Expanding and improving nanobody repertoires using a yeast display method: Targeting SARS-CoV-2.

COVID-19, caused by the coronavirus SARS-CoV-2, represents a serious worldwide health issue, with continually emerging new variants challenging current therapeutics. One promising alternate therapeutic avenue is represented by nanobodies, small single-chain antibodies derived from camelids with numerous advantageous properties and the potential to neutralize the virus. For identification and characterization of a broad spectrum of anti-SARS-CoV-2 Spike nanobodies, we further optimized a yeast display method, leveraging a previously published mass spectrometry-based method, using B-cell complementary DNA from the same immunized animals as a source of VHH sequences. Yeast display captured many of the sequences identified by the previous approach, as well as many additional sequences that proved to encode a large new repertoire of nanobodies with high affinities and neutralization activities against different SARS-CoV-2 variants. We evaluated DNA shuffling applied to the three complementarity-determining regions of antiviral nanobodies. The results suggested a surprising degree of modularity to complementarity-determining region function. Importantly, the yeast display approach applied to nanobody libraries from immunized animals allows parallel interrogation of a vast number of nanobodies. For example, we employed a modified yeast display to carry out massively parallel epitope binning. The current yeast display approach proved comparable in efficiency and specificity to the mass spectrometry-based approach, while requiring none of the infrastructure and expertise required for that approach, making these highly complementary approaches that together appear to comprehensively explore the paratope space. The larger repertoires produced maximize the likelihood of discovering broadly specific reagents and those that powerfully synergize in mixtures.

Cryptic-site-specific antibodies to the SARS-CoV-2 receptor binding domain can retain functional binding affinity to spike variants.

IMPORTANCE: Multiple SARS-CoV-2 variants of concern have emerged and caused a significant number of infections and deaths worldwide. These variants of concern contain mutations that might significantly affect antigen-targeting by antibodies. It is therefore important to further understand how antibody binding and neutralization are affected by the mutations in SARS-CoV-2 variants. We highlighted how antibody epitope specificity can influence antibody binding to SARS-CoV-2 spike protein variants and neutralization of SARS-CoV-2 variants. We showed that weakened spike binding and neutralization of Beta (B.1.351) and Omicron (BA.1) variants compared to wildtype are not universal among the panel of antibodies and identified antibodies of a specific binding footprint exhibiting consistent enhancement of spike binding and retained neutralization to Beta variant. These data and analysis can inform how antigen-targeting by antibodies might evolve during a pandemic and prepare for potential future sarbecovirus outbreaks.

Characterizing Epitope Binding Regions of Entire Antibody Panels by Combining Experimental and Computational Analysis of Antibody: Antigen Binding Competition.

Vaccines and immunotherapies depend on the ability of antibodies to sensitively and specifically recognize particular antigens and specific epitopes on those antigens. As such, detailed characterization of antibody-antigen binding provides important information to guide development. Due to the time and expense required, high-resolution structural characterization techniques are typically used sparingly and late in a development process. Here, we show that antibody-antigen binding can be characterized early in a process for whole panels of antibodies by combining experimental and computational analyses of competition between monoclonal antibodies for binding to an antigen. Experimental "epitope binning" of monoclonal antibodies uses high-throughput surface plasmon resonance to reveal which antibodies compete, while a new complementary computational analysis that we call "dock binning" evaluates antibody-antigen docking models to identify why and where they might compete, in terms of possible binding sites on the antigen. Experimental and computational characterization of the identified antigenic hotspots then enables the refinement of the competitors and their associated epitope binding regions on the antigen. While not performed at atomic resolution, this approach allows for the group-level identification of functionally related monoclonal antibodies (i.e., communities) and identification of their general binding regions on the antigen. By leveraging extensive epitope characterization data that can be readily generated both experimentally and computationally, researchers can gain broad insights into the basis for antibody-antigen recognition in wide-ranging vaccine and immunotherapy discovery and development programs.

Combination of two anti-CD5 monoclonal antibodies synergistically induces complement-dependent cytotoxicity of chronic lymphocytic leukaemia cells.

