Deep sequencing of phage display libraries to support antibody discovery

A phage-displayed disulfide constrained peptide discovery platform yields novel human plasma protein binders

Disulfide constrained peptides (DCPs) show great potential as templates for drug discovery. They are characterized by conserved cysteine residues that form intramolecular disulfide bonds. Taking advantage of phage display technology, we designed and generated twenty-six DCP phage libraries with enriched molecular diversity to enable the discovery of ligands against disease-causing proteins of interest. The libraries were designed based on five DCP scaffolds, namely Momordica charantia 1 (Mch1), gurmarin, Asteropsin-A, antimicrobial peptide-1 (AMP-1), and potato carboxypeptidase inhibitor (CPI). We also report optimized workflows for screening and producing synthetic and recombinant DCPs. Examples of novel DCP binders identified against various protein targets are presented, including human IgG Fc, serum albumin, vascular endothelial growth factor-A (VEGF-A) and platelet-derived growth factor (PDGF). We identified DCPs against human IgG Fc and serum albumin with sub-micromolar affinity from primary panning campaigns, providing alternative tools for potential half-life extension of peptides and small protein therapeutics. Overall, the molecular diversity of the DCP scaffolds included in the designed libraries, coupled with their distinct biochemical and biophysical properties, enables efficient and robust identification of de novo binders to drug targets of therapeutic relevance.

The rise of big data: deep sequencing-driven computational methods are transforming the landscape of synthetic antibody design

Synthetic antibodies (Abs) represent a category of artificial proteins capable of closely emulating the functions of natural Abs. Their in vitro production eliminates the need for an immunological response, streamlining the process of Ab discovery, engineering, and development. These artificially engineered Abs offer novel approaches to antigen recognition, paratope site manipulation, and biochemical/biophysical enhancements. As a result, synthetic Abs are fundamentally reshaping conventional methods of Ab production. This mirrors the revolution observed in molecular biology and genomics as a result of deep sequencing, which allows for the swift and cost-effective sequencing of DNA and RNA molecules at scale. Within this framework, deep sequencing has enabled the exploration of whole genomes and transcriptomes, including particular gene segments of interest. Notably, the fusion of synthetic Ab discovery with advanced deep sequencing technologies is redefining the current approaches to Ab design and development. Such combination offers opportunity to exhaustively explore Ab repertoires, fast-tracking the Ab discovery process, and enhancing synthetic Ab engineering. Moreover, advanced computational algorithms have the capacity to effectively mine big data, helping to identify Ab sequence patterns/features hidden within deep sequencing Ab datasets. In this context, these methods can be utilized to predict novel sequence features thereby enabling the successful generation of de novo Ab molecules. Hence, the merging of synthetic Ab design, deep sequencing technologies, and advanced computational models heralds a new chapter in Ab discovery, broadening our comprehension of immunology and streamlining the advancement of biological therapeutics.

Application of Deep Sequencing in Phage Display

This chapter describes the workflow to implement deep sequencing into standard phage display experiments on protein libraries. By harvesting the power of high throughput of these techniques, it allows for comprehensive analysis of the naïve library and library evolution in response to selection by ligand binding. The mutagenized target region of the protein variants encoded by the phage pool is analyzed by Illumina paired-end sequencing. Sequence data are processed to extract selection-enriched amino acid motifs. In addition, a complementary long-read sequencing approach is proposed enabling the monitoring of display vector stability.

Position-Specific Enrichment Ratio Matrix scores predict antibody variant properties from deep sequencing data

MOTIVATION

Deep sequencing of antibody and related protein libraries after phage or yeast-surface display sorting is widely used to identify variants with increased affinity, specificity, and/or improvements in key biophysical properties. Conventional approaches for identifying optimal variants typically use the frequencies of observation in enriched libraries or the corresponding enrichment ratios. However, these approaches disregard the vast majority of deep sequencing data and often fail to identify the best variants in the libraries.

RESULTS

Here, we present a method, Position-Specific Enrichment Ratio Matrix (PSERM) scoring, that uses entire deep sequencing datasets from pre- and post-selections to score each observed protein variant. The PSERM scores are the sum of the site-specific enrichment ratios observed at each mutated position. We find that PSERM scores are much more reproducible and correlate more strongly with experimentally measured properties than frequencies or enrichment ratios, including for multiple antibody properties (affinity and non-specific binding) for a clinical-stage antibody (emibetuzumab). We expect that this method will be broadly applicable to diverse protein engineering campaigns.

AVAILABILITY AND IMPLEMENTATION

All deep sequencing datasets and code to perform the analyses presented within are available via https://github.com/Tessier-Lab-UMich/PSERM_paper.

