bims-metlip 2021-11-21 papers

bims-metlip

Biomed News

on Methods and protocols in metabolomics and lipidomics

Issue of 2021–11–21
24 papers selected by
Sofia Costa, Icahn School of Medicine at Mount Sinai

Modifying Chromatography Conditions for Improved Unknown Feature Identification in Untargeted Metabolomics.
Determination of up to twenty carboxylic acid containing compounds in clinically relevant matrices by o-benzylhydroxylamine derivatization and liquid chromatography-tandem mass spectrometry.
A High-Throughput HILIC-MS-Based Metabolomic Assay for the Analysis of Polar Metabolites.
Bioinformatics in Lipidomics: Automating Large-Scale LC-MS-Based Untargeted Lipidomics Profiling with SimLipid Software.
Native mass spectrometry-based metabolomics identifies metal-binding compounds.
GC-MS/MS Profiling of Plant Metabolites.
Detection of catecholamine metabolites in urine based on ultra high performance liquid chromatography-tandem mass spectrometry.
Targeted profiling of 24 sulfated and non-sulfated bile acids in urine using two-dimensional isotope dilution UHPLC-MS/MS.
Development and validation of a HILIC-MS/MS method for the quantitation of fructose in human urine in support of clinical programs.
Simultaneous estimation of ZY-19489 and its active metabolite ZY-20486 in human plasma using LC-MS/MS, a novel antimalarial compound.
Non-targeted Lipidomics Using a Robust and Reproducible Lipid Separation Using UPLC with Charged Surface Hybrid Technology and High-Resolution Mass Spectrometry.
Comprehensive Analysis of Plant Lipids Using Sub-2-μm Particle CO2-Based Chromatography Coupled to Mass Spectrometry.
Novel hydrophilic-phase extraction, HILIC and high-resolution MS quantification of an RNA oligonucleotide in plasma.
Analysis of Grape Volatiles Using Atmospheric Pressure Ionization Gas Chromatography Mass Spectrometry-Based Metabolomics.
Spatial metabolomics using imaging mass spectrometry to identify the localization of asparaptine A in Asparagus officinalis.
Lipidomic and metabolomic analysis reveals changes in biochemical pathways for non-small cell lung cancer tissues.
Ultra-high pressure liquid chromatography coupled to travelling wave ion mobility-time of flight mass spectrometry for the screening of pharmaceutical metabolites in wastewater samples: Application to antiretrovirals.
A multimodal metabolomics approach using imaging mass spectrometry and liquid chromatography-tandem mass spectrometry for spatially characterizing monoterpene indole alkaloids secreted from roots.
Automated high confidence compound identification of electron ionization mass spectra for nontargeted analysis.
Analytical and bioanalytical HPLC method for simultaneous estimation of 5-fluorouracil and sonidegib.
Quantification of Epigenetic DNA Modifications in the Subchromatin Structure Matrix Attachment Regions by Stable Isotope Dilution UHPLC-MS/MS Analysis.
Use ggbreak to Effectively Utilize Plotting Space to Deal With Large Datasets and Outliers.
Development, validation, and application of an HPLC-MS/MS method for quantification of oxidized fatty acids in plants.
High-Resolution Multi-Isotope Imaging Mass Spectrometry (MIMS) Imaging Applications in Stem Cell Biology.

Anal Chem. 2021 Nov 18.

Modifying Chromatography Conditions for Improved Unknown Feature Identification in Untargeted Metabolomics.

Brady G Anderson, Alexander Raskind, Hani Habra, Robert T Kennedy, Charles R Evans.

Untargeted metabolomics is an essential component of systems biology research, but it is plagued by a high proportion of detectable features not identified with a chemical structure. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments produce spectra that can be searched against databases to help identify or classify these unknowns, but many features do not generate spectra of sufficient quality to enable successful annotation. Here, we explore alterations to gradient length, mass loading, and rolling precursor ion exclusion parameters for reversed phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) that improve compound identification performance for human plasma samples. A manual review of spectral matches from the HILIC data set was used to determine reasonable thresholds for search score and other metrics to enable semi-automated MS/MS data analysis. Compared to typical LC-MS/MS conditions, methods adapted for compound identification increased the total number of unique metabolites that could be matched to a spectral database from 214 to 2052. Following data alignment, 68.0% of newly identified features from the modified conditions could be detected and quantitated using a routine 20-min LC-MS run. Finally, a localized machine learning model was developed to classify the remaining unknowns and select a subset that shared spectral characteristics with successfully identified features. A total of 576 and 749 unidentified features in the HILIC and RPLC data sets were classified by the model as high-priority unknowns or higher-importance targets for follow-up analysis. Overall, our study presents a simple strategy to more deeply annotate untargeted metabolomics data for a modest additional investment of time and sample.

DOI: https://doi.org/10.1021/acs.analchem.1c02149
J Pharm Biomed Anal. 2021 Oct 29. pii: S0731-7085(21)00561-6. [Epub ahead of print]208 114450

Determination of up to twenty carboxylic acid containing compounds in clinically relevant matrices by o-benzylhydroxylamine derivatization and liquid chromatography-tandem mass spectrometry.

Alex Gomez-Gomez, Eulàlia Olesti, Blanca Montero-San-Martin, Angie Soldevila, Tessa Deschamps, Nieves Pizarro, Rafael de la Torre, Oscar J Pozo.

