Dual-Responsive Carbon Quantum Dots for the Simultaneous Detection of Cytosine and 5-Methylcytosine Interpreted by a Machine Learning-Assisted Smartphone.
5-methylcytosine
DNA methylation
carbon quantum dot
cytosine
density functional theory
machine learning
Journal
ACS applied materials & interfaces
ISSN: 1944-8252
Titre abrégé: ACS Appl Mater Interfaces
Pays: United States
ID NLM: 101504991
Informations de publication
Date de publication:
30 Aug 2023
30 Aug 2023
Historique:
medline:
1
9
2023
pubmed:
16
8
2023
entrez:
16
8
2023
Statut:
ppublish
Résumé
DNA methylation is an epigenetic alteration that results in 5-methylcytosine (5-mC) through the addition of a methyl group to the fifth carbon of a cytosine (C) residue. The methylation level, the ratio of 5-mC to C, in urine might be related to the whole-body epigenetic status and the occurrence of common cancers. To date, never before have any nanomaterials been developed to simultaneously determine C and 5-mC in urine samples. Herein, a dual-responsive fluorescent sensor for the urinary detection of C and 5-mC has been developed. This assay relied on changes in the optical properties of nitrogen-doped carbon quantum dots (CQDs) prepared by microwave-assisted pyrolysis. In the presence of C, the blue-shifted fluorescence intensity of the CQDs increased. However, fluorescence quenching was observed upon the addition of 5-mC. This was primarily due to photoinduced electron transfer as confirmed by the density functional theory calculation. In urine samples, our sensitive fluorescent sensor had detection limits for C and 5-mC of 43.4 and 74.4 μM, respectively, and achieved satisfactory recoveries ranging from 103.5 to 115.8%. The simultaneous detection of C and 5-mC leads to effective methylation level detection, achieving recoveries in the range of 104.6-109.5%. Besides, a machine learning-enabled smartphone was also developed, which can be effectively applied to the determination of methylation levels (0-100%). These results demonstrate a simple but very effective approach for detecting the methylation level in urine, which could have significant implications for predicting the clinical prognosis.
Identifiants
pubmed: 37585565
doi: 10.1021/acsami.3c00785
doi:
Substances chimiques
5-Methylcytosine
6R795CQT4H
Cytosine
8J337D1HZY
Carbon
7440-44-0
Nitrogen
N762921K75
Fluorescent Dyes
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM