PT  - JOURNAL ARTICLE
AU  - Andrew E S Barentine
AU  - Yu Lin
AU  - Edward M Courvan
AU  - Phylicia Kidd
AU  - Miao Liu
AU  - Leonhard Balduf
AU  - Timy Phan
AU  - Felix Rivera-Molina
AU  - Michael R Grace
AU  - Zach Marin
AU  - Mark Lessard
AU  - Juliana Rios Chen
AU  - Siyuan Wang
AU  - Karla M Neugebauer
AU  - Joerg Bewersdorf
AU  - David Baddeley
TI  - An Integrated Platform for High-Throughput Nanoscopy
AID  - 10.1101/606954
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 606954
4099  - http://biorxiv.org/content/early/2022/04/20/606954.short
4100  - http://biorxiv.org/content/early/2022/04/20/606954.full
AB  - Diffraction-unlimited single-molecule techniques like STORM and (F)PALM enable three-dimensional (3D) fluorescence imaging at tens of nanometer resolution and are invaluable to investigate sub-cellular organization. The multitude of camera frames required to reconstruct a super-resolved image limits the typical throughput of these techniques to tens of cells per day, rendering these methods incompatible with large-scale cell biological or clinical application. STORM acquisition rates can be increased by over an order of magnitude, however the data volumes of about 40 TB a day and concomitant analysis burdens exceed the capacity of existing workflows. Here we present an integrated platform which transforms SMLM from a trick-pony technique into a work horse for cell biology. We leverage our developments in microscopy-specific data compression, distributed storage, and distributed analysis to automatically perform real-time localization analysis, which enable SMLM at throughputs of 10,000 cells a day. We implemented these advances in a fully-integrated environment that supports a highly-flexible architecture for distributed analysis, enabling quickly- and graphically-reconfigurable analyses to be automatically initiated from the microscope during acquisition, remotely executed, and even feedback 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, the PYthon-Microscopy Environment (PYME), is easily configurable for hardware control on custom microscopes, and includes a plugin framework so users can readily extend all components of their imaging, visualization, and analysis pipeline. PYME is cross-platform, open source, and efficiently puts high-caliber visualization and analysis tools into the hands of both microscope developers and users.Competing Interest Statementificant financial interest in Bruker Corp. and Hamamatsu Photonics