Fundamentals of Advanced Omics Technologies

Fundamentals of Advanced Omics Technologies

Fundamentals of Advanced Omics
Technologies: From Genes to
Metabolites
Comprehensive Analytical Chemistry
Volume 63
ADVISORY BOARD
Joseph A. Caruso
University of Cincinnati, Cincinnati, OH, USA
Hendrik Emons
Joint Research Centre, Geel, Belgium
Gary Hieftje
Indiana University, Bloomington, IN, USA
Kiyokatsu Jinno
Toyohashi University of Technology, Toyohashi, Japan
Uwe Karst
University of Münster, Münster, Germany
Gyrögy Marko-Varga
AstraZeneca, Lund, Sweden
Janusz Pawliszyn
University of Waterloo, Waterloo, Ont., Canada
Susan Richardson
US Environmental Protection Agency, Athens, GA, USA
Fundamentals of
Advanced Omics
Technologies: From
Genes to Metabolites
Comprehensive Analytical Chemistry
Volume 63
Edited by
Carolina Simó
Laboratory of Foodomics, Institute of Food Science Research (CIAL),
CSIC. Nicolás Cabrera 9, Madrid, Spain
Alejandro Cifuentes
Laboratory of Foodomics, Institute of Food Science Research (CIAL),
CSIC. Nicolás Cabrera 9, Madrid, Spain
Virginia Garcı́a-Cañas
Laboratory of Foodomics, Institute of Food Science Research (CIAL),
CSIC. Nicolás Cabrera 9, Madrid, Spain
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14 15 16 17 10 9 8 7 6 5 4 3 2 1
Contents
Contributors to Volume 63
Series Editor’s Preface
Preface
1. DNA Microarrays Technology: Overview
and Current Status
xiii
xvii
xix
1
Alex Sánchez-Pla
1. Introduction and Overview
1.1. A Brief History of Microarrays
2. Types of DNA Microarrays
2.1. Spotted or Printed Microarrays
2.2. In Situ Synthesized Microarrays
2.3. High-Density Bead Arrays
3. Applications of Microarrays
3.1. Microarrays for Gene Expression Analysis
3.2. SNP Arrays for Variation Analysis and Genotyping
3.3. CGH Arrays for Comparative Genomic Hybridization
3.4. ChIP-on-Chip Arrays for Transcription Factor
Binding Analysis
3.5. Arrays for the Analysis of Alternative Splicing
and Related Issues
4. Microarray Bioinformatics
4.1. The MIAME Standard
4.2. Microarray Databases
5. Discussion and Concluding Remarks
References
2. Challenges and Future Trends in DNA
Microarray Analysis
1
3
4
4
5
9
11
11
16
17
17
18
18
19
19
20
21
25
Abootaleb Sedighi and Paul C.H. Li
1. Introduction
2. Toward Microarray POC Devices
2.1. Microfluidic Microarrays
2.2. Label-Free Detection
2.3. Miniaturized Nanoarray Platforms
2.4. Integrated LOC Devices
3. Validity of Microarray Data
4. Clinical Adoption
25
27
28
33
35
36
37
39
v
vi
Contents
5. Future Trends of Microarray
6. Conclusion
References
3. Next-Generation Sequencing: New Tools
to Solve Old Challenges
41
43
44
47
I. Gobernado, A. Sanchez-Herranz and A. Jimenez-Escrig
1. Introduction
2. Basis for NGS
3. Sample Preparation for NGS
3.1. Clonal Amplification
3.2. Single-Molecule Sequencing
4. Sequencing Techniques
4.1. Sequencing-by-Synthesis
4.2. Sequencing-by-Ligation
4.3. Other Sequencing Technologies
5. NGS Data Analysis
6. Main Applications of NGS
6.1. Whole-Genome Sequencing
6.2. Targeted Region Resequencing
6.3. Metagenomics
6.4. RNA-Sequencing
6.5. Other NGS Applications
7. Integrating Omics Data
References
4. Omics Tools for the Genome-Wide Analysis