  Carboxylic acid containing compounds (R-COOH) are involved in a large number of biological processes and they are relevant for several pathological processes such as neurodegeneration or cancer. Comprehensive methodologies for the quantitative determination of R-COOH in biological samples are required. In this study we have developed a LC-MS/MS method for the quantification of 20 endogenous R-COOH belonging to different pathways such as kynurenine metabolism, serotoninergic pathway, glycolysis, tricarboxylic acid cycle, dopaminergic pathway, short chain fatty acids and glycine metabolism. The approach included derivatization with o-benzylhydroxylamine (reaction time 1 h), liquid-liquid extraction with ethyl acetate and LC-MS/MS detection (run time 10 min). The method was optimized and validated in 5 different matrices (urine, plasma, saliva, brain and liver) following two different approaches: (i) using surrogate matrices and (ii) using actual human samples by standard additions. A suitable linearity was obtained in the endogenous range of the analytes. Adequate intra and inter-assay accuracies (80-120%) and intra- and inter-assay precisions (<20%) were achieved for almost all analytes in all studied matrices. The method was applied in several scenarios to confirm (i) human urinary changes produced in glycolysis after exercise, (ii) metabolic changes produced in rat brain and plasma by methamphetamine administration and (iii) metabolic alterations in human plasma caused by vitamin B6 deficiency. Additionally, the application of the method allowed for establishing previously unreported alterations in R-COOH metabolites under these conditions. Due to the comprehensive analyte and matrix coverage and the wide applicability of the developed methodology, it can be considered as a suitable tool for the study of R-COOH status in health and disease by targeted metabolomics.

Keywords:  Carboxylic acids; Derivatization; LC–MS/MS; O-benzylhydroxylamine; Targeted metabolomics; Tricarboxylic acid cycle

DOI:  https://doi.org/10.1016/j.jpba.2021.114450
Methods Mol Biol. 2022 ;2396 137-159

A High-Throughput HILIC-MS-Based Metabolomic Assay for the Analysis of Polar Metabolites.

Giuseppe Paglia, Giuseppe Astarita.

  Mass spectrometry (MS)-based metabolomics approaches have been used for characterizing the metabolite content and composition of biological samples in drug discovery and development, as well as in metabolic engineering, and food and plant sciences applications. Here, we describe a protocol routinely used in our laboratory to conduct a metabolic profiling of small polar metabolites from biological samples. Metabolites can be extracted from each sample using a methanol-based single-phase extraction procedure. The combination of LC-based hydrophilic interaction liquid chromatography (HILIC) and a hybrid quadrupole-time of flight (Q-ToF) mass spectrometer allows the comprehensive analysis of small polar metabolites including sugars, phosphorylated compounds, purines and pyrimidines, nucleotides, nucleosides, acylcarnitines, carboxylic acids, hydrophilic vitamins and amino acids. Retention times and accurate masses of metabolites involved in key metabolic pathways are annotated for routine high-throughput screening in both untargeted and targeted metabolomics analyses.

Keywords:  HILIC; LC-MS; Mass spectrometry; Metabolomics; Polar metabolites; qTOF

DOI:  https://doi.org/10.1007/978-1-0716-1822-6_11
Methods Mol Biol. 2022 ;2396 197-214

Bioinformatics in Lipidomics: Automating Large-Scale LC-MS-Based Untargeted Lipidomics Profiling with SimLipid Software.

Ningombam Sanjib Meitei, Vladimir Shulaev.

  Liquid chromatography-mass spectrometry (LC-MS) provides one of the most popular platforms for untargeted plant lipidomics analysis (Shulaev and Chapman, Biochim Biophys Acta 1862(8):786-791, 2017; Rupasinghe and Roessner, Methods Mol Biol 1778:125-135, 2018; Welti et al., Front Biosci 12:2494-506, 2007; Shiva et al., Plant Methods 14:14, 2018). We have developed SimLipid software in order to streamline the analysis of large-volume datasets generated by LC-MS-based untargeted lipidomics methods. SimLipid contains a customizable library of lipid species; graphical user interfaces (GUIs) for visualization of raw data; the identified lipid molecules and their associated mass spectra annotated with fragment ions and parent ions; and detailed information of each identified lipid species all in a single workbench enabling users to rapidly review the results by examining the data for confident identifications of lipid molecular species. In this chapter, we present the functionality of the software and workflow for automating large-scale LC-MS-based untargeted lipidomics profiling.

Keywords:  Bioinformatics; Grapes; LC-MS; Lipid identification; Lipidomics

DOI:  https://doi.org/10.1007/978-1-0716-1822-6_15
Nat Chem. 2021 Nov 18.

Native mass spectrometry-based metabolomics identifies metal-binding compounds.

Allegra T Aron, Daniel Petras, Robin Schmid, Julia M Gauglitz, Isabell Büttel, Luis Antelo, Hui Zhi, Sean-Paul Nuccio, Christina C Saak, Kien P Malarney, Eckhard Thines, Rachel J Dutton, Lihini I Aluwihare, Manuela Raffatellu, Pieter C Dorrestein.

