Translatome analysis of CHO cells to identify key growth genes

The 'Omics Revolution in CHO Biology: Roadmap to Improved CHO Productivity

Chinese hamster ovary (CHO) cell physiology understanding has advanced very rapidly in the past few years with incredible improvements in long-read sequencing, improved resolution, and increased computational power. Multiple parental lines have been sequenced and the resultant pan-genome can be leveraged to increase our understanding of the diverse pathways CHO cells can take to get high-productivity phenotypes. The same improvements in workflows have complemented transcriptomic studies. Microfluidics and label-free innovations have further increased the sensitivity and accuracy of proteomic methods, while also making proteomics more accessible. In this 'omics era, high-throughput screening methods, sophisticated informatic tools, and models continually drive major innovations in cell line development and process engineering. This review describes the various recent achievements in 'omics techniques and their application to improve recombinant protein expression from CHO cell lines.

Insights into the Impact of Rosmarinic Acid on CHO Cell Culture Improvement through Transcriptomics Analysis

The use of antioxidants in Chinese hamster ovary (CHO) cell cultures to improve monoclonal antibody production has been a topic of great interest. Nevertheless, the antioxidants do not have consistent benefits of production improvement, which might be cell line specific and/or process specific. In this work, we investigated how treatment with the antioxidant rosmarinic acid (RA) improved cell growth and titer in CHO cell cultures using transcriptomics. In particular, transcriptomics analysis indicated that RA treatment modified gene expression and strongly affected the MAPK and PI3K/Akt signaling pathways, which regulate cell survival and cell death. Moreover, it was observed that these signaling pathways, which had been identified to be up-regulated on day 2 and day 6 by RA, were also up-regulated over time (from initial growth phase day 2 to slow growth or protein production phase day 6) in both conditions. In summary, this transcriptomics analysis provides insights into the role of the antioxidant RA in industrial cell culture processes. The current study also represents an example in the industry of how omics can be applied to gain an in-depth understanding of CHO cell biology and to identify critical pathways that can contribute to cell culture process improvement and cell line engineering.

Selection of Cashmere Fineness Functional Genes by Translatomics

Cashmere fineness is an important index to evaluate cashmere quality. Liaoning Cashmere Goat (LCG) has a large cashmere production and long cashmere fiber, but its fineness is not ideal. Therefore, it is important to find genes involved in cashmere fineness that can be used in future endeavors aiming to improve this phenotype. With the continuous advancement of research, the regulation of cashmere fineness has made new developments through high-throughput sequencing and genome-wide association analysis. It has been found that translatomics can identify genes associated with phenotypic traits. Through translatomic analysis, the skin tissue of LCG sample groups differing in cashmere fineness was sequenced by Ribo-seq. With these data, we identified 529 differentially expressed genes between the sample groups among the 27197 expressed genes. From these, 343 genes were upregulated in the fine LCG group in relation to the coarse LCG group, and 186 were downregulated in the same relationship. Through GO enrichment analysis and KEGG enrichment analysis of differential genes, the biological functions and pathways of differential genes can be found. In the GO enrichment analysis, 491 genes were significantly enriched, and the functional region was mainly in the extracellular region. In the KEGG enrichment analysis, the enrichment of the human papillomavirus infection pathway was seen the most. We found that the COL6A5 gene may affect cashmere fineness.

Genome-Wide Association Study and Cost-Efficient Genomic Predictions for Growth and Fillet Yield in Nile Tilapia (Oreochromis niloticus)

Fillet yield (FY) and harvest weight (HW) are economically important traits in Nile tilapia production. Genetic improvement of these traits, especially for FY, are lacking, due to the absence of efficient methods to measure the traits without sacrificing fish and the use of information from relatives to selection. However, genomic information could be used by genomic selection to improve traits that are difficult to measure directly in selection candidates, as in the case of FY. The objectives of this study were: (i) to perform genome-wide association studies (GWAS) to dissect the genetic architecture of FY and HW, (ii) to evaluate the accuracy of genotype imputation and (iii) to assess the accuracy of genomic selection using true and imputed low-density (LD) single nucleotide polymorphism (SNP) panels to determine a cost-effective strategy for practical implementation of genomic information in tilapia breeding programs. The data set consisted of 5,866 phenotyped animals and 1,238 genotyped animals (108 parents and 1,130 offspring) using a 50K SNP panel. The GWAS were performed using all genotyped and phenotyped animals. The genotyped imputation was performed from LD panels (LD0.5K, LD1K and LD3K) to high-density panel (HD), using information from parents and 20% of offspring in the reference set and the remaining 80% in the validation set. In addition, we tested the accuracy of genomic selection using true and imputed genotypes comparing the accuracy obtained from pedigree-based best linear unbiased prediction (PBLUP) and genomic predictions. The results from GWAS supports evidence of the polygenic nature of FY and HW. The accuracy of imputation ranged from 0.90 to 0.98 for LD0.5K and LD3K, respectively. The accuracy of genomic prediction outperformed the estimated breeding value from PBLUP. The use of imputation for genomic selection resulted in an increased relative accuracy independent of the trait and LD panel analyzed. The present results suggest that genotype imputation could be a cost-effective strategy for genomic selection in Nile tilapia breeding programs.

