Label-free metabolic optical biomarkers track stem cell fate transition in real time-Reference-Cited by-同舟云学术

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

Published:2024-05-10 Issue:19 Volume:10 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Zhou Hao¹^ORCID,Li Irene¹^ORCID,Bramlett Charles S.²^ORCID,Wang Bowen²^ORCID,Hao Jia¹,Yen Daniel P.¹^ORCID,Ando Yuta¹,Fraser Scott E.¹²³⁴^ORCID,Lu Rong¹²⁵⁶^ORCID,Shen Keyue¹⁵⁷^ORCID

Affiliation:

1. Department of Biomedical Engineering, University of Southern California, Los Angeles, CA 90089, USA.

2. Department of Stem Cell Biology and Regenerative Medicine, University of Southern California, Los Angeles, CA 90033, USA.

3. Translational Imaging Center, University of Southern California, Los Angeles, CA 90089, USA.

4. Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.

5. Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA 90033, USA.

6. Department of Medicine, University of Southern California, Los Angeles, CA 90033, USA.

7. USC Stem Cell, University of Southern California, Los Angeles, CA 90033, USA.

Abstract

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.

Publisher

American Association for the Advancement of Science (AAAS)

Link

https://www.science.org/doi/pdf/10.1126/sciadv.adi6770

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