Nanoscopic subcellular imaging enabled by ion beam tomography

Ahmet F. Coskun (), Guojun Han, Shambavi Ganesh, Shih-Yu Chen, Xavier Rovira Clavé, Stefan Harmsen, Sizun Jiang, Christian M. Schürch, Yunhao Bai, Chuck Hitzman and Garry P. Nolan ()
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Ahmet F. Coskun: Stanford University School of Medicine
Guojun Han: Stanford University School of Medicine
Shambavi Ganesh: Georgia Institute of Technology and Emory University
Shih-Yu Chen: Stanford University School of Medicine
Xavier Rovira Clavé: Stanford University School of Medicine
Stefan Harmsen: Stanford University School of Medicine
Sizun Jiang: Stanford University School of Medicine
Christian M. Schürch: Stanford University School of Medicine
Yunhao Bai: Stanford University
Chuck Hitzman: Stanford University
Garry P. Nolan: Stanford University School of Medicine

Nature Communications, 2021, vol. 12, issue 1, 1-19

Abstract: Abstract Multiplexed ion beam imaging (MIBI) has been previously used to profile multiple parameters in two dimensions in single cells within tissue slices. Here, a mathematical and technical framework for three-dimensional (3D) subcellular MIBI is presented. Ion-beam tomography (IBT) compiles ion beam images that are acquired iteratively across successive, multiple scans, and later assembled into a 3D format without loss of depth resolution. Algorithmic deconvolution, tailored for ion beams, is then applied to the transformed ion image series, yielding 4-fold enhanced ion beam data cubes. To further generate 3D sub-ion-beam-width precision visuals, isolated ion molecules are localized in the raw ion beam images, creating an approach coined as SILM, secondary ion beam localization microscopy, providing sub-25 nm accuracy in original ion images. Using deep learning, a parameter-free reconstruction method for ion beam tomograms with high accuracy is developed for low-density targets. In cultured cancer cells and tissues, IBT enables accessible visualization of 3D volumetric distributions of genomic regions, RNA transcripts, and protein factors with 5 nm axial resolution using isotope-enrichments and label-free elemental analyses. Multiparameter imaging of subcellular features at near macromolecular resolution is implemented by the IBT tools as a general biocomputation pipeline for imaging mass spectrometry.

Date: 2021
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DOI: 10.1038/s41467-020-20753-5

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