Mechanical inhibition of microtubule depolymerisation by kinesin

Kinesin-driven transport of molecular cargo along microtubules is central to the self-organisation of eukaryotic cells. We investigated the effect of kinesin-1 on microtubule stability using in vitro techniques. We found that kinesin-1, which was previously reported to have no influence on microtubule dynamics, to reduce shrinkage rates by approximately two orders of magnitude if maintained in a nucleotide-free or ATP-bound state. No effect was observed in the presence of high ADP concentrations, indicating that the microtubule-stabilising ability of kinesin-1 is constrained to a subset of the kinetic states of its ATPase cycle. By decorating just one side of the microtubule lattice with kinesin, we were able to gain additional insights into the mechanics of microtubules. By stabilising just 2-3 protofilaments with kinesin, the structural integrity of most of the microtubule could be maintained. Curiously, in such circumstances the microtubule would split at its ends. We further showed that microtubule curvature induced by hydrodynamic flow is trapped or even increased by nucleotide-free kinesin. We propose a mechanism whereby kinesin-1 drives the conformation of polymerised GDP-tubulin into a slightly elongated and shrinkage-resistant conformation. This is essentially the converse mechanism of that reported for the kinesin-13, MCAK, which supports tubulin in a curved conformation that is incompatible with the microtubule lattice

Alp7/TACC-Alp14/TOG generates long-lived, fast-growing MTs by an unconventional mechanism

Alp14 is a TOG-family microtubule polymerase from S. pombe that tracks plus ends and accelerates their growth. To interrogate its mechanism, we reconstituted dynamically unstable single isoform S. pombe microtubules with full length Alp14/TOG and Alp7, the TACC-family binding partner of Alp14. We find that Alp14 can drive microtubule plus end growth at GTP-tubulin concentrations at least 10-fold below the usual critical concentration, at the expense of increased catastrophe. This reveals Alp14 to be a highly unusual enzyme that biases the equilibrium for the reaction that it catalyses. Alp7/TACC enhances the effectiveness of Alp14, by increasing its occupancy. Consistent with this, we show in live cells that Alp7 deletion produces very similar MT dynamics defects to Alp14 deletion. The ability of Alp7/14 to accelerate and bias GTP-tubulin exchange at microtubule plus ends allows it to generate long-lived, fast-growing microtubules at very low cellular free tubulin concentrations

CFT dual of the AdS Dirichlet problem: Fluid/Gravity on cut-off surfaces

We study the gravitational Dirichlet problem in AdS spacetimes with a view to understanding the boundary CFT interpretation. We define the problem as bulk Einstein's equations with Dirichlet boundary conditions on fixed timelike cut-off hypersurface. Using the fluid/gravity correspondence, we argue that one can determine non-linear solutions to this problem in the long wavelength regime. On the boundary we find a conformal fluid with Dirichlet constitutive relations, viz., the fluid propagates on a `dynamical' background metric which depends on the local fluid velocities and temperature. This boundary fluid can be re-expressed as an emergent hypersurface fluid which is non-conformal but has the same value of the shear viscosity as the boundary fluid. The hypersurface dynamics arises as a collective effect, wherein effects of the background are transmuted into the fluid degrees of freedom. Furthermore, we demonstrate that this collective fluid is forced to be non-relativistic below a critical cut-off radius in AdS to avoid acausal sound propagation with respect to the hypersurface metric. We further go on to show how one can use this set-up to embed the recent constructions of flat spacetime duals to non-relativistic fluid dynamics into the AdS/CFT correspondence, arguing that a version of the membrane paradigm arises naturally when the boundary fluid lives on a background Galilean manifold.Comment: 71 pages, 2 figures. v2: Errors in bulk metrics dual to non-relativistic fluids (both on cut-off surface and on the boundary) have been corrected. New appendix with general results added. Fixed typos. 82 pages, 2 figure

Holographic Wilsonian flows and emergent fermions in extremal charged black holes