The treatment of chronic lymphocytic leukaemia (CLL) has been improved by introduction of monoclonal antibodies (mAbs) that exert their effect through secondary effector mechanisms. CLL cells are characterized by expression of CD5 and CD23 along with CD19 and CD20, hence anti-CD5 Abs that engage secondary effector functions represent an attractive opportunity for CLL treatment. Here, a repertoire of mAbs against human CD5 was generated and tested for ability to induce complement-dependent cytotoxicity (CDC) and antibody-dependent cell-mediated cytotoxicity (ADCC) both as single mAbs and combinations of two mAbs against non-overlapping epitopes on human CD5. The results demonstrated that combinations of two mAbs significantly increased the level of CDC compared to the single mAbs, while no enhancement of ADCC was seen with anti-CD5 mAb combinations. High levels of CDC and ADCC correlated with low levels of Ab-induced CD5 internalization and degradation. Importantly, an anti-CD5 mAb combination enhanced CDC of CLL cells when combined with the anti-CD20 mAbs rituximab and ofatumumab as well as with the anti-CD52 mAb alemtuzumab. These results suggest that an anti-CD5 mAb combination inducing CDC and ADCC may be effective alone, in combination with mAbs against other targets or combined with chemotherapy for CLL and other CD5-expressing haematological or lymphoid malignancies.

Epitope Binning of Monoclonal and Polyclonal Antibodies by Biolayer Interferometry.

Understanding the epitopes of antibodies elicited by infection and vaccination is often useful in immunogen design. In this chapter, we describe biolayer interferometry (BLI)-based methods to evaluate such epitopes and permit simultaneous analysis of antibodies from several sources, including monoclonal antibodies (mAbs) and polyclonal serum antibodies (pAbs). Using previously characterized antibodies with known epitopes as controls, the distribution of epitopes for the influenza hemagglutinin (HA) is shown for isolated human mAbs and pooled serum from HA-immunized mice. This method is versatile, high-throughput, and can be adapted to several antigens.

Moving beyond Titers.

Vaccination to prevent and even eliminate disease is amongst the greatest achievements of modern medicine. Opportunities remain in vaccine development to improve protection across the whole population. A next step in vaccine development is the detailed molecular characterization of individual humoral immune responses against a pathogen, especially the rapidly evolving pathogens. New technologies such as sequencing the immune repertoire in response to disease, immunogenomics/vaccinomics, particularly the individual HLA variants, and high-throughput epitope characterization offer new insights into disease protection. Here, we highlight the emerging technologies that could be used to identify variation within the human population, facilitate vaccine discovery, improve vaccine safety and efficacy, and identify mechanisms of generating immunological memory. In today's vaccine-hesitant climate, these techniques used individually or especially together have the potential to improve vaccine effectiveness and safety and thus vaccine uptake rates. We highlight the importance of using these techniques in combination to understand the humoral immune response as a whole after vaccination to move beyond neutralizing titers as the standard for immunogenicity and vaccine efficacy, especially in clinical trials.

Computational epitope binning reveals functional equivalence of sequence-divergent paratopes.

The therapeutic efficacy of a protein binder largely depends on two factors: its binding site and its binding affinity. Advances in in vitro library display screening and next-generation sequencing have enabled accelerated development of strong binders, yet identifying their binding sites still remains a major challenge. The differentiation, or "binning", of binders into different groups that recognize distinct binding sites on their target is a promising approach that facilitates high-throughput screening of binders that may show different biological activity. Here we study the extent to which the information contained in the amino acid sequences comprising a set of target-specific binders can be leveraged to bin them, inferring functional equivalence of their binding regions, or paratopes, based directly on comparison of the sequences, their modeled structures, or their modeled interactions. Using a leucine-rich repeat binding scaffold known as a "repebody" as the source of diversity in recognition against interleukin-6 (IL-6), we show that the "Epibin" approach introduced here effectively utilized structural modelling and docking to extract specificity information encoded in the repebody amino acid sequences and thereby successfully recapitulate IL-6 binding competition observed in immunoassays. Furthermore, our computational binning provided a basis for designing in vitro mutagenesis experiments to pinpoint specificity-determining residues. Finally, we demonstrate that the Epibin approach can extend to antibodies, retrospectively comparing its predictions to results from antigen-specific antibody competition studies. The study thus demonstrates the utility of modeling structure and binding from the amino acid sequences of different binders against the same target, and paves the way for larger-scale binning and analysis of entire repertoires.

