uFLIM - Unsupervised analysis of FLIM-FRET microscopy data

Masia, Francesco ORCID: https://orcid.org/0000-0003-4958-410X, Dewitte, Walter ORCID: https://orcid.org/0000-0002-0606-1686, Borri, Paola ORCID: https://orcid.org/0000-0002-7873-3314 and Langbein, Wolfgang ORCID: https://orcid.org/0000-0001-9786-1023 2022. uFLIM - Unsupervised analysis of FLIM-FRET microscopy data. Medical Image Analysis 82 , 102579. 10.1016/j.media.2022.102579

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Abstract

Despite their widespread use in cell biology, fluorescence lifetime imaging microscopy (FLIM) data-sets are challenging to analyse, because each spatial position can contain a superposition of multiple fluorescent components. Here, we present a data analysis method employing all information in the available photon budget, as well as being fast. The method, called uFLIM, determines spatial distributions and temporal dynamics of multiple fluorescent components with no prior knowledge. It goes significantly beyond current approaches which either assume the functional dependence of the dynamics, e.g. an exponential decay, or require dynamics to be known, or calibrated. Its efficient non-negative matrix factorization algorithm allows for real-time data processing. We validate in silico that uFLIM is capable to disentangle the spatial distribution and spectral properties of five fluorescing probes, from only two excitation and detection channels and a photon budget of 100 detected photons per pixel. By adapting the method to data exhibiting Förster resonant energy transfer (FRET), we retrieve the spatial and transfer rate distribution of the bound species, without constrains on donor and acceptor dynamics.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Physics and Astronomy Biosciences
Additional Information:	This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0)
Publisher:	Elsevier
ISSN:	1361-8415
Date of First Compliant Deposit:	30 August 2022
Date of Acceptance:	11 August 2022
Last Modified:	04 May 2023 00:55
URI:	https://orca.cardiff.ac.uk/id/eprint/152199

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