Position-Specific Enrichment Ratio Matrix scores predict antibody variant properties from deep sequencing data

Motivation

Deep sequencing of antibody and related protein libraries after phage or yeast-surface display sorting is widely used to identify variants with increased affinity, specificity and/or improvements in key biophysical properties. Conventional approaches for identifying optimal variants typically use the frequencies of observation in enriched libraries or the corresponding enrichment ratios. However, these approaches disregard the vast majority of deep sequencing data and often fail to identify the best variants in the libraries.

Results

Here, we present a method, Position-Specific Enrichment Ratio Matrix (PSERM) scoring, that uses entire deep sequencing datasets from pre- and post-selections to score each observed protein variant. The PSERM scores are the sum of the site-specific enrichment ratios observed at each mutated position. We find that PSERM scores are much more reproducible and correlate more strongly with experimentally measured properties than frequencies or enrichment ratios, including for multiple antibody properties (affinity and non-specific binding) for a clinical-stage antibody (emibetuzumab). We expect that this method will be broadly applicable to diverse protein engineering campaigns.

Availability

All deep sequencing datasets and code to do the analyses presented within are available via GitHub.

Contact

Peter Tessier, ptessier@umich.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Mutational scan inferred binding energetics and structure in intrinsically disordered protein CcdA

Unlike globular proteins, mutational effects on the function of Intrinsically Disordered Proteins (IDPs) are not well-studied. Deep Mutational Scanning of a yeast surface displayed mutant library yields insights into sequence-function relationships in the CcdA IDP. The approach enables facile prediction of interface residues and local structural signatures of the bound conformation. In contrast to previous titration-based approaches which use a number of ligand concentrations, we show that use of a single rationally chosen ligand concentration can provide quantitative estimates of relative binding constants for large numbers of protein variants. This is because the extended interface of IDP ensures that energetic effects of point mutations are spread over a much smaller range than for globular proteins. Our data also provides insights into the much-debated role of helicity and disorder in partner binding of IDPs. Based on this exhaustive mutational sensitivity dataset, a rudimentary model was developed in an attempt to predict mutational effects on binding affinity of IDPs that form alpha-helical structures upon binding.

Identification of New Antibodies Targeting Tumor Cell Surface Antigens by Phage Display

The majority of therapeutic antibodies, bispecific antibodies, and chimeric antigen receptor (CAR) T cells in cancer therapy are based on an antibody or antibody fragment that specifically binds a target present on the surface of a tumor cell. Suitable antigens that can be used for immunotherapy are ideally tumor-specific or tumor-associated and stably expressed on the tumor cell. The identification of new target structures to further optimize immunotherapies could be realized by comparing healthy and tumor cells using "omics" methods to select promising proteins. However, differences in post-translational modifications and structural alterations that can be present on the tumor cell surface are difficult to identify or even not accessible by these techniques. In this chapter, we describe an alternative approach to potentially identify antibodies targeting novel tumor-associated antigens (TAA) or epitopes by using cellular screening and phage display of antibody libraries. Isolated antibody fragments can be further converted into chimeric IgG or other antibody formats to investigate the anti-tumor effector functions and finally identify and characterize the respective antigen.

Identification of New Antibodies Targeting Malignant Plasma Cells for Immunotherapy by Next-Generation Sequencing-Assisted Phage Display

To identify new antibodies for the treatment of plasma cell disorders including multiple myeloma (MM), a single-chain Fragment variable (scFv) antibody library was generated by immunizing mice with patient-derived malignant plasma cells. To enrich antibodies binding myeloma antigens, phage display with cellular panning was performed. After depleting the immune library with leukocytes of healthy donors, selection of antibodies was done with L-363 plasma cell line in two consecutive panning rounds. Monitoring the antibodies’ enrichment throughout the panning by next-generation sequencing (NGS) identified several promising candidates. Initially, 41 unique scFv antibodies evolving from different B cell clones were selected. Nine of these antibodies strongly binding to myeloma cells and weakly binding to peripheral blood mononuclear cells (PBMC) were characterized. Using stably transfected Chinese hamster ovary cells expressing individual myeloma-associated antigens revealed that two antibodies bind CD38 and intercellular adhesion molecule-1 (ICAM-1), respectively, and 7 antibodies target yet unknown antigens. To evaluate the therapeutic potential of our new antibodies, in a first proof-of-concept study the CD38 binding scFv phage antibody was converted into a chimeric IgG1. Further analyses revealed that #5-CD38-IgG1 shared an overlapping epitope with daratumumab and isatuximab and had potent anti-myeloma activity comparable to the two clinically approved CD38 antibodies. These results indicate that by phage display and deep sequencing, new antibodies with therapeutic potential for MM immunotherapy can be identified.

Computational epitope binning reveals functional equivalence of sequence-divergent paratopes

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Epitope binning groups target-specific protein binders recognizing the same binding region.

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The “Epibin” method utilizes docking models to computationally predict competition and identify bins.

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Epibin recapitulated binding competition of repebody variants as determined by immunoassays.

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In addition, Epibin enabled identification of ‘paratope-equivalent’ residues in sequence-dissimilar variants.

