Error-based extraction of states and energy landscapes from experimental single-molecule time-series.

J Nicholas Taylor,David R Cooper,Chun-Biu Li,Christy F Landes,Tamiki Komatsuzaki

doi:10.1038/srep09174

J Nicholas Taylor, David R Cooper + Show 3 more

Open Access

https://doi.org/10.1038/srep09174

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Journal: Scientific Reports	Publication Date: Mar 17, 2015
Citations: 15	License type: CC BY 4.0

Affiliation: Hokkaido University, Rice University

Abstract

Characterization of states, the essential components of the underlying energy landscapes, is one of the most intriguing subjects in single-molecule (SM) experiments due to the existence of noise inherent to the measurements. Here we present a method to extract the underlying state sequences from experimental SM time-series. Taking into account empirical error and the finite sampling of the time-series, the method extracts a steady-state network which provides an approximation of the underlying effective free energy landscape. The core of the method is the application of rate-distortion theory from information theory, allowing the individual data points to be assigned to multiple states simultaneously. We demonstrate the method's proficiency in its application to simulated trajectories as well as to experimental SM fluorescence resonance energy transfer (FRET) trajectories obtained from isolated agonist binding domains of the AMPA receptor, an ionotropic glutamate receptor that is prevalent in the central nervous system.

Highlights

Characterization of states, the essential components of the underlying energy landscapes, is one of the most intriguing subjects in single-molecule (SM) experiments due to the existence of noise inherent to the measurements
We demonstrate the method’s proficiency in its application to simulated trajectories as well as to experimental SM fluorescence resonance energy transfer (FRET) trajectories obtained from isolated agonist binding domains of the AMPA receptor, an ionotropic glutamate receptor that is prevalent in the central nervous system
The segmentation procedure of local equilibrium state analysis[12] is used to construct the state-to-state network directly along the time-series. In this demonstration we use a SM FRET efficiency trajectory acquired from a nitrowillardiine-bound agonist binding domain (ABD) of an AMPA receptor (GluA2)[34], but we note that the procedure does not rely on the nature of the physical quantity being observed

Summary

Introduction

Characterization of states, the essential components of the underlying energy landscapes, is one of the most intriguing subjects in single-molecule (SM) experiments due to the existence of noise inherent to the measurements. A recent change-point identification method revealed that the possibility of misidentifying the underlying SM kinetics exists when a simpler thresholding procedure is used to determine the states or levels comprising the time-series[28] This was due to large, fast fluctuation of the noise contaminating the signals. The segmentation procedure of local equilibrium state analysis[12] is used to construct the state-to-state network directly along the time-series In this demonstration we use a SM FRET efficiency trajectory acquired from a nitrowillardiine-bound agonist binding domain (ABD) of an AMPA receptor (GluA2)[34], but we note that the procedure does not rely on the nature of the physical quantity being observed. An underlying assumption in clustering the segments is that those arising from the same underlying state have small distances and segments arising from different underlying states have larger distances

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Conclusion