Volumetric imaging of fast cellular dynamics with deep learning enhanced bioluminescence microscopy

Author:

Morales-Curiel Luis Felipe,Gonzalez Adriana Carolina,Castro-Olvera Gustavo,Lin Li-ChunORCID,El-Quessny Malak,Porta-de-la-Riva Montserrat,Severino JacquelineORCID,Morera Laura Battle,Venturini ValeriaORCID,Ruprecht VerenaORCID,Ramallo Diego,Loza-Alvarez PabloORCID,Krieg MichaelORCID

Abstract

AbstractBioluminescence 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 movingCaenorhabditis elegans.

Funder

EC | Horizon 2020 Framework Programme

Human Frontier Science Program

Ministerio de Economía, Industria y Competitividad, Gobierno de España

Publisher

Springer Science and Business Media LLC

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,Medicine (miscellaneous)

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