MARS: A Multipurpose Software for Untargeted LC–MS-Based Metabolomics and Exposomics

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This article references 66 other publications.

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   Mussap, M. Special Issue on ″The Application of Metabolomics in Clinical Practice: Challenges and Opportunities″. Metabolites 2022, 12 (4), 296,  DOI: 10.3390/metabo12040296

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   Special Issue on "The Application of Metabolomics in Clinical Practice: Challenges and Opportunities"

   Mussap, Michele

   Metabolites (2022), 12 (4), 296CODEN: METALU; ISSN:2218-1989. (MDPI AG)

   There is no expanded citation for this reference.

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   Geller, S.; Lieberman, H.; Belanger, A. J.; Yew, N. S.; Kloss, A.; Ivanov, A. R. Comparison of Microflow and Analytical Flow Liquid Chromatography Coupled to Mass Spectrometry Global Metabolomics Methods Using a Urea Cycle Disorder Mouse Model. J. Proteome Res. 2022, 21 (1), 151– 163,  DOI: 10.1021/acs.jproteome.1c00628

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   Comparison of Microflow and Analytical Flow Liquid Chromatography Coupled to Mass Spectrometry Global Metabolomics Methods Using a Urea Cycle Disorder Mouse Model

   Geller, Sarah; Lieberman, Harvey; Belanger, Adam J.; Yew, Nelson S.; Kloss, Alla; Ivanov, Alexander R.

   Journal of Proteome Research (2022), 21 (1), 151-163CODEN: JPROBS; ISSN:1535-3893. (American Chemical Society)

   Microscale-based sepns. are increasingly being applied in the field of metabolomics for the anal. of small-mol. metabolites. These methods have the potential to provide improved sensitivity, less solvent waste, and reduced sample-size requirements. Ion-pair free microflow-based global metabolomics methods, which we recently reported, were further compared to anal. flow ion-pairing reagent contg. methods using a sample set from a urea cycle disorder (UCD) mouse model. Mouse urine and brain homogenate samples representing healthy, diseased, and disease-treated animals were analyzed by both methods. Data processing was performed using univariate and multivariate techniques followed by analyte trend anal. The microflow methods performed comparably to the anal. flow ion-pairing methods with the ability to sep. the three sample groups when analyzed by partial least-squares anal. The no. of detected metabolic features present after each data processing step was similar between the microflow-based methods and the ion-pairing methods in the neg. ionization mode. The obsd. analyte trend and coverage of known UCD biomarkers were the same for both evaluated approaches. The 12.5-fold redn. in sample injection vol. required for the microflow-based sepns. highlights the potential of this method to support studies with sample-size limitations.

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   Alarcon-barrera, J. C.; Kostidis, S.; Ondo-mendez, A.; Giera, M. Recent advances in metabolomics analysis for early drug development. Drug Discov Today 2022, 27 (6), 1763– 1773,  DOI: 10.1016/j.drudis.2022.02.018

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   Recent advances in metabolomics analysis for early drug development

   Alarcon-Barrera, Juan Carlos; Kostidis, Sarantos; Ondo-Mendez, Alejandro; Giera, Martin

   Drug Discovery Today (2022), 27 (6), 1763-1773CODEN: DDTOFS; ISSN:1359-6446. (Elsevier Ltd.)

   A review. The pharmaceutical industry adapted proteomics and other 'omics technologies for drug research early following their initial introduction. Although metabolomics lacked behind in this development, it has now become an accepted and widely applied approach in early drug development. Over the past few decades, metabolomics has evolved from a pure exploratory tool to a more mature and quant. biochem. technol. Several metabolomics-based platforms are now applied during the early phases of drug discovery. Metabolomics anal. assists in the definition of the physiol. response and target engagement (TE) markers as well as elucidation of the mode of action (MoA) of drug candidates under investigation. In this review, we highlight recent examples and novel developments of metabolomics analyses applied during early drug development.

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   Utpott, M.; Rodrigues, E.; Rios, A. O.; Mercali, G. D.; Flores, S. H. Metabolomics: An analytical technique for food processing evaluation. Food Chem. 2022, 366, 130685  DOI: 10.1016/j.foodchem.2021.130685

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   Metabolomics: An analytical technique for food processing evaluation

   Utpott, Michele; Rodrigues, Eliseu; Rios, Alessandro de Oliveira; Mercali, Giovana Domeneghini; Flores, Simone Hickmann

   Food Chemistry (2022), 366 (), 130685CODEN: FOCHDJ; ISSN:0308-8146. (Elsevier Ltd.)

   A review. This review aimed to retrieve the most recent research with strong impact concerning the application of metabolomics anal. in food processing. The literature reveals the high capacity of this methodol. to evaluate chem. and organoleptic transformations that occur during food prodn. Current and potential applications of metabolomics anal. will be addressed, focusing on process-compn.-function relationships. The use of the metabolomics approach to evaluate transformations in foods submitted to minimal processes, heat or cold treatments, drying, fermn., chem. and enzymic treatments and processes using innovative technologies will be discussed. Moreover, the main strategies and advantages of metabolomics-based approaches are reviewed, as well as the most used anal. platforms. Overall, metabolomics can be seen as an important tool to support academia and industry on pursuing knowledge about the transformation of raw animal or plant materials into ready-to-eat products.

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   Valentino, G.; Graziani, V.; D’abrosca, B.; Pacifico, S.; Fiorentino, A.; Scognamiglio, M. NMR-Based Plant Metabolomics in Nutraceutical Research: An Overview. Molecules 2020, 25 (6), 1444,  DOI: 10.3390/molecules25061444

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   NMR-based plant metabolomics in nutraceutical research: an overview

   Valentino, Giovanna; Graziani, Vittoria; D'Abrosca, Brigida; Pacifico, Severina; Fiorentino, Antonio; Scognamiglio, Monica

   Molecules (2020), 25 (6), 1444CODEN: MOLEFW; ISSN:1420-3049. (MDPI AG)

   A review. Few topics are able to channel the interest of researchers, the public, and industries, like nutraceuticals. The ever-increasing demand of new compds. or new sources of known active compds., along with the need of a better knowledge about their effectiveness, mode of action, safety, etc., led to a significant effort towards the development of anal. approaches able to answer the many questions related to this topic. Therefore, the application of cutting edges approaches to this area has been obsd. Among these approaches, metabolomics is a key player. Herewith, the applications of NMR-based metabolomics to nutraceutical research are discussed: after a brief overview of the anal. workflow, the use of NMR-based metabolomics to the search for new compds. or new sources of known nutraceuticals are reviewed. Then, possible applications for quality control and nutraceutical optimization are suggested. Finally, the use of NMR-based metabolomics to study the impact of nutraceuticals on human metab. is discussed.

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   Viant, M. R. Recent developments in environmental metabolomics. Mol. Biosyst 2008, 4 (10), 980– 6,  DOI: 10.1039/b805354e

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   Recent developments in environmental metabolomics

   Viant, Mark R.

   Molecular BioSystems (2008), 4 (10), 980-986CODEN: MBOIBW; ISSN:1742-206X. (Royal Society of Chemistry)

   A review. Metabolomics is increasingly being used to characterize the interactions of organisms with their natural environment. This article describes the latest developments in this vibrant field. The first section highlights environmental studies that are exploiting recent technol. advances in metabolomics, including developments in NMR spectroscopy and mass spectrometry, with a particular focus on toxicity testing in ecol. risk assessment. Subsequently, recent lab. studies of organism function and metabolic responses to stress are reviewed, including investigations of cold, heat, and anoxic stress. The importance of model organisms and systems biol. within environmental metabolomics is then highlighted. Finally, the first applications of metabolomics to actual field investigations are discussed, with a particular focus on environmental monitoring. During the past year, environmental metabolomics research has been conducted on >20 model and non-model species, including 8 freshwater and marine fish, 9 species of aquatic and terrestrial invertebrates, as well as plants and microbes, demonstrating the rapid growth of this field.

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7. 7

   Eisenbeiss, L.; Binz, T. M.; Baumgartner, M. R.; Kraemer, T.; Steuer, A. E. Cheating on forensic hair testing? Detection of potential biomarkers for cosmetically altered hair samples using untargeted hair metabolomics. Analyst 2020, 145 (20), 6586– 6599,  DOI: 10.1039/D0AN01265C

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   Cheating on forensic hair testing? Detection of potential biomarkers for cosmetically altered hair samples using untargeted hair metabolomics

   Eisenbeiss, Lisa; Binz, Tina M.; Baumgartner, Markus R.; Kraemer, Thomas; Steuer, Andrea E.

   Analyst (Cambridge, United Kingdom) (2020), 145 (20), 6586-6599CODEN: ANALAO; ISSN:0003-2654. (Royal Society of Chemistry)

   Hair anal. has become an integral part in forensic toxicol. labs. for e.g. assessment of drug or alc. abstinence. However, hair samples can be manipulated by cosmetic treatments, altering drug concns. which eventually leads to false neg. hair test results. In particular oxidative bleaching of hair samples under alk. conditions significantly affects incorporated drug concns. To date, current techniques to detect cosmetic hair adulterations bear limitations such as the implementation of cut-off values or the requirement of specialized instrumentations. As a new approach, untargeted hair metabolomics anal. was applied to detect altered, endogenous biomols. that could be used as biomarkers for oxidative cosmetic hair treatments. For this, genuine hair samples were treated in vitro with 9% hydrogen peroxide (H2O2) for 30 min. Untreated and treated hair samples were analyzed using liq.-chromatog. high-resoln. time-of-flight mass spectrometry. In total, 69 metabolites could be identified as significantly altered after hair bleaching. The majority of metabolites decreased after bleaching, yet totally degraded metabolites were most promising as suitable biomarkers. The formation of biomarker ratios of metabolites decreasing and increasing in concns. improved the discrimination of untreated and treated hair samples. With the results of this study, the high variety of identified biomarkers now offers the possibility to include single biomarkers or biomarker selections into routine screening methods for improved data interpretation of hair test results.

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   Stecher, G.; Huck, C. W.; Stoggl, W. M.; Bonn, G. K. Phytoanalysis: a challenge in phytomics. Trac-Trend Anal Chem. 2003, 22 (1), 1– 14,  DOI: 10.1016/S0165-9936(03)00108-0

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9. 9

   Frigerio, G.; Moruzzi, C.; Mercadante, R.; Schymanski, E. L.; Fustinoni, S. Development and Application of an LC-MS/MS Untargeted Exposomics Method with a Separated Pooled Quality Control Strategy. Molecules 2022, 27 (8), 2580,  DOI: 10.3390/molecules27082580

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   Development and Application of an LC-MS/MS Untargeted Exposomics Method with a Separated Pooled Quality Control Strategy

   Frigerio, Gianfranco; Moruzzi, Camilla; Mercadante, Rosa; Schymanski, Emma L.; Fustinoni, Silvia

   Molecules (2022), 27 (8), 2580CODEN: MOLEFW; ISSN:1420-3049. (MDPI AG)

   Pooled quality controls (QCs) are usually implemented within untargeted methods to improve the quality of datasets by removing features either not detected or not reproducible. However, this approach can be limiting in exposomics studies conducted on groups of exposed and nonexposed subjects, as compds. present at low levels only in exposed subjects can be dild. and thus not detected in the pooled QC. The aim of this work is to develop and apply an untargeted workflow for human biomonitoring in urine samples, implementing a novel sepd. approach for prepg. pooled quality controls. An LC-MS/MS workflow was developed and applied to a case study of smoking and non-smoking subjects. Three different pooled quality controls were prepd.: mixing an aliquot from every sample (QC-T), only from non-smokers (QC-NS), and only from smokers (QC-S). The feature tables were filtered using QC-T (T-feature list), QC-S, and QC-NS, sep. The last two feature lists were merged (SNS-feature list). A higher no. of features was obtained with the SNS-feature list than the T-feature list, resulting in identification of a higher no. of biol. significant compds. The sepd. pooled QC strategy implemented can improve the nontargeted human biomonitoring for groups of exposed and nonexposed subjects.

