Methods in Molecular Biology 1603 Paula Meleady Editor Heterologous Protein Production in CHO Cells Methods and Protocols Methods in Molecular Biology 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 Heterologous Protein Production in CHO Cells Methods and Protocols Edited by Paula Meleady National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Editor Paula Meleady National Institute for Cellular Biotechnology Dublin City University Dublin, Ireland ISSN 1064-3745     ISSN 1940-6029 (electronic) Methods in Molecular Biology ISBN 978-1-4939-6971-5    ISBN 978-1-4939-6972-2 (eBook) DOI 10.1007/978-1-4939-6972-2 Library of Congress Control Number: 2017935545 © Springer Science+Business Media LLC 2017 This work is subject to copyright All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed The use of general descriptive names, registered names, trademarks, service marks, etc in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations Cover Illustration: The front cover image, kindly provided by Alan Costello (National Institute for Cellular Biotechnology, Dublin City University), shows Chinese hamster ovary (CHO) cells with inducible green fluorescent protein (GFP) expression (from Chapter 6) Printed on acid-free paper This Humana Press imprint is published by Springer Nature The registered company is Springer Science+Business Media LLC The registered company address is: 233 Spring Street, New York, NY 10013, U.S.A Preface Since their introduction into the market over 20 years ago, biotherapeutics have constituted a large and growing percentage of the total pharmaceutical market, as well as approximately 25% of the R&D pipeline in industry These biotherapeutics are having a huge global impact on the treatment of challenging and previously untreatable chronic disease Currently biopharmaceuticals generate global revenues of $163 billion, making up about 20% of the pharma market, and predicted to grow to over $320 billion by 2020 The number of approved products in Europe and the USA has steadily increased to 2016 in 2014, of which 37 have “blockbuster” status, i.e., sales over $1 billion per year, with monoclonal antibodies (Mabs) representing the most lucrative single product class [1] Most significantly, nearly 50% of these biopharmaceutical products are produced in a single production host, i.e., Chinese hamster ovary (CHO) cells Improving the efficiency of production of these biologics will be critical in controlling costs to healthcare systems as more of these drugs come to market There has been considerable success in developing high-producing CHO cell culture processes using approaches such as optimization of media formulation, improvements in expression vector design, and also improvements in the design of bioreactors The next generation of improvements is expected to be made via genetic engineering of the host (CHO) cell itself to increase or decrease the expression of endogenous genes depending on the desired outcome, in order to improve the efficiency of the production of therapeutic protein product In order to enhance the production capabilities and efficiency of the host cell line, an increased understanding of cellular physiology of CHO cells is of critical importance There are substantial research efforts in progress focusing on the ‘omic analysis and systems biology of CHO cells to understand CHO cell physiology The publication of the draft CHO-K1 genome in 2011 represented a major milestone in CHO systems biology This information has been supplemented further with the publication of draft genomes for Chinese hamster and the CHO-S, CHO DG44 and CHO DXB11 cell lines Availability of the genome sequence will facilitate the interpretation and analysis of transcriptomic and proteomic data to assess the physiological state of the cells under different growth and production systems Combining all levels of regulation through systems biology models will unveil the underlying complexity inherent in CHO cell biology and will ultimately enhance and accelerate CHO productive capabilities in the coming decades This book includes reviews and protocols for genetic manipulation of CHO cells for recombinant protein production, including “difficult-to-express” therapeutics A method is also included on the use of the recently described genome editing tool, CRISPR/Cas9, and how this can be applied to CHO cells The book also includes a review and protocols for characterization of CHO cells using ‘omic approaches and how these methods can be used to improve efficiency of recombinant protein production during cell line development Analytical methods for characterization of recombinant protein product, such as glycosylation and host cell protein analysis, are also described in this book v vi Preface I am deeply grateful to all authors for giving up their valuable time and for contributing to the book I would also like to thank the series editor, Prof John Walker, for help and guidance during the process of getting the book to publication Dublin, Ireland Paula Meleady Reference Walsh G (2014) Biopharmaceutical benchmarks 2014 Nat Biotechnol 32(10):992–1000 Contents Preface v Contributors ix   Strategies and Considerations for Improving Expression of “Difficult to Express” Proteins in CHO Cells Christina S Alves and Terrence M Dobrowsky   Glycoengineering of CHO Cells to Improve Product Quality Qiong Wang, Bojiao Yin, Cheng-Yu Chung, and Michael J Betenbaugh   Large-Scale Transient Transfection of Chinese Hamster Ovary Cells in Suspension Yashas Rajendra, Sowmya Balasubramanian, and David L Hacker   Cloning of Single-Chain Antibody Variants by Overlap-­Extension PCR for Evaluation of Antibody Expression in Transient Gene Expression Patrick Mayrhofer and Renate Kunert   Anti-Apoptosis Engineering for Improved Protein Production from CHO Cells Eric Baek, Soo Min Noh, and Gyun Min Lee   Conditional Knockdown of Endogenous MicroRNAs in CHO Cells Using TET-ON-SanDI Sponge Vectors Alan Costello, Nga