428 research outputs found

    Efficient algorithms for reconstructing gene content by co-evolution

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    <p>Abstract</p> <p>Background</p> <p>In a previous study we demonstrated that co-evolutionary information can be utilized for improving the accuracy of ancestral gene content reconstruction. To this end, we defined a new computational problem, the Ancestral Co-Evolutionary (ACE) problem, and developed algorithms for solving it.</p> <p>Results</p> <p>In the current paper we generalize our previous study in various ways. First, we describe new efficient computational approaches for solving the ACE problem. The new approaches are based on reductions to classical methods such as linear programming relaxation, quadratic programming, and min-cut. Second, we report new computational hardness results related to the ACE, including practical cases where it can be solved in polynomial time.</p> <p>Third, we generalize the ACE problem and demonstrate how our approach can be used for inferring parts of the genomes of <it>non-ancestral</it> organisms. To this end, we describe a heuristic for finding the portion of the genome ('dominant set’) that can be used to reconstruct the rest of the genome with the lowest error rate. This heuristic utilizes both evolutionary information and co-evolutionary information.</p> <p>We implemented these algorithms on a large input of the ACE problem (95 unicellular organisms, 4,873 protein families, and 10, 576 of co-evolutionary relations), demonstrating that some of these algorithms can outperform the algorithm used in our previous study. In addition, we show that based on our approach a ’dominant set’ cab be used reconstruct a major fraction of a genome (up to 79%) with relatively low error-rate (<it>e.g.</it> 0.11). We find that the ’dominant set’ tends to include metabolic and regulatory genes, with high evolutionary rate, and low protein abundance and number of protein-protein interactions.</p> <p>Conclusions</p> <p>The <it>ACE</it> problem can be efficiently extended for inferring the genomes of organisms that exist today. In addition, it may be solved in polynomial time in many practical cases. Metabolic and regulatory genes were found to be the most important groups of genes necessary for reconstructing gene content of an organism based on other related genomes.</p

    Discovering local patterns of co - evolution: computational aspects and biological examples

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    <p>Abstract</p> <p>Background</p> <p>Co-evolution is the process in which two (or more) sets of orthologs exhibit a similar or correlative pattern of evolution. Co-evolution is a powerful way to learn about the functional interdependencies between sets of genes and cellular functions and to predict physical interactions. More generally, it can be used for answering fundamental questions about the evolution of biological systems.</p> <p>Orthologs that exhibit a strong signal of co-evolution in a certain part of the evolutionary tree may show a mild signal of co-evolution in other branches of the tree. The major reasons for this phenomenon are noise in the biological input, genes that gain or lose functions, and the fact that some measures of co-evolution relate to rare events such as positive selection. Previous publications in the field dealt with the problem of finding sets of genes that co-evolved along an entire underlying phylogenetic tree, without considering the fact that often co-evolution is local.</p> <p>Results</p> <p>In this work, we describe a new set of biological problems that are related to finding patterns of <it>local </it>co-evolution. We discuss their computational complexity and design algorithms for solving them. These algorithms outperform other bi-clustering methods as they are designed specifically for solving the set of problems mentioned above.</p> <p>We use our approach to trace the co-evolution of fungal, eukaryotic, and mammalian genes at high resolution across the different parts of the corresponding phylogenetic trees. Specifically, we discover regions in the fungi tree that are enriched with positive evolution. We show that metabolic genes exhibit a remarkable level of co-evolution and different patterns of co-evolution in various biological datasets.</p> <p>In addition, we find that protein complexes that are related to gene expression exhibit non-homogenous levels of co-evolution across different parts of the <it>fungi </it>evolutionary line. In the case of mammalian evolution, signaling pathways that are related to <it>neurotransmission </it>exhibit a relatively higher level of co-evolution along the <it>primate </it>subtree.</p> <p>Conclusions</p> <p>We show that finding local patterns of co-evolution is a computationally challenging task and we offer novel algorithms that allow us to solve this problem, thus opening a new approach for analyzing the evolution of biological systems.</p

