[eBook Code] Cell Culture Engineering (eBook Code, 1st)

· 제목 : [eBook Code] Cell Culture Engineering (eBook Code, 1st) (Recombinant Protein Production)
· 분류 : 외국도서 > 과학/수학/생태 > 과학 > 생명공학
· ISBN : 9783527811380
· 쪽수 : 440쪽

About the Series Editors xvii

1 Platform Technology for Therapeutic Protein Production 1
Tae Kwang Ha, Jae Seong Lee, and Gyun Min Lee

1.1 Introduction 1

1.2 Overall Trend Analysis 3

1.2.1 Mammalian Cell Lines 3

1.2.2 Brief Introduction of Advances and Techniques 5

1.3 General Guidelines for Recombinant Cell Line Development 6

1.3.1 Host Selection 6

1.3.2 Expression Vector 7

1.3.3 Transfection/Selection 7

1.3.4 Clone Selection 8

1.3.4.1 Primary Parameters During Clone Selection 8

1.3.4.2 Clone Screening Technologies 9

1.4 Process Development 9

1.4.1 Media Development 10

1.4.2 Culture Environment 10

1.4.3 Culture Mode (Operation) 10

1.4.4 Scale-up and Single-Use Bioreactor 11

1.4.5 Quality Analysis 12

1.5 Downstream Process Development 12

1.5.1 Purification 12

1.5.2 Quality by Design (QbD) 13

1.6 Trends in Platform Technology Development 14

1.6.1 Rational Strategies for Cell Line and Process Development 14

1.6.2 Hybrid Culture Mode and Continuous System 15

1.6.3 Recombinant Human Cell Line Development for Therapeutic Protein Production 16

1.7 Conclusion 17

Acknowledgment 17

Conflict of Interest 17

References 17

2 Cell Line Development for Therapeutic Protein Production 23
Soo Min Noh, Seunghyeon Shin, and Gyun Min Lee

2.1 Introduction 23

2.2 Mammalian Host Cell Lines for Therapeutic Protein Production 25

2.2.1 CHO Cell Lines 25

2.2.2 Human Cell Lines 26

2.2.3 Other Mammalian Cell Lines 27

2.3 Development of Recombinant CHO Cell Lines 27

2.3.1 Expression Systems for CHO Cells 28

2.3.2 Cell Line Development Process Using CHO Cells Based on Random Integration 28

2.3.2.1 Vector Construction 29

2.3.2.2 Transfection and Selection 30

2.3.2.3 Gene Amplification 30

2.3.2.4 Clone Selection 31

2.3.3 Cell Line Development Process Using CHO Cells Based on Site-Specific Integration 32

2.4 Development of Recombinant Human Cell Lines 34

2.4.1 Necessity for Human Cell Lines 34

2.4.2 Stable Cell Line Development Process Using Human Cell Lines 35

2.5 Important Consideration for Cell Line Development 36

2.5.1 Clonality 36

2.5.2 Stability 36

2.5.3 Quality of Therapeutic Proteins 37

2.6 Conclusion 38

References 38

3 Transient Gene Expression-Based Protein Production in Recombinant Mammalian Cells 49
Joo-Hyoung Lee, Henning G. Hansen, Sun-Hye Park, Jong-Ho Park, and Yeon-Gu Kim

3.1 Introduction 49

3.2 Gene Delivery: Transient Transfection Methods 50

3.2.1 Calcium Phosphate-Based Transient Transfection 50

3.2.2 Electroporation 51

3.2.3 Polyethylenimine-Based Transient Transfection 52

3.2.4 Liposome-Based Transient Transfection 52

3.3 Expression Vectors 53

3.3.1 Expression Vector Composition and Preparation 53

3.3.2 Episomal Replication 53

3.3.3 Coexpression Strategies 54

3.4 Mammalian Cell Lines 54

3.4.1 HEK293 Cell-Based TGE Platforms 55

3.4.2 CHO Cell-Based TGE Platforms 56

3.4.3 TGE Platforms Using Other Cell Lines 58

3.5 Cell Culture Strategies 58

3.5.1 Culture Media for TGE 58

3.5.2 Optimization of Cell Culture Processes for TGE 59

3.5.3 q_p-Enhancing Factors in TGE-Based Culture Processes 59

3.5.4 Culture Longevity-Enhancing Factors in TGE-Based Culture Processes 59

3.6 Large-Scale TGE-Based Protein Production 60

3.7 Concluding Remarks 62

References 62

4 Enhancing Product and Bioprocess Attributes Using Genome-Scale Models of CHO Metabolism 73
Shangzhong Li, Anne Richelle, and Nathan E. Lewis

