High-throughput sequencing of the T-cell receptor repertoire: pitfalls and opportunities.

T-cell specificity is determined by the T-cell receptor, a heterodimeric protein coded for by an extremely diverse set of genes produced by imprecise somatic gene recombination. Massively parallel high-throughput sequencing allows millions of different T-cell receptor genes to be characterized from a single sample of blood or tissue. However, the extraordinary heterogeneity of the immune repertoire poses significant challenges for subsequent analysis of the data. We outline the major steps in processing of repertoire data, considering low-level processing of raw sequence files and high-level algorithms, which seek to extract biological or pathological information. The latest generation of bioinformatics tools allows millions of DNA sequences to be accurately and rapidly assigned to their respective variable V and J gene segments, and to reconstruct an almost error-free representation of the non-templated additions and deletions that occur. High-level processing can measure the diversity of the repertoire in different samples, quantify V and J usage and identify private and public T-cell receptors. Finally, we discuss the major challenge of linking T-cell receptor sequence to function, and specifically to antigen recognition. Sophisticated machine learning algorithms are being developed that can combine the paradoxical degeneracy and cross-reactivity of individual T-cell receptors with the specificity of the overall T-cell immune response. Computational analysis will provide the key to unlock the potential of the T-cell receptor repertoire to give insight into the fundamental biology of the adaptive immune system and to provide powerful biomarkers of disease

Clinical T Cell Receptor Repertoire Deep Sequencing and Analysis: An Application to Monitor Immune Reconstitution Following Cord Blood Transplantation

Spectratyping assays are well recognized as the clinical gold standard for assessing the T cell receptor (TCR) repertoire in haematopoietic stem cell transplant (HSCT) recipients. These assays use length distributions of the hyper variable complementarity-determining region 3 (CDR3) to characterize a patient's T cell immune reconstitution post-transplant. However, whilst useful, TCR spectratyping is notably limited by its resolution, with the technique unable to provide data on the individual clonotypes present in a sample. High-resolution clonotype data are necessary to provide quantitative clinical TCR assessments and to better understand clonotype dynamics during clinically relevant events such as viral infections or GvHD. In this study we developed and applied a CDR3 Next Generation Sequencing (NGS) methodology to assess the TCR repertoire in cord blood transplant (CBT) recipients. Using this, we obtained comprehensive TCR data from 16 CBT patients and 5 control cord samples at Great Ormond Street Hospital (GOSH). These were analyzed to provide a quantitative measurement of the TCR repertoire and its constituents in patients post-CBT. We were able to both recreate and quantify inferences typically drawn from spectratyping data. Additionally, we demonstrate that an NGS approach to TCR assessment can provide novel insights into the recovery of the immune system in these patients. We show that NGS can be used to accurately quantify TCR repertoire diversity and to provide valuable inference on clonotypes detected in a sample. We serially assessed the progress of T cell immune reconstitution demonstrating that there is dramatic variation in TCR diversity immediately following transplantation and that the dynamics of T cell immune reconstitution is perturbed by the presence of GvHD. These findings provide a proof of concept for the adoption of NGS TCR sequencing in clinical practice

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.</p

Human TCRs and CDR3s sequenced from healthy volunteers and HIV-infected patients, before and after 14 weeks of therapy

<p>We have employed an error-correcting, high-throughput transcript sequencing protocol to profile impact of HIV infection upon the T-cell receptor repertoire.</p> <p>We have sequences both alpha and beta chain TCR repertoires from 2.5ml of peripheral blood for 16 antiretroviral (ART)-naive HIV patients (de-identified reference numbers prefixed 'P0'). Two samples per patient were processed: one immediately before starting therapy ('v1') and another shortly after starting ('v2', after an average 14 weeks). We additionally sequenced the repertoires of ten healthy volunteers ('HV'), taking two blood samples three months apart for four of those donors (HV01 to HV04) in order to compare TCR dynamics over a comparable time frame. One of these healthy donors (HV01) and a further healthy donor (HVD1) also gave a larger blood sample, which was separated into CD4+ and CD8+ T-cell populations by FACS, and their TCR repertoires were seqeunced.</p> <p>Having amplified and sequenced the TCR repertoires of these 100 samples, we identified their VJ recombinations using a modified version of Decombinator (called vDCR), TCR analysis software designed in our lab. We then made use of random barcode sequences introduced before amplification to error- and frequency-correct our Decombinator assignations (DCRs), before translating them and extracting their complementarity determining region 3 (CDR3) sequences.</p> <p>Here we present the results of these analyses. The .dcrcdr3 files in this fileset consist of a unique DCR assignation per line, the CDR3 sequence it encodes, and the frequency with which that TCR appeared in the data following error-correction. Each line follows the format:</p> <p>'V, J, Vdel, Jdel, insert: CDR3, freq'</p> <p>(V = V gene, J = J gene, Vdel = number of deletions from V, Jdel = number of deletions from J, insert = string of nucleotides from the end of the deleted V to the start of the deleted J, CDR3 = translation CDR3 sequence, from the second conserved cysteine residue in the V to the conserved phenylalanine of the FGXG motif of the J, freq = error-corrected frequency of that assignation.)</p> <p>The raw sequence data fastq files from which these TCRs were extracted is available in the Sequence Read Archive (SRA) under the Study accession number SRP045430. The AccessionKey.xls spreadsheet cross-references all filenames with their appropriate SRA individual accession numbers.</p> <p>The Python scripts which were used to generate this data from that raw fastq data are also available on figshare (see links below).</p

Idiosyncratic T-cell receptor repertoire perturbation and loss of diversity in HIV+ individuals revealed by deep-sequencing

