bims-metlip 2022-05-22 papers

bims-metlip

Biomed News

on Methods and protocols in metabolomics and lipidomics

Issue of 2022‒05‒22
twenty papers selected by
Sofia Costa

Trapped ion mobility spectrometry-mass spectrometry improves the coverage and accuracy of four-dimensional untargeted lipidomics.
Low and high resolution gas chromatography-mass spectrometry for untargeted metabolomics: A tutorial.
Simultaneous determination of vitamin D metabolites 25(OH)D3 and 1α,25(OH)2D3 in human plasma using liquid chromatography tandem mass spectrometry.
IDSL.IPA Characterizes the Organic Chemical Space in Untargeted LC/HRMS Data Sets.
Development and application of a fast ultra-high performance liquid chromatography-trapped ion mobility mass spectrometry method for untargeted lipidomics.
Norm ISWSVR: A Data Integration and Normalization Approach for Large-Scale Metabolomics.
Studying Metabolism by NMR-Based Metabolomics.
Mechanism-aware imputation: a two-step approach in handling missing values in metabolomics.
Purification and Analysis of Nucleotides and Nucleosides from Plants.
Liquid extraction surface analysis-mass spectrometry: An advanced and environment-friendly analytical tool in modern analysis.
Quantification of endocannabinoids in human cerebrospinal fluid using a novel micro-flow liquid chromatography-mass spectrometry method.
MTBSTFA derivatization-LC-MS/MS approach for the quantitative analysis of endogenous nucleotides in human colorectal carcinoma cells.
MINE 2.0: Enhanced biochemical coverage for peak identification in untargeted metabolomics.
Development of an off-line heart cutting two-dimensional HPLC system for enantioselective analysis of serine, threonine and allo-threonine in human physiological fluids.
Simultaneous determination of abiraterone and its five metabolites in human plasma by LC-MS/MS: Application to pharmacokinetic study in healthy Chinese subjects.
Evaluation and optimization of quantitative analysis of cofactors from yeast by liquid chromatography/mass spectrometry.
CeCaFLUX: the first web server for standardized and visual instationary 13C metabolic flux analysis.
Diagnostic Fragmentation Pathways for Identification of Phthalate Metabolites in Nontargeted Analysis Studies.
Simultaneous Assessment of Serum Levels and Pharmacologic Effects of Cannabinoids on Endocannabinoids and N-Acylethanolamines by Liquid Chromatography-Tandem Mass Spectrometry.
A novel UHPLC-ESI-MS/MS method and automatic calculation software for regiospecific analysis of triacylglycerols in natural fats and oils.

Anal Chim Acta. 2022 Jun 01. pii: S0003-2670(22)00457-3. [Epub ahead of print]1210 339886

Trapped ion mobility spectrometry-mass spectrometry improves the coverage and accuracy of four-dimensional untargeted lipidomics.

Xi Chen, Yandong Yin, Mingdu Luo, Zhiwei Zhou, Yuping Cai, Zheng-Jiang Zhu.

  Lipids play vital roles in many physiological and pathological processes in living organisms. Due to the high structural diversity and the numerous isomers and isobars of lipids, high-coverage and high-accuracy lipidomic analysis of complex biological samples remain the bottleneck to investigate lipid metabolism. Here, we developed the trapped ion mobility spectrometry-mass spectrometry (TIMS-MS) based four-dimensional untargeted lipidomics to support accurate lipid identification and quantification in biological samples. We first demonstrated that the TIMS based multi-dimensional separation improved the differentiations of isomeric and isobaric lipids, and increased the purity of precursor ion isolation and the quality of MS/MS spectra. Hyphenation of TIMS and PASEF technologies significantly improved the coverages of MS/MS spectra. These technological advantages jointly improved the coverage and accuracy of lipid identification in untargeted lipidomics. We further demonstrated that the CCS values of lipids acquired using TIMS were highly consistent with those from drift tube ion mobility spectrometry (DTIMS). Lipid identification and quantification results of NIST human plasma samples were also verified with inter-laboratory reports. Finally, we applied the TIMS-MS based untargeted lipidomics to characterize the spatial distributions of 1393 distinctive lipids in the mouse brain, and demonstrated that diverse lipid distributions and compositions among brain regions contributed to different functions of brain regions. Altogether, TIMS-MS based four-dimensional untargeted lipidomics significantly improved the coverage and accuracy of untargeted metabolomics, thereby facilitating a system-level understanding of lipid metabolism in biological organisms.

Keywords:  Isobaric and isomeric lipids; Lipid identification; Trapped ion mobility spectrometry; Untargeted lipidomics

DOI:  https://doi.org/10.1016/j.aca.2022.339886
Anal Chim Acta. 2022 Jun 01. pii: S0003-2670(21)00869-2. [Epub ahead of print]1210 339043

Low and high resolution gas chromatography-mass spectrometry for untargeted metabolomics: A tutorial.

