Magennis E P, Hook A L, Davies M C, Alexander C, Williams P, Alexander M R
Laboratory of Biophysics and Surface Analysis, School of Pharmacy, University of Nottingham, Nottingham, UK.
Drug Delivery and Tissue Engineering, School of Pharmacy, University of Nottingham, Nottingham, UK.
Acta Biomater. 2016 Apr 1;34:84-92. doi: 10.1016/j.actbio.2015.11.008. Epub 2015 Nov 28.
Controlling the colonisation of materials by microorganisms is important in a wide range of industries and clinical settings. To date, the underlying mechanisms that govern the interactions of bacteria with material surfaces remain poorly understood, limiting the ab initio design and engineering of biomaterials to control bacterial attachment. Combinatorial approaches involving high-throughput screening have emerged as key tools for identifying materials to control bacterial attachment. The hundreds of different materials assessed using these methods can be carried out with the aid of computational modelling. This approach can develop an understanding of the rules used to predict bacterial attachment to surfaces of non-toxic synthetic materials. Here we outline our view on the state of this field and the challenges and opportunities in this area for the coming years.
This opinion article on high throughput screening methods reflects one aspect of how the field of biomaterials research has developed and progressed. The piece takes the reader through key developments in biomaterials discovery, particularly focusing on need to reduce bacterial colonisation of surfaces. Such bacterial resistant surfaces are increasingly required in this age of antibiotic resistance. The influence and origin of high-throughput methods are discussed with insights into the future of biomaterials development where computational methods may drive materials development into new fertile areas of discovery. New biomaterials will exhibit responsiveness to adapt to the biological environment and promote better integration and reduced rejection or infection.
在众多行业和临床环境中,控制微生物在材料上的定殖非常重要。迄今为止,人们对细菌与材料表面相互作用的潜在机制仍知之甚少,这限制了用于控制细菌附着的生物材料的从头设计和工程化。涉及高通量筛选的组合方法已成为识别控制细菌附着材料的关键工具。借助计算建模可以对使用这些方法评估的数百种不同材料进行研究。这种方法有助于深入了解预测细菌附着在无毒合成材料表面的规则。在此,我们概述了我们对该领域现状以及未来几年该领域面临的挑战和机遇的看法。
这篇关于高通量筛选方法的观点文章反映了生物材料研究领域的一个发展和进步方面。文章带领读者了解生物材料发现的关键进展,特别关注减少表面细菌定殖的需求。在这个抗生素耐药性时代,对这种抗细菌表面的需求日益增加。文中讨论了高通量方法的影响和起源,并对生物材料发展的未来进行了展望,其中计算方法可能会推动材料开发进入新的富有成果的发现领域。新型生物材料将表现出响应能力,以适应生物环境并促进更好的整合,减少排斥或感染。