Bioinformatics analysis of SARS coronavirus genome polymorphism

BACKGROUND: We have compared 38 isolates of the SARS-CoV complete genome. The main goal was twofold: first, to analyze and compare nucleotide sequences and to identify positions of single nucleotide polymorphism (SNP), insertions and deletions, and second, to group them according to sequence similarity, eventually pointing to phylogeny of SARS-CoV isolates. The comparison is based on genome polymorphism such as insertions or deletions and the number and positions of SNPs. RESULTS: The nucleotide structure of all 38 isolates is presented. Based on insertions and deletions and dissimilarity due to SNPs, the dataset of all the isolates has been qualitatively classified into three groups each having their own subgroups. These are the A-group with "regular" isolates (no insertions / deletions except for 5' and 3' ends), the B-group of isolates with "long insertions", and the C-group of isolates with "many individual" insertions and deletions. The isolate with the smallest average number of SNPs, compared to other isolates, has been identified (TWH). The density distribution of SNPs, insertions and deletions for each group or subgroup, as well as cumulatively for all the isolates is also presented, along with the gene map for TWH. Since individual SNPs may have occurred at random, positions corresponding to multiple SNPs (occurring in two or more isolates) are identified and presented. This result revises some previous results of a similar type. Amino acid changes caused by multiple SNPs are also identified (for the annotated sequences, as well as presupposed amino acid changes for non-annotated ones). Exact SNP positions for the isolates in each group or subgroup are presented. Finally, a phylogenetic tree for the SARS-CoV isolates has been produced using the CLUSTALW program, showing high compatibility with former qualitative classification. CONCLUSIONS: The comparative study of SARS-CoV isolates provides essential information for genome polymorphism, indication of strain differences and variants evolution. It may help with the development of effective treatment

Bioinformatics analysis of disordered proteins in prokaryotes

<p>Abstract</p> <p>Background</p> <p>A significant number of proteins have been shown to be intrinsically disordered, meaning that they lack a fixed 3 D structure or contain regions that do not posses a well defined 3 D structure. It has also been proven that a protein's disorder content is related to its function. We have performed an exhaustive analysis and comparison of the disorder content of proteins from prokaryotic organisms (i.e., superkingdoms Archaea and Bacteria) with respect to functional categories they belong to, i.e., Clusters of Orthologous Groups of proteins (COGs) and groups of COGs-Cellular processes (Cp), Information storage and processing (Isp), Metabolism (Me) and Poorly characterized (Pc).</p> <p>We also analyzed the disorder content of proteins with respect to various genomic, metabolic and ecological characteristics of the organism they belong to. We used correlations and association rule mining in order to identify the most confident associations between specific modalities of the characteristics considered and disorder content.</p> <p>Results</p> <p>Bacteria are shown to have a somewhat higher level of protein disorder than archaea, except for proteins in the Me functional group. It is demonstrated that the Isp and Cp functional groups in particular (L-repair function and N-cell motility and secretion COGs of proteins in specific) possess the highest disorder content, while Me proteins, in general, posses the lowest. Disorder fractions have been confirmed to have the lowest level for the so-called order-promoting amino acids and the highest level for the so-called disorder promoters.</p> <p>For each pair of organism characteristics, specific modalities are identified with the maximum disorder proteins in the corresponding organisms, e.g., high genome size-high GC content organisms, facultative anaerobic-low GC content organisms, aerobic-high genome size organisms, etc. Maximum disorder in archaea is observed for high GC content-low genome size organisms, high GC content-facultative anaerobic or aquatic or mesophilic organisms, etc. Maximum disorder in bacteria is observed for high GC content-high genome size organisms, high genome size-aerobic organisms, etc.</p> <p>Some of the most reliable association rules mined establish relationships between high GC content and high protein disorder, medium GC content and both medium and low protein disorder, anaerobic organisms and medium protein disorder, Gammaproteobacteria and low protein disorder, etc. A web site <it>Prokaryote Disorder Database </it>has been designed and implemented at the address <url>http://bioinfo.matf.bg.ac.rs/disorder</url>, which contains complete results of the analysis of protein disorder performed for 296 prokaryotic completely sequenced genomes.</p> <p>Conclusions</p> <p>Exhaustive disorder analysis has been performed by functional classes of proteins, for a larger dataset of prokaryotic organisms than previously done. Results obtained are well correlated to those previously published, with some extension in the range of disorder level and clear distinction between functional classes of proteins. Wide correlation and association analysis between protein disorder and genomic and ecological characteristics has been performed for the first time. The results obtained give insight into multi-relationships among the characteristics and protein disorder. Such analysis provides for better understanding of the evolutionary process and may be useful for taxon determination. The main drawback of the approach is the fact that the disorder considered has been predicted and not experimentally established.</p

