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.

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.

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.

Base composition analysis of human mitochondrial DNA using electrospray ionization mass spectrometry: a novel tool for the identification and differentiation of humans.

In traditional approaches, mitochondrial DNA (mtDNA) variation is exploited for forensic identity testing by sequencing the two hypervariable regions of the human mtDNA control region. To reduce time and labor, single nucleotide polymorphism (SNP) assays are being sought to possibly replace sequencing. However, most SNP assays capture only a portion of the total variation within the desired regions, require a priori knowledge of the position of the SNP in the genome, and are generally not quantitative. Furthermore, with mtDNA, the clustering of SNPs complicates the design of SNP extension primers or hybridization probes. This article describes an automated electrospray ionization mass spectrometry method that can detect a number of clustered SNPs within an amplicon without a priori knowledge of specific SNP positions and can do so quantitatively. With this technique, the base composition of a PCR amplicon, less than 140 nucleotides in length, can be calculated. The difference in base composition between two samples indicates the presence of an SNP. Therefore, no post-PCR analytical construct needs to be developed to assess variation within a fragment. Of the 2754 different mtDNA sequences in the public forensic mtDNA database, nearly 90% could be resolved by the assay. The mass spectrometer is well suited to characterize and quantitate heteroplasmic samples or those containing mixtures. This makes possible the interpretation of mtDNA mixtures (as well as mixtures when assaying other SNPs). This assay can be expanded to assess genetic variation in the coding region of the mtDNA genome and can be automated to facilitate analysis of a large number of samples such as those encountered after a mass disaster.

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.

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.