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Follicular helper T (TFH) cells are implicated in type 1 diabetes (T1D), and their development has been linked to CD28 costimulation. We tested whether TFH cells were decreased by costimulation blockade using the CTLA-4–immunoglobulin (Ig) fusion protein (abatacept) in a mouse model of diabetes and in individuals with new-onset T1D. Unbiased bioinformatics analysis identified that inducible costimulatory molecule (ICOS)+ TFH cells and other ICOS+ populations, including peripheral helper T cells, were highly sensitive to costimulation blockade. We used pretreatment TFH profiles to derive a model that could predict clinical response to abatacept in individuals with T1D. Using two independent approaches, we demonstrated that higher frequencies of ICOS+ TFH cells at baseline were associated with a poor clinical response following abatacept administration. Therefore, TFH analysis may represent a new stratification tool, permitting the identification of individuals most likely to benefit from costimulation blockade. The CTLA-4–Ig fusion protein (abatacept) can have beneficial effects in autoimmune disease. Walker and colleagues show in mouse and human type 1 diabetes that abatacept targets pathogenic follicular helper T cells, and the frequencies of these cells at baseline can be used to stratify treatment responses in patients.

Retinal dystrophies are an overlapping group of genetically heterogeneous conditions resulting from mutations in more than 250 genes. Here we describe five families affected by an adult-onset retinal dystrophy with early macular involvement and associated central visual loss in the third or fourth decade of life. Affected individuals were found to harbor disease-causing variants in DRAM2 (DNA-damage regulated autophagy modulator protein 2). Homozygosity mapping and exome sequencing in a large, consanguineous British family of Pakistani origin revealed a homozygous frameshift variant (c.140delG [p.Gly47Valfs∗3]) in nine affected family members. Sanger sequencing of DRAM2 in 322 unrelated probands with retinal dystrophy revealed one European subject with compound heterozygous DRAM2 changes (c.494G>A [p.Trp165∗] and c.131G>A [p.Ser44Asn]). Inspection of previously generated exome sequencing data in unsolved retinal dystrophy cases identified a homozygous variant in an individual of Indian origin (c.64_66del [p.Ala22del]). Independently, a gene-based case-control association study was conducted via an exome sequencing dataset of 18 phenotypically similar case subjects and 1,917 control subjects. Using a recessive model and a binomial test for rare, presumed biallelic, variants, we found DRAM2 to be the most statistically enriched gene; one subject was a homozygote (c.362A>T [p.His121Leu]) and another a compound heterozygote (c.79T>C [p.Tyr27His] and c.217_225del [p.Val73_Tyr75del]). DRAM2 encodes a transmembrane lysosomal protein thought to play a role in the initiation of autophagy. Immunohistochemical analysis showed DRAM2 localization to photoreceptor inner segments and to the apical surface of retinal pigment epithelial cells where it might be involved in the process of photoreceptor renewal and recycling to preserve visual function.

Infection with hepatitis B virus (HBV) results in disparate degrees of tissue injury: the virus can either replicate without pathological consequences or trigger immune-mediated necroinflammatory liver damage. We investigated the potential for myeloid-derived suppressor cells (MDSCs) to suppress T cell-mediated immunopathology in this setting. Granulocytic MDSCs (gMDSCs) expanded transiently in acute resolving HBV, decreasing in frequency prior to peak hepatic injury. In persistent infection, arginase-expressing gMDSCs (and circulating arginase) increased most in disease phases characterized by HBV replication without immunopathology, whilst L-arginine decreased. gMDSCs expressed liver-homing chemokine receptors and accumulated in the liver, their expansion supported by hepatic stellate cells. We provide in vitro and ex vivo evidence that gMDSCs potently inhibited T cells in a partially arginase-dependent manner. L-arginine-deprived T cells upregulated system L amino acid transporters to increase uptake of essential nutrients and attempt metabolic reprogramming. These data demonstrate the capacity of expanded arginase-expressing gMDSCs to regulate liver immunopathology in HBV infection.

