Reliabilities of parsimony-based and likelihood-based methods for detecting positive selection at single amino acid sites.

The reliabilities of parsimony-based and likelihood-based methods for inferring positive selection at single amino acid sites were studied using the nucleotide sequences of human leukocyte antigen (HLA) genes, in which positive selection is known to be operating at the antigen recognition site. The results indicate that the inference by parsimony-based methods is robust to the use of different evolutionary models and generally more reliable than that by likelihood-based methods. In contrast, the results obtained by likelihood-based methods depend on the models and on the initial parameter values used. It is sometimes difficult to obtain the maximum likelihood estimates of parameters for a given model, and the results obtained may be false negatives or false positives depending on the initial parameter values. It is therefore preferable to use parsimony-based methods as long as the number of sequences is relatively large and the branch lengths of the phylogenetic tree are relatively small.     

Identification of amino acid residues of Ras protein that are essential for signal-transducing activity but not for enhancement of GTPase activity by GAP.

To determine the amino acid residues required for the signal-transducing activity of the human c-Ha-Ras protein, we introduced point mutations at residues 45-54 near the 'effector region' (residues 32-40). We transfected PC12 cells with these mutant genes and also micro-injected the mutant proteins, bound with an unhydrolyzable GTP analog, into PC12 cells. Both procedures showed that Val45----Glu and Gly48----Cys mutations impaired the ability of the Ras protein to induce morphological change of PC12 cells. These mutations did not affect the guanine nucleotide-binding activity or GTPase activity in the absence or presence of bovine GTPase-activating protein (GAP). Therefore, the Val45 and Gly48 residues should be included by definition in the effector region responsible for the signal transduction, while only a subset of the effector-region residues is required for enhancement of the GTPase activity by GAP.     

Siliques are Red1 from Arabidopsis acts as a bidirectional amino acid transporter that is crucial for the amino acid homeostasis of siliques

Many membrane proteins are involved in the transport of nutrients in plants. While the import of amino acids into plant cells is, in principle, well understood, their export has been insufficiently described. Here, we present the identification and characterization of the membrane protein Siliques Are Red1 (SIAR1) from Arabidopsis (Arabidopsis thaliana) that is able to translocate amino acids bidirectionally into as well as out of the cell. Analyses in yeast and oocytes suggest a SIAR1-mediated export of amino acids. In Arabidopsis, SIAR1 localizes to the plasma membrane and is expressed in the vascular tissue, in the pericycle, in stamen, and in the chalazal seed coat of ovules and developing seeds. Mutant alleles of SIAR1 accumulate anthocyanins as a symptom of reduced amino acid content in the early stages of silique development. Our data demonstrate that the SIAR1-mediated export of amino acids plays an important role in organic nitrogen allocation and particularly in amino acid homeostasis in developing siliques.     

Identification of amino acid residues in BK virus VP1 that are critical for viability and growth

BK virus (BKV) is a ubiquitous pathogen that establishes a persistent infection in the urinary tract of 80% of the human population. Like other polyomaviruses, the major capsid protein of BKV, virion protein 1 (VP1), is critical for host cell receptor recognition and for proper virion assembly. BKV uses a carbohydrate complex containing alpha(2,3)-linked sialic acid attached to glycoprotein and glycolipid motifs as a cellular receptor. To determine the amino acids important for BKV binding to the sialic acid portion of the complex, we generated a series of 17 point mutations in VP1 and scored them for viral growth. The first set of mutants behaved identically to wild-type virus, suggesting that these amino acids were not critical for virus propagation. Another group of VP1 mutants rendered the virus nonviable. These mutations failed to protect viral DNA from DNase I digestion, indicating a role for these domains in capsid assembly and/or packaging of DNA. A third group of VP1 mutations packaged DNA similarly to the wild type but failed to propagate. The initial burst size of these mutations was similar to that of the wild type, indicating that there is no defect in the lytic release of the mutated virions. Binding experiments revealed that a subset of the BKV mutants were unable to attach to their host cells. These motifs are likely important for sialic acid recognition. We next mapped these mutations onto a model of BKV VP1 to provide atomic insight into the role of these sites in the binding of sialic acid to VP1.     

Combining mathematics and empirical data to predict emergence of RNA viruses that differ in reservoir use

RNA viruses may be particularly capable of contributing to the increasing biomedical problem of infectious disease emergence. Empirical studies and epidemiological models are informative for the understanding of evolutionary processes that promote pathogen emergence, but rarely are these approaches combined in the same study. Here, we used an epidemiology model containing observations of pathogen productivity in reservoirs, as a means to predict which pathogens should be most prone to emerge in a primary host such as humans. We employed as a model system a collection of vesicular stomatitis virus populations that had previously diverged in host-use strategy: specialists, directly selected generalists and indirectly selected (fortuitous) generalists. Using data from experiments where these viral strategists were challenged to grow on unencountered novel hosts in vitro, logistic growth models determined that the directly selected generalist viruses tended to grow best on model reservoirs. Furthermore, when we used the growth data to estimate average reproductive rate across secondary reservoirs, we showed that the combined approach could be used to estimate relative success of the differing virus strategists when encountering a primary host. Our study suggests that synergistic approaches combining epidemiological modelling with empirical data from experimental evolution may be useful for developing efforts to predict which types of pathogens pose the greatest probability of emerging in the future.     

