Booß-Bavnbek / Klösgen / Larsen BetaSys

Systems Biology of Regulated Exocytosis in Pancreatic ß-Cells
1. Auflage 2011
ISBN: 978-1-4419-6956-9
Verlag: Springer-Verlag
Format: PDF
Kopierschutz: Wasserzeichen (»Systemvoraussetzungen)

E-Book, Englisch, 556 Seiten

BetaSys uses the example of regulated exocytosis in pancreatic ß-cells, and its relevance to diabetes, to illustrate the major concepts of systems biology, its methods and applications.

Autoren/Hrsg.

Booß-Bavnbek, Bernhelm

Klösgen, Beate

Larsen, Jesper

Pociot, Flemming

Renström, Erik

Inhaltsverzeichnis

1;Preface;5
2;Acknowledgements;8
3;Contents;9
4;Contributors;12
5;Systems Biology Approach to ß-Cells;16
5.1;Systems Biology of the ß-Cell – Revisited;17
5.1.1;1.1 Introduction;17
5.1.2;1.2 The ß-cell and Diabetes;18
5.1.3;1.3 Genetics of Diabetes – From GWA to NWA Studies;21
5.1.4;The History of Diabetes;22
5.1.5;1.4 Why Systems Biology?;23
5.1.6;1.5 Systems Biology – How?;24
5.1.7;Ludwig von Bertalanffy (1901–1972);25
5.1.8;1.6 Challenges of Methodological Advances;28
5.1.9;1.7 Summary;28
5.1.10;1.8 Understanding Pancreatic ß-cell Death in Type 1 Diabetes – A Systems Biology Approach;29
5.1.11;1.9 Conclusions;33
5.1.12;References;34
5.2;Established Facts and Open Questions of Regulated Exocytosis in ß- Cells – A Background for a Focused Systems Analysis Approach;38
5.2.1;2.1 Introduction;40
5.2.2;2.2 The Basic Organization and Characteristics of the Exocytotic System in Pancreatic ß- Cells;41
5.2.3;Typical Length Scales (Rough Estimates of Diameters) in ß- Cell Research;43
5.2.4;Observation Means and Scales – From Light Microscopy to Electron Microscopy;48
5.2.5;2.3 The Role of the Pancreatic ß-Cell in Type 2 Diabetes and Future Challenges for ß- Cell Research;56
5.2.6;References;58
5.3;Mitochondria and Metabolic Signals in ß-Cells;66
5.3.1;3.1 Introduction;66
5.3.2;3.2 Overview of Metabolism-Secretion Coupling;67
5.3.3;3.3 Mitochondrial NADH Shuttles as Metabolic Sensors;68
5.3.4;3.4 Getting In and Out of the Tricarboxylic Acid Cycle;69
5.3.5;3.5 Mitochondrial Control of the Glutamate Dehydrogenase;70
5.3.6;3.6 Mitochondrial Activation;71
5.3.7;3.7 The Amplifying Pathway of the Secretory Response;72
5.3.8;3.8 Mitochondria-Derived Nucleotides as Coupling Factors;72
5.3.9;3.9 Fatty Acid Pathways and the Secretory Response;73
5.3.10;3.10 Mitochondria-Derived Metabolites as Coupling Factors;74
5.3.11;Panorama of ß-Cell Organelles;76
5.3.12;3.11 Reactive Oxygen Species Participate to ß-Cell Function;77
5.3.13;3.12 Conclusion;77
5.3.14;References;78
5.4;ß-Cell Ontogenesis and the Insulin Production Apparatus;85
5.4.1;4.1 Early Pancreatic Organogenesis;85
5.4.2;4.2 Expansion of Progenitors;87
5.4.3;4.3 Early Differentiation;87
5.4.4;4.4 The Choice to Become a ß-Cell;88
5.4.5;4.5 Young ß-Cells;88
5.4.6;4.6 Mature ß-Cells;89
5.4.7;References;90
5.5;The Role of the Cytoskeleton in Transport and Release of Insulin- Containing Granules by Pancreatic ß- Cells;94
5.5.1;5.1 Introduction;94
