Mapping the topography of a protein energy landscape

Protein energy landscapes are highly complex, yet the vast majority of states within them tend to be invisible to experimentalists. Here, using site-directed mutagenesis and exploiting the simplicity of tandem-repeat protein structures, we delineate a network of these states and the routes between them. We show that our target, gankyrin, a 226-residue 7-ankyrin-repeat protein, can access two alternative (un)folding pathways. We resolve intermediates as well as transition states, constituting a comprehensive series of snapshots that map early and late stages of the two pathways and show both to be polarized such that the repeat array progressively unravels from one end of the molecule or the other. Strikingly, we find that the protein folds via one pathway but unfolds via a different one. The origins of this behavior can be rationalized using the numerical results of a simple statistical mechanics model that allows us to visualize the equilibrium behavior as well as single-molecule folding/unfolding trajectories, thereby filling in the gaps that are not accessible to direct experimental observation. Our study highlights the complexity of repeat-protein folding arising from their symmetrical structures; at the same time, however, this structural simplicity enables us to dissect the complexity and thereby map the precise topography of the energy landscape in full breadth and remarkable detail. That we can recapitulate the key features of the folding mechanism by computational analysis of the native structure alone will help toward the ultimate goal of designed amino-acid sequences with made-to-measure folding mechanisms—the Holy Grail of protein folding

Dark Stars and Boosted Dark Matter Annihilation Rates

Dark Stars (DS) may constitute the first phase of stellar evolution, powered by dark matter (DM) annihilation. We will investigate here the properties of DS assuming the DM particle has the required properties to explain the excess positron and elec- tron signals in the cosmic rays detected by the PAMELA and FERMI satellites. Any possible DM interpretation of these signals requires exotic DM candidates, with an- nihilation cross sections a few orders of magnitude higher than the canonical value required for correct thermal relic abundance for Weakly Interacting Dark Matter can- didates; additionally in most models the annihilation must be preferentially to lep- tons. Secondly, we study the dependence of DS properties on the concentration pa- rameter of the initial DM density profile of the halos where the first stars are formed. We restrict our study to the DM in the star due to simple (vs. extended) adiabatic contraction and minimal (vs. extended) capture; this simple study is sufficient to illustrate dependence on the cross section and concentration parameter. Our basic results are that the final stellar properties, once the star enters the main sequence, are always roughly the same, regardless of the value of boosted annihilation or concentration parameter in the range between c=2 and c=5: stellar mass ~ 1000M\odot, luminosity ~ 10^7 L\odot, lifetime ~ 10^6 yrs (for the minimal DM models considered here; additional DM would lead to more massive dark stars). However, the lifetime, final mass, and final luminosity of the DS show some dependence on boost factor and concentration parameter as discussed in the paper.Comment: 37 pages, 11 figure

PREDICTORS OF HYPERTENSION

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74570/1/j.1749-6632.1978.tb25565.x.pd

A systematic search strategy identifies cubilin as independent prognostic marker for renal cell carcinoma

$\textbf{Background:}$ There is an unmet clinical need for better prognostic and diagnostic tools for renal cell carcinoma (RCC). $\textbf{Methods:}$ Human Protein Atlas data resources, including the transcriptomes and proteomes of normal and malignant human tissues, were searched for RCC-specific proteins and cubilin (CUBN) identified as a candidate. Patient tissue representing various cancer types was constructed into a tissue microarray ($n$ = 940) and immunohistochemistry used to investigate the specificity of CUBN expression in RCC as compared to other cancers. Two independent RCC cohorts ($n$ = 181; $n$ = 114) were analyzed to further establish the sensitivity of CUBN as RCC-specific marker and to explore if the fraction of RCCs lacking CUBN expression could predict differences in patient survival. $\textbf{Results:}$ CUBN was identified as highly RCC-specific protein with 58% of all primary RCCs staining positive for CUBN using immunohistochemistry. In venous tumor thrombi and metastatic lesions, the frequency of CUBN expression was increasingly lost. Clear cell RCC (ccRCC) patients with CUBN positive tumors had a significantly better prognosis compared to patients with CUBN negative tumors, independent of T-stage, Fuhrman grade and nodal status (HR 0.382, CI 0.203–0.719, $P$ = 0.003). $\textbf{Conclusions:}$ CUBN expression is highly specific to RCC and loss of the protein is significantly and independently associated with poor prognosis. CUBN expression in ccRCC provides a promising positive prognostic indicator for patients with ccRCC. The high specificity of CUBN expression in RCC also suggests a role as a new diagnostic marker in clinical cancer differential diagnostics to confirm or rule out RCC.This work was supported by the Swedish Cancer Society and the Knut and Alice Wallenberg Foundation. The work of DJH and GDS was funded by the Chief Scientist Office (grant number ETM37), Renal Cancer Research Fund and Kidney Cancer Scotland

Impact of inactivity and exercise on the vasculature in humans

The effects of inactivity and exercise training on established and novel cardiovascular risk factors are relatively modest and do not account for the impact of inactivity and exercise on vascular risk. We examine evidence that inactivity and exercise have direct effects on both vasculature function and structure in humans. Physical deconditioning is associated with enhanced vasoconstrictor tone and has profound and rapid effects on arterial remodelling in both large and smaller arteries. Evidence for an effect of deconditioning on vasodilator function is less consistent. Studies of the impact of exercise training suggest that both functional and structural remodelling adaptations occur and that the magnitude and time-course of these changes depends upon training duration and intensity and the vessel beds involved. Inactivity and exercise have direct “vascular deconditioning and conditioning” effects which likely modify cardiovascular risk

Impact of cell types and culture methods on the functionality of in vitro liver systems - A review of cell systems for hepatotoxicity assessment.

Xenobiotic safety assessment is an area that impacts a multitude of different industry sectors such as medicinal drugs, agrochemicals, industrial chemicals, cosmetics and environmental contaminants. As such there are a number of well-developed in vitro, in vivo and in silico approaches to evaluate their properties and potential impact on the environment and to humans. Additionally, there is the continual investment in multidisciplinary scientists to explore non-animal surrogate technologies to predict specific toxicological outcomes and to improve our understanding of the biological processes regarding the toxic potential of xenobiotics. Here we provide a concise, critical evaluation of a number of in vitro systems utilised to assess the hepatotoxic potential of xenobiotics

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism