CDR3 Research Articles

An Integrated Strategy to Identify Tyrosine Sulfation from the Therapeutic Proteins.

Posttranslational modifications (PTMs) are potential critical quality attributes in biotherapeutic development, as they can affect drug efficacy and safety. Tyrosine sulfation plays a critical role in protein-protein interactions and has been found on many surface receptors as well as antibody complementarity-determining regions (CDR). However, the presence and function of tyrosine sulfation in therapeutic proteins have not been broadly investigated due to difficulties in detecting the modification. Here, we establish an integrated strategy to identify tyrosine sulfation in biotherapeutic proteins. In silico prediction was used to estimate possible modification sites, followed by the elucidation with intact LCMS and native SCX-MS. The combination of these three steps takes less than 1 h, which provides quick and confident preliminary detection of potential CQAs. Taking NB1 as an example, three +80 Da mass shifts were observed from intact mass analysis and three acidic peaks were monitored by SCX, allowing confirmation of modification as either phosphorylation or sulfation. Peptide mapping, Fe3+-IMAC enrichment, and dephosphorylation were further conducted to provide improved signal intensity and differentiation of modification such as sulfation or phosphorylation. With this integrated strategy, we were able to identify for the first time both tyrosine sulfation and serine phosphorylation in one therapeutic protein.

Predictability of antigen binding based on short motifs in the antibody CDRH3.

Adaptive immune receptors, such as antibodies and T-cell receptors, recognize foreign threats with exquisite specificity. A major challenge in adaptive immunology is discovering the rules governing immune receptor-antigen binding in order to predict the antigen binding status of previously unseen immune receptors. Many studies assume that the antigen binding status of an immune receptor may be determined by the presence of a short motif in the complementarity determining region 3 (CDR3), disregarding other amino acids. To test this assumption, we present a method to discover short motifs which show high precision in predicting antigen binding and generalize well to unseen simulated and experimental data. Our analysis of a mutagenesis-based antibody dataset reveals 11 336 position-specific, mostly gapped motifs of 3-5 amino acids that retain high precision on independently generated experimental data. Using a subset of only 178 motifs, a simple classifier was made that on the independently generated dataset outperformed a deep learning model proposed specifically for such datasets. In conclusion, our findings support the notion that for some antibodies, antigen binding may be largely determined by a short CDR3 motif. As more experimental data emerge, our methodology could serve as a foundation for in-depth investigations into antigen binding signals.

Development and experimental validation of computational methods for human antibody affinity enhancement.

High affinity is crucial for the efficacy and specificity of antibody. Due to involving high-throughput screens, biological experiments for antibody affinity maturation are time-consuming and have a low success rate. Precise computational-assisted antibody design promises to accelerate this process, but there is still a lack of effective computational methods capable of pinpointing beneficial mutations within the complementarity-determining region (CDR) of antibodies. Moreover, random mutations often lead to challenges in antibody expression and immunogenicity. In this study, to enhance the affinity of a human antibody against avian influenza virus, a CDR library was constructed and evolutionary information was acquired through sequence alignment to restrict the mutation positions and types. Concurrently, a statistical potential methodology was developed based on amino acid interactions between antibodies and antigens to calculate potential affinity-enhanced antibodies, which were further subjected to molecular dynamics simulations. Subsequently, experimental validation confirmed that a point mutation enhancing 2.5-fold affinity was obtained from 10 designs, resulting in the antibody affinity of 2nM. A predictive model for antibody-antigen interactions based on the binding interface was also developed, achieving an Area Under the Curve (AUC) of 0.83 and a precision of 0.89 on the test set. Lastly, a novel approach involving combinations of affinity-enhancing mutations and an iterative mutation optimization scheme similar to the Monte Carlo method were proposed. This study presents computational methods that rapidly and accurately enhance antibody affinity, addressing issues related to antibody expression and immunogenicity.

Structural insights into CXCR4 modulation and oligomerization.

Activation of the chemokine receptor CXCR4 by its chemokine ligand CXCL12 regulates diverse cellular processes. Previously reported crystal structures of CXCR4 revealed the architecture of an inactive, homodimeric receptor. However, many structural aspects of CXCR4 remain poorly understood. Here, we use cryo-electron microscopy to investigate various modes of human CXCR4 regulation. CXCL12 activates CXCR4 by inserting its N terminus deep into the CXCR4 orthosteric pocket. The binding of US Food and Drug Administration-approved antagonist AMD3100 is stabilized by electrostatic interactions with acidic residues in the seven-transmembrane-helix bundle. A potent antibody blocker, REGN7663, binds across the extracellular face of CXCR4 and inserts its complementarity-determining region H3 loop into the orthosteric pocket. Trimeric and tetrameric structures of CXCR4 reveal modes of G-protein-coupled receptor oligomerization. We show that CXCR4 adopts distinct subunit conformations in trimeric and tetrameric assemblies, highlighting how oligomerization could allosterically regulate chemokine receptor function.

