GC content-independent amino acid patterns in bacteria and archaea

The genome of Candidatus phytoplasma ziziphi provides insights into their biological characteristics

Phytoplasmas are obligate cell wall-less prokaryotic bacteria that primarily multiply in plant phloem tissue. Jujube witches' broom (JWB) associated with phytoplasma is a destructive disease of jujube (Ziziphus jujuba Mill.). Here we report the complete 'Candidatus Phytoplasma ziziphi' chromosome of strain Hebei-2018, which is a circular genome of 764,108-base pairs with 735 predicted CDS. Notably, extra 19,825 bp (from 621,995 to 641,819 bp) compared to the previously reported one complements the genes involved in glycolysis, such as pdhA, pdhB, pdhC, pdhD, ackA, pduL and LDH. The synonymous codon usage bias (CUB) patterns by using comparative genomics analysis among the 9 phytoplasmas were similar for most codons. The ENc-GC3s analysis among the 9 phytoplasmas showed a greater effect under the selection on the CUBs of phytoplasmas genes than mutation and other factors. The genome exhibited a strongly reduced ability in metabolic synthesis, while the genes encoding transporter systems were well developed. The genes involved in sec-dependent protein translocation system were also identified.The expressions of nine FtsHs encoding membrane associated ATP-dependent Zn proteases and Mn-SodA with redox capacity in the Ca. P. ziziphi was positively correlated with the phytoplasma concentration. Taken together, the genome will not only expand the number of phytoplasma species and provide some new information about Ca. P. ziziphi, but also contribute to exploring its pathogenic mechanism.

The Structure of Evolutionary Model Space for Proteins across the Tree of Life

The factors that determine the relative rates of amino acid substitution during protein evolution are complex and known to vary among taxa. We estimated relative exchangeabilities for pairs of amino acids from clades spread across the tree of life and assessed the historical signal in the distances among these clade-specific models. We separately trained these models on collections of arbitrarily selected protein alignments and on ribosomal protein alignments. In both cases, we found a clear separation between the models trained using multiple sequence alignments from bacterial clades and the models trained on archaeal and eukaryotic data. We assessed the predictive power of our novel clade-specific models of sequence evolution by asking whether fit to the models could be used to identify the source of multiple sequence alignments. Model fit was generally able to correctly classify protein alignments at the level of domain (bacterial versus archaeal), but the accuracy of classification at finer scales was much lower. The only exceptions to this were the relatively high classification accuracy for two archaeal lineages: Halobacteriaceae and Thermoprotei. Genomic GC content had a modest impact on relative exchangeabilities despite having a large impact on amino acid frequencies. Relative exchangeabilities involving aromatic residues exhibited the largest differences among models. There were a small number of exchangeabilities that exhibited large differences in comparisons among major clades and between generalized models and ribosomal protein models. Taken as a whole, these results reveal that a small number of relative exchangeabilities are responsible for much of the structure of the "model space" for protein sequence evolution. The clade-specific models we generated may be useful tools for protein phylogenetics, and the structure of evolutionary model space that they revealed has implications for phylogenomic inference across the tree of life.

Physicochemical classification of organisms

The hypervariable residues that compose the major part of proteins’ surfaces are generally considered outside evolutionary control. Yet, these “nonconserved” residues determine the outcome of stochastic encounters in crowded cells. It has recently become apparent that these encounters are not as random as one might imagine, but carefully orchestrated by the intracellular electrostatics to optimize protein diffusion, interactivity, and partner search. The most influential factor here is the protein surface-charge density, which takes different optimal values across organisms with different intracellular conditions. In this study, we examine how far the net-charge density and other physicochemical properties of proteomes will take us in terms of distinguishing organisms in general. The results show that these global proteome properties not only follow the established taxonomical hierarchy, but also provide clues to functional adaptation. In many cases, the proteome–property divergence is even resolved at species level. Accordingly, the variable parts of the genes are not as free to drift as they seem in sequence alignment, but present a complementary tool for functional, taxonomic, and evolutionary assignment.

