Clonal expansion under the microscope: studying lymphocyte activation and differentiation using live-cell imaging

Clonal expansion of lymphocytes is a hallmark of vertebrate adaptive immunity. A small number of precursor cells that recognize a specific antigen proliferate into expanded clones, differentiate and acquire various effector and memory phenotypes, which promote effective immune responses. Recent studies establish a large degree of heterogeneity in the level of expansion and in cell state between and within expanding clones. Studying these processes in vivo, while providing insightful information on the level of heterogeneity, is challenging due to the complex microenvironment and the inability to continuously track individual cells over extended periods of time. Live cell imaging of ex vivo cultures within micro fabricated arrays provides an attractive methodology for studying clonal expansion. These experiments facilitate continuous acquisition of a large number of parameters on cell number, proliferation, death and differentiation state, with single-cell resolution on thousands of expanding clones that grow within controlled environments. Such data can reveal stochastic and instructive mechanisms that contribute to observed heterogeneity and elucidate the sequential order of differentiation events. Intercellular interactions can also be studied within these arrays by following responses of a controlled number of interacting cells, all trapped within the same microwell. Here we describe implementations of live-cell imaging within microwell arrays for studies of lymphocyte clonal expansion, portray insights already gained from these experiments and outline directions for future research. These tools, together with in vivo experiments tracking single-cell responses, will expand our understanding of adaptive immunity and the ways by which it can be manipulated

Predicting T Cell Receptor Antigen Specificity From Structural Features Derived From Homology Models of Receptor-Peptide-Major Histocompatibility Complexes

The physical interaction between the T cell receptor (TCR) and its cognate antigen causes T cells to activate and participate in the immune response. Understanding this physical interaction is important in predicting TCR binding to a target epitope, as well as potential cross-reactivity. Here, we propose a way of collecting informative features of the binding interface from homology models of T cell receptor-peptide-major histocompatibility complex (TCR-pMHC) complexes. The information collected from these structures is sufficient to discriminate binding from non-binding TCR-pMHC pairs in multiple independent datasets. The classifier is limited by the number of crystal structures available for the homology modelling and by the size of the training set. However, the classifier shows comparable performance to sequence-based classifiers requiring much larger training sets

A Linear Epitope in the N-Terminal Domain of CCR5 and Its Interaction with Antibody.

The CCR5 receptor plays a role in several key physiological and pathological processes and is an important therapeutic target. Inhibition of the CCR5 axis by passive or active immunisation offers one very selective strategy for intervention. In this study we define a new linear epitope within the extracellular domain of CCR5 recognised by two independently produced monoclonal antibodies. A short peptide encoding the linear epitope can induce antibodies which recognise the intact receptor when administered colinear with a tetanus toxoid helper T cell epitope. The monoclonal antibody RoAb 13 is shown to bind to both cells and peptide with moderate to high affinity (6x10^8 and 1.2x107 M-1 respectively), and binding to the peptide is enhanced by sulfation of tyrosines at positions 10 and 14. RoAb13, which has previously been shown to block HIV infection, also blocks migration of monocytes in response to CCR5 binding chemokines and to inflammatory macrophage conditioned medium. A Fab fragment of RoAb13 has been crystallised and a structure of the antibody is reported to 2.1 angstrom resolution

Cell-type-specific modulation of innate immune signalling by vitamin D in human mononuclear phagocytes

Vitamin D is widely reported to inhibit innate immune signalling and dendritic cell (DC) maturation as a potential immunoregulatory mechanism. It is not known whether vitamin D has global or gene-specific effects on transcriptional responses downstream of innate immune stimulation, or whether vitamin D inhibition of innate immune signalling is common to different cells. We confirmed vitamin D inhibition of nuclear factor-κB (NF-κB) and p38 mitogen-activated protein kinase (MAPK) signalling in monocyte-derived DC (MDDC) stimulated with lipopolysaccharide (LPS). This was associated with global but modest attenuation of LPS-induced transcriptional changes at genome-wide level. Surprisingly, vitamin D did not inhibit innate immune NF-κB activation in monocyte-derived macrophages. Consistent with our findings in MDDC, ex vivo vitamin D treatment of primary peripheral blood myeloid DC also led to significant inhibition of LPS-inducible NF-κB activation. Unexpectedly, in the same samples, vitamin D enhanced activation of both NF-κB and MAPK signalling in primary peripheral blood monocytes. In a cross-sectional clinical cohort, we found no relationship between peripheral blood vitamin D levels and LPS-inducible activation of NF-κB and MAPK pathways in monocytes of myeloid DC. Remarkably, however, in vivo supplementation of people with vitamin D deficiency in this clinical cohort also enhanced LPS-inducible MAPK signalling in peripheral blood monocytes. Therefore, we report that vitamin D differentially modulates the molecular response to innate immune stimulation in monocytes, macrophages and dendritic cells. These results are of importance in the design of studies on vitamin D supplementation in infectious and immunological diseases

The clonal structure and dynamics of the human T cell response to an organic chemical hapten

Diphenylcyclopropenone (DPC) is an organic chemical hapten which induces allergic contact dermatitis, and is used in treatment of warts, melanoma and alopecia areata. This therapeutic setting therefore provided an opportunity to study T cell receptor (TCR) repertoire changes in response to hapten sensitization in humans. Repeated exposure to DPC induced highly dynamic transient expansions of a polyclonal diverse T cell population. The number of TCRs expanded early after sensitization varies between individuals, and predicts the magnitude of the allergic reaction. The expanded TCRs show preferential TCR V and J gene usage, and consist of clusters of TCRs with similar sequences, two characteristic features of antigen-driven responses. The expanded TCRs share subtle sequence motifs that can be captured using a Dynamic Bayesian Network. These observations suggest the response to DPC is mediated by a polyclonal population of T cells recognizing a small number of dominant antigens

Dynamic Perturbations of the T-Cell Receptor Repertoire in Chronic HIV Infection and following Antiretroviral Therapy

HIV infection profoundly affects many parameters of the immune system and ultimately leads to AIDS, yet which factors are most important for determining resistance, pathology, and response to antiretroviral treatment - and how best to monitor them - remain unclear. We develop a quantitative high-throughput sequencing pipeline to characterize the TCR repertoires of HIV-infected individuals before and after antiretroviral therapy, working from small, unfractionated samples of peripheral blood. This reveals the TCR repertoires of HIV(+) individuals to be highly perturbed, with considerably reduced diversity as a small proportion of sequences are highly overrepresented. HIV also causes specific qualitative changes to the repertoire including an altered distribution of V gene usage, depletion of public TCR sequences, and disruption of TCR networks. Short-term antiretroviral therapy has little impact on most of the global damage to repertoire structure, but is accompanied by rapid changes in the abundance of many individual TCR sequences, decreases in abundance of the most common sequences, and decreases in the majority of HIV-associated CDR3 sequences. Thus, high-throughput repertoire sequencing of small blood samples that are easy to take, store, and process can shed light on various aspects of the T-cell immune compartment and stands to offer insights into patient stratification and immune reconstitution

T cell receptor sequence clustering and antigen specificity

There has been increasing interest in the role of T cells and their involvement in cancer, autoimmune and infectious diseases. However, the nature of T cell receptor (TCR) epitope recognition at a repertoire level is not yet fully understood. Due to technological advances a plethora of TCR sequences from a variety of disease and treatment settings has become readily available. Current efforts in TCR specificity analysis focus on identifying characteristics in immune repertoires which can explain or predict disease outcome or progression, or can be used to monitor the efficacy of disease therapy. In this context, clustering of TCRs by sequence to reflect biological similarity, and especially to reflect antigen specificity have become of paramount importance. We review the main TCR sequence clustering methods and the different similarity measures they use, and discuss their performance and possible improvement. We aim to provide guidance for non-specialists who wish to use TCR repertoire sequencing for disease tracking, patient stratification or therapy prediction, and to provide a starting point for those aiming to develop novel techniques for TCR annotation through clustering

PD1-Expressing T Cell Subsets Modify the Rejection Risk in Renal Transplant Patients

We tested whether multi-parameter immune phenotyping before or after renal ­transplantation can predict the risk of rejection episodes. Blood samples collected before and weekly for 3 months after transplantation were analyzed by multi-parameter flow cytometry to define 52 T cell and 13 innate lymphocyte subsets in each sample, producing more than 11,000 data points that defined the immune status of the 28 patients included in this study. Principle component analysis suggested that the patients with histologically confirmed rejection episodes segregated from those without rejection. Protein death 1 (PD-1)-expressing subpopulations of regulatory and conventional T cells had the greatest influence on the principal component segregation. We constructed a statistical tool to predict rejection using a support vector machine algorithm. The algorithm correctly identified 7 out of 9 patients with rejection, and 14 out of 17 patients without rejection. The immune profile before transplantation was most accurate in determining the risk of rejection, while changes of immune parameters after transplantation were less accurate in discriminating rejection from non-rejection. The data indicate that pretransplant immune subset analysis has the potential to identify patients at risk of developing rejection episodes, and suggests that the proportion of PD1-expressing T cell subsets may be a key indicator of rejection risk

Feature selection using a one dimensional naïve Bayes' classifier increases the accuracy of support vector machine classification of CDR3 repertoires.

MOTIVATION: Somatic DNA recombination, the hallmark of vertebrate adaptive immunity, has the potential to generate a vast diversity of antigen receptor sequences. How this diversity captures antigen specificity remains incompletely understood. In this study we use high throughput sequencing to compare the global changes in T cell receptor β chain complementarity determining region 3 (CDR3β) sequences following immunization with ovalbumin administered with complete Freund's adjuvant (CFA) or CFA alone. RESULTS: The CDR3β sequences were deconstructed into short stretches of overlapping contiguous amino acids. The motifs were ranked according to a one-dimensional Bayesian classifier score comparing their frequency in the repertoires of the two immunization classes. The top ranking motifs were selected and used to create feature vectors which were used to train a support vector machine. The support vector machine achieved high classification scores in a leave-one-out validation test reaching  : >90% in some cases. SUMMARY: The study describes a novel two-stage classification strategy combining a one-dimensional Bayesian classifier with a support vector machine. Using this approach we demonstrate that the frequency of a small number of linear motifs three amino acids in length can accurately identify a CD4 T cell response to ovalbumin against a background response to the complex mixture of antigens which characterize Complete Freund's Adjuvant. AVAILABILITY AND IMPLEMENTATION: The sequence data is available at www.ncbi.nlm.nih.gov/sra/?term¼SRP075893 The Decombinator package is available at github.com/innate2adaptive/Decombinator The R package e1071 is available at the CRAN repository https://cran.r-project.org/web/packages/e1071/index.html CONTACT: [email protected] information: Supplementary data are available at Bioinformatics online