Anthrax molecular epidemiology and forensics: using the appropriate marker for different evolutionary scales

• Published in: Infection, Genetics and Evolution Genetics and Evolution, 2004-09, Vol.4 (3), p.205-213
• Main Authors: Keim, Paul, Van Ert, Matthew N., Pearson, Talima, Vogler, Amy J., Huynh, Lynn Y., Wagner, David M.
• Format: Article
• Language: English
• Subjects: Animals; Anthrax; Anthrax - epidemiology; Bacillus anthracis; Bacillus anthracis - classification; Bacillus anthracis - genetics; Biological Evolution; Bioterrorism; Canonical SNPs; canSNPs; Forensic Sciences; Genetic Markers; Humans; Microbial forensics; MLVA; Molecular Epidemiology; PHRANA; Phylogeny; Polymorphism, Genetic; SNPs; SNR
• ISSN: 1567-1348; 1567-7257
• DOI: 10.1016/j.meegid.2004.02.005

Precise identification of Bacillus anthracis isolates has aided forensic and epidemiological analyses of natural anthrax cases, bioterrorism acts and industrial scale accidents by state-sponsored bioweapons programs. Because there is little molecular variation among B. anthracis isolates, identifying and using rare variation is crucial for precise strain identification. We think that mutation is the primary diversifying force in a clonal, recently emerged pathogen, such as B. anthracis, since mutation rate is correlated with diversity on a per locus basis. While single nucleotide polymorphisms (SNPs) are rare, their detection is facilitated by whole genome discovery approaches. As highly stable phylogenetic markers, SNPs are useful for identifying long branches or key phylogenetic positions. Selection of single, diagnostic “Canonical SNPs” (canSNPs) for these phylogenetic positions allows for efficient and defining assays. We have taken a nested hierarchal strategy for subtyping B. anthracis, which is consistent with traditional diagnostics and applicable to a wide range of pathogens. Progressive hierarchical resolving assays using nucleic acids (PHRANA) uses a progression of diagnostic genomic loci that are initially highly stable but with low resolution and, ultimately, very unstable but with high resolution. This approach mitigates the need for data weighting and provides both a deeply rooted phylogenetic hypothesis and high resolution discrimination among closely related isolates.