Avoiding or restricting defectors in public goods games?

When creating a public good, strategies or mechanisms are required to handle defectors. We first show mathematically and numerically that prior agreements with posterior compensations provide a strategic solution that leads to substantial levels of cooperation in the context of public goods games, results that are corroborated by available experimental data. Notwithstanding this success, one cannot, as with other approaches, fully exclude the presence of defectors, raising the question of how they can be dealt with to avoid the demise of the common good. We show that both avoiding creation of the common good, whenever full agreement is not reached, and limiting the benefit that disagreeing defectors can acquire, using costly restriction mechanisms, are relevant choices. Nonetheless, restriction mechanisms are found the more favourable, especially in larger group interactions. Given decreasing restriction costs, introducing restraining measures to cope with public goods free-riding issues is the ultimate advantageous solution for all participants, rather than avoiding its creation.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Relative amino acid composition signatures of organisms and environments

BACKGROUND: Identifying organism-environment interactions at the molecular level is crucial to understanding how organisms adapt to and change the chemical and molecular landscape of their habitats. In this work we investigated whether relative amino acid compositions could be used as a molecular signature of an environment and whether such a signature could also be observed at the level of the cellular amino acid composition of the microorganisms that inhabit that environment. METHODOLOGIES/PRINCIPAL FINDINGS: To address these questions we collected and analyzed environmental amino acid determinations from the literature, and estimated from complete genomic sequences the global relative amino acid abundances of organisms that are cognate to the different types of environment. Environmental relative amino acid abundances clustered into broad groups (ocean waters, host-associated environments, grass land environments, sandy soils and sediments, and forest soils), indicating the presence of amino acid signatures specific for each environment. These signatures correlate to those found in organisms. Nevertheless, relative amino acid abundance of organisms was more influenced by GC content than habitat or phylogeny. CONCLUSIONS: Our results suggest that relative amino acid composition can be used as a signature of an environment. In addition, we observed that the relative amino acid composition of organisms is not highly determined by environment, reinforcing previous studies that find GC content to be the major factor correlating to amino acid composition in living organisms.AM was supported by Fundação para a Ciência e a Tecnologia, Portugal, through the postdoctoral grant SFRH/BPD/72256/2010. RA was partially supported by the Ministerio de Ciencia e Innovación (Spain) through grant BFU2010-17704, and by the Generalitat de Catalunya through a grant for research group 2009SGR809. MAS was supported in part by a grant from the US Public Health Service (RO1-GM30054). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Authors wish to thank Albert Sorribas, Enrique Herrero and Ester Vilaprinyo for critical reading of the manuscript and Ester Vilaprinyo for assistance with Wolfram Mathematica software.publishe

Minimal Functional Sites Allow a Classification of Zinc Sites in Proteins

Zinc is indispensable to all forms of life as it is an essential component of many different proteins involved in a wide range of biological processes. Not differently from other metals, zinc in proteins can play different roles that depend on the features of the metal-binding site. In this work, we describe zinc sites in proteins with known structure by means of three-dimensional templates that can be automatically extracted from PDB files and consist of the protein structure around the metal, including the zinc ligands and the residues in close spatial proximity to the ligands. This definition is devised to intrinsically capture the features of the local protein environment that can affect metal function, and corresponds to what we call a minimal functional site (MFS). We used MFSs to classify all zinc sites whose structures are available in the PDB and combined this classification with functional annotation as available in the literature. We classified 77% of zinc sites into ten clusters, each grouping zinc sites with structures that are highly similar, and an additional 16% into seven pseudo-clusters, each grouping zinc sites with structures that are only broadly similar. Sites where zinc plays a structural role are predominant in eight clusters and in two pseudo-clusters, while sites where zinc plays a catalytic role are predominant in two clusters and in five pseudo-clusters. We also analyzed the amino acid composition of the coordination sphere of zinc as a function of its role in the protein, highlighting trends and exceptions. In a period when the number of known zinc proteins is expected to grow further with the increasing awareness of the cellular mechanisms of zinc homeostasis, this classification represents a valuable basis for structure-function studies of zinc proteins, with broad applications in biochemistry, molecular pharmacology and de novo protein design

Quantification of codon selection for comparative bacterial genomics

<p>Abstract</p> <p>Background</p> <p>Statistics measuring codon selection seek to compare genes by their sensitivity to selection for translational efficiency, but existing statistics lack a model for testing the significance of differences between genes. Here, we introduce a new statistic for measuring codon selection, the Adaptive Codon Enrichment (ACE).</p> <p>Results</p> <p>This statistic represents codon usage bias in terms of a probabilistic distribution, quantifying the extent that preferred codons are over-represented in the gene of interest relative to the mean and variance that would result from stochastic sampling of codons. Expected codon frequencies are derived from the observed codon usage frequencies of a broad set of genes, such that they are likely to reflect nonselective, genome wide influences on codon usage (<it>e.g</it>. mutational biases). The relative adaptiveness of synonymous codons is deduced from the frequency of codon usage in a pre-selected set of genes relative to the expected frequency. The ACE can predict both transcript abundance during rapid growth and the rate of synonymous substitutions, with accuracy comparable to or greater than existing metrics. We further examine how the composition of reference gene sets affects the accuracy of the statistic, and suggest methods for selecting appropriate reference sets for any genome, including bacteriophages. Finally, we demonstrate that the ACE may naturally be extended to quantify the genome-wide influence of codon selection in a manner that is sensitive to a large fraction of codons in the genome. This reveals substantial variation among genomes, correlated with the tRNA gene number, even among groups of bacteria where previously proposed whole-genome measures show little variation.</p> <p>Conclusions</p> <p>The statistical framework of the ACE allows rigorous comparison of the level of codon selection acting on genes, both within a genome and between genomes.</p

