The Case for Absolute Ligand Discrimination: Modeling Information Processing and Decision by Immune T Cells

Some cells have to take decision based on the quality of surroundings ligands, almost irrespective of their quantity, a problem we name “absolute discrimination”. An example of absolute discrimination is recognition of not-self by immune T Cells. We show how the problem of absolute discrimination can be solved by a process called “adaptive sorting”. We review several implementations of adaptive sorting, as well as its generic properties such as antagonism. We show how kinetic proofreading with negative feedback implement an approximate version of adaptive sorting in the immune context. Finally, we revisit the decision problem at the cell population level, showing how phenotypic variability and feedbacks between population and single cells are crucial for proper decision.

[1]  Grégoire Altan-Bonnet,et al.  T Cells Integrate Local and Global Cues to Discriminate between Structurally Similar Antigens. , 2015, Cell reports.

[2]  A. Khoruts,et al.  Single-cell analysis of signal transduction in CD4 T cells stimulated by antigen in vivo , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[3]  W. Bialek,et al.  Maximum entropy models for antibody diversity , 2009, Proceedings of the National Academy of Sciences.

[4]  P. Allen,et al.  The Study of High-Affinity TCRs Reveals Duality in T Cell Recognition of Antigen: Specificity and Degeneracy1 , 2006, The Journal of Immunology.

[5]  Grégoire Altan-Bonnet,et al.  Cell-to-Cell Variability Analysis Dissects the Plasticity of Signaling of Common γ Chain Cytokines in T Cells , 2013, Science Signaling.

[6]  W. Lim,et al.  Defining Network Topologies that Can Achieve Biochemical Adaptation , 2009, Cell.

[7]  P. Allen,et al.  Fidelity of T cell activation through multistep T cell receptor zeta phosphorylation. , 1998, Science.

[8]  Ofer Feinerman,et al.  Quantitative challenges in understanding ligand discrimination by αβ T cells , 2008 .

[9]  R. Germain,et al.  Variability and Robustness in T Cell Activation from Regulated Heterogeneity in Protein Levels , 2008, Science.

[10]  Jay T. Groves,et al.  Synaptic pattern formation during cellular recognition , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Paul François,et al.  Phenotypic model for early T-cell activation displaying sensitivity, specificity, and antagonism , 2013, Proceedings of the National Academy of Sciences.

[12]  Arup K. Chakraborty,et al.  Fast on-rates allow short dwell time ligands to activate T cells , 2010, Proceedings of the National Academy of Sciences.

[13]  Ilya Nemenman,et al.  Simple biochemical networks allow accurate sensing of multiple ligands with a single receptor , 2017, PLoS Comput. Biol..

[14]  Grégoire Altan-Bonnet,et al.  T cells translate individual, quantal activation into collective, analog cytokine responses via time-integrated feedbacks , 2014, eLife.

[15]  Aleksandra M Walczak,et al.  Information transmission in genetic regulatory networks: a review , 2011, Journal of physics. Condensed matter : an Institute of Physics journal.

[16]  T. McKeithan,et al.  Kinetic proofreading in T-cell receptor signal transduction. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[17]  Paul François,et al.  Phenotypic spandrel: absolute discrimination and ligand antagonism , 2015, bioRxiv.

[18]  W. Bialek,et al.  Probing the Limits to Positional Information , 2007, Cell.

[19]  Bernhard Hemmer,et al.  TCR ligand discrimination is enforced by competing ERK positive and SHP-1 negative feedback pathways , 2003, Nature Immunology.

[20]  Dmitri I. Kotov,et al.  T cell receptor cross-reactivity between similar foreign and self peptides influences naive cell population size and autoimmunity. , 2015, Immunity.

[21]  James R Faeder,et al.  Stochastic effects and bistability in T cell receptor signaling. , 2008, Journal of theoretical biology.

[22]  Michael W. Sneddon,et al.  Single-cell quantification of IL-2 response by effector and regulatory T cells reveals critical plasticity in immune response , 2010, Molecular systems biology.

[23]  Massimo Vergassola,et al.  Bacterial strategies for chemotaxis response , 2010, Proceedings of the National Academy of Sciences.

[24]  N. Shoresh,et al.  Regulation of phenotypic variability by a threshold-based mechanism underlies bacterial persistence , 2010, Proceedings of the National Academy of Sciences.

[25]  Alexis M. Kalergis,et al.  Efficient T cell activation requires an optimal dwell-time of interaction between the TCR and the pMHC complex , 2001, Nature Immunology.

[26]  Cheng Zhu,et al.  Accumulation of Dynamic Catch Bonds between TCR and Agonist Peptide-MHC Triggers T Cell Signaling , 2014, Cell.

[27]  Ronald N Germain,et al.  Modeling T Cell Antigen Discrimination Based on Feedback Control of Digital ERK Responses , 2005, PLoS biology.

[28]  Jayajit Das,et al.  Purely stochastic binary decisions in cell signaling models without underlying deterministic bistabilities , 2007, Proceedings of the National Academy of Sciences.

[29]  Paul François,et al.  Chemodetection in fluctuating environments: Receptor coupling, buffering, and antagonism , 2015, Proceedings of the National Academy of Sciences.

[30]  Jeremy Gunawardena,et al.  Models in biology: ‘accurate descriptions of our pathetic thinking’ , 2014, BMC Biology.

