Cindy Desmarais

Using synthetic templates to design an unbiased multiplex PCR assay

T and B cell receptor loci undergo combinatorial rearrangement, generating a diverse immune receptor repertoire, which is vital for recognition of potential antigens. Here we use a multiplex PCR with a mixture of primers targeting the rearranged variable and joining segments to capture receptor diversity. Differential hybridization kinetics can introduce significant amplification biases that alter the composition of sequence libraries prepared by multiplex PCR. Using a synthetic immune receptor repertoire, we identify and minimize such biases and computationally remove residual bias after sequencing. We apply this method to a multiplex T cell receptor gamma sequencing assay. To demonstrate accuracy in a biological setting, we apply the method to monitor minimal residual disease in acute lymphoblastic leukaemia patients. A similar methodology can be extended to any adaptive immune locus.

Ultra-sensitive detection of rare T cell clones

Advances in high-throughput sequencing have enabled technologies that probe the adaptive immune system with unprecedented depth. We have developed a multiplex PCR method to sequence tens of millions of T cell receptors (TCRs) from a single sample in a few days. A method is presented to test the precision, accuracy, and sensitivity of this assay. T cell clones, each with one fixed productive TCR rearrangement, are doped into complex blood cell samples. TCRs from a total of eleven samples are sequenced, with the doped T cell clones ranging from 10% of the total sample to 0.001% (one cell in 100,000). The assay is able to detect even the rarest clones. The precision of the assay is demonstrated across five orders of magnitude. The accuracy for each clone is within an overall factor of three across the 100,000 fold dynamic range. Additionally, the assay is shown to be highly repeatable.

Intramuscular Therapeutic Vaccination Targeting HPV16 Induces T Cell Responses That Localize in Mucosal Lesions

T helper 1 (TH1) immune responses are detectable in target lesions after therapeutic vaccination. Putting Cancer Vaccines in Context Despite the notable success of vaccines for infectious diseases, cancer vaccines remain a challenge. Cancer vaccines must overcome many hurdles, including an immunosuppressive tumor microenvironment, antigenic similarity to healthy cells, and the vast diversity of cancer types and origins. Even vaccines that target infection-induced cancer, such as for cervical intraepithelial neoplasias (CINs) caused by human papillomavirus (HPV), have had limited success at inducing peripheral blood T cell responses. Now, Maldonado et al. suggest that peripheral therapeutic vaccination to HPV can induce a tissue-localized effector immune response. The authors hypothesized that context was important when looking for immune responses to the therapeutic HPV vaccine. Although CIN patients had only modest changes in the immune response in the blood, these changes were much more pronounced in the target lesion microenvironment. They found evidence of immune proliferation and activation in the CIN lesions that was not detectible in peripheral blood. These data suggest that some early vaccine “failures,” which are often determined by peripheral blood T cells response, may not be failures at all and that looking in the target lesion may be the best place to determine vaccine response. About 25% of high-grade cervical intraepithelial neoplasias (CIN2/3) caused by human papillomavirus serotype 16 (HPV16) undergo complete spontaneous regression. However, to date, therapeutic vaccination strategies for HPV disease have yielded limited success when measured by their ability to induce robust peripheral blood T cell responses to vaccine antigen. We report marked immunologic changes in the target lesion microenvironment after intramuscular therapeutic vaccination targeting HPV16 E6/E7 antigens, in subjects with CIN2/3 who had modest detectable responses in circulating T lymphocytes. Histologic and molecular changes, including markedly (average threefold) increased intensity of CD8+ T cell infiltrates in both the stromal and epithelial compartments, suggest an effector response to vaccination. Postvaccination cervical tissue immune infiltrates included organized tertiary lymphoid-like structures in the stroma subjacent to residual intraepithelial lesions and, unlike infiltrates in unvaccinated lesions, showed evidence of proliferation induced by recognition of cognate antigen. At a molecular level, these histologic changes in the stroma were characterized by increased expression of genes associated with immune activation (CXCR3) and effector function (Tbet and IFNβ), and were also associated with an immunologic signature in the overlying dysplastic epithelium. High-throughput T cell receptor sequencing of unmanipulated specimens identified clonal expansions in the tissue that were not readily detectable in peripheral blood. Together, these findings indicate that peripheral therapeutic vaccination to HPV antigens can induce a robust tissue-localized effector immune response, and that analyses of immune responses at sites of antigen are likely to be much more informative than analyses of cells that remain in the circulation.

