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Scientific Unit
The cytoskeletal protein vimentin is secreted under various physiological conditions. Extracellular vimentin exists primarily in two forms: attached to the outer cell surface and secreted into the extracellular space. While surface vimentin is involved in processes such as viral infections and cancer progression, secreted vimentin modulates inflammation through reduction of neutrophil infiltration, promotes bacterial elimination in activated macrophages, and supports axonal growth in astrocytes through activation of the IGF-1 receptor. This receptor is overexpressed in cancer cells, and its activation pathway has significant roles in general cellular functions. In this study, we investigated the functional role of extracellular vimentin in non-tumorigenic (MCF-10a) and cancer (MCF-7) cells through the evaluation of its effects on cell migration, proliferation, adhesion, and monolayer permeability. Upon treatment with extracellular recombinant vimentin, MCF-7 cells showed increased migration, proliferation, and adhesion, compared to MCF-10a cells. Further, MCF-7 monolayers showed reduced permeability, compared to MCF-10a monolayers. It has been shown that the receptor binding domain of SARS-CoV-2 spike protein can alter blood–brain barrier integrity. Surface vimentin also acts as a co-receptor between the SARS-CoV-2 spike protein and the cell-surface angiotensin-converting enzyme 2 receptor. Therefore, we also investigated the permeability of MCF-10a and MCF-7 monolayers upon treatment with extracellular recombinant vimentin, and its modulation of the SARS-CoV-2 receptor binding domain. These findings show that binding of extracellular recombinant vimentin to the cell surface enhances the permeability of both MCF-10a and MCF-7 monolayers. However, with SARS-CoV-2 receptor binding domain addition, this effect is lost with MCF-7 monolayers, as the extracellular vimentin binds directly to the viral domain. This defines an influence of extracellular vimentin in SARS-CoV-2 infections.
The cytoskeleton is a dynamic network of filaments comprising actin filaments, microtubules, and intermediate filaments in the cytoplasm of cells. Vimentin is an intermediate filament protein that plays a crucial role in adhesion, migration, and signalling. These functions of vimentin have broader implications on inflammation, wound healing, cell physiology, and immune response. Inside the cell, the vimentin network extends from the nucleus to the cell's periphery. However, vimentin gets out to the extracellular environment under the circumstances such as activation, stress, and senescence. However, the influence of such vimentin on general cellular functions and its characteristics is not well established. This thesis demonstrates that extracellular addition of vimentin enhances proliferation, adhesion and migration prominently in cancer cells (MCF-7), overexpressing insulin-like growth factor 1 (IGF1-R). Interestingly, in SARS-CoV-2 infection, the extracellular vimentin preincubation with the SARS-CoV-2 receptor binding domain protected the cancer (MCF-7) cell's monolayer integrity. Further investigation on the characteristics of extracellular vimentin found secretion of vimentin from the back of activated macrophages in the form of small fragments, enhancing phagocytosis and migration of activated macrophages. Collectively, this work demonstrates new insights into vimentin secretion and its implications on cellular functionality.
The rapid development of advanced microscopy techniques over recent decades has significantly increased the quality of imaging and our understanding of subcellular structures, such as the organization of the filaments of the cytoskeleton using fluorescence and electron microscopy. However, these recent improvements in imaging techniques have not been matched by similar development of techniques for computational analysis of the images of filament networks that can now be obtained. Hence, for a wide range of applications, reliable computational analysis of such two-dimensional methods remains challenging. Here, we present a new algorithm for tracing of filament networks. This software can extract many important parameters from grayscale images of filament networks, including the mesh hole size, and filament length and connectivity (also known as Coordination Number). In addition, the method allows sub-networks to be distinguished in two-dimensional images using intensity thresholding. We show that the algorithm can be used to analyze images of cytoskeleton networks obtained using different advanced microscopy methods. We have thus developed a new improved method for computational analysis of two-dimensional images of filamentous networks that has wide applications for existing imaging techniques. The algorithm is available as open-source software.