Fernanda Rey-Stolle, Danuta Dudzik, Carolina Gonzalez-Riano, Miguel Fernández-García, Vanesa Alonso-Herranz, David Rojo, Coral Barbas, Antonia García.

  GC-MS for untargeted metabolomics is a well-established technique. Small molecules and molecules made volatile by derivatization can be measured and those compounds are key players in main biological pathways. This tutorial provides ready-to-use protocols for GC-MS-based metabolomics, using either the well-known low-resolution approach (GC-Q-MS) with nominal mass or the more recent high-resolution approach (GC-QTOF-MS) with accurate mass, discussing their corresponding strengths and limitations. Analytical procedures are covered for different types of biofluids (plasma/serum, bronchoalveolar lavage, urine, amniotic fluid) tissue samples (brain/hippocampus, optic nerve, lung, kidney, liver, pancreas) and samples obtained from cell cultures (adipocytes, macrophages, Leishmania promastigotes, mitochondria, culture media). Together with the sample preparation and data acquisition, data processing strategies are described specially focused on Agilent equipments, including deconvolution software and database annotation using spectral libraries. Manual curation strategies and quality control are also deemed. Finally, considerations to obtain a semiquantitative value for the metabolites are also described. As a case study, an illustrative example from one of our experiments at CEMBIO Research Centre, is described and findings discussed.

Keywords:  Compound identification; GC-MS protocols; High-resolution mass spectrometry; Metabolic fingerprinting; Metabolomics or metabonomics; Spectral library

DOI:  https://doi.org/10.1016/j.aca.2021.339043
J Mass Spectrom Adv Clin Lab. 2022 Apr;24 65-79

Simultaneous determination of vitamin D metabolites 25(OH)D3 and 1α,25(OH)2D3 in human plasma using liquid chromatography tandem mass spectrometry.

Shan Xu, Rui Ni, Lihong Lv, Rui Chen, Yao Chen, Fengjiao Huang, Zhiru Xu.

  Background: Although measurement of 25(OH)D3 is a routine analytical method to determine plasma vitamin D status, 1α,25(OH)2D3 is the biologically active form. Hence, simultaneous measurement of 25(OH)D3 and 1α,25(OH)2D3 could provide better insight into vitamin D status and pharmacokinetics. However, 1α,25(OH)2D3 has a low plasma concentration, making its quantification challenging for most analytical techniques. Here, we demonstrate use of liquid chromatography tandem mass spectrometry (LC-MSMS) for the development of a simple and rapid method for the simultaneous quantification of 25(OH)D3 and 1α,25(OH)2D3.Methods: Samples were purified from 250 µL human plasma. Chromatography was performed on an analytical column, under gradient conditions using a mobile phase consisting of methanol-lithium acetate. The mass detector was operated in positive multiple reaction monitoring mode. The established method was validated according to the guidance issued by ICH and FDA. Furthermore, a clinical study was performed using this method to detect the plasma concentrations of 1α,25(OH)2D3 after oral administration of calcitriol.
Results and conclusion: The method was acceptably linear over the concentration ranges of 20-1200 pg/mL for 1α,25(OH)2D3 and 1-60 ng/mL for 25(OH)D3, respectively, with correlation coefficients of r2 > 0.993. Both the inter-assay and intra-assay precision was < 15%, and the analytical recoveries were within 100% ± 10%, with no significant matrix effect or carryover. Thereby, we, provide a facile method for the simultaneous detection of vitamin D metabolites in plasma.

Keywords:  1α; 1α,25(OH)2D3, 1α,25-dihydroxy vitamin D3; 25(OH)2D3; 25(OH)D3; 25(OH)D3, 25-hydroxyvitamin D3; BSA, bovine serum albumin; ESI, electrospray ionization; FDA, Food and Drug Administration; ICH, International Council on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use; IS, internal standard; LC-MS/MS; LC-MS/MS, liquid chromatography tandem mass spectrometry; LLE, liquid liquid extraction; MRM, multiple reaction monitoring; PPT, protein precipitation; Pharmacokinetics; Plasma; SPE, solid phase extraction; VD, vitamin D; m/z, mass-to-charge ratios

DOI:  https://doi.org/10.1016/j.jmsacl.2022.04.001
J Proteome Res. 2022 May 17.

IDSL.IPA Characterizes the Organic Chemical Space in Untargeted LC/HRMS Data Sets.

Sadjad Fakouri Baygi, Yashwant Kumar, Dinesh Kumar Barupal.

  Generating comprehensive and high-fidelity metabolomics data matrices from LC/HRMS data remains to be extremely challenging for population-scale large studies (n > 200). Here, we present a new data processing pipeline, the Intrinsic Peak Analysis (IDSL.IPA) R package (https://ipa.idsl.me), to generate such data matrices specifically for organic compounds. The IDSL.IPA pipeline incorporates (1) identifying potential 12C and 13C ion pairs in individual mass spectra; (2) detecting and characterizing chromatographic peaks using a new sensitive and versatile approach to perform mass correction, peak smoothing, baseline development for local noise measurement, and peak quality determination; (3) correcting retention time and cross-referencing peaks from multiple samples by a dynamic retention index marker approach; (4) annotating peaks using a reference database of m/z and retention time; and (5) accelerating data processing using a parallel computation of the peak detection and alignment steps for larger studies. This pipeline has been successfully evaluated for studies ranging from 200 to 1600 samples. By specifically isolating high quality and reliable signals pertaining to carbon-containing compounds in untargeted LC/HRMS data sets from larger studies, IDSL.IPA opens new opportunities for discovering new biological insights in the population-scale metabolomics and exposomics projects. The package is available in the R CRAN repository at https://cran.r-project.org/package=IDSL.IPA.

Keywords:  12C/13C isotope pairs; chromatography analysis; mass spectrometry; metabolomics; peak-picking; retention time correction; untargeted analysis

DOI:  https://doi.org/10.1021/acs.jproteome.2c00120
J Chromatogr A. 2022 May 06. pii: S0021-9673(22)00317-X. [Epub ahead of print]1673 463124

Development and application of a fast ultra-high performance liquid chromatography-trapped ion mobility mass spectrometry method for untargeted lipidomics.

Fabrizio Merciai, Simona Musella, Eduardo Sommella, Alessia Bertamino, Anna Maria D'Ursi, Pietro Campiglia.

  The alteration of lipid profile in biological specimens, such as plasma, mirrors abnormalities in their homeostasis and offers pivotal information for disease comprehension. Fast analytical methods are needed to highlight changes in plasma lipid profile and deliver rapid results. In this study we developed a fast reversed phase ultra high performance liquid chromatography-trapped ion mobility mass spectrometry (RP-UHPLC-TIMS-MS) method for untargeted lipidomics. A short, narrow-bore fully porous particle CSH column (50 mm × 2.1 mm, 1.7 µm) was used, and by selecting appropriate flow rate, temperature and gradient conditions, the total analysis time was reduced from 20 to 4 min. TIMS was operated in parallel accumulation serial fragmentation mode (PASEF) which allowed to select multiple precursors for MS/MS and separate co-eluting lipids based on their different mobility. Lipid annotation was performed by rule-based approach, comparison with LipidBlast spectral library and manual data curation, by taking into account class-specific fragmentation pattern, accurate mass, adduct form, retention behavior in RP and comparison of their collision cross-section (CCS) values for increased confidence. 306 unique lipids from 21 subclasses were annotated from 20 µL of plasma, while their concentration was estimated by class-specific deuterated internal standards. The analytical method was validated and finally applied to elucidate the alteration of plasma lipid profiles in a small cohort of amyotrophic lateral sclerosis (ALS) patients. Univariate and multivariate statistics evidenced significant differences with respect to control patients, particularly in the levels of ether linked lipids (PC-O, PE-O, PE-P and LPC-O), sphingolipids (Ceramides), and triacylglycerols, showing the usefulness of this fast approach in providing accurate and rapid results with respect to longer (≥15 min) untargeted UHPLC-HRMS methods.

Keywords:  Amyotrophic lateral sclerosis; Plasma; Trapped ion mobility; UHPLC; Untargeted lipidomics

DOI:  https://doi.org/10.1016/j.chroma.2022.463124
Anal Chem. 2022 May 18.

Norm ISWSVR: A Data Integration and Normalization Approach for Large-Scale Metabolomics.

Xian Ding, Fen Yang, Yanhua Chen, Jing Xu, Jiuming He, Ruiping Zhang, Zeper Abliz.

Large-scale and long-period metabolomics study is more susceptible to various sources of systematic errors, resulting in nonreproducibility and poor data quality. A reliable and robust batch correction method removes unwanted systematic variations and improves the statistical power of metabolomics data, which undeniably becomes an important issue for the quality control of metabolomics. This study proposed a novel data normalization and integration method, Norm ISWSVR. It is a two-step approach via combining the best-performance internal standard correction with support vector regression normalization, comprehensively removing the systematic and random errors and matrix effects. This method was investigated in three untargeted lipidomics or metabolomics datasets, and the performance was further evaluated systematically in comparison with that of 11 other normalization methods. As a result, Norm ISWSVR decreased the data's median cross-validated relative standard deviation (cvRSD), increased the correlation between QCs, improved the classification accuracy of biomarkers, and was well-compatible with quantitative data. More importantly, Norm ISWSVR also allows a low frequency of QCs, which could significantly decrease the burden of a large-scale experiment. Correspondingly, Norm ISWSVR favorably improves the data quality of large-scale metabolomics data.

DOI: https://doi.org/10.1021/acs.analchem.1c05502
Front Mol Biosci. 2022 ;9 882487

Studying Metabolism by NMR-Based Metabolomics.

Sofia Moco.

  During the past few decades, the direct analysis of metabolic intermediates in biological samples has greatly improved the understanding of metabolic processes. The most used technologies for these advances have been mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. NMR is traditionally used to elucidate molecular structures and has now been extended to the analysis of complex mixtures, as biological samples: NMR-based metabolomics. There are however other areas of small molecule biochemistry for which NMR is equally powerful. These include the quantification of metabolites (qNMR); the use of stable isotope tracers to determine the metabolic fate of drugs or nutrients, unravelling of new metabolic pathways, and flux through pathways; and metabolite-protein interactions for understanding metabolic regulation and pharmacological effects. Computational tools and resources for automating analysis of spectra and extracting meaningful biochemical information has developed in tandem and contributes to a more detailed understanding of systems biochemistry. In this review, we highlight the contribution of NMR in small molecule biochemistry, specifically in metabolic studies by reviewing the state-of-the-art methodologies of NMR spectroscopy and future directions.

Keywords:  NMR; metabolism; metabolite-protein interactions; metabolomics; qNMR; stable isotopes

DOI:  https://doi.org/10.3389/fmolb.2022.882487
BMC Bioinformatics. 2022 May 16. 23(1): 179

Mechanism-aware imputation: a two-step approach in handling missing values in metabolomics.

Jonathan P Dekermanjian, Elin Shaddox, Debmalya Nandy, Debashis Ghosh, Katerina Kechris.

  When analyzing large datasets from high-throughput technologies, researchers often encounter missing quantitative measurements, which are particularly frequent in metabolomics datasets. Metabolomics, the comprehensive profiling of metabolite abundances, are typically measured using mass spectrometry technologies that often introduce missingness via multiple mechanisms: (1) the metabolite signal may be smaller than the instrument limit of detection; (2) the conditions under which the data are collected and processed may lead to missing values; (3) missing values can be introduced randomly. Missingness resulting from mechanism (1) would be classified as Missing Not At Random (MNAR), that from mechanism (2) would be Missing At Random (MAR), and that from mechanism (3) would be classified as Missing Completely At Random (MCAR). Two common approaches for handling missing data are the following: (1) omit missing data from the analysis; (2) impute the missing values. Both approaches may introduce bias and reduce statistical power in downstream analyses such as testing metabolite associations with clinical variables. Further, standard imputation methods in metabolomics often ignore the mechanisms causing missingness and inaccurately estimate missing values within a data set. We propose a mechanism-aware imputation algorithm that leverages a two-step approach in imputing missing values. First, we use a random forest classifier to classify the missing mechanism for each missing value in the data set. Second, we impute each missing value using imputation algorithms that are specific to the predicted missingness mechanism (i.e., MAR/MCAR or MNAR). Using complete data, we conducted simulations, where we imposed different missingness patterns within the data and tested the performance of combinations of imputation algorithms. Our proposed algorithm provided imputations closer to the original data than those using only one imputation algorithm for all the missing values. Consequently, our two-step approach was able to reduce bias for improved downstream analyses.

Keywords:  Imputation; Machine learning; Metabolomics; Missing data

DOI:  https://doi.org/10.1186/s12859-022-04659-1
Methods Mol Biol. 2022 ;2466 145-155

Purification and Analysis of Nucleotides and Nucleosides from Plants.

Henryk Straube, Marco Herde.

  This protocol describes necessary steps to isolate and quantify nucleotides and nucleosides from plant samples. Proper sample preparation in combination with liquid chromatography coupled to mass spectrometry enables the sensitive detection and quantification of metabolites of low abundance. Utilizing a liquid-liquid extraction in combination with a weak anion-exchange solid phase extraction enables the separation of negatively charged molecules from uncharged metabolites or cations.

Keywords:  Liquid chromatography; Mass spectrometry; Metabolomics; Plant nucleotide metabolism; Polar metabolomics; Weak anion-exchange solid phase extraction

DOI:  https://doi.org/10.1007/978-1-0716-2176-9_11
J Sep Sci. 2022 May 17.

Liquid extraction surface analysis-mass spectrometry: An advanced and environment-friendly analytical tool in modern analysis.

Shibam Das, Rohit Bhatia.

  The Liquid Extraction Surface Analysis technique is a new high-throughput instrument for ambient mass spectrometry. The benefits of the Liquid Extraction Surface Analysis-Mass Spectrometry approach are the high throughput screening of samples and the absence of sample preparation. Liquid Extraction Surface Analysis-Mass Spectrometry also consumes less solvent for extraction, making it more environmentally friendly and there is no substrate restriction. It utilizes advanced instrumentation like the use of robotic pipettes, nanoelectrospray systems, electronspray ionization chips which makes it highly efficient. In recent years, Liquid Extraction Surface Analysis-Mass Spectrometry has seen widespread use in a variety of analytical fields including drug metabolite analysis, mapping drug distribution in tissues, protein and lipid characterization etc. In this review, we have summarized the basic working principles of the Liquid Extraction Surface Analysis-Mass Spectrometry approach in detail along with a detailed description of the recently reported applications in the analysis of proteins, lipids, drugs and foods. The investigated analytes along with detection methodologies and significant outcomes of various research reports have been presented with the help of tables. This tool has also been utilized in clinical investigations of biological fluids, fingerprint analysis and authentication of agarwood. This article is protected by copyright. All rights reserved.

