Understanding the constitutive presentation of MHC class I immunopeptidomes in primary tissues

Understanding the molecular principles that govern the composition of the MHC-I immunopeptidome across different primary tissues is fundamentally important to predict how T cells respond in different contexts in vivo. Here, we performed a global analysis of the MHC-I immunopeptidome from 29 to 19 primary human and mouse tissues, respectively. First, we observed that different HLA-A, HLA-B, and HLA-C allotypes do not contribute evenly to the global composition of the MHC-I immunopeptidome across multiple human tissues. Second, we found that tissue-specific and housekeeping MHC-I peptides share very distinct properties. Third, we discovered that proteins that are evolutionarily hyperconserved represent the primary source of the MHC-I immunopeptidome at the organism-wide scale. Fourth, we uncovered new components of the antigen processing and presentation network, including the carboxypeptidases CPE, CNDP1/2, and CPVL. Together, this study opens up new avenues toward a system-wide understanding of antigen presentation in vivo across mammalian species.

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Tissue-specific and housekeeping MHC class I peptides share distinct properties

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HLA-A, HLA-B, and HLA-C allotypes contribute very unevenly to the pool of class I peptides

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MHC-I immunopeptidomes are represented by evolutionarily conserved proteins

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An extended antigen processing and presentation pathway is uncovered

DIAproteomics: A Multifunctional Data Analysis Pipeline for Data-Independent Acquisition Proteomics and Peptidomics

Data-independent acquisition (DIA) is becoming a leading analysis method in biomedical mass spectrometry. The main advantages include greater reproducibility and sensitivity and a greater dynamic range compared with data-dependent acquisition (DDA). However, the data analysis is complex and often requires expert knowledge when dealing with large-scale data sets. Here we present DIAproteomics, a multifunctional, automated, high-throughput pipeline implemented in the Nextflow workflow management system that allows one to easily process proteomics and peptidomics DIA data sets on diverse compute infrastructures. The central components are well-established tools such as the OpenSwathWorkflow for the DIA spectral library search and PyProphet for the false discovery rate assessment. In addition, it provides options to generate spectral libraries from existing DDA data and to carry out the retention time and chromatogram alignment. The output includes annotated tables and diagnostic visualizations from the statistical postprocessing and computation of fold-changes across pairwise conditions, predefined in an experimental design. DIAproteomics is well documented open-source software and is available under a permissive license to the scientific community at https://www.openms.de/diaproteomics/.

HLA Ligand Atlas: a benign reference of HLA-presented peptides to improve T-cell-based cancer immunotherapy

BACKGROUND

The human leucocyte antigen (HLA) complex controls adaptive immunity by presenting defined fractions of the intracellular and extracellular protein content to immune cells. Understanding the benign HLA ligand repertoire is a prerequisite to define safe T-cell-based immunotherapies against cancer. Due to the poor availability of benign tissues, if available, normal tissue adjacent to the tumor has been used as a benign surrogate when defining tumor-associated antigens. However, this comparison has proven to be insufficient and even resulted in lethal outcomes. In order to match the tumor immunopeptidome with an equivalent counterpart, we created the HLA Ligand Atlas, the first extensive collection of paired HLA-I and HLA-II immunopeptidomes from 227 benign human tissue samples. This dataset facilitates a balanced comparison between tumor and benign tissues on HLA ligand level.

METHODS

Human tissue samples were obtained from 16 subjects at autopsy, five thymus samples and two ovary samples originating from living donors. HLA ligands were isolated via immunoaffinity purification and analyzed in over 1200 liquid chromatography mass spectrometry runs. Experimentally and computationally reproducible protocols were employed for data acquisition and processing.