We study holographic Wilsonian RG in a general class of asymptotically AdS backgrounds with a U(1) gauge field. We consider free charged Dirac fermions in such a background, and integrate them up to an intermediate radial distance, yielding an equivalent low energy dual field theory. The new ingredient, compared to scalars, involves a `generalized' basis of coherent states which labels a particular half of the fermion components as coordinates or momenta, depending on the choice of quantization (standard or alternative). We apply this technology to explicitly compute RG flows of charged fermionic operators and their composites (double trace operators) in field theories dual to (a) pure AdS and (b) extremal charged black hole geometries. The flow diagrams and fixed points are determined explicitly. In the case of the extremal black hole, the RG flows connect two fixed points at the UV AdS boundary to two fixed points at the IR AdS_2 region. The double trace flow is shown, both numerically and analytically, to develop a pole singularity in the AdS_2 region at low frequency and near the Fermi momentum, which can be traced to the appearance of massless fermion modes on the low energy cut-off surface. The low energy field theory action we derive exactly agrees with the semi-holographic action proposed by Faulkner and Polchinski in arXiv:1001.5049 [hep-th]. In terms of field theory, the holographic version of Wilsonian RG leads to a quantum theory with random sources. In the extremal black hole background the random sources become `light' in the AdS_2 region near the Fermi surface and emerge as new dynamical degrees of freedom.Comment: 37 pages (including 8 pages of appendix), 10 figures and 2 table

Kinesin expands and stabilizes the GDP-microtubule lattice

Kinesin-1 is a nanoscale molecular motor that walks towards the fast-growing (plus) ends of microtubules, hauling molecular cargo to specific reaction sites in cells. Kinesin-driven transport is central to the self-organization of eukaryotic cells and shows great promise as a tool for nano-engineering1. Recent work hints that kinesin may also play a role in modulating the stability of its microtubule track, both in vitro2,3 and in vivo4, but the results are conflicting5,6,7 and the mechanisms are unclear. Here, we report a new dimension to the kinesin–microtubule interaction, whereby strong-binding state (adenosine triphosphate (ATP)-bound and apo) kinesin-1 motor domains inhibit the shrinkage of guanosine diphosphate (GDP) microtubules by up to two orders of magnitude and expand their lattice spacing by ~1.6%. Our data reveal an unexpected mechanism by which the mechanochemical cycles of kinesin and tubulin interlock, and so allow motile kinesins to influence the structure, stability and mechanics of their microtubule track

Characterisation of paediatric brain tumours by their MRS metabolite profiles

1H‐magnetic resonance spectroscopy (MRS) has the potential to improve the noninvasive diagnostic accuracy for paediatric brain tumours. However, studies analysing large, comprehensive, multicentre datasets are lacking, hindering translation to widespread clinical practice. Single‐voxel MRS (point‐resolved single‐voxel spectroscopy sequence, 1.5 T: echo time [TE] 23–37 ms/135–144 ms, repetition time [TR] 1500 ms; 3 T: TE 37–41 ms/135–144 ms, TR 2000 ms) was performed from 2003 to 2012 during routine magnetic resonance imaging for a suspected brain tumour on 340 children from five hospitals with 464 spectra being available for analysis and 281 meeting quality control. Mean spectra were generated for 13 tumour types. Mann–Whitney U‐tests and Kruskal–Wallis tests were used to compare mean metabolite concentrations. Receiver operator characteristic curves were used to determine the potential for individual metabolites to discriminate between specific tumour types. Principal component analysis followed by linear discriminant analysis was used to construct a classifier to discriminate the three main central nervous system tumour types in paediatrics. Mean concentrations of metabolites were shown to differ significantly between tumour types. Large variability existed across each tumour type, but individual metabolites were able to aid discrimination between some tumour types of importance. Complete metabolite profiles were found to be strongly characteristic of tumour type and, when combined with the machine learning methods, demonstrated a diagnostic accuracy of 93% for distinguishing between the three main tumour groups (medulloblastoma, pilocytic astrocytoma and ependymoma). The accuracy of this approach was similar even when data of marginal quality were included, greatly reducing the proportion of MRS excluded for poor quality. Children's brain tumours are strongly characterised by MRS metabolite profiles readily acquired during routine clinical practice, and this information can be used to support noninvasive diagnosis. This study provides both key evidence and an important resource for the future use of MRS in the diagnosis of children's brain tumours