Summary: High-throughput sequencing provides an opportunity to analyse the repertoire of antigen-specific receptors with an unprecedented breadth and depth. However, the quantity of raw data produced by this technology requires efficient ways to categorize and store the output for subsequent analysis. To this end, we have defined a simple five-item identifier that uniquely and unambiguously defines each TcR sequence. We then describe a novel application of finite-state automaton to map Illumina short-read sequence data for individual TcRs to their respective identifier. An extension of the standard algorithm is also described, which allows for the presence of single-base pair mismatches arising from sequencing error. The software package, named Decombinator, is tested first on a set of artificial in silico sequences and then on a set of published human TcR-β sequences. Decombinator assigned sequences at a rate more than two orders of magnitude faster than that achieved by classical pairwise alignment algorithms, and with a high degree of accuracy (>88%), even after introducing up to 1% error rates in the in silico sequences. Analysis of the published sequence dataset highlighted the strong V and J usage bias observed in the human peripheral blood repertoire, which seems to be unconnected to antigen exposure. The analysis also highlighted the enormous size of the available repertoire and the challenge of obtaining a comprehensive description for it. The Decombinator package will be a valuable tool for further in-depth analysis of the T-cell repertoire. Availability and implementation: The Decombinator package is implemented in Python (v2.6) and is freely available at https://github.com/uclinfectionimmunity/Decombinator along with full documentation and examples of typical usage. Contact: b.chain@ucl.ac.uk

BACKGROUND. Novel rapid diagnostics for active tuberculosis (TB) are required to overcome the time delays and inadequate sensitivity of current microbiological tests that are critically dependent on sampling the site of disease. Multiparametric blood transcriptomic signatures of TB have been described as potential diagnostic tests. We sought to identify the best transcript candidates as host biomarkers for active TB, extend the evaluation of their specificity by comparison with other infectious diseases, and to test their performance in both pulmonary and extrapulmonary TB. METHODS. Support vector machine learning, combined with feature selection, was applied to new and previously published blood transcriptional profiles in order to identify the minimal TB‑specific transcriptional signature shared by multiple patient cohorts including pulmonary and extrapulmonary TB, and individuals with and without HIV-1 coinfection. RESULTS. We identified and validated elevated blood basic leucine zipper transcription factor 2 (BATF2) transcript levels as a single sensitive biomarker that discriminated active pulmonary and extrapulmonary TB from healthy individuals, with receiver operating characteristic (ROC) area under the curve (AUC) scores of 0.93 to 0.99 in multiple cohorts of HIV-1–negative individuals, and 0.85 in HIV-1–infected individuals. In addition, we identified and validated a potentially novel 4-gene signature comprising CD177, haptoglobin, immunoglobin J chain, and galectin 10 that discriminated active pulmonary and extrapulmonary TB from other febrile infections, giving ROC AUCs of 0.94 to 1. CONCLUSIONS. Elevated blood BATF2 transcript levels provide a sensitive biomarker that discriminates active TB from healthy individuals, and a potentially novel 4-gene transcriptional signature differentiates between active TB and other infectious diseases in individuals presenting with fever. FUNDING. MRC, Wellcome Trust, Rosetrees Trust, British Lung Foundation, NIHR., Blood BATF2 transcripts provide a single biomarker for active tuberculosis and a novel four-gene transcriptional signature differentiates active TB from other infectious diseases with fever.

Motivation: The clonal theory of adaptive immunity proposes that immunological responses are encoded by increases in the frequency of lymphocytes carrying antigen-specific receptors. In this study, we measure the frequency of different T-cell receptors (TcR) in CD4 + T cell populations of mice immunized with a complex antigen, killed Mycobacterium tuberculosis, using high throughput parallel sequencing of the TcRβ chain. Our initial hypothesis that immunization would induce repertoire convergence proved to be incorrect, and therefore an alternative approach was developed that allows accurate stratification of TcR repertoires and provides novel insights into the nature of CD4 + T-cell receptor recognition. Results: To track the changes induced by immunization within this heterogeneous repertoire, the sequence data were classified by counting the frequency of different clusters of short (3 or 4) continuous stretches of amino acids within the antigen binding complementarity determining region 3 (CDR3) repertoire of different mice. Both unsupervised (hierarchical clustering) and supervised (support vector machine) analyses of these different distributions of sequence clusters differentiated between immunized and unimmunized mice with 100% efficiency. The CD4 + TcR repertoires of mice 5 and 14 days postimmunization were clearly different from that of unimmunized mice but were not distinguishable from each other. However, the repertoires of mice 60 days postimmunization were distinct both from naive mice and the day 5/14 animals. Our results reinforce the remarkable diversity of the TcR repertoire, resulting in many diverse private TcRs contributing to the T-cell response even in genetically identical mice responding to the same antigen. However, specific motifs defined by short stretches of amino acids within the CDR3 region may determine TcR specificity and define a new approach to TcR sequence classification. Availability and implementation: The analysis was implemented in R and Python, and source code can be found in Supplementary Data. Contact: b.chain@ucl.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

