Interpreting the Lipidome: Bioinformatic Approaches to Embrace the Complexity

Kyle, Jennifer E.; Aimo, Lucila; Bridge, Alan J.; Clair, Geremy CD; Fedorova, Maria; Helms, J B.; Molenaar, Martijn R.; Ni, Zhixu; Oresic, Matej; Slenter, Denise (BIGCAT); Willighagen, Egon L.; Webb-Robertson, Bobbie-Jo M.

doi:10.1007/s11306-021-01802-6

Interpreting the Lipidome: Bioinformatic Approaches to Embrace the Complexity

Journal Article · Mon Aug 02 00:00:00 EDT 2021 · Metabolomics

DOI:https://doi.org/10.1007/s11306-021-01802-6· OSTI ID:1811833

Kyle, Jennifer E. ^[1]; Aimo, Lucila ^[2]; Bridge, Alan J. ^[2]; ^[1]; Fedorova, Maria ^[3]; Helms, J B. ^[4]; Molenaar, Martijn R. ^[5]; Ni, Zhixu ^[3]; Oresic, Matej ^[6]; Slenter, Denise (BIGCAT) ^[7]; Willighagen, Egon L. ^[7]; Webb-Robertson, Bobbie-Jo M. ^[1]

BATTELLE (PACIFIC NW LAB)
Swiss Institute for Bioinformatics
Universitat Leipzig
Utrecht University
European Molecular Biology Laboratory
Orebro University
Maastricht University

Background Improvements in mass spectrometry (MS) technologies coupled with bioinformatics developments have allowed considerable advancement in the measurement and interpretation of lipidomics data in recent years. Since research areas employing lipidomics are rapidly increasing, there is a great need for bioinformatic tools that capture and utilize the complexity of the data. Currently, the diversity and complexity within the lipidome is often concealed by summing over or averaging individual lipids up to (sub)class-based descriptors, losing valuable information about biological function and interactions with other distinct lipids molecules, proteins and/or metabolites. Aim of review To address this gap in knowledge, novel bioinformatics methods are needed to improve identification, quantification, integration and interpretation of lipidomics data. The purpose of this mini-review is to summarize exemplary methods to explore the complexity of the lipidome. Key scientific concepts of review Here we describe six approaches that capture three core focus areas for lipidomics: (1) lipidome annotation including a resolvable database identifier, (2) interpretation via pathway- and enrichment-based methods, and (3) understanding complex interactions to emphasize specific steps in the analytical process and highlight challenges in analyses associated with the complexity of lipidome data.

Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE

DOE Contract Number:: AC05-76RL01830

OSTI ID:: 1811833

Report Number(s):: PNNL-SA-162774

Journal Information:: Metabolomics, Journal Name: Metabolomics Journal Issue: 8 Vol. 17

Country of Publication:: United States

Language:: English

References (61)