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Computational epitope binning can scale to allow characterization of entire antigen-specific antibody repertoires.

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.

A Simple Whole-Plasmid PCR Method to Construct High-Diversity Synthetic Phage Display Libraries

Phage display technology utilises peptide and antibody libraries with very high diversities to select ligands with specific binding properties. The production of such libraries can be labour intensive and technically challenging and whilst there are commercial sources of libraries, the exploitation of the resulting binders is constrained by ownership of the libraries. Here, a peptide library of ~ 1 × 10⁹ variants for display on gene VIII was produced alongside three VHH antibody libraries with similar diversity, where 12mer, 16mer or 21mer CDR3s were introduced into the highly stable cAbBCII10 scaffold displayed on gene III. The cloning strategy used a simple whole-plasmid PCR method and type IIS restriction enzyme assembly that facilitate the seamless insertion of diversity into any suitable phage coat protein or antibody scaffold. This method reproducibly produced 1 × 10⁹ variants from just 10 transformations and the four libraries had relatively low bias with 82 to 86% of all sequences present as single copies. The functionality of both peptide and antibody libraries were demonstrated by selection of ligands with specific binding properties by biopanning. The peptide library was used to epitope map a monoclonal antibody. The VHH libraries were pooled and used to select an antibody to recombinant human collagen type 1.

Reconstruction of full antibody sequences in NGS datasets and accurate VL:VH coupling by cluster coordinate matching of non-overlapping reads

Next-generation sequencing (NGS) is an indispensable tool in antibody discovery projects. However, the limits on NGS read length make it difficult to reconstruct full antibody sequences from the sequencing runs, especially if the six CDRs are randomized. To overcome that, we took advantage of Illumina’s cluster mapping capabilities to pair non-overlapping reads and reconstruct full Fab sequences with accurate V_L:V_H pairings. The method relies on in silico cluster coordinate information, and not on extensive in vitro manipulation, making the protocol easily deployable and less prone to PCR-derived errors. This work maintains the throughput necessary for antibody discovery campaigns, and a high degree of fidelity, which potentiates not only phage-display and synthetic library-based discovery methods, but also the NGS-driven analysis of naïve and immune libraries.

Biological controls for standardization and interpretation of adaptive immune receptor repertoire profiling

Use of adaptive immune receptor repertoire sequencing (AIRR-seq) has become widespread, providing new insights into the immune system with potential broad clinical and diagnostic applications. However, like many high-throughput technologies, it comes with several problems, and the AIRR Community was established to understand and help solve them. We, the AIRR Community’s Biological Resources Working Group, have surveyed scientists about the need for standards and controls in generating and annotating AIRR-seq data. Here, we review the current status of AIRR-seq, provide the results of our survey, and based on them, offer recommendations for developing AIRR-seq standards and controls, including future work.

CellectSeq: In silico discovery of antibodies targeting integral membrane proteins combining in situ selections and next-generation sequencing

Synthetic antibody (Ab) technologies are efficient and cost-effective platforms for the generation of monoclonal Abs against human antigens. Yet, they typically depend on purified proteins, which exclude integral membrane proteins that require the lipid bilayers to support their native structure and function. Here, we present an Ab discovery strategy, termed CellectSeq, for targeting integral membrane proteins on native cells in complex environment. As proof of concept, we targeted three transmembrane proteins linked to cancer, tetraspanin CD151, carbonic anhydrase 9, and integrin-α11. First, we performed in situ cell-based selections to enrich phage-displayed synthetic Ab pools for antigen-specific binders. Then, we designed next-generation sequencing procedures to explore Ab diversities and abundances. Finally, we developed motif-based scoring and sequencing error-filtering algorithms for the comprehensive interrogation of next-generation sequencing pools to identify Abs with high diversities and specificities, even at extremely low abundances, which are very difficult to identify using manual sampling or sequence abundances.

A novel framework for engineering protein loops exploring length and compositional variation

Insertions and deletions (indels) are known to affect function, biophysical properties and substrate specificity of enzymes, and they play a central role in evolution. Despite such clear significance, this class of mutation remains an underexploited tool in protein engineering with few available platforms capable of systematically generating and analysing libraries of varying sequence composition and length. We present a novel DNA assembly platform (InDel assembly), based on cycles of endonuclease restriction digestion and ligation of standardised dsDNA building blocks, that can generate libraries exploring both composition and sequence length variation. In addition, we developed a framework to analyse the output of selection from InDel-generated libraries, combining next generation sequencing and alignment-free strategies for sequence analysis. We demonstrate the approach by engineering the well-characterized TEM-1 β-lactamase Ω-loop, involved in substrate specificity, identifying multiple novel extended spectrum β-lactamases with loops of modified length and composition-areas of the sequence space not previously explored. Together, the InDel assembly and analysis platforms provide an efficient route to engineer protein loops or linkers where sequence length and composition are both essential functional parameters.

