Use of a multi-way method to analyze the amino acid composition of a conserved group of orthologous proteins in prokaryotes

BACKGROUND: Amino acids in proteins are not used equally. Some of the differences in the amino acid composition of proteins are between species (mainly due to nucleotide composition and lifestyle) and some are between proteins from the same species (related to protein function, expression or subcellular localization, for example). As several factors contribute to the different amino acid usage in proteins, it is difficult both to analyze these differences and to separate the contributions made by each factor. RESULTS: Using a multi-way method called Tucker3, we have analyzed the amino composition of a set of 64 orthologous groups of proteins present in 62 archaea and bacteria. This dataset corresponds to essential proteins such as ribosomal proteins, tRNA synthetases and translational initiation or elongation factors, which are common to all the species analyzed. The Tucker3 model can be used to study the amino acid variability within and between species by taking into consideration the tridimensionality of the data set. We found that the main factor behind the amino acid composition of proteins is independent of the organism or protein function analyzed. This factor must be related to the biochemical characteristics of each amino acid. The difference between the non-ribosomal proteins and the ribosomal proteins (which are rich in arginine and lysine) is the main factor behind the differences in amino acid composition within species, while G+C content and optimal growth temperature are the main factors behind the differences in amino acid usage between species. CONCLUSION: We show that a multi-way method is useful for comparing the amino acid composition of several groups of orthologous proteins from the same group of species. This kind of dataset is extremely useful for detecting differences between and within species

CAIcal: A combined set of tools to assess codon usage adaptation

<p>Abstract</p> <p>Background</p> <p>The Codon Adaptation Index (CAI) was first developed to measure the synonymous codon usage bias for a DNA or RNA sequence. The CAI quantifies the similarity between the synonymous codon usage of a gene and the synonymous codon frequency of a reference set.</p> <p>Results</p> <p>We describe here CAIcal, a web-server available at <url>http://genomes.urv.es/CAIcal</url> that includes a complete set of utilities related with the CAI. The server provides useful important features, such as the calculation and graphical representation of the CAI along either an individual sequence or a protein multiple sequence alignment translated to DNA. The automated calculation of CAI and its expected value is also included as one of the CAIcal tools. The software is also free to be downloaded as a standalone application for local use.</p> <p>Conclusion</p> <p>The CAIcal server provides a complete set of tools to assess codon usage adaptation and to help in genome annotation.</p> <p>Reviewers</p> <p>This article was reviewed by Purificación López-García, Dan Graur, Rob Knight and Shamil Sunyaev.</p

HEG-DB: a database of predicted highly expressed genes in prokaryotic complete genomes under translational selection

The highly expressed genes database (HEG-DB) is a genomic database that includes the prediction of which genes are highly expressed in prokaryotic complete genomes under strong translational selection. The current version of the database contains general features for almost 200 genomes under translational selection, including the correspondence analysis of the relative synonymous codon usage for all genes, and the analysis of their highly expressed genes. For each genome, the database contains functional and positional information about the predicted group of highly expressed genes. This information can also be accessed using a search engine. Among other statistical parameters, the database also provides the Codon Adaptation Index (CAI) for all of the genes using the codon usage of the highly expressed genes as a reference set. The ‘Pathway Tools Omics Viewer’ from the BioCyc database enables the metabolic capabilities of each genome to be explored, particularly those related to the group of highly expressed genes. The HEG-DB is freely available at http://genomes.urv.cat/HEG-DB

OGtree: a tool for creating genome trees of prokaryotes based on overlapping genes

OGtree is a web-based tool for constructing genome trees of prokaryotic species based on a measure of combining overlapping-gene content and overlapping-gene order in their whole genomes. The overlapping genes (OGs) are defined as adjacent genes whose coding sequences overlap partially or entirely. In fact, OGs are ubiquitous in microbial genomes and more conserved between species than non-OGs. Based on these properties, it has been suggested that OGs can serve as better phylogenetic characters than non-OGs for reconstructing the evolutionary relationships among microbial genomes. OGtree takes the accession numbers of prokaryotic genomes as its input. It then downloads their complete genomes from the National Centre for Biotechnology Information and identifies OGs in each genome and their orthologous OGs in other genomes. Next, OGtree computes an overlapping-gene distance between each pair of input genomes based on a combination of their OG content and orthologous OG order. Finally, it utilizes distance-based methods of building tree to reconstruct the genome trees of input prokaryotic genomes according to their pairwise OG distance. OGtree is available online at http://bioalgorithm.life.nctu.edu.tw/OGtree/

Codon Usages of Genes on Chromosome, and Surprisingly, Genes in Plasmid are Primarily Affected by Strand-specific Mutational Biases in Lawsonia intracellularis

