液相质谱联用的代谢组方法优化及其在蓝细菌分析中的应用

为了准确鉴定光合蓝细菌中的各种代谢物,需要对基于液相色谱–质谱联用仪(LC-MS)的代谢组学分析方法进行有针对性的优化。本研究选取了24种涉及中心碳代谢和能量代谢的代谢物作为LC-MS的检测目标,获得了每个代谢物的最适色谱分离条件和质谱参数;同时以光合蓝细菌Synechocystis sp.PCC6803为主要对象,针对性地优化了样品前处理条件,结果显示适当延长梯度洗脱顺序表的时间并将流速设为0.2 m L/min可以得到最佳的分离效果,同时选择80%(V/V)甲醇(-80?C)作为代谢物萃取剂。分析结果证明这一代谢组分析技术可以成功地应用到光合蓝细菌的研究中。     

Towards high-throughput metabolomics using ultrahigh-field Fourier transform ion cyclotron resonance mass spectrometry

With unmatched mass resolution, mass accuracy, and exceptional detection sensitivity, Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) has the potential to be a powerful new technique for high-throughput metabolomic analysis. In this study, we examine the properties of an ultrahigh-field 12-Tesla (12T) FTICR-MS for the identification and absolute quantitation of human plasma metabolites, and for the untargeted metabolic fingerprinting of inbred-strain mouse serum by direct infusion (DI). Using internal mass calibration (mass error ≤1 ppm), we determined the rational elemental compositions (incorporating unlimited C, H, N and O, and a maximum of two S, three P, two Na, and one K per formula) of approximately 250 out of 570 metabolite features detected in a 3-min infusion analysis of aqueous extract of human plasma, and were able to identify more than 100 metabolites. Using isotopically-labeled internal standards, we were able to obtain excellent calibration curves for the absolute quantitation of choline with sub-pmol sensitivity, using 500 times less sample than previous LC/MS analyses. Under optimized serum dilution conditions, chemical compounds spiked into mouse serum as metabolite mimics showed a linear response over a 600-fold concentration range. DI/FTICR-MS analysis of serum from 26 mice from 2 inbred strains, with and without acute trichloroethylene (TCE) treatment, gave a relative standard deviation (RSD) of 4.5%. Finally, we extended this method to the metabolomic fingerprinting of serum samples from 49 mice from 5 inbred strains involved in an acute alcohol toxicity study, using both positive and negative electrospray ionization (ESI). Using these samples, we demonstrated the utility of this method for high-throughput metabolomics, with more than 400 metabolites profiled in only 24 h. Our experiments demonstrate that DI/FTICR-MS is well-suited for high-throughput metabolomic analysis. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Accurate Mass Measurements Using MALDI-TOF with Delayed Extraction

Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry is now an essential tool in biopolymer analysis. Sensitivity and mass range are unsurpassed, but mass measurement accuracy and resolution have been limited. With delayed extraction and a reflecting analyzer, mass measurements using MALDI-TOF can be made with an accuracy of a few parts per million (ppm). It is possible to distinguish Lys from Gln in peptides, and to determine the elemental composition of smaller molecules (mass 100–500). In database searching strategies, a smaller mass window, resulting from an increase in mass accuracy, greatly decreases the number of possible candidates. Mass measurement accuracy with errors less than 5 ppm is demonstrated on a mixture of 12 peptides ranging in mass from ca. 900 to 3700 Da. Mass measurements on 13 peaks in an unseparated tryptic digest of myoglobin gave results with an overall average error less than 3.5 ppm, with a maximum error of 7 ppm.     

