June 4, 2013
UNIVERSITY PARK, Pa.Researchers at Penn State's College of Agricultural Sciences have developed a new approach that may reduce the time it takes health officials to identify Salmonella strains by nearly 50%. The finding may significantly speed up the response to many outbreaks of foodborne illness, allowing epidemiological investigators to identify the exact strains of Salmonella that make people sick and to more quickly find and eliminate the source of the disease.
"Right now, public-health laboratories use a technique called pulse field gel electrophoresis, or PFGE, to subtype Salmonella strains, and it normally takes one to three days to identify a specific strain. The technique we devised often takes just one day," said study lead author Nikki Shariat, postdoctoral researcher in molecular microbiology in the Department of Food Science.
Working in collaboration with Carol Sandt, a scientist with the Bureau of Laboratories, Division of Clinical Microbiology in the Pennsylvania Department of Health and Eija Trees, a microbiologist at the CDC, Shariat used Salmonella samples supplied by the state health department. Results of the study were published in the Journal of Clinical Microbiology.
"Compared to the current method being used nationally and internationally to subtype Salmonella, our approach is faster," Shariat said. "The significance of that is you need to trace the source of an outbreak as quickly as you can before you start insisting on restaurant and farm closures. It is important to pinpoint the source of the bacteriathe quicker you do that the quicker you can respond to the disease outbreak."
In April 2013, a report by the Centers for Disease Control and Prevention (CDC) revealed the rates of foodborne illnesses in the United States rose in 2012 with a total of 19,531 illnesses, 4,563 hospitalizations and 68 deaths from nine germs commonly spread through foods in 2012.
The researchers developed the new approach to identify strains of the Salmonella serotype Newport. The method focuses on two virulence genes and two novel regions of Salmonella DNA called clustered regularly interspaced short palindromic repeats, or CRISPRs. The researchers devised a method of multi-virulence-locus sequence typing, or MVLST, that can detect strain-specific differences in the DNA at these four locations. The researchers designated the method as CRISPR-MVLST.
Newport is the third most common serological variant of Salmonella and its incidence increased by 46% between 1999 and 2009. In 2009, Newport accounted for 9.3% of total salmonellosis cases.
"The significance of our work is not just that we can subtype Salmonella strains in half the time or less compared to the protocol that is used right now," she said, "but also our approach is very comparable in terms of the dataour method yields results that are accurate and similar to the PFGE method now widely used."
The researchers tested the accuracy of their CRISPR-MVLST method in an impromptu blind study. Toward the end of the research project, they applied their analysis to a Salmonella outbreak, associated with tomatoes that occurred in Pennsylvania in summer 2012 in which 37 people got sick.
"The Pennsylvania Department of Health sent us 20 isolates, 10 from the outbreak and 10 not from the outbreak, and we did the analysis not knowing which ones were which," Shariat said. "We were able to identify exactly those that were associated with the outbreak. Additionally, the DNA sequence is basically a text file that is very easy to communicate and share between laboratories nationally and internationally. The data is definitely more robust."
The new method is different because it looks at the DNA sequence, whereas the other method basically cuts the DNA into small pieces with no actual sequence information.
"Fifty percent of bacteria have CRISPR regions, and using these for identification has been done with quite a few bacteria, such as Mycobacterium tuberculosis, as well as with some that cause foodborne illness, such as Campylobacter and E. coli," Shariat said.
You May Also Like