Publications by authors named "Jerome Samir"

6 Publications

  • Page 1 of 1

Natural killer cell receptors regulate responses of HLA-E-restricted T cells.

Sci Immunol 2021 Apr;6(58)

Department of Microbiology and Immunology, University of Melbourne at the Peter Doherty Institute, Parkville, Victoria 3010, Australia.

Human cytomegalovirus (CMV) infection can stimulate robust human leukocyte antigen (HLA)-E-restricted CD8 T cell responses. These T cells recognize a peptide from UL40, which differs by as little as a single methyl group from self-peptides that also bind HLA-E, challenging their capacity to avoid self-reactivity. Unexpectedly, we showed that the UL40/HLA-E T cell receptor (TCR) repertoire included TCRs that had high affinities for HLA-E/self-peptide. However, paradoxically, lower cytokine responses were observed from UL40/HLA-E T cells bearing TCRs with high affinity for HLA-E. RNA sequencing and flow cytometric analysis revealed that these T cells were marked by the expression of inhibitory natural killer cell receptors (NKRs) KIR2DL1 and KIR2DL2/L3. On the other hand, UL40/HLA-E T cells bearing lower-affinity TCRs expressed the activating receptor NKG2C. Activation of T cells bearing higher-affinity TCRs was regulated by the interaction between KIR2D receptors and HLA-C. These findings identify a role for NKR signaling in regulating self/non-self discrimination by HLA-E-restricted T cells, allowing for antiviral responses while avoiding contemporaneous self-reactivity.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1126/sciimmunol.abe9057DOI Listing
April 2021

Human CD8 T-stem cell memory subsets phenotypic and functional characterization are defined by expression of CD122 or CXCR3.

Eur J Immunol 2021 Jul 23;51(7):1732-1747. Epub 2021 Apr 23.

Viral Immunology Systems Program (VISP), The Kirby Institute, University of New South Wales, Sydney, Australia.

Long-lived T-memory stem cells (T ) are key to both naturally occurring and vaccine-conferred protection against infection. These cells are characterized by the CD45RA CCR7 CD95 phenotype. Significant heterogeneity within the T population is recognized, but distinguishing surface markers and functional characterization of potential subsets are lacking. Human CD8 T subsets were identified in healthy subjects who had been previously exposed to CMV or Influenza (Flu) virus in flow cytometry by expression of CD122 or CXCR3, and then characterized in proliferation, multipotency, self-renewal, and intracellular cytokine production (TNF-α, IL-2, IFN-γ), together with transcriptomic profiles. The T CD122 -expressing subset (versus CD122 ) demonstrated greater proliferation, greater multipotency, and enhanced polyfunctionality with higher frequencies of triple positive (TNF-α, IL-2, IFN-γ) cytokine-producing cells upon exposure to recall antigen. The T CXCR3 subpopulation also had increased proliferation and polyfunctional cytokine production. Transcriptomic analysis further showed that the T CD122 population had increased expression of activation and homing molecules, such as Ccr6, Cxcr6, Il12rb, and Il18rap, and downregulated cell proliferation inhibitors, S100A8 and S100A9. These data reveal that the T CD122 phenotype is associated with increased proliferation, enhanced multipotency and polyfunctionality with an activated memory-cell like transcriptional profile, and hence, may be favored for induction by immunization and for adoptive immunotherapy.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1002/eji.202049057DOI Listing
July 2021

Exploring and analysing single cell multi-omics data with VDJView.

BMC Med Genomics 2020 02 18;13(1):29. Epub 2020 Feb 18.

School of Medical Sciences and Kirby Institute for Infection and Immunity, UNSW Sydney, Sydney, Australia.

Background: Single cell RNA sequencing provides unprecedented opportunity to simultaneously explore the transcriptomic and immune receptor diversity of T and B cells. However, there are limited tools available that simultaneously analyse large multi-omics datasets integrated with metadata such as patient and clinical information.

Results: We developed VDJView, which permits the simultaneous or independent analysis and visualisation of gene expression, immune receptors, and clinical metadata of both T and B cells. This tool is implemented as an easy-to-use R shiny web-application, which integrates numerous gene expression and TCR analysis tools, and accepts data from plate-based sorted or high-throughput single cell platforms. We utilised VDJView to analyse several 10X scRNA-seq datasets, including a recent dataset of 150,000 CD8 T cells with available gene expression, TCR sequences, quantification of 15 surface proteins, and 44 antigen specificities (across viruses, cancer, and self-antigens). We performed quality control, filtering of tetramer non-specific cells, clustering, random sampling and hypothesis testing to discover antigen specific gene signatures which were associated with immune cell differentiation states and clonal expansion across the pathogen specific T cells. We also analysed 563 single cells (plate-based sorted) obtained from 11 subjects, revealing clonally expanded T and B cells across primary cancer tissues and metastatic lymph-node. These immune cells clustered with distinct gene signatures according to the breast cancer molecular subtype. VDJView has been tested in lab meetings and peer-to-peer discussions, showing effective data generation and discussion without the need to consult bioinformaticians.

Conclusions: VDJView enables researchers without profound bioinformatics skills to analyse immune scRNA-seq data, integrating and visualising this with clonality and metadata profiles, thus accelerating the process of hypothesis testing, data interpretation and discovery of cellular heterogeneity. VDJView is freely available at https://bitbucket.org/kirbyvisp/vdjview.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1186/s12920-020-0696-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7029546PMC
February 2020

VDJdb in 2019: database extension, new analysis infrastructure and a T-cell receptor motif compendium.

Nucleic Acids Res 2020 01;48(D1):D1057-D1062

Pirogov Russian Medical State University, Moscow, Russia.

Here, we report an update of the VDJdb database with a substantial increase in the number of T-cell receptor (TCR) sequences and their cognate antigens. The update further provides a new database infrastructure featuring two additional analysis modes that facilitate database querying and real-world data analysis. The increased yield of TCR specificity identification methods and the overall increase in the number of studies in the field has allowed us to expand the database more than 5-fold. Furthermore, several new analysis methods are included. For example, batch annotation of TCR repertoire sequencing samples allows for annotating large datasets on-line. Using recently developed bioinformatic methods for TCR motif mining, we have built a reduced set of high-quality TCR motifs that can be used for both training TCR specificity predictors and matching against TCRs of interest. These additions enhance the versatility of the VDJdb in the task of exploring T-cell antigen specificities. The database is available at https://vdjdb.cdr3.net.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/nar/gkz874DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6943061PMC
January 2020

Single-Cell Transcriptome Analysis of T Cells.

Methods Mol Biol 2019 ;2048:155-205

Kirby Institute for Infection and Immunity, The University of New South Wales, Sydney, NSW, Australia.

Single-cell RNA-seq (scRNA-seq) has provided novel routes to investigate the heterogeneous populations of T cells and is rapidly becoming a common tool for molecular profiling and identification of novel subsets and functions. This chapter offers an experimental and computational workflow for scRNA-seq analysis of T cells. We focus on the analyses of scRNA-seq data derived from plate-based sorted T cells using flow cytometry and full-length transcriptome protocols such as Smart-Seq2. However, the proposed pipeline can be applied to other high-throughput approaches such as UMI-based methods. We describe a detailed bioinformatics pipeline that can be easily reproduced and discuss future directions and current limitations of these methods in the context of T cell biology.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1007/978-1-4939-9728-2_16DOI Listing
June 2020

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

Bioinformatics 2018 08;34(16):2846-2847

Kirby Institute for Infection and Immunity, Sydney, Australia.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.1093/bioinformatics/bty203DOI Listing
August 2018