Optimization of RNA Purification and Analysis for Automated, Pre-Symptomatic Disease Diagnostics
When diagnosing disease, time is often a more formidable enemy than the pathogen itself. Current detection methods rely primarily on post-symptomatic protein production (i.e. antibodies), which does not occur in noticeable levels until several weeks after infection. As such, a major goal among researchers today is to expedite pre-symptomatic disease recognition and treatment. Since most pathogens are known to leave a unique signature on the genetic expression of the host, one potential diagnostic tool is host mRNA. In my experiments, I examined several methods of isolating RNA and reading its genetic sequence. I first used two types of reverse transcriptase polymerase chain reactions (using commercial RNA) and examined the resultant complementary DNA through gel electrophoresis. I then proceeded to isolate and purify whole RNA from actual human monocytes and THP-1 cells using several published methods, and examined gene expression on the RNA itself. I compared the two RT-PCR methods and concluded that a double step RT-PCR is superior to the single step method. I also compared the various techniques of RNA isolation by examining the yield and purity of the resultant RNA. Finally, I studied the level of cellular IL-8 and IL-1 gene expression, two genes involved in the human immune response, which can serve as a baseline for future genetic comparison with LPS-exposed cells. Based on the results, I have determined which conditions and procedures are optimal for RNA isolation, RT-PCR, and RNA yield assessment. The overall goal of my research is to develop a flow-through system of RNA analysis, whereby blood samples can be collected and analyzed for disease prior to the onset of symptoms. The Pathomics group hopes to automate this process by removing the human labor factor, thereby decreasing the procedure's cost and increasing its availability to the general population. Eventually, our aim is to have an autonomous diagnostic system based on RNA analysis that would significantly mitigate the effects of disease and as a close parallel, of large-scale bioterrorism.
- Research Organization:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 15016765
- Report Number(s):
- UCRL-TR-213336; TRN: US200516%%95
- Country of Publication:
- United States
- Language:
- English
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