New cell sorting strategy enhances stem cell purity for cultured meat production
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New cell sorting strategy enhances stem cell purity for cultured meat production

01/05/2025 TranSpread

By optimizing cell surface marker combinations, the study significantly improves stem cell purity and myogenic potential during passaging, offering a robust source of seed cells essential for advancing cultured meat technologies.

Cultured meat technology, which cultivates animal-derived stem cells into edible meat products, presents an eco-friendly alternative to traditional livestock farming. However, significant challenges remain in obtaining and maintaining high-quality seed cells.MuSCs are pivotal for generating meat fibers, but isolating pure populations from complex muscle tissue has been difficult. Furthermore, standard cell sorting methods often result in declining stemness and differentiation ability during cell expansion. Addressing these limitations is crucial for producing viable, scalable cultured meat products. Based on these challenges, there is an urgent need to develop improved strategies for isolating and maintaining functional muscle stem cells for cultured meat production.

A study (DOI: 10.48130/fmr-0025-0001) published in Food Materials Research on 28 February 2025 by Renpeng Guo, Shijie Ding and Guanghong Zhou’s team, Nanjing Agricultural University, offers a reliable and scalable method to produce high-quality seed cells crucial for cultured meat manufacturing.

To optimize the isolation of porcine MuSCs, researchers initially applied Ding’s method, using enzymatic digestion to obtain mononuclear cells from piglet muscle tissue, followed by staining with fluorescent antibodies (CD31, CD45, CD56, and CD29) and fluorescence-activated cell sorting (FACS) to isolate CD31/CD45/CD29+/CD56+ MuSCs. Although this method initially achieved an 85% PAX7-positive cell population, successive passaging led to a dramatic decrease in stemness, with PAX7 expression dropping to 16.7% and myogenic fusion capacity declining to about 33% by passage five (P5). To address these limitations, a novel strategy incorporating CD31, CD45, JAM1, ITGA5, and ITGA7 markers was developed. By gating CD31/CD45/JAM1 cells and further subdividing based on ITGA5 and ITGA7 expression, three populations were identified: ITGA5+/ITGA7 (FAPs), ITGA5+/ITGA7+ (SMCs), and ITGA5/ITGA7+ (MuSCs). Immunofluorescence, qPCR, and Western blot analyses revealed that the refined method achieved higher purity, with over 90% PAX7-positive MuSCs, enhanced PDGFRA and CNN1 marker specificity for FAPs and SMCs, respectively, and significantly more uniform cell morphology. Transcriptome sequencing further validated these identities, confirming distinct gene expression profiles and significant enrichment in skeletal muscle development pathways for the MuSC-enriched group. Functionally, the 57+ MuSCs exhibited superior differentiation potential, achieving a 90% myotube fusion rate compared to 61% using the conventional method, and maintained higher PAX7 expression and lower contaminating cell markers across multiple passages. Collectively, this novel sorting strategy significantly improves the isolation, expansion, and myogenic performance of porcine MuSCs, providing a more robust cell source for cultured meat production.

In summary, this study lays a critical foundation for the large-scale production of cultured pork, paving the way for sustainable, ethical, and high-quality meat alternatives.

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References

DOI

10.48130/fmr-0025-0001

Original Source URL

https://doi.org/10.48130/fmr-0025-0001

Funding information

The funding for this study was provided by the Nanjing Major Science and Technology Special (Comprehensive Category) Project (Grant No. 202309014), the Jiangsu Agricultural Science and Technology Innovation Fund [Grant No. CX(24)1019], the National Natural Science Foundation of China for Young Scientists (Grant No. 32101991), the Fundamental Research Funds for the Central Universities (Grant Nos KYT2023003; KYT2023004; KYT2024003), Jiangsu Synergetic Innovation Center of Meat Processing and Quality Control, and the State Key Laboratory of Meat Quality Control and Cultured Meat Development, the National Natural Science Foundation of China (Grant No. 32272468), and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant No. KYCX23_0769).

About Food Materials Research

The open-access journal Food Materials Research (e-ISSN 2771-4683) is published by Maximum Academic Press in partnership with Nanjing Agricultural University. The article types include original research papers, reviews, methods, editorials, short communications, and perspectives. All articles published in Food Materials Research represent significant advances in the genetic, molecular, biochemical, physiological processes and pathways related to food materials and sources and will provide scientific information towards overcoming technological limitations in developing conventional and alternative foods.

Title of original paper: Isolation and purification of different high-purity cell populations from pig muscle tissue
Authors: Zenan Hu1#, Zheng Liu1#, Renpeng Guo1*, Shijie Ding2* and Guanghong Zhou1*
Journal: Food Materials Research
Original Source URL: https://doi.org/10.48130/fmr-0025-0001
DOI: 10.48130/fmr-0025-0001
Latest article publication date: 28 February 2025
Subject of research: Not applicable
COI statement: The authors declare that they have no competing interests.
Archivos adjuntos
  • Figure 3. Transcriptome analysis of three types of cells. (a) PCA of RNA-seq using all gene read counts. N = 3 cell lines per group. (b) Heatmap of different cell type markers across the three populations. (c) Expression levels of ITGA5 and ITGA7 in the three cell types. (d) Gene Set Enrichment Analysis (GSEA) for the cell populations. (e) Venn diagram depicting the intersection of comparisons between Group A and Group B, Group A, and Group C. Fold change > 1, p-value < 0.05. (f) GO analysis of biological processes is based on (e). (g) Enrichment analysis of transcription factors based on (e). Error bars represent the standard deviation (SD).
01/05/2025 TranSpread
Regions: North America, United States, Asia, China
Keywords: Applied science, Engineering, Science, Agriculture & fishing

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