Bias in the αβ T-cell repertoire: implications for disease pathogenesis and vaccination

The na?ve T-cell repertoire is vast, containing millions of unique T-cell receptor (TCR) structures. Faced with such diversity, the mobilization of TCR structures from this enormous pool was once thought to be a stochastic, even chaotic, process. However, steady and systematic dissection over the last 20 years has revealed that this is not the case. Instead, the TCR repertoire deployed against individual antigens is routinely ordered and biased. Often, identical and near-identical TCR repertoires can be observed across different individuals, suggesting that the system encompasses an element of predictability. This review provides a catalog of αβ TCR bias by disease and by species, and discusses the mechanisms that govern this inherent and widespread phenomenon.     

The Dynamics of T-Cell Receptor Repertoire Diversity Following Thymus Transplantation for DiGeorge Anomaly

T cell populations are regulated both by signals specific to the T-cell receptor (TCR) and by signals and resources, such as cytokines and space, that act independently of TCR specificity. Although it has been demonstrated that disruption of either of these pathways has a profound effect on T-cell development, we do not yet have an understanding of the dynamical interactions of these pathways in their joint shaping of the T cell repertoire. Complete DiGeorge Anomaly is a developmental abnormality that results in the failure of the thymus to develop, absence of T cells, and profound immune deficiency. After receiving thymic tissue grafts, patients suffering from DiGeorge anomaly develop T cells derived from their own precursors but matured in the donor tissue. We followed three DiGeorge patients after thymus transplantation to utilize the remarkable opportunity these subjects provide to elucidate human T-cell developmental regulation. Our goal is the determination of the respective roles of TCR-specific vs. TCR-nonspecific regulatory signals in the growth of these emerging T-cell populations. During the course of the study, we measured peripheral blood T-cell concentrations, TCRβ V gene-segment usage and CDR3-length spectratypes over two years or more for each of the subjects. We find, through statistical analysis based on a novel stochastic population-dynamic T-cell model, that the carrying capacity corresponding to TCR-specific resources is approximately 1000-fold larger than that of TCR-nonspecific resources, implying that the size of the peripheral T-cell pool at steady state is determined almost entirely by TCR-nonspecific mechanisms. Nevertheless, the diversity of the TCR repertoire depends crucially on TCR-specific regulation. The estimated strength of this TCR-specific regulation is sufficient to ensure rapid establishment of TCR repertoire diversity in the early phase of T cell population growth, and to maintain TCR repertoire diversity in the face of substantial clonal expansion-induced perturbation from the steady state.     

Conventional and Regulatory CD4+ T Cells That Share Identical TCRs Are Derived from Common Clones

Results from studies comparing the diversity and specificity of the TCR repertoires expressed by conventional (Tconv) and regulatory (Treg) CD4⁺ T cell have varied depending on the experimental system employed. We developed a new model in which T cells express a single fixed TCRα chain, randomly rearranged endogenous TCRβ chains, and a Foxp3-GFP reporter. We purified CD4⁺Foxp3^- and CD4⁺Foxp3⁺ cells, then performed biased controlled multiplex PCR and high throughput sequencing of endogenous TCRβ chains. We identified >7,000 different TCRβ sequences in the periphery of 5 individual mice. On average, ~12% of TCR sequences were expressed by both conventional and regulatory populations within individual mice. The CD4⁺ T cells that expressed shared TCR sequences were present at higher frequencies compared to T cells expressing non-shared TCRs. Furthermore, nearly all (>90%) of the TCR sequences that were shared within mice were identical at the DNA sequence level, indicating that conventional and regulatory T cells that express shared TCRs are derived from common clones. Analysis of TCR repertoire overlap in the thymus reveals that a large proportion of Tconv and Treg sharing observed in the periphery is due to clonal expansion in the thymus. Together these data show that there are a limited number of TCR sequences shared between Tconv and Tregs. Also, Tconv and Tregs sharing identical TCRs are found at relatively high frequencies and are derived from common progenitors, of which a large portion are generated in the thymus.     

