Transcriptome and proteome analysis of antibody‐producing mouse myeloma NS0 cells cultivated at different cell densities in perfusion culture

Abstract

A combined gene and protein expression profiling was performed to gain a deeper insight into the intracellular response of the antibody-producing GS-NS0 cell line in continuous perfusion culture. Growth rate, production rate, metabolic activity and viability declined with increasing cell density, dilution rate and time. Transcriptome and proteome analyses of cells at three different densities revealed 53 genes and 47 proteins as having significantly altered expression levels at HCD (high cell density). The results showed an increased up-regulation of genes/proteins involved in cellular energy production with increasing cell density. Furthermore, the intensified process triggered a cellular response to external stress stimuli, revealed by an overexpression of the genes/proteins implicated in cell-cycle arrest [e.g. Rb1 (retinoblastoma 1 gene) and Cdkn1b (cyclin-dependent kinase inhibitor 1B gene)] and in the induction of pro-apoptotic genes/proteins [e.g. Tnfrsf (tumour necrosis factor receptor superfamily gene), Nfkappa bia (gene coding for nuclear factor-kappaB inhibitor), HSP60 (heat-shock protein of molecular mass 60 kDa) and heterogeneous nuclear ribonucleoprotein K]. Interestingly, we observed a down-regulation of the transcription factor interferon regulatory factor 4 involved in the unfolded-protein-response process and protein disulfide-isomerase family members responsible for protein folding and assembly. Additionally, subunits of proteasome complex were highly expressed at HCD. Microarray, real-time quantitative reverse-transcription PCR and Western-blot analyses demonstrated a consistent trend of decrease in IgG heavy-chain level with increasing cell density. HSP60, which inhibits apoptosis by complexing with pro-apoptotic proteins such as Bax and Bak, was repressed at HCD. Overall, the data suggested that the balance among several factors involved in energy metabolism might be essential for fine-tuning the cell choice between survival and apoptosis, leaning towards the side of apoptosis at HCD. The results provide significant information for cell-engineering strategies and solutions to problems that prevail in HCD culture.

Chemostat‐based transcriptional analysis of growth rate change and BCL‐2 over‐expression in NS0 cells

“…Increasingly, efforts have been made to probe transcriptomic and proteomic alterations between cells of different productivities (Charaniya et al, 2009;Khoo et al, 2007;Seth et al, 2007;Smales et al, 2004), culture conditions (Krampe et al, 2008;Shen et al, 2010;Swiderek and Al-Rubeai, 2007) or cells treated with chemical agents (Kantardjieff et al, 2010). Indeed, ''omic'' data available for mammalian cells have so far mainly been obtained in conventional batch/fed-batch shaker or bioreactor cultures.…”

“…One of these genes was the eukaryotic translation initiation factor 4E binding protein whose gene product prevents downstream assembly of eIF4F key translation complex for protein biosynthesis and has been shown to reduce cell size (Fingar et al, 2002). Genome-wide regulation of transcription in response to environmental changes or transcriptional variation between cell lines is an essential component of many studies in mammalian cell culture (Khoo et al, 2007;Krampe et al, 2008;Wong et al, 2006). However, it is apparent that the functional relationships of many changed transcripts are difficult if not impossible to explain when using a dynamic culture system such as batch, fed-batch, or perfusion.…”

Microarray and proteomics expression profiling identifies several candidates, including the valosin‐containing protein (VCP), involved in regulating high cellular growth rate in production CHO cell lines

“…As previous work has established that the correlation between transcriptome and proteome expression is not always linear (Anderson and Seilhamer, 1997;de Nobel et al, 2001;Gygi et al, 1999;Yoshida et al, 2001), a combined approach in which both the transcriptome and proteome are profiled is predicted to be more powerful than the use of either approach alone (Seth et al, 2007b). As a result, several subsequent studies (Baik et al, 2006;Korke et al, 2004;Krampe et al, 2008;Nissom et al, 2006;Seth et al, 2007a;Yee et al, 2007) employ such a combined approach. In this article, we present combined microarray and proteomics analysis of two CHO production cell line comparison pairs, each pairing differing markedly in their growth rate profiles.…”

Genomics in mammalian cell culture bioprocessing

“…However, none of the affected genes were glycosylation-related. To gain further insight into culture production decline, transcriptome and proteome studies were conducted on continuous NS0 cultures expressing a monoclonal antibody (Krampe et al, 2008). They determined that cell cycle arrest, apoptosis, and several stress-related genes were up-regulated and interferon regulatory factor 4 and protein folding related genes were down-regulated later in the cultures (Krampe et al, 2008).…”

“…To gain further insight into culture production decline, transcriptome and proteome studies were conducted on continuous NS0 cultures expressing a monoclonal antibody (Krampe et al, 2008). They determined that cell cycle arrest, apoptosis, and several stress-related genes were up-regulated and interferon regulatory factor 4 and protein folding related genes were down-regulated later in the cultures (Krampe et al, 2008). Swiderek and Al-Rubeai (2007) and Swiderek et al (2008) investigated the effects of culture temperature and hypoxia on NS0 cells using DNA microarrays.…”