5.5.2;5.2 Models to Study Insulin Secretion;96
5.5.3;5.3 Metabolic Effects of Glucose in ß-Cells;96
5.5.4;5.4 The Response of the ß-Cell;97
5.5.5;5.5 The Intracellular Cytoskeleton;98
5.5.6;5.6 Some Basic Properties of Microtubules;98
5.5.7;5.7 Conventional Kinesin Transports Insulin Granules During Second- Phase Secretion;99
5.5.8;5.8 Some Basic Properties of F-Actin Filaments;100
5.5.9;5.9 The Role of the Actin Cytoskeleton During Exocytosis;101
5.5.10;5.10 Myosin Va and F-Actin Are Necessary for the Final Delivery of Insulin Granules to the Plasma Membrane;102
5.5.11;5.11 Control of Granule Docking;102
5.5.12;Scaffolds;103
5.5.13;5.12 Control of Granule and Plasma Membrane Fusion by F- Actin;104
5.5.14;5.13 Summary;104
5.5.15;References;105
5.6;The Mathematical Microscope – Making the Inaccessible Accessible;107
5.6.1;6.1 Introduction;107
5.6.2;6.2 The Mathematical Microscope Harvey’s Mathematical Microscope;109
5.6.3;6.3 Models Are Crucial in Measurements and Experiments;111
5.6.4;Theory–Model–Experiment: Towards a Classification;112
5.6.5;6.4 What Insights Can Modelling Provide?;113
5.6.6;6.5 Example 1: Cardiovascular Diseases;115
5.6.7;6.6 Example 2: Type 1 Diabetes;117
5.6.8;6.7 Example 3: Type 2 Diabetes;119
5.6.9;6.8 Example 4: Depression;119
5.6.10;6.9 Example 5: The Grey Triangle in the Metabolic Syndrome;121
5.6.11;6.10 Discussion and Conclusions;124
5.6.12;References;125
6;Imaging and Sensors;129
6.1;Magnetic Resonance Imaging of Pancreatic ß- Cells;130
6.1.1;7.1 Introduction;130
6.1.2;7.2 The Physics of MRI;131
6.1.3;7.3 ß-Cell MRI;145
6.1.4;Quantum Mechanics Playing into Macro-space;146
6.1.5;7.4 Conclusions;153
6.1.6;References;153
6.2;Mapping the ß-Cell in 3D at the Nanoscale Using Novel Cellular Electron Tomography and Computational Approaches;156
6.2.1;8.1 General Introduction;158
6.2.2;8.2 Background to Methods and Rationale;159
6.2.3;8.3 “Holistic” Insights from 3D Image Reconstruction of the ß- Cell at Nanometre Resolution;173
6.2.4;Tomography – Translating Maps into Images;177
6.2.5;8.4 Conclusions and Future Directions;182
6.2.6;References;183
6.3;In Vivo Applications of Inorganic Nanoparticles;193
6.3.1;9.1 Introduction;194
6.3.2;9.2 Bioconjugation;196
6.3.3;9.3 Imaging;199
6.3.4;Inorganic Nanoparticles;201
6.3.5;9.4 Therapy;209
6.3.6;9.5 Toxicity;213
6.3.7;References;218
6.4;Cell Cultivation and Sensor-Based Assays for Dynamic Measurements of Cell Vitality;229
6.4.1;10.1 Introduction;230
6.4.2;10.2 Prerequisites for Assessing Cell Vitality and Function In Vitro;233
6.4.3;10.3 Biochemical Assays and Their Information;235
6.4.4;10.4 Dynamic Measurements Via Multiparametric Sensor-Based Assays;237
6.4.5;MEMS – A New Generation of Miniaturized Integrated Devices;239
6.4.6;10.5 What Can Sensor-Based Method Contribute to Systems Biology of Islets and ß- Cells?;245
6.4.7;References;246
6.5;Bioimpedance Spectroscopy;249
6.5.1;11.1 Introduction;250
6.5.2;11.2 Theoretical Background of Bioimpedance Spectroscopy;250
6.5.3;11.3 Experimental Set-up;259
