Niall Barron

Exercise intensity‐dependent regulation of peroxisome proliferator‐activated receptor γ coactivator‐1α mRNA abundance is associated with differential activation of upstream signalling kinases in human skeletal muscle

Skeletal muscle contraction increases intracellular ATP turnover, calcium flux, and mechanical stress, initiating signal transduction pathways that modulate peroxisome proliferator‐activated receptor γ coactivator‐1α (PGC‐1α)‐dependent transcriptional programmes. The purpose of this study was to determine if the intensity of exercise regulates PGC‐1α expression in human skeletal muscle, coincident with activation of signalling cascades known to regulate PGC‐1α transcription. Eight sedentary males expended 400 kcal (1674 kj) during a single bout of cycle ergometer exercise on two separate occasions at either 40% (LO) or 80% (HI) of . Skeletal muscle biopsies from the m. vastus lateralis were taken at rest and at +0, +3 and +19 h after exercise. Energy expenditure during exercise was similar between trials, but the high intensity bout was shorter in duration (LO, 69.9 ± 4.0 min; HI, 36.0 ± 2.2 min, P < 0.05) and had a higher rate of glycogen utilization (P < 0.05). PGC‐1α mRNA abundance increased in an intensity‐dependent manner +3 h after exercise (LO, 3.8‐fold; HI, 10.2‐fold, P < 0.05). AMP‐activated protein kinase (AMPK) (2.8‐fold, P < 0.05) and calcium/calmodulin‐dependent protein kinase II (CaMKII) phosphorylation (84%, P < 0.05) increased immediately after HI but not LO. p38 mitogen‐activated protein kinase (MAPK) phosphorylation increased after both trials (∼2.0‐fold, P < 0.05), but phosphorylation of the downstream transcription factor, activating transcription factor‐2 (ATF‐2), increased only after HI (2.4‐fold, P < 0.05). Cyclic‐AMP response element binding protein (CREB) phosphorylation was elevated at +3 h after both trials (∼80%, P < 0.05) and class IIa histone deacetylase (HDAC) phosphorylation increased only after HI (2.0‐fold, P < 0.05). In conclusion, exercise intensity regulates PGC‐1α mRNA abundance in human skeletal muscle in response to a single bout of exercise. This effect is mediated by differential activation of multiple signalling pathways, with ATF‐2 and HDAC phosphorylation proposed as key intensity‐dependent mediators.

Steroid Receptor RNA Activator Stimulates Proliferation as Well as Apoptosis In Vivo

ABSTRACT Steroid receptor RNA activator (SRA) is an RNA that coactivates steroid hormone receptor-mediated transcription in vitro. Its expression is strongly up-regulated in many human tumors of the breast, uterus, and ovary, suggesting a potential role in pathogenesis. To assess SRA function in vivo, a transgenic-mouse model was generated to enable robust human SRA expression by using the transcriptional activity of the mouse mammary tumor virus long terminal repeat. Transgenic SRA was expressed in the nuclei of luminal epithelial cells of the mammary gland and tissues of the male accessory sex glands. Distinctive evidence for SRA function in vivo was obtained from the elevated levels of estrogen-controlled expression of progesterone receptor in transgenic mammary glands. Although overexpression of SRA showed strong promoting activities on cellular proliferation and differentiation, no alterations progressed to malignancy. Epithelial hyperplasia was accompanied by increased apoptosis, and preneoplastic lesions were cleared by focal degenerative transformations. In bitransgenic mice, SRA also antagonized ras-induced tumor formation. This work indicates that although coactivation of steroid-dependent transcription by SRA is accompanied by a proliferative response, overexpression is not in itself sufficient to induce turmorigenesis. Our results underline an intricate relationship between the different physiological roles of steroid receptors in conjunction with the RNA activator in the regulation of development, tissue homeostasis, and reproduction.

