Optica Open
Browse

Homogeneous large field-of-view and compact iSCAT-TIRF setup for dynamic single molecule measurements

Download all (1.6 MB)
preprint
posted on 2024-06-17, 05:24 authored by Christian Eggeling, Giovanni De Angelis, Jacopo Abramo, Mariia Miasnikova, Marcel Taubert, Francesco Reina
Interferometric Scattering Microscopy (iSCAT) enables prolonged and high frame rate Single Particle Tracking (SPT) for single molecule dynamics studies. Typically, iSCAT setups employ scanning illumination schemes to achieve uniform sample illumination. However, this implementation limits the field of view (FoV) and maximum sampling rate, while increasing hardware requirements and setup size. We demonstrate the realization of a large (60µm x 60µm) uniformly illuminated FoV through a passive refractive optical element in the iSCAT illumination path. This scanning-free iSCAT microscopy setup is further combined with an objective based Total Internal Reflection Fluorescence Microscopy (TIRF) channel for a complementary fluorescence readout, a focus-lock system, and a tailored control platform via the open-source ImSwitch software, and has a compact footprint. As a proof-of-principle, we highlight the performance of the setup through the acquisition of iSCAT images with a uniform contrast and a ≤10 nm localization precision throughout the whole FoV. The performance is further demonstrated through dynamic iSCAT SPT and imaging Fluorescence Correlation Spectroscopy of lipid diffusion in a model membrane system. Our iSCAT setup thus depicts an accurate and improved way of recording fast molecular dynamics in life sciences.

History

Funder Name

Deutsche Forschungsgemeinschaft (EXC 2051 390713860,SFB 1278,316213987 ,GRK M-M-M,GRK 2723/1 – 2023 – ID 44711651,PolaRas EG 325/2-1); Freistaat Thüringen (Advanced Flu-Spec / 2020 FGZ: FGI 0031,Multi-XUV / 2023 FGR 0054); Deutscher Akademischer Austauschdienst (GSSP, 2022, Project-ID : 57597951); HORIZON EUROPE European Research Council (Grant Agreement No. 779472,Grant Agreement n.101016665); Chan Zuckerberg Initiative (DAF2022-311155); Bundesministerium für Bildung und Forschung (FKZ: 13N15713 / 13N15717)

Preprint ID

115143

Usage metrics

    Categories

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC