Development of multi-modal single-cell technology to dissect epitope specificity to HIV

开发多模式单细胞技术来剖析 HIV 表位特异性

• 批准号: 10632020
• 负责人: Steven Edward Bosinger
• 金额: $ 127.53万
• 依托单位: EMORY UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-06-26 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10632020
• 关键词: Acceleration; Address; Algorithms; Antibodies; Antigens; B-Lymphocytes; Bar Codes; Benchmarking; Bioinformatics; Biological Assay; Cells; Clinical Research; Communities; DNA; Data; Development; Dissection; Epigenetic Process; Epitopes; Funding; Gene Expression; Genetic Transcription; Genomics; Genotype; Goals; Grant; HIV; HIV Envelope Protein gp120; HIV Infections; HIV vaccine; Immune response; Immune system; Immunity; Immunoglobulin Genes; Immunology; Individual; Measures; Mediating; Membrane Proteins; Methodology; Methods; Modality; Modernization; Molecular Structure; Oligonucleotides; Patients; Productivity; Reagent; Research; Resolution; Series; Specificity; Structure; Surface; System; T cell response; T-Cell Immunologic Specificity; T-Lymphocyte; Technology; Vaccinee; Vaccines; Validation; Viral; Viral Genome; Virus; Work; antigen-specific T cells; immune function; in vivo; monomer; multimodality; neutralizing antibody; new technology; novel; protein expression; receptor; response; single cell technology; single-cell RNA sequencing; technology development; tool; transcriptome; transcriptomic profiling; transcriptomics; vaccine platform

ABSTRACT/SUMMARY: Single-cell genomic technology is transforming modern immunology. Single-cell transcriptomic profiling combined with DNA bar-coding technology is capable of acquiring information on multiple modalities simultaneously; surface receptor quantitation, paired clonotype identity, and genotype can now be measured alongside the transcriptome in relatively routine technology. Extending this rapid technological development in single-cell genomics, it is now possible to probe epitope- specificity of individual antigen-specific cells in a high-throughput fashion. The goal of this proposal is to apply DNA bar-coding technology to build reagents capable of assessing B and T cell specificity to HIV epitopes alongside other single-cell cell readouts, and in a high throughput manner. The development of technology capable of rapid resolution of epitope specific responses would address several needs in HIV research: (i) it would greatly accelerate the discovery of novel broadly neutralizing antibodies against HIV; (ii) it would allow comprehensively profiling of T cell HIV epitopes, allowing more rapid identification of epitopes associated with protective immunity; (iii) it would characterize transcriptional states of HIV-infected cells and accurately assess differences between productively-infected, latently-infected and uninfected bystander cells. In the incumbent grant (i.e. prior funding period), we developed novel methodology to obtain paired clonotype identity and transcriptome data in antigen-specific B cells, including development, validation and benchmarking of a novel bioinformatics algorithm capable of accurately reconstructing paired immunoglobulin gene sequences in vaccine-elicited B cells. Here, we extend our prior work to incorporate additional information: antigen specificity for HIV epitopes. We will use DNA bar-coding technology to develop reagents capable of resolving epitope- specificity of HIV-specific B and T cells in a high throughput fashion. Specifically, we will apply DNA-bar codes to native HIV trimers and gp120 monomers to accelerate identification of B cells producing neutralizing antibodies. We will also develop DNA bar-coded tetramer-based technology to massively profile HIV-specific T cell responses epitope resolution. Lastly, we will build on our ability to simultaneous quantify viral genomes and host cell transcriptome data in single cells and develop methodology to differentiate the transcriptomes from latently-infected, productively-infected, and uninfected bystander cells in HIV infection. These technologies would be broadly applicable to HIV research and would provide high throughput means to identify correlates of protection in several advanced HIV vaccine platforms.

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