CHOmics: A web-based tool for multi-omics data analysis and interactive visualization in CHO cell lines.

Dongdong Lin,Xinmin Zhang,Yizhou Zhou,Nathan E Lewis,Christina S Alves,Sara P Bjørn,Hima B Yalamanchili,Joost Groot,Tune Wulff,Johnny Arnsdorf,Baohong Zhang,Bjørn G Voldborg,Jason A Papin

doi:10.1371/journal.pcbi.1008498

Abstract

Chinese hamster ovary (CHO) cell lines are widely used in industry for biological drug production. During cell culture development, considerable effort is invested to understand the factors that greatly impact cell growth, specific productivity and product qualities of the biotherapeutics. While high-throughput omics approaches have been increasingly utilized to reveal cellular mechanisms associated with cell line phenotypes and guide process optimization, comprehensive omics data analysis and management have been a challenge. Here we developed CHOmics, a web-based tool for integrative analysis of CHO cell line omics data that provides an interactive visualization of omics analysis outputs and efficient data management. CHOmics has a built-in comprehensive pipeline for RNA sequencing data processing and multi-layer statistical modules to explore relevant genes or pathways. Moreover, advanced functionalities were provided to enable users to customize their analysis and visualize the output systematically and interactively. The tool was also designed with the flexibility to accommodate other types of omics data and thereby enabling multi-omics comparison and visualization at both gene and pathway levels. Collectively, CHOmics is an integrative platform for data analysis, visualization and management with expectations to promote the broader use of omics in CHO cell research.

Highlights

With the increased usage of Chinese hamster ovary (CHO) cells in the large-scale production of pharmaceutical proteins, knowledge about the process optimization and biotherapeutic product quality becomes essential
CHO cells have been largely ignored in the development of publicly available tools to facilitate
Starting at 72 hr into culture and every 12 hr thereafter to 108 hr, cells were harvested for transcriptomic analysis via RNA sequencing (RNA-Seq) and proteomics analysis was conducted via mass spectrometry to identify genes differentially expressed from exponential growth to stationary phase

Summary

Introduction

With the increased usage of CHO cells in the large-scale production of pharmaceutical proteins, knowledge about the process optimization and biotherapeutic product quality becomes essential. Cell line and cell culture process development are mostly based on empirical knowledge and statistical designs, and investigation of product quality deviation to identify the root cause often requires tremendous resources and time. Omics and systems biology approaches have shown the potential to facilitate identification of predictive markers and the molecular mechanisms associated with various bioprocess phenotypes [1,2,3]. While individual omics technologies have great utility for improving bioproduction in CHO, they are closely interconnected, and each can influence data interpretation from others. Analyzing data derived from multi omics technologies together will enable scientists to accurately predict and optimize cell culture aspects and further genetically modify cell lines

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Conclusion