A combined transcriptome and proteome analysis was carried out to identify key genes and proteins differentially expressed in Chinese hamster ovary (CHO) cells producing high and low levels of dhfr-GFP fusion protein. Comparison of transcript levels was performed using a proprietary 15K CHO cDNA microarray chip, whereas proteomic analysis was performed using iTRAQ quantitative protein profiling technique. Microarray analysis revealed 77 differentially expressed genes, with 53 genes upregulated and 24 genes downregulated. Proteomic analysis gave 75 and 80 proteins for the midexponential and stationary phase, respectively. Although there was a general lack of correlation between mRNA levels and quantitated protein abundance, results from both datasets concurred on groups of proteins/genes based on functional categorization. A number of genes (20%) and proteins (45 and 23%) were involved in processes related to protein biosynthesis. We also identified three genes/proteins involved in chromatin modification. Enzymes responsible for opening up chromatin, Hmgn3 and Hmgb1, were upregulated whereas enzymes that condense chromatin, histone H1.2, were downregulated. Genes and proteins that promote cell growth (Igfbp4, Ptma, S100a6, and Lgals3) were downregulated, whereas those that deter cell growth (Ccng2, Gsg2, and S100a11) were upregulated. Other main groups of genes and proteins include carbohydrate metabolism, signal transduction, and transport. Our findings show that an integrated genomic and proteomics approach can be effectively utilized to monitor transcriptional and posttranscriptional events of mammalian cells in culture.

No abstract

DNA microarray technology has been widely utilized for species with extensive genome sequence information available. Given the limited genomic information pertaining to Chinese hamster ovary (CHO) cell line, cross-species hybridization using mouse microarrays provides a viable alternative. In this study, the utility of mouse Affymetrix microarrays for transcriptome profiling in CHO cells was assessed by hybridizing identical sets of cRNA samples from CHO cells on both mouse and CHO Affymetrix microarrays. Expression level measured by probe sets for orthologous transcripts on the two microarrays was compared. Only a fraction of the orthologous probes which detected expression calls in same species hybridization were similarly called present in cross species hybridization. In further analysis at the 25-mer probe level, it was revealed that specific hybridization signals were detectable by the subset of mouse probes that have a high degree of homology to the corresponding CHO sequences. The feasibility of cross species hybridization for quantifying the extent of differential expression was assessed by comparing transcript levels of CHO cells cultivated with and without sodium butyrate. While same species hybridization gave consistent degree of differential expression calls in replicated runs, a much inferior ability in quantifying differential expression was seen with cross species hybridization. Our results demonstrate that through detailed analysis of homology at the probe pair level, a subset of probes on existing mouse Affymetrix oligo-array can be used successfully for transcriptome profiling of CHO cells.

The high-throughput DNA sequencing Illumina Solexa GAII platform was employed to characterize the transcriptome of an antibody-producing Chinese hamster ovary (CHO) cell line. More than 55 million sequencing reads were generated and mapped to an existing set of CHO unigenes derived from expressed sequence tags (ESTs), as well as several public sequence databases. A very significant fraction of sequencing reads has not been previously seen. The frequency with which fragments of a unigene were sequenced was taken as an estimate of the abundance level of the corresponding transcripts. A wide dynamic range of transcript abundance levels was observed, spanning six orders of magnitude. However, the distribution of coverage across transcript lengths was found to vary, from relatively uniform to highly variable. This observation suggests that more challenges are yet to be resolved before direct sequencing can be used as a true quantitative measure of transcript level and for differential gene expression analysis. With the depth that high-throughput sequencing methods can reach, one can expect that the entire transcriptome of this industrially important organism will be decoded in the near future.

BackgroundOne of the key challenges in biotherapeutics production is the selection of a high-producing animal cell line to maximize protein yield in cell culture. Clone selection is often a tedious process, involving rounds of selection and single cell cloning which is costly in both money and time. In an effort to increase the throughput of clone selection, we seek to identify key signatures of a highly productive cell line using an integrated genomic and proteomic platform. In our study, we analysed microarray and proteomics data generated from a characterization of two populations of CHO cells stably expressing high and low levels of green fluorescent protein (GFP). The high producer cells (HP) make 6x more GFP than the low producer cells (LP) as determined by ELISA. Comparison of transcript levels between HP and LP in the mid-exponential phase was performed using a proprietary 15k CHO cDNA microarray chip, of which 7559 genes are unique [1], while proteomic analysis on samples in the mid-exponential and stationary phases was performed using iTRAQ quantitative protein profiling technique [2]. Although there was a general lack of correlation between mRNA levels and quantitated protein abundance, results from both datasets concurred on groups of proteins/genes based on functional categorization. ResultsFrom microarray analysis, 84 genes had a change in relative abundance of ≥ 1.5-fold, either up or down, with pvalue of ≤ 0.05. A significant number (23%) was involved in protein metabolism, transcription and RNA processing. Other major groups of genes include cell cycle regulation, signal transduction and transport. 50% of the genes had unknown functions and this could serve as a source of discovery for new and novel genes. Proteomic analysis gave 20 and 26 proteins that satisfied the cut-off criteria (≥ 1.2-fold change, 95% confidence) for the mid-exponential and stationary phase respectively. Proteins identified were mainly involved in protein metabolism, carbohydrate metabolism and transport (Figure 1). Proteome and transcriptome profiles of HP showed an up-regulation of biological processes related to protein metabolism such as protein folding (PPIB and Hyou1) and translation (Eef1a1, EIF2S3). With more protein production, genes involved in ubiquitylation (Arih1, Nedd4, Psma4, Psmc5 and Usp10) were also up-regulated to regulate misfolded proteins. Interestingly, a few of the identified genes involved in ubiquitylation have also been implicated in transcription. In particular Psmc5, a subunit of the 19S proteasome, interacts with TADs (Transcriptional Activation Domain) and general transcription factors TBP and TFIIH [3]. Key molecular chaperone genes of the UPR (unfolded protein response) pathway did not show significant differential expression, except for GRP78, an endo- plasmic reticulum molecular chaperone gene implicated in ER overload response, which was down-regulated in HP. We also found differential expression in transcription and splicing factors, which give rise to a more active transcription and mo...