Although metals are essential for the molecular machineries of life, systematic methods for discovering metal-small molecule complexes from biological samples are limited. Here, we describe a two-step native electrospray ionization-mass spectrometry method, in which post-column pH adjustment and metal infusion are combined with ion identity molecular networking, a rule-based data analysis workflow. This method enabled the identification of metal-binding compounds in complex samples based on defined mass (m/z) offsets of ion species with the same chromatographic profiles. As this native electrospray metabolomics approach is suited to the use of any liquid chromatography-mass spectrometry system to explore the binding of any metal, this method has the potential to become an essential strategy for elucidating metal-binding molecules in biology.

DOI: https://doi.org/10.1038/s41557-021-00803-1
Methods Mol Biol. 2022 ;2396 101-115

GC-MS/MS Profiling of Plant Metabolites.

Feroza Kaneez Choudhury, Prajita Pandey, Ron Meitei, Dwain Cardona, Amit C Gujar, Vladimir Shulaev.

  Gas chromatography coupled to electron ionization (EI) quadrupole mass spectrometry (GC-MS) is currently one of the most developed and robust metabolomics technologies. This approach allows for simultaneous measurements of large number of chemically diverse compounds including organic acids, amino acids, sugars, sugar alcohols, aromatic amines, and fatty acids. Untargeted GC-MS profiling based on full scan data acquisition requires complicated raw data processing and sometime provides ambiguous metabolite identifications. Targeted analysis using GC-MS/MS can provide better specificity, increase sensitivity, and simplify data processing and compound identification but wider application of targeted GC-MS/MS approach in metabolomics is hampered by the lack of extensive databases of MRM transitions for non-derivatized and derivatized endogenous metabolites. The focus of this chapter is the automation of GC-MS/MS method development which makes it feasible to develop quantitative methods for several hundred metabolites and use this strategy for plant metabolomics applications.

Keywords:  Arabidopsis; AutoSRM; GC-MS /MS; Metabolomics

DOI:  https://doi.org/10.1007/978-1-0716-1822-6_9
Biomed Chromatogr. 2021 Nov 17. e5280

Detection of catecholamine metabolites in urine based on ultra high performance liquid chromatography-tandem mass spectrometry.

Hui Li, Guolei Zhang, Wei Wang, Li-Li Jiao, Chang-Bao Chen, Jing-Rui Huo, Wei Wu.

  Neurotransmitter metabolites excretion in normal individuals is of great significance for health monitoring. A rapid quantitative method was developed with ultra performance liquid chromatography-tandem mass spectrometry (UHPLC-MS). The method was further applied to the determination of catecholamine metabolites vanilymandelic acid (VMA), methoxy hydroxyphenyl glycol (MHPG), dihydroxy-phenyl acetic acid (DOPAC), and homovanillic acid (HVA) in urine. Urine was collected from six healthy volunteers (20-22 years old) for 10 consecutive days. Urine was pre-column derivatized with dansyl chloride (DNS-Cl). Subsequently, the sample was detected by triple quadrupole mass spectrometry with ESI in positive and multi-reaction monitoring (MRM) mode. The method was sensitive and repeatable with the recoveries 92.7-104.30 %, LODs 0.01-0.05 μg/mL, and coefficients no less than 0.9938. The excretion content of four target compounds in random urine samples were 0.20 ± 0.086 μg/mL (MHPG), 1.27 ± 1.24 μg/mL (VMA), 3.29 ± 1.36 μg/mL (HVA) and 1.13 ± 1.07 μg/mL (DOPAC). In urine, VMA, the metabolite of norepinephrine and adrenaline, were more than MHPG, while HVA, the metabolite of dopamine, was more than DOPAC too. This paper detected the levels of catecholamine metabolites, as well as summarized the characteristics of excretion using random urine samples, which could provide valuable information for clinical practice.

Keywords:  catecholamine metabolites; pre-column derivation; ultra performance liquid chromatography-tandem mass spectrometry (UHPLC-MS); urine

DOI:  https://doi.org/10.1002/bmc.5280
Clin Chem Lab Med. 2021 Nov 22.

Targeted profiling of 24 sulfated and non-sulfated bile acids in urine using two-dimensional isotope dilution UHPLC-MS/MS.

Katharina Habler, Bernhard Koeppl, Franz Bracher, Michael Vogeser.

   OBJECTIVES: Bile acids serve as biomarkers for liver function and are indicators for cholestatic and hepatobiliary diseases like hepatitis, cirrhosis, and intrahepatic cholestasis of pregnancy (ICP). Sulfation and renal excretion of bile acids are important elimination steps. The power of ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) allows specific profiling of primary and secondary bile acids as well as their sulfated counterparts.
METHODS: Twenty-four sulfated and non-sulfated primary and secondary bile acids were quantified in urine with 15 corresponding stable isotope labeled internal standards by using two-dimensional UHPLC-MS/MS. The sample preparation was based on a simple dilution with a methanolic zinc sulfate solution followed by an automated online solid phase extraction clean up.
RESULTS: The validation results of the method fulfilled the criteria of the European Medicine Agency (EMA) "Guideline on bioanalytical method validation". To verify fitness for purpose, 40 urine samples were analyzed which showed an average of 86% sulfation, 9.1% taurine-conjugation, 14% non-conjugation, and 77% glycine-conjugation rates.
CONCLUSIONS: Lossless one-pot sample preparation, automated sample purification, and high number of internal standards are major innovations of the presented profiling method, which may allow diagnostic application of BA profiling in the future.