Phosphorylation Site Dynamics of Early T-cell Receptor Signaling

In adaptive immune responses, T-cell receptor (TCR) signaling impacts multiple cellular processes and results in T-cell differentiation, proliferation, and cytokine production. Although individual protein–protein interactions and phosphorylation events have been studied extensively, we lack a systems-level understanding of how these components cooperate to control signaling dynamics, especially during the crucial first seconds of stimulation. Here, we used quantitative proteomics to characterize reshaping of the T-cell phosphoproteome in response to TCR/CD28 co-stimulation, and found that diverse dynamic patterns emerge within seconds. We detected phosphorylation dynamics as early as 5 s and observed widespread regulation of key TCR signaling proteins by 30 s. Development of a computational model pointed to the presence of novel regulatory mechanisms controlling phosphorylation of sites with central roles in TCR signaling. The model was used to generate predictions suggesting unexpected roles for the phosphatase PTPN6 (SHP-1) and shortcut recruitment of the actin regulator WAS. Predictions were validated experimentally. This integration of proteomics and modeling illustrates a novel, generalizable framework for solidifying quantitative understanding of a signaling network and for elucidating missing links.     

Primates as Predictors of Mammal Community Diversity in the Forest Ecosystems of Madagascar

The geographic distribution of species is the typical metric for identifying priority areas for conservation. Since most biodiversity remains poorly studied, a subset of charismatic species, such as primates, often stand as surrogates for total biodiversity. A central question is therefore, how effectively do primates predict the pooled species richness of other mammalian taxa? We used lemurs as indicator species to predict total non-primate mammal community richness in the forest ecosystems of Madagascar. We combine environmental and species occurrence data to ascertain the extent to which primate diversity can predict (1) non-primate mammal α-diversity (species richness), (2) non-primate complementarity, and (3) non-primate β-diversity (species turnover). Our results indicate that primates are effective predictors of non-primate mammal community diversity in the forest ecosystems of Madagascar after controlling for habitat. When individual orders of mammals are considered, lemurs effectively predict the species richness of carnivorans and rodents (but not afrosoricids), complementarity of rodents (but not carnivorans or afrosoricids), and all individual components of β-diversity. We conclude that lemurs effectively predict total non-primate community richness. However, surrogate species alone cannot achieve complete representation of biodiversity.     

T-cell activation decreases miRNA-15a/16 levels to promote MEK1–ERK1/2–Elk1 signaling and proliferative capacity

While miRs have been extensively studied in the context of malignancy and tumor progression, their functions in regulating T-cell activation are less clear. In initial studies, we found reduced levels of miR-15a/16 at 3 to 18 h post–T-cell receptor (TCR) stimulation, suggesting a role for decreased levels of this miR pair in shaping T-cell activation. To further explore this, we developed an inducible miR15a/16 transgenic mouse model to determine how elevating miR-15a/16 levels during early stages of activation would affect T-cell proliferation and to identify TCR signaling pathways regulated by this miR pair. Doxycycline (DOX)-induced expression of miR-15a/16 from 0 to 18 h post-TCR stimulation decreased ex vivo T-cell proliferation as well as in vivo antigen-specific T-cell proliferation. We also combined bioinformatics and proteomics approaches to identify the mitogen-activated protein kinase kinase 1 (MEK1) (Map2k1) as a target of miR-15a/16. MEK1 targeting by miR-15a/16 was confirmed using miR mimics that decreased Map2k1 mRNA containing the 3′-UTR target nucleotide sequence (UGCUGCUA) but did not decrease Map2k1 containing a mutated control sequence (AAAAAAAA). Phosphorylation of downstream signaling molecules, extracellular signal–regulated protein kinase 1/2 (ERK1/2) and Elk1, was also decreased by DOX-induced miR-15a/16 expression. In addition to MEK1, ERK1 was subsequently found to be targeted by miR-15a/16, with DOX-induced miR-15a/16 reducing total ERK1 levels in T cells. These findings show that TCR stimulation reduces miR-15a/16 levels at early stages of T-cell activation to facilitate increased MEK1 and ERK1, which promotes the sustained MEK1–ERK1/2–Elk1 signaling required for optimal proliferation.     

Diversity and evolution of T-cell receptor variable region genes in mammals and birds

 The receptor of a T lymphocyte (TCR) recognizes nonself antigens in the company of major histocompatibility complex (MHC) molecules presented to it by the antigen-presenting cell. The variable region of TCR is encoded by either a concatenation of variable region (TCR-V), diversity region (TCR-D), and joining region (TCR-J) genes, or a concatenation of TCR-V and TCR-J genes. The TCR-V genes exist as a multigene family in vertebrate species. Here we study the evolutionary relationships of TCR-V genes from humans, sheep, cattle, rabbits, mice, and chicken. These six species can be classified into two groups according to the frequency of γδ T-cells in their peripheral T-cell populations. The "γδ low" group of species includes humans and mice, in which γδ T-cells constitute very limited portion of the T-cell population. The "γδ high" group includes sheep, cattle, rabbits, and chicken, in which γδ T-cells comprise up to 60% of the T-cell population. Here, we compiled TCR-V sequences from the six species and conducted a phylogenetic analysis. We identified various TCR-V gene subgroups based on the analysis. We found that humans and mice have representatives from nearly all of the subgroups identified, while other species have lost subgroups to different extent. Therefore, the γδ low species have a high degree of diversity of TCR-V genes, while γδ high species all have limited diversity of TCR-V genes. This pattern is similar to that found for immunoglobulin variable region (IGV) genes. Received: 20 May 1999 / Revised: 13 July 1999     

