Dynamic modelling reveals the separable contributions to achieving correct spindle orientation in a noisy system

The mechanisms by which the mammalian mitotic spindle is guided to a predefined orientation through microtubule-cortex interactions have recently received considerable interest, but there has been no dynamic model that describes spindle movements toward the preferred axis in human cells. Here, we develop a dynamic model based on stochastic activity of cues anisotropically positioned around the cortex of the mitotic cell and we show that the mitotic spindle does not reach equilibrium before chromosome segregation. Our model successfully captures the characteristic experimental behavior of noisy spindle rotation dynamics in human epithelial cells, including a weak underlying bias in the direction of rotation, suppression of motion close to the alignment axis, and the effect of the aspect ratio of the interphase cell shape in defining the final alignment axis. We predict that the force exerted per cue has a value that minimizes the deviation of the spindle from the predefined axis. The model has allowed us to systematically explore the parameter space around experimentally relevant configurations, and predict the mechanistic function of a number of established regulators of spindle orientation, highlighting how physical modeling of a noisy system can lead to functional biological understanding. We provide key insights into measurable parameters in live cells that can help distinguish between mechanisms of microtubule and cortical-cue interactions that jointly control the final orientation of the spindle.This work was supported by Cancer Research UKThis is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.bpj.2015.08.01

Observation of the Early Structural Changes Leading to the Formation of Protein Superstructures.

Formation of superstructures in protein aggregation processes has been indicated as a general pathway for several proteins, possibly playing a role in human pathologies. There is a severe lack of knowledge on the origin of such species in terms of both mechanisms of formation and structural features. We use equine lysozyme as a model protein, and by combining spectroscopic techniques and microscopy with X-ray fiber diffraction and ab initio modeling of Small Angle X-ray Scattering data, we isolate the partially unfolded state from which one of these superstructures (i.e., particulate) originates. We reveal the low-resolution structure of the unfolded state and its mechanism of formation, highlighting the physicochemical features and the possible pathway of formation of the particulate structure. Our findings provide a novel detailed knowledge of such a general and alternative aggregation pathway for proteins, this being crucial for a basic and broader understanding of the aggregation phenomena.This is the author's accepted manuscript and will be under embargo until the 3rd of September 2015. The final version is published by ACS in The Journal of Physical Chemistry Letters here: http://pubs.acs.org/doi/abs/10.1021/jz501614e

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Small angle X-ray scattering investigation of deformation in PMMA toughened with core-shell particles

info:eu-repo/semantics/publishe