Full-Length Immune Repertoire Reconstruction and Profiling at the Transcriptome Level Using Long-Read Sequencing.

Due to the diversity of the immune repertoire (IR), reconstructing full-length IR using traditional short-read sequencing has proven challenging. A full-length IR sequencing (FLIRseq) work flow was developed with linear rolling circle amplification and nanopore sequencing. Its accuracy and quantification ability were verified by plasmid mixtures and commercial B-cell receptor/T-cell receptor sequencing (BCR/TCR-seq) based on short reads. IRs in tissues and the peripheral blood from 8 patients with acute lymphoblastic leukemia, 3 patients with allergic diseases, 4 patients with psoriasis, and 5 patients with prostate cancer were analyzed using FLIRseq. FLIRseq reads had lower mismatch rates and gap rates, and higher identify rates than nanopore reads (all P < 2.2 × -16). The relative quantification of components by FLIRseq was consistent with the actual quantification (P > 0.05). FLIRseq had superiority over BCR/TCR-seq, providing the long complementarity-determining region 3, B-cell isotype, and the rarely used V gene sequence. FLIRseq observed an increase in clonotype diversity (P < 0.05) and a decrease in the percentage of abnormal BCRs/TCRs in patients with leukemia in remission. For patients with allergic diseases or psoriasis, FLIRseq provided direct insights into V(D)J recombination and specific immunoglobulin classes. Compared with that in prostate cancer tissues, the full-length V segment of the biased T-cell receptor β chain from lymphocytes in psoriatic tissues showed a more consistent AlphaFold2-predicted protein structure (P < 0.05). FLIRseq enables unbiased and comprehensive analyses of direct V(D)J recombination and immunoglobulin classes, thereby contributing to characterizing pathogenic mechanisms, monitoring minimal residual disease, and customizing adoptive cell therapy.

The 1H, 15N, and 13C resonance assignments of a single-domain antibody against immunoglobulin G.

Research on camelid-derived single-domain antibodies (sdAbs) has demonstrated their significant utility in diverse biotechnological applications, including therapy and diagnostic. This is largely due to their relative simplicity as monomeric proteins, ranging from 12 to 15kDa, in contrast to immunoglobulin G (IgG) antibodies, which are glycosylated heterotetramers of 150-160kDa. Single-domain antibodies exhibit high conformational stability and adopt the typical immunoglobulin domain fold, consisting of a two-layer sandwich of 7-9 antiparallel beta-strands. They contain three loops, known as complementary-determining regions (CDRs), which are assembled on the sdAb surface and are responsible for antigen recognition. The single-domain antibody examined in this study, sdAb-mrh-IgG, was engineered to recognize IgG from rats, mice, but it also weakly recognizes IgG from humans (Pleiner et al. 2018). A search of the Protein Data Bank revealed only one NMR structure of a single-domain antibody, which is unrelated to sdAb-mrh-IgG. The NMR chemical shift assignments of sdAb-mrh-IgG will be utilized to study its molecular dynamics and interactions with antigens in solution, which is fundamental for the rational design of novel single-domain antibodies.

FvFold: A model to predict antibody Fv structure using protein language model with residual network and Rosetta minimization

The immune system depends on antibodies (Abs) to recognize and attach to a wide range of antigens, playing a pivotal role in immunity. The precise prediction of the variable fragment (Fv) region of antibodies is vital for the progress of therapeutic and commercial applications, particularly in the treatment of diseases such as cancer. Although deep learning models exist for accurate antibody structure prediction, challenges persist, particularly in modeling complementarity-determining regions (CDRs) and the overall antibody Fv structures. Introducing the FvFold model, a deep learning approach harnessing the capabilities of the ProtT5-XL-UniRef50 protein language model which is capable of predicting accurate antibody Fv structure. Through evaluations on various benchmarks, our model outperforms existing models, demonstrating superior accuracy by achieving lower Root Mean Square Deviation (RMSD) in almost all loops and Orientational Coordinate Distance (OCD) values in the RosettaAntibody benchmark, Therapeutic benchmark and IgFold benchmark compared to the previous top-performing model.

