Biology subjects

Shillcock, J. C.

Publications and source records attributed to Shillcock, J. C..

5 recordsLinked to original sources

bioRxiv2022

Macromolecular crowding is surprisingly unable to deform the structure of a model biomolecular condensate

The crowded interior of a living cell makes experiments on simpler in vitro systems attractive. Although these reveal interesting phenomena, their biological relevance can be questionable. A topical example is the phase separation of intrinsically-disordered proteins into biomolecular condensates, which is proposed to underlie the membraneless compartmentalisation of many cellular functions. How a cell reliably controls biochemical reactions in compartments open to the compositionally-varying cytoplasm is an important question for understanding cellular homeostasis. Computer simulations are often used to study the phase behaviour of model biomolecular condensates, but the number of relevant parameters explodes as the number of protein components increases. It is unfeasible to exhaustively simulate such models for all parameter combinations, although interesting phenomena are almost certainly hidden in the jungle of their high-dimensional parameter space. Here we have studied the phase behaviour of a model biomolecular condensate in the presence of a polymeric crowding agent. We used a novel compute framework to execute dozens of simultaneous simulations spanning the protein/crowder concentration space. We then combined the results into a graphical representation for human interpretation, which provided an efficient way to search the models high-dimensional parameter space. We found that steric repulsion from the crowder drives a near-critical system across the phase boundary, but the molecular arrangement within the resulting biomolecular condensate is rather insensitive to the crowder concentration and molecular weight. We propose that a cell may use the local cytoplasmic concentration to assist formation of biomolecular condensates, while relying on the dense phase reliably providing a stable, structured, fluid milieu for cellular biochemistry despite being open to its changing environment.

biophysics↗

bioRxiv2022

Model biomolecular condensates have heterogeneous structure quantitatively dependent on the interaction profile of their constituent macromolecules

Biomolecular condensates play numerous roles in cells by selectively concentrating client proteins while excluding others. These functions are likely to be sensitive to the spatial organization of the scaffold proteins forming the condensate. We use coarse-grained molecular simulations to show that model intrinsically-disordered proteins phase separate into a heterogeneous, structured fluid characterized by a well-defined length scale. The proteins are modelled as semi-flexible polymers with punctate, multifunctional binding sites in good solvent conditions. Their dense phase is highly solvated with a spatial structure that is more sensitive to the separation of the binding sites than their affinity. We introduce graph theoretic measures to show that the proteins are heterogeneously distributed throughout the dense phase, an effect that increases with increasing binding site number, and exhibit multi-timescale dynamics. The simulations predict that the structure of the dense phase is modulated by the location and affinity of binding sites distant from the termini of the proteins, while sites near the termini more strongly affect its phase behaviour. The relations uncovered between the arrangement of weak interaction sites on disordered proteins and the material properties of their dense phase can be experimentally tested to give insight into the biophysical properties and rational design of biomolecular condensates.

biophysics↗

bioRxiv2021

Non-monotonic fibril surface occlusion by GFP tags from coarse-grained molecular simulations

The pathological growth of amyloid fibrils in neurons underlies the progression of neurodegenerative diseases including Alzheimers and Parkinsons disease. Fibrils form when soluble monomers oligomerise in the cytoplasm. Their subsequent growth occurs via nucleated polymerization mechanisms involving the free ends of the fibrils augmented by secondary nucleation of new oligomers at their surface. Amyloid fibrils possess a complex interactome with diffusing cytoplasmic proteins that regulates many aspects of their growth, seeding capacity, biochemical activity and transition to pathological inclusions in diseased brains. Changes to their surface are also expected to modify their interactome, pathogenicity and spreading in the brain. Many assays visualise fibril formation, growth and inclusion formation by decorating monomeric proteins with fluorescent tags such as GFP. Recent studies from our group suggest that tags with sizes comparable to the fibril radius may modify the fibril surface accessibility and thus their PTM pattern, interactome and ability to form inclusions. Using coarse-grained molecular simulations of a single alpha synuclein fibril tagged with GFP we find that thermal fluctuations of the tags create a non-monotonic, size-dependent sieve around the fibril that perturbs its interactome with diffusing species. Our results indicate that experiments using tagged and untagged monomers to study the growth and interactome of fibrils should be compared with caution, and the confounding effects of the tags are more complex than a reduction in surface accessibility. The prevalence of fluorescent tags in amyloid fibril growth experiments suggests this has implications beyond the specific alpha synuclein fibrils we model here.

