کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7231332 | 1470956 | 2016 | 17 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
High-throughput sample-to-answer detection of DNA/RNA in crude samples within functionalized micro-pipette tips
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
شیمی
شیمی آنالیزی یا شیمی تجزیه
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چکیده انگلیسی
We develop a micro-pipette tip-based nucleic acid test (MTNT) for high-throughput sample-to-answer detection of both DNA and RNA from crude samples including cells, bacteria, and solid plants, without the need of sample pretreatment and complex operation. MTNT consists of micro-pipette tips and embedded solid phase nucleic acid extraction membranes, and fully integrates the functions of nucleic acid extraction from crude samples, loop-mediated isothermal amplification (LAMP) of nucleic acids, and visual readout of assays. The total assaying time for DNA or RNA from a variety of crude samples ranges from 90 to 160Â min. The limit of detection (LOD) of MTNT is 2 copies of plasmids containing the target nucleic acid fragments of Ebola virus, and 8 CFU of Escherichia coli carrying Ebola virus-derived plasmids. MTNT can also detect CK-19 mRNA from as few as 2 cancer cells without complicated procedures such as RNA extraction and purification. We further demonstrate MTNT in a high-throughput format using an eight-channel pipette and a homemade mini-heater, with a maximum throughput of 40 samples. Compared with other point-of-care (POC) nucleic acid tests (NAT), MTNT could assay both DNA and RNA directly from liquid (cells/bacteria/blood) or solid (plant) samples in a straightforward, sensitive, high-throughput, and containment-free manner, suggesting a considerable promise for low-cost and POC NAT in remote areas.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Biosensors and Bioelectronics - Volume 75, 15 January 2016, Pages 28-33
Journal: Biosensors and Bioelectronics - Volume 75, 15 January 2016, Pages 28-33
نویسندگان
Wenjing Lu, Jidong Wang, Qiong Wu, Jiashu Sun, Yiping Chen, Lu Zhang, Chunsheng Zheng, Wenna Gao, Yi Liu, Xingyu Jiang,