Guiding Diffusion Models for Antibody Sequence and Structure Co-design with Developability Properties

Recent advances in deep generative methods have allowed antibody sequence and structure co-design. This study addresses the challenge of tailoring the highly variable complementarity-determining regions (CDRs) in antibodies to fulfill developability requirements. We introduce a guidance approach that integrates property information into the antibody design process using diffusion probabilistic models. This approach allows us to simultaneously design CDRs conditioned on antigen structures while considering critical properties like solubility and folding stability. Our property-guided diffusion model offers versatility by accommodating diverse property constraints, presenting a promising avenue for computational antibody design in therapeutic applications. Published by the American Physical Society 2024

EpiScan: accurate high-throughput mapping of antibody-specific epitopes using sequence information

The identification of antibody-specific epitopes on virus proteins is crucial for vaccine development and drug design. Nonetheless, traditional wet-lab approaches for the identification of epitopes are both costly and labor-intensive, underscoring the need for the development of efficient and cost-effective computational tools. Here, EpiScan, an attention-based deep learning framework for predicting antibody-specific epitopes, is presented. EpiScan adopts a multi-input and single-output strategy by designing independent blocks for different parts of antibodies, including variable heavy chain (VH), variable light chain (VL), complementary determining regions (CDRs), and framework regions (FRs). The block predictions are weighted and integrated for the prediction of potential epitopes. Using multiple experimental data samples, we show that EpiScan, which only uses antibody sequence information, can accurately map epitopes on specific antigen structures. The antibody-specific epitopes on the receptor binding domain (RBD) of SARS coronavirus 2 (SARS-CoV-2) were located by EpiScan, and the potentially valuable vaccine epitope was identified. EpiScan can expedite the epitope mapping process for high-throughput antibody sequencing data, supporting vaccine design and drug development. Availability: For the convenience of related wet-experimental researchers, the source code and web server of EpiScan are publicly available at https://github.com/gzBiomedical/EpiScan.

Extended Conformational Selection in the Antigen-Antibody Interaction of the PfAMA1 Protein.

Plasmodium falciparum apical membrane antigen 1 (PfAMA1) is a surface protein found in two stages of the malaria life cycle. This is a protein involved in a reorientation movement of the parasite so that cell invasion occurs in the so-called "moving junction", relevant when the membranes of the parasite and the host are in contact. The structure of a conformational epitope of domain III of PfAMA1 in complex with the monoclonal antibody Fab F8.12.19 is experimentally known. Here, we used molecular dynamics with enhanced sampling by Hamiltonian replica exchange molecular dynamics (HREMD) to understand the effect of intermolecular interactions, conformational variability, and intrinsically disordered regions on the mechanism of antigen-antibody interaction. Clustering methods and the analysis of conformational variability were used in order to understand the influence of the presence of the partner protein in the complex. The free-state epitope accesses a broader conformational pool, including disordered conformations not seen in the bound state. The simulations suggest an extended conformational selection mechanism in which the antibody stabilizes a conformational set of the epitope existing in the free state. The stabilization of the active conformation occurs mainly through hydrogen bonds: Tyr(H33)-Asp493, His(L94)-Val510, Ser(L93)-Glu511, Tyr(H56)-Asp485, and Tyr(H35)-Asp493. The antibody has a structure with few flexible regions, and only the complementarity determining region (CDR) H3 shows greater plasticity in the presence of the epitope.

Microbial community composition in subgingival plaques and heterogeneity of tumor tissue TCRβ CDR3 repertoire in patients with moderate-to-severe periodontitis and oral squamous cell carcinoma.

