Inferring secretory and metabolic pathway activity from omic data with secCellFie

• Published in: Metabolic engineering 2024-01, Vol.81, p.273-285
• Main Authors: Masson, Helen O., Samoudi, Mojtaba, Robinson, Caressa M., Kuo, Chih-Chung, Weiss, Linus, Shams Ud Doha, Km, Campos, Alex, Tejwani, Vijay, Dahodwala, Hussain, Menard, Patrice, Voldborg, Bjorn G., Robasky, Bradley, Sharfstein, Susan T., Lewis, Nathan E.
• Format: Article
• Language: English
• Subjects: Computational biology; Genome-scale model; Metabolism; Omic data; Secretory pathway; Systems biology
• ISSN: 1096-7176; 1096-7184; 1096-7184
• DOI: 10.1016/j.ymben.2023.12.006

Understanding protein secretion has considerable importance in biotechnology and important implications in a broad range of normal and pathological conditions including development, immunology, and tissue function. While great progress has been made in studying individual proteins in the secretory pathway, measuring and quantifying mechanistic changes in the pathway's activity remains challenging due to the complexity of the biomolecular systems involved. Systems biology has begun to address this issue with the development of algorithmic tools for analyzing biological pathways; however most of these tools remain accessible only to experts in systems biology with extensive computational experience. Here, we expand upon the user-friendly CellFie tool which quantifies metabolic activity from omic data to include secretory pathway functions, allowing any scientist to infer properties of protein secretion from omic data. We demonstrate how the secretory expansion of CellFie (secCellFie) can help predict metabolic and secretory functions across diverse immune cells, hepatokine secretion in a cell model of NAFLD, and antibody production in Chinese Hamster Ovary cells. •secCellFie augments interpretation of omics data beyond conventional enrichment to find mechanistic drivers of phenotype.•secCellFie leverages genome scale models of metabolism and protein secretion to quantify metabolic and secretion functions.•secCellFie generates hypotheses in various contexts ranging from biomedical questions to biopharmaceutical manufacturing.