The ML1Nx2 phosphatidylinositol 3,5-bisphosphate probe shows poor selectivity in cells

Phosphatidylinositol (3,5)-bisphosphate (PtdIns(3,5)P2) is a quantitatively minor phospholipid in eukaryotic cells that plays a fundamental role in regulating endocytic membrane traffic. Despite its clear importance for cellular function and organism physiology, mechanistic details of its biology have so far not been fully elucidated. In part, this is due to a lack of experimental tools that specifically probe for PtdIns(3,5)P2 in cells to unambiguously identify its dynamics and site(s) of action. In this study, we have evaluated a recently reported PtdIns(3,5)P2 biosensor, GFP-ML1Nx2, for its veracity as such a probe. We report that, in live cells, the localization of this biosensor to sub-cellular compartments is largely independent of PtdIns(3,5)P2, as assessed after pharmacological, chemical genetic or genomic interventions that block the lipid's synthesis. We therefore conclude that it is unwise to interpret the localization of ML1Nx2 as a true and unbiased biosensor for PtdIns(3,5)P2

A model of the PI cycle reveals the regulating roles of lipid-binding proteins and pitfalls of using mosaic biological data

The phosphatidylinositol (PI) cycle is central to eukaryotic cell signaling. Its complexity, due to the number of reactions and lipid and inositol phosphate intermediates involved makes it difficult to analyze experimentally. Computational modelling approaches are seen as a way forward to elucidate complex biological regulatory mechanisms when this cannot be achieved solely through experimental approaches. Whilst mathematical modelling is well established in informing biological systems, many models are often informed by data sourced from multiple unrelated cell types (mosaic data) or from purified enzyme data. In this work, we develop a model of the PI cycle informed by experimental and omics data taken from a single cell type, namely platelets. We were able to make a number of predictions regarding the regulation of PI cycle enzymes, the importance of the number of receptors required for successful GPCR signaling and the importance of lipid- and protein-binding proteins in regulating second messenger outputs. We then consider how pathway behavior differs, when fully informed by data for HeLa cells and show that model predictions remain consistent. However, when informed by mosaic experimental data model predictions greatly vary illustrating the risks of using mosaic datasets from unrelated cell types