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Classification of T-cell activation via autofluorescence lifetime imaging.

Authors :
Walsh AJ
Mueller KP
Tweed K
Jones I
Walsh CM
Piscopo NJ
Niemi NM
Pagliarini DJ
Saha K
Skala MC
Source :
Nature biomedical engineering [Nat Biomed Eng] 2021 Jan; Vol. 5 (1), pp. 77-88. Date of Electronic Publication: 2020 Jul 27.
Publication Year :
2021

Abstract

The function of a T cell depends on its subtype and activation state. Here, we show that imaging of the autofluorescence lifetime signals of quiescent and activated T cells can be used to classify the cells. T cells isolated from human peripheral blood and activated in culture using tetrameric antibodies against the surface ligands CD2, CD3 and CD28 showed specific activation-state-dependent patterns of autofluorescence lifetime. Logistic regression models and random forest models classified T cells according to activation state with 97-99% accuracy, and according to activation state (quiescent or activated) and subtype (CD3 <superscript>+</superscript> CD8 <superscript>+</superscript> or CD3 <superscript>+</superscript> CD4 <superscript>+</superscript> ) with 97% accuracy. Autofluorescence lifetime imaging can be used to non-destructively determine T-cell function.

Details

Language :
English
ISSN :
2157-846X
Volume :
5
Issue :
1
Database :
MEDLINE
Journal :
Nature biomedical engineering
Publication Type :
Academic Journal
Accession number :
32719514
Full Text :
https://doi.org/10.1038/s41551-020-0592-z