ABSTRACT
BACKGROUND: In vitro wound healing assays are experimental models commonly used to analyze cell behavior during the migration process. A new approach is proposed for the quantification of cell motility based on an optical flow method. METHODS: We assumed that cell-population dynamics can be defined by an a priori affine-motion model. Identified model parameters are used as motion descriptors quantifying both elementary and complex cell movements, either at the wound margins or within the cell monolayer. RESULTS: When compared with the estimation of cell motility calculated from wound area temporal variation, it allows a more detailed and precise characterization of cell population movements. Comparative analysis of normal and cancerous cell lines revealed that typical measured velocities were about 2 microm/h and 7 microm/h for L929 and HeLa cells, respectively, at the beginning of the wound closure. The quantification of the effect of Hoechst 33342 on cell dynamics showed a similar behavior for control and stained cells within 20 h after wound scratching, but then a decreased velocity of stained cells. CONCLUSIONS: The results demonstrate that this approach can be used to gain new insights into the dynamic changes induced by the extracellular environment and by anticancer drugs.
Subject(s)
Cell Movement/physiology , Flow Cytometry/methods , Wound Healing/physiology , Animals , Benzimidazoles , Cell Size/physiology , DNA/analysis , Fibroblasts/cytology , Fluorescent Dyes , HeLa Cells , Humans , In Vitro Techniques , Microscopy, Video , Optics and Photonics , Rats , RhabdomyosarcomaABSTRACT
This paper deals with the spatio-temporal analysis of two-dimensional deformation and motion of cells from time series of digitized video images. A parametric motion approach based on an affine model has been proposed for the quantitative characterization of cellular movements in different experimental areas of cellular biology including spontaneous cell deformation, cell mitosis, individual cell migration and collective migration of cell populations as cell monolayer. The accuracy and robustness of the affine model parameter estimation, which is based on a multiresolution algorithm, has been established from synthesized image sequences. A major interest of our approach is to follow with time the evolution of a few number of parameters characteristic of cellular motion and deformation. From the time-varying eigenvalues of the affine model square matrix, a precise quantification of the cell pseudopodial activity, as well as of cell division has been performed. For migrating cells, the motion quantification confirms that cell body deformation has a leading role in controlling nucleus displacement, the nucleus itself undergoing a larger rotational motion. At the cell population level, image motion analysis of in vitro wound healing experiments quantifies the heterogeneous cell populations dynamics.
Subject(s)
Cell Movement , Fibroblasts/cytology , Image Processing, Computer-Assisted , Linear Models , Models, Biological , Algorithms , Animals , Cell Division/physiology , Cell Nucleus/physiology , Mice , Motion , Wound Healing/physiologyABSTRACT
This paper presents a new model for the segmentation and analysis of living cells. A multi-agent model has been developed for this application. It is based on a generic agent model, which is composed of different behaviors: perception, interaction and reproduction. The agent is further specialized to accomplish a specific goal. Different goals are defined from the different components of the cell images. The specialization specifies the parameters of the behaviors for the achievement of the agent's goal. From these goal-oriented agents, a society is defined, and it evolves dynamically as the agents are created and deleted. An internal manager is integrated in the agent to control the behavior's execution. It makes use of an event-driven scheme to manage the behavior priorities. The present design is mainly oriented toward image segmentation, however, it includes some features on tracking and motion analysis.
Subject(s)
Artificial Intelligence , Fibroblasts/cytology , HeLa Cells/cytology , Image Processing, Computer-Assisted/methods , Animals , Cell Membrane/ultrastructure , Cell Movement , Cell Nucleus/ultrastructure , Cytoplasm/ultrastructure , Database Management Systems , Humans , Image Interpretation, Computer-Assisted , Mice , Microscopy, Fluorescence , Microscopy, Phase-Contrast , Pseudopodia/ultrastructure , SoftwareABSTRACT
The organization of eukaryotic chromatin is not static but changes as a function of cell status during processes such as proliferation, differentiation, and migration. DNA quantification has not been used extensively to investigate chromatin dynamics in combination with cellular migration. In this context, an optimized DNA-specific, nonperturbant method has been developed for studying chromatin organization, using the fluorescent vital bisbenzimidazole probe Hoechst 33342: this property has been described by Hamori et al. (1980). Computer-assisted image analysis was used to follow migratory activity and chromatin organization of L929 fibroblasts during in vitro wound healing. Cell movements were analyzed using an optical flow technique, which consists in the calculation of the velocity field of cells and nuclear movements in the frame. This system allows the correlation of cell migration and position in the cell cycle. It makes it possible to study chromatin dynamics using a quantitative analysis of nuclear differentiation reorganization (nuclear texture) and to correlate this with migration characteristics. The present system would be of interest for studying cell-extracellular matrix interactions using differing substrates, and also the migratory response to chemotactic factors. Such a model is a prerequisite for gaining better understanding of drug action.