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An automated Bayesian pipeline for rapid analysis of single-molecule binding data
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 exi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6336789/ https://www.ncbi.nlm.nih.gov/pubmed/30655518 http://dx.doi.org/10.1038/s41467-018-08045-5 |
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author | Smith, Carlas S. Jouravleva, Karina Huisman, Maximiliaan Jolly, Samson M. Zamore, Phillip D. Grunwald, David |
author_facet | Smith, Carlas S. Jouravleva, Karina Huisman, Maximiliaan Jolly, Samson M. Zamore, Phillip D. Grunwald, David |
author_sort | Smith, Carlas S. |
collection | PubMed |
description | 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. In addition, our method enables state estimation on multivariate Gaussian signals. We validate our approach using simulated data, and benchmark 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 use 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. |
format | Online Article Text |
id | pubmed-6336789 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-63367892019-01-22 An automated Bayesian pipeline for rapid analysis of single-molecule binding data Smith, Carlas S. Jouravleva, Karina Huisman, Maximiliaan Jolly, Samson M. Zamore, Phillip D. Grunwald, David Nat Commun Article 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. In addition, our method enables state estimation on multivariate Gaussian signals. We validate our approach using simulated data, and benchmark 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 use 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. Nature Publishing Group UK 2019-01-17 /pmc/articles/PMC6336789/ /pubmed/30655518 http://dx.doi.org/10.1038/s41467-018-08045-5 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Smith, Carlas S. Jouravleva, Karina Huisman, Maximiliaan Jolly, Samson M. Zamore, Phillip D. Grunwald, David An automated Bayesian pipeline for rapid analysis of single-molecule binding data |
title | An automated Bayesian pipeline for rapid analysis of single-molecule binding data |
title_full | An automated Bayesian pipeline for rapid analysis of single-molecule binding data |
title_fullStr | An automated Bayesian pipeline for rapid analysis of single-molecule binding data |
title_full_unstemmed | An automated Bayesian pipeline for rapid analysis of single-molecule binding data |
title_short | An automated Bayesian pipeline for rapid analysis of single-molecule binding data |
title_sort | automated bayesian pipeline for rapid analysis of single-molecule binding data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6336789/ https://www.ncbi.nlm.nih.gov/pubmed/30655518 http://dx.doi.org/10.1038/s41467-018-08045-5 |
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