Engineering CHO cell growth and recombinant protein productivity by overexpression of miR-7

The efficient production of recombinant proteins by Chinese Hamster Ovary (CHO) cells in modern bioprocesses is often augmented by the use of proliferation control strategies. The most common method is to shift the culture temperature from 37 °C to 28-33 °C though genetic approaches to achieving the same effect are also of interest. In this work we used qRT-PCR-based expression profiling using TLDA™ cards to identify miRNAs displaying differential expression 24h after temperature-shift (TS) from 37 °C to 31 °C. Six miRNAs were found to be significantly up-regulated (mir-219, mir-518d, mir-126, mir-30e, mir-489 and mir-345) and four down-regulated (mir-7, mir-320, mir-101 and mir-199). Furthermore, qRT-PCR analysis of miR-7 expression over a 6 day batch culture, with and without TS, demonstrated decreased expression over time in both cultures but to a significantly greater extent in cells shifted to a lower culture temperature. Unexpectedly, when miR-7 levels were increased transiently by transfection with miR-7 mimic in CHO-K1 cells, cell proliferation at 37 °C was effectively blocked over a 96 h culture period. On the other hand, transient inhibition of endogenous miR-7 levels using antagonists had no impact on cell growth. The exogenous overexpression of miR-7 also resulted in increased normalised (per cell) production at 37 °C, though the yield was lower than cells grown at reduced temperature. This is the first report demonstrating a functional impact of specific miRNA disregulation on CHO cell behavior in batch culture and provides some evidence of the potential which these molecules may have in terms of engineering targets in CHO production clones. Finally, we report the cloning and sequencing of the hamster-specific cgr-miR-7.

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.

A high rate of cell growth (µ) leading to rapid accumulation of viable biomass is a desirable phenotype during scale up operations and the early stages of production cultures. In order to identify genes and proteins that contribute to higher growth rates in Chinese hamster ovary (CHO) cells, a combined approach using microarray and proteomic expression profiling analysis was carried out on two matched pairs of CHO production cell lines that displayed either fast or slow growth rates. Statistical analysis of the microarray and proteomic data separately resulted in the identification of 118 gene transcripts and 58 proteins that were differentially expressed between the fast‐ and slow‐growing cells. Overlap comparison of both datasets identified a priority list of 21 candidates associated with a high growth rate phenotype in CHO. Functional analysis (by siRNA) of five of these candidates identified the valosin‐containing protein (VCP) as having a substantial impact on CHO cell growth and viability. Knockdown of HSPB1 and ENO1 also had an effect on cell growth (negative and positive, respectively). Further functional validation in CHO using both gene knockdown (siRNA) and overexpression (cDNA) confirmed that altered VCP expression impacted CHO cell proliferation, indicating that VCP and other genes and proteins identified here may play an important role in the regulation of CHO cell growth during log phase culture and are potential candidates for CHO cell line engineering strategies. Biotechnol. Bioeng. 2010; 106: 42–56.

Integrated miRNA, mRNA and protein expression analysis reveals the role of post-transcriptional regulation in controlling CHO cell growth rate

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.

Large scale microarray profiling and coexpression network analysis of CHO cells identifies transcriptional modules associated with growth and productivity

Weighted gene coexpression network analysis (WGCNA) was utilised to explore Chinese hamster ovary (CHO) cell transcriptome patterns associated with bioprocess relevant phenotypes. The dataset set used in this study consisted of 295 microarrays from 121 individual CHO cultures producing a range of biologics including monoclonal antibodies, fusion proteins and therapeutic factors; non-producing cell lines were also included. Samples were taken from a wide range of process scales and formats that varied in terms of seeding density, temperature, medium, feed medium, culture duration and product type. Cells were sampled for gene expression analysis at various stages of the culture and bioprocess-relevant characteristics including cell density, growth rate, viability, lactate, ammonium and cell specific productivity (Qp) were determined. WGCNA identified six distinct clusters of co-expressed genes, five of which were found to have associations with bioprocess variables. Two coexpression clusters were found to be associated with culture growth rate (1 positive and 1 negative). In addition, associations between a further three coexpression modules and Qp were observed (1 positive and 2 negative). Gene set enrichment analysis (GSEA) identified a number of significant biological processes within coexpressed gene clusters including cell cycle, protein secretion and vesicle transport. In summary, the approach presented in this study provides a novel perspective on the CHO cell transcriptome.

