Morales-Curiel, Luis FelipeGonzalez, Adriana CarolinaCastro-Olvera, GustavoLin, Li-Chun LynnEl-Quessny, MalakPorta-de-la-Riva, MontserratSeverino, Jacqueline, 1990-Batlle Masó, Laura, 1993-Venturini, ValeriaRuprecht, VerenaRamallo, DiegoLoza-Alvarez, PabloKrieg, Michael2023-02-232023-02-232022Morales-Curiel LF, Gonzalez AC, Castro-Olvera G, Lin LL, El-Quessny M, Porta-de-la-Riva M, Severino J, Morera LB, Venturini V, Ruprecht V, Ramallo D, Loza-Alvarez P, Krieg M. Volumetric imaging of fast cellular dynamics with deep learning enhanced bioluminescence microscopy. Commun Biol. 2022 Dec 3;5(1):1330. DOI: 10.1038/s42003-022-04292-x2399-3642http://hdl.handle.net/10230/55869Bioluminescence microscopy is an appealing alternative to fluorescence microscopy, because it does not depend on external illumination, and consequently does neither produce spurious background autofluorescence, nor perturb intrinsically photosensitive processes in living cells and animals. The low photon emission of known luciferases, however, demands long exposure times that are prohibitive for imaging fast biological dynamics. To increase the versatility of bioluminescence microscopy, we present an improved low-light microscope in combination with deep learning methods to image extremely photon-starved samples enabling subsecond exposures for timelapse and volumetric imaging. We apply our method to image subcellular dynamics in mouse embryonic stem cells, epithelial morphology during zebrafish development, and DAF-16 FoxO transcription factor shuttling from the cytoplasm to the nucleus under external stress. Finally, we concatenate neural networks for denoising and light-field deconvolution to resolve intracellular calcium dynamics in three dimensions of freely moving Caenorhabditis elegans.application/pdfeng© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.info:eu-repo/semantics/articlehttp://dx.doi.org/10.1038/s42003-022-04292-xBioluminescence imagingImage processingMachine learningOptogeneticsinfo:eu-repo/semantics/openAccess