Toward Understanding the Subcellular Distributions of Cholesterol and Sphingolipids Using High-Resolution NanoSIMS Imaging.

Characterizing the subcellular distributions of biomolecules of interest is a basic inquiry that helps inform on the potential roles of these molecules in biological functions. Presently, the functions of specific lipid species and cholesterol are not well understood, partially because cholesterol and lipid species of interest are difficult to image with high spatial resolution but without perturbing them. Because cholesterol and lipids are relatively small and their distributions are influenced by noncovalent interactions with other biomolecules, functionalizing them with relatively large labels that permit their detection may alter their distributions in membranes and between organelles. This challenge has been surmounted by exploiting rare stable isotopes as labels that may be metabolically incorporated into cholesterol and lipids without altering their chemical compositions, and the Cameca NanoSIMS 50 instrument's ability to image rare stable isotope labels with high spatial resolution. This Account covers the use of secondary ion mass spectrometry (SIMS) performed with a Cameca NanoSIMS 50 instrument for imaging cholesterol and sphingolipids in the membranes of mammalian cells. The NanoSIMS 50 detects monatomic and diatomic secondary ions ejected from the sample to map the elemental and isotopic composition at the surface of the sample with better than 50 nm lateral resolution and 5 nm depth resolution. Much effort has focused on using NanoSIMS imaging of rare isotope-labeled cholesterol and sphingolipids for testing the long-standing hypothesis that cholesterol and sphingolipids colocalize within distinct domains in the plasma membrane. By using a NanoSIMS 50 to image rare isotope-labeled cholesterol and sphingolipids in parallel with affinity-labeled proteins of interest, a hypothesis regarding the colocalization of specific membrane proteins with cholesterol and sphingolipids in distinct plasma membrane domains has been tested. NanoSIMS performed in a depth profiling mode has enabled imaging the intracellular distributions of cholesterol and sphingolipids. Important progress has also been made in developing a computational depth correction strategy for constructing more accurate three-dimensional (3D) NanoSIMS depth profiling images of intracellular component distribution without requiring additional measurements with complementary techniques or signal collection. This Account provides an overview of this exciting progress, focusing on the studies from our laboratory that shifted understanding of plasma membrane organization, and the development of enabling tools for visualizing intracellular lipids.

Depth Correction of 3D NanoSIMS Images Shows Intracellular Lipid and Cholesterol Distributions while Capturing the Effects of Differential Sputter Rate.

Knowledge of the distributions of drugs, metabolites, and drug carriers within cells is a prerequisite for the development of effective disease treatments. Intracellular component distribution may be imaged with high sensitivity and spatial resolution by using a NanoSIMS in the depth profiling mode. Depth correction strategies that capture the effects of differential sputtering without requiring additional measurements could enable producing accurate 3D NanoSIMS depth profiling images of intracellular component distributions. Here we describe an approach for depth correcting 3D NanoSIMS depth profiling images of cells that accounts for differential sputter rates. Our approach uses the secondary ion and secondary electron depth profiling images to reconstruct the cell's morphology at every raster plane. These cell morphology reconstructions are used to adjust the z-positions and heights of the voxels in the component-specific 3D NanoSIMS images. We validated this strategy using AFM topography data and reconstructions created from depth profiling images acquired with focused ion beam-secondary electron microscopy. Good agreement was found for the shapes and relative heights of the reconstructed morphologies. Application of this depth correction strategy to 3D NanoSIMS depth profiling images of a metabolically labeled cell better resolved the transport vesicles, organelles, and organellar membranes containing 18O-cholesterol and 15N-sphingolipids. Accurate 3D NanoSIMS images of intracellular component distributions may now be produced without requiring correlated analyses with separate instruments or the assumption of a constant sputter rate. This will allow visualization of the subcellular distributions of lipids, metabolites, drugs, and nanoparticles in 3D, information pivotal to understanding and treating disease.

Depth correction of 3D NanoSIMS images using secondary electron pixel intensities.

Strategies that do not require additional characterization to be performed on the sample or the collection of additional secondary ion signals are needed to depth correct 3D SIMS images of cells. Here, we develop a depth correction strategy that uses the pixel intensities in the secondary electron images acquired during negative-ion NanoSIMS depth profiling to reconstruct the sample morphology. This morphology reconstruction was then used to depth correct the 3D SIMS images that show the components of interest in the sample. As a proof of concept, we applied this approach to NanoSIMS depth profiling data that show the 15N-enrichment and 18O-enrichment from 15N-sphingolipids and 18O-cholesterol, respectively, within a metabolically labeled Madin-Darby canine kidney cell. Comparison of the cell morphology reconstruction to the secondary electron images collected with the NanoSIMS revealed that the assumption of a constant sputter rate produced small inaccuracies in sample morphology after approximately 0.66 µm of material was sputtered from the cell. Nonetheless, the resulting 3D renderings of the lipid-specific isotope enrichments better matched the shapes and positions of the subcellular compartments that contained 15N-sphingolipids and 18O-cholesterol than the uncorrected 3D SIMS images. This depth correction of the 3D SIMS images also facilitated the detection of spherical cholesterol-rich compartments that were surrounded by membranes containing cholesterol and sphingolipids. Thus, we expect this approach will facilitate identifying the subcellular structures that are enriched with biomolecules of interest in 3D SIMS images while eliminating the need for correlated analyses or additional secondary ion signals for the depth correction of 3D NanoSIMS images.

Measurement of Absolute Concentration at the Subcellular Scale.

The concentration of a pharmaceutical drug or bioactive metabolite within the target organelle influences the effects elicited by the drug or metabolite. Although the relative concentrations of many compounds of interest within subcellular compartments have been measured, measurements of absolute concentrations in the organelle remain elusive. In this Perspective, we discuss a significant advance in using nano secondary ion mass spectrometry (nanoSIMS) to measure the absolute concentration of a 13C-labeled metabolite within secretory vesicles, as reported by Thomen et al. in the April issue of ACS Nano.