of Methylation and Histone Modifications
47
50
51
51
52
54
54
59
59
63
63
63
66
68
69
70
72
73
81
Josep C. Jiménez-Chillarón, Rubén Dı́az
and Marta Ramón-Krauel
1. Omics Meets Epigenetics
1.1. Omics
1.2. Epigenetics
1.3. Epigenomics: When -Omics Met Epigenetics
2. Methods in Epigenomics
2.1. DNA Methylation
2.2. Histone Modifications
2.3. Noncoding RNAs
3. Concluding Remarks
References
5. An Overview of Quantitative Proteomic Approaches
81
81
82
86
87
87
96
99
106
106
111
Adam J. McShane, Vahid Farrokhi, Reza Nemati, Song Li
and Xudong Yao
1. Introduction
2. Immuno-Based Detection Methods
111
112
Contents
2.1. Gel-Based Approaches
2.2. Non-Gel-Based Approaches
3. Mass Spectrometry-Based Detection Methods
3.1. Introduction
3.2. Mass Spectrometers
3.3. Derivatization-Free Techniques
3.4. Derivatization-Based Techniques
3.5. Activity-Based Probes
3.6. Sample Preparation
3.7. Liquid Chromatography
3.8. Software
3.9. Analyte Multiplexing and Sample Throughput
4. Conclusions
Acknowledgments
References
6. Emerging Nanotechniques in Proteomics
vii
112
113
115
115
115
117
119
121
122
125
128
128
128
129
129
137
Noelia Dasilva, Maria Gonzalez-Gonzalez, Paula Diez,
Ricardo Jara-Acevedo, Lucia Lourido, J.M. Sayagues,
Alberto Orfao and Manuel Fuentes
1. Introduction
2. Overview of Protein Microarrays
2.1. Target Microarray
2.2. Reverse-Phase Protein Array (RPP)
2.3. In Situ Expressed Protein Array
3. Detection Platforms in Nanoproteomics
3.1. Label Detection Techniques
3.2. Label-Free Detection Methods
4. Biomarker Discovery by Nanoproteomics Approaches
4.1. AuNPs and QDs
4.2. Surface Plasmon Resonance
4.3. Microcantilevers and AFM
4.4. ESI-MS
4.5. CyTof Applications
5. Conclusions
Acknowledgments
References
137
138
139
139
140
140
141
141
146
148
148
150
150
152
154
154
155
7. Mass Spectrometry Imaging in Proteomics and
Metabolomics
159
Benjamin Balluff, Ricardo J. Carreira and Liam
A. McDonnell
1. The Need for Imaging-Based Proteomics and Metabolomics
2. Mass Spectrometry Imaging
2.1. Mass Spectrometry
159
161
161
viii
Contents
2.2. Sample Preparation
2.3. Data Processing in MSI
2.4. Statistical Analysis of MSI Data
2.5. Strategies for the Identification of m/z Signals
3. Applications of MSI
3.1. Applications in Disease Pathology
3.2. Applications in Drug Imaging
4. Future Developments
References
8. Advances in NMR-Based Metabolomics
168
170
172
175
178
178
179
180
181
187
G.A. Nagana Gowda and Daniel Raftery
1. Introduction
2. NMR Methods
2.1. One-Dimensional NMR Methods
2.2. Two-Dimensional NMR Methods
2.3. Isotope-Enhanced NMR Methods
3. Micro-Coil NMR
4. Fast NMR Methods
5. Hyperpolarization in NMR
6. Statistical and Data Analysis Methods
7. Spectral Assignment and Metabolite Quantitation Methods
7.1. Automation
7.2. Analysis of Heteronuclear 2D Spectra
8. STOCSY and RANSY Methods
9. Applications
10. Conclusions
11. Acknowledgment
12. Disclosure of Potential Conflict of Interest
References
9. The Role of Mass Spectrometry in Nontargeted
Metabolomics
187
188
189
190
191
193
195
195
196
198
199
199
200
201
204
205
205
205
213
Helen G. Gika, Ian D. Wilson and
Georgios A. Theodoridis
1.
