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 Rediske; Amanda 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

doi:10.1016/j.watres.2022.119162

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 journal › Article › peer-review

Abstract

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 language	English (US)
Journal	Water Research
DOIs	https://doi.org/10.1016/j.watres.2022.119162
State	Published - Oct 15 2022

Keywords

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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10.1016/j.watres.2022.119162

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Sivaganesan, M., Willis, J. R., Karim, M., Babatola, A., Catoe, D., Boehm, A. B., Wilder, M., Green, H., Lobos, A., Harwood, V. J., Hertel, S., Klepikow, R., Howard, M. F., Laksanalamai, P., Roundtree, A., Mattioli, M., Eytcheson, S., Molina, M., Lane, M., ... Shanks, O. C. (2022). Interlaboratory performance and quantitative PCR data acceptance metrics for NIST SRM® 2917. Water Research. https://doi.org/10.1016/j.watres.2022.119162

Sivaganesan, M, Willis, JR, Karim, M, Babatola, A, Catoe, D, Boehm, AB, Wilder, M, Green, H, Lobos, A, Harwood, VJ, Hertel, S, Klepikow, R, Howard, MF, Laksanalamai, P, Roundtree, A, Mattioli, M, Eytcheson, S, Molina, M, Lane, M, Rediske, R, Ronan, A, D'Souza, N, Rose, JB, Shrestha, A, Hoar, C, Silverman, AI, Faulkner, W, Wickman, K, Kralj, JG, Servetas, SL, Hunter, ME, Jackson, SA & Shanks, OC 2022, 'Interlaboratory performance and quantitative PCR data acceptance metrics for NIST SRM® 2917', Water Research. https://doi.org/10.1016/j.watres.2022.119162

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title = "Interlaboratory performance and quantitative PCR data acceptance metrics for NIST SRM{\textregistered} 2917",

abstract = "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{\textregistered} 2917 (NIST SRM{\textregistered} 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.",

keywords = "Microbial source tracking, Multiple laboratory, Rapid fecal indicator, Standard calibration material, qPCR",

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

note = "Publisher Copyright: {\textcopyright} 2022",

year = "2022",

month = oct,

day = "15",

doi = "10.1016/j.watres.2022.119162",

language = "English (US)",

journal = "Water Research",

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T1 - Interlaboratory performance and quantitative PCR data acceptance metrics for NIST SRM® 2917

AU - Sivaganesan, Mano

AU - Willis, Jessica R.

AU - Karim, Mohammad

AU - Babatola, Akin

AU - Catoe, David

AU - Boehm, Alexandria B.

AU - Wilder, Maxwell

AU - Green, Hyatt

AU - Lobos, Aldo

AU - Harwood, Valerie J.

AU - Hertel, Stephanie

AU - Klepikow, Regina

AU - Howard, Mondraya F.

AU - Laksanalamai, Pongpan

AU - Roundtree, Alexis

AU - Mattioli, Mia

AU - Eytcheson, Stephanie

AU - Molina, Marirosa

AU - Lane, Molly

AU - Rediske, Richard

AU - Ronan, Amanda

AU - D'Souza, Nishita

AU - Rose, Joan B.

AU - Shrestha, Abhilasha

AU - Hoar, Catherine

AU - Silverman, Andrea I.

AU - Faulkner, Wyatt

AU - Wickman, Kathleen

AU - Kralj, Jason G.

AU - Servetas, Stephanie L.

AU - Hunter, Monique E.

AU - Jackson, Scott A.

AU - Shanks, Orin C.

PY - 2022/10/15

Y1 - 2022/10/15

N2 - 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.

AB - 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.

KW - Microbial source tracking

KW - Multiple laboratory

KW - Rapid fecal indicator

KW - Standard calibration material

KW - qPCR

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DO - 10.1016/j.watres.2022.119162

M3 - Article

C2 - 36191524

AN - SCOPUS:85139034294

SN - 0043-1354

JO - Water Research

JF - Water Research

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

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