RESUMEN
The continual evolution of SARS-CoV-2 and the emergence of variants that show resistance to vaccines and neutralizing antibodies threaten to prolong the COVID-19 pandemic. Selection and emergence of SARS-CoV-2 variants are driven in part by mutations within the viral spike protein and in particular the ACE2 receptor-binding domain (RBD), a primary target site for neutralizing antibodies. Here, we develop deep mutational learning (DML), a machine-learning-guided protein engineering technology, which is used to investigate a massive sequence space of combinatorial mutations, representing billions of RBD variants, by accurately predicting their impact on ACE2 binding and antibody escape. A highly diverse landscape of possible SARS-CoV-2 variants is identified that could emerge from a multitude of evolutionary trajectories. DML may be used for predictive profiling on current and prospective variants, including highly mutated variants such as Omicron, thus guiding the development of therapeutic antibody treatments and vaccines for COVID-19.
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Enzima Convertidora de Angiotensina 2/metabolismo , COVID-19 , SARS-CoV-2 , Glicoproteína de la Espiga del Coronavirus/metabolismo , Enzima Convertidora de Angiotensina 2/química , Enzima Convertidora de Angiotensina 2/genética , Anticuerpos Neutralizantes , Anticuerpos Antivirales , Vacunas contra la COVID-19 , Humanos , Mutación , Pandemias , Unión Proteica , SARS-CoV-2/genética , Glicoproteína de la Espiga del Coronavirus/química , Glicoproteína de la Espiga del Coronavirus/genéticaRESUMEN
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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Inmunoterapia Adoptiva , Receptores de Antígenos de Linfocitos T , Antígenos de Neoplasias , Humanos , Inmunoterapia , PéptidosRESUMEN
Effective clustering of T-cell receptor (TCR) sequences could be used to predict their antigen-specificities. TCRs with highly dissimilar sequences can bind to the same antigen, thus making their clustering into a common antigen group a central challenge. Here, we develop TouCAN, a method that relies on contrastive learning and pretrained protein language models to perform TCR sequence clustering and antigen-specificity predictions. Following training, TouCAN demonstrates the ability to cluster highly dissimilar TCRs into common antigen groups. Additionally, TouCAN demonstrates TCR clustering performance and antigen-specificity predictions comparable to other leading methods in the field.
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Receptores de Antígenos de Linfocitos T , Receptores de Antígenos de Linfocitos T/inmunología , Receptores de Antígenos de Linfocitos T/metabolismo , Receptores de Antígenos de Linfocitos T/genética , Análisis por Conglomerados , Humanos , Antígenos/inmunología , Biología Computacional/métodos , Algoritmos , Aprendizaje AutomáticoRESUMEN
Abs are versatile molecules with the potential to achieve exceptional binding to target Ags, while also possessing biophysical properties suitable for therapeutic drug development. Protein display and directed evolution systems have transformed synthetic Ab discovery, engineering, and optimization, vastly expanding the number of Ab clones able to be experimentally screened for binding. Moreover, the burgeoning integration of high-throughput screening, deep sequencing, and machine learning has further augmented in vitro Ab optimization, promising to accelerate the design process and massively expand the Ab sequence space interrogated. In this Brief Review, we discuss the experimental and computational tools employed in synthetic Ab engineering and optimization. We also explore the therapeutic challenges posed by developing Abs for infectious diseases, and the prospects for leveraging machine learning-guided protein engineering to prospectively design Abs resistant to viral escape.
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Anticuerpos , Ingeniería de Proteínas , Anticuerpos/genética , Aprendizaje Automático , Proteínas , Ensayos Analíticos de Alto RendimientoRESUMEN
We present proximity sequencing (Prox-seq) for simultaneous measurement of proteins, protein complexes and mRNAs in thousands of single cells. Prox-seq combines proximity ligation assay with single-cell sequencing to measure proteins and their complexes from all pairwise combinations of targeted proteins, providing quadratically scaled multiplexing. We validate Prox-seq and analyze a mixture of T cells and B cells to show that it accurately identifies these cell types and detects well-known protein complexes. Next, by studying human peripheral blood mononuclear cells, we discover that naïve CD8+ T cells display the protein complex CD8-CD9. Finally, we study protein interactions during Toll-like receptor (TLR) signaling in human macrophages. We observe the formation of signal-specific protein complexes, find CD36 co-receptor activity and additive signal integration under lipopolysaccharide (TLR4) and Pam2CSK4 (TLR2) stimulation, and show that quantification of protein complexes identifies signaling inputs received by macrophages. Prox-seq provides access to an untapped measurement modality for single-cell phenotyping and can discover uncharacterized protein interactions in different cell types.
