Insights into T Cell Recognition of Antigen: Significance of Two-Dimensional Kinetic Parameters

The T cell receptor (TCR) interacts with peptide-major histocompatibility complex (pMHC) to enable T cell development and trigger adaptive immune responses. For this reason, TCR:pMHC interactions have been intensely studied for over two decades. However, the details of how various binding parameters impact T cell activation remain elusive. Most measurements were made using recombinant proteins by surface plasmon resonance, a three-dimensional (3D) technique in which fluid-phase receptors and ligands are removed from their cellular environment. This approach found TCR:pMHC interactions with relatively low affinities and slow off-rates for agonist peptides. Newer generation techniques have analyzed TCR:pMHC interactions in two dimensions (2D), with both proteins anchored in apposing plasma membranes. These approaches reveal in situ TCR:pMHC interaction kinetics that are of high affinity and exhibit rapid on- and off-rates upon interaction with agonist ligands. Importantly, 2D binding parameters correlate better with T cell functional responses to a spectrum of ligands than 3D measures

When does humoral memory enhance infection?

Antibodies and humoral memory are key components of the adaptive immune system. We consider and computationally model mechanisms by which humoral memory present at baseline might instead increase infection load; we refer to this effect as EI-HM (enhancement of infection by humoral memory). We first consider antibody dependent enhancement (ADE) in which antibody enhances the growth of the pathogen, typically a virus, and typically at intermediate "Goldilocks" levels of antibody. Our ADE model reproduces ADE in vitro and enhancement of infection in vivo from passive antibody transfer. But notably the simplest implementation of our ADE model never results in EI-HM. Adding complexity, by making the cross-reactive antibody much less neutralizing than the de novo generated antibody or by including a sufficiently strong non-antibody immune response, allows for ADE-mediated EI-HM. We next consider the possibility that cross-reactive memory causes EI-HM by crowding out a possibly superior de novo immune response. We show that, even without ADE, EI-HM can occur when the cross-reactive response is both less potent and "directly" (i.e. independently of infection load) suppressive with regard to the de novo response. In this case adding a non-antibody immune response to our computational model greatly reduces or completely eliminates EI-HM, which suggests that "crowding out" is unlikely to cause substantial EI-HM. Hence, our results provide examples in which simple models give qualitatively opposite results compared to models with plausible complexity. Our results may be helpful in interpreting and reconciling disparate experimental findings, especially from dengue, and for vaccination

Ligand-engaged TCR is triggered by Lck not associated with CD8 coreceptor

Producción CientíficaThe earliest molecular events in T-cell recognition have not yet been fully described, and the initial T-cell receptor (TCR)-triggering mechanism remains a subject of controversy. Here, using total internal reflection/Forster resonance energy transfer microscopy, we observe a two-stage interaction between TCR, CD8 and major histocompatibility complex (MHC)-peptide. There is an early (within seconds) interaction between CD3ζ and the coreceptor CD8 that is independent of the binding of CD8 to MHC, but that requires CD8 association with Lck. Later (several minutes) CD3ζ–CD8 interactions require CD8–MHC binding. Lck can be found free or bound to the coreceptor. This work indicates that the initial TCR-triggering event is induced by free Lck. The early signalling events that trigger initial T-cell receptor signalling are not clearly defined. Here the authors show that this occurs in two stages, the first between the CD8 coreceptor and CD3 requiring Lck association to CD8, while the second interaction requires binding of major histocompatibility molecules

Modelling cross-reactivity and memory in the cellular adaptive immune response to influenza infection in the host

The cellular adaptive immune response plays a key role in resolving influenza infection. Experiments where individuals are successively infected with different strains within a short timeframe provide insight into the underlying viral dynamics and the role of a cross-reactive immune response in resolving an acute infection. We construct a mathematical model of within-host influenza viral dynamics including three possible factors which determine the strength of the cross-reactive cellular adaptive immune response: the initial naive T cell number, the avidity of the interaction between T cells and the epitopes presented by infected cells, and the epitope abundance per infected cell. Our model explains the experimentally observed shortening of a second infection when cross-reactivity is present, and shows that memory in the cellular adaptive immune response is necessary to protect against a second infection.Comment: 35 pages, 12 figure

Functional heterogeneity in CD4+ T cell responses against a bacterial pathogen

To investigate how CD4+ T cells function against a bacterial pathogen, we generated a Listeria monocytogenes-specific CD4+ T cell model. In this system, two TCRtg mouse lines, LLO56 and LLO118 recognize the same immunodominant epitope (LLO190-205) of Listeria monocytogenes and have identical in vitro responses. However, in vivo LLO56 and LLO118 display vastly different responses during both primary and secondary infection. LLO118 dominates in the primary response and in providing CD8 T cell help. LLO56 predominates in the secondary response. We have also shown that both specific (TCR-mediated) and nonspecific stimuli (bypassing the TCR) elicit distinct responses from the two transgenics, leading us to conclude that the strength of self-pMHC signaling during development tightly dictates the cell’s future response in the periphery. Herein, we review our findings in this transfer system, focusing on the contribution of the immunomodulatory molecule CD5 and the importance of self-interaction in peripheral maintenance of the cell. We also discuss the manner in which individual TCR affinities to foreign and self-pMHC contribute to the outcome of an immune response; our assertion is that there exists a spectrum of possible T cell responses to recognition of cognate antigen during infection, adding immense diversity to the immune system’s response to pathogens

