Ultrasensitive quantification of circulating disease biomarkers through enzymatic labeling and single molecule counting

Smith, Lucas David

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https://hdl.handle.net/2142/98221 Copy

Description

Title

Ultrasensitive quantification of circulating disease biomarkers through enzymatic labeling and single molecule counting

Author(s)

Smith, Lucas David

Issue Date

2017-05-26

Director of Research (if dissertation) or Advisor (if thesis)

Smith, Andrew M.

Department of Study

School of Integrative Biology

Discipline

Biology

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Micro-ribonucleic acid (miRNA)
• Deoxyribonucleic acid (DNA)
• Synthesis
• Microscopy
• Single molecule imaging
• Fluorophore
• Circulating biomarker
• Deoxyribonucleic acid (DNA) synthesis
• Quantum dot

Abstract

The focus of my graduate research is on the development of simplified and ultrasensitive methods for quantifying low abundance biomarkers with the ultimate goal of developing robust tools for advancing disease diagnosis. In recent years there has been an immense expansion in the identification of sensitive and specific indicators of disease. As our understanding of these biochemical parameters continues to advance, the ability to quantify low abundance biomarkers from small samples sizes has become increasingly important to continue expanding the range of available disease indicators. Further, as medical diagnostics continues to transition to point-of-care testing, the development of simplified protocols capable of producing rapid results has been a main element limiting the development of portable devices. Together, each of these factors will play a critical role in the analysis of clinical samples for the purpose of providing more robust diagnostic and prognostic information to patients suffering from diseases ranging from infectious disease to cancer, metabolic, autoimmune, and gastrointestinal disorders. This thesis focuses on two independent projects which aim to address these limitations through the design of improved methods for the quantification of microRNA (miRNA) and protein in biological fluids. The first of my projects relates to the ultrasensitive detection of miRNA, one of the most exciting emerging classes of biomarkers. In recent years, miRNA in blood circulating have been identified as robust indicators of a variety of diseases. Despite extensive research into the potential impact of miRNAs as clinical indicators, state of the art methods remain dependent on incredibly complex and time consuming techniques. Together, these limitations have been main factors extending research timelines and precluding the development of POC assays. Main factors contributing to the complexity of existing tests include the dependence on reverse transcriptase, DNA ligase, and PCR steps, each of which necessitate time consuming reagent handling as well as 1-2 h incubations. To addresses these issues, my research has focused on the development of an efficient RNA amplification technique which uses enzymatic chemical labeling to generate densely labeled double stranded products that are then labeled with fluorescent probes. Individual molecules are then directly counted using total internal reflection fluorescence microscopy, as opposed to conventional indirect methods using the polymerase chain reaction (PCR). This technology provides a fundamental framework for the development of an ultrasensitive miRNA detection method which allows for the absolute and direct quantification of miRNAs in clinical samples. This thesis demonstrates enzymatic labeling of miRNA with fluorescent probes as well as the optimization of surface attachment and probe labeling methods. Ultimately this research concludes with the successful detection of labeled miRNA, establishing a framework for advancing the sensitivity of this method toward the fundamental level of digital single molecule counting.

Graduation Semester

2017-08

Type of Resource

text

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http://hdl.handle.net/2142/98221

Copyright and License Information

Copyright 2017 Lucas David Smith

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