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Linfocitos T CD8-positivos , Leucocitos Mononucleares , Humanos , ARN Mensajero/genética , Receptor Toll-Like 2RESUMEN
The capacity of humoral B cell-mediated immunity to effectively respond to and protect against pathogenic infections is largely driven by the presence of a diverse repertoire of polyclonal antibodies in the serum, which are produced by plasma cells (PCs). Recent studies have started to reveal the balance between deterministic mechanisms and stochasticity of antibody repertoires on a genotypic level (i.e., clonal diversity, somatic hypermutation, and germline gene usage). However, it remains unclear if clonal selection and expansion of PCs follow any deterministic rules or are stochastic with regards to phenotypic antibody properties (i.e., antigen-binding, affinity, and epitope specificity). Here, we report on the in-depth genotypic and phenotypic characterization of clonally expanded PC antibody repertoires following protein immunization. We find that clonal expansion drives antigen specificity of the most expanded clones (top â¼10), whereas among the rest of the clonal repertoire antigen specificity is stochastic. Furthermore, we report both on a polyclonal repertoire and clonal lineage level that antibody-antigen binding affinity does not correlate with clonal expansion or somatic hypermutation. Last, we provide evidence for convergence toward targeting dominant epitopes despite clonal sequence diversity among the most expanded clones. Our results highlight the extent to which clonal expansion can be ascribed to antigen binding, affinity, and epitope specificity, and they have implications for the assessment of effective vaccines.
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Antígenos , Células Plasmáticas , Animales , Anticuerpos/genética , Afinidad de Anticuerpos , Epítopos/genética , RatonesRESUMEN
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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Ecosistema , Ornitorrinco , Animales , Biología Computacional/métodos , Filogenia , Aprendizaje Automático , Programas InformáticosRESUMEN
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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Anticuerpos Antivirales , Selección Clonal Mediada por Antígenos , Cadenas Pesadas de Inmunoglobulina , Cadenas Ligeras de Inmunoglobulina , Coriomeningitis Linfocítica , Virus de la Coriomeningitis Linfocítica/inmunología , Células Plasmáticas/inmunología , Análisis de la Célula Individual , Animales , Anticuerpos Antivirales/genética , Anticuerpos Antivirales/inmunología , Enfermedad Crónica , Femenino , Cadenas Pesadas de Inmunoglobulina/genética , Cadenas Pesadas de Inmunoglobulina/inmunología , Cadenas Ligeras de Inmunoglobulina/genética , Cadenas Ligeras de Inmunoglobulina/inmunología , Coriomeningitis Linfocítica/genética , Coriomeningitis Linfocítica/inmunología , RatonesRESUMEN
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 Productoras de Anticuerpos , Autoantígenos , Ratones , Animales , Linfocitos B , Virus de la Coriomeningitis Linfocítica , EncéfaloRESUMEN
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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Autoinmunidad , Coriomeningitis Linfocítica , Animales , Linfocitos T CD8-positivos , Modelos Animales de Enfermedad , Coriomeningitis Linfocítica/genética , Ratones , Ratones Endogámicos C57BL , Péptidos , Receptores de Antígenos de Linfocitos T/genéticaRESUMEN
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 , Genómica , Humanos , Mutación , SARS-CoV-2/genética , Secuenciación Completa del GenomaRESUMEN
Throughout the last several decades, vaccination has been key to prevent and eradicate infectious diseases. However, many pathogens (e.g., respiratory syncytial virus [RSV], influenza, dengue, and others) have resisted vaccine development efforts, largely because of the failure to induce potent antibody responses targeting conserved epitopes. Deep profiling of human B cells often reveals potent neutralizing antibodies that emerge from natural infection, but these specificities are generally subdominant (i.e., are present in low titers). A major challenge for next-generation vaccines is to overcome established immunodominance hierarchies and focus antibody responses on crucial neutralization epitopes. Here, we show that a computationally designed epitope-focused immunogen presenting a single RSV neutralization epitope elicits superior epitope-specific responses compared to the viral fusion protein. In addition, the epitope-focused immunogen efficiently boosts antibodies targeting the palivizumab epitope, resulting in enhanced neutralization. Overall, we show that epitope-focused immunogens can boost subdominant neutralizing antibody responses in vivo and reshape established antibody hierarchies.
