Event Title

Software Development for FRET-based Analysis of Protein-Protein Interactions

Presenter Information

Robert Lindert

Mentor 1

Valerica Raicu

Location

Union Wisconsin Room

Start Date

27-4-2018 1:00 PM

Description

G-protein-coupled receptors (GPCRs) are the largest family of transmembrane receptors in eukaryotic cells. They respond to a variety of stimuli, which may be present outside of the cell, and hence are the target of more than 60% of modern clinical drugs. Many GPCRs have been proven to associate into homo-oligomeric complexes whose functional roles remain largely unknown. Association of GPCRs in living cells may be probed via detection of the changes in light emission caused by transfer of energy between fluorescent tags attached to the proteins of interest. The transfer process, called Förster Resonance Energy Transfer (FRET), relies on coupling between the transition dipole of a fluorescent “acceptor” (A) molecule and that of an optically excited “donor” (D) molecule when they are within 10 nm of each other. Raicu Lab has introduced a method called FRET spectrometry, which involves the use of laser light to excite the donor at its excitation maximum wavelength and determine the efficiency of energy transfer for each pixel in an image. Recently, we have expanded the method to allow scanning the sample at a second excitation wavelength, which more closely matches the acceptor excitation maximum. Two additional quantities can be measured as a result: the donor and acceptor concentrations at pixel level. The current analysis process requires use of several software packages and is labor intensive. The goal of the current project is to write new software that streamlines this procedure. In addition to speeding up the analysis process, the software will also reduce errors resulting from pairing the two excitation wavelength images incorrectly. The developed code is based on object-oriented programing, which facilitates database construction and maintenance, as the processed information is vast and diverse (e.g., 3D images, fluorescent tag data, fitting and analysis of the experimental data, etc.).

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Apr 27th, 1:00 PM

Software Development for FRET-based Analysis of Protein-Protein Interactions

Union Wisconsin Room

G-protein-coupled receptors (GPCRs) are the largest family of transmembrane receptors in eukaryotic cells. They respond to a variety of stimuli, which may be present outside of the cell, and hence are the target of more than 60% of modern clinical drugs. Many GPCRs have been proven to associate into homo-oligomeric complexes whose functional roles remain largely unknown. Association of GPCRs in living cells may be probed via detection of the changes in light emission caused by transfer of energy between fluorescent tags attached to the proteins of interest. The transfer process, called Förster Resonance Energy Transfer (FRET), relies on coupling between the transition dipole of a fluorescent “acceptor” (A) molecule and that of an optically excited “donor” (D) molecule when they are within 10 nm of each other. Raicu Lab has introduced a method called FRET spectrometry, which involves the use of laser light to excite the donor at its excitation maximum wavelength and determine the efficiency of energy transfer for each pixel in an image. Recently, we have expanded the method to allow scanning the sample at a second excitation wavelength, which more closely matches the acceptor excitation maximum. Two additional quantities can be measured as a result: the donor and acceptor concentrations at pixel level. The current analysis process requires use of several software packages and is labor intensive. The goal of the current project is to write new software that streamlines this procedure. In addition to speeding up the analysis process, the software will also reduce errors resulting from pairing the two excitation wavelength images incorrectly. The developed code is based on object-oriented programing, which facilitates database construction and maintenance, as the processed information is vast and diverse (e.g., 3D images, fluorescent tag data, fitting and analysis of the experimental data, etc.).