Structural determinants of T-cell receptor bias in immunity

Antigen-specific T-cell responses induced by infection, transplantation, autoimmunity or hypersensitivity are characterized by cells expressing biased profiles of T-cell receptors (TCRs) that are selected from a diverse, naive repertoire. Here, we review the evidence for these TCR biases, focusing on crystallographic analysis of the structural constraints that determine the binding of a TCR to its ligand and the persistence of certain TCRs in an immune repertoire. We discuss the ways in which diversity in a selected TCR repertoire can contribute to protective immunity and the implications of this for vaccine design and immunotherapy.     

Testing species richness estimation methods using museum label data on the Danish Asilidae

Museum collections are treasure troves of biodiversity information thatcan potentially be used for species richness estimation. Using label data on theDanish Asilidae (Diptera), we test eight species richness estimation techniques(abundance-based coverage estimator (ACE), ICE, Chao1, Chao2, first and secondorder Jackknife, Bootstrap and MMMeans) by comparing the estimates to the numberof species likely to occur in Denmark based on distributional information,expert opinion, and a species–area curve. We are investigating which ofthe estimators are most suited for the task. Furthermore, through theuse of four different subsampling schemes we study which kind of label information isnecessary in order to apply these estimation procedures. The first and secondorder Jackknife estimators yield the most accurate estimate of the number ofcollectable species in Denmark, while ACE, Bootstrap and Chao1 only provideslight improvements over observed values. We find that all estimatorsunderestimate the true diversity of Danish Asilidae and speculate that thisperformance is due to a discrepancy between the total and the collectable faunain the region. Finally, we discuss the implications for species richnessestimation and emphasize that for most terrestrial arthropod taxa thesediscrepancies are of such a magnitude that estimated species richness values maybe dangerously low and of limited use in conservation decision making.     

Cholesterol and Sphingomyelin Drive Ligand-independent T-cell Antigen Receptor Nanoclustering

The T-cell antigen receptor (TCR) exists in monomeric and nanoclustered forms independently of antigen binding. Although the clustering is involved in the regulation of T-cell sensitivity, it is unknown how the TCR nanoclusters form. We show that cholesterol is required for TCR nanoclustering in T cells and that this clustering enhances the avidity but not the affinity of the TCR-antigen interaction. Investigating the mechanism of the nanoclustering, we found that radioactive photocholesterol specifically binds to the TCRβ chain in vivo. In order to reduce the complexity of cellular membranes, we used a synthetic biology approach and reconstituted the TCR in liposomes of defined lipid composition. Both cholesterol and sphingomyelin were required for the formation of TCR dimers in phosphatidylcholine-containing large unilamellar vesicles. Further, the TCR was localized in the liquid disordered phase in giant unilamellar vesicles. We propose a model in which cholesterol and sphingomyelin binding to the TCRβ chain causes TCR dimerization. The lipid-induced TCR nanoclustering enhances the avidity to antigen and thus might be involved in enhanced sensitivity of memory compared with naive T cells. Our work contributes to the understanding of the function of specific nonannular lipid-membrane protein interactions.     

Analysis of peptide/MHC-induced TCR downregulation

The interaction of T0lymphocytes with antigen-presenting cells displaying a small number of specific peptide/major histocompatibility complexes results in the downregulation of a large number of T-cell receptors (TCR), suggesting serial TCR triggering. However, the details of TCR downregulation are controversial. In particular, the level of comodulation of nonengaged TCR reported by different authors ranges from essentially none to considerable levels. Here, we address this controversy using complementary experimental and mathematical techniques. We find that TCR downregulation is very rapid during the first 2–4 min after T-cell antigen-presenting cells contact formation. After this phase, TCR downregulation proceeds at a relatively slow rate. Statistical and computational analyses show that this pronounced change in downregulation kinetics is compatible with the notion of initial serial triggering of clustered TCR followed by serial triggering of individual TCR. We further propose a compatible mechanism for concurrent triggering of multiple TCR by a single peptide/major histocompatibility complex. We provide a unified picture of productive TCR engagement and downregulation in which TCR triggering characteristics evolve from an initial cooperative phase to a sustained phase of signal accumulation.     