Lao, Martin Clynes, and Niall Barron   Application of CRISPR/Cas9 Genome Editing to Improve Recombinant Protein Production in CHO Cells Lise Marie Grav, Karen Julie la Cour Karottki, Jae Seong Lee, and Helene Faustrup Kildegaard   Improved CHO Cell Line Stability and Recombinant Protein Expression During Long-Term Culture Zeynep Betts and Alan J Dickson   Selection of High-Producing Clones Using FACS for CHO Cell Line Development Clair Gallagher and Paul S Kelly 10 The ‘Omics Revolution in CHO Biology: Roadmap to Improved CHO Productivity Hussain Dahodwala and Susan T Sharfstein 11 A Bioinformatics Pipeline for the Identification of CHO Cell Differential Gene Expression from RNA-Seq Data Craig Monger, Krishna Motheramgari, John McSharry, Niall Barron, and Colin Clarke vii 25 45 57 71 87 101 119 143 153 169 viii Contents 12 Filter-Aided Sample Preparation (FASP) for Improved Proteome Analysis of Recombinant Chinese Hamster Ovary Cells Orla Coleman, Michael Henry, Martin Clynes, and Paula Meleady 13 Phosphopeptide Enrichment and LC-MS/MS Analysis to Study the Phosphoproteome of Recombinant Chinese Hamster Ovary Cells Michael Henry, Orla Coleman, Prashant, Martin Clynes, and Paula Meleady 14 Engineer Medium and Feed for Modulating N-Glycosylation of Recombinant Protein Production in CHO Cell Culture Yuzhou Fan, Helene Faustrup Kildegaard, and Mikael Rørdam Andersen 15 Glycosylation Analysis of Therapeutic Glycoproteins Produced in CHO Cells Sara Carillo, Stefan Mittermayr, Amy Farrell, Simone Albrecht, and Jonathan Bones 16 Characterization of Host Cell Proteins (HCPs) in CHO Cell Bioprocesses Catherine E.M Hogwood, Lesley M Chiverton, and C Mark Smales 187 195 209 227 243 Index 251 Contributors Simone Albrecht  •  National Institute for Bioprocessing Research and Training (NIBRT), Dublin, Ireland Christina S. Alves  •  Biogen Inc., Cambridge, MA, USA Mikael Rørdam Andersen  •  Department of Systems Biology, Technical University of Denmark, Kgs Lyngby, Denmark Eric Baek  •  Department of Biological Sciences, KAIST, Daejeon, Republic of Korea Sowmya Balasubramanian  •  Laboratory of Cellular Biotechnology (LBTC), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland Niall Barron  •  National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Michael J. Betenbaugh  •  Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA Zeynep Betts  •  Faculty of Science and Literature, Department of Biology, Kocaeli University, Izmit, Kocaeli, Turkey Jonathan Bones  •  National Institute for Bioprocessing Research and Training (NIBRT), Dublin, Ireland Sara Carillo  •  National Institute for Bioprocessing Research and Training (NIBRT), Dublin, Ireland Lesley M. Chiverton  •  Industrial Biotechnology Centre and School of Biosciences, University of Kent, Canterbury, Kent, UK Cheng-Yu Chung  •  Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA Colin Clarke  •  National Institute for Bioprocessing Research and Training (NIBRT), Dublin, Ireland Martin Clynes  •  National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Orla Coleman  •  National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Alan Costello  •  National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Hussain Dahodwala  •  Vaccine production program (VPP), VRC/NIAID/NIH, Gaithersburg, MD, USA; SUNY Polytechnic Institute, Albany, NY, USA Alan J. Dickson  •  Faculty of Life Sciences, The University of Manchester, Manchester, UK Terrence M. Dobrowsky  •  Biogen Inc., Cambridge, MA, USA Yuzhou Fan  •  Department of Systems Biology, Technical University of Denmark, Kgs Lyngby, Denmark; The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark Amy Farrell  •  National Institute for Bioprocessing Research and Training (NIBRT), Dublin, Ireland Clair Gallagher  •  National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland ix x Contributors Lise Marie Grav  •  The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Hørsholm, Denmark David L. Hacker  •  Laboratory of Cellular Biotechnology (LBTC), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Protein Expression Core Facility (PECF), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland Michael Henry  •  National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Catherine E.M. Hogwood  •  Industrial Biotechnology Centre and School of Biosciences, University of Kent, Canterbury, Kent, UK Paul S. Kelly  •  National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Karen Julie la Cour Karottki  •  The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark Helene Faustrup Kildegaard  •  The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark Renate Kunert  •  Department of Biotechnology, Vienna Institute of BioTechnology, University of Natural Resources and Life Sciences-Vienna, Vienna, Austria Nga Lao  •  National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Gyun Min Lee  •  Department of Biological Sciences, KAIST, Daejeon, Republic of Korea Jae Seong Lee  •  The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark Patrick Mayrhofer  •  Department of Biotechnology, Vienna Institute of BioTechnology, University of Natural Resources and Life Sciences-Vienna, Vienna, Austria John McSharry  •  National Institute for Bioprocessing Research and Training (NIBRT), Dublin, Ireland Paula Meleady  •  National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Stefan Mittermayr  •  National Institute for Bioprocessing Research and Training (NIBRT), Dublin, Ireland Craig Monger  •  National Institute for Bioprocessing Research and Training (NIBRT), Dublin, Ireland; National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Krishna Motheramgari  •  National Institute for Bioprocessing Research and Training (NIBRT), Dublin, Ireland; National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Soo Min Noh  •  Department of Biological Sciences, KAIST, Daejeon, Republic of Korea Prashant  •  National Institute for Cellular Biotechnology, Dublin City