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A major challenge in adoptive T cell immunotherapy is the discovery of natural T cell receptors (TCRs) with high activity and specificity to tumor antigens. Engineering synthetic TCRs for increased tumor antigen recognition is complicated by the risk of introducing cross-reactivity and by the poor correlation that can exist between binding affinity and activity of TCRs in response to antigen (peptide-MHC). Here, we developed TCR-Engine, a method combining genome editing, computational design, and deep sequencing to engineer the functional activity and specificity of TCRs on the surface of a human T cell line at high throughput. We applied TCR-Engine to successfully engineer synthetic TCRs for increased potency and specificity to a clinically relevant tumor-associated antigen (MAGE-A3) and validated their translational potential through multiple in vitro and in vivo assessments of safety and efficacy. Thus, TCR-Engine represents a valuable technology for engineering of safe and potent synthetic TCRs for immunotherapy applications.
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Imunoterapia Adotiva , Receptores de Antígenos de Linfócitos T , Antígenos de Neoplasias , Humanos , Imunoterapia , PeptídeosRESUMO
MOTIVATION: The maturation of systems immunology methodologies requires novel and transparent computational frameworks capable of integrating diverse data modalities in a reproducible manner. RESULTS: 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 an open-source web-based platform and provides programming tutorials and an integrative database that helps elucidate signatures of B and T cell clonal selection. 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. AVAILABILITY AND IMPLEMENTATION: Platypus code used in this manuscript can be found at github.com/alexyermanos/Platypus.
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Ecossistema , Ornitorrinco , Animais , Biologia Computacional/métodos , Filogenia , Aprendizado de Máquina , SoftwareRESUMO
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 BM 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 nonviral and autoantigens. 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.
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Anticorpos Antivirais , Seleção Clonal Mediada por Antígeno , Cadeias Pesadas de Imunoglobulinas , Cadeias Leves de Imunoglobulina , Coriomeningite Linfocítica , Vírus da Coriomeningite Linfocítica/imunologia , Plasmócitos/imunologia , Análise de Célula Única , Animais , Anticorpos Antivirais/genética , Anticorpos Antivirais/imunologia , Doença Crônica , Feminino , Cadeias Pesadas de Imunoglobulinas/genética , Cadeias Pesadas de Imunoglobulinas/imunologia , Cadeias Leves de Imunoglobulina/genética , Cadeias Leves de Imunoglobulina/imunologia , Coriomeningite Linfocítica/genética , Coriomeningite Linfocítica/imunologia , CamundongosRESUMO
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, and proliferating ASCs was detected in the cerebrospinal fluid of relapsing multiple sclerosis (RMS) patients. Taken together, our findings support the existence of B cells that populate the CNS and are capable of responding to locally encountered autoantigens.
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Células Produtoras de Anticorpos , Autoantígenos , Camundongos , Animais , Linfócitos B , Vírus da Coriomeningite Linfocítica , EncéfaloRESUMO
Adaptive immune repertoires are composed by the ensemble of B and T-cell receptors within an individual, reflecting 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. Here, we recovered transcriptome and immune repertoire information for polyclonal T follicular helper cells following lymphocytic choriomeningitis virus (LCMV) infection, CD8+ T cells with binding specificity restricted to two distinct LCMV peptides, and B and T cells isolated from the nervous system in the context of experimental autoimmune encephalomyelitis. We could relate 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 immunologists that can be integrated with future single-cell immune repertoire and transcriptome sequencing datasets.
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Autoimunidade , Coriomeningite Linfocítica , Animais , Linfócitos T CD8-Positivos , Modelos Animais de Doenças , Coriomeningite Linfocítica/genética , Camundongos , Camundongos Endogâmicos C57BL , Peptídeos , Receptores de Antígenos de Linfócitos T/genéticaRESUMO
BACKGROUND: The continued spread of SARS-CoV-2 and emergence of new variants with higher transmission rates and/or partial resistance to vaccines has further highlighted the need for large-scale testing and genomic surveillance. However, current diagnostic testing (e.g., PCR) and genomic surveillance methods (e.g., whole genome sequencing) are performed separately, thus limiting the detection and tracing of SARS-CoV-2 and emerging variants. RESULTS: Here, we developed DeepSARS, a high-throughput platform for simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2 by the integration of molecular barcoding, targeted deep sequencing, and computational phylogenetics. DeepSARS enables highly sensitive viral detection, while also capturing genomic diversity and viral evolution. We show that DeepSARS can be rapidly adapted for identification of emerging variants, such as alpha, beta, gamma, and delta strains, and profile mutational changes at the population level. CONCLUSIONS: DeepSARS sets the foundation for quantitative diagnostics that capture viral evolution and diversity. DeepSARS uses molecular barcodes (BCs) and multiplexed targeted deep sequencing (NGS) to enable simultaneous diagnostic detection and genomic surveillance of SARS-CoV-2. Image was created using Biorender.com .
