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

AI Article Synopsis

  • Epidemic respiratory infections cause significant health issues and fatalities in both military and civilian settings.
  • A new high-throughput method using electrospray ionization mass spectrometry and PCR analysis allows for the efficient identification and quantity assessment of pathogenic bacteria in respiratory samples.
  • The method revealed high levels of bacteria like Haemophilus influenzae and Streptococcus pyogenes in samples from military recruits during outbreaks, showing nearly identical genotypes in affected individuals.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1138257PMC
http://dx.doi.org/10.1073/pnas.0409920102DOI Listing

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