PyFMLab: Open-source software for atomic force microscopy microrheology data analysis

Abstract

Background 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. Methods 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. Results 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. Conclusions 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.

Nanoactuator for Neuronal Optoporation

“…The breakthrough forces were recorded from 500 to 700 curves from each sample, obtained by acquiring at least five grids of 10 × 10 points in a 15 × 15 μm square. The breakthrough force, corresponding to a sudden penetration of the AFM tip through the membrane, i.e., a local maximum of the force jump on the force–distance curve, was analyzed using a Python code based on PyFMLab software . The breakthrough force was determined by localizing the local maximum in the force–distance curve.…”

“…The breakthrough force, corresponding to a sudden penetration of the AFM tip through the membrane, i.e., a local maximum of the force jump on the force−distance curve, was analyzed using a Python code based on PyFMLab software. 63 The breakthrough force was determined by localizing the local maximum in the force−distance curve. After obtaining the breakthrough force from each curve, a histogram of the distribution of the breakthrough forces was obtained and fitted to a Gaussian distribution to obtain the mean and standard deviation.…”

Atomic Force Microscopy for the Study of Cell Mechanics in Pharmaceutics

“…Gwyddion can analyze force–distance curves, but only for a limited number of models and file types. Python programs with Graphical User Interfaces such as PyJibe [ 52 ], Nanite [ 53 ] (supporting machine learning), and PyFMLab [ 54 ] (supporting rheology) have been published, but unfortunately not as stand-alone software, thus making them inaccessible to researchers without knowledge of Python.…”