Label-free metabolic optical biomarkers track stem cell fate transition in real time.

Autor: Zhou H; Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA., Li I; Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA., Bramlett CS; Department of Stem Cell Biology and Regenerative Medicine, University of Southern California, Los Angeles, CA 90033, USA., Wang B; Department of Stem Cell Biology and Regenerative Medicine, University of Southern California, Los Angeles, CA 90033, USA., Hao J; Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA., Yen DP; Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA., Ando Y; Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA., Fraser SE; Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.; Department of Stem Cell Biology and Regenerative Medicine, University of Southern California, Los Angeles, CA 90033, USA.; Translational Imaging Center, University of Southern California, Los Angeles, CA 90089, USA.; Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA., Lu R; Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.; Department of Stem Cell Biology and Regenerative Medicine, University of Southern California, Los Angeles, CA 90033, USA.; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA.; Department of Medicine, University of Southern California, Los Angeles, CA 90033, USA., Shen K; Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA.; USC Stem Cell, University of Southern California, Los Angeles, CA 90033, USA.
Jazyk: angličtina
Zdroj: Science advances [Sci Adv] 2024 May 10; Vol. 10 (19), pp. eadi6770. Date of Electronic Publication: 2024 May 08.
DOI: 10.1126/sciadv.adi6770
Abstrakt: Tracking stem cell fate transition is crucial for understanding their development and optimizing biomanufacturing. Destructive single-cell methods provide a pseudotemporal landscape of stem cell differentiation but cannot monitor stem cell fate in real time. We established a metabolic optical metric using label-free fluorescence lifetime imaging microscopy (FLIM), feature extraction and machine learning-assisted analysis, for real-time cell fate tracking. From a library of 205 metabolic optical biomarker (MOB) features, we identified 56 associated with hematopoietic stem cell (HSC) differentiation. These features collectively describe HSC fate transition and detect its bifurcate lineage choice. We further derived a MOB score measuring the "metabolic stemness" of single cells and distinguishing their division patterns. This score reveals a distinct role of asymmetric division in rescuing stem cells with compromised metabolic stemness and a unique mechanism of PI3K inhibition in promoting ex vivo HSC maintenance. MOB profiling is a powerful tool for tracking stem cell fate transition and improving their biomanufacturing from a single-cell perspective.
Databáze: MEDLINE
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