Keywords:  bile acids; intrahepatic cholestasis of pregnancy (ICP); liquid chromatography-tandem mass spectrometry (LC-MS/MS); liver disease; profiling; urine

DOI:  https://doi.org/10.1515/cclm-2021-1111
J Pharm Biomed Anal. 2021 Nov 10. pii: S0731-7085(21)00573-2. [Epub ahead of print]208 114462

Development and validation of a HILIC-MS/MS method for the quantitation of fructose in human urine in support of clinical programs.

Fumin Li, Gang Xing, Christopher Cousineau, Sara Clemens, Melissa Mofikoya, Moo-Young Kim, Jenny Yanhua Zhang, Yizhong Zhang, Nancy Raha.

  In a previous publication [1], a 20-minute UPLC®-MS/MS method, employing a surrogate analyte approach, was developed and validated to measure fructose and sorbitol, as mechanistic biomarkers, in human plasma to support first-in-human (FIH) studies. Different from plasma which maintains its homeostasis, urine has no such homeostasis mechanisms [2], therefore it is expected to be able to accommodate more changes. Here we describe the development and validation of a LC-MS/MS method for the quantiation of fructose in human urine to support clinical trials. A hydrophilic interaction chromatography (HILIC) method using an Asahipak NH2P-50 column (Shodex, 4.6 × 250 mm, 5 µm) was developed. Acetone precipitation was utilized to extract fructose from urine. For validation, stable isotope-labeled 13C6-fructose was used as the surrogate analyte for fructose in the preparation of calibration curves. QCs were prepared using both the surrogate analyte (13C6-fructose) and the authentic analyte (fructose). Difficulties were encountered for post-extraction stability experiments especially for authentic fructose QCs at low concentrations. Extensive troubleshooting revealed that fructose's chromatography improved as the column aged. As a result, the response factor of fructose increased over time for low concentration samples, leading to failed post-extraction stability experiments. A column cleaning procedure was implemented to ensure consistency in chromatography performance. The HILIC-MS/MS method was successfully validated and applied to analyze clinical samples with a 91% overall run passing rate.

Keywords:  Clinical; Fructose; HILIC-MS/MS; Quantitation; Urine; Validation

DOI:  https://doi.org/10.1016/j.jpba.2021.114462
Bioanalysis. 2021 Dec;13(23): 1761-1777

Simultaneous estimation of ZY-19489 and its active metabolite ZY-20486 in human plasma using LC-MS/MS, a novel antimalarial compound.

Ashok M Ghoghari, Harilal V Patel, Nisarg N Nayak, Tariq H Mansuri, Soma M Pillai, Mukul R Jain, Hardik B Patel, Kevin Kansagra, Ilaria Di Resta, Jörg Möhrle, Deven V Parmar.

  Aim: ZY-19489 is a new antimalarial drug candidate and selective LC-MS/MS method was established for estimation of ZY-19489 and its metabolite in human plasma. Materials & methods: LLE was employed for extraction, mass spectrometric quantification performed using positive ionization mode and DCP-IMP was used as an internal standard. The chromatographic separation was achieved using mobile phase 5 mM ammonium formate in water and 0.1% v/v ammonia solution in methanol:acetonitrile (90:10% v/v) and column Agilent Zorbex Extended C18, 3.5 μm, 100 × 4.6 mm with a 6-min run time. Results: The calibration curve of ZY-19489 was linear over range 1-500 ng/ml and 2-200 ng/ml for metabolite. Assay was reproducible, selective and devoid of matrix effect. Conclusion: The validated assay was implemented for clinical sample analysis derived from healthy human subjects and parasitemia-induced subjects.

Keywords:  LC–MS/MS; ZY-19489; ZY-20486; human plasma; method validation

DOI:  https://doi.org/10.4155/bio-2021-0194
Methods Mol Biol. 2022 ;2396 175-186

Non-targeted Lipidomics Using a Robust and Reproducible Lipid Separation Using UPLC with Charged Surface Hybrid Technology and High-Resolution Mass Spectrometry.

Giorgis Isaac, Vladimir Shulaev, Robert S Plumb.

  Lipids play an important role in the energy storage, cellular signaling, and pathophysiology of diseases such as cancer, neurodegenerative diseases, infections, and diabetes. Due to high importance of diverse lipid classes in human health and disease, manipulating lipid abundance and composition is an important target for metabolic engineering. The extreme structural diversity of lipids in real biological samples is challenging for analytical techniques due to large difference in physicochemical properties of individual lipid species. This chapter describes lipidomic analysis of large sample sets requiring reliable and robust methodology. Rapid and robust methods facilitate the support of longitudinal studies allowing the transfer of methodology between laboratories. We describe a high-throughput reversed-phase LC-MS methodology using Ultra Performance Liquid Chromatography (UPLC®) with charged surface hybrid technology and accurate mass detection for high-throughput non-targeted lipidomics. The methodology showed excellent specificity, robustness, and reproducibility for over 100 LC-MS injections.

Keywords:  LC-MS; Non-targeted lipidomics

DOI:  https://doi.org/10.1007/978-1-0716-1822-6_13
Methods Mol Biol. 2022 ;2396 187-195

Comprehensive Analysis of Plant Lipids Using Sub-2-μm Particle CO2-Based Chromatography Coupled to Mass Spectrometry.

