Using molecular markers to characterize productivity in Chinese hamster ovary cell lines.

PLoS ONE. 2013;8(10):e75935 DOI 10.1371/journal.pone.0075935

 

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Journal Title: PLoS ONE

ISSN: 1932-6203 (Online)

Publisher: Public Library of Science (PLoS)

LCC Subject Category: Medicine | Science

Country of publisher: United States

Language of fulltext: English

Full-text formats available: PDF, HTML, XML

 

AUTHORS

Raihana Z Edros
Susan McDonnell
Mohamed Al-Rubeai

EDITORIAL INFORMATION

Peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 24 weeks

 

Abstract | Full Text

Selection of high producing cell lines to produce maximum product concentration is a challenging and time consuming task for the biopharmaceutical industry. The identification of early markers to predict high productivity will significantly reduce the time required for new cell line development. This study identifies candidate determinants of high productivity by profiling the molecular and morphological characteristics of a panel of six Chinese Hamster Ovary (CHO) stable cell lines with varying recombinant monoclonal antibody productivity levels ranging between 2 and 50 pg/cell/day. We examined the correlation between molecular parameters and specific productivity (qp ) throughout the growth phase of batch cultures. Results were statistically analyzed using Pearson correlation coefficient. Our study revealed that, overall, heavy chain (HC) mRNA had the strongest association with qp followed by light chain (LC) mRNA, HC intracellular polypeptides, and intracellular antibodies. A significant correlation was also obtained between qp and the following molecular markers: growth rate, biomass, endoplasmic reticulum, and LC polypeptides. However, in these cases, the correlation was not observed at all-time points throughout the growth phase. The repeated sampling throughout culture duration had enabled more accurate predictions of productivity in comparison to performing a single-point measurement. Since the correlation varied from day to day during batch cultivation, single-point measurement was of limited use in making a reliable prediction.