2.
3.
4.
5.
Introduction
Study Design
Sample Preparation
Analytical Strategies
MS-Based Untargeted Metabolomics
5.1. LC Opportunities and Issues
5.2. GC Opportunities and Issues
5.3. MS Opportunities and Issues
6. Data Analysis
213
215
216
218
221
221
223
224
225
Contents
7. Identification of Biomarkers and Biochemical Pathway
Visualization
8. Synopsis
References
10. Direct Mass Spectrometry-Based Approaches
in Metabolomics
ix
227
230
231
235
Clara Ibáñez, Virginia Garcı́a-Cañas, Alberto Valdés
and Carolina Simó
1. Introduction
2. Matrix-Assisted and Matrix-Free Laser
Desorption/Ionization MS
3. Direct-Infusion MS
4. Ambient-Ionization MS
5. Imaging MS
6. Conclusions
References
11. Functional Glycomics Analysis: Challenges and
Methodologies
235
236
238
240
243
250
250
255
Nathan W. Stebbins and Ram Sasisekharan
1. Introduction
2. Structural Analysis of Glycans
2.1. General Consideration for Glycan Analysis
2.2. High-Performance Liquid Chromatography
2.3. Capillary Electrophoresis
2.4. MS for Glycomics
2.5. Lectins as Structural Probes
3. Functional Analysis of Glycans
3.1. Genetics Approach to Glycomics
3.2. Glycan Array and Synthesis Technologies
4. Integrating Structure and Function: A Case Study
5. Conclusions
Acknowledgments
References
12. Applications of Glycan Microarrays to Functional
Glycomics
255
258
259
261
262
264
266
267
268
270
271
275
276
276
281
Ying Yu, Xuezheng Song, David F. Smith and
Richard D. Cummings
1. Introduction
2. Generation of Glycan Microarrays
2.1. Glycan Sources
2.2. Glycan Immobilization
2.3. Shotgun Glycan Microarray (SGM)
281
283
283
285
288
x
Contents
3. Examples of Reported Glycan Microarrays
4. Identification of Virus Receptors with Glycan Microarrays
4.1. Influenza Virus
4.2. Minute Virus of Mice
4.3. Rotavirus
5. Conclusions
Acknowledgments
References
290
294
294
297
298
299
300
300
13. High-Resolution Analytical Tools for Quantitative
Peptidomics
305
Sayani Dasgupta and Lloyd D. Fricker
1. Introduction
2. Absolute Quantification
3. Relative Quantification
3.1. Label-Free Quantification
3.2. Metabolic Labeling
3.3. Chemical Labeling
3.4. Proteolytic Labeling
4. Concluding Remarks
References
14. Analysis of Deep Sequencing Data: Insights
and Challenges
305
306
307
308
311
312
319
320
320
325
Jacob W. Malcom and John H. Malone
1. Introduction
2. Fundamentals
2.1. Quality Control
2.2. Mapping
3. Applications
3.1. DNA Applications
3.2. RNA Applications
3.3. Relating Sequence and Expression Variation
to Phenotypes
3.4. Application Pitfalls: Data Heterogeneity,
Normalization, and False Discovery
4. The Computing Side of Deep Sequencing
4.1. Data Management and Computational Power
4.2. Visualization
4.3. Public Data
4.4. Communicating Analyses: Galaxy and Code Repositories
4.5. Resources
5. Summary and Future Directions
Acknowledgments
References
325
326
327
329
333
334
338
344
346
347
348
348
349
349
351
351
352
352
Contents
15. Gene Expression Analysis and Profiling of
Microarrays Data and RNA-Sequencing Data
xi
355
Javier De Las Rivas, Sara Aibar and Beatriz Roson
1. Human Genome and Transcriptome: From Gene Loci
to Gene Products
1.1. Redefinition of Gene in the Context of Modern
Transcriptomics
1.2. Types of Genes and RNA Complexity: Emerging
Interest in ncRNAs
1.3. Protein-Coding Genes: cDNA Collections and ORFeomes
