OLIGOPY, A PYHTON MODULE TO DETERMINE THE OLIGOMERIZATION STATE OF NUCLEAR PARTICLES IN IMAGES FROM LIVE CELLS

EVELYN OLSZANOWSKI; ADALI PECCI; DIEGO PRESMAN

Buenos Aires (Virtual)

Congreso; 1st Congress of Women in Bioinformatics and Data Science Latin America; 2020

Amajor challenge in cell biology is to determine the quaternarystructure of proteins within their natural environment. We present aPython-based module for analyzing images from live cells acquiredwith confocal microscopy to obtain the oligomerization state of afluorescent-tagged protein. This package is based on the Number &Brightness (N&B) technique first introduced by the Gratton lab in2008, which use moment-analysis for the measurement of the averagenumber of molecules and brightness in each pixel in fluorescencemicroscopy images. The average brightness of the particle is obtainedfrom the ratio of the variance to the average intensity at eachpixel. The representation of the brightness versus the averageintensity at each pixel is used to distinguish and select thedifferent compartments of the cell (cytoplasm, nucleus, nucleolus,etc.); and a brightness value for the desired section can beobtained. Comparing the measured brightness value to a known sample,one can determine the particle?s oligomerization state. Oligopyrelies on numpy, scipy, matplotlib, pandas and seaborn, providingcomputations and graphic visualization of results. As aproof-of-concept, we compared data analysis from mammaryadenocarcinoma 3617 cells transiently transfected with GlucocorticoidReceptor tagged with Green Fluorescent Protein, previously analyzedby the SimFCS software (Globals for images). We show our routinepresent comparable results to SimFCS, and since our implementationrequires less steps from the end-user, it works as a suitablealternative for N&B analysis.