New technologies such as mass cytometry have greatly expanded our ability to deepen our understanding of the complexity of lymphocytes and related populations. The Stanford CCHI group has been particularly attuned to the potential in following the lead of the Nolan lab in exploiting this technology, with ground-breaking studies of T cells, NK cells, and cancer immunology. But a clear need has been for high dimensional methods to interrogate tissue sections in a wide variety of circumstances. This inspired several complementary efforts by Dr. Nolan and his group, specifically MIBI, which uses metal labeled antibodies in a high-resolution format, and CODEX (CODetection by inDEXing), a multi- parameter fluorescence-based imaging technology adaptable to most standard three-color fluorescence microscopes, and currently capable of sensitively and quantitatively measuring more than 60 markers in a single tissue. CODEX extends the deep phenotyping capabilities of multi-parameter flow cytometry while enabling the associated spatial context of a multitude of cell types, including rare cell types implicated in disease mechanisms. To achieve this high-parameter capability, antibodies against target epitopes are each tagged with unique DNA oligonucleotides and iterative cycles of imaging and removal of corresponding tags is performed to collect single cell proteomic measurements across all parameters. We will deploy CODEX for deep phenotyping of the 2D and 3D architecture of tonsil organoids. Recognizing a growing international biomedical and pharmaceutical interest in imaging applications to immunology, vaccine and drug development, this Technology Development Project will extend the current features of CODEX to deep phenotypic profiling of tonsil tissue architecture before and after exposure to influenza vaccine. Specifically, the Davis lab has developed a unique tonsil organoid system that can be exposed to a flu vaccine with subsequent production of high affinity antibodies several days to a week later. The versatility of this organoid system provides an unprecedented opportunity to modify and test influenza vaccine constructs and adjuvants in a fully human system and determine how best to trigger production of broadly neutralizing influenza antibodies, a goal toward generating a universal vaccine. We will extract feature data with this unprecedentedly deep data for the understanding of wholesale and minor tissue alterations that occur in response to influenza vaccine challenge?enabling a first ever map of ?tissue-omics? at the single cell level for the influenza vaccine response. We will also take advantage of the various manipulations that will be employed in Project 1 on this organoid system in order to gauge their effects on the organization of these cells and use this to formulate hypotheses regarding the significance of particular cellular groupings that we see in tonsils, which we refer to as ?neighborhoods?.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
2U19AI057229-16
Application #
9674976
Study Section
Special Emphasis Panel (ZAI1)
Project Start
Project End
Budget Start
2019-04-01
Budget End
2020-03-31
Support Year
16
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Stanford University
Department
Type
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304
Vallania, Francesco; Tam, Andrew; Lofgren, Shane et al. (2018) Leveraging heterogeneity across multiple datasets increases cell-mixture deconvolution accuracy and reduces biological and technical biases. Nat Commun 9:4735
Bongen, Erika; Vallania, Francesco; Utz, Paul J et al. (2018) KLRD1-expressing natural killer cells predict influenza susceptibility. Genome Med 10:45
Sweeney, Timothy E; Azad, Tej D; Donato, Michele et al. (2018) Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters. Crit Care Med 46:915-925
Lin, Dongxia; Maecker, Holden T (2018) Mass Cytometry Assays for Antigen-Specific T Cells Using CyTOF. Methods Mol Biol 1678:37-47
Goltsev, Yury; Samusik, Nikolay; Kennedy-Darling, Julia et al. (2018) Deep Profiling of Mouse Splenic Architecture with CODEX Multiplexed Imaging. Cell 174:968-981.e15
Gee, Marvin H; Sibener, Leah V; Birnbaum, Michael E et al. (2018) Stress-testing the relationship between T cell receptor/peptide-MHC affinity and cross-reactivity using peptide velcro. Proc Natl Acad Sci U S A 115:E7369-E7378
Cheung, Peggie; Vallania, Francesco; Warsinske, Hayley C et al. (2018) Single-Cell Chromatin Modification Profiling Reveals Increased Epigenetic Variations with Aging. Cell 173:1385-1397.e14
Mamedov, Murad R; Scholzen, Anja; Nair, Ramesh V et al. (2018) A Macrophage Colony-Stimulating-Factor-Producing ?? T Cell Subset Prevents Malarial Parasitemic Recurrence. Immunity 48:350-363.e7
Kooreman, Nigel G; Kim, Youngkyun; de Almeida, Patricia E et al. (2018) Autologous iPSC-Based Vaccines Elicit Anti-tumor Responses In Vivo. Cell Stem Cell 22:501-513.e7
Haynes, Winston A; Tomczak, Aurelie; Khatri, Purvesh (2018) Gene annotation bias impedes biomedical research. Sci Rep 8:1362

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