Putting computational models of immunity to the test-An invited challenge to predict B.pertussis vaccination responses.

Systems vaccinology studies have been used to build computational models that predict individual vaccine responses and identify the factors contributing to differences in outcome. Comparing such models is challenging due to variability in study designs. To address this, we established a community resource to compare models predicting B.

Putting computational models of immunity to the test - an invited challenge to predict vaccination outcomes.

Systems vaccinology studies have been used to build computational models that predict individual vaccine responses and identify the factors contributing to differences in outcome. Comparing such models is challenging due to variability in study designs. To address this, we established a community resource to compare models predicting booster responses and generate experimental data for the explicit purpose of model evaluation.

The receiver operating characteristic curve accurately assesses imbalanced datasets.

Many problems in biology require looking for a "needle in a haystack," corresponding to a binary classification where there are a few positives within a much larger set of negatives, which is referred to as a class imbalance. The receiver operating characteristic (ROC) curve and the associated area under the curve (AUC) have been reported as ill-suited to evaluate prediction performance on imbalanced problems where there is more interest in performance on the positive minority class, while the precision-recall (PR) curve is preferable. We show via simulation and a real case study that this is a misinterpretation of the difference between the ROC and PR spaces, showing that the ROC curve is robust to class imbalance, while the PR curve is highly sensitive to class imbalance.

Next-generation IEDB tools: a platform for epitope prediction and analysis.

The Next-Generation (NG) IEDB Tools website (https://nextgen-tools.iedb.org) provides users with a redesigned interface to many of the algorithms for epitope prediction and analysis that were originally released on the legacy IEDB Tools website.

A multi-omics systems vaccinology resource to develop and test computational models of immunity.

Systems vaccinology studies have identified factors affecting individual vaccine responses, but comparing these findings is challenging due to varying study designs. To address this lack of reproducibility, we established a community resource for comparing Bordetella pertussis booster responses and to host annual contests for predicting patients' vaccination outcomes. We report here on our experiences with the "dry-run" prediction contest.

Late-rising CD4 T cells resolve mouse cytomegalovirus persistent replication in the salivary gland.

Conventional antiviral memory CD4 T cells typically arise during the first two weeks of acute infection. Unlike most viruses, cytomegalovirus (CMV) exhibits an extended persistent replication phase followed by lifelong latency accompanied with some gene expression. We show that during mouse CMV (MCMV) infection, CD4 T cells recognizing an epitope derived from the viral M09 protein only develop after conventional memory T cells have already peaked and contracted.

Intra-tumoral T cells in pediatric brain tumors display clonal expansion and effector properties.

Brain tumors in children are a devastating disease in a high proportion of patients. Owing to inconsistent results in clinical trials in unstratified patients, the role of immunotherapy remains unclear. We performed an in-depth survey of the single-cell transcriptomes and clonal relationship of intra-tumoral T cells from children with brain tumors.

PEPMatch: a tool to identify short peptide sequence matches in large sets of proteins.

Background: Numerous tools exist for biological sequence comparisons and search. One case of particular interest for immunologists is finding matches for linear peptide T cell epitopes, typically between 8 and 15 residues in length, in a large set of protein sequences. Both to find exact matches or matches that account for residue substitutions.

A systems vaccinology resource to develop and test computational models of immunity.

Computational models that predict an individual's response to a vaccine offer the potential for mechanistic insights and personalized vaccination strategies. These models are increasingly derived from systems vaccinology studies that generate immune profiles from human cohorts pre- and post-vaccination. Most of these studies involve relatively small cohorts and profile the response to a single vaccine.

Linked CD4+/CD8+ T cell neoantigen vaccination overcomes immune checkpoint blockade resistance and enables tumor regression.

