Single cell, Label free Characterisation of Human Mesenchymal Stromal cell Stemness and Future Growth Potential by Autofluorescence Multispectral Imaging.
Autofluorescence
Cytometry
Mesenchymal stem cell
Microscopy
Senescence
Journal
Stem cell reviews and reports
ISSN: 2629-3277
Titre abrégé: Stem Cell Rev Rep
Pays: United States
ID NLM: 101752767
Informations de publication
Date de publication:
27 Aug 2024
27 Aug 2024
Historique:
accepted:
15
08
2024
medline:
27
8
2024
pubmed:
27
8
2024
entrez:
27
8
2024
Statut:
aheadofprint
Résumé
To use autofluorescence multispectral imaging (AFMI) to develop a non-invasive assay for the in-depth characterisation of human bone marrow derived mesenchymal stromal cells (hBM-MSCs). hBM-MSCs were imaged by AFMI on gridded dishes, stained for endpoints of interest (STRO-1 positivity, alkaline phosphatase, beta galactosidase, DNA content) then relocated and results correlated. Intensity, texture and morphological features were used to characterise the colour distribution of regions of interest, and canonical discriminant analysis was used to separate groups. Additionally, hBM-MSC lines were cultured to arrest, with AFMI images taken after each passage to investigate whether an assay could be developed for growth potential. STRO-1 positivity could be predicted with a receiver operator characteristic area under the curve (AUC) of 0.67. For spontaneous differentiation this was 0.66, for entry to the cell-cycle it was 0.77 and for senescence it was 0.77. Growth potential (population doublings remaining) was estimated with an RMSPE = 2.296. The Mean Absolute Error of the final prediction model indicated that growth potential could be predicted with an error of ± 1.86 doublings remaining. This non-invasive methodology enabled the in-depth characterisation of hBM-MSCs from a single assay. This approach is advantageous for clinical applications as well as research and stands out for the characterisation of both present status as well as future behaviour. The use of data from five MSC lines with heterogenous AFMI profiles supports potential generalisability.
Identifiants
pubmed: 39190057
doi: 10.1007/s12015-024-10778-4
pii: 10.1007/s12015-024-10778-4
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Australian Research Council Discovery project
ID : DP170101863
Organisme : Australian Research Council Discovery project
ID : DP210102960
Organisme : Cancer Council NSW
ID : 2021/ECF1291
Informations de copyright
© 2024. The Author(s).
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