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10. 10

    Smirnov, D.; Mazin, P.; Osetrova, M.; Stekolshchikova, E.; Khrameeva, E. The Hitchhiker’s Guide to Untargeted Lipidomics Analysis: Practical Guidelines. Metabolites 2021, 11 (11), 713,  DOI: 10.3390/metabo11110713

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    The Hitchhiker's Guide to Untargeted Lipidomics Analysis: Practical Guidelines

    Smirnov, Dmitrii; Mazin, Pavel; Osetrova, Maria; Stekolshchikova, Elena; Khrameeva, Ekaterina

    Metabolites (2021), 11 (11), 713CODEN: METALU; ISSN:2218-1989. (MDPI AG)

    Lipidomics is a newly emerged discipline involving the identification and quantification of thousands of lipids. As a part of the omics field, lipidomics has shown rapid growth both in the no. of studies and in the size of lipidome datasets, thus, requiring specific and efficient data anal. approaches. This paper aims to provide guidelines for analyzing and interpreting lipidome data obtained using untargeted methods that rely on liq. chromatog. coupled with mass spectrometry (LC-MS) to detect and measure the intensities of lipid compds. We present a state-of-the-art untargeted LC-MS workflow for lipidomics, from study design to annotation of lipid features, focusing on practical, rather than theor., approaches for data anal., and we outline possible applications of untargeted lipidomics for biol. studies. We provide a detailed R notebook designed specifically for untargeted lipidome LC-MS data anal., which is based on xcms software.

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    Han, X.; Gross, R. W. The foundations and development of lipidomics. J. Lipid Res. 2022, 63 (2), 100164  DOI: 10.1016/j.jlr.2021.100164

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    The foundations and development of lipidomics

    Han, Xianlin; Gross, Richard W.

    Journal of Lipid Research (2022), 63 (2), 100164CODEN: JLPRAW; ISSN:1539-7262. (Elsevier Inc.)

    A review. For over a century, the importance of lipid metab. in biol. was recognized but difficult to mechanistically understand due to the lack of sensitive and robust technologies for identification and quantification of lipid mol. species. The enabling technol. breakthroughs emerged in the 1980s with the development of soft ionization methods (Electrospray Ionization and Matrix Assisted Laser Desorption/Ionization) that could identify and quantify intact individual lipid mol. species. These soft ionization technologies laid the foundations for what was to be later named the field of lipidomics. Further innovative advances in multistage fragmentation, dramatic improvements in resoln. and mass accuracy, and multiplexed sample anal. fueled the early growth of lipidomics through the early 1990s. The field exponentially grew through the use of a variety of strategic approaches, which included direct infusion, chromatog. sepn., and charge-switch derivatization, which facilitated access to the low abundance species of the lipidome. In this Thematic Review, we provide a broad perspective of the foundations, enabling advances, and predicted future directions of growth of the lipidomics field.

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    Want, E. J. LC-MS Untargeted Analysis. Methods Mol. Biol. 2018, 1738, 99– 116,  DOI: 10.1007/978-1-4939-7643-0_7

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    LC-MS untargeted analysis

    Want, Elizabeth J.

    Methods in Molecular Biology (New York, NY, United States) (2018), 1738 (Metabolic Profiling), 99-116CODEN: MMBIED; ISSN:1940-6029. (Springer)

    LC-MS untargeted anal. is a valuable tool in the field of metabolic profiling (metabonomics/metabolomics), and the applications of this technol. have grown rapidly over the past decade. LC-MS offers advantages over other anal. platforms such as speed, sensitivity, relative ease of sample prepn., and large dynamic range. As with any anal. approach, there are still drawbacks and challenges to overcome, but advances are constantly being made regarding both column chemistries and instrumentation. There are numerous untargeted LC-MS approaches which can be used in this ever-growing research field; these can be optimized depending on sample type and the nature of the study or biol. question. Some of the main LC-MS approaches for the untargeted anal. of biol. samples will be described in detail in the following protocol.

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    Brown, S. C.; Kruppa, G.; Dasseux, J. L. Metabolomics applications of FT-ICR mass spectrometry. Mass Spectrom Rev. 2005, 24 (2), 223– 31,  DOI: 10.1002/mas.20011

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    Metabolomics applications of FT-ICR mass spectrometry

    Brown, Stephen C.; Kruppa, Gary; Dasseux, Jean-Louis

    Mass Spectrometry Reviews (2005), 24 (2), 223-231CODEN: MSRVD3; ISSN:0277-7037. (John Wiley & Sons, Inc.)

    A review. Metabolomics, also known as Metabolic Profiling, is an emerging discipline under the umbrella concept of systems biol. The goal of metabolomics is to know and understand the concns. and fluxes of endogenous metabolites within a living biol. system under study. General tools are being developed for the rapid measurement of many metabolites in a single expt., most of which are mass spectrometric methods. FT-ICR has unique advantages, as a mass spectrometric method, in this regard. Applications of FT-ICR to metabolomics analyses will be discussed and reviewed in the context of the single publication currently available.

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14. 14

    Chong, J.; Soufan, O.; Li, C.; Caraus, I.; Li, S.; Bourque, G.; Wishart, D. S.; Xia, J. MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis. Nucleic Acids Res. 2018, 46 (W1), W486– W494,  DOI: 10.1093/nar/gky310

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    MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis

    Chong, Jasmine; Soufan, Othman; Li, Carin; Caraus, Iurie; Li, Shuzhao; Bourque, Guillaume; Wishart, David S.; Xia, Jianguo

    Nucleic Acids Research (2018), 46 (W1), W486-W494CODEN: NARHAD; ISSN:1362-4962. (Oxford University Press)

    We present a new update to MetaboAnalyst (version 4.0) for comprehensive metabolomic data anal., interpretation, and integration with other omics data. Since the last major update in 2015, MetaboAnalyst has continued to evolve based on user feedback and technol. advancements in the field. For this year's update, four new key features have been added to MetaboAnalyst 4.0, including: (1) real-time R command tracking and display coupled with the release of a companion MetaboAnalystR package; (2) a MS Peaks to Pathways module for prediction of pathway activity from untargeted mass spectral data using the mummichog algorithm; (3) a Biomarker Meta-anal. module for robust biomarker identification through the combination of multiple metabolomic datasets and (4) a Network Explorer module for integrative anal. of metabolomics, metagenomics, and/or transcriptomics data. The user interface of MetaboAnalyst 4.0 has been reengineered to provide a more modern look and feel, as well as to give more space and flexibility to introduce new functions. The underlying knowledge bases (compd. libraries, metabolite sets, and metabolic pathways) have also been updated based on the latest data from the Human Metabolome Database (HMDB). A Docker image of MetaboAnalyst is also available to facilitate download and local installation of MetaboAnalyst.

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15. 15

    Schmid, R.; Heuckeroth, S.; Korf, A.; Smirnov, A.; Myers, O.; Dyrlund, T. S.; Bushuiev, R.; Murray, K. J.; Hoffmann, N.; Lu, M.; Sarvepalli, A.; Zhang, Z.; Fleischauer, M.; Duhrkop, K.; Wesner, M.; Hoogstra, S. J.; Rudt, E.; Mokshyna, O.; Brungs, C.; Ponomarov, K.; Mutabdzija, L.; Damiani, T.; Pudney, C. J.; Earll, M.; Helmer, P. O.; Fallon, T. R.; Schulze, T.; Rivas-ubach, A.; Bilbao, A.; Richter, H.; Nothias, L. F.; Wang, M.; Oresic, M.; Weng, J. K.; Bocker, S.; Jeibmann, A.; Hayen, H.; Karst, U.; Dorrestein, P. C.; Petras, D.; Du, X.; Pluskal, T. Integrative analysis of multimodal mass spectrometry data in MZmine 3. Nat. Biotechnol. 2023, 41 (1), 447– 449,  DOI: 10.1038/s41587-023-01690-2

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    Integrative analysis of multimodal mass spectrometry data in MZmine 3

    Schmid, Robin; Heuckeroth, Steffen; Korf, Ansgar; Smirnov, Aleksandr; Myers, Owen; Dyrlund, Thomas S.; Bushuiev, Roman; Murray, Kevin J.; Hoffmann, Nils; Lu, Miaoshan; Sarvepalli, Abinesh; Zhang, Zheng; Fleischauer, Markus; Duhrkop, Kai; Wesner, Mark; Hoogstra, Shawn J.; Rudt, Edward; Mokshyna, Olena; Brungs, Corinna; Ponomarov, Kirill; Mutabdzija, Lana; Damiani, Tito; Pudney, Chris J.; Earll, Mark; Helmer, Patrick O.; Fallon, Timothy R.; Schulze, Tobias; Rivas-Ubach, Albert; Bilbao, Aivett; Richter, Henning; Nothias, Louis-Felix; Wang, Mingxun; Oresic, Matej; Weng, Jing-Ke; Bocker, Sebastian; Jeibmann, Astrid; Hayen, Heiko; Karst, Uwe; Dorrestein, Pieter C.; Petras, Daniel; Du, Xiuxia; Pluskal, Tomas

    Nature Biotechnology (2023), 41 (4), 447-449CODEN: NABIF9; ISSN:1087-0156. (Nature Portfolio)

    There is no expanded citation for this reference.

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    Tsugawa, H.; Ikeda, K.; Takahashi, M.; Satoh, A.; Mori, Y.; Uchino, H.; Okahashi, N.; Yamada, Y.; Tada, I.; Bonini, P.; Higashi, Y.; Okazaki, Y.; Zhou, Z.; Zhu, Z. J.; Koelmel, J.; Cajka, T.; Fiehn, O.; Saito, K.; Arita, M.; Arita, M. A lipidome atlas in MS-DIAL 4. Nat. Biotechnol. 2020, 38 (10), 1159– 1163,  DOI: 10.1038/s41587-020-0531-2

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    16

    A lipidome atlas in MS-DIAL 4

    Tsugawa, Hiroshi; Ikeda, Kazutaka; Takahashi, Mikiko; Satoh, Aya; Mori, Yoshifumi; Uchino, Haruki; Okahashi, Nobuyuki; Yamada, Yutaka; Tada, Ipputa; Bonini, Paolo; Higashi, Yasuhiro; Okazaki, Yozo; Zhou, Zhiwei; Zhu, Zheng-Jiang; Koelmel, Jeremy; Cajka, Tomas; Fiehn, Oliver; Saito, Kazuki; Arita, Masanori; Arita, Makoto

    Nature Biotechnology (2020), 38 (10), 1159-1163CODEN: NABIF9; ISSN:1087-0156. (Nature Research)

    Abstr.: We present Mass Spectrometry-Data Independent Anal. software version 4 (MS-DIAL 4), a comprehensive lipidome atlas with retention time, collision cross-section and tandem mass spectrometry information. We formulated mass spectral fragmentations of lipids across 117 lipid subclasses and included ion mobility tandem mass spectrometry. Using human, murine, algal and plant biol. samples, we annotated and semiquantified 8,051 lipids using MS-DIAL 4 with a 1-2% estd. false discovery rate. MS-DIAL 4 helps standardize lipidomics data and discover lipid pathways.

