Infectious disease remains a major cause of morbidity across the globe. Successful medical intervention requires accurate diagnosis, which can be challenging due to symptoms shared among infections. Moreover, increasing drug resistance makes it important to identify and characterize pathogenic microbes and choose effective treatments in a timely manner. In this competing renewal, we will extend technology developed under our previous R01 to enable rapid, sensitive, and information-rich infectious disease diagnosis. Our new technology, which we dub Gigapixel NGS, extends our Gigapixel digital PCR (dPCR) technology from the previous R01 by incorporating a powerful next-generation sequencing capability. The core innovation of Gigapixel dPCR was to perform dPCR assays in double emulsion vesicles, rather than conventional water-in- oil droplets utilized by commercial dPCR instruments (Bio-Rad, RainDance). Vesicles obviate the need for specialized droplet analyzers and allow common flow cytometers to be used for quantification. Flow cytometers are ubiquitous in research and clinical labs, with superior analysis capabilities (i.e. speed, sensitivity, and multiplexing) in comparison to specialized droplet analyzers. This allows Gigapixel dPCR to increase the number of compartments that can be analyzed to over 100 million, providing a 100-fold increase in sensitivity of quantification. Moreover, flow cytometers can sort out vesicles in which PCR has detected a DNA target, a functionality not found in existing droplet analyzers. In this competing renewal, we will leverage the capability of Gigapixel NGS to detect, isolate and sequence infectious pathogen genomes directly from patient samples. The proposed workflow will increase the efficiency and sensitivity of pathogen sequencing, yielding higher-quality draft genomes at far lower cost. In collaboration with Dr. Charles Chiu, an infectious disease physician at UCSF specializing in clinical sample sequencing for pathogen detection, we will develop bioinformatic tools to interrogate the recovered genomes for relevant biomarker sequences, such as virulence factors and drug resistance genes. Through further collaboration with Fluent Biosciences, we will adapt Gigapixel NGS to their commercial platform, allowing the protocol to be implemented by research and clinical labs as a commercially available kit.
The Specific Aims of our proposal are to: 1) Extend Gigapixel PCR into a clinically relevant platform, in the form of Gigapixel NGS. 2) Demonstrate integrated quantification and accurate genome sequencing of bacterial infections in meningitis. 3) Apply the technology for in silico identification and diagnosis of flavivirus infections from (liquid) biopsy samples such as plasma and cerebrospinal fluid.

Public Health Relevance

Infectious disease remains a major cause of morbidity across the globe. Successful medical intervention requires accurate diagnosis, which can be challenging due to symptoms shared among different infections. Moreover, increasing drug resistance makes it important to characterize the causative pathogens and choose appropriate and effective treatments. Additionally, diagnosis must be made rapidly since prognosis can depend on sample-to-answer turnaround time. In this competing renewal, we will extend technology developed under our previous R01 to enable rapid, sensitive, and information-rich infectious disease diagnosis from clinical samples.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
5R01EB019453-06
Application #
9972907
Study Section
Enabling Bioanalytical and Imaging Technologies Study Section (EBIT)
Program Officer
Atanasijevic, Tatjana
Project Start
2014-09-30
Project End
2023-03-31
Budget Start
2020-04-01
Budget End
2021-03-31
Support Year
6
Fiscal Year
2020
Total Cost
Indirect Cost
Name
University of California San Francisco
Department
Pharmacology
Type
Schools of Pharmacy
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94118
Siltanen, Christian A; Cole, Russell H; Poust, Sean et al. (2018) An Oil-Free Picodrop Bioassay Platform for Synthetic Biology. Sci Rep 8:7913
Hatori, Makiko N; Kim, Samuel C; Abate, Adam R (2018) Particle-Templated Emulsification for Microfluidics-Free Digital Biology. Anal Chem 90:9813-9820
Kim, Samuel C; Clark, Iain C; Shahi, Payam et al. (2018) Single-Cell RT-PCR in Microfluidic Droplets with Integrated Chemical Lysis. Anal Chem 90:1273-1279
Demaree, Benjamin; Weisgerber, Daniel; Lan, Freeman et al. (2018) An Ultrahigh-throughput Microfluidic Platform for Single-cell Genome Sequencing. J Vis Exp :
Lan, Freeman; Demaree, Benjamin; Ahmed, Noorsher et al. (2017) Single-cell genome sequencing at ultra-high-throughput with microfluidic droplet barcoding. Nat Biotechnol 35:640-646
Sukovich, David J; Kim, Samuel C; Ahmed, Noorsher et al. (2017) Bulk double emulsification for flow cytometric analysis of microfluidic droplets. Analyst 142:4618-4622
Sukovich, David J; Lance, Shea T; Abate, Adam R (2017) Sequence specific sorting of DNA molecules with FACS using 3dPCR. Sci Rep 7:39385
Shahi, Payam; Kim, Samuel C; Haliburton, John R et al. (2017) Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding. Sci Rep 7:44447
Lim, Shaun W; Lance, Shea T; Stedman, Kenneth M et al. (2017) PCR-activated cell sorting as a general, cultivation-free method for high-throughput identification and enrichment of virus hosts. J Virol Methods 242:14-21
Kim, Samuel C; Premasekharan, Gayatri; Clark, Iain C et al. (2017) Measurement of copy number variation in single cancer cells using rapid-emulsification digital droplet MDA. Microsyst Nanoeng 3:

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