Autoimmune (AI) disorders like rheumatoid arthritis (RA) and systemic lupus erythmatosus (SLE) afflict 1 in 50 Americans and cost more than $100B annually. A hallmark of autoimmunity is recognition and binding to self- antigens by host B cell/T cell receptors (BCR/TCR) resulting in cycles of host cell apoptosis and inflammation. To date, there are few druggable targets for treatment of autoimmunity. Instead, clinicians use broadly immunosuppressant antibodies that indiscriminately target all B cells in an effort to inhibit those that bind self-antigen peptides (SAP). This results in significant collateral damage because most B cells are a healthy component of the immune system. The ideal treatment for autoimmune disorders would specifically target autoimmunogenic B cells while leaving the healthy cells unscathed;however, identifying these cells is extremely challenging because it requires knowledge of the autoimmunogenic BCR sequences and the self- antigens they bind. To address this unmet need, I will develop microfluidic autoimmunoprofiling (MAP), a methodology that will enable the discovery of autoimmunogenic BCRs and the self-antigens they bind. The MAP process will leverage recent developments from my lab in performing PCR reactions on single cells in microfluidic drops, which is a critical step in the workflow that is ued to covalently link the sequence of phage expressing self-peptides to the variable region of the heavy chain of the BCR that binds that self- antigen. Previous attempts at performing PCR on individual mammalian cells in microdroplets failed because mammalian cell lysate is a potent inhibitor of PCR, particularly when contained in picoliter volumes. To overcome inhibition, my lab developed a microfluidic workflow that treats cell lysate using detergents and protease digestion, dilutes it to workable concentrations, and then injects PCR reagent after the proteases are heat-inactivated;these essential steps are all performed while maintaining the compartmentalization of the droplets and keeping the RNA and genomes of individual cells segregated from one another. Moreover, as we have shown, this methodology is ultrahigh-throughput, allowing millions of cells to be subjected to single cell droplet PCR. The ultrahigh-throughput is critical for MAP because it is the enabling feature that will allow us to screen the entire self-antigen peptide/BCR space of binding interactions and capture all interactions. With MAP, we will be able to analyze an autoimmune patient's repertoire to uncover all self-antigens recognized by antibodies in the repertoire, and the specific antibodies that are responsible for this recognition. In addition, using PCR-activated cell sorting, another technology developed by my lab, we will be able purify the autoimmunogenic B cells out of the repertoire to subject them to individual transcriptome analysis. This may ultimately allow us to identify biomarkers unique to this disease-causing cell population and, potentially, identify new ways to specifically inhibit them, thereby treating the disease with fewer side effects. This project should therefore broadly impact our ability to understand the fundamental biology of autoimmunity while also enabling new diagnostics and targeted, personalized therapies.

Public Health Relevance

Autoreactive B cells play a central role in autoimmune disorders, but there is no effective way to detect and recover these cells for isolated analysis. Using a new microfluidic autoimmunoprofiling method, we will detect these cells in patient blood and recover them isolated analysis. By studying these cells in isolation we will be able to identif differences in the biology of these and healthy cells and potentially discover new mechanisms leading to the breakdown of immunological tolerance. This will enable a deeper understanding autoimmunity and may pave the way for new diagnostics and personalized autoimmune therapies.

National Institute of Health (NIH)
National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS)
NIH Director’s New Innovator Awards (DP2)
Project #
Application #
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Wang, Yan Z
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of California San Francisco
Schools of Pharmacy
San Francisco
United States
Zip Code
Sidore, Angus M; Lan, Freeman; Lim, Shaun W et al. (2016) Enhanced sequencing coverage with digital droplet multiple displacement amplification. Nucleic Acids Res 44:e66
Cole, Russell H; Gartner, Zev J; Abate, Adam R (2016) Multicolor Fluorescence Detection for Droplet Microfluidics Using Optical Fibers. J Vis Exp :
Lan, Freeman; Haliburton, John R; Yuan, Aaron et al. (2016) Droplet barcoding for massively parallel single-molecule deep sequencing. Nat Commun 7:11784
Lance, Shea T; Sukovich, David J; Stedman, Kenneth M et al. (2016) Peering below the diffraction limit: robust and specific sorting of viruses with flow cytometry. Virol J 13:201
de Lange, N; Tran, T M; Abate, A R (2016) Electrical lysis of cells for detergent-free droplet assays. Biomicrofluidics 10:024114
Cole, Russell H; Tran, Tuan M; Abate, Adam R (2015) Double Emulsion Generation Using a Polydimethylsiloxane (PDMS) Co-axial Flow Focus Device. J Vis Exp :e53516
Romero, Philip A; Tran, Tuan M; Abate, Adam R (2015) Dissecting enzyme function with microfluidic-based deep mutational scanning. Proc Natl Acad Sci U S A 112:7159-64
Kim, Samuel C; Sukovich, David J; Abate, Adam R (2015) Patterning microfluidic device wettability with spatially-controlled plasma oxidation. Lab Chip 15:3163-9
Cole, Russell H; de Lange, Niek; Gartner, Zev J et al. (2015) Compact and modular multicolour fluorescence detector for droplet microfluidics. Lab Chip 15:2754-8
Sciambi, Adam; Abate, Adam R (2015) Accurate microfluidic sorting of droplets at 30 kHz. Lab Chip 15:47-51

Showing the most recent 10 out of 11 publications