University, Dublin, Ireland Yashas Rajendra  •  Laboratory of Cellular Biotechnology (LBTC), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Biotechnology Discovery Research, Lilly Research Laboratories, Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN, USA Susan T. Sharfstein  •  SUNY Polytechnic Institute, Albany, NY, USA C. Mark Smales  •  Industrial Biotechnology Centre and School of Biosciences, University of Kent, Canterbury, Kent, UK Qiong Wang  •  Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA Bojiao Yin  •  Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, USA Glycosylation Analysis of Therapeutic Glycoproteins 237 + RT (min) Glycan Structure 10 Symbolic Representation 12 14 16 Monoisotopic mass + 2-AA 18 20 Experimental [M-2H]2- (ppm) 6.16 FA1 1437.5393 689.2507 (1.3) 6.52 A2 1380.5178 717.7583 (5.7) 7.45 FA2 1583.5972 790.7913 (1.0) 8.41 MAN5 1355.4862 676.7405 (6.9) 8.57 FA1[6]G1 1542.5706 770.2864 (10.9) 8.63 A2[6]G1 1599.5921 798.7952 (8.0) 8.96 A2[3]G1 1599.5921 798.801 (15.3) 9.67 FA2[6]G1 1745.6500 871.8160 (1.9) 10.03 FA2[3]G1 1745.6500 871.8160 (1.9) 12.42 FA2G2 1907.7028 952.8459 (1.9) 14.98 FA2G2S1 2198.7983 1098.3748 (15.6) Fig UPLC-MS BPI chromatogram from 2-AA labeled N-glycans released by IgG1 produced in CHO-DP12 cell line; MS data for each glycan are listed in embedded table 238 Sara Carillo et al 2 Several fluorescent labels have been used for N-glycan derivatization [18] For example, 2-aminobenzoic acid (2-AA), inherently bearing a negative charge (pKa = 2.18 and pKa = 4.84), is recommended for glycans bearing two or less additional negative charges (e.g sialic acid residues) to facilitate the elution off chromatographic columns with cationic characteristics 2-AB, aniline, or other neutral labels are recommended with highly charged glycans The 2-AB label is of more general use (the dextran ladder system is based on 2-AB label and also facilitates data searching within the GlycoBase database) For labeling solution preparation, dissolve 50 mg of 2-AB or 2-AA or aniline and 60 mg of sodium cyanoborohydride in 1 mL of 30:70 acetic acid in DMSO. Make labels up in DMSO (solution can be heated to promote dissolution) and add the 30% acetic acid in only at the very last step Labeling reactions for 2-AA and aniline have longer incubation time, and 16 h are recommended, respectively MS/MS fragmentation is a key technique for the structural determination of glycan molecules Glycan fragments are commonly named according to a well-recognized nomenclature established by Domon and Costello [17] Fragments resulting from the cleavage of a single intermolecular glycosidic bond, such as the reducing-end containing fragments Y and Z and their counterparts B and C, are most frequently observed in glycan MS/MS spectra (Fig. 4) Additional cross-ring fragmentation resulting from the cleavage of two intramolecular glycosidic bonds, i.e., the reducing-end containing fragment X and its counterpart A, may be present depending on fragmentation conditions The manual interpretation of glycan fragmentation data is time-consuming and laborious GlycoWorkbench is a freely available software tool for the semi-automated annotation of glycan fragmentation spectra which was developed as part of the EUROCarbDB initiative to support the interpretation of glycan MS data [19, 20] Essentially, GlycoWorkbench performs in-silico fragmentation of the proposed structures defined by the user and compares the resulting fragment lists with the experimental MS/MS spectral data The graphical interface of GlycoWorkbench is based on GlycanBuilder [21], a user-friendly tool for the manual input of putative glycan structures The tool allows for the specification of monosaccharide subunits, their linkage and anomeric type, and their modifications such as permethylation or acetylation using various symbolic notations including CFG and Oxford symbol nomenclature as well as the specification of reducing end derivatizations such as fluorescent labels It further allows the definition of experimental and instrument-­specific parameters that are of relevance for the spectral interpretation, such as ion adducts (H+, Na+, K+, Li+), charge state, and ionization mode m/z 150 262.09 200 250 244.08 202.07 179.05 142.05 300 350 400 383.13 372.09 312.07 350.11 311.17 306.12 291.09 450 500 550 534.15 C2α/β [470.15]-1 B2α/β [452.14]-1 Y1β [443.14]-1 424.15 B1α B1α 600 586.20 C2β C2α B3β B3α 650 700 750 738.23 B5 800 850 836.28 C4α/β [835.28]-1 B4β Z3β B4α/β [817.27]-1 C4β B4α Z3α C4α 715.24 737.22 B3α/β [655.22]-1 B2β B2α 900 950 939.31 1050 1059.87 1000 B5Z3α/β [961.30]-1 Y1β 1100 1095.89 1150 1200 1150.41 1250 1233.97 1233.45 1224.44 1223.94 FA2G2S2 [1221.93]-2 1149.92 Y1α [1148.91]-2 1132.89 Aniline Y1α Fig MSE spectrum of aniline-labeled FA2G2S2 glycan Signals in the spectrum are assigned, according to Domon and Costello nomenclature, with the help of GlycoWorkBench software % 100 B1α/β [290.09]-1 MSe of aniline-labeled FA2G2S2 Glycosylation Analysis of Therapeutic Glycoproteins 239 240 Sara Carillo et al Sequential filtration is preferable as direct filtration with 0.2 μm membrane will result in a slower filtration and possibly filter blockage To enable further protein relaxation and accessibility of potentially shielded glycosylation sites, UA solution is recommended as reaction buffer Monitor volumes in spin filters Don’t concentrate beyond 20 mg/mL to avoid overconcentration and associated potential formation of aggregates Other vendors can refer to different activity units Check the conversion between vendors unit and IUB (International Union of Biochemistry) unit Formic acid treatment assures conversion of released glycosylamines to reducing terminal sugars and also promotes opening of the reducing end sugar ring, thereby maximizing labeling efficiency Interference of free dye with glycan peaks and nonselective injection to LC instruments may occur if excess fluorescent agent is not completely removed