Issue 17, 2023

High-throughput photo-chemiluminescence imaging for HIV DNA determination based on a sulfur-doped graphitic carbonitride photocatalyst

Abstract

In this work, a novel photo-chemiluminescence (PCL) array imaging technique was developed to detect HIV DNA sequences using water-dispersed ultrathin sulfur-doped g-C3N4 porous nanosheets (SCNNSs) as photocatalysts, with complementary chains of HIV DNA as the biorecognition elements. The PCL response was enhanced when a suitable amount of SCNNSs was used. The large specific surface area and π-conjugated structure of the SCNNSs provided a good platform for immobilizing the complementary chains of HIV DNA. When DNA complementary chains were present, some of the catalytically active sites of SCNNSs were blocked, and the PCL of the platform was weakened. When the HIV DNA was added, the DNA double chain was far away from the surfaces of the SCNNSs because the Image ID:d3ay00312d-t1.gif stacking interactions between the formed dsDNA and SCNNSs were weak. Therefore, the addition of the target HIV DNA sequence noticeably restored the signal. In the range of 5.00 × 10−8 M to 200 × 10−8 M, the enhanced PCL response was linearly related to the concentration of the HIV DNA sequence, and the detection limit (3S/N) was 1.50 × 10−8 mol L−1. In addition, the combination of SCNNSs with complementary chains of HIV DNA successfully produced a high-performance PCL imaging sensor. In these proof-of-concept experiments, we demonstrated that our method was fast, portable, and ultra-sensitive, with high throughput.

Graphical abstract: High-throughput photo-chemiluminescence imaging for HIV DNA determination based on a sulfur-doped graphitic carbonitride photocatalyst

Supplementary files

Article information

Article type
Paper
Submitted
02 Mar 2023
Accepted
06 Apr 2023
First published
24 Apr 2023

Anal. Methods, 2023,15, 2114-2120

High-throughput photo-chemiluminescence imaging for HIV DNA determination based on a sulfur-doped graphitic carbonitride photocatalyst

H. Zhang, Y. Jiang, J. Wang and Z. Jiang, Anal. Methods, 2023, 15, 2114 DOI: 10.1039/D3AY00312D

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