Accurate and quantitative single cell sequencing with digital droplet MDA PI: Adam R. Abate Abstract: Accurate single cell genomic sequencing is important for applications ranging from copy number variation analysis in cancer to the investigation of uncultivable microbes. To provide sufficient DNA for sequencing, a single cell's genome must be massively amplified. However, existing methods introduce errors (MALBAC) or result in significant bias (MDA), yielding low-confidence genomes with gaps in coverage. In this proposal, we will develop single cell digital droplet MDA (sc-ddMDA), a method that will combine the uniform amplification of MALBAC with the high copying accuracy of MDA. This project will extend our preliminary results in which we have demonstrated the ability to reliably and uniformly amplify the genomes of just ten bacterial cells. Using novel biochemical and microfluidic methods, we will push the limit to a single cell and will implement automation for high-throughput processing of, ultimately, thousands of single cells. Importantly, we will provide two versions of the technology, one using no specialized equipment accessible to any lab with molecular biology expertise, and a higher-throughput version using microfluidics and robotic automation.
Aim 1 : Optimize methods to uniformly amplify and sequence the genomes of single cells.
Aim 2 : Develop high-throughput single cell ddMDA.
Aim 3 : Implement microfluidic pre-amplification for accurate, high-throughput single cell sequencing.

Public Health Relevance

The objective of the proposed study will be to enable accurate, quantitative, and high throughput sequencing of single cells. The technologies developed will advance the fields of genomics and single cell analysis and will provide new tools to understand pathogen evolution and human disease. These technologies should ultimately have broad biomedical, biotechnological, and industrial applications.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
5R01HG008978-02
Application #
9350384
Study Section
Instrumentation and Systems Development Study Section (ISD)
Program Officer
Smith, Michael
Project Start
2016-09-09
Project End
2019-06-30
Budget Start
2017-07-01
Budget End
2018-06-30
Support Year
2
Fiscal Year
2017
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
Delley, Cyrille L; Liu, Leqian; Sarhan, Maen F et al. (2018) Combined aptamer and transcriptome sequencing of single cells. Sci Rep 8:2919
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 :
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
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
Karbaschi, Mohsen; Shahi, Payam; Abate, Adam R (2017) Rapid, chemical-free breaking of microfluidic emulsions with a hand-held antistatic gun. Biomicrofluidics 11:044107
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
Clark, Iain C; Abate, Adam R (2017) Finding a helix in a haystack: nucleic acid cytometry with droplet microfluidics. Lab Chip 17:2032-2045
Abatemarco, Joseph; Sarhan, Maen F; Wagner, James M et al. (2017) RNA-aptamers-in-droplets (RAPID) high-throughput screening for secretory phenotypes. Nat Commun 8:332

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