Next generation sequencing platforms have revolutionized modern approaches for understanding a wide variety of biological processes, including immune responses and cancer. However, increasing evidence shows that the diversity of the cells involved in these processes has important implications for understanding biologic outcomes. For instance, the diversity of T cell receptors on lymphocytes during responses to virus or cancer can have dramatic effects on disease outcome. Conversely, the diversity of cancer cells has important implications for successful control of disease. Therefore, a critical hurdle in these situations is the ability to provide single-cell analysis techniques coupled with high-throughput next generation sequencing, to adequately measure the diversity of cells. Unfortunately, current single-cell analysis approaches are either unfeasible for large cell populations, too expensive, and/or require specialized equipment that is not available to most labs while bulk sequencing approaches provide no information on individual cells. To address this problem, we have engineered DNA origami nanostructures that are able to specifically bind and protect two different mRNA within transfected cells, and used DNA origami-specific matching barcodes upstream of capture sequences to generate to identify in HT-NGS output sequences which sequences came from the same nanostructure and therefore from the same transfected cell. In this proposal we develop this approach for quantitating the diversity of clonally-distributed TCR? and TCR? T cell receptors in human T lymphocyte populations and directly compare the throughput, efficiency, cost and error rates to both conventional bulk- sequencing and single-cell sequencing approaches. We have previously developed this approach for analysis of mouse TCR pairs from primary T cells, and expect little difficulty in adapting this modular platform to human T cells. This technology will be useful for downstream application to a wide variety of biologic processes, by relatively simple modifications to the DNA origami nanostructure probe sequences, including single-cell analysis of other diverse lymphocyte populations, including other T cell subsets or antibody producing B cells, as well as single cells analysis of heterogeneous tumors or diverse microbial communities. Moreover, because this approach utilizes equipment found in most modern molecular biology laboratories, it could be easily adopted by many researchers for these analyses.
Project Terms: Academic Medical Centers; Address; Adopted; Antibodies; Arizona; B-Lymphocytes; Binding; Biological Process; Biological Sciences; Biotechnology; cancer cell; cancer therapy; Cells; Chromium; Clone Cells; Collaborations; Consensus; cost; Cost efficiency; Coupled; Data; design; Detection; Diagnosis; Disease Outcome; disorder control; DNA; DNA analysis; DNA sequencing; droplet sequencing; Engineering; Environment; Equipment; Evaluation; Evolution; experimental study; Genes; genomic platform; genomic tools; Genomics; Goals; Gold; Heterogeneity; High-Throughput Nucleotide Sequencing; Human; Immune; Immune response; Immune system; Immunooncology; improved; Individual; Laboratories; large scale production; Lymphocyte; Malignant Neoplasms; Measurement; Measures; Messenger RNA; Methods; microbial community; Microfluidics; Modernization; Modification; Molecular Biology; Mus; Mutation; nanoprobe; Nanostructures; next generation sequencing; novel strategies; Outcome; outcome forecast; Output; Peripheral Blood Mononuclear Cell; Play; Population; Principal Investigator; Process; Production; programs; receptor; Research Personnel; Resolution; response; RNA; Role; Running; Sampling; sequencing platform; single cell analysis; single cell sequencing; single-cell RNA sequencing; Split-Pool Ligation Transcriptome sequencing; System; T-cell diversity; T-Cell Receptor; T-Cell Receptor Genes; T-Lymphocyte; T-Lymphocyte Subsets; Techniques; Technology; Testing; tool; transcriptome sequencing; Tube; tumor; Universities; Virus;
