Simone Rizzetto

Linking the T cell receptor to the single cell transcriptome in antigen-specific human T cells

Heterogeneity of T cells is a hallmark of a successful adaptive immune response, harnessing the vast diversity of antigen‐specific T cells into a coordinated evolution of effector and memory outcomes. The T cell receptor (TCR) repertoire is highly diverse to account for the highly heterogeneous antigenic world. During the response to a virus multiple individual clones of antigen specific CD8+ (Ag‐specific) T cells can be identified against a single epitope and multiple epitopes are recognised. Advances in single‐cell technologies have provided the potential to study Ag‐specific T cell heterogeneity at both surface phenotype and transcriptome levels, thereby allowing investigation of the diversity within the same apparent sub‐population. We propose a new method (VDJPuzzle) to reconstruct the native TCRαβ from single cell RNA‐seq data of Ag‐specific T cells and then to link these with the gene expression profile of individual cells. We applied this method using rare Ag‐specific T cells isolated from peripheral blood of a subject who cleared hepatitis C virus infection. We successfully reconstructed productive TCRαβ in 56 of a total of 63 cells (89%), with double α and double β in 18, and 7% respectively, and double TCRαβ in 2 cells. The method was validated via standard single cell PCR sequencing of the TCR. We demonstrate that single‐cell transcriptome analysis can successfully distinguish Ag‐specific T cell populations sorted directly from resting memory cells in peripheral blood and sorted after ex vivo stimulation. This approach allows a detailed analysis of the TCR diversity and its relationship with the transcriptional profile of different clones.

A Liver Capsular Network of Monocyte-Derived Macrophages Restricts Hepatic Dissemination of Intraperitoneal Bacteria by Neutrophil Recruitment

&NA; The liver is positioned at the interface between two routes traversed by pathogens in disseminating infection. Whereas blood‐borne pathogens are efficiently cleared in hepatic sinusoids by Kupffer cells (KCs), it is unknown how the liver prevents dissemination of peritoneal pathogens accessing its outer membrane. We report here that the hepatic capsule harbors a contiguous cellular network of liver‐resident macrophages phenotypically distinct from KCs. These liver capsular macrophages (LCMs) were replenished in the steady state from blood monocytes, unlike KCs that are embryonically derived and self‐renewing. LCM numbers increased after weaning in a microbiota‐dependent process. LCMs sensed peritoneal bacteria and promoted neutrophil recruitment to the capsule, and their specific ablation resulted in decreased neutrophil recruitment and increased intrahepatic bacterial burden. Thus, the liver contains two separate and non‐overlapping niches occupied by distinct resident macrophage populations mediating immunosurveillance at these two pathogen entry points to the liver. Graphical Abstract Figure. No caption available. HighlightsA distinct subset of resident macrophages (LCMs) occupies the hepatic capsuleLCMs are replenished from blood monocytes in the steady stateLCMs recruit neutrophils in response to bacteria reaching the liver capsuleLCM depletion decreases neutrophil recruitment and increases liver pathogen load &NA; The hepatic sinusoids harbor a well‐characterized resident macrophage population, Kupffer cells. Sierro et al. report an additional liver‐resident macrophage population occupying the hepatic capsule, phenotypically and developmentally distinct from Kupffer cells, which plays a role in immunosurveillance by sensing peritoneal pathogens and recruiting neutrophils to control intrahepatic bacterial dissemination.

Qualitative and Quantitative Protein Complex Prediction Through Proteome-Wide Simulations.

Despite recent progress in proteomics most protein complexes are still unknown. Identification of these complexes will help us understand cellular regulatory mechanisms and support development of new drugs. Therefore it is really important to establish detailed information about the composition and the abundance of protein complexes but existing algorithms can only give qualitative predictions. Herein, we propose a new approach based on stochastic simulations of protein complex formation that integrates multi-source data—such as protein abundances, domain-domain interactions and functional annotations—to predict alternative forms of protein complexes together with their abundances. This method, called SiComPre (Simulation based Complex Prediction), achieves better qualitative prediction of yeast and human protein complexes than existing methods and is the first to predict protein complex abundances. Furthermore, we show that SiComPre can be used to predict complexome changes upon drug treatment with the example of bortezomib. SiComPre is the first method to produce quantitative predictions on the abundance of molecular complexes while performing the best qualitative predictions. With new data on tissue specific protein complexes becoming available SiComPre will be able to predict qualitative and quantitative differences in the complexome in various tissue types and under various conditions.

Clonally diverse CD38 + HLA-DR + CD8 + T cells persist during fatal H7N9 disease

Severe influenza A virus (IAV) infection is associated with immune dysfunction. Here, we show circulating CD8+ T-cell profiles from patients hospitalized with avian H7N9, seasonal IAV, and influenza vaccinees. Patient survival reflects an early, transient prevalence of highly activated CD38+HLA-DR+PD-1+ CD8+ T cells, whereas the prolonged persistence of this set is found in ultimately fatal cases. Single-cell T cell receptor (TCR)-αβ analyses of activated CD38+HLA-DR+CD8+ T cells show similar TCRαβ diversity but differential clonal expansion kinetics in surviving and fatal H7N9 patients. Delayed clonal expansion associated with an early dichotomy at a transcriptome level (as detected by single-cell RNAseq) is found in CD38+HLA-DR+CD8+ T cells from patients who succumbed to the disease, suggesting a divergent differentiation pathway of CD38+HLA-DR+CD8+ T cells from the outset during fatal disease. Our study proposes that effective expansion of cross-reactive influenza-specific TCRαβ clonotypes with appropriate transcriptome signatures is needed for early protection against severe influenza disease.Virus-specific CD8+ T cells are crucial during H7N9 influenza infection, but CD8+ T cell dysfunction is associated with poor prognosis. Here, the authors use molecular and phenotypic analysis to establish persistence of clonally diverse CD8+ T cell populations during fatal infection.

