University of Dundee

Modelling the dynamic organisation of crowded and complex cell membranes: from the nano to the meso scale”

Event Date: 
Thursday, March 28, 2019 - 15:00 to 16:00
Event Location: 
MSI Small Lecture Theatre
Host: 
Professor Geoff Barton FRSE FRSB
Event Speaker: 
Dr Anna Duncan
Institution: 
University of Oxford
Event Type: 
Seminar
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Abstract:
 
It is well-understood that cell membranes are crowded and complex environments, containing up to 50 % protein by mass and myriad types of lipid species.  Less well-understood in molecular detail are the effects of complexity and crowding on membrane organisation and dynamics. In order to study this I have used coarse-grained (CG) molecular dynamics (MD) to simulate >100 copies of potassium channels in the mammalian cell membrane (1) and beta-barrel proteins in the bacterial outer membrane (2,3). I will discuss the interplay between protein-lipid interactions, protein and lipid diffusion, and protein clustering observed in these systems, and the impact of these processes on the mesoscale organisation.
 
In simulating systems of  >100 nm in dimension whilst retaining membrane complexity at a molecular level, we move further towards the use of simulation as a 'computational microscope'. However, time and length scales of such CG MD simulations are state-of-the-art and necessitate the use of high performance computing resources. Thus, in order to link simulations directly with lower spatial and temporal resolution experimental techniques, such as fluorescence microscopy, we require an intermediate 'mesoscale' model. 
 
I have developed a mesoscale model that can incorporate 1000s of proteins, trained on the results of coarse-grained molecular dynamics simulations (3).  Using molecular dynamics and mesoscale simulations I show that protein clusters on bacterial outer membrane proteins form a mesh of moving barriers, which recapitulate restricted diffusion characteristics in vitro. The mesoscale model provides a powerful integrated approach to understand physiologically accurate biological membranes at mesoscale length and time scales.
 
 
 
References
 
1.  Duncan et al, Sci Rep, 7, 16647, 2017
2.  Rassam et al, Nature, 253, 333-6, 2015
3.  Chavent et al, Nat Commun, 9, 2846, 2018