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Anticuerpos Neutralizantes/biosíntesis , Anticuerpos Antivirales/biosíntesis , Epítopos/química , Receptores de Antígenos de Linfocitos B/inmunología , Proteínas Recombinantes de Fusión/química , Virus Sincitiales Respiratorios/inmunología , Proteínas Virales de Fusión/química , Animales , Anticuerpos Monoclonales Humanizados/química , Anticuerpos Monoclonales Humanizados/inmunología , Anticuerpos Neutralizantes/genética , Anticuerpos Antivirales/genética , Clonación Molecular , Diseño Asistido por Computadora , Epítopos/inmunología , Escherichia coli/genética , Escherichia coli/metabolismo , Femenino , Expresión Génica , Vectores Genéticos/química , Vectores Genéticos/metabolismo , Inmunización/métodos , Inmunogenicidad Vacunal , Ratones , Ratones Endogámicos BALB C , Nanopartículas/administración & dosificación , Nanopartículas/química , Palivizumab/química , Palivizumab/inmunología , Receptores de Antígenos de Linfocitos B/química , Receptores de Antígenos de Linfocitos B/genética , Proteínas Recombinantes de Fusión/administración & dosificación , Proteínas Recombinantes de Fusión/genética , Proteínas Recombinantes de Fusión/inmunología , Vacunas contra Virus Sincitial Respiratorio/administración & dosificación , Vacunas contra Virus Sincitial Respiratorio/biosíntesis , Vacunas contra Virus Sincitial Respiratorio/genética , Homología Estructural de Proteína , Proteínas Virales de Fusión/administración & dosificación , Proteínas Virales de Fusión/genética , Proteínas Virales de Fusión/inmunologíaRESUMEN
Neuroinflammation plays a crucial role during ageing and various neurological conditions, including Alzheimer's disease, multiple sclerosis and infection. Technical limitations, however, have prevented an integrative analysis of how lymphocyte immune receptor repertoires and their accompanying transcriptional states change with age in the central nervous system. Here, we leveraged single-cell sequencing to simultaneously profile B cell receptor and T cell receptor repertoires and accompanying gene expression profiles in young and old mouse brains. We observed the presence of clonally expanded B and T cells in the central nervous system of aged male mice. Furthermore, many of these B cells were of the IgM and IgD isotypes, and had low levels of somatic hypermutation. Integrating gene expression information additionally revealed distinct transcriptional profiles of these clonally expanded lymphocytes. Our findings implicate that clonally related T and B cells in the CNS of elderly mice may contribute to neuroinflammation accompanying homeostatic ageing.
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Sistema Nervioso Central , Transcriptoma , Animales , Linfocitos B , Linfocitos , Masculino , RatonesRESUMEN
SUMMARY: B- and T-cell receptor repertoires of the adaptive immune system have become a key target for diagnostics and therapeutics research. Consequently, there is a rapidly growing number of bioinformatics tools for immune repertoire analysis. Benchmarking of such tools is crucial for ensuring reproducible and generalizable computational analyses. Currently, however, it remains challenging to create standardized ground truth immune receptor repertoires for immunoinformatics tool benchmarking. Therefore, we developed immuneSIM, an R package that allows the simulation of native-like and aberrant synthetic full-length variable region immune receptor sequences by tuning the following immune receptor features: (i) species and chain type (BCR, TCR, single and paired), (ii) germline gene usage, (iii) occurrence of insertions and deletions, (iv) clonal abundance, (v) somatic hypermutation and (vi) sequence motifs. Each simulated sequence is annotated by the complete set of simulation events that contributed to its in silico generation. immuneSIM permits the benchmarking of key computational tools for immune receptor analysis, such as germline gene annotation, diversity and overlap estimation, sequence similarity, network architecture, clustering analysis and machine learning methods for motif detection. AVAILABILITY AND IMPLEMENTATION: The package is available via https://github.com/GreiffLab/immuneSIM and on CRAN at https://cran.r-project.org/web/packages/immuneSIM. The documentation is hosted at https://immuneSIM.readthedocs.io. CONTACT: sai.reddy@ethz.ch or victor.greiff@medisin.uio.no. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Benchmarking , Programas Informáticos , Simulación por Computador , Receptores de Antígenos de Linfocitos T/genéticaRESUMEN
In recent years, chimeric antigen receptor (CAR) T cell cancer immunotherapies have advanced substantially in the clinic. However, challenges related to safety persist; one major concern occurs when CARs trigger a response to antigen present on healthy cells (on-target, off-tumor response). A strategy to ameliorate this relies on the complex relationship between receptor affinity and signaling, such that one can engineer a CAR that is only activated by tumor cells expressing high antigen levels. Here, we developed a CAR T cell display platform with stable genomic expression and rapid functional screening based on interleukin-2 signaling. Starting with a CAR with high affinity toward its target antigen, we combined CRISPR-Cas9 genome editing and deep mutational scanning to generate a library of antigen-binding domain variants. This library was subjected to multiple rounds of selection based on either antigen binding or cell signaling. Deep sequencing of the resulting libraries and a comparative analysis revealed the enrichment and depletion of specific variants from which we selected CARs that were selectively activated by tumor cells based on antigen expression levels. Our platform demonstrates how directed evolution based on functional screening and deep sequencing-guided selection can be combined to enhance the selectivity and safety of CARs.
