Wet-Etched Microchamber Array Digital PCR Chip for SARS-CoV-2 Virus and Ultra-Early Stage Lung Cancer Quantitative Detection.
Yimeng SunYaru HuangTong QiQinghui JinChunping JiaJianlong ZhaoShilun FengLijuan LiangPublished in: ACS omega (2022)
We report a novel design of chamber-based digital polymerase chain reaction (cdPCR) chip structure. Using a wet etching process and silicon-glass bonding, the chamber size can be adjusted independently of the process and more feasibly in a normal lab. In addition, the structure of the chip is optimized through hydrodynamic computer simulations to eliminate dead space when the sample is injected into the chip. The samples will be distributed to each separated microchambers for an isolated reaction based on Poisson distribution. Due to the difference in expansion coefficients, isolation of the sample in the microchambers by the oil phase on top ensures homogeneity and independence of the sample in the microchambers. The prepared microarray cdPCR chip enables high-throughput and high-sensitivity quantitative measurement of the SARS-CoV-2 virus gene and the mutant lung cancer gene. We applied the chip for the detection of different concentrations of the mix containing the open reading frame 1ab (ORF1ab) gene, the most specific and conservative gene region of the SARS-CoV-2 virus. In addition to this, we also successfully detected the fluorescence of the epidermal growth factor receptor (EGFR) mutant gene in independent microchambers. At a throughput of 46 200 microchambers, solution mixtures containing both genes were successfully tested quantitatively, with a detection limit of 10 copies/μL. Importantly, the chips are individually inexpensive and easy to industrialize. In addition, the microarray can provide a unified solution for other viral sequences, cancer marker assay development, and point-of-care testing (POCT).
Keyphrases
- high throughput
- sars cov
- epidermal growth factor receptor
- genome wide
- genome wide identification
- circulating tumor cells
- copy number
- early stage
- high resolution
- small cell lung cancer
- real time pcr
- tyrosine kinase
- advanced non small cell lung cancer
- minimally invasive
- machine learning
- papillary thyroid
- deep learning
- mass spectrometry
- bioinformatics analysis
- quantum dots
- energy transfer
- neoadjuvant chemotherapy
- resting state