The human oral cavity contains over 700 types of bacteria that may protect the body against colonization by exogenous pathogens and maintain relative homeostasis. However, alterations in the immune status can disrupt the balance between microorganisms and the host, inducing various diseases such as oral cancer and diabetes mellitus. The mechanism underlying this process is not clearly understood. The purpose of this study was to investigate the relationships between subgingival bacteria, T-cell receptor β-chain complementarity-determining region 3 (TCRβ CDR3), and the development oforal squamous cell carcinoma (OSCC). We grouped patients as "healthy periodontal" (H), "moderate-to-severe chronic periodontitis" (C), and "moderate-to-severe chronic periodontitis with OSCC" (T). Bacterial groups were "subgingival plaque" (bp) and "gingival/tumor tissue" (g). We also recorded patients' age, gender, attachment level (AL), bleeding on probing (BOP), and probing depth (PD). We extracted and sequenced RNA from plaques, gingival tissues, tumors, and teeth. We performed high-throughput sequencing on TCRβ CDR3 and plaque bacteria. Synergistetes and Veillonella parvula were more abundant in the H group than in the T group. Granulicatella, Peptostreptococcus, and Streptococcus infantis were enriched in the T-bp group. AL, BOP, and PD were positively correlated with Granulicatella, Peptostreptococcus, and Pseudomonas but negatively correlated with Prevotella nigrescens and V. parvula. TCRβ CDR3 diversity was C > H > T. TCR β-chain Variable gene (TRBV)20-1 usage varied among the H, C, and T groups. TRBV2 and TRBV5-1 usage was greater in the T group than in the C group. TRBJ1-1, TRBJ1-2, TRBJ2-2, TRBJ2-7, and TRBJ2-5 were most frequently used. These trends and the reduction of gingival Synergistetes were correlated with OSCC. TCRβ CDR3 diversity was the lowest in patients in the T group, and there were considerable changes in the expression of TRBV2 and TRBJ. Therefore, plaque bacterial composition can influence TCRβ CDR3.

Construction and validation of a synthetic phage-displayed nanobody library.

Nanobodies derived from camelids and sharks offer unique advantages in therapeutic applications due to their ability to bind to epitopes that were previously inaccessible. Traditional methods of nanobody development face challenges such as ethical concerns and antigen toxicity. Our study presents a synthetic, phagedisplayed nanobody library using trinucleotide-directed mutagenesis technology, which allows precise amino acid composition in complementarity-determining regions (CDRs), with a focus on CDR3 diversity. This approach avoids common problems such as frameshift mutations and stop codon insertions associated with other synthetic antibody library construction methods. By analyzing FDA-approved nanobodies and Protein Data Bank sequences, we designed sub-libraries with different CDR3 lengths and introduced amino acid substitutions to improve solubility. The validation of our library through the successful isolation of nanobodies against targets such as PD-1, ATXN1 and STAT3 demonstrates a versatile and ethical platform for the development of high specificity and affinity nanobodies and represents a significant advance in biotechnology.

Germline-targeting HIV vaccination induces neutralizing antibodies to the CD4 binding site.

Eliciting potent and broadly neutralizing antibodies (bnAbs) is a major goal in HIV-1 vaccine development. Here, we describe how germline-targeting immunogen BG505 SOSIP germline trimer 1.1 (GT1.1), generated through structure-based design, engages a diverse range of VRC01-class bnAb precursors. A single immunization with GT1.1 expands CD4 binding site (CD4bs)-specific VRC01-class B cells in knock-in mice and drives VRC01-class maturation. In nonhuman primates (NHPs), GT1.1 primes CD4bs-specific neutralizing serum responses. Selected monoclonal antibodies (mAbs) isolated from GT1.1-immunized NHPs neutralize fully glycosylated BG505 virus. Two mAbs, 12C11 and 21N13, neutralize subsets of diverse heterologous neutralization-resistant viruses. High-resolution structures revealed that 21N13 targets the same conserved residues in the CD4bs as VRC01-class and CH235-class bnAbs despite its low sequence similarity (~40%), whereas mAb 12C11 binds predominantly through its heavy chain complementarity-determining region 3. These preclinical data underpin the ongoing evaluation of GT1.1 in a phase 1 clinical trial in healthy volunteers.

A Novel Antigen Design Strategy to Isolate Single-Domain Antibodies that Target Human Nav1.7 and Reduce Pain in Animal Models.

Genetic studies have identified the voltage-gated sodium channel 1.7 (Nav1.7) as pain target. Due to the ineffectiveness of small molecules and monoclonal antibodies as therapeutics for pain, single-domain antibodies (VHHs) are developed against the human Nav1.7 (hNav1.7) using a novel antigen presentation strategy. A 70 amino-acid peptide from the hNav1.7 protein is identified as a target antigen. A recombinant version of this peptide is grafted into the complementarity determining region 3 (CDR3) loop of an inert VHH in order to maintain the native 3D conformation of the peptide. This antigen is used to isolate one VHH able to i) bind hNav1.7, ii) slow the deactivation of hNav1.7, iii) reduce the ability of eliciting action potentials in nociceptors, and iv) reverse hyperalgesia in in vivo rat and mouse models. This VHH exhibits the potential to be developed as a therapeutic capable of suppressing pain. This novel antigen presentation strategy can be applied to develop biologics against other difficult targets such as ion channels, transporters and GPCRs.