Metabolomic database annotations via query of elemental compositions: Mass accuracy is insufficient even at less than 1 ppm

Background  

Metabolomic studies are targeted at identifying and quantifying all metabolites in a given biological context. Among the tools used for metabolomic research, mass spectrometry is one of the most powerful tools. However, metabolomics by mass spectrometry always reveals a high number of unknown compounds which complicate in depth mechanistic or biochemical understanding. In principle, mass spectrometry can be utilized within strategies of de novo structure elucidation of small molecules, starting with the computation of the elemental composition of an unknown metabolite using accurate masses with errors <5 ppm (parts per million). However even with very high mass accuracy (<1 ppm) many chemically possible formulae are obtained in higher mass regions. In automatic routines an additional orthogonal filter therefore needs to be applied in order to reduce the number of potential elemental compositions. This report demonstrates the necessity of isotope abundance information by mathematical confirmation of the concept.     

An innovative approach to grape metabolomics: stilbene profiling by suspect screening analysis

Suspect screening analysis is a targeted metabolomics approach in which identification of compounds relies on specific available information such as their molecular formula and isotopic pattern. This method was applied to the study of grape metabolomics with an UPLC/MS high-resolution Q-TOF mass spectrometer (nominal resolution 40,000) coupled with a Jet Stream ionization source. The present paper describes the detailed qualitative and quantitative study of grape stilbenes, the principal polyphenols associated with the beneficial effects of drinking wine. For identification of compounds, a new database was expressly constructed from the molecular information of potential metabolites of grape and wine from the literature and other electronic databases. Currently, GrapeMetabolomics contains about a thousand putative grape compounds. If untargeted analysis of a sample provides identification of a new compound with a sufficiently confident score, it is added to the database. Thus, by increasing the number of samples studied, GrapeMetabolomics can be expanded. This method is effective for identification of the molecular formulae of several hundred metabolites in two runs (positive and negative ionization) with minimal sample preparation, and can also be used to analyse some single classes of compounds involved in cell and tissue metabolism. With this approach, a total of 18 stilbene derivatives was identified in two grape samples (Raboso Piave and Primitivo) on the basis of accurate mass measurements and isotopic patterns, and identification was confirmed by MS/MS analysis. The approach can also potentially be applied to the metabolomics of other plant varieties.     

Mass spectrometry imaging with high resolution in mass and space

Mass spectrometry (MS) imaging links molecular information and the spatial distribution of analytes within a sample. In contrast to most histochemical techniques, mass spectrometry imaging can differentiate molecular modifications and does not require labeling of targeted compounds. We have recently introduced the first mass spectrometry imaging method that provides highly specific molecular information (high resolution and accuracy in mass) at cellular dimensions (high resolution in space). This method is based on a matrix-assisted laser desorption/ionization (MALDI) imaging source working at atmospheric pressure which is coupled to an orbital trapping mass spectrometer. Here, we present a number of application examples and demonstrate the benefit of ‘mass spectrometry imaging with high resolution in mass and space.’ Phospholipids, peptides and drug compounds were imaged in a number of tissue samples at a spatial resolution of 5–10 μm. Proteins were analyzed after on-tissue tryptic digestion at 50-μm resolution. Additional applications include the analysis of single cells and of human lung carcinoma tissue as well as the first MALDI imaging measurement of tissue at 3 μm pixel size. MS image analysis for all these experiments showed excellent correlation with histological staining evaluation. The high mass resolution (R = 30,000) and mass accuracy (typically 1 ppm) proved to be essential for specific image generation and reliable identification of analytes in tissue samples. The ability to combine the required high-quality mass analysis with spatial resolution in the range of single cells is a unique feature of our method. With that, it has the potential to supplement classical histochemical protocols and to provide new insights about molecular processes on the cellular level.     

