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Lieng B, Quaile AT, Domingo-Almenara X, Röst HL, Montenegro-Burke JR. Computational Expansion of High-Resolution-MS n Spectral Libraries. Anal Chem 2023; 95:17284-17291. [PMID: 37963318 PMCID: PMC10688228 DOI: 10.1021/acs.analchem.3c03343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 10/31/2023] [Accepted: 10/31/2023] [Indexed: 11/16/2023]
Abstract
Commonly, in MS-based untargeted metabolomics, some metabolites cannot be confidently identified due to ambiguities in resolving isobars and structurally similar species. To address this, analytical techniques beyond traditional MS2 analysis, such as MSn fragmentation, can be applied to probe metabolites for additional structural information. In MSn fragmentation, recursive cycles of activation are applied to fragment ions originating from the same precursor ion detected on an MS1 spectrum. This resonant-type collision-activated dissociation (CAD) can yield information that cannot be ascertained from MS2 spectra alone, which helps improve the performance of metabolite identification workflows. However, most approaches for metabolite identification require mass-to-charge (m/z) values measured with high resolution, as this enables the determination of accurate mass values. Unfortunately, high-resolution-MSn spectra are relatively rare in spectral libraries. Here, we describe a computational approach to generate a database of high-resolution-MSn spectra by converting existing low-resolution-MSn spectra using complementary high-resolution-MS2 spectra generated by beam-type CAD. Using this method, we have generated a database, derived from the NIST20 MS/MS database, of MSn spectral trees representing 9637 compounds and 19386 precursor ions where at least 90% of signal intensity was converted from low-to-high resolution.
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Affiliation(s)
- Brandon
Y. Lieng
- Terrence
Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S
3E1, Canada
- Department
of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
- Institute
of Biomedical Engineering, University of
Toronto, Toronto, ON M5S 3G9, Canada
| | - Andrew T. Quaile
- Terrence
Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S
3E1, Canada
- Department
of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
- Institute
of Biomedical Engineering, University of
Toronto, Toronto, ON M5S 3G9, Canada
| | - Xavier Domingo-Almenara
- Centre
for Omics Sciences, Eurecat—Technology Centre of Catalonia
& Rovira i Virgili University Joint Unit, Reus 43204, Catalonia, Spain
- Department of Electrical, Electronic and Control
Engineering, Universitat Rovira i Virgili, Tarragona 43007, Catalonia, Spain
| | - Hannes L. Röst
- Terrence
Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S
3E1, Canada
- Department
of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - J. Rafael Montenegro-Burke
- Terrence
Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S
3E1, Canada
- Department
of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada
- Institute
of Biomedical Engineering, University of
Toronto, Toronto, ON M5S 3G9, Canada
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2
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Guijas C, To A, Montenegro-Burke JR, Domingo-Almenara X, Alipio-Gloria Z, Kok BP, Saez E, Alvarez NH, Johnson KA, Siuzdak G. Drug-Initiated Activity Metabolomics Identifies Myristoylglycine as a Potent Endogenous Metabolite for Human Brown Fat Differentiation. Metabolites 2022; 12:749. [PMID: 36005620 PMCID: PMC9415469 DOI: 10.3390/metabo12080749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 08/02/2022] [Accepted: 08/04/2022] [Indexed: 11/21/2022] Open
Abstract
Worldwide, obesity rates have doubled since the 1980s and in the USA alone, almost 40% of adults are obese, which is closely associated with a myriad of metabolic diseases such as type 2 diabetes and arteriosclerosis. Obesity is derived from an imbalance between energy intake and consumption, therefore balancing energy homeostasis is an attractive target for metabolic diseases. One therapeutic approach consists of increasing the number of brown-like adipocytes in the white adipose tissue (WAT). Whereas WAT stores excess energy, brown adipose tissue (BAT) can dissipate this energy overload in the form of heat, increasing energy expenditure and thus inhibiting metabolic diseases. To facilitate BAT production a high-throughput screening approach was developed on previously known drugs using human Simpson-Golabi-Behmel Syndrome (SGBS) preadipocytes. The screening allowed us to discover that zafirlukast, an FDA-approved small molecule drug commonly used to treat asthma, was able to differentiate adipocyte precursors and white-biased adipocytes into functional brown adipocytes. However, zafirlukast is toxic to human cells at higher dosages. Drug-Initiated Activity Metabolomics (DIAM) was used to investigate zafirlukast as a BAT inducer, and the endogenous metabolite myristoylglycine was then discovered to mimic the browning properties of zafirlukast without impacting cell viability. Myristoylglycine was found to be bio-synthesized upon zafirlukast treatment and was unique in inducing brown adipocyte differentiation, raising the possibility of using endogenous metabolites and bypassing the exogenous drugs to potentially alleviate disease, in this case, obesity and other related metabolic diseases.