In this study, the factors driving genome-wide patterns of codon usages in Lawsonia intracellularis genome are determined. For genes on the chromosome of the bacterium, it is found that the most important source of variation results from strand-specific mutational biases. A lesser trend of variation is attributable to genes that are presumed as horizontally transferred. These putative alien genes are unusually GC richer than the other genes, whereas horizontally transferred genes have been observed to be AT rich in bacteria with medium and relatively low G + C contents. Hydropathy of encoded protein and expression level are also found to influence codon usage. Therefore, codon usage in L. intracellularis chromosome is the result of a complex balance among the different mutational and selectional factors. When analyzing genes in the largest plasmid, for the first time it is found that the strand-specific mutational biases are responsible for the primary variation of codon usages in plasmid. Genes, particularly highly expressed genes of this plasmid, are mainly located on the leading strands and this supposed to be the effects exerted by replicational–transcriptional selection. These facts suggest that this plasmid adopts the similar mechanism of replication as the chromosome in L. intracellularis. Common characters among the 10 bacteria in whose genomes the strand-specific mutational biases are the primary source of variation of codon usage are also investigated. For example, it is found that genes dnaT and fis that are involved in DNA replication initiation and re-initiation pathways are absent in all of the 10 bacteria

An Integrative Method for Identifying the Over-Annotated Protein-Coding Genes in Microbial Genomes

The falsely annotated protein-coding genes have been deemed one of the major causes accounting for the annotating errors in public databases. Although many filtering approaches have been designed for the over-annotated protein-coding genes, some are questionable due to the resultant increase in false negative. Furthermore, there is no webserver or software specifically devised for the problem of over-annotation. In this study, we propose an integrative algorithm for detecting the over-annotated protein-coding genes in microorganisms. Overall, an average accuracy of 99.94% is achieved over 61 microbial genomes. The extremely high accuracy indicates that the presented algorithm is efficient to differentiate the protein-coding genes from the non-coding open reading frames. Abundant analyses show that the predicting results are reliable and the integrative algorithm is robust and convenient. Our analysis also indicates that the over-annotated protein-coding genes can cause the false positive of horizontal gene transfers detection. The webserver of the proposed algorithm can be freely accessible from www.cbi.seu.edu.cn/RPGM

Bacterial genomic G + C composition-eliciting environmental adaptation

Bacterial genomes reflect their adaptation strategies through nucleotide usage trends found in their chromosome composition. Bacteria, unlike eukaryotes contain a wide range of genomic G + C. This wide variability may be viewed as a response to environmental adaptation. Two overarching trends are observed across bacterial genomes, the first, correlates genomic G + C to environmental niches and lifestyle, while the other utilizees intra-genomic G + C incongruence to delineate horizontally transferred material. In this review, we focus on the influence of several properties including biochemical, genetic flows, selection biases, and the biochemical-energetic properties shaping genome composition. Outcomes indicate a trend toward high G + C and larger genomes in free-living organisms, as a result of more complex and varied environments (higher chance for horizontal gene transfer). Conversely, nutrient limiting and nutrient poor environments dictate smaller genomes of low GC in attempts to conserve replication expense. Varied processes including translesion repair mechanisms, phage insertion and cytosine degradation has been shown to introduce higher AT in genomic sequences. We conclude the review with an analysis of current bioinformatics tools seeking to elicit compositional variances and highlight the practical implications when using such techniques

Networks of Gene Sharing among 329 Proteobacterial Genomes Reveal Differences in Lateral Gene Transfer Frequency at Different Phylogenetic Depths

Lateral gene transfer (LGT) is an important mechanism of natural variation among prokaryotes. Over the full course of evolution, most or all of the genes resident in a given prokaryotic genome have been affected by LGT, yet the frequency of LGT can vary greatly across genes and across prokaryotic groups. The proteobacteria are among the most diverse of prokaryotic taxa. The prevalence of LGT in their genome evolution calls for the application of network-based methods instead of tree-based methods to investigate the relationships among these species. Here, we report networks that capture both vertical and horizontal components of evolutionary history among 1,207,272 proteins distributed across 329 sequenced proteobacterial genomes. The network of shared proteins reveals modularity structure that does not correspond to current classification schemes. On the basis of shared protein-coding genes, the five classes of proteobacteria fall into two main modules, one including the alpha-, delta-, and epsilonproteobacteria and the other including beta- and gammaproteobacteria. The first module is stable over different protein identity thresholds. The second shows more plasticity with regard to the sequence conservation of proteins sampled, with the gammaproteobacteria showing the most chameleon-like evolutionary characteristics within the present sample. Using a minimal lateral network approach, we compared LGT rates at different phylogenetic depths. In general, gene evolution by LGT within proteobacteria is very common. At least one LGT event was inferred to have occurred in at least 75% of the protein families. The average LGT rate at the species and class depth is about one LGT event per protein family, the rate doubling at the phylum level to an average of two LGT events per protein family. Hence, our results indicate that the rate of gene acquisition per protein family is similar at the level of species (by recombination) and at the level of classes (by LGT). The frequency of LGT per genome strongly depends on the species lifestyle, with endosymbionts showing far lower LGT frequencies than free-living species. Moreover, the nature of the transferred genes suggests that gene transfer in proteobacteria is frequently mediated by conjugation