Detection of distant evolutionary relationships between protein families using theory of sequence profile-profile comparison

<p>Abstract</p> <p>Background</p> <p>Detection of common evolutionary origin (homology) is a primary means of inferring protein structure and function. At present, comparison of protein families represented as sequence profiles is arguably the most effective homology detection strategy. However, finding the best way to represent evolutionary information of a protein sequence family in the profile, to compare profiles and to estimate the biological significance of such comparisons, remains an active area of research.</p> <p>Results</p> <p>Here, we present a new homology detection method based on sequence profile-profile comparison. The method has a number of new features including position-dependent gap penalties and a global score system. Position-dependent gap penalties provide a more biologically relevant way to represent and align protein families as sequence profiles. The global score system enables an analytical solution of the statistical parameters needed to estimate the statistical significance of profile-profile similarities. The new method, together with other state-of-the-art profile-based methods (HHsearch, COMPASS and PSI-BLAST), is benchmarked in all-against-all comparison of a challenging set of SCOP domains that share at most 20% sequence identity. For benchmarking, we use a reference ("gold standard") free model-based evaluation framework. Evaluation results show that at the level of protein domains our method compares favorably to all other tested methods. We also provide examples of the new method outperforming structure-based similarity detection and alignment. The implementation of the new method both as a standalone software package and as a web server is available at <url>http://www.ibt.lt/bioinformatics/coma</url>.</p> <p>Conclusion</p> <p>Due to a number of developments, the new profile-profile comparison method shows an improved ability to match distantly related protein domains. Therefore, the method should be useful for annotation and homology modeling of uncharacterized proteins.</p

Quantum Measurement Theory in Gravitational-Wave Detectors

The fast progress in improving the sensitivity of the gravitational-wave (GW) detectors, we all have witnessed in the recent years, has propelled the scientific community to the point, when quantum behaviour of such immense measurement devices as kilometer-long interferometers starts to matter. The time, when their sensitivity will be mainly limited by the quantum noise of light is round the corner, and finding the ways to reduce it will become a necessity. Therefore, the primary goal we pursued in this review was to familiarize a broad spectrum of readers with the theory of quantum measurements in the very form it finds application in the area of gravitational-wave detection. We focus on how quantum noise arises in gravitational-wave interferometers and what limitations it imposes on the achievable sensitivity. We start from the very basic concepts and gradually advance to the general linear quantum measurement theory and its application to the calculation of quantum noise in the contemporary and planned interferometric detectors of gravitational radiation of the first and second generation. Special attention is paid to the concept of Standard Quantum Limit and the methods of its surmounting.Comment: 147 pages, 46 figures, 1 table. Published in Living Reviews in Relativit

Infinitesimal Idealization, Easy Road Nominalism, and Fractional Quantum Statistics

It has been recently debated whether there exists a so-called “easy road” to nominalism. In this essay, I attempt to fill a lacuna in the debate by making a connection with the literature on infinite and infinitesimal idealization in science through an example from mathematical physics that has been largely ignored by philosophers. Specifically, by appealing to John Norton’s distinction between idealization and approximation, I argue that the phenomena of fractional quantum statistics bears negatively on Mary Leng’s proposed path to easy road nominalism, thereby partially defending Mark Colyvan’s claim that there is no easy road to nominalism

HIV-1 Tat and AIDS-associated cancer: targeting the cellular anti-cancer barrier?

The acquired immunodeficiency syndrome (AIDS) is accompanied by a significant increase in the incidence of neoplasms. Several causative agents have been proposed for this phenomenon. These include immunodeficiency and oncogenic DNA viruses and the HIV-1 protein Tat. Cancer in general is closely linked to genomic instability and DNA repair mechanisms. The latter maintains genomic stability and serves as a cellular anti-cancer barrier. Defects in DNA repair pathway are associated with carcinogenesis

Profiling the HER3/PI3K Pathway in Breast Tumors Using Proximity-Directed Assays Identifies Correlations between Protein Complexes and Phosphoproteins

The identification of patients for targeted antineoplastic therapies requires accurate measurement of therapeutic targets and associated signaling complexes. HER3 signaling through heterodimerization is an important growth-promoting mechanism in several tumor types and may be a principal resistance mechanism by which EGFR and HER2 expressing tumors elude targeted therapies. Current methods that can study these interactions are inadequate for formalin-fixed, paraffin-embedded (FFPE) tumor samples.Herein, we describe a panel of proximity-directed assays capable of measuring protein-interactions and phosphorylation in FFPE samples in the HER3/PI3K/Akt pathway and examine the capability of these assays to inform on the functional state of the pathway. We used FFPE breast cancer cell line and tumor models for this study. In breast cancer cell lines we observe both ligand-dependent and independent activation of the pathway and strong correlations between measured activation of key analytes. When selected cell lines are treated with HER2 inhibitors, we not only observe the expected molecular effects based on mechanism of action knowledge, but also novel effects of HER2 inhibition on key targets in the HER receptor pathway. Significantly, in a xenograft model of delayed tumor fixation, HER3 phosphorylation is unstable, while alternate measures of pathway activation, such as formation of the HER3PI3K complex is preserved. Measurements in breast tumor samples showed correlations between HER3 phosphorylation and receptor interactions, obviating the need to use phosphorylation as a surrogate for HER3 activation.This assay system is capable of quantitatively measuring therapeutically relevant responses and enables molecular profiling of receptor networks in both preclinical and tumor models