Purification step needs to be non-selective, i.e., prevent the loss of specific glycan classes (e.g., small versus large or neutral versus charged glycans) It is recommended to reach a final volume of 100 μL of 85% acetonitrile in water; acetonitrile should be added to the sample just before subjection to HILIC purification due to potential precipitation effects in high solvent concentrations 10 If excess fluorescent dye is not completely removed detector oversaturation may occur, so it is advised to disable detection from to 2.5 min while the free dye is eluting off the HILIC column 11 Monitor the loss of monosaccharides based on enzyme specificity Either with retention time shift and or with mass loss between digestions 12 Produced fragments depend on multiple factors such as ­occupancy of reducing terminal end and instrument-dependent dissociation method 13 The charge state of the theoretical fragments predicted by Glycoworkbench will match the precursor charge state set by the user However, experimental fragment ions generally have a lower charge state than their precursor (e.g -2 vs -1) The precursor charge state therefore needs to be adjusted to the charge state of the fragment ions Acknowledgments This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) under Grant Numbers SFI/11/SIRG/B107 and SFI/13/CDA/2196 Glycosylation Analysis of Therapeutic Glycoproteins 241 References Pouech C, Lafay F, Wiest L, Baudot R, Léonard D, Cren-Olivé C (2014) Monitoring the extraction of additives and additive degradation products from polymer packaging into solutions by multi-residue method including solid phase extraction and ultra-high performance liquid chromatography-tandem mass spectrometry analysis Anal Bioanal Chem 406(5):1493–1507 Durocher Y, Butler M (2009) Expression systems for therapeutic glycoprotein production Curr Opin Biotechnol 20(6):700–707 doi:10.1016/j.copbio.2009.10.008 Planinc A, Bones J, Dejaegher B, Van Antwerpen P, Delporte C (2016) Glycan 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glycosylation on antibody function: implications for genetic engineering Trends Biotechnol 15(1): 26–32 doi:10.1016/S0167-7799(96)10062-7 Jefferis R (2005) Glycosylation of recombinant antibody therapeutics Biotechnol Prog 21(1):11–16 doi:10.1021/bp040016j 10 Shields RL, Lai J, Keck R, O’Connell LY, Hong K, Meng YG, Weikert SH, Presta LG (2002) Lack of fucose on human IgG1 N-linked oligosaccharide improves binding to human FcγRIII and antibody-dependent cellular toxicity J Biol Chem 277(30): 26733–26740 11 Umaña P, Jean-Mairet J, Moudry R, Amstutz H, Bailey JE (1999) Engineered glycoforms of an antineuroblastoma IgG1 with optimized antibody-dependent cellular cytotoxic activity Nat Biotechnol 17(2):176–180 12 Malhotra R, Wormald MR, Rudd PM, Fischer PB, Dwek RA, Sim RB (1995) Glycosylation changes of IgG associated with rheumatoid arthritis can activate complement via the mannose-­ binding protein Nat Med 1(3): 237–243 13 Farrell A, Mittermayr S, Morrissey B, Mc Loughlin N, Navas Iglesias N, Marison IW, Bones J (2015) Quantitative host cell protein analysis using two dimensional data inde­pendent LC–MSE. Anal Chem 87(18):9186–9193 14 Ruhaak L, Zauner G, Huhn C, Bruggink C, Deelder A, Wuhrer M (2010) Glycan labeling strategies and their use in identification and quantification Anal Bioanal Chem 397(8): 3457–3481 15 Royle L, Radcliffe CM, Dwek RA, Rudd PM (2006) Detailed structural analysis of N-glycans released from glycoproteins in SDS-PAGE gel bands using HPLC combined with exoglyco­ sidase array digestions Method Mol Biol 347:125–143 16 Atwood JA, Cheng L, Alvarez-Manilla G, Warren NL, York WS, Orlando R (2008) Quantitation by isobaric labeling: applications to glycomics J Proteome Res 7(1):367–374 doi:10.1021/pr070476i 17 Domon B, Costello CE (1988) A systematic nomenclature for carbohydrate fragmentations in FAB-MS/MS spectra of glycoconjugates Glycoconj J 5(4):397–409 doi:10.1007/ bf01049915 18 Harvey DJ (2011) Derivatization of carbohydrates for analysis by chromatography; electrophoresis and mass spectrometry J Chromatogr B 879(17–18):1196–1225 d ­oi:10.1016/j jchromb.2010.11.010 19 EUROCarbDB. Tools to analyse MS spectra: GlycoWorkbench 20 Ceroni A, Maass K, Geyer H, Geyer R, Dell A, Haslam SM (2008) GlycoWorkbench: a tool for the computer-assisted annotation of mass spectra of glycans J Proteome Res 7(4):1650– 1659 doi:10.1021/pr7008252 21 Ceroni A, Dell A, Haslam SM (2007) The GlycanBuilder: a fast, intuitive and flexible software tool for building and displaying glycan structures Source Code Biol Med 2:3–3 doi:10.1186/1751-0473-2-3 Chapter 16 Characterization of Host Cell Proteins (HCPs) in CHO Cell Bioprocesses Catherine E.M. Hogwood, Lesley M. Chiverton, and C. Mark Smales Abstract Host cell protein content during bioprocessing of biotherapeutic proteins generated from cultured Chinese hamster ovary (CHO) cells is typically measured using immunological and gel-based methods Estimation of HCP concentration is usually undertaken using Enzyme-Linked ImmunoSorbent Assays (ELISA), while estimation of HCP clearance/presence can be achieved by comparing 2D-PAGE images of samples and by undertaking western blotting of 2D-PAGE analyzed samples Here, we describe the analyses of HCP content using these methodologies Key words Host cell proteins (HCPs), ELISA, 2D-PAGE, Western blotting 1  Introduction The manufacturing of biotherapeutic proteins in Chinese hamster ovary (CHO) cells results in the presence of not only the target protein of interest being present in the final cell culture harvest material, but also impurities in the form of host cell proteins (HCPs), DNA, RNA, lipids, and other cellular material [1] HCPs present a potential risk to the patient if not mitigated against [2] and hence the amounts must be reduced to acceptable concentrations in the final biotherapeutic preparation Although each product is currently treated on a case-by-case basis, general guidelines suggest