TY - JOUR
T1 - A computational framework for the investigation of phosphoinositide regulation
AU - Cheung, Hilaire Yam Fung
AU - Tantiwong, Chukiat
AU - Kale, Dipali
AU - Gibbins, Jonathan M.
AU - Watson, Steve P.
AU - Heemskerk, Johan W.M.
AU - Sickmann, Albert
AU - Ahrends, Robert
AU - Dunster, Joanne L.
N1 - Publisher Copyright:
Copyright: © 2025 Cheung et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Accession Number
WOS:001585712600004
PubMed ID
41026787
PY - 2025/9/30
Y1 - 2025/9/30
N2 - Phosphoinositides are a group of interconvertible lipids that are located in the membrane of eukaryotic cells. They turnover via complex network of reactions (called the phosphoinositide pathway) that respond rapidly to regulate many aspects of a cell's response to their environment. Given their low-abundance they are difficult to characterise experimentally. Here we utilise a new experimental method to generate an unusually large dataset that characterises the time-dependent changes in five membrane bound phospoinositides and a soluble inositide in platelet, downstream of its GPVI receptor, where we know the phosphoinositide pathway is particularly active. To shed light on regulatotory steps that are often opaque to experimentation we use this data within a mathematical and computational framework. We construct and assess eleven mathematical models that represent competing interpretations of the dominant mechanisms that regulate the pathway. We find that while four of the models can generate the available data only one model, that incorporates an additional pool of PtdIns, is consistent with the data and is able to successfully predict the effects of an inhibitor. We publish all models openly in a form that is easily usable and adaptable for other researchers to use alongside our or their own data. We studied how changes in the shape and magnitude of events that stimulate the phosphoinositide pathway affect its dynamics. Despite these perturbations, the abundance of Phosphatidylinositol 4,5-bisphosphate (PtdIns(4,5)P2) remained stable, consistent with findings reported in the literature.
AB - Phosphoinositides are a group of interconvertible lipids that are located in the membrane of eukaryotic cells. They turnover via complex network of reactions (called the phosphoinositide pathway) that respond rapidly to regulate many aspects of a cell's response to their environment. Given their low-abundance they are difficult to characterise experimentally. Here we utilise a new experimental method to generate an unusually large dataset that characterises the time-dependent changes in five membrane bound phospoinositides and a soluble inositide in platelet, downstream of its GPVI receptor, where we know the phosphoinositide pathway is particularly active. To shed light on regulatotory steps that are often opaque to experimentation we use this data within a mathematical and computational framework. We construct and assess eleven mathematical models that represent competing interpretations of the dominant mechanisms that regulate the pathway. We find that while four of the models can generate the available data only one model, that incorporates an additional pool of PtdIns, is consistent with the data and is able to successfully predict the effects of an inhibitor. We publish all models openly in a form that is easily usable and adaptable for other researchers to use alongside our or their own data. We studied how changes in the shape and magnitude of events that stimulate the phosphoinositide pathway affect its dynamics. Despite these perturbations, the abundance of Phosphatidylinositol 4,5-bisphosphate (PtdIns(4,5)P2) remained stable, consistent with findings reported in the literature.
UR - https://www.scopus.com/pages/publications/105018320979
U2 - 10.1371/journal.pcbi.1013477
DO - 10.1371/journal.pcbi.1013477
M3 - Article
C2 - 41026787
AN - SCOPUS:105018320979
SN - 1553-734X
VL - 21
SP - 1
EP - 25
JO - PLoS Computational Biology
JF - PLoS Computational Biology
IS - 9
M1 - e1013477
ER -