Abstract

BackgroundTo study the role of microRNA (miRNA) in the regulation of Chinese hamster ovary (CHO) cell growth, qPCR, microarray and quantitative LC-MS/MS analysis were utilised for simultaneous expression profiling of miRNA, mRNA and protein. The sample set under investigation consisted of clones with variable cellular growth rates derived from the same population. In addition to providing a systems level perspective on cell growth, the integration of multiple profiling datasets can facilitate the identification of non-seed miRNA targets, complement computational prediction tools and reduce false positive and false negative rates.Results51 miRNAs were associated with increased growth rate (35 miRNAs upregulated and 16 miRNAs downregulated). Gene ontology (GO) analysis of genes (n=432) and proteins (n=285) found to be differentially expressed (DE) identified biological processes driving proliferation including mRNA processing and translation. To investigate the influence of miRNA on these processes we combined the proteomic and transcriptomic data into two groups. The first set contained candidates where evidence of translational repression was observed (n=158). The second group was a mixture of proteins and mRNAs where evidence of translational repression was less clear (n=515). The TargetScan algorithm was utilised to predict potential targets within these two groups for anti-correlated DE miRNAs.ConclusionsThe evidence presented in this study indicates that biological processes such as mRNA processing and protein synthesis are correlated with growth rate in CHO cells. Through the integration of expression data from multiple levels of the biological system a number of proteins central to these processes including several hnRNPs and components of the ribosome were found to be post-transcriptionally regulated. We utilised the expression data in conjunction with in-silico tools to identify potential miRNA-mediated regulation of mRNA/proteins involved in CHO cell growth rate. These data have allowed us to prioritise candidates for cell engineering and/or biomarkers relevant to industrial cell culture. We also expect the knowledge gained from this study to be applicable to other fields investigating the role of miRNAs in mammalian cell growth.

Highlights

  • To study the role of microRNA in the regulation of Chinese hamster ovary (CHO) cell growth, qPCR, microarray and quantitative LC-MS/MS analysis were utilised for simultaneous expression profiling of miRNA, Messenger Ribonucleic acid (RNA) (mRNA) and protein

  • Consistent behaviour in the samples subjected to expression profiling in terms of growth rate and productivity was ensured by monitoring over 40 passages

  • By choosing sister clones derived from the same transfection pool with similar recombinant protein production rates and differing only in growth rate we sought to eliminate noise and expose those variations related to the proliferation phenotype

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Summary

Introduction

To study the role of microRNA (miRNA) in the regulation of Chinese hamster ovary (CHO) cell growth, qPCR, microarray and quantitative LC-MS/MS analysis were utilised for simultaneous expression profiling of miRNA, mRNA and protein. Since the discovery of miRNA in C.elegans [2], the miRBase data repository has expanded to hold sequence data from over 21,000 mature miRNAs across 168 species [3] These short, highly conserved RNA molecules (~22 nucleotides) form a layer of post-transcriptional control of gene expression, generally repressing translation [1] (via translational inhibition, transcriptional degradation and in some instances mRNA deadenylation [4]) or in rare cases enhancing translation [5]. Previous studies have yielded less than encouraging false positive and false negative rates resulting from the use of algorithms [17,18] prompting an increasing focus on combining multiple expression profiling datasets with in-silico target prediction [19]

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