that the upper limit of HCPs in a biotherapeutic preparation should be 100 ng/mL [3] As such, HCPs are often monitored as part of bioprocess design, but also during manufacturing to ensure these are being cleared to acceptable amounts HCPs are usually removed via the use of multiple purification steps, in most cases chromatography based, to deliver a produce with acceptable amounts of HCPs [4] Furthermore, the abundance and clearance of HCPs during a bioprocess is considered a critical quality attribute that can be used as a benchmark of process robustness [5] Paula Meleady (ed.), Heterologous Protein Production in CHO Cells: Methods and Protocols, Methods in Molecular Biology, vol 1603, DOI 10.1007/978-1-4939-6972-2_16, © Springer Science+Business Media LLC 2017 243 244 Catherine E Hogwood et al A comprehensive review of methodologies for host cell protein analysis has been published by Tscheliessnig et al [6] The current “work horse” for the analysis of HCPs in biotherapeutic proteins is the use of Enzyme-Linked ImmunoSorbent Assays (ELISA) [7] and 2D-gel-based [6] comparative analyses including western blotting using anti-CHO HCP immunodetection of 2D-PAGE analyzed samples The immune-detection ELISA-based approach has high selectively and can be used in a high-throughput manner This approach traditionally relies on the generation of a polyclonal antibody pool to CHO proteins via the immunization of animals with a null host cell line to determine the concentration of HCPs in a sample using a standard curve [1] 2D-PAGE analysis, and 2D-DIGE (two-dimensional fluorescence difference gel electrophoresis), is used to compare the final biotherapeutic preparation with either the culture harvest material or another reference sample to determine the number of HCPs that have been cleared and to map those remaining [8] This can also be subjected to western blotting to allow the comparison of the immunodetected HCPs to those observed via 2D-PAGE or 2D-DIGE. He we described the analysis of HCPs in a biotherapeutic protein sample for each of these methods 2  Materials Prepare any buffers or reagents with Milli-Q quality water All reagents should be of analytical grade at least 2.1  Recovery of Host Cell Proteins for Analysis Wash Buffer: 25 mM sodium phosphate, 10 mM sodium chloride pH 7.5 General protease inhibitor cocktail Benzonase nuclease Centrifugation-based membrane concentrators with molecular weight cutoff of 5000 Da Commercially available 2-D Clean Up Kit (GE Healthcare) 2D-PAGE resolubilization buffer: 7 M urea, 2 M thoiurea, 4% CHAPS, 40 mM DTT, and 0.5% pH 3–10 pharmalytes 2.2  ELISA Analysis of Host Cell Protein Content Commercially available CHO host cell protein ELISA kit (e.g., Cygnus Technologies HCP ELISA Kit for CHO, 3G Catalogue number P6787-50TAB) 2.3  2D-PAGE Analysis of Host Cell Proteins Immobine DryStrip, pH 3–10 Non-Linear 7 cm IPG strips Ettan IPGphor II system (GE Healthcare) Immobiline PlusOne Drystrip cover fluid (GE Healthcare) CHO HCP Analysis 245 SDS equilibration buffer: 6 M urea, 50 mM Tris–HCl pH 8.8, 29.3% glycerol, 2% (w/v) SDS Dithiothreitol (DTT) and iodoacetamide (IAA) Reducing SDS equilibration buffer: 6 M urea, 50 mM Tris– HCl pH 8.8, 29.3% glycerol, 2% (w/v) SDS, and 1% (w/v) DTT Alkylating SDS equilibration buffer: 6 M urea, 50 mM Tris– HCl pH 8.8, 29.3% glycerol, 2% (w/v) SDS, and 2.5% (w/v) iodoacetamide A few grains of bromophenol blue Standard 12% Tris-Glycine gels and running buffer 10 Agarose sealing solution: 25 mM Tris base, 192 mM glycine, 0.1% SDS and 0.5% agarose 11 Bio-Safe Coomassie G-250 Stain 2.4  2D-PAGE Immunoblotting Analysis of Host Cell Proteins PVDF membrane TBST solution: Tris buffered Saline (TBS, 0.15 M NaCl, 3 mM KCl, 25 mM Tris) containing 0.05% Tween 20 Anti-CHO host cell protein antibody Secondary antibody appropriate for recognizing primary antibody with HRP label 3  Methods 3.1  Recovery of Host Cell Proteins Select the method of recovery of HCPs to be used based upon the subsequent analysis methodology that will be applied to the samples (see Notes and 2) 3.1.1  Recovery for ELISA Analysis If the method of subsequent analysis is ELISA based, samples from any stage of cell culture or downstream processing may be recovered directly from the material to be analyzed For ELISA analysis of harvest material from cell culture, remove cellular material by centrifugation to pellet cells and cell debris and then remove supernatant material for HCP analysis Store at −20 °C 3.1.2  Recovery of Material for Gel-Based Proteomic Analysis Recover cell culture supernatant material by centrifugation to remove cell debris Sufficient material should be recovered for the analysis intended For ELISA 50–100 μL may be sufficient, 20 mL of culture material is sufficient for multiple analyses by 1D- or 2D-PAGE (see Note 3) No further processing is required for ELISA samples For 2D-PAGE samples, wash the cell culture supernatant ­sample with 20 mL of Wash Buffer, while concentrating a ­minimum of fivefold using centrifugation-based concentrators (see Note 4) 246 Catherine E Hogwood et al - pH A pH11 + - pH High MW Low B pH11 + High MW Low Fig 2D-PAGE analysis of the cell culture supernatant of an antibody-producing cell line at harvest when stained with Coomassie blue (a) or Sypro Ruby (b) The antibody heavy and light chains are the most prominent bands on the right-hand side of the image Host cell proteins are also present Add a general protease inhibitor to the sample and 100 units of benzonase nuclease per mL of sample for 1 h on ice (see Note 5) Estimate the total protein concentration in the recovered samples using an appropriate protein assay (see Note 6) Prior to 2D-PAGE-based analysis the protein should be desalted, concentrated by precipitation, and resolubilized in a suitable buffer (see Note 7) Take 100 μg of total protein (as determined in step above) and subject to the 2-D Clean Up Kit process following the manufacturer’s instructions (see Note 8) Resolubilize the protein pellet in 125 μL (see Note 9) of 2D-PAGE resolubilization buffer and either use immediately for analysis or store at −80 °C 3.2  ELISA Analysis of Host Cell Protein Content ELISA analysis requires appropriate anti-CHO host cell protein antibodies and standards In most cases, these will not be directly available for the analyst and commercial reagents will need to be purchased (see Note 10) In this case, the directions of the manufacturer should be followed precisely 3.3  2D-PAGE Analysis of Host Cell Proteins The most common approach taken for visualizing total HCP content in a sample and comparing HCP content between samples is to use a combination of 2D-PAGE and 2D-PAGE western blotting This allows an assessment of the immunocoverage using a specific polyclonal anti-HCP reagent The stained 2D-PAGE gel (see Fig. 1 for example) is then directly compared to the western blot analysis (see Note 11) For each sample to be analyzed, an Immobine DryStrip, pH 3–10 Non-Linear 7 cm IPG strip is overlaid onto the 125 μL sample (see Note 12) CHO HCP Analysis 247 The strip and sample is then covered with Immobiline PlusOne Drystrip cover fluid Isoelectric focusing (IEF) is then performed to a total of 8 kVh We recommend the following protocol to achieve this if using an Ettan IPGphor II system; Rehydration 20 °C for 1 h; Step step-n-hold at 30 V for up 12 h; Step gradient from 200 V over 45 min; Step step-n-hold to 500 V for 45 min; Step step-n-hold to 1000 V for 45 min; Step ­gradient to 8000 V over 30 min; Step hold at 8000 V until a total of 8000 kVh is achieved Once a total of 8000 kVh is achieved remove the strips, rinse with Milli-Q water, and either store at −80 °C or subject immediately to second-dimension SDS-PAGE analysis Reduce IPG strips in Reducing SDS equilibration buffer for 15 min with gentle agitation Pour off the reducing buffer, rinse the strips with Milli-Q water, and then place in Alkylating SDS equilibration buffer with the addition of a few grains of bromophenol blue (to form a dye front when running the SDS-PAGE) for 15 min with gentle agitation Wash the strips with the SDS-PAGE Tris-glycine buffer to be used for running the SDS-PAGE system Seal each of the equilibrated strips on the top of a 12% Tris-­ Glycine gel without a stacking gel with agarose sealing solution Run the second dimension as appropriate for the SDS-PAGE system until the dye front reaches the bottom of the gel 10 Stain the 2D-gel with Bio-Safe Coomassie G-250 Stain 11 Capture the gel images at 600 dpi, preferably using 16 bit color depth in grayscales and RGB using an appropriate scanner 12 Analyze the 2D-PAGE images using appropriate 2D-PAGE software (see Note 13) 3.4  2D-PAGE Immunoblotting Analysis of Host Cell Proteins For 2D-PAGE western blotting for HCPs, the initial analysis is undertaken up until step as described in Subheading 3.2 After this follow the protocol as below Remove the 2D-PAGE gel from the tank and transfer to PVDF membrane following an appropriate protocol Remove the membrane from the transfer apparatus and block with nonfat dried milk powder (5% w/v) in TBST solution for 1 h at room temperature with gentle agitation Pour off the block solution and wash the membrane with TBST before discarding this wash 248 Catherine E Hogwood et al Dilute the commercial anti-CHO HCP antibody (primary antibody) as recommended by the manufacturer in TBST and pour onto the membrane Incubate overnight at 4 °C with gentle agitation Pour off the primary antibody and wash the membrane five times with excess TBST Add an appropriate secondary antibody diluted in TBST and incubate for 1 h Use an appropriate reagent (e.g., ECL chemiluminescent reagent) and imagining system to capture the western blot 2D-western blot images for HCPs can then be compared to 2D-PAGE images generated for total protein content in Subheading 3.2 above using an appropriate software package 4  Notes The method of recovery of HCPs from extracellular samples (e.g., cell culture harvest material, during downstream processing) can influence both those proteins recovered and the subsequent analysis methods that can be applied to these samples For proteomic gel-based analyses (e.g., 1D and 2D-PAGE) different considerations and processes will be required than those for non-gel-based mass spectrometry approaches A com­p­arison of suitable methods for these types of HCP analyses has been published by Valente et al [9] For the analysis of HCPs throughout a downstream process or in the drug substance/drug product, the method of analysis must consider that the HCP content should be in the range of 1–100 ng/mL while the drug substance may be at a con­ centration in the order of g/L. Approaches such as 1D and 2D-PAGE are unlikely to be appropriate under such conditions unless used for immunoblotting Under such conditions, when loading a set amount of protein onto gels for analysis, the drug substance predominates and can interfere with the running or observation of HCPs that may be present For gel-based analysis of samples from downstream processed samples the amount of material for analysis will need to be judged on a case-by-case basis and consider the concentration of drug substance and anticipated concentration of HCPs The concentration of HCPs can be determined before recovery for gel-based analysis by ELISA to aid in determining the amount of sample to recover HCPs from We recommend using concentrators that have a molecular weight cutoff of 5000 Da which should be sufficient to ensure the majority of recombinant protein and HCPs are retained CHO HCP Analysis 249 Users should consider the membrane used and if this is likely to result in any loss of proteins (e.g., due to proteins “sticking” to the membrane) Alternatively, a precipitation-based method can be used to precipitate the protein and then resolubilize this is an appropriate volume of buffer to generate a smaller volume with a higher concentration