RESULTS

The initial release covers 51 HLA-I and 86 HLA-II allotypes presenting 90,428 HLA-I- and 142,625 HLA-II ligands. The HLA allotypes are representative for the world population. We observe that immunopeptidomes differ considerably between tissues and individuals on source protein and HLA-ligand level. Moreover, we discover 1407 HLA-I ligands from non-canonical genomic regions. Such peptides were previously described in tumors, peripheral blood mononuclear cells (PBMCs), healthy lung tissues and cell lines. In a case study in glioblastoma, we show that potential on-target off-tumor adverse events in immunotherapy can be avoided by comparing tumor immunopeptidomes to the provided multi-tissue reference.

CONCLUSION

Given that T-cell-based immunotherapies, such as CAR-T cells, affinity-enhanced T cell transfer, cancer vaccines and immune checkpoint inhibition, have significant side effects, the HLA Ligand Atlas is the first step toward defining tumor-associated targets with an improved safety profile. The resource provides insights into basic and applied immune-associated questions in the context of cancer immunotherapy, infection, transplantation, allergy and autoimmunity. It is publicly available and can be browsed in an easy-to-use web interface at https://hla-ligand-atlas.org .

Association between Subcutaneous Adipose Tissue Inflammation, Insulin Resistance, and Calorie Restriction in Obese Females

The worldwide epidemic of overweight and obesity has led to an increase in associated metabolic comorbidities. Obesity induces chronic low-grade inflammation in white adipose tissue (WAT). However, the function and regulation of both innate and adaptive immune cells in human WAT under conditions of obesity and calorie restriction (CR) is not fully understood yet. Using a randomized interventional design, we investigated postmenopausal overweight or obese female subjects who either underwent CR for 3 mo followed by a 4-wk phase of weight maintenance or had to maintain a stable weight over the whole study period. A comprehensive immune phenotyping protocol was conducted using validated multiparameter flow cytometry analysis in blood and s.c. WAT (SAT). The TCR repertoire was analyzed by next-generation sequencing and cytokine levels were determined in SAT. Metabolic parameters were determined by hyperinsulinemic-euglycemic clamp. We found that insulin resistance correlates significantly with a shift toward the memory T cell compartment in SAT. TCR analysis revealed a diverse repertoire in SAT of overweight or obese individuals. Additionally, whereas weight loss improved systemic insulin sensitivity in the intervention group, SAT displayed no significant improvement of inflammatory parameters (cytokine levels and leukocyte subpopulations) compared with the control group. Our data demonstrate the accumulation of effector memory T cells in obese SAT and an association between systemic glucose homeostasis and inflammatory parameters in obese females. The long-standing effect of obesity-induced changes in SAT was demonstrated by preserved immune cell composition after short-term CR-induced weight loss.

The HLA Ligand Atlas: A novel immuno-oncology resource for T-cell antigen discovery

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Background: The human leukocyte antigen (HLA) complex regulates the adaptive immune response by showcasing the intracellular and extracellular protein content to the immune system, which is the basis for T cell-dependent tumor rejection. Therefore, a comprehensive map of the entirety of both HLA class I- and class II-presented peptides from various benign tissues is a highly sought after resource, as it enables the definition of tumor-association on the immunologically pivotal level of the HLA ligandome. Methods: Human tissue samples were snap frozen post mortem during autopsy. The study was approved by the local IRB. HLA ligands were immunopurified and characterized using an Orbitrap Fusion Lumos mass spectrometer coupled to an Ultimate 3000 RSLC Nano UHPLC System. Data acquisition was performed as technical triplicates in data-dependent mode, and data were analyzed using the containerized, computational pipeline MHCquant. Results: In this work, we describe the HLA Ligand Atlas, a comprehensive collection of matched HLA class I and class II ligandomes from 29 non-malignant tissues and 13 human subjects (208 samples in total), covering 38 HLA class I, and 17 HLA*DRB alleles and comprising 48,381 HLA class I and 16,146 HLA class II peptides. Nearly 50% of HLA ligands have not been previously described. The HLA Ligand Atlas is publicly available as a raw data resource, but also in the form of a user-friendly web interface that allows users to quickly formulate complex queries against the data set. Both downloadable data and the query interface are available at www.hla-ligand-atlas.org. Conclusions: This data set provides a valuable tool for research in diverse fields such as systems biology, general immunology, autoimmune disease and organ transplantation. Most importantly, the HLA Ligand Atlas provides essential information for translational applications in immuno-oncology. The knowledge of HLA ligands from benign tissues strongly supports the informed design of proteogenomic HLA-dependent target discovery approaches.