Therapeutic benefit to immune checkpoint blockade (ICB) is currently limited to the subset of cancers thought to possess a sufficient tumor mutational burden (TMB) to allow for the spontaneous recognition of neoantigens (NeoAg) by autologous T cells. We explored whether the response to ICB of an aggressive low-TMB squamous cell tumor could be improved through combination immunotherapy using functionally defined NeoAg as targets for endogenous CD4+ and CD8+ T cells. We found that, whereas vaccination with CD4+ or CD8+ NeoAg alone did not offer prophylactic or therapeutic immunity, vaccines containing NeoAg recognized by both subsets overcame ICB resistance and led to the eradication of large established tumors that contained a subset of PD-L1+ tumor-initiating cancer stem cells (tCSC), provided the relevant epitopes were physically linked.

Linked CD4 /CD8 T cell neoantigen vaccination overcomes immune checkpoint blockade resistance and enables tumor regression.

Therapeutic benefit to immune checkpoint blockade (ICB) is currently limited to the subset of cancers thought to possess a sufficient tumor mutational burden (TMB) to allow for the spontaneous recognition of neoantigens (NeoAg) by autologous T cells. We explored whether the response of an aggressive low TMB squamous cell tumor to ICB could be improved through combination immunotherapy using functionally defined NeoAg as targets for endogenous CD4 and CD8 T cells. We found that, whereas vaccination with CD4 or CD8 NeoAg alone did not offer prophylactic or therapeutic immunity, vaccines containing NeoAg recognized by both subsets overcame ICB resistance and led to the eradication of large established tumors that contained a subset of PD-L1 tumor-initiating cancer stem cells (tCSC), provided the relevant epitopes were physically linked.

Coronavirus Immunotherapeutic Consortium Database.

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has seen multiple anti-SARS-CoV-2 antibodies being generated globally. It is difficult, however, to assemble a useful compendium of these biological properties if they are derived from experimental measurements performed at different sites under different experimental conditions. The Coronavirus Immunotherapeutic Consortium (COVIC) circumvents these issues by experimentally testing blinded antibodies side by side for several functional activities.

Estimating tissue-specific peptide abundance from public RNA-Seq data.

Several novel MHC class I epitope prediction tools additionally incorporate the abundance levels of the peptides' source antigens and have shown improved performance for predicting immunogenicity. Such tools require the user to input the MHC alleles and peptide sequences of interest, as well as the abundance levels of the peptides' source proteins. However, such expression data is often not directly available to users, and retrieving the expression level of a peptide's source antigen from public databases is not trivial.

Tumor cells fail to present MHC-II-restricted epitopes derived from oncogenes to CD4+ T cells.

CD4+ T cells play a critical role in antitumor immunity via recognition of peptide antigens presented on MHC class II (MHC-II). Although some solid cancers can be induced to express MHC-II, the extent to which this enables direct recognition by tumor-specific CD4+ T cells is unclear. We isolated and characterized T cell antigen receptors (TCRs) from naturally primed CD4+ T cells specific for 2 oncoproteins, HPV-16 E6 and the activating KRASG12V mutation, from patients with head and neck squamous cell carcinoma and pancreatic ductal adenocarcinoma, respectively, and determined their ability to recognize autologous or human leukocyte antigen-matched antigen-expressing tumor cells.

A comprehensive analysis of the IEDB MHC class-I automated benchmark.

In 2014, the Immune Epitope Database automated benchmark was created to compare the performance of the MHC class I binding predictors. However, this is not a straightforward process due to the different and non-standardized outputs of the methods. Additionally, some methods are more restrictive regarding the HLA alleles and epitope sizes for which they predict binding affinities, while others are more comprehensive.

Distinguishing cell-cell complexes from dual lineage cells using single-cell transcriptomics is not trivial.

In their recent correspondence, Jie et al. strongly defend that the DE cell population they discovered are always dual lineage co-expressing cells and not complexes of B cells and T cells, which we have previously described as frequently present in single-cell RNA sequencing data. Here, we respond to the specific arguments made in their correspondence.

Developmentally distinct CD4 T lineages shape the CD8 T cell response to acute infection.

SignificanceThe CD4 T response following acute infection is heterogeneous and deploys two distinct modes of suppression coinciding with initial pathogen exposure and resolution of infection. This bimodal suppression of CD8 T cells during priming and contraction is mediated by separate T lineages. These findings make a significant contribution to our understanding of the functional plasticity inherent within T, which allows these cells to serve as a sensitive and dynamic cellular rheostat for the immune system to prevent autoimmune pathology in the face of inflammation attendant to acute infection, enable expansion of the pathogen-specific response needed to control the infection, and reestablish immune homeostasis after the threat has been contained.

