research product . 2021

Profiling Multiomic Biomarkers using Particle Detection Counters and Spectral-FLIM Microscopy

Vu, Tam Minh;
Open Access English
  • Published: 01 Jan 2021
  • Publisher: eScholarship, University of California
  • Country: United States
Profiling multiomic biomarkers in bulk and in situ provides critical information which enables basic research and clinical applications. Unfortunately, most existing profiling methods are limited due to either low multiplexing, sensitivity, costs, or assay complexity. This thesis aims to develop two core technologies that address 1) bulk profiling issues with sensitivity and low throughput as well as 2) in situ profiling issues with low multiplexing capabilities, costs, and limited throughput. To address the first issue, this work introduces a novel liquid biopsy approach that utilizes a platform technology called Integrated Comprehensive Droplet Digital Detection (IC3D). This integrated approach combines microfluidic droplet partitioning technology, fluorescent multiplexed PCR chemistry, and our own unique and rapid particle counting technology to deliver ultrasensitive and ultrafast detection of colorectal cancer-specific genomic biomarkers from minimally processed blood samples. To address the second issue, this work introduces a new spatial multi-omics technology termed Multi Omic Single-scan Assay with Integrated Combinatorial Analysis (MOSAICA) that integrates a) in situ labeling of molecular markers (e.g. mRNA, proteins) in cells or tissues with combinatorial fluorescence spectral and lifetime encoded probes, and b) spectra and time-resolved fluorescence imaging and analysis to enable rapid, high-throughput, and cost-effective spatial profiling of multi-omics biomarkers. By utilizing both time and intensity domains for labeling and imaging, this technology seeks to discriminate a vast repertoire of lifetime and spectral components simultaneously within the same pixel or image of a sample to enable highly increased multiplexing capabilities with standard optical systems. Overall, these two technologies represent simple, versatile, and scalable tools which enable more rapid, sensitive, and/or multiplexed protein/transcriptomic analysis.
ACM Computing Classification System: ComputingMethodologies_PATTERNRECOGNITION
free text keywords: Biomedical engineering, FISH, FLIM, Hyperspectral, Spatial, Spectral-FLIM, Transcriptomic
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