1.4. Biological Databases to Identify and Explore Expression
of Protein-Coding Genes: Entrez Gene, ENSEMBL,
GATExplorer, and ProteinAtlas
1.5. Gene Expression Regulation: Transcription Factors
2. Experimental Technologies for Genome-Wide Expression
Analysis
2.1. Measuring Gene Expression: Real-Time qPCR
2.2. Microarrays
2.3. RNA Sequencing
2.4. Other High-Throughput Platforms to Investigate
Regulation of Gene Expression
3. Bioinformatic Analysis of Gene Expression Data
3.1. Computational Methods to Achieve Gene
Expression Profiling and Find Gene Signatures
3.2. Algorithms to Analyze Microarray Expression Data
3.3. Algorithms to Analyze RNA-Seq Data
3.4. Methods for Functional and Pathway Enrichment
Analysis of Selected Gene Lists
References
16. Bioinformatic Approaches to Increase Proteome
Coverage
356
356
357
359
360
362
364
364
365
370
372
375
375
377
378
381
382
385
Francesco M. Mancuso, Salvatore Cappadona
and Eduard Sabidó
1. Introduction
2. Increasing the Number of Fragmented Features
2.1. Protein-Level Separation
2.2. Peptide-Level Separation
2.3. MS-Level Separation
3. Reducing the Number of Unassigned Spectra
3.1. Reducing Rates of Unidentified Peptides
3.2. Increasing Rates of Identifiable Peptides
4. Summary
Acknowledgments
References
385
388
388
389
391
393
394
399
409
411
411
xii
Contents
17. Transcriptome and Metabolome Data
Integration—Technical Perquisites for Successful
Data Fusion and Visualization
421
Michael Witting and Philippe Schmitt-Kopplin
1. Introduction
2. Extraction, Measurement, Raw Data Analysis, and
Data Fusion
2.1. Transcriptomics
2.2. Metabolomics
2.3. Data Fusion Types
3. Visualization
3.1. Visualization on KEGG Pathways
3.2. Visualization on MetaCyc Pathways
3.3. Network Visualization and Analysis
4. MassTRIX Reloaded—Combined Analysis and
Visualization of Metabolome and Trascriptome Data
4.1. Annotation of Mass Spectrometric Data
4.2. Analysis of Transcriptomic Data
4.3. Comparison Against Other Existing Resources
4.4. Future Directions for MassTRIX
5. Conclusions
References
18. Computational Approaches for Visualization
and Integration of Omics Data
421
424
424
427
430
433
433
435
435
436
436
437
437
439
440
441
443
Vasudha Sehgal, Tyler J. Moss and Prahlad T. Ram
1. Introduction
2. Data Overview
2.1. Data Types
2.2. Data Sources
3. Data Processing and Analyzing Tools
4. Network and Pathway Databases
4.1. Protein Interaction Databases
4.2. Pathway Commons
5. Visualization of Omics Data
5.1. Clustering and Heatmaps
5.2. Tools for Network Creation, Visualization, and Analysis
6. Conclusion
References
Index
443
444
444
445
448
448
449
449
450
450
451
453
453
455
Contributors to Volume 63
Sara Aibar, Bioinformatics and Functional Genomics Group, Cancer Research Center
(CiC-IBMCC, CSIC/USAL), Salamanca, Spain
Benjamin Balluff, Center for Proteomics and Metabolomics, Leiden University
Medical Center, Leiden, The Netherlands
Salvatore Cappadona, Proteomics Unit, Centre for Genomic Regulation (CRG) and
Universitat Pompeu Fabra (UPF), Barcelona, Spain
Ricardo J. Carreira, Center for Proteomics and Metabolomics, Leiden University
Medical Center, Leiden, The Netherlands
Richard D. Cummings, Department of Biochemistry and the Glycomics Center,
Emory University School of Medicine, Atlanta, Georgia, USA
Sayani Dasgupta, Department of Molecular Pharmacology, Albert Einstein College of
