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Advanced Registration and Analysis of MALDI Imaging Mass Spectrometry Measurements through Autofluorescence Microscopy

  • Nathan Heath Patterson
    Nathan Heath Patterson
    Mass Spectrometry Research Center  and  Departments of Biochemistry, Vanderbilt University, Nashville, Tennessee 37232-8575, United States
  • Michael Tuck
    Michael Tuck
    Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee 37232-8575, United States
    More by Michael Tuck
  • Raf Van de Plas
    Raf Van de Plas
    Mass Spectrometry Research Center  and  Departments of Biochemistry, Vanderbilt University, Nashville, Tennessee 37232-8575, United States
    Delft Center for Systems and Control (DCSC), Delft University of Technology, 2628 CD Delft, The Netherlands
  • , and 
  • Richard M. Caprioli*
    Richard M. Caprioli
    Mass Spectrometry Research Center,  Departments of Biochemistry,  Chemistry  and  Pharmacology and Medicine, Vanderbilt University, Nashville, Tennessee 37232-8575, United States
    *E-mail: [email protected]
Cite this: Anal. Chem. 2018, 90, 21, 12395–12403
Publication Date (Web):October 1, 2018
Copyright © 2018 American Chemical Society

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    Abstract Image

    The correlation of imaging mass spectrometry (IMS) with histopathology can help relate novel molecular findings obtained through IMS to the well-characterized and validated histopathology knowledge base. The quality of correlation between these two modalities is limited by the quality of the spatial mapping that is obtained by registration of the two image types. In this work, we develop novel workflows for MALDI IMS-to-microscopy data registration and analysis using nondestructive IMS-compatible wide field autofluorescence (AF) microscopy combined with computational image registration. First, a substantially automated procedure for high-accuracy registration between IMS and microscopy data of the same section is described that explicitly links the MALDI laser ablation pattern imaged by microscopy to its corresponding IMS pixel. Subsequent examination of the registered data allows for high-confidence colocalization of image features between the two modalities, down to single-cell scales within tissue. Building on this IMS-microscopy spatial mapping, we furthermore demonstrate the automated spatial correlation between IMS measurements from serial sections. This AF-registration-driven inter-section analysis, using a combination of nonlinear AF-to-AF and IMS-to-AF image registrations, can be applied to tissue sections that are prepared and imaged with different sample preparations (e.g., lipids vs proteins) and/or that are measured using different spatial resolutions. Importantly, all registrations, whether within a single section or across serial sections, are entirely independent of the IMS intensity signal content and thus unbiased by it.

    Supporting Information

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    The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.analchem.8b02884.

    • Supplemental methods, experimental walkthrough, accuracy evaluation scheme for Workflow I, and evaluation of fundamentals for Workflow II (PDF)

    • Low- (Video S1) and high-magnification (Video S2) videos of the sequence of microscopy layers explicitly linking IMS pixels to their microscopy location in the 30 μm rat kidney MALDI IMS data set (ZIP)

    • Source code for the MSRC Registration Toolbox to perform experiments (ZIP)

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