Transcription factor engineering in CHO cells for recombinant protein production

The continuous increase of approved biopharmaceutical products drives the development of more efficient recombinant protein expression systems. Chinese hamster ovary (CHO) cells are the mainstay for this purpose but have some drawbacks, such as low levels of expression. Several strategies have been applied to increase the productivity of CHO cells with different outcomes. Transcription factor (TF) engineering has emerged as an interesting and successful approach, as these proteins can act as master regulators; the expression and function of a TF can be controlled by small molecules, and it is possible to design tailored TFs and promoters with desired features. To date, the majority of studies have focused on the use of TFs with growth, metabolic, cell cycle or endoplasmic reticulum functions, although there is a trend to develop new, synthetic TFs. Moreover, new synthetic biological approaches are showing promising advances for the development of specific TFs, even with tailored ligand sensitivity. In this article, we summarize the strategies to increase recombinant protein expression by modulating and designing TFs and with advancements in synthetic biology. We also illustrate how this class of proteins can be used to develop more robust expression systems.

The Long Non-Coding RNA Transcriptome Landscape in CHO Cells Under Batch and Fed-Batch Conditions

The role of non-coding RNAs in determining growth, productivity, and recombinant product quality attributes in Chinese hamster ovary (CHO) cells has received much attention in recent years, exemplified by studies into microRNAs in particular. However, other classes of non-coding RNAs have received less attention. One such class are the non-coding RNAs known collectively as long non-coding RNAs (lncRNAs). The authors have undertaken the first landscape analysis of the lncRNA transcriptome in CHO using a mouse based microarray that also provided for the surveillance of the coding transcriptome. The authors report on those lncRNAs present in a model host CHO cell line under batch and fed-batch conditions on two different days and relate the expression of different lncRNAs to each other. The authors demonstrate that the mouse microarray is suitable for the detection and analysis of thousands of CHO lncRNAs and validated a number of these by qRT-PCR. The authors then further analyzed the data to identify those lncRNAs whose expression changed the most between growth and stationary phases of culture or between batch and fed-batch culture to identify potential lncRNA targets for further functional studies with regard to their role in controlling growth of CHO cells. The authors discuss the implications for the publication of this rich dataset and how this may be used by the community.

Genetic engineering of host organisms for pharmaceutical synthesis

Pharmaceutical production hosts may be derived from almost any organism, from Chinese Hamster Ovary (CHO) cell lines to isolated actinomycetes. Each host can be improved, historically only through adaptive evolution. Recently, the maturation of organism engineering has expanded the available models, methods, and tools for altering host phenotypes. New tools like CRISPR-associated endonucleases promise to enable precise cellular reprogramming and to access previously intractable hosts. In this review, we discuss the most recent advances in engineering several types of pharmaceutical production hosts. These include model organisms, potential platform hosts with advantageous metabolism or physiology, specialized producers capable of unique biosynthesis, and CHO, the most widely used recombinant protein production host. To realize improved engineered hosts, an increasing number of approaches involving DNA sequencing and synthesis, host rewriting technologies, computational methods, and organism engineering strategies must be used. Integrative workflows that enable application of the right combination of methods to the right production host could enable economical production solutions for emerging human health treatments.

Ribosome profiling-guided depletion of an mRNA increases cell growth rate and protein secretion

Recombinant protein production coopts the host cell machinery to provide high protein yields of industrial enzymes or biotherapeutics. However, since protein translation is energetically expensive and tightly controlled, it is unclear if highly expressed recombinant genes are translated as efficiently as host genes. Furthermore, it is unclear how the high expression impacts global translation. Here, we present the first genome-wide view of protein translation in an IgG-producing CHO cell line, measured with ribosome profiling. Through this we found that our recombinant mRNAs were translated as efficiently as the host cell transcriptome, and sequestered up to 15% of the total ribosome occupancy. During cell culture, changes in recombinant mRNA translation were consistent with changes in transcription, demonstrating that transcript levels influence specific productivity. Using this information, we identified the unnecessary resistance marker NeoR to be a highly transcribed and translated gene. Through siRNA knock-down of NeoR, we improved the production- and growth capacity of the host cell. Thus, ribosomal profiling provides valuable insights into translation in CHO cells and can guide efforts to enhance protein production.

