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.

National Institute of Health (NIH)
National Institute of Allergy and Infectious Diseases (NIAID)
Research Program--Cooperative Agreements (U19)
Project #
Application #
Study Section
Special Emphasis Panel (ZAI1-QV-I)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Scripps Research Institute
La Jolla
United States
Zip Code
Bendall, Sean C; Davis, Kara L; Amir, El-Ad David et al. (2014) Single-cell trajectory detection uncovers progression and regulatory coordination in human B cell development. Cell 157:714-25
Zak, Daniel E; Tam, Vincent C; Aderem, Alan (2014) Systems-level analysis of innate immunity. Annu Rev Immunol 32:547-77
Gaudillière, Brice; Fragiadakis, Gabriela K; Bruggner, Robert V et al. (2014) Clinical recovery from surgery correlates with single-cell immune signatures. Sci Transl Med 6:255ra131
Knijnenburg, Theo A; Ramsey, Stephen A; Berman, Benjamin P et al. (2014) Multiscale representation of genomic signals. Nat Methods 11:689-94
Gold, Elizabeth S; Diercks, Alan H; Podolsky, Irina et al. (2014) 25-Hydroxycholesterol acts as an amplifier of inflammatory signaling. Proc Natl Acad Sci U S A 111:10666-71
Yang, Yong; Kulka, Kathleen; Montelaro, Ronald C et al. (2014) A hydrolase of trehalose dimycolate induces nutrient influx and stress sensitivity to balance intracellular growth of Mycobacterium tuberculosis. Cell Host Microbe 15:153-63
Altin, John A; Daley, Stephen R; Howitt, Jason et al. (2014) Ndfip1 mediates peripheral tolerance to self and exogenous antigen by inducing cell cycle exit in responding CD4+ T cells. Proc Natl Acad Sci U S A 111:2067-74
Zeng, Ming; Hu, Zeping; Shi, Xiaolei et al. (2014) MAVS, cGAS, and endogenous retroviruses in T-independent B cell responses. Science 346:1486-92
Angelo, Michael; Bendall, Sean C; Finck, Rachel et al. (2014) Multiplexed ion beam imaging of human breast tumors. Nat Med 20:436-42
Wang, James Q; Jeelall, Yogesh S; Beutler, Bruce et al. (2014) Consequences of the recurrent MYD88(L265P) somatic mutation for B cell tolerance. J Exp Med 211:413-26

Showing the most recent 10 out of 23 publications