Leibniz Institute of Polymer Research Dresden, Max Bergmann Center of Biomaterials, 01069, Dresden, Germany.
Medical Clinic and Policlinic I, University Hospital Carl Gustav Carus, Technische Universität Dresden, 01307, Dresden, Germany.
Small Methods. 2023 Jun;7(6):e2201157. doi: 10.1002/smtd.202201157. Epub 2023 Mar 28.
Identifying characteristic extracellular matrix (ECM) variants is a key challenge in mechanistic biology, bioengineering, and medical diagnostics. The reported study demonstrates the potential of time-of-flight secondary ion mass spectrometry (ToF-SIMS) to detect subtle differences between human mesenchymal stromal cell (MSC)-secreted ECM types as induced by exogenous stimulation or emerging pathology. ToF-SIMS spectra of decellularized ECM samples are evaluated by discriminant principal component analysis (DPCA), an advanced multivariate analysis technique, to decipher characteristic compositional features. To establish the approach, signatures of major ECM proteins are determined from samples of pre-defined mixtures. Based on that, sets of ECM variants produced by MSCs in vitro are analyzed. Differences in the content of collagen, fibronectin, and laminin in the ECM resulting from the combined supplementation of MSC cultures with polymers that induce macromolecular crowding and with ascorbic acid are detected from the DPCA of ToF-SIMS spectra. The results are verified by immunostaining. Finally, the comparative ToF-SIMS analysis of ECM produced by MSCs of healthy donors and patients suffering from myelodysplastic syndrome display the potential of the novel methodology to reveal disease-associated alterations of the ECM composition.
鉴定特征性细胞外基质 (ECM) 变体是机械生物学、生物工程和医学诊断学的一个关键挑战。本研究报告表明,飞行时间二次离子质谱 (ToF-SIMS) 具有检测人间充质基质细胞 (MSC) 分泌的 ECM 类型在外源性刺激或出现病理时产生的细微差异的潜力。通过判别主成分分析 (DPCA) 对脱细胞 ECM 样本的 ToF-SIMS 光谱进行评估,DPCA 是一种先进的多元分析技术,用于破译特征性组成特征。为了建立该方法,从预先定义的混合物样本中确定主要 ECM 蛋白的特征。在此基础上,分析了体外 MSC 产生的 ECM 变体集。从 ToF-SIMS 光谱的 DPCA 中检测到,通过向 MSC 培养物中添加诱导大分子拥挤的聚合物和抗坏血酸,导致 ECM 中胶原蛋白、纤连蛋白和层粘连蛋白含量的差异。结果通过免疫染色进行验证。最后,对来自健康供体和骨髓增生异常综合征患者的 MSC 产生的 ECM 的比较 ToF-SIMS 分析显示,该新方法具有揭示 ECM 组成与疾病相关变化的潜力。