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Affiliation(s)
- Carlos Guijas
- Scripps Center for Metabolomics, Scripps Research, La Jolla, CA 92037, USA
| | - Andrew To
- California Institute for Biomedical Research (Calibr), Scripps Research, La Jolla, CA 92037, USA
| | - J. Rafael Montenegro-Burke
- Scripps Center for Metabolomics, Scripps Research, La Jolla, CA 92037, USA
- Department of Molecular Genetics, Donnelly Center, University of Toronto, Toronto, ON M5S 3E1, Canada
| | - Xavier Domingo-Almenara
- Scripps Center for Metabolomics, Scripps Research, La Jolla, CA 92037, USA
- Computational Metabolomics for Systems Biology Lab, Omics Sciences Unit, Eurecat—Technology Centre of Catalonia, 08005 Barcelona, Spain
| | - Zaida Alipio-Gloria
- California Institute for Biomedical Research (Calibr), Scripps Research, La Jolla, CA 92037, USA
| | - Bernard P. Kok
- Department of Molecular Medicine, Scripps Research, La Jolla, CA 92037, USA
| | - Enrique Saez
- Department of Molecular Medicine, Scripps Research, La Jolla, CA 92037, USA
| | - Nicole H. Alvarez
- California Institute for Biomedical Research (Calibr), Scripps Research, La Jolla, CA 92037, USA
| | - Kristen A. Johnson
- California Institute for Biomedical Research (Calibr), Scripps Research, La Jolla, CA 92037, USA
| | - Gary Siuzdak
- Scripps Center for Metabolomics, Scripps Research, La Jolla, CA 92037, USA
- Departments of Chemistry, Molecular, and Computational Biology, Scripps Research, La Jolla, CA 92037, USA
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3
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Rinschen MM, Palygin O, El-Meanawy A, Domingo-Almenara X, Palermo A, Dissanayake LV, Golosova D, Schafroth MA, Guijas C, Demir F, Jaegers J, Gliozzi ML, Xue J, Hoehne M, Benzing T, Kok BP, Saez E, Bleich M, Himmerkus N, Weisz OA, Cravatt BF, Krüger M, Benton HP, Siuzdak G, Staruschenko A. Accelerated lysine metabolism conveys kidney protection in salt-sensitive hypertension. Nat Commun 2022; 13:4099. [PMID: 35835746 PMCID: PMC9283537 DOI: 10.1038/s41467-022-31670-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 06/27/2022] [Indexed: 01/07/2023] Open
Abstract
Hypertension and kidney disease have been repeatedly associated with genomic variants and alterations of lysine metabolism. Here, we combined stable isotope labeling with untargeted metabolomics to investigate lysine's metabolic fate in vivo. Dietary 13C6 labeled lysine was tracked to lysine metabolites across various organs. Globally, lysine reacts rapidly with molecules of the central carbon metabolism, but incorporates slowly into proteins and acylcarnitines. Lysine metabolism is accelerated in a rat model of hypertension and kidney damage, chiefly through N-alpha-mediated degradation. Lysine administration diminished development of hypertension and kidney injury. Protective mechanisms include diuresis, further acceleration of lysine conjugate formation, and inhibition of tubular albumin uptake. Lysine also conjugates with malonyl-CoA to form a novel metabolite Nε-malonyl-lysine to deplete malonyl-CoA from fatty acid synthesis. Through conjugate formation and excretion as fructoselysine, saccharopine, and Nε-acetyllysine, lysine lead to depletion of central carbon metabolites from the organism and kidney. Consistently, lysine administration to patients at risk for hypertension and kidney disease inhibited tubular albumin uptake, increased lysine conjugate formation, and reduced tricarboxylic acid (TCA) cycle metabolites, compared to kidney-healthy volunteers. In conclusion, lysine isotope tracing mapped an accelerated metabolism in hypertension, and lysine administration could protect kidneys in hypertensive kidney disease.
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Affiliation(s)
- Markus M Rinschen
- Scripps Center for Metabolomics, Scripps Research, La Jolla, CA, 92037, USA.
- Department of Biomedicine, Aarhus University, Aarhus, Denmark.
- III. Medical Clinic, University Hospital Hamburg Eppendorf, Hamburg, Germany.
- AIAS, Aarhus Institute of Advanced Studies (AIAS), Aarhus University, Aarhus, Denmark.
| | - Oleg Palygin
- Division of Nephrology, Department of Medicine, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Ashraf El-Meanawy
- Division of Nephrology, Department of Medicine, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Xavier Domingo-Almenara
- Scripps Center for Metabolomics, Scripps Research, La Jolla, CA, 92037, USA
- Omics Sciences Unit, EURECAT, Technology Centre of Catalonia, Reus, Catalonia, Spain
| | - Amelia Palermo
- Scripps Center for Metabolomics, Scripps Research, La Jolla, CA, 92037, USA
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, USA
| | - Lashodya V Dissanayake
- Department of Molecular Pharmacology and Physiology, University of South Florida, Tampa, FL, 33602, USA
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Daria Golosova
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | | | - Carlos Guijas
- Scripps Center for Metabolomics, Scripps Research, La Jolla, CA, 92037, USA
| | - Fatih Demir
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | | | - Megan L Gliozzi
- Renal Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15261, USA
| | - Jingchuan Xue
- Scripps Center for Metabolomics, Scripps Research, La Jolla, CA, 92037, USA
| | - Martin Hoehne
- Center for Molecular Medicine Cologne, Cologne, Germany
- Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, Cologne, Germany
- Department II of Internal Medicine, University Hospital of Cologne, Cologne, Germany
| | - Thomas Benzing
- Center for Molecular Medicine Cologne, Cologne, Germany
- Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, Cologne, Germany
- Department II of Internal Medicine, University Hospital of Cologne, Cologne, Germany
| | - Bernard P Kok
- Department of Molecular Medicine, Scripps Research, La Jolla, CA, 92037, USA
| | - Enrique Saez
- Department of Molecular Medicine, Scripps Research, La Jolla, CA, 92037, USA
| | - Markus Bleich
- Institute of Physiology, University Kiel, Kiel, Germany
| | | | - Ora A Weisz
- Renal Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, 15261, USA
| | | | - Marcus Krüger
- Center for Molecular Medicine Cologne, Cologne, Germany
- Cologne Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases, Cologne, Germany
| | - H Paul Benton
- Scripps Center for Metabolomics, Scripps Research, La Jolla, CA, 92037, USA
| | - Gary Siuzdak
- Scripps Center for Metabolomics, Scripps Research, La Jolla, CA, 92037, USA.
| | - Alexander Staruschenko
- Department of Molecular Pharmacology and Physiology, University of South Florida, Tampa, FL, 33602, USA.