Postexperiment monoisotopic mass filtering and refinement (PE-MMR) of tandem mass spectrometric data increases accuracy of peptide identification in LC/MS/MS

Methods for treating MS/MS data to achieve accurate peptide identification are currently the subject of much research activity. In this study we describe a new method for filtering MS/MS data and refining precursor masses that provides highly accurate analyses of massive sets of proteomics data. This method, coined "postexperiment monoisotopic mass filtering and refinement" (PE-MMR), consists of several data processing steps: 1) generation of lists of all monoisotopic masses observed in a whole LC/MS experiment, 2) clusterization of monoisotopic masses of a peptide into unique mass classes (UMCs) based on their masses and LC elution times, 3) matching the precursor masses of the MS/MS data to a representative mass of a UMC, and 4) filtration of the MS/MS data based on the presence of corresponding monoisotopic masses and refinement of the precursor ion masses by the UMC mass. PE-MMR increases the throughput of proteomics data analysis, by efficiently removing "garbage" MS/MS data prior to database searching, and improves the mass measurement accuracies (i.e. 0.05 +/- 1.49 ppm for yeast data (from 4.46 +/- 2.81 ppm) and 0.03 +/- 3.41 ppm for glycopeptide data (from 4.8 +/- 7.4 ppm)) for an increased number of identified peptides. In proteomics analyses of glycopeptide-enriched samples, PE-MMR processing greatly reduces the degree of false glycopeptide identification by correctly assigning the monoisotopic masses for the precursor ions prior to database searching. By applying this technique to analyses of proteome samples of varying complexities, we demonstrate herein that PE-MMR is an effective and accurate method for treating massive sets of proteomics data.     

The yeast metabolome addressed by electrospray ionization mass spectrometry: Initiation of a mass spectral library and its applications for metabolic footprinting by direct infusion mass spectrometry

Mass spectrometry (MS) has been a major driver for metabolomics, and gas chromatography (GC)-MS has been one of the primary techniques used for microbial metabolomics. The use of liquid chromatography (LC)-MS has however been limited, but electrospray ionization (ESI) is very well suited for ionization of microbial metabolites without any previous derivatization needed. To address the capabilities of ESI-MS in detecting the metabolome of Saccharomyces cerevisiae, the in silico metabolome of this organism was used as a template to present a theoretical metabolome. This showed that in combination with the specificity of MS up to 84% of the metabolites can be identified in a high mass accuracy ESI-spectrum. A total of 66 metabolites were systematically analyzed by positive and negative ESI-MS/MS with the aim of initiating a spectral library for ESI of microbial metabolites. This systematic analysis gave insight into the ionization and fragmentation characteristics of the different metabolites. With this insight, a small study of metabolic footprinting with ESI-MS demonstrated that biological information can be extracted from footprinting spectra. Statistical analysis of the footprinting data revealed discriminating ions, which could be assigned using the in silico metabolome. By this approach metabolic footprinting can advance from a classification method that is used to derive biological information based on guilt-by-association, to a tool for extraction of metabolic differences, which can guide new targeted biological experiments. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Characterization of a high field Orbitrap mass spectrometer for proteome analysis

The field of proteomics continues to be driven by improvements in analytical technology, notably in peptide separation, quantitative MS, and informatics. In this study, we have characterized a hybrid linear ion trap high field Orbitrap mass spectrometer (Orbitrap Elite) for proteomic applications. The very high resolution available on this instrument allows 95% of all peptide masses to be measured with sub‐ppm accuracy that in turn improves protein identification by database searching. We further confirm again that mass accuracy in tandem mass spectra is a valuable parameter for improving the success of protein identification. The new CID rapid scan type of the Orbitrap Elite achieves similar performance as higher energy collision induced dissociation fragmentation and both allow the identification of hundreds of proteins from as little as 0.1 ng of protein digest on column. The new instrument outperforms its predecessor the Orbitrap Velos by a considerable margin on each metric assessed that makes it a valuable and versatile tool for MS‐based proteomics.     