The human immune system has a highly complex, multi-layered structure which has evolved to detect and respond to changes in the internal microenvironment of the body. Recognition occurs at the molecular or submolecular scale, via classical reversible receptor–ligand interactions, and can lead to a response with great sensitivity and speed. Remarkably, recognition is coupled to memory, such that responses are modulated by events which occurred years or even decades before. Although the immune system in general responds differently and more vigorously to stimuli entering the body from the outside (e.g. infections), this is an emergent property of the system: many of the recognition molecules themselves have no inherent bias towards external stimuli (non-self) but also bind targets found within the body (self). It is quite clear that the immune response registers pathophysiological changes in general. Cancer, wounding and chronic tissue injury are some obvious examples. Against this background, the immune system ‘state’ tracks the internal processes of the body, and is likely to encode information regarding both current and past disease processes. Moreover, the distributed nature of most immune responses (e.g. typically involving lymphoid tissue, non-lymphoid tissue, bone marrow, blood, extracellular interstitial spaces, etc.) means that many of the changes associated with immune responses are manifested systemically, and specifically can be detected in blood. This provides a very convenient route to sampling immune cells. We consider two different and complementary ways of querying the human immune ‘state’ using high-dimensional genomic screening methodologies, and discuss the potentials of these approaches and some of the technological and computational challenges to be overcome.

Herpes simplex virus (HSV) has often been suggested as a vector for gene delivery to the nervous system although it is also capable of infecting many other cell types. HSV also has the ability to package large genetic insertions so the expression of multiple genes from a single virus is possible. Here we show that a green fluorescent protein (GFP) expressing HSV1 vector can transduce two primary human cell types--quiescent human CD34+ hematopoietic progenitor cells and dendritic cells--which are both hard to transduce by other means. We also show that GFP is an effective marker when expressed from an HSV vector in vivo in the mouse brain. When GFP is expressed together with a second gene (in this case lacZ) from a single virus, transduced GFP-positive CD34+ hematopoietic progenitor cells or dendritic cells can both be generated at an effective efficiency of 100% for the second gene. Here transduction with the vector is combined with flow cytometry allowing GFP-positive cells to be sorted from the untransduced population. Such completely transduced populations of quiescent CD34+ hematopoietic progenitor and dendritic cells cannot easily be achieved by other means, and might thus allow experimental or therapeutic protocols to be carried out requiring high-level transduction which would not otherwise be possible. Such an approach using HSV vectors might also be applicable to other cell types for which transduction is as yet unreliable or of low efficiency.

Naive T lymphocytes exhibit extensive antigen-independent recirculation between blood and lymph nodes, where they may encounter dendritic cells carrying cognate antigen. We examine how long different T cells may spend in an individual lymph node by examining data from long term cannulation of blood and efferent lymphatics of a single lymph node in the sheep. We determine empirically the distribution of transit times of migrating T cells by applying the Least Absolute Shrinkage & Selection Operator (LASSO) or regularised S-LASSO to fit experimental data describing the proportion of labelled infused cells in blood and efferent lymphatics over time. The optimal inferred solution reveals a distribution with high variance and strong skew. The mode transit time is typically between 10 and 20 hours, but a significant number of cells spend more than 70 hours before exiting. We complement the empirical machine learning based approach by modelling lymphocyte passage through the lymph node insilico. On the basis of previous two photon analysis of lymphocyte movement, we optimised distributions which describe the transit times (first passage times) of discrete one dimensional and continuous (Brownian) three dimensional random walks with drift. The optimal fit is obtained when drift is small, i.e. the ratio of probabilities of migrating forward and backward within the node is close to one. These distributions are qualitatively similar to the inferred empirical distribution, with high variance and strong skew. In contrast, an optimised normal distribution of transit times (symmetrical around mean) fitted the data poorly. The results demonstrate that the rapid recirculation of lymphocytes observed at a macro level is compatible with predominantly randomised movement within lymph nodes, and significant probabilities of long transit times. We discuss how this pattern of migration may contribute to facilitating interactions between low frequency T cells and antigen presenting cells carrying cognate antigen.

Introduction and Objectives Differentiating tuberculosis and sarcoidosis can be difficult, particularly in the context of mediastinal lymphadenopathy, because both diseases are characterised by overlapping clinical phenotypes and histologically similar granulomatous inflammation. Currently, diagnosis relies heavily on microbiological confirmation of tuberculosis which is only available in