Biology subjects

Lebedev, Y. B.

Publications and source records attributed to Lebedev, Y. B..

8 recordsLinked to original sources

bioRxiv2023

Non-canonical D1-D2 rearrangements are bimodal and represent a conservative hidden stage of VDJ recombination in TCR beta locus

T-cell receptor (TCR) diversity is generated by VDJ recombination. The classical course of TCR beta (TRB) chain production starts with D and J segment recombination and finishes with subsequent recombination between the resulting DJ junction and V segment. In this study, we performed deep sequencing of poorly explored incomplete TRBD1 to TRBD2 rearrangements in T-cell genomic DNA. We reconstructed full repertoires of human incomplete TRB DD rearrangements and validated its authenticity by detecting excision circles with RSS (recombination signal sequence) junctions for the first time. The identified rearrangements generated in compliance with the classical 12/23 rule are common for humans, rats, and mice and contain typical VDJ recombination footprints. Detected bimodal distribution of DD junctions indicates two active recombination sites producing long and short DD rearrangements. Unlike long DD rearrangements, the short ones have unusual origin resulting from non-canonical intrachromosomal RSSs junctions formation. Identified DD rearrangements lead to deleting J1 and C1 segments and creating diverse hybrid D segments, which recombine further with J2 and V segments. Resulting functional TRB VDDJ rearrangements are present in the memory T-cells subset proving its participation in antigen recognition.

immunology↗

bioRxiv2021

The use of non-functional clonotypes as a natural spike-in for multiplex PCR bias correction in immune receptor repertoire profiling

High-throughput sequencing of adaptive immune receptor repertoires is a valuable tool for receiving insights in adaptive immunity studies. Several powerful TCR/BCR repertoire reconstruction and analysis methods have been developed in the past decade. However, detecting and correcting the discrepancy between real and experimentally observed lymphocyte clone frequencies is still challenging. Here we discovered a hallmark anomaly in the ratio between read count and clone count-based frequencies of non-functional clonotypes in multiplex PCR-based immune repertoires. Calculating this anomaly, we formulated a quantitative measure of V- and J-genes frequency bias driven by multiplex PCR during library preparation called Over Amplification Rate (OAR). Based on the OAR concept, we developed an original software for multiplex PCR-specific bias evaluation and correction named iROAR: Immune Repertoire Over Amplification Removal (https://github.com/smiranast/iROAR). The iROAR algorithm was successfully tested on previously published TCR repertoires obtained using both 5 RACE (Rapid Amplification of cDNA Ends)-based and multiplex PCR-based approaches and compared with a biological spike-in-based method for PCR bias evaluation. The developed approach can increase the accuracy and consistency of repertoires reconstructed by different methods making them more applicable for comparative analysis.

immunology↗

bioRxiv2020

Longitudinal high-throughput TCR repertoire profiling reveals the dynamics of T cell memory formation after mild COVID-19 infection

COVID-19 is a global pandemic caused by the SARS-CoV-2 coronavirus. T cells play a key role in the adaptive antiviral immune response by killing infected cells and facilitating the selection of virus-specific antibodies. However neither the dynamics and cross-reactivity of the SARS-CoV-2-specific T cell response nor the diversity of resulting immune memory are well understood. In this study we use longitudinal high-throughput T cell receptor (TCR) sequencing to track changes in the T cell repertoire following two mild cases of COVID-19. In both donors we identified CD4+ and CD8+ T cell clones with transient clonal expansion after infection. The antigen specificity of CD8+ TCR sequences to SARS-CoV-2 epitopes was confirmed by both MHC tetramer binding and presence in large database of SARS-CoV-2 epitope-specific TCRs. We describe characteristic motifs in TCR sequences of COVID-19-reactive clones and show preferential occurence of these motifs in publicly available large dataset of repertoires from COVID-19 patients. We show that in both donors the majority of infection-reactive clonotypes acquire memory phenotypes. Certain T cell clones were detected in the memory fraction at the pre-infection timepoint, suggesting participation of pre-existing cross-reactive memory T cells in the immune response to SARS-CoV-2.

immunology↗

bioRxiv2019

Comprehensive analysis of antiviral adaptive immunity formation and reactivation down to single-cell level

