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Isom M, Desaire H. Skin Surface Sebum Analysis by ESI-MS. Biomolecules 2024; 14:790. [PMID: 39062504 PMCID: PMC11274890 DOI: 10.3390/biom14070790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Revised: 06/26/2024] [Accepted: 06/28/2024] [Indexed: 07/28/2024] Open
Abstract
The skin surface is an important sample source that the metabolomics community has only just begun to explore. Alterations in sebum, the lipid-rich mixture coating the skin surface, correlate with age, sex, ethnicity, diet, exercise, and disease state, making the skin surface an ideal sample source for future noninvasive biomarker exploration, disease diagnosis, and forensic investigation. The potential of sebum sampling has been realized primarily via electrospray ionization mass spectrometry (ESI-MS), an ideal approach to assess the skin surface lipidome. However, a better understanding of sebum collection and subsequent ESI-MS analysis is required before skin surface sampling can be implemented in routine analyses. Challenges include ambiguity in definitive lipid identification, inherent biological variability in sebum production, and methodological, technical variability in analyses. To overcome these obstacles, avoid common pitfalls, and achieve reproducible, robust outcomes, every portion of the workflow-from sample collection to data analysis-should be carefully considered with the specific application in mind. This review details current practices in sebum sampling, sample preparation, ESI-MS data acquisition, and data analysis, and it provides important considerations in acquiring meaningful lipidomic datasets from the skin surface. Forensic researchers investigating sebum as a means for suspect elimination in lieu of adequate fingerprint ridge detail or database matches, as well as clinical researchers interested in noninvasive biomarker exploration, disease diagnosis, and treatment monitoring, can use this review as a guide for developing methods of best-practice.
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Affiliation(s)
| | - Heather Desaire
- Department of Chemistry, University of Kansas, Lawrence, KS 66045, USA;
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2
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Sacher M, DeLoriea J, Mehranfar M, Casey C, Naaz A, Gamberi C. TANGO2 deficiency disease is predominantly caused by a lipid imbalance. Dis Model Mech 2024; 17:dmm050662. [PMID: 38836374 PMCID: PMC11179719 DOI: 10.1242/dmm.050662] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2024] Open
Abstract
TANGO2 deficiency disease (TDD) is a rare genetic disorder estimated to affect ∼8000 individuals worldwide. It causes neurodegeneration often accompanied by potentially lethal metabolic crises that are triggered by diet or illness. Recent work has demonstrated distinct lipid imbalances in multiple model systems either depleted for or devoid of the TANGO2 protein, including human cells, fruit flies and zebrafish. Importantly, vitamin B5 supplementation has been shown to rescue TANGO2 deficiency-associated defects in flies and human cells. The notion that vitamin B5 is needed for synthesis of the lipid precursor coenzyme A (CoA) corroborates the hypothesis that key aspects of TDD pathology may be caused by lipid imbalance. A natural history study of 73 individuals with TDD reported that either multivitamin or vitamin B complex supplementation prevented the metabolic crises, suggesting this as a potentially life-saving treatment. Although recently published work supports this notion, much remains unknown about TANGO2 function, the pathological mechanism of TDD and the possible downsides of sustained vitamin supplementation in children and young adults. In this Perspective, we discuss these recent findings and highlight areas for immediate scientific attention.
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Affiliation(s)
- Michael Sacher
- Department of Biology, Concordia University, Montreal H4B 1R6, Canada
- Department of Anatomy and Cell Biology, McGill University, Montreal H3A 0C7, Canada
| | - Jay DeLoriea
- Department of Biology, Coastal Carolina University, Conway, SC 29526, USA
| | - Mahsa Mehranfar
- Department of Chemistry and Biochemistry, Concordia University, Montreal H4B 1R6, Canada
| | - Cody Casey
- Department of Biology, Coastal Carolina University, Conway, SC 29526, USA
| | - Aaliya Naaz
- Department of Biology, Concordia University, Montreal H4B 1R6, Canada
| | - Chiara Gamberi
- Department of Biology, Coastal Carolina University, Conway, SC 29526, USA
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3
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Lin P, Sledziona J, Akkaya-Colak KB, Mihaylova MM, Lane AN. Determination of fatty acid uptake and desaturase activity in mammalian cells by NMR-based stable isotope tracing. Anal Chim Acta 2024; 1303:342511. [PMID: 38609261 PMCID: PMC11016156 DOI: 10.1016/j.aca.2024.342511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 03/17/2024] [Accepted: 03/20/2024] [Indexed: 04/14/2024]
Abstract
BACKGROUND Mammalian cells both import exogenous fatty acids and synthesize them de novo. Palmitate, the end product of fatty acid synthase (FASN) is a substrate for stearoyl-CoA desaturases (Δ-9 desaturases) that introduce a single double bond into fatty acyl-CoA substrates such as palmitoyl-CoA and stearoyl-CoA. This process is particularly upregulated in lipogenic tissues and cancer cells. Tracer methodology is needed to determine uptake versus de novo synthesis of lipids and subsequent chain elongation and desaturation. Here we describe an NMR method to determine the uptake of 13C-palmitate from the medium into HCT116 human colorectal cancer cells, and the subsequent desaturation and incorporation into complex lipids. RESULTS Exogenous 13C16-palmitate was absorbed from the medium by HCT116 cells and incorporated primarily into complex glycerol lipids. Desaturase activity was determined from the quantification of double bonds in acyl chains, which was greatly reduced by ablation of the major desaturase SCD1. SIGNIFICANCE The NMR approach requires minimal sample preparation, is non-destructive, and provides direct information about the level of saturation and incorporation of fatty acids into complex lipids.