T-cell receptor architecture and clonal tiding provide insight into the transformation trajectory of peripheral T-cell lymphomas.

While T cell lymphomas are classified as mature neoplasms, emerging evidence indicates that malignant transformation may occur at an earlier stage of T cell maturation. In this study, we determined clonal architectures in a broad range of T cell lymphomas. Our multidimensional profiling indicates that a large part of these lymphomas in fact emerge from an immature lymphoid T cell precursor at a maturation stage prior to V(D)J rearrangement that undergoes branching evolution. Consequently, at single cell resolution we observed considerable clonal tiding under selective therapeutic pressure. T cell receptor next-generation sequencing suggested a highly biased usage of TRBV20-1 gene segments as part of multiple antigen receptor rearrangements per patient. The predominance of TRBV20-1 was found across all major T cell lymphoma subtypes analyzed. This suggested that this particular V gene - independently of complementarity-determining region 3 (CDR3) configuration - may represent a driver of malignant transformation. Together, our data indicate that T cell lymphomas derive from immature lymphoid precursors and display considerable intratumoral heterogeneity that may provide the basis for relapse and resistance in these hard-to-treat cancers.

Worse Wilms' Tumor Outcomes Associated With Chemical Complementarity for Multiple T-Cell Receptor CDR3-CMV Epitope Pairs.

Wilms' tumors are pediatric renal tumors that generally have a good prognosis and outcomes. Viral illnesses have been linked to development of neoplasms and should be considered as a factor that could modulate overall survival. We considered recently developed adaptive immune receptor, genomics and bioinformatics approaches to assess the potential impact of cytomegalovirus (CMV) infections in Wilms' tumor. T-cell receptor (TCR) complementarity determining region-3 (CDR3) amino acid sequences from Wilms' tumor specimens represented by the Therapeutically Applicable Research to Generate Effective Treatments dataset were compared with known anti-CMV TCR CDR3s, indicating that cases representing the anti-CMV TCR CDR3s had worse outcomes. Then, a chemical complementarity scoring approach for the Wilms' tumor, TCR CDR3s and a series of CMV antigens further indicated that cases representing a higher chemical complementarity to the CMV antigens had worse outcomes. Overall, we present a potentially novel method to assess CMV infections and identify patients who could benefit from therapies that address such infections.

Fully human monoclonal antibodies against Ebola virus possess complete protection in a hamster model

ABSTRACT Ebola disease is a lethal viral hemorrhagic fever caused by ebolaviruses within the Filoviridae family with mortality rates of up to 90%. Monoclonal antibody (mAb) based therapies have shown great potential for the treatment of EVD. However, the potential emerging ebolavirus isolates and the negative effect of decoy protein on the therapeutic efficacy of antibodies highlight the necessity of developing novel antibodies to counter the threat of Ebola. Here, 11 fully human mAbs were isolated from transgenic mice immunized with GP protein and recombinant vesicular stomatitis virus-bearing GP (rVSV-EBOV GP). These mAbs were divided into five groups according to their germline genes and exhibited differential binding activities and neutralization capabilities. In particular, mAbs 8G6, 2A4, and 5H4 were cross-reactive and bound at least three ebolavirus glycoproteins. mAb 4C1 not only exhibited neutralizing activity but no cross-reaction with sGP. mAb 7D8 exhibited the strongest neutralizing capacity. Further analysis on the critical residues for the bindings of 4C1 and 8G6 to GPs was conducted using antibodies complementarity-determining regions (CDRs) alanine scanning. It has been shown that light chain CDR3 played a crucial role in binding and neutralization and that any mutation in CDRs could not improve the binding of 4C1 to sGP. Importantly, mAbs 7D8, 8G6, and 4C1 provided complete protections against EBOV infection in a hamster lethal challenge model when administered 12 h post-infection. These results support mAbs 7D8, 8G6, and 4C1 as potent antibody candidates for further investigations and pave the way for further developments of therapies and vaccines.

