Biology subjects

Hong, K.-L.

Publications and source records attributed to Hong, K.-L..

11 recordsLinked to original sources

bioRxiv2025

Predicting TCR antigen specificity at proteome-scale with synthetic immune cells and machine learning

TCR specificity to peptide-HLA antigens is central to immunology, impacting responses in infection, autoimmunity and cancer. Achieving precise recognition while avoiding off-target reactivity is critical for effective immunity and safe therapeutic interventions. Comprehensive, proteome-wide specificity profiling of TCRs is challenging with current methods, which notably lack integrated machine learning for large-scale analysis. Here, we report a synthetic immune cell system coupled with machine learning to enable TCR functional and specificity mapping of peptide-HLA antigens at proteome-scale. Multi-step immunogenomic engineering of synthetic antigen-presenting cells (APCs) was performed to enable stable mono-allelic integration and precise display of peptide antigens and HLA class I from a defined genomic locus, ensuring genomically-encoded antigen presentation. Compatible with a synthetic TCR displaying T cell system, this platform incorporates a fluorescent reporter of cytokine-mediated signaling for real-time activation detection in both synthetic APCs and T cells. We combined this screening with diverse peptide antigen libraries and deep sequencing to train supervised machine learning models. These models were applied to predict TCR specificity to peptide-HLA antigens across the entire human proteome. Experimental validation confirmed novel off-targets for therapeutic TCR candidates, including for a clinically-approved TCR therapeutic. This integrated synthetic immune cell and machine learning approach provides unprecedented proteome-wide peptide-HLA specificity mapping to support the development of safer TCR-based therapies. One sentence summaryWe present a synthetic immune cell platform integrated with machine learning that enables prediction of TCR specificity to peptide-HLA antigens at proteome-scale.

immunology↗

bioRxiv2024

Clonally expanded IgG antibody-secreting cells preferentially target influenza nucleoprotein following homologous and heterologous infections

Infection with influenza virus remains a significant global health concern due to its ability to acquire mutations at key antigenic sites to escape antibody recognition. While germinal center (GC) and memory B cells have been well studied following influenza infection, the clonal dynamics of antibody secreting cells (ASCs), particularly those within the bone marrow (BM) niche that are responsible for serum immune protection, remain poorly understood. Here, we combine single-cell RNA (scRNA) and B cell receptor (BCR) sequencing to characterize individual ASCs following various Influenza exposure histories. We find that BM repertories are populated by highly expanded and class-switched ASCs following Influenza infection with similar transcriptional and repertoire characteristics regardless of homologous or heterologous infection histories. By combining single-cell analysis with monoclonal antibody expression and characterization, we find that a large proportion of the expanded IgG-, but not IgA-, ASC repertoire demonstrates specificity to influenza nucleoprotein (NP). Together, our data reveal the complex relationship between BM ASC repertoires, mucosal humoral immune responses, and BCR antigen specificity during influenza infection.

immunology↗

bioRxiv2023

Multimodal single-cell profiling of T cell specificity and reactivity in lung cancer