Carolina Salazar, Michael D Jones, Giorgis Isaac, Vladimir Shulaev.

  Lipids play an essential role in plants, and historically manipulating their levels and composition has been an important target for metabolic engineering. A variety of analytical techniques, many based on mass spectrometry, have been utilized for lipid profiling, but the analysis of complex lipid mixtures still poses significant analytical challenges. Recent advances in technology have revived the supercritical fluid chromatography (SFC) as a promising separation technique for lipid analysis. Utilization of sub-2-μm particle columns improves the separation efficiency and robustness of the SFC systems. The combination of SFC with sub-2-μm particle separation, commonly referred as ultra-performance convergence chromatography, has been successfully used for separation of both polar and neutral lipids. In this chapter, we present a simple method for lipid class separation using Sub-2-μm particle CO2-based chromatography coupled to mass spectrometry. The supercritical fluid chromatography methodology is flexible and can be altered to provide greater retention and separation of lipid classes or individual lipids within class.

Keywords:  Mass spectrometry; SFC; SFC-MS; Supercritical fluid chromatography; Ultra-performance convergence chromatography

DOI:  https://doi.org/10.1007/978-1-0716-1822-6_14
Bioanalysis. 2021 Nov 15.

Novel hydrophilic-phase extraction, HILIC and high-resolution MS quantification of an RNA oligonucleotide in plasma.

Prachi Anand, Michael Koleto, Dilipkumar R Kandula, Lei Xiong, Robert MacNeill.

Aim: In the theme of quantitative LC-MS bioanalysis of oligonucleotides free of ion-pairing, a 22-mer RNA oligonucleotide took center stage. The focus was on a unique polar-based retention scheme to produce a high-recovery extraction presenting a high-performance alternative extraction means, also there was the opportunity to involve hydrophilic-interaction liquid chromatography and contemporary high-resolution MS as the end point. Results: Original LC-MS methodology was developed for the oligonucleotide and the performance was robust for both nominal and accurate mass detection, the latter affording 10× improvement in sensitivity and 4000-fold linear dynamic range, 500 pM to 2000 nM. Conclusion: A novel means of solid-phase extraction is exhibited within a robust pair-free methodology, reaching pM sensitivity with the demonstrably beneficial accurate mass platform.

DOI: https://doi.org/10.4155/bio-2021-0216
Methods Mol Biol. 2022 ;2396 117-136

Analysis of Grape Volatiles Using Atmospheric Pressure Ionization Gas Chromatography Mass Spectrometry-Based Metabolomics.

Manoj Ghaste, Fulvio Mattivi, Giuseppe Astarita, Vladimir Shulaev.

  Analysis of volatile compounds in fruits and plants can be a challenging task as they present in a large amount with structural diversity and high aroma threshold, the information on molecular ion can be very useful for compound identification. Electron ionization gas-chromatography-mass spectrometry (EI-GC-MS) which is widely used for the analysis of plant volatiles has a certain limitation providing the limited capability to characterize novel metabolites in a complex biological matrix due to hard fragmentation level. Atmospheric pressure ionization using APGC source in combination with high-resolution time-of-flight mass spectrometry (TOF-MS) provides an excellent combination of GC with high-resolution mass spectrometry. The APGC-MS approach provides several advantages over the conventional EI and CI based GC-MS techniques in metabolomics studies due to highly reduced fragmentation, which preserves molecular ion, and accurate mass measurement by HRMS allows to deduce the elemental composition of the volatile compounds. Moreover, the use of MSE mode provides spectral similarity to EI in high-energy mode which can be used for the further confirmation of metabolite identity. We describe an APGC-MS-based untargeted metabolomics approach with a case study of grape volatile compounds and the development of a spectral library for metabolite identification.

Keywords:  Atmospheric pressure ionization; Gas chromatography; Grape metabolomics; High-resolution time-of-flight mass spectrometry; Mass spectrometry; Volatiles

DOI:  https://doi.org/10.1007/978-1-0716-1822-6_10
Plant Biotechnol (Tokyo). 2021 Sep 25. 38(3): 311-315

Spatial metabolomics using imaging mass spectrometry to identify the localization of asparaptine A in Asparagus officinalis.

Ryo Nakabayashi, Kei Hashimoto, Tetsuya Mori, Kiminori Toyooka, Hiroshi Sudo, Kazuki Saito.

  Spatial metabolomics uses imaging mass spectrometry (IMS) to localize metabolites within tissue section. Here, we performed matrix-assisted laser desorption/ionization-Fourier transform ion cyclotron resonance-IMS (MALDI-FTICR-IMS) to identify the localization of asparaptine A, a naturally occurring inhibitor of angiotensin-converting enzyme, in green spears of asparagus (Asparagus officinalis). Spatial metabolome data were acquired in an untargeted manner. Segmentation analysis using the data characterized tissue-type-dependent and independent distribution patterns in cross-sections of asparagus spears. Moreover, asparaptine A accumulated at high levels in developing lateral shoot tissues. Quantification of asparaptine A in lateral shoots using liquid chromatography-tandem mass spectrometry (LC-MS/MS) validated the IMS analysis. These results provide valuable information for understanding the function of asparaptine A in asparagus, and identify the lateral shoot as a potential region of interest for multiomics studies to examine gene-to-metabolite associations in the asparaptine A biosynthesis.