Deconstruction of archaeal genome depict strategic consensus in core pathways coding sequence assembly

A comprehensive in silico analysis of 71 species representing the different taxonomic classes and physiological genre of the domain Archaea was performed. These organisms differed in their physiological attributes, particularly oxygen tolerance and energy metabolism. We explored the diversity and similarity in the codon usage pattern in the genes and genomes of these organisms, emphasizing on their core cellular pathways. Our thrust was to figure out whether there is any underlying similarity in the design of core pathways within these organisms. Analyses of codon utilization pattern, construction of hierarchical linear models of codon usage, expression pattern and codon pair preference pointed to the fact that, in the archaea there is a trend towards biased use of synonymous codons in the core cellular pathways and the Nc-plots appeared to display the physiological variations present within the different species. Our analyses revealed that aerobic species of archaea possessed a larger degree of freedom in regulating expression levels than could be accounted for by codon usage bias alone. This feature might be a consequence of their enhanced metabolic activities as a result of their adaptation to the relatively O²-rich environment. Species of archaea, which are related from the taxonomical viewpoint, were found to have striking similarities in their ORF structuring pattern. In the anaerobic species of archaea, codon bias was found to be a major determinant of gene expression. We have also detected a significant difference in the codon pair usage pattern between the whole genome and the genes related to vital cellular pathways, and it was not only species-specific but pathway specific too. This hints towards the structuring of ORFs with better decoding accuracy during translation. Finally, a codon-pathway interaction in shaping the codon design of pathways was observed where the transcription pathway exhibited a significantly different coding frequency signature.

Evolution of complete proteomes: guanine-cytosine pressure, phylogeny and environmental influences blend the proteomic architecture

Background

Guanine-cytosine (GC) composition is an important feature of genomes. Likewise, amino acid composition is a distinct, but less valued, feature of proteomes. A major concern is that it is not clear what valuable information can be acquired from amino acid composition data. To address this concern, in-depth analyses of the amino acid composition of the complete proteomes from 63 archaea, 270 bacteria, and 128 eukaryotes were performed.

Results

Principal component analysis of the amino acid matrices showed that the main contributors to proteomic architecture were genomic GC variation, phylogeny, and environmental influences. GC pressure drove positive selection on Ala, Arg, Gly, Pro, Trp, and Val, and adverse selection on Asn, Lys, Ile, Phe, and Tyr. The physico-chemical framework of the complete proteomes withstood GC pressure by frequency complementation of GC-dependent amino acid pairs with similar physico-chemical properties. Gln, His, Ser, and Val were responsible for phylogeny and their constituted components could differentiate archaea, bacteria, and eukaryotes. Environmental niche was also a significant factor in determining proteomic architecture, especially for archaea for which the main amino acids were Cys, Leu, and Thr. In archaea, hyperthermophiles, acidophiles, mesophiles, psychrophiles, and halophiles gathered successively along the environment-based principal component. Concordance between proteomic architecture and the genetic code was also related closely to genomic GC content, phylogeny, and lifestyles.

Conclusions

Large-scale analyses of the complete proteomes of a wide range of organisms suggested that amino acid composition retained the trace of GC variation, phylogeny, and environmental influences during evolution. The findings from this study will help in the development of a global understanding of proteome evolution, and even biological evolution.

SARP: A Novel Algorithm to Assess Compositional Biases in Protein Sequences

The composition of a defined set of subunits (nucleotides, amino acids) is one of the key features of biological sequences. Compositional biases are local shifts in amino acid or nucleotide frequencies that can occur as an adaptation of an organism to an extreme ecological niche, or as the signature of a specific function or localization of the corresponding protein. The calculation of probability is a method for annotating compositional bias and providing accurate detection of biased subsequences. Here, we present a Sequence Analysis based on the Ranking of Probabilities (SARP), a novel algorithm for the annotation of compositional biases based on ranking subsequences by their probabilities. SARP provides the same accuracy as the previously published Lower Probability Subsequences (LPS) algorithm but performs at an approximately 230-fold faster rate. It can be recommended for use when working with large datasets to reduce the time and resources required.