RÉSUMÉ
SUMMARY: Spatial omics technologies are increasingly leveraged to characterize how disease disrupts tissue organization and cellular niches. While multiple methods to analyze spatial variation within a sample have been published, statistical and computational approaches to compare cell spatial organization across samples or conditions are mostly lacking. We present GraphCompass, a comprehensive set of omics-adapted graph analysis methods to quantitatively evaluate and compare the spatial arrangement of cells in samples representing diverse biological conditions. GraphCompass builds upon the Squidpy spatial omics toolbox and encompasses various statistical approaches to perform cross-condition analyses at the level of individual cell types, niches, and samples. Additionally, GraphCompass provides custom visualization functions that enable effective communication of results. We demonstrate how GraphCompass can be used to address key biological questions, such as how cellular organization and tissue architecture differ across various disease states and which spatial patterns correlate with a given pathological condition. GraphCompass can be applied to various popular omics techniques, including, but not limited to, spatial proteomics (e.g. MIBI-TOF), spot-based transcriptomics (e.g. 10× Genomics Visium), and single-cell resolved transcriptomics (e.g. Stereo-seq). In this work, we showcase the capabilities of GraphCompass through its application to three different studies that may also serve as benchmark datasets for further method development. With its easy-to-use implementation, extensive documentation, and comprehensive tutorials, GraphCompass is accessible to biologists with varying levels of computational expertise. By facilitating comparative analyses of cell spatial organization, GraphCompass promises to be a valuable asset in advancing our understanding of tissue function in health and disease. .
Sujet(s)
Logiciel , Humains , Protéomique/méthodes , Biologie informatique/méthodes , Génomique/méthodes , Animaux , Transcriptome , Analyse sur cellule unique/méthodesRÉSUMÉ
Intermediate filaments are a major structural element in the cytoskeleton of animal cells that mechanically integrate other cytoskeletal components and absorb externally applied stress. Their role is likely to be linked to their complex molecular architecture which is the product of a multi-step assembly pathway. Intermediate filaments form tetrameric subunits which assemble in the presence of monovalent salts to form unit length filaments that subsequently elongate by end-to-end annealing. The present work characterizes this complex assembly process using reconstituted vimentin intermediate filaments with monovalent salts as an assembly trigger. A multi-scale approach is used, comprising static light scattering, dynamic light scattering and quantitative scanning transmission electron microscopy (STEM) mass measurements. Light scattering reveals the radius of gyration (Rg), molecular weight (Mw) and diffusion coefficient (D) of the assembling filaments as a function of time and salt concentration (cS) for the given protein concentration of 0.07 g L-1. At low cS (10 mM KCl) no lateral or elongational growth is observed, whereas at cS = 50-200 mM, the hydrodynamic cross-sectional radius and the elongation rate increases with cS. Rgversus Mw plots suggest that the mass per unit length increases with increasing salt content, which is confirmed by STEM mass measurements. A kinetic model based on rate equations for a two step process is able to accurately describe the variation of mass, length and diffusion coefficient of the filaments with time and provides a consistent description of the elongation accelerated by increasing cS.