A network biology workflow to study transcriptomics data of the diabetic liver Kutmon, Martina; Evelo, Chris T.; Coort, Susan L. BMC Genomics, Vol. 15, Issue 1 https://doi.org/10.1186/1471-2164-15-971	journal	January 2014
Understanding the diversity of membrane lipid composition Harayama, Takeshi; Riezman, Howard Nature Reviews Molecular Cell Biology, Vol. 19, Issue 5 https://doi.org/10.1038/nrm.2017.138	journal	February 2018
Recon3D enables a three-dimensional view of gene variation in human metabolism Brunk, Elizabeth; Sahoo, Swagatika; Zielinski, Daniel C. Nature Biotechnology, Vol. 36, Issue 3 https://doi.org/10.1038/nbt.4072	journal	February 2018
Lipidomics: Current state of the art in a fast moving field O'Donnell, Valerie B.; Ekroos, Kim; Liebisch, Gerhard Wiley Interdisciplinary Reviews: Systems Biology and Medicine https://doi.org/10.1002/wsbm.1466	journal	October 2019
Integration of clinical data with a genome‐scale metabolic model of the human adipocyte Mardinoglu, Adil; Agren, Rasmus; Kampf, Caroline Molecular Systems Biology, Vol. 9, Issue 1 https://doi.org/10.1038/msb.2013.5	journal	January 2013
SMPDB 2.0: Big Improvements to the Small Molecule Pathway Database Jewison, Timothy; Su, Yilu; Disfany, Fatemeh Miri Nucleic Acids Research, Vol. 42, Issue D1 https://doi.org/10.1093/nar/gkt1067	journal	November 2013
The BridgeDb framework: standardized access to gene, protein and metabolite identifier mapping services van Iersel, Martijn P.; Pico, Alexander R.; Kelder, Thomas BMC Bioinformatics, Vol. 11, Issue 1 https://doi.org/10.1186/1471-2105-11-5	journal	January 2010
Informatics and computational strategies for the study of lipids Orešič, Matej Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids, Vol. 1811, Issue 11 https://doi.org/10.1016/j.bbalip.2011.06.012	journal	November 2011
Systems biology of lipid metabolism: From yeast to human Nielsen, Jens FEBS Letters, Vol. 583, Issue 24 https://doi.org/10.1016/j.febslet.2009.10.054	journal	October 2009
LIPID MAPS: Serving the next generation of lipid researchers with tools, resources, data, and training O’Donnell, Valerie B.; Dennis, Edward A.; Wakelam, Michael J. O. Science Signaling, Vol. 12, Issue 563 https://doi.org/10.1126/scisignal.aaw2964	journal	January 2019
Software tools, databases and resources in metabolomics: updates from 2018 to 2019 O’Shea, Keiron; Misra, Biswapriya B. Metabolomics, Vol. 16, Issue 3 https://doi.org/10.1007/s11306-020-01657-3	journal	March 2020
WikiPathways: connecting communities Martens, Marvin; Ammar, Ammar; Riutta, Anders Nucleic Acids Research, Vol. 49, Issue D1 https://doi.org/10.1093/nar/gkaa1024	journal	November 2020
Computational solutions in redox lipidomics – Current strategies and future perspectives Ni, Zhixu; Goracci, Laura; Cruciani, Gabriele Free Radical Biology and Medicine, Vol. 144 https://doi.org/10.1016/j.freeradbiomed.2019.04.027	journal	November 2019
WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research Slenter, Denise N.; Kutmon, Martina; Hanspers, Kristina Nucleic Acids Research, Vol. 46, Issue D1 https://doi.org/10.1093/nar/gkx1064	journal	November 2017
Lipids in host–pathogen interactions: Pathogens exploit the complexity of the host cell lipidome van der Meer-Janssen, Ynske P. M.; van Galen, Josse; Batenburg, Joseph J. Progress in Lipid Research, Vol. 49, Issue 1 https://doi.org/10.1016/j.plipres.2009.07.003	journal	January 2010
