Monitoring islet specific immune responses in type 1 diabetes clinical immunotherapy trials

The number of immunotherapeutic clinical trials in type 1 diabetes currently being conducted is expanding, and thus there is a need for robust immune-monitoring assays which are capable of detecting and characterizing islet specific immune responses in peripheral blood. Islet- specific T cells can serve as biomarkers and as such can guide drug selection, dosing regimens and immunological efficacy. Furthermore, these biomarkers can be utilized in patient stratification which can then benchmark suitability for participation in future clinical trials. This review focusses on the commonly used immune-monitoring techniques including multimer and antigen induced marker assays and the potential to combine these with single cell transcriptional profiling which may provide a greater understanding of the mechanisms underlying immuno-intervention. Although challenges remain around some key areas such as the need for harmonizing assays, technological advances mean that multiparametric information derived from a single sample can be used in coordinated efforts to harmonize biomarker discovery and validation. Moreover, the technologies discussed here have the potential to provide a unique insight on the effect of therapies on key players in the pathogenesis of T1D that cannot be obtained using antigen agnostic approaches.

Using the T Cell Receptor as a Biomarker in Type 1 Diabetes

T cell receptors (TCRs) are unique markers that define antigen specificity for a given T cell. With the evolution of sequencing and computational analysis technologies, TCRs are now prime candidates for the development of next-generation non-cell based T cell biomarkers, which provide a surrogate measure to assess the presence of antigen-specific T cells. Type 1 diabetes (T1D), the immune-mediated form of diabetes, is a prototypical organ specific autoimmune disease in which T cells play a pivotal role in targeting pancreatic insulin-producing beta cells. While the disease is now predictable by measuring autoantibodies in the peripheral blood directed to beta cell proteins, there is an urgent need to develop T cell markers that recapitulate T cell activity in the pancreas and can be a measure of disease activity. This review focuses on the potential and challenges of developing TCR biomarkers for T1D. We summarize current knowledge about TCR repertoires and clonotypes specific for T1D and discuss challenges that are unique for autoimmune diabetes. Ultimately, the integration of large TCR datasets produced from individuals with and without T1D along with computational 'big data' analysis will facilitate the development of TCRs as potentially powerful biomarkers in the development of T1D.

A single donor is sufficient to produce a highly functional in vitro antibody library

Antibody complementarity determining region diversity has been considered to be the most important metric for the production of a functional antibody library. Generally, the greater the antibody library diversity, the greater the probability of selecting a diverse array of high affinity leads. According to this paradigm, the primary means of elevating library diversity has been by increasing the number of donors. In the present study we explored the possibility of creating an in vitro antibody library from a single healthy individual, showing that the number of lymphocytes, rather than the number of donors, is the key criterion in the production of a diverse and functional antibody library. We describe the construction of a high-quality phage display library comprising 5 × 10⁹ human antibodies by applying an efficient B cell extraction protocol from a single donor and a targeted V-gene amplification strategy favoring specific antibody families for their improved developability profiles. Each step of the library generation process was followed and validated by next generation sequencing to monitor the library quality and diversity. The functionality of the library was tested using several therapeutically relevant targets for which a vast number of different antibodies with desired biophysical properties were obtained.

Diagnostic differentiation of Zika and dengue virus exposure by analyzing T cell receptor sequences from peripheral blood of infected HLA-A2 transgenic mice

Zika virus (ZIKV) is a significant global health threat due to its potential for rapid emergence and association with severe congenital malformations during infection in pregnancy. Despite the urgent need, accurate diagnosis of ZIKV infection is still a major hurdle that must be overcome. Contributing to the inaccuracy of most serologically-based diagnostic assays for ZIKV, is the substantial geographic and antigenic overlap with other flaviviruses, including the four serotypes of dengue virus (DENV). Within this study, we have utilized a novel T cell receptor (TCR) sequencing platform to distinguish between ZIKV and DENV infections. Using high-throughput TCR sequencing of lymphocytes isolated from DENV and ZIKV infected mice, we were able to develop an algorithm which could identify virus-associated TCR sequences uniquely associated with either a prior ZIKV or DENV infection in mice. Using this algorithm, we were then able to separate mice that had been exposed to ZIKV or DENV infection with 97% accuracy. Overall this study serves as a proof-of-principle that T cell receptor sequencing can be used as a diagnostic tool capable of distinguishing between closely related viruses. Our results demonstrate the potential for this innovative platform to be used to accurately diagnose Zika virus infection and potentially the next emerging pathogen(s).

