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Pathogen Detection and Identification: The Next Generation of Analyses


NIST and FDA are co-developing DNA-based materials for mixed microbial detection. Our annual workshop brings together private and public interests to discuss measurement issues involved with clinical, environmental, and other samples.


Human disease resulting from pathogens represents a tremendous burden on the health care system. Many hospitals have adopted new, rapid polymerase chain reaction (PCR)-based detection systems because the time to diagnose and begin effective treatment has a direct impact on patient survival and significantly reduces the time in hospital. Still, many pathogens have developed resistance to conventional therapies (e.g. methicillin-resistant Staphylococcus aureus, or MRSA), and detection of genetic markers for these resistances has proven difficult because they are difficult to predict and many are not the same from location to location.

High-throughput, or "Next Generation," sequencing technologies have undergone a technological revolution, enabling genome-scale sequence measurements in just days to hours. Additionally, computational tools have been developed alongside to perform various tasks such as assembling genomes from the data and aligning the data to known organisms (mapping). This has enabled the technology to perform sequencing on DNA isolated from unknown pathogens, rapidly identify them within a background of host (human) DNA, and even inform treatment. New/emerging pathogens and resistant microbial strains can be identified without a priori knowledge of the sample, making this a potentially powerful tool to address these critical challenges facing today's health care system.

With these new sequencing-based tools in place, developers and regulatory agencies have identified the need for standards to benchmark the performance of these systems and verify performance for limits of detection and distinguishing "near-neighbor" organisms with varying degrees of genetic similarity. In particular, mixtures of microbial samples are needed, as these better represent the kinds of samples being analyzed using these methods. Data and samples that have been vetted and well-characterized will enable cross-comparability of the tools, supply developers with early feedback on system performance, and give regulators a means to assess the veracity of technological claims.

Created May 10, 2016, Updated April 26, 2024