Click the links to see some recent and not so recent research interests and projects.
The Highly Predictive Heteromorphic Polymer (HiP-HoP) Model
We developed a polymer-based simulation model for predicting the folding and looping of chromatin fibres at high-resolution around specific genes. The model combines several mechanisms which drive chromosome organisation (including the bridging-induced attraction and loop extrusion) with a heteromorphic polymer. Put simply, this is a polymer which has properties which vary along its length - in this case some regions have a thicker more compact structure, which others are thinner and more flexible. We have applied the model to study the Pax6 gene locus in mouse. A simpler version of the model was used to study the alpha and beta globin genes.
with Nick Gilbert and Davide Marenduzzo.
Chromatin domains in yeast
In recent experiments using MicroC (a nucleosome resolution HiC-like chromosome conformation capture method) revealed that the yeast genome is organised into domains of enriched self-interactions. These are, however, much smaller than the topologically associated domains (TADs) found in mammals and other organisms (5-10kbp domains in yeast compared to 100kbp-1Mbp in mammals). To study the mechanism of formation of these domains we developed a simple polymer model for chromatin where nucleosomes were represented by 10nm sphere, and linker DNA was represented by chains of 2.5nm spheres. Using data on nucleosome positions (from MNase-seq experiments) to set the lengths of DNA linkers allows specific chromosome regions to be simulated. Despite being highly simplified, the model gives very good predictions of MicroC interaction maps - since nucleosome positions are the only input, this implies that the small scale domains arise simply due to the underlying chromatin structure, and do not require the more complex mechanisms found in mammals.
Facilitated diffusion
Many important cellular processes, such as gene regulation, require proteins to bind to short
specific target sequences on large DNA molecules. The target needs to be
found quickly and accurately. To do this it is thought that proteins
move through the bacterial cell, or eukaryotic nucleus by making
alternating rounds of free 3D diffusion, and 1D scanning along the DNA
molecule. Whilst there is a long history of theoretical treatment of
this process, there has been little work on simulations which take into
account the full dynamics of both the proteins and DNA. Using coarse
grained Brownian dynamics we have studied aspects such as the effect of
DNA configuration, the presence of non-target "traps" in the DNA
sequence, and the effect of crowding proteins in the cellular media,
including those which are diffusing freely, as well as those bound to
the DNA.
with Davide Marenduzzo and Mike Cates.
CA Brackley, et al., Phys. Rev. Lett. 111 108101 (2013)
CA Brackley, et al., Biochem. Soc. Trans. 41 582 (2013)
CA Brackley, et al., Phys. Rev. Lett. 109 168103 (2012)
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The bridging induced attraction as a driver of chromosome organisation
Ribosome Traffic in mRNA Translation
We use the versatile TASEP as a
model for ribosome traffic flow in the biological process of protein
production. This is a fundamental model in non-equilibrium statistical
physics. We study features such
as the effect of bottlenecks, and the interplay between supply and
demand of resources, and how this might impact (and allow control of)
protein levels and ultimately the characteristic of a cell.
with M
Carmen Romano, Marco Thiel, Celso Grebogi and Ian Stansfield.
FS Heldt, et al., Phil. Trans. R. Soc. A 373 20150107 (2015)
CA Brackley, et al., J. Stat. Mech. P03002 (2012)
CA Brackley, et al., PLoS Comput. Biol. 7 e1002203 (2011)
CA Brackley, et al., Phys. Rev. E 82 051920 (2010)
CA Brackley, et al., Phys. Rev. Lett.105 078102 (2010)
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