Antibody design using LSTM based deep generative model from phage display library for affinity maturation

Molecular evolution is an important step in the development of therapeutic antibodies. However, the current method of affinity maturation is overly costly and labor-intensive because of the repetitive mutation experiments needed to adequately explore sequence space. Here, we employed a long short term memory network (LSTM)—a widely used deep generative model—based sequence generation and prioritization procedure to efficiently discover antibody sequences with higher affinity. We applied our method to the affinity maturation of antibodies against kynurenine, which is a metabolite related to the niacin synthesis pathway. Kynurenine binding sequences were enriched through phage display panning using a kynurenine-binding oriented human synthetic Fab library. We defined binding antibodies using a sequence repertoire from the NGS data to train the LSTM model. We confirmed that likelihood of generated sequences from a trained LSTM correlated well with binding affinity. The affinity of generated sequences are over 1800-fold higher than that of the parental clone. Moreover, compared to frequency based screening using the same dataset, our machine learning approach generated sequences with greater affinity.

Discovering Selected Antibodies From Deep-Sequenced Phage-Display Antibody Library Using ATTILA

Phage display is a powerful technique to select high-affinity antibodies for different purposes, including biopharmaceuticals. Next-generation sequencing (NGS) presented itself as a robust solution, making it possible to assess billions of sequences of the variable domains from selected sublibraries. Handling this process, a central difficulty is to find the selected clones. Here, we present the AutomaTed Tool For Immunoglobulin Analysis (ATTILA), a new tool to analyze and find the enriched variable domains throughout a biopanning experiment. The ATTILA is a workflow that combines publicly available tools and in-house programs and scripts to find the fold-change frequency of deeply sequenced amplicons generated from selected VH and VL domains. We analyzed the same human Fab library NGS data using ATTILA in 5 different experiments, as well as on 2 biopanning experiments regarding performance, accuracy, and output. These analyses proved to be suitable to assess library variability and to list the more enriched variable domains, as ATTILA provides a report with the amino acid sequence of each identified domain, along with its complementarity-determining regions (CDRs), germline classification, and fold change. Finally, the methods employed here demonstrated a suitable manner to combine amplicon generation and NGS data analysis to discover new monoclonal antibodies (mAbs).

Machine Learning-Guided Prediction of Antigen-Reactive In Silico Clonotypes Based on Changes in Clonal Abundance through Bio-Panning

c-Met is a promising target in cancer therapy for its intrinsic oncogenic properties. However, there are currently no c-Met-specific inhibitors available in the clinic. Antibodies blocking the interaction with its only known ligand, hepatocyte growth factor, and/or inducing receptor internalization have been clinically tested. To explore other therapeutic antibody mechanisms like Fc-mediated effector function, bispecific T cell engagement, and chimeric antigen T cell receptors, a diverse panel of antibodies is essential. We prepared a chicken immune scFv library, performed four rounds of bio-panning, obtained 641 clones using a high-throughput clonal retrieval system (TrueRepertoireTM, TR), and found 149 antigen-reactive scFv clones. We also prepared phagemid DNA before the start of bio-panning (round 0) and, after each round of bio-panning (round 1-4), performed next-generation sequencing of these five sets of phagemid DNA, and identified 860,207 HCDR3 clonotypes and 443,292 LCDR3 clonotypes along with their clonal abundance data. We then established a TR data set consisting of antigen reactivity for scFv clones found in TR analysis and the clonal abundance of their HCDR3 and LCDR3 clonotypes in five sets of phagemid DNA. Using the TR data set, a random forest machine learning algorithm was trained to predict the binding properties of in silico HCDR3 and LCDR3 clonotypes. Subsequently, we synthesized 40 HCDR3 and 40 LCDR3 clonotypes predicted to be antigen reactive (AR) and constructed a phage-displayed scFv library called the AR library. In parallel, we also prepared an antigen non-reactive (NR) library using 10 HCDR3 and 10 LCDR3 clonotypes predicted to be NR. After a single round of bio-panning, we screened 96 randomly-selected phage clones from the AR library and found out 14 AR scFv clones consisting of 5 HCDR3 and 11 LCDR3 AR clonotypes. We also screened 96 randomly-selected phage clones from the NR library, but did not identify any AR clones. In summary, machine learning algorithms can provide a method for identifying AR antibodies, which allows for the characterization of diverse antibody libraries inaccessible by traditional methods.