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17. 17

    Gil-de-la-fuente, A.; Godzien, J.; Saugar, S.; Garcia-carmona, R.; Badran, H.; Wishart, D. S.; Barbas, C.; Otero, A. CEU Mass Mediator 3.0: A Metabolite Annotation Tool. J. Proteome Res. 2019, 18 (2), 797– 802,  DOI: 10.1021/acs.jproteome.8b00720

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    17

    CEU Mass Mediator 3.0: A Metabolite Annotation Tool

    Gil-de-la-Fuente, Alberto; Godzien, Joanna; Saugar, Sergio; Garcia-Carmona, Rodrigo; Badran, Hasan; Wishart, David S.; Barbas, Coral; Otero, Abraham

    Journal of Proteome Research (2019), 18 (2), 797-802CODEN: JPROBS; ISSN:1535-3893. (American Chemical Society)

    CEU Mass Mediator (CMM, http://ceumass.eps.uspceu.es) is an online tool that has evolved from a simple interface to query different metabolomic databases (CMM 1.0) to a tool that unifies the compds. from these databases and, using an expert system with knowledge about the exptl. setup and the compds. properties, filters and scores the query results (CMM 2.0). Since this last major revision, CMM has continued to grow, expanding the knowledge base of its expert system and including new services to support researchers in the metabolite annotation and identification process. The information from external databases has been refreshed, and an inhouse library with oxidized lipids not present in other sources has been added. This has increased the no. of exptl. metabolites up 332,665 and the no. of predicted metabolites to 681,198. Furthermore, new taxonomy and ontol. metadata have been included. CMM has expanded its functionalities with a service for the annotation of oxidized glycerophosphocholines, a service for spectral comparison from MS2 data, and a spectral quality-assessment service to det. the reliability of a spectrum for compd. identification purposes. To facilitate the collaboration and integration of CMM with external tools and metabolomic platforms, a RESTful API has been created, and it has already been integrated into the HMDB (Human Metabolome Database). This paper will present the novel functionalities incorporated into version 3.0 of CMM.

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18. 18

    Chang, H. Y.; Colby, S. M.; Du, X.; Gomez, J. D.; Helf, M. J.; Kechris, K.; Kirkpatrick, C. R.; Li, S.; Patti, G. J.; Renslow, R. S.; Subramaniam, S.; Verma, M.; Xia, J.; Young, J. D. A Practical Guide to Metabolomics Software Development. Anal. Chem. 2021, 93 (4), 1912– 1923,  DOI: 10.1021/acs.analchem.0c03581

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    A practical guide to metabolomics software development

    Chang, Hui-Yin; Colby, Sean M.; Du, Xiuxia; Gomez, Javier D.; Helf, Maximilian J.; Kechris, Katerina; Kirkpatrick, Christine R.; Li, Shuzhao; Patti, Gary J.; Renslow, Ryan S.; Subramaniam, Shankar; Verma, Mukesh; Xia, Jianguo; Young, Jamey D.

    Analytical Chemistry (Washington, DC, United States) (2021), 93 (4), 1912-1923CODEN: ANCHAM; ISSN:0003-2700. (American Chemical Society)

    A review. A growing no. of software tools have been developed for metabolomics data processing and anal. Many new tools are contributed by metabolomics practitioners who have limited prior experience with software development, and the tools are subsequently implemented by users with expertise that ranges from basic point-and-click data anal. to advanced coding. This Perspective is intended to introduce metabolomics software users and developers to important considerations that det. the overall impact of a publicly available tool within the scientific community. The recommendations reflect the collective experience of an NIH-sponsored Metabolomics Consortium working group that was formed with the goal of researching guidelines and best practices for metabolomics tool development. The recommendations are aimed at metabolomics researchers with little formal background in programming and are organized into three stages: (i) prepn., (ii) tool development, and (ii) distribution and maintenance.

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19. 19

    Misra, B. B. New software tools, databases, and resources in metabolomics: updates from 2020. Metabolomics 2021, 17 (5), 49,  DOI: 10.1007/s11306-021-01796-1

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    New software tools, databases, and resources in metabolomics: updates from 2020

    Misra, Biswapriya B.

    Metabolomics (2021), 17 (5), 49CODEN: METAHQ; ISSN:1573-3882. (Springer)

    Abstr.: Background: Precision medicine, space exploration, drug discovery to characterization of dark chem. space of habitats and organisms, metabolomics takes a center stage in providing answers to diverse biol., biomedical, and environmental questions. With technol. advances in mass-spectrometry and spectroscopy platforms that aid in generation of information rich datasets that are complex big-data, data analytics tend to co-evolve to match the pace of anal. instrumentation. Software tools, resources, databases, and solns. help in harnessing the concealed information in the generated data for eventual translational success. Aim of the review: In this review, ∼ 85 metabolomics software resources, packages, tools, databases, and other utilities that appeared in 2020 are introduced to the research community. Key scientific concepts of review: In Table 1 the computational dependencies and downloadable links of the tools are provided, and the resources are categorized based on their utility. The review aims to keep the community of metabolomics researchers updated with all the resources developed in 2020 at a collated avenue, in line with efforts form 2015 onwards to help them find these at one place for further referencing and use.

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20. 20

    Godzien, J.; Gil de la fuente, A.; Otero, A.; Barbas, C. Chapter Fifteen - Metabolite Annotation and Identification. Compr. Anal. Chem. 2018, 82, 415– 445,  DOI: 10.1016/bs.coac.2018.07.004

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    Metabolite Annotation and identification

    Godzien, Joanna; Gil de la Fuente, Alberto; Otero, Abraham; Barbas, Coral

    Comprehensive Analytical Chemistry (2018), 82 (), 415-445CODEN: 24JWAZ ISSN:. (Elsevier B.V.)

    A review. The long list of quoted software and tools clearly illustrates the importance of the robustness and reliability of the identification process. Such a noticeable explosion of different approaches and strategies is the answer to the need for the improvement in the field of identification, since only a limited no. of signals are successfully assigned in untargeted metabolomics expts. In this point, it is important to highlight that each anal. platform has its own advantages and disadvantages with respect to the annotation process. Annotation of GC-EI-MS data is relatively nonproblematic and straightforward, the problems caused by ESI and MT shift locates CE-ESI-MS data on the second place, while LC-ESI-MS data are ranked last, due to the multiple sources of confounding signals. Paradoxically, considering the attractiveness of each technique from the metabolite coverage point of view, the opposite order is obtained, placing LC-ESI-QTOF at the first position while GC-EI-MS will be the last place. The annotation process will never be free of false identifications due to the plurality of problem sources that arise in each and every step of the metabolomics workflow. Therefore, to minimize misidentifications, systematic solns. are needed to address problems such as chromatog. issues (peak shoulders, poor retention, peak-picking errors), MS redundancy (fragments, adducts, isotopes), and noise impact (contaminants and MS signal processing artifacts). The confidence of identification is the resultant of many different aspects including the anal. platform employed and its robustness, databases and software resources, as well as personal knowledge. Although (semi)automation reduces the human factor and therefore standardizes the annotation process, curation and supervision from the researcher will never be redundant. In contrast, despite the significant development of many tools and software, the scientist's experience is invaluable.

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21. 21

    Goracci, L.; Tortorella, S.; Tiberi, P.; Pellegrino, R. M.; Di veroli, A.; Valeri, A.; Cruciani, G. Lipostar, a Comprehensive Platform-Neutral Cheminformatics Tool for Lipidomics. Anal. Chem. 2017, 89 (11), 6257– 6264,  DOI: 10.1021/acs.analchem.7b01259

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    Lipostar, a Comprehensive Platform-Neutral Cheminformatics Tool for Lipidomics

    Goracci, Laura; Tortorella, Sara; Tiberi, Paolo; Pellegrino, Roberto Maria; Di Veroli, Alessandra; Valeri, Aurora; Cruciani, Gabriele

    Analytical Chemistry (Washington, DC, United States) (2017), 89 (11), 6257-6264CODEN: ANCHAM; ISSN:0003-2700. (American Chemical Society)

    To date, the main limitations for LC-MS-based untargeted lipidomics reside in the lack of adequate computational and cheminformatics tools that are able to support the anal. of several thousands of species from biol. samples, enabling data mining and automating lipid identification and external prediction processes. To address these issues, the authors developed Lipostar, novel vendor-neutral high-throughput software that effectively supports both targeted and untargeted LC-MS lipidomics, implementing data acquisition, user-friendly multivariate anal. (to be used for model generation and new sample predictions), and advanced lipid identification protocols that can work with or without the support of preformed lipid databases. Moreover, Lipostar integrates the lipidomic processes with a full metabolite identification (MetID) procedure, essential in drug safety applications and in translational studies. Case studies demonstrating a no. of Lipostar features are also presented.

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22. 22

    Ni, Z.; Angelidou, G.; Lange, M.; Hoffmann, R.; Fedorova, M. LipidHunter Identifies Phospholipids by High-Throughput Processing of LC-MS and Shotgun Lipidomics Datasets. Anal. Chem. 2017, 89 (17), 8800– 8807,  DOI: 10.1021/acs.analchem.7b01126

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    LipidHunter Identifies Phospholipids by High-Throughput Processing of LC-MS and Shotgun Lipidomics Datasets

    Ni, Zhixu; Angelidou, Georgia; Lange, Mike; Hoffmann, Ralf; Fedorova, Maria

    Analytical Chemistry (Washington, DC, United States) (2017), 89 (17), 8800-8807CODEN: ANCHAM; ISSN:0003-2700. (American Chemical Society)

    Lipids are dynamic constituents of biol. systems, rapidly responding to any changes in physiol. conditions. Thus, there is a large interest in lipid-derived markers for diagnostic and prognostic applications, esp. in translational and systems medicine research. As lipid identification remains a bottleneck of modern untargeted lipidomics, we developed LipidHunter, a new open source software for the high-throughput identification of phospholipids in data acquired by LC-MS and shotgun expts. LipidHunter resembles a workflow of manual spectra annotation. Lipid identification is based on MS/MS data anal. in accordance with defined fragmentation rules for each phospholipid (PL) class. The software tool matches product and neutral loss signals obtained by collision-induced dissocn. to a user-defined white list of fatty acid residues and PL class-specific fragments. The identified signals are tested against elemental compn. and bulk identification provided via LIPID MAPS search. Furthermore, LipidHunter provides information-rich tabular and graphical reports allowing to trace back key identification steps and perform data quality control. Thereby, 202 discrete lipid species were identified in lipid exts. from rat primary cardiomyocytes treated with a peroxynitrite donor. Their relative quantification allowed the monitoring of dynamic reconfiguration of the cellular lipidome in response to mild nitroxidative stress.

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23. 23

    Hartler, J.; Triebl, A.; Ziegl, A.; Trotzmuller, M.; Rechberger, G. N.; Zeleznik, O. A.; Zierler, K. A.; Torta, F.; Cazenave-gassiot, A.; Wenk, M. R.; Fauland, A.; Wheelock, C. E.; Armando, A. M.; Quehenberger, O.; Zhang, Q.; Wakelam, M. J. O.; Haemmerle, G.; Spener, F.; Kofeler, H. C.; Thallinger, G. G. Deciphering lipid structures based on platform-independent decision rules. Nat. Methods 2017, 14 (12), 1171– 1174,  DOI: 10.1038/nmeth.4470

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    Deciphering lipid structures based on platform-independent decision rules

    Hartler, Juergen; Triebl, Alexander; Ziegl, Andreas; Troetzmueller, Martin; Rechberger, Gerald N.; Zeleznik, Oana A.; Zierler, Kathrin A.; Torta, Federico; Cazenave-Gassiot, Amaury; Wenk, Markus R.; Fauland, Alexander; Wheelock, Craig E.; Armando, Aaron M.; Quehenberger, Oswald; Zhang, Qifeng; Wakelam, Michael J. O.; Haemmerle, Guenter; Spener, Friedrich; Koefeler, Harald C.; Thallinger, Gerhard G.

    Nature Methods (2017), 14 (12), 1171-1174CODEN: NMAEA3; ISSN:1548-7091. (Nature Research)

    We achieve automated and reliable annotation of lipid species and their mol. structures in high-throughput data from chromatog.-coupled tandem mass spectrometry using decision rule sets embedded in Lipid Data Analyzer (LDA; http://genome.tugraz.at/lda2). Using various low- and high-resoln. mass spectrometry instruments with several collision energies, we proved the method's platform independence. We propose that the software's reliability, flexibility, and ability to identify novel lipid mol. species may now render current state-of-the-art lipid libraries obsolete.

