A Poisson-Independent Approach to Precision Nucleic Acid Quantification in Microdroplets.

Droplet Poisson statistics competitive PCR deoxyribonucleic acid (DNA) quantification

Journal

ACS applied bio materials
ISSN: 2576-6422
Titre abrégé: ACS Appl Bio Mater
Pays: United States
ID NLM: 101729147

Informations de publication

Date de publication:
24 Apr 2024
Historique:
medline: 25 4 2024
pubmed: 25 4 2024
entrez: 24 4 2024
Statut: aheadofprint

Résumé

Digital PCR (dPCR) has become indispensable in nucleic acid (NA) detection across various fields, including viral diagnostics and mutant detection. However, misclassification of partitions in dPCR can significantly impact accuracy. Despite existing methods to minimize misclassification bias, accurate classification remains elusive, especially for nonamplified target partitions. To address these challenges, this study introduces an innovative microdroplet-based competitive PCR platform for nucleic acid quantification in microfluidic devices independent of Poisson statistics. In this approach, the target concentration (T) is determined from the concentration of competitor DNA (C) at the equivalence point (E.P.), where C/T is 1. Competitive PCR ensures that the ratio of target to competitor DNA remains constant during amplification, reflected in the resultant fluorescence intensity, allowing the quantification of target DNA concentration at the equivalence point. The unique amplification technique eliminates Poisson distribution, addressing misclassification challenges. Additionally, our approach reduces the need for post-PCR procedures and shortens analytical time. We envision this platform as versatile, reproducible, and easily adaptable for driving significant progress in molecular biology and diagnostics.

Identifiants

pubmed: 38658190
doi: 10.1021/acsabm.4c00350
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Auteurs

Reya Ganguly (R)

Department of Chemical Engineering and Applied Chemistry, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Republic of Korea.

Chang-Soo Lee (CS)

Department of Chemical Engineering and Applied Chemistry, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Republic of Korea.

Classifications MeSH