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An Automated Bayesian Pipeline for Rapid Analysis of Single-Molecule Binding Data [preprint]

Smith, Carlas
Jouravleva, Karina
Huisman, Maximiliaan
Jolly, Samson M.
Zamore, Phillip D.
Grunwald, David
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Abstract

Single-molecule binding assays enable the study of how molecular machines assemble and function. Current algorithms can identify and locate individual molecules, but require tedious manual validation of each spot. Moreover, no solution for high-throughput analysis of single-molecule binding data exists. Here, we describe an automated pipeline to analyze single-molecule data over a wide range of experimental conditions. We benchmarked the pipeline by measuring the binding properties of the well-studied, DNA-guided DNA endonuclease, TtAgo, an Argonaute protein from the Eubacterium Thermus thermophilus. We also used the pipeline to extend our understanding of TtAgo by measuring the protein's binding kinetics at physiological temperatures and for target DNAs containing multiple, adjacent binding sites.

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bioRxiv 261917; doi: https://doi.org/10.1101/26191. Link to preprint on bioRxiv service.

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10.1101/261917
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Now published in Nature Communications doi: 10.1038/s41467-018-08045-5

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The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-NC-ND 4.0 International license.