Keywords:  Electrospray ionization; High-field asymmetric waveform ion mobility; Liquid Extraction Surface Analysis; metabolite analysis; robotic pipettes

DOI:  https://doi.org/10.1002/jssc.202100996
Anal Chim Acta. 2022 Jun 01. pii: S0003-2670(22)00459-7. [Epub ahead of print]1210 339888

Quantification of endocannabinoids in human cerebrospinal fluid using a novel micro-flow liquid chromatography-mass spectrometry method.

Bingshu He, Xinyu Di, Faisa Guled, Aster V E Harder, Arn M J M van den Maagdenberg, Gisela M Terwindt, Elke H J Krekels, Isabelle Kohler, Amy Harms, Rawi Ramautar, Thomas Hankemeier.

  The endocannabinoid system (ECS) is implicated in various brain disorders. Changes in the composition of the cerebrospinal fluid (CSF) may be associated with ECS-related pathologies. Endocannabinoids (eCBs) and their analogues are present at low concentrations in human CSF, which hampered the investigation of the ECS in this body fluid. In this study, we developed a highly sensitive and selective micro-flow liquid chromatography-tandem mass spectrometry (micro-LC-MS/MS) method for the analysis of eCBs and eCB analogues in human CSF. The developed method allowed for the quantitative analysis of 16 eCBs and their analogues in human CSF. Micro-LC-MS/MS analyses were performed at a flow-rate of 4 μL min-1 with a 0.3-mm inner diameter column. A minor modification of a novel spray needle was carried out to improve the robustness of our method. By using an injection volume of 3 μL, our method reached limits of detection in the range from 0.6 to 1293.4 pM and limits of quantification in range from 2.0 to 4311.3 pM while intra- and interday precisions were below 13.7%. The developed workflow was successfully used for the determination of eCBs in 288 human CSF samples. It is anticipated that the proposed approach will contribute to a deeper understanding of the role of ECS in various brain disorders.

Keywords:  Cerebrospinal fluid; Down-scaling analysis; Endocannabinoids; Micro-LC-MS

DOI:  https://doi.org/10.1016/j.aca.2022.339888
J Pharm Anal. 2022 Feb;12(1): 77-86

MTBSTFA derivatization-LC-MS/MS approach for the quantitative analysis of endogenous nucleotides in human colorectal carcinoma cells.

Huixia Zhang, Yan Li, Zheng Li, Christopher Wai-Kei Lam, Peng Zhu, Caiyun Wang, Hua Zhou, Wei Zhang.

  Endogenous ribonucleotides (RNs) and deoxyribonucleotides (dRNs) are important metabolites related to the pathogenesis of many diseases. In light of their physiological and pathological significances, a novel and sensitive pre-column derivatization method with N-(t-butyldimethylsilyl)-N-methyltrifluoroacetamide (MTBSTFA) was developed to determine RNs and dRNs in human cells using high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS). A one-step extraction of cells with 85% methanol followed by a simple derivatization reaction within 5 min at room temperature contributed to shortened analysis time. The derivatives of 22 nucleoside mono-, di- and triphosphates were retained on the typical C18 column and eluted by ammonium acetate and acetonitrile in 9 min. Under these optimal conditions, good linearity was achieved in the tested calibration ranges. The lower limit of quantitation (LLOQ) was determined to be 0.1-0.4 μM for the tested RNs and 0.001-0.1 μM for dRNs. In addition, the precision (CV) was <15% and the RSD of stability was lower than 10.4%. Furthermore, this method was applied to quantify the endogenous nucleotides in human colorectal carcinoma cell lines HCT 116 exposed to 10-hydroxycamptothecin. In conclusion, our method has proven to be simple, rapid, sensitive, and reliable. It may be used for specific expanded studies on intracellular pharmacology in vitro.

Keywords:  Deoxyribonucleotides; Derivatization; High-performance liquid chromatography tandem mass spectrometry; N-(t-butyldimethylsilyl)-N- methyltrifluoroacetamide; Ribonucleotides

DOI:  https://doi.org/10.1016/j.jpha.2021.01.001
Bioinformatics. 2022 May 20. pii: btac331. [Epub ahead of print]

MINE 2.0: Enhanced biochemical coverage for peak identification in untargeted metabolomics.

Jonathan Strutz, Kevin M Shebek, Linda J Broadbelt, Keith E J Tyo.

