MATISSE: An analysis protocol for combining imaging mass cytometry with fluorescence microscopy to generate single-cell data

Daniëlle Krijgsman; Neeraj Sinha; Matthijs J D Baars; Stephanie van Dam; Mojtaba Amini; Yvonne Vercoulen

doi:10.1016/j.xpro.2021.101034

MATISSE: An analysis protocol for combining imaging mass cytometry with fluorescence microscopy to generate single-cell data

STAR Protoc. 2021 Dec 15;3(1):101034. doi: 10.1016/j.xpro.2021.101034. eCollection 2022 Mar 18.

Authors

Daniëlle Krijgsman^{1

2}, Neeraj Sinha¹, Matthijs J D Baars¹, Stephanie van Dam^{1

3}, Mojtaba Amini¹, Yvonne Vercoulen¹

Affiliations

¹ Molecular Cancer Research, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, the Netherlands.
² Center for Translational Immunology, University Medical Center Utrecht, Utrecht University, 3584 CX Utrecht, the Netherlands.
³ Oncode Institute, Utrecht, the Netherlands.

Abstract

Exploring tissue heterogeneity on a single-cell level by imaging mass cytometry (IMC) remains challenging because of its limiting resolution. We previously demonstrated that combining higher resolution fluorescence with IMC data in the analysis pipeline resulted in high-quality single-cell segmentation. Here, we provide a step-by-step workflow of this MATISSE pipeline, including instructions regarding the staining procedure, and the analysis route to generate single-cell data. For complete details on the use and execution of this protocol, please refer to Baars et al., 2021.

Keywords: Antibody; Bioinformatics; Biotechnology and bioengineering; Cell Biology; Flow Cytometry/Mass Cytometry; Microscopy; Single Cell.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Image Cytometry*
Microscopy, Fluorescence
Staining and Labeling
Workflow