Photobleaching Imprinting Enhanced Background Rejection in Line-Scanning Temporal Focusing Microscopy.

background rejection biomedical imaging photobleaching imprinting temporal focusing microscope two-photon effect

Journal

Frontiers in chemistry
ISSN: 2296-2646
Titre abrégé: Front Chem
Pays: Switzerland
ID NLM: 101627988

Informations de publication

Date de publication:
2020
Historique:
received: 16 10 2020
accepted: 20 11 2020
entrez: 4 1 2021
pubmed: 5 1 2021
medline: 5 1 2021
Statut: epublish

Résumé

Compared with two-photon point-scanning microscopy, two-photon temporal focusing microscopy (2pTFM) provides a parallel high-speed imaging strategy with optical sectioning capability. Owing to out-of-focus fluorescence induced by scattering, 2pTFM suffers deteriorated signal-to-background ratio (SBR) for deep imaging in turbid tissue, Here, we utilized the photobleaching property of fluorophore to eliminate out-of-focus fluorescence. According to different decay rates in different focal depth, we extract the in-focus signals out of backgrounds through time-lapse images. We analyzed the theoretical foundations of photobleaching imprinting of the line-scanning temporal focusing microscopy, simulated implementation for background rejection, and demonstrated the contrast enhancement in MCF-10A human mammary epithelial cells and cleared Thy1-YFP mouse brains. More than 50% of total background light rejection was achieved, providing higher SBR images of the MCF-10A samples and mouse brains. The photobleaching imprinting method can be easily adapted to other fluorescence dyes or proteins, which may have application in studies involving relatively large and nontransparent organisms.

Identifiants

pubmed: 33392156
doi: 10.3389/fchem.2020.618131
pmc: PMC7773834
doi:

Types de publication

Journal Article

Langues

eng

Pagination

618131

Informations de copyright

Copyright © 2020 Zhuang, Li, Zhang, Kong, Xie and Dai.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Références

Nat Biotechnol. 2003 Nov;21(11):1369-77
pubmed: 14595365
Opt Lett. 2005 Jul 1;30(13):1686-8
pubmed: 16075538
Biomed Opt Express. 2011 Feb 25;2(3):696-704
pubmed: 21412473
Science. 1990 Apr 6;248(4951):73-6
pubmed: 2321027
Opt Express. 2017 Sep 18;25(19):23109-23121
pubmed: 29041614
Opt Express. 2020 Mar 30;28(7):9464-9476
pubmed: 32225553
Light Sci Appl. 2017 May 5;6:e16255
pubmed: 29152380
Nat Commun. 2014 Jun 05;5:3997
pubmed: 24898000
Nat Methods. 2015 Aug;12(8):759-62
pubmed: 26167641
Biomed Opt Express. 2014 Jul 08;5(8):2526-36
pubmed: 25136483
Nat Methods. 2010 Oct;7(10):848-54
pubmed: 20852649
J Cell Sci. 2014 Jan 15;127(Pt 2):288-94
pubmed: 24317295
Opt Express. 2011 Mar 14;19(6):4937-48
pubmed: 21445129
Biochemistry. 2005 May 10;44(18):7085-94
pubmed: 15865453
Opt Express. 2019 Jul 22;27(15):20117-20132
pubmed: 31510112
Nat Methods. 2005 Dec;2(12):932-40
pubmed: 16299478
Opt Commun. 2008 Apr 1;281(7):1796-1805
pubmed: 18496597
J Opt Soc Am A Opt Image Sci Vis. 2006 Dec;23(12):3139-49
pubmed: 17106469
Opt Lett. 2009 Jun 15;34(12):1786-8
pubmed: 19529703
Micromachines (Basel). 2017;8(3):
pubmed: 29387484
Appl Phys Lett. 2013 Oct 28;103(18):183703
pubmed: 24273331
Opt Express. 2013 Mar 11;21(5):5677-87
pubmed: 23482141
Opt Express. 2012 Apr 9;20(8):8939-48
pubmed: 22513605
Biomed Opt Express. 2018 Jul 05;9(8):3534-3543
pubmed: 30338138
Opt Lett. 2018 Oct 15;43(20):4919-4922
pubmed: 30320783
Opt Express. 2006 Oct 30;14(22):10565-73
pubmed: 19529458
Cold Spring Harb Protoc. 2015 Feb 02;2015(2):145-51
pubmed: 25646508
J R Soc Interface. 2014 Jan 29;11(93):20130851
pubmed: 24478278
Opt Express. 2005 Mar 7;13(5):1468-76
pubmed: 19495022
Opt Express. 2017 Dec 11;25(25):32010-32020
pubmed: 29245869
Opt Express. 2018 Aug 20;26(17):21518-21526
pubmed: 30130858
Biophys J. 2000 Apr;78(4):2159-62
pubmed: 10733993

Auteurs

Chaowei Zhuang (C)

Department of Automation, Tsinghua University, Beijing, China.

Xinyang Li (X)

Department of Automation, Tsinghua University, Beijing, China.

Yuanlong Zhang (Y)

Department of Automation, Tsinghua University, Beijing, China.

Lingjie Kong (L)

Department of Precision Instrument, Tsinghua University, Beijing, China.

Hao Xie (H)

Department of Automation, Tsinghua University, Beijing, China.

Qionghai Dai (Q)

Department of Automation, Tsinghua University, Beijing, China.
Beijing National Research Center for Information Science and Technology, Beijing, China.
Institute for Brain and Cognitive Science, Tsinghua University, Beijing, China.
Beijing Laboratory of Brain and Cognitive Intelligence, Beijing Municipal Education Commission, Beijing, China.

Classifications MeSH