SUMMARY: Although advances in untargeted metabolomics have made it possible to gather data on thousands of cellular metabolites in parallel, identification of novel metabolites from these datasets remains challenging. To address this need, Metabolic in silico Network Expansions (MINEs) were developed. A MINE is an expansion of known biochemistry which can be used as a list of potential structures for unannotated metabolomics peaks. Here, we present MINE 2.0, which utilizes a new set of biochemical transformation rules that covers 93% of MetaCyc reactions (compared to 25% in MINE 1.0). This results in a 17-fold increase in database size and a 40% increase in MINE database compounds matching unannotated peaks from an untargeted metabolomics dataset. MINE 2.0 is thus a significant improvement to this community resource.AVAILABILITY AND IMPLEMENTATION: The MINE 2.0 website can be accessed at https://minedatabase.ci.northwestern.edu. The MINE 2.0 web API documentation can be accessed at https://mine-api.readthedocs.io/en/latest/. The data and code underlying this article are available in the MINE-2.0-Paper repository at https://github.com/tyo-nu/MINE-2.0-Paper. MINE 2.0 source code can be accessed at https://github.com/tyo-nu/MINE-Database (MINE construction), https://github.com/tyo-nu/MINE-Server (backend web API), and https://github.com/tyo-nu/MINE-app (web app).
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DOI: https://doi.org/10.1093/bioinformatics/btac331
J Pharm Biomed Anal. 2022 Apr 30. pii: S0731-7085(22)00228-X. [Epub ahead of print]217 114807

Development of an off-line heart cutting two-dimensional HPLC system for enantioselective analysis of serine, threonine and allo-threonine in human physiological fluids.

Mai Oyaide, Aogu Furusho, Chiharu Ishii, Takeyuki Akita, Masashi Mita, Tomomi Ide, Kenji Hamase.

  A highly-selective two-dimensional high-performance liquid chromatographic (2D-HPLC, off-line heart cutting mode) system was developed for the determination of serine (Ser), threonine (Thr) and allo-threonine (aThr) enantiomers in human physiological fluids. Ser, Thr and aThr have a hydroxy group in their side chains, and the development of a simultaneous analytical method with a practically sufficient enantio/chemo-selectivity has been required to clarify their amounts in human physiological fluids. The amino acids in the samples were derivatized with 4-fluoro-7-nitro-2,1,3-benzoxadiazole and were isolated by a reversed-phase column (Singularity RP18, 1.0 x 250 mm) in the first dimension. After the target amino acids were collected, the fractions were manually introduced into an enantioselective column in the second dimension and were detected by their fluorescence. For the second dimension, a Pirkle-type chiral stationary phase (Singularity CSP-013S, 1.5 x 250 mm) was used. The resolution values of the enantiomers obtained by the Singularity CSP-013S column were 7.64 for Ser, 7.58 for Thr and 4.71 for aThr by using the mixture of methanol and acetonitrile containing formic acid as the mobile phases. The developed method was validated and applied to human plasma and urine. In the plasma, the obtained %d values (the percentage of d-form to total amino acid) were 1.7 for Ser, and trace levels of d-aThr and d-Thr were observed. In the urine, the %d values were 48.0 for Ser, 1.6 for Thr and 8.0 for aThr (calculated using d-aThr and l-Thr).

Keywords:  Chiral separation; Hydroxy amino acids; Two-dimensional HPLC

DOI:  https://doi.org/10.1016/j.jpba.2022.114807
J Pharm Biomed Anal. 2022 May 10. pii: S0731-7085(22)00247-3. [Epub ahead of print]217 114826

Simultaneous determination of abiraterone and its five metabolites in human plasma by LC-MS/MS: Application to pharmacokinetic study in healthy Chinese subjects.

Yixin Hu, Jianyuan Wu, Xin Jiang, Guiying Chen, Yang Zhang, Luqin Si, Hongliang Jiang, Jiangeng Huang, Jianying Huang.

  In this study, a rapid, simple and sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated to simultaneously quantify abiraterone (ABI), a widely used anti-metastatic castration-resistant prostate cancer drug, and its metabolites comprising Δ4-abiraterone (D4A), 3-keto-5α-abiraterone (5αA), abiraterone N-oxide (A-NO), abiraterone sulfate (A-Sul) and abiraterone N-oxide sulfate (A-NO-Sul) in human plasma. The analytes were extracted by protein precipitation with acetonitrile and ideal chromatographic separation was achieved on ACE-C18 column (2.1 × 50 mm, 5 µm) using a gradient elution. Triple Quad™ 6500+ mass spectrometer equipped with an electrospray ionization (ESI) source was used and the multiple reaction mode (MRM) was performed. In terms of method validation, good linearity was observed in preassigned validated concentration range for each analyte of interest. Both intra- and inter-batch accuracy was within the range of 87.6-113.8% for all analytes, while intra- and inter-batch precision was below 14.0%. Additionally, both low matrix effects and high recovery were obtained. All analytes remained stable in human plasma at room temperature for 4 h, on wet ice for 8 h, at - 80 °C for 42 d, over three freeze-thaw cycles and under auto-sampler temperature (4 °C) for 48 h post sample preparation. Subsequently, the validated LC-MS/MS method was applied for pharmacokinetic study in healthy Chinese volunteers following an oral dose of 250 mg abiraterone acetate tablet under fasted conditions. Our study for the first time reported the pharmacokinetic parameters of the ABI metabolites in Chinese subjects.