Common clonal origin of central and resident memory T cells following skin immunization

Central memory T (TCM) cells in lymph nodes (LNs) and resident memory T (TRM) cells in peripheral tissues have distinct roles in protective immunity. Both are generated after primary infections, but their clonal origins have been unclear. To address this question, we immunized mice through the skin with a protein antigen, a chemical hapten, or a non-replicating poxvirus. We then analyzed antigen-activated T cells from different tissues using high-throughput sequencing (HTS) of the gene encoding the T cell receptor (TCR) β-chain (Trb, also known as Tcrb) using CDR3 sequences to simultaneously track thousands of unique T cells. For every abundant TRM cell clone generated in the skin, an abundant TCM cell clone bearing the identical TCR was present in the LNs. Thus, antigen-reactive skin TRM and LN TCM cell clones were derived from a common naive T cell precursor after skin immunization, generating overlapping TCR repertoires. Although they bore the same TCR, TRM cells mediated rapid contact hypersensitivity responses, whereas TCM cells mediated delayed and attenuated responses. Studies in human subjects confirmed the generation of skin TRM cells in allergic contact dermatitis. Thus, immunization through skin simultaneously generates skin TRM and LN TCM cells in similar numbers from the same naive T cells.

Deep Sequencing of the Human TCRγ and TCRβ Repertoires Suggests that TCRβ Rearranges After αβ and γδ T Cell Commitment

Deep sequencing provides new insights about T cell receptor rearrangement in humans. Feng Shui for T Cells In the ancient art of feng shui, buildings and even furniture are rearranged to more auspicious orientations. Lymphocytes are the feng shui masters of the immune system. Unlike other cells, which distinguish themselves by differentially expressing certain genes, T lymphocytes and other cells of the adaptive immune system actively rearrange their DNA, cutting and splicing different parts of their antigen receptor genes to respond to the vast number of pathogens that can attack the body. It has been long thought that for T lymphocytes, functional T cell receptor (TCR) chain rearrangement was required for T cell commitment to a particular lineage and function. Sherwood et al. now use deep sequencing of the repertoires of two chains of the TCR, TCRγ and TCRβ, to show that TCRβ may rearrange after lineage commitment. The two main lineages of T cells are classified based on their TCR usage: αβ and γδ T cells. These cells have different functions and are found in different locations in the body: αβ T cells respond to peptides presented in the context of human leukocyte antigen (HLA) molecules and are the predominant T cells in the blood, whereas γδ T cells may not bind HLA-peptide complexes and are found frequently in the lining of the gut. It had previously been thought that TCRβ, γ, and δ chains all rearranged before a T cell’s commitment to one or the other lineage, which suggests a decisive role for rearrangement in the commitment choice. However, Sherwood et al. show through deep sequencing of millions of TCRs in either γδ or αβ T cells that although TCRγ is rearranged in all T lymphocytes, TCRβ is rearranged only in less than 4% of γδ T cells. These data suggest that TCRβ rearrangement may not be required for lineage commitment after all. Moreover, they see both common and diverse TCR rearrangements in γδ T cells, which indicate possible adaptive- and innate-like roles for these two populations. Thus, TCR rearrangement may not only increase TCR diversity but also guide function as well. After all, what could be more auspicious than a healthy immune system? T lymphocytes respond to a broad array of pathogens with the combinatorial diversity of the T cell receptor (TCR). This adaptive response is possible because of the unique structure of the TCR, which is composed of two chains, either αβ or γδ, that undergo genetic rearrangement in the thymus. αβ and γδ T cells are functionally distinct within the host but are derived from a common multipotent precursor. The canonical model for T cell lineage commitment assumes that the γ, δ, and β chains rearrange before αβ or γδ T cell commitment. To test the standard model in humans, we used high-throughput sequencing to catalog millions of TCRγ and TCRβ chains from peripheral blood αβ and γδ T cells from three unrelated individuals. Almost all sampled αβ and γδ T cells had rearranged TCRγ sequences. Although sampled αβ T cells had a diverse repertoire of rearranged TCRβ chains, less than 4% of γδ T cells in peripheral blood had a rearranged TCRβ chain. Our data suggest that TCRγ rearranges in all T lymphocytes, consistent with TCRγ rearranging before T cell lineage commitment. However, rearrangement of the TCRβ locus appears to be restricted after T cell precursors commit to the αβ T cell lineage. Indeed, in T cell leukemias and lymphomas, TCRγ is almost always rearranged and TCRβ is only rearranged in a subset of cancers. Because high-throughput sequencing of TCRs is translated into the clinic for monitoring minimal residual for leukemia/lymphoma, our data suggest the sequencing target should be TCRγ.

