Hiroshi Tsugawa

MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis

Data-independent acquisition (DIA) in liquid chromatography (LC) coupled to tandem mass spectrometry (MS/MS) provides comprehensive untargeted acquisition of molecular data. We provide an open-source software pipeline, which we call MS-DIAL, for DIA-based identification and quantification of small molecules by mass spectral deconvolution. For a reversed-phase LC-MS/MS analysis of nine algal strains, MS-DIAL using an enriched LipidBlast library identified 1,023 lipid compounds, highlighting the chemotaxonomic relationships between the algal strains.

Current metabolomics: Technological advances

Metabolomics, the global quantitative assessment of metabolites in a biological system, has played a pivotal role in various fields of science in the post-genomic era. Metabolites are the result of the interaction of the systems genome with its environment and are not merely the end product of gene expression, but also form part of the regulatory system in an integrated manner. Therefore, metabolomics is often considered a powerful tool to provide an instantaneous snapshot of the physiology of a cell. The power of metabolomics lies on the acquisition of analytical data in which metabolites in a cellular system are quantified, and the extraction of the most meaningful elements of the data by using various data analysis tool. In this review, we discuss the latest development of analytical techniques and data analyses methods in metabolomics study.

Practical non-targeted gas chromatography/mass spectrometry-based metabolomics platform for metabolic phenotype analysis.

Gas chromatography coupled to mass spectrometry (GC/MS) is a core analytical method for metabolomics and has been used as a platform in non-targeted analysis, especially for hydrophilic metabolites. Non-targeted GC/MS-based metabolomics generally requires a high-throughput technology to handle a large volume of samples and an accumulated database (reference library) of the retention times and mass spectra of standard compounds for accurate peak identification. In this study, we provide a practical GC/MS platform and an auto peak identification technique that is not restricted to certain types of mass spectrometers. The platform utilizes a quadrupole mass spectrometer capable of high-speed scanning, resulting in greater output compared with Pegasus GC-time of flight (TOF)/MS, which has been an essential instrument for high-throughput experiments. Moreover, we show that our reference library is broadly applicable to other instruments; peak identification can be readily performed using the library without constructing a reference resource. The usefulness and versatility of our system are demonstrated by the analyses of three experimental metabolomics data sets, including standard mixtures and real biological samples.

MRMPROBS: a data assessment and metabolite identification tool for large-scale multiple reaction monitoring based widely targeted metabolomics.

We developed a new software program, MRMPROBS, for widely targeted metabolomics by using the large-scale multiple reaction monitoring (MRM) mode. The strategy became increasingly popular for the simultaneous analysis of up to several hundred metabolites at high sensitivity, selectivity, and quantitative capability. However, the traditional method of assessing measured metabolomics data without probabilistic criteria is not only time-consuming but is often subjective and makeshift work. Our program overcomes these problems by detecting and identifying metabolites automatically, by separating isomeric metabolites, and by removing background noise using a probabilistic score defined as the odds ratio from an optimized multivariate logistic regression model. Our software program also provides a user-friendly graphical interface to curate and organize data matrices and to apply principal component analyses and statistical tests. For a demonstration, we conducted a widely targeted metabolome analysis (152 metabolites) of propagating Saccharomyces cerevisiae measured at 15 time points by gas and liquid chromatography coupled to triple quadrupole mass spectrometry. MRMPROBS is a useful and practical tool for the assessment of large-scale MRM data available to any instrument or any experimental condition.

Bulk RNA degradation by nitrogen starvation‐induced autophagy in yeast

Autophagy is a catabolic process conserved among eukaryotes. Under nutrient starvation, a portion of the cytoplasm is non‐selectively sequestered into autophagosomes. Consequently, ribosomes are delivered to the vacuole/lysosome for destruction, but the precise mechanism of autophagic RNA degradation and its physiological implications for cellular metabolism remain unknown. We characterized autophagy‐dependent RNA catabolism using a combination of metabolome and molecular biological analyses in yeast. RNA delivered to the vacuole was processed by Rny1, a T2‐type ribonuclease, generating 3′‐NMPs that were immediately converted to nucleosides by the vacuolar non‐specific phosphatase Pho8. In the cytoplasm, these nucleosides were broken down by the nucleosidases Pnp1 and Urh1. Most of the resultant bases were not re‐assimilated, but excreted from the cell. Bulk non‐selective autophagy causes drastic perturbation of metabolism, which must be minimized to maintain intracellular homeostasis.

