BTG1 mutation yields supercompetitive B cells primed for malignant transformation.

Multicellular life requires altruistic cooperation between cells. The adaptive immune system is a notable exception, wherein germinal center B cells compete vigorously for limiting positive selection signals. Studying primary human lymphomas and developing new mouse models, we found that mutations affecting BTG1 disrupt a critical immune gatekeeper mechanism that strictly limits B cell fitness during antibody affinity maturation. This mechanism converted germinal center B cells into supercompetitors that rapidly outstrip their normal counterparts. This effect was conferred by a small shift in MYC protein induction kinetics but resulted in aggressive invasive lymphomas, which in humans are linked to dire clinical outcomes. Our findings reveal a delicate evolutionary trade-off between natural selection of B cells to provide immunity and potentially dangerous features that recall the more competitive nature of unicellular organisms.

Using Graph-Based Signatures to Guide Rational Antibody Engineering.

Antibodies are essential experimental and diagnostic tools and as biotherapeutics have significantly advanced our ability to treat a range of diseases. With recent innovations in computational tools to guide protein engineering, we can now rationally design better antibodies with improved efficacy, stability, and pharmacokinetics. Here, we describe the use of the mCSM web-based in silico suite, which uses graph-based signatures to rapidly identify the structural and functional consequences of mutations, to guide rational antibody engineering to improve stability, affinity, and specificity.

Immunoglobulin somatic hypermutation in a defined biochemical system recapitulates affinity maturation and permits antibody optimization.

We describe a purified biochemical system to produce monoclonal antibodies (Abs) in vitro using activation-induced deoxycytidine deaminase (AID) and DNA polymerase η (Polη) to diversify immunoglobulin variable gene (IgV) libraries within a phage display format. AID and Polη function during B-cell affinity maturation by catalyzing somatic hypermutation (SHM) of immunoglobulin variable genes (IgV) to generate high-affinity Abs. The IgV mutational motif specificities observed in vivo are conserved in vitro. IgV mutations occurred in antibody complementary determining regions (CDRs) and less frequently in framework (FW) regions. A unique feature of our system is the use of AID and Polη to perform repetitive affinity maturation on libraries reconstructed from a preceding selection step. We have obtained scFv Abs against human glucagon-like peptide-1 receptor (GLP-1R), a target in the treatment of type 2 diabetes, and VHH nanobodies targeting Fatty Acid Amide Hydrolase (FAAH), involved in chronic pain, and artemin, a neurotropic factor that regulates cold pain. A round of in vitro affinity maturation typically resulted in a 2- to 4-fold enhancement in Ab-Ag binding, demonstrating the utility of the system. We tested one of the affinity matured nanobodies and found that it reduced injury-induced cold pain in a mouse model.

Long-primed germinal centres with enduring affinity maturation and clonal migration.

Germinal centres are the engines of antibody evolution. Here, using human immunodeficiency virus (HIV) Env protein immunogen priming in rhesus monkeys followed by a long period without further immunization, we demonstrate germinal centre B (BGC) cells that last for at least 6 months. A 186-fold increase in BGC cells was present by week 10 compared with conventional immunization. Single-cell transcriptional profiling showed that both light- and dark-zone germinal centre states were sustained. Antibody somatic hypermutation of BGC cells continued to accumulate throughout the 29-week priming period, with evidence of selective pressure. Env-binding BGC cells were still 49-fold above baseline at 29 weeks, which suggests that they could remain active for even longer periods of time. High titres of HIV-neutralizing antibodies were generated after a single booster immunization. Fully glycosylated HIV trimer protein is a complex antigen, posing considerable immunodominance challenges for B cells1,2. Memory B cells generated under these long priming conditions had higher levels of antibody somatic hypermutation, and both memory B cells and antibodies were more likely to recognize non-immunodominant epitopes. Numerous BGC cell lineage phylogenies spanning more than the 6-month germinal centre period were identified, demonstrating continuous germinal centre activity and selection for at least 191 days with no further antigen exposure. A long-prime, slow-delivery (12 days) immunization approach holds promise for difficult vaccine targets and suggests that patience can have great value for tuning of germinal centres to maximize antibody responses.

Correlation between the binding affinity and the conformational entropy of nanobody SARS-CoV-2 spike protein complexes.

