Fluorescence Aptasensor of Tuberculosis Interferon-γ in Clinical Samples Regulated by Steric Hindrance and Selective Identification.
Piaopiao ChenWu PengRunlian QuYaqin HeTangyuheng LiuJin HuangBinwu YingPublished in: Analytical chemistry (2022)
Although there are many interferon gamma (IFN-γ)-based tools for tuberculosis (TB) diagnosis, they are less sensitive and laborious. Here, we developed an IFN-γ aptasensor using pyrophosphate-cerium coordination polymeric nanoparticles (PPi-Ce CPNs) as signal reporters and a double-stranded DNA as a probe. The sensor was realized by sterically regulating the polymerization elongation of terminal deoxynucleotidyl transferase (TdT) and the selective recognition reaction of PPi-Ce CPNs. This method employs PPi-Ce CPNs to selectively identify Cu 2+ and polyT-templated copper nanoparticles (Cu NPs), as well as a TdT-assisted amplification technique. Our data showed that under optimized experimental conditions, a limit of detection of as low as 0.25 fg/mL was achieved, with a linear range of 1-100 fg/mL, and a good target protein specificity. The detection sensitivity was an order of magnitude higher than that observed with Cu NPs when used as signal reporters. This IFN-γ quantification technique was further validated in clinical samples using 57 clinical TB patients (22 negative and 35 positive). Our findings agreed with those from enzyme-linked immunosorbent assay, GeneXpert MTB/rifampin assay, and polymerase chain reaction detection of TB-DNA and those from clinical imaging techniques. Therefore, our analytical system may provide an additional and more sensitive tool for the early diagnosis of TB.
Keyphrases
- mycobacterium tuberculosis
- dendritic cells
- label free
- immune response
- quantum dots
- single molecule
- pulmonary tuberculosis
- protein protein
- high throughput
- loop mediated isothermal amplification
- sensitive detection
- end stage renal disease
- binding protein
- chronic kidney disease
- nucleic acid
- ejection fraction
- high resolution
- circulating tumor
- electronic health record
- real time pcr
- machine learning
- hepatitis c virus
- mass spectrometry
- artificial intelligence
- patient reported outcomes
- oxide nanoparticles
- patient reported
- fluorescence imaging