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA.
- James A. Haley Veterans' Hospital, Tampa, FL, 33612, USA.
- Hypertension and Kidney Research Center, University of South Florida, Tampa, FL, 33602, USA.
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4
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Guijas C, Horton LE, Hoang L, Domingo-Almenara X, Billings EM, Ware BC, Sullivan B, Siuzdak G. Microbial Metabolite 3-Indolepropionic Acid Mediates Immunosuppression. Metabolites 2022; 12:metabo12070645. [PMID: 35888769 PMCID: PMC9317520 DOI: 10.3390/metabo12070645] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 06/27/2022] [Accepted: 07/06/2022] [Indexed: 01/07/2023] Open
Abstract
The microbial-derived metabolite, 3-indolepropionic acid (3-IPA), has been intensely studied since its origins were discovered in 2009; however, 3-IPA's role in immunosuppression has had limited attention. Untargeted metabolomic analyses of T-cell exhaustion and immunosuppression, represented by dysfunctional under-responsive CD8+ T cells, reveal a potential role of 3-IPA in these responses. T-cell exhaustion was examined via infection of two genetically related mouse strains, DBA/1J and DBA/2J, with lymphocytic choriomeningitis virus (LCMV) Clone 13 (Cl13). The different mouse strains produced disparate outcomes driven by their T-cell responses. Infected DBA/2J presented with exhausted T cells and persistent infection, and DBA/1J mice died one week after infection from cytotoxic T lymphocytes (CTLs)-mediated pulmonary failure. Metabolomics revealed over 70 metabolites were altered between the DBA/1J and DBA/2J models over the course of the infection, most of them in mice with a fatal outcome. Cognitive-driven prioritization combined with statistical significance and fold change were used to prioritize the metabolites. 3-IPA, a tryptophan-derived metabolite, was identified as a high-priority candidate for testing. To test its activity 3-IPA was added to the drinking water of the mouse models during LCMV Cl13 infection, with the results showing that 3-IPA allowed the mice to survive longer. This negative immune-modulation effect might be of interest for the modulation of CTL responses in events such as autoimmune diseases, type I diabetes or even COVID-19. Moreover, 3-IPA's bacterial origin raises the possibility of targeting the microbiome to enhance CTL responses in diseases such as cancer and chronic infection.
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Affiliation(s)
- Carlos Guijas
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA; (C.G.); (L.H.); (E.M.B.)
| | - Lucy E. Horton
- Department of Immunology and Microbiology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA; (L.E.H.); (B.C.W.)
| | - Linh Hoang
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA; (C.G.); (L.H.); (E.M.B.)
| | - Xavier Domingo-Almenara
- Computational Metabolomics for Systems Biology Lab, Omics Sciences Unit, Eurecat—Technology Centre of Catalonia, 08005 Barcelona, Catalonia, Spain;
| | - Elizabeth M. Billings
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA; (C.G.); (L.H.); (E.M.B.)
| | - Brian C. Ware
- Department of Immunology and Microbiology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA; (L.E.H.); (B.C.W.)
| | - Brian Sullivan
- Department of Immunology and Microbiology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA; (L.E.H.); (B.C.W.)
- Correspondence: (B.S.); (G.S.); Tel.: +1-858-784-9425 (G.S.)
| | - Gary Siuzdak
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA; (C.G.); (L.H.); (E.M.B.)
- Departments of Chemistry, Molecular, and Computational Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA
- Correspondence: (B.S.); (G.S.); Tel.: +1-858-784-9425 (G.S.)
