Modelling the combined effect of surface roughness and topography on bacterial attachment
Modelling the combined effect of surface roughness and topography on bacterial attachment
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DOI：
10.1016/j.jmst.2021.01.011
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发表时间：
2021-08
影响因子：
10.9
通讯作者：
S. Chinnaraj;P. G. Jayathilake;Jack Dawson;Y. Ammar;J. Portoles;N. Jakubovics;Jinju Chen
中科院分区：
文献类型：
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作者：
S. Chinnaraj;P. G. Jayathilake;Jack Dawson;Y. Ammar;J. Portoles;N. Jakubovics;Jinju Chen
细菌附着是一个复杂的过程，受流动条件、施加的应力以及支持材料和细胞的表面性质和结构的影响。本文报道了格氏链球菌（Streptococcus gordonii，S. gordonii），牙菌斑的一个重要的早期殖民者，对不锈钢（SS）样品的研究已在这项工作中报道。本研究的主要目的是确定SS样品的表面粗糙度和拓扑结构对细菌细胞初始附着的影响（如果有的话）。gordonii。选择这种材料和细菌是因为它们与牙种植体和牙种植体感染相关。在细菌附着之前，表面受到界面环境（例如来自口腔的唾液膜）的调节。出于这个原因，还研究了细胞附着到用唾液预包被的SS样品。通过实施扩展Derjaguin朗道Verwey和Overbeek（XDLVO）理论，结合对流扩散反应方程和表面粗糙度信息，开发了一个计算模型，以帮助更好地理解细胞粘附的物理过程。表面粗糙度建模重建的表面形貌使用来自原子力显微镜（AFM）测量的统计参数。使用这个计算模型，在静态和流动的流体环境中，粗糙度和表面图案对细菌附着的影响进行了定量研究。结果表明，粗糙的表面（在亚微米尺度内）通常会增加静态流体条件下的细菌附着，这与实验测量结果在数量上一致。在流动条件下，计算流体动力学（CFD）模拟预测通道内的对流扩散减少，这将减少细菌附着。当与表面粗糙度效应相结合时，计算模型还预测，在这项工作中讨论的表面形貌产生了总体细菌附着的轻微下降。这表明表面图案的附着防止效果优于有利于粘附的亚微米级表面粗糙度;因此，产生粘附细胞的净减少。这在定性上与这里报道的实验观察一致，并且在测量误差内定量地匹配低流速的实验观察。
Bacterial attachment is a complex process affected by flow conditions, imparted stresses, and the surface properties and structure of both the supporting material and the cell. Experiments on the initial attachment of cells of the bacteriumStreptococcus gordonii(S. gordonii), an important early coloniser of dental plaque, to samples of stainless steel (SS) have been reported in this work. The primary aim motivating this study was to establish what affect, if any, the surface roughness and topology of samples of SS would have on the initial attachment of cells of the bacteriumS. gordonii. This material and bacterium were chosen by virtue of their relevance to dental implants and dental implant infections. Prior to bacterial attachment, surfaces become conditioned by the interfacing environment (salivary pellicle from the oral cavity for instance). For this reason, cell attachment to samples of SS pre-coated with saliva was also studied. By implementing the Extended Derjaguin Landau Verwey and Overbeek (XDLVO) theory coupled with convection-diffusion-reaction equations and the surface roughness information, a computational model was developed to help better understand the physics of cell adhesion. Surface roughness was modelled by reconstructing the surface topography using statistical parameters derived from atomic force microscopy (AFM) measurements. Using this computational model, the effects of roughness and surface patterns on bacterial attachment were examined quantitatively in both static and flowing fluid environments. The results have shown that rougher surfaces (within the sub-microscale) generally increase bacterial attachment in static fluid conditions which quantitatively agrees with experimental measurements. Under flow conditions, computational fluid dynamics (CFD) simulations predicted reduced convection-diffusion inside the channel which would act to decrease bacterial attachment. When combined with surface roughness effects, the computational model also predicted that the surface topographies discussed within this work produced a slight decrease in overall bacterial attachment. This would suggest that the attachment-preventing effects of surface patterns dominate over the adhesion-favourable sub-microscale surface roughness; hence, producing a net reduction in adhered cells. This qualitatively agreed with experimental observations reported here and quantitatively matched experimental observations for low flow rates within measurement error.