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24. 24

    Koelmel, J. P.; Kroeger, N. M.; Ulmer, C. Z.; Bowden, J. A.; Patterson, R. E.; Cochran, J. A.; Beecher, C. W. W.; Garrett, T. J.; Yost, R. A. LipidMatch: an automated workflow for rule-based lipid identification using untargeted high-resolution tandem mass spectrometry data. BMC Bioinformatics 2017, 18 (1), 331,  DOI: 10.1186/s12859-017-1744-3

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    LipidMatch: an automated workflow for rule-based lipid identification using untargeted high-resolution tandem mass spectrometry data

    Koelmel, Jeremy P.; Kroeger, Nicholas M.; Ulmer, Candice Z.; Bowden, John A.; Patterson, Rainey E.; Cochran, Jason A.; Beecher, Christopher W. W.; Garrett, Timothy J.; Yost, Richard A.

    BMC Bioinformatics (2017), 18 (), 331/1-331/11CODEN: BBMIC4; ISSN:1471-2105. (BioMed Central Ltd.)

    Lipids are ubiquitous and serve numerous biol. functions; thus lipids have been shown to have great potential as candidates for elucidating biomarkers and pathway perturbations assocd. with disease. Methods expanding coverage of the lipidome increase the likelihood of biomarker discovery and could lead to more comprehensive understanding of disease etiol. We introduce LipidMatch, an R-based tool for lipid identification for liq. chromatog. tandem mass spectrometry workflows. LipidMatch currently has over 250,000 lipid species spanning 56 lipid types contained in in silico fragmentation libraries. Unique fragmentation libraries, compared to other open source software, include oxidized lipids, bile acids, sphingosines, and previously uncharacterized adducts, including ammoniated cardiolipins. LipidMatch uses rule-based identification. For each lipid type, the user can select which fragments must be obsd. for identification. Rule-based identification allows for correct annotation of lipids based on the fragments obsd., unlike typical identification based solely on spectral similarity scores, where over-reporting structural details that are not conferred by fragmentation data is common. Another unique feature of LipidMatch is ranking lipid identifications for a given feature by the sum of fragment intensities. For each lipid candidate, the intensities of exptl. fragments with exact mass matches to expected in silico fragments are summed. The lipid identifications with the greatest summed intensity using this ranking algorithm were comparable to other lipid identification software annotations, MS-DIAL and Greazy. For example, for features with identifications from all 3 software, 92% of LipidMatch identifications by fatty acyl constituents were corroborated by at least one other software in pos. mode and 98% in neg. ion mode. LipidMatch allows users to annotate lipids across a wide range of high resoln. tandem mass spectrometry expts., including imaging expts., direct infusion expts., and expts. employing liq. chromatog. LipidMatch leverages the most extensive in silico fragmentation libraries of freely available software. When integrated into a larger lipidomics workflow, LipidMatch may increase the probability of finding lipid-based biomarkers and detg. etiol. of disease by covering a greater portion of the lipidome and using annotation which does not over-report biol. relevant structural details of identified lipid mols.

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25. 25

    Kendrick, E. A Mass Scale Based on CH2 = 14.0000 for High Resolution Mass Spectrometry of Organic Compounds. Anal. Chem. 1963, 35 (13), 2146– 2154,  DOI: 10.1021/ac60206a048

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    Mass scale based on CH2 = 14.0000 for high-resolution mass spectrometry of organic compounds

    Kendrick, Edward

    (1963), 35 (13), 2146-54CODEN: ANCHAM; ISSN:0003-2700.

    The advantages of this scale are: (1) ions differing by one or more CH2 groups have the same mass defect; (2) the no. of precise masses to be calcd., stored, and compared with data from a sample is reduced; (3) the same defects apply in the higher mass ranges; (4) the identification of ions is simplified. Tables are presented of the mass defects for combinations of H, 12C, 13C, N, O, 32S, and 34S.

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26. 26

    Korf, A.; Vosse, C.; Schmid, R.; Helmer, P. O.; Jeck, V.; Hayen, H. Three-dimensional Kendrick mass plots as a tool for graphical lipid identification. Rapid Commun. Mass Spectrom. 2018, 32 (12), 981– 991,  DOI: 10.1002/rcm.8117

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    Three-dimensional Kendrick mass plots as a tool for graphical lipid identification

    Korf, Ansgar; Vosse, Christian; Schmid, Robin; Helmer, Patrick O.; Jeck, Viola; Hayen, Heiko

    Rapid Communications in Mass Spectrometry (2018), 32 (12), 981-991CODEN: RCMSEF; ISSN:0951-4198. (John Wiley & Sons Ltd.)

    Rationale : The rising field of lipidomics strongly relies on the identification of lipids in complex matrixes. Recent tech. advances regarding liq. chromatog. (LC) and high-resoln. mass spectrometry (HRMS) enable the mapping of the lipidome of an organism with short data acquisition times. However, interpretation and evaluation of resulting multidimensional datasets are challenging and this is still the bottleneck regarding overall anal. times. Methods : A novel adaptation of Kendrick mass plot anal. is presented for a rapid and accurate anal. of lipids in complex matrixes. Sepn. of lipids by their resp. head group was achieved via hydrophilic interaction liq. chromatog. (HILIC) coupled to HRMS. The resulting LC/HRMS datasets are processed to a list of chromatog. sepd. features by applying an optimized MZmine 2 workflow. All features are plotted in a three-dimensional Kendrick mass plot, which allows a fast identification of present lipid classes, based on equidistant features with fitting retention times and the same Kendrick mass defect. Suspected lipid classes were used for exact mass database matching to annotate features. A second three-dimensional Kendrick mass plot of annotated features of a single lipid class helps to reveal potential database mismatches, resulting in a curated list of identified lipid species. Results : The use of the novel adaptation of the Kendrick mass plot has accelerated the identification of the relevant lipid species in the green alga Chlamydomonas reinhardtii. A total of 106 species were identified within the lipid classes: phosphatidylserine, phosphatidylethanolamine, phosphatidylglycerol, phosphatidylinositol, monogalactosyldiacylglycerol, digalactosyldiacylglycerol, and sulfoquinovosyldiacylglycerol. Conclusions : This work shows how the addn. of chromatog. information, i.e. the retention time, to a classical two-dimensional Kendrick mass plot enables rapid and accurate anal. of LC/HRMS datasets, exemplified on a green alga (C. reinhardtii) sample. Three-dimensional Kendrick mass plots have improved lipid class identification and fast spotting of falsely annotated lipid species.

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27. 27

    Folberth, J.; Begemann, K.; Johren, O.; Schwaninger, M.; Othman, A. MS(2) and LC libraries for untargeted metabolomics: Enhancing method development and identification confidence. J. Chromatogr B Analyt Technol. Biomed Life Sci. 2020, 1145, 122105  DOI: 10.1016/j.jchromb.2020.122105

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    MS2 and LC libraries for untargeted metabolomics: Enhancing method development and identification confidence

    Folberth, Julica; Begemann, Kimberly; Joehren, Olaf; Schwaninger, Markus; Othman, Alaa

    Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences (2020), 1145 (), 122105CODEN: JCBAAI; ISSN:1570-0232. (Elsevier B.V.)

    As part of the "omics" technologies in the life sciences, metabolomics is becoming increasingly important. In untargeted metabolomics, unambiguous metabolite identification and the inevitable coverage bias that comes with the selection of anal. conditions present major challenges. Reliable compd. annotation is essential for translating metabolomics data into meaningful biol. information. Here, the authors developed a fast and transferable method for generating inhouse MS2 libraries to improve metabolite identification. Using the new method the authors established an inhouse MS2 library that includes over 4000 fragmentation spectra of 506 std. compds. for 6 different normalized collision energies (NCEs). Addnl., the authors generated a comprehensive liq. chromatog. (LC) library by testing 57 different LC-MS conditions for 294 compds. The authors used the library information to develop an untargeted metabolomics screen with max. coverage of the metabolome that was successfully tested in a study of 360 human serum samples. The current work demonstrates a workflow for LC-MS/MS-based metabolomics, with enhanced metabolite identification confidence and the possibility to select suitable anal. conditions according to the specific research interest.

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28. 28

    Zhao, X.; Zeng, Z.; Chen, A.; Lu, X.; Zhao, C.; Hu, C.; Zhou, L.; Liu, X.; Wang, X.; Hou, X.; Ye, Y.; Xu, G. Comprehensive Strategy to Construct In-House Database for Accurate and Batch Identification of Small Molecular Metabolites. Anal. Chem. 2018, 90 (12), 7635– 7643,  DOI: 10.1021/acs.analchem.8b01482

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    Comprehensive Strategy to Construct In-House Database for Accurate and Batch Identification of Small Molecular Metabolites

    Zhao, Xinjie; Zeng, Zhongda; Chen, Aiming; Lu, Xin; Zhao, Chunxia; Hu, Chunxiu; Zhou, Lina; Liu, Xinyu; Wang, Xiaolin; Hou, Xiaoli; Ye, Yaorui; Xu, Guowang

    Analytical Chemistry (Washington, DC, United States) (2018), 90 (12), 7635-7643CODEN: ANCHAM; ISSN:0003-2700. (American Chemical Society)

    Identification of the metabolites is an essential step in metabolomics study to interpret the regulatory mechanism of pathol. and physiol. processes. However, it is still difficult in LC-MSn-based studies because of the complexity of mass spectrometry, chem. diversity of metabolites, and deficiency of stds. database. A comprehensive strategy is developed for accurate and batch metabolite identification in nontargeted metabolomics studies. First, a well-defined procedure was applied to generate reliable and std. LC-MS2 data, including tR, MS1, and MS2 information at a std. operational procedure. An inhouse database including ∼2000 metabolites was constructed and used to identify the metabolites in nontargeted metabolic profiling by retention time calibration using internal stds., precursor ion alignment and ion fusion, auto-MS2 information extn. and selection, and database batch searching and scoring. As an application example, a pooled serum sample was analyzed to deliver the strategy, and 202 metabolites were identified in the pos. ion mode. It shows the authors' strategy is useful for LC-MSn-based nontargeted metabolomics study.

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    Garcia-jaramillo, M.; Beaver, L. M.; Truong, L.; Axton, E. R.; Keller, R. M.; Prater, M. C.; Magnusson, K. R.; Tanguay, R. L.; Stevens, J. F.; Hord, N. G. Nitrate and nitrite exposure leads to mild anxiogenic-like behavior and alters brain metabolomic profile in zebrafish. PLoS One 2020, 15 (12), e0240070  DOI: 10.1371/journal.pone.0240070

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    Nitrate and nitrite exposure leads to mild anxiogenic-like behavior and alters brain metabolomic profile in zebrafish

    Garcia-Jaramillo, Manuel; Beaver, Laura M.; Truong, Lisa; Axton, Elizabeth R.; Keller, Rosa M.; Prater, Mary C.; Magnusson, Kathy R.; Tanguay, Robyn L.; Stevens, Jan F.; Hord, Norman G.

    PLoS One (2020), 15 (12), e0240070CODEN: POLNCL; ISSN:1932-6203. (Public Library of Science)

    Dietary nitrate lowers blood pressure and improves athletic performance in humans, yet data supporting observations that it may increase cerebral blood flow and improve cognitive performance are mixed. We tested the hypothesis that nitrate and nitrite treatment would improve indicators of learning and cognitive performance in a zebrafish (Danio rerio) model. We utilized targeted and untargeted liq. chromatog.-tandem mass spectrometry (LC-MS/MS) anal. to examine the extent to which treatment resulted in changes in nitrate or nitrite concns. in the brain and altered the brain metabolome. Fish were exposed to sodium nitrate (606.9 mg/L), sodium nitrite (19.5 mg/L), or control water for 2-4 wk and free swim, startle response, and shuttle box assays were performed. Nitrate and nitrite treatment did not change fish wt., length, predator avoidance, or distance and velocity traveled in an unstressed environment. Overall, the depletion in brain metabolites is plausibly assocd. with the regulation of neuronal activity including statistically significant redns. in the inhibitory neurotransmitter γ-aminobutyric acid (GABA; 18-19%), and its precursor, glutamine (17-22%). Nitrate and nitrite treatment did not adversely affect multiple parameters of zebrafish health. It is plausible that indirect NO-mediated mechanisms may be responsible for the nitrate and nitrite-mediated effects on the brain metabolome and behavior in zebrafish.