Camelid single-domain antibodies, also known as nanobodies, can be readily isolated from naïve libraries for specific targets but often bind too weakly to their targets to be immediately useful. Laboratory-based genetic engineering methods to enhance their affinity, termed maturation, can deliver useful reagents for different areas of biology and potentially medicine. Using the receptor binding domain (RBD) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and a naïve library, we generated closely related nanobodies with micromolar to nanomolar binding affinities. By analyzing the structure-activity relationship using X-ray crystallography, cryoelectron microscopy, and biophysical methods, we observed that higher conformational entropy losses in the formation of the spike protein-nanobody complex are associated with tighter binding. To investigate this, we generated structural ensembles of the different complexes from electron microscopy maps and correlated the conformational fluctuations with binding affinity. This insight guided the engineering of a nanobody with improved affinity for the spike protein.

E484K and N501Y SARS-CoV 2 spike mutants Increase ACE2 recognition but reduce affinity for neutralizing antibody.

SARS-CoV2 mutants B.1.1.7, B.1.351, and P.1 contain a key mutation N501Y. B.1.135 and P.1 lineages have another mutation, E484K. Here, we decode the effect of these two mutations on the host receptor, ACE2, and neutralizing antibody (B38) recognition. The N501Y RBD mutant binds to ACE2 with higher affinity due to improved π-π stacking and π-cation interactions. The higher binding affinity of the E484K mutant is caused due to the formation of additional hydrogen bond and salt-bridge interactions with ACE2. Both the mutants bind to the B38 antibody with reduced affinity due to the loss of several hydrogen-bonding interactions. The insights obtained from the study are crucial to interpret the increased transmissibility and reduced neutralization efficacy of rapidly emerging SARS-CoV2 VOCs.

An integrated computational pipeline for designing high-affinity nanobodies with expanded genetic codes.

Protein engineering and design principles employing the 20 standard amino acids have been extensively used to achieve stable protein scaffolds and deliver their specific activities. Although this confers some advantages, it often restricts the sequence, chemical space, and ultimately the functional diversity of proteins. Moreover, although site-specific incorporation of non-natural amino acids (nnAAs) has been proven to be a valuable strategy in protein engineering and therapeutics development, its utility in the affinity-maturation of nanobodies is not fully explored. Besides, current experimental methods do not routinely employ nnAAs due to their enormous library size and infinite combinations. To address this, we have developed an integrated computational pipeline employing structure-based protein design methodologies, molecular dynamics simulations and free energy calculations, for the binding affinity prediction of an nnAA-incorporated nanobody toward its target and selection of potent binders. We show that by incorporating halogenated tyrosines, the affinity of 9G8 nanobody can be improved toward epidermal growth factor receptor (EGFR), a crucial cancer target. Surface plasmon resonance (SPR) assays showed that the binding of several 3-chloro-l-tyrosine (3MY)-incorporated nanobodies were improved up to 6-fold into a picomolar range, and the computationally estimated binding affinities shared a Pearson's r of 0.87 with SPR results. The improved affinity was found to be due to enhanced van der Waals interactions of key 3MY-proximate nanobody residues with EGFR, and an overall increase in the nanobody's structural stability. In conclusion, we show that our method can facilitate screening large libraries and predict potent site-specific nnAA-incorporated nanobody binders against crucial disease-targets.

Immune evasion of SARS-CoV-2 variants of concern is driven by low affinity to neutralizing antibodies.

SARS-CoV-2 VOC immune evasion is mainly due to lower cross-reactivity from previously elicited class I/II neutralizing antibodies, while increased affinity to hACE2 plays a minor role. The affinity between antibodies and VOCs is impacted by remodeling of the electrostatic surface potential of the Spike RBDs. The P.3 variant is a putative VOC.

An in vivo method for diversifying the functions of therapeutic antibodies.

V(D)J recombination generates mature B cells that express huge repertoires of primary antibodies as diverse immunoglobulin (Ig) heavy chain (IgH) and light chain (IgL) of their B cell antigen receptors (BCRs). Cognate antigen binding to BCR variable region domains activates B cells into the germinal center (GC) reaction in which somatic hypermutation (SHM) modifies primary variable region-encoding sequences, with subsequent selection for mutations that improve antigen-binding affinity, ultimately leading to antibody affinity maturation. Based on these principles, we developed a humanized mouse model approach to diversify an anti-PD1 therapeutic antibody and allow isolation of variants with novel properties. In this approach, component Ig gene segments of the anti-PD1 antibody underwent de novo V(D)J recombination to diversify the anti-PD1 antibody in the primary antibody repertoire in the mouse models. Immunization of these mouse models further modified the anti-PD1 antibodies through SHM. Known anti-PD1 antibodies block interaction of PD1 with its ligands to alleviate PD1-mediated T cell suppression, thereby boosting antitumor T cell responses. By diversifying one such anti-PD1 antibody, we derived many anti-PD1 antibodies, including anti-PD1 antibodies with the opposite activity of enhancing PD1/ligand interaction. Such antibodies theoretically might suppress deleterious T cell activities in autoimmune diseases. The approach we describe should be generally applicable for diversifying other therapeutic antibodies.