Adoptive transfer of autologous tumor-infiltrating lymphocyte T cells (TILs) offers one of the most promising approaches for cancer immunotherapy. However, high variability in patient responses highlight the need for an enhanced understanding of the transcriptional phenotypes of TILs and reactivity of their T cell receptors (TCR). Here, we employ single-cell multiomics approaches and TCR functional screening to investigate TILs from treatment-naive non-small cell lung cancer patients. This comprehensive analysis integrates scRNA-seq, scTCR-seq, and scATAC-seq, enabling a high-resolution examination of TILs within lung cancer tissue, as well as the adjacent non-tumor tissue. We apply a cellular functional screening platform to identify reactive TCRs that represent >1,000 TILs and have specificity towards a multitude of targets, including primary tumor cells, neoantigens, tumor-associated antigens, and viral antigens. Tumor-reactive TILs were primarily associated with dysfunctional phenotypes, whereas viral antigen-reactive TCRs were found in effector phenotype clusters. Key marker genes were identified and used to construct a tumor or viral reactivity score. Comparing clones shared in tumor and non-tumor tissue, a higher fraction of exhausted cells was observed in the tumor tissue, whereas non-tumor adjacent tissue possessed more effector cells, thus providing insight into potential sources for therapeutic T cells. Elucidating the specific T cell populations within TILs and their associated TCRs may support strategies to enhance the efficacy of TIL-based therapies. Graphical AbstractO_ST_ABSMultimodal single cell profiling and reactivity testing of TILsC_ST_ABS(A) CD8+ T cells of treatment naive non-small cell lung cancer patients and adjacent lung tissue were isolated by fluorescence-activated cell sorting (FACS) and were then subjected to scRNA-seq + scTCR-seq or scATAC-seq. (B) TCRs were functionally screened using a cellular platform (TnT cells) and target cells (tumor cells, antigen-pulsed antigen-presenting cells, PBMCs) by flow cytometry and deep sequencing. (C) scRNA-seq + scATAC-seq allowed trajectory inference of transcription factors and genes along pseudotime. (D) Gene scores for tumor- and virus-reactivity were developed by combining functional reactivity and transcriptomic profiling for each CD8+ T cell. (E) TIL scRNA-seq pre and post IL-2 treatment in tumor suspension displayed as alluvial plot shows change of clonal cell state composition. O_FIG O_LINKSMALLFIG WIDTH=196 HEIGHT=200 SRC="FIGDIR/small/560863v1_ufig1.gif" ALT="Figure 1"> View larger version (51K): org.highwire.dtl.DTLVardef@12fcc20org.highwire.dtl.DTLVardef@1027dccorg.highwire.dtl.DTLVardef@911711org.highwire.dtl.DTLVardef@18171e5_HPS_FORMAT_FIGEXP M_FIG C_FIG

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

B cell clonal expansion is correlated with antigen-specificity in young but not old mice

Murine models of immunization have played a major role in discovering antibody candidates against therapeutic targets. It nevertheless remains time-consuming and expensive to identify antibodies with diverse binding modalities against druggable candidate molecules. Although new genomics-based pipelines have potential to augment antibody discovery, these methods remain in their infancy due to an incomplete understanding of the selection process that governs B cell clonal selection, expansion and antigen specificity. Furthermore, it remains unknown how factors such as aging and reduction of tolerance influence B cell selection in murine models of immunization. Here we perform single-cell sequencing of antibody repertoires and transcriptomes of B cells following immunizations with a model therapeutic antigen target (human Tumor necrosis factor receptor 2, TNFR2). We determine the relationship between antibody repertoires, gene expression signatures and antigen specificity across 100,000 B cells. Recombinant expression and characterization of 227 monoclonal antibodies revealed the existence of clonally expanded and class-switched antigen-specific B cells that were more frequent in young mice. Although integrating multiple repertoire features such as germline gene usage, somatic hypermutation, and transcriptional signatures failed to distinguish antigen-specific from non-specific B cells, other features such as IgG-subtype and sequence composition correlated with antigen-specificity. This work provides a single-cell resource for B cells relating antibody repertoires, transcriptomes and antigen specificity.

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↗

bioRxiv2021

Clonally expanded virus-specific CD8 T cells acquire diverse transcriptional phenotypes during acute, chronic, and latent infections