Metabolomic profiling reveals bacterial metabolic adaptation strategies and new metabolites

How has metabolomics helped our understanding of infectious diseases? With the threat of antimicrobial resistance to human health around the world, metabolomics has emerged as a powerful tool to comprehensively characterize metabolic pathways to identify new drug targets. However, its output is constrained to known metabolites and their metabolic pathways. Recent advances in instrumentation, methodologies, and computational mass spectrometry have accelerated the use of metabolomics to understand pathogen–host metabolic interactions. This short review discusses a selection of recent publications using metabolomics in infectious/bacterial diseases. These studies unravel the links between metabolic adaptations to environments and host metabolic responses. Moreover, they highlight the importance of enzyme function and metabolite characterization in identifying new drug targets and biomarkers, as well as precision medicine in monitoring therapeutics and diagnosing diseases.     

Accurate determination of the molecular weight of the major surface layer protein isolated from Clostridium thermosaccharolyticum by time-of-flight mass spectrometry.

Matrix-assisted laser desorption with concomitant ionization, in combination with a linear time-of-flight mass spectrometer, was used to analyze underivatized and hard-to-solubilize surface layer proteins and glycoproteins by depositing them on top of a microcrystalline layer of the matrix alpha-cyano-4-hydroxycinnamic acid. Use of this special sample preparation technique allowed the first successful desorption-ionization of intact surface layer proteins and accurate determination of their molecular weights by mass spectrometry. The molecular mass of the monomeric subunit of the major surface layer protein isolated from Clostridium thermosaccharolyticum E207-71 was determined to be 75,621 +/- 81 Da. The obtainable mass accuracy of the technique is conservatively considered to be within +/- 0.2%. This result deviates from that given by sodium dodecyl sulfate-polyacrylamide gel electrophoresis by approximately 7.4 kDa because this method is strongly affected and biased by the three-dimensional structure of this type of surface protein. With the apparent advantages of unsurpassed mass accuracy, low dependence on the physicochemical properties of the surface layer proteins, and high sensitivity, it can be concluded that a linear time-of-flight instrument combined with UV matrix-assisted laser desorption with concomitant ionization is better suited for molecular weight determination than is gel electrophoresis.     

Stable isotope-resolved metabolomics (SIRM) in cancer research with clinical application to nonsmall cell lung cancer

Metabolomics provides a readout of the state of metabolism in cells or tissue and their responses to external perturbations. For this reason, the approach has great potential in clinical diagnostics. Clinical metabolomics using stable isotope resolved metabolomics (SIRM) for pathway tracing represents an important new approach to obtaining metabolic parameters in human cancer subjects in situ. Here we provide an overview of the technology development of labeling from cells in culture and mouse models. The high throughput analytical methods NMR and mass spectrometry, especially Fourier transform ion cyclotron resonance, for analyzing the resulting metabolite isotopomers and isotopologues are described with examples of applications in cancer biology. Special technical considerations for clinical applications of metabolomics using stable isotope tracers are described. The whole process from concept to analysis will be exemplified by our on-going study of nonsmall cell lung cancer (NSCLC) metabolomics. This powerful new approach has already provided important new insights into metabolic adaptations in lung cancer cells, including the upregulation of anaplerosis via pyruvate carboxylation in NSCLC.     

关于组学大数据背景下《微生物学》教材框架的思考

微生物学是生物学的重要内容,是全国高等院校生物学专业或相关专业的本科生必修的一门核心基础课,其主要任务是给学生提供基础的、系统的、前沿的微生物学知识和理论。随着高通量测序、质谱、芯片等高通量技术的快速发展,生命科学领域快速进入了以海量多元组学(基因组学、转录组学、蛋白质组学、免疫组学、代谢组学等)数据为特征的大数据时代,而这势必会对微生物学教材已有的内容产生冲击和补充。本文对如何在组学大数据背景下对国内经典的微生物学教材进行改革,将目前最具突破性的组学成果整合到已有的教材框架中或革新现有教材框架进行了初步探讨。     

Increased protein identification capabilities through novel tandem MS calibration strategies

