Table Of ContentMethods in
Molecular Biology 1978
Angelo D’Alessandro Editor
High-Throughput
Metabolomics
Methods and Protocols
M M B
ethods in olecular iology
Series Editor
John M. Walker
School of Life and Medical Sciences
University of Hertfordshire
Hatfield, Hertfordshire, AL10 9AB, UK
For further volumes:
http://www.springer.com/series/7651
High-Throughput Metabolomics
Methods and Protocols
Edited by
Angelo D’Alessandro
Department of Biochemistry and Molecular Genetics, University of Colorado Denver,
Aurora, CO, USA
Editor
Angelo D’Alessandro
Department of Biochemistry and Molecular Genetics
University of Colorado Denver
Aurora, CO, USA
ISSN 1064-3745 ISSN 1940-6029 (electronic)
Methods in Molecular Biology
ISBN 978-1-4939-9235-5 ISBN 978-1-4939-9236-2 (eBook)
https://doi.org/10.1007/978-1-4939-9236-2
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Preface
High-Throughput Metabolomics: So Much to Discover, So Little Time…
Dum loquimur fugerit invida aetas… (Horace, Odes 1, 11, 8)
The post-genomic era and the bioinformatic revolution that accompanied it fostered new
strides in the fields of metabolomics and lipidomics. These “omics” approaches are often
referred to—rightfully so—as the “closest to the phenotype” and perceived by the scientific
community as novel, especially in comparison to genomics, transcriptomics, and pro-
teomics. Despite the aggressive and largely successful efforts to rebrand this discipline,
metabolomics—defined as the comprehensive analysis of small molecule metabolites—is
perhaps the oldest analytical tool mankind managed to harness. History is full of records
describing symptoms and metabolic characteristics of metabolic diseases such as (ante lit-
teram) diabetes: “the sweet taste” and “capacity to attract ants” of urine have been docu-
mented since the fifth century BCE in India and Greece, second century BCE in China.
Centuries of advancements in the fields of chemistry and (clinical) biochemistry, recently
accompanied by the introduction of tools like NMR and mass spectrometers, have simply
provided a novel “magnifying lens” to expand our understanding of the small molecule
world as a function of our attempts to “poke nature.” From this perspective, metabolomics
is nothing but the next iteration of a discipline that scientists have been investigating for
decades with much less sophisticated tools, often compensating for the technological gap
with incredible rigor and acumen. Building on decades of advancements and empowered
by novel analytical and bioinformatics tools, scientists have embraced the “new” field of
metabolomics to generate a wealth of data from laboratory studies, some of which are
slowly transitioning into the clinics. This transition can be significantly sped up owing to
the opportunity to perform large-scale studies in a high- throughput fashion both at the
discovery phase (e.g., high-throughput screening of novel drugs) and clinical testing (e.g.,
in large-scale prospective studies). In this view, this entry of the Methods in Molecular
Biology series focuses on recent technological, computational, and biostatistical advances in
the field of high-throughput metabolomics. Chapters encompass methods, platforms, and
analytical strategies for steady-state measurements and metabolic flux analysis with stable
isotope-labeled tracers, in biological matrices of clinical relevance and model organisms.
Mass spectrometry-based or orthogonal methods are discussed, along with computational
and statistical methods to address data sparsity in high-t hroughput metabolomics
approaches. Finally, a few representative applications are discussed, including biodosimetry,
sports and wellness, and personalized metabolomics. The main take-home message we wish
to share with the interested reader is that high-t hroughput metabolomics tools can bring
about the next generation of clinical biochemistry in a cost-effective, but not necessarily less
rigorous fashion than current analytical approaches, exponentially advancing our capacity
to investigate nature while easing the advent of personalized medicine.
v
vi Preface
Prior to concluding this quick introduction to the contents of the book, I will take the
chance to thank all the contributing authors for their support to this successful initiative
and Dr. John Walker and David C. Casey (Springer Nature) and Julie Reisz Haines
(University of Colorado Denver, Anschutz Medical Campus) for their invaluable editorial
assistance.
Conflict of Interest
A.D. is founder and CSO of Omix Technologies, Inc.