    Small Polarons in Transition Metal Oxides

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    The formation of polarons is a pervasive phenomenon in transition metal oxide compounds, with a strong impact on the physical properties and functionalities of the hosting materials. In its original formulation the polaron problem considers a single charge carrier in a polar crystal interacting with its surrounding lattice. Depending on the spatial extension of the polaron quasiparticle, originating from the coupling between the excess charge and the phonon field, one speaks of small or large polarons. This chapter discusses the modeling of small polarons in real materials, with a particular focus on the archetypal polaron material TiO2. After an introductory part, surveying the fundamental theoretical and experimental aspects of the physics of polarons, the chapter examines how to model small polarons using first principles schemes in order to predict, understand and interpret a variety of polaron properties in bulk phases and surfaces. Following the spirit of this handbook, different types of computational procedures and prescriptions are presented with specific instructions on the setup required to model polaron effects.Comment: 36 pages, 12 figure

    Rational manipulation of mRNA folding free energy allows rheostat control of pneumolysin production by Streptococcus pneumoniae

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    Rational manipulation of mRNA folding free energy allows rheostat control of pneumolysin production by Streptococcus pneumoniaeThe contribution of specific factors to bacterial virulence is generally investigated through creation of genetic "knockouts" that are then compared to wild-type strains or complemented mutants. This paradigm is useful to understand the effect of presence vs. absence of a specific gene product but cannot account for concentration-dependent effects, such as may occur with some bacterial toxins. In order to assess threshold and dose-response effects of virulence factors, robust systems for tunable expression are required. Recent evidence suggests that the folding free energy (?G) of the 5' end of mRNA transcripts can have a significant effect on translation efficiency and overall protein abundance. Here we demonstrate that rational alteration of 5' mRNA folding free energy by introduction of synonymous mutations allows for predictable changes in pneumolysin (PLY) expression by Streptococcus pneumoniae without the need for chemical inducers or heterologous promoters. We created a panel of isogenic S. pneumoniae strains, differing only in synonymous (silent) mutations at the 5' end of the PLY mRNA that are predicted to alter ?G. Such manipulation allows rheostat-like control of PLY production and alters the cytotoxicity of whole S. pneumoniae on primary and immortalized human cells. These studies provide proof-of-principle for further investigation of mRNA ?G manipulation as a tool in studies of bacterial pathogenesis.National Institutes of Health (www.nih.gov) (R01 AI092743 and R21 AI111020 to A.J.R.). F.E.A. was supported by the Portuguese Foundation for Science and Technology (www.fct.pt) SFRH/BD/33901/2009 and the Luso-American Development Foundation (www.flad.pt). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

    Predictors of linkage to care following community-based HIV counseling and testing in rural Kenya

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    Despite innovations in HIV counseling and testing (HCT), important gaps remain in understanding linkage to care. We followed a cohort diagnosed with HIV through a community-based HCT campaign that trained persons living with HIV/AIDS (PLHA) as navigators. Individual, interpersonal, and institutional predictors of linkage were assessed using survival analysis of self-reported time to enrollment. Of 483 persons consenting to follow-up, 305 (63.2%) enrolled in HIV care within 3 months. Proportions linking to care were similar across sexes, barring a sub-sample of men aged 18–25 years who were highly unlikely to enroll. Men were more likely to enroll if they had disclosed to their spouse, and women if they had disclosed to family. Women who anticipated violence or relationship breakup were less likely to link to care. Enrolment rates were significantly higher among participants receiving a PLHA visit, suggesting that a navigator approach may improve linkage from community-based HCT campaigns.Vestergaard Frandse

    Professionalism, Golf Coaching and a Master of Science Degree: A commentary

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    As a point of reference I congratulate Simon Jenkins on tackling the issue of professionalism in coaching. As he points out coaching is not a profession, but this does not mean that coaching would not benefit from going through a professionalization process. As things stand I find that the stimulus article unpacks some critically important issues of professionalism, broadly within the context of golf coaching. However, I am not sure enough is made of understanding what professional (golf) coaching actually is nor how the development of a professional golf coach can be facilitated by a Master of Science Degree (M.Sc.). I will focus my commentary on these two issues

    Economic Support to Patients in HIV and TB Grants in Rounds 7 and 10 from the Global Fund to Fight AIDS, Tuberculosis and Malaria.