Potent neutralization of clinical isolates of SARS-CoV-2 D614 and G614 variants by a monomeric, sub-nanomolar affinity nanobody.

Despite unprecedented global efforts to rapidly develop SARS-CoV-2 treatments, in order to reduce the burden placed on health systems, the situation remains critical. Effective diagnosis, treatment, and prophylactic measures are urgently required to meet global demand: recombinant antibodies fulfill these requirements and have marked clinical potential. Here, we describe the fast-tracked development of an alpaca Nanobody specific for the receptor-binding-domain (RBD) of the SARS-CoV-2 Spike protein with potential therapeutic applicability. We present a rapid method for nanobody isolation that includes an optimized immunization regimen coupled with VHH library E. coli surface display, which allows single-step selection of Nanobodies using a simple density gradient centrifugation of the bacterial library. The selected single and monomeric Nanobody, W25, binds to the SARS-CoV-2 S RBD with sub-nanomolar affinity and efficiently competes with ACE-2 receptor binding. Furthermore, W25 potently neutralizes SARS-CoV-2 wild type and the D614G variant with IC50 values in the nanomolar range, demonstrating its potential as antiviral agent.

Combinatorial mutagenesis with alternative CDR-L1 and -H2 loop lengths contributes to affinity maturation of antibodies.

Loop length variation in the complementary determining regions (CDRs) 1 and 2 encoded in germline variable antibody genes provides structural diversity in naïve antibody libraries. In synthetic single framework libraries the parental CDR-1 and CDR-2 length is typically unchanged and alternative lengths are provided only at CDR-3 sites. Based on an analysis of the germline repertoire and structure-solved anti-hapten and anti-peptide antibodies, we introduced combinatorial diversity with alternative loop lengths into the CDR-L1, CDR-L3 and CDR-H2 loops of anti-digoxigenin and anti-microcystin-LR single chain Fv fragments (scFvs) sharing human IGKV3-20/IGHV3-23 frameworks. The libraries were phage display selected for folding and affinity, and analysed by single clone screening and deep sequencing. Among microcystin-LR binders the most frequently encountered alternative loop lengths were one amino acid shorter (6 aa) and four amino acids longer (11 aa) CDR-L1 loops leading up to 17- and 28-fold improved affinity, respectively. Among digoxigenin binders, 2 amino acids longer (10 aa) CDR-H2 loops were strongly enriched, but affinity improved anti-digoxigenin scFvs were also encountered with 7 aa CDR-H2 and 11 aa CDR-L1 loops. Despite the fact that CDR-L3 loop length variants were not specifically enriched in selections, one clone with 22-fold improved digoxigenin binding affinity was identified containing a 2 residues longer (10 aa) CDR-L3 loop. Based on our results the IGKV3-20/IGHV3-23 scaffold tolerates loop length variation, particularly in CDR-L1 and CDR-H2 loops, without compromising antibody stability, laying the foundation for developing novel synthetic antibody libraries with loop length combinations not existing in the natural human Ig gene repertoire.

Predicting antibody affinity changes upon mutations by combining multiple predictors.

Antibodies are proteins working in our immune system with high affinity and specificity for target antigens, making them excellent tools for both biotherapeutic and bioengineering applications. The prediction of antibody affinity changes upon mutations ([Formula: see text]) is important for antibody engineering. Numerous computational methods have been proposed based on different approaches including molecular mechanics and machine learning. However, the accuracy by each individual predictor is not enough for efficient antibody development. In this study, we develop a new prediction method by combining multiple predictors based on machine learning. Our method was tested on the SiPMAB database, evaluating the Pearson's correlation coefficient between predicted and experimental [Formula: see text]. Our method achieved higher accuracy (R = 0.69) than previous molecular mechanics or machine-learning based methods (R = 0.59) and the previous method using the average of multiple predictors (R = 0.64). Feature importance analysis indicated that the improved accuracy was obtained by combining predictors with different importance, which have different protocols for calculating energies and for generating mutant and unbound state structures. This study demonstrates that machine learning is a powerful framework for combining different approaches to predict antibody affinity changes.

Beyond affinity: selection of antibody variants with optimal biophysical properties and reduced immunogenicity from mammalian display libraries.

