Adjacent Cell Marker Lateral Spillover Compensation and Reinforcement for Multiplexed Images

• Published in: Frontiers in immunology Vol. 12; p. 652631
• Main Authors: Bai, Yunhao, Zhu, Bokai, Rovira-Clave, Xavier, Chen, Han, Markovic, Maxim, Chan, Chi Ngai, Su, Tung-Hung, McIlwain, David R, Estes, Jacob D, Keren, Leeat, Nolan, Garry P, Jiang, Sizun
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 05-07-2021
• Subjects: Animals; Biomarkers; cell annotation; Cell Lineage; Fluorescent Antibody Technique - methods; image correction; Image Processing, Computer-Assisted; Immunology; Molecular Imaging - methods; Molecular Imaging - standards; multiplexed tissue imaging; Reproducibility of Results; Sensitivity and Specificity; signal spillover; Signal-To-Noise Ratio; Single-Cell Analysis - methods; Single-Cell Analysis - standards; single-cell biology; spatial proteomics; signal spillover; spatial proteomics; cell annotation; multiplexed tissue imaging; image correction; single-cell biology
• ISSN: 1664-3224; 1664-3224
• DOI: 10.3389/fimmu.2021.652631

Multiplex imaging technologies are now routinely capable of measuring more than 40 antibody-labeled parameters in single cells. However, lateral spillage of signals in densely packed tissues presents an obstacle to the assignment of high-dimensional spatial features to individual cells for accurate cell-type annotation. We devised a method to correct for lateral spillage of cell surface markers between adjacent cells termed REinforcement Dynamic Spillover EliminAtion (REDSEA). The use of REDSEA decreased contaminating signals from neighboring cells. It improved the recovery of marker signals across both isotopic (i.e., Multiplexed Ion Beam Imaging) and immunofluorescent (i.e., Cyclic Immunofluorescence) multiplexed images resulting in a marked improvement in cell-type classification.