Biology subjects

Shlesinger, D.

Publications and source records attributed to Shlesinger, D..

5 recordsLinked to original sources

bioRxiv2022

Asymmetric cell division safeguards memory CD8 T cell development

The strength of T cell receptor (TCR) stimulation and asymmetric distribution of fate determinants are both implied to affect T cell differentiation. Here, we uncovered asymmetric cell division (ACD) as a safeguard mechanism for memory CD8 T cell generation specifically upon strong TCR stimulation. Using live imaging approaches, we found that strong TCR stimulation induced elevated ACD rates and subsequent single cell derived colonies comprised both effector and memory precursor cells. The abundance of memory precursor cells emerging from a single activated T cell positively correlated with first mitosis ACD. Accordingly, preventing ACD by inhibition of PKC{zeta} during the first mitosis upon strong TCR stimulation markedly curtailed the formation of memory precursor cells. Conversely, no effect of ACD on fate commitment was observed upon weak TCR stimulation. Our data provide new mechanistic insights into the role of ACD for CD8 T cell fate regulation upon different activation conditions.

immunology↗

bioRxiv2022

ePlatypus: an ecosystem for computational analysis of immunogenomics data

The maturation of systems immunology methodologies requires novel and transparent computational frameworks capable of integrating diverse data modalities in a reproducible manner. Here, we present the ePlatypus computational immunology ecosystem for immunogenomics data analysis, with a focus on adaptive immune repertoires and single-cell sequencing. ePlatypus is a web-based platform and provides programming tutorials and an integrative database that elucidates selection patterns of adaptive immunity. Furthermore, the ecosystem links novel and established bioinformatics pipelines relevant for single-cell immune repertoires and other aspects of computational immunology such as predicting ligand-receptor interactions, structural modeling, simulations, machine learning, graph theory, pseudotime, spatial transcriptomics and phylogenetics. The ePlatypus ecosystem helps extract deeper insight in computational immunology and immunogenomics and promote open science. Accessibilityhttps://alexyermanos.github.io/Platypus/index.html

immunology↗

bioRxiv2022

Persistent virus-specific and clonally expanded antibody secreting cells respond to induced self antigen in the CNS

B cells contribute to the pathogenesis of both cellular- and humoral-mediated central nervous system (CNS) inflammatory diseases through a variety of mechanisms. In such conditions, B cells may enter the CNS parenchyma and contribute to local tissue destruction. It remains unexplored, however, how infection and autoimmunity drive transcriptional phenotypes, repertoire features, and antibody functionality. Here, we profiled B cells from the CNS of murine models of intracranial (i.c.) viral infections and autoimmunity. We identified a population of clonally expanded, antibody secreting cells (ASCs) that had undergone class-switch recombination and extensive somatic hypermutation following i.c. infection with attenuated lymphocytic choriomeningitis virus (rLCMV). Recombinant expression and characterisation of these antibodies revealed specificity to viral antigens (LCMV glycoprotein GP), correlating with ASC persistence in the brain weeks after resolved infection. Furthermore, these virus-specific ASCs upregulated proliferation and expansion programs in response to the conditional and transient induction of the LCMV GP as a neo-self antigen by astrocytes. This class-switched, clonally expanded, and mutated population persisted and was even more pronounced when peripheral B cells were depleted prior to autoantigen induction in the CNS. In contrast, the most expanded B cell clones in mice with persistent expression of LCMV GP in the CNS did not exhibit neo-self antigen specificity, potentially a consequence of local tolerance induction. Finally, a comparable population of clonally expanded, class-switched, proliferating ASCs was detected in the cerebrospinal fluid of multiple sclerosis patients. Taken together, our findings support the existence of B cells that populate the CNS and are capable of responding to locally encountered autoantigens. Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

immunology↗

bioRxiv2022

Single-cell immune repertoire sequencing of B and T cells in murine models of infection and autoimmunity

Adaptive immune repertoires are composed by the ensemble of B and T cell receptors (BCR, TCR) within an individual and reflect both past and current immune responses. Recent advances in single-cell sequencing enable recovery of the complete adaptive immune receptor sequences in addition to transcriptional information. Such high-dimensional datasets enable the molecular quantification of clonal selection of B and T cells across a wide variety of conditions such as infection and disease. Due to costs, time required for the analysis and current practices of academic publishing, small-scale sequencing studies are often not made publicly available, despite having informative potential to elucidate immunological principles and guide future-studies. Here, we performed single-cell sequencing of B and T cells to profile clonal selection across murine models of viral infection and autoimmune disease. Specifically, we recovered transcriptome and immune repertoire information for polyclonal T follicular helper cells following acute and chronic viral infection, CD8+ T cells with binding specificity restricted to two distinct peptides of lymphocytic choriomeningitis virus, and B and T cells isolated from the nervous system in the context of experimental autoimmune encephalomyelitis. We could relate repertoire features such as clonal expansion, germline gene usage, and clonal convergence to cell phenotypes spanning activation, memory, naive, antibody secretion, T cell inflation, and regulation. Together, this dataset provides a resource for experimental and computational immunologists that can be integrated with future single-cell immune repertoire and transcriptome sequencing datasets.

immunology↗

bioRxiv2021

Echidna: integrated simulations of single-cell immune receptor repertoires and transcriptomes

Single-cell sequencing now enables the recovery of full-length immune repertoires [B cell receptor (BCR) and T cell receptor (TCR) repertoires], in addition to gene expression information. The feature-rich datasets produced from such experiments require extensive and diverse computational analyses, each of which can significantly influence the downstream immunological interpretations, such as clonal selection and expansion. Simulations produce validated standard datasets, where the underlying generative model can be precisely defined and furthermore perturbed to investigate specific questions of interest. Currently, there is no tool that can be used to simulate a comprehensive ground truth single-cell dataset that incorporates both immune receptor repertoires and gene expression. Therefore, we developed Echidna, an R package that simulates immune receptors and transcriptomes at single-cell resolution. Our simulation tool generates annotated single-cell sequencing data with user-tunable parameters controlling a wide range of features such as clonal expansion, germline gene usage, somatic hypermutation, and transcriptional phenotypes. Echidna can additionally simulate time-resolved B cell evolution, producing mutational networks with complex selection histories incorporating class-switching and B cell subtype information. Finally, we demonstrate the benchmarking potential of Echidna by simulating clonal lineages and comparing the known simulated networks with those inferred from only the BCR sequences as input. Together, Echidna provides a framework that can incorporate experimental data to simulate single-cell immune repertoires to aid software development and bioinformatic benchmarking of clonotyping, phylogenetics, transcriptomics and machine learning strategies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=60 SRC="FIGDIR/small/452792v1_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@1c9930eorg.highwire.dtl.DTLVardef@d5a50eorg.highwire.dtl.DTLVardef@47584forg.highwire.dtl.DTLVardef@1f6bb17_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