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Antígenos de Neoplasias/inmunología , Neoplasias de la Mama/inmunología , Ingeniería Celular/métodos , Inmunoterapia Adoptiva/métodos , Receptor ErbB-2/inmunología , Receptores de Antígenos de Linfocitos T alfa-beta/genética , Receptores de Antígenos de Linfocitos T alfa-beta/inmunología , Receptores Quiméricos de Antígenos/genética , Receptores Quiméricos de Antígenos/inmunología , Animales , Afinidad de Anticuerpos , Antígenos de Neoplasias/metabolismo , Neoplasias de la Mama/patología , Sistemas CRISPR-Cas , Técnicas de Cocultivo , Femenino , Edición Génica/métodos , Células HEK293 , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Humanos , Interleucina-2/genética , Interleucina-2/metabolismo , Células MCF-7 , Ratones , Receptor ErbB-2/metabolismo , Receptores de Antígenos de Linfocitos T alfa-beta/metabolismo , Receptores Quiméricos de Antígenos/metabolismo , Anticuerpos de Cadena Única/inmunologíaRESUMEN
Protection and neutralization of a vast array of pathogens is accomplished by the tremendous diversity of the B cell receptor (BCR) repertoire. For jawed vertebrates, this diversity is initiated via the somatic recombination of immunoglobulin (Ig) germline elements. While it is clear that the number of these germline segments differs from species to species, the extent of cross-species sequence diversity remains largely uncharacterized. Here we use extensive computational and statistical methods to investigate the sequence diversity and evolutionary relationship between Ig variable (V), diversity (D), and joining (J) germline segments across nine commonly studied species ranging from zebrafish to human. Metrics such as guanine-cytosine (GC) content showed low redundancy across Ig germline genes within a given species. Other comparisons, including amino acid motifs, evolutionary selection, and sequence diversity, revealed species-specific properties. Additionally, we showed that the germline-encoded diversity differs across antibody (recombined V-D-J) repertoires of various B cell subsets. To facilitate future comparative immunogenomics analysis, we created VDJgermlines, an R package that contains the germline sequences from multiple species. Our study informs strategies for the humanization and engineering of therapeutic antibodies.
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Variación Genética , Región Variable de Inmunoglobulina/genética , Filogenia , Secuencias de Aminoácidos , Animales , Diversidad de Anticuerpos/genética , Subgrupos de Linfocitos B/metabolismo , Linfocitos B/metabolismo , Composición de Base , Humanos , Cadenas Pesadas de Inmunoglobulina/química , Cadenas Pesadas de Inmunoglobulina/genética , Cadenas Pesadas de Inmunoglobulina/metabolismo , Región Variable de Inmunoglobulina/química , Selección Genética , Especificidad de la Especie , Recombinación V(D)J/genética , VertebradosRESUMEN
Antibody engineering is often performed to improve therapeutic properties by directed evolution, usually by high-throughput screening of phage or yeast display libraries. Engineering antibodies in mammalian cells offer advantages associated with expression in their final therapeutic format (full-length glycosylated IgG); however, the inability to express large and diverse libraries severely limits their potential throughput. To address this limitation, we have developed homology-directed mutagenesis (HDM), a novel method which extends the concept of CRISPR/Cas9-mediated homology-directed repair (HDR). HDM leverages oligonucleotides with degenerate codons to generate site-directed mutagenesis libraries in mammalian cells. By improving HDR to a robust efficiency of 15-35% and combining mammalian display screening with next-generation sequencing, we validated this approach can be used for key applications in antibody engineering at high-throughput: rational library construction, novel variant discovery, affinity maturation and deep mutational scanning (DMS). We anticipate that HDM will be a valuable tool for engineering and optimizing antibodies in mammalian cells, and eventually enable directed evolution of other complex proteins and cellular therapeutics.
