136 research outputs found
Modeling T Cell Antigen Discrimination Based on Feedback Control of Digital ERK Responses
T-lymphocyte activation displays a remarkable combination of speed, sensitivity, and discrimination in response to peptide–major histocompatibility complex (pMHC) ligand engagement of clonally distributed antigen receptors (T cell receptors or TCRs). Even a few foreign pMHCs on the surface of an antigen-presenting cell trigger effective signaling within seconds, whereas 1 × 10(5)–1 × 10(6) self-pMHC ligands that may differ from the foreign stimulus by only a single amino acid fail to elicit this response. No existing model accounts for this nearly absolute distinction between closely related TCR ligands while also preserving the other canonical features of T-cell responses. Here we document the unexpected highly amplified and digital nature of extracellular signal-regulated kinase (ERK) activation in T cells. Based on this observation and evidence that competing positive- and negative-feedback loops contribute to TCR ligand discrimination, we constructed a new mathematical model of proximal TCR-dependent signaling. The model made clear that competition between a digital positive feedback based on ERK activity and an analog negative feedback involving SH2 domain-containing tyrosine phosphatase (SHP-1) was critical for defining a sharp ligand-discrimination threshold while preserving a rapid and sensitive response. Several nontrivial predictions of this model, including the notion that this threshold is highly sensitive to small changes in SHP-1 expression levels during cellular differentiation, were confirmed by experiment. These results combining computation and experiment reveal that ligand discrimination by T cells is controlled by the dynamics of competing feedback loops that regulate a high-gain digital amplifier, which is itself modulated during differentiation by alterations in the intracellular concentrations of key enzymes. The organization of the signaling network that we model here may be a prototypic solution to the problem of achieving ligand selectivity, low noise, and high sensitivity in biological responses
Mechanistic model of natural killer cell proliferative response to IL-15 receptor stimulation
Natural killer (NK) cells are innate lymphocytes that provide early host defense against intracellular pathogens, such as viruses. Although NK cell development, homeostasis, and proliferation are regulated by IL-15, the influence of IL-15 receptor (IL-15R)-mediated signaling at the cellular level has not been quantitatively characterized. We developed a mathematical model to analyze the kinetic interactions that control the formation and localization of IL-15/IL-15R complexes. Our computational results demonstrated that IL-15/IL-15R complexes on the cell surface were a key determinant of the magnitude of the IL-15 proliferative signal and that IL-15R occupancy functioned as an effective surrogate measure of receptor signaling. Ligand binding and receptor internalization modulated IL-15R occupancy. Our work supports the hypothesis that the total number and duration of IL-15/IL-15R complexes on the cell surface crosses a quantitative threshold prior to the initiation of NK cell division. Furthermore, our model predicted that the upregulation of IL-15Rα on NK cells substantially increased IL-15R complex formation and accelerated the expansion of dividing NK cells with the greatest impact at low IL-15 concentrations. Model predictions of the threshold requirement for NK cell recruitment to the cell cycle and the subsequent exponential proliferation correlated well with experimental data. In summary, our modeling analysis provides quantitative insight into the regulation of NK cell proliferation at the receptor level and provides a framework for the development of IL-15 based immunotherapies to modulate NK cell proliferation
Systems model of T cell receptor proximal signaling reveals emergent ultrasensitivity
Receptor phosphorylation is thought to be tightly regulated because phosphorylated receptors initiate signaling cascades leading to cellular activation. The T cell antigen receptor (TCR) on the surface of T cells is phosphorylated by the kinase Lck and dephosphorylated by the phosphatase CD45 on multiple immunoreceptor tyrosine-based activation motifs (ITAMs). Intriguingly, Lck sequentially phosphorylates ITAMs and ZAP-70, a cytosolic kinase, binds to phosphorylated ITAMs with differential affinities. The purpose of multiple ITAMs, their sequential phosphorylation, and the differential ZAP-70 affinities are unknown. Here, we use a systems model to show that this signaling architecture produces emergent ultrasensitivity resulting in switch-like responses at the scale of individual TCRs. Importantly, this switch-like response is an emergent property, so that removal of multiple ITAMs, sequential phosphorylation, or differential affinities abolishes the switch. We propose that highly regulated TCR phosphorylation is achieved by an emergent switch-like response and use the systems model to design novel chimeric antigen receptors for therapy
Single-molecule experiments in biological physics: methods and applications
I review single-molecule experiments (SME) in biological physics. Recent
technological developments have provided the tools to design and build
scientific instruments of high enough sensitivity and precision to manipulate
and visualize individual molecules and measure microscopic forces. Using SME it
is possible to: manipulate molecules one at a time and measure distributions
describing molecular properties; characterize the kinetics of biomolecular
reactions and; detect molecular intermediates. SME provide the additional
information about thermodynamics and kinetics of biomolecular processes. This
complements information obtained in traditional bulk assays. In SME it is also
possible to measure small energies and detect large Brownian deviations in
biomolecular reactions, thereby offering new methods and systems to scrutinize
the basic foundations of statistical mechanics. This review is written at a
very introductory level emphasizing the importance of SME to scientists
interested in knowing the common playground of ideas and the interdisciplinary
topics accessible by these techniques. The review discusses SME from an
experimental perspective, first exposing the most common experimental
methodologies and later presenting various molecular systems where such
techniques have been applied. I briefly discuss experimental techniques such as
atomic-force microscopy (AFM), laser optical tweezers (LOT), magnetic tweezers
(MT), biomembrane force probe (BFP) and single-molecule fluorescence (SMF). I
then present several applications of SME to the study of nucleic acids (DNA,
RNA and DNA condensation), proteins (protein-protein interactions, protein
folding and molecular motors). Finally, I discuss applications of SME to the
study of the nonequilibrium thermodynamics of small systems and the
experimental verification of fluctuation theorems. I conclude with a discussion
of open questions and future perspectives.Comment: Latex, 60 pages, 12 figures, Topical Review for J. Phys. C (Cond.