A unifying mathematical framework for experimental TCR-pMHC kinetic constants

Receptor binding and triggering are central in Immunology as T cells activated through their T cell receptors (TCR) by protein antigens orchestrate immune responses. In order to understand receptor-ligand interactions, many groups working with different experimental techniques and assays have generated a vast body of knowledge during the last decades. However, in recent years a type of assays, referred to as two-dimensional or membrane-to-membrane, has questioned our current understanding of the role of different kinetic constants (for instance, on- versus off-rate constants) on TCR-ligand interaction and subsequent T cell activation. Here we present a general mathematical framework that provides a unifying umbrella to relate fundamental and effective (or experimentally determined) kinetic constants, as well as describe and compare state-of-the-art experimental methods. Our framework is able to predict the correlations between functional output, such as 1/EC50, and effective kinetic constants for a range of different experimental assays (in two and three dimensions). Furthermore, our approach can be applied beyond Immunology, and serve as a “translation method” for the biochemical characterization of receptor-ligand interactions

Some deterministic and stochastic mathematical models of naive T-cell homeostasis

Humans live for decades, whereas mice live for months. Over these long timescales, naïve T cells die or divide infrequently enough that it makes sense to approximate death and division as instantaneous events. The population of T cells in the body is naturally divided into clonotypes; a clonotype is the set of cells that have identical T‐cell receptors. While total numbers of cells, such as naïve CD4+ T cells, are large enough that ordinary differential equations are an appropriate starting point for mathematical models, the numbers of cells per clonotype are not. Here, we review a number of basic mathematical models of the maintenance of clonal diversity. As well as deterministic models, we discuss stochastic models that explicitly track the integer number of naïve T cells in many competing clonotypes over the lifetime of a mouse or human, including the effect of waning thymic production. Experimental evaluation of clonal diversity by bulk high‐throughput sequencing has many difficulties, but the use of single‐cell sequencing is restricted to numbers of cells many orders of magnitude smaller than the total number of T cells in the body. Mathematical questions associated with extrapolating from small samples are therefore key to advances in understanding the diversity of the repertoire of T cells. We conclude with some mathematical models on how to advance in this area

Intermediate levels of vaccination coverage may minimize seasonal influenza outbreaks

For most pathogens, vaccination reduces the spread of the infection and total number of cases; thus, public policy usually advocates maximizing vaccination coverage. We use simple mathematical models to explore how this may be different for pathogens, such as influenza, which exhibit strain variation. Our models predict that the total number of seasonal influenza infections is minimized at an intermediate (rather than maximal) level of vaccination, and, somewhat counter-intuitively, further increasing the level of the vaccination coverage may lead to higher number of influenza infections and be detrimental to the public interest. This arises due to the combined effects of: competition between multiple co-circulating strains; limited breadth of protection afforded by the vaccine; and short-term strain-transcending immunity following natural infection. The study highlights the need for better quantification of the components of vaccine efficacy and longevity of strain-transcending cross-immunity in order to generate nuanced recommendations for influenza vaccine coverage levels. © 2018 Zarnitsyna et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Competing Heterogeneities in Vaccine Effectiveness Estimation

Understanding waning of vaccine-induced protection is important for both immunology and public health. Population heterogeneities in underlying (pre-vaccination) susceptibility and vaccine response can cause measured vaccine effectiveness (mVE) to change over time even in the absence of pathogen evolution and any actual waning of immune responses. We use a multi-scale agent-based models parameterized using epidemiological and immunological data, to investigate the effect of these heterogeneities on mVE as measured by the hazard ratio. Based on our previous work, we consider waning of antibodies according to a power law and link it to protection in two ways: 1) motivated by correlates of risk data and 2) using a within-host model of stochastic viral extinction. The effect of the heterogeneities is given by concise and understandable formulas, one of which is essentially a generalization of Fisher's fundamental theorem of natural selection to include higher derivatives. Heterogeneity in underlying susceptibility accelerates apparent waning, whereas heterogeneity in vaccine response slows down apparent waning. Our models suggest that heterogeneity in underlying susceptibility is likely to dominate. However, heterogeneity in vaccine response offsets 100% (median of 29%) of this effect in our simulations. Our methodology and results may be helpful in understanding competing heterogeneities and waning of immunity and vaccine-induced protection. Our study suggests heterogeneity is more likely to 'bias' mVE downwards towards faster waning of immunity but a subtle bias in the opposite direction is also plausible