Genetic Analysis of Larval Dispersal, Gene Flow, and Connectivity

Genetic data can be used to characterize the scale or magnitude of connectivity via larval dispersal in the plankton as the per capita migration rate (m), the rate of gene flow (Nm), or counts of immigrant individuals. Population-based methods infer average effective rates of connectivity on long time scales (hundreds to thousands of generations), and those estimates will influenced by many processes (including larval dispersal). Individual-based methods based on clustering or assignment of individual genotypes to populations or families are suitable for estimating connectivity on short timescales. The typical or characteristic larval dispersal distance for any one system of populations may best be characterized by isolation-by-distance patterns (using population model methods) or by the dispersal kernel (using parentage-based methods). Migration rates estimated from individual-based methods may be more relevant to ecological studies of demographic connectivity (e.g., among demes in a network of marine prote ted areas) compared to rates of gene flow estimated from population-based methods

On the glueball spectrum in O(a)-improved lattice QCD

We calculate the light `glueball' mass spectrum in N_f=2 lattice QCD using a fermion action that is non-perturbatively O(a) improved. We work at lattice spacings a ~0.1 fm and with quark masses that range down to about half the strange quark mass. We find the statistical errors to be moderate and under control on relatively small ensembles. We compare our mass spectrum to that of quenched QCD at the same value of a. Whilst the tensor mass is the same (within errors), the scalar mass is significantly smaller in the dynamical lattice theory, by a factor of ~(0.84 +/- 0.03). We discuss what the observed m_q dependence of this suppression tells us about the dynamics of glueballs in QCD. We also calculate the masses of flux tubes that wind around the spatial torus, and extract the string tension from these. As we decrease the quark mass we see a small but growing vacuum expectation value for the corresponding flux tube operators. This provides clear evidence for `string breaking' and for the (expected) breaking of the associated gauge centre symmetry by sea quarks.Comment: 33pp LaTeX. Version to appear in Phys. Rev.

Molecular Evolution of Mammalian Genes with Epistatic Interactions in Fertilization

Background Genes that encode proteins associated with sperm competition, fertilization, and sexual conflicts of interest are often among the most rapidly evolving parts of animal genomes. One family of sperm-expressed genes (Zp3r, C4bpa) in the mammalian gene cluster called the regulator of complement activation (RCA) encodes proteins that bind eggs and mediate reproductive success, and are therefore expected to show high relative rates of nonsynonymous nucleotide substitution in response to sexual selection in comparison to other genes not involved in gamete binding at fertilization. We tested that working hypothesis by using phylogenetic models of codon evolution to identify episodes of diversifying positive selection. We used a comparative approach to quantify the evidence for episodic diversifying selection acting on RCA genes with known functions in fertilization (and sensitivity to sexual selection), and contrast them with other RCA genes in the same gene family that function in innate immunity (and are not sensitive to sexual selection). Results We expected but did not find evidence for more episodes of positive selection on Zp3r in Glires (the rodents and lagomorphs) or on C4BPA in Primates, in comparison to other paralogous RCA genes in the same taxon, or in comparison to the same orthologous RCA gene in the other taxon. That result was not unique to RCA genes: we also found little evidence for more episodes of diversifying selection on genes that encode selective sperm-binding molecules in the egg coat or zona pellucida (Zp2, Zp3) in comparison to members of the same gene family that encode structural elements of the egg coat (Zp1, Zp4). Similarly, we found little evidence for episodic diversifying selection acting on two other recently discovered genes (Juno, Izumo1) that encode essential molecules for sperm–egg fusion. Conclusions These negative results help to illustrate the importance of a comparative context for this type of codon model analysis. The results may also point to other phylogenetic contexts in which the effects of selection acting on these fertilization proteins might be more readily discovered and documented in mammals and other taxa

Liposomal delivery of hydrophobic RAMBAs provides good bioavailability and significant enhancement of retinoic acid signalling in neuroblastoma tumour cells

Retinoid treatment is employed during residual disease treatment in neuroblastoma, where the aim is to induce neural differentiation or death in tumour cells. However, although therapeutically effective, retinoids have only modest benefits and suffer from poor pharmacokinetic properties. In vivo, retinoids induce CYP26 enzyme production in the liver, enhancing their own rapid metabolic clearance, while retinoid resistance in tumour cells themselves is considered to be due in part to increased CYP26 production. Retinoic acid metabolism blocking agents (RAMBAs), which inhibit CYP26 enzymes, can improve retinoic acid pharmacokinetics in pre-clinical neuroblastoma models. Here we demonstrate that in cultured neuroblastoma tumour cells, RAMBAs enhance retinoic acid action as seen by morphological differentiation, AKT signalling and suppression of MYCN protein. Although active as retinoid enhancers, these RAMBAs are highly hydrophobic and their effective delivery in humans will be very challenging. Here we demonstrate that such RAMBAs can be loaded efficiently into cationic liposomal particles, where the RAMBAs achieve good bioavailability and activity in cultured tumour cells. This demonstrates the efficacy of RAMBAs in enhancing retinoid signaling in neuroblastoma cells and shows for the first time that liposomal delivery of hydrophobic RAMBAs is a viable approach, providing novel opportunities for their delivery and application in humans

Topological Superconductivity in a Phase-Controlled Josephson Junction

Topological superconductors can support localized Majorana states at their boundaries. These quasi-particle excitations have non-Abelian statistics that can be used to encode and manipulate quantum information in a topologically protected manner. While signatures of Majorana bound states have been observed in one-dimensional systems, there is an ongoing effort to find alternative platforms that do not require fine-tuning of parameters and can be easily scalable to large numbers of states. Here we present a novel experimental approach towards a two-dimensional architecture. Using a Josephson junction made of HgTe quantum well coupled to thin-film aluminum, we are able to tune between a trivial and a topological superconducting state by controlling the phase difference $\phi$ across the junction and applying an in-plane magnetic field. We determine the topological state of the induced superconductor by measuring the tunneling conductance at the edge of the junction. At low magnetic fields, we observe a minimum in the tunneling spectra near zero bias, consistent with a trivial superconductor. However, as the magnetic field increases, the tunneling conductance develops a zero-bias peak which persists over a range of $\phi$ that expands systematically with increasing magnetic fields. Our observations are consistent with theoretical predictions for this system and with full quantum mechanical numerical simulations performed on model systems with similar dimensions and parameters. Our work establishes this system as a promising platform for realizing topological superconductivity and for creating and manipulating Majorana modes and will therefore open new avenues for probing topological superconducting phases in two-dimensional systems.Comment: Supplementary contains resized figures. Original files are available upon reques

Modelling proteins’ hidden conformations to predict antibiotic resistance

AbstractTEM β-lactamase confers bacteria with resistance to many antibiotics and rapidly evolves activity against new drugs. However, functional changes are not easily explained by differences in crystal structures. We employ Markov state models to identify hidden conformations and explore their role in determining TEM’s specificity. We integrate these models with existing drug-design tools to create a new technique, called Boltzmann docking, which better predicts TEM specificity by accounting for conformational heterogeneity. Using our MSMs, we identify hidden states whose populations correlate with activity against cefotaxime. To experimentally detect our predicted hidden states, we use rapid mass spectrometric footprinting and confirm our models’ prediction that increased cefotaxime activity correlates with reduced Ω-loop flexibility. Finally, we design novel variants to stabilize the hidden cefotaximase states, and find their populations predict activity against cefotaxime in vitro and in vivo. Therefore, we expect this framework to have numerous applications in drug and protein design.</jats:p