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Inferring secretory and metabolic pathway activity from omic data with secCellFie.
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.
Afiliación
  • Masson HO; Department of Bioengineering, UC San Diego, La Jolla, CA, USA.
  • Samoudi M; Department of Pediatrics, UC San Diego, La Jolla, CA, USA.
  • Robinson CM; Department of Pediatrics, UC San Diego, La Jolla, CA, USA.
  • Kuo CC; Department of Bioengineering, UC San Diego, La Jolla, CA, USA.
  • Weiss L; Department of Biochemistry, Eberhard Karls University of Tübingen, Germany.
  • Shams Ud Doha K; Proteomics Core, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA.
  • Campos A; Proteomics Core, Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA, USA.
  • Tejwani V; College of Nanoscale Science and Engineering, SUNY Polytechnic Institute, Albany, NY, USA.
  • Dahodwala H; College of Nanoscale Science and Engineering, SUNY Polytechnic Institute, Albany, NY, USA.
  • Menard P; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark.
  • Voldborg BG; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark; National Biologics Facility, Technical University of Denmark, Lyngby, Denmark.
  • Robasky B; University of Denver, Co, USA.
  • Sharfstein ST; College of Nanoscale Science and Engineering, SUNY Polytechnic Institute, Albany, NY, USA.
  • Lewis NE; Department of Bioengineering, UC San Diego, La Jolla, CA, USA; Department of Pediatrics, UC San Diego, La Jolla, CA, USA. Electronic address: nlewisres@ucsd.edu.
Metab Eng ; 81: 273-285, 2024 Jan.
Article en En | MEDLINE | ID: mdl-38145748
ABSTRACT
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.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Biología de Sistemas / Redes y Vías Metabólicas Límite: Animals Idioma: En Revista: Metab Eng Asunto de la revista: ENGENHARIA BIOMEDICA / METABOLISMO Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Bélgica
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Biología de Sistemas / Redes y Vías Metabólicas Límite: Animals Idioma: En Revista: Metab Eng Asunto de la revista: ENGENHARIA BIOMEDICA / METABOLISMO Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Bélgica