Simultaneous disruption of PRC2 and enhancer function underlies histone H3.3-K27M oncogenic activity in human hindbrain neural stem cells.

Driver mutations in genes encoding histone H3 proteins resulting in p.Lys27Met substitutions (H3-K27M) are frequent in pediatric midline brain tumors. However, the precise mechanisms by which H3-K27M causes tumor initiation remain unclear. Here, we use human hindbrain neural stem cells to model the consequences of H3.3-K27M on the epigenomic landscape in a relevant developmental context. Genome-wide mapping of epitope-tagged histone H3.3 revealed that both the wild type and the K27M mutant incorporate abundantly at pre-existing active enhancers and promoters, and to a lesser extent at Polycomb repressive complex 2 (PRC2)-bound regions. At active enhancers, H3.3-K27M leads to focal H3K27ac loss, decreased chromatin accessibility and reduced transcriptional expression of nearby neurodevelopmental genes. In addition, H3.3-K27M deposition at a subset of PRC2 target genes leads to increased PRC2 and PRC1 binding and augmented transcriptional repression that can be partially reversed by PRC2 inhibitors. Our work suggests that, rather than imposing de novo transcriptional circuits, H3.3-K27M drives tumorigenesis by locking initiating cells in their pre-existing, immature epigenomic state, via disruption of PRC2 and enhancer functions.

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.

PRC2.1 and PRC2.2 Synergize to Coordinate H3K27 Trimethylation.

Polycomb repressive complex 2 (PRC2) is composed of EED, SUZ12, and EZH1/2 and mediates mono-, di-, and trimethylation of histone H3 at lysine 27. At least two independent subcomplexes exist, defined by their specific accessory proteins: PRC2.1 (PCL1-3, EPOP, and PALI1/2) and PRC2.2 (AEBP2 and JARID2). We show that PRC2.1 and PRC2.2 share the majority of target genes in mouse embryonic stem cells. The loss of PCL1-3 is sufficient to evict PRC2.1 from Polycomb target genes but only leads to a partial reduction of PRC2.2 and H3K27me3. Conversely, disruption of PRC2.2 function through the loss of either JARID2 or RING1A/B is insufficient to completely disrupt targeting of SUZ12 by PCLs. Instead, the combined loss of both PRC2.1 and PRC2.2 is required, leading to the global mislocalization of SUZ12. This supports a model in which the specific accessory proteins within PRC2.1 and PRC2.2 cooperate to direct H3K27me3 via both synergistic and independent mechanisms.

Understanding biopharmaceutical production at single nucleotide resolution using ribosome footprint profiling.

Biopharmaceuticals such as monoclonal antibodies have revolutionised the treatment of a variety of diseases. The production of recombinant therapeutic proteins, however, remains expensive due to the manufacturing complexity of mammalian expression systems and the regulatory burden associated with administrating these medicines to patients in a safe and efficacious manner. In recent years, academic and industrial groups have begun to develop a greater understanding of the biology of host cell lines, such as Chinese hamster ovary (CHO) cells and utilise that information for process development and cell line engineering. In this review, we focus on ribosome footprint profiling (RiboSeq), an exciting next generation sequencing (NGS) method that provides genome-wide information on translation, and discuss how its application can transform our understanding of therapeutic protein 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 .

Ultra-deep next generation mitochondrial genome sequencing reveals widespread heteroplasmy in Chinese hamster ovary cells.

Recent sequencing of the Chinese hamster ovary (CHO) cell and Chinese hamster genomes has dramatically advanced our ability to understand the biology of these mammalian cell factories. In this study, we focus on the powerhouse of the CHO cell, the mitochondrion. Utilizing a high-resolution next generation sequencing approach we sequenced the Chinese hamster mitochondrial genome for the first time and surveyed the mutational landscape of CHO cell mitochondrial DNA (mtDNA). Depths of coverage ranging from ~3,319X to 8,056X enabled accurate identification of low frequency mutations (>1%), revealing that mtDNA heteroplasmy is widespread in CHO cells. A total of 197 variants at 130 individual nucleotide positions were identified across a panel of 22 cell lines with 81% of variants occurring at an allele frequency of between 1% and 99%. 89% of the heteroplasmic mutations identified were cell line specific with the majority of shared heteroplasmic SNPs and INDELs detected in clones from 2 cell line development projects originating from the same host cell line. The frequency of common predicted loss of function mutations varied significantly amongst the clones indicating that heteroplasmic mtDNA variation could lead to a continuous range of phenotypes and play a role in cell to cell, production run to production run and indeed clone to clone variation in CHO cell metabolism. Experiments that integrate mtDNA sequencing with metabolic flux analysis and metabolomics have the potential to improve cell line selection and enhance CHO cell metabolic phenotypes for biopharmaceutical manufacturing through rational mitochondrial genome engineering.

Towards next generation CHO cell biology: Bioinformatics methods for RNA-Seq-based expression profiling.

High throughput, cost effective next generation sequencing (NGS) has enabled the publication of genome sequences for Cricetulus griseus and several Chinese hamster ovary (CHO) cell lines. RNA-Seq, the utilization of NGS technology to study the transcriptome, is expanding our understanding of the CHO cell biological system in areas ranging from the analysis of transcription start sites to the discovery of small noncoding RNAs. The analysis of RNA-Seq data, often comprised of several million short reads, presents a considerable challenge. If the CHO cell biology field is to fully exploit the potential of RNA-Seq, the development of robust data analysis pipelines is critical. In this manuscript, we outline bioinformatics approaches for the stages of a typical RNA-Seq expression profiling experiment including quality control, pre-processing, alignment and de novo transcriptome assembly. Algorithms for the analysis of mRNA and microRNA (miRNA) expression as well as methods for the detection of alternative splicing from RNA-Seq data are also presented. At this relatively early stage of Cricetulus griseus genome assembly and annotation, it is likely that a combination of isoform deconvolution and raw count based methods will provide the most complete picture of transcript expression patterns in CHO cell RNA-Seq experiments.