High-Throughput Generation of In Silico Derived Synthetic Antibodies via One-step Enzymatic DNA Assembly of Fragments

Phage-display technology offers robust methods for isolating antibody (Ab) molecules with specificity for different target antigens. Recent advancements couple Ab selections with in silico strategies, such as predictive computational models or next-generation sequencing metadata analysis of Ab selections. These advancements result in enhanced Ab clonal diversities with potential for enlarged epitope coverage of the target antigen. A current limitation however, is that de novo Ab sequences must undergo DNA gene synthesis, and subsequent expression as Ab proteins for downstream validations. Due to the high costs and time for commercially generating large sets of DNA genes, we report a high-throughput platform for the synthesis of in silico derived Ab clones. As a proof of concept we demonstrate the simultaneous synthesis of 96 unique Abs with varied lengths and complementary determining region compositions. Each of the 96 Ab clones undergoes a one-step enzymatic assembly of distinct DNA fragments that combine into a circularized Fab expression plasmid. This strategy allows for the rapid and efficient synthesis of 96 DNA constructs in a 3 day window, and exhibits high percentage fidelity-greater than 93%. Accordingly, the synthesis of Ab DNA constructs as Fab expression plasmids allow for rapid execution of downstream Ab protein validations, with potential for implementation into high-throughput Ab protein characterization pipelines. Altogether, the platform presented here proves rapid and also cost-effective, which is important for labs with limited resources, since it utilizes standard laboratory equipment and molecular reagents.

Selection of Antibody Fragments for CAR-T Cell Therapy from Phage Display Libraries

CAR-T cell therapy emerged in the last years as a great promise to cancer treatment. Nowadays, there is a run to improve the breadth of its use, and thus, new chimeric antigen receptors (CAR) are being proposed. The antigen-binding counterpart of CAR is an antibody fragment, scFv (single chain variable fragment), that recognizes a membrane protein associated to a cancer cell. In this chapter, the use of human scFv phage display libraries as a source of new mAbs against surface antigen is discussed. Protocols focusing in the use of extracellular domains of surface protein in biotinylated format are proposed as selection antigen. Elution with unlabeled peptide and selection in solution is described. The analysis of enriched scFvs throughout the selection using NGS is also outlined. Taken together these protocols allow for the isolation of new scFvs able to be useful in the construction of new chimeric antigen receptors for application in cancer therapy.

Multifaceted antibodies development against synthetic α-dystroglycan mucin glycopeptide as promising tools for dystroglycanopathies diagnostic

Dystroglycanopathies are diseases characterized by progressive muscular degeneration and impairment of patient's quality of life. They are associated with altered glycosylation of the dystrophin-glycoprotein (DGC) complex components, such as α-dystroglycan (α-DG), fundamental in the structural and functional stability of the muscle fiber. The diagnosis of dystroglycanopathies is currently based on the observation of clinical manifestations, muscle biopsies and enzymatic measures, and the available monoclonal antibodies are not specific for the dystrophic hypoglycosylated muscle condition. Thus, modified α-DG mucins have been considered potential targets for the development of new diagnostic strategies toward these diseases. In this context, this work describes the synthesis of the hypoglycosylated α-DG mimetic glycopeptide NHAc-Gly-Pro-Thr-Val-Thr[αMan]-Ile-Arg-Gly-BSA (1) as a potential tool for the development of novel antibodies applicable to dystroglycanopathies diagnosis. Glycopeptide 1 was used for the development of polyclonal antibodies and recombinant monoclonal antibodies by Phage Display technology. Accordingly, polyclonal antibodies were reactive to glycopeptide 1, which enables the application of anti-glycopeptide 1 antibodies in immune reactive assays targeting hypoglycosylated α-DG. Regarding monoclonal antibodies, for the first time variable heavy (VH) and variable light (VL) immunoglobulin domains were selected by Phage Display, identified by NGS and described by in silico analysis. The best-characterized VH and VL domains were cloned, expressed in E. coli Shuffle T7 cells, and used to construct a single chain fragment variable that recognized the Glycopeptide 1 (GpαDG1 scFv). Molecular modelling of glycopeptide 1 and GpαDG1 scFv suggested that their interaction occurs through hydrogen bonds and hydrophobic contacts involving amino acids from scFv (I51, Y33, S229, Y235, and P233) and R8 and α-mannose from Glycopeptide 1.

Next-generation sequencing-guided identification and reconstruction of antibody CDR combinations from phage selection outputs

Next-generation sequencing (NGS) technologies have been employed in several phage display platforms for analyzing natural and synthetic antibody sequences and for identifying and reconstructing single-chain variable fragments (scFv) and antigen-binding fragments (Fab) not found by conventional ELISA screens. In this work, we developed an NGS-assisted antibody discovery platform by integrating phage-displayed, single-framework, synthetic Fab libraries. Due to limitations in attainable read and amplicon lengths, NGS analysis of Fab libraries and selection outputs is usually restricted to either V_H or V_L. Since this information alone is not sufficient for high-throughput reconstruction of Fabs, we developed a rapid and simple method for linking and sequencing all diversified CDRs in phage Fab pools. Our method resulted in a reliable and straightforward platform for converting NGS information into Fab clones. We used our NGS-assisted Fab reconstruction method to recover low-frequency rare clones from phage selection outputs. While previous studies chose rare clones for rescue based on their relative frequencies in sequencing outputs, we chose rare clones for reconstruction from less-frequent CDRH3 lengths. In some cases, reconstructed rare clones (frequency ∼0.1%) showed higher affinity and better specificity than high-frequency top clones identified by Sanger sequencing, highlighting the significance of NGS-based approaches in synthetic antibody discovery.

