Noninvasive, label-free image approaches to predict multimodal molecular markers in pluripotency assessment

Bibliographic Details
Title: Noninvasive, label-free image approaches to predict multimodal molecular markers in pluripotency assessment
Authors: Ryutaro Akiyoshi, Takeshi Hase, Mayuri Sathiyananthavel, Samik Ghosh, Hiroaki Kitano, Ayako Yachie
Source: Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Publisher Information: Nature Portfolio, 2024.
Publication Year: 2024
Collection: LCC:Medicine
LCC:Science
Subject Terms: Medicine, Science
More Details: Abstract Manufacturing regenerative medicine requires continuous monitoring of pluripotent cell culture and quality assessment while eliminating cell destruction and contaminants. In this study, we employed a novel method to monitor the pluripotency of stem cells through image analysis, avoiding the traditionally used invasive procedures. This approach employs machine learning algorithms to analyze stem cell images to predict the expression of pluripotency markers, such as OCT4 and NANOG, without physically interacting with or harming cells. We cultured induced pluripotent stem cells under various conditions to induce different pluripotent states and imaged the cells using bright-field microscopy. Pluripotency states of induced pluripotent stem cells were assessed using invasive methods, including qPCR, immunostaining, flow cytometry, and RNA sequencing. Unsupervised and semi-supervised learning models were applied to evaluate the results and accurately predict the pluripotency of the cells using only image analysis. Our approach directly links images to invasive assessment results, making the analysis of cell labeling and annotation of cells in images by experts dispensable. This core achievement not only contributes for safer and more reliable stem cell research but also opens new avenues for real-time monitoring and quality control in regenerative medicine manufacturing. Our research fills an important gap in the field by providing a viable, noninvasive alternative to traditional invasive methods for assessing pluripotency. This innovation is expected to make a significant contribution to improving regenerative medicine manufacturing because it will enable a more detailed and feasible understanding of cellular status during the manufacturing process.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2045-2322
Relation: https://doaj.org/toc/2045-2322
DOI: 10.1038/s41598-024-66591-z
Access URL: https://doaj.org/article/0f230cfaa42c4db59cfafb33f567f7d3
Accession Number: edsdoj.0f230cfaa42c4db59cfafb33f567f7d3
Database: Directory of Open Access Journals
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More Details
ISSN:20452322
DOI:10.1038/s41598-024-66591-z
Published in:Scientific Reports
Language:English