Measurement of Absolute Concentration at the Subcellular Scale

Advanced imaging techniques for tracking drug dynamics at the subcellular level

Optical microscopes are an important imaging tool that have effectively advanced the development of modern biomedicine. In recent years, super-resolution microscopy (SRM) has become one of the most popular techniques in the life sciences, especially in the field of living cell imaging. SRM has been used to solve many problems in basic biological research and has great potential in clinical application. In particular, the use of SRM to study drug delivery and kinetics at the subcellular level enables researchers to better study drugs' mechanisms of action and to assess the efficacy of their targets in vivo. The purpose of this paper is to review the recent advances in SRM and to highlight some of its applications in assessing subcellular drug dynamics.

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.

Nanoprojectile Secondary Ion Mass Spectrometry for Analysis of Extracellular Vesicles

We describe a technique based on secondary ion mass spectrometry with nanoprojectiles (NP-SIMS) for determining the protein content of extracellular vesicles, EVs, via tagged antibodies. The technique uses individual gold nanoprojectiles (e.g., Au₄₀₀⁴⁺ and Au₂₈₀₀⁸⁺), separated in time and space, to bombard a surface. For each projectile impact (10-20 nm in diameter), the co-emitted molecules are mass analyzed and recorded as an individual mass spectrum. Examining these individual mass spectra for co-localized species allows for nanoscale mass spectrometry to be performed. The high lateral resolution of this technique is well suited for analyzing nano-objects. SIMS is generally limited to analyzing small molecules (below ∼1500 Da); therefore, we evaluated three molecules (eosin, erythrosine, and BHHTEGST) as prospective mass spectrometry tags. We tested these on a model surface comprising a mixture of all three tags conjugated to antibodies and found that NP-SIMS could detect all three tags from a single projectile impact. Applying the method, we tagged two surface proteins common in urinary EVs, CD63 and CD81, with anti-CD63-erythrosine and anti-CD81-BHHTEGST. We found that NP-SIMS could determine the relative abundance of the two proteins and required only a few hundred or thousand EVs in the analysis region to detect the presence of the tagged antibodies.