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基于形态学的猪肌肉干细胞增殖和分化潜能预测及其在培养肉生产中的应用。

Morphology-Based Prediction of Proliferation and Differentiation Potencies of Porcine Muscle Stem Cells for Cultured Meat Production.

机构信息

State Key Laboratory of Meat Quality Control and Cultured Meat Development, Key Laboratory of Meat Processing, Ministry of Agriculture, Key Lab of Meat Processing and Quality Control, Ministry of Education, Jiangsu Collaborative Innovation Center of Meat Production and Processing, College of Food Science and Technology, Nanjing Agricultural University, Nanjing 210095, China.

出版信息

J Agric Food Chem. 2023 Nov 29;71(47):18613-18621. doi: 10.1021/acs.jafc.3c06919. Epub 2023 Nov 14.

Abstract

Inconsistent efficiency of cell production caused by cellular quality variations has become a significant problem in the cultured meat industry. In our study, morphological information on passages 5-9 of porcine muscle stem cells (pMuSCs) from three lots was analyzed and used as input data in prediction models. Cell proliferation and differentiation potencies were measured by cell growth rate and average stained area of the myosin heavy chain. Analysis of PCA and heatmap showed that the morphological parameters could be used to discriminate the differences of passages and lots. Various morphological parameters were analyzed, which revealed that accumulating time-course information regarding morphological heterogeneity in cell populations is crucial to predicting the potencies. Based on the 36 and 60 h morphological profiles, the best proliferation potency prediction model ( = 0.95, RMSE = 1.1) and differentiation potency prediction model ( = 0.74, RMSE = 1.2) were explored. Correlation analysis demonstrated that morphological parameters selected in models are related to the quality of porcine muscle stem cells.

摘要

细胞生产效率的不一致性是由细胞质量的变化引起的,这已成为培养肉行业的一个重大问题。在我们的研究中,分析了来自三个批次的猪肌肉干细胞(pMuSCs)的第 5-9 代的形态信息,并将其作为预测模型的输入数据。通过细胞生长速率和肌球蛋白重链的平均染色面积来测量细胞增殖和分化能力。PCA 和热图分析表明,形态参数可用于区分代次和批次的差异。分析了各种形态参数,结果表明积累有关细胞群体形态异质性的时间过程信息对于预测能力至关重要。基于 36 和 60 h 的形态特征,可以探索最佳的增殖能力预测模型( = 0.95,RMSE = 1.1)和分化能力预测模型( = 0.74,RMSE = 1.2)。相关性分析表明,模型中选择的形态参数与猪肌肉干细胞的质量有关。

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