dbPTM: an information repository of protein post-translational modification

dbPTM is a database that compiles information on protein post-translational modifications (PTMs), such as the catalytic sites, solvent accessibility of amino acid residues, protein secondary and tertiary structures, protein domains and protein variations. The database includes all of the experimentally validated PTM sites from Swiss-Prot, PhosphoELM and O-GLYCBASE. Only a small fraction of Swiss-Prot proteins are annotated with experimentally verified PTM. Although the Swiss-Prot provides rich information about the PTM, other structural properties and functional information of proteins are also essential for elucidating protein mechanisms. The dbPTM systematically identifies three major types of protein PTM (phosphorylation, glycosylation and sulfation) sites against Swiss-Prot proteins by refining our previously developed prediction tool, KinasePhos (). Solvent accessibility and secondary structure of residues are also computationally predicted and are mapped to the PTM sites. The resource is now freely available at

Genetic alterations and cancer formation in a European flatfish at sites of different contamination burdens

Fish diseases are an indicator for marine ecosystem health since they provide a biological end-point of historical exposure to stressors. Liver cancer has been used to monitor the effects of exposure to anthropogenic pollution in flatfish for many years. The prevalence of liver cancer can exceed 20%. Despite the high prevalence and the opportunity of using flatfish to study environmentally induced cancer, the genetic and environmental factors driving tumor prevalence across sites are poorly understood. This study aims to define the link between genetic deterioration, liver disease progression, and anthropogenic contaminant exposures in the flatfish dab (Limanda limanda). We assessed genetic changes in a conserved cancer gene, Retinoblastoma (Rb), in association with histological diagnosis of normal, pretumor, and tumor pathologies in the livers of 165 fish from six sites in the North Sea and English Channel. The highest concentrations of metals (especially cadmium) and organic chemicals correlated with the presence of tumor pathology and with defined genetic profiles of the Rb gene, from these sites. Different Rb genetic profiles were found in liver tissue near each tumor phenotype, giving insight into the mechanistic molecular-level cause of the liver pathologies. Different Rb profiles were also found at sampling sites of differing contaminant burdens. Additionally, profiles indicated that histological “normal” fish from Dogger sampling locations possessed Rb profiles associated with pretumor disease. This study highlights an association between Rb and specific contaminants (especially cadmium) in the molecular etiology of dab liver tumorigenesis

Framework for a Protein Ontology

Biomedical ontologies are emerging as critical tools in genomic and proteomic research, where complex data in disparate resources need to be integrated. A number of ontologies describe properties that can be attributed to proteins. For example, protein functions are described by the Gene Ontology (GO) and human diseases by SNOMED CT or ICD10. There is, however, a gap in the current set of ontologies – one that describes the protein entities themselves and their relationships. We have designed the PRotein Ontology (PRO) to facilitate protein annotation and to guide new experiments. The components of PRO extend from the classification of proteins on the basis of evolutionary relationships to the representation of the multiple protein forms of a gene (products generated by genetic variation, alternative splicing, proteolytic cleavage, and other post-translational modifications). PRO will allow the specification of relationships between PRO, GO and other ontologies in the OBO Foundry. Here we describe the initial development of PRO, illustrated using human and mouse proteins involved in the transforming growth factor-beta and bone morphogenetic protein signaling pathways

Computational Analysis of Mass Spectrometric Data for Whole Organism Proteomic Studies