Keywords:  Abiraterone; LC-MS/MS; Metabolites; Pharmacokinetics

DOI:  https://doi.org/10.1016/j.jpba.2022.114826
Anal Chim Acta. 2022 Jun 08. pii: S0003-2670(22)00461-5. [Epub ahead of print]1211 339890

Evaluation and optimization of quantitative analysis of cofactors from yeast by liquid chromatography/mass spectrometry.

Jungyeon Kim, Inho Jung, Yu Eun Cheong, Kyoung Heon Kim.

  Cofactors play pivotal roles in catabolism and anabolism in all living organisms. Many studies have investigated the concentration of cofactors in living organisms to understand their metabolic status, which can be used to produce valuable chemicals or to understand the pathophysiology of diseases. Among various analytical platforms, liquid chromatography/mass spectrometry (LC/MS) is the most frequently used method for the quantification of cofactors. Several studies have reported various analytical methods for cofactors using LC/MS. However, the lack of optimal LC/MS methods makes it challenging to analyze various cofactors simultaneously. In addition, the method of extracting cofactors from cells needs to be optimized because conventional protocols probably have low extraction efficiency, which makes it difficult to reflect the actual concentration of cofactors in cells. In this study, we systematically compared various analytical methods and suggested optimal methods for the analysis of cofactors using LC/MS. In addition, we systematically compared quenching methods and extraction solvents and suggested optimal methods for the extraction of cofactors from Saccharomyces cerevisiae. The optimized methods can be used as standard protocols for LC/MS analysis and the extraction of cofactors from S. cerevisiae.

Keywords:  Cofactors; Liquid chromatography/mass spectrometry; Metabolome; Saccharomyces cerevisiae; Yeast

DOI:  https://doi.org/10.1016/j.aca.2022.339890
Bioinformatics. 2022 May 20. pii: btac341. [Epub ahead of print]

CeCaFLUX: the first web server for standardized and visual instationary 13C metabolic flux analysis.

Zhentao Liu, Zhengdong Zhang, Sheng Liang, Zhen Chen, Xiaoyao Xie, Tie Shen.

SUMMARY: The number of instationary 13C-metabolic flux (INST-MFA) studies grows every year, making it more important than ever to ensure the clarity, standardization and reproducibility of each study. We proposed CeCaFLUX, the first user-friendly web server that derives metabolic flux distribution from instationary 13C-labeled data. Flux optimization and statistical analysis are achieved through an evolutionary optimization in a parallel manner. It can visualize the flux optimizing process in real time and the ultimate flux outcome. It will also function as a database to enhance the consistency and to facilitate sharing of flux studies.AVAILABILITY AND IMPLEMENTATION: CeCaFLUX is freely available at https://www.cecaflux.net, the source code can be downloaded at https://github.com/zhzhd82/CeCaFLUX.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DOI: https://doi.org/10.1093/bioinformatics/btac341
J Am Soc Mass Spectrom. 2022 May 19.

Diagnostic Fragmentation Pathways for Identification of Phthalate Metabolites in Nontargeted Analysis Studies.

Yong-Lai Feng, Randolph Singh, Alex Chao, Yan Li.

  Phthalates have been studied due to their linkages with adverse developmental effects; however, metabolites of this class of compounds are undercharacterized and are poorly captured by traditional targeted analysis. In this study, we developed a nontargeted analysis approach for identifying and classifying phthalate metabolites based on a comprehensive study of their fragmentation pathways in electrospray ionization (ESI) quadrupole-time-of-flight mass spectrometry (QTOF-MS). This approach identifies molecular features in the data as phthalate metabolites via the detection of three structurally significant fragment ions. Then phthalate metabolites are classified into four types based on the presence of additional fragment ions specific to each type. Cleavage mechanisms for each class of phthalate metabolite are proposed based on fragmentation patterns generated at various collision energies (CE). All of the tested phthalate metabolites including oxidative and nonoxidative metabolites produced a fragment ion at m/z 121.0295, representing the deprotonated benzoate ion [C6H5COO]-. Most tested phthalate metabolites can produce a specific ion at m/z 147.0088, the deprotonated o-phthalic anhydride ion. However, phthalate carboxylate metabolites can only produce the [M-H-R]- ion at m/z 165.0193 and do not produce the fragment at m/z 147.0088. Other phthalate oxidative metabolites (hydroxyl- and oxo-) follow a different fragmentation pathway than nonoxidative metabolites. With this workflow, eight unknown phthalate metabolites were putatively identified in pooled urine, with one identified as a previously unreported metabolite by a combination of the MS/MS spectrum and the predicted retention time. Method detection limits for phthalate metabolites in urine were also estimated.

Keywords:  all ion fragmentation; fragmentation pathway; human urine; nontargeted analysis; phthalate metabolites

DOI:  https://doi.org/10.1021/jasms.2c00052
Cannabis Cannabinoid Res. 2022 May 17.