Performance of nonparametric species richness estimators in a high diversity plant community

Abstract. The efficiency of four nonparametric species richness estimators — first‐order Jackknife, second‐order Jackknife, Chao2 and Bootstrap — was tested using simulated quadrat sampling of two field data sets (a sandy ‘Dune’ and adjacent ‘Swale’) in high diversity shrublands (kwongan) in south‐western Australia. The data sets each comprised > 100 perennial plant species and > 10 000 individuals, and the explicit (x‐y co‐ordinate) location of every individual. We applied two simulated sampling strategies to these data sets based on sampling quadrats of unit sizes 1/400th and 1/100th of total plot area. For each site and sampling strategy we obtained 250 independent sample curves, of 250 quadrats each, and compared the estimators’ performances by using three indices of bias and precision: MRE (mean relative error), MSRE (mean squared relative error) and OVER (percentage overestimation). The analysis presented here is unique in providing sample estimates derived from a complete, field‐based population census for a high diversity plant community. In general the true reference value was approached faster for a comparable area sampled for the smaller quadrat size and for the swale field data set, which was characterized by smaller plant size and higher plant density. Nevertheless, at least 15–30% of the total area needed to be sampled before reasonable estimates of S_t (total species richness) were obtained. In most field surveys, typically less than 1% of the total study domain is likely to be sampled, and at this sampling intensity underestimation is a problem. Results showed that the second‐order Jackknife approached the actual value of S_t more quickly than the other estimators. All four estimators were better than S_obs (observed number of species). However, the behaviour of the tested estimators was not as good as expected, and even with large sample size (number of quadrats sampled) all of them failed to provide reliable estimates. First‐ and second‐order Jackknives were positively biased whereas Chao2 and Bootstrap were negatively biased. The observed limitations in the estimators’ performance suggests that there is still scope for new tools to be developed by statisticians to assist in the estimation of species richness from sample data, especially in communities with high species richness.     

Temporal Patterns of Species Accumulation in a Survey of Lepidoptera in a Beech-Maple Forest

One of the most significant challenges to insect conservation is lack of information concerning species diversity and distribution. Because a complete inventory of all species in an area is virtually impossible, interest has turned to developing statistical techniques to guide sampling design and to estimate total species richness within a site. We used two such techniques, diversity partitioning and non-parametric richness estimation, to determine how variation in sampling effort over time affected species accumulation for a survey of Lepidoptera in an old-growth beech-maple forest. Temporal scaling of sampling effort had significant effects on two measures of species diversity. Increases in species richness were primarily driven by changes in species occurrences with season, while Shannon diversity was largely determined at the scale of individual sampling units (i.e. by spatial effects). Variation in sampling effort affected the values of the two most widely regarded richness estimators (ICE and Chao 2); neither diversity estimator achieved stable values across a range of sampling efforts. Even after 52 trap-nights and accounting for seasonality, rare species (singletons and uniques) remained a significant component of the moth community. To the extent that moth communities in other forest systems are similarly comprised of many rare species, non-parametric richness estimators should be expected to yield variable estimates with increased effort and should only be used to provide a minimum benchmark for predicting the number of species remaining to be sampled. Our results suggest the best strategy for a short-term survey of forest Lepidoptera should emphasize spreading sampling intervals throughout a given year rather than focusing on intensive sampling during a short time period or prolonged sampling over many years.     

Tumor-infiltrating lymphocytes in colorectal tumors display a diversity of T cell receptor sequences that differ from the T cells in adjacent mucosal tissue

Tumors from colorectal cancer (CRC) are generally immunogenic and commonly infiltrated with T lymphocytes. However, the details of the adaptive immune reaction to these tumors are poorly understood. We have accrued both colon tumor samples and adjacent healthy mucosal samples from 15 CRC patients to study lymphocytes infiltrating these tissues. We apply a method for detailed sequencing of T-cell receptor (TCR) sequences from tumor-infiltrating lymphocytes (TILs) in CRC tumors at high throughput to probe T-cell clones in comparison with the TCRs from adjacent healthy mucosal tissue. In parallel, we captured TIL counts using standard immunohistochemistry. The variation in diversity of the TIL repertoire was far wider than the variation of T-cell clones in the healthy mucosa, and the oligoclonality was higher on average in the tumors. However, the diversity of the T-cell repertoire in both CRC tumors and healthy mucosa was on average 100-fold lower than in peripheral blood. Using the TCR sequences to identify and track clones between mucosal and tumor samples, we determined that the immune response in the tumor is different than in the adjacent mucosal tissue, and the number of shared clones is not dependent on distance between the samples. Together, these data imply that CRC tumors induce a specific adaptive immune response, but that this response differs widely in strength and breadth between patients.     

