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DNA Electrochemical Biosensor Based on Iron Oxide/Nanocellulose Crystalline Composite Modified Screen-Printed Carbon Electrode for Detection of Mycobacterium tuberculosis
Death from tuberculosis has resulted in an increased need for early detection to prevent a tuberculosis (TB) epidemic, especially in closed and crowded populations. Herein, a sensitive electrochemical DNA biosensor based on functionalized iron oxide with mercaptopropionic acid (MPA-Fe(3)O(4)) nanopa...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7435410/ https://www.ncbi.nlm.nih.gov/pubmed/32722334 http://dx.doi.org/10.3390/molecules25153373 |
Sumario: | Death from tuberculosis has resulted in an increased need for early detection to prevent a tuberculosis (TB) epidemic, especially in closed and crowded populations. Herein, a sensitive electrochemical DNA biosensor based on functionalized iron oxide with mercaptopropionic acid (MPA-Fe(3)O(4)) nanoparticle and nanocellulose crystalline functionalized cetyl trimethyl ammonium bromide (NCC/CTAB) has been fabricated for the detection of Mycobacterium tuberculosis (MTB). In this study, a simple drop cast method was applied to deposit solution of MPA-Fe(3)O(4)/NCC/CTAB onto the surface of the screen-printed carbon electrode (SPCE). Then, a specific sequence of MTB DNA probe was immobilized onto a modified SPCE surface by using the 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide/N-hydroxysuccinimide (EDC/NHS) coupling mechanism. For better signal amplification and electrochemical response, ruthenium bipyridyl Ru(bpy)(3)(2+) was assigned as labels of hybridization followed by the characteristic test using differential pulse voltammetry (DPV). The results of this biosensor enable the detection of target DNA until a concentration as low as 7.96 × 10(−13) M with a wide detection range from 1.0 × 10(−6) to 1.0 × 10(−12) M. In addition, the developed biosensor has shown a differentiation between positive and negative MTB samples in real sampel analysis. |
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