Back to Search Start Over

Morphology-based noninvasive early prediction of serial-passage potency enhances the selection of clone-derived high-potency cell bank from mesenchymal stem cells

Authors :
Takashi Suyama
Yuto Takemoto
Hiromi Miyauchi
Yuko Kato
Yumi Matsuzaki
Ryuji Kato
Source :
Inflammation and Regeneration, Vol 42, Iss 1, Pp 1-13 (2022)
Publication Year :
2022
Publisher :
BMC, 2022.

Abstract

Abstract Background Rapidly expanding clones (RECs) are one of the single-cell-derived mesenchymal stem cell clones sorted from human bone marrow mononuclear cells (BMMCs), which possess advantageous features. The RECs exhibit long-lasting proliferation potency that allows more than 10 repeated serial passages in vitro, considerably benefiting the manufacturing process of allogenic MSC-based therapeutic products. Although RECs aid the preparation of large-variation clone libraries for a greedy selection of better-quality clones, such a selection is only possible by establishing multiple-candidate cell banks for quality comparisons. Thus, there is a high demand for a novel method that can predict “low-risk and high-potency clones” early and in a feasible manner given the excessive cost and effort required to maintain such an establishment. Methods LNGFR and Thy-1 co-positive cells from BMMCs were single-cell-sorted into 96-well plates, and only fast-growing clones that reached confluency in 2 weeks were picked up and passaged as RECs. Fifteen RECs were prepared as passage 3 (P3) cryostock as the primary cell bank. From this cryostock, RECs were passaged until their proliferation limitation; their serial-passage limitation numbers were labeled as serial-passage potencies. At the P1 stage, phase-contrast microscopic images were obtained over 6–90 h to identify time-course changes of 24 morphological descriptors describing cell population information. Machine learning models were constructed using the morphological descriptors for predicting serial-passage potencies. The time window and field-of-view-number effects were evaluated to identify the most efficient image data usage condition for realizing high-performance serial-passage potency models. Results Serial-passage test results indicated variations of 7–13-repeated serial-passage potencies within RECs. Such potency values were predicted quantitatively with high performance (RMSE

Details

Language :
English
ISSN :
18808190
Volume :
42
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Inflammation and Regeneration
Publication Type :
Academic Journal
Accession number :
edsdoj.2a47cd614aa54655a2de44bfd059b0ae
Document Type :
article
Full Text :
https://doi.org/10.1186/s41232-022-00214-w