Aurora, CO, USA Angelo D’Alessandro
Contents
Preface ............................................................... v
Contributors .......................................................... xi
Part I Methods
1 Sample Preparation and Reporting Standards for Metabolomics
of Adherent Mammalian Cells...................................... 3
Sarah Hayton, Robert D. Trengove, and Garth L. Maker
2 High-Throughput Metabolomics: Isocratic and Gradient Mass
Spectrometry-Based Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Travis Nemkov, Julie A. Reisz, Sarah Gehrke, Kirk C. Hansen,
and Angelo D’Alessandro
3 High-Throughput Metabolomics Based on Direct Mass Spectrometry
Analysis in Biomedical Research .................................... 27
Raúl González-Domínguez, Álvaro González-Domínguez, Carmen Segundo,
Mónica Schwarz, Ana Sayago, Rosa María Mateos, Enrique Durán-Guerrero,
Alfonso María Lechuga-Sancho, and Ángeles Fernández-Recamales
4 Traveling Wave Ion Mobility Mass Spectrometry:
Metabolomics Applications........................................ 39
Giuseppe Paglia and Giuseppe Astarita
5 Capillary Electrophoresis Mass Spectrometry as a Tool for Untargeted
Metabolomics.................................................. 55
Ángeles López-Gonzálvez, Joanna Godzien, Antonia García, and Coral Barbas
Part II LIPIdoMIcs
6 Overview of Lipid Mass Spectrometry and Lipidomics.................... 81
Simona Zarini, Robert M. Barkley, Miguel A. Gijón, and Robert C. Murphy
7 LC-MS/MS-MRM-Based Targeted Metabolomics for Quantitative
Analysis of Polyunsaturated Fatty Acids and Oxylipins.................... 107
Xiaoyun Fu, Mikayla Anderson, Yi Wang, and James C. Zimring
8 Untargeted and Semi-targeted Lipid Analysis of Biological Samples
Using Mass Spectrometry-Based Metabolomics......................... 121
Julie A. Reisz, Connie Zheng, Angelo D’Alessandro, and Travis Nemkov
9 HPLC-MS/MS Methods for Diacylglycerol and Sphingolipid Molecular
Species in Skeletal Muscle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
Kathleen A. Harrison and Bryan C. Bergman
vii
viii Contents
Part III MetaboLoMIcs of anIMaL and PLant ModeLs
10 Quantification of d- and L-2-Hydroxyglutarate in Drosophila melanogaster
Tissue Samples Using Gas Chromatography- Mass Spectrometry ............ 155
Hongde Li and Jason M. Tennessen
11 Comprehensive LC-MS-Based Metabolite Fingerprinting Approach
for Plant and Fungal-Derived Samples................................ 167
Kirstin Feussner and Ivo Feussner
12 Untargeted Metabolomics of Plant Leaf Tissues ........................ 187
Federica Gevi, Giuseppina Fanelli, Lello Zolla, and Sara Rinalducci
Part IV tracIng exPerIMents and MetaboLIc fLux anaLysIs
13 Analysis of Arginine Metabolism Using LC-MS and Isotopic Labeling........ 199
Gretchen L. Seim, Emily C. Britt, and Jing Fan
14 Quantifying Intermediary Metabolism and Lipogenesis in Cultured
Mammalian Cells Using Stable Isotope Tracing and Mass Spectrometry ...... 219
Thekla Cordes and Christian M. Metallo
15 Insights into Dynamic Network States Using Metabolomic Data............ 243
Reihaneh Mostolizadeh, Andreas Dräger, and Neema Jamshidi
16 Analysis of Endothelial Fatty Acid Metabolism Using Tracer Metabolomics.... 259
Joanna Kalucka, Bart Ghesquière, Sarah-Maria Fendt, and Peter Carmeliet
17 Stable Isotope Tracers for Metabolic Pathway Analysis.................... 269
Sara Violante, Mirela Berisa, Tiffany H. Thomas, and Justin R. Cross
Part V data ProcessIng In MetaboLoMIcs
18 Data Processing for GC-MS- and LC-MS-Based Untargeted Metabolomics .... 287
Linxing Yao, Amy M. Sheflin, Corey D. Broeckling, and Jessica E. Prenni
19 El-MAVEN: A Fast, Robust, and User-Friendly Mass Spectrometry
Data Processing Engine for Metabolomics............................. 301
Shubhra Agrawal, Sahil Kumar, Raghav Sehgal, Sabu George,
Rishabh Gupta, Surbhi Poddar, Abhishek Jha, and Swetabh Pathak
20 Pre-analytic Considerations for Mass Spectrometry-Based
Untargeted Metabolomics Data .................................... 323