Keywords:  Asparagus officinalis; asparaptine A; imaging mass spectrometry; spatial metabolomics; sulfur-containing metabolite

DOI:  https://doi.org/10.5511/plantbiotechnology.21.0504b
Biochim Biophys Acta Mol Cell Biol Lipids. 2021 Nov 15. pii: S1388-1981(21)00210-9. [Epub ahead of print] 159082

Lipidomic and metabolomic analysis reveals changes in biochemical pathways for non-small cell lung cancer tissues.

Eva Cífková, Radana Brumarová, Magdaléna Ovčačíková, Dana Dobešová, Kateřina Mičová, Aleš Kvasnička, Zuzana Vaňková, Jiří Šiller, Lukáš Sákra, David Friedecký, Michal Holčapek.

  Lung cancer represents one of the leading worldwide causes of cancer death, but the pathobiochemistry of this disease is still not fully understood. Here we characterize the lipidomic and metabolomic profiles of the tumor and surrounding normal tissues for 23 patients with non-small cell lung cancer. In total, 500 molecular species were identified and quantified by a combination of the lipidomic shotgun tandem mass spectrometry (MS/MS) analysis and the targeted metabolomic approach using liquid chromatography (LC) - MS/MS. The statistical evaluation includes multivariate and univariate methods with the emphasis on paired statistical approaches. Our research revealed significant changes in several biochemical pathways related to the central carbon metabolism, acylcarnitines, dipeptides as well as the disruption in the lipid metabolism observed mainly for glycerophospholipids, sphingolipids, and cholesteryl esters.

Keywords:  Lipidomics; Lung cancer; Mass spectrometry; Metabolism; Metabolomics

DOI:  https://doi.org/10.1016/j.bbalip.2021.159082
J Chromatogr A. 2021 Oct 29. pii: S0021-9673(21)00772-X. [Epub ahead of print]1660 462650

Ultra-high pressure liquid chromatography coupled to travelling wave ion mobility-time of flight mass spectrometry for the screening of pharmaceutical metabolites in wastewater samples: Application to antiretrovirals.

Tlou T Mosekiemang, Maria A Stander, André de Villiers.

  The presence of pharmaceutical compounds in the aquatic environment is a significant environmental health concern, which is exacerbated by recent evidence of the contribution of drug metabolites to the overall pharmaceutical load. In light of a recent report of the occurrence of metabolites of antiretroviral drugs (ARVDs) in wastewater, we investigate in the present work the occurrence of further ARVD metabolites in samples obtained from a domestic wastewater treatment plant in the Western Cape, South Africa. Pharmacokinetic data indicate that ARVDs are biotransformed into several positional isomeric metabolites, only two of which have been reported wastewater samples. Given the challenges associated with the separation and identification of isomeric species in complex wastewater samples, a method based on liquid chromatography hyphenated to ion mobility spectrometry-high resolution mass spectrometry (LC-IMS-HR-MS) was implemented. Gradient LC separation was achieved on a sub-2 µm reversed phase column, while the quadrupole-time-of-flight MS was operated in data independent acquisition (DIA) mode to increase spectral coverage of detected features. A mass defect filter (MDF) template was implemented to detect ARVD metabolites with known phase I and phase II mass shifts and fractional mass differences and to filter out potential interferents. IMS proved particularly useful in filtering the MS data for co-eluting species according to arrival time to provide cleaner mass spectra. This approach allowed us to confirm the presence of two known hydroxylated efavirenz and nevirapine metabolites using authentic standards, and to tentatively identify a carboxylate metabolite of abacavir previously reported in literature. Furthermore, three hydroxylated-, two sulphated and one glucuronidated metabolite of efavirenz, two hydroxylated metabolites of nevirapine and one hydroxylated metabolite of ritonavir were tentatively or putatively identified in wastewater samples for the first time. Assignment of the metabolites is discussed in terms of high resolution fragmentation data, while collisional cross section (CCS) values measured for the detected analytes are reported to facilitate further work in this area.

Keywords:  Antiretrovirals; Ion mobility spectrometry; Mass defect filtering; Metabolites; Wastewater

DOI:  https://doi.org/10.1016/j.chroma.2021.462650
Plant Biotechnol (Tokyo). 2021 Sep 25. 38(3): 305-310

A multimodal metabolomics approach using imaging mass spectrometry and liquid chromatography-tandem mass spectrometry for spatially characterizing monoterpene indole alkaloids secreted from roots.

Ryo Nakabayashi, Noriko Takeda-Kamiya, Yutaka Yamada, Tetsuya Mori, Mai Uzaki, Takashi Nirasawa, Kiminori Toyooka, Kazuki Saito.

