Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/126901
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Type: Journal article
Title: Non-invasive real-time imaging of reactive oxygen species (ROS) using auto-fluorescence multispectral imaging technique: a novel tool for redox biology
Author: Habibalahi, A.
Moghari, M.
Campbell, J.
Anwer, A.
Mahbub, S.
Gosnell, M.
Saad, S.
Pollock, C.
Goldys, E.
Citation: Redox Biology, 2020; 34:101561-1-101561-6
Publisher: Elsevier
Issue Date: 2020
ISSN: 2213-2317
2213-2317
Statement of
Responsibility: 
Abbas Habibalahi, Mahdieh Dashtbani Moghari, Jared M. Campbell, Ayad G. Anwer, Saabah B. Mahbub, Martin Gosnell, Sonia Saad, Carol Pollock, Ewa M. Goldys
Abstract: Detecting reactive oxygen species (ROS) that play a critical role as redox modulators and signalling molecules in biological systems currently requires invasive methods such as ROS -specific indicators for imaging and quantification. We developed a non-invasive, real-time, label-free imaging technique for assessing the level of ROS in live cells and thawed cryopreserved tissues that is compatible with in-vivo imaging. The technique is based on autofluorescence multispectral imaging (AFMI) carried out in an adapted fluorescence microscope with an expanded number of spectral channels spanning specific excitation (365 nm-495 nm) and emission (420 nm-700 nm) wavelength ranges. We established a strong quantitative correlation between the spectral information obtained from AFMI and the level of ROS obtained from CellROX staining. The results were obtained in several cell types (HeLa, PANC1 and mesenchymal stem cells) and in live kidney tissue. Additioanly,two spectral regimes were considered: with and without UV excitation (wavelengths > 400 nm); the latter being suitable for UV-sensitive systems such as the eye. Data were analyzed by linear regression combined with an optimization method of swarm intelligence. This allowed the calibration of AFMI signals to the level of ROS with excellent correlation (R = 0.84, p = 0.00) in the entire spectral range and very good correlation (R = 0.78, p = 0.00) in the limited, UV-free spectral range. We also developed a strong classifier which allowed us to distinguish moderate and high levels of ROS in these two regimes (AUC = 0.91 in the entire spectral range and AUC = 0.78 for UV-free imaging). These results indicate that ROS in cells and tissues can be imaged non-invasively, which opens the way to future clinical applications in conditions where reactive oxygen species are known to contribute to progressive disease such as in ophthalmology, diabetes, kidney disease, cancer and neurodegenerative diseases.
Rights: © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
RMID: 1000022328
DOI: 10.1016/j.redox.2020.101561
Grant ID: http://purl.org/au-research/grants/arc/CE140100003
http://purl.org/au-research/grants/arc/DP170101863
http://purl.org/au-research/grants/nhmrc/1144619
Appears in Collections:Public Health publications

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