Uncovering biologically significant lipid isomers with liquid chromatography, ion mobility spectrometry and mass spectrometry Kyle, Jennifer E.; Zhang, Xing; Weitz, Karl K. The Analyst, Vol. 141, Issue 5 https://doi.org/10.1039/c5an02062j	journal	January 2016
Automated, parallel mass spectrometry imaging and structural identification of lipids Ellis, Shane R.; Paine, Martin R. L.; Eijkel, Gert B. Nature Methods, Vol. 15, Issue 7 https://doi.org/10.1038/s41592-018-0010-6	journal	May 2018
Computational Lipidomics of the Neuronal Plasma Membrane Ingólfsson, Helgi I.; Carpenter, Timothy S.; Bhatia, Harsh Biophysical Journal, Vol. 113, Issue 10 https://doi.org/10.1016/j.bpj.2017.10.017	journal	November 2017
OmicsNet: a web-based tool for creation and visual analysis of biological networks in 3D space Zhou, Guangyan; Xia, Jianguo Nucleic Acids Research, Vol. 46, Issue W1 https://doi.org/10.1093/nar/gky510	journal	June 2018
UniProt: the universal protein knowledgebase in 2021 Bateman, Alex; Martin, Maria-Jesus; Orchard, Sandra Nucleic Acids Research, Vol. 49, Issue D1 https://doi.org/10.1093/nar/gkaa1100	journal	November 2020
Integrated Lipidomics and Proteomics Point to Early Blood-Based Changes in Childhood Preceding Later Development of Psychotic Experiences: Evidence From the Avon Longitudinal Study of Parents and Children Madrid-Gambin, Francisco; Föcking, Melanie; Sabherwal, Sophie Biological Psychiatry, Vol. 86, Issue 1 https://doi.org/10.1016/j.biopsych.2019.01.018	journal	July 2019
Computational Lipidomics with insane : A Versatile Tool for Generating Custom Membranes for Molecular Simulations Wassenaar, Tsjerk A.; Ingólfsson, Helgi I.; Böckmann, Rainer A. Journal of Chemical Theory and Computation, Vol. 11, Issue 5 https://doi.org/10.1021/acs.jctc.5b00209	journal	April 2015
Shorthand notation for lipid structures derived from mass spectrometry Liebisch, Gerhard; Vizcaíno, Juan Antonio; Köfeler, Harald Journal of Lipid Research, Vol. 54, Issue 6 https://doi.org/10.1194/jlr.M033506	journal	June 2013
Tools and resources for metabolomics research community: A 2017-2018 update Misra, Biswapriya B.; Mohapatra, Subhashree ELECTROPHORESIS, Vol. 40, Issue 2 https://doi.org/10.1002/elps.201800428	journal	November 2018
Pathview Web: user friendly pathway visualization and data integration Luo, Weijun; Pant, Gaurav; Bhavnasi, Yeshvant K. Nucleic Acids Research, Vol. 45, Issue W1 https://doi.org/10.1093/nar/gkx372	journal	May 2017
Metabolite-related dietary patterns and the development of islet autoimmunity Johnson, Randi K.; Vanderlinden, Lauren; DeFelice, Brian C. Scientific Reports, Vol. 9, Issue 1 https://doi.org/10.1038/s41598-019-51251-4	journal	October 2019
Update on LIPID MAPS classification, nomenclature, and shorthand notation for MS-derived lipid structures Liebisch, Gerhard; Fahy, Eoin; Aoki, Junken Journal of Lipid Research, Vol. 61, Issue 12 https://doi.org/10.1194/jlr.S120001025	journal	December 2020
MS-DIAL: data-independent MS/MS deconvolution for comprehensive metabolome analysis Tsugawa, Hiroshi; Cajka, Tomas; Kind, Tobias Nature Methods, Vol. 12, Issue 6 https://doi.org/10.1038/nmeth.3393	journal	May 2015
The SwissLipids knowledgebase for lipid biology Aimo, Lucila; Liechti, Robin; Hyka-Nouspikel, Nevila Bioinformatics, Vol. 31, Issue 17 https://doi.org/10.1093/bioinformatics/btv285	journal	May 2015
Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks Shannon, P. Genome Research, Vol. 13, Issue 11 https://doi.org/10.1101/gr.1239303	journal	November 2003
