School of Biosystems and Food Engineering, University College Dublin, Belfield, Dublin 4, Ireland.
UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.
ACS Appl Mater Interfaces. 2020 May 27;12(21):24466-24478. doi: 10.1021/acsami.0c04261. Epub 2020 May 15.
Biomaterials' surface properties elicit diverse cellular responses in biomedical and biotechnological applications. Predicting the cell behavior on a polymeric surface is an ongoing challenge due to its complexity. This work proposes a novel modeling methodology based on attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy. Spectra were collected on wetted polymeric surfaces to incorporate both surface chemistry and information on water-polymer interactions. Results showed that predictive models built with spectra from wetted surfaces ("wet spectra") performed much better than models built using spectra acquired from dry surfaces ("dry spectra"), suggesting that the water-polymer interaction is critically important to the prediction of subsequent cell behavior. The best model was seen to predict total area of focal adhesions with coefficient of determination for prediction () of 0.94 and root-mean-square errors of prediction (RMSEP) of 4.03 μm when tested on an independent experimental set. This work offers new insights into our understanding of cell-biomaterial interactions. The presence of carboxyl groups in polymers promoted larger adhesion areas, yet the formation of carbonyl-to-water interaction decreased adhesion areas. Surface wettability, which was related to the water-polymer interaction, was proven to highly influence cell adhesion. The good predictive ability opens new possibilities for high throughput monitoring of cell attachment on polymeric substrates.
生物材料的表面特性在生物医学和生物技术应用中引发了各种细胞反应。由于其复杂性,预测细胞在聚合物表面的行为仍然是一个挑战。本工作提出了一种基于衰减全反射-傅里叶变换红外(ATR-FTIR)光谱的新型建模方法。在润湿的聚合物表面上采集光谱,以结合表面化学和水-聚合物相互作用的信息。结果表明,基于润湿表面光谱(“湿光谱”)构建的预测模型比基于干燥表面光谱(“干光谱”)构建的模型表现要好得多,这表明水-聚合物相互作用对预测后续细胞行为至关重要。当在独立的实验数据集上进行测试时,最佳模型被证明可以以 0.94 的预测决定系数()预测焦点黏附总面积,且预测均方根误差(RMSEP)为 4.03 μm。这项工作为我们理解细胞-生物材料相互作用提供了新的见解。聚合物中存在羧基基团会促进更大的黏附面积,而羰基-水相互作用的形成会减少黏附面积。表面润湿性与水-聚合物相互作用有关,被证明会极大地影响细胞黏附。良好的预测能力为在聚合物基底上高通量监测细胞附着开辟了新的可能性。