Our long-term goal is to probe theoretically and experimentally how reliable immune responses emerge at the system level from the unreliable responses of individual T cells. Our first project aims at probing how heterogeneity in the expression levels of key signaling proteins generates phenotypic variability in T cells'responsiveness to ligands. We will also probe how such stochasticity of signaling responses translates into functional phenotypic variability.
Our second aim tests how multiplexed signals (e.g. T cell ligands and IL15 cytokine) can activate signaling crosstalks that modulate the levels and/or activity of key signaling proteins and make T cells hyperresponsive to self-derived ligands.
Our third aim probes how cytokine regulation integrates cell variability in antigen response at the individual cell level towards a regulated collective response. This project focuses on Interleukin-2 as a critical cytokine that controls quorum sensing among effector T cells and suppression by regulatory T cells. Our approach is fundamentally interdisciplinary with concomitant computational modeling and experimental testing. It consists in making and validating theoretical predictions to quantify and control how immune responses emerge as dynamically- and collectively-regulated properties of individual T cells.

Public Health Relevance

Our project focuses on developing experimentally-validated computer models of T cell activation. Our goal is to identify how reliable immune responses emerge dynamically from the unreliable activation of individual T cells. The long-term impact of our research is in a better control of immune responses towards immunotherapies for cancer and auto- immune disorders.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI083408-04
Application #
8306678
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Gondre-Lewis, Timothy A
Project Start
2009-08-05
Project End
2013-07-31
Budget Start
2012-08-01
Budget End
2013-07-31
Support Year
4
Fiscal Year
2012
Total Cost
$488,944
Indirect Cost
$231,605
Name
Sloan-Kettering Institute for Cancer Research
Department
Type
DUNS #
064931884
City
New York
State
NY
Country
United States
Zip Code
10065
Malandro, Nicole; Budhu, Sadna; Kuhn, Nicholas F et al. (2016) Clonal Abundance of Tumor-Specific CD4(+) T Cells Potentiates Efficacy and Alters Susceptibility to Exhaustion. Immunity 44:179-93
Chen, Ying-Han; Du, WenLi; Hagemeijer, Marne C et al. (2015) Phosphatidylserine vesicles enable efficient en bloc transmission of enteroviruses. Cell 160:619-30
Voisinne, Guillaume; Nixon, Briana G; Melbinger, Anna et al. (2015) T Cells Integrate Local and Global Cues to Discriminate between Structurally Similar Antigens. Cell Rep 11:1208-19
Prill, Robert J; Vogel, Robert; Cecchi, Guillermo A et al. (2015) Noise-driven causal inference in biomolecular networks. PLoS One 10:e0125777
Tkach, Karen E; Oyler, Jennifer E; Altan-Bonnet, Grégoire (2014) Cracking the NF-κB code. Sci Signal 7:pe5
Tkach, Karen E; Barik, Debashis; Voisinne, Guillaume et al. (2014) T cells translate individual, quantal activation into collective, analog cytokine responses via time-integrated feedbacks. Elife 3:e01944
Cotari, Jesse W; Voisinne, Guillaume; Altan-Bonnet, Grégoire (2013) Diversity training for signal transduction: leveraging cell-to-cell variability to dissect cellular signaling, differentiation and death. Curr Opin Biotechnol 24:760-6
Tkach, Karen; Altan-Bonnet, Gregoire (2013) T cell responses to antigen: hasty proposals resolved through long engagements. Curr Opin Immunol 25:120-5
Francois, Paul; Voisinne, Guillaume; Siggia, Eric D et al. (2013) Phenotypic model for early T-cell activation displaying sensitivity, specificity, and antagonism. Proc Natl Acad Sci U S A 110:E888-97
Cotari, Jesse W; Voisinne, Guillaume; Dar, Orly Even et al. (2013) Cell-to-cell variability analysis dissects the plasticity of signaling of common γ chain cytokines in T cells. Sci Signal 6:ra17

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