Simple Display System of Mechanical Properties of Cells and Their Dispersion

The mechanical properties of cells are unique indicators of their states and functions. Though, it is difficult to recognize the degrees of mechanical properties, due to small size of the cell and broad distribution of the mechanical properties. Here, we developed a simple virtual reality system for presenting the mechanical properties of cells and their dispersion using a haptic device and a PC. This system simulates atomic force microscopy (AFM) nanoindentation experiments for floating cells in virtual environments. An operator can virtually position the AFM spherical probe over a round cell with the haptic handle on the PC monitor and feel the force interaction. The Young's modulus of mesenchymal stem cells and HEK293 cells in the floating state was measured by AFM. The distribution of the Young's modulus of these cells was broad, and the distribution complied with a log-normal pattern. To represent the mechanical properties together with the cell variance, we used log-normal distribution-dependent random number determined by the mode and variance values of the Young's modulus of these cells. The represented Young's modulus was determined for each touching event of the probe surface and the cell object, and the haptic device-generating force was calculated using a Hertz model corresponding to the indentation depth and the fixed Young's modulus value. Using this system, we can feel the mechanical properties and their dispersion in each cell type in real time. This system will help us not only recognize the degrees of mechanical properties of diverse cells but also share them with others

Alpha-mangostin inhibits the migration and invasion of A549 lung cancer cells

Several studies have indicated that α-mangostin exerts anti-metastasis and anti-subsistence effects on several types of cancer cells. Especially, the anti-metastatic effect of α-mangostin on cancer cells is a prospective function in cancer treatment. However, the metastasis process is complicated, and includes migration, invasion, intravasation, and extravasation; thus, the main target of anti-metastatic effect of α-mangostin is not known. In this study, we investigated the effects of α-mangostin on the invasion, subsistence, and migration of lung cancer cells under co-culture conditions with normal cells and regular mono-culture conditions. We found that α-mangostin killed the lung cancer and normal cells in a dose-dependent manner. Furthermore, the alteration in the surface mechanical properties of cells was examined by using atomic force microscopy. Although the α-mangostin concentrations of 5 and 10 µM did not affect the short-term cell viability, they considerably decreased the Young’s modulus of lung cancer cells implying a decline in cell surface actin cytoskeletal properties. Additionally, these concentrations of α-mangostin inhibited the migration of lung cancer cells. In co-culture conditions (cancer cells with normal cells), the invasive activities of cancer cells on normal cells were discernibly observed, and was inhibited after treatment with 5 and 10 µM of α-mangostin. Taken together, α-mangostin suppressed the subsistence of lung cancer cells and displayed anti-metastatic activities by inhibiting the migration and invasion, and reducing the actin cytoskeleton of cancer cells. Our findings suggest that α-mangostin could be a potential therapeutic agent for cancer treatment

In silico characterization of cell–cell interactions using a cellular automata model of cell culture

Abstract Background Cell proliferation is a key characteristic of eukaryotic cells. During cell proliferation, cells interact with each other. In this study, we developed a cellular automata model to estimate cell–cell interactions using experimentally obtained images of cultured cells. Results We used four types of cells; HeLa cells, human osteosarcoma (HOS) cells, rat mesenchymal stem cells (MSCs), and rat smooth muscle A7r5 cells. These cells were cultured and stained daily. The obtained cell images were binarized and clipped into squares containing about 104 cells. These cells showed characteristic cell proliferation patterns. The growth curves of these cells were generated from the cell proliferation images and we determined the doubling time of these cells from the growth curves. We developed a simple cellular automata system with an easily accessible graphical user interface. This system has five variable parameters, namely, initial cell number, doubling time, motility, cell–cell adhesion, and cell–cell contact inhibition (of proliferation). Within these parameters, we obtained initial cell numbers and doubling times experimentally. We set the motility at a constant value because the effect of the parameter for our simulation was restricted. Therefore, we simulated cell proliferation behavior with cell–cell adhesion and cell–cell contact inhibition as variables. By comparing growth curves and proliferation cell images, we succeeded in determining the cell–cell interaction properties of each cell. Simulated HeLa and HOS cells exhibited low cell–cell adhesion and weak cell–cell contact inhibition. Simulated MSCs exhibited high cell–cell adhesion and positive cell–cell contact inhibition. Simulated A7r5 cells exhibited low cell–cell adhesion and strong cell–cell contact inhibition. These simulated results correlated with the experimental growth curves and proliferation images. Conclusions Our simulation approach is an easy method for evaluating the cell–cell interaction properties of cells

Measurement of biomolecular diffusion in extracellular matrix condensed by fibroblasts using fluorescence correlation spectroscopy.