We have developed a protocol that combines unbiased amplification, high-throughput DNA sequencing and error-correcting bioinformatic protocols to extract T-cell receptor (TCR) repertoire data from small, easily collected samples of unfractionated blood. We have applied this protocol to study the effect of HIV infection (and subsequent treatment) upon TCR repertoires. <p>Whole blood samples were collected from 16 HIV+ patients immediately before, and shortly after commencing antiretroviral therapy (ART): repertoires were sequenced and compared to those of ten healthy controls.</p> <p>The TCR repertoires of HIV-infected individuals were highly perturbed, showing a considerable loss of diversity relative to controls primarily through accumulation of a small number of very highly-expanded sequences. </p> <p><a></a> TCR sequences in HIV patients' repertoires diverged in their TCR gene usage, both from uninfected donors and from one another. Sequences were also more likely to be retained in HIV+ individuals during ART than those in healthy donors over the same period, but were less likely to be shared between individuals, demonstrating comparatively highly individualistic TCR repertoires. Moreover the majority of dysregulated repertoire features failed to revert to healthy parameter ranges over the short course of therapy between samples, despite a significant increase in CD4+ T-cell levels.</p> <p>Repertoires were also searched for sequences belonging to published invariant or epitope-specific TCRs, revealing significantly fewer mucosally associated invariant T (MAIT) cell sequences in HIV patients relative to controls, and a loss of HIV-associated CDR3s during treatment.</p> <p>TCR repertoire sequencing of HIV infected individuals is therefore able to produce qualitative and quantitative data pertaining to a variety of perturbations to patient immune systems, which could inform treatment and potentially lead to development of biomarkers for patient stratification.</p

The naive t-cell receptor repertoire has an extremely broad distribution of clone sizes

The clone size distribution of the human naive T-cell receptor (TCR) repertoire is an important determinant of adaptive immunity. We estimated the abundance of TCR sequences in samples of naive T cells from blood using an accurate quantitative sequencing protocol. We observe most TCR sequences only once, consistent with the enormous diversity of the repertoire. However, a substantial number of sequences were observed multiple times. We detect abundant TCR sequences even after exclusion of methodological confounders such as sort contamination, and multiple mRNA sampling from the same cell. By combining experimental data with predictions from models we describe two mechanisms contributing to TCR sequence abundance. TCRa abundant sequences can be primarily attributed to many identical recombination events in different cells, while abundant TCRb sequences are primarily derived from large clones, which make up a small percentage of the naive repertoire, and could be established early in the development of the T-cell repertoire

The naive t-cell receptor repertoire has an extremely broad distribution of clone sizes

The clone size distribution of the human naive T-cell receptor (TCR) repertoire is an important determinant of adaptive immunity. We estimated the abundance of TCR sequences in samples of naive T cells from blood using an accurate quantitative sequencing protocol. We observe most TCR sequences only once, consistent with the enormous diversity of the repertoire. However, a substantial number of sequences were observed multiple times. We detect abundant TCR sequences even after exclusion of methodological confounders such as sort contamination, and multiple mRNA sampling from the same cell. By combining experimental data with predictions from models we describe two mechanisms contributing to TCR sequence abundance. TCRa abundant sequences can be primarily attributed to many identical recombination events in different cells, while abundant TCRb sequences are primarily derived from large clones, which make up a small percentage of the naive repertoire, and could be established early in the development of the T-cell repertoire

Quantitative Characterization of the T Cell Receptor Repertoire of Naïve and Memory Subsets Using an Integrated Experimental and Computational Pipeline Which Is Robust, Economical, and Versatile

The T cell receptor (TCR) repertoire can provide a personalized biomarker for infectious and non-infectious diseases. We describe a protocol for amplifying, sequencing, and analyzing TCRs which is robust, sensitive, and versatile. The key experimental step is ligation of a single-stranded oligonucleotide to the 3′ end of the TCR cDNA. This allows amplification of all possible rearrangements using a single set of primers per locus. It also introduces a unique molecular identifier to label each starting cDNA molecule. This molecular identifier is used to correct for sequence errors and for effects of differential PCR amplification efficiency, thus producing more accurate measures of the true TCR frequency within the sample. This integrated experimental and computational pipeline is applied to the analysis of human memory and naive subpopulations, and results in consistent measures of diversity and inequality. After error correction, the distribution of TCR sequence abundance in all subpopulations followed a power law over a wide range of values. The power law exponent differed between naïve and memory populations, but was consistent between individuals. The integrated experimental and analysis pipeline we describe is appropriate to studies of T cell responses in a broad range of physiological and pathological contexts

Offentlig upphandling i praktiken : en fallstudie av Brommageriatriken AB

Rapporten belyser ett exempel på praktisk tillämpning av upphandlingsförfarandet inom vård och omsorg. Fallet som skildras är en geriatrisk klinik i Stockholm, Brommageriatriken AB, från och med tiden innan företaget blivit personal ägt till och med våren 2007 då det efter en förlorad upphandling köptes upp av upphandlingsvinnaren. Fallstudien baseras på ett antal offentliga dokument, tidningsartiklar och åtta intervjuer med representanterna för samtliga inblandade parter: Brommageriatriken AB, Stockholms läns landsting och Stiftelsen Stockholms sjukhem som vann upphandlingen. Bilden ges att beslutet att upphandla offentlig verksamhet ofta medför ekonomiska problem för det upphandlade företaget som på kort tid får ställa om sin verksamhet till marknadsmässiga villkor. Vidare, om företaget förlorar upphandlingen om sin egen verksamhet vid ett senare tillfälle kan det riskera att avvecklas. Sist men inte minst är det främst stora och kapitalstarka aktörer som gynnas vid upphandlingsförfarandet då de kan erbjuda lägre pris på anbudet samt riskerar mindre vid en eventuell upphandlingsförlust