Depth Correction of TOF-SIMS Depth Profiling Images Using the Total Ion Count Images

Area of Science:

• Cellular Biology
• Analytical Chemistry
• Biophysics

Background:

• Depth profiling time of flight secondary ion mass spectrometry (TOF-SIMS) is a powerful technique for imaging metabolite distributions within cells.
• 3D reconstructions from TOF-SIMS data often suffer from z-axis distortion, hindering accurate interpretation of cellular structures.

Purpose of the Study:

• To develop and validate a method for correcting z-axis distortion in 3D TOF-SIMS depth profiling images of cells.
• To improve the accuracy of 3D reconstructions for visualizing subcellular structures, specifically endoplasmic reticulum-plasma membrane (ER-PM) junctions.

Main Methods:

• Utilized total ion images from TOF-SIMS depth profiling to construct a 3D cell surface morphology model.
• Applied the morphology model to correct the z-position and height of voxels in component-specific 3D TOF-SIMS images.
• Tested the correction method on 3D TOF-SIMS data of ER-PM junctions in a simplified cellular model.

Main Results:

• The developed approach successfully corrected z-axis distortion in 3D TOF-SIMS images.
• Depth-corrected 3D images provided a more accurate representation of ER-PM junction structures compared to uncorrected images.
• Projection of corrected images onto the morphology model enhanced visualization of junctions relative to cell surface features.

Conclusions:

• Accurate, component-specific 3D images can now be generated from depth profiling TOF-SIMS datasets.
• This correction method facilitates the identification of lipids and metabolites at ER-PM junctions.
• The findings may advance the understanding of metabolite roles in neuronal function.