López-Alonso Javier, Eroles Mar, Janel Sébastien, Berardi Massimiliano, Pellequer Jean-Luc, Dupres Vincent, Lafont Frank, Rico Felix
Universite de Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019-UMR9017, CILL-Center of Infection and Immunity of Lille, Lille, F-59000, France.
Aix-Marseille Univ., CNRS, INSERM, LAI, Turing Centre for Living Systems, Marseille, 13009, France.
Open Res Eur. 2024 Jul 24;3:187. doi: 10.12688/openreseurope.16550.1. eCollection 2023.
Atomic force microscopy (AFM) is one of the main techniques used to characterize the mechanical properties of soft biological samples and biomaterials at the nanoscale. Despite efforts made by the AFM community to promote open-source data analysis tools, standardization continues to be a significant concern in a field that requires common analysis procedures. AFM-based mechanical measurements involve applying a controlled force to the sample and measure the resulting deformation in the so-called force-distance curves. These may include simple approach and retract or oscillatory cycles at various frequencies (microrheology). To extract quantitative parameters, such as the elastic modulus, from these measurements, AFM measurements are processed using data analysis software. Although open tools exist and allow obtaining the mechanical properties of the sample, most of them only include standard elastic models and do not allow the processing of microrheology data. In this work, we have developed an open-source software package (called PyFMLab, as of python force microscopy laboratory) capable of determining the viscoelastic properties of samples from both conventional force-distance curves and microrheology measurements.
PyFMLab has been written in Python, which provides an accessible syntax and sufficient computational efficiency. The software features were divided into separate, self-contained libraries to enhance code organization and modularity and to improve readability, maintainability, testability, and reusability. To validate PyFMLab, two AFM datasets, one composed of simple force curves and another including oscillatory measurements, were collected on HeLa cells.
The viscoelastic parameters obtained on the two datasets analysed using PyFMLab were validated against data processing proprietary software and against validated MATLAB routines developed before obtaining equivalent results.
Its open-source nature and versatility makes PyFMLab an open-source solution that paves the way for standardized viscoelastic characterization of biological samples from both force-distance curves and microrheology measurements.
原子力显微镜(AFM)是用于在纳米尺度表征软生物样品和生物材料力学性能的主要技术之一。尽管AFM领域的研究人员努力推广开源数据分析工具,但在这个需要通用分析程序的领域,标准化仍然是一个重大问题。基于AFM的力学测量包括对样品施加可控力,并在所谓的力-距离曲线中测量由此产生的变形。这些测量可能包括简单的接近和回缩操作,或在各种频率下的振荡循环(微观流变学)。为了从这些测量中提取诸如弹性模量等定量参数,需要使用数据分析软件对AFM测量数据进行处理。虽然存在一些开源工具可以获取样品的力学性能,但大多数工具仅包含标准弹性模型,不允许处理微观流变学数据。在这项工作中,我们开发了一个开源软件包(称为PyFMLab,即Python力显微镜实验室),它能够从传统的力-距离曲线和微观流变学测量中确定样品的粘弹性特性。
PyFMLab是用Python编写的,它提供了易理解的语法和足够的计算效率。该软件的功能被划分为独立的、自包含的库,以增强代码的组织性和模块化,并提高可读性、可维护性、可测试性和可重用性。为了验证PyFMLab,我们在HeLa细胞上收集了两个AFM数据集,一个由简单力曲线组成,另一个包括振荡测量。
使用PyFMLab分析的两个数据集所获得的粘弹性参数,通过与数据处理专有软件以及在获得等效结果之前开发的经过验证的MATLAB程序进行对比验证。
PyFMLab的开源性质和多功能性使其成为一种开源解决方案,为从力-距离曲线和微观流变学测量中对生物样品进行标准化粘弹性表征铺平了道路。