title: Influence of node abundance on signaling network state and dynamics analyzed by mass cytometry.
abstract: Signaling networks are key regulators of cellular function. Although the concentrations of signaling proteins are perturbed in disease states, such as cancer, and are modulated by drug therapies, our understanding of how such changes shape the properties of signaling networks is limited. Here we couple mass-cytometry-based single-cell analysis with overexpression of tagged signaling proteins to study the dependence of signaling relationships and dynamics on protein node abundance. Focusing on the epidermal growth factor receptor (EGFR) signaling network in HEK293T cells, we analyze 20 signaling proteins during a 1-h EGF stimulation time course using a panel of 35 antibodies. Data analysis with BP-R2, a measure that quantifies complex signaling relationships, reveals abundance-dependent network states and identifies novel signaling relationships. Further, we show that upstream signaling proteins have abundance-dependent effects on downstream signaling dynamics. Our approach elucidates the influence of node abundance on signal transduction networks and will further our understanding of signaling in health and disease.
authors.affiliation: Institute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.|Molecular Life Science PhD Program, Life Science Zürich Graduate School, ETH Zürich and University of Zürich, Zürich, Switzerland.
authors.forename: Xiao-Kang
authors.initials: XK
authors.lastname: Lun
authors.affiliation: Institute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.|Systems Biology PhD Program, Life Science Zürich Graduate School, ETH Zürich and University of Zürich, Zürich, Switzerland.
authors.forename: Vito R T
authors.initials: VR
authors.lastname: Zanotelli
authors.affiliation: Institute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.|Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Georgia, USA.
authors.forename: James D
authors.initials: JD
authors.lastname: Wade
authors.affiliation: Institute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.|Systems Biology PhD Program, Life Science Zürich Graduate School, ETH Zürich and University of Zürich, Zürich, Switzerland.
authors.forename: Denis
authors.initials: D
authors.lastname: Schapiro
authors.affiliation: Institute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.|Molecular Life Science PhD Program, Life Science Zürich Graduate School, ETH Zürich and University of Zürich, Zürich, Switzerland.|Institute of Biochemistry, ETH Zürich, Zürich, Switzerland.
authors.forename: Marco
authors.initials: M
authors.lastname: Tognetti
authors.affiliation: Institute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.
authors.forename: Nadine
authors.initials: N
authors.lastname: Dobberstein
authors.affiliation: Institute of Molecular Life Sciences, University of Zürich, Zürich, Switzerland.
authors.forename: Bernd
authors.initials: B
authors.lastname: Bodenmiller
mesh_terms: D003198:Computer Simulation; D004815:Epidermal Growth Factor / Q000378:metabolism*; D066246:ErbB Receptors / Q000378:metabolism*; D005434:Flow Cytometry / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods; D005786:Gene Expression Regulation / Q000502:physiology*; D057809:HEK293 Cells; D006801:Humans; D008954:Models, Biological; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction
chemical_list: D020543:Proteome; D004815:Epidermal Growth Factor; C512478:EGFR protein, human; D066246:ErbB Receptors