Simultaneous Assessment of Serum Levels and Pharmacologic Effects of Cannabinoids on Endocannabinoids and N-Acylethanolamines by Liquid Chromatography-Tandem Mass Spectrometry.

Timothy A Couttas, Carola Boost, Franziska Pahlisch, Eliska B Sykorova, Judith E Leweke, Dagmar Koethe, Heike Endepols, Cathrin Rohleder, F Markus Leweke.

  Introduction: The primary compounds of Cannabis sativa, delta-9-tetrahydrocannabinol (Δ9-THC) and cannabidiol (CBD), inflict a direct influence on the endocannabinoid system-a complex lipid signaling network with a central role in neurotransmission and control of inhibitory and excitatory synapses. These phytocannabinoids often interact with endogenously produced endocannabinoids (eCBs), as well as their structurally related N-acylethanolamines (NAEs), to drive neurobiological, nociceptive, and inflammatory responses. Identifying and quantifying changes in these lipid neuromodulators can be challenging owing to their low abundance in complex matrices. Materials and Methods: This article describes a robust liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the extraction and quantification of the eCBs anandamide and 2-arachidonoylglycerol, along with their congener NAEs oleoylethanolamine and palmitoylethanolamine, and phytocannabinoids CBD, Δ9-THC, and 11-Nor-9-carboxy-Δ9-tetrahydrocannabinol, a major metabolite of Δ9-THC. Our method was applied to explore pharmacokinetic and pharmacodynamic effects from intraperitoneal injections of Δ9-THC and CBD on circulating levels of eCBs and NAEs in rodent serum. Results: Detection limits ranged from low nanomolar to picomolar in concentration for eCBs (0.012-0.24 pmol/mL), NAEs (0.059 pmol/mL), and phytocannabinoids (0.24-0.73 pmol/mL). Our method displayed good linearity for calibration curves of all analytes (R2>0.99) as well as acceptable accuracy and precision, with quality controls not deviating >15% from their nominal value. Our LC-MS/MS method reliably identified changes to these endogenous lipid mediators that followed a causal relationship, which was dependent on both the type of phytocannabinoid administered and its pharmaceutical preparation. Conclusion: We present a rapid and reliable method for the simultaneous quantification of phytocannabinoids, eCBs, and NAEs in serum using LC-MS/MS. The accuracy and sensitivity of our assay infer it can routinely monitor endogenous levels of these lipid neuromodulators in serum and their response to external stimuli, including cannabimimetic agents.

Keywords:  N-acylethanolamines; cannabidiol; endocannabinoids; liquid chromatography–tandem mass spectrometry; rat serum; Δ9-tetrahydrocannabinol

DOI:  https://doi.org/10.1089/can.2021.0181
Anal Chim Acta. 2022 Jun 01. pii: S0003-2670(22)00458-5. [Epub ahead of print]1210 339887

A novel UHPLC-ESI-MS/MS method and automatic calculation software for regiospecific analysis of triacylglycerols in natural fats and oils.

Md Abdullah Al Sazzad, Mikael Fabritius, Pontus Boström, Marko Tarvainen, Marika Kalpio, Kaisa M Linderborg, Heikki Kallio, Baoru Yang.

  Regioisomeric analysis of triacylglycerols (TAGs) in natural oils and fats is a highly challenging task in analytical chemistry. Here we present a software (TAG Analyzer) for automatic calculation of regioisomeric composition of TAGs based on the mass spectral data from recently reported ultra-high performance liquid chromatography electrospray ionization tandem mass spectrometry (UHPLC-ESI-MS/MS) method for analyzing TAG regioisomers. The software enables fast and accurate processing of complex product ion spectra containing structurally informative diacylglycerol [M+NH4-RCO2H-NH3]+ and fatty acid ketene [RCO]+ fragment ions. Compared to manual processing, the developed software offers higher throughput with faster calculation as well as more accurate interpretation of chromatographically overlapping isobaric TAGs. The software determines results by constructing a synthetic spectrum to match the measured fragment ion spectrum, and by reporting the optimal concentrations of TAGs used to create the synthetic spectrum. This type of calculation is often extremely challenging for manual interpretation of the fragment ion spectra of isobaric TAGs with shared fragments, hence the need for automated data processing. The developed software was validated by analyzing a wide range of mixtures of regiopure TAG reference compounds of known composition and a commercial olive oil sample. Additionally, the method was also applied for regiospecific analysis of TAGs in human milk as an example of natural fats and oils with a highly complex TAG profile. The results indicate that the software is capable of resolving regioisomeric composition of natural TAGs even of the most complex composition. This novel calculation software combined with our existing UHPLC-ESI-MS/MS method form a highly efficient tool for regioisomeric analysis of TAGs in natural fats and oils.

Keywords:  Automated data processing; Data analysis; Mass spectrometry; Regioisomer; Triacylglycerol

DOI:  https://doi.org/10.1016/j.aca.2022.339887