Dataset Information

Time-lapse contact microscopy of cell cultures based on non-coherent illumination.

ABSTRACT: Video microscopy offers outstanding capabilities to investigate the dynamics of biological and pathological mechanisms in optimal culture conditions. Contact imaging is one of the simplest imaging architectures to digitally record images of cells due to the absence of any objective between the sample and the image sensor. However, in the framework of in-line holography, other optical components, e.g., an optical filter or a pinhole, are placed underneath the light source in order to illuminate the cells with a coherent or quasi-coherent incident light. In this study, we demonstrate that contact imaging with an incident light of both limited temporal and spatial coherences can be achieved with sufficiently high quality for most applications in cell biology, including monitoring of cell sedimentation, rolling, adhesion, spreading, proliferation, motility, death and detachment. Patterns of cells were recorded at various distances between 0 and 1000 ?m from the pixel array of the image sensors. Cells in suspension, just deposited or at mitosis focalise light into photonic nanojets which can be visualised by contact imaging. Light refraction by cells significantly varies during the adhesion process, the cell cycle and among the cell population in connection with every modification in the tridimensional morphology of a cell.

SUBMITTER: Gabriel M

PROVIDER: S-EPMC4602279 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Time-lapse contact microscopy of cell cultures based on non-coherent illumination.

Gabriel Marion M Balle Dorothée D Bigault Stéphanie S Pornin Cyrille C Gétin Stéphane S Perraut François F Block Marc R MR Chatelain François F Picollet-D'hahan Nathalie N Gidrol Xavier X Haguet Vincent V

Scientific reports 20151013

Video microscopy offers outstanding capabilities to investigate the dynamics of biological and pathological mechanisms in optimal culture conditions. Contact imaging is one of the simplest imaging architectures to digitally record images of cells due to the absence of any objective between the sample and the image sensor. However, in the framework of in-line holography, other optical components, e.g., an optical filter or a pinhole, are placed underneath the light source in order to illuminate t ...[more]

PMID: 26459014

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Project description:Time-lapse imaging of cell colonies in microfluidic chambers provides time series of bioimages, i.e., biomovies. They show the behavior of cells over time under controlled conditions. One of the main remaining bottlenecks in this area of research is the analysis of experimental data and the extraction of cell growth characteristics, such as lineage information. The extraction of the cell line by human observers is time-consuming and error-prone. Previously proposed methods often fail because of their reliance on the accurate detection of a single cell, which is not possible for high density, high diversity of cell shapes and numbers, and high-resolution images with high noise. Our task is to characterize subpopulations in biomovies. In order to shift the analysis of the data from individual cell level to cellular groups with similar fluorescence or even subpopulations, we propose to represent the cells by two new abstractions: the particle and the patch. We use a three-step framework: preprocessing, particle tracking, and construction of the patch lineage. First, preprocessing improves the signal-to-noise ratio and spatially aligns the biomovie frames. Second, cell sampling is performed by assuming particles, which represent a part of a cell, cell or group of contiguous cells in space. Particle analysis includes the following: particle tracking, trajectory linking, filtering, and color information, respectively. Particle tracking consists of following the spatiotemporal position of a particle and gives rise to coherent particle trajectories over time. Typical tracking problems may occur (e.g., appearance or disappearance of cells, spurious artifacts). They are effectively processed using trajectory linking and filtering. Third, the construction of the patch lineage consists in joining particle trajectories that share common attributes (i.e., proximity and fluorescence intensity) and feature common ancestry. This step is based on patch finding, patching trajectory propagation, patch splitting, and patch merging. The main idea is to group together the trajectories of particles in order to gain spatial coherence. The final result of CYCASP is the complete graph of the patch lineage. Finally, the graph encodes the temporal and spatial coherence of the development of cellular colonies. We present results showing a computation time of less than 5?min for biomovies and simulated films. The method, presented here, allowed for the separation of colonies into subpopulations and allowed us to interpret the growth of colonies in a timely manner.

Dataset Information

Time-lapse contact microscopy of cell cultures based on non-coherent illumination.

Publications

Time-lapse contact microscopy of cell cultures based on non-coherent illumination.

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