In the last decades great breakthroughs have been achieved in the study of the genomes, supplying us with the vast knowledge of the genes and a large number of sequenced organisms. With the availability of genome information, the new systematic studies have arisen. One of the most prominent areas is proteomics. Proteomics is a discipline devoted to the study of the organism’s expressed protein content. Proteomics studies are concerned with a wide range of problems. Some of the major proteomics focuses upon the studies of protein expression patterns, the detection of protein-protein interactions, protein quantitation, protein localization analysis, and characterization of post-translational modifications. The emergence of proteomics shows great promise to furthering our understanding of the cellular processes and mechanisms of life. One of the main techniques used for high-throughput proteomic studies is mass spectrometry. Capable of detecting masses of biological compounds in complex mixtures, it is currently one of the most powerful methods for protein characterization. New horizons are opening with the new developments of mass spectrometry instrumentation, which can now be applied to a variety of proteomic problems. One of the most popular applications of proteomics involves whole organism high-throughput experiments. However, as new instrumentation is being developed, followed by the design of new experiments, we find ourselves needing new computational algorithms to interpret the results of the experiments. As the thresholds of the current technology are being probed, the new algorithmic designs are beginning to emerge to meet the challenges of the mass spectrometry data evaluation and interpretation. This dissertation is devoted to computational analysis of mass spectrometric data, involving a combination of different topics and techniques to improve our understanding of biological processes using high-throughput whole organism proteomic studies. It consists of the development of new algorithms to improve the data interpretation of the current tools, introducing a new algorithmic approach for post-translational modification detection, and the characterization of a set of computational simulations for biological agent detection in a complex organism background. These studies are designed to further the capabilities of understanding the results of high-throughput mass spectrometric experiments and their impact in the field of proteomics

fine-tuning of ribosomal structure and functions by pseudouridylation and rna-protein interactions

ABSTRACT Fine-tuning of ribosomal structure and functions by pseudouridylation and RNA-protein interactions by JUN JIANG AUGUST 2012 Advisor: Prof. John SantaLucia Jr. Major: Chemistry (Biochemistry) Degree: Doctor of Philosophy Ribosomal structure and functions appear to be fine-tuned by pseudouridylation and RNA-protein interactions. Pseudouridylation may promote base stacking interactions by mediating the base stacking between residues on both sides. In the RNA duplex region, this enhanced stacking interaction contributes to stabilization of duplex folding. In the loop region, enhanced stacking in one structural motif may destabilize the conformation of adjacent structural residues. This hypothesis is supported by both UV-melting experiments, where pseudouridylation significantly stabilized H69 stem duplex folding, while destabilize the loop conformation. In addition, NMR also supports this hypothesis. The NMR structure of H69UUU shows that the U1915, A1916, and U1917 form a local sheared stacking, instead of participating in an extensive stacking which extends to C1924. The NMR structure and crystal structures of H69ΨΨΨ shows that Ψ1915 and Ψ1917 (E. coli numbering) mediate the extensive stacking. The dynamic property was also revealed in the NMR spectrum of H69ΨΨΨ (C1914), which suggests that the enhanced stacking interactions from Ψ1915 to C1924 may contribute to the destabilization of the loop conformation of H69ΨΨΨ and pre-organization of the stem-loop structure of H69ΨΨΨ for ribosomal subunits association. RNA-protein interactions are another method to regulate ribosome biogenesis and activity. An ambient dissociation constant between the ribosomal RNA and ribosomal protein is required for the optimal ribosome biogenesis and activity (77nM for the E. coli cognate pair and 198 nM for the P. aeruginosa cognate pair). Either a too weak (dissociation constants of 77 nM vs. 312 nM for Ech9 - EcS20/PaS20) or a too strong interaction (dissociation constants of 198 nM vs. 51 nM for Pah9 - PaS20/EcS20) could affect the ability of S20 ribosomal protein to coordinate the correct folding of 16S rRNA

Proteomics Databases and Websites

Information avalanche (overload or expansion) in various scientific fields is a novel issue turned out by a number of factors considered necessary to facilitate their record and registration. Though, the biological science and its diverse fields like proteomics are not immune of this event and even may be as the event’s herald. On the other hand, time as the most valued anxiety of human has encountered a huge mass of information. Therefore, in order to maintain access and ease the understanding of information in several fields some emprises have been prepared. Bioinformatics is an upshot of this anxiety and emprise. Interestingly, proteomics through studying proteins collection in alive things has covered a great portion of bioinformatics. Consequently, a noteworthy outlook on proteomics related databases (DBs) and websites not only can help investigators to face the upcoming archive of databases but also estimate the volume of the needed facilitates. Furthermore, enrichment of the DBs or related websites must be the priority of researchers. Herein, by covering the major proteomics related databases and websites, we have presented a comprehensive classification to simplify and clarify their understanding and applications

