Lund Anne Mathilde, Kaas Christian Schrøder, Brandl Julian, Pedersen Lasse Ebdrup, Kildegaard Helene Faustrup, Kristensen Claus, Andersen Mikael Rørdam
Department of Biotechnology and Biomedicine, Technical University of Denmark, Søltofts Plads 223, DK-2800, Kgs. Lyngby, Denmark.
Recombinant Expression Technologies, Global Research Unit, Novo Nordisk A/S, Novo Nordisk Park, DK-2760, Måløv, Denmark.
BMC Syst Biol. 2017 Mar 15;11(1):37. doi: 10.1186/s12918-017-0414-4.
Protein secretion is one of the most important processes in eukaryotes. It is based on a highly complex machinery involving numerous proteins in several cellular compartments. The elucidation of the cell biology of the secretory machinery is of great importance, as it drives protein expression for biopharmaceutical industry, a 140 billion USD global market. However, the complexity of secretory process is difficult to describe using a simple reductionist approach, and therefore a promising avenue is to employ the tools of systems biology.
On the basis of manual curation of the literature on the yeast, human, and mouse secretory pathway, we have compiled a comprehensive catalogue of characterized proteins with functional annotation and their interconnectivity. Thus we have established the most elaborate reconstruction (RECON) of the functional secretion pathway network to date, counting 801 different components in mouse. By employing our mouse RECON to the CHO-K1 genome in a comparative genomic approach, we could reconstruct the protein secretory pathway of CHO cells counting 764 CHO components. This RECON furthermore facilitated the development of three alternative methods to study protein secretion through graphical visualizations of omics data. We have demonstrated the use of these methods to identify potential new and known targets for engineering improved growth and IgG production, as well as the general observation that CHO cells seem to have less strict transcriptional regulation of protein secretion than healthy mouse cells.
The RECON of the secretory pathway represents a strong tool for interpretation of data related to protein secretion as illustrated with transcriptomic data of Chinese Hamster Ovary (CHO) cells, the main platform for mammalian protein production.
蛋白质分泌是真核生物中最重要的过程之一。它基于一个高度复杂的机制,涉及多个细胞区室中的众多蛋白质。阐明分泌机制的细胞生物学非常重要,因为它推动了生物制药行业的蛋白质表达,这是一个全球市场规模达1400亿美元的行业。然而,分泌过程的复杂性难以用简单的还原论方法描述,因此一个有前景的途径是采用系统生物学工具。
基于对酵母、人类和小鼠分泌途径文献的人工整理,我们编制了一份具有功能注释及其相互联系的已表征蛋白质的综合目录。因此,我们建立了迄今为止功能分泌途径网络最详尽的重建模型(RECON),小鼠的该模型包含801个不同成分。通过在比较基因组学方法中将我们的小鼠RECON应用于CHO-K1基因组,我们能够重建CHO细胞的蛋白质分泌途径,该途径包含764个CHO成分。这个RECON还通过组学数据的图形可视化促进了三种研究蛋白质分泌的替代方法的开发。我们展示了这些方法在识别用于工程改造以改善生长和IgG生产的潜在新靶点和已知靶点方面的应用,以及CHO细胞似乎比健康小鼠细胞对蛋白质分泌的转录调控更宽松这一普遍观察结果。
分泌途径的RECON是解释与蛋白质分泌相关数据的有力工具,如中国仓鼠卵巢(CHO)细胞(哺乳动物蛋白质生产的主要平台)的转录组数据所示。