Development of a facile method to compute collagen network pathological anisotropy using AFM imaging

Khattignavong, E. and Neshatian, M. and Vaez, M. and Guillermin, A. and . Tauer, J.T. and Odlyha, Marianne and Mittal, N. and Komarova, S.V. and Zahouani, H. and Bozec, L. (2023) Development of a facile method to compute collagen network pathological anisotropy using AFM imaging. Scientific Reports 13 (20173), ISSN 2045-2322.

Abstract

Type I collagen, a fundamental extracellular matrix (ECM) component, is pivotal in maintaining tissue integrity and strength. It is also the most prevalent fbrous biopolymer within the ECM, ubiquitous in mammalian organisms. This structural protein provides essential mechanical stability and resilience to various tissues, including tendons, ligaments, skin, bone, and dentin. Collagen has been structurally investigated for several decades, and variation to its ultrastructure by histology has been associated with several pathological conditions. The current study addresses a critical challenge in the feld of collagen research by providing a novel method for studying collagen fbril morphology at the nanoscale. It ofers a computational approach to quantifying collagen properties, enabling a deeper understanding of how collagen type I can be afected by pathological conditions. The application of Fast Fourier Transform (FFT) coupled with Atomic Force Microscope (AFM) imaging distinguishes not only healthy and diseased skin but also holds potential for automated diagnosis of connective tissue disorders (CTDs), contributing to both clinical diagnostics and fundamental research in this area. Here we studied the changes in the structural parameters of collagen fbrils in Ehlers Danlos Syndrome (EDS). We have used skin extracted from genetically mutant mice that exhibit EDS phenotype as our model system (Col1a1Jrt/+ mice). The collagen fbrils were analyzed by AFM based descriptive-structural parameters, coupled with a 2D Fast Fourier Transform(2D-FFT) approach that automated the analysis of AFM images. In addition, each sample was characterized based on its FFT and power spectral density. Our qualitative data showed morphological diferences in collagen fbril clarity (clearness of the collagen fbril edge with their neighbouring fbri), D-banding, orientation, and linearity. We have also demonstrated that FFT could be a new tool for distinguishing healthy from tissues with CTDs by measuring the disorganization of fbrils in the matrix. We have also employed FFT to reveal the orientations of the collagen fbrils, providing clinically relevant phenotypic information on their organization and anisotropy. The result of this study can be used to develop a new automated tool for better diagnosis of CTDs

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