Ratios of radical to conservative amino acid replacement are affected by mutational and compositional factors and may not be indicative of positive Darwinian selection

The ratio of radical to conservative amino acid replacements is frequently used to infer positive Darwinian selection. This method is based on the assumption that radical replacements are more likely than conservative replacements to improve the function of a protein. Therefore, if positive selection plays a major role in the evolution of a protein, one would expect the radical-conservative ratio to exceed the expectation under neutrality. Here, we investigate the possibility that factors unrelated to selection, i.e., transition-transversion ratio, codon usage, genetic code, and amino acid composition, influence the radical-conservative replacement ratio. All factors that have been studied were found to affect the radical-conservative replacement ratio. In particular, amino acid composition and transition-transversion ratio are shown to have the most profound effects. Because none of the studied factors had anything to do with selection (positive or otherwise) and also because all of them (singly or in combination) affected a measure that was supposed to be indicative of positive selection, we conclude that selectional inferences based on radical-conservative replacement ratios should be treated with suspicion.     

Specific amino acid substitutions are not required for transformation by v-myb of avian myeloblastosis virus.

The protein product of the v-myb oncogene of avian myeloblastosis virus, p48v-myb, differs structurally in several ways from its normal cellular homolog, p75c-myb. We demonstrated that the 11 specific amino acid substitutions found in two independent molecular clones of this virus were not required for the transformation of myeloblasts by v-myb.     

Not so different after all: a comparison of methods for detecting amino acid sites under selection

We consider three approaches for estimating the rates of nonsynonymous and synonymous changes at each site in a sequence alignment in order to identify sites under positive or negative selection: (1) a suite of fast likelihood-based counting methods that employ either a single most likely ancestral reconstruction, weighting across all possible ancestral reconstructions, or sampling from ancestral reconstructions; (2) a random effects likelihood (REL) approach, which models variation in nonsynonymous and synonymous rates across sites according to a predefined distribution, with the selection pressure at an individual site inferred using an empirical Bayes approach; and (3) a fixed effects likelihood (FEL) method that directly estimates nonsynonymous and synonymous substitution rates at each site. All three methods incorporate flexible models of nucleotide substitution bias and variation in both nonsynonymous and synonymous substitution rates across sites, facilitating the comparison between the methods. We demonstrate that the results obtained using these approaches show broad agreement in levels of Type I and Type II error and in estimates of substitution rates. Counting methods are well suited for large alignments, for which there is high power to detect positive and negative selection, but appear to underestimate the substitution rate. A REL approach, which is more computationally intensive than counting methods, has higher power than counting methods to detect selection in data sets of intermediate size but may suffer from higher rates of false positives for small data sets. A FEL approach appears to capture the pattern of rate variation better than counting methods or random effects models, does not suffer from as many false positives as random effects models for data sets comprising few sequences, and can be efficiently parallelized. Our results suggest that previously reported differences between results obtained by counting methods and random effects models arise due to a combination of the conservative nature of counting-based methods, the failure of current random effects models to allow for variation in synonymous substitution rates, and the naive application of random effects models to extremely sparse data sets. We demonstrate our methods on sequence data from the human immunodeficiency virus type 1 env and pol genes and simulated alignments.     

Assessment of a method for cultivar selection based on regional trial data

Summary In this study a method for analyzing regional trial data is investigated for its effectiveness in cultivar selection. The method is a synthesis of three procedures: (1) regression analysis for genotype × environment (GE) interaction, and subsequent cluster analysis for grouping cultivars for similarity of response; (2) superiority measure analysis of cultivar performance based on the distance mean square between the test cultivar and the maximum response; (3) type 4 stability analysis for three-way classification data (cultivar × location × year), to measure a cultivar's stability. Each of these three procedures is aimed at different aspects of the selection problem: the first obtains an overview of the types of cultivar response; the second measures a cultivar's general adaptability within the region; the third assesses a cultivar's ability to withstand unpredictable variation, namely that caused by year effects. Four sets of published data, each originally analyzed by a univariate or a multivariate approach, were used as examples. The results suggest that the present method provides direct and useful information for selection purposes. The superiority measure, which is the core of the method, can be used even if the data do not fit the linear model for GE interaction. Plotting the data with a fixed standard represented by the maximum response provides a simple visual tool for identifying environments where a cultivar performs well.Contribution No. C-035 from Research Program Service, Research Branch, Agriculture Canada, Ottawa, Ontario, K1A 0C6     