Diagnostic differentiation between dengue virus and Zika virus infections is a challenge due to serological cross-reactivity. In this study, we used a novel T cell receptor sequencing platform to identify T cell receptor sequences significantly associated with either dengue or Zika virus infection in HLA-A2 transgenic mice. These libraries were used to computationally train diagnostic classifiers which were capable of distinguishing between dengue and Zika virus in independent cohorts of infected mice.

Identifying and Tracking Low-Frequency Virus-Specific TCR Clonotypes Using High-Throughput Sequencing

Tracking antigen-specific T cell responses over time within individuals is difficult because of lack of knowledge of antigen-specific TCR sequences, limitations in sample size, and assay sensitivities. We hypothesized that analyses of high-throughput sequencing of TCR clonotypes could provide functional readouts of individuals' immunological histories. Using high-throughput TCR sequencing, we develop a database of TCRβ sequences from large cohorts of mice before (naive) and after smallpox vaccination. We computationally identify 315 vaccine-associated TCR sequences (VATS) that are used to train a diagnostic classifier that distinguishes naive from vaccinated samples in mice up to 9 months post-vaccination with >99% accuracy. We determine that the VATS library contains virus-responsive TCRs by in vitro expansion assays and virus-specific tetramer sorting. These data outline a platform for advancing our capabilities to identify pathogen-specific TCR sequences, which can be used to identify and quantitate low-frequency pathogen-specific TCR sequences in circulation over time with exceptional sensitivity.

Standardizing T-Cell Biomarkers in Type 1 Diabetes: Challenges and Recent Advances

Type 1 diabetes (T1D) results from the progressive destruction of pancreatic β-cells in a process mediated primarily by T lymphocytes. The T1D research community has made dramatic progress in understanding the genetic basis of the disease as well as in the development of standardized autoantibody assays that inform both disease risk and progression. Despite these advances, there remains a paucity of robust and accepted biomarkers that can effectively inform on the activity of T cells during the natural history of the disease or in response to treatment. In this article, we discuss biomarker development and validation efforts for evaluation of T-cell responses in patients with and at risk for T1D as well as emerging technologies. It is expected that with systematic planning and execution of a well-conceived biomarker development pipeline, T-cell-related biomarkers would rapidly accelerate disease progression monitoring efforts and the evaluation of intervention therapies in T1D.

Circulating monocytes and tumor-associated macrophages express recombined immunoglobulins in glioblastoma patients

BACKGROUND

Glioblastoma is the most common and malignant brain tumor in adults. Glioblastoma is usually fatal 12-15 months after diagnosis and the current possibilities in therapy are mostly only palliative. Therefore, new forms of diagnosis and therapy are urgently needed. Since tumor-associated macrophages are key players in tumor progression and survival there is large potential in investigating their immunological characteristics in glioblastoma patients. Recent evidence shows the expression of variable immunoglobulins and TCRαβ in subpopulations of monocytes, in vitro polarized macrophages and macrophages in the tumor microenvironment. We set out to investigate the immunoglobulin sequences of circulating monocytes and tumor-associated macrophages from glioblastoma patients to evaluate their potential as novel diagnostic or therapeutic targets.

RESULTS

We routinely find consistent expression of immunoglobulins in tumor-associated macrophages (TAM) and circulating monocytes from all glioblastoma patients analyzed in this study. However, the immunoglobulin repertoires of circulating monocytes and TAM are generally more restricted compared to B cells. Furthermore, the immunoglobulin expression in the macrophage populations negatively correlates with the tumor volume. Interestingly, the comparison of somatic mutations, V-chain usage, CDR3-length and the distribution of used heavy chain genes on the locus of chromosome 14 of the immunoglobulins from myeloid to B cells revealed virtually no differences.

CONCLUSIONS

The investigation of the immunoglobulin repertoires from TAM and circulating monocytes in glioblastoma-patients revealed a negative correlation to the tumor volume, which could not be detected in the immunoglobulin repertoires of the patients' B lymphocytes. Furthermore, the immunoglobulin repertoires of monocytes were more diverse than the repertoires of the macrophages in the tumor microenvironment from the same patients suggesting a tumor-specific immune response which could be advantageous for the use as diagnostic or therapeutic target.