MicroRNAs: tiny targets for engineering CHO cell phenotypes?

The ability of microRNAs to influence gene expression is now recognized as a fundamental layer of regulation within the cell. MicroRNAs have a major impact on most biological processes and have generated considerable interest as potential biomarkers as well as therapeutic or engineering targets. In this review we provide a brief overview of their biogenesis, genomic organization and mode of action, followed by a description of the methods and approaches to studying their expression. We go on to consider some of the approaches to utilizing them as tools and their potential application in the bioprocessing area, with particular emphasis on Chinese hamster ovary cell engineering.

CHO microRNA engineering is growing up : recent successes and future challenges

microRNAs with their ability to regulate complex pathways that control cellular behavior and phenotype have been proposed as potential targets for cell engineering in the context of optimization of biopharmaceutical production cell lines, specifically of Chinese Hamster Ovary cells. However, until recently, research was limited by a lack of genomic sequence information on this industrially important cell line. With the publication of the genomic sequence and other relevant data sets for CHO cells since 2011, the doors have been opened for an improved understanding of CHO cell physiology and for the development of the necessary tools for novel engineering strategies. In the present review we discuss both knowledge on the regulatory mechanisms of microRNAs obtained from other biological models and proof of concepts already performed on CHO cells, thus providing an outlook of potential applications of microRNA engineering in production cell lines.

Predicting cell-specific productivity from CHO gene expression.

Improving the rate of recombinant protein production in Chinese hamster ovary (CHO) cells is an important consideration in controlling the cost of biopharmaceuticals. We present the first predictive model of productivity in CHO bioprocess culture based on gene expression profiles. The dataset used to construct the model consisted of transcriptomic data from 70 stationary phase, temperature-shifted CHO production cell line samples, for which the cell-specific productivity had been determined. These samples were utilised to investigate gene expression over a range of high to low monoclonal antibody and fc-fusion-producing CHO cell lines. We utilised a supervised regression algorithm, partial least squares (PLS) incorporating jackknife gene selection, to produce a model of cell-specific productivity (Qp) capable of predicting Qp to within 4.44 pg/cell/day root mean squared error in cross model validation (RMSE(CMV)). The final model, consisting of 287 genes, was capable of accurately predicting Qp in a further panel of 10 additional samples which were incorporated as an independent validation. Several of the genes constituting the model are linked with biological processes relevant to protein metabolism.

Impact of miR-7 over-expression on the proteome of Chinese hamster ovary cells

MicroRNAs play critical roles in the regulation of biological processes such as growth, apoptosis, productivity and secretion thus representing a potential route toward enhancing desirable characteristics of mammalian cells for biopharmaceutical production. We have previously found that miR-7 over-expression significantly inhibits the growth of CHO-SEAP cells without impacting cellular viability, with an associated increase in normalised productivity. Understanding the biological basis of this effect might open the way to new strategies for bioprocess-relevant growth regulation. In this study we have carried out a quantitative label-free LC-MS profiling study of proteins exhibiting altered levels following over-expression of miR-7 to gain insights into potential mechanisms involved in the observed phenotype. From the analysis we found 93 proteins showing decreased levels and 74 proteins with increased levels following over-expression of miR-7. Pathway analysis suggests that proteins involved in protein translation (e.g. ribosomal proteins), RNA and DNA processing (including histones) are enriched in the list of proteins showing decreased expression. Proteins involved in protein folding and secretion were found to be up-regulated following miR-7 over-expression. In silico bioinformatic analysis using miRWalk, which combined the output from 6 selected miRNA target prediction algorithms, was used to evaluate if any of the down-regulated proteins were potential direct targets of miR-7. Two genes, stathmin and catalase, which both have known roles in the regulation of cellular growth, were found to overlap a number of the predictive target database searches in both mouse and rat, and are likely to be possible direct targets of miR-7 in CHO cells. This is the first report investigating the impact of a miRNA on the proteome of CHO cells.