Impact of sequencing depth and read length on single cell RNA sequencing data of T cells

Single cell RNA sequencing (scRNA-seq) provides great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant T cell subsets, and the identification of the full length T cell receptor (TCRαβ), which defines the specificity against cognate antigens. Several factors, e.g. RNA library capture, cell quality, and sequencing output affect the quality of scRNA-seq data. We studied the effects of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCRαβ reconstruction, utilising 1,305 single cells from 8 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. Successful TCRαβ reconstruction was achieved for 6 datasets (81% − 100%) with at least 0.25 millions (PE) reads of length >50 bp, while it failed for datasets with <30 bp reads. Sufficient read length and sequencing depth can control technical noise to enable accurate identification of TCRαβ and gene expression profiles from scRNA-seq data of T cells.

B-cell receptor reconstruction from single-cell RNA-seq with VDJPuzzle

Motivation The B-cell receptor (BCR) performs essential functions for the adaptive immune system including recognition of pathogen-derived antigens. The vast repertoire and adaptive variation of BCR sequences due to V(D)J recombination and somatic hypermutation necessitates single-cell characterization of BCR sequences. Single-cell RNA sequencing presents the opportunity for simultaneous capture of paired BCR heavy and light chains and the transcriptomic signature. Results We developed VDJPuzzle, a novel bioinformatic tool that reconstructs productive, full-length B-cell receptor sequences of both heavy and light chains and extract somatic mutations on the VDJ region. VDJPuzzle successfully reconstructed BCRs from 100% (n=117) human and 96.5% (n=200) murine B cells. The reconstructed BCRs were successfully validated with single-cell Sanger sequencing. Availability and implementation VDJPuzzle is available at https://bitbucket.org/kirbyvisp/vdjpuzzle2. Supplementary information Supplementary data are available at Bioinformatics online.

Context-dependent prediction of protein complexes by SiComPre

Most cellular processes are regulated by groups of proteins interacting together to form protein complexes. Protein compositions vary between different tissues or disease conditions enabling or preventing certain protein−protein interactions and resulting in variations in the complexome. Quantitative and qualitative characterization of context-specific protein complexes will help to better understand context-dependent variations in the physiological behavior of cells. Here, we present SiComPre 1.0, a computational tool that predicts context-specific protein complexes by integrating multi-omics sources. SiComPre outperforms other protein complex prediction tools in qualitative predictions and is unique in giving quantitative predictions on the complexome depending on the specific interactions and protein abundances defined by the user. We provide tutorials and examples on the complexome prediction of common model organisms, various human tissues and how the complexome is affected by drug treatment.

Mass Cytometry for the Assessment of Immune Reconstitution After Hematopoietic Stem Cell Transplantation

Mass cytometry, or Cytometry by Time-Of-Flight, is a powerful new platform for high-dimensional single-cell analysis of the immune system. It enables the simultaneous measurement of over 40 markers on individual cells through the use of monoclonal antibodies conjugated to rare-earth heavy-metal isotopes. In contrast to the fluorochromes used in conventional flow cytometry, metal isotopes display minimal signal overlap when resolved by single-cell mass spectrometry. This review focuses on the potential of mass cytometry as a novel technology for studying immune reconstitution in allogeneic hematopoietic stem cell transplant (HSCT) recipients. Reconstitution of a healthy donor-derived immune system after HSCT involves the coordinated regeneration of innate and adaptive immune cell subsets in the recipient. Mass cytometry presents an opportunity to investigate immune reconstitution post-HSCT from a systems-level perspective, by allowing the phenotypic and functional features of multiple cell populations to be assessed simultaneously. This review explores the current knowledge of immune reconstitution in HSCT recipients and highlights recent mass cytometry studies contributing to the field.

Impact Of Sequencing Depth And Read Length On Single Cell RNA Sequencing Data: Lessons From T Cells

Single cell RNA sequencing (scRNA-seq) has shown great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant sub-populations of T cells, and notably the identification of the full length T cell receptor (TCRαβ), which defines the specificity against cognate antigens. Several factors, such as RNA library capture, cell quality, and sequencing output have been suggested to affect the quality of scRNA-seq data, but these factors have not been systematically examined. We studied the effect of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCRαβ reconstruction, utilising 1,305 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. TCRαβ were detected in 1,027 cells (79%), with a success rate between 81% and 100% for datasets with at least 250,000 (PE) reads of length >50 bp. Sufficient read length and sequencing depth can control technical noise to enable accurate identification of TCRαβ and gene expression profiles from scRNA-seq data of T cells.