The Microbial Rosetta Stone: a database system for tracking infectious microorganisms.

The Microbial Rosetta Stone (MRS) database system was developed to support the law enforcement community by providing a comprehensive and connected microbial pathogen data-information repository. To handle the myriad types of pathogen information required to support law enforcement and intelligence community investigations, a data model previously developed for medical and epidemiological information was enhanced. The data contained in MRS are a broad collection of expert-curated microbial pathogen information, but given the multitude of potential microbes and toxins that may be used in a biocrime or bioterrorism act continual information collection and updating are required. The MRS currently relates governmental community-specific pathogen priority lists, sequence metadata, taxonomic classifications, and diseases to strain collections, specific detection and treatment protocols, and experimental results for biothreat agents. The system contains software tools that help to load, curate, and connect the data. A shared MRS database can be populated in real time by multiple users in multiple locations. Querying tools also provide simple and powerful means to access the data in any part of the database.

Word frequency analysis reveals enrichment of dinucleotide repeats on the human X chromosome and [GATA]n in the X escape region.

Most of the human genome encodes neither protein nor known functional RNA, yet available approaches to seek meaningful information in the "noncoding" sequence are limited. The unique biology of the X chromosome, one of which is silenced in mammalian females, can yield clues into sequence motifs involved in chromosome packaging and function. Although autosomal chromatin has some capacity for inactivation, evidence indicates that sequences enriched on the X chromosome render it fully competent for silencing, except in specific regions that escape inactivation. Here we have used a linguistic approach by analyzing the frequency and distribution of nine base-pair genomic "words" throughout the human genome. Results identify previously unknown sequence differences on the human X chromosome. Notably, the dinucleotide repeats [AT]n, [AC]n, and [AG]n are significantly enriched across the X chromosome compared with autosomes. Moreover, a striking enrichment (>10-fold) of [GATA]n is revealed throughout the 10-Mb segment at Xp22 that escapes inactivation, and is confirmed by fluorescence in situ hybridization. A similar enrichment is found in other eutherian genomes. Our findings clearly demonstrate sequence differences relevant to the novel biology and evolution of the X chromosome. Furthermore, they implicate simple sequence repeats, linked to gene regulation and unusual DNA structures, in the regulation and formation of facultative heterochromatin. Results suggest a new paradigm whereby a regional escape from X inactivation is due to the presence of elements that prevent heterochromatinization, rather than the lack of other elements that promote it.

The Microbial Rosetta Stone database: A common structure for microbial biosecurity threat agents.

Infectious microorganisms are important to multiple communities engaged in biodefense and biosecurity, including the agencies responsible for health, defense, law enforcement, agriculture, and drug and food safety. Many agencies have created lists of high priority infectious microorganisms to prioritize research efforts or to formally control the possession and distribution of specific organisms or toxins. However, the biological classification of infectious microorganisms is often complex and ambiguous, leading to uncertainty and confusion for scientists involved in biosecurity work. To address this problem, we created a database, known as the Microbial Rosetta Stone, which resolves many of these ambiguities and includes links to additional information on the microbes, such as gene sequence data and scientific literature. Here we discuss the efforts to coordinate organism names from pathogen lists from various governmental agencies according to biological relatedness and show the overlap of high-priority organisms from multiple agencies. To our knowledge, this is the first comprehensive coordination of pathogens, synonyms, and correct taxonomic names. The organized tables and visual aids are freely available at http://www.microbialrosettastone.com. This website provides a single location where access to information on a broad range of disease-causing organisms and toxins is available to members of the biosecurity community.

Rapid identification and strain-typing of respiratory pathogens for epidemic surveillance.

