Unravelling mitochondrial dynamics in T cells using high-speed image-enabled flow cytometry 2302022

Abstract Introduction T cells have critical roles in immune response to infections, tumors, and other pathologies, and their efficacy is rooted in their functional and metabolic status. Mitochondria are important intracellular organelles intertwined with T cell metabolism and function. Upon T cell activation, mitochondria undergo dynamic remodeling marked by a series of structural changes associated with efficient electron transport and metabolic transitions. Failure to induce these metabolic changes can prevent T cell proliferation, activation and effector function. Although mitochondrial structure and metabolic programs are of wide interest to researchers, tools for rapidly assessing T cell mitochondrial morphology together with other phenotypic features remain limited. Methods Currently, researchers utilize various microscopy techniques to visualize mitochondria, which is technically demanding and can be biased due to limited number of images available for analysis. In this study, we addressed this technical gap by leveraging high-speed imaging flow cytometry to enable interrogation of mitochondrial dynamics in T cells. Results Using an in vitro system of T-cell activation that recapitulated increases in the number and volume of mitochondria, we identified unique mitochondrial phenotypes using a high-speed imaging flow cytometer. A set of intuitive spatial image parameters were examined to select ideal parameters based on unsupervised clustering. Using these imaging parameters, we quantified and sorted T cells with distinct mitochondrial morphology at high speed. Subsequent transcriptomic characterization revealed metabolic heterogeneity associated with distinct mitochondrial phenotypes, validating the new imaging flow cytometry and cell sorting method. Conclusion This work develops a high-throughput method to characterize phenotypic variation in mitochondrial morphology, and provides a workflow integrating cell activation, sorting, and transcriptomics to elucidate mechanisms underlying mitochondrial dynamics. 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/vkag141.1235
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Unravelling mitochondrial dynamics in T cells using high-speed image-enabled flow cytometry 2302022

Moen Sen, Xiaoshan Shi, Scott Bornheimer, Aaron Middlebrook et al.
The Journal of Immunology
Single-cell and spatial transcriptomics
article

Unravelling mitochondrial dynamics in T cells using high-speed image-enabled flow cytometry 2302022

Moen Sen, Xiaoshan Shi, Scott Bornheimer, Aaron Middlebrook, Stephanie Widmann
article en

Abstract

Abstract Introduction T cells have critical roles in immune response to infections, tumors, and other pathologies, and their efficacy is rooted in their functional and metabolic status. Mitochondria are important intracellular organelles intertwined with T cell metabolism and function. Upon T cell activation, mitochondria undergo dynamic remodeling marked by a series of structural changes associated with efficient electron transport and metabolic transitions. Failure to induce these metabolic changes can prevent T cell proliferation, activation and effector function. Although mitochondrial structure and metabolic programs are of wide interest to researchers, tools for rapidly assessing T cell mitochondrial morphology together with other phenotypic features remain limited. Methods Currently, researchers utilize various microscopy techniques to visualize mitochondria, which is technically demanding and can be biased due to limited number of images available for analysis. In this study, we addressed this technical gap by leveraging high-speed imaging flow cytometry to enable interrogation of mitochondrial dynamics in T cells. Results Using an in vitro system of T-cell activation that recapitulated increases in the number and volume of mitochondria, we identified unique mitochondrial phenotypes using a high-speed imaging flow cytometer. A set of intuitive spatial image parameters were examined to select ideal parameters based on unsupervised clustering. Using these imaging parameters, we quantified and sorted T cells with distinct mitochondrial morphology at high speed. Subsequent transcriptomic characterization revealed metabolic heterogeneity associated with distinct mitochondrial phenotypes, validating the new imaging flow cytometry and cell sorting method. Conclusion This work develops a high-throughput method to characterize phenotypic variation in mitochondrial morphology, and provides a workflow integrating cell activation, sorting, and transcriptomics to elucidate mechanisms underlying mitochondrial dynamics. Funding Source n/a Topic Categories Technological Innovations in Immunology (TECH)

The Journal of ImmunologyVol. 215(Supplement_1)
BD Biosciences (United States) (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 14%
Single-cell and spatial transcriptomics
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