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Data · dataset · 2023

A Multi-Parametric and High-Throughput Platform for Host-Virus Binding Screens

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Description

General information This item containst data sets for Schlegel et al, Nano Letters, 2023. DOI: doi.org/10.1021/acs.nanolett.2c04884 It contains confocal images, lattice light sheet images, flow cytometry data, compiled data as excle sheet and raw figure files.

Abstract

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Speed is key during infectious disease outbreaks. It is essential, for example, to identify critical host binding factors to pathogens as fast as possible. The complexity of host plasma membrane is often a limiting factor hindering fast and accurate determination of host binding factors as well as high-throughput screening for neutralizing antimicrobial drug targets.

Here, we describe a multiparametric and high-throughput platform tackling this bottleneck and enabling fast screens for host binding factors as well as new antiviral drug targets. The sensitivity and robustness of our platform were validated by blocking SARS-CoV-2 particles with nanobodies and IgGs from human serum samples. Data usage Researchers are welcome to use the data contained in the dataset for any projects.

Please cite this item upon use or when published. We encourage reuse using the same CC BY 4.0 License. Data Content Excel files for graphs Microscopy Images Flow cytometry data Software to open files: .csv: Fiji (imagej.net/software/fiji/downloads) or Microsoft Excel .xlsx: Microsoft Excel .tif, .lsm: Fiji (imagej.net/software/fiji/downloads) .pzfx: GraphPad Prism .svg: Inkscape (inkscape.org/) .fcs: FCS Express .pdf: AdobeAcrobat or Mozilla Firefox .ijm: Fiji (imagej.net/software/fiji/downloads)

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Inferred from text
Biochemistry and cell biology 73% · Disease 75% · Image 65% · Microscopy 75%
Provenance · 1 source records, 12 field assertions
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