Dysfunctional peripheral T follicular helper cells dominate in people with impaired influenza vaccine responses: Results from the FLORAH study

Antigen-primed cluster of differentiation (CD) 4+ T follicular helper (Tfh) cells interact with B cells in the germinal centers (GCs) of lymph nodes to generate vaccine-induced antibody (Ab) responses. In the circulation, peripheral Tfh (pTfh) cells, a subset of memory CD4 T cells, serve as surrogates for GC Tfh because of several functional and phenotypic similarities between them. We investigated features of H1N1 influenza antigen-specific pTfh (Ag.pTfh) in virologically controlled HIV+ volunteers on antiretroviral therapy (ART) and healthy control (HC) participants selected from a seasonal influenza vaccine responsiveness study. Selection of the participants was made based on age, defined as young (18-40 y) and old (>60 y) and on their classification as a vaccine responder (VR) or vaccine nonresponder (VNR). VRs demonstrated expansion of CD40L+ and CD69+ Ag.pTfh, with induction of intracellular interleukin 21 (IL-21) and inducible costimulator (ICOS) post vaccination; these responses were strongest in young HC VRs and were less prominent in HIV+ individuals of all ages. Ag.pTfh in VNRs exhibited dramatically different characteristics from VRs, displaying an altered phenotype and a cytokine profile dominated by cytokines IL-2, tumor necrosis factor alpha (TNF-α), or IL-17 but lacking in IL-21. In coculture experiments, sorted pTfh did not support the B cell IgG production in VNRs and were predominantly an inflammatory T helper 1 (Th1)/T helper 17 (Th17) phenotype with lower ICOS and higher programmed cell death protein 1 (PD1) expression. Induction of IL-21 and ICOS on Ag.pTfh cells are negatively affected by both aging and HIV infection. Our findings demonstrate that dysfunctional Ag.pTfh cells with an altered IL-21/IL-2 axis contribute to inadequate vaccine responses. Approaches for targeting inflammation or expanding functional Tfh may improve vaccine responses in healthy aging and those aging with HIV infection.

High-throughput T cell receptor sequencing identifies clonally expanded CD8+ T cell populations in alopecia areata

Alopecia areata (AA) is an autoimmune disease in which cytotoxic T cells specifically target growing hair follicles. We used high-throughput TCR sequencing in the C3H/HeJ mouse model of AA and in human AA patients to gain insight into pathogenic T cell populations and their dynamics, which revealed clonal CD8+ T cell expansions in lesional skin. In the C3H/HeJ model, we observed interindividual sharing of TCRβ chain protein sequences, which strongly supports a model of antigenic drive in AA. The overlap between the lesional TCR repertoire and a population of CD8+NKG2D+ T cells in skin-draining lymph nodes identified this subset as pathogenic effectors. In AA patients, treatment with the oral JAK inhibitor tofacitinib resulted in a decrease in clonally expanded CD8+ T cells in the scalp but also revealed that many expanded lesional T cell clones do not completely disappear from either skin or blood during treatment with tofacitinib, which may explain in part the relapse of disease after stopping treatment.

T cell receptor β-chains display abnormal shortening and repertoire sharing in type 1 diabetes

Defects in T cell receptor (TCR) repertoire are proposed to predispose to autoimmunity. Here we show, by analyzing >2 × 10⁸TCRB sequences of circulating naive, central memory, regulatory and stem cell-like memory CD4⁺ T cell subsets from patients with type 1 diabetes and healthy donors, that patients have shorter TCRB complementarity-determining region 3s (CDR3), in all cell subsets, introduced by increased deletions/reduced insertions during VDJ rearrangement. High frequency of short CDR3s is also observed in unproductive TCRB sequences, which are not subjected to thymic culling, suggesting that the shorter CDR3s arise independently of positive/negative selection. Moreover, TCRB CDR3 clonotypes expressed by autoantigen-specific CD4⁺ T cells are shorter compared with anti-viral T cells, and with those from healthy donors. Thus, early events in thymic T cell development and repertoire generation are abnormal in type 1 diabetes, which suggest that short CDR3s increase the potential for self-recognition, conferring heightened risk of autoimmune disease.

T cell receptors are generated by somatic gene recombination, and are normally selected against autoreactivity. Here the authors show that CD4 T cells from patients with autoimmune type 1 diabetes have shorter TCRβ sequences, broader repertoire diversity, and more repertoire sharing than those from healthy individuals.

