CHO gene expression profiling in biopharmaceutical process analysis and design

Abstract

Increase in both productivity and product yields in biopharmaceutical process development with recombinant protein producing mammalian cells can be mainly attributed to the advancements in cell line development, media, and process optimization. Only recently, genome-scale technologies enable a system-level analysis to elucidate the complex biomolecular basis of protein production in mammalian cells promising an increased process understanding and the deduction of knowledge-based approaches for further process optimization. Here, the use of gene expression profiling for the analysis of a low titer (LT) and high titer (HT) fed batch process using the same IgG producing CHO cell line was investigated. We found that gene expression (i) significantly differed in HT versus LT process conditions due to differences in applied chemically defined, serum-free media, (ii) changed over the time course of the fed batch processes, and that (iii) both metabolic pathways and 14 biological functions such as cellular growth or cell death were affected. Furthermore, detailed analysis of metabolism in a standard process format revealed the potential use of transcriptomics for rational media design as is shown for the case of lipid metabolism where the product titer could be increased by about 20% based on a lipid modified basal medium. The results demonstrate that gene expression profiling can be an important tool for mammalian biopharmaceutical process analysis and optimization.

Predicting cell-specific productivity from CHO gene expression

“…Previous microarray expression profiling studies focussing on productivity in CHO Schaub et al, 2010;Trummer et al, 2008;Kantardjieff et al, 2010;Yee et al, 2007) and in the commercially used mouse myeloma NS0 cell line (Charaniya et al, 2009;Khoo et al, 2007;Seth et al, 2007) have identified several crucial pathways and processes. These microarray-based productivity studies have also been complemented by proteomics studies in CHO (Carlage et al, 2009;Meleady et al, 2008;Nissom et al, 2006) and NS0 Smales et al, 2004;Alete et al, 2005;Dinnis et al, 2006).…”

Into the unknown: expression profiling without genome sequence information in CHO by next generation sequencing

“…Such large-scale datasets would enable both a detailed analysis of a specific phenotype of a certain cell clone (e.g. cell-specific productivity) and a comprehensive molecular picture of the cellular responses to environmental changes such as a change in the composition of cell culture media (14). Thus, these data could greatly help to improve cell lines and production processes to finally obtain high recombinant product concentrations of correctly glycosylated antibodies.…”

Analysis of time-course gene expression profiles to study regulation of cell growth in fed-batch bioreactors

“…This intensity based approach for filtering is commonly used [26] and a threshold of 50-100 is typical in the literature [27,28]. This step led to the reduction of relevant probes from 45,101 to 15,742 with a signal distinguishable from noise.…”