  Plants release specialized (secondary) metabolites from their roots to communicate with other organisms, including soil microorganisms. The spatial behavior of such metabolites around these roots can help us understand roles for the communication; however, currently, they are unclear because soil-based studies are complex. Here, we established a multimodal metabolomics approach using imaging mass spectrometry (IMS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to spatially assign metabolites under laboratory conditions using agar. In a case study using Catharanthus roseus, we showed that 58 nitrogen (N)-containing metabolites are released from the roots into the agar. For the metabolite assignment, we used 15N-labeled and non-labeled LC-MS/MS data, previously reported. Four metabolite ions were identified using authentic standard compounds as derived from monoterpene indole alkaloids (MIAs) such as ajmalicine, catharanthine, serpentine, and yohimbine. An alkaloid network analysis using dot products and spinglass methods characterized five clusters to which the 58 ions belong. The analysis clustered ions from the indolic skeleton-type MIAs to a cluster, suggesting that other communities may represent distinct metabolite groups. For future chemical assignments of the serpentine community, key fragmentation patterns were characterized using the 15N-labeled and non-labeled MS/MS spectra.

Keywords:  imaging mass spectrometry; liquid chromatography-tandem mass spectrometry; metabolomics; monoterpene indole alkaloid; secretion

DOI:  https://doi.org/10.5511/plantbiotechnology.21.0504a
J Chromatogr A. 2021 Oct 31. pii: S0021-9673(21)00778-0. [Epub ahead of print]1660 462656

Automated high confidence compound identification of electron ionization mass spectra for nontargeted analysis.

Joseph Bendik, Richa Kalia, Jeet Sukumaran, William H Richardot, Eunha Hoh, Scott T Kelley.

  Nontargeted analysis based on mass spectrometry is a rising practice in environmental monitoring for identifying contaminants of emerging concern. Nontargeted analysis performed using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC/TOF-MS) generates large numbers of possible analytes. Moreover, the default spectral library similarity score-based search algorithm used by LECO® ChromaTOF® does not ensure that high similarity scores result in correct library matches. Therefore, an additional manual screening is necessary, but leads to human errors especially when dealing with large amounts of data. To improve the speed and accuracy of the chemical identification, we developed CINeMA.py (Classification Is Never Manual Again). This programming suite automates GC×GC/TOF-MS data interpretation by determining the confidence of a match between the observed analyte mass spectrum and the LECO® ChromaTOF® software generated library hit from the NIST Electron Ionization Mass Spectral (NIST EI-MS) library. Our script allows the user to evaluate the confidence of the match using an algorithmic method that mimics the manual curation process and two different machine learning approaches (neural networks and random forest). The script allows the user to adjust various parameters (e.g., similarity threshold) and study their effects on prediction accuracy. To test CINeMA.py, we used data from two different environmental contaminant studies: an EPA study on household dust and a study on stormwater runoff. Using a reference set based on the analysis performed by highly trained users of the ChromaTOF and GC×GC/TOF-MS systems, the random forest model had the highest prediction accuracies of 86% and 83% on the EPA and Stormwater data sets, respectively. The algorithmic approach had the second-best prediction accuracy (82% and 79%), while the neural network accuracy had the lowest (63% and 67%). All the approaches required less than 1 min to classify 986 observed analytes, whereas manual data analysis required hours or days to complete. Our methods were also able to detect high confidence matches missed during the manual review. Overall, CINeMA.py provides users with a powerful suite of tools that should significantly speed-up data analysis while reducing the possibilities of manual errors and discrepancies among users, and can be applicable to other GC/EI-MS instrument based nontargeted analysis.

Keywords:  ChromaTOF; Machine learning; Mass spectral comparison; Nontargeted analysis; PyAutoGUI; Suspect screening

DOI:  https://doi.org/10.1016/j.chroma.2021.462656
Bioanalysis. 2021 Nov 17.

Analytical and bioanalytical HPLC method for simultaneous estimation of 5-fluorouracil and sonidegib.

Bharath S Padya, Aswathi R Hegde, Sadhana P Mutalik, Swati Biswas, Srinivas Mutalik.

  Aim: To develop a new sensitive RP-HPLC method for simultaneous estimation of 5-fluorouracil (5-FU) and sonidegib (SDG). Materials & methods: Analytical and bioanalytical methods for simultaneous quantification of 5-FU and SDG in bulk, nanoformulations and in rat plasma were developed and validated using a gradient elution technique. Results: Separation of the analytes was effected on a Luna® C18 LC column using a mobile mixture comprising acetonitrile and acidified water. 5-FU and SDG were extracted from plasma matrix using liquid-liquid extraction. The applicability of the method was verified through single-dose oral pharmacokinetic study in Wistar rats. Conclusion: The developed methods allow a specific, sensitive and steady analytical procedure for the simultaneous estimation of 5-FU and SDG in nanoformulations and biological matrix.

Keywords:  5-fluorouracil; RP-HPLC; bioanalytical; simultaneous estimation; sonidegib

DOI:  https://doi.org/10.4155/bio-2021-0212
Anal Chem. 2021 Nov 16.

Quantification of Epigenetic DNA Modifications in the Subchromatin Structure Matrix Attachment Regions by Stable Isotope Dilution UHPLC-MS/MS Analysis.

Rui Zhang, Weiyi Lai, Hailin Wang.

To date, subchromatin structure-based quantification of epigenetic DNA modifications is limited. Matrix attachment regions (MARs), an important subchromatin structure, contain DNA elements that specifically bind chromatin to the nuclear matrix in eukaryotes and are involved in a number of diseases. Here, we exploited a high-salt extraction-based subchromatin fractionation approach for the isolation of MAR DNA and other fractions and further developed heavy stable isotope-diluted ultrahigh-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) for the specific quantification of epigenetic DNA modifications in the subchromatin structures. By this approach, we showed for the first time that the content of a DNA demethylation intermediate, 5-hydroxymethylcytosine (5hmdC), in MARs decreased significantly in four tested cell lines compared to the contents in genomic DNA. In particular, the content of DNA 5hmdC in the MARs of 293T cell lines decreased the most at approximately 41.09%. Together, our findings implicate that MAR DNA is less sensitive than genomic DNA to DNA demethylation.