Medicine, Bronx, New York, USA
Noelia Dasilva, Centro de Investigación del Cáncer/IBMCC (USAL/CSIC), IBSAL,
Departamento de Medicina Unidad de Proteomica & Servicio General de
Citometrı́a, University of Salamanca, Salamanca, Spain
Javier De Las Rivas, Bioinformatics and Functional Genomics Group, Cancer
Research Center (CiC-IBMCC, CSIC/USAL), Salamanca, Spain
Rubén Dı́az, Hospital Sant Joan de Deu, Endocrinology, Fundacio per la Recerca Sant
Joan de Deu, Barcelona, Spain
Paula Diez, Centro de Investigación del Cáncer/IBMCC (USAL/CSIC), IBSAL,
Departamento de Medicina Unidad de Proteomica & Servicio General de
Citometrı́a, University of Salamanca, Salamanca, Spain
Vahid Farrokhi, Department of Chemistry, University of Connecticut, Storrs,
Connecticut, USA
Lloyd D. Fricker, Department of Molecular Pharmacology, Albert Einstein College of
Medicine, Bronx, New York, USA
Manuel Fuentes, Centro de Investigación del Cáncer/IBMCC (USAL/CSIC), IBSAL,
Departamento de Medicina Unidad de Proteomica & Servicio General de
Citometrı́a, University of Salamanca, Salamanca, Spain
Virginia Garcı́a-Cañas, Laboratory of Foodomics, Institute of Food Science Research
(CIAL), CSIC. Nicolás Cabrera 9, Madrid, Spain
Helen G. Gika, Department of Chemical Engineering, Aristotle University
Thessaloniki, Thessaloniki, Greece
I. Gobernado, Servicio de Psiquiatrı́a, Hospital Ramón y Cajal, Madrid, Spain
xiii
xiv
Contributors to Volume 63
Maria Gonzalez-Gonzalez, Centro de Investigación del Cáncer/IBMCC (USAL/
CSIC), IBSAL, Departamento de Medicina Unidad de Proteomica & Servicio
General de Citometrı́a, University of Salamanca, Salamanca, Spain
Clara Ibáñez, Laboratory of Foodomics, Institute of Food Science Research (CIAL),
CSIC. Nicolás Cabrera 9, Madrid, Spain
Ricardo Jara-Acevedo, ImmunoStep, Edificio Centro de Investigación del Cáncer,
Avda. Coimbra s/n, Campus Miguel de Unamuno, Salamanca, Spain
A. Jimenez-Escrig, Servicio de Neurologı́a, Hospital Ramón y Cajal, Madrid, Spain
Josep C. Jiménez-Chillarón, Hospital Sant Joan de Deu, Endocrinology, Fundacio per
la Recerca Sant Joan de Deu, Barcelona, Spain
Paul C.H. Li, Department of Chemistry, Simon Fraser University, Burnaby, British
Columbia, Canada
Song Li, Department of Chemistry, University of Connecticut, Storrs, Connecticut,
USA
Lucia Lourido, Instituto de Investigación Biomedica da Coruña (INIBIC), Hospital
Universitario A Coruña, A Coruña, Spain
Jacob W. Malcom, Department of Molecular and Cell Biology, University of
Connecticut, Storrs, Connecticut, USA
John H. Malone, Department of Molecular and Cell Biology, University of
Connecticut, Storrs, Connecticut, USA
Francesco M. Mancuso, Proteomics Unit, Centre for Genomic Regulation (CRG) and
Universitat Pompeu Fabra (UPF), Barcelona, Spain
Liam A. McDonnell, Center for Proteomics and Metabolomics, Leiden University
Medical Center, Leiden, The Netherlands
Adam J. McShane, Department of Chemistry, University of Connecticut, Storrs,
Connecticut, USA
Tyler J. Moss, Department of Systems Biology, UT MD Anderson Cancer Center,
Houston, Texas, USA
G.A. Nagana Gowda, Department of Anesthesiology and Pain Medicine, Northwest
Metabolomics Research Center, University of Washington, Seattle, Washington, USA
Reza Nemati, Department of Chemistry, University of Connecticut, Storrs, Connecticut, USA