CD8+ T cells play a crucial role in the control and resolution of viral infections and can adopt a wide range of phenotypes and effector functions depending on the inflammatory context and the duration and extent of antigen exposure. Similarly, viral infections can exert diverse selective pressures on populations of clonally related T cells. Technical limitations have nevertheless made it challenging to investigate the relationship between clonal selection and transcriptional phenotypes of virus-specific T cells. We therefore performed single-cell T cell receptor (TCR) repertoire and transcriptome sequencing of virus-specific CD8 T cells in murine models of acute, chronic and latent infection. We observed clear infection-specific populations corresponding to memory, effector, exhausted, and inflationary phenotypes. We further uncovered a mouse-specific and polyclonal T cell response, despite all T cells sharing specificity to a single viral epitope, which was accompanied by stereotypic TCR germline gene usage in all three infection types. Persistent antigen exposure during chronic and latent viral infections resulted in a higher proportion of clonally expanded T cells relative to acute infection. We furthermore observed a relationship between transcriptional heterogeneity and clonal expansion for all three infections, with highly expanded clones having distinct transcriptional phenotypes relative to lowly expanded clones. Finally, we developed and utilized a bioinformatic pipeline integrating pseudotime and clonality, termed Clonotyme, to further support a model in which expanded virus-specific CD8+ T cells adopt heterogenic, yet preferentially, effector-like phenotypes. Together our work relates clonal selection to gene expression in the context of viral infection and further provides a dataset and accompanying software for the immunological community.

immunology↗

bioRxiv2021

Single-cell sequencing of plasma cells from COVID-19 patients reveals highly expanded clonal lineages produce specific and neutralizing antibodies to SARS-CoV-2

Isolation and characterization of antibodies in COVID-19 patients has largely focused on memory B cells, however it is the antibody-secreting plasma cells that are directly responsible for the production of serum antibodies, which play a critical role in controlling and resolving SARS-CoV-2 infection. To date there is little known about the specificity of plasma cells in COVID-19 patients. This is largely because plasma cells lack surface antibody expression, which complicates their screening. Here, we describe a technology pipeline that integrates single-cell antibody repertoire sequencing and high-throughput mammalian display screening to interrogate the specificity of plasma cells from 16 convalescent COVID-19 patients. Single-cell sequencing allows us to profile antibody repertoire features in these patients and identify highly expanded clonal lineages. Mammalian display screening is employed to reveal that 37 antibodies (out of 132 candidates) derived from expanded plasma cell clonal lineages are specific for SARS-CoV-2 antigens, including antibodies that target the receptor binding domain (RBD) with high affinity and exhibit potent neutralization of SARS-CoV-2. One Sentence SummarySingle-cell antibody repertoire sequencing and high-throughput screening identifies highly expanded plasma cells from convalescent COVID-19 patients that produce SARS-CoV-2-specific antibodies capable of potent neutralization.

immunology↗

bioRxiv2021

Single-cell sequencing reveals clonally expanded plasma cells during chronic viral infection produce virus-specific and cross-reactive antibodies

Plasma cells and their secreted antibodies play a central role in the long-term protection against chronic viral infection. However, due to experimental limitations, a comprehensive description of linked genotypic, phenotypic, and antibody repertoire features of plasma cells (gene expression, clonal frequency, virus specificity, and affinity) has been challenging to obtain. To address this, we performed single-cell transcriptome and antibody repertoire sequencing of the murine bone marrow plasma cell population following chronic lymphocytic choriomeningitis virus infection. Our single-cell sequencing approach recovered full-length and paired heavy and light chain sequence information for thousands of plasma cells and enabled us to perform recombinant antibody expression and specificity screening. Antibody repertoire analysis revealed that, relative to protein immunization, chronic infection led to increased levels of clonal expansion, class-switching, and somatic variants. Furthermore, antibodies from the highly expanded and class-switched (IgG) plasma cells were found to be specific for multiple viral antigens and a subset of clones exhibited cross-reactivity to non-viral- and auto-antigens. Integrating single-cell transcriptome data with antibody specificity suggested that plasma cell transcriptional phenotype was correlated to viral antigen specificity. Our findings demonstrate that chronic viral infection can induce and sustain plasma cell clonal expansion, combined with significant somatic hypermutation, and can generate cross-reactive antibodies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=69 SRC="FIGDIR/small/428852v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@9d0852org.highwire.dtl.DTLVardef@18d46fcorg.highwire.dtl.DTLVardef@2f7f80org.highwire.dtl.DTLVardef@5be3fd_HPS_FORMAT_FIGEXP M_FIG Graphical abstract.Single-cell sequencing reveals clonally expanded plasma cells during chronic viral infection produce virus-specific and cross-reactive antibodies. C_FIG

immunology↗