Hard-wired lattice light-sheet microscopy for imaging of expanded samples.


Journal

Optics express
ISSN: 1094-4087
Titre abrégé: Opt Express
Pays: United States
ID NLM: 101137103

Informations de publication

Date de publication:
11 May 2020
Historique:
entrez: 15 5 2020
pubmed: 15 5 2020
medline: 7 4 2021
Statut: ppublish

Résumé

Light-sheet fluorescence microscopy (LSFM) helps investigate small structures in developing cells and tissue for three-dimensional localization microscopy and large-field brain imaging in neuroscience. Lattice light-sheet microscopy is a recent development with great potential to improve axial resolution and usable field sizes, thus improving imaging speed. In contrast to the commonly employed Gaussian beams for light-sheet generation in conventional LSFM, in lattice light-sheet microscopy an array of low diverging Bessel beams with a suppressed side lobe structure is used. We developed a facile elementary lattice light-sheet microscope using a micro-fabricated fixed ring mask for lattice light-sheet generation. In our setup, optical hardware elements enable a stable and simple illumination path without the need for spatial light modulators. This setup, in combination with long-working distance objectives and the possibility for simultaneous dual-color imaging, provides optimal conditions for imaging extended optically cleared tissue samples. We here present experimental data of fluorescently stained neurons and neurites from mouse hippocampus following tissue expansion and demonstrate the high homogeneous resolution throughout the entire imaged volume. Utilizing our purpose-built lattice light-sheet microscope, we reached a homogeneous excitation and an axial resolution of 1.2 µm over a field of view of (333 µm)

Identifiants

pubmed: 32403583
pii: 431606
doi: 10.1364/OE.393728
doi:

Substances chimiques

Luminescent Agents 0
Green Fluorescent Proteins 147336-22-9

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

15587-15600

Auteurs

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Classifications MeSH