Molecular counting analysis of infectious disease
Abstract/Contents
- Abstract
- Infectious diseases have a profound impact on humankind, influencing the course of wars and the fate of nations. The case for applying next-generation sequencing (NGS) in clinical microbiology is becoming increasingly clear. A flood of recent studies have shown how this powerful technology can address pressing modern problems in infectious diseases, including resistance, rare infections, and outbreaks. In this thesis, we show that molecular counting of pathogen-derived cell-free DNA is a new diagnostic paradigm for infectious disease. We built a pipeline for counting pathogen-derived cell-free molecules in human plasma and a web appli- cation for browsing the resulting data. We applied these tools to thousands of clin- ical samples collected from hundreds of patients at Stanford hospital. We further processed thousands of clinical test records in order to show that this method can be broadly applied for non-invasive monitoring of viral, bacterial, and fungal infec- tions in deep tissues. Finally, we show that unbiased pathogen monitoring using this technique can track infections that escape hypothesis-centric clinical testing. As well as demonstrating this new diagnostic application of NGS, we show how NGS technology can be used to understand infectious disease mechanism. We de- veloped a pipeline for counting of sequencing reads derived from RNA-protein in- teractions in vivo. We show that this method (CLIP-seq) can be applied to viruses that have infected human cells and use it to reveal novel interactions between the Hepatitis-C virus (HCV) genome and human protein PCBP2. We also applied this method to HERV-K, an endogenous retrovirus. We showed that human embryo development occurs in the presence of retroviral products, which may protect the embryo from exogenous infection and help regulate early development. We highlight three separate ways to validate results from mechanistic CLIP-seq experiments, including comparative analysis, replicate matching, and functional studies. We also developed a multiplexed RNA-protein interaction assay that is compatible with the scale of CLIP-seq experiments and exceeds the throughput of common biochemical assays. We applied this technology to a model RNA-protein interaction (histone stem-loop and stem loop binding protein), recapitulating two decades of biochemistry and revealing novel features of the interaction. In summary, we built computational tools that apply molecular counting to in- fectious disease diagnostics and mechanism. For validation of these results, we developed a novel microfluidic tool for high-throughput biophysical measurements.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2015; ©2015 |
| Publication date | 2019; 2015 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Martin, Richard Lance |
|---|---|
| Degree supervisor | Chang, Howard Y. (Howard Yuan-Hao), 1972- |
| Thesis advisor | Chang, Howard Y. (Howard Yuan-Hao), 1972- |
| Thesis advisor | Quake, Stephen Ronald |
| Thesis advisor | Sarnow, P. (Peter) |
| Degree committee member | Quake, Stephen Ronald |
| Degree committee member | Sarnow, P. (Peter) |
| Associated with | Stanford University, Department of Bioengineering. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Lance Martin. |
|---|---|
| Note | Submitted to the Department of Bioengineering. |
| Thesis | Thesis Ph.D. Stanford University 2015. |
| Location | electronic resource |
Access conditions
- Copyright
- © 1969 by Richard Lance Martin
Also listed in
Loading usage metrics...