Identification of peptide coatings that enhance diffusive transport of nanoparticles through the tumor microenvironment

In solid tumors, increasing drug penetration promotes their regression and improves the therapeutic index of compounds. However, the heterogeneous extracellular matrix (ECM) acts as a steric and interaction barrier that hinders effective transport of therapeutics, including nanomedicines. Specifically, the interactions between the ECM and surface physicochemical properties of nanomedicines (e.g. charge, hydrophobicity) affect their diffusion and penetration. To address the challenges using existing surface chemistries, we used peptide-presenting phage libraries as a high-throughput approach to screen and identify peptides as coatings with desired physicochemical properties that improve diffusive transport through the tumor microenvironment. Through iterative screening against the ECM and identification by next-generation DNA sequencing and analysis, we selected individual clones and quantify their transport by diffusion assays. Here, we identified a net-neutral charge, hydrophilic peptide P4 that facilitates significantly higher diffusive transport of phage than negative control through in vitro tumor ECM. Through alanine mutagenesis, we confirmed that the hydrophilicity, charge, and spatial ordering impact diffusive transport. The P4 phage clone exhibited almost 200-fold improved uptake in ex vivo pancreatic tumor xenografts compared to the negative control. Nanoparticles coated with P4 exhibited ∼40-fold improvement in diffusivity in pancreatic tumor tissues, and P4-coated particles demonstrated less hindered diffusivity through the ECM compared to functionalized control particles. By leveraging the power of molecular diversity using phage display, we can greatly expand the chemical space of surface chemistries that can improve the transport of nanomedicines through the complex tumor microenvironment to ultimately improve their efficacy.

Deep Mining of Complex Antibody Phage Pools Generated by Cell Panning Enables Discovery of Rare Antibodies Binding New Targets and Epitopes

Phage display technology is a common approach for discovery of therapeutic antibodies. Drug candidates are typically isolated in two steps: First, a pool of antibodies is enriched through consecutive rounds of selection on a target antigen, and then individual clones are characterized in a screening procedure. When whole cells are used as targets, as in phenotypic discovery, the output phage pool typically contains thousands of antibodies, binding, in theory, hundreds of different cell surface receptors. Clonal expansion throughout the phage display enrichment process is affected by multiple factors resulting in extremely complex output phage pools where a few antibodies are highly abundant and the majority is very rare. This is a huge challenge in the screening where only a fraction of the antibodies can be tested using a conventional binding analysis, identifying mainly the most abundant clones typically binding only one or a few targets. As the expected number of antibodies and specificities in the pool is much higher, complementing methods, to reach deeper into the pool, are required, called deep mining methods. In this study, four deep mining methods were evaluated: 1) isolation of rare sub-pools of specific antibodies through selection on recombinant proteins predicted to be expressed on the target cells, 2) isolation of a sub-pool enriched for antibodies of unknown specificities through depletion of the primary phage pool on recombinant proteins corresponding to receptors known to generate many binders, 3) isolation of a sub-pool enriched for antibodies through selection on cells blocked with antibodies dominating the primary phage pool, and 4) next-generation sequencing-based analysis of isolated antibody pools followed by antibody gene synthesis and production of rare but enriched clones. We demonstrate that antibodies binding new targets and epitopes, not discovered through screening alone, can be discovered using described deep mining methods. Overall, we demonstrate the complexity of phage pools generated through selection on cells and show that a combination of conventional screening and deep mining methods are needed to fully utilize such pools. Deep mining will be important in future phenotypic antibody drug discovery efforts to increase the diversity of identified antibodies and targets.

SAROTUP: a suite of tools for finding potential target-unrelated peptides from phage display data

SAROTUP (Scanner And Reporter Of Target-Unrelated Peptides) 3.1 is a significant upgrade to the widely used SAROTUP web server for the rapid identification of target-unrelated peptides (TUPs) in phage display data. At present, SAROTUP has gathered a suite of tools for finding potential TUPs and other purposes. Besides the TUPScan, the motif-based tool, and three tools based on the BDB database, i.e., MimoScan, MimoSearch, and MimoBlast, three predictors based on support vector machine, i.e., PhD7Faster, SABinder and PSBinder, are integrated into SAROTUP. The current version of SAROTUP contains 27 TUP motifs and 823 TUP sequences. We also developed the standalone SAROTUP application with graphical user interface (GUI) and command line versions for processing deep sequencing phage display data and distributed it as an open source package, which can perform perfectly locally on almost all systems that support C++ with little or no modification. The web interfaces of SAROTUP have also been redesigned to be more self-evident and user-friendly. The latest version of SAROTUP is freely available at http://i.uestc.edu.cn/sarotup3.