BKV Clearance Time Correlates With Exhaustion State and T-Cell Receptor Repertoire Shape of BKV-Specific T-Cells in Renal Transplant Patients

Reactivation of the BK polyomavirus is known to lead to severe complications in kidney transplant patients. The current treatment strategy relies on decreasing the immunosuppression to allow the immune system to clear the virus. Recently, we demonstrated a clear association between the resolution of BKV reactivation and reconstitution of BKV-specific CD4⁺ T-cells. However, which factors determine the duration of viral infection clearance remains so far unclear. Here we apply a combination of in-depth multi-parametric flow cytometry and NGS-based CDR3 beta chain receptor repertoire analysis of BKV-specific T-cells to a cohort of 7 kidney transplant patients during the clinical course of BKV reactivation. This way we followed TCR repertoires at single clone levels and functional activity of BKV-specific T-cells during the resolution of BKV infection. The duration of BKV clearance did not depend on the number of peripheral blood BKV-specific T-cells nor on a few immunodominant BKV-specific T-cell clones. Rather, the T-cell receptor repertoire diversity and exhaustion status of BKV-specific T-cells affected the duration of viral clearance: high clonotype diversity and lack of PD1 and TIM3 exhaustion markers on BKV-specific T-cells was associated with short clearance time. Our data thus demonstrate how the diversity and the exhaustion state of the T-cells can determine the clinical course of BKV infection.

The Role of Pre-existing Cross-Reactive Central Memory CD4 T-Cells in Vaccination With Previously Unseen Influenza Strains

Influenza vaccination is a common approach to prevent seasonal and pandemic influenza. Pre-existing antibodies against close viral strains might impair antibody formation against previously unseen strains-a process called original antigenic sin. The role of this pre-existing cellular immunity in this process is, despite some hints from animal models, not clear. Here, we analyzed cellular and humoral immunity in healthy individuals before and after vaccination with seasonal influenza vaccine. Based on influenza-specific hemagglutination inhibiting (HI) titers, vaccinees were grouped into HI-negative and -positive cohorts followed by in-depth cytometric and TCR repertoire analysis. Both serological groups revealed cross-reactive T-cell memory to the vaccine strains at baseline that gave rise to the majority of vaccine-specific T-cells post vaccination. On the contrary, very limited number of vaccine-specific T-cell clones was recruited from the naive pool. Furthermore, baseline quantity of vaccine-specific central memory helper T-cells and clonotype richness of this population directly correlated with the vaccination efficacy. Our findings suggest that the deliberate recruitment of pre-existing cross-reactive cellular memory might help to improve vaccination outcome.

Finding approximate gene clusters with Gecko 3

Gene-order-based comparison of multiple genomes provides signals for functional analysis of genes and the evolutionary process of genome organization. Gene clusters are regions of co-localized genes on genomes of different species. The rapid increase in sequenced genomes necessitates bioinformatics tools for finding gene clusters in hundreds of genomes. Existing tools are often restricted to few (in many cases, only two) genomes, and often make restrictive assumptions such as short perfect conservation, conserved gene order or monophyletic gene clusters. We present Gecko 3, an open-source software for finding gene clusters in hundreds of bacterial genomes, that comes with an easy-to-use graphical user interface. The underlying gene cluster model is intuitive, can cope with low degrees of conservation as well as misannotations and is complemented by a sound statistical evaluation. To evaluate the biological benefit of Gecko 3 and to exemplify our method, we search for gene clusters in a dataset of 678 bacterial genomes using Synechocystis sp. PCC 6803 as a reference. We confirm detected gene clusters reviewing the literature and comparing them to a database of operons; we detect two novel clusters, which were confirmed by publicly available experimental RNA-Seq data. The computational analysis is carried out on a laptop computer in <40 min.

