Development of a plasmid reference material to improve the accuracy of quantitative detection of <i>Bovine parvovirus</i>

Reference materials (RMs) serve as essential standards for the quantitative analysis of nucleic acid molecules using quantitative real-time PCR (qPCR), a widely employed method for pathogen detection. However, the lack of universal reference materials traceable to the International System of Units (SI) compromises the accuracy and comparability of quantitative results. To address this gap, we developed a plasmid RM for the quantitative detection of the <i>Bovine Parvovirus</i> (BPV) VP1 gene. To determine the reference value of the plasmid RM, we established a highly accurate and specific digital PCR (dPCR) method. This dPCR assay demonstrated excellent linearity across five orders of magnitude (10<sup>0</sup>-10<sup>5</sup> copies/reaction, <i>R</i><sup>2</sup> > 0.999). The limits of detection (LOD) and quantification (LOQ) were determined to be 9 copies/reaction and 30 copies/reaction, respectively. Using the validated dPCR method, the reference value of the BPV plasmid RM was quantified as (2.21 ± 0.25) × 10<sup>6</sup> copies per μL, with an expanded uncertainty (coverage factor <i>k</i> = 2). The developed plasmid RM provides a reliable standard for the quantitative detection of BPV using qPCR, offering improved accuracy and traceability in diagnostic applications.

Authors

Institutions

Publication Details

Journal
Analytical Methods
Published
2025-01-01
DOI
https://doi.org/10.1039/d5ay00491h
Primary Topic
Animal Virus Infections Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of a plasmid reference material to improve the accuracy of quantitative detection of Bovine parvovirus

Jingya Yang, Jiayi Yang, Xia Wang, Mingyue Lv et al.
Analytical Methods
Animal Virus Infections Studies
article

Development of a plasmid reference material to improve the accuracy of quantitative detection of Bovine parvovirus

Jingya Yang, Jiayi Yang, Xia Wang, Mingyue Lv, Yanmin Lin, Caihang Zhang, Lianhua Dong, Liang Yu
article en

Abstract

Reference materials (RMs) serve as essential standards for the quantitative analysis of nucleic acid molecules using quantitative real-time PCR (qPCR), a widely employed method for pathogen detection. However, the lack of universal reference materials traceable to the International System of Units (SI) compromises the accuracy and comparability of quantitative results. To address this gap, we developed a plasmid RM for the quantitative detection of the <i>Bovine Parvovirus</i> (BPV) VP1 gene. To determine the reference value of the plasmid RM, we established a highly accurate and specific digital PCR (dPCR) method. This dPCR assay demonstrated excellent linearity across five orders of magnitude (10<sup>0</sup>-10<sup>5</sup> copies/reaction, <i>R</i><sup>2</sup> > 0.999). The limits of detection (LOD) and quantification (LOQ) were determined to be 9 copies/reaction and 30 copies/reaction, respectively. Using the validated dPCR method, the reference value of the BPV plasmid RM was quantified as (2.21 ± 0.25) × 10<sup>6</sup> copies per μL, with an expanded uncertainty (coverage factor <i>k</i> = 2). The developed plasmid RM provides a reliable standard for the quantitative detection of BPV using qPCR, offering improved accuracy and traceability in diagnostic applications.

Analytical MethodsVol. 17(26)
National Institute of Metrology (CN), Shanghai Ocean University (CN)
Openalex Percentile: Top 85%
Animal Virus Infections Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.