Correcting Artifacts in Ratiometric Biosensor Imaging; an Improved Approach for Dividing Noisy Signals

• Type of Material: Article
• Authors: Daniel J Marston, University of North Carolina; Scott D Slattery, University of North Carolina; Klaus M Hahn, University of North Carolina; Denis Tsygankov, Emory University
• Language: English
• Date: 2021-08-20
• Publisher: FRONTIERS MEDIA SA
• Publication Version: Final Published Version
• Copyright Statement: © 2021 Marston, Slattery, Hahn and Tsygankov.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.3389/fcell.2021.685825
• Title of Journal or Parent Work: FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
• Volume: 9
• Start Page: 685825
• End Page: 685825
• Grant/Funding Information: This work was supported by grants from the U.S. Army Research Office (ARO, W911NF-17-1-0395) and the National Science Foundation (CMMI 1942561) to DT, and by NIGMS grant GM-R35GM122596 to KH.
• Keywords: Life Sciences & Biomedicine; Cell Biology; FRET biosensors; image processing; ratiometric analysis; Developmental Biology; cell morphodynamics; Science & Technology; Rho (Rho GTPase)
• Research Categories: Health Sciences, Pharmacology; Health Sciences, Medicine and Surgery; Engineering, Biomedical

Abstract

The accuracy of biosensor ratio imaging is limited by signal/noise. Signals can be weak when biosensor concentrations must be limited to avoid cell perturbation. This can be especially problematic in imaging of low volume regions, e.g., along the cell edge. The cell edge is an important imaging target in studies of cell motility. We show how the division of fluorescence intensities with low signal-to-noise at the cell edge creates specific artifacts due to background subtraction and division by small numbers, and that simply improving the accuracy of background subtraction cannot address these issues. We propose a new approach where, rather than simply subtracting background from the numerator and denominator, we subtract a noise correction factor (NCF) from the numerator only. This NCF can be derived from the analysis of noise distribution in the background near the cell edge or from ratio measurements in the cell regions where signal-to-noise is high. We test the performance of the method first by examining two noninteracting fluorophores distributed evenly in cells. This generated a uniform ratio that could provide a ground truth. We then analyzed actual protein activities reported by a single chain biosensor for the guanine exchange factor (GEF) Asef, and a dual chain biosensor for the GTPase Cdc42. The reduction of edge artifacts revealed persistent Asef activity in a narrow band (∼640 nm wide) immediately adjacent to the cell edge. For Cdc42, the NCF method revealed an artifact that would have been obscured by traditional background subtraction approaches.