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Intracellular Entropy-Driven Multi-Bit DNA Computing for Tumor Progression Discrimination |
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| Authors: | Min Bai Prof. Feng Chen Xiaowen Cao Dr. Yue Zhao Jing Xue Prof. Xu Yu Prof. Chunhai Fan Prof. Yongxi Zhao |
| Affiliation: | 1. Institute of Analytical Chemistry and Instrument for Life Science, The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xianning West Road, Xi'an, Shaanxi, 710049 China These authors contributed equally to this work.;2. Institute of Analytical Chemistry and Instrument for Life Science, The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xianning West Road, Xi'an, Shaanxi, 710049 China;3. Institute of Molecular Medicine, Renji Hospital, School of Medicine and School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, Shanghai, 200127 China |
| Abstract: | Tumor progressions such as metastasis are complicated events that involve abnormal expression of different miRNAs and enzymes. Monitoring these biomolecules in live cells with computational DNA nanotechnology may enable discrimination of tumor progression via digital outputs. Herein, we report intracellular entropy-driven multivalent DNA circuits to implement multi-bit computing for simultaneous analysis of intracellular telomerase and microRNAs including miR-21 and miR-31. These three biomolecules can trigger respective DNA strand displacement recycling reactions for signal amplification. They are visualized by fluorescence imaging, and their signal outputs are encoded as multi-bit binary codes for different cell types. The results can discriminate non-tumorigenic, malignant and metastatic breast cells as well as respective tumors. This DNA computing circuit is further performed in a microfluidic chip to differentiate rare co-cultured cells, which holds a potential for the analysis of clinical samples. |
| Keywords: | DNA nanotechnology enzyme and RNA microfluidic chip molecular computing tumor discrimination |