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Anticuerpos/inmunología , Sistemas CRISPR-Cas , Mutagénesis Sitio-Dirigida , Ingeniería de Proteínas/métodos , Secuencia de Aminoácidos , Animales , Anticuerpos/genética , Anticuerpos/metabolismo , Afinidad de Anticuerpos/genética , Afinidad de Anticuerpos/inmunología , Secuencia de Bases , Línea Celular , Roturas del ADN de Doble Cadena , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Humanos , Hibridomas , Oligonucleótidos/genética , Oligonucleótidos/metabolismo , Reparación del ADN por RecombinaciónRESUMEN
Recent studies have revealed that immune repertoires contain a substantial fraction of public clones, which may be defined as Ab or TCR clonal sequences shared across individuals. It has remained unclear whether public clones possess predictable sequence features that differentiate them from private clones, which are believed to be generated largely stochastically. This knowledge gap represents a lack of insight into the shaping of immune repertoire diversity. Leveraging a machine learning approach capable of capturing the high-dimensional compositional information of each clonal sequence (defined by CDR3), we detected predictive public clone and private clone-specific immunogenomic differences concentrated in CDR3's N1-D-N2 region, which allowed the prediction of public and private status with 80% accuracy in humans and mice. Our results unexpectedly demonstrate that public, as well as private, clones possess predictable high-dimensional immunogenomic features. Our support vector machine model could be trained effectively on large published datasets (3 million clonal sequences) and was sufficiently robust for public clone prediction across individuals and studies prepared with different library preparation and high-throughput sequencing protocols. In summary, we have uncovered the existence of high-dimensional immunogenomic rules that shape immune repertoire diversity in a predictable fashion. Our approach may pave the way for the construction of a comprehensive atlas of public mouse and human immune repertoires with potential applications in rational vaccine design and immunotherapeutics.
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Linfocitos B/fisiología , Regiones Determinantes de Complementariedad/genética , Inmunoterapia/métodos , Receptores de Antígenos de Linfocitos B/genética , Receptores de Antígenos de Linfocitos T/genética , Linfocitos T/fisiología , Vacunas/inmunología , Animales , Diversidad de Anticuerpos , Selección Clonal Mediada por Antígenos , Células Clonales , Conjuntos de Datos como Asunto , Secuenciación de Nucleótidos de Alto Rendimiento , Humanos , Ratones , Ratones Endogámicos BALB C , Ratones Endogámicos C57BLRESUMEN
Monoclonal antibody discovery and engineering is a field that has traditionally been dominated by high-throughput screening platforms (e.g. hybridomas and surface display). In recent years the emergence of high-throughput sequencing has made it possible to obtain large-scale information on antibody repertoire diversity. Additionally, it has now become more routine to perform high-throughput sequencing on antibody repertoires to also directly discover antibodies. In this review, we provide an overview of the progress in this field to date and show how high-throughput screening and sequencing are converging to deliver powerful new workflows for monoclonal antibody discovery and engineering.
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Anticuerpos Monoclonales/genética , Anticuerpos Monoclonales/inmunología , Descubrimiento de Drogas , Ingeniería Genética , Secuenciación de Nucleótidos de Alto Rendimiento , Ensayos Analíticos de Alto Rendimiento , Animales , Anticuerpos Monoclonales/farmacología , Descubrimiento de Drogas/métodos , Ingeniería Genética/métodos , Secuenciación de Nucleótidos de Alto Rendimiento/métodos , Ensayos Analíticos de Alto Rendimiento/métodos , HumanosRESUMEN
MOTIVATION: The evolution of antibody repertoires represents a hallmark feature of adaptive B-cell immunity. Recent advancements in high-throughput sequencing have dramatically increased the resolution to which we can measure the molecular diversity of antibody repertoires, thereby offering for the first time the possibility to capture the antigen-driven evolution of B cells. However, there does not exist a repertoire simulation framework yet that enables the comparison of commonly utilized phylogenetic methods with regard to their accuracy in inferring antibody evolution. RESULTS: Here, we developed AbSim, a time-resolved antibody repertoire simulation framework, which we exploited for testing the accuracy of methods for the phylogenetic reconstruction of B-cell lineages and antibody molecular evolution. AbSim enables the (i) simulation of intermediate stages of antibody sequence evolution and (ii) the modeling of immunologically relevant parameters such as duration of repertoire evolution, and the method and frequency of mutations. First, we validated that our repertoire simulation framework recreates replicates topological similarities observed in experimental sequencing data. Second, we leveraged Absim to show that current methods fail to a certain extent to predict the true phylogenetic tree correctly. Finally, we formulated simulation-validated guidelines for antibody evolution, which in the future will enable the development of accurate phylogenetic methods. AVAILABILITY AND IMPLEMENTATION: https://cran.r-project.org/web/packages/AbSim/index.html. CONTACT: sai.reddy@ethz.ch. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.