The early phase of protein drug development has traditionally focused on target binding properties leading to a desired mode of therapeutic action. As more protein therapeutics pass through the development pipeline; however, it is clear that non-optimal biophysical properties can emerge, particularly as proteins are formulated at high concentrations, causing aggregation or polyreactivity. Such late-stage "developability" problems can lead to delay or failure in traversing the development process. Aggregation propensity is also correlated with increased immunogenicity, resulting in expensive, late-stage clinical failures. Using nucleases-directed integration, we have constructed large mammalian display libraries where each cell contains a single antibody gene/cell inserted at a single locus, thereby achieving transcriptional normalization. We show a strong correlation between poor biophysical properties and display level achieved in mammalian cells, which is not replicated by yeast display. Using two well-documented examples of antibodies with poor biophysical characteristics (MEDI-1912 and bococizumab), a library of variants was created based on surface hydrophobic and positive charge patches. Mammalian display was used to select for antibodies that retained target binding and permitted increased display level. The resultant variants exhibited reduced polyreactivity and reduced aggregation propensity. Furthermore, we show in the case of bococizumab that biophysically improved variants are less immunogenic than the parental molecule. Thus, mammalian display helps to address multiple developability issues during the earliest stages of lead discovery, thereby significantly de-risking the future development of protein drugs.

In vitro evolution of antibody affinity via insertional scanning mutagenesis of an entire antibody variable region.

We report a systematic combinatorial exploration of affinity enhancement of antibodies by insertions and deletions (InDels). Transposon-based introduction of InDels via the method TRIAD (transposition-based random insertion and deletion mutagenesis) was used to generate large libraries with random in-frame InDels across the entire single-chain variable fragment gene that were further recombined and screened by ribosome display. Knowledge of potential insertion points from TRIAD libraries formed the basis of exploration of length and sequence diversity of novel insertions by insertional-scanning mutagenesis (InScaM). An overall 256-fold affinity improvement of an anti-IL-13 antibody BAK1 as a result of InDel mutagenesis and combination with known point mutations validates this approach, and suggests that the results of this InDel mutagenesis and conventional exploration of point mutations can synergize to generate antibodies with higher affinity.

Conformational diversity facilitates antibody mutation trajectories and discrimination between foreign and self-antigens.

Conformational diversity and self-cross-reactivity of antigens have been correlated with evasion from neutralizing antibody responses. We utilized single cell B cell sequencing, biolayer interferometry and X-ray crystallography to trace mutation selection pathways where the antibody response must resolve cross-reactivity between foreign and self-proteins bearing near-identical contact surfaces, but differing in conformational flexibility. Recurring antibody mutation trajectories mediate long-range rearrangements of framework (FW) and complementarity determining regions (CDRs) that increase binding site conformational diversity. These antibody mutations decrease affinity for self-antigen 19-fold and increase foreign affinity 67-fold, to yield a more than 1,250-fold increase in binding discrimination. These results demonstrate how conformational diversity in antigen and antibody does not act as a barrier, as previously suggested, but rather facilitates high affinity and high discrimination between foreign and self.

Affinity maturation of antibodies by combinatorial codon mutagenesis versus error-prone PCR.

IN VITRO: affinity maturation of therapeutic monoclonal antibodies is commonly applied to achieve desired properties, such as improved binding kinetics and affinity. Currently there are no universally accepted protocols for generation of variegated antibody libraries or selection thereof. Here, we performed affinity maturation using a yeast-based single-chain variable fragment (scFv) expression system to compare two mutagenesis methods: random mutagenesis across the entire V(D)J region by error-prone PCR, and a novel combinatorial mutagenesis process limited to the complementarity-determining regions (CDRs). We applied both methods of mutagenesis to four human antibodies against well-known immuno-oncology target proteins. Detailed sequence analysis showed an even mutational distribution across the entire length of the scFv for the error-prone PCR method and an almost exclusive targeting of the CDRs for the combinatorial method. Though there were distinct mutagenesis profiles for each target antibody and mutagenesis method, we found that both methods improved scFv affinity with similar efficiency. When a subset of the affinity-matured antibodies was expressed as full-length immunoglobulin, the measured affinity constants were mostly comparable to those of the respective scFv, but the full-length antibodies were inferior to their scFv counterparts for one of the targets. Furthermore, we found that improved affinity for the full-length antibody did not always translate into enhanced binding to cell-surface expressed antigen or improved immune checkpoint blocking ability, suggesting that screening with full-length antibody or antigen-binding fragment formats might be advantageous and the subject of a future study.