Evolutionary Analysis of Inter-Farm Transmission Dynamics in a Highly Pathogenic Avian Influenza Epidemic

Phylogenetic studies have largely contributed to better understand the emergence, spread and evolution of highly pathogenic avian influenza during epidemics, but sampling of genetic data has never been detailed enough to allow mapping of the spatiotemporal spread of avian influenza viruses during a single epidemic. Here, we present genetic data of H7N7 viruses produced from 72% of the poultry farms infected during the 2003 epidemic in the Netherlands. We use phylogenetic analyses to unravel the pathways of virus transmission between farms and between infected areas. In addition, we investigated the evolutionary processes shaping viral genetic diversity, and assess how they could have affected our phylogenetic analyses. Our results show that the H7N7 virus was characterized by a high level of genetic diversity driven mainly by a high neutral substitution rate, purifying selection and limited positive selection. We also identified potential reassortment in the three genes that we have tested, but they had only a limited effect on the resolution of the inter-farm transmission network. Clonal sequencing analyses performed on six farm samples showed that at least one farm sample presented very complex virus diversity and was probably at the origin of chronological anomalies in the transmission network. However, most virus sequences could be grouped within clearly defined and chronologically sound clusters of infection and some likely transmission events between farms located 0.8–13 Km apart were identified. In addition, three farms were found as most likely source of virus introduction in distantly located new areas. These long distance transmission events were likely facilitated by human-mediated transport, underlining the need for strict enforcement of biosafety measures during outbreaks. This study shows that in-depth genetic analysis of virus outbreaks at multiple scales can provide critical information on virus transmission dynamics and can be used to increase our capacity to efficiently control epidemics

Examination of polymorphic glutathione S-transferase (GST) genes, tobacco smoking and prostate cancer risk among Men of African Descent: A case-control study

<p>Abstract</p> <p>Background</p> <p>Polymorphisms in <it>glutathione S-transferase </it>(GST) genes may influence response to oxidative stress and modify prostate cancer (PCA) susceptibility. These enzymes generally detoxify endogenous and exogenous agents, but also participate in the activation and inactivation of oxidative metabolites that may contribute to PCA development. Genetic variations within selected <it>GST </it>genes may influence PCA risk following exposure to carcinogen compounds found in cigarette smoke and decreased the ability to detoxify them. Thus, we evaluated the effects of polymorphic <it>GSTs </it>(<it>M1</it>, <it>T1</it>, and <it>P1</it>) alone and combined with cigarette smoking on PCA susceptibility.</p> <p>Methods</p> <p>In order to evaluate the effects of <it>GST </it>polymorphisms in relation to PCA risk, we used TaqMan allelic discrimination assays along with a multi-faceted statistical strategy involving conventional and advanced statistical methodologies (e.g., Multifactor Dimensionality Reduction and Interaction Graphs). Genetic profiles collected from 873 men of African-descent (208 cases and 665 controls) were utilized to systematically evaluate the single and joint modifying effects of <it>GSTM1 </it>and <it>GSTT1 </it>gene deletions, <it>GSTP1 </it>105 Val and cigarette smoking on PCA risk.</p> <p>Results</p> <p>We observed a moderately significant association between risk among men possessing at least one variant <it>GSTP1 </it>105 Val allele (OR = 1.56; 95%CI = 0.95-2.58; p = 0.049), which was confirmed by MDR permutation testing (p = 0.001). We did not observe any significant single gene effects among <it>GSTM1 </it>(OR = 1.08; 95%CI = 0.65-1.82; p = 0.718) and <it>GSTT1 </it>(OR = 1.15; 95%CI = 0.66-2.02; p = 0.622) on PCA risk among all subjects. Although the <it>GSTM1</it>-<it>GSTP1 </it>pairwise combination was selected as the best two factor LR and MDR models (p = 0.01), assessment of the hierarchical entropy graph suggested that the observed synergistic effect was primarily driven by the <it>GSTP1 </it>Val marker. Notably, the <it>GSTM1</it>-<it>GSTP1 </it>axis did not provide additional information gain when compared to either loci alone based on a hierarchical entropy algorithm and graph. Smoking status did not significantly modify the relationship between the <it>GST </it>SNPs and PCA.</p> <p>Conclusion</p> <p>A moderately significant association was observed between PCA risk and men possessing at least one variant <it>GSTP1 </it>105 Val allele (p = 0.049) among men of African descent. We also observed a 2.1-fold increase in PCA risk associated with men possessing the <it>GSTP1 </it>(Val/Val) and <it>GSTM1 </it>(*1/*1 + *1/*0) alleles. MDR analysis validated these findings; detecting <it>GSTP1 </it>105 Val (p = 0.001) as the best single factor for predicting PCA risk. Our findings emphasize the importance of utilizing a combination of traditional and advanced statistical tools to identify and validate single gene and multi-locus interactions in relation to cancer susceptibility.</p

Study of B Meson Production in p plus Pb Collisions at root s(NN)=5.02 TeV Using Exclusive Hadronic Decays

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