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5
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Montenegro-Burke JR, Kok BP, Guijas C, Domingo-Almenara X, Moon C, Galmozzi A, Kitamura S, Eckmann L, Saez E, Siuzdak GE, Wolan DW. Metabolomics activity screening of T cell-induced colitis reveals anti-inflammatory metabolites. Sci Signal 2021; 14:eabf6584. [PMID: 34582249 DOI: 10.1126/scisignal.abf6584] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- J Rafael Montenegro-Burke
- Scripps Center for Metabolomics and Mass Spectrometry, Scripps Research Institute; La Jolla, California 92037, USA
| | - Bernard P Kok
- Scripps Center for Metabolomics and Mass Spectrometry, Scripps Research Institute; La Jolla, California 92037, USA
| | - Carlos Guijas
- Scripps Center for Metabolomics and Mass Spectrometry, Scripps Research Institute; La Jolla, California 92037, USA
| | - Xavier Domingo-Almenara
- Scripps Center for Metabolomics and Mass Spectrometry, Scripps Research Institute; La Jolla, California 92037, USA
| | - Clara Moon
- Department of Molecular Medicine, Scripps Research Institute, La Jolla, CA 92037, USA
| | - Andrea Galmozzi
- Department of Molecular Medicine, Scripps Research Institute, La Jolla, CA 92037, USA
| | - Seiya Kitamura
- Department of Molecular Medicine, Scripps Research Institute, La Jolla, CA 92037, USA
| | - Lars Eckmann
- Department of Medicine, University of California, La Jolla CA 92093, USA
| | - Enrique Saez
- Department of Molecular Medicine, Scripps Research Institute, La Jolla, CA 92037, USA
| | - Gary E Siuzdak
- Scripps Center for Metabolomics and Mass Spectrometry, Scripps Research Institute; La Jolla, California 92037, USA.,Department of Structural and Computational Biology, Scripps Research Institute, La Jolla, CA 92037, USA
| | - Dennis W Wolan
- Department of Molecular Medicine, Scripps Research Institute, La Jolla, CA 92037, USA.,Department of Structural and Computational Biology, Scripps Research Institute, La Jolla, CA 92037, USA
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Sidibé J, Domingo-Almenara X, Julijana I, Augsburger M, Thomas A. XCMS-MRM et METLIN-MRM : outils bio-informatiques pour l’analyse ciblée de petites molécules appliqués à la toxicologie. Toxicologie Analytique et Clinique 2020. [DOI: 10.1016/j.toxac.2020.09.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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7
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Guijas C, Montenegro-Burke JR, Cintron-Colon R, Domingo-Almenara X, Sanchez-Alavez M, Aguirre CA, Shankar K, Majumder ELW, Billings E, Conti B, Siuzdak G. Metabolic adaptation to calorie restriction. Sci Signal 2020; 13:13/648/eabb2490. [PMID: 32900879 DOI: 10.1126/scisignal.abb2490] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Calorie restriction (CR) enhances health span (the length of time that an organism remains healthy) and increases longevity across species. In mice, these beneficial effects are partly mediated by the lowering of core body temperature that occurs during CR. Conversely, the favorable effects of CR on health span are mitigated by elevating ambient temperature to thermoneutrality (30°C), a condition in which hypothermia is blunted. In this study, we compared the global metabolic response to CR of mice housed at 22°C (the standard housing temperature) or at 30°C and found that thermoneutrality reverted 39 and 78% of total systemic or hypothalamic metabolic variations caused by CR, respectively. Systemic changes included pathways that control fuel use and energy expenditure during CR. Cognitive computing-assisted analysis of these metabolomics results helped to prioritize potential active metabolites that modulated the hypothermic response to CR. Last, we demonstrated with pharmacological approaches that nitric oxide (NO) produced through the citrulline-NO pathway promotes CR-triggered hypothermia and that leucine enkephalin directly controls core body temperature when exogenously injected into the hypothalamus. Because thermoneutrality counteracts CR-enhanced health span, the multiple metabolites and pathways altered by thermoneutrality may represent targets for mimicking CR-associated effects.
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Affiliation(s)
- Carlos Guijas
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA.
| | - J Rafael Montenegro-Burke
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Rigo Cintron-Colon
- Department of Molecular Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Xavier Domingo-Almenara
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Manuel Sanchez-Alavez
- Department of Molecular Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Carlos A Aguirre
- Department of Molecular Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Kokila Shankar
- Department of Molecular Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Erica L-W Majumder
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Elizabeth Billings
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Bruno Conti
- Department of Molecular Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA. .,Department of Neuroscience and Dorris Neuroscience Center, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA
| | - Gary Siuzdak
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA. .,Departments of Chemistry, Molecular, and Computational Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, CA 92037, USA
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8
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Xue J, Domingo-Almenara X, Guijas C, Palermo A, Rinschen MM, Isbell J, Benton HP, Siuzdak G. Enhanced in-Source Fragmentation Annotation Enables Novel Data Independent Acquisition and Autonomous METLIN Molecular Identification. Anal Chem 2020; 92:6051-6059. [DOI: 10.1021/acs.analchem.0c00409] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- Jingchuan Xue
- Scripps Center for Metabolomics and Department of Molecular and Computational Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Xavier Domingo-Almenara
- Centre for Omic Sciences, EURECAT − Technology Centre of Catalonia and Rovira i Virgili University Joint Unit, Reus, Catalonia, Spain
| | - Carlos Guijas
- Scripps Center for Metabolomics and Department of Molecular and Computational Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Amelia Palermo
- Scripps Center for Metabolomics and Department of Molecular and Computational Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Markus M. Rinschen
- Scripps Center for Metabolomics and Department of Molecular and Computational Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - John Isbell
- Discovery Chemistry, Genomics Institute of the Novartis Research Foundation, Metabolism and Pharmacokinetics, San Diego, California 92121, United States
| | - H. Paul Benton
- Scripps Center for Metabolomics and Department of Molecular and Computational Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Gary Siuzdak
- Scripps Center for Metabolomics and Department of Molecular and Computational Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
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Abstract
XCMS is one of the most used software for liquid chromatography-mass spectrometry (LC-MS) data processing and it exists both as an R package and as a cloud-based platform known as XCMS Online. In this chapter, we first overview the nature of LC-MS data to contextualize the need for data processing software. Next, we describe the algorithms used by XCMS and the role that the different user-defined parameters play in the data processing. Finally, we describe the extended capabilities of XCMS Online.
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Affiliation(s)
| | - Gary Siuzdak
- Scripps Center for Metabolomics, The Scripps Research Institute, La Jolla, CA, USA
- Department of Molecular and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA
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10
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Rinschen MM, Palygin O, Guijas C, Palermo A, Palacio-Escat N, Domingo-Almenara X, Montenegro-Burke R, Saez-Rodriguez J, Staruschenko A, Siuzdak G. Metabolic rewiring of the hypertensive kidney. Sci Signal 2019; 12:12/611/eaax9760. [PMID: 31822592 DOI: 10.1126/scisignal.aax9760] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Hypertension is a persistent epidemic across the developed world that is closely associated with kidney disease. Here, we applied a metabolomic, phosphoproteomic, and proteomic strategy to analyze the effect of hypertensive insults on kidneys. Our data revealed the metabolic aspects of hypertension-induced glomerular sclerosis, including lipid breakdown at early disease stages and activation of anaplerotic pathways to regenerate energy equivalents to counter stress. For example, branched-chain amino acids and proline, required for collagen synthesis, were depleted in glomeruli at early time points. Furthermore, indicators of metabolic stress were reflected by low amounts of ATP and NADH and an increased abundance of oxidized lipids derived from lipid breakdown. These processes were specific to kidney glomeruli where metabolic signaling occurred through mTOR and AMPK signaling. Quantitative phosphoproteomics combined with computational modeling suggested that these processes controlled key molecules in glomeruli and specifically podocytes, including cytoskeletal components and GTP-binding proteins, which would be expected to compete for decreasing amounts of GTP at early time points. As a result, glomeruli showed increased expression of metabolic enzymes of central carbon metabolism, amino acid degradation, and lipid oxidation, findings observed in previously published studies from other disease models and patients with glomerular damage. Overall, multilayered omics provides an overview of hypertensive kidney damage and suggests that metabolic or dietary interventions could prevent and treat glomerular disease and hypertension-induced nephropathy.
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Affiliation(s)
- Markus M Rinschen
- Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, La Jolla, CA 92122, USA.,Department II of Internal Medicine and Center for Molecular Medicine, University of Cologne, Cologne 50931, Germany
| | - Oleg Palygin
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA
| | - Carlos Guijas
- Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, La Jolla, CA 92122, USA
| | - Amelia Palermo
- Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, La Jolla, CA 92122, USA
| | - Nicolas Palacio-Escat
- COMBINE-Joint Research Center for Computational Biomedicine RWTH Aachen University, Aachen 52074, Germany.,Institute of Computational Biomedicine, Bioquant, Faculty of Medicine and Heidelberg University Hospital, Heidelberg University, Heidelberg 69120, Germany.,Faculty of Biosciences, University of Heidelberg, Heidelberg 69120, Germany
| | - Xavier Domingo-Almenara
- Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, La Jolla, CA 92122, USA
| | - Rafael Montenegro-Burke
- Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, La Jolla, CA 92122, USA
| | - Julio Saez-Rodriguez
- COMBINE-Joint Research Center for Computational Biomedicine RWTH Aachen University, Aachen 52074, Germany.,Institute of Computational Biomedicine, Bioquant, Faculty of Medicine and Heidelberg University Hospital, Heidelberg University, Heidelberg 69120, Germany.,Molecular Medicine Partnership Unit (MMPU), European Molecular Biology Laboratory and Heidelberg University, Heidelberg 69120, Germany
| | - Alexander Staruschenko
- Department of Physiology, Medical College of Wisconsin, Milwaukee, WI 53226, USA. .,Clement J. Zablocki VA Medical Center, Milwaukee, WI 53295, USA
| | - Gary Siuzdak
- Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, La Jolla, CA 92122, USA.
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11
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Domingo-Almenara X, Montenegro-Burke JR, Guijas C, Majumder ELW, Benton HP, Siuzdak G. Autonomous METLIN-Guided In-source Fragment Annotation for Untargeted Metabolomics. Anal Chem 2019; 91:3246-3253. [PMID: 30681830 DOI: 10.1021/acs.analchem.8b03126] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Computational metabolite annotation in untargeted profiling aims at uncovering neutral molecular masses of underlying metabolites and assign those with putative identities. Existing annotation strategies rely on the observation and annotation of adducts to determine metabolite neutral masses. However, a significant fraction of features usually detected in untargeted experiments remains unannotated, which limits our ability to determine neutral molecular masses. Despite the availability of tools to annotate, relatively few of them benefit from the inherent presence of in-source fragments in liquid chromatography-electrospray ionization-mass spectrometry. In this study, we introduce a strategy to annotate in-source fragments in untargeted data using low-energy tandem mass spectrometry (MS) spectra from the METLIN library. Our algorithm, MISA (METLIN-guided in-source annotation), compares detected features against low-energy fragments from MS/MS spectra, enabling robust annotation and putative identification of metabolic features based on low-energy spectral matching. The algorithm was evaluated through an annotation analysis of a total of 140 metabolites across three different sets of biological samples analyzed with liquid chromatography-mass spectrometry. Results showed that, in cases where adducts were not formed or detected, MISA was able to uncover neutral molecular masses by in-source fragment matching. MISA was also able to provide putative metabolite identities via two annotation scores. These scores take into account the number of in-source fragments matched and the relative intensity similarity between the experimental data and the reference low-energy MS/MS spectra. Overall, results showed that in-source fragmentation is a highly frequent phenomena that should be considered for comprehensive feature annotation. Thus, combined with adduct annotation, this strategy adds a complementary annotation layer, enabling in-source fragments to be annotated and increasing putative identification confidence. The algorithm is integrated into the XCMS Online platform and is freely available at http://xcmsonline.scripps.edu .
