Single-photon smFRET. III. Application to pulsed illumination.

IF 2.4 Q3 BIOPHYSICS
Biophysical reports Pub Date : 2022-11-25 eCollection Date: 2022-12-14 DOI:10.1016/j.bpr.2022.100088
Matthew Safar, Ayush Saurabh, Bidyut Sarkar, Mohamadreza Fazel, Kunihiko Ishii, Tahei Tahara, Ioannis Sgouralis, Steve Pressé
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引用次数: 0

Abstract

Förster resonance energy transfer (FRET) using pulsed illumination has been pivotal in leveraging lifetime information in FRET analysis. However, there remain major challenges in quantitative single-photon, single-molecule FRET (smFRET) data analysis under pulsed illumination including 1) simultaneously deducing kinetics and number of system states; 2) providing uncertainties over estimates, particularly uncertainty over the number of system states; and 3) taking into account detector noise sources such as cross talk and the instrument response function contributing to uncertainty; in addition to 4) other experimental noise sources such as background. Here, we implement the Bayesian nonparametric framework described in the first companion article that addresses all aforementioned issues in smFRET data analysis specialized for the case of pulsed illumination. Furthermore, we apply our method to both synthetic as well as experimental data acquired using Holliday junctions.

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单光子 smFRET。III.脉冲照明的应用。
使用脉冲照明的佛斯特共振能量转移(FRET)在利用寿命信息进行 FRET 分析方面发挥了关键作用。然而,脉冲照明下的单光子、单分子 FRET(smFRET)数据定量分析仍面临重大挑战,包括:1)同时推断动力学和系统状态数;2)提供估计值的不确定性,尤其是系统状态数的不确定性;3)考虑探测器噪声源,如交叉干扰和仪器响应函数对不确定性的影响;以及 4)其他实验噪声源,如背景。在此,我们实施了第一篇配套文章中描述的贝叶斯非参数框架,该框架专门针对脉冲照明情况,解决了 smFRET 数据分析中的所有上述问题。此外,我们还将我们的方法应用于使用霍利迪结法获得的合成数据和实验数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Biophysical reports
Biophysical reports Biophysics
CiteScore
2.40
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0.00%
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审稿时长
75 days
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