“Employing the co-localization benefit of ddPCR, dd-Check STEC will reduce the number of false positive samples to quickly confirm the linkage of stx and eae,” says Mike Clark, MS, international PCR group manager of Bio-Rad’s Food Science Division.
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“ddPCR technology is a method for performing digital PCR within several thousand water-oil emulsion droplets,” Clark relates. “The key to ddPCR is sample partitioning. In traditional PCR, a single measurement is performed on a single sample. In ddPCR, a single sample is partitioned into thousands of nano-sized droplets allowing thousands of independent, single amplification events within that sample.”
With a PCR reaction taking place in individual droplets, this technology brings several advantages and benefits to food safety testing. “These benefits include absolute quantification without the need for running a standard curve, greater tolerance to PCR inhibitors, and one-step unambiguous identification/confirmation of genomes bearing dependent markers (co-localization of markers),” Clark points out.
Co-localization ddPCR can detect true enterohemorrhagic E. coli (EHEC) positive samples in a variety of food matrices, Clark says. “Food matrices confirmed positive for EHEC, a highly pathogenic subset of STEC, results when two virulence factors, Shiga toxin (stx) and intimin (eae), are present together within one E. coli bacterium,” he elaborates. “The ddPCR technology makes it possible to detect both virulence markers in a single bacterium by observing the percent linkage of two markers (stx and eae) making it possible to discriminate bacterium containing both markers from multiple bacteria each carrying a single marker.”
The current method for detection of EHEC in food involves enriching a sample and using PCR to screen for the stx1/stx2 and eae genes.
“The challenge with this type of testing is that typical PCR cannot distinguish between bacteria carrying both virulence markers and mixed cultures in which these target genes are present in different cells,” Clark explains. “These presumptive samples must then go through a laborious confirmation process resulting in a high number of these samples confirming as negative for EHEC.”
NCBI Gene ID Tools
At the National Center for Biotechnology Information (NCBI), Bethesda, Md., involvement with rapid testing methods is limited to tools and databases used for rapid analysis of whole genome sequencing data, according to Michael Feldgarden, PhD, an NCBI staff scientist.
“We don’t have wet labs at NCBI, but instead collaborate with labs at public health agencies, such as the FDA, CDC, and USDA to analyze their whole genome sequencing data in real time,” Dr. Feldgarden points out. “Our tools are used by these collaborators to facilitate investigation of foodborne disease outbreaks and to track antimicrobial resistance genes.”
The NCBI Pathogen Detection pipeline currently has data on over 280,000 bacterial isolates, including the four major foodborne bacterial pathogens—Campylobacter, E. coli, Listeria, and Salmonella—as well as 18 other pathogens. “Within 24 hours of sequence data submission, the pipeline can identify closely related isolates, describe how they are related to each other, and provide different visualizations of these relationships and data in NCBI’s Isolate Browser,” Dr. Feldgarden says.
In 2018, for several of the foodborne pathogens, NCBI has added the capacity to identify a preliminary set of isolates related to a particular isolate within 60 minutes of the sequence data being uploaded to NCBI. “These tools provide a provisional set of isolates for our partner agencies and programs to investigate, helping them to focus their resources more effectively and determine cases for a full epidemiological analysis,” Dr. Feldgarden explains.
“In addition, NCBI recently developed AMRFinder, a publicly available software tool that uses a curated database of antimicrobial resistance genes we produced to identify antimicrobial resistance genes in genomes,” Dr. Feldgarden says. “All of the isolates in the Pathogen Detection system are screened for resistance genes through ARMFinder and these data are made available through the Isolates Browser.”