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Affiliation(s)
- Penghui Lin
- Center for Environmental and Systems Biochemistry, Dept. of Toxicology and Cancer Biology, Markey Cancer Center, University of Kentucky, Lexington, KY, USA
| | - James Sledziona
- Department of Biological Chemistry and Pharmacology, The Ohio State University, 1060 Carmack Rd, Columbus, OH, 43210, USA; The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Kubra B Akkaya-Colak
- Department of Biological Chemistry and Pharmacology, The Ohio State University, 1060 Carmack Rd, Columbus, OH, 43210, USA; The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Maria M Mihaylova
- Department of Biological Chemistry and Pharmacology, The Ohio State University, 1060 Carmack Rd, Columbus, OH, 43210, USA; The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Andrew N Lane
- Center for Environmental and Systems Biochemistry, Dept. of Toxicology and Cancer Biology, Markey Cancer Center, University of Kentucky, Lexington, KY, USA.
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4
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Sarkar S, Roy D, Chatterjee B, Ghosh R. Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases. Metabolomics 2024; 20:37. [PMID: 38459207 DOI: 10.1007/s11306-024-02100-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 02/06/2024] [Indexed: 03/10/2024]
Abstract
BACKGROUND Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts. AIM OF THE REVIEW The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies. KEY SCIENTIFIC CONCEPTS OF REVIEW Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.
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Affiliation(s)
- Sutanu Sarkar
- Amity Institute of Biotechnology (AIBNK), Amity University, Rajarhat, Newtown Action Area 2, Kolkata, 700135, West Bengal, India
| | - Deotima Roy
- Amity Institute of Biotechnology (AIBNK), Amity University, Rajarhat, Newtown Action Area 2, Kolkata, 700135, West Bengal, India
| | - Bhaskar Chatterjee
- Amity Institute of Biotechnology (AIBNK), Amity University, Rajarhat, Newtown Action Area 2, Kolkata, 700135, West Bengal, India
| | - Rajgourab Ghosh
- Amity Institute of Biotechnology (AIBNK), Amity University, Rajarhat, Newtown Action Area 2, Kolkata, 700135, West Bengal, India.
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Goracci L, Tiberi P, Di Bona S, Bonciarelli S, Passeri GI, Piroddi M, Moretti S, Volpi C, Zamora I, Cruciani G. MARS: A Multipurpose Software for Untargeted LC-MS-Based Metabolomics and Exposomics. Anal Chem 2024; 96:1468-1477. [PMID: 38236168 PMCID: PMC10831794 DOI: 10.1021/acs.analchem.3c03620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 12/24/2023] [Accepted: 12/29/2023] [Indexed: 01/19/2024]
Abstract
Untargeted metabolomics is a growing field, in which recent advances in high-resolution mass spectrometry coupled with liquid chromatography (LC-MS) have facilitated untargeted approaches as a result of improvements in sensitivity, mass accuracy, and resolving power. However, a very large amount of data are generated. Consequently, using computational tools is now mandatory for the in-depth analysis of untargeted metabolomics data. This article describes MetAbolomics ReSearch (MARS), an all-in-one vendor-agnostic graphical user interface-based software applying LC-MS analysis to untargeted metabolomics. All of the analytical steps are described (from instrument data conversion and processing to statistical analysis, annotation/identification, quantification, and preliminary biological interpretation), and tools developed to improve annotation accuracy (e.g., multiple adducts and in-source fragmentation detection, trends across samples, and the MS/MS validator) are highlighted. In addition, MARS allows in-house building of reference databases, to bypass the limits of freely available MS/MS spectra collections. Focusing on the flexibility of the software and its user-friendliness, which are two important features in multipurpose software, MARS could provide new perspectives in untargeted metabolomics data analysis.