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30. 30

    Metabolomics Workbench. https://www.metabolomicsworkbench.org/databases/externaldatabases.php (accessed April 2023).

    There is no corresponding record for this reference.
31. 31

    Vinaixa, M.; Schymanski, E. L.; Neumann, S.; Navarro, M.; Salek, R. M.; Yanes, O. Mass spectral databases for LC/MS- and GC/MS-based metabolomics: State of the field and future prospects. TrAC Trends Anal. Chem. 2016, 78, 23– 35,  DOI: 10.1016/j.trac.2015.09.005

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    Mass spectral databases for LC/MS- and GC/MS-based metabolomics: State of the field and future prospects

    Vinaixa, Maria; Schymanski, Emma L.; Neumann, Steffen; Navarro, Miriam; Salek, Reza M.; Yanes, Oscar

    TrAC, Trends in Analytical Chemistry (2016), 78 (), 23-35CODEN: TTAEDJ; ISSN:0165-9936. (Elsevier B. V.)

    At present, mass spectrometry (MS)-based metabolomics has been widely used to obtain new insights into human, plant, and microbial biochem.; drug and biomarker discovery; nutrition research; and food control. Despite the high research interest, identifying and characterizing the structure of metabolites has become a major drawback for converting raw MS data into biol. knowledge. Comprehensive and well-annotated MS-based spectral databases play a key role in serving this purpose via the formation of metabolite annotations. The main characteristics of the mass spectral databases currently used in MS-based metabolomics are reviewed in this study, underlining their advantages and limitations. In addn., the overlap of compds. with MSn (n ≥ 2) spectra from authentic chem. stds. in most public and com. databases has been calcd. for the first time. Finally, future prospects of mass spectral databases are discussed in terms of the needs posed by novel applications and instrumental advancements.

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    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BC28Xhsl2qs7s%253D&md5=2f22a47116d59cd9bcf4470847c11918
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    Wishart, D. S.; Guo, A.; Oler, E.; Wang, F.; Anjum, A.; Peters, H.; Dizon, R.; Sayeeda, Z.; Tian, S.; Lee, B. L.; Berjanskii, M.; Mah, R.; Yamamoto, M.; Jovel, J.; Torres-calzada, C.; Hiebert-giesbrecht, M.; Lui, V. W.; Varshavi, D.; Varshavi, D.; Allen, D.; Arndt, D.; Khetarpal, N.; Sivakumaran, A.; Harford, K.; Sanford, S.; Yee, K.; Cao, X.; Budinski, Z.; Liigand, J.; Zhang, L.; Zheng, J.; Mandal, R.; Karu, N.; Dambrova, M.; Schioth, H. B.; Greiner, R.; Gautam, V. HMDB 5.0: the Human Metabolome Database for 2022. Nucleic Acids Res. 2022, 50 (D1), D622– D631,  DOI: 10.1093/nar/gkab1062

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    HMDB 5.0: the human metabolome database for 2022

    Wishart, David S.; Guo, AnChi; Oler, Eponine; Wang, Fei; Anjum, Afia; Peters, Harrison; Dizon, Raynard; Sayeeda, Zinat; Tian, Siyang; Lee, Brian L.; Berjanskii, Mark; Mah, Robert; Yamamoto, Mai; Jovel, Juan; Torres-Calzada, Claudia; Hiebert-Giesbrecht, Mickel; Lui, Vicki W.; Varshavi, Dorna; Varshavi, Dorsa; Allen, Dana; Arndt, David; Khetarpal, Nitya; Sivakumaran, Aadhavya; Harford, Karxena; Sanford, Selena; Yee, Kristen; Cao, Xuan; Budinski, Zachary; Liigand, Jaanus; Zhang, Lun; Zheng, Jiamin; Mandal, Rupasri; Karu, Naama; Dambrova, Maija; Schioth, Helgi B.; Greiner, Russell; Gautam, Vasuk

    Nucleic Acids Research (2022), 50 (D1), D622-D631CODEN: NARHAD; ISSN:1362-4962. (Oxford University Press)

    A review. The Human Metabolome Database or HMDB has been providing comprehensive ref. information about human metabolites and their assocd. biol., physiol. and chem. properties since 2007. Over the past 15 years, the HMDB has grown and evolved significantly to meet the needs of the metabolomics community and respond to continuing changes in internet and computing technol. This year's update, HMDB 5.0, brings a no. of important improvements and upgrades to the database. These should make the HMDB more useful and more appealing to a larger cross-section of users. In particular, these improvements include: (i) a significant increase in the no. of metabolite entries (from 114 100 to 217 920 compds.); (ii) enhancements to the quality and depth of metabolite descriptions; (iii) the addn. of new structure, spectral and pathway visualization tools; (iv) the inclusion of many new and much more accurately predicted spectral data sets, including predicted NMR spectra, more accurately predicted MS spectra, predicted retention indexes and predicted collision cross section data and (v) enhancements to the HMDB's search functions to facilitate better compd. identification. Many other minor improvements and updates to the content, the interface, and general performance of the HMDB website have also been made. Overall, we believe these upgrades and updates should greatly enhance the HMDB's ease of use and its potential applications not only in human metabolomics but also in exposomics, lipidomics, nutritional science, biochem. and clin. chem.

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    Montenegro-burke, J. R.; Guijas, C.; Siuzdak, G. METLIN: A Tandem Mass Spectral Library of Standards. Methods Mol. Biol. 2020, 2104, 149– 163,  DOI: 10.1007/978-1-0716-0239-3_9

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    METLIN: A Tandem Mass Spectral Library of Standards

    Montenegro-Burke, J. Rafael; Guijas, Carlos; Siuzdak, Gary

    Methods in Molecular Biology (New York, NY, United States) (2020), 2104 (Computational Methods and Data Analysis for Metabolomics), 149-163CODEN: MMBIED; ISSN:1940-6029. (Springer)

    A review. Untargeted mass spectrometry metabolomics studies rely on accurate databases for the identification of metabolic features. Leveraging unique fragmentation patterns as well as characteristic dissocn. routes allows for structural information to be gained for specific metabolites and mol. classes, resp. Here we describe the evolution of METLIN as a resource for small mol. anal. as well as the tools (e.g., Fragment Similarity Search and Neutral Loss Search) used to query the database and their workflows for the identification of mol. entities. Addnl., we will discuss the functionalities of isoMETLIN, a database of isotopic metabolites, and the latest addn. to the METLIN family, METLIN-MRM, which facilitates the anal. of quant. mass spectrometry data generated with triple quadrupole instrumentation.

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    Sud, M.; Fahy, E.; Cotter, D.; Brown, A.; Dennis, E. A.; Glass, C. K.; Merrill, A. H., Jr.; Murphy, R. C.; Raetz, C. R.; Russell, D. W.; Subramaniam, S. LMSD: LIPID MAPS structure database. Nucleic Acids Res. 2007, 35 (Database issue), D527– D532,  DOI: 10.1093/nar/gkl838

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    LMSD: LIPID MAPS structure database

    Sud, Manish; Fahy, Eoin; Cotter, Dawn; Brown, Alex; Dennis, Edward A.; Glass, Christopher K.; Merrill, Alfred H., Jr.; Murphy, Robert C.; Raetz, Christian R. H.; Russell, David W.; Subramaniam, Shankar

    Nucleic Acids Research (2007), 35 (Database Iss), D527-D532CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)

    The LIPID MAPS Structure Database (LMSD) is a relational database encompassing structures and annotations of biol. relevant lipids. Structures of lipids in the database come from four sources: (i) LIPID MAPS Consortium's core labs. and partners; (ii) lipids identified by LIPID MAPS expts.; (iii) computationally generated structures for appropriate lipid classes; (iv) biol. relevant lipids manually curated from LIPID BANK, LIPIDAT and other public sources. All the lipid structures in LMSD are drawn in a consistent fashion. In addn. to a classification-based retrieval of lipids, users can search LMSD using either text-based or structure-based search options. The text-based search implementation supports data retrieval by any combination of these data fields: LIPID MAPS ID, systematic or common name, mass, formula, category, main class, and subclass data fields. The structure-based search, in conjunction with optional data fields, provides the capability to perform a substructure search or exact match for the structure drawn by the user. Search results, in addn. to structure and annotations, also include relevant links to external databases.

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    https://chemport.cas.org/services/resolver?origin=ACS&resolution=options&coi=1%3ACAS%3A528%3ADC%252BD2sXivFGktQ%253D%253D&md5=7e21955e0551313a6bea8c2a71fe76c8
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    Kind, T.; Liu, K. H.; Lee, D. Y.; Defelice, B.; Meissen, J. K.; Fiehn, O. LipidBlast in silico tandem mass spectrometry database for lipid identification. Nat. Methods 2013, 10 (8), 755– 8,  DOI: 10.1038/nmeth.2551

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    LipidBlast in silico tandem mass spectrometry database for lipid identification

    Kind, Tobias; Liu, Kwang-Hyeon; Lee, Do Yup; DeFelice, Brian; Meissen, John K.; Fiehn, Oliver

    Nature Methods (2013), 10 (8), 755-758CODEN: NMAEA3; ISSN:1548-7091. (Nature Publishing Group)

    Current tandem mass spectral libraries for lipid annotations in metabolomics are limited in size and diversity. We provide a freely available computer-generated tandem mass spectral library of 212,516 spectra covering 119,200 compds. from 26 lipid compd. classes, including phospholipids, glycerolipids, bacterial lipoglycans and plant glycolipids. We show platform independence by using tandem mass spectra from 40 different mass spectrometer types including low-resoln. and high-resoln. instruments.

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    Collins, S. L.; Koo, I.; Peters, J. M.; Smith, P. B.; Patterson, A. D. Current Challenges and Recent Developments in Mass Spectrometry-Based Metabolomics. Annu. Rev. Anal Chem. (Palo Alto Calif) 2021, 14 (1), 467– 487,  DOI: 10.1146/annurev-anchem-091620-015205

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    Current Challenges and Recent Developments in Mass Spectrometry-Based Metabolomics

    Collins Stephanie L; Koo Imhoi; Peters Jeffrey M; Patterson Andrew D; Koo Imhoi; Smith Philip B

    Annual review of analytical chemistry (Palo Alto, Calif.) (2021), 14 (1), 467-487 ISSN:.

    High-resolution mass spectrometry (MS) has advanced the study of metabolism in living systems by allowing many metabolites to be measured in a single experiment. Although improvements in mass detector sensitivity have facilitated the detection of greater numbers of analytes, compound identification strategies, feature reduction software, and data sharing have not kept up with the influx of MS data. Here, we discuss the ongoing challenges with MS-based metabolomics, including de novo metabolite identification from mass spectra, differentiation of metabolites from environmental contamination, chromatographic separation of isomers, and incomplete MS databases. Because of their popularity and sensitive detection of small molecules, this review focuses on the challenges of liquid chromatography-mass spectrometry-based methods. We then highlight important instrumentational, experimental, and computational tools that have been created to address these challenges and how they have enabled the advancement of metabolomics research.

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    Johnson, S. R.; Lange, B. M. Open-access metabolomics databases for natural product research: present capabilities and future potential. Front. Bioeng. Biotechnol. 2015, 3, 22  DOI: 10.3389/fbioe.2015.00022

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    Open-access metabolomics databases for natural product research: present capabilities and future potential

    Johnson Sean R; Lange Bernd Markus

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    Various databases have been developed to aid in assigning structures to spectral peaks observed in metabolomics experiments. In this review article, we discuss the utility of currently available open-access spectral and chemical databases for natural products discovery. We also provide recommendations on how the research community can contribute to further improvements.

