Imaging Flow Cytometry Enhances Characterization of Immune Cell Phenotype and Function 2255710

Abstract Introduction The addition of cellular imaging to high-speed, single-cell flow cytometry has revolutionized simultaneous immunophenotyping with morphological and spatial insights. Methods We have pioneered the utilization of imaging-enabled platforms such as the CytPix and FACSDiscover to characterize cell biology. The CytPix combines standard flow cytometry with a 20X equivalent brightfield camera to provide detailed morphological information, while the FACSDiscover enables cellular marker localization using three fluorescence imaging detectors in addition to a full spectral cytometer. Results Both platforms process images at ultra-high throughput, with FACSDiscover reaching up to 10,000 cells per second. Imaging-derived features and AI-based analysis provide morphological and spatial information, uncovering insights not possible with traditional flow cytometry. This includes enhanced identification of immune cell subsets with unique functionalities, improved resolution of senescence, and more detailed signaling and metabolic characterization of mitochondrial activity and distribution. Moreover, imaging cytometry allows to characterize immunological synapses, which was previously impossible with flow cytometry. Conclusion Current developments include leveraging AI to identify cellular states and activation label-free, simplifying cellular characterization and profiling, and bridging phenotype with mechanism–thereby driving innovation in immune cell research across multiple therapeutic areas. Funding Source n/a Topic Categories Technological Innovations in Immunology (TECH)

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Publication Details

Journal
The Journal of Immunology
Published
2026-07-28
DOI
https://doi.org/10.1093/jimmun/vkag141.280
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
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article

Imaging Flow Cytometry Enhances Characterization of Immune Cell Phenotype and Function 2255710

Raffaello Cimbro, Lilja Hardardottir, Nicholas Battaglia, Jiangfang Wang et al.
The Journal of Immunology
Single-cell and spatial transcriptomics
article

Imaging Flow Cytometry Enhances Characterization of Immune Cell Phenotype and Function 2255710

Raffaello Cimbro, Lilja Hardardottir, Nicholas Battaglia, Jiangfang Wang, Viji Premkumar, Nicola Heller, Radhika Patel, Mohamed Moustafa
article en

Abstract

Abstract Introduction The addition of cellular imaging to high-speed, single-cell flow cytometry has revolutionized simultaneous immunophenotyping with morphological and spatial insights. Methods We have pioneered the utilization of imaging-enabled platforms such as the CytPix and FACSDiscover to characterize cell biology. The CytPix combines standard flow cytometry with a 20X equivalent brightfield camera to provide detailed morphological information, while the FACSDiscover enables cellular marker localization using three fluorescence imaging detectors in addition to a full spectral cytometer. Results Both platforms process images at ultra-high throughput, with FACSDiscover reaching up to 10,000 cells per second. Imaging-derived features and AI-based analysis provide morphological and spatial information, uncovering insights not possible with traditional flow cytometry. This includes enhanced identification of immune cell subsets with unique functionalities, improved resolution of senescence, and more detailed signaling and metabolic characterization of mitochondrial activity and distribution. Moreover, imaging cytometry allows to characterize immunological synapses, which was previously impossible with flow cytometry. Conclusion Current developments include leveraging AI to identify cellular states and activation label-free, simplifying cellular characterization and profiling, and bridging phenotype with mechanism–thereby driving innovation in immune cell research across multiple therapeutic areas. Funding Source n/a Topic Categories Technological Innovations in Immunology (TECH)

The Journal of ImmunologyVol. 215(Supplement_1)
AstraZeneca (Brazil) (BR)
Industry, innovation and infrastructure
Openalex Percentile: Top 14%
Single-cell and spatial transcriptomics
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