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Affiliation(s)
- Laura Goracci
- Department
of Chemistry, Biology and Biotechnology, Universita degli Studi di Perugia, via Elce di Sotto 8, Perugia 06123, Italy
| | - Paolo Tiberi
- Molecular
Discovery Ltd., Centennial
Park, Borehamwood, Hertfordshire WD6 4PJ, U.K.
| | - Stefano Di Bona
- Molecular
Horizon, Via Montelino,
30, Bettona (PG) 06084, Italy
| | - Stefano Bonciarelli
- Molecular
Discovery Ltd., Centennial
Park, Borehamwood, Hertfordshire WD6 4PJ, U.K.
| | | | - Marta Piroddi
- Molecular
Horizon, Via Montelino,
30, Bettona (PG) 06084, Italy
| | - Simone Moretti
- Molecular
Horizon, Via Montelino,
30, Bettona (PG) 06084, Italy
| | - Claudia Volpi
- Department
of Medicine and Surgery, P.le Gambuli 1, Perugia 06129, Italy
| | - Ismael Zamora
- Mass
Analytica, Rambla de
celler 113, Sant Cugat del Vallés 08173, Spain
| | - Gabriele Cruciani
- Department
of Chemistry, Biology and Biotechnology, Universita degli Studi di Perugia, via Elce di Sotto 8, Perugia 06123, Italy
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6
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Chen Q, Dwaraka VB, Carreras-Gallo N, Mendez K, Chen Y, Begum S, Kachroo P, Prince N, Went H, Mendez T, Lin A, Turner L, Moqri M, Chu SH, Kelly RS, Weiss ST, Rattray NJ, Gladyshev VN, Karlson E, Wheelock C, Mathé EA, Dahlin A, McGeachie MJ, Smith R, Lasky-Su JA. OMICmAge: An integrative multi-omics approach to quantify biological age with electronic medical records. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.16.562114. [PMID: 37904959 PMCID: PMC10614756 DOI: 10.1101/2023.10.16.562114] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/02/2023]
Abstract
Biological aging is a multifactorial process involving complex interactions of cellular and biochemical processes that is reflected in omic profiles. Using common clinical laboratory measures in ~30,000 individuals from the MGB-Biobank, we developed a robust, predictive biological aging phenotype, EMRAge, that balances clinical biomarkers with overall mortality risk and can be broadly recapitulated across EMRs. We then applied elastic-net regression to model EMRAge with DNA-methylation (DNAm) and multiple omics, generating DNAmEMRAge and OMICmAge, respectively. Both biomarkers demonstrated strong associations with chronic diseases and mortality that outperform current biomarkers across our discovery (MGB-ABC, n=3,451) and validation (TruDiagnostic, n=12,666) cohorts. Through the use of epigenetic biomarker proxies, OMICmAge has the unique advantage of expanding the predictive search space to include epigenomic, proteomic, metabolomic, and clinical data while distilling this in a measure with DNAm alone, providing opportunities to identify clinically-relevant interconnections central to the aging process.
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Affiliation(s)
- Qingwen Chen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | | | | | - Kevin Mendez
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Yulu Chen
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Sofina Begum
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Priyadarshini Kachroo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Nicole Prince
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | | | | | - Aaron Lin
- TruDiagnostic, Inc., Lexington, KY USA
| | | | - Mahdi Moqri
- Division of Genetics, Dept. of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, USA
| | - Su H. Chu
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Rachel S. Kelly
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Scott T. Weiss
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Nicholas J.W Rattray
- Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Glasgow, UK
- Strathclyde Centre for Molecular Bioscience, University of Strathclyde, Glasgow, UK
| | - Vadim N. Gladyshev
- Division of Genetics, Dept. of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Elizabeth Karlson
- Department of Personalized Medicine, Mass General Brigham and Harvard Medical School, Boston, MA, USA
| | - Craig Wheelock
- Division of Physiological Chemistry 2, Dept of Medical Biochemistry and Biophysics, Karolinska Institute, Stockholm, Sweden
| | - Ewy A. Mathé
- Division of Preclinical Innovation, National Center for Advancing Translational Science, National Institutes of Health, Rockville, MD, USA
| | - Amber Dahlin
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Michae J. McGeachie
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Jessica A. Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
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7
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Untargeted lipidomic profiling of grapes highlights the importance of modified lipid species beyond the traditional compound classes. Food Chem 2023; 410:135360. [PMID: 36628919 DOI: 10.1016/j.foodchem.2022.135360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 11/15/2022] [Accepted: 12/28/2022] [Indexed: 12/31/2022]
Abstract
The aim of this paper is to provide a detailed characterisation of grape lipidome. To achieve this objective, it starts by describing a pipeline implemented in R software to allow the semi-automatic annotation of the detected lipid species. It also provides an extensive description of the different properties of each molecule (such as retention time dependencies, mass accuracy, adduct formation and fragmentation patterns), which allowed the annotations to be made more accurately. Most annotated lipids in the grape samples were (lyso)glycerophospholipids and glycerolipids, although a few free fatty acids, hydroxyceramides and sitosterol esters were also observed. The proposed pipeline also allowed the identification of a series of methylated glycerophosphates never previously observed in grapes. The current results highlight the importance of expanding chemical analyses beyond the classical lipid categories.