4.1 Introduction 73

4.1.1 Cell Line Optimization 73

4.1.2 CHO Genome 75

4.1.2.1 Development of Genomic Resources of CHO 75

4.1.2.2 Development of Transcriptomics and Proteomics Resources of CHO 75

4.2 Genome-Scale Metabolic Model 76

4.2.1 What Is a Genome-Scale Metabolic Model 76

4.2.2 Reconstruction of GEMs 77

4.2.2.1 Knowledge-Based Construction 77

4.2.2.2 Draft Reconstruction 77

4.2.2.3 Curation of the Reconstruction 77

4.2.2.4 Conversion to a Computational Format 79

4.2.2.5 Model Validation and Evaluation 79

4.3 GEM Application 80

4.3.1 Common Usage and Prediction Capacities of Genome-Scale Models 82

4.3.2 GEMs as a Platform for Omics Data Integration, Linking Genotype to Phenotype 83

4.3.3 Predicting Nutrient Consumption and Controlling Phenotype 84

4.3.4 Enhancing Protein Production and Bioprocesses 85

4.3.5 Case Studies 86

4.4 Conclusion 86

Acknowledgments 88

References 88

5 Genome Variation, the Epigenome and Cellular Phenotypes 97
Martina Baumann, Gerald Klanert, Sabine Vcelar,Marcus Weinguny, Nicolas Marx, and Nicole Borth

5.1 Phenotypic Instability in the Context of Mammalian Production Cell Lines 97

5.2 Genomic Instability 99

5.3 Epigenetics 101

5.3.1 DNA Methylation 102

5.3.2 Histone Modifications 102

5.3.3 Downstream Effectors 104

5.3.4 Noncoding RNAs 104

5.4 Control of CHO Cell Phenotype by the Epigenome 105

5.5 Manipulating the Epigenome 107

5.5.1 Global Epigenetic Modification 107

5.5.1.1 Manipulating Global DNA Methylation 107

5.5.1.2 Manipulating Global Histone Acetylation 108

5.5.2 Targeted Epigenetic Modification 109

5.5.2.1 Targeted Histone Modification 110

5.5.2.2 Targeted DNA Methylation 112

5.6 Conclusion and Outlook 113

References 114

6 Adaption of Generic Metabolic Models to Specific Cell Lines for Improved Modeling of Biopharmaceutical Production and Prediction of Processes 127
Calmels Cyrielle, Chintan Joshi, Nathan E. Lewis, Malphettes Laetitia, and Mikael R. Andersen

6.1 Introduction 127

6.1.1 Constraint-Based Models 127

6.1.2 Limitations of Flux Balance Analysis 131

6.1.2.1 Thermodynamically Infeasible Cycles 131

6.1.2.2 Genetic Regulation 131

6.1.2.3 Limitation of Intracellular Space 132

6.1.2.4 Multiple States in the Solution 132

6.1.2.5 Biological Objective Function 133

6.1.2.6 Kinetics and Metabolite Concentrations 133

6.2 Main Source of Optimization Issues with Large Genome-Scale Models: Thermodynamically Infeasible Cycles 134

6.2.1 Definition of Thermodynamically Infeasible Fluxes 134

6.2.2 Loops Involving External Exchange Reactions 134

6.2.2.1 Reversible Passive Transporters from Major Facilitator Superfamily (MFS) 135

6.2.2.2 Reversible Passive Antiporters from Amino Acid-Polyamine-organoCation (APC) Superfamily 136

6.2.2.3 Na⁺-linked Transporters 136

6.2.2.4 Transport via Proton Symport 137

6.2.3 Tools to Identify Thermodynamically Infeasible Cycles 138

6.2.3.1 Visualizing Fluxes on a Network Map 138

6.2.3.2 Algorithms Developed 138

6.2.4 Methods Available to Remove Thermodynamically Infeasible Cycles 139

6.2.4.1 Manual Curation 139

6.2.4.2 Software and Algorithms Developed for the Removal of Thermodynamically Infeasible Loops from Flux Distributions 140