The extracellular matrix (ECM) comprises the heterogeneous environment outside of cells in a biological system. The ECM is dynamically organized and regulated, and many biomolecules secreted from cells diffuse throughout the ECM, regulating a variety of cellular processes. Therefore, investigation of the diffusive behaviors of biomolecules in the extracellular environment is critical. In this study, we investigated the diffusion coefficients of biomolecules of various sizes, measuring from 1 to 10 nm in radius, by fluorescence correlation spectroscopy in contracted collagen gel caused by fibroblasts, a traditional culture model of dynamic rearrangement of collagen fibers. The diffusion coefficients of the biomolecules in control collagen gel without cells decreased slightly as compared to those in solution, while the diffusion coefficients of biomolecules in the contracted gel at the cell vicinity decreased dramatically. Additionally, the diffusion coefficients of biomolecules were inversely correlated with molecular radius. In collagen gels populated with fibroblasts, the diffusion coefficient at the cell vicinity clearly decreased in the first 24 h of culture. Furthermore, molecular diffusion was greatly restricted, with a central focus on the populated cells. By using the obtained diffusion coefficients of biomolecules, we calculated the collagen fiber condensation ratio by fibroblasts in the cell vicinity at 3 days of culture to represent a 52-fold concentration. Thus, biomolecular diffusion is restricted in the vicinity of the cells where collagen fibers are highly condensed

Osteogenic cells form mineralized particles, a few μm in size, in a 3D collagen gel culture

Osteogenic cells form mineralized matrices in vitro, as well as in vivo. The formation and shape of the mineralized matrices are highly regulated by the cells. In vitro formation of mineralized matrices by osteogenic cells can be a model for in vivo osteogenesis. In this study, using a three-dimensional (3D) collagen gel culture system, we developed a new in vitro model for the formation of mineralized particles, a few µm in size, by the osteogenic cells. Human osteosarcoma (HOS) cells formed spherical mineralized matrices (about 12 µm) at approximately 7 days when cultured with β-glycerophosphate (β-GP)-containing culture media on 2D tissue culture plates. Alternately, when they were cultured in a 3D collagen gel containing β-GP, they formed mineralized particles with about 1.7 µm in the gel at approximately 3 days. Calcium precipitation in the gel was evaluated by measuring the gel turbidity. This type of mineralization of HOS cells, which formed mineralized particles inside the gel, was also observed in a peptide-based hydrogel culture. The mineralized particles were completely diminished by inhibiting the activity of Pit-1, phosphate cotransporter, of the HOS cells. When mouse osteoblast-like MC3T3-E1 cells, which form large and flat mineralized matrices in 2D osteogenic conditions at approximately 3 weeks of culture, were cultured in a 3D collagen gel, they also formed mineralized particles in the gel, similar to those in HOS cells, at approximately 18 days. Thus, osteogenic cells cultured in the 3D collagen gel form mineralized particles over a shorter period, and the mineralization could be easily determined by gel turbidity. This 3D gel culture system of osteogenic cells acts as a useful model for cells forming particle-type mineralized matrices, and we assume that the mineralized particles in the 3D hydrogel are calcospherulites, which are derived from matrix vesicles secreted by osteogenic cells

Conformation of Amyloid Fibrils of β2-Microglobulin Probed by Tryptophan Mutagenesis

This research was originally published in the Journal of Biological Chemistry. Miho Kihara, Eri Chatani, Kentaro Iwata, Kaori Yamamoto, Takanori Matsuura, Atsushi Nakagawa, Hironobu Naiki and Yuji Goto. Conformation of Amyloid Fibrils of β2-Microglobulin Probed by Tryptophan Mutagenesis. J. Biol. Chem. 2006; 281, 31061–31069. © the American Society for Biochemistry and Molecular Biolog

Schematic diagram of probe diffusion in the contracted collagen gel.

<p>Collagen fibers are well condensed in the area surrounding the cell due to cellular activity. Biomolecules diffuse throughout the collagen fiber-containing space, in which the concentration of the collagen fibers varies from region to region. Diffusion behaviors of the biomolecules are probably affected by the local concentration of the collagen fibers. By measuring the diffusion behaviors of the biomolecules locally, we can develop a better understanding of the behaviors of these molecules in the heterogeneous ECM and of the physical environment surrounding the cells.</p

Fluorescent micrographs of the condensation process of collagen fibrils by populated fibroblasts.

<p>TIG-1 cells were cultured in FITC-labeled collagen gels (0.7 mg/mL). The populated cells were seen as completely black objects (arrowheads). Each time is shown at the upper left of the corresponding micrograph. FITC-labeled collagen fibers were condensed into the area surrounding the cell. Bar: 50 µm.</p