The Annals of Applied Statistics

Toward Bayesian inference of the spatial distribution of proteins from three-cube Förster resonance energy transfer data

Jan-Otto Hooghoudt, Margarida Barroso, and Rasmus Waagepetersen

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Abstract

Förster resonance energy transfer (FRET) is a quantum-physical phenomenon where energy may be transferred from one molecule to a neighbor molecule if the molecules are close enough. Using fluorophore molecule marking of proteins in a cell, it is possible to measure in microscopic images to what extent FRET takes place between the fluorophores. This provides indirect information of the spatial distribution of the proteins. Questions of particular interest are whether (and if so to which extent) proteins of possibly different types interact or whether they appear independently of each other. In this paper we propose a new likelihood-based approach to statistical inference for FRET microscopic data. The likelihood function is obtained from a detailed modeling of the FRET data-generating mechanism conditional on a protein configuration. We next follow a Bayesian approach and introduce a spatial point process prior model for the protein configurations depending on hyperparameters quantifying the intensity of the point process. Posterior distributions are evaluated using Markov chain Monte Carlo. We propose to infer microscope-related parameters in an initial step from reference data without interaction between the proteins. The new methodology is applied to simulated and real datasets.

Article information

Source
Ann. Appl. Stat. Volume 11, Number 3 (2017), 1711-1737.

Dates
Received: August 2016
Revised: March 2017
First available in Project Euclid: 5 October 2017

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1507168845

Digital Object Identifier
doi:10.1214/17-AOAS1054

Keywords
Bayesian inference Markov chain Monte Carlo Förster resonance energy transfer spatial point process spatial distribution proteins fluorophores

Citation

Hooghoudt, Jan-Otto; Barroso, Margarida; Waagepetersen, Rasmus. Toward Bayesian inference of the spatial distribution of proteins from three-cube Förster resonance energy transfer data. Ann. Appl. Stat. 11 (2017), no. 3, 1711--1737. doi:10.1214/17-AOAS1054. https://projecteuclid.org/euclid.aoas/1507168845


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Supplemental materials

  • Supplement A: Preliminary statistical analysis of the in vitro three-cube FRET dataset. The supplementary material contains a preliminary statistical analysis of the in vitro three cube FRET dataset. Sample preparation and experimental setup are discussed as well the channel dataset extracted from the samples. The amount of photobleaching for the remeasurements in the three channels is studied and the mean–variance relations of the dataset are compared with the ones given by our statistical model. Further, estimates for the microscope parameters are obtained through various non-Bayesian methods.
  • Supplement B: The MCMC sampler. The supplementary material contains a detailed description of the steps performed in the MCMC sampler.
  • Supplement C: Inference of the microscope parameters. The supplementary material contains a detailed description of the inference of the microscope parameters.