Predicting active site residue annotations in the Pfam database

<p>Abstract</p> <p>Background</p> <p>Approximately 5% of Pfam families are enzymatic, but only a small fraction of the sequences within these families (<0.5%) have had the residues responsible for catalysis determined. To increase the active site annotations in the Pfam database, we have developed a strict set of rules, chosen to reduce the rate of false positives, which enable the transfer of experimentally determined active site residue data to other sequences within the same Pfam family.</p> <p>Description</p> <p>We have created a large database of predicted active site residues. On comparing our active site predictions to those found in UniProtKB, Catalytic Site Atlas, PROSITE and <it>MEROPS </it>we find that we make many novel predictions. On investigating the small subset of predictions made by these databases that are not predicted by us, we found these sequences did not meet our strict criteria for prediction. We assessed the sensitivity and specificity of our methodology and estimate that only 3% of our predicted sequences are false positives.</p> <p>Conclusion</p> <p>We have predicted 606110 active site residues, of which 94% are not found in UniProtKB, and have increased the active site annotations in Pfam by more than 200 fold. Although implemented for Pfam, the tool we have developed for transferring the data can be applied to any alignment with associated experimental active site data and is available for download. Our active site predictions are re-calculated at each Pfam release to ensure they are comprehensive and up to date. They provide one of the largest available databases of active site annotation.</p

Application of Chinese Jun-Cao technique for the production of Brazilian Ganoderma lucidum strains

Ganoderma lucidum is a medicinal mushroom traditionally used in China against a wide range of diseases such as cancer and also for its prevention. In this work, commercial Chinese strains G. lucidum were compared to wild Brazilian strains aiming to determine the cultivation potential through the use of Jun-Cao. Six formulations were tested and the strains presented good response to the applied method. In general, the mixture between the grass and wood was well suited for the basidiomycetes, contributing to the preparation of substrates that generated better results in Jun Cao

Automatic prediction of catalytic residues by modeling residue structural neighborhood

Background: Prediction of catalytic residues is a major step in characterizing the function of enzymes. In its simpler formulation, the problem can be cast into a binary classification task at the residue level, by predicting whether the residue is directly involved in the catalytic process. The task is quite hard also when structural information is available, due to the rather wide range of roles a functional residue can play and to the large imbalance between the number of catalytic and non-catalytic residues.Results: We developed an effective representation of structural information by modeling spherical regions around candidate residues, and extracting statistics on the properties of their content such as physico-chemical properties, atomic density, flexibility, presence of water molecules. We trained an SVM classifier combining our features with sequence-based information and previously developed 3D features, and compared its performance with the most recent state-of-the-art approaches on different benchmark datasets. We further analyzed the discriminant power of the information provided by the presence of heterogens in the residue neighborhood.Conclusions: Our structure-based method achieves consistent improvements on all tested datasets over both sequence-based and structure-based state-of-the-art approaches. Structural neighborhood information is shown to be responsible for such results, and predicting the presence of nearby heterogens seems to be a promising direction for further improvements.Journal ArticleResearch Support, N.I.H. Extramuralinfo:eu-repo/semantics/publishe

Networks of High Mutual Information Define the Structural Proximity of Catalytic Sites: Implications for Catalytic Residue Identification

Identification of catalytic residues (CR) is essential for the characterization of enzyme function. CR are, in general, conserved and located in the functional site of a protein in order to attain their function. However, many non-catalytic residues are highly conserved and not all CR are conserved throughout a given protein family making identification of CR a challenging task. Here, we put forward the hypothesis that CR carry a particular signature defined by networks of close proximity residues with high mutual information (MI), and that this signature can be applied to distinguish functional from other non-functional conserved residues. Using a data set of 434 Pfam families included in the catalytic site atlas (CSA) database, we tested this hypothesis and demonstrated that MI can complement amino acid conservation scores to detect CR. The Kullback-Leibler (KL) conservation measurement was shown to significantly outperform both the Shannon entropy and maximal frequency measurements. Residues in the proximity of catalytic sites were shown to be rich in shared MI. A structural proximity MI average score (termed pMI) was demonstrated to be a strong predictor for CR, thus confirming the proposed hypothesis. A structural proximity conservation average score (termed pC) was also calculated and demonstrated to carry distinct information from pMI. A catalytic likeliness score (Cls), combining the KL, pC and pMI measures, was shown to lead to significantly improved prediction accuracy. At a specificity of 0.90, the Cls method was found to have a sensitivity of 0.816. In summary, we demonstrate that networks of residues with high MI provide a distinct signature on CR and propose that such a signature should be present in other classes of functional residues where the requirement to maintain a particular function places limitations on the diversification of the structural environment along the course of evolution