Polymorphisms of the IL1-Receptor Antagonist Gene (IL1RN) Are Associated With Multiple Markers of Systemic Inflammation

Background—Circulating levels of acute phase reactant proteins such as plasma C-reactive protein (CRP) are likely influenced by multiple genes regulating the innate immune response. Methods and Results—We screened a set of 16 inflammation-related genes for association with CRP in a large population-based study of healthy young adults (n=1627). Results were validated in 2 independent studies (n=1208 and n=4310), including a pooled analysis of all 3 studies. In the pooled analysis, the minor allele of IL1RN 1018 (rs4251961) within the gene encoding interleukin (IL)-1 receptor antagonist (IL-1RA) was significantly associated with higher mean plasma log(CRP) level (P<1×10−4). The same IL1RN 1018 allele was associated with higher mean plasma log(IL-6) levels (P=0.004). In the pooled analysis, the minor allele of IL1RN 13888 (rs2232354) was associated with higher fibrinogen, (P=0.001). The IL1RN 1018 and 13888 variant alleles tag a clade of IL1RN haplotypes linked to allele 1 of an 86-bp VNTR polymorphism. We confirmed that the IL1RN 1018 variant (rs4251961) was associated with decreased cellular IL-1RA production ex vivo. Conclusions—Common functional polymorphisms of the IL1RN gene are associated with several markers of systemic inflammation.

IgH-V(D)J NGS-MRD measurement pre- and early post-allotransplant defines very low- and very high-risk ALL patients.

Positive detection of minimal residual disease (MRD) by multichannel flow cytometry (MFC) prior to hematopoietic cell transplantation (HCT) of patients with acute lymphoblastic leukemia (ALL) identifies patients at high risk for relapse, but many pre-HCT MFC-MRD negative patients also relapse, and the predictive power MFC-MRD early post-HCT is poor. To test whether the increased sensitivity of next-generation sequencing (NGS)-MRD better identifies pre- and post-HCT relapse risk, we performed immunoglobulin heavy chain (IgH) variable, diversity, and joining (V[D]J) DNA sequences J NGS-MRD on 56 patients with B-cell ALL enrolled in Childrens Oncology Group trial ASCT0431. NGS-MRD predicted relapse and survival more accurately than MFC-MRD (P < .0001), especially in the MRD negative cohort (relapse, 0% vs 16%; P = .02; 2-year overall survival, 96% vs 77%; P = .003). Post-HCT NGS-MRD detection was better at predicting relapse than MFC-MRD (P < .0001), especially early after HCT (day 30 MFC-MRD positive relapse rate, 35%; NGS-MRD positive relapse rate, 67%; P = .004). Any post-HCT NGS positivity resulted in an increase in relapse risk by multivariate analysis (hazard ratio, 7.7; P = .05). Absence of detectable IgH-V(D)J NGS-MRD pre-HCT defines good-risk patients potentially eligible for less intense treatment approaches. Post-HCT NGS-MRD is highly predictive of relapse and survival, suggesting a role for this technique in defining patients early who would be eligible for post-HCT interventions. The trial was registered at www.clinicaltrials.gov as #NCT00382109.