The 'Omics Revolution in CHO Biology: Roadmap to Improved CHO Productivity

Increased understanding of Chinese hamster ovary (CHO) cell physiology has been ushered in upon availability of the parental CHO-K1 cell line genome. Free and openly accessible sequence information has complemented transcriptomic and proteomic studies. The previous decade has also seen an increase in sensitivity and accuracy of proteomic methods due to technology development. In this genomic era, high-throughput screening methods, sophisticated informatic tools, and models continually drive major innovations in cell line development and process engineering. This review describes the various achievements in 'omics techniques and their application to improve recombinant protein expression from CHO cell lines.

A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism

Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell-line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells provide the biochemical basis of growth and recombinant protein production. The models accurately predict growth phenotypes and known auxotrophies in CHO cells. With the models, we quantify the protein synthesis capacity of CHO cells and demonstrate that common bioprocess treatments, such as histone deacetylase inhibitors, inefficiently increase product yield. However, our simulations show that the metabolic resources in CHO are more than three times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses.

A signature of 12 microRNAs is robustly associated with growth rate in a variety of CHO cell lines

As Chinese Hamster Ovary (CHO) cells are the cell line of choice for the production of human-like recombinant proteins, there is interest in genetic optimization of host cell lines to overcome certain limitations in their growth rate and protein secretion. At the same time, a detailed understanding of these processes could be used to advantage by identification of marker transcripts that characterize states of performance. In this context, microRNAs (miRNAs) that exhibit a robust correlation to the growth rate of CHO cells were determined by analyzing miRNA expression profiles in a comprehensive collection of 46 samples including CHO-K1, CHO-S and CHO-DUKXB11, which were adapted to various culture conditions, and analyzed in different growth stages using microarrays. By applying Spearman or Pearson correlation coefficient criteria of>|0.6|, miRNAs with high correlation to the overall growth, or growth rates observed in exponential, serum-free, and serum-free exponential phase were identified. An overlap of twelve miRNAs common for all sample sets was revealed, with nine positively and three negatively correlating miRNAs. The here identified panel of miRNAs can help to understand growth regulation in CHO cells and contains putative engineering targets as well as biomarkers for cell lines with advantageous growth characteristics.

Multi-omics data driven analysis establishes reference codon biases for synthetic gene design in microbial and mammalian cells

In this study, we analyzed multi-omics data and subsets thereof to establish reference codon usage biases for codon optimization in synthetic gene design. Specifically, publicly available genomic, transcriptomic, proteomic and translatomic data for microbial and mammalian expression hosts, Escherichia coli, Saccharomyces cerevisiae, Pichia pastoris and Chinese hamster ovary (CHO) cells, were compiled to derive their individual codon and codon pair frequencies. Then, host dependent and -omics specific codon biases were generated and compared by principal component analysis and hierarchical clustering. Interestingly, our results indicated the similar codon bias patterns of the highly expressed transcripts, highly abundant proteins, and efficiently translated mRNA in microbial cells, despite the general lack of correlation between mRNA and protein expression levels. However, for CHO cells, the codon bias patterns among various -omics subsets are not distinguishable, forming one cluster. Thus, we further investigated the effect of different input codon biases on codon optimized sequences using the codon context (CC) and individual codon usage (ICU) design parameters, via in silico case study on the expression of human IFNγ sequence in CHO cells. The results supported that CC is more robust design parameter than ICU for improved heterologous gene design.

Biological insights into the expression of translation initiation factors from recombinant CHOK1SV cell lines and their relationship to enhanced productivity

We show for translation initiation factors involved in formation of the closed loop mRNA, their expression is associated with recombinant antibody productivity in Chinese hamster ovary cells and maintaining these is important in determining the cells capacity for antibody productivity.

The use of 'Omics technology to rationally improve industrial mammalian cell line performance