biophysics↗

bioRxiv2020

Computational synthesis of cortical dendritic morphologies

Neuronal morphologies provide the foundation for the electrical behavior of neurons, the connectomes they form, and the dynamical properties of the brain. Comprehensive neuron models are essential for defining cell types, discerning their functional roles and investigating structural alterations associated with diseased brain states. Recently, we introduced a topological descriptor that reliably categorizes dendritic morphologies. We apply this descriptor to digitally synthesize dendrites to address the challenge of insufficient biological reconstructions. The synthesized cortical dendrites are statistically indistinguishable from the corresponding reconstructed dendrites in terms of morpho-electrical properties and connectivity. This topology-guided synthesis enables the rapid digital reconstruction of entire brain regions from relatively few reference cells, thereby allowing the investigation of links between neuronal morphologies and brain function across different spatio-temporal scales. We synthesized cortical networks based on structural alterations of dendrites associated with medical conditions and revealed principles linking branching properties to the structure of large-scale networks. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=198 SRC="FIGDIR/small/040410v1_ufig1.gif" ALT="Figure 1"> View larger version (80K): org.highwire.dtl.DTLVardef@1ae790org.highwire.dtl.DTLVardef@58c3eborg.highwire.dtl.DTLVardef@1a6a9b1org.highwire.dtl.DTLVardef@ceae91_HPS_FORMAT_FIGEXP M_FIG Graphical abstractA topological model of neuronal shapes is used to investigate the link between the branching patterns of dendritic morphologies and the connectivity of the neuronal networks they form. Starting from reconstructed cells (in black) of cortical dendrites, we extract the topological barcode that is used to create a statistically similar synthesized pyramidal cell (in red), and respectively a group of pyramidal cells of the same morphological type. From reconstructed cells examples of all layers and morphological types we generate synthesized dendrites and build a synthesized cortical column (colors corresponds to cortical layers). The synthesized dedrites are statistically similar to the reconstructed dendrites in terms of morpho-electrical properties and the connectome of the synthesized column (colored connectome) is almost indistinguishable from the connectome of the reconstructed column (greyscale). C_FIG

neuroscience↗

bioRxiv2019

Structure of Biomolecular Condensates from Dissipative Particle Dynamics Simulations

Phase separation of immiscible fluids is a common phenomenon in polymer chemistry, and is recognized as an important mechanism by which cells compartmentalize their biochemical reactions. Biomolecular condensates are condensed fluid droplets in cells that form by liquid-liquid phase separation of intrinsically-disordered proteins. They have a wide range of functions and are associated with chronic neurodegenerative diseases in which they become pathologically rigid. Intrinsically-disordered proteins are conformationally flexible and possess multiple, distributed binding sites for each other or for RNA. However, it remains unclear how their material properties depend on the molecular structure of the proteins. Here we use coarse-grained simulations to explore the phase behavior and structure of a model biomolecular condensate composed of semi-flexible polymers with attractive end-caps in a good solvent. Although highly simplified, the model contains the minimal molecular features that are sufficient to observe liquid-liquid phase separation of soluble polymers. The polymers condense into a porous, three-dimensional network in which their end-caps reversibly bind at junctions. The spatial separation of connected junctions scales with the polymer backbone length as a self-avoiding random walk over a wide range of concentration with a weak affinity-dependent prefactor. By contrast, the average number of polymers that meet at the junctions depends strongly on the end-cap affinity but only weakly on the polymer length. The regularity and porosity of the condensed network suggests a mechanism for cells to regulate biomolecular condensates. Interaction sites along a protein may be turned on or off to modulate the condensates porosity and tune the diffusion and interaction of additional proteins.

biophysics↗