6.3 Consideration of Additional Biological Cellular Constraints 144

6.3.1 Genetic Regulation 144

6.3.1.1 Advantages of Considering Gene Regulation in Genome-Scale Modeling 144

6.3.1.2 Methods Developed to Take into Account a Feedback of FBA on the Regulatory Network 145

6.3.2 Context Specificity 146

6.3.2.1 What Are Context-Specific Models (CSMs)? 146

6.3.2.2 Methods and Algorithms Developed to Reconstruct Context-Specific Models (CSMs) 146

6.3.2.3 Performance of CSMs 148

6.3.2.4 Cautions About CSMs 149

6.3.3 Molecular Crowding 150

6.3.3.1 Consequences on the Predictions 150

6.3.3.2 Methods Developed to Account for a Total Enzymatic Capacity into the FBA Framework 151

6.4 Conclusion 152

References 153

7 Toward Integrated Multi-omics Analysis for Improving CHO Cell Bioprocessing 163
Kok Siong Ang, Jongkwang Hong, Meiyappan Lakshmanan, and Dong-Yup Lee

7.1 Introduction 163

7.2 High-Throughput Omics Technologies 165

7.2.1 Sequencing-Based Omics Technologies 165

7.2.1.1 Historical Developments of Nucleotide Sequencing Techniques 165

7.2.1.2 Genome Sequencing of CHO Cells 166

7.2.1.3 Transcriptomics of CHO Cells 167

7.2.1.4 Epigenomics of CHO Cells 168

7.2.2 Mass Spectrometry-Based Omics Technologies 168

7.2.2.1 Mass Spectrometry Techniques 168

7.2.2.2 Proteomics of CHO Cells 170

7.2.2.3 Metabolomics/Lipidomics of CHO Cells 171

7.2.2.4 Glycomics of CHO Cells 172

7.3 Current CHO Multi-omics Applications 172

7.3.1 Bioprocess Optimization 174

7.3.2 Cell Line Characterization 174

7.3.3 Engineering Target Identification 176

7.4 Future Prospects 177

References 178

8 CRISPR Toolbox for Mammalian Cell Engineering 185
Daria Sergeeva, Karen Julie la Cour Karottki, Jae Seong Lee, and Helene Faustrup Kildegaard

