4.8 Article

Non-invasive functional molecular phenotyping of human smooth muscle cells utilized in cardiovascular tissue engineering

期刊

ACTA BIOMATERIALIA
卷 89, 期 -, 页码 193-205

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.actbio.2019.03.026

关键词

Smooth muscle cell heterogeneity; Phenotypic switching; Blood vessel; Raman microspectroscopy; Marker-independent imaging

资金

  1. DAAD Faculty Research Visit Fellowship
  2. Deutsche Forschungsgemeinschaft [SCHE701/14-1, INST 2388/30-1, INST 2388/64-1]
  3. Ministry of Science, Research and Arts of Baden Wurttemberg [Az.: SI-BW 01222-91, 33-729.55-3/214-8]

向作者/读者索取更多资源

Smooth muscle cell (SMC) diversity and plasticity are limiting factors in their characterization and application in cardiovascular tissue engineering. This work aimed to evaluate the potential of Raman microspectroscopy and Raman imaging to distinguish SMCs of different tissue origins and phenotypes. Cultured human SMCs isolated from different vascular and non-vascular tissues as well as fixed human SMC-containing tissues were analyzed. In addition, Raman spectra and images of tissue-engineered SMC constructs were acquired. Routine techniques such as qPCR, histochemistry, histological and immunocytological staining were performed for comparative gene and protein expression analysis. We identified that SMCs of different tissue origins exhibited unique spectral information that allowed a separation of all groups of origin by multivariate data analysis (MVA). We were further able to non-invasively monitor phenotypic switching in cultured SMCs and assess the impact of different culture conditions on extracellular matrix remodeling in the tissue-engineered ring constructs. Interestingly, we identified that the Raman signature of the human SMC-based ring constructs was similar to the one obtained from native aortic tissue. We conclude that Raman microspectroscopic methods are promising tools to characterize cells and define cellular and extracellular matrix components on a molecular level. In this study, in situ measurements were marker-independent, fast, and identified cellular differences that were not detectable by established routine techniques. Perspectively, Raman microspectroscopy and MVA in combination with artificial intelligence can be suitable for automated quality monitoring of (stem) cell and cell-based tissue engineering products. Statement of Significance The accessibility of autologous blood vessels for surgery is limited. Tissue engineering (TE) aims to develop functional vascular replacements; however, no commercially available TE vascular graft (TEVG) exists to date. One limiting factor is the availability of a well-characterized and safe cell source. Smooth muscle cells (SMCs) are generally used for TEVGs. To engineer a TEVG, proliferating SMCs of the synthesizing phenotype are essential, whereas functional, sustainable TEVGs require SMCs of the contractile phenotype. SMC diversity and plasticity are therefore limiting factors, also for their quality monitoring and application in TE. In this study, Raman microspectroscopy and imaging combined with machine learning tools allowed the non-destructive, marker-independent characterization of SMCs, smooth muscle tissues and TE SMC-constructs. The spectral information was specific enough to distinguish for the first time the phenotypic switching in SMCs in real-time, and monitor the impact of culture conditions on ECM remodeling in the TE SMC-constructs. (C) 2019 Acta Materialia Inc. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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