A Conserved TCRβ Signature Dominates a Highly Polyclonal T-Cell Expansion During the Acute Phase of a Murine Malaria Infection

A systematic analysis of the human immune response to Plasmodium vivax

BACKGROUNDThe biology of Plasmodium vivax is markedly different from that of P. falciparum; how this shapes the immune response to infection remains unclear. To address this shortfall, we inoculated human volunteers with a clonal field isolate of P. vivax and tracked their response through infection and convalescence.METHODSParticipants were injected intravenously with blood-stage parasites and infection dynamics were tracked in real time by quantitative PCR. Whole blood samples were used for high dimensional protein analysis, RNA sequencing, and cytometry by time of flight, and temporal changes in the host response to P. vivax were quantified by linear regression. Comparative analyses with P. falciparum were then undertaken using analogous data sets derived from prior controlled human malaria infection studies.RESULTSP. vivax rapidly induced a type I inflammatory response that coincided with hallmark features of clinical malaria. This acute-phase response shared remarkable overlap with that induced by P. falciparum but was significantly elevated (at RNA and protein levels), leading to an increased incidence of pyrexia. In contrast, T cell activation and terminal differentiation were significantly increased in volunteers infected with P. falciparum. Heterogeneous CD4+ T cells were found to dominate this adaptive response and phenotypic analysis revealed unexpected features normally associated with cytotoxicity and autoinflammatory disease.CONCLUSIONP. vivax triggers increased systemic interferon signaling (cf P. falciparum), which likely explains its reduced pyrogenic threshold. In contrast, P. falciparum drives T cell activation far in excess of P. vivax, which may partially explain why falciparum malaria more frequently causes severe disease.TRIAL REGISTRATIONClinicalTrials.gov NCT03797989.FUNDINGThe European Union's Horizon 2020 Research and Innovation programme, the Wellcome Trust, and the Royal Society.

Exploiting big data survival information to unify risk-stratification related, adaptive immune receptor parameters for multiple myeloma

With the improvement of treatment options, multiple myeloma related life expectancy has been prolonged, but the disease remains largely incurable. Immunotherapy is a growing field that shows promise in advancements for treatment, and recent work has demonstrated an opportunity to use immune receptor, complementarity determining region-3 (CDR3)-candidate antigen chemical complementarity scores to identify survival distinctions among subgroups of patients. Here, we have applied the complementarity scoring algorithm to identify multiple myeloma related, CDR3-cancer testis antigen (CTA) relationships associated with survival distinctions. Furthermore, we have overlapped these immune receptor features with a previous study that showed a dramatic survival distinction based on T-cell receptor, V- and J-gene segment usage, HLA allele combinations, whereby 100% of the patients in certain combination groups had no mortality related to multiple myeloma, during the study period. This overlap evaluation was consistent with the idea that there are likely considerable constraints on productive TRB-antigen-HLA combinations but more flexibility, and unpredictability, for the TRA-antigen-HLA combinations. Also, the approaches in this reported indicated the potential importance of the CTA, IGSF11, as a multiple myeloma antigen, an antigen previously, independently considered as a vaccine candidate in other settings.

TRB CDR3-cancer testis antigen chemical complementarity scoring for identifying productive immune responses in renal cell carcinoma

BACKGROUND

Immunogenomics approaches to the characterization of renal cell carcinoma (RCC) have helped to better our understanding of the features of RCC immune dysfunction. However, much is still unknown with regard to specific immune interactions and their impact in the tumor microenvironment.

OBJECTIVE

This study applied chemical complementarity scoring for the TRB complementarity determining region-3 (CDR3) amino acid sequences and cancer testis antigens (CTAs) to determine whether such complementarity correlated with survival and the expression of immune marker genes.

METHODS

TRB recombination reads from RCC tumor samples from RNAseq files obtained from two separate databases, Moffitt Cancer Center and The Cancer Genome Atlas (TCGA), were evaluated. Chemical complementarity scores (CSs) were calculated for TRB CDR3-CTA pairs and survival assessments based on those CSs were performed.

