多路复用
基因表达
注意事项
实时聚合酶链反应
基因
计算生物学
DNA微阵列
生物
医学
生物信息学
遗传学
病理
作者
Ana Sofia de Olazarra,Fan‐En Chen,Tza‐Huei Wang,Shan X. Wang
出处
期刊:ACS Sensors
[American Chemical Society]
日期:2023-06-27
卷期号:8 (7): 2780-2790
被引量:7
标识
DOI:10.1021/acssensors.3c00696
摘要
Host-based gene expression analysis is a promising tool for a broad range of clinical applications, including rapid infectious disease diagnostics and real-time disease monitoring. However, the complex instrumentation requirements and slow turnaround-times associated with traditional gene expression analysis methods have hampered their widespread adoption at the point-of-care (POC). To overcome these challenges, we have developed an automated and portable platform that utilizes polymerase chain reaction (PCR) and giant magnetoresistive (GMR) biosensors to perform rapid multiplexed, targeted gene expression analysis at the POC. As proof-of-concept, we utilized our platform to amplify and measure the expression of four genes (HERC5, HERC6, IFI27, and IFIH1) that were previously shown to be upregulated in hosts infected with influenza viruses. The compact instrument conducted highly automated PCR amplification and GMR detection to measure the expression of the four genes in multiplex, then utilized Bluetooth communication to relay results to users on a smartphone application. To validate the platform, we tested 20 cDNA samples from symptomatic patients that had been previously diagnosed as either influenza-positive or influenza-negative using a RT-PCR virology panel. A non-parametric Mann–Whitney test revealed that day 0 (day of symptom onset) gene expression was significantly different between the two groups (p < 0.0001, n = 20). Hence, we preliminarily demonstrated that our platform could accurately discriminate between symptomatic influenza and non-influenza populations based on host gene expression in ∼30 min. This study not only establishes the potential clinical utility of our proposed assay and device for influenza diagnostics but it also paves the way for broadscale and decentralized implementation of host-based gene expression diagnostics at the POC.
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