Dominik Reinhold, Harrison Pielke-Lombardo, Sean Jacobson,
Debashis Ghosh, and Katerina Kechris
Part VI MetaboLIc MeasureMents wIth technIques orthogonaL
to Mass sPectroMetry
21 Temporal Metabolite, Ion, and Enzyme Activity Profiling Using
Fluorescence Microscopy and Genetically Encoded Biosensors ............. 343
Douglas A. Chapnick, Eric Bunker, Xuedong Liu, and William M. Old
22 Microplate Assays for Spectrophotometric Measurement
of Mitochondrial Enzyme Activity................................... 355
Rachel C. Janssen and Kristen E. Boyle
Contents ix
23 Quantitative NMR-Based Metabolomics on Tissue Biomarkers
and Its Translation into In Vivo Magnetic Resonance Spectroscopy.......... 369
Natalie J. Serkova, Denise M. Davis, Jenna Steiner, and Rajesh Agarwal
Part VII towards PersonaLIzed MetaboLoMIcs
24 Metabolomic Applications in Radiation Biodosimetry .................... 391
Evagelia C. Laiakis
25 Metabolomics Analyses to Investigate the Role of Diet
and Physical Training ............................................ 403
Pol Herrero, Miguel Ángel Rodríguez, Maria Rosa Ras, Antoni del Pino,
Lluís Arola, and Núria Canela
26 Blood Biomarkers in Sports Medicine and Performance
and the Future of Metabolomics.................................... 431
Iñigo San-Millán
27 Personalized Metabolomics........................................ 447
David P. Marciano and Michael P. Snyder
Index............................................................ 457
Contributors
rajesh agarwaL • Department of Pharmaceutical Sciences, Skaggs School of Pharmacy
and Pharmaceutical Sciences, University of Colorado Denver, Aurora, CO, USA
shubhra agrawaL • Elucidata, Inc., Cambridge, MA, USA
MIkayLa anderson • Bloodworks Northwest Research Institute, Seattle, WA, USA
LLuís aroLa • Biochemistry and Biotechnological Department, Nutrigenomics Research
Group, Universitat Rovira i Virgili, Tarragona, Spain; Biotechnological Area,
EURECAT-Technological Center of Catalonia, Reus, Spain
gIusePPe astarIta • Department of Biochemistry and Molecular and Cellular Biology,
Georgetown University, Washington, DC, USA
coraL barbas • Facultad de Farmacia, Centro de Metabolómica y Bioanálisis
(CEMBIO), Universidad CEU San Pablo, Madrid, Spain
robert M. barkLey • Department of Pharmacology, University of Colorado Denver,
Aurora, CO, USA
bryan c. bergMan • Division of Endocrinology, Diabetes, and Metabolism, School of
Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, USA
MIreLa berIsa • Donald B. and Catherine C. Cancer Metabolism Center, Memorial Sloan
Kettering Cancer Center, New York, NY, USA
krIsten e. boyLe • Department of Pediatrics, Section of Nutrition, University of
Colorado Anschutz Medical Campus, Aurora, CO, USA
eMILy c. brItt • Morgridge Institute for Research, Madison, WI, USA; Department of
Nutritional Sciences, University of Wisconsin-Madison, Madison, WI, USA
corey d. broeckLIng • Proteomics and Metabolomics Facility, Colorado State University,
Fort Collins, CO, USA
erIc bunker • Department of Chemistry and Biochemistry, University of Colorado,
Boulder, CO, USA
núrIa caneLa • Technological Joint Unit of Omic Sciences, EURECAT-Technological
Center of Catalonia, Universitat Rovira i Virgili, Reus, Spain
Peter carMeLIet • Laboratory of Angiogenesis and Vascular Metabolism, VIB Center for
Cancer Biology (CCB), VIB, Leuven, Belgium; Laboratory of Angiogenesis and Vascular
Metabolism, Department of Oncology and Leuven Cancer Institute (LKI), KU Leuven,
Leuven, Belgium
dougLas a. chaPnIck • Department of Chemistry and Biochemistry, University of
Colorado, Boulder, CO, USA
thekLa cordes • Department of Bioengineering, University of California San Diego, La
Jolla, CA, USA
justIn r. cross • Donald B. and Catherine C. Cancer Metabolism Center, Memorial
Sloan Kettering Cancer Center, New York, NY, USA
angeLo d’aLessandro • Department of Biochemistry and Molecular Genetics, University
of Colorado Denver, Aurora, CO, USA
denIse M. daVIs • Department of Radiology, School of Medicine, University of Colorado
Denver, Aurora, CO, USA
xi