The Effects of Framework Mutations at the Variable Domain Interface on Antibody Affinity Maturation in an HIV-1 Broadly Neutralizing Antibody Lineage.

Understanding affinity maturation of antibodies that can target many variants of HIV-1 is important for vaccine development. While the antigen-binding site of antibodies is known to mutate throughout the co-evolution of antibodies and viruses in infected individuals, the roles of the mutations in the antibody framework region are not well understood. Throughout affinity maturation, the CH103 broadly neutralizing antibody lineage, from an individual designated CH505, altered the orientation of one of its antibody variable domains. The change in orientation was a response to insertions in the variable loop 5 (V5) of the HIV envelope. In this study, we generated CH103 lineage antibody variants in which residues in the variable domain interface were mutated, and measured the binding to both autologous and heterologous HIV-1 envelopes. Our data show that very few mutations in an early intermediate antibody of the lineage can improve binding toward both autologous and heterologous HIV-1 envelopes. We also crystallized an antibody mutant to show that framework mutations alone can result in a shift in relative orientations of the variable domains. Taken together, our results demonstrate the functional importance of residues located outside the antigen-binding site in affinity maturation.

The immunogenetics of sexual parasitism.

Sexual parasitism has evolved as a distinctive mode of reproduction among deep-sea anglerfishes. The permanent attachment of males to host females observed in these species represents a form of anatomical joining, which is otherwise unknown in nature. Pronounced modifications to immune facilities are associated with this reproductive trait. The genomes of species with temporarily attaching males lack functional aicda genes that underpin affinity maturation of antibodies. Permanent attachment is associated with additional alterations, culminating in the loss of functional rag genes in some species, abolishing somatic diversification of antigen receptor genes, the hallmark of canonical adaptive immunity. In anglerfishes, coevolution of innate and adaptive immunity has been disentangled, implying that an alternative form of immunity supported the emergence of this evolutionarily successful group of vertebrates.

BCR selection and affinity maturation in Peyer's patch germinal centres.

The antigen-binding variable regions of the B cell receptor (BCR) and of antibodies are encoded by exons that are assembled in developing B cells by V(D)J recombination1. The BCR repertoires of primary B cells are vast owing to mechanisms that create diversity at the junctions of V(D)J gene segments that contribute to complementarity-determining region 3 (CDR3), the region that binds antigen1. Primary B cells undergo antigen-driven BCR affinity maturation through somatic hypermutation and cellular selection in germinal centres (GCs)2,3. Although most GCs are transient3, those in intestinal Peyer's patches (PPs)-which depend on the gut microbiota-are chronic4, and little is known about their BCR repertoires or patterns of somatic hypermutation. Here, using a high-throughput assay that analyses both V(D)J segment usage and somatic hypermutation profiles, we elucidate physiological BCR repertoires in mouse PP GCs. PP GCs from different mice expand public BCR clonotypes (clonotypes that are shared between many mice) that often have canonical CDR3s in the immunoglobulin heavy chain that, owing to junctional biases during V(D)J recombination, appear much more frequently than predicted in naive B cell repertoires. Some public clonotypes are dependent on the gut microbiota and encode antibodies that are reactive to bacterial glycans, whereas others are independent of gut bacteria. Transfer of faeces from specific-pathogen-free mice to germ-free mice restored germ-dependent clonotypes, directly implicating BCR selection. We identified somatic hypermutations that were recurrently selected in such public clonotypes, indicating that affinity maturation occurs in mouse PP GCs under homeostatic conditions. Thus, persistent gut antigens select recurrent BCR clonotypes to seed chronic PP GC responses.

mmCSM-AB: guiding rational antibody engineering through multiple point mutations.

While antibodies are becoming an increasingly important therapeutic class, especially in personalized medicine, their development and optimization has been largely through experimental exploration. While there have been many efforts to develop computational tools to guide rational antibody engineering, most approaches are of limited accuracy when applied to antibody design, and have largely been limited to analysing a single point mutation at a time. To overcome this gap, we have curated a dataset of 242 experimentally determined changes in binding affinity upon multiple point mutations in antibody-target complexes (89 increasing and 153 decreasing binding affinity). Here, we have shown that by using our graph-based signatures and atomic interaction information, we can accurately analyse the consequence of multi-point mutations on antigen binding affinity. Our approach outperformed other available tools across cross-validation and two independent blind tests, achieving Pearson's correlations of up to 0.95. We have implemented our new approach, mmCSM-AB, as a web-server that can help guide the process of affinity maturation in antibody design. mmCSM-AB is freely available at http://biosig.unimelb.edu.au/mmcsm_ab/.