanning out the contents of a complex sample before their injection into the spectrometer, but is not strictly necessary for the analysis. Extraction and sample treatment procedures are evaluated and matrix effects discussed. Using this method, the known mechanism of action of a well-characterized porphyrinogenic agent was verified in liver extracts from treated rats. The method was also validated for use with bacterial cells. This exact-mass method uses workhorse instruments available in many laboratories, providing a highly flexible alternative to existing HPLC- and MS/MS-based approaches for the simultaneous analysis of multiple compounds in biological media.     

High-performance liquid chromatographic analysis of estradiol-17β and metabolites in biological media

A method was developed to resolve radiolabeled estradiol-17β and its various metabolites in biological fluids and tissues. After a rapid initial clean-up step, samples were analyzed with the sequential use of reversed-phase and normal-phase high-performance liquid chromatographic systems. Approximately 25 conjugated and non-conjugated standards could be resolved by the combined use of six systems. Radiolabeled parent compound and metabolites from biological samples were separated and tentatively identified by comparing their retention times to those of known standards. The method was found to be reproducible and quantitative for the majority of the estrogens and their conjugates, and semiquantitative for some of the more polar and di-conjugated estrogens.     

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry (UPLC-HRMS)

Here we present a workflow to analyze the metabolic profiles for biological samples of interest including; cells, serum, or tissue. The sample is first separated into polar and non-polar fractions by a liquid-liquid phase extraction, and partially purified to facilitate downstream analysis. Both aqueous (polar metabolites) and organic (non-polar metabolites) phases of the initial extraction are processed to survey a broad range of metabolites. Metabolites are separated by different liquid chromatography methods based upon their partition properties. In this method, we present microflow ultra-performance (UP)LC methods, but the protocol is scalable to higher flows and lower pressures. Introduction into the mass spectrometer can be through either general or compound optimized source conditions. Detection of a broad range of ions is carried out in full scan mode in both positive and negative mode over a broad m/z range using high resolution on a recently calibrated instrument. Label-free differential analysis is carried out on bioinformatics platforms. Applications of this approach include metabolic pathway screening, biomarker discovery, and drug development.     

Liquid chromatography-mass spectrometry/mass spectrometry method development for drug metabolism studies: Examining lipid matrix ionization effects in plasma

Glycerophosphocholines (GPCho's) are known to cause liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) matrix ionization effects during the analysis of biological samples (i.e. blood, plasma). We have developed a convenient new method, which we refer to as "in-source multiple reaction monitoring" (IS-MRM), for detecting GPCho's during LC-MS/MS method development. The approach uses high energy in-source collisionally induced dissociation (CID) to yield trimethylammonium-ethyl phosphate ions (m/z 184), which are formed from mono- and disubstituted GPCho's. The resulting ion is selected by the first quadrupole (Q1), passed through the collision cell (Q2) in the presence of collision gas at low energy to minimize fragmentation, and m/z 184 selected by the third quadrupole. This approach can be combined with standard multiple reaction monitoring (MRM) transitions with little compromise in sensitivity during method development and sample analysis. Hence, this approach was used to probe ionization matrix effects in plasma samples. The resulting information was employed to develop LC-MS/MS analyses for drugs and their metabolites with cycle times less than 5 min.     

Semi-targeted metabolomic approaches to validate potential markers of health for micronutrients: analytical perspectives

Recommended dietary allowances for micronutrients fluctuate noticeably within European Union countries. The Network of Excellence EURRECA (EURopean micronutrient RECommendations Aligned) aims at harmonising micronutrient intake recommendations through population groups. The lack of proper markers of status for some micronutrients limits progress in this area: metabolomics could help identifying such new markers. We developed an original metabolomic strategy in order to monitor the largest fraction of a list of >270 metabolites known to be influenced by the micronutrients of interest. To improve the coverage of these metabolites in plasma, a multi platform approach was performed using both liquid and gas chromatography coupled to mass spectrometry. A sample preparation protocol based on a three-step plasma fractionation has been set up, using both liquid and solid phase extractions. Four fractions were obtained containing respectively polar metabolites, neutral lipids, free fatty acids and polar lipids. Recoveries were determined using spiked plasma samples, and the advantages and drawbacks of the fractionation method compared to a commonly used single preparation step method were investigated in terms of metabolites detection and robustness. Fractionation improved coverage of the endogenous metabolome more than twice in terms of extracted features, allowing to identify 90?metabolites.     

Comprehensive proteome analysis of ovarian cancers using liquid phase separation, mass mapping and tandem mass spectrometry: a strategy for identification of candidate cancer biomarkers

A two-dimensional (2-D) liquid phase separation method, liquid isoelectric focusing followed by nonporous reversed-phase high performance liquid chromatography (HPLC), was used to separate proteins from human ovarian epithelial whole cell lysates. HPLC eluent was interfaced on-line to an electrospray ionization (ESI) time of flight (TOF) mass spectrometer to obtain accurate intact protein molecular weights (Mr). 2-D protein expression maps were generated displaying protein isoelectric point (pI) versus intact protein Mr. Resulting 2-D images effectively displayed quantitative differential protein expression in ovarian cancer cells versus non-neoplastic ovarian epithelial cells. Protein peak fractions were collected from the HPLC eluent, enzymatically digested, and analyzed by matrix-assisted laser desorption/ionization (MALDI) TOF-mass spectrometry (MS) peptide mass fingerprinting and by MALDI-quadrupole TOF tandem mass spectrometry peptide sequencing. Interlysate comparisons of differential protein expression between two ovarian adenocarcinoma cell lines, ES2 and MDAH-2774, and ovarian surface epithelial cells was performed. Five pI fractions from each sample were selected for comparative study and over 300 unique proteins were positively identified from the 2-D liquid expression maps using MS, which covered around 60% of proteins detected by on-line ESI-TOF-MS. This represents one of the most comprehensive proteomic analyses of ovarian cancer samples to date. Protein bands with significant up- or down-regulation in one cell line versus another as viewed in the 2-D expression maps were identified. This strategy may prove useful in identifying novel ovarian cancer marker proteins.