Quantifying single-cell diacylglycerol signaling kinetics after uncaging.


Journal

Biophysical journal
ISSN: 1542-0086
Titre abrégé: Biophys J
Pays: United States
ID NLM: 0370626

Informations de publication

Date de publication:
17 Nov 2023
Historique:
received: 02 03 2023
revised: 07 07 2023
accepted: 15 11 2023
pubmed: 18 11 2023
medline: 18 11 2023
entrez: 18 11 2023
Statut: aheadofprint

Résumé

Studying the role of molecularly distinct lipid species in cell signaling remains challenging due to a scarcity of methods for performing quantitative lipid biochemistry in living cells. We have recently used lipid uncaging to quantify lipid-protein affinities and rates of lipid trans-bilayer movement and turnover in the diacylglycerol signaling pathway. This approach is based on acquiring live-cell dose-response curves requiring light dose titrations and experimental determination of uncaging photoreaction efficiency. We here aimed to develop a methodological approach that allows us to retrieve quantitative kinetic data from uncaging experiments that 1) require only typically available datasets without the need for specialized additional constraints and 2) should in principle be applicable to other types of photoactivation experiments. Our new analysis framework allows us to identify model parameters such as diacylglycerol-protein affinities and trans-bilayer movement rates, together with initial uncaged diacylglycerol levels, using noisy single-cell data for a broad variety of structurally different diacylglycerol species. We find that lipid unsaturation degree and side-chain length generally correlate with faster lipid trans-bilayer movement and turnover and also affect lipid-protein affinities. In summary, our work demonstrates how rate parameters and lipid-protein affinities can be quantified from single-cell signaling trajectories with sufficient sensitivity to resolve the subtle kinetic differences caused by the chemical diversity of cellular signaling lipid pools.

Identifiants

pubmed: 37978803
pii: S0006-3495(23)00713-0
doi: 10.1016/j.bpj.2023.11.013
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2023 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests The authors declare no competing interests.

Auteurs

David T Gonzales (DT)

Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany; Center for Systems Biology Dresden, Dresden, Germany.

Milena Schuhmacher (M)

Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany; École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.

H Mathilda Lennartz (HM)

Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.

Juan M Iglesias-Artola (JM)

Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.

Sascha M Kuhn (SM)

Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.

Pavel Barahtjan (P)

Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany.

Christoph Zechner (C)

Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany; Center for Systems Biology Dresden, Dresden, Germany. Electronic address: zechner@mpi-cbg.de.

André Nadler (A)

Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany. Electronic address: nadler@mpi-cbg.de.

Classifications MeSH