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    Schrimpe-rutledge, A. C.; Codreanu, S. G.; Sherrod, S. D.; Mclean, J. A. Untargeted Metabolomics Strategies-Challenges and Emerging Directions. J. Am. Soc. Mass Spectrom. 2016, 27 (12), 1897– 1905,  DOI: 10.1007/s13361-016-1469-y

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    Untargeted Metabolomics Strategies-Challenges and Emerging Directions

    Schrimpe-Rutledge, Alexandra C.; Codreanu, Simona G.; Sherrod, Stacy D.; McLean, John A.

    Journal of the American Society for Mass Spectrometry (2016), 27 (12), 1897-1905CODEN: JAMSEF; ISSN:1044-0305. (Springer)

    A review. Metabolites are building blocks of cellular function. These species are involved in enzyme-catalyzed chem. reactions and are essential for cellular function. Upstream biol. disruptions result in a series of metabolomic changes and, as such, the metabolome holds a wealth of information that is thought to be most predictive of phenotype. Uncovering this knowledge is a work in progress. The field of metabolomics is still maturing; the community has leveraged proteomics experience when applicable and developed a range of sample prepn. and instrument methodol. along with myriad data processing and anal. approaches. Research focuses have now shifted toward a fundamental understanding of the biol. responsible for metabolomic changes. There are several types of metabolomics expts. including both targeted and untargeted analyses. While untargeted, hypothesis generating workflows exhibit many valuable attributes, challenges inherent to the approach remain. This Crit. Insight comments on these challenges, focusing on the identification process of LC-MS-based untargeted metabolomics studies-specifically in mammalian systems. Biol. interpretation of metabolomics data hinges on the ability to accurately identify metabolites. The range of confidence assocd. with identifications that is often overlooked is reviewed, and opportunities for advancing the metabolomics field are described.

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    Lippa, K. A.; Aristizabal-henao, J. J.; Beger, R. D.; Bowden, J. A.; Broeckling, C.; Beecher, C.; Clay davis, W.; Dunn, W. B.; Flores, R.; Goodacre, R.; Gouveia, G. J.; Harms, A. C.; Hartung, T.; Jones, C. M.; Lewis, M. R.; Ntai, I.; Percy, A. J.; Raftery, D.; Schock, T. B.; Sun, J.; Theodoridis, G.; Tayyari, F.; Torta, F.; Ulmer, C. Z.; Wilson, I.; Ubhi, B. K. Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC). Metabolomics 2022, 18 (4), 24,  DOI: 10.1007/s11306-021-01848-6

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    Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)

    Lippa, Katrice A.; Aristizabal-Henao, Juan J.; Beger, Richard D.; Bowden, John A.; Broeckling, Corey; Beecher, Chris; Clay Davis, W.; Dunn, Warwick B.; Flores, Roberto; Goodacre, Royston; Gouveia, Goncalo J.; Harms, Amy C.; Hartung, Thomas; Jones, Christina M.; Lewis, Matthew R.; Ntai, Ioanna; Percy, Andrew J.; Raftery, Dan; Schock, Tracey B.; Sun, Jinchun; Theodoridis, Georgios; Tayyari, Fariba; Torta, Federico; Ulmer, Candice Z.; Wilson, Ian; Ubhi, Baljit K.

    Metabolomics (2022), 18 (4), 24CODEN: METAHQ; ISSN:1573-3890. (Springer)

    Abstr.: Introduction: The metabolomics quality assurance and quality control consortium (mQACC) is enabling the identification, development, prioritization, and promotion of suitable ref. materials (RMs) to be used in quality assurance (QA) and quality control (QC) for untargeted metabolomics research. Objectives: This review aims to highlight current RMs, and methodologies used within untargeted metabolomics and lipidomics communities to ensure standardization of results obtained from data anal., interpretation and cross-study, and cross-lab. comparisons. The essence of the aims is also applicable to other 'omics areas that generate high dimensional data. Results: The potential for game-changing biochem. discoveries through mass spectrometry-based (MS) untargeted metabolomics and lipidomics are predicated on the evolution of more confident qual. (and eventually quant.) results from research labs. RMs are thus crit. QC tools to be able to assure standardization, comparability, repeatability and reproducibility for untargeted data anal., interpretation, to compare data within and across studies and across multiple labs. Std. operating procedures (SOPs) that promote, describe and exemplify the use of RMs will also improve QC for the metabolomics and lipidomics communities. Conclusions: The application of RMs described in this review may significantly improve data quality to support metabolomics and lipidomics research. The continued development and deployment of new RMs, together with interlab. studies and educational outreach and training, will further promote sound QA practices in the community.

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    Paglia, G.; Smith, A. J.; Astarita, G. Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics. Mass Spectrom Rev. 2022, 41 (5), 722– 765,  DOI: 10.1002/mas.21686

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    Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics

    Paglia, Giuseppe; Smith, Andrew J.; Astarita, Giuseppe

    Mass Spectrometry Reviews (2022), 41 (5), 722-765CODEN: MSRVD3; ISSN:0277-7037. (John Wiley & Sons, Inc.)

    A review. Researchers worldwide are taking advantage of novel, com. available, technologies, such as ion mobility mass spectrometry (IM-MS), for metabolomics and lipidomics applications in a variety of fields including life, biomedical, and food sciences. IM-MS provides three main tech. advantages over traditional LC-MS workflows. Firstly, in addn. to mass, IM-MS allows collision cross-section values to be measured for metabolites and lipids, a physicochem. identifier related to the chem. shape of an analyte that increases the confidence of identification. Second, IM-MS increases peak capacity and the signal-to-noise, improving fingerprinting as well as quantification, and better defining the spatial localization of metabolites and lipids in biol. and food samples. Third, IM-MS can be coupled with various fragmentation modes, adding new tools to improve structural characterization and mol. annotation. Here, we review the state-of-the-art in IM-MS technologies and approaches utilized to support metabolomics and lipidomics applications and we assess the challenges and opportunities in this growing field.

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    Delvaux, A.; Rathahao-paris, E.; Alves, S. Different ion mobility-mass spectrometry coupling techniques to promote metabolomics. Mass Spectrom Rev. 2022, 41 (5), 695– 721,  DOI: 10.1002/mas.21685

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    Different ion mobility-mass spectrometry coupling techniques to promote metabolomics

    Delvaux, Aurelie; Rathahao-Paris, Estelle; Alves, Sandra

    Mass Spectrometry Reviews (2022), 41 (5), 695-721CODEN: MSRVD3; ISSN:0277-7037. (John Wiley & Sons, Inc.)

    A review. Metabolomics has become increasingly popular in recent years for many applications ranging from clin. diagnosis, human health to biotechnol. questioning. Despite technol. advances, metabolomic studies are still currently limited by the difficulty of identifying all metabolites, a class of compds. with great chem. diversity. Although lengthy chromatog. analyses are often used to obtain comprehensive data, many isobar and isomer metabolites still remain unresolved, which is a crit. point for the compd. identification. Currently, ion mobility spectrometry is being explored in metabolomics as a way to improve metabolome coverage, anal. throughput and isomer sepn. In this review, all the steps of a typical workflow for untargeted metabolomics are discussed considering the use of an ion mobility instrument. An overview of metabolomics is first presented followed by a brief description of ion mobility instrumentation. The ion mobility potential for complex mixt. anal. is discussed regarding its coupling with a mass spectrometer alone, providing gas-phase sepn. before mass anal. as well as its combination with different sepn. platforms (conventional hyphenation but also multidimensional ion mobility couplings), offering multidimensional sepn. Various instrumental and anal. conditions for improving the ion mobility sepn. are also described. Finally, data mining, including software packages and visualization approaches, as well as the construction of ion mobility databases for the metabolite identification are examd.

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    A review with 46 refs. Principal component anal. and its application in chem. anal. are discussed.

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    Tanabe, K.; Hayashi, C.; Katahira, T.; Sasaki, K.; Igami, K. Multiblock metabolomics: An approach to elucidate whole-body metabolism with multiblock principal component analysis. Comput. Struct Biotechnol J. 2021, 19, 1956– 1965,  DOI: 10.1016/j.csbj.2021.04.015

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    Multiblock metabolomics: An approach to elucidate whole-body metabolism with multiblock principal component analysis

    Tanabe, Kazuhiro; Hayashi, Chihiro; Katahira, Tomoko; Sasaki, Katsuhiko; Igami, Ko

    Computational and Structural Biotechnology Journal (2021), 19 (), 1956-1965CODEN: CSBJAC; ISSN:2001-0370. (Elsevier B.V.)

    Principal component anal. (PCA) is a useful tool for omics anal. to identify underlying factors and visualize relationships between biomarkers. However, this approach is limited in addressing life complexity and further improvement is required. This study aimed to develop a new approach that combines mass spectrometry-based metabolomics with multiblock PCA to elucidate the whole-body global metabolic network, thereby generating comparable metabolite maps to clarify the metabolic relationships among several organs. To evaluate the newly developed method, Zucker diabetic fatty (ZDF) rats (n = 6) were used as type 2 diabetic models and Sprague Dawley (SD) rats (n = 6) as controls. Metabolites in the heart, kidney, and liver were analyzed by capillary electrophoresis and liq. chromatog. mass spectrometry, resp., and the detected metabolites were analyzed by multiblock PCA. More than 300 metabolites were detected in the heart, kidney, and liver. When the metabolites obtained from the three organs were analyzed with multiblock PCA, the score and loading maps obtained were highly synchronized and their metab. patterns were visually comparable. A significant finding in this study was the different expression patterns in lipid metab. among the three organs; notably triacylglycerols with polyunsatd. fatty acids or less unsatd. fatty acids showed specific accumulation patterns depending on the organs.

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    Tortorella, S.; Servili, M.; Toschi, T. G.; Cruciani, G.; Camacho, J. Subspace discriminant index to expedite exploration of multi-class omics data. Chemometrics and Intelligent Laboratory Systems 2020, 206, 104160  DOI: 10.1016/j.chemolab.2020.104160

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    Subspace discriminant index to expedite exploration of multi-class omics data

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    Omics datasets, comprehensively characterizing biol. samples at a mol. level, are continuously increasing in both complexity and dimensionality. In this scenario, there is a need for tools to improve data interpretability, expediting the process of extg. relevant biochem. information. Here we introduce the subspace discriminant index (SDI) for multi-component models, which points to the most promising components to explore pre-defined groups of observations, and can also be used to compare several modeling variants in terms of discriminative power. The SDI is esp. useful during the initial exploration of a data set, in order to make informed decisions on, e.g., pre-processing or modeling variants for further anal. The versatility and the efficiency of the proposed index is demonstrated in two real world omics case studies, including a highly complex multi-class problem. The code for the computation of the SDI is freely available in the Matlab MEDA toolbox and linked in the present manuscript. By boosting the interpretation capabilities, the SDI represents a significant addn. to the chemometric toolbox.

