PathoGenetix Research Shows Rapid Identification of Multiple <em>Salmonella</em> Serovars in Food Samples

PathoGenetix™, Inc., a commercial-stage developer of an automated system for rapid bacterial identification, will presented new research demonstrating the use of Genome Sequence Scanning™ (GSS™) technology to confirm and identify multiple serovars of Salmonella in enriched food samples in less than five hours. The data, included in a poster presentation at the 4th American Society for Microbiology (ASM) Conference on Salmonella in Boston, add to a growing body of research demonstrating the use of PathoGenetix’s proprietary genotyping technology to reliably identify pathogens of public health and food safety significance, including Salmonella and Shiga toxin-producing E. coli (STECs).

The study evaluated the use of GSS in molecular serotyping and sub-typing of Salmonella, and as a tool for simultaneous detection of multiple serovars of Salmonella in complex mixtures. The study results show that GSS can be used to infer the serotype of an unknown Salmonella strain, based on the location of the strain on the GSS tree and the identity of its neighbors.

The results also demonstrate the ability of GSS to shorten the time to just five hours for pathogen subtyping and serotype determination from an enriched food sample, including those containing multiple serovars.

Because Genome Sequence Scanning is culture independent, and fully automated from sample preparation to final report, the technology greatly reduces the time, complexity and skill required when compared to other molecular and next generation sequencing (NGS) identification approaches. The strain-type information provided by GSS is comparable to pulsed field gel electrophoresis (PFGE), the current standard for pathogen typing in foodborne outbreak investigation and response. As a result, GSS offers a powerful new tool for epidemiological investigations and outbreak monitoring that can enable quicker decisions affecting food safety and public health. The GSS technology will be commercially available in 2014 in the RESOLUTION™ Microbial Genotyping System.

According to the American Society of Microbiology, Salmonella infections continue to be a major public health problem in many parts of the world. In the U.S., Salmonella is the leading cause of foodborne illnesses leading to hospitalization and death.

The Salmonella genus has more than 2,500 serotypes or serovars, based on the antigens that the organism presents on its surface. In the U.S., Salmonella Enteritidis and Salmonella Typhimurium are the most common serotypes, accounting for half of all Salmonella infections in people.

The 4th ASM Conference on Salmonella brings together scientists from a variety of backgrounds to present the most recent research and discoveries in the field, including new approaches in diagnosis, treatment and prevention of infections.

PathoGenetix’s research, entitled “Evaluation of Genome Sequence Scanning technology for molecular (sub)-serotyping of Salmonella and simultaneous detection of multiple Salmonella serovars in complex mixtures” is being presented in a poster session at the meeting on October 9.

The research tested the strain typing capability of GSS using more than 400 strains and genome sequences representing the most frequently encountered Salmonella serovars from food products associated with human illness. The results show that Genome Sequence Scanning clustered Salmonella strains into serovar-specific branches on the GSS tree, clearly demarcating the major serovars from each other. Polyphyletic lineage serovars like S. Newport and S. Saintpaul formed more than one distinctly separated branch on the tree, reflecting the genetic heterogeneity within these serovars. GSS assigned correct serovar designations to strains untypeable by conventional serotyping and to antigenic variants of serovars based on genetic similarity. Genome Sequence Scanning also reliably detected the presence of up to three different serovars of Salmonella in the presence of complex background flora, demonstrating the technology’s ability to provide strain information directly from complex mixtures.