Quantitative phase imaging with temporal kinetics predicts hematopoietic stem cell diversity
Abstract Innovative identification technologies for hematopoietic stem cells (HSCs) have expanded the scope of stem cell biology. Clinically, the functional quality of HSCs critically influences the safety and therapeutic efficacy of stem cell therapies. However, most analytical techniques capture o...
Saved in:
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-61846-3 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849234725979291648 |
|---|---|
| author | Takao Yogo Yuichiro Iwamoto Hans Jiro Becker Takaharu Kimura Reiko Ishida Ayano Sugiyama-Finnis Tomomasa Yokomizo Toshio Suda Sadao Ota Satoshi Yamazaki |
| author_facet | Takao Yogo Yuichiro Iwamoto Hans Jiro Becker Takaharu Kimura Reiko Ishida Ayano Sugiyama-Finnis Tomomasa Yokomizo Toshio Suda Sadao Ota Satoshi Yamazaki |
| author_sort | Takao Yogo |
| collection | DOAJ |
| description | Abstract Innovative identification technologies for hematopoietic stem cells (HSCs) have expanded the scope of stem cell biology. Clinically, the functional quality of HSCs critically influences the safety and therapeutic efficacy of stem cell therapies. However, most analytical techniques capture only a single snapshot, disregarding the temporal context. A comprehensive understanding of the temporal heterogeneity of HSCs necessitates live-cell, real-time and non-invasive analysis. Here, we developed a prediction system for HSC diversity by integrating single-HSC ex vivo expansion technology with quantitative phase imaging (QPI)-driven machine learning. By analyzing the cellular kinetics of individual HSCs, we discovered previously undetectable diversity that snapshot analysis cannot resolve. The QPI-driven algorithm quantitatively evaluates stemness at the single-cell level and leverages temporal information to significantly improve prediction accuracy. This platform advances the field from snapshot-based identification of HSCs to dynamic, time-resolved prediction of their functional quality based on past cellular kinetics. |
| format | Article |
| id | doaj-art-cd1601caca344041afce6a2f853b41e4 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-cd1601caca344041afce6a2f853b41e42025-08-20T04:03:02ZengNature PortfolioNature Communications2041-17232025-07-0116111410.1038/s41467-025-61846-3Quantitative phase imaging with temporal kinetics predicts hematopoietic stem cell diversityTakao Yogo0Yuichiro Iwamoto1Hans Jiro Becker2Takaharu Kimura3Reiko Ishida4Ayano Sugiyama-Finnis5Tomomasa Yokomizo6Toshio Suda7Sadao Ota8Satoshi Yamazaki9Division of Cell Regulation, Center for Experimental Medicine and Systems Biology, The Institute of Medical Science, The University of TokyoResearch Center for Advanced Science and Technology, The University of TokyoDivision of Cell Regulation, Center for Experimental Medicine and Systems Biology, The Institute of Medical Science, The University of TokyoDivision of Cell Regulation, Center for Experimental Medicine and Systems Biology, The Institute of Medical Science, The University of TokyoDivision of Cell Regulation, Center for Experimental Medicine and Systems Biology, The Institute of Medical Science, The University of TokyoDivision of Cell Regulation, Center for Experimental Medicine and Systems Biology, The Institute of Medical Science, The University of TokyoDepartment of Microscopic and Developmental Anatomy, Tokyo Women’s Medical UniversityInternational Research Center for Medical Sciences, Kumamoto UniversityResearch Center for Advanced Science and Technology, The University of TokyoDivision of Cell Regulation, Center for Experimental Medicine and Systems Biology, The Institute of Medical Science, The University of TokyoAbstract Innovative identification technologies for hematopoietic stem cells (HSCs) have expanded the scope of stem cell biology. Clinically, the functional quality of HSCs critically influences the safety and therapeutic efficacy of stem cell therapies. However, most analytical techniques capture only a single snapshot, disregarding the temporal context. A comprehensive understanding of the temporal heterogeneity of HSCs necessitates live-cell, real-time and non-invasive analysis. Here, we developed a prediction system for HSC diversity by integrating single-HSC ex vivo expansion technology with quantitative phase imaging (QPI)-driven machine learning. By analyzing the cellular kinetics of individual HSCs, we discovered previously undetectable diversity that snapshot analysis cannot resolve. The QPI-driven algorithm quantitatively evaluates stemness at the single-cell level and leverages temporal information to significantly improve prediction accuracy. This platform advances the field from snapshot-based identification of HSCs to dynamic, time-resolved prediction of their functional quality based on past cellular kinetics.https://doi.org/10.1038/s41467-025-61846-3 |
| spellingShingle | Takao Yogo Yuichiro Iwamoto Hans Jiro Becker Takaharu Kimura Reiko Ishida Ayano Sugiyama-Finnis Tomomasa Yokomizo Toshio Suda Sadao Ota Satoshi Yamazaki Quantitative phase imaging with temporal kinetics predicts hematopoietic stem cell diversity Nature Communications |
| title | Quantitative phase imaging with temporal kinetics predicts hematopoietic stem cell diversity |
| title_full | Quantitative phase imaging with temporal kinetics predicts hematopoietic stem cell diversity |
| title_fullStr | Quantitative phase imaging with temporal kinetics predicts hematopoietic stem cell diversity |
| title_full_unstemmed | Quantitative phase imaging with temporal kinetics predicts hematopoietic stem cell diversity |
| title_short | Quantitative phase imaging with temporal kinetics predicts hematopoietic stem cell diversity |
| title_sort | quantitative phase imaging with temporal kinetics predicts hematopoietic stem cell diversity |
| url | https://doi.org/10.1038/s41467-025-61846-3 |
| work_keys_str_mv | AT takaoyogo quantitativephaseimagingwithtemporalkineticspredictshematopoieticstemcelldiversity AT yuichiroiwamoto quantitativephaseimagingwithtemporalkineticspredictshematopoieticstemcelldiversity AT hansjirobecker quantitativephaseimagingwithtemporalkineticspredictshematopoieticstemcelldiversity AT takaharukimura quantitativephaseimagingwithtemporalkineticspredictshematopoieticstemcelldiversity AT reikoishida quantitativephaseimagingwithtemporalkineticspredictshematopoieticstemcelldiversity AT ayanosugiyamafinnis quantitativephaseimagingwithtemporalkineticspredictshematopoieticstemcelldiversity AT tomomasayokomizo quantitativephaseimagingwithtemporalkineticspredictshematopoieticstemcelldiversity AT toshiosuda quantitativephaseimagingwithtemporalkineticspredictshematopoieticstemcelldiversity AT sadaoota quantitativephaseimagingwithtemporalkineticspredictshematopoieticstemcelldiversity AT satoshiyamazaki quantitativephaseimagingwithtemporalkineticspredictshematopoieticstemcelldiversity |