Phosphatidylinositol (PI) lipids control critical biological processes, so aberrant biosynthesis often leads to disease. As a result, the capability to track the production and localization of these compounds in cells is vital for elucidating their complex roles. Herein, we report the design, synthesis, and application of clickable myo-inositol probe 1 a for bioorthogonal labeling of PI products. To validate this platform, we initially conducted PI synthase assays to show that 1 a inhibits PI production in vitro. Fluorescence microscopy experiments next showed probe-dependent imaging in T-24 human bladder cancer and Candida albicans cells. Growth studies in the latter showed that replacement of myo-inositol with probe 1 a led to an enhancement in cell growth. Finally, fluorescence-based TLC analysis and mass spectrometry experiments support the labeling of PI lipids. This approach provides a promising means for tracking the complex biosynthesis and trafficking of these lipids in cells.
Metabolic labeling, in which substrate analogs containing diminutive tags can infiltrate biosynthetic pathways and generate labeled products in cells, has led to dramatic advancements in the means by which complex biomolecules can be detected and biological processes can be elucidated. Within this realm, metabolic labeling of lipid products, particularly in a manner that is headgroup-specific, brings about a number of technical challenges including the complexity of lipid metabolic pathways as well as the simplicity of biosynthetic precursors to headgroup functionality. As such, only a handful of strategies for metabolic labeling of lipids have thus far been reported. However, these approaches provide enticing examples of how strategic modifications to substrate structures, particularly by introducing clickable moieties, can enable the hijacking of lipid biosynthesis. Furthermore, early work in this field has led to an explosion in diverse applications by which these techniques have been exploited to answer key biological questions or detect and track various lipid-containing biological entities. In this article, we review these efforts and emphasize recent advancements in the development and application of lipid metabolic labeling strategies.
Phosphatidylserine (PS) is a key lipid that plays important roles in disease-related biological processes, and therefore, the means to track PS in live cells are invaluable. Herein, we describe the metabolic labeling of PS in Saccharomyces cerevisiae cells using analogues of serine, a PS precursor, derivatized with azide moieties at either the amino (N-L-SerN 3 ) or carbonyl (C-L-SerN 3 ) groups. The conservative click tag modification enabled these compounds to infiltrate normal lipid biosynthetic pathways, thereby producing tagged PS molecules as supported by mass spectrometry studies, thin-layer chromatography (TLC) analysis, and further derivatization with fluorescent reporters via click chemistry to enable imaging in yeast cells. This approach shows strong prospects for elucidating the complex biosynthetic and trafficking pathways involving PS.
Signaling lipids present in cellular membranes act as important regulators of biological processes and have been implicated in the onset of numerous diseases. A common role of these lipids is the recruitment of proteins to the cell membrane surface through binding events that generally regulate protein function and localization. While understanding these interactions at the molecular level is of great interest, such efforts are hindered by the complexity of the membrane environment in which binding occurs. Towards this end, chemical strategies will be presented by which protein–membrane recognition events can be efficiently characterized. Firstly, the development and application of lipid activity probes for the proteomic identification of lipid‐binding proteins will be described. In addition, microarray platforms for the characterization of protein‐membrane binding interactions will be presented. Finally, strategies for the labeling and detection of lipids in native environments will also be discussed.
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