In-situ quantification of lipids in live cells through imaging approaches

In Situ Quantitative Imaging of Plasma Membrane Stiffness in Live Cells Using a Genetically Encoded FRET Sensor

Cell membrane stiffness is critical for cellular function, with cholesterol and sphingomyelin as pivot contributors. Current methods for measuring membrane stiffness are often invasive, ex situ, and slow in process, prompting the need for innovative techniques. Here, we present a fluorescence resonance energy transfer (FRET)-based protein sensor designed to address these challenges. The sensor consists of two fluorescent units targeting sphingomyelin and cholesterol, connected by a linker that responds to the proximity of these lipids. In rigid membranes, cholesterol and sphingomyelin are in close proximity, leading to an increased FRET signal. We utilized this sensor in combination with confocal microscopy to explore changes in plasma membrane stiffness under various conditions, including differences in osmotic pressure, the presence of reactive oxygen species (ROS) and variations in substrate stiffness. Furthermore, we explored the impact of SARS-CoV-2 on membrane stiffness and the distribution of ACE2 after attachment to the cell membrane. This tool offers substantial potential for future investigations in the field of mechanobiology.

Quantitative mass spectrometry imaging: therapeutics & biomolecules

Mass spectrometry imaging (MSI) has become increasingly utilized in the analysis of biological molecules. MSI grants the ability to spatially map thousands of molecules within one experimental run in a label-free manner. While MSI is considered by most to be a qualitative method, recent advancements in instrumentation, sample preparation, and development of standards has made quantitative MSI (qMSI) more common. In this feature article, we present a tailored review of recent advancements in qMSI of therapeutics and biomolecules such as lipids and peptides/proteins. We also provide detailed experimental considerations for conducting qMSI studies on biological samples, aiming to advance the methodology.