Probabilistic reconstruction of truncated particle trajectories on a closed surface

TL;DR

This paper develops a probabilistic method to reconstruct 3D biomolecule trajectories on cylindrical surfaces from partial 2D microscopy data, addressing the challenge of missing data due to surface truncation.

Contribution

It introduces a novel statistical approach for reconstructing particle trajectories on a 3D surface from incomplete 2D observations, specifically for cylindrical geometries.

Findings

Method accurately reconstructs trajectories in simulated data

Demonstrates effectiveness on bacterial protein dynamics

Handles particles appearing and disappearing on the surface

Abstract

Investigation of dynamic processes in cell biology very often relies on the observation in two dimensions of 3D biological processes. Consequently, the data are partial and statistical methods and models are required to recover the parameters describing the dynamical processes. In the case of molecules moving over the 3D surface, such as proteins on walls of bacteria cell, a large portion of the 3D surface is not observed in 2D-time microscopy. It follows that biomolecules may disappear for a period of time in a region of interest, and then reappear later. Assuming Brownian motion with drift, we address the mathematical problem of the reconstruction of biomolecules trajectories on a cylindrical surface. A subregion of the cylinder is typically recorded during the observation period, and biomolecules may appear or disappear in any place of the 3D surface. The performance of the method is demonstrated on simulated particle trajectories that mimic MreB protein dynamics observed in 2D time-lapse fluorescence microscopy in rod-shaped bacteria.