The Pseudomonas aeruginosa Transcriptome in Planktonic Cultures and Static Biofilms Using RNA Sequencing

In this study, we evaluated how gene expression differs in mature Pseudomonas aeruginosa biofilms as opposed to planktonic cells by the use of RNA sequencing technology that gives rise to both quantitative and qualitative information on the transcriptome. Although a large proportion of genes were consistently regulated in both the stationary phase and biofilm cultures as opposed to the late exponential growth phase cultures, the global biofilm gene expression pattern was clearly distinct indicating that biofilms are not just surface attached cells in stationary phase. A large amount of the genes found to be biofilm specific were involved in adaptation to microaerophilic growth conditions, repression of type three secretion and production of extracellular matrix components. Additionally, we found many small RNAs to be differentially regulated most of them similarly in stationary phase cultures and biofilms. A qualitative analysis of the RNA-seq data revealed more than 3000 putative transcriptional start sites (TSS). By the use of rapid amplification of cDNA ends (5′-RACE) we confirmed the presence of three different TSS associated with the pqsABCDE operon, two in the promoter of pqsA and one upstream of the second gene, pqsB. Taken together, this study reports the first transcriptome study on P. aeruginosa that employs RNA sequencing technology and provides insights into the quantitative and qualitative transcriptome including the expression of small RNAs in P. aeruginosa biofilms

Kaposin-B Enhances the PROX1 mRNA Stability during Lymphatic Reprogramming of Vascular Endothelial Cells by Kaposi's Sarcoma Herpes Virus

Kaposi's sarcoma (KS) is the most common cancer among HIV-positive patients. Histogenetic origin of KS has long been elusive due to a mixed expression of both blood and lymphatic endothelial markers in KS tumor cells. However, we and others discovered that Kaposi's sarcoma herpes virus (KSHV) induces lymphatic reprogramming of blood vascular endothelial cells by upregulating PROX1, which functions as the master regulator for lymphatic endothelial differentiation. Here, we demonstrate that the KSHV latent gene kaposin-B enhances the PROX1 mRNA stability and plays an important role in KSHV-mediated PROX1 upregulation. We found that PROX1 mRNA contains a canonical AU-rich element (ARE) in its 3′-untranslated region that promotes PROX1 mRNA turnover and that kaposin-B stimulates cytoplasmic accumulation of the ARE-binding protein HuR through activation of the p38/MK2 pathway. Moreover, HuR binds to and stabilizes PROX1 mRNA through its ARE and is necessary for KSHV-mediated PROX1 mRNA stabilization. Together, our study demonstrates that kaposin-B plays a key role in PROX1 upregulation during lymphatic reprogramming of blood vascular endothelial cells by KSHV

Comparative analyses imply that the enigmatic sigma factor 54 is a central controller of the bacterial exterior

Contains fulltext : 95738.pdf (publisher's version ) (Open Access)BACKGROUND: Sigma-54 is a central regulator in many pathogenic bacteria and has been linked to a multitude of cellular processes like nitrogen assimilation and important functional traits such as motility, virulence, and biofilm formation. Until now it has remained obscure whether these phenomena and the control by Sigma-54 share an underlying theme. RESULTS: We have uncovered the commonality by performing a range of comparative genome analyses. A) The presence of Sigma-54 and its associated activators was determined for all sequenced prokaryotes. We observed a phylum-dependent distribution that is suggestive of an evolutionary relationship between Sigma-54 and lipopolysaccharide and flagellar biosynthesis. B) All Sigma-54 activators were identified and annotated. The relation with phosphotransfer-mediated signaling (TCS and PTS) and the transport and assimilation of carboxylates and nitrogen containing metabolites was substantiated. C) The function annotations, that were represented within the genomic context of all genes encoding Sigma-54, its activators and its promoters, were analyzed for intra-phylum representation and inter-phylum conservation. Promoters were localized using a straightforward scoring strategy that was formulated to identify similar motifs. We found clear highly-represented and conserved genetic associations with genes that concern the transport and biosynthesis of the metabolic intermediates of exopolysaccharides, flagella, lipids, lipopolysaccharides, lipoproteins and peptidoglycan. CONCLUSION: Our analyses directly implicate Sigma-54 as a central player in the control over the processes that involve the physical interaction of an organism with its environment like in the colonization of a host (virulence) or the formation of biofilm