A General Introduction to MicroRNAs,Their Investigation and Exploitation in CHO Cell Lines - MicroRNAs as Tools in Biopharmaceutical Production - page 4

et al. 2010 , Min and Yoon 2010 ). To date such approaches have been limited in CHO
due to the lack of a publicly available annotated genome, however with the recent
publication of the CHO genome such limitations should soon be removed.

1.3.2 MicroRNA Networks

The hundreds of targets predicted to be influenced by a single microRNA suggest a
complex interplay between all genes involved. MicroRNAs are known to play an im-
portant role in development, proliferation, differentiation, and apoptosis (Wijnhoven
et al. 2007 ; Bueno et al. 2008 ). Controlling all of these aspects of cell behaviour is
crucial to the development of robust industrial cell factories. A better understanding
of the miRNA-mediated network of genes and cellular pathways is essential if one
is to manipulate miRNA in an informed manner with the aim of improving the cell
“biology” and enhance its bioprocessing capacity. A few bioinformatics tools dedi-
cated to network analysis have recently emerged that may assist this approach. For,
example DIANA-mirPatch identifies molecular pathways potentially altered by the
expression of one or several microRNAs by looking at KEGG pathway enrichment.
Unfortunately, up to now these web-tools remain limited to a set of microRNAs and
exclude the CHO genome. Recently, Hsu et al. ( 2008 ) studied the human microRNA-
regulated protein-protein interaction (PPI) network by utilizing the Human Protein
Reference Database (HPRD) and the miRNA target prediction program TargetScan.
They found that an individual miRNA often targets the core gene of the PPI net-
work. Despite advances in such in silico prediction software, the construction of a
microRNA network must be supported by sufficient experimental data. With regard
to this, of particular use for identifying microRNAs that may play a role in an in-
dustrial bioprocessing sense, has been the development of (i) microRNA arrays that
allow the monitoring of microRNA expression of a library of microRNAs associated
with a particular phenotype of interest, (ii) RNA sequencing, (iii) qRT-PCR assays
for the accurate measurement of microRNA amounts in a given sample, (iv) over-
expression and sponge vectors to increase and reduce microRNA levels respectively.
These tools, alongside the in silico prediction tools, now provide the investigator
with a suite of tools to predict, screen for, and validate the influence of microRNA
levels on cell phenotype. Such approaches can now be aligned with transcriptomic
and proteomic investigations that can identify the target mRNAs and subsequent
proteins that microRNA manipulation ultimately influences.

1.4 Parameters that Govern Repression

1.4.1 MicroRNA Stability and Abundance

Aside from the prediction of the microRNA binding sites, the 3 UTR local features,
the actual number and respective abundance of the potential targets must be con-
sidered in any experimental design as they all impact on the microRNA binding. A