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31 December 2019 Detection of methylated cytosine on single strand DNA based on immune-functionalized and glutaraldehyde modified liquid exfoliated graphene field effect transistor
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Abstract
Detection of the 5-methylcytosine (5mC) is one of the requirements of modern epigenetics research. The main challenges in this issue are how to distinguish the 5mC site from the unmethylated ones in the chain of nucleotides, and determine its amount. To streamline the tedious operations in traditional bisulfite conversion (BC) and polymerase chain reaction (PCR) based detection methods, lots of graphene derivatives and electrochemistry (EC) sensors have been exploited. In this work, we would like to propose an electronic method for DNA methylation detection by using five testing single strand DNA (ssDNA) chains as proof-of-concepts, based on the glutaraldehyde modified liquid exfoliated graphene field effect transistor (LEG-FET). First of all, for the sake of identifying the 5mC site, the immunorecognition strategy is utilized and incorporated with LEG-FET working principle. That is, the methylation sites on testing ssDNA chains are first recognized by the fixed 5mC’s antibody (5mCab) molecules on the channel of LEG-FET, then they are transduced to the varied current between the electrodes of drain and source (IDS). It is found, the changing ratios of IDS (ΔIDS/IDS0) are in negative relation with the amount of 5mC sites (NmC) at each of the ssDNA concentrations (CssDNA). When CssDNA is varied from 1 to 106 pM, the slopes of the responding curves -ΔIDS/IDS0 vs. NmC are increased from 0.54 to 3.70 %/NmC; meanwhile, at each of constant Nmc, the slopes of -ΔIDS/IDS0 vs. CssDNA are also examined to proof the repeatability in DNA methylation detection.
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Jizhao Zhang, Shihiu Hu, Zhongrong Wang, and Yunfang Jia "Detection of methylated cytosine on single strand DNA based on immune-functionalized and glutaraldehyde modified liquid exfoliated graphene field effect transistor", Proc. SPIE 11384, Eleventh International Conference on Signal Processing Systems, 113841D (31 December 2019); https://doi.org/10.1117/12.2559509
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