Protocol exchange 

About: Protocol exchange is an academic journal. The journal publishes majorly in the area(s): Induced pluripotent stem cell & Stem cell. It has an ISSN identifier of 2043-0116. Over the lifetime, 449 publications have been published receiving 2323 citations.

Quantifying chromogen intensity in immunohistochemistry via reciprocal intensity

Abstract: Immunohistochemistry is a routine procedure for detecting the expression of biological markers in formalin-fixed and paraffin-embedded tissues. Chromogens, which can appear as different colors (brown, blue, red) under bright field microscopy, are localized in fixed tissues to antigens of interest via an antibody-antigen detection system. The advantage of a chromogen system is that the stained tissue section is permanently fixed, and the staining quality is maintained for many years. The shortcoming, however, is quantifying the intensity of such stains. Unlike immunofluorescent protocols in which the brightness of a region is directly proportional to the amount of localized antigen, chromogen stains appear darker in regions with more antigen. This dark staining is visible to the human eye under white light, but darker spots have lower intensity values; something that is counterintuitive and cumbersome for the purposes of quantitation. We report that this limitation can be overcome by measuring the “reciprocal intensity” of the chromogen stain. A typical red-green-blue image resulting from bright field microscopy has its maximum intensity value found in the white, non-stained area. Areas that contain any coloration, due to the chromogen or a counterstain, have an intensity of less than the maximum. By subtracting the intensity of the stained area of interest from the maximum, the staining in these areas can be represented as a quantity that is positively correlated with increasing darkness. This is a more intuitive means of assessing the intensity of a chromogen stain, and allows for more sensitivity in quantifying gradients of coloration between treatment groups. This approach has the potential to stratify nuanced protein expression in previously published human specimen data sets into cohorts with clearer clinical outcomes.