Interlaboratory performance and quantitative PCR data acceptance metrics for NIST SRM® 2917

Mano Sivaganesan, Jessica R. Willis, Mohammad Karim, Akin Babatola, David Catoe, Alexandria B. Boehm, Maxwell Wilder, Hyatt Green, Aldo Lobos, Valerie J. Harwood, Stephanie Hertel, Regina Klepikow, Mondraya F. Howard, Pongpan Laksanalamai, Alexis Roundtree, Mia Mattioli, Stephanie Eytcheson, Marirosa Molina, Molly Lane, Richard RediskeAmanda Ronan, Nishita D'Souza, Joan B. Rose, Abhilasha Shrestha, Catherine Hoar, Andrea I. Silverman, Wyatt Faulkner, Kathleen Wickman, Jason G. Kralj, Stephanie L. Servetas, Monique E. Hunter, Scott A. Jackson, Orin C. Shanks

Research output: Contribution to journalArticlepeer-review


Surface water quality quantitative polymerase chain reaction (qPCR) technologies are expanding from a subject of research to routine environmental and public health laboratory testing. Readily available, reliable reference material is needed to interpret qPCR measurements, particularly across laboratories. Standard Reference Material® 2917 (NIST SRM® 2917) is a DNA plasmid construct that functions with multiple water quality qPCR assays allowing for estimation of total fecal pollution and identification of key fecal sources. This study investigates SRM 2917 interlaboratory performance based on repeated measures of 12 qPCR assays by 14 laboratories (n = 1008 instrument runs). Using a Bayesian approach, single-instrument run data are combined to generate assay-specific global calibration models allowing for characterization of within- and between-lab variability. Comparable data sets generated by two additional laboratories are used to assess new SRM 2917 data acceptance metrics. SRM 2917 allows for reproducible single-instrument run calibration models across laboratories, regardless of qPCR assay. In addition, global models offer multiple data acceptance metric options that future users can employ to minimize variability, improve comparability of data across laboratories, and increase confidence in qPCR measurements.

Original languageEnglish (US)
JournalWater Research
StatePublished - Oct 15 2022


  • Microbial source tracking
  • Multiple laboratory
  • Rapid fecal indicator
  • Standard calibration material
  • qPCR

ASJC Scopus subject areas

  • Environmental Engineering
  • Civil and Structural Engineering
  • Ecological Modeling
  • Water Science and Technology
  • Waste Management and Disposal
  • Pollution


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