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12
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Huan T, Palermo A, Ivanisevic J, Rinehart D, Edler D, Phommavongsay T, Benton HP, Guijas C, Domingo-Almenara X, Warth B, Siuzdak G. Autonomous Multimodal Metabolomics Data Integration for Comprehensive Pathway Analysis and Systems Biology. Anal Chem 2018; 90:8396-8403. [PMID: 29893550 DOI: 10.1021/acs.analchem.8b00875] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Comprehensive metabolomic data can be achieved using multiple orthogonal separation and mass spectrometry (MS) analytical techniques. However, drawing biologically relevant conclusions from this data and combining it with additional layers of information collected by other omic technologies present a significant bioinformatic challenge. To address this, a data processing approach was designed to automate the comprehensive prediction of dysregulated metabolic pathways/networks from multiple data sources. The platform autonomously integrates multiple MS-based metabolomics data types without constraints due to different sample preparation/extraction, chromatographic separation, or MS detection method. This multimodal analysis streamlines the extraction of biological information from the metabolomics data as well as the contextualization within proteomics and transcriptomics data sets. As a proof of concept, this multimodal analysis approach was applied to a colorectal cancer (CRC) study, in which complementary liquid chromatography-mass spectrometry (LC-MS) data were combined with proteomic and transcriptomic data. Our approach provided a highly resolved overview of colon cancer metabolic dysregulation, with an average 17% increase of detected dysregulated metabolites per pathway and an increase in metabolic pathway prediction confidence. Moreover, 95% of the altered metabolic pathways matched with the dysregulated genes and proteins, providing additional validation at a systems level. The analysis platform is currently available via the XCMS Online ( XCMSOnline.scripps.edu ).
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Affiliation(s)
| | | | - Julijana Ivanisevic
- Metabolomics Platform, Faculty of Biology and Medicine , University of Lausanne , CH-1005 Lausanne , Switzerland
| | | | - David Edler
- Department of Molecular Medicine and Surgery , Karolinska Institute , 171 77 Stockholm , Sweden
| | | | | | | | | | - Benedikt Warth
- Department of Food Chemistry and Toxicology, Faculty of Chemistry and Vienna Metabolomics Center (VIME) , University of Vienna , Währingerstrasse 38 , 1090 Vienna , Austria
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13
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Guijas C, Montenegro-Burke JR, Domingo-Almenara X, Palermo A, Warth B, Hermann G, Koellensperger G, Huan T, Uritboonthai W, Aisporna AE, Wolan DW, Spilker ME, Benton HP, Siuzdak G. METLIN: A Technology Platform for Identifying Knowns and Unknowns. Anal Chem 2018; 90:3156-3164. [PMID: 29381867 PMCID: PMC5933435 DOI: 10.1021/acs.analchem.7b04424] [Citation(s) in RCA: 576] [Impact Index Per Article: 96.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
METLIN originated as a database to characterize known metabolites and has since expanded into a technology platform for the identification of known and unknown metabolites and other chemical entities. Through this effort it has become a comprehensive resource containing over 1 million molecules including lipids, amino acids, carbohydrates, toxins, small peptides, and natural products, among other classes. METLIN's high-resolution tandem mass spectrometry (MS/MS) database, which plays a key role in the identification process, has data generated from both reference standards and their labeled stable isotope analogues, facilitated by METLIN-guided analysis of isotope-labeled microorganisms. The MS/MS data, coupled with the fragment similarity search function, expand the tool's capabilities into the identification of unknowns. Fragment similarity search is performed independent of the precursor mass, relying solely on the fragment ions to identify similar structures within the database. Stable isotope data also facilitate characterization by coupling the similarity search output with the isotopic m/ z shifts. Examples of both are demonstrated here with the characterization of four previously unknown metabolites. METLIN also now features in silico MS/MS data, which has been made possible through the creation of algorithms trained on METLIN's MS/MS data from both standards and their isotope analogues. With these informatic and experimental data features, METLIN is being designed to address the characterization of known and unknown molecules.
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Affiliation(s)
- Carlos Guijas
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - J. Rafael Montenegro-Burke
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Xavier Domingo-Almenara
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Amelia Palermo
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Benedikt Warth
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
- Department of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna, Waehringerstrasse 38, Vienna 1090, Austria
| | - Gerrit Hermann
- Institute of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringerstrasse 38, Vienna 1090, Austria
- ISOtopic Solutions, Waehringerstrasse 38, Vienna 1090, Austria
| | - Gunda Koellensperger
- Institute of Analytical Chemistry, Faculty of Chemistry, University of Vienna, Waehringerstrasse 38, Vienna 1090, Austria
| | - Tao Huan
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Winnie Uritboonthai
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Aries E. Aisporna
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Dennis W. Wolan
- Departments of Molecular and Experimental Medicine, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Mary E. Spilker
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - H. Paul Benton
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Gary Siuzdak
- Scripps Center for Metabolomics, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
- Departments of Chemistry, Molecular, and Computational Biology, The Scripps Research Institute, 10550 North Torrey Pines Road, La Jolla, California 92037, United States
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14
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Abstract
Metabolite identification is still considered an imposing bottleneck in liquid chromatography mass spectrometry (LC/MS) untargeted metabolomics. The identification workflow usually begins with detecting relevant LC/MS peaks via peak-picking algorithms and retrieving putative identities based on accurate mass searching. However, accurate mass search alone provides poor evidence for metabolite identification. For this reason, computational annotation is used to reveal the underlying metabolites monoisotopic masses, improving putative identification in addition to confirmation with tandem mass spectrometry. This review examines LC/MS data from a computational and analytical perspective, focusing on the occurrence of neutral losses and in-source fragments, to understand the challenges in computational annotation methodologies. Herein, we examine the state-of-the-art strategies for computational annotation including: (i) peak grouping or full scan (MS1) pseudo-spectra extraction, i.e., clustering all mass spectral signals stemming from each metabolite; (ii) annotation using ion adduction and mass distance among ion peaks; (iii) incorporation of biological knowledge such as biotransformations or pathways; (iv) tandem MS data; and (v) metabolite retention time calibration, usually achieved by prediction from molecular descriptors. Advantages and pitfalls of each of these strategies are discussed, as well as expected future trends in computational annotation.