8.1 Introduction 185

8.2 Mechanism of CRISPR/Cas9 Genome Editing 186

8.3 Variants of CRISPR-RNA-guided Endonucleases 187

8.3.1 Diversity of CRISPR/Cas Systems 187

8.3.2 Engineered Cas9 Variants 188

8.4 Experimental Design for CRISPR-mediated Genome Editing 188

8.4.1 Target Site Selection and Design of gRNAs 189

8.4.2 Delivery of CRISPR/Cas9 Components 191

8.5 Development of CRISPR/Cas9 Tools 192

8.5.1 CRISPR/Cas9-mediated Gene Editing 192

8.5.1.1 Gene Knockout 192

8.5.1.2 Site-Specific Gene Integration 194

8.5.2 CRISPR/Cas9-mediated Genome Modification 195

8.5.2.1 Transcriptional Regulation 195

8.5.2.2 Epigenetic Modification 196

8.5.3 RNA Targeting 196

8.6 Genome-Scale CRISPR Screening 197

8.7 Applications of CRISPR/Cas9 for CHO Cell Engineering 197

8.8 Conclusion 199

Acknowledgment 200

References 200

9 CHO Cell Engineering for Improved Process Performance and Product Quality 207
Simon Fischer and Kerstin Otte

9.1 CHO Cell Engineering 207

9.2 Methods in Cell Line Engineering 208

9.2.1 Overexpression of Engineering Genes 208

9.2.2 Gene Knockout 209

9.2.3 Noncoding RNA-mediated Gene Silencing 209

9.3 Applications of Cell Line Engineering Approaches in CHO Cells 211

9.3.1 Enhancing Recombinant Protein Production 211

9.3.2 Repression of Cell Death and Acceleration of Growth 221

9.3.3 Modulation of Posttranslational Modifications to Improve Protein Quality 227

9.4 Conclusions 233

References 234

10 Metabolite Profiling of Mammalian Cells 251
Claire E. Gaffney, Alan J. Dickson, and Mark Elvin

10.1 Value of Metabolic Data for the Enhancement of Recombinant Protein Production 251

10.2 Technologies Used in the Generation of Metabolic Data Sets 252

10.2.1 Targeted and Untargeted Metabolic Analysis 253

10.2.2 Analytical Technologies Used in the Generation of Metabolite Profiles 253

10.2.2.1 Nuclear Magnetic Resonance 254

10.2.2.2 Mass Spectrometry 255

10.2.3 Metabolite Sample Preparation 256

10.2.3.1 Extracellular Sample Preparation 257

10.2.3.2 Quenching of Intracellular Metabolite Samples 257

10.2.3.3 Metabolite Extraction from Quenched Cells 257

10.2.3.4 Metabolic Flux Analysis 257

10.3 Approaches for Metabolic Data Analysis 257

10.3.1 Data Processing 258

10.3.2 Data Analysis 258

10.3.3 Data Interpretation and Integration 260

10.4 Implementation of Metabolic Data in Bioprocessing 261

10.4.1 Relationship Between Growth Phase and Metabolism 261

10.4.2 Identification of Metabolic Indicators Associated with High Cell-Specific Productivity 263

10.4.3 Utilizing Metabolic Data to Improve Biomass and Recombinant Protein Yield 263

10.4.4 Utilizing Metabolic Understanding to Improve Product Quality 265

10.4.5 Cell Line Engineering to Redirect Metabolic Pathways 265

10.5 Future Perspectives 266

Acknowledgments 267

References 267

11 Current Considerations and Future Advances in Chemically Defined Medium Development for the Production of Protein Therapeutics in CHO Cells 279
Wai Lam W. Ling

