Science Inventory

Data Acceptance Criteria for Standardized Human-Associated Fecal Source Identification Quantitative Real-Time PCR Methods

Citation:

Shanks, O., C. Kelty, R. Oshiro, Rich Haugland, T. Madi, L. Brooks, K. Field, AND Mano Sivaganesan. Data Acceptance Criteria for Standardized Human-Associated Fecal Source Identification Quantitative Real-Time PCR Methods. APPLIED AND ENVIRONMENTAL MICROBIOLOGY. American Society for Microbiology, Washington, DC, 82(9):2773-2782, (2016).

Impact/Purpose:

To inform the public.

Description:

There is a growing interest in the application of human-associated fecal sourceidentification quantitative real-time PCR (qPCR) technologies for water quality management. The transition from a research tool to a standardized protocol requires a high degree of confidence in data quality across laboratories. Data quality is typically determined through a series of specifications that ensure good experimental practice and the absence of bias in results due to DNA isolation and amplification interferences. However, there is currently a lack of consensus on how best to evaluate and interpret human fecal source identification qPCR experiments. This is, in part, due to the lack of standardized protocols and information on inter laboratory variability in conditions for data acceptance. The aim of this study is to provide users and reviewers with a complete series of conditions for data acceptance derived from a multiple laboratory data set using a standardized procedure. To establish these benchmarks, data from HF183/BacR287 and HumM2 human-associated qPCR methods was generated across 14 laboratories. Each laboratory followed a standardized protocol utilizing the same lot of reference DNA materials, DNA isolation kits, amplification reagents, and test samples to generate comparable data. After removing outliers, a nested ANOVA was used to establish proficiency metrics that include lab-to-lab, replicate testing within a lab, and random error for amplification inhibition and sample processing controls. Other data acceptance measurements included extraneous DNA contamination assessments (no template and extraction blank controls) and calibration model performance (correlation coefficient, amplification efficiency, lower limit of quantification). To demonstrate the implementation of proposed standardized protocols and data acceptance criteria, comparable data from two additional laboratories was reviewed.

URLs/Downloads:

http://dx.doi.org/10.1128/AEM.03661-15   Exit

Record Details:

Record Type: DOCUMENT (JOURNAL/PEER REVIEWED JOURNAL)
Product Published Date: 05/02/2016
Record Last Revised: 04/27/2016
OMB Category: Other
Record ID: 312452