Dataset Information

Whole-proteome analysis of twelve species of alphaproteobacteria links four pathogens.

ABSTRACT: Thousands of whole-genome and whole-proteome sequences have been made available through advances in sequencing technology, and sequences of millions more organisms will become available in the coming years. This wealth of genetic information will provide numerous opportunities to enhance our understanding of these organisms including a greater understanding of relationships among species. Researchers have used 16S rRNA and other gene sequences to study the evolutionary origins of bacteria, but these strategies do not provide insight into the sharing of genes among bacteria via horizontal transfer. In this work we use an open source software program called pClust to cluster proteins from the complete proteomes of twelve species of Alphaproteobacteria and generate a dendrogram from the resulting orthologous protein clusters. We compare the results with dendrograms constructed using the 16S rRNA gene and multiple sequence alignment of seven housekeeping genes. Analysis of the whole proteomes of these pathogens grouped Rickettsia typhi with three other animal pathogens whereas conventional sequence analysis failed to group these pathogens together. We conclude that whole-proteome analysis can give insight into relationships among species beyond their phylogeny, perhaps reflecting the effects of horizontal gene transfer and potentially providing insight into the functions of shared genes by means of shared phenotypes.

SUBMITTER: Zhou Y

PROVIDER: S-EPMC4235700 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

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Whole-proteome analysis of twelve species of alphaproteobacteria links four pathogens.

Zhou Yunyun Y Call Douglas R DR Broschat Shira L SL

Pathogens (Basel, Switzerland) 20131126 4

Thousands of whole-genome and whole-proteome sequences have been made available through advances in sequencing technology, and sequences of millions more organisms will become available in the coming years. This wealth of genetic information will provide numerous opportunities to enhance our understanding of these organisms including a greater understanding of relationships among species. Researchers have used 16S rRNA and other gene sequences to study the evolutionary origins of bacteria, but t ...[more]

PMID: 25437336

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Project description:Background: The rapid increase in antibiotic resistance by various bacterial pathogens underlies the significance of developing new therapies and exploring different drug targets. A fraction of bacterial pathogens abbreviated as ESKAPE by the European Center for Disease Prevention and Control have been considered a major threat due to the rise in nosocomial infections. Here, we compared putative drug binding pockets of twelve essential and mostly conserved metabolic enzymes in numerous bacterial pathogens including those of the ESKAPE group and Mycobacterium tuberculosis. The comparative analysis will provide guidelines for the likelihood of transferability of the inhibitors from one species to another.Methods: Nine bacterial species including six ESKAPE pathogens, Mycobacterium tuberculosis along with Mycobacterium smegmatis and Eschershia coli, two non-pathogenic bacteria, have been selected for drug binding pocket analysis of twelve essential enzymes. The amino acid sequences were obtained from Uniprot, aligned using ICM v3.8-4a and matched against the Pocketome encyclopedia. We used known co-crystal structures of selected target enzyme orthologs to evaluate the location of their active sites and binding pockets and to calculate a matrix of pairwise sequence identities across each target enzyme across the different species. This was used to generate sequence maps.Results: High sequence identity of enzyme binding pockets, derived from experimentally determined co-crystallized structures, was observed among various species. Comparison at both full sequence level and for drug binding pockets of key metabolic enzymes showed that binding pockets are highly conserved (sequence similarity up to 100%) among various ESKAPE pathogens as well as Mycobacterium tuberculosis. Enzymes orthologs having conserved binding sites may have potential to interact with inhibitors in similar way and might be helpful for design of similar class of inhibitors for a particular species. The derived pocket alignments and distance-based maps provide guidelines for drug discovery and repurposing. In addition they also provide recommendations for the relevant model bacteria that may be used for initial drug testing.Discussion: Comparing ligand binding sites through sequence identity calculation could be an effective approach to identify conserved orthologs as drug binding pockets have shown higher level of conservation among various species. By using this approach we could avoid the problems associated with full sequence comparison. We identified essential metabolic enzymes among ESKAPE pathogens that share high sequence identity in their putative drug binding pockets (up to 100%), of which known inhibitors can potentially antagonize these identical pockets in the various species in a similar manner.

Project description:Codon usage bias (CUB), the uneven use of synonymous codons, is a ubiquitous observation in virtually all organisms examined. The pattern of codon usage is generally similar among closely related species, but differs significantly among distantly related organisms, e.g., bacteria, yeast, and Drosophila. Several explanations for CUB have been offered and some have been supported by observations and experiments, although a thorough understanding of the evolutionary forces (random drift, mutation bias, and selection) and their relative importance remains to be determined. The recently available complete genome DNA sequences of twelve phylogenetically defined species of Drosophila offer a hitherto unprecedented opportunity to examine these problems. We report here the patterns of codon usage in the twelve species and offer insights on possible evolutionary forces involved.(1) Codon usage is quite stable across 11/12 of the species: G- and especially C-ending codons are used most frequently, thus defining the preferred codons. (2) The only amino acid that changes in preferred codon is Serine with six species of the melanogaster group favoring TCC while the other species, particularly subgenus Drosophila species, favor AGC. (3) D. willistoni is an exception to these generalizations in having a shifted codon usage for seven amino acids toward A/T in the wobble position. (4) Amino acids differ in their contribution to overall CUB, Leu having the greatest and Asp the least. (5) Among two-fold degenerate amino acids, A/G ending amino acids have more selection on codon usage than T/C ending amino acids. (6) Among the different chromosome arms or elements, genes on the non-recombining element F (dot chromosome) have the least CUB, while genes on the element A (X chromosome) have the most. (7) Introns indicate that mutation bias in all species is approximately 2:1, AT:GC, the opposite of codon usage bias. (8) There is also evidence for some overall regional bias in base composition that may influence codon usage.Overall, these results suggest that natural selection has acted on codon usage in the genus Drosophila, at least often enough to leave a footprint of selection in modern genomes. However, there is evidence in the data that random forces (drift and mutation) have also left patterns in the data, especially in genes under weak selection for codon usage for example genes in regions of low recombination. The documentation of codon usage patterns in each of these twelve genomes also aids in ongoing annotation efforts.

Dataset Information

Whole-proteome analysis of twelve species of alphaproteobacteria links four pathogens.

Publications

Whole-proteome analysis of twelve species of alphaproteobacteria links four pathogens.

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