Sreenivasappa, Harini Bytaraya (2009-12). Raster Image Correlation Spectroscopy [RICS] Analysis of HeLa cells. Master's Thesis. Thesis uri icon

abstract

  • The objective of the project is to use the RICS analysis technique in complement with confocal microscopy to determine the diffusion coefficient of the selectively labeled green fluorescent protein (GFP), GFP-EGFR and GFP-p53 in cervical cancer cells. This is a collaboration work with MD Anderson Cancer Center. The application of the study is to lay the foundation for further study in understanding the cell metabolism, subcellular morphologic and dynamic biochemical processes to aid in the diagnosis and to potentially screen cancers. Fluorescence microscopy techniques have been developed for the study of cellular processes and molecular signal pathway. However, the spatial resolution to distinguish and resolve the interactions of single molecular complexes or molecule in cells is limited by the wavelength. Hence, indirect image correlation methods complementary to the imaging techniques were developed to obtain the dynamic information within the cell. RICS is one such mathematical image processing method to determine the dynamics of the cell. HeLa cells are transfected with GFP to highlight the protein of interest. These samples were imaged with confocal microscope, Olympus FV1000 with a 60 x 1.2 NA water objective in the pseudo photon counting mode with an excitation of 488 nm argon ion laser. About 100 frames of scan area 256x256 pixels were collected from each sample at scan speed of 12.5 seconds per pixel. The stacks of images were processed with SimFCS software. The images were subjected to immobile subtraction algorithm to remove the immobile features. Consequently, each frame in the stack is subjected to 2D-correlation; then, the average 2D-spatial correlation is calculated. This 2D-spatial correlated data constitutes as RICS data which is then displayed and analyzed by fitting it to specific models. This generates a spatial temporal map of the molecular dynamics of fluorescently labeled probes within the cell. In summary, we apply RICS techniques based on correlation spectroscopy to the image data and quantify diffusion coefficient of protein of interest in cancerous cells with different treatments. This is expected to better understand cellular dynamics of cancerous cells and build better diagnostic biosensor devices for early screening.
  • The objective of the project is to use the RICS analysis technique in complement with

    confocal microscopy to determine the diffusion coefficient of the selectively labeled

    green fluorescent protein (GFP), GFP-EGFR and GFP-p53 in cervical cancer cells. This

    is a collaboration work with MD Anderson Cancer Center. The application of the study

    is to lay the foundation for further study in understanding the cell metabolism, subcellular

    morphologic and dynamic biochemical processes to aid in the diagnosis and to

    potentially screen cancers.

    Fluorescence microscopy techniques have been developed for the study of cellular

    processes and molecular signal pathway. However, the spatial resolution to distinguish

    and resolve the interactions of single molecular complexes or molecule in cells is limited

    by the wavelength. Hence, indirect image correlation methods complementary to the

    imaging techniques were developed to obtain the dynamic information within the cell.

    RICS is one such mathematical image processing method to determine the dynamics of

    the cell.

    HeLa cells are transfected with GFP to highlight the protein of interest. These samples

    were imaged with confocal microscope, Olympus FV1000 with a 60 x 1.2 NA water

    objective in the pseudo photon counting mode with an excitation of 488 nm argon ion

    laser. About 100 frames of scan area 256x256 pixels were collected from each sample at

    scan speed of 12.5 seconds per pixel. The stacks of images were processed with SimFCS

    software. The images were subjected to immobile subtraction algorithm to remove the

    immobile features. Consequently, each frame in the stack is subjected to 2D-correlation;

    then, the average 2D-spatial correlation is calculated. This 2D-spatial correlated data

    constitutes as RICS data which is then displayed and analyzed by fitting it to specific

    models. This generates a spatial temporal map of the molecular dynamics of

    fluorescently labeled probes within the cell.

    In summary, we apply RICS techniques based on correlation spectroscopy to the image

    data and quantify diffusion coefficient of protein of interest in cancerous cells with

    different treatments. This is expected to better understand cellular dynamics of

    cancerous cells and build better diagnostic biosensor devices for early screening.

publication date

  • December 2009