Network reconstruction of the mouse secretory pathway applied on CHO cell transcriptome data

Area of Science:

• Cell Biology
• Systems Biology
• Biotechnology

Background:

• Protein secretion is a vital eukaryotic process involving complex cellular machinery.
• Understanding this pathway is crucial for the biopharmaceutical industry.
• Systems biology offers a powerful approach to study its complexity.

Purpose of the Study:

• To compile a comprehensive network reconstruction (RECON) of the protein secretion pathway.
• To develop novel methods for analyzing protein secretion using omics data.
• To identify targets for improving biopharmaceutical production in Chinese Hamster Ovary (CHO) cells.

Main Methods:

• Manual literature curation of yeast, human, and mouse secretory pathways.
• Comparative genomic analysis to reconstruct the CHO cell secretion pathway.
• Development of graphical visualization methods for omics data interpretation.

Main Results:

• Established the most elaborate functional secretion pathway network reconstruction (RECON) to date (801 components in mouse, 764 in CHO cells).
• Developed three novel methods for studying protein secretion via omics data visualization.
• Identified potential targets for enhancing growth and IgG production in CHO cells.
• Observed less strict transcriptional regulation of protein secretion in CHO cells compared to mouse cells.

Conclusions:

• The RECON of the secretory pathway is a valuable tool for interpreting protein secretion data.
• This approach is particularly useful for analyzing transcriptomic data from CHO cells, a key platform for mammalian protein production.