Phage display screening of TIGIT-specific antibody for antitumor immunotherapy

The fully synthetic humanized phage antibody library has the advantages including the minimized immunogenicity, which frequently happened in hybridoma cell-based antibody production. In this paper, using the constructed diverse complementarity determining region gene library and the germline gene as the backbone, we constructed eight single-chain antibody libraries and a combinatorial antibody library with a big capacity of 1.41 × 10¹⁰. M13EEA helper phage that was engineered from M13KO7 was applied to prepare phage antibody library. The eukaryotic expression of T-cell immune receptor with Ig and ITIM domain (TIGIT) antigen was used as a target antigen for screening. The screening of antigen-specific single-chain Fc-fused protein was performed through evaluation of binding affinity based on ELISA analysis. The IgG antibody was prepared with the screened single-chain protein. Finally, the CB3 antibody was screened out which exhibits the highest binding affinity with TIGIT with the K_d value of 8.155 × 10^-10 M.

A High-Throughput Platform for the Generation of Synthetic Ab Clones by Single-Strand Site-Directed Mutagenesis

Current developments in meta-data analysis and predictive computational models offer alternative routes for the identification of antibodies. In silico-based technologies and NGS data analysis from Ab phage-display selections offer expanded selections of Ab candidates. Accordingly, the identified de novo Abs with predicted selectivity for a target antigen must undergo rapid gene synthesis for downstream Ab characterizations. Here we describe a high-throughput strategy for the generation of synthetic Ab clones for expression as Fab proteins in Escherichia coli. Our approach utilizes simultaneous single-stranded site-directed mutagenesis of diversified Ab regions of a phagemid template with engineered complementary determining regions that contain multiple stop codon and restriction enzyme sites. Subsequently, we perform rapid screening of Ab DNA clones for correct gene assemblies by high-throughput Ab-phage protein expression screens. Identified sequences are corroborated by Sanger DNA sequencing analysis. In summary, our work describes a rapid and cost-effective platform for the high-throughput synthesis of synthetic Ab genes as Fab proteins for implementation into downstream protein validation pipelines.

Current trends in biomarker discovery and analysis tools for traumatic brain injury

Traumatic brain injury (TBI) affects 1.7 million people in the United States each year, causing lifelong functional deficits in cognition and behavior. The complex pathophysiology of neural injury is a primary barrier to developing sensitive and specific diagnostic tools, which consequentially has a detrimental effect on treatment regimens. Biomarkers of other diseases (e.g. cancer) have provided critical insight into disease emergence and progression that lend to developing powerful clinical tools for intervention. Therefore, the biomarker discovery field has recently focused on TBI and made substantial advancements to characterize markers with promise of transforming TBI patient diagnostics and care. This review focuses on these key advances in neural injury biomarkers discovery, including novel approaches spanning from omics-based approaches to imaging and machine learning as well as the evolution of established techniques.

High-throughput retrieval of physical DNA for NGS-identifiable clones in phage display library

In antibody discovery, in-depth analysis of an antibody library and high-throughput retrieval of clones in the library are crucial to identifying and exploiting rare clones with different properties. However, existing methods have technical limitations, such as low process throughput from the laborious cloning process and waste of the phenotypic screening capacity from unnecessary repetitive tests on the dominant clones. To overcome the limitations, we developed a new high-throughput platform for the identification and retrieval of clones in the library, TrueRepertoire™. This new platform provides highly accurate sequences of the clones with linkage information between heavy and light chains of the antibody fragment. Additionally, the physical DNA of clones can be retrieved in high throughput based on the sequence information. We validated the high accuracy of the sequences and demonstrated that there is no platform-specific bias. Moreover, the applicability of TrueRepertoire™ was demonstrated by a phage-displayed single-chain variable fragment library targeting human hepatocyte growth factor protein.

Cross-Reactive and Lineage-Specific Single Domain Antibodies against Influenza B Hemagglutinin

Influenza B virus (IBV) circulates in the human population and causes considerable disease burden worldwide, each year. Current IBV vaccines can struggle to mount an effective cross-reactive immune response, as strains become mismatched, due to constant antigenic changes. Additional strategies which use monoclonal antibodies, with broad reactivity, are of considerable interest, both, as diagnostics and as immunotherapeutics. Alternatives to conventional monoclonal antibodies, such as single domain antibodies (NanobodiesTM) with well-documented advantages for applications in infectious disease, have been emerging. In this study we have isolated single domain antibodies (sdAbs), specific to IBV, using alpacas immunised with recombinant hemagglutinin (HA) from two representative viruses, B/Florida/04/2006 (B/Yamagata lineage) and B/Brisbane/60/2008 (B/Victoria lineage). Using phage display, we have isolated a panel of single domain antibodies (sdAbs), with both cross-reactive and lineage-specific binding. Several sdAbs recognise whole virus antigens, corresponding to influenza B strains included in vaccines spanning over 20 years, and were capable of neutralising IBV pseudotypes corresponding to prototype strains from both lineages. Lineage-specific sdAbs recognised the head domain, whereas, sdAbs identified as cross-reactive could be classified as either head binding or stem binding. Using yeast display, we were able to correlate lineage specificity with naturally occurring sequence divergence, at residue 122 in the highly variable 120 loop of the HA1 domain. The single domain antibodies described, might have applications in IBV diagnostics, vaccine potency testing and as immunotherapeutics.