Biologics represent an increasingly important class of therapeutics, with 7 of the 10 top selling drugs from 2013 being in this class. Furthermore, health authority approval of biologics in the immuno-oncology space is expected to transform treatment of patients with debilitating and deadly diseases. The growing importance of biologics in the healthcare field has also resulted in the recent approvals of several biosimilars. These recent developments, combined with pressure to provide treatments at lower costs to payers, are resulting in increasing need for the industry to quickly and efficiently develop high yielding, robust processes for the manufacture of biologics with the ability to control quality attributes within narrow distributions. Achieving this level of manufacturing efficiency and the ability to design processes capable of regulating growth, death and other cellular pathways through manipulation of media, feeding strategies, and other process parameters will undoubtedly be facilitated through systems biology tools generated in academic and public research communities. Here we discuss the intersection of systems biology, 'Omics technologies, and mammalian bioprocess sciences. Specifically, we address how these methods in conjunction with traditional monitoring techniques represent a unique opportunity to better characterize and understand host cell culture state, shift from an empirical to rational approach to process development and optimization of bioreactor cultivation processes. We summarize the following six key areas: (i) research applied to parental, non-recombinant cell lines; (ii) systems level datasets generated with recombinant cell lines; (iii) datasets linking phenotypic traits to relevant biomarkers; (iv) data depositories and bioinformatics tools; (v) in silico model development, and (vi) examples where these approaches have been used to rationally improve cellular processes. We critically assess relevant and state of the art research being conducted in academic, government and industrial laboratories. Furthermore, we apply our expertise in bioprocess to define a potential model for integration of these systems biology approaches into biologics development.

Multifaceted regulation of somatic cell reprogramming by mRNA translational control

Translational control plays a pivotal role in the regulation of the pluripotency network in embryonic stem cells, but its effect on reprogramming somatic cells to pluripotency has not been explored. Here, we show that eukaryotic translation initiation factor 4E (eIF4E) binding proteins (4E-BPs), which are translational repressors, have a multifaceted effect on the reprogramming of mouse embryonic fibroblasts (MEFs) into induced pluripotent stem cells (iPSCs). Loss of 4E-BP expression attenuates the induction of iPSCs at least in part through increased translation of p21, a known inhibitor of somatic cell reprogramming. However, MEFs lacking both p53 and 4E-BPs show greatly enhanced reprogramming resulting from a combination of reduced p21 transcription and enhanced translation of endogenous mRNAs such as Sox2 and Myc and can be reprogrammed through the expression of only exogenous Oct4. Thus, 4E-BPs exert both positive and negative effects on reprogramming, highlighting the key role that translational control plays in regulating this process.

28S rRNA is inducibly pseudouridylated by the mTOR pathway translational control in CHO cell cultures

The mTOR pathway is a conserved master regulator of translational activity that influences the fate of industrially relevant CHO cell cultures, yet its molecular mechanisms remain unclear. Interestingly, rapamycin specific inhibition of the mTOR pathway in CHO cells was found to down-regulate the small nucleolar RNA U19 (snoRNA U19) by 2-fold via translatome profiling. snoRNA U19 guides the two most conserved pseudouridylation modifications on 28S ribosomal RNA (rRNA) that are important for the biogenesis and proper function of ribosomes. In order to further understand the role of snoRNA U19 as a potential player in the mTOR pathway, we measured 28S rRNA pseudouridylation upon rapamycin treatments and/or snoRNA U19 overexpression conditions, thereby characterizing the subsequent effects on ribosome efficiency and global translation by polysome profiling. We showed that 28S rRNA pseudouridylation was increased by rapamycin treatment and/or overexpression of snoRNA U19, but only the latter condition improved ribosome efficiency toward higher global translation, thus implying that the mTOR pathway induces pseudouridylation at different sites along the 28S rRNA possibly with either positive or negative effects on the cellular phenotype. This discovery of snoRNA U19 as a new downstream effector of the mTOR pathway suggests that cell engineering of snoRNAs can be used to regulate translation and improve cellular growth in CHO cell cultures in the future.

Understanding translational control mechanisms of the mTOR pathway in CHO cells by polysome profiling

The mammalian target of rapamycin (mTOR) pathway plays essential roles in the regulation of translational activity in many eukaryotes. Thus, from a bioprocessing point of view, understanding its molecular mechanisms may provide potential avenues for improving cell culture performance. Toward this end, the mTOR pathway of CHO cells in batch cultures was subjected to rapamycin treatment (inhibition) or nutrient supplementation (induction) and translational activities of CHO cells producing a monoclonal antibody (mAb) were evaluated with polysome profiling technology. Expectedly, rapamycin induced a shift of mRNAs from polysomes towards monosomes, thus reducing maximum cellular growth rate by 30%, while feeding additional nutrients extended mTOR pathway activity during the stationary growth phase in control batch culture, thereby contributing to an increase in global translation activity by up to 2-fold, and up to 5-fold higher specific translation of the heavy and light chains of the recombinant mAb. These increases in translation activity correlated with a 5-day extension in cellular growth and a 4-fold higher final product titer observed upon nutrient feeding. This first study of the relationship between the mTOR pathway and translational activity in CHO cultures provides key insights into the role of translational control in supporting greater productivity, which will lead to further enhancement of CHO cultures.