Matt
Stacking Interactions in Denaturation of DNA Fragments
A mesoscopic model for heterogeneous DNA denaturation is developed in the
framework of the path integral formalism. The base pair stretchings are treated
as one-dimensional, time dependent paths contributing to the partition
function. The size of the paths ensemble, which measures the degree of
cooperativity of the system, is computed versus temperature consistently with
the model potential physical requirements. It is shown that the ensemble size
strongly varies with the molecule backbone stiffness providing a quantitative
relation between stacking and features of the melting transition. The latter is
an overall smooth crossover which begins from the \emph{adenine-thymine} rich
portions of the fragment. The harmonic stacking coupling shifts, along the
-axis, the occurrence of the multistep denaturation but it does not change
the character of the crossover. The methods to compute the fractions of open
base pairs versus temperature are discussed: by averaging the base pair
displacements over the path ensemble we find that such fractions signal the
multisteps of the transition in good agreement with the indications provided by
the specific heat plots.Comment: European Physical Journal E (2011) in pres
Self-antigen–specific CD8+ T cell precursor frequency determines the quality of the antitumor immune response
A primary goal of cancer immunotherapy is to improve the naturally occurring, but weak, immune response to tumors. Ineffective responses to cancer vaccines may be caused, in part, by low numbers of self-reactive lymphocytes surviving negative selection. Here, we estimated the frequency of CD8+ T cells recognizing a self-antigen to be <0.0001% (∼1 in 1 million CD8+ T cells), which is so low as to preclude a strong immune response in some mice. Supplementing this repertoire with naive antigen-specific cells increased vaccine-elicited tumor immunity and autoimmunity, but a threshold was reached whereby the transfer of increased numbers of antigen-specific cells impaired functional benefit, most likely because of intraclonal competition in the irradiated host. We show that cells primed at precursor frequencies below this competitive threshold proliferate more, acquire polyfunctionality, and eradicate tumors more effectively. This work demonstrates the functional relevance of CD8+ T cell precursor frequency to tumor immunity and autoimmunity. Transferring optimized numbers of naive tumor-specific T cells, followed by in vivo activation, is a new approach that can be applied to human cancer immunotherapy. Further, precursor frequency as an isolated variable can be exploited to augment efficacy of clinical vaccine strategies designed to activate any antigen-specific CD8+ T cells
T cell cytolytic capacity is independent of initial stimulation strength.
How cells respond to myriad stimuli with finite signaling machinery is central to immunology. In naive T cells, the inherent effect of ligand strength on activation pathways and endpoints has remained controversial, confounded by environmental fluctuations and intercellular variability within populations. Here we studied how ligand potency affected the activation of CD8+ T cells in vitro, through the use of genome-wide RNA, multi-dimensional protein and functional measurements in single cells. Our data revealed that strong ligands drove more efficient and uniform activation than did weak ligands, but all activated cells were fully cytolytic. Notably, activation followed the same transcriptional pathways regardless of ligand potency. Thus, stimulation strength did not intrinsically dictate the T cell-activation route or phenotype; instead, it controlled how rapidly and simultaneously the cells initiated activation, allowing limited machinery to elicit wide-ranging responses
Attenuated T Cell Responses to a High-Potency Ligand In Vivo
According to this study, the strongest T cell receptor ligands in vitro do not necessarily induce the strongest T cell responses in vivo, suggesting that vaccine designers may need to reconsider their strategies
Natural Killer Cell Signal Integration Balances Synapse Symmetry and Migration
Imaging immune surveillance by natural killer (NK) cells has revealed that integration of activating and inhibitory signals determines whether or not NK cells stop to kill the target cell or retain a migratory configuration
The Case for Absolute Ligand Discrimination: Modeling Information Processing and Decision by Immune T Cells
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