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COVID-19 , SARS-CoV-2 , COVID-19/diagnóstico , Genômica , Humanos , Mutação , SARS-CoV-2/genética , Sequenciamento Completo do GenomaRESUMO
BACKGROUND: The methanol-regulated AOX1 promoter (PAOX1) is the most widely used promoter in the production of recombinant proteins in the methylotrophic yeast Pichia pastoris. However, as the tight regulation and methanol dependence of PAOX1 restricts its application, it is necessary to develop a flexible induction system to avoid the problems of methanol without losing the advantages of PAOX1. The availability of synthetic biology tools enables researchers to reprogram the cellular behaviour of P. pastoris to achieve this goal. RESULTS: The characteristics of PAOX1 are highly related to the expression profile of methanol expression regulator 1 (Mxr1). In this study, we applied a biologically inspired strategy to reprogram regulatory networks in P. pastoris. A reprogrammed P. pastoris was constructed by inserting a synthetic positive feedback circuit of Mxr1 driven by a weak AOX2 promoter (PAOX2). This novel approach enhanced PAOX1 efficiency by providing extra Mxr1 and generated switchable Mxr1 expression to allow PAOX1 to be induced under glycerol starvation or carbon-free conditions. Additionally, the inhibitory effect of glycerol on PAOX1 was retained because the synthetic circuit was not activated in response to glycerol. Using green fluorescent protein as a demonstration, this reprogrammed P. pastoris strain displayed stronger fluorescence intensity than non-reprogrammed cells under both methanol induction and glycerol starvation. Moreover, with single-chain variable fragment (scFv) as the model protein, increases in extracellular scFv productivity of 98 and 269% were observed in Mxr1-reprogrammed cells under methanol induction and glycerol starvation, respectively, compared to productivity in non-reprogrammed cells under methanol induction. CONCLUSIONS: We successfully demonstrate that the synthetic positive feedback circuit of Mxr1 enhances recombinant protein production efficiency in P. pastoris and create a methanol-free induction system to eliminate the potential risks of methanol.
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Proteínas Fúngicas/genética , Regulação Fúngica da Expressão Gênica , Pichia/genética , Regiões Promotoras Genéticas , Retroalimentação Fisiológica , Proteínas Fúngicas/metabolismo , Glicerol/metabolismo , Metanol/metabolismo , Pichia/metabolismo , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismoRESUMO
Biology often provides the inspiration for functional soft matter, but biology can do more: it can provide the raw materials and mechanisms for hierarchical assembly. Biology uses polymers to perform various functions, and biologically derived polymers can serve as sustainable, self-assembling, and high-performance materials platforms for life-science applications. Biology employs enzymes for site-specific reactions that are used to both disassemble and assemble biopolymers both to and from component parts. By exploiting protein engineering methodologies, proteins can be modified to make them more susceptible to biology's native enzymatic activities. They can be engineered with fusion tags that provide (short sequences of amino acids at the C- and/or N- termini) that provide the accessible residues for the assembling enzymes to recognize and react with. This "biobased" fabrication not only allows biology's nanoscale components (i.e., proteins) to be engineered, but also provides the means to organize these components into the hierarchical structures that are prevalent in life.
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Aminoácidos/química , Materiais Biocompatíveis/química , Bioengenharia/métodos , Engenharia de Proteínas/métodos , Proteínas/química , Aminoácidos/genética , Aminoácidos/metabolismo , Animais , Bactérias/química , Bactérias/genética , Bactérias/metabolismo , Proteínas de Bactérias/química , Proteínas de Bactérias/genética , Proteínas de Bactérias/metabolismo , Biocatálise , Materiais Biocompatíveis/metabolismo , Humanos , Modelos Moleculares , Monofenol Mono-Oxigenase/metabolismo , Proteínas/genética , Proteínas/metabolismo , Percepção de Quorum , Transglutaminases/metabolismoRESUMO
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. Here we perform single-cell sequencing of antibody repertoires and transcriptomes of murine B cells following immunizations with a model therapeutic antigen target. 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 and transcriptional signatures failed to distinguish antigen-specific from nonspecific B cells, other features such as immunoglobulin G (IgG) subtype and sequence composition correlated with antigen specificity.
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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 less expanded clones. 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.