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    Wishart, D. S.; Oler, E.; Peters, H.; Guo, A.; Girod, S.; Han, S.; Saha, S.; Lui, V. W.; Levatte, M.; Gautam, V.; Kaddurah-daouk, R.; Karu, N. MiMeDB: the Human Microbial Metabolome Database. Nucleic Acids Res. 2023, 51 (D1), D611– D620,  DOI: 10.1093/nar/gkac868

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    MiMeDB: the human microbial metabolome database

    Wishart, David S.; Oler, Eponine; Peters, Harrison; Guo, AnChi; Girod, Sagan; Han, Scott; Saha, Sukanta; Lui, Vicki W.; LeVatte, Marcia; Gautam, Vasuk; Kaddurah-Daouk, Rima; Karu, Naama

    Nucleic Acids Research (2023), 51 (D1), D611-D620CODEN: NARHAD; ISSN:1362-4962. (Oxford University Press)

    The Human Microbial Metabolome Database (MiMeDB) is a comprehensive, multi-omic, microbiome resource that connects: (i) microbes to microbial genomes; (ii) microbial genomes to microbial metabolites; (iii) microbial metabolites to the human exposome and (iv) all of these 'omes' to human health. MiMeDB was established to consolidate the growing body of data connecting the human microbiome and the chems. it produces to both health and disease. MiMeDB contains detailed taxonomic, microbiol. and body-site location data on most known human microbes (bacteria and fungi). This microbial data is linked to extensive genomic and proteomic sequence data that is closely coupled to colorful interactive chromosomal maps. The database also houses detailed information about all the known metabolites generated by these microbes, their structural, chem. and spectral properties, the reactions and enzymes responsible for these metabolites and the primary exposome sources (food, drug, cosmetic, pollutant, etc.) that ultimately lead to the obsd. microbial metabolites in humans. Addnl., extensively referenced data about the known or presumptive health effects, measured biosample concns. and human protein targets for these compds. is provided. All of this information is housed in richly annotated, highly interactive, visually pleasing database that has been designed to be easy to search, easy to browse and easy to navigate. Currently MiMeDB contains data on 626 health effects or bioactivities, 1904 microbes, 3112 refs., 22 054 reactions, 24 254 metabolites or exposure chems., 648 861 MS and NMR spectra, 6.4 million genes and 7.6 billion DNA bases. We believe that MiMeDB represents the kind of integrated, multi-omic or systems biol. database that is needed to enable comprehensive multi-omic integration.

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    Zamora, I.; Fontaine, F.; Serra, B.; Plasencia, G. High-throughput, computer assisted, specific MetID. A revolution for drug discovery. Drug Discov Today Technol. 2013, 10 (1), e199– 205,  DOI: 10.1016/j.ddtec.2012.10.015

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    Zhao, Y. Y.; Boyd, J.; Hrudey, S. E.; Li, X. F. Characterization of new nitrosamines in drinking water using liquid chromatography tandem mass spectrometry. Environ. Sci. Technol. 2006, 40 (24), 7636– 41,  DOI: 10.1021/es061332s

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    Characterization of new nitrosamines in drinking water using liquid chromatography tandem mass spectrometry

    Zhao, Yuan-Yuan; Boyd, Jessica; Hrudey, Steve E.; Li, Xing-Fang

    Environmental Science & Technology (2006), 40 (24), 7636-7641CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)

    N-nitrosodimethylamine (NDMA), a probable human carcinogen, was detected as a disinfection byproduct (DBP) in drinking water supplies in Canada and the US. To comprehensively investigate the possible occurrence of nitrosamines in drinking water supplies, a liq. chromatog.-tandem mass spectrometry method was developed to detect thermally stable and unstable nitrosamines. This method consisted of solid phase extn. (SPE), liq. chromatog. (LC) sepn., and tandem quadrupole linear ion trap mass spectrometry (MS/MS) detection. It detd. sub-ng/L concns. of 9 nitrosamines. Isotope-labeled N-nitrosodimethylamine-d6 (NDMA-d6) was used as the surrogate std. for detg. recovery; N-nitrosodi-n-propylamine-d14 (NDPA-d14) was used as the internal std. for quantification. Method detection limits were estd. to be 0.1-10.6 ng/L, and av. recovery was 41-111% for the 9 nitrosamines; of these, NDMA, N-nitrosopyrrolidine (NPyr), N-nitrosopiperidine (NPip), and N-nitrosodiphenylamine (NDPhA) were identified and quantified in drinking water collected from 4 sites within the same distribution system. Generally, concns. of these 4 nitrosamines in this distribution system increased with increasing distance from the treatment facility, indicating the amt. of formation was greater than the amt. of decompn. in this time frame. Identification of NPip and NDPhA in drinking water systems and distribution profiles of these nitrosamines have not been previously reported. These nitrosamines are toxic and their presence as DBP in drinking water may have toxicol. relevance.

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    Asare, S. O.; Hoskins, J. N.; Blessing, R. A.; Hertzler, R. L. Mass spectrometry based fragmentation patterns of nitrosamine compounds. Rapid Commun. Mass Spectrom. 2022, 36 (8), e9261  DOI: 10.1002/rcm.9261

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    55

    Mass spectrometry based fragmentation patterns of nitrosamine compounds

    Asare, Shardrack O.; Hoskins, Jessica N.; Blessing, Richard A.; Hertzler, Russell L.

    Rapid Communications in Mass Spectrometry (2022), 36 (8), e9261CODEN: RCMSEF; ISSN:0951-4198. (John Wiley & Sons Ltd.)

    Nitrosamines are a class of mutagenic substances that can display high carcinogenic potential. New chem. entities may have the potential to form unique nitrosamines specific to the drug substance. It is therefore essential to understand the gas-phase fragmentation behavior of nitrosamine compds. to enable the development of anal. methods to characterize novel nitrosamine compds. The gas-phase fragmentation behavior of eight model nitrosamine compds. representing the common substructures seen in many small mol. pharmaceutical compds. was studied with pos. electrospray ionization tandem mass spectrometry (ESI-MS/MS). The fragmentation patterns of these compds. under various collision parameters available in com. available mass spectrometers were studied. Protonated nitrosamine compds. produced diagnostic fragment ions upon MS/MS. Three primary structure-dependent fragmentation pathways were obsd. The first pathway involves the loss of 30 Da which corresponds to the loss of the NO radical from the protonated nitrosamine compd. (Group 1). The second and third fragmentation pathways, which have not been reported for nitrosamine compds., proceed via the loss of H2O from the protonated nitrosamine compd. (Group 2), and elimination and a loss of 46 Da (loss of NH2NO) from the nitrosamine compd. (Group 3). Results presented in this work provide an overview of the gas-phase fragmentation patterns of nitrosamine compds. and may be useful in identifying novel nitrosamine compds. in complex matrixes.

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    Schymanski, E. L.; Jeon, J.; Gulde, R.; Fenner, K.; Ruff, M.; Singer, H. P.; Hollender, J. Identifying small molecules via high resolution mass spectrometry: communicating confidence. Environ. Sci. Technol. 2014, 48 (4), 2097– 8,  DOI: 10.1021/es5002105

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    Identifying Small Molecules via High Resolution Mass Spectrometry: Communicating Confidence

    Schymanski, Emma L.; Jeon, Junho; Gulde, Rebekka; Fenner, Kathrin; Ruff, Matthias; Singer, Heinz P.; Hollender, Juliane

    Environmental Science & Technology (2014), 48 (4), 2097-2098CODEN: ESTHAG; ISSN:0013-936X. (American Chemical Society)

    A method and framework for describing the identification of small mols. by high resoln. mass spectrometry (HRMS) is presented. A 5 level classification scheme was developed to indicate the proposed identification confidence levels in HRMS. The levels are confirmed structure, probable structure, substance class, unequivocal mol. formula, and exact mass of interest.

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    Creek, D. J. Stable isotope labeled metabolomics improves identification of novel metabolites and pathways. Bioanalysis 2013, 5 (15), 1807– 10,  DOI: 10.4155/bio.13.131

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    Stable isotope labeled metabolomics improves identification of novel metabolites and pathways

    Creek, Darren J.

    Bioanalysis (2013), 5 (15), 1807-1810CODEN: BIOAB4; ISSN:1757-6180. (Future Science Ltd.)

    A review. Stable isotope labeling is an established approach for investigation of the dynamics of metabolic pathways. Metabolite identification with stable isotopes, metabolic pathway elucidation are discussed.

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58. 58

    Kanehisa, M.; Goto, S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000, 28 (1), 27– 30,  DOI: 10.1093/nar/28.1.27

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    KEGG: Kyoto Encyclopedia of Genes and Genomes

    Kanehisa, Minoru; Goto, Susumu

    Nucleic Acids Research (2000), 28 (1), 27-30CODEN: NARHAD; ISSN:0305-1048. (Oxford University Press)

    KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic anal. of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metab., membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpath-ways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are esp. useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chem. compds., enzyme mols. and enzymic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation.

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59. 59

    Wishart, D. S.; Li, C.; Marcu, A.; Badran, H.; Pon, A.; Budinski, Z.; Patron, J.; Lipton, D.; Cao, X.; Oler, E.; Li, K.; Paccoud, M.; Hong, C.; Guo, A. C.; Chan, C.; Wei, W.; Ramirez-gaona, M. PathBank: a comprehensive pathway database for model organisms. Nucleic Acids Res. 2020, 48 (D1), D470– D478,  DOI: 10.1093/nar/gkz861

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    PathBank: a comprehensive pathway database for model organisms

    Wishart, David S.; Li, Carin; Marcu, Ana; Badran, Hasan; Pon, Allison; Budinski, Zachary; Patron, Jonas; Lipton, Debra; Cao, Xuan; Oler, Eponine; Li, Krissa; Paccoud, Mailys; Hong, Chelsea; Guo, An C.; Chan, Christopher; Wei, William; Ramirez-Gaona, Miguel

    Nucleic Acids Research (2020), 48 (D1), D470-D478CODEN: NARHAD; ISSN:1362-4962. (Oxford University Press)

    A review. PathBank is a new, comprehensive, visually rich pathway database contg. more than 110 000 machine-readable pathways found in 10 model organisms (Homo sapiens, Bos taurus, Rattus norvegicus, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Arabidopsis thaliana, Saccharomyces cerevisiae, Escherichia coli and Pseudomonas aeruginosa). PathBank aims to provide a pathway for every protein and a map for every metabolite. This resource is designed specifically to support pathway elucidation and pathway discovery in transcriptomics, proteomics, metabolomics and systems biol. It provides detailed, fully searchable, hyperlinked diagrams of metabolic, metabolite signaling, protein signaling, disease, drug and physiol. pathways. All PathBank pathways include information on the relevant organs, organelles, subcellular compartments, cofactors, mol. locations, chem. structures and protein quaternary structures. Each small mol. is hyperlinked to the rich data contained in public chem. databases such as HMDB or DrugBank and each protein or enzyme complex is hyperlinked to UniProt. All PathBank pathways are accompanied with refs. and detailed descriptions which provide an overview of the pathway, condition or processes depicted in each diagram. Every PathBank pathway is downloadable in several machine-readable and image formats including BioPAX, SBML, PWML, SBGN, RXN, PNG and SVG. PathBank also supports community annotations and submissions through the web-based PathWhiz pathway illustrator. The vast majority of PathBank's pathways (>95%) are not found in any other public pathway database.

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    Kapoore, R. V.; Vaidyanathan, S. Towards quantitative mass spectrometry-based metabolomics in microbial and mammalian systems. Philos. Trans., A: Math. Phys. Eng. Sci. 2016, 374 (2079), 20150363  DOI: 10.1098/rsta.2015.0363

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    Towards quantitative mass spectrometry-based metabolomics in microbial and mammalian systems

    Kapoore, Rahul Vijay; Vaidyanathan, Seetharaman

    Philosophical Transactions of the Royal Society, A: Mathematical, Physical & Engineering Sciences (2016), 374 (2079), 20150363/1-20150363/14CODEN: PTRMAD; ISSN:1364-503X. (Royal Society)

    A review. Metabolome analyses are a suite of anal. approaches that enable us to capture changes in the metabolome (small mol. wt. components, typically less than 1500 Da) in biol. systems. Mass spectrometry (MS) has been widely used for this purpose. The key challenge here is to be able to capture changes in a reproducible and reliant manner that is representative of the events that take place in vivo. Typically, the anal. is carried out in vitro, by isolating the system and extg. the metabolome. MS-based approaches enable us to capture metabolomic changes with high sensitivity and resoln. When developing the technique for different biol. systems, there are similarities in challenges and differences that are specific to the system under investigation. Here, we review some of the challenges in capturing quant. changes in the metabolome with MS based approaches, primarily in microbial and mammalian systems.

