Fluorescent microscopy is a popular technique in molecular and cellular biology that is used to examine spatial information and interactions of specific components of an organism. Drawing conclusions from fluorescent imaging micrographs is often a very qualitative process. A method of quantitation is presented to extract numeric data out of these images, using the brightness intensities of each pixel. The program accounts for nonspecific antibody staining and background by applying a mask that only exposes the chromosome and can be used with sets of data containing several fluorescent tags. Two other variant programs are also available: one that calculates area and luminescence of individual objects within the mask and one that displays the fluorescence intensity along a user inputted line.

Interfaces

The codes use thresholds to negate background in a fluorescent image and quantify the image's signal intensity. There are three available programs.

 

Name for the program is pending! If you have any ideas email me (Contact page).

Uses & Theoretical Background

Allows for easier comparison between sets of data, and creating numeric relations between images or groups of images.

The theoretical background of each program is discussed in depth within the instructions for each program, but is also outlined here.

 

Example using Drosophila melanogaster polytene chromosomes:

An experiment using two fluorescent labels (DAPI top, Chd1 bottom)

The "black" background is not completely dark, and technically has some "brightness". Thus the DAPI picture has a lower intensity when only the area of the DNA is being used for calculations. This area is then applied to the Chd1 image, which has a large amount of background. The negation of that greatly reduces the numeric intensity.

A second level of background negation can be done, for non specific staining within the area of the mask itself. The batch masking program can use a lower threshold value to cut out this background, inside the mask.

The outputted numbers of all of the images can then be analyzed and graphed, and a numerical relationship can be established.

Results, graphed

(However, variation in experiments from different days, with different microscope exposure times and variability from experiment to experiment makes it impossible to directly compare different experiments.)

Tetrahymena and object differentiation:

(under construction)

 

Goal for the future: create a macro for ImageJ.

To add:

-The name

-Get codes, put in downloads page

-Finish up pdfs, put in downloads page

-Change the page titles for each page. How to make the template editable there?

-Figure out how to reduce parspace

-icon?