Genetic Locus Required for Antigenic Maturation of \u3cem\u3eRhizobium etli\u3c/em\u3e CE3 Lipopolysaccharide

Rhizobium etli modifies lipopolysaccharide (LPS) structure in response to environmental signals, such as low pH and anthocyanins. These LPS modifications result in the loss of reactivity with certain monoclonal antibodies. The same antibodies fail to recognize previously isolated R. etli mutant strain CE367, even in the absence of such environmental cues. Chemical analysis of the LPS in strain CE367 demonstrated that it lacked the terminal sugar of the wild-type O antigen, 2,3,4-tri-O-methylfucose. A 3-kb stretch of DNA, designated as lpe3, restored wild-type antigenicity when transferred into CE367. From the sequence of this DNA, five open reading frames were postulated. Site-directed mutagenesis and complementation analysis suggested that the genes were organized in at least two transcriptional units, both of which were required for the production of LPS reactive with the diagnostic antibodies. Growth in anthocyanins or at low pH did not alter the specific expression of gusA from the transposon insertion of mutant CE367, nor did the presence of multiple copies of lpe3 situated behind a strong, constitutive promoter prevent epitope changes induced by these environmental cues. Mutations of the lpe genes did not prevent normal nodule development on Phaseolus vulgaris and had very little effect on the occupation of nodules in competition with the wild-type strain

ProSight PTM 2.0: improved protein identification and characterization for top down mass spectrometry

ProSight PTM 2.0 (http://prosightptm2.scs.uiuc.edu) is the next generation of the ProSight PTM web-based system for the identification and characterization of proteins using top down tandem mass spectrometry. It introduces an entirely new data-driven interface, integrated Sequence Gazer for protein characterization, support for fixed modifications, terminal modifications and improved support for multiple precursor ions (multiplexing). Furthermore, it supports data import and export for local analysis and collaboration

System level dynamics of post-translational modifications

Attempts to characterize cellular behaviors with static, univariate measurements cannot fully capture biological complexity and lead to an inadequate interpretation of cellular processes. Significant biological insight can be gleaned by considering the contribution of dynamic protein post-translational modifications (PTMs) utilizing systems-level quantitative analysis. High-resolution mass spectrometry coupled with computational modeling of dynamic signal–response relationships is a powerful tool to reveal PTM-mediated regulatory networks. Recent advances using this approach have defined network kinetics of growth factor signaling pathways, identified systems level responses to cytotoxic perturbations, elucidated kinase–substrate relationships, and unraveled the dynamics of PTM cross-talk. Innovations in multiplex measurement capacity, PTM annotation accuracy, and computational integration of datasets promise enhanced resolution of dynamic PTM networks and further insight into biological intricacies

AntigenDB: an immunoinformatics database of pathogen antigens

The continuing threat of infectious disease and future pandemics, coupled to the continuous increase of drug-resistant pathogens, makes the discovery of new and better vaccines imperative. For effective vaccine development, antigen discovery and validation is a prerequisite. The compilation of information concerning pathogens, virulence factors and antigenic epitopes has resulted in many useful databases. However, most such immunological databases focus almost exclusively on antigens where epitopes are known and ignore those for which epitope information was unavailable. We have compiled more than 500 antigens into the AntigenDB database, making use of the literature and other immunological resources. These antigens come from 44 important pathogenic species. In AntigenDB, a database entry contains information regarding the sequence, structure, origin, etc. of an antigen with additional information such as B and T-cell epitopes, MHC binding, function, gene-expression and post translational modifications, where available. AntigenDB also provides links to major internal and external databases. We shall update AntigenDB on a rolling basis, regularly adding antigens from other organisms and extra data analysis tools. AntigenDB is available freely at http://www.imtech.res.in/raghava/antigendb and its mirror site http://www.bic.uams.edu/raghava/antigendb