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61. 61

    Flasch, M.; Fitz, V.; Rampler, E.; Ezekiel, C. N.; Koellensperger, G.; Warth, B. Integrated Exposomics/Metabolomics for Rapid Exposure and Effect Analyses. JACS Au 2022, 2 (11), 2548– 2560,  DOI: 10.1021/jacsau.2c00433

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    61

    Integrated Exposomics/Metabolomics for Rapid Exposure and Effect Analyses

    Flasch, Mira; Fitz, Veronika; Rampler, Evelyn; Ezekiel, Chibundu N.; Koellensperger, Gunda; Warth, Benedikt

    JACS Au (2022), 2 (11), 2548-2560CODEN: JAAUCR; ISSN:2691-3704. (American Chemical Society)

    The totality of environmental exposures and lifestyle factors, commonly referred to as the exposome, is poorly understood. Measuring the myriad of chems. that humans are exposed to is immensely challenging, and identifying disrupted metabolic pathways is even more complex. Here, we present a novel technol. approach for the comprehensive, rapid, and integrated anal. of the endogenous human metabolome and the chem. exposome. By combining reverse-phase and hydrophilic interaction liq. chromatog. and fast polarity-switching, mols. with highly diverse chem. structures can be analyzed in 15 min with a single anal. run as both column's effluents are combined before anal. Std. ref. materials and authentic stds. were evaluated to critically benchmark performance. Highly sensitive median limits of detection (LODs) with 0.04μM for >140 quant. assessed endogenous metabolites and 0.08 ng/mL for the >100 model xenobiotics and human estrogens in solvent were obtained. In the matrix, the median LOD values were higher with 0.7 ng/mL (urine) and 0.5 ng/mL (plasma) for exogenous chems. To prove the dual-column approach's applicability, real-life urine samples from sub-Saharan Africa (high-exposure scenario) and Europe (low-exposure scenario) were assessed in a targeted and nontargeted manner. Our liq. chromatog. high-resoln. mass spectrometry (LC-HRMS) approach demonstrates the feasibility of quant. and simultaneously assessing the endogenous metabolome and the chem. exposome for the high-throughput measurement of environmental drivers of diseases.

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62. 62

    Pallotta, M. T.; Rossini, S.; Suvieri, C.; Coletti, A.; Orabona, C.; Macchiarulo, A.; Volpi, C.; Grohmann, U. Indoleamine 2,3-dioxygenase 1 (IDO1): an up-to-date overview of an eclectic immunoregulatory enzyme. FEBS J. 2022, 289 (20), 6099– 6118,  DOI: 10.1111/febs.16086

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    62

    Indoleamine 2,3-dioxygenase 1 (IDO1): an up-to-date overview of an eclectic immunoregulatory enzyme

    Pallotta, Maria Teresa; Rossini, Sofia; Suvieri, Chiara; Coletti, Alice; Orabona, Ciriana; Macchiarulo, Antonio; Volpi, Claudia; Grohmann, Ursula

    FEBS Journal (2022), 289 (20), 6099-6118CODEN: FJEOAC; ISSN:1742-464X. (Wiley-Blackwell)

    A review. Indoleamine 2,3-dioxygenase 1 (IDO1) catalyzes the initial rate-limiting step in the degrdn. of the essential amino acid tryptophan along the kynurenine pathway. When discovered more than 50 years ago, IDO1 was thought to be an effector mol. capable of mediating a survival strategy based on the deprivation of bacteria and tumor cells of the essential amino acid tryptophan. Since 1998, when tryptophan catabolism was discovered to be crucially involved in the maintenance of maternal T-cell tolerance, IDO1 has become the focus of several labs. around the world. Indeed, IDO1 is now considered as an authentic immune regulator not only in pregnancy, but also in autoimmune diseases, chronic inflammation, and tumor immunity. However, in the last years, a bulk of new information-including structural, biol., and functional evidence-on IDO1 has come to light. For instance, we now know that IDO1 has a peculiar conformational plasticity and, in addn. to a complex and highly regulated catalytic activity, is capable of performing a nonenzymic function that reprograms the expression profile of immune cells toward a highly immunoregulatory phenotype. With this state-of-the-art review, we aimed at gathering the most recent information obtained for this eclectic protein as well as at highlighting the major unresolved questions.

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63. 63

    Lewis-Ballester, A.; Pham, K. N.; Batabyal, D.; Karkashon, S.; Bonanno, J. B.; Poulos, T. L.; Yeh, S. R. Structural insights into substrate and inhibitor binding sites in human indoleamine 2,3-dioxygenase 1. Nat. Commun. 2017, 8 (1), 1693,  DOI: 10.1038/s41467-017-01725-8

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    63

    Structural insights into substrate and inhibitor binding sites in human indoleamine 2,3-dioxygenase 1

    Lewis-Ballester Ariel; Pham Khoa N; Karkashon Shay; Yeh Syun-Ru; Batabyal Dipanwita; Poulos Thomas L; Batabyal Dipanwita; Poulos Thomas L; Batabyal Dipanwita; Poulos Thomas L; Bonanno Jeffrey B

    Nature communications (2017), 8 (1), 1693 ISSN:.

    Human indoleamine 2,3-dioxygenase 1 (hIDO1) is an attractive cancer immunotherapeutic target owing to its role in promoting tumoral immune escape. However, drug development has been hindered by limited structural information. Here, we report the crystal structures of hIDO1 in complex with its substrate, Trp, an inhibitor, epacadostat, and/or an effector, indole ethanol (IDE). The data reveal structural features of the active site (Sa) critical for substrate activation; in addition, they disclose a new inhibitor-binding mode and a distinct small molecule binding site (Si). Structure-guided mutation of a critical residue, F270, to glycine perturbs the Si site, allowing structural determination of an inhibitory complex, where both the Sa and Si sites are occupied by Trp. The Si site offers a novel target site for allosteric inhibitors and a molecular explanation for the previously baffling substrate-inhibition behavior of the enzyme. Taken together, the data open exciting new avenues for structure-based drug design.

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64. 64

    Orecchini, E.; Belladonna, M. L.; Pallotta, M. T.; Volpi, C.; Zizi, L.; Panfili, E.; Gargaro, M.; Fallarino, F.; Rossini, S.; Suvieri, C.; Macchiarulo, A.; Bicciato, S.; Mondanelli, G.; Orabona, C. The signaling function of IDO1 incites the malignant progression of mouse B16 melanoma. Oncoimmunology 2023, 12 (1), 2170095  DOI: 10.1080/2162402X.2023.2170095

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    64

    The signaling function of IDO1 incites the malignant progression of mouse B16 melanoma

    Orecchini, E.; Belladonna, Ml; Pallotta, Mt; Volpi, C.; Zizi, L.; Panfili, E.; Gargaro, M.; Fallarino, F.; Rossini, S.; Suvieri, C.; Macchiarulo, A.; Bicciato, S.; Mondanelli, G.; Orabona, C.

    OncoImmunology (2023), 12 (1), 2170095/1CODEN: ONCOGX; ISSN:2162-402X. (Taylor & Francis, Inc.)

    Indoleamine 2,3 dioxygenase 1 (IDO1), a leader tryptophan-degrading enzyme, represents a recognized immune checkpoint mol. In neoplasia, IDO1 is often highly expressed in dendritic cells infiltrating the tumor and/or in tumor cells themselves, particularly in human melanoma. In dendritic cells, IDO1 does not merely metabolize tryptophan into kynurenine but, after phosphorylation of crit. tyrosine residues in the non-catalytic small domain, it triggers a signaling pathway prolonging its immunoregulatory effects by a feed-forward mechanism. We here investigated whether the non-enzymic function of IDO1 could also play a role in tumor cells by using B16-F10 mouse melanoma cells transfected with either the wild-type Ido1 gene (Ido1WT) or a mutated variant lacking the catalytic, but not signaling activity (Ido1H350A). As compared to the Ido1WT-transfected counterpart (B16WT), B16-F10 cells expressing Ido1H350A (B16H350A) were characterized by an in vitro accelerated growth mediated by increased Ras and Erk activities. Faster growth and malignant progression of B16H350A cells, also detectable in vivo, were found to be accompanied by a redn. in tumor-infiltrating CD8+ T cells and an increase in Foxp3+ regulatory T cells. Our data, therefore, suggest that the IDO1 signaling function can also occur in tumor cells and that alternative therapeutic approach strategies should be undertaken to effectively tackle this important immune checkpoint mol.

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65. 65

    Platten, M.; Nollen, E. A. A.; Rohrig, U. F.; Fallarino, F.; Opitz, C. A. Tryptophan metabolism as a common therapeutic target in cancer, neurodegeneration and beyond. Nat. Rev. Drug Discov 2019, 18 (5), 379– 401,  DOI: 10.1038/s41573-019-0016-5

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    Tryptophan metabolism as a common therapeutic target in cancer, neurodegeneration and beyond

    Platten, Michael; Nollen, Ellen A. A.; Roehrig, Ute F.; Fallarino, Francesca; Opitz, Christiane A.

    Nature Reviews Drug Discovery (2019), 18 (5), 379-401CODEN: NRDDAG; ISSN:1474-1776. (Nature Research)

    A review. L-Tryptophan (Trp) metab. through the kynurenine pathway (KP) is involved in the regulation of immunity, neuronal function and intestinal homeostasis. Imbalances in Trp metab. in disorders ranging from cancer to neurodegenerative disease have stimulated interest in therapeutically targeting the KP, particularly the main rate-limiting enzymes indoleamine-2,3-dioxygenase 1 (IDO1), IDO2 and tryptophan-2,3-dioxygenase (TDO) as well as kynurenine monooxygenase (KMO). However, although small-mol. IDO1 inhibitors showed promise in early-stage cancer immunotherapy clin. trials, a phase III trial was neg. This Review summarizes the physiol. and pathophysiol. roles of Trp metab., highlighting the vast opportunities and challenges for drug development in multiple diseases.

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66. 66

    Fallarino, F.; Uyttenhove, C.; Boon, T.; Gajewski, T. F. Endogenous IL-12 is necessary for rejection of P815 tumor variants in vivo. J. Immunol. 1996, 156 (3), 1095– 1100,  DOI: 10.4049/jimmunol.156.3.1095

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    Endogenous IL-12 is necessary for rejection of P815 tumor variants in vivo

    Fallarino, Francesca; Uyttenhove, Catherine; Boon, Thierry; Gajewski, Thomas F.

    Journal of Immunology (1996), 156 (3), 1095-100CODEN: JOIMA3; ISSN:0022-1767. (American Association of Immunologists)

    Although murine tumor cells have been transfected to express a multitude of different cytokines and shown to be rejected in vivo, it is unclear which of these factors might be useful to facilitate tumor antigen immunization schemes. A study of the normal immune mechanisms involved in tumor rejection when it naturally occurs should reveal crit. signals for generation of antitumor CTL in vivo. The highly transfectable variant of P815, P1.HTR, was rejected in the hind footpads by approx. 1/3 of syngeneic DBA/2 mice. Anal. of draining popliteal lymph nodes revealed a large influx of CD4+ and CD8+ T lymphocytes in all mice, indicating that a failure to reject was not due to the complete absence of an inflammatory response. However, although IL-2 and IL-3 were produced by lymph node cells from all mice, only approx. 1/3 generated a high IFN-γ response. IL-4 was not detected. To explore a role for IL-12 in the induction of the IFN-γ-producing phenotype, a histidine-tagged IL-12 fusion protein was expressed in mammalian cells and purified by nickel-chelate chromatog., and a rabbit antiserum was produced. Neutralization of IL-12 in vivo eliminated the high IFN-γ response and prevented rejection of P1.HTR tumors and also a more immunogenic tum- variant of P815, P198. Conversely, exogenous IL-12 delivered early during challenge with P1.HTR cells induced high IFN-γ prodn. and resulted in tumor rejection in most mice. Therefore, endogenous IL-12 is vital for the rejection of these tumors when it naturally occurs, supporting a role for exogenous administration of this cytokine to favor a Th1-like phenotype in the immunotherapy of cancer.

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