MannDB - a microbial database of automated protein sequence analyses and evidence integration for protein characterization.

BACKGROUND: MannDB was created to meet a need for rapid, comprehensive automated protein sequence analyses to support selection of proteins suitable as targets for driving the development of reagents for pathogen or protein toxin detection. Because a large number of open-source tools were needed, it was necessary to produce a software system to scale the computations for whole-proteome analysis. Thus, we built a fully automated system for executing software tools and for storage, integration, and display of automated protein sequence analysis and annotation data. DESCRIPTION: MannDB is a relational database that organizes data resulting from fully automated, high-throughput protein-sequence analyses using open-source tools. Types of analyses provided include predictions of cleavage, chemical properties, classification, features, functional assignment, post-translational modifications, motifs, antigenicity, and secondary structure. Proteomes (lists of hypothetical and known proteins) are downloaded and parsed from Genbank and then inserted into MannDB, and annotations from SwissProt are downloaded when identifiers are found in the Genbank entry or when identical sequences are identified. Currently 36 open-source tools are run against MannDB protein sequences either on local systems or by means of batch submission to external servers. In addition, BLAST against protein entries in MvirDB, our database of microbial virulence factors, is performed. A web client browser enables viewing of computational results and downloaded annotations, and a query tool enables structured and free-text search capabilities. When available, links to external databases, including MvirDB, are provided. MannDB contains whole-proteome analyses for at least one representative organism from each category of biological threat organism listed by APHIS, CDC, HHS, NIAID, USDA, USFDA, and WHO. CONCLUSION: MannDB comprises a large number of genomes and comprehensive protein sequence analyses representing organisms listed as high-priority agents on the websites of several governmental organizations concerned with bio-terrorism. MannDB provides the user with a BLAST interface for comparison of native and non-native sequences and a query tool for conveniently selecting proteins of interest. In addition, the user has access to a web-based browser that compiles comprehensive and extensive reports. Access to MannDB is freely available at http://manndb.llnl.gov/.

System to assess genome sequencing needs for viral protein diagnostics and therapeutics.

Computational analyses of genome sequences may elucidate protein signatures unique to a target pathogen. We constructed a Protein Signature Pipeline to guide the selection of short peptide sequences to serve as targets for detection and therapeutics. In silico identification of good target peptides that are conserved among strains and unique compared to other species generates a list of peptides. These peptides may be developed in the laboratory as targets of antibody, peptide, and ligand binding for detection assays and therapeutics or as targets for vaccine development. In this paper, we assess how the amount of sequence data affects our ability to identify conserved, unique protein signature candidates. To determine the amount of sequence data required to select good protein signature candidates, we have built a computationally intensive system called the Sequencing Analysis Pipeline (SAP). The SAP performs thousands of Monte Carlo simulations, each calling the Protein Signature Pipeline, to assess how the amount of sequence data for a target organism affects the ability to predict peptide signature candidates. Viral species differ substantially in the number of genomes required to predict protein signature targets. Patterns do not appear based on genome structure. There are more protein than DNA signatures due to greater intraspecific conservation at the protein than at the nucleotide level. We conclude that it is necessary to use the SAP as a dynamic system to assess the need for continued sequencing for each species individually and to update predictions with each additional genome that is sequenced.

Limitations of TaqMan PCR for detecting divergent viral pathogens illustrated by hepatitis A, B, C, and E viruses and human immunodeficiency virus.

Recent events illustrate the imperative to rapidly and accurately detect and identify pathogens during disease outbreaks, whether they are natural or engineered. Particularly for our primary goal of detecting bioterrorist releases, detection techniques must be both species-wide (capable of detecting all known strains of a given species) and species specific. Due to classification restrictions on the publication of data for species that may pose a bioterror threat, we illustrate the challenges of finding such assays using five nonthreat organisms that are nevertheless of public health concern: human immunodeficiency virus (HIV) and four species of hepatitis viruses. Fluorogenic probe-based PCR assays (TaqMan; Perkin-Elmer Corp., Applied Biosystems, Foster City, Calif.) may be sensitive, fast methods for the identification of species in which the genome is conserved among strains, such as hepatitis A virus. For species such as HIV, however, the strains are highly divergent. We use computational methods to show that nine TaqMan primer and probe sequences, or signatures, are needed to ensure that all strains will be detected, but this is an unfeasible number, considering the cost of TaqMan probes. Strains of hepatitis B, C, and E viruses show intermediate divergence, so that two to three TaqMan signatures are required to detect all strains of each virus. We conclude that for species such as hepatitis A virus with high levels of sequence conservation among strains, signatures can be found computationally for detection by the TaqMan assay, which is a sensitive, rapid, and cost-effective method. However, for species such as HIV with substantial genetic divergence among strains, the TaqMan assay becomes unfeasible and alternative detection methods may be required. We compare the TaqMan assay with some of the alternative nucleic acid-based detection techniques of microarray, chip, and bead technologies in terms of sensitivity, speed, and cost.

High-density microarray of small-subunit ribosomal DNA probes.

Ribosomal DNA sequence analysis, originally conceived as a way to provide a universal phylogeny for life forms, has proven useful in many areas of biological research. Some of the most promising applications of this approach are presently limited by the rate at which sequences can be analyzed. As a step toward overcoming this limitation, we have investigated the use of photolithography chip technology to perform sequence analyses on amplified small-subunit rRNA genes. The GeneChip (Affymetrix Corporation) contained 31,179 20-mer oligonucleotides that were complementary to a subalignment of sequences in the Ribosomal Database Project (RDP) (B. L. Maidak et al., Nucleic Acids Res. 29:173-174, 2001). The chip and standard Affymetrix software were able to correctly match small-subunit ribosomal DNA amplicons with the corresponding sequences in the RDP database for 15 of 17 bacterial species grown in pure culture. When bacteria collected from an air sample were tested, the method compared favorably with cloning and sequencing amplicons in determining the presence of phylogenetic groups. However, the method could not resolve the individual sequences comprising a complex mixed sample. Given these results and the potential for future enhancement of this technology, it may become widely useful.