Single-cell eQTL analysis of activated T cell subsets reveals activation and cell type-dependent effects of disease-risk variants.

The impact of genetic variants on cells challenged in biologically relevant contexts has not been fully explored. Here, we activated CD4 T cells from 89 healthy donors and performed a single-cell RNA sequencing assay with >1 million cells to examine cell type-specific and activation-dependent effects of genetic variants. Single-cell expression quantitative trait loci (sc-eQTL) analysis of 19 distinct CD4 T cell subsets showed that the expression of over 4000 genes is significantly associated with common genetic polymorphisms and that most of these genes show their most prominent effects in specific cell types.

TCRMatch: Predicting T-Cell Receptor Specificity Based on Sequence Similarity to Previously Characterized Receptors.

The adaptive immune system in vertebrates has evolved to recognize non-self antigens, such as proteins expressed by infectious agents and mutated cancer cells. T cells play an important role in antigen recognition by expressing a diverse repertoire of antigen-specific receptors, which bind epitopes to mount targeted immune responses. Recent advances in high-throughput sequencing have enabled the routine generation of T-cell receptor (TCR) repertoire data.

Comprehensive analysis of T cell immunodominance and immunoprevalence of SARS-CoV-2 epitopes in COVID-19 cases.

T cells are involved in control of SARS-CoV-2 infection. To establish the patterns of immunodominance of different SARS-CoV-2 antigens and precisely measure virus-specific CD4 and CD8 T cells, we study epitope-specific T cell responses of 99 convalescent coronavirus disease 2019 (COVID-19) cases. The SARS-CoV-2 proteome is probed using 1,925 peptides spanning the entire genome, ensuring an unbiased coverage of human leukocyte antigen (HLA) alleles for class II responses.

Comprehensive analysis of T cell immunodominance and immunoprevalence of SARS-CoV-2 epitopes in COVID-19 cases.

T cells are involved in control of SARS-CoV-2 infection. To establish the patterns of immunodominance of different SARS-CoV-2 antigens, and precisely measure virus-specific CD4 and CD8 T cells, we studied epitope-specific T cell responses of approximately 100 convalescent COVID-19 cases. The SARS-CoV-2 proteome was probed using 1,925 peptides spanning the entire genome, ensuring an unbiased coverage of HLA alleles for class II responses.

A behind-the-scenes tour of the IEDB curation process: an optimized process empirically integrating automation and human curation efforts.

The Immune Epitope Database and Analysis Resource (IEDB) provides the scientific community with open access to epitope data, as well as epitope prediction and analysis tools. The IEDB houses the most extensive collection of experimentally validated B-cell and T-cell epitope data, sourced primarily from published literature by expert curation. The data procurement requires systematic identification, categorization, curation and quality-checking processes.

Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals.

Understanding adaptive immunity to SARS-CoV-2 is important for vaccine development, interpreting coronavirus disease 2019 (COVID-19) pathogenesis, and calibration of pandemic control measures. Using HLA class I and II predicted peptide "megapools," circulating SARS-CoV-2-specific CD8 and CD4 T cells were identified in ∼70% and 100% of COVID-19 convalescent patients, respectively. CD4 T cell responses to spike, the main target of most vaccine efforts, were robust and correlated with the magnitude of the anti-SARS-CoV-2 IgG and IgA titers.

TLR9 Sensing of Self-DNA Controls Cell-Mediated Immunity to Listeria Infection via Rapid Conversion of Conventional CD4 T Cells to T.

CD4 T lymphocytes are crucial for controlling a range of innate and adaptive immune effectors. For CD8 cytotoxic T lymphocyte (CTL) responses, CD4 T cells can function as helpers (T) to amplify magnitude and functionality or as regulatory cells (T) capable of profound inhibition. It is unclear what determines differentiation to these phenotypes and whether pathogens provoke alternate programs.