A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
PhotoFiTT: a quantitative framework for assessing phototoxicity in live-cell microscopy experiments
Tekijät: Del Rosario, Mario; Gómez-de-Mariscal, Estibaliz; Morgado, Leonor; Portela, Raquel; Jacquemet, Guillaume; Pereira, Pedro M.; Henriques, Ricardo
Kustantaja: Springer Nature
Julkaisuvuosi: 2025
Lehti: Nature Communications
eISSN: 2041-1723
DOI: https://doi.org/ 10.1038/s41467-025-66209-6
Julkaisun avoimuus kirjaamishetkellä: Avoimesti saatavilla
Julkaisukanavan avoimuus : Kokonaan avoin julkaisukanava
Verkko-osoite: https://www.nature.com/articles/s41467-025-66209-6
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/506019376
Phototoxicity in live-cell fluorescence microscopy can compromise experimental outcomes, yet quantitative methods to assess its impact remain limited. Here, we present PhotoFiTT (Phototoxicity Fitness Time Trial), an integrated framework combining a standardised experimental protocol with advanced image analysis to quantify light-induced cellular stress in label-free settings. PhotoFiTT leverages machine learning and cell cycle dynamics to analyse mitotic timing, cell size changes, and overall cellular activity in response to controlled light exposure. Using adherent mammalian cells, we demonstrate PhotoFiTT’s ability to detect wavelength- and dose-dependent effects, showcasing that near-UV light induces significant mitotic delays at doses as low as 0.6 J/cm2, while longer wavelengths require higher doses for comparable deleterious effects. PhotoFiTT enables researchers to establish quantitative benchmarks for acceptable levels of photodamage, facilitating the optimisation of imaging protocols that balance image quality with sample health.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
Julkaisussa olevat rahoitustiedot:
M.D.R., E.G.-d.-M. and R.H. acknowledge the support of the Gulbenkian Foundation (Fundação Calouste Gulbenkian), the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 101001332) (to R.H.) and funding from the European Union through the Horizon Europe programme (AI4LIFE project with grant agreement 101057970-AI4LIFE and RT-SuperES project with grant agreement 101099654-RT-SuperES to R.H.). Funded by the European Union. Views and opinions expressed are, however, those of the authors only and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them. This work was also supported by a European Molecular Biology Organisation (EMBO) installation grant (EMBO-4102020-IG-4734 to R.H.), an EMBO postdoctoral fellowship (EMBO ALTF 174-2022 to E.G.-d.-M.), a Chan Zuckerberg Initiative Visual Proteomics Grant (vpi-0000000044 with https://doi.org/10.37921/743590vtudfp to R.H.) and a Chan Zuckerberg Initiative Essential Open Source Software for Science (EOSS6-0000000260). A joint collaboration between Abbelight and the Instituto Gulbenkian de Ciência kindly supports L.M. The Fundação para a Ciência e Tecnologia (FCT, Portugal) supported E.G.-d.-M. (2023.09182.CEECIND/CP2854/CT0004), and R.H. and P.M.P. through national funds to the Associate Laboratory LS4FUTURE (LA/P/0087/2020, DOI 10.54499/LA/P/0087/2020). P.M.P. and R.P. acknowledges support from Fundação para a Ciência e Tecnologia (Portugal) project grant (PTDC/BIA-MIC/2422/2020), the R&D unit Mostmicro (UIDB/04612/2020, UIDP/04612/2020). P.M.P. acknowledges support from La Caixa Junior Leader Fellowship (LCF/BQ/PI20/11760012) financed by 'la Caixa' Foundation (ID 100010434) and by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 847648, and a Maratona da Saúde award. R.P. was supported by a Fundação para a Ciência e Tecnologia (Portugal) CEEC (2023.06402.CEECIND/CP2836/CT0008, https://doi.org/10.54499/2023). This work was partially supported by PPBI—Portuguese Platform of BioImaging (PPBI-POCI-01-0145-FEDER-022122) co-funded by national funds from OE—'Orçamento de Estado' and by European funds from FEDER—'Fundo Europeu de Desenvolvimento Regional', through the Bacterial Imaging Cluster (BIC ITQB NOVA). This study was also supported by the Research Council of Finland (338537 to G.J.), the Sigrid Juselius Foundation (to G.J.), the Cancer Society of Finland (Syöpäjärjestöt; to G.J.), and the Solutions for Health strategic funding to Åbo Akademi University (to G.J.). This research was supported by the InFLAMES Flagship Programme of the Academy of Finland (decision numbers: 337530, 337531, 357910 and 357911). This work was partially supported by PPBI—Portuguese Platform of BioImaging (PPBI-POCI-01-0145-FEDER-022122), co-funded by national funds from OE - 'Orçamento de Estado' and by European funds from FEDER—'Fundo Europeu de Desenvolvimento Regional'.