CMV reactivation drives posttransplant T-cell reconstitution and results in defects in the underlying TCRβ repertoire

Although cytomegalovirus (CMV) reactivation has long been implicated in posttransplant immune dysfunction, the molecular mechanisms that drive this phenomenon remain undetermined. To address this, we combined multiparameter flow cytometric analysis and T-cell subpopulation sorting with high-throughput sequencing of the T-cell repertoire, to produce a thorough evaluation of the impact of CMV reactivation on T-cell reconstitution after unrelated-donor hematopoietic stem cell transplant. We observed that CMV reactivation drove a >50-fold specific expansion of Granzyme B(high)/CD28(low)/CD57(high)/CD8(+) effector memory T cells (Tem) and resulted in a linked contraction of all naive T cells, including CD31(+)/CD4(+) putative thymic emigrants. T-cell receptor β (TCRβ) deep sequencing revealed a striking contraction of CD8(+) Tem diversity due to CMV-specific clonal expansions in reactivating patients. In addition to querying the topography of the expanding CMV-specific T-cell clones, deep sequencing allowed us, for the first time, to exhaustively evaluate the underlying TCR repertoire. Our results reveal new evidence for significant defects in the underlying CD8 Tem TCR repertoire in patients who reactivate CMV, providing the first molecular evidence that, in addition to driving expansion of virus-specific cells, CMV reactivation has a detrimental impact on the integrity and heterogeneity of the rest of the T-cell repertoire. This trial was registered at www.clinicaltrials.gov as #NCT01012492.

Fractal Organization of the Human T Cell Repertoire in Health and after Stem Cell Transplantation

T cell repertoire diversity is generated in part by recombination of variable (V), diversity (D), and joining (J) segments in the T cell receptor β (TCR) locus. T cell clonal frequency distribution determined by high-throughput sequencing of TCR β in 10 stem cell transplantation (SCT) donors revealed a fractal, self-similar frequency distribution of unique TCR bearing clones with respect to V, D, and J segment usage in the T cell repertoire of these individuals. Further, ranking of T cell clones by frequency of gene segment usage in the observed sequences revealed an ordered distribution of dominant clones conforming to a power law, with a fractal dimension of 1.6 and 1.8 in TCR β DJ and VDJ containing clones in healthy stem cell donors. This self-similar distribution was perturbed in the recipients after SCT, with patients demonstrating a lower level of complexity in their TCR repertoire at day 100 followed by a modest improvement by 1 year post-SCT. A large shift was observed in the frequency distribution of the dominant T cell clones compared to the donor, with fewer than one third of the VDJ-containing clones shared in the top 4 ranks. In conclusion, the normal T cell repertoire is highly ordered with a TCR gene segment usage that results in a fractal self-similar motif of pattern repetition across levels of organization. Fractal analysis of high-throughput TCR β sequencing data provides a comprehensive measure of immune reconstitution after SCT.

The Restricted DH Gene Reading Frame Usage in the Expressed Human Antibody Repertoire Is Selected Based upon its Amino Acid Content

The Ab repertoire is not uniform. Some variable, diversity, and joining genes are used more frequently than others. Nonuniform usage can result from the rearrangement process, or from selection. To study how the Ab repertoire is selected, we analyzed one part of diversity generation that cannot be driven by the rearrangement mechanism: the reading frame usage of DH genes. We have used two high-throughput sequencing methodologies, multiple subjects and advanced algorithms to measure the DH reading frame usage in the human Ab repertoire. In most DH genes, a single reading frame is used predominantly, and inverted reading frames are practically never observed. The choice of a single DH reading frame is not limited to a single position of the DH gene. Rather, each DH gene participates in rearrangements of differing CDR3 lengths, restricted to multiples of three. In nonproductive rearrangements, there is practically no reading frame bias, but there is still a striking absence of inversions. Biases in DH reading frame usage are more pronounced, but also exhibit greater interindividual variation, in IgG+ and IgA+ than in IgM+ B cells. These results suggest that there are two developmental checkpoints of DH reading frame selection. The first occurs during VDJ recombination, when inverted DH genes are usually avoided. The second checkpoint occurs after rearrangement, once the BCR is expressed. The second checkpoint implies that DH reading frames are subjected to differential selection. Following these checkpoints, clonal selection induces a host-specific DH reading frame usage bias.