Mechanism of subunit interaction at ketosynthase-dehydratase junctions in trans-AT polyketide synthases

Modular polyketide synthases (PKSs) produce numerous structurally complex natural products with diverse applications in medicine and agriculture. They typically consist of several multienzyme subunits that utilize structurally-defined docking domains (DDs) at their N- and C-termini to ensure correct assembly into functional multi-protein complexes. Here we report a fundamentally different mechanism for subunit assembly in trans-AT modular PKSs at the junction between ketosynthase (KS) and dehydratase (DH) domains. This involves direct interaction of a largely unstructured docking domain (DD) at the C-terminus of the KS with the surface of the downstream DH. Acyl transfer assays and mechanism-based cross-linking established that the DD is required for the KS to communicate with the acyl carrier protein appended to the DH. Two distinct regions for binding of the DD to the DH were identified using NMR spectroscopy, carbene foot-printing and mutagenesis, providing a foundation for future elucidation of the molecular basis for interaction specificity

Structural disorder of plasmid-encoded proteins in Bacteria and Archaea

Abstract Background In the last decade and a half it has been firmly established that a large number of proteins do not adopt a well-defined (ordered) structure under physiological conditions. Such intrinsically disordered proteins (IDPs) and intrinsically disordered (protein) regions (IDRs) are involved in essential cell processes through two basic mechanisms: the entropic chain mechanism which is responsible for rapid fluctuations among many alternative conformations, and molecular recognition via short recognition elements that bind to other molecules. IDPs possess a high adaptive potential and there is special interest in investigating their involvement in organism evolution. Results We analyzed 2554 Bacterial and 139 Archaeal proteomes, with a total of 8,455,194 proteins for disorder content and its implications for adaptation of organisms, using three disorder predictors and three measures. Along with other findings, we revealed that for all three predictors and all three measures (1) Bacteria exhibit significantly more disorder than Archaea; (2) plasmid-encoded proteins contain considerably more IDRs than proteins encoded on chromosomes (or whole genomes) in both prokaryote superkingdoms; (3) plasmid proteins are significantly more disordered than chromosomal proteins only in the group of proteins with no COG category assigned; (4) antitoxin proteins in comparison to other proteins, are the most disordered (almost double) in both Bacterial and Archaeal proteomes; (5) plasmidal proteins are more disordered than chromosomal proteins in Bacterial antitoxins and toxin-unclassified proteins, but have almost the same disorder content in toxin proteins. Conclusion Our results suggest that while disorder content depends on genome and proteome characteristics, it is more influenced by functional engagements than by gene location (on chromosome or plasmid)

Towards a database for genotype-phenotype association research: mining data from encyclopaedia

To associate phenotypic characteristics of an organism to molecules encoded by its genome, there is a need for well-structured genotype and phenotype data. We use a novel method for extracting data on phenotype and genotype characteristics of microorganisms from text. As a resource, we use an encyclopedia of microorganisms, which holds phenotypic and genotypic data and create a structured, flexible data resource, which can be exported to a range of database formats, containing genotype and phenotype data for 2412 species and 873 genera of microbes. This data source has great potential as a resource for future biological research on genotype-phenotype associations. In this paper, we focus on describing the structure and content of the resulting database and on evaluating the method used for extracting the data. We conclude that the resulting database can be used as a reliable complementary resource for research into genotype-phenotype association