Quantifying the Dynamics of the Endoplasmic Reticulum in Mammalian Cells

Abstract

The dynamics of the endoplasmic reticulum (ER), a subcellular organelle consisting of a network of membrane tubules and sheets, were studied using fluorescence microscopy. Strong links have been found between diseases and perturbed network morphology. More recently, altered ER dynamics have also been linked to disease. Both ER structure and motion are therefore likely to influence functionality. In this work, methods to quantify ER morphology and dynamics have been developed and optimised. By analysing ER morphology in a kidney fibroblast-like cell line (Vero), we concluded that ER tubules can be modelled as semi-flexible polymers, with a mean length of 1.148 +/- 0.007 um that is comparable to the persistence length, 8.3 +/- 0.2 um. Hallmarks of uneven tensile forces acting on the network and potential membrane contact sites (MCSs) were observed by analysing angles at network junctions. New, extending tubules moved super-diffusively, as expected for motor-protein driven processes, whereas the midpoints of established tubules oscillated sub-diffusively, following predictions for thermalised semi-flexible polymers under tension. When the complete contours were analysed, signatures of active motion were detected for at least one point on the majority of tubules. Together, these results led to the hypothesis that ER tubules in live cells oscillate due to a background of thermal motion, with regular active perturbations along the contour. Tubule curvature was predominantly transient, most likely due to short-lived influences of MCSs between the ER and motile organelles. Tubule dynamics were also found to depend on position within the cell, with tubules at the extreme periphery less mobile than those closer to the nucleus. ER sheet dynamics were assessed for the first time using differential dynamic microscopy. Longer relaxation times and lower anomalous exponents were found for sheets than for tubules, as predicted theoretically. For all network architectures, double compressed decays modelled the data best, with the faster decay following predictions for relaxation due to slow network rearrangements. Altogether, this work has expanded our understanding of ER organisation and dynamics in healthy cells. The tracking and analysis methods described here provide the basis for future studies to compare the motion of the ER in healthy and diseased cells, therefore beginning to clarify the functional benefit of ER network dynamics.

Date of Award	1 Aug 2022
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Philip Woodman (Supervisor), Viki Allan (Supervisor) & Thomas Waigh (Supervisor)