High-Throughput Immunogenetics for Clinical and Research Applications in Immunohematology: Potential and Challenges

Analysis and interpretation of Ig and TCR gene rearrangements in the conventional, low-throughput way have their limitations in terms of resolution, coverage, and biases. With the advent of high-throughput, next-generation sequencing (NGS) technologies, a deeper analysis of Ig and/or TCR (IG/TR) gene rearrangements is now within reach, which impacts on all main applications of IG/TR immunogenetic analysis. To bridge the generation gap from low- to high-throughput analysis, the EuroClonality-NGS Consortium has been formed, with the main objectives to develop, standardize, and validate the entire workflow of IG/TR NGS assays for 1) clonality assessment, 2) minimal residual disease detection, and 3) repertoire analysis. This concerns the preanalytical (sample preparation, target choice), analytical (amplification, NGS), and postanalytical (immunoinformatics) phases. Here we critically discuss pitfalls and challenges of IG/TR NGS methodology and its applications in hemato-oncology and immunology.

High-throughput sequencing reveals restricted TCR Vβ usage and public TCRβ clonotypes among pancreatic lymph node memory CD4(+) T cells and their involvement in autoimmune diabetes

Islet-reactive memory CD4(+) T cells are an essential feature of type 1 diabetes (T1D) as they are involved in both spontaneous disease and in its recurrence after islet transplantation. Expansion and enrichment of memory T cells have also been shown in the peripheral blood of diabetic patients. Here, using high-throughput sequencing, we investigated the clonal diversity of the TCRβ repertoire of memory CD4(+) T cells in the pancreatic lymph nodes (PaLN) of non-obese diabetic (NOD) mice and examined their clonal overlap with islet-infiltrating memory CD4T cells. Both prediabetic and diabetic NOD mice exhibited a restricted TCRβ repertoire dominated by clones expressing TRBV13-2, TRBV13-1 or TRBV5 gene segments. There is a limited degree of TCRβ overlap between the memory CD4 repertoire of PaLN and pancreas as well as between the prediabetic and diabetic group. However, public TCRβ clonotypes were identified across several individual animals, some of them with sequences similar to the TCRs from the islet-reactive T cells suggesting their antigen-driven expansion. Moreover, the majority of the public clonotypes expressed TRBV13-2 (Vβ8.2) gene segment. Nasal vaccination with an immunodominat peptide derived from the TCR Vβ8.2 chain led to protection from diabetes, suggesting a critical role for Vβ8.2(+) CD4(+) memory T cells in T1D. These results suggest that memory CD4(+) T cells bearing limited dominant TRBV genes contribute to the autoimmune diabetes and can be potentially targeted for intervention in diabetes. Furthermore, our results have important implications for the identification of public T cell clonotypes as potential novel targets for immune manipulation in human T1D.

Dynamics of Individual T Cell Repertoires: From Cord Blood to Centenarians

The diversity, architecture, and dynamics of the TCR repertoire largely determine our ability to effectively withstand infections and malignancies with minimal mistargeting of immune responses. In this study, we have employed deep TCRβ repertoire sequencing with normalization based on unique molecular identifiers to explore the long-term dynamics of T cell immunity. We demonstrate remarkable stability of repertoire, where approximately half of all T cells in peripheral blood are represented by clones that persist and generally preserve their frequencies for 3 y. We further characterize the extremes of lifelong TCR repertoire evolution, analyzing samples ranging from umbilical cord blood to centenarian peripheral blood. We show that the fetal TCR repertoire, albeit structurally maintained within regulated borders due to the lower numbers of randomly added nucleotides, is not limited with respect to observed functional diversity. We reveal decreased efficiency of nonsense-mediated mRNA decay in umbilical cord blood, which may reflect specific regulatory mechanisms in development. Furthermore, we demonstrate that human TCR repertoires are functionally more similar at birth but diverge during life, and we track the lifelong behavior of CMV- and EBV-specific T cell clonotypes. Finally, we reveal gender differences in dynamics of TCR diversity constriction, which come to naught in the oldest age. Based on our data, we propose a more general explanation for the previous observations on the relationships between longevity and immunity.

