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Counting of Total Fluorescence in a Cell
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In this experiment, image processing techniques are to applied to count total fluorescence in a cell.

 

Objective:

 

To count the total fluorescence per cell using image analysis software.

 

Theory:

 

Image analysis has become a powerful tool for the quantification of histological detections mainly in the medical sciences. Biologists are increasingly interested in using the image analysis protocols to convert the microscopic images into more relatively quantitative measurements. Advances in the cell biology techniques reveal that fluorescence images are critical data for the cell analysis, and thus increasingly used in quantitative assays. Fluorescence microscopy helps in providing a more spatial and temporal measurements of the concentration of multiple molecules in the cells, tissues and in whole animals. The use of specifically labelled molecules such as genetically encoded fluorescent proteins helps to transform the fluorescent microscopy techniques from a simple localization test to quantitative data for further functional analysis of the cell. Image analysis software thus becomes an important tool for most biologists to evaluate the microscopic fluorescent images into more reliable quantitative manner. In this lab, image analysis techniques are applied to count the total fluorescence in a stained cell using software ImageJ, which is basically a public domain Java image processing program that was developed at the National Institute of Health, USA. The basic steps involved in counting of fluorescent cells are listed below:

 

  1. The fluorescently stained cell to be analyzed is imported into the software.
  2. RGB image (Red Green Blue image) is then converted to 8 bit to make the quantification more reliable.
  3. The basic measurements to analyze the cell such as Area, Mean Gray Value and Integrated Density are then adjusted using the software menu bar.
  4. A specified area for the fluorescent stained cell for analysis is selected using free hand selection. This helps to quantify a specific region of the imported cell for fluorescence. The measurements are then analyzed.
  5. A rectangular section near the analyzed cell that is the non – fluorescent part of the image is selected which can be used to minimize the maximum errors in the fluorescent counting of a cell.
  6. From the results, the total fluorescence per cell is then analyzed using Excel sheet.

     

Immunofluorescence Technique

 

Immunofluorescence is a basic laboratory technique, based on an antigen antibody reaction, where the antibodies are labelled with florescent dyes known as fluorochromes. They can absorb the ultra violet rays and emit visible light and the process is termed as fluorescence. Antibodies are chemically conjugated with dyes such as fluorescein isothiocyanate (FITC) or Tetra methyl Rhodamine Isothiocyanate (TRITC). This will react directly or indirectly with antigen and the Antigen-Antibody complex can be visualized using a fluorescent microscope. It excites the dyes by light of one or more wavelengths, which in turn emits a light at a characteristic wavelength which is captured by a selective filter in the microscope. The image is then projected with localized regions of fluorescence indicating different antigens labelled by antibodies of distinctive color.

 

Types of Immunofluorescence

 

There are two major types of immunofluorescence staining methods. They are

 

Direct Immunofluorescence

                                                                                                                                                  

In this method, the antibody against the molecule of interest is simply conjugated with a fluorescent dye. This can be widely applicable to detect viral, parasitic and tumor antigens in clinical specimens (Figure 1) and to identify the anatomic distribution of an antigen with in a tissue or within the compartments of a cell.  

 

                                                                             

Figure 1: Direct immunofluorescence image. In this histological section of human skin is fluorescently labelled using an anti-IgA antibody     

Image source: en.wikipedia.org/wiki/Immunofluorescence                

 

Indirect immunofluorescence

 

In this method, the primary antibody (antibody for the specific molecule of interest) is unlabeled and a secondary antibody (anti-immunoglobulin antibody directed towards the primary antibody) is labelled with the fluorescent dye. Hence the indirect immunofluorescence is also known as a double-layer technique. This is widely employed to detect the antibodies in patient serum, commonly to detect anti-nuclear antibodies in the Systemic Lupus Erythematosus patient’s serum (Figure 2).       

 

     

 

Figure 2: Indirect immunofluorescence showing double stranded DNA antibodies on HEp-20-10 cells

 

Image source: en.wikipedia.org/wiki/Anti-nuclear_antibody

 

 

Image Analysis

 

Quantitative fluorescence image analysis is a rapidly technology in cell biology and molecular biology sciences with a potential application in both clinical and basic research fields. The microscopic image of the fluorescent cell obtained in the wet laboratory techniques are further analyzed for the quantitative analysis of total fluorescence in a cell. Image processing methods such as adjustments of contrast, brightness, scaling etc help to highlight more on the selected fluorescence cell. Total fluorescence per cell can be calculated in an Excel sheet by applying the measurements obtained from the analyzed cell using ImageJ software.

 

CTCF (Corrected Total Cell Fluorescence) =  Integrated Density - (Area of selected cell X Mean fluorescence of background readings)

 

Quantitative immunofluorescence image analysis is applied widely in the urinary tract cytology and carcinoma cells (Parry WL, Hemstreet GP 3rd, 1988).

 

 

 

 

 

                                                                                                                                                                                                                                                                                

 

 

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