DOI: https://doi.org/10.1021/acs.analchem.1c04151
Front Genet. 2021 ;12 774846

Use ggbreak to Effectively Utilize Plotting Space to Deal With Large Datasets and Outliers.

Shuangbin Xu, Meijun Chen, Tingze Feng, Li Zhan, Lang Zhou, Guangchuang Yu.

  With the rapid increase of large-scale datasets, biomedical data visualization is facing challenges. The data may be large, have different orders of magnitude, contain extreme values, and the data distribution is not clear. Here we present an R package ggbreak that allows users to create broken axes using ggplot2 syntax. It can effectively use the plotting area to deal with large datasets (especially for long sequential data), data with different magnitudes, and contain outliers. The ggbreak package increases the available visual space for a better presentation of the data and detailed annotation, thus improves our ability to interpret the data. The ggbreak package is fully compatible with ggplot2 and it is easy to superpose additional layers and applies scale and theme to adjust the plot using the ggplot2 syntax. The ggbreak package is open-source software released under the Artistic-2.0 license, and it is freely available on CRAN (https://CRAN.R-project.org/package=ggbreak) and Github (https://github.com/YuLab-SMU/ggbreak).

Keywords:  axis break; gap plot; ggplot2; long sequential data; outlier

DOI:  https://doi.org/10.3389/fgene.2021.774846
J Chromatogr B Analyt Technol Biomed Life Sci. 2021 Oct 22. pii: S1570-0232(21)00487-6. [Epub ahead of print]1186 123006

Development, validation, and application of an HPLC-MS/MS method for quantification of oxidized fatty acids in plants.

Marília Almeida-Trapp, Gezimar Donizetti de Souza, Kirti Shekhawat, Arsheed H Sheikh, Axel Mithöfer, Heribert Hirt, Edson Rodrigues-Filho.

  Oxylipins constitute a huge class of compounds produced by oxidation of long-chain unsaturated fatty acids either chemically (by radicals such as reactive oxygen species, ROS) or enzymatically (by lipoxygenases, LOX; cyclooxygenases, COX; or cytochrome P450 pathways). This process generates fatty acids peroxides, which can then be further modified in a broad range to epoxy, hydroxy, keto, ether fatty acids, and also hydrolyzed to generate small aldehydes and alcohols. In general, oxylipins are present in almost all living organisms and have a wide range of signaling, metabolic, physiological, and ecological roles depending on the particular organism and on their structure. In plants, oxylipins have been extensively studied over the past 35 years. However, these studies have focused mainly on the jasmonates and so-called green leaves volatiles. The function of early LOX products (like keto and hydroxy fatty acids) is yet not well understood in plants, where they are mainly analyzed by indirect methods or by GC-MS what requires a laborious sample preparation. Here, we developed and validated a straightforward, precise, accurate, and sensitive method for quantifying oxylipins in plant tissues using HPLC-MS/MS, with a one-step extraction procedure using low amount of plant tissues. We successfully applied this method to quantify the oxylipins in different plant species and Arabidopsis thaliana plants treated with various biotic and abiotic stress conditions.

Keywords:  Alternanthera brasiliana; Arabidopsis thaliana; HPLC-MS/MS quantification; Lipoxygenase products; Octadecanoids; Oxylipins; Plant

DOI:  https://doi.org/10.1016/j.jchromb.2021.123006
Curr Protoc. 2021 Nov;1(11): e290

High-Resolution Multi-Isotope Imaging Mass Spectrometry (MIMS) Imaging Applications in Stem Cell Biology.

G McMahon, C P Lechene.

  Multi-isotope imaging mass spectrometry (MIMS) allows the measurement of turnover of molecules within intracellular compartments with a spatial resolution down to 30 nm. We use molecules enriched in stable isotopes administered to animals by diet or injection, or to cells through the culture medium. The stable isotopes used are, in general, 15 N, 13 C, 18 O, and 2 H. For stem cell studies, we essentially use 15 N-thymidine, 13 C-thymidine, and 81 Br from BrdU. This protocol describes the practical use of MIMS with specific reference to applications in stem cell research. This includes choice and administration of stable isotope label(s), sample preparation, best practice for high-resolution imaging, secondary ion mass spectrometry using the Cameca NanoSIMS 50L, and methods for robust statistical analysis of label incorporation in regions of interest (ROI). © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Stable isotope labeling of DNA in cultured cells Basic Protocol 2: Stable isotope labeling of DNA in animals Basic Protocol 3: Preparation of Si chips, the general sample support for NanoSIMS analysis Basic Protocol 4: Stable isotope analysis of DNA replication in single nuclei in a population of cells with NanoSIMS Basic Protocol 5: Data reduction and processing.

Keywords:  BrdU; MIMS; NanoSIMS; OpenMIMS; stable isotopes; thymidine

DOI:  https://doi.org/10.1002/cpz1.290