Non-Supersymmetric String Theory

A class of non-supersymmetric string backgrounds can be constructed using twists that involve space-time fermion parity. We propose a non-perturbative definition of string theory in these backgrounds via gauge theories with supersymmetry softly broken by twisted boundary conditions. The perturbative string spectrum is reproduced, and qualitative effects of the interactions are discussed. Along the way, we find an interesting mechanism for inflation. The end state of closed string tachyon condensation is a highly excited state in the gauge theory which, in all likelihood, does not have a geometric interpretation.Comment: 35 pages, 2 figures; revision adds a computation of the relevant orbifold state

Metabolite selection for machine learning in childhood brain tumour classification

MRS can provide high accuracy in the diagnosis of childhood brain tumours when combined with machine learning. A feature selection method such as principal component analysis is commonly used to reduce the dimensionality of metabolite profiles prior to classification. However, an alternative approach of identifying the optimal set of metabolites has not been fully evaluated, possibly due to the challenges of defining this for a multi‐class problem. This study aims to investigate metabolite selection from in vivo MRS for childhood brain tumour classification. Multi‐site 1.5 T and 3 T cohorts of patients with a brain tumour and histological diagnosis of ependymoma, medulloblastoma and pilocytic astrocytoma were retrospectively evaluated. Dimensionality reduction was undertaken by selecting metabolite concentrations through multi‐class receiver operating characteristics and compared with principal component analysis. Classification accuracy was determined through leave‐one‐out and k‐fold cross‐validation. Metabolites identified as crucial in tumour classification include myo‐inositol (P < 0.05, AUC = 0 . 81 ± 0 . 01 ), total lipids and macromolecules at 0.9 ppm (P < 0.05, AUC = 0 . 78 ± 0 . 01 ) and total creatine (P < 0.05, AUC = 0 . 77 ± 0 . 01 ) for the 1.5 T cohort, and glycine (P < 0.05, AUC = 0 . 79 ± 0 . 01 ), total N‐acetylaspartate (P < 0.05, AUC = 0 . 79 ± 0 . 01 ) and total choline (P < 0.05, AUC = 0 . 75 ± 0 . 01 ) for the 3 T cohort. Compared with the principal components, the selected metabolites were able to provide significantly improved discrimination between the tumours through most classifiers (P < 0.05). The highest balanced classification accuracy determined through leave‐one‐out cross‐validation was 85% for 1.5 T 1H‐MRS through support vector machine and 75% for 3 T 1H‐MRS through linear discriminant analysis after oversampling the minority. The study suggests that a group of crucial metabolites helps to achieve better discrimination between childhood brain tumours

Temporal, spatial, and structural patterns of adult trembling aspen and white spruce mortality in Quebec's boreal forest

Temporal, spatial, and structural patterns of adult trembling aspen (Populus tremuloides Michx.) and white spruce (Picea glauca (Moench) Voss) mortality were studied in intact 150-year-old stands in the southwestern boreal forest of Quebec. For both species, mortality decreases (number of dead trees/total number of trees) with distance from the lake edge until 100-150 m, from which point it slightly increases. Strong peaks in mortality were found for 40- to 60-year-old aspen mainly between 1974 and 1992. Such mortality in relatively young aspen is likely related to competition for light from the dominant canopy trees. Also, the recruitment of this young aspen cohort is presumably the result of a stand breakup that occurred when the initial aspen-dominated stand was between 90 and 110 years old. For spruce, strong peaks in mortality were found in 110- to 150-year-old trees and they occurred mainly after 1980. No clear explanation could be found for these peaks, but we suggest that they may be related to senescence or weakening of the trees following the last spruce budworm outbreak. Suppressed and codominant aspen had a much higher mortality ratio than spruce in the same height class, while more surprisingly, no difference in mortality rate was found between dominant trees of the two species. Most spruce trees were found as standing dead, which leads us to reject the hypothesis that windthrow is an important cause of mortality for spruce in our forests