The diverse repertoire of T-cell receptors (TCR) plays a key role in the adaptive immune response to infections. Previous studies show that secondary responses to the yellow fever vaccine -- the model for acute infection in humans -- are weaker than primary ones, but only quantitative measurements can describe the concentration changes and lineage fates for distinct T-cell clones in vivo over time. Using TCR alpha and beta repertoire sequencing for T-cell subsets, as well as single-cell RNAseq and TCRseq, we track the concentrations and phenotypes of individual T-cell clones in response to primary and secondary yellow fever immunization showing their large diversity. We confirm the secondary response is an order of magnitude weaker, albeit 10 days faster than the primary one. Estimating the fraction of the T-cell response directed against the single immunodominant epitope, we identify the sequence features of TCRs that define the high precursor frequency of the two major TCR motifs specific for this particular epitope. We also show the consistency of clonal expansion dynamics between bulk alpha and beta repertoires, using a new methodology to reconstruct alpha-beta pairings from clonal trajectories.

immunology↗

bioRxiv2018

Detecting T-cell receptors involved in immune responses from single repertoire snapshots

Hypervariable T-cell receptors (TCR) play a key role in adaptive immunity, recognising a vast diversity of pathogen-derived antigens. High throughput sequencing of TCR repertoires (RepSeq) produces huge datasets of T-cell receptor sequences from blood and tissue samples [1, 2]. However, our ability to extract clinically relevant information from RepSeq data is limited, mainly because little is known about TCR-disease associations. Here we present a statistical approach called ALICE (Antigen-specific Lymphocyte Identification by Clustering of Expanded sequences) that identifies TCR sequences that are actively involved in the current immune response from a single RepSeq sample, and apply it to repertoires of patients with a variety of disorders -- autoimmune disease (ankylosing spondylitis [3]), patients under cancer immunotherapy [4, 5], or subject to an acute infection (live yellow fever vaccine [6]). The methods robustness is demonstrated by the agreement of its predictions with independent assays, and is supported by its ability to selectively detect responding TCR in the memory but not in the naive subset. ALICE requires no longitudinal data collection [6, 7] nor large cohorts [8-10], and is thus directly applicable to most RepSeq datasets. Its results facilitate the identification of TCR variants associated with a wide variety of diseases and conditions, which can be used for diagnostics, rational vaccine design and evaluation of the adaptive immune system state.

immunology↗

bioRxiv2018

Precise tracking of vaccine-responding T-cell clones reveals convergent and personalized response in identical twins

T-cell receptor (TCR) repertoire data contain information about infections that could be used in disease diagnostics and vaccine development, but extracting that information remains a major challenge. Here we developed a statistical framework to detect TCR clone proliferation and contraction from longitudinal repertoire data. We applied this framework to data from three pairs of identical twins immunized with the yellow fever vaccine. We identified 500-1500 responding TCRs in each donor and validated them using three independent assays. While the responding TCRs were mostly private, albeit with higher overlap between twins, they could be well predicted using a classifier based on sequence similarity. Our method can also be applied to samples obtained post-infection, making it suitable for systematic discovery of new infection-specific TCRs in the clinic.

immunology↗

bioRxiv2018

Genomic normalization for sequencing libraries enrichment for rare somatic retroelement insertions

BackgroundThere is increasing evidence that the transpositional activity of retroelements (REs) is not limited to germ line cells, but often occurs in tumor and normal somatic cells. Somatic transpositions were found in several human tissues and are especially typical for the brain. Several computational and experimental approaches for detection of somatic retroelement insertions was developed in the past few years. These approaches were successfully applied to detect somatic insertions in clonally expanded tumor cells. At the same time, identification of somatic insertions presented in small proportion of cells, such as neurons, remains a considerable challenge.\n\nResultsIn this study, we developed a normalization procedure for library enrichment by DNA sequences corresponding to rare somatic RE insertions. Two rounds of normalization increased the number of fragments adjacent to somatic REs in the sequenced sample by more than 26-fold, and the number of identified somatic REs was increased by 7.9-fold.\n\nConclusionsThe developed technique can be used in combination with vast majority of modern RE identification approaches and can dramatically increase their capacity to detect rare somatic RE insertions in different types of cells.

genomics↗

bioRxiv2017

Method for identification of condition-associated public antigen receptor sequences

Diverse repertoires of hypervariable immunoglobulin receptors (TCR and BCR) recognize antigens in the adaptive immune system. The development of immunoglobulin receptor repertoire sequencing methods makes it possible to perform repertoire-wide disease association studies of antigen receptor sequences. We developed a statistical framework for associating receptors to disease from only a small cohort of patients, with no need for a control cohort. Our method successfully identifies previously validated Cytomegalovirus and type 1 diabetes responsive receptors.

immunology↗