MERLN Institute, Maastricht University, Maastricht, 6229 ER, The Netherlands.
Department of Biomedical Engineering and Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, 5600 MB, The Netherlands.
Adv Mater. 2021 Aug;33(31):e2102084. doi: 10.1002/adma.202102084. Epub 2021 Jun 24.
Surface topography is a tool to endow biomaterials with bioactive properties. However, the large number of possible designs makes it challenging to find the optimal surface structure to induce a specific cell response. The TopoChip platform is currently the largest collection of topographies with 2176 in silico designed microtopographies. Still, it is exploring only a small part of the design space due to design algorithm limitations and the surface engineering strategy. Inspired by the diversity of natural surfaces, it is assessed as to what extent the topographical design space and consequently the resulting cellular responses can be expanded using natural surfaces. To this end, 26 plant and insect surfaces are replicated in polystyrene and their surface properties are quantified using white light interferometry. Through machine-learning algorithms, it is demonstrated that natural surfaces extend the design space of the TopoChip, which coincides with distinct morphological and focal adhesion profiles in mesenchymal stem cells (MSCs) and Pseudomonas aeruginosa colonization. Furthermore, differentiation experiments reveal the strong potential of the holy lotus to improve osteogenesis in MSCs. In the future, the design algorithms will be trained with the results obtained by natural surface imprint experiments to explore the bioactive properties of novel surface topographies.
表面形貌是赋予生物材料生物活性的一种手段。然而,由于可能的设计数量众多,因此很难找到能够诱导特定细胞反应的最佳表面结构。目前,TopoChip 平台是具有 2176 种计算机设计微形貌的最大形貌集合。但是,由于设计算法的限制和表面工程策略,它仍在探索设计空间的一小部分。受自然表面多样性的启发,评估了使用自然表面在多大程度上可以扩展形貌设计空间以及由此产生的细胞反应。为此,在聚苯乙烯中复制了 26 种植物和昆虫表面,并使用白光干涉法对其表面性能进行了量化。通过机器学习算法,证明了自然表面扩展了 TopoChip 的设计空间,这与间充质干细胞 (MSCs) 和铜绿假单胞菌定植中的形态和黏附斑分布明显不同。此外,分化实验表明,圣莲具有改善间充质干细胞成骨的巨大潜力。将来,将使用自然表面压印实验获得的结果来训练设计算法,以探索新型表面形貌的生物活性特性。