6.5.4;11.4 Applications;262
6.5.5;Complex Numbers;270
6.5.6;11.5 Phenomenological Relaxation Regions in Biomaterial;271
6.5.7;11.6 Conclusion;272
6.5.8;References;274
7;Genetics and Proteomics;280
7.1;DNA Variations, Impaired Insulin Secretion and Type 2 Diabetes;281
7.1.1;12.1 Introduction;281
7.1.2;Genetic Epidemiology;283
7.1.3;Genotyping Arrays;285
7.1.4;Pattern Recognition in Gene Analysis and the Hidden Markov Model ( HMM);291
7.1.5;12.2 Clinical Implications and Future Directions;296
7.1.6;References;297
7.2;Genetically Programmed Defects in ß-Cell Function;304
7.2.1;13.1 Introduction;304
7.2.2;13.2 The Pancreatic ß-Cell, Insulin Secretion and the Main Targets of Genetically Programmed Defects;308
7.2.3;13.3 Glucose Transporter 2 (GLUT 2) and Fanconi–Bickel Syndrome;309
7.2.4;13.4 Glucokinase and Defects in Glucose Homeostasis;310
7.2.5;13.5 Mitochondrial Mutations Impairing ß-Cell Function and Mitochondrial Diabetes and Deafness ( MIDD);312
7.2.6;13.6 The KATP Channel and Defects in Glucose Homeostasis;313
7.2.7;13.7 Defects in Glucose Homeostasis due to Mutations in Genes Encoding ß- Cell Transcription Factors;315
7.2.8;13.8 Mutations in Carboxy Ester Lipase (CEL) Cause Maturity-Onset Diabetes of the Young Subtype CEL (CEL-MODY);318
7.2.9;13.9 Endoplasmic Reticulum (ER) Stress as a Cause of ß-Cell Death and Defects in Glucose Homeostasis;319
7.2.10;13.10 Common Genetic Variants Associated with T2D in Genes Implicated in Monogenic Forms of ß- Cell Dysfunction;320
7.2.11;13.11 Summary;320
7.2.12;References;321
7.3;Proteomic Analysis of the Pancreatic Islet ß-Cell Secretory Granule: Current Understanding and Future Opportunities;332
7.3.1;14.1 Introduction: Proteomics and the ß-Cell Secretory Granule;333
7.3.2;Proteomic Analysis;334
7.3.3;14.2 ß-Cell Secretory Granules: Structural Regions and Functional Specialization;339
7.3.4;14.3 Evolution of a Question That Might be Addressed by Proteomics: ’ How Might Amylin Misfolding Cause T2DM?’;341
7.3.5;14.4 The ß-Cell Secretory Granule Proteome;345
7.3.6;14.5 Next Steps;359
7.3.7;References;360
7.4;Physiological and Pathophysiological Role of Islet Amyloid Polypeptide ( IAPP, Amylin);368
7.4.1;15.1 Islet Amyloid Polypeptide;368
7.4.2;15.2 Regulation of the IAPP Gene;370
7.4.3;15.3 Receptor for IAPP;370
7.4.4;15.4 IAPP in Other Species;371
7.4.5;15.5 Physiology of IAPP;371
7.4.6;15.6 Amyloid;374
7.4.7;Amyloid;374
7.4.8;15.7 Conclusion;382
7.4.9;References;382
8;Physiological, Pharmaceutical and Clinical Applications and Perspectives;392
8.1;Present State of Islet Transplantation for Type 1 Diabetes Patients;393
8.1.1;16.1 The Prospects of ß-Cell Replacement Therapy in Type 1 Diabetes;393
8.1.2;16.2 The History of ß-Cell Replacement Therapy;394
8.1.3;16.3 Immunosuppression;395
8.1.4;16.4 Indications for Clinical Islet Transplantation;397
8.1.5;16.5 Results Obtained in Clinical Islet Transplantation Trials 2000– 2009;398
8.1.6;16.6 Practical Issues in Clinical Islet Transplantation Today;400
8.1.7;The History of Transplantation;403