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Affiliation(s)
- Xavier Domingo-Almenara
- Scripps Center for Metabolomics, The Scripps Research Institute , 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - J Rafael Montenegro-Burke
- Scripps Center for Metabolomics, The Scripps Research Institute , 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - H Paul Benton
- Scripps Center for Metabolomics, The Scripps Research Institute , 10550 North Torrey Pines Road, La Jolla, California 92037, United States
| | - Gary Siuzdak
- Scripps Center for Metabolomics, The Scripps Research Institute , 10550 North Torrey Pines Road, La Jolla, California 92037, United States
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15
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Warth B, Spangler S, Fang M, Johnson CH, Forsberg EM, Granados A, Martin RL, Domingo-Almenara X, Huan T, Rinehart D, Montenegro-Burke JR, Hilmers B, Aisporna A, Hoang LT, Uritboonthai W, Benton HP, Richardson SD, Williams AJ, Siuzdak G. Exposome-Scale Investigations Guided by Global Metabolomics, Pathway Analysis, and Cognitive Computing. Anal Chem 2017; 89:11505-11513. [DOI: 10.1021/acs.analchem.7b02759] [Citation(s) in RCA: 85] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Affiliation(s)
- Benedikt Warth
- Department
of Food Chemistry and Toxicology, Faculty of Chemistry, University of Vienna, Währingerstraße 38, 1090 Vienna, Austria
| | - Scott Spangler
- IBM Almaden Research Lab, 650 Harry Road, San Jose, California 95120, United States
| | - Mingliang Fang
- School
of Civil and Environmental Engineering, Nanyang Technological University, 639798 Singapore
| | - Caroline H. Johnson
- Department
of Environmental Health Sciences, Yale School of Public
Health, Yale University, 60 College Street, New Haven, Connecticut 06520, United States
| | | | | | - Richard L. Martin
- IBM Almaden Research Lab, 650 Harry Road, San Jose, California 95120, United States
| | | | | | | | | | | | | | | | | | | | - Susan D. Richardson
- Department
of Chemistry and Biochemistry, University of South Carolina, Columbia, South Carolina 29208, United States
| | - Antony J. Williams
- National Center
for Computational Toxicology, U.S. Environmental Protection Agency, 109 T.W. Alexander
Drive, Research Triangle Park, North Carolina 27711, United States
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16
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Domingo-Almenara X, Perera A, Brezmes J. Avoiding hard chromatographic segmentation: A moving window approach for the automated resolution of gas chromatography–mass spectrometry-based metabolomics signals by multivariate methods. J Chromatogr A 2016; 1474:145-151. [DOI: 10.1016/j.chroma.2016.10.066] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2016] [Revised: 10/24/2016] [Accepted: 10/25/2016] [Indexed: 01/17/2023]
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17
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Domingo-Almenara X, Brezmes J, Vinaixa M, Samino S, Ramirez N, Ramon-Krauel M, Lerin C, Díaz M, Ibáñez L, Correig X, Perera-Lluna A, Yanes O. eRah: A Computational Tool Integrating Spectral Deconvolution and Alignment with Quantification and Identification of Metabolites in GC/MS-Based Metabolomics. Anal Chem 2016; 88:9821-9829. [PMID: 27584001 DOI: 10.1021/acs.analchem.6b02927] [Citation(s) in RCA: 77] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Gas chromatography coupled to mass spectrometry (GC/MS) has been a long-standing approach used for identifying small molecules due to the highly reproducible ionization process of electron impact ionization (EI). However, the use of GC-EI MS in untargeted metabolomics produces large and complex data sets characterized by coeluting compounds and extensive fragmentation of molecular ions caused by the hard electron ionization. In order to identify and extract quantitative information on metabolites across multiple biological samples, integrated computational workflows for data processing are needed. Here we introduce eRah, a free computational tool written in the open language R composed of five core functions: (i) noise filtering and baseline removal of GC/MS chromatograms, (ii) an innovative compound deconvolution process using multivariate analysis techniques based on compound match by local covariance (CMLC) and orthogonal signal deconvolution (OSD), (iii) alignment of mass spectra across samples, (iv) missing compound recovery, and (v) identification of metabolites by spectral library matching using publicly available mass spectra. eRah outputs a table with compound names, matching scores and the integrated area of compounds for each sample. The automated capabilities of eRah are demonstrated by the analysis of GC-time-of-flight (TOF) MS data from plasma samples of adolescents with hyperinsulinaemic androgen excess and healthy controls. The quantitative results of eRah are compared to centWave, the peak-picking algorithm implemented in the widely used XCMS package, MetAlign, and ChromaTOF software. Significantly dysregulated metabolites are further validated using pure standards and targeted analysis by GC-triple quadrupole (QqQ) MS, LC-QqQ, and NMR. eRah is freely available at http://CRAN.R-project.org/package=erah .