Letter to the Glyco-Forum: SphinGOMAP—A web-based biosynthetic pathway map of sphingolipids and glycosphingolipids Merrill, Alfred H. Glycobiology, Vol. 15, Issue 6 https://doi.org/10.1093/glycob/cwi070	journal	June 2005
LipiDex: An Integrated Software Package for High-Confidence Lipid Identification Hutchins, Paul D.; Russell, Jason D.; Coon, Joshua J. Cell Systems, Vol. 6, Issue 5 https://doi.org/10.1016/j.cels.2018.03.011	journal	May 2018
LPPtiger software for lipidome-specific prediction and identification of oxidized phospholipids from LC-MS datasets Ni, Zhixu; Angelidou, Georgia; Hoffmann, Ralf Scientific Reports, Vol. 7, Issue 1 https://doi.org/10.1038/s41598-017-15363-z	journal	November 2017
Update of the LIPID MAPS comprehensive classification system for lipids Fahy, Eoin; Subramaniam, Shankar; Murphy, Robert C. Journal of Lipid Research, Vol. 50, Issue Supplement https://doi.org/10.1194/jlr.R800095-JLR200	journal	December 2008
LIQUID: an-open source software for identifying lipids in LC-MS/MS-based lipidomics data Kyle, Jennifer E.; Crowell, Kevin L.; Casey, Cameron P. Bioinformatics, Vol. 33, Issue 11 https://doi.org/10.1093/bioinformatics/btx046	journal	January 2017
The reactome pathway knowledgebase Jassal, Bijay; Matthews, Lisa; Viteri, Guilherme Nucleic Acids Research https://doi.org/10.1093/nar/gkz1031	journal	November 2019
A Mouse Macrophage Lipidome Dennis, Edward A.; Deems, Raymond A.; Harkewicz, Richard Journal of Biological Chemistry, Vol. 285, Issue 51 https://doi.org/10.1074/jbc.M110.182915	journal	December 2010
LipidHunter Identifies Phospholipids by High-Throughput Processing of LC-MS and Shotgun Lipidomics Datasets Ni, Zhixu; Angelidou, Georgia; Lange, Mike Analytical Chemistry, Vol. 89, Issue 17 https://doi.org/10.1021/acs.analchem.7b01126	journal	August 2017
PathVisio 3: An Extendable Pathway Analysis Toolbox Kutmon, Martina; van Iersel, Martijn P.; Bohler, Anwesha PLOS Computational Biology, Vol. 11, Issue 2 https://doi.org/10.1371/journal.pcbi.1004085	journal	February 2015
Lipid Mini-On: mining and ontology tool for enrichment analysis of lipidomic data Clair, Geremy; Reehl, Sarah; Stratton, Kelly G. Bioinformatics, Vol. 35, Issue 21 https://doi.org/10.1093/bioinformatics/btz250	journal	April 2019
Metabolic alterations in immune cells associate with progression to type 1 diabetes Sen, Partho; Dickens, Alex M.; López-Bascón, María Asunción Diabetologia, Vol. 63, Issue 5 https://doi.org/10.1007/s00125-020-05107-6	journal	February 2020
A lipidome atlas in MS-DIAL 4 Tsugawa, Hiroshi; Ikeda, Kazutaka; Takahashi, Mikiko Nature Biotechnology, Vol. 38, Issue 10 https://doi.org/10.1038/s41587-020-0531-2	journal	June 2020
Association of Lipidome Remodeling in the Adipocyte Membrane with Acquired Obesity in Humans Pietiläinen, Kirsi H.; Róg, Tomasz; Seppänen-Laakso, Tuulikki PLoS Biology, Vol. 9, Issue 6 https://doi.org/10.1371/journal.pbio.1000623	journal	June 2011
Enzyme annotation in UniProtKB using Rhea Morgat, Anne; Lombardot, Thierry; Coudert, Elisabeth Bioinformatics https://doi.org/10.1093/bioinformatics/btz817	journal	November 2019
Genome-scale study reveals reduced metabolic adaptability in patients with non-alcoholic fatty liver disease Hyötyläinen, Tuulia; Jerby, Livnat; Petäjä, Elina M. Nature Communications, Vol. 7, Issue 1 https://doi.org/10.1038/ncomms9994	journal	February 2016