8.1.8;16.7 The Liver as the “Gold Standard” for Clinical Islet Transplantation and Alternative Sites;403
8.1.9;16.8 Monitoring the Islet Graft;404
8.1.10;References;406
8.2;Predictive Protein Networks and Identification of Druggable Targets in the ß- Cell;410
8.2.1;17.1 The Need for NewWays of Identifying Druggable Targets;410
8.2.2;Drug Development;411
8.2.3;17.2 How Can Drug Target Identification Be Optimized?;411
8.2.4;The History of Insulin;413
8.2.5;Clinical Trials;420
8.2.6;References;421
8.3;Nanotoxicity;422
8.3.1;18.1 Nanotoxicology and Nanoparticles;422
8.3.2;18.2 Potential Routes of Exposure;424
8.3.3;18.3 Historical Perspective;427
8.3.4;18.4 Nanoparticle Toxicity;428
8.3.5;18.5 Nanomedicines for Pancreatic Disease;431
8.3.6;Classical Toxicity Studies;433
8.3.7;18.6 Summary;434
8.3.8;References;434
9;Mathematical Modelling and Numerical Simulation;438
9.1;From Silicon Cell to Silicon Human;439
9.1.1;19.1 Introduction;440
9.1.2;19.2 How Systems Biology?;441
9.1.3;Information and Complexity;447
9.1.4;19.3 Towards the Silicon Human;455
9.1.5;References;458
9.2;Probing Cellular Dynamics with Mesoscopic Simulations;461
9.2.1;20.1 Introduction;461
9.2.2;20.2 Particle-Based Computer Simulations in Biophysics;463
9.2.3;Buffon’s Needle Problem – An Early Forerunner of Monte Carlo Simulation;466
9.2.4;20.3 Dissipative Particle Dynamics Simulations of Vesicle Fusion;466
9.2.5;20.4 Conclusions and Outlook;471
9.2.6;References;473
9.3;What Drives Calcium Oscillations in ß-Cells? New Tasks for Cyclic Analysis;476
9.3.1;21.1 Introduction;477
9.3.2;Fourier Analysis;478
9.3.3;21.2 Schematic Model;479
9.3.4;21.3 [Ca2+]c as the Pacemaker Component;480
9.3.5;21.4 Role of [ATP]/[ADP] Ratio as Pacemaker;481
9.3.6;21.5 ER Ca2+ as a Pacemaker Component;483
9.3.7;21.6 Intracellular [Na+] as a Slow Component in a Pacemaker Mechanism;485
9.3.8;21.7 Mechanistic Interactions and Compound Patterns of Bursting and [Ca2+]c Oscillations;487
9.3.9;21.8 Summary;487
9.3.10;References;488
9.4;Whole-Body and Cellular Models of Glucose- Stimulated Insulin Secretion;490
9.4.1;22.1 Introduction;490
9.4.2;22.2 Modelling Issues in Assessing ß-Cell Function;491
9.4.3;22.3 Minimal Models of Insulin Secretion;494
9.4.4;Compartment Models;497
9.4.5;22.4 Minimal Models of Insulin Action and Hepatic Insulin Extraction;497
9.4.6;22.5 Cellular Model of Insulin Secretion;498
9.4.7;22.6 Cellular Modelling: Insight into Minimal Models;500
9.4.8;22.7 Conclusions;501
9.4.9;References;501
9.5;Geometric and Electromagnetic Aspects of Fusion Pore Making;505
9.5.1;23.1 Introduction;506
9.5.2;23.2 Synopsis of Established Facts;508
9.5.3;The Four Maxwell’s Equations at a Glance;516
9.5.4;23.3 The Model;521
9.5.5;High-Voltage Devices: Quantitative Comparison of Electric Field Strengths in Electrical Power Plants and Animal Cells;527
9.5.6;23.4 Apposite Results on Parabolic Obstacle Problems;529
9.5.7;Experiment and Discovery;533
9.5.8;23.5 Conclusions;534
9.5.9;References;536
10;Index;539