Download pdf
The Principle, Application and Development Prospect of the Technology PCR
- 1 Nanchang No.2 Middle School, Nanchang, China
* Author to whom correspondence should be addressed.
Abstract
Conventional diagnostic methods for pathogen identification face significant limitations in clinical practice. These include inadequate sensitivity for low microbial loads, prolonged processing times, and susceptibility to sample matrix interference. As a result, this review focuses on recent progress in polymerase chain reaction technology, with particular emphasis on digital PCR platforms. Digital PCR represents a substantial improvement over quantitative PCR methodology. It provides three key advantages: direct absolute quantification without standard curves, enhanced detection capability for rare targets (sensitivity to 1 copy/μL), and superior performance in inhibitor-containing samples. These characteristics address many limitations observed in traditional diagnostic approaches. Emerging PCR-CRISPR integrations (e.g., PCR-Cas13a for H. pylori) are also discussed in this review. Current limitations include equipment complexity and sample interference, but portable devices, multiplex platforms, and AI-assisted analysis show promise for overcoming these challenges and improving diagnostics. These advancements are expanding PCR's applications in precision medicine and infectious disease management.
Keywords
Digital PCR (dPCR), Pathogen detection, CRISPR diagnostics, Molecular testing
[1]. Lei S, Chen S, Zhong Q. Digital PCR for accurate quantification of pathogens: Principles, applications, challenges and future prospects. Int J Biol Macromol. 2021 Aug 1;184:750-759. doi: 10.1016/j.ijbiomac.2021.06.132. Epub 2021 Jun 24. PMID: 34171259.
[2]. Wang Y, Liu L, Liu X, Wu K, Zhu X, Ma L, Su J. An Ultrasensitive PCR-Based CRISPR-Cas13a Method for the Detection of Helicobacter pylori. J Pers Med. 2022 Dec 17;12(12):2082. doi: 10.3390/jpm12122082. PMID: 36556302; PMCID: PMC9784247.
[3]. Chu J, Romero A, Taulbee J, Aran K. Development of Single Molecule Techniques for Sensing and Manipulation of CRISPR and Polymerase Enzymes. Small. 2023 Sep;19(38):e2300328. doi: 10.1002/smll.202300328. Epub 2023 May 24. PMID: 37226388; PMCID: PMC10524706.
[4]. Smith CJ, Osborn AM. Advantages and limitations of quantitative PCR (Q-PCR)-based approaches in microbial ecology. FEMS Microbiol Ecol. 2009 Jan;67(1):6-20. doi: 10.1111/j.1574-6941.2008.00629.x. PMID: 19120456.
[5]. Ma X, Xia H, Pan Y, Huang Y, Xu T, Guan F. Double-Tube Multiplex TaqMan Real-Time PCR for the Detection of Eight Animal-Derived Dairy Ingredients. J Agric Food Chem. 2024 May 22;72(20):11640-11651. doi: 10.1021/acs.jafc.4c01294. Epub 2024 May 9. PMID: 38725129; PMCID: PMC11117397.
[6]. Zarlenga DS, Higgins J. PCR as a diagnostic and quantitative technique in veterinary parasitology. Vet Parasitol. 2001 Nov 22;101(3-4):215-30. doi: 10.1016/s0304-4017(01)00568-4. PMID: 11707298.
[7]. Pedlar M, Emery MJ, Warburton PJ. Amplifying PCR productivity and environmental sustainability through shortened cycling protocols. Biochimie. 2024 Jun;221:60-64. doi: 10.1016/j.biochi.2024.01.013. Epub 2024 Jan 21. PMID: 38262587.
[8]. Yang S, Rothman RE. PCR-based diagnostics for infectious diseases: uses, limitations, and future applications in acute-care settings. Lancet Infect Dis. 2004 Jun;4(6):337-48. doi: 10.1016/S1473-3099(04)01044-8. PMID: 15172342; PMCID: PMC7106425.
[9]. Galluzzi L, Ceccarelli M, Diotallevi A, Menotta M, Magnani M. Real-time PCR applications for diagnosis of leishmaniasis. Parasit Vectors. 2018 May 2;11(1):273. doi: 10.1186/s13071-018-2859-8. PMID: 29716641; PMCID: PMC5930967.Guo J, Starr D,
[10]. Guo H. Classification and review of free PCR primer design software. Bioinformatics. 2021 Apr 1;36(22-23):5263-5268. doi: 10.1093/bioinformatics/btaa910. PMID: 33104196.
Cite this article
Li,Z. (2025). The Principle, Application and Development Prospect of the Technology PCR. Theoretical and Natural Science,112,35-41.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
Disclaimer/Publisher's Note
The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
About volume
Volume title: Proceedings of ICEGEE 2025 Symposium: Sensor Technology and Multimodal Data Analysis
© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and
conditions of the Creative Commons Attribution (CC BY) license. Authors who
publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons
Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this
series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published
version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial
publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and
during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See
Open access policy for details).