Alberto Orfao, Centro de Investigación del Cáncer/IBMCC (USAL/CSIC), IBSAL,
Departamento de Medicina Unidad de Proteomica & Servicio General de
Citometrı́a, University of Salamanca, Salamanca, Spain
Daniel Raftery, Department of Anesthesiology and Pain Medicine, Northwest
Metabolomics Research Center, University of Washington, and Public Health
Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington,
USA
Prahlad T. Ram, Department of Systems Biology, UT MD Anderson Cancer Center,
Houston, Texas, USA
Contributors to Volume 63
xv
Marta Ramón-Krauel, Hospital Sant Joan de Deu, Endocrinology, Fundacio per la
Recerca Sant Joan de Deu, Barcelona, Spain
Beatriz Roson, Bioinformatics and Functional Genomics Group, Cancer Research
Center (CiC-IBMCC, CSIC/USAL), Salamanca, Spain
Eduard Sabidó, Proteomics Unit, Centre for Genomic Regulation (CRG) and
Universitat Pompeu Fabra (UPF), Barcelona, Spain
A. Sanchez-Herranz, Servicio de Neurobiologı́a-Investigación, Unidad Central de
Genómica Translacional, Hospital Ramón y Cajal, Madrid, Spain
Alex Sánchez-Pla, Statistics Department, Facultat de Biologia, University of
Barcelona, and Statistics and Bioinformatics Unit, Vall d’Hebron Institut de
Recerca (VHIR), Barcelona, Spain
Ram Sasisekharan, Department of Biological Engineering, Koch Institute for
Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge,
Massachusetts, USA
J.M. Sayagues, Centro de Investigación del Cáncer/IBMCC (USAL/CSIC), IBSAL,
Departamento de Medicina Unidad de Proteomica & Servicio General de
Citometrı́a, University of Salamanca, Salamanca, Spain
Philippe Schmitt-Kopplin, Research Unit Analytical BioGeoChemistry, Helmholtz
Zentrum München, German Research Center for Environmental Health,
Neuherberg, and Chair of Analytical Food Chemistry, Technische Universität
München, Freising-Weihenstephan, Germany
Abootaleb Sedighi, Department of Chemistry, Simon Fraser University, Burnaby,
British Columbia, Canada
Vasudha Sehgal, Department of Systems Biology, UT MD Anderson Cancer Center,
Houston, Texas, USA
Carolina Simó, Laboratory of Foodomics, Institute of Food Science Research (CIAL),
CSIC. Nicolás Cabrera 9, Madrid, Spain
David F. Smith, Department of Biochemistry and the Glycomics Center, Emory
University School of Medicine, Atlanta, Georgia, USA
Xuezheng Song, Department of Biochemistry and the Glycomics Center, Emory
University School of Medicine, Atlanta, Georgia, USA
Nathan W. Stebbins, Department of Biological Engineering, Koch Institute for
Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge,
Massachusetts, USA
Georgios A. Theodoridis, Department of Chemistry, Aristotle University Thessaloniki,
Thessaloniki, Greece
Alberto Valdés, Laboratory of Foodomics, Institute of Food Science Research (CIAL),
CSIC. Nicolás Cabrera 9, Madrid, Spain
Ian D. Wilson, Department of Surgery and Cancer, Faculty of Medicine, Imperial
College, South Kensington, London, United Kingdom
xvi
Contributors to Volume 63
Michael Witting, Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum
München, German Research Center for Environmental Health, Neuherberg, Germany
Xudong Yao, Department of Chemistry, University of Connecticut, Storrs, Connecticut,
USA
Ying Yu, Department of Biochemistry and the Glycomics Center, Emory University
School of Medicine, Atlanta, Georgia, USA