Parameters for accurate genome alignment

<p>Abstract</p> <p>Background</p> <p>Genome sequence alignments form the basis of much research. Genome alignment depends on various mundane but critical choices, such as how to mask repeats and which score parameters to use. Surprisingly, there has been no large-scale assessment of these choices using real genomic data. Moreover, rigorous procedures to control the rate of spurious alignment have not been employed.</p> <p>Results</p> <p>We have assessed 495 combinations of score parameters for alignment of animal, plant, and fungal genomes. As our gold-standard of accuracy, we used genome alignments implied by multiple alignments of proteins and of structural RNAs. We found the HOXD scoring schemes underlying alignments in the UCSC genome database to be far from optimal, and suggest better parameters. Higher values of the X-drop parameter are not always better. E-values accurately indicate the rate of spurious alignment, but only if tandem repeats are masked in a non-standard way. Finally, we show that γ-centroid (probabilistic) alignment can find highly reliable subsets of aligned bases.</p> <p>Conclusions</p> <p>These results enable more accurate genome alignment, with reliability measures for local alignments and for individual aligned bases. This study was made possible by our new software, LAST, which can align vertebrate genomes in a few hours <url>http://last.cbrc.jp/</url>.</p

Analysis of CpG methylation sites and CGI among human papillomavirus DNA genomes

<p>Abstract</p> <p>Background</p> <p>The Human Papillomavirus (HPV) genome is divided into early and late coding sequences, including 8 open reading frames (ORFs) and a regulatory region (LCR). Viral gene expression may be regulated through epigenetic mechanisms, including cytosine methylation at CpG dinucleotides. We have analyzed the distribution of CpG sites and CpG islands/clusters (CGI) among 92 different HPV genomes grouped in function of their preferential tropism: cutaneous or mucosal. We calculated the proportion of CpG sites (PCS) for each ORF and calculated the expected CpG values for each viral type.</p> <p>Results</p> <p>CpGs are underrepresented in viral genomes. We found a positive correlation between CpG observed and expected values, with mucosal high-risk (HR) virus types showing the smallest O/E ratios. The ranges of the PCS were similar for most genomic regions except <it>E4</it>, where the majority of CpGs are found within islands/clusters. At least one CGI belongs to each <it>E2/E4 </it>region. We found positive correlations between PCS for each viral ORF when compared with the others, except for the LCR against four ORFs and <it>E6 </it>against three other ORFs. The distribution of CpG islands/clusters among HPV groups is heterogeneous and mucosal HR-HPV types exhibit both lower number and shorter island sizes compared to cutaneous and mucosal Low-risk (LR) HPVs (all of them significantly different).</p> <p>Conclusions</p> <p>There is a difference between viral and cellular CpG underrepresentation. There are significant correlations between complete genome PCS and a lack of correlations between several genomic region pairs, especially those involving LCR and <it>E6</it>. <it>L2 </it>and <it>L1 </it>ORF behavior is opposite to that of oncogenes <it>E6 </it>and <it>E7</it>. The first pair possesses relatively low numbers of CpG sites clustered in CGIs while the oncogenes possess a relatively high number of CpG sites not associated to CGIs. In all HPVs, <it>E2/E4 </it>is the only region with at least one CGI and shows a higher content of CpG sites in every HPV type with an identified <it>E4</it>. The mucosal HR-HPVs show either the shortest CGI size, followed by the mucosal LR-HPVs and lastly by the cutaneous viral subgroup, and a trend to the lowest CGI number, followed by the cutaneous viral subgroup and lastly by the mucosal LR-HPVs.</p

Clustering of classical swine fever virus isolates by codon pair bias

<p>Abstract</p> <p>Background</p> <p>The genetic code consists of non-random usage of synonymous codons for the same amino acids, termed codon bias or codon usage. Codon juxtaposition is also non-random, referred to as codon context bias or codon pair bias. The codon and codon pair bias vary among different organisms, as well as with viruses. Reasons for these differences are not completely understood. For classical swine fever virus (CSFV), it was suggested that the synonymous codon usage does not significantly influence virulence, but the relationship between variations in codon pair usage and CSFV virulence is unknown. Virulence can be related to the fitness of a virus: Differences in codon pair usage influence genome translation efficiency, which may in turn relate to the fitness of a virus. Accordingly, the potential of the codon pair bias for clustering CSFV isolates into classes of different virulence was investigated.</p> <p>Results</p> <p>The complete genomic sequences encoding the viral polyprotein of 52 different CSFV isolates were analyzed. This included 49 sequences from the GenBank database (NCBI) and three newly sequenced genomes. The codon usage did not differ among isolates of different virulence or genotype. In contrast, a clustering of isolates based on their codon pair bias was observed, clearly discriminating highly virulent isolates and vaccine strains on one side from moderately virulent strains on the other side. However, phylogenetic trees based on the codon pair bias and on the primary nucleotide sequence resulted in a very similar genotype distribution.</p> <p>Conclusion</p> <p>Clustering of CSFV genomes based on their codon pair bias correlate with the genotype rather than with the virulence of the isolates.</p