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    People with TB and/or HIV frequently experience severe economic barriers to health care, including out-of-pocket expenses related to diagnosis and treatment, as well as indirect costs due to loss of income. These barriers can both aggravate economic hardship and prevent or delay diagnosis, treatment and successful outcome, leading to increased transmission, morbidity and mortality. WHO, UNAIDS and the ILO argue that economic support of various kinds is essential to enable vulnerable people to protect themselves from infection, avoid delayed diagnosis and treatment, overcome barriers to adherence, and avert destitution. This paper analyses successful country proposals to the Global Fund to Fight AIDS, Tuberculosis and Malaria that include economic support in Rounds 7 and 10; 36 and 20 HIV and TB grants in Round 7 and 32 and 26, respectively, in Round 10. Of these, up to 84 percent included direct or indirect economic support for beneficiaries, although the amount constituted a very small proportion of the total grant. In TB grants, the objectives of economic support were generally clearly stated, and focused on mechanisms to improve treatment uptake and adherence, and the case was most clearly made for MDR-TB patients. In HIV grants, the objectives were much broader in scope, including mitigation of adverse economic and social effects of HIV and its treatment on both patients and families. The analysis shows that economic support is on the radar for countries developing Global Fund proposals, and a wide range of economic support activities are in place. In order to move forward in this area, the wealth of country experience that exists needs to be collated, assessed and disseminated. In addition to trials, operational research and programme evaluations, more precise guidance to countries is needed to inform evidence-based decision about activities that are cost-effective, affordable and feasible

    Reduced mRNA Secondary-Structure Stability Near the Start Codon Indicates Functional Genes in Prokaryotes

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    Several recent studies have found that selection acts on synonymous mutations at the beginning of genes to reduce mRNA secondary-structure stability, presumably to aid in translation initiation. This observation suggests that a metric of relative mRNA secondary-structure stability, ZΔG, could be used to test whether putative genes are likely to be functionally important. Using the Escherichia coli genome, we compared the mean ZΔG of genes with known functions, genes with known orthologs, genes where function and orthology are unknown, and pseudogenes. Genes in the first two categories demonstrated similar levels of selection for reduced stability (increased ZΔG), whereas for pseudogenes stability did not differ from our null expectation. Surprisingly, genes where function and orthology were unknown were also not different from the null expectation, suggesting that many of these open reading frames are not functionally important. We extended our analysis by constructing a Bayesian phylogenetic mixed model based on data from 145 prokaryotic genomes. As in E. coli, genes with no known function had consistently lower ZΔG, even though we expect that many of the currently unannotated genes will ultimately have their functional utility discovered. Our findings suggest that functional genes tend to evolve increased ZΔG, whereas nonfunctional ones do not. Therefore, ZΔG may be a useful metric for identifying genes of potentially important function and could be used to target genes for further functional study

    Visual gene developer: a fully programmable bioinformatics software for synthetic gene optimization

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    <p>Abstract</p> <p>Background</p> <p>Direct gene synthesis is becoming more popular owing to decreases in gene synthesis pricing. Compared with using natural genes, gene synthesis provides a good opportunity to optimize gene sequence for specific applications. In order to facilitate gene optimization, we have developed a stand-alone software called Visual Gene Developer.</p> <p>Results</p> <p>The software not only provides general functions for gene analysis and optimization along with an interactive user-friendly interface, but also includes unique features such as programming capability, dedicated mRNA secondary structure prediction, artificial neural network modeling, network & multi-threaded computing, and user-accessible programming modules. The software allows a user to analyze and optimize a sequence using main menu functions or specialized module windows. Alternatively, gene optimization can be initiated by designing a gene construct and configuring an optimization strategy. A user can choose several predefined or user-defined algorithms to design a complicated strategy. The software provides expandable functionality as platform software supporting module development using popular script languages such as VBScript and JScript in the software programming environment.</p> <p>Conclusion</p> <p>Visual Gene Developer is useful for both researchers who want to quickly analyze and optimize genes, and those who are interested in developing and testing new algorithms in bioinformatics. The software is available for free download at <it><url>http://www.visualgenedeveloper.net</url></it>.</p
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