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Anal Chim Acta ; 1294: 342266, 2024 Mar 15.
Article in English | MEDLINE | ID: mdl-38336407

ABSTRACT

BACKGROUND: Differentiating between different states in nucleic acid circuits is crucial for various biological applications. One approach, there is a requirement for complicated sequential summation, which can be excessive for practical purposes. By selectively labeling biologically significant states, this study tackles the issue and presents a more cost-effective and streamlined solution. The challenge is to efficiently distinguish between different states in a nucleic acid circuit. RESULTS: An innovative method is introduced in this study to distinguish between states in a nucleic acid circuit, emphasizing the biologically relevant ones. The circuit comprises four DNA logic gates and two detection modules, one for determining fetal gender and the other for diagnosing X-linked genetic disorders. The primary module generates a G-quadruplex DNAzyme when activated by specific biomarkers, which leads to a distinct colorimetric signal. The secondary module responds to hemophilia and choroideremia biomarkers, generating one or two DNAzymes. The absence of female fetus indicators results in no DNAzyme or color change. The circuit can differentiate various fetal states by producing one to four active DNAzymes in response to male fetus biomarkers. A single-color solution for state differentiation is provided by this approach, which promises significant advancements in DNA computing and diagnostic applications. SIGNIFICANCE: The innovative approach used in this study to distinguish states in nucleic acid circuits holds great significance. By selectively labeling biologically relevant states, circuit design is simplified and complexity is reduced. This advancement enables cost-effective and efficient diagnostic applications and contributes to DNA computing, providing a valuable solution to a fundamental problem.


Subject(s)
DNA, Catalytic , G-Quadruplexes , Female , Male , Humans , DNA, Catalytic/metabolism , Computers, Molecular , DNA/genetics , Biomarkers
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