A bioinformatic framework for immune repertoire diversity profiling enables detection of immunological status

BACKGROUND

Lymphocyte receptor repertoires are continually shaped throughout the lifetime of an individual in response to environmental and pathogenic exposure. Thus, they may serve as a fingerprint of an individual's ongoing immunological status (e.g., healthy, infected, vaccinated), with far-reaching implications for immunodiagnostics applications. The advent of high-throughput immune repertoire sequencing now enables the interrogation of immune repertoire diversity in an unprecedented and quantitative manner. However, steadily increasing sequencing depth has revealed that immune repertoires vary greatly among individuals in their composition; correspondingly, it has been reported that there are few shared sequences indicative of immunological status ('public clones'). Disconcertingly, this means that the wealth of information gained from repertoire sequencing remains largely unused for determining the current status of immune responses, thereby hampering the implementation of immune-repertoire-based diagnostics.

METHODS

Here, we introduce a bioinformatics repertoire-profiling framework that possesses the advantage of capturing the diversity and distribution of entire immune repertoires, as opposed to singular public clones. The framework relies on Hill-based diversity profiles composed of a continuum of single diversity indices, which enable the quantification of the extent of immunological information contained in immune repertoires.

RESULTS

We coupled diversity profiles with unsupervised (hierarchical clustering) and supervised (support vector machine and feature selection) machine learning approaches in order to correlate patients' immunological statuses with their B- and T-cell repertoire data. We could predict with high accuracy (greater than or equal to 80 %) a wide range of immunological statuses such as healthy, transplantation recipient, and lymphoid cancer, suggesting as a proof of principle that diversity profiling can recover a large amount of immunodiagnostic fingerprints from immune repertoire data. Our framework is highly scalable as it easily allowed for the analysis of 1000 simulated immune repertoires; this exceeds the size of published immune repertoire datasets by one to two orders of magnitude.

CONCLUSIONS

Our framework offers the possibility to advance immune-repertoire-based fingerprinting, which may in the future enable a systems immunogenomics approach for vaccine profiling and the accurate and early detection of disease and infection.

Quantitative assessment of the robustness of next-generation sequencing of antibody variable gene repertoires from immunized mice

BACKGROUND

Next-generation sequencing (NGS) of antibody variable regions has emerged as a powerful tool in systems immunology by providing quantitative molecular information on polyclonal humoral immune responses. Reproducible and robust information on antibody repertoires is valuable for basic and applied immunology studies: thus, it is essential to establish the reliability of antibody NGS data.

RESULTS

We isolated RNA from antibody-secreting cells (ASCs) from either 1 mouse or a pool of 9 immunized mice in order to simulate both normal and high diversity populations. Next, we prepared three technical replicates of antibody libraries by RT-PCR from each diversity scenario, which were sequenced using the Illumina MiSeq platform resulting in >106 250 bp paired-end reads per replicate. We then assessed the robustness of antibody repertoire data based on clonal identification defined by amino acid sequence of either full-length VDJ region or the complementarity determining region 3 (CDR3). Leveraging modeling approaches adapted from mathematical ecology, we found that in either diversity scenario both CDR3 and VDJ detection nears completeness indicating deep coverage of ASC repertoires. Additionally, we defined reliability thresholds for accurate quantification and ranking of CDR3s and VDJs. Importantly, we show that both factors-(i) replicate sequencing and (ii) sequencing depth-are crucial for robust CDR3 and VDJ detection and ranking.

CONCLUSIONS

In summary, we established widely applicable experimental and computational guidelines for robust antibody NGS and analysis, which will help advance systems immunology studies related to the quantitative profiling of antibody responses following infection and vaccination.

Comprehensive evaluation and optimization of amplicon library preparation methods for high-throughput antibody sequencing

High-throughput sequencing (HTS) of antibody repertoire libraries has become a powerful tool in the field of systems immunology. However, numerous sources of bias in HTS workflows may affect the obtained antibody repertoire data. A crucial step in antibody library preparation is the addition of short platform-specific nucleotide adapter sequences. As of yet, the impact of the method of adapter addition on experimental library preparation and the resulting antibody repertoire HTS datasets has not been thoroughly investigated. Therefore, we compared three standard library preparation methods by performing Illumina HTS on antibody variable heavy genes from murine antibody-secreting cells. Clonal overlap and rank statistics demonstrated that the investigated methods produced equivalent HTS datasets. PCR-based methods were experimentally superior to ligation with respect to speed, efficiency, and practicality. Finally, using a two-step PCR based method we established a protocol for antibody repertoire library generation, beginning from inputs as low as 1 ng of total RNA. In summary, this study represents a major advance towards a standardized experimental framework for antibody HTS, thus opening up the potential for systems-based, cross-experiment meta-analyses of antibody repertoires.