OOPS: A GUI-based software package for object-oriented analysis of fluorescence polarization microscopy data.

Abstract

Excitation-resolved fluorescence polarization microscopy (FPM) is a powerful technique that enables the study of orientational order and dynamics in biological systems. Compared to methods like X-ray crystallography, nuclear magnetic resonance spectroscopy, and cryo-electron microscopy, FPM offers key advantages, particularly when applied to lipid membranes, membrane proteins, or membrane-associated protein assemblies. Unlike traditional structural methods, FPM can be configured on standard optical microscopes by simply adding a polarization modulator to the excitation path. However, these experimental advantages are countered by the extensive image processing and analysis required to interpret the polarization response data. Consequently, the use of FPM remains limited to a small subset of laboratories, typically relying on custom-built software designed for a particular biological system of interest. Here, we describe OOPS (Object-Oriented Polarization Software), a software package written in MATLAB that offers a convenient graphical user interface, designed to make FPM analysis accessible to researchers at all skill levels. We demonstrate the power and flexibility of our approach by analyzing FPM data acquired of both punctate and filamentous structures. First, we apply OOPS to desmosomes, cell adhesion complexes that are incredibly difficult to study using traditional methods. Our analyses reveal novel, domain-specific differences in orientational order in the transmembrane components of desmosomes, the desmosomal cadherins. We further show how FPM data can be used to reveal the underlying geometry of large, membrane-associated protein assemblies. Finally, to illustrate the flexibility of OOPS, we also collected and analyzed FPM data of F-actin. We demonstrate how our software can quickly and reliably retrieve pixel-by-pixel F-actin filament orientations under a variety of experimental conditions. Importantly, OOPS does not rely on a specific labeling method, meaning the approaches detailed here could easily be extended to a wide array of biological systems.