Nanopore Cas9-targeted sequencing enables accurate and simultaneous identification of transgene integration sites, their structure and epigenetic status in recombinant Chinese hamster ovary cells.

The integration of a transgene expression construct into the host genome is the initial step for the generation of recombinant cell lines used for biopharmaceutical production. The stability and level of recombinant gene expression in Chinese hamster ovary (CHO) can be correlated to the copy number, its integration site as well as the epigenetic context of the transgene vector. Also, undesired integration events, such as concatemers, truncated, and inverted vector repeats, are impacting the stability of recombinant cell lines. Thus, to characterize cell clones and to isolate the most promising candidates, it is crucial to obtain information on the site of integration, the structure of integrated sequence and the epigenetic status. Current sequencing techniques allow to gather this information separately but do not offer a comprehensive and simultaneous resolution. In this study, we present a fast and robust nanopore Cas9-targeted sequencing (nCats) pipeline to identify integration sites, the composition of the integrated sequence as well as its DNA methylation status in CHO cells that can be obtained simultaneously from the same sequencing run. A Cas9-enrichment step during library preparation enables targeted and directional nanopore sequencing with up to 724× median on-target coverage and up to 153 kb long reads. The data generated by nCats provides sensitive, detailed, and correct information on the transgene integration sites and the expression vector structure, which could only be partly produced by traditional Targeted Locus Amplification-seq data. Moreover, with nCats the DNA methylation status can be analyzed from the same raw data without prior DNA amplification.

Single-cell RNA sequencing reveals homogeneous transcriptome patterns and low variance in a suspension CHO-K1 and an adherent HEK293FT cell line in culture conditions.

Recombinant mammalian host cell lines, in particular CHO and HEK293 cells, are used for the industrial production of therapeutic proteins. Despite their well-known genomic instability, the control mechanisms that enable cells to respond to changes in the environmental conditions are not yet fully understood, nor do we have a good understanding of the factors that lead to phenotypic shifts in long-term cultures. A contributing factor could be inherent diversity in transcriptomes within a population. In this study, we used a full-length coverage single-cell RNA sequencing (scRNA-seq) approach to investigate and compare cell-to-cell variability and the impact of standardized and homogenous culture conditions on the diversity of individual cell transcriptomes, comparing suspension CHO-K1 and adherent HEK293FT cells. Our data showed a critical batch effect from the sequencing of four 96-well plates of CHO-K1 single cells stored for different periods of time, which was and may be therefore identified as a technical variable to consider in experimental planning. Besides, in an artificial and controlled culture environment such as used in routine cell culture technology, the gene expression pattern of a given population does not reveal any marker gene capable to disclose relevant cell population substructures, both for CHO-K1 cells and for HEK293FT cells. The variation observed is primarily driven by the cell cycle.

SLAM-seq reveals early transcriptomic response mechanisms upon glutamine deprivation in Chinese hamster ovary cells.

Mammalian cells frequently encounter subtle perturbations during recombinant protein production. Identifying the genetic factors that govern the cellular stress response can facilitate targeted genetic engineering to obtain production cell lines that demonstrate a higher stress tolerance. To simulate nutrient stress, Chinese hamster ovary (CHO) cells were transferred into a glutamine(Q)-free medium and transcriptional dynamics using thiol(SH)-linked alkylation for the metabolic sequencing of RNA (SLAM-seq) along with standard RNA-seq of stressed and unstressed cells were investigated. The SLAM-seq method allows differentiation between actively transcribed, nascent mRNA, and total (previously present) mRNA in the sample, adding an additional, time-resolved layer to classic RNA-sequencing. The cells tackle amino acid (AA) limitation by inducing the integrated stress response (ISR) signaling pathway, reflected in Atf4 overexpression in the early hours post Q deprivation, leading to subsequent activation of its targets, Asns, Atf3, Ddit3, Eif4ebp1, Gpt2, Herpud1, Slc7a1, Slc7a11, Slc38a2, Trib3, and Vegfa. The GCN2-eIF2α-ATF4 pathway is confirmed by a significant halt in transcription of translation-related genes at 24 h post Q deprivation. The downregulation of lipid synthesis indicates the inhibition of the mTOR pathway, further confirmed by overexpression of Sesn2. Furthermore, SLAM-seq detects short-lived transcription factors, such as Egr1, that would have been missed in standard experimental designs with RNA-seq. Our results describe the successful establishment of SLAM-seq in CHO cells and therefore facilitate its future use in other scenarios where dynamic transcriptome profiling in CHO cells is essential.

Expanding the Chinese hamster ovary cell long noncoding RNA transcriptome using RNASeq.

Our ability to study Chinese hamster ovary (CHO) cell biology has been revolutionised over the last decade following the development of next generation sequencing technology and publication of reference DNA sequences for CHO cells and the Chinese hamster. RNA sequencing has not only enabled the association of transcript expression with bioreactor conditions and desirable bioprocess phenotypes but played a key role in the characterisation of protein coding and small noncoding RNAs. The annotation of long noncoding RNAs, and therefore our understanding of their role in CHO cell biology, has been limited to date. In this manuscript, we use high-resolution RNASeq data to more than double the number of annotated lncRNA transcripts for the CHO K1 genome. In addition, the utilisation of strand-specific sequencing enabled the identification of more than 1,000 new antisense and divergent lncRNAs. The utility of monitoring lncRNA expression is demonstrated through an analysis of the transcriptomic response to a reduction of cell culture temperature and identification of simultaneous sense/antisense differential expression for the first time in CHO cells. To enable further studies of lncRNAs, the transcripts annotated in this study have been made available for the CHO cell biology community.

Subphysiological temperature induces pervasive alternative splicing in Chinese hamster ovary cells.

RNA sequencing (RNASeq) has been widely used to associate alterations in Chinese hamster ovary (CHO) cell gene expression with bioprocess phenotypes; however, alternative messenger RNA (mRNA) splicing, has thus far, received little attention. In this study, we utilized RNASeq for transcriptomic analysis of a monoclonal antibody (mAb) producing CHO K1 cell line subjected to a temperature shift. More than 2,465 instances of differential splicing were observed 24 hr after the reduction of cell culture temperature. A total of 1,197 of these alternative splicing events were identified in genes where no changes in abundance were detected by standard differential expression analysis. Ten examples of alternative splicing were selected for independent validation using quantitative polymerase chain reaction in the mAb-producing CHO K1 cell line used for RNASeq and a further two CHO K1 cell lines. This analysis provided evidence that exon skipping and mutually exclusive splicing events occur in genes linked to the cellular response to changes in temperature and mitochondrial function. While further work is required to determine the impact of these changes in mRNA sequence on cellular phenotype, this study demonstrates that alternative splicing analysis can be utilized to gain a deeper understanding of post-transcriptional regulation in CHO cells during biopharmaceutical production.

A Bioinformatics Pipeline for the Identification of CHO Cell Differential Gene Expression from RNA-Seq Data.

In recent years, the publication of genome sequences for the Chinese hamster and Chinese hamster ovary (CHO) cell lines has facilitated study of these biopharmaceutical cell factories with unprecedented resolution. Our understanding of the CHO cell transcriptome, in particular, has rapidly advanced through the application of next-generation sequencing (NGS) technology to characterize RNA expression (RNA-Seq). In this chapter, we present a computational pipeline for the analysis of CHO cell RNA-Seq data from the Illumina platform to identify differentially expressed genes. The example data and bioinformatics workflow required to run this analysis are freely available at www.cgcdb.org/rnaseq_analysis_protocol.html .