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Infecções por Arenaviridae/imunologia , Linfócitos T CD8-Positivos/imunologia , Vírus da Coriomeningite Linfocítica/imunologia , Receptores de Antígenos de Linfócitos T/genética , Transcriptoma , Doença Aguda , Animais , Infecções por Arenaviridae/genética , Infecções por Arenaviridae/metabolismo , Infecções por Arenaviridae/virologia , Linfócitos T CD8-Positivos/metabolismo , Linfócitos T CD8-Positivos/virologia , Doença Crônica , Células Clonais/metabolismo , Modelos Animais de Doenças , Feminino , Infecção Latente , Vírus da Coriomeningite Linfocítica/patogenicidade , Camundongos , Camundongos Endogâmicos C57BL , Fenótipo , Receptores de Antígenos de Linfócitos T/imunologia , Receptores de Antígenos de Linfócitos T/metabolismo , VirosesRESUMO
Motivation: Single-cell sequencing now enables the recovery of full-length immune receptor 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 single-cell datasets incorporating immune receptor repertoires and gene expression. Results: We developed Echidna, an R package that simulates immune receptors and transcriptomes at single-cell resolution with user-tunable parameters controlling a wide range of features such as clonal expansion, germline gene usage, somatic hypermutation, transcriptional phenotypes and spatial location. Echidna can additionally simulate time-resolved B cell evolution, producing mutational networks with complex selection histories incorporating class-switching and B cell subtype information. We demonstrated 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. Finally, we simulated immune repertoire information onto existing spatial transcriptomic experiments, thereby generating novel datasets that could be used to develop and integrate methods to profile clonal selection in a spatially resolved manner. 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. Availability and implementation: The R package and code used in this manuscript can be found at github.com/alexyermanos/echidna and also in the R package Platypus (Yermanos et al., 2021). Installation instructions and the vignette for Echidna is described in the Platypus Computational Ecosystem (https://alexyermanos.github.io/Platypus/index.html). Publicly available data and corresponding sample accession numbers can be found in Supplementary Tables S2 and S3. Supplementary information: Supplementary data are available at Bioinformatics Advances online.
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Characterization of COVID-19 antibodies 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 resolving SARS-CoV-2 infection. Little is known about the specificity of plasma cells, largely because plasma cells lack surface antibody expression, thereby complicating their screening. Here, we describe a technology pipeline that integrates single-cell antibody repertoire sequencing and mammalian display to interrogate the specificity of plasma cells from 16 convalescent patients. Single-cell sequencing allows us to profile antibody repertoire features and identify expanded clonal lineages. Mammalian display screening is used to reveal that 43 antibodies (of 132 candidates) derived from expanded plasma cell lineages are specific to SARS-CoV-2 antigens, including antibodies with high affinity to the SARS-CoV-2 receptor-binding domain (RBD) that exhibit potent neutralization and broad binding to the RBD of SARS-CoV-2 variants (of concern/interest).
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Anticorpos Neutralizantes/isolamento & purificação , Plasmócitos/metabolismo , SARS-CoV-2/imunologia , Análise de Célula Única/métodos , Animais , Anticorpos Antivirais/isolamento & purificação , COVID-19/imunologia , COVID-19/prevenção & controle , Células Cultivadas , Estudos de Coortes , Biblioteca Gênica , Células HEK293 , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Humanos , Mamíferos , Testes de Neutralização , Biblioteca de Peptídeos , Plasmócitos/químicaRESUMO
To explore the medication rules of famous veteran traditional Chinese medicine practitioners in treating infertility based on medical cases of infertility collected from book series of Hundred Traditional Chinese Medicine Clinicians of Hundred Years in China and Prescription Proven by Traditional Chinese Medicine Masters. Researchers extracted the information of prescriptions from these cases according to the inclusion and exclusion criteria. Then, Excel 2010, SPSS Clementine(ver.12.0) and SPSS(ver. 22.0) were adopted respectively for frequency analysis, association rules analysis, cluster analysis and factor analysis. Cluster analysis was carried out by Ochiai algorithm of binary variable data, which was a systematic clustering method. And principal component analysis was used for factor analysis. Besides, KMO test and Bartlett spherical test were used for factor adaptation test. Finally, 151 medical cases and 396 prescriptions were included in total. A total of 60 kinds of frequently used herbs were identified according to the results of frequency analysis for medication, they were mainly used for activating blood and resolving stasis, tonifying and clearing heat respectively. The association rules analysis found out 25 drug pair association rules and 14 3-drug combination association rules. A total of 15 medicine groups were extracted by cluster analysis. KMO test and Bartlett spherical test indicated that the method was suitable for factor analysis, and 21 common factors were respectively extracted by factor analysis. Association rules indicated the characteristics of the therapeutic methods, like tonifying Qi and replenishing blood. The famous veteran traditional Chinese medicine practitioners utilized modified Siwu Decoction for tonifying blood and preferred Atractylodis Macrocephalae Rhizoma(Baizhu) for tonifying Qi. The results of both cluster analysis and factor analysis demonstrated the characteristics of the therapies for tonifying kidney, activating blood, tonifying spleen and dispelling dampness. In addition, factor analysis could reflect the therapies for nourishing Yin, tonifying kidney, warming the meridian, dissipating cold, nourishing blood and dispelling blood stasis. These results of analysis comprehensively showed out the medication characteristics of famous veteran traditional Chinese medicine practitioners of strictly following the pathogenesis, making good use of classical formulas and providing proper compatibility. In conclusion, data mining techniques(including frequency analysis, association rules analysis, cluster analysis and factor analysis) were used to comprehensively analyze the medication rules of famous veteran traditional Chinese medicine practitioners in treating infertility, which is helpful for guiding the clinical practice of treating infertility with traditional Chinese medicine.