RESULTS

Moffitt Cancer Center and TCGA cases representing the upper 50th percentile of chemical CSs for TRB CDR3 amino acid sequences and the CTA POTEA were found to be associated with a better overall survival (OS) Also, greater tumor RNA expression of multiple immune signature genes, including granzyme A, granzyme B, and interferon-gamma were correlated with the higher chemical CSs.

CONCLUSIONS

These results indicate that TRB CDR3-CTA chemical complementarity scoring may be useful in distinguishing RCC cases with a productive, anti-tumor immune response from cases where basic immune parameter assessments are inconsistent with a productive immune response.

Perturbations in the T cell receptor β repertoire during malaria infection in children: A preliminary study

The changes occurring in the T cell repertoire during clinical malaria infection in children remain unknown. In this study, we undertook the first detailed comparative study of the T cell repertoire in African children with and without clinical malaria to test the hypothesis that clonotypic expansions that occur during P. falciparum infection will contribute to the generation of a T cell repertoire that is unique to each disease state. We profiled the complementarity-determining region 3 (CDR3) of the TCRβ chain sequences from children with Plasmodium falciparum infections (asymptomatic, uncomplicated and severe malaria) and compared these with sequences from healthy children. Interestingly, we discovered that children with symptomatic malaria have a lower TCR diversity and frequency of shared (or “public”) TCR sequences compared to asymptomatic children. Also, TCR diversity was inversely associated with parasitemia. Furthermore, by clustering TCR sequences based on their predicted antigen specificities, we identified a specificity cluster, with a 4-mer amino acid motif, that is overrepresented in the asymptomatic group compared to the diseased groups. Further investigations into this finding may help in delineating important antigenic targets for vaccine and therapeutic development. The results show that the T cell repertoire in children is altered during malaria, suggesting that exposure to P. falciparum antigens disrupts the adaptive immune response, which is an underlying feature of the disease.

T-Cell Receptor Repertoire Analysis with Computational Tools-An Immunologist's Perspective

Over the last few years, there has been a rapid expansion in the application of information technology to biological data. Particularly the field of immunology has seen great strides in recent years. The development of next-generation sequencing (NGS) and single-cell technologies also brought forth a revolution in the characterization of immune repertoires. T-cell receptor (TCR) repertoires carry comprehensive information on the history of an individual’s antigen exposure. They serve as correlates of host protection and tolerance, as well as biomarkers of immunological perturbation by natural infections, vaccines or immunotherapies. Their interrogation yields large amounts of data. This requires a suite of highly sophisticated bioinformatics tools to leverage the meaning and complexity of the large datasets. Many different tools and methods, specifically designed for various aspects of immunological research, have recently emerged. Thus, researchers are now confronted with the issue of having to choose the right kind of approach to analyze, visualize and ultimately solve their task at hand. In order to help immunologists to choose from the vastness of available tools for their data analysis, this review addresses and compares commonly used bioinformatics tools for TCR repertoire analysis and illustrates the advantages and limitations of these tools from an immunologist’s perspective.

Understanding the pathogenesis of infectious diseases by single-cell RNA sequencing

Infections are highly orchestrated and dynamic processes, which involve both pathogen and host. Transcriptional profiling at the single-cell level enables the analysis of cell diversity, heterogeneity of the immune response, and detailed molecular mechanisms underlying infectious diseases caused by bacteria, viruses, fungi, and parasites. Herein, we highlight recent remarkable advances in single-cell RNA sequencing (scRNA-seq) technologies and their applications in the investigation of host-pathogen interactions, current challenges and potential prospects for disease treatment are discussed as well. We propose that with the aid of scRNA-seq, the mechanism of infectious diseases will be further revealed thus inspiring the development of novel interventions and therapies.