11.1 Introduction 279

11.2 Traditional Approach to Medium Development 279

11.2.1 Cell Line Selection 279

11.2.2 Design and Optimization 280

11.2.3 Process Consideration 282

11.2.4 Additional Considerations in Medium Development 284

11.3 Future Perspectives for Medium Development 284

11.3.1 Systems Biology and Synthetic Biology 284

Acknowledgment 288

Conflict of Interest 288

References 288

12 Host Cell Proteins During Biomanufacturing 295
Jong Youn Baik, Jing Guo, and Kelvin H. Lee

12.1 Introduction 295

12.2 Removal of HCP Impurities 295

12.2.1 Antibody Product 296

12.2.2 Non-antibody Protein Product 297

12.2.3 Difficult-to-Remove HCPs 298

12.3 Impacts of Residual HCPs 298

12.3.1 Drug Efficacy, Quality, and Shelf Life 298

12.3.2 Immunogenicity 299

12.3.3 Biological Activity 299

12.4 HCP Detection and Monitoring Methods 300

12.4.1 Anti-HCP Antiserum and Enzyme-Linked Immunosorbent Assay (ELISA) 300

12.4.2 Proteomics Approaches as Orthogonal Methods 302

12.5 Efforts for HCP Control 302

12.5.1 Upstream Efforts 303

12.5.2 Downstream Efforts 304

12.5.3 HCP Risk Assessment in CHO Cells 305

12.6 Future Directions 305

Acknowledgments 306

References 306

13 Mammalian Fed-batch Cell Culture for Biopharmaceuticals 313
William C. Yang

13.1 Introduction 313

13.2 Objectives of Cell Culture Process Development 314

13.2.1 Yield and Product Quality 314

13.2.2 Glycosylation 314

13.2.3 Charge Heterogeneity 315

13.2.4 Aggregation 316

13.3 Cells and Cell Culture Formats 316

13.3.1 Adherent Cells 316

13.3.2 Suspended Cells 316

13.3.3 Batch Cultures 317

13.4 Fed-batch Cultures 317

13.5 Cell Culture Media 319

13.5.1 Basal Media 319

13.5.2 Feed Media 320

13.6 Feeding Strategies 321

13.6.1 Metabolite Based 321

13.6.2 Respiration Based 323

13.7 Feed Media Design 323

13.8 Process Variable Design 325

13.8.1 Temperature 325

13.8.2 pH and pCO₂ 325

13.8.3 Dissolved Oxygen 326

13.8.4 Culture Duration 327

13.9 Cell Culture Supplements 327

13.9.1 Yield 328

13.9.2 Glycosylation 328

13.10 New and Emerging Technologies 329

13.10.1 Analytical Technologies 329

13.10.2 Bioreactor Technologies 331

13.11 Future Directions 332

References 333

14 Continuous Biomanufacturing 347
Sadettin S. Ozturk

14.1 Introduction 347

14.2 Continuous Upstream (Cell Culture) Processes 347

14.2.1 Continuous Culture without Cell Retention (Chemostat) 348

14.2.2 Continuous Culture with Cell Retention (Perfusion) 348

14.2.2.1 Cell Retention by Immobilization or Entrapment 349

14.2.2.2 Cell Retention by Cell Retention Device 350

14.2.3 Semicontinuous Culture 351

14.3 Advantages of Continuous Perfusion 351

14.3.1 Higher Volumetric Productivities 351

14.3.2 Better Utilization of Biomanufacturing Facilities 352

14.3.3 Better Product Quality and Consistency 352

14.3.4 Scale-up and Commercial Production 353

14.4 Cell Retention Systems for Continuous Perfusion 354

14.4.1 Cell Retention Devices 354

14.4.1.1 Filtration-Based Devices 354

14.4.1.2 Spin Filters 355

14.4.1.3 Continuous Centrifugation 356

14.4.1.4 Settler 356

14.4.1.5 BioSep Device 357

14.4.1.6 Hydrocyclones 358

14.5 Operation and Control of Continuous Perfusion Bioreactors 358

14.5.1 Feed and Harvest Flow and Volume Control 358

14.5.2 Circulation or Return Pump 359

14.5.3 Control of Perfusion Rate and Cell Density 359

14.5.3.1 Cell Build-up Phase 359

14.5.3.2 Production Phase 360

14.5.3.3 Cell Bleed or Purge 360

14.6 Current Status of Continuous Perfusion 360

14.7 Conclusions 362

Acknowledgment 362

References 363

15 Process Analytical Technology and Quality by Design for Animal Cell Culture 365
Hae-Woo Lee, Hemlata Bhatia, Seo-Young Park, Mark-Henry Kamga, Thomas Reimonn, Sha Sha, Zhuangrong Huang, Shaun Galbraith, Huolong Liu, and Seongkyu Yoon

15.1 PAT and QbD – US FDA’s Regulatory Initiatives 365

15.2 PAT and QbD – Challenges 365

15.3 PAT and QbD Implementations 366

15.3.1 NIR Spectroscopy 366

15.3.2 Mid-Infrared (MIR) Spectroscopy 367

15.3.3 Raman Spectroscopy 367

15.3.4 Fluorescence Spectroscopy 368

15.3.5 Chromatographic Techniques 368

15.3.6 Other Useful Techniques 369

15.3.7 Data Analysis and Modeling Tools 369

15.4 Case Studies 370

15.4.1 Estimation of Raw Material Performance in Mammalian Cell Culture Using Near-Infrared Spectra Combined with Chemometrics Approaches 370

15.4.2 Design Space Exploration for Control of Critical Quality Attributes of mAb 372

15.4.3 Quantification of Protein Mixture in Chromatographic Separation Using Multiwavelength UV Spectra 372

15.4.4 Characterization of Mammalian Cell Culture Raw Materials by Combining Spectroscopy and Chemometrics 374

15.4.5 Effect of Amino Acid Supplementation on Titer and Glycosylation Distribution in Hybridoma Cell Cultures 375

15.4.6 Metabolic Responses and Pathway Changes of Mammalian Cells Under Different Culture Conditions with Media Supplementations 377

15.4.7 Estimation and Control of N-Linked Glycoform Profiles of Monoclonal Antibody with Extracellular Metabolites and Two-Step Intracellular Models 378

15.4.8 Quantitative Intracellular Flux Modeling and Applications in Biotherapeutic Development and Production Using CHO Cell Cultures 381

15.5 Conclusion 383

References 383

16 Development and Qualification of a Cell Culture Scale-Down Model 391
Sarwat Khattak and Valerie Pferdeort

16.1 Purpose of the Scale-Down Model 391

16.1.1 Development Challenges 391

16.2 Types of Scale-Down Models 392

16.2.1 Power/Volume (P/V) and Air velocity 392

16.2.2 Oxygen Transfer Coefficient (k_La) 392

16.2.3 Gas Entrance Velocity (GEV) 393

16.2.4 Oxygen Transfer Rate (OTR) 393

16.2.5 Model Refinement Workflow 395

16.3 Evaluation of a Scale-Down Model 395

16.3.1 Univariate Analysis 395

16.3.2 Multivariate Analysis 396

16.3.2.1 Statistical Background 396

16.3.2.2 Qualification Data Set 396

16.3.2.3 Observation Level Analysis 397

16.3.2.4 Batch-Level Analysis 397

16.3.2.5 Scores Contribution Plots 398

16.3.3 Equivalence Testing 399

16.3.3.1 Statistical Background 399

16.3.3.2 Considerations for Evaluation and Test Data Sets 399

16.3.3.3 Types of Analysis Outcomes 400

16.4 Conclusions and Perspectives 401

References 402

Index 407