An integrated platform for high-throughput nanoscopy

被引：22

作者：

Barentine, Andrew E. S. ^{[1
,2
]}

Lin, Yu ^{[1
,2
]}

Courvan, Edward M. ^{[1
,3
]}

Kidd, Phylicia ^{[1
]}

Liu, Miao ^{[4
]}

Balduf, Leonhard ^{[1
,5
]}

Phan, Timy ^{[1
,5
]}

Rivera-Molina, Felix ^{[1
]}

Grace, Michael R. ^{[1
]}

Marin, Zach ^{[1
,2
,6
]}

Lessard, Mark ^{[1
]}

Chen, Juliana Rios ^{[1
]}

Wang, Siyuan ^{[1
,4
]}

Neugebauer, Karla M. ^{[1
,3
]}

Bewersdorf, Joerg ^{[1
,2
,7
,8
]}

Baddeley, David ^{[1
,6
,8
]}

机构：

[1] Yale Sch Med, Dept Cell Biol, New Haven, CT 06510 USA

[2] Yale Univ, Dept Biomed Engn, New Haven, CT 06520 USA

[3] Yale Sch Med, Dept Mol Biophys & Biochem, New Haven, CT USA

[4] Yale Sch Med, Dept Genet, New Haven, CT USA

[5] Univ Appl Sci, Dept Comp Sci & Math, Munich, Germany

[6] Univ Auckland, Auckland Bioengn Inst, Auckland, New Zealand

[7] Yale Univ, Dept Phys, New Haven, CT 06520 USA

[8] Yale Univ, Nanobiol Inst, West Haven, CT 06520 USA

来源：

NATURE BIOTECHNOLOGY | 2023年 / 41卷 / 11期

基金：

美国国家卫生研究院;

关键词：

SINGLE-MOLECULE LOCALIZATION; SUPERRESOLUTION MICROSCOPY;

D O I：

10.1038/s41587-023-01702-1

中图分类号：

Q81 [生物工程学（生物技术）]; Q93 [微生物学];

学科分类号：

071005 ; 0836 ; 090102 ; 100705 ;

摘要：

Single-molecule localization microscopy enables three-dimensional fluorescence imaging at tens-of-nanometer resolution, but requires many camera frames to reconstruct a super-resolved image. This limits the typical throughput to tens of cells per day. While frame rates can now be increased by over an order of magnitude, the large data volumes become limiting in existing workflows. Here we present an integrated acquisition and analysis platform leveraging microscopy-specific data compression, distributed storage and distributed analysis to enable an acquisition and analysis throughput of 10,000 cells per day. The platform facilitates graphically reconfigurable analyses to be automatically initiated from the microscope during acquisition and remotely executed, and can even feed back and queue new acquisition tasks on the microscope. We demonstrate the utility of this framework by imaging hundreds of cells per well in multi-well sample formats. Our platform, implemented within the PYthon-Microscopy Environment (PYME), is easily configurable to control custom microscopes, and includes a plugin framework for user-defined extensions. A fast data processing platform enables super-resolution microscopy with increased throughput.

引用

页码：1549 / +

页数：15