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8
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Kovilakath A, Wohlford G, Cowart LA. Circulating sphingolipids in heart failure. Front Cardiovasc Med 2023; 10:1154447. [PMID: 37229233 PMCID: PMC10203217 DOI: 10.3389/fcvm.2023.1154447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 04/04/2023] [Indexed: 05/27/2023] Open
Abstract
Lack of significant advancements in early detection and treatment of heart failure have precipitated the need for discovery of novel biomarkers and therapeutic targets. Over the past decade, circulating sphingolipids have elicited promising results as biomarkers that premonish adverse cardiac events. Additionally, compelling evidence directly ties sphingolipids to these events in patients with incident heart failure. This review aims to summarize the current literature on circulating sphingolipids in both human cohorts and animal models of heart failure. The goal is to provide direction and focus for future mechanistic studies in heart failure, as well as pave the way for the development of new sphingolipid biomarkers.
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Affiliation(s)
- Anna Kovilakath
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, United States
| | - George Wohlford
- Pauley Heart Center, Virginia Commonwealth University, Richmond, VA, United States
| | - L. Ashley Cowart
- Department of Biochemistry and Molecular Biology and the Massey Cancer Center, Virginia Commonwealth University, Richmond, VA, United States
- Richmond Veteran's Affairs Medical Center, Richmond, VA, United States
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9
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Shen T, Conway C, Rempfert KR, Kyle JE, Colby SM, Gaul DA, Habra H, Kong F, Bloodsworth KJ, Allen D, Evans BS, Du X, Fernandez FM, Metz TO, Fiehn O, Evans CR. The unknown lipids project: harmonized methods improve compound identification and data reproducibility in an inter-laboratory untargeted lipidomics study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.01.526566. [PMID: 36778509 PMCID: PMC9915661 DOI: 10.1101/2023.02.01.526566] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
Abstract
Untargeted lipidomics allows analysis of a broader range of lipids than targeted methods and permits discovery of unknown compounds. Previous ring trials have evaluated the reproducibility of targeted lipidomics methods, but inter-laboratory comparison of compound identification and unknown feature detection in untargeted lipidomics has not been attempted. To address this gap, five laboratories analyzed a set of mammalian tissue and biofluid reference samples using both their own untargeted lipidomics procedures and a common chromatographic and data analysis method. While both methods yielded informative data, the common method improved chromatographic reproducibility and resulted in detection of more shared features between labs. Spectral search against the LipidBlast in silico library enabled identification of over 2,000 unique lipids. Further examination of LC-MS/MS and ion mobility data, aided by hybrid search and spectral networking analysis, revealed spectral and chromatographic patterns useful for classification of unknown features, a subset of which were highly reproducible between labs. Overall, our method offers enhanced compound identification performance compared to targeted lipidomics, demonstrates the potential of harmonized methods to improve inter-site reproducibility for quantitation and feature alignment, and can serve as a reference to aid future annotation of untargeted lipidomics data.
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10
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Harvey FC, Collao V, Bhattacharya SK. High-Resolution Liquid Chromatography-Mass Spectrometry for Lipidomics. Methods Mol Biol 2023; 2625:57-63. [PMID: 36653631 DOI: 10.1007/978-1-0716-2966-6_4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) is a powerful tool for identification and classification of lipids. Ultra-high performance liquid chromatography (UHPLC) allows for robust separations of complex mixtures, while high-resolution mass spectrometry (HRMS) identifies compounds with efficiency and accuracy (Zullig T and Kofeler HC, Mass Spectrom Rev 40:162-176, 2021). The high specificity and sensitivity of mass spectrometry makes it the method of choice when analyzing lipids (Kofeler HC, J Lipid Res 62:100138, 2021). Untargeted mass spectrometry identifies all lipids within a sample and is useful for identification and further discovery. This chapter describes the use of a Q Exactive mass spectrometer to perform an untargeted LC-MS/MS lipidomics analysis.
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Affiliation(s)
- Faith Christine Harvey
- Department of Ophthalmology, Bascom Palmer Eye Institute, Miller School of Medicine at University of Miami, Miami, FL, USA.,Miami Integrative Metabolomics Research Center, Miami, FL, USA
| | - Vanessa Collao
- Department of Ophthalmology, Bascom Palmer Eye Institute, Miller School of Medicine at University of Miami, Miami, FL, USA
| | - Sanjoy K Bhattacharya
- Department of Ophthalmology, Bascom Palmer Eye Institute, Miller School of Medicine at University of Miami, Miami, FL, USA. .,Miami Integrative Metabolomics Research Center, Miami, FL, USA.
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