Research

Simulating cancer genomes

Many cancers arise due to genome rearrangements such as chromosome translocations, where two parts of different chromosomes can become fused together after a breakage. Genome regulation often involve chromosome looping and founding in 3D, and rearrangements can change the local 3D environment of a gene leading to mis-regulation. In this work we used polymer simulations based on the HiP-HoP model to study the changes in 3D structure which occur after a rearrangement. This has provided new insight into the processes involved in gene mid-regulation, and has also help us identify "interaction hotspots", which could in the future be targets for therapies. In our initial work we focused on rearrangement in B-cells involving the immunoglobulin heavy locus and the cell cycle gene CCND1. B-cells are part of the immune system, and programmed DNA breaking an repair is used to generate the genetic diversity required for generating immunity. Unfortunately these processes can go wrong, giving rise to different malignancies.

with Lisa Russell and Daniel Rico

D. Rico et al., bioRxiv (2020)

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.

A. Buckle, et al., Molecular Cell 72 1-12 (2018)

C. A. Brackley, et al., Genome Biology 17 1 (2016)

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.

O. Wiese, et al., Proc. Natl. Acad. Sci. USA 116 17307-17315 (2019)

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)

The bridging induced attraction as a driver of chromosome organisation

There are many DNA and chromatin binding proteins which from complexes which can mediate bridging interactions between different chromatin regions. Using coarse grained Brownian dynamics we uncovered a general tendency for such bridge-forming complexes to form clusters, even in the absence of attractive interactions between the complexes. This "bridging-induced attraction" not only provides a mechanism for the formation of the protein foci which are observed in vivo via microscopy, but it can also act to drive large scale chromatin organisation.

with Davide Marenduzzo and Peter Cook.

C. A. Brackley J. Phys. Cond. Matt. doi:10.1088/1361-648X/ab7f6c (2020)

J Johnson, et al., J. Phys. Cond. Matt. 27 064119 (2015)

CA Brackley, et al., Proc. Natl. Acad. Sci. USA 110 E3605 (2013)

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)