IMmuneCite: an integrated workflow for analysis of immune enriched spatial proteomic data
Arianna Barbetta, Sarah Bangerth, Jason T.C. Lee, Brittany Rocque, Evanthia T Roussos Torres, Rohit Kohli, Omid Akbari, Juliet Emamaullee
TL;DR
IMmuneCite is a new computational tool that improves the analysis of immune cell types in spatial proteomic data from tissues like the liver.
Contribution
IMmuneCite introduces a novel workflow for reliable immune cell segmentation and phenotype assignment in spatial proteomics.
Findings
IMmuneCite identified 32 distinct immune cell phenotypes in human liver samples.
The tool reduces nonbiological cell clusters caused by overlapping marker signals.
It successfully analyzed immune landscapes in liver transplantation and hepatocellular carcinoma.
Abstract
Spatial proteomics enable detailed analysis of tissue at single cell resolution. However, creating reliable segmentation masks and assigning accurate cell phenotypes to discrete cellular phenotypes can be challenging. We introduce IMmuneCite, a computational framework for comprehensive image pre-processing and single-cell dataset creation, focused on defining complex immune landscapes when using spatial proteomics platforms. We demonstrate that IMmuneCite facilitates the identification of 32 discrete immune cell phenotypes using data from human liver samples while substantially reducing nonbiological cell clusters arising from co-localization of markers for different cell lineages. We established its versatility and ability to accommodate any antibody panel and different species by applying IMmuneCite to data from murine liver tissue. This approach enabled deep characterization of…
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Taxonomy
TopicsSingle-cell and spatial transcriptomics · Cell Image Analysis Techniques · Advanced Proteomics Techniques and Applications