of material Although it is not absolutely necessary to add an inhibitor, we recommend this to ensure that protein degradation does not occur due to the presence of any proteases If samples are to be used to investigate protease activity/presence, protease inhibitors should not be included The addition of benzonase nuclease should result in the degradation of any DNA and/or RNA present Again, if the samples are to be used for host cell DNA or RNA analysis this should be excluded Protein concentration can be readily determined by comparison to a standard curve using a method such as that described by Bradford (see [10]) For samples containing recombinant proteins recovered from CHO cell culture supernatants, it should be remembered that it is likely that the majority of proteins in a sample are the recombinant protein and not host cell protein A review of methods for HCP precipitation is provided in [9] A commercial kit does not have to be used or purchased One of the precipitation methods reported in ref can be reliably used instead A total of 125 μL of sample is loaded when undertaking 2D-PAGE with 7 cm Immobiline Drystrip IPG isoelectric focusing strips If longer strips or a greater concentration of total protein is to be used, this should be adjusted as appropriate 10 A number of commercial CHO HCP ELISA assay kits are available which may or may not offer the appropriate ­sensitivity and coverage for a particular CHO host and/or recombinant cell line 11 2D Fluorescence Difference Gel Electrophoresis (2D-DIGE) is often used to directly compare two samples for HCP content/amount A good description of this methodology for the HCP analysis is provided by Grzeskowiak et al [11] This approach allows you to run two samples simultaneously on the same gel and directly compare those proteins/spots present and their relative abundance 12 We recommend using a nonlinear pH range 3–10 strip for initial investigations However, if investigation of a narrower pH range is desired then strips with a range of different pH ranges are available 250 Catherine E Hogwood et al 13 A number of software packages are available for the analysis of 2D-PAGE gels Recently, some of these have been developed to allow the comparison of 2D-PAGE gels with the corres­ ponding immunoblots specifically for HCP analysis (for example, SpotMap from TotalLab) References Bracewell DG, Francis R, Smales CM (2015) The future of host cell protein (HCP) identification during process development and manufacturing linked to a risk based management for their control Biotechnol Bioeng 112: 1727–1737 Bailey-Kellogg C, Gutiérrez AH, Moise L, Terry F, Martin WD, De Groot AS (2014) CHOPPI: a web tool for the analysis of immunogenicity risk from host cell proteins in CHO-­ based protein production Biotechnol Bioeng 111:2170–2182 Chon JH, Zarbis-Papastoitsis G (2011) Advances in the production and downstream processing of antibodies N Biotechnol 28: 458–463 Hogwood CE, Tait AS, Koloteva-Levine N, Bracewell DG, Smales CM (2013) The dynamics of the CHO host cell protein profile during clarification and protein A capture in a platform antibody purification process Biotechnol Bioeng 110:240–251 Tait AS, Hogwood CE, Smales CM, Bracewell DG (2012) Host cell protein dynamics in the supernatant of a mAb producing CHO cell line Biotechnol Bioeng 109:971–982 Tscheliessnig AL, Konrath J, Bates R, Jungbauer A (2013) Host cell protein analysis in therapeutic protein bioprocessing—methods and applications Biotechnol J 8:655–670 Zhu-Shimoni J, Yu C, Nishihara J, Wong RM, Gunawan F, Lin M, Krawitz D, Liu P, Sandoval W, Vanderlaan M (2014) Host cell protein testing by ELISAs and the use of orthogonal methods Biotechnol Bioeng 111:2367–2379 Jin M, Szapiel N, Zhang J, Hickey J, Ghose S (2010) Profiling of host cell proteins by two-­ dimensional difference gel electrophoresis (2D-DIGE): Implications for downstream ­process development Biotechnol Bioeng 105: 306–316 Valente KN, Schaefer AK, Kempton HR, Lenhoff AM, Lee KH (2014) Recovery of Chinese hamster ovary host cell proteins for proteomic analysis Biotechnol J 9:87–99 10 Ramagli LS (1999) Quantifying protein in 2-D PAGE solubilization buffers In: Link AJ (ed) Methods in molecular biology: 2-D proteome analysis protocols Humana Press Inc., Totowa, NJ, pp 99–103 11 Grzeskowiak JK, Tscheliessnig A, Toh PC, Chusainow J, Lee YY, Wong N, Jungbauer A (2009) 2-D DIGE to expedite downstream process development for human monoclonal antibody purification Protein Expr Purif 66: 58–65 Index A Aggregation Russell bodies���������������������������������������������������������������14 Apoptosis���������������������������������������������7, 72, 77, 80, 152, 196 B Biopharmaceutical��������������� 25, 28, 71–73, 87, 152, 169, 227 C Cell culture�������������������������������������������12, 14, 16–18, 36, 37, 45–47, 50, 62, 72–74, 96, 101, 139, 144–146, 152, 195, 210, 212–219, 222, 230, 243, 245, 246, 248, 249 Cell engineering����������������������������������������������������� 9, 40, 196 Cell line development����������������������������2, 4, 90–91, 143–152 Cell line stability�������������������������������������������������������119–140 Chaperones������������������������������������������������������������� 11–13, 26 Chinese hamster ovary (CHO)������������������������� 1, 45, 71–84, 119, 169, 187, 195, 209, 243 CHO cell engineering������������������������������������������������������196 CHO cells������������������������������� 46, 71, 87, 101, 120, 209, 228 CHO genome����������������������������������������������������������������4, 82 Codon optimization�������������������������������������������������������������9 CRISPR/Cas9���������������������������������������4, 5, 10, 73, 101–117 Fluorescent in situ hybridization (FISH).