Simulation study of the reliability and robustness of the statistical methods for detecting positive selection at single amino acid sites

Inferring positive selection at single amino acid sites is of biological and medical importance. Parsimony-based and likelihood-based methods have been developed for this purpose, but the reliabilities of these methods are not well understood. Because the evolutionary models assumed in these methods are only rough approximations to reality, it is desirable that the methods are not very sensitive to violation of the assumptions made. In this study we show by computer simulation that the likelihood-based method is sensitive to violation of the assumptions and produces many false-positive results under certain conditions, whereas the parsimony-based method tends to be conservative. These observations, together with those from previous studies, suggest that the positively selected sites inferred by the parsimony-based method are more reliable than those inferred by the likelihood-based method.     

Structural studies on the Ebola virus matrix protein VP40 indicate that matrix proteins of enveloped RNA viruses are analogues but not homologues

Matrix proteins are the driving force of assembly of enveloped viruses. Their main function is to interact with and polymerize at cellular membranes and link other viral components to the matrix-membrane complex resulting in individual particle shapes and ensuring the integrity of the viral particle. Although matrix proteins of different virus families show functional analogy, they share no sequence or structural homology, Their diversity is also evident in that they use a variety of late domain motifs to commit the cellular vacuolar protein sorting machinery to virus budding. Here, we discuss the structural and functional aspects of teh filovirus matrix protein VP40 and compare them to other known matrix protein structures from vesicular stomatitis virus adn retroviral matrix protein.     

Extract‐SAGE: An integrated platform for cross­analysis and GA­based selection of SAGE data

Serial analysis of gene expression (SAGE) is a powerful quantification technique for gene expression data. The huge amount of tag data in SAGE libraries of samples is difficult to analyze with current SAGE analysis tools. Data is often not provided in a biologically significant way for cross‐analysis and ‐comparison, thus limiting its application. Hence, an integrated software platform that can perform such a complex task is required. Here, we implement set theory for cross‐analyzing gene expression data among different SAGE libraries of tissue sources; up‐ or down‐regulated tissue‐specific tags can be identified computationally. Extract‐SAGE employs a genetic algorithm (GA) to reduce the number of genes among the SAGE libraries. Its representative tag mining will facilitate the discovery of the candidate genes with discriminating gene expression.     

Identification of amino acid residues within simian virus 40 capsid proteins Vp1, Vp2, and Vp3 that are required for their interaction and for viral infection

Interaction of simian virus 40 (SV40) major capsid protein Vp1 with the minor capsid proteins Vp2 and Vp3 is an integral aspect of the SV40 architecture. Two Vp3 sequence elements mediate Vp1 pentamer binding in vitro, Vp3 residues 155 to 190, or D1, and Vp3 residues 222 to 234, or D2. Of the two, D1 but not D2 was necessary and sufficient to direct the interaction with Vp1 in vivo. Rational mutagenesis of Vp3 residues (Phe157, Ile158, Pro164, Gly165, Gly166, Leu177, and Leu181) or Vp1 residues (Val243 and Leu245), based on a structural model of the SV40 Vp1 pentamer complexed with Vp3 D1, was carried out to disrupt the interaction between Vp1 and Vp3 and to study the consequences of these mutations for viral viability. Altering these residues to bulky, charged residues blocked the interaction in vitro. When these alterations were introduced into the viral genome, they reduced viral viability. Mutants with alterations in Vp1 Val243, Leu245, or both to glutamate were nearly nonviable, whereas those with Vp3 alterations reduced, but did not eliminate, viability. Our results defined the residues of Vp1 and the minor capsid proteins that are essential for both the interaction of the capsid proteins and viral viability in permissive cells.     

Nitric oxide donor-mediated inhibition of phosphorylation shows that light-mediated degradation of photosystem II D1 protein and phosphorylation are not tightly linked

An outcome of the photochemistry during oxygenic photosynthesis is the rapid turn over of the D1 protein in the light compared to the other proteins of the photosystem II (PS II) reaction center. D1 is a major factor of PS II instability and its replacement a primary event of the PS II repair cycle. D1 also undergoes redox-dependent phosphorylation prior to its degradation. Although it has been suggested that phosphorylation modulates D1 metabolism, reversible D1 phosphorylation was reported not to be essential for PS II repair in Arabidopsis. Thus, the involvement of phosphorylation in D1 degradation is controversial. We show here that nitric oxide donors inhibit in vivo phosphorylation of the D1 protein in Spirodela without inhibiting degradation of the protein. Thus, D1 phosphorylation is not tightly linked to D1 degradation in the intact plant.