Genotyping of Bacillus cereus Strains by Microarray-Based Resequencing

The ability to distinguish microbial pathogens from closely related but nonpathogenic strains is key to understanding the population biology of these organisms. In this regard, Bacillus anthracis, the bacterium that causes inhalational anthrax, is of interest because it is closely related and often difficult to distinguish from other members of the B. cereus group that can cause diverse diseases. We employed custom-designed resequencing arrays (RAs) based on the genome sequence of Bacillus anthracis to generate 422 kb of genomic sequence from a panel of 41 Bacillus cereus sensu lato strains. Here we show that RAs represent a “one reaction” genotyping technology with the ability to discriminate between highly similar B. anthracis isolates and more divergent strains of the B. cereus s.l. Clade 1. Our data show that RAs can be an efficient genotyping technology for pre-screening the genetic diversity of large strain collections to selected the best candidates for whole genome sequencing

Tridimensional model structure and patterns of molecular evolution of Pepino mosaic virus TGBp3 protein

<p>Abstract</p> <p>Background</p> <p><it>Pepino mosaic virus </it>(PepMV) is considered one of the most dangerous pathogens infecting tomatoes worldwide. The virus is highly diverse and four distinct genotypes, as well as inter-strain recombinants, have already been described. The isolates display a wide range on symptoms on infected plant species, ranging from mild mosaic to severe necrosis. However, little is known about the mechanisms and pattern of PepMV molecular evolution and about the role of individual proteins in host-pathogen interactions.</p> <p>Methods</p> <p>The nucleotide sequences of the triple gene block 3 (TGB3) from PepMV isolates varying in symptomatology and geographic origin have been analyzed. The modes and patterns of molecular evolution of the TGBp3 protein were investigated by evaluating the selective constraints to which particular amino acid residues have been subjected during the course of diversification. The tridimensional structure of TGBp3 protein has been modeled <it>de novo </it>using the Rosetta algorithm. The correlation between symptoms development and location of specific amino acids residues was analyzed.</p> <p>Results</p> <p>The results have shown that TGBp3 has been evolving mainly under the action of purifying selection operating on several amino acid sites, thus highlighting its functional role during PepMV infection. Interestingly, amino acid 67, which has been previously shown to be a necrosis determinant, was found to be under positive selection.</p> <p>Conclusions</p> <p>Identification of diverse selection events in TGB3p3 will help unraveling its biological functions and is essential to an understanding of the evolutionary constraints exerted on the <it>Potexvirus </it>genome. The estimated tridimensional structure of TGBp3 will serve as a platform for further sequence, structural and function analysis and will stimulate new experimental advances.</p

Integrated Assessment of Genomic Correlates of Protein Evolutionary Rate

Rates of evolution differ widely among proteins, but the causes and consequences of such differences remain under debate. With the advent of high-throughput functional genomics, it is now possible to rigorously assess the genomic correlates of protein evolutionary rate. However, dissecting the correlations among evolutionary rate and these genomic features remains a major challenge. Here, we use an integrated probabilistic modeling approach to study genomic correlates of protein evolutionary rate in Saccharomyces cerevisiae. We measure and rank degrees of association between (i) an approximate measure of protein evolutionary rate with high genome coverage, and (ii) a diverse list of protein properties (sequence, structural, functional, network, and phenotypic). We observe, among many statistically significant correlations, that slowly evolving proteins tend to be regulated by more transcription factors, deficient in predicted structural disorder, involved in characteristic biological functions (such as translation), biased in amino acid composition, and are generally more abundant, more essential, and enriched for interaction partners. Many of these results are in agreement with recent studies. In addition, we assess information contribution of different subsets of these protein properties in the task of predicting slowly evolving proteins. We employ a logistic regression model on binned data that is able to account for intercorrelation, non-linearity, and heterogeneity within features. Our model considers features both individually and in natural ensembles (“meta-features”) in order to assess joint information contribution and degree of contribution independence. Meta-features based on protein abundance and amino acid composition make strong, partially independent contributions to the task of predicting slowly evolving proteins; other meta-features make additional minor contributions. The combination of all meta-features yields predictions comparable to those based on paired species comparisons, and approaching the predictive limit of optimal lineage-insensitive features. Our integrated assessment framework can be readily extended to other correlational analyses at the genome scale

PPR proteins - orchestrators of organelle RNA metabolism.

Pentatricopeptide repeat (PPR) proteins are important RNA regulators in chloroplasts and mitochondria, aiding in RNA editing, maturation, stabilisation or intron splicing, and in transcription and translation of organellar genes. In this review, we summarise all PPR proteins documented so far in plants and the green alga Chlamydomonas. By further analysis of the known target RNAs from Arabidopsis thaliana PPR proteins, we find that all organellar-encoded complexes are regulated by these proteins, although to differing extents. In particular, the orthologous complexes of NADH dehydrogenase (Complex I) in the mitochondria and NADH dehydrogenase-like (NDH) complex in the chloroplast were the most regulated, with respectively 60 and 28% of all characterised A. thaliana PPR proteins targeting their genes

The two tryptophans of β2-microglobulin have distinct roles in function and folding and might represent two independent responses to evolutionary pressure

We have recently discovered that the two tryptophans of human β2-microglobulin have distinctive roles within the structure and function of the protein. Deeply buried in the core, Trp95 is essential for folding stability, whereas Trp60, which is solvent-exposed, plays a crucial role in promoting the binding of β2-microglobulin to the heavy chain of the class I major histocompatibility complex (MHCI). We have previously shown that the thermodynamic disadvantage of having Trp60 exposed on the surface is counter-balanced by the perfect fit between it and a cavity within the MHCI heavy chain that contributes significantly to the functional stabilization of the MHCI. Therefore, based on the peculiar differences of the two tryptophans, we have analysed the evolution of β2-microglobulin with respect to these residues

Computational analysis of the evolutionarily conserved Missing In Metastasis/Metastasis Suppressor 1 gene predicts novel interactions, regulatory regions and transcriptional control

Missing in Metastasis (MIM), or Metastasis Suppressor 1 (MTSS1), is a highly conserved protein, which links the plasma membrane to the actin cytoskeleton. MIM has been implicated in various cancers, however, its modes of action remain largely enigmatic. Here, we performed an extensive in silico characterisation of MIM to gain better understanding of its function. We detected previously unappreciated functional motifs including adaptor protein (AP) complex interaction site and a C-helix, pointing to a role in endocytosis and regulation of actin dynamics, respectively. We also identified new functional regions, characterised with phosphorylation sites or distinct hydrophilic properties. Strong negative selection during evolution, yielding high conservation of MIM, has been combined with positive selection at key sites. Interestingly, our analysis of intra-molecular co-evolution revealed potential regulatory hotspots that coincided with reduced potentially\ua0pathogenic polymorphisms. We explored databases for the mutations and expression levels of MIM in cancer. Experimentally, we focused on chronic lymphocytic leukaemia (CLL), where MIM showed high overall expression, however, downregulation on poor prognosis samples. Finally, we propose strong conservation of MTSS1 also on the transcriptional level and predict novel transcriptional regulators. Our data highlight important targets for future studies on the role of MIM in different tissues and cancers