[31]  Massimo Vergassola,et al.  ‘Infotaxis’ as a strategy for searching without gradients , 2007, Nature.

[32]  Daniel Coombs,et al.  Antigen Potency and Maximal Efficacy Reveal a Mechanism of Efficient T Cell Activation , 2011, Science Signaling.

[33]  Simon J Davis,et al.  The kinetic-segregation model: TCR triggering and beyond , 2006, Nature Immunology.

[34]  J. Allard,et al.  Mechanical modulation of receptor-ligand interactions at cell-cell interfaces. , 2012, Biophysical journal.

[35]  J. Ninio.  Kinetic amplification of enzyme discrimination. , 1975, Biochimie.

[36]  S. Mangan,et al.  Structure and function of the feed-forward loop network motif , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[37]  Wendell A. Lim,et al.  Sending Mixed Messages for Cell Population Control , 2014, Cell.

[38]  Ofer Feinerman,et al.  Quantitative challenges in understanding ligand discrimination by alphabeta T cells. , 2008, Molecular immunology.

[39]  H. Berg,et al.  Adaptation kinetics in bacterial chemotaxis , 1983, Journal of bacteriology.

[40]  V. Balasubramanian,et al.  How a well-adapted immune system is organized , 2014, Proceedings of the National Academy of Sciences.

[41]  David J Schwab,et al.  Energetic costs of cellular computation , 2012, Proceedings of the National Academy of Sciences.

[42]  Nir Friedman,et al.  Paradoxical Signaling by a Secreted Molecule Leads to Homeostasis of Cell Levels , 2014, Cell.

[43]  Paul François,et al.  A case study of evolutionary computation of biochemical adaptation , 2008, Physical biology.

[44]  J. Hopfield.  Kinetic proofreading: a new mechanism for reducing errors in biosynthetic processes requiring high specificity. , 1974, Proceedings of the National Academy of Sciences of the United States of America.

[45]  S. Alam,et al.  T-cell receptor binding kinetics in T-cell development and activation , 2001, Expert Reviews in Molecular Medicine.

[46]  Michael B. Elowitz,et al.  Architecture-Dependent Noise Discriminates Functionally Analogous Differentiation Circuits , 2009, Cell.

[47]  Arup K Chakraborty,et al.  Insights into the initiation of TCR signaling , 2014, Nature Immunology.

[48]  K D Wittrup,et al.  In vitro evolution of a T cell receptor with high affinity for peptide/MHC. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[49]  W. Bialek.  Biophysics: Searching for Principles , 2012 .

[50]  Eric D. Siggia,et al.  Decisions on the fly in cellular sensory systems , 2013, Proceedings of the National Academy of Sciences.

[51]  Mark M Davis,et al.  Linking T-cell receptor sequence to functional phenotype at the single-cell level , 2014, Nature Biotechnology.

[52]  S. Leibler,et al.  Bacterial Persistence as a Phenotypic Switch , 2004, Science.

[53]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[54]  Mark M Davis,et al.  A single peptide-major histocompatibility complex ligand triggers digital cytokine secretion in CD4(+) T cells. , 2013, Immunity.

[55]  Alexandre V. Morozov,et al.  Decoding Complex Chemical Mixtures with a Physical Model of a Sensor Array , 2011, PLoS Comput. Biol..

[56]  D. Fremont,et al.  High- and low-potency ligands with similar affinities for the TCR: the importance of kinetics in TCR signaling. , 1998, Immunity.

[57]  Cheng Zhu,et al.  The kinetics of two dimensional TCR and pMHC interactions determine T cell responsiveness , 2010, Nature.

[58]  P. Swain,et al.  Stochastic Gene Expression in a Single Cell , 2002, Science.

[59]  Paul François,et al.  Evolving phenotypic networks in silico. , 2014, Seminars in cell & developmental biology.

[60]  Sean C. Bendall,et al.  Conditional density-based analysis of T cell signaling in single-cell data , 2014, Science.

[61]  Structural basis for molecular discrimination by a 3',3'-cGAMP sensing riboswitch. , 2015, Cell reports.

[62]  H. Metzger,et al.  An unusual mechanism for ligand antagonism. , 1998, Science.

[63]  Paul François,et al.  Principles of adaptive sorting revealed by in silico evolution. , 2013, Physical review letters.

[64]  Francis Corson,et al.  Geometry, epistasis, and developmental patterning , 2012, Proceedings of the National Academy of Sciences.

[65]  S. Leibler,et al.  Phenotypic Diversity, Population Growth, and Information in Fluctuating Environments , 2005, Science.

[66]  J. Vilar,et al.  From molecular noise to behavioural variability in a single bacterium , 2004, Nature.

[67]  C. Janeway,et al.  Cross-antagonism of a T cell clone expressing two distinct T cell receptors. , 1999, Immunity.

[68]  Omer Dushek,et al.  Phenotypic models of T cell activation , 2014, Nature Reviews Immunology.

[69]  Nir Friedman,et al.  Coupled IL-2–Dependent Extracellular Feedbacks Govern Two Distinct Consecutive Phases of CD4 T Cell Activation , 2013, The Journal of Immunology.

[70]  Thierry Mora,et al.  Physical Limit to Concentration Sensing Amid Spurious Ligands. , 2015, Physical review letters.

[71]  Arup K Chakraborty,et al.  Quorum sensing allows T cells to discriminate between self and nonself , 2013, Proceedings of the National Academy of Sciences.