Accurate determination of epitope for antibodies with unknown 3D structures.

MAbTope is a docking-based method for the determination of epitopes. It has been used to successfully determine the epitopes of antibodies with known 3D structures. However, during the antibody discovery process, this structural information is rarely available. Although we already have evidence that homology models of antibodies could be used instead of their 3D structure, the choice of the template, the methodology for homology modeling and the resulting performance still have to be clarified. Here, we show that MAbTope has the same performance when working with homology models of the antibodies as compared to crystallographic structures. Moreover, we show that even low-quality models can be used. We applied MAbTope to determine the epitope of dupilumab, an anti- interleukin 4 receptor alpha subunit therapeutic antibody of unknown 3D structure, that we validated experimentally. Finally, we show how the MAbTope-determined epitopes for a series of antibodies targeting the same protein can be used to predict competitions, and demonstrate the accuracy with an experimentally validated example.3D: three-dimensionalRMSD: root mean square deviationCDR: complementary-determining regionCPU: central processing unitsVH: heavy chain variable regionVL: light chain variable regionscFv: single-chain variable fragmentsVHH: single-chain antibody variable regionIL4Rα: Interleukin 4 receptor alpha chainSPR: surface plasmon resonancePDB: protein data bankHEK293: Human embryonic kidney 293 cellsEDTA: Ethylenediaminetetraacetic acidFBS: Fetal bovine serumANOVA: Analysis of varianceEGFR: Epidermal growth factor receptorPE: PhycoerythrinAPC: AllophycocyaninFSC: forward scatterSSC: side scatterWT: wild typeKeywords: MAbTope, Epitope Mapping, Molecular docking, Antibody modeling, Antibody-antigen docking.

Development and Characterization of Nanobodies Targeting the Kupffer Cell.

Nanobodies that are derived from single-chain antibodies of camelids have served as powerful tools in diagnostics, therapeutics and investigation of membrane receptors' structure and function. In this study, we developed a series of nanobodies by a phage display screening building from lymphocytes isolated from an alpaca immunized with recombinant mouse Kupffer cell receptor Clec4F, which is involved in pathogen recognition by binding to galactose and N-acetylgalactosamine. Bio-panning selections retrieved 14 different nanobodies against Clec4F with an affinity ranging from 0.2 to 2 nM as determined by SPR. Those nanobodies mainly recognize 4 different epitopes as analyzed via competitive epitope binning. By analysis of the radioactivity in each organ after injection of 99mTc labeled Clec4F nanobodies in naïve mice, we found that these nanobodies are targeting the liver. Furthermore, we performed a structural characterization at atomic resolution of two of the Clec4F nanobodies from different epitope groups, which revealed distinct features within the CDR2 and CDR3 regions. Taken together, we developed a series of nanobodies targeting multiple distinct recognition epitopes of the Kupffer cell-specific receptor Clec4F which may be useful for its structural and functional investigation as well as for use as molecular imaging and therapeutic agents.

Accelerated antibody discovery targeting the SARS-CoV-2 spike protein for COVID-19 therapeutic potential.

BACKGROUND: Rapid deployment of technologies capable of high-throughput and high-resolution screening is imperative for timely response to viral outbreaks. Risk mitigation in the form of leveraging multiple advanced technologies further increases the likelihood of identifying efficacious treatments in aggressive timelines. METHODS: In this study, we describe two parallel, yet distinct, in vivo approaches for accelerated discovery of antibodies targeting the severe acute respiratory syndrome coronavirus-2 spike protein. Working with human transgenic Alloy-GK mice, we detail a single B-cell discovery workflow to directly interrogate antibodies secreted from plasma cells for binding specificity and ACE2 receptor blocking activity. Additionally, we describe a concurrent accelerated hybridoma-based workflow utilizing a DiversimAb™ mouse model for increased diversity. RESULTS: The panel of antibodies isolated from both workflows revealed binding to distinct epitopes with both blocking and non-blocking profiles. Sequence analysis of the resulting lead candidates uncovered additional diversity with the opportunity for straightforward engineering and affinity maturation. CONCLUSIONS: By combining in vivo models with advanced integration of screening and selection platforms, lead antibody candidates can be sequenced and fully characterized within one to three months.