����������� 4, 121, 125, 134–137 G Genome-editing������������������������������������������������� 72, 102, 169 Glutamine synthetase (GS)�������������������������������� 80, 102, 212 Glycan analysis������������������������������������������������� 230, 235, 236 Glycoengineering���������������������������������������������������������25–40 Glycosylation site insertion�������������������������������������� 228, 240 H Heterogeneity������������������������������������������17, 26, 39, 169, 228 Histone acetylation���������������������������������������������������������������6 Host Cell Proteins (HCPs)��������������������������������������243–250 Human embryonic kidney (HEK293)�������������� 28, 58, 61, 67 I Inducible������������������������������������������������������15, 16, 88, 89, 98 K Knockdown������������������������������������������������������������ 32, 87–99 Knockout������������������������������� 39, 72, 101, 102, 105, 115–117 L LC-MS/MS������������������������������197, 203–204, 219, 229, 231 Liquid chromatography���������������������������� 159, 219, 229, 231 D Design of Experiment (DOE)����������������������������������� 17, 222 Differential gene expression�������������������������������������169–186 Difficult to express protein���������������������������������������������1–18 DNA methylation����������������������������������������������������������������6 2D-PAGE����������������������������������������������������������������244–250 E Enzyme-Linked Immunosorbent Assay (ELISA)���������������48, 52, 120, 123–124, 128–129, 244–246, 248, 249 Fed-batch culture��������������������������������������� 72, 213, 214, 222 Filter-aided sample preparation (FASP)���������� 187–193, 219 Flow cytometry����������������������������������������������������������������120 Fluorescence-Activated Cell Sorting (FACS)������������� 91, 98, 104–105, 113–114, 116, 144, 146–151 M Mass Spectrometry����������������������������188, 204–205, 236, 248 Medium and feed optimization����������������������������������������210 miRNA������������������������������������������������������������� 87–89, 91, 99 miRNA sponge vector�������������������������������������������� 89, 95–98 Monoclonal antibodies (mAb)�������������������������� 1, 26, 46, 57, 71, 144, 216, 228, 229, 236 N Next generation sequencing (NGS)�����������������������������4, 169 N-glycans������������������������������������������������������������������ 229, 233 N-glycosylation������������������������������������������27, 29, 36, 38, 39, 209–211, 215, 217, 219–221, 228, 229 Paula Meleady (ed.), Heterologous Protein Production in CHO Cells: Methods and Protocols, Methods in Molecular Biology, vol 1603, DOI 10.1007/978-1-4939-6972-2, © Springer Science+Business Media LLC 2017 251 Heterologous Protein Production in CHO Cells: Methods and Protocols 252  Index    N-linked glycosylation��������������������������������������������������26, 38 P PCR overlap-extension PCR������������������������� 58, 59, 62, 64–65 real-time PCR������������������������������������������������������������121 Phosphopeptide enrichment IMAC�������������������������������������������������������������������������197 TiO2, 199 Phosphoproteomic�����������������������������������������������������������197 Polyethyleneimine (PEI)����������������������������������������������45, 47 Process optimization��������������������������������������������������� 87, 159 Productivity�����������������������������������80, 88, 102, 120, 121, 143 Protein folding�����������������������������������������1, 2, 11, 13, 39, 143 Protein translation����������������������������������������������������������������9 Protein solubilization��������������������������������������������������������188 Proteomics����������������� 154, 159, 160, 187, 196, 215, 218–219 R Real-Time PCR��������������������������������������� 120, 121, 129–134 Recombinant protein production����������������������������� 209, 212 Recombinant proteins��������������������������������������������������������13 RNA-Seq�����������������������������������������������������������������169–186 S Secretion��������������������������������������������������������� 2, 12, 148, 149 Selection����������������������������������������������������������� 14, 35, 71, 73 Short interfering RNA (siRNA)���������������������� 30, 37, 73, 75 Sialylation��������������������������������������������������������������� 13, 29–37 Site specific phosphorylation��������������������������������������������197 Sort�����������������������������105, 113, 116, 144, 147, 150, 152, 176 Suspension adaptation��������������������������������������������������������77 Systems biotechnology�������������������������������������������������������40 T TET-ON���������������������������������������������������� 15, 89, 90, 93–98 Tetracycline (Tet)��������������������������������������������������� 15, 88, 89 Therapeutic proteins������������������� 1, 33, 35, 36, 39, 71, 73, 80 Transcriptomic������������������������������������������������� 180, 196, 219 Transfection�����������������������������������������������2, 6, 12, 14, 45–55 Transient gene expression (TGE)����������������������� 6, 45, 62, 67 V Vector design������������������������������������������������������������������6, 18 Vector design elements Matrix associated regions (MARs)�����������������������������7, ubiquitous chromatin opening elements (UCOEs)��������������������������������������������������������������7, W Western blotting�������������������������������������14, 74, 79, 115, 123, 127–128, 244, 246 ... solutions in the bioprocessing space such as operating parameters or media and feed o ­ ptimization Paula Meleady (ed.), Heterologous Protein Production in CHO Cells: Methods and Protocols, Methods in. .. National Institute for Bioprocessing Research and Training (NIBRT), Dublin, Ireland Craig Monger  •  National Institute for Bioprocessing Research and Training (NIBRT), Dublin, Ireland; National Institute... phase increased cell-specific production and eliminated protein aggregation [57] The disparity in these findings suggests that the engineering of molecular chaperones for increased protein expression