Systems biology strategies to study lipidomes in health and disease Hyötyläinen, Tuulia; Orešič, Matej Progress in Lipid Research, Vol. 55 https://doi.org/10.1016/j.plipres.2014.06.001	journal	July 2014
Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease Mardinoglu, Adil; Agren, Rasmus; Kampf, Caroline Nature Communications, Vol. 5, Issue 1 https://doi.org/10.1038/ncomms4083	journal	January 2014
ChEBI in 2016: Improved services and an expanding collection of metabolites Hastings, Janna; Owen, Gareth; Dekker, Adriano Nucleic Acids Research, Vol. 44, Issue D1 https://doi.org/10.1093/nar/gkv1031	journal	October 2015
LION/web: a web-based ontology enrichment tool for lipidomic data analysis Molenaar, Martijn R.; Jeucken, Aike; Wassenaar, Tsjerk A. GigaScience, Vol. 8, Issue 6 https://doi.org/10.1093/gigascience/giz061	journal	May 2019
Eicosanoid storm in infection and inflammation Dennis, Edward A.; Norris, Paul C. Nature Reviews Immunology, Vol. 15, Issue 8 https://doi.org/10.1038/nri3859	journal	July 2015
Using OmicsNet for Network Integration and 3D Visualization Zhou, Guangyan; Xia, Jianguo Current Protocols in Bioinformatics, Vol. 65, Issue 1 https://doi.org/10.1002/cpbi.69	journal	December 2018
Dysregulation of lipid and amino acid metabolism precedes islet autoimmunity in children who later progress to type 1 diabetes Orešič, Matej; Simell, Satu; Sysi-Aho, Marko Journal of Experimental Medicine, Vol. 205, Issue 13 https://doi.org/10.1084/jem.20081800	journal	December 2008
Wikidata as a knowledge graph for the life sciences Waagmeester, Andra; Stupp, Gregory; Burgstaller-Muehlbacher, Sebastian eLife, Vol. 9 https://doi.org/10.7554/eLife.52614	journal	March 2020
NIST lipidomics workflow questionnaire: an assessment of community-wide methodologies and perspectives Bowden, John A.; Ulmer, Candice Z.; Jones, Christina M. Metabolomics, Vol. 14, Issue 5 https://doi.org/10.1007/s11306-018-1340-1	journal	March 2018
The DAVID Gene Functional Classification Tool: a novel biological module-centric algorithm to functionally analyze large gene lists Huang, Da; Sherman, Brad T.; Tan, Qina Genome Biology, Vol. 8, Issue 9 https://doi.org/10.1186/gb-2007-8-9-r183	journal	January 2007
High-coverage lipidomics for functional lipid and pathway analyses Lam, Sin Man; Wang, Zehua; Li, Bowen Analytica Chimica Acta, Vol. 1147 https://doi.org/10.1016/j.aca.2020.11.024	journal	February 2021
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. BMC Bioinformatics, Vol. 18, Issue 1 https://doi.org/10.1186/s12859-017-1744-3	journal	July 2017
Systems biology approaches to study lipidomes in health and disease Alves, Marina Amaral; Lamichhane, Santosh; Dickens, Alex Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids, Vol. 1866, Issue 2 https://doi.org/10.1016/j.bbalip.2020.158857	journal	February 2021
LipidCreator workbench to probe the lipidomic landscape Peng, Bing; Kopczynski, Dominik; Pratt, Brian S. Nature Communications, Vol. 11, Issue 1 https://doi.org/10.1038/s41467-020-15960-z	journal	April 2020
LipidFinder on LIPID MAPS: peak filtering, MS searching and statistical analysis for lipidomics Fahy, Eoin; Alvarez-Jarreta, Jorge; Brasher, Christopher J. Bioinformatics https://doi.org/10.1093/bioinformatics/bty679	journal	August 2018
A community-driven global reconstruction of human metabolism Thiele, Ines; Swainston, Neil; Fleming, Ronan M. T. Nature Biotechnology, Vol. 31, Issue 5 https://doi.org/10.1038/nbt.2488	journal	March 2013

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