The Bioinformatics Core will employ computational approaches to extract biological insights from the high throughput data sets generated in each of the Projects. The overall aim of the Core will be to help the consortium 1) prioritize genes that are likely to be immune regulators, 2) identify in vivo models where a given point mutation is likely to be most relevant, 3) generate hypotheses regarding the molecular mechanisms underlying immune phenotypes that have been identified, 4) manage and analyze high throughput datasets, in conjunction with the Systems Biology and CyTOF Cores, to determine the mechanism by which the mutation affects immune function, and 5) disseminate all data generated in the Projects and Cores via the Systems Immunology and Mutagenetix web sites (in collaboration with the Annotation Core). Using the substantial in-house database of transcriptomic data from immune cells (both wild-type and various signaling pathway mutants) stimulated with various PAMPs and intact pathogens, the Core has already identified a compendium of candidate regulatory molecules whose function in regulating the immune response is not known. As ENU-induced mutations in these genes are identified, this list of candidates will guide the work in all of the Projects, either by A) allowing enrichment of the pedigree for mutations of interest in order to increase the efficiency of screening (Project 1 and 2), or B) immediately breeding to homozygosity mutations of high interest for more detailed analysis (Project 3). This set of candidates will be continuously refined as the program progresses and more data become available. In addition, the Core will conduct systems-level analysis of the transcriptomic, proteomic, and Cy-TOF data generated in the Systems Biology and CyTOF Cores, to support mechanistic studies of mutations that induce an immune phenotype. The Core will integrate these datasets with networks representing known biological pathways or molecular interactions to predict pathways that are likely to be dysregulated in the mutant immune cells.

Public Health Relevance

The computational analyses undertaken in this Core will suggest hypotheses for how immune cells defend the body against infection. These hypotheses will be tested in the laboratory, extending our understanding of the immune system, and identifying molecules that could be targeted to increase the efficacy of vaccines or to treat infectious and inflammatory diseases.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
5U19AI100627-03
Application #
8717573
Study Section
Special Emphasis Panel (ZAI1)
Project Start
Project End
Budget Start
2014-09-01
Budget End
2015-08-31
Support Year
3
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Scripps Research Institute
Department
Type
DUNS #
City
La Jolla
State
CA
Country
United States
Zip Code
Anchang, Benedict; Davis, Kara L; Fienberg, Harris G et al. (2018) DRUG-NEM: Optimizing drug combinations using single-cell perturbation response to account for intratumoral heterogeneity. Proc Natl Acad Sci U S A 115:E4294-E4303
Good, Zinaida; Sarno, Jolanda; Jager, Astraea et al. (2018) Single-cell developmental classification of B cell precursor acute lymphoblastic leukemia at diagnosis reveals predictors of relapse. Nat Med 24:474-483
McAlpine, William; Sun, Lei; Wang, Kuan-Wen et al. (2018) Excessive endosomal TLR signaling causes inflammatory disease in mice with defective SMCR8-WDR41-C9ORF72 complex function. Proc Natl Acad Sci U S A 115:E11523-E11531
Morin, Matthew D; Wang, Ying; Jones, Brian T et al. (2018) Diprovocims: A New and Exceptionally Potent Class of Toll-like Receptor Agonists. J Am Chem Soc 140:14440-14454
Johnson, Jarrod S; Lucas, Sasha Y; Amon, Lynn M et al. (2018) Reshaping of the Dendritic Cell Chromatin Landscape and Interferon Pathways during HIV Infection. Cell Host Microbe 23:366-381.e9
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
Wagle, Mayura V; Marchingo, Julia M; Howitt, Jason et al. (2018) The Ubiquitin Ligase Adaptor NDFIP1 Selectively Enforces a CD8+ T Cell Tolerance Checkpoint to High-Dose Antigen. Cell Rep 24:577-584
Wang, Tao; Bu, Chun Hui; Hildebrand, Sara et al. (2018) Probability of phenotypically detectable protein damage by ENU-induced mutations in the Mutagenetix database. Nat Commun 9:441
O'Gorman, W E; Kong, D S; Balboni, I M et al. (2017) Mass cytometry identifies a distinct monocyte cytokine signature shared by clinically heterogeneous pediatric SLE patients. J Autoimmun :
Choi, Jin Huk; Wang, Kuan-Wen; Zhang, Duanwu et al. (2017) IgD class switching is initiated by microbiota and limited to mucosa-associated lymphoid tissue in mice. Proc Natl Acad Sci U S A 114:E1196-E1204

Showing the most recent 10 out of 121 publications