Nanoscopic subcellular imaging enabled by ion beam tomography.
IF: 17.694
Cited by: 8


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.


Gene Expression

MeSH terms

Cluster Analysis
Deep Learning
Electron Microscope Tomography
Gene Expression Regulation, Neoplastic
HeLa Cells
Imaging, Three-Dimensional
Mass Spectrometry
Single-Cell Analysis
Transcription, Genetic


Coskun, Ahmet F
Han, Guojun
Ganesh, Shambavi
Chen, Shih-Yu
Clavé, Xavier Rovira
Harmsen, Stefan
Jiang, Sizun
Schürch, Christian M
Bai, Yunhao
Hitzman, Chuck
Nolan, Garry P

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