Automated multi-sample acquisition and analysis using atomic force microscopy for biomedical applications.,PLOS ONE

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Automated multi-sample acquisition and analysis using atomic force microscopy for biomedical applications.
PLOS ONE ( IF 2.9 ) Pub Date : 2019-03-15 , DOI: 10.1371/journal.pone.0213853
Antoine Dujardin _{1,

2} , Peter De Wolf ₂ , Frank Lafont ₁ , Vincent Dupres ₁

Affiliation

In the last 20 years, atomic force microscopy (AFM) has emerged as a ubiquitous technique in biological research, allowing the analysis of biological samples under near-physiological conditions from single molecules to living cells. Despite its growing use, the low process throughput remains a major drawback. Here, we propose a solution validated on a device allowing a fully automated, multi-sample analysis. Our approach is mainly designed to study samples in fluid and biological cells. As a proof of concept, we demonstrate its feasibility applied to detect and scan both fixed and living bacteria before completion of data processing. The effect of two distinct treatments (i.e. gentamicin and heating) is then evidenced on physical parameters of fixed Yersinia pseudotuberculosis bacteria. The multi-sample analysis presented allows an increase in the number of scanned samples while limiting the user's input. Importantly, cantilever cleaning and control steps are performed regularly-as part of the automated process-to ensure consistent scanning quality. We discuss how such an approach is paving the way to AFM developments in medical and clinical fields, in which statistical significance of results is a prerequisite.

中文翻译：

使用原子力显微镜自动进行多样本采集和分析，用于生物医学应用。

在过去的20年中，原子力显微镜（AFM）已经成为生物学研究中的一种普遍技术，可以在接近生理条件下分析从单个分子到活细胞的生物样品。尽管其用途越来越广泛，但是低的处理产量仍然是主要的缺点。在这里，我们提出了一种在设备上经过验证的解决方案，该解决方案可以进行全自动的多样本分析。我们的方法主要用于研究液体和生物细胞中的样品。作为概念验证，我们证明了其在完成数据处理之前用于检测和扫描固定细菌和活细菌的可行性。然后在固定的耶尔森氏菌假结核细菌的物理参数上证明了两种不同的处理方法（即庆大霉素和加热）。呈现的多样本分析允许增加扫描样本的数量，同时限制用户的输入。重要的是，作为自动化过程的一部分，需要定期执行悬臂清洁和控制步骤，以确保一致的扫描质量。我们讨论了这种方法如何为医学和临床领域中AFM的发展铺平道路，其中结果的统计意义是前提。

更新日期：2019-03-17

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