High mass measurement accuracy is critical for confident protein identification and characterization in proteomics research. Fourier transform ion cyclotron resonance (FTICR) mass spectrometry is a unique technique which can provide unparalleled mass accuracy and resolving power. However, the mass measurement accuracy of FTICR-MS can be affected by space charge effects. Here, we present a novel internal calibrant-free calibration method that corrects for space charge-induced frequency shifts in FTICR fragment spectra called Calibration Optimization on Fragment Ions (COFI). This new strategy utilizes the information from fixed mass differences between two neighboring peptide fragment ions (such as y(1) and y(2)) to correct the frequency shift after data collection. COFI has been successfully applied to LC-FTICR fragmentation data. Mascot MS/MS ion search data demonstrate that most of the fragments from BSA tryptic digested peptides can be identified using a much lower mass tolerance window after applying COFI to LC-FTICR-MS/MS of BSA tryptic digest. Furthermore, COFI has been used for multiplexed LC-CID-FTICR-MS which is an attractive technique because of its increased duty cycle and dynamic range. After the application of COFI to a multiplexed LC-CID-FTICR-MS of BSA tryptic digest, we achieved an average measured mass accuracy of 2.49 ppm for all the identified BSA fragments.     

Mass accuracy and sequence requirements for protein database searching.

To elucidate the role of high mass accuracy in mass spectrometric peptide mapping and database searching, selected proteins were subjected to tryptic digestion and the resulting mixtures were analyzed by electrospray ionization on a 7 Tesla Fourier transform mass spectrometer with a mass accuracy of 1 ppm. Two extreme cases were examined in detail: equine apomyoglobin, which digested easily and gave very few spurious masses, and bovine alpha-lactalbumin, which under the conditions used, gave many spurious masses. The effectiveness of accurate mass measurements in minimizing false protein matches was examined by varying the mass error allowed in the search over a wide range (2-500 ppm). For the "clean" data obtained from apomyoglobin, very few masses were needed to return valid protein matches, and the mass error allowed in the search had little effect up to 500 ppm. However, in the case of alpha-lactalbumin more mass values were needed, and low mass errors increased the search specificity. Mass errors below 30 ppm were particularly useful in eliminating false protein matches when few mass values were used in the search. Collision-induced dissociation of an unassigned peak in the alpha-lactalbumin digest provided sufficient data to unambiguously identify the peak as a fragment from alpha-lactalbumin and eliminate a large number of spurious proteins found in the peptide mass search. The results show that even with a relatively high mass error (0.8 Da for mass differences between singly charged product ions), collision-induced dissociation can help identify proteins in cases where unfavorable digest conditions or modifications render digest peaks unidentifiable by a simple mass mapping search.     

An ultra-fast metabolite prediction algorithm

Small molecules are central to all biological processes and metabolomics becoming an increasingly important discovery tool. Robust, accurate and efficient experimental approaches are critical to supporting and validating predictions from post-genomic studies. To accurately predict metabolic changes and dynamics, experimental design requires multiple biological replicates and usually multiple treatments. Mass spectra from each run are processed and metabolite features are extracted. Because of machine resolution and variation in replicates, one metabolite may have different implementations (values) of retention time and mass in different spectra. A major impediment to effectively utilizing untargeted metabolomics data is ensuring accurate spectral alignment, enabling precise recognition of features (metabolites) across spectra. Existing alignment algorithms use either a global merge strategy or a local merge strategy. The former delivers an accurate alignment, but lacks efficiency. The latter is fast, but often inaccurate. Here we document a new algorithm employing a technique known as quicksort. The results on both simulated data and real data show that this algorithm provides a dramatic increase in alignment speed and also improves alignment accuracy.     

Innovation: Metabolomics: the apogee of the omics trilogy

Metabolites, the chemical entities that are transformed during metabolism, provide a functional readout of cellular biochemistry. With emerging technologies in mass spectrometry, thousands of metabolites can now be quantitatively measured from minimal amounts of biological material, which has thereby enabled systems-level analyses. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanism are being revealed and are shaping our understanding of cell biology, physiology and medicine.