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Affiliation(s)
- Xavier Domingo-Almenara
- Metabolomics Platform, Department of Electronic Engineering (DEEEA), Universitat Rovira i Virgili , 43003 Tarragona, Catalonia, Spain.,Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM) , 28029 Madrid, Spain
| | - Jesus Brezmes
- Metabolomics Platform, Department of Electronic Engineering (DEEEA), Universitat Rovira i Virgili , 43003 Tarragona, Catalonia, Spain.,Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM) , 28029 Madrid, Spain
| | - Maria Vinaixa
- Metabolomics Platform, Department of Electronic Engineering (DEEEA), Universitat Rovira i Virgili , 43003 Tarragona, Catalonia, Spain.,Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM) , 28029 Madrid, Spain
| | - Sara Samino
- Metabolomics Platform, Department of Electronic Engineering (DEEEA), Universitat Rovira i Virgili , 43003 Tarragona, Catalonia, Spain.,Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM) , 28029 Madrid, Spain
| | - Noelia Ramirez
- Metabolomics Platform, Department of Electronic Engineering (DEEEA), Universitat Rovira i Virgili , 43003 Tarragona, Catalonia, Spain.,Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM) , 28029 Madrid, Spain
| | - Marta Ramon-Krauel
- Institut de Recerca Pediàtrica, Hospital Sant Joan de Déu, University of Barcelona , 08950 Barcelona, Catalonia, Spain
| | - Carles Lerin
- Institut de Recerca Pediàtrica, Hospital Sant Joan de Déu, University of Barcelona , 08950 Barcelona, Catalonia, Spain
| | - Marta Díaz
- Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM) , 28029 Madrid, Spain.,Institut de Recerca Pediàtrica, Hospital Sant Joan de Déu, University of Barcelona , 08950 Barcelona, Catalonia, Spain
| | - Lourdes Ibáñez
- Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM) , 28029 Madrid, Spain.,Institut de Recerca Pediàtrica, Hospital Sant Joan de Déu, University of Barcelona , 08950 Barcelona, Catalonia, Spain
| | - Xavier Correig
- Metabolomics Platform, Department of Electronic Engineering (DEEEA), Universitat Rovira i Virgili , 43003 Tarragona, Catalonia, Spain.,Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM) , 28029 Madrid, Spain
| | - Alexandre Perera-Lluna
- B2SLab, Center for Biomedical Engineering Research (CREB), CIBERBBN, Department of ESAII, Universitat Politècnica de Catalunya , 08028 Barcelona, Catalonia, Spain
| | - Oscar Yanes
- Metabolomics Platform, Department of Electronic Engineering (DEEEA), Universitat Rovira i Virgili , 43003 Tarragona, Catalonia, Spain.,Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM) , 28029 Madrid, Spain
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18
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Domingo-Almenara X, Perera A, Ramírez N, Brezmes J. Automated resolution of chromatographic signals by independent component analysis-orthogonal signal deconvolution in comprehensive gas chromatography/mass spectrometry-based metabolomics. Comput Methods Programs Biomed 2016; 130:135-141. [PMID: 27208528 DOI: 10.1016/j.cmpb.2016.03.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2015] [Revised: 03/01/2016] [Accepted: 03/02/2016] [Indexed: 06/05/2023]
Abstract
Comprehensive gas chromatography-mass spectrometry (GC×GC-MS) provides a different perspective in metabolomics profiling of samples. However, algorithms for GC×GC-MS data processing are needed in order to automatically process the data and extract the purest information about the compounds appearing in complex biological samples. This study shows the capability of independent component analysis-orthogonal signal deconvolution (ICA-OSD), an algorithm based on blind source separation and distributed in an R package called osd, to extract the spectra of the compounds appearing in GC×GC-MS chromatograms in an automated manner. We studied the performance of ICA-OSD by the quantification of 38 metabolites through a set of 20 Jurkat cell samples analyzed by GC×GC-MS. The quantification by ICA-OSD was compared with a supervised quantification by selective ions, and most of the R(2) coefficients of determination were in good agreement (R(2)>0.90) while up to 24 cases exhibited an excellent linear relation (R(2)>0.95). We concluded that ICA-OSD can be used to resolve co-eluted compounds in GC×GC-MS.
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Affiliation(s)
- Xavier Domingo-Almenara
- Metabolomics Platform - IISPV, Department of Electrical and Automation Engineering (DEEEA), Universitat Rovira i Virgili, Tarragona, Catalonia, Spain; Biomedical Research Networking Center in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain.
| | - Alexandre Perera
- B2SLAB, Department d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, Barcelona, Catalonia, Spain; Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
| | - Noelia Ramírez
- Metabolomics Platform - IISPV, Department of Electrical and Automation Engineering (DEEEA), Universitat Rovira i Virgili, Tarragona, Catalonia, Spain; Biomedical Research Networking Center in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain
| | - Jesus Brezmes
- Metabolomics Platform - IISPV, Department of Electrical and Automation Engineering (DEEEA), Universitat Rovira i Virgili, Tarragona, Catalonia, Spain; Biomedical Research Networking Center in Diabetes and Associated Metabolic Disorders (CIBERDEM), Madrid, Spain
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19
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Domingo-Almenara X, Perera A, Ramírez N, Cañellas N, Correig X, Brezmes J. Compound identification in gas chromatography/mass spectrometry-based metabolomics by blind source separation. J Chromatogr A 2015. [DOI: 10.1016/j.chroma.2015.07.044] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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