Structural Basis for the Recognition of GPRC5D by Talquetamab, a Bispecific Antibody for Multiple Myeloma

Multiple myeloma (MM) is a complex hematological malignancy characterized by abnormal antibody production from plasma cells. Despite advances in the treatment, many patients experience disease relapse or become refractory to treatment. G-protein-coupled receptor class C group 5 member D (GPRC5D), an orphan GPCR predominantly expressed in MM cells, is emerging as a promising target for MM immunotherapy. Talquetamab, a Food and Drug Administration-approved T-cell-directing bispecific antibody developed for treatment of MM, targets GPRC5D. Here, we elucidate the structure of GPRC5D complexed with the Fab fragment of talquetamab, using cryo-electron microscopy, providing the basis for recognition of GPRC5D by the bispecific antibody. GPRC5D forms a symmetric homodimer with the interface between transmembrane helix (TM) 4 of one protomer and TM4/5 of the other protomer. A single talquetamab Fab interacts with the GPRC5D dimer with its orientation toward the dimer interface. All six complementarity-determining regions of talquetamab engage with extracellular loops and TM3/5/7. In particular, the side-chain of an arginine residue from the antibody penetrates into a shallow pocket on the extracellular surface of GPRC5D. The structure offers insights for optimizing antibody design against GPRC5D for relapsed or refractory MM therapy.

Characterization of a Novel Monoclonal Antibody with High Affinity and Specificity against Aflatoxins: A Discovery from Rosetta Antibody-Ligand Computational Simulation.

Aflatoxin B1 (AFB1) accumulates in crops, where it poses a threat to human health. To detect AFB1, anti-AFB1 monoclonal antibodies have been developed and are widely used. While the sensitivity and specificity of these antibodies have been extensively studied, information regarding the atomic-level docking of AFB1 (and its derivatives) with these antibodies is limited. Such information is crucial for understanding the key interactions that are required for high affinity and specificity in aflatoxin binding. First, a 3D comparative model of anti-AFB1 antibody (Ab-4B5G6) was predicted from the sequence using RosettaAntibody. We then utilized RosettaLigand to dock AFB1 onto ten homology models, producing a total of 10,000 binding modes. Interestingly, the best-scoring mode predicted strong interactions involving four sites within the heavy chain: ALA33, ASN52, HIS95, and TRP99. Importantly, these strong binding interactions exclusively involve the variable domain of the heavy chain. The best-scoring mode with AFB1 was also obtained through AF multimer combined with RosettaLigand, and two interactions at TRP and HIS were consistent with those found by Rosetta antibody-ligand computational simulation. The role of tryptophan in π interactions in antibodies was confirmed through mutation experiments, and the resulting mutant (W99A) exhibited a >1000-fold reduction in binding affinity for AFB1 and analogs, indicating the effect of tryptophan on the stability of CDR-H3 region. Additionally, we evaluated the binding of two glycolic acid-derived molecular derivatives (with impaired hydrogen bonding potential), and these derivatives (AFB2-GA and AFG2-GA) demonstrated a very weak binding affinity for Ab-4B5G6. The heavy chain was successfully isolated, and its sensitivity and specificity were consistent with those of the intact antibody. The homology models of variable heavy (VH) single-domain antibodies were established by RosettaAntibody, and the docking analysis revealed the same residues, including Ala, His, and Trp. Compared to the potential binding mode of fragment variable (FV) region, the results from a model of VH indicated that there are seven models involved in hydrophobic interaction with TYR32, which is usually referred to as polar amino acid and has both hydrophobic and hydrophilic features depending on the circumstances. Our work encompasses the entire process of Rosetta antibody-ligand computational simulation, highlighting the significance of variable heavy domain structural design in enhancing molecular interactions.

Generation of Chicken Antibody Libraries and Selection of Antigen Binders.

Chicken antibodies have been widely used for research and diagnostic purposes. Chicken antibodies are often cross-reactive to epitopes shared by humans, nonhuman primates, and other mammals, and can be tested in many mouse disease models, which provides an advantage for their preclinical study and evaluation. In addition, the variable region of chicken antibodies has unique structural characteristics, including noncanonical cysteine residues in the heavy chain complementarity-determining region (CDR)3 and a long heavy chain CDR3, which together with a short light chain CDR enable the formation of unconventional antibody paratopes. As chickens have single functional copies of the V H and J H genes, and the somatic gene conversion process usually involves D H genes, all functional VDJ gene fragments can be obtained from the B-cell repertoire using a single PCR primer set, without any primer bias. As for the light chain, chickens only have a V λ light chain, composed of a single V λ and J λ gene pair. Therefore, the chicken light chain repertoire can also be accurately amplified using a single primer set. This unbiased reconstitution of the chicken B-cell repertoire provides a great advantage not only in the construction of phage display libraries but also for the in silico selection of antigen binders from a virtual B-cell receptor repertoire. Here, we introduce the use of chicken antibodies in research, diagnostic, and therapeutic fields. In addition, the chromosomal organization of chicken immunoglobulin genes and its diversification mechanisms for shaping the antibody repertoire are also discussed.