Human CD45RA(-) FoxP3(hi) Memory-Type Regulatory T Cells Show Distinct TCR Repertoires With Conventional T Cells and Play an Important Role in Controlling Early Immune Activation

Adoptive immunotherapy with regulatory T cells (Treg) is a new option to promote immune tolerance following solid organ transplantation (SOT). However, Treg from elderly patients awaiting transplantation are dominated by the CD45RA(-) CD62L(+) central memory type Treg subset (TregCM), and the yield of well-characterized and stable naïve Treg (TregN) is low. It is, therefore, important to determine whether these TregCM are derived from the thymus and express high stability, suppressive capacity and a broad antigen repertoire like TregN. In this study, we showed that TregCM use a different T cell receptor (TCR) repertoire from conventional T cells (Tconv), using next-generation sequencing of all 24 Vβ families, with an average depth of 534 677 sequences. This showed almost no contamination with induced Treg. Furthermore, TregCM showed enhanced suppressive activity on Tconv at early checkpoints of immune activation controlling activation markers expression and cytokine secretion, but comparable inhibition of proliferation. Following in vitro expansion under mTOR inhibition, TregCM expanded equally as well as TregN without losing their function. Despite relatively limited TCR repertoire, TregCM also showed specific alloresponse, although slightly reduced compared to TregN. These results support the therapeutic usefulness of manufacturing Treg products from CD45RA(-) CD62L(+) Treg-enriched starting material to be applied for adoptive Treg therapy.

Methods for the detection and assembly of novel sequence in high-throughput sequencing data

MOTIVATION

Large insertions of novel sequence are an important type of structural variants. Previous studies used traditional de novo assemblers for assembling non-mapping high-throughput sequencing (HTS) or capillary reads and then tried to anchor them in the reference using paired read information.

RESULTS

We present approaches for detecting insertion breakpoints and targeted assembly of large insertions from HTS paired data: BASIL and ANISE. On near identity repeats that are hard for assemblers, ANISE employs a repeat resolution step. This results in far better reconstructions than obtained by the compared methods. On simulated data, we found our insert assembler to be competitive with the de novo assemblers ABYSS and SGA while yielding already anchored inserted sequence as opposed to unanchored contigs as from ABYSS/SGA. On real-world data, we detected novel sequence in a human individual and thoroughly validated the assembled sequence. ANISE was found to be superior to the competing tool MindTheGap on both simulated and real-world data.

AVAILABILITY AND IMPLEMENTATION

ANISE and BASIL are available for download at http://www.seqan.de/projects/herbarium under a permissive open source license.

TCR repertoire analysis by next generation sequencing allows complex differential diagnosis of T cell-related pathology

Clonotype analysis is essential for complete characterization of antigen-specific T cells. Moreover, knowledge on clonal identity allows tracking of antigen-specific T cells in whole blood and tissue infiltrates and can provide information on antigenic specificity. Here, we developed a next generation sequencing (NGS)-based platform for the highly quantitative clonotype characterization of T cells and determined requirements for the unbiased characterization of the input material (DNA, RNA, ex vivo derived or cell culture expanded T cells). Thereafter we performed T cell receptor (TCR) repertoire analysis of various specimens in clinical settings including cytomegalovirus (CMV), polyomavirus BK (BKV) reactivation and acute cellular allograft rejection. Our results revealed dynamic nature of virus-specific T cell clonotypes; CMV reactivation was linked to appearance of new highly abundant antigen-specific clonalities. Moreover, analysis of clonotype overlap between BKV-, alloantigen-specific T cell-, kidney allograft- and urine-derived lymphocytes provided hints for the differential diagnosis of allograft dysfunction and enabled appropriate therapy adjustment. We believe that the established approach will provide insights into the regulation of virus-specific/anti-tumor immunity and has high diagnostic potential in the clinical routine.