A possible basis for major histocompatibility complex-restricted T-cell recognition

Four distinct T-cell antigen-receptor gene loci have now been identified and partly characterized: alpha, beta, gamma and delta. All of these loci can rearrange in an immunoglobulin-like fashion and express polypeptides that contribute to either alpha:beta or gamma:delta T-cell receptor-CD3 complexes. Surprisingly, the T-cell receptor (TCR) delta coding regions are located entirely, or almost entirely, within the TCR alpha locus and share at least some of the V region gene segments, thus at least partly linking the two different types of receptor heterodimers. Analysis of potential T-cell receptor diversity, particularly that of the delta chain, indicates a striking concentration of somatic polymorphism in the V-J junctional region of the two heterodimers, four to six orders of magnitude higher than similar calculations for immunoglobulin light- and heavy-chain combinations. In contrast, the number of possible V region combinations in T-cell receptors is one hundredth to one thousandth that of immunoglobulins. TCR alpha: beta heterodimers are known to recognize many possible fragments of antigens embedded in the peptide-binding clefts of a relatively small number of major histocompatibility complex (MHC) molecules. Thus it is attractive to speculate that the V-J junctional portions of both types of T-cell receptor contact peptide antigens, whereas the remaining diversity regions contact the MHC. This contention is supported by molecular modelling studies and has interesting implications for the evolution of antigen-receptor genes.     

How does variation in total and relative abundance contribute to gradients of species diversity?

Patterns of biodiversity provide insights into the processes that shape biological communities around the world. Variation in species diversity along biogeographical or ecological gradients, such as latitude or precipitation, can be attributed to variation in different components of biodiversity: changes in the total abundance (i.e., more‐individual effects) and changes in the regional species abundance distribution (SAD). Rarefaction curves can provide a tool to partition these sources of variation on diversity, but first must be converted to a common unit of measurement. Here, we partition species diversity gradients into components of the SAD and abundance using the effective number of species (ENS) transformation of the individual‐based rarefaction curve. Because the ENS curve is unconstrained by sample size, it can act as a standardized unit of measurement when comparing effect sizes among different components of biodiversity change. We illustrate the utility of the approach using two data sets spanning latitudinal diversity gradients in trees and marine reef fish and find contrasting results. Whereas the diversity gradient of fish was mostly associated with variation in abundance (86%), the tree diversity gradient was mostly associated with variation in the SAD (59%). These results suggest that local fish diversity may be limited by energy through the more‐individuals effect, while species pool effects are the larger determinant of tree diversity. We suggest that the framework of the ENS‐curve has the potential to quantify the underlying factors influencing most aspects of diversity change.     

Characterization of excised DNA intermediates associated with V(D)J recombination at the T-cell receptor delta locus.

Lymphocyte development requires the assembly of antigen receptor genes through the specialized process of V(D)J recombination. This process is initiated by cleavage at the junction between coding segments (V, D, and J) and the recombination signal sequences that border these segments, resulting in generation of double-strand break intermediates. We have used a two-dimensional gel system to characterize broken molecules arising from V(D)J recombination at the T-cell receptor (TCR) delta locus and have identified linear species excised by Ddelta1-Ddelta2 and V-Ddelta2 rearrangement in thymus DNA. Relatively few (approximately 10) V-Ddelta2-excised linear species were detected in DNA from fetal thymocytes. The sizes of these species corresponded to the estimated distances between Ddelta2 and the V gene segments utilized by gammadelta T cells and indicated that both Ddelta2-proximal and -distal V gene segments are targeted for V-Ddelta2 rearrangement. Similar-sized species were observed in DNA from thymocytes of scid mice in which T-cell development is arrested prior to TCR expression. Since previous studies suggest that the TCR alpha/delta locus encodes more than 100 V gene segments, our results indicate that a few select V gene segments are predominantly targeted for rearrangement to Ddelta2, and this primarily accounts for the restricted Vdelta gene repertoire of gammadelta T cells.