A screening method to assess biological effects of microRNA overexpression in Chinese hamster ovary cells
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Abstract
MicroRNAs (miRNAs) are a novel class of short non-coding RNAs, which negatively regulate target gene expression at post-transcriptional level. They mediate an important layer of control in the global regulation of gene networks, controlling a broad range of physiological as well as patho-physiological pathways including development, cancer, metabolism, proliferation, and stress resistance. So far, more than 365 miRNA genes have been identified in CHO cells. The functional analysis of the physiological effect of such large numbers of miRNAs, however, requires an efficient functional screening method. In the current study, we therefore established and evaluated a protocol to perform miRNA overexpression and to screen their effect on bio-industrially relevant phenotypes, such as growth, viability and productivity, using a recombinant, Epo-Fc producing CHO cell line. For protocol optimization, four CHO miRNAs (cgr-miR-17, cgr-miR-221, cgr-miR-21, and cgr-miR-210) were cloned into small hairpin vectors including a GFP cassette and transfected. After transfection cells were analyzed for growth and productivity over a 4-day period. Even from this small set of four miRNAs, the overexpression of miR-17, one of the members of the oncogenic miR-17-92 cluster, gave proof of principle that this method enables the identification of miRNA engineering candidates as its overexpression increased the speed of cell proliferation without negatively impacting specific productivity. The here presented method is applicable for medium-throughput screening for microRNA, miR-sponge, siRNA, or mRNA overexpression along with detailed functional characterization using the same experimental set up. As the same procedure can be applied to different production cell lines, the protocol can also be used to test for individual, cell line specific responses to microRNAs. Thus our system represents a general platform to functionally screen candidates for rational cell factory design.
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