Highly sensitive and selective analysis of widely targeted metabolomics using gas chromatography/triple-quadrupole mass spectrometry

In metabolomics studies, gas chromatography coupled with time-of-flight or quadrupole mass spectrometry has frequently been used for the non-targeted analysis of hydrophilic metabolites. However, because the analytical platform employs the deconvolution method to extract single-metabolite information from co-eluted peaks and background noise, the extracted peak is artificial product depending on the mathematical parameters and is not completely compatible with the pure component obtained by analyzing a standard compound. Moreover, it has insufficient ability for quantitative metabolomics. Therefore, highly sensitive and selective methods capable of pure peak extraction without any complicated mathematical techniques are needed. For this purpose, we have developed a novel analytical method using gas chromatography coupled with triple-quadrupole mass spectrometry (GC-QqQ/MS). We developed a selected reaction monitoring (SRM) method to analyze the trimethylsilyl derivatives of 110 metabolites, using electron ionization. This methodology enables us to utilize two complementary techniques-non-targeted and widely targeted metabolomics in the same sample preparation protocol, which would facilitate the formulation or verification of novel hypotheses in biological sciences. The GC-QqQ/MS analysis can accurately identify a metabolite using multichannel SRM transitions and intensity ratios in the analysis of living organisms. In addition, our methodology offers a wide dynamic range, high sensitivity, and highly reproducible metabolite profiles, which will contribute to the biomarker discoveries and quality evaluations in biology, medicine, and food sciences.

Identification of small molecules using accurate mass MS/MS search

Tandem mass spectral library search (MS/MS) is the fastest way to correctly annotate MS/MS spectra from screening small molecules in fields such as environmental analysis, drug screening, lipid analysis, and metabolomics. The confidence in MS/MS-based annotation of chemical structures is impacted by instrumental settings and requirements, data acquisition modes including data-dependent and data-independent methods, library scoring algorithms, as well as post-curation steps. We critically discuss parameters that influence search results, such as mass accuracy, precursor ion isolation width, intensity thresholds, centroiding algorithms, and acquisition speed. A range of publicly and commercially available MS/MS databases such as NIST, MassBank, MoNA, LipidBlast, Wiley MSforID, and METLIN are surveyed. In addition, software tools including NIST MS Search, MS-DIAL, Mass Frontier, SmileMS, Mass++, and XCMS2 to perform fast MS/MS search are discussed. MS/MS scoring algorithms and challenges during compound annotation are reviewed. Advanced methods such as the in silico generation of tandem mass spectra using quantum chemistry and machine learning methods are covered. Community efforts for curation and sharing of tandem mass spectra that will allow for faster distribution of scientific discoveries are discussed.

MRMPROBS Suite for metabolomics using large-scale MRM assays

UNLABELLED We developed new software environment for the metabolome analysis of large-scale multiple reaction monitoring (MRM) assays. It supports the data format of four major mass spectrometer vendors and mzML common data format. This program provides a process pipeline from the raw-format import to high-dimensional statistical analyses. The novel aspect is graphical user interface-based visualization to perform peak quantification, to interpolate missing values and to normalize peaks interactively based on quality control samples. Together with the software platform, the MRM standard library of 301 metabolites with 775 transitions is also available, which contributes to the reliable peak identification by using retention time and ion abundances. AVAILABILITY AND IMPLEMENTATION MRMPROBS is available for Windows OS under the creative-commons by-attribution license at http://prime.psc.riken.jp.

Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography–mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography–mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives.

MRM-DIFF: data processing strategy for differential analysis in large scale MRM-based lipidomics studies.

Based on theoretically calculated comprehensive lipid libraries, in lipidomics as many as 1000 multiple reaction monitoring (MRM) transitions can be monitored for each single run. On the other hand, lipid analysis from each MRM chromatogram requires tremendous manual efforts to identify and quantify lipid species. Isotopic peaks differing by up to a few atomic masses further complicate analysis. To accelerate the identification and quantification process we developed novel software, MRM-DIFF, for the differential analysis of large-scale MRM assays. It supports a correlation optimized warping (COW) algorithm to align MRM chromatograms and utilizes quality control (QC) sample datasets to automatically adjust the alignment parameters. Moreover, user-defined reference libraries that include the molecular formula, retention time, and MRM transition can be used to identify target lipids and to correct peak abundances by considering isotopic peaks. Here, we demonstrate the software pipeline and introduce key points for MRM-based lipidomics research to reduce the mis-identification and overestimation of lipid profiles. The MRM-DIFF program, example data set and the tutorials are downloadable at the “Standalone software” section of the PRIMe (Platform for RIKEN Metabolomics, http://prime.psc.riken.jp/) database website.