Program in Systems Immunology and Infectious Disease Modeling (PSIIM)

Lead, Molecular and Cell Biology Group
Tenure-Track Investigator

Molecular and Cell Biology Group
Dr. Fraser received his Ph.D. from Imperial College, London, and after postdoctoral research with John Scott at the Vollum Institute, Portland, he joined the Alliance for Cellular Signaling research consortium, co-directing the molecular biology group with Mel Simon at the California Institute of Technology. He joined the Program in Systems Immunology and Infectious Disease Modeling (PSIIM) in August 2008. 

His research has focused on the mechanistic basis of cellular signaling, both in G protein signaling networks and more recently in Toll-like receptor signaling in innate immune cells. He is interested in the application of systems biology approaches to decipher how mammalian cells integrate stimuli in a complex environment to ensure context-dependent cellular responses. This is vital to understanding how a breakdown in information processing through cell-surface receptors and their linked signal transduction pathways leads to human disease. Dr. Fraser has developed sophisticated approaches for RNAi-based perturbation analysis of immune cell signaling, as well as cloning platforms and plasmid repositories for high-throughput imaging and cell biological applications. 

Description of Research Program

The PSIIM Molecular and Cell Biology Group is focused on the design, implementation, and interpretation of screening efforts to identify and determine the interactions among the components in immune cell signaling networks. In addition to identifying mechanisms that control the response of immune cells to pathogenic stimuli, we seek to use multiple complementary datasets to define the control principles used by the cell to integrate complex signals and to model this cellular response using software developed by the PSIIM Computational Biology Team.

Recent studies of how macrophages respond to combinations of stimuli suggest that signaling networks are not irreducibly complex and that there is an infrastructure in place that dictates the frequency of signaling pathway interaction. However, cellular responses are not predictable from knowledge of single stimulus response profiles, and there remains a pressing need in the biomedical research community to adopt more quantitative computational approaches to gain insight into complex datasets. 

High-content screening assay: Nuclear accumulation of NFkB (RelA) in macrophage cells treated with LPS. Credit: NIAID

We seek to determine the sensitivity characteristics of hematopoietic signaling networks by perturbation screens and to use state-of-the-art technologies to generate datasets for the development of quantitative, predictive models.

Ongoing projects in the lab include the following:

• Genome-wide RNAi and chemical screens to characterize signaling network topology in hematopoietic cells
• Development of high-content, kinetic, and endpoint cell-based assays for screening applications
• Development of spectrally distinct fluorescent biosensors for multiplexing high-content readouts
• Broad use of RNAi applications for conditional, multi-gene target knockdown and generation of kinetic data for dynamic modeling of signaling events
• Quantitative profiling of signaling protein expression and stimulus-induced post-translational modification 

Postdoctoral Opportunities

To inquire about current openings in the lab, e-mail fraseri@niaid.nih.gov.

Selected Publications

(View list in PubMed.)

Fraser ID, Germain RN. Navigating the network: signaling cross-talk in hematopoietic cells. Nat Immunol. 2009 Apr;10(4):327-31.

Wall EA, Zavzavadjian JR, Chang MS, Randhawa B, Zhu X, Hsueh RC, Liu J, Driver A, Bao XR, Sternweis PC, Simon MI, Fraser IDC. Suppression of LPS-induced TNF-alpha production in macrophages by cAMP is mediated by PKA-AKAP95-p105. Sci Signal. 2009 Jun 16;2(75):ra28.

Hsueh RC, Natarajan M, Fraser I, Pond B, Liu J, Mumby S, Han H, Jiang LI, Simon MI, Taussig R, Sternweis PC. Deciphering signaling outcomes from a system of complex networks. Sci Signal. 2009 May 19;2(71):ra22.

Shin KJ, Wall EA, Zavzavadjian JR, Santat LA, Liu J, Hwang JI, Rebres R, Roach T, Seaman W, Simon MI, Fraser ID. A single lentiviral vector platform for microRNA-based conditional RNA interference and coordinated transgene expression. Proc Natl Acad Sci U S A. 2006 Sep 12;103(37):13759-64.

Zhu X, Santat LA, Chang M, Liu J, Zavzavadjian JR, Wall EA, Kivork C, Simon MI, Fraser ID. A versatile approach to multiple gene RNA interference using microRNA-based short hairpin RNAs. BMC Mol Biol. 2007 Oct 30;8:98.

Zavzavadjian JR, Couture S, Park WS, Whalen J, Lyon S, Lee G, Fung E, Mi Q, Liu J, Wall E, Santat L, Dhandapani K, Kivork C, Driver A, Zhu X, Chang MS, Randhawa B, Gehrig E, Bryan H, Verghese M, Maer A, Saunders B, Ning Y, Subramaniam S, Meyer T, Simon MI, O'Rourke N, Chandy G, Fraser ID. The alliance for cellular signaling plasmid collection: a flexible resource for protein localization studies and signaling pathway analysis. Mol Cell Proteomics. 2007 Mar;6(3):413-24.

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