Fast and flexible processing of large FRET image stacks using the FRET-IBRA toolkit

• Published in: PLoS computational biology Vol. 18; no. 4; p. e1009242
• Main Authors: Munglani, Gautam, Vogler, Hannes, Grossniklaus, Ueli
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01.04.2022; Public Library of Science (PLoS)
• Subjects: Algorithms; Background noise; Benchmarks; Biology and Life Sciences; Calcium ions; Computer and Information Sciences; Configurations; Datasets; Energy transfer; Engineering and Technology; Flexibility; Fluorescence; Fluorescence Resonance Energy Transfer; Image processing; Image Processing, Computer-Assisted - methods; Methods; Microscopy; Noise; Outliers (statistics); Photobleaching; Physical Sciences; Pollen; Pollen tubes; Research and Analysis Methods; Run time (computers); Signal to noise ratio; Software; Source code; Spatial distribution; Stacks; Subtraction; Temporal resolution; Toolkits; Switzerland
• ISSN: 1553-7358; 1553-734X; 1553-7358
• DOI: 10.1371/journal.pcbi.1009242

Ratiometric time-lapse FRET analysis requires a robust and accurate processing pipeline to eliminate bias in intensity measurements on fluorescent images before further quantitative analysis can be conducted. This level of robustness can only be achieved by supplementing automated tools with built-in flexibility for manual ad-hoc adjustments. FRET-IBRA is a modular and fully parallelized configuration file-based tool written in Python. It simplifies the FRET processing pipeline to achieve accurate, registered, and unified ratio image stacks. The flexibility of this tool to handle discontinuous image frame sequences with tailored configuration parameters further streamlines the processing of outliers and time-varying effects in the original microscopy images. FRET-IBRA offers cluster-based channel background subtraction, photobleaching correction, and ratio image construction in an all-in-one solution without the need for multiple applications, image format conversions, and/or plug-ins. The package accepts a variety of input formats and outputs TIFF image stacks along with performance measures to detect both the quality and failure of the background subtraction algorithm on a per frame basis. Furthermore, FRET-IBRA outputs images with superior signal-to-noise ratio and accuracy in comparison to existing background subtraction solutions, whilst maintaining a fast runtime. We have used the FRET-IBRA package extensively to quantify the spatial distribution of calcium ions during pollen tube growth under mechanical constraints. Benchmarks against existing tools clearly demonstrate the need for FRET-IBRA in extracting reliable insights from FRET microscopy images of dynamic physiological processes at high spatial and temporal resolution. The source code for Linux and Mac operating systems is released under the BSD license and, along with installation instructions, test images, example configuration files, and a step-by-step tutorial, is freely available at github.com/gmunglani/fret-ibra .