Epidemic respiratory infections are responsible for extensive morbidity and mortality within both military and civilian populations. We describe a high-throughput method to simultaneously identify and genotype species of bacteria from complex mixtures in respiratory samples. The process uses electrospray ionization mass spectrometry and base composition analysis of PCR amplification products from highly conserved genomic regions to identify and determine the relative quantity of pathogenic bacteria present in the sample. High-resolution genotyping of specific species is achieved by using additional primers targeted to highly variable regions of specific bacterial genomes. This method was used to examine samples taken from military recruits during respiratory disease outbreaks and for follow up surveillance at several military training facilities. Analysis of respiratory samples revealed high concentrations of pathogenic respiratory species, including Haemophilus influenzae, Neisseria meningitidis, and Streptococcus pyogenes. When S. pyogenes was identified in samples from the epidemic site, the identical genotype was found in almost all recruits. This analysis method will provide information fundamental to understanding the polymicrobial nature of explosive epidemics of respiratory disease.

The Microbial Rosetta Stone Database: a compilation of global and emerging infectious microorganisms and bioterrorist threat agents.

BACKGROUND: Thousands of different microorganisms affect the health, safety, and economic stability of populations. Many different medical and governmental organizations have created lists of the pathogenic microorganisms relevant to their missions; however, the nomenclature for biological agents on these lists and pathogens described in the literature is inexact. This ambiguity can be a significant block to effective communication among the diverse communities that must deal with epidemics or bioterrorist attacks. RESULTS: We have developed a database known as the Microbial Rosetta Stone. The database relates microorganism names, taxonomic classifications, diseases, specific detection and treatment protocols, and relevant literature. The database structure facilitates linkage to public genomic databases. This paper focuses on the information in the database for pathogens that impact global public health, emerging infectious organisms, and bioterrorist threat agents. CONCLUSION: The Microbial Rosetta Stone is available at http://www.microbialrosettastone.com/. The database provides public access to up-to-date taxonomic classifications of organisms that cause human diseases, improves the consistency of nomenclature in disease reporting, and provides useful links between different public genomic and public health databases.

Rapid identification of emerging pathogens: coronavirus.

We describe a new approach for infectious disease surveillance that facilitates rapid identification of known and emerging pathogens. The process uses broad-range polymerase chain reaction (PCR) to amplify nucleic acid targets from large groupings of organisms, electrospray ionization mass spectrometry for accurate mass measurements of PCR products, and base composition signature analysis to identify organisms in a sample. We demonstrate this principle by using 14 isolates of 9 diverse Coronavirus spp., including the severe acute respiratory syndrome-associated coronavirus (SARS-CoV). We show that this method could identify and distinguish between SARS and other known CoV, including the human CoV 229E and OC43, individually and in a mixture of all 3 human viruses. The sensitivity of detection, measured by using titered SARS-CoV spiked into human serum, was approximate, equals1 PFU/mL. This approach, applicable to the surveillance of bacterial, viral, fungal, or protozoal pathogens, is capable of automated analysis of >900 PCR reactions per day.

Discovery of RNA structural elements using evolutionary computation.

RNA molecules fold into characteristic secondary and tertiary structures that account for their diverse functional activities. Many of these RNA structures, or certain structural motifs within them, are thought to recur in multiple genes within a single organism or across the same gene in several organisms and provide a common regulatory mechanism. Search algorithms, such as RNAMotif, can be used to mine nucleotide sequence databases for these repeating motifs. RNAMotif allows users to capture essential features of known structures in detailed descriptors and can be used to identify, with high specificity, other similar motifs within the nucleotide database. However, when the descriptor constraints are relaxed to provide more flexibility, or when there is very little a priori information about hypothesized RNA structures, the number of motif 'hits' may become very large. Exhaustive methods to search for similar RNA structures over these large search spaces are likely to be computationally intractable. Here we describe a powerful new algorithm based on evolutionary computation to solve this problem. A series of experiments using ferritin IRE and SRP RNA stem-loop motifs were used to verify the method. We demonstrate that even when searching extremely large search spaces, of the order of 10(23) potential solutions, we could find the correct solution in a fraction of the time it would have taken for exhaustive comparisons.