Coupling Brain Perfusion Screens and Next Generation Sequencing to Identify Blood-Brain Barrier Binding Antibodies

Antibodies that target the blood-brain barrier (BBB) in vivo are of particular interest for the treatment of neurological diseases. Here, we screened a phage display single-chain antibody (scFv) library by brain perfusion in an attempt to isolate scFv that target the rat BBB. After four rounds of screening, the resulting antibody pool remained highly complex and discrete clonal sampling did not identify any scFvs capable of binding to the rat BBB. Thus, the heavy chain CDR3 in the resulting pools was subjected to NGS, and the resulting data was used to identify 12 scFv clones that were of high abundance and/or enriched from round 3 to 4, signifying potential hits. Of these, two scFv, denoted scFv 4 and scFv 40, were identified that bound the rat BBB. Neither of these scFvs was identified by discrete sampling, motivating NGS as a tool to identify lead antibodies from complex in vivo screens.

Primer Design and Inverse PCR on Yeast Display Antibody Selection Outputs

The display of antibodies on the surface of Saccharomyces cerevisiae cells enables the high-throughput and precise selection of specific binders for the target antigen. The recent implementation of next-generation sequencing (NGS) to antibody display screening provides a complete picture of the entire selected polyclonal population. As such, NGS overcomes the limitations of random clones screening, but it comes with two main limitations: (1) depending upon the platform, the sequencing is usually restricted to the variable heavy chain domain complementary determining region 3 (HCDR3), or VH gene, and does not provide additional information on the rest of the antibody gene, including the VL; and (2) the sequence-identified clones are not physically available for validation. Here, we describe a rapid and effective protocol based on an inverse-PCR method to recover specific antibody clones based on their HCDR3 sequence from a yeast display selection output.

Biopanning data bank 2018: hugging next generation phage display

The 2018 update of the biopanning data bank (BDB) stores phage display data sequenced by Sanger sequencing and next generation sequencing technologies. In this work, we upgraded the database with more biopanning data sets and several new features, including (i) incorporation of next generation biopanning data and the unselected population where the target is not determined and the round of screening is zero; (ii) addition of sequencing information; (iii) improvement of browsing and searching systems and 3 D chemical structure viewer; (iv) integration of standalone tools for target-unrelated peptides analysis within conventional phage display and next generation phage display (NGPD) data. In the current version of BDB (released on 19 January 2018), the database houses 3291 sets of biopanning data collected from 1540 published articles, including 95 NGPD data sets and 3196 traditional biopanning data sets. The BDB database serves as an important and comprehensive resource for developing peptide ligands.

Database URL: The BDB database is available at http://immunet.cn/bdb

Phage display peptide libraries: deviations from randomness and correctives

Peptide-expressing phage display libraries are widely used for the interrogation of antibodies. Affinity selected peptides are then analyzed to discover epitope mimetics, or are subjected to computational algorithms for epitope prediction. A critical assumption for these applications is the random representation of amino acids in the initial naïve peptide library. In a previous study, we implemented next generation sequencing to evaluate a naïve library and discovered severe deviations from randomness in UAG codon over-representation as well as in high G phosphoramidite abundance causing amino acid distribution biases. In this study, we demonstrate that the UAG over-representation can be attributed to the burden imposed on the phage upon the assembly of the recombinant Protein 8 subunits. This was corrected by constructing the libraries using supE44-containing bacteria which suppress the UAG driven abortive termination. We also demonstrate that the overabundance of G stems from variant synthesis-efficiency and can be corrected using compensating oligonucleotide-mixtures calibrated by mass spectroscopy. Construction of libraries implementing these correctives results in markedly improved libraries that display random distribution of amino acids, thus ensuring that enriched peptides obtained in biopanning represent a genuine selection event, a fundamental assumption for phage display applications.

Characterizing Phage Genomes for Therapeutic Applications

Multi-drug resistance is increasing at alarming rates. The efficacy of phage therapy, treating bacterial infections with bacteriophages alone or in combination with traditional antibiotics, has been demonstrated in emergency cases in the United States and in other countries, however remains to be approved for wide-spread use in the US. One limiting factor is a lack of guidelines for assessing the genomic safety of phage candidates. We present the phage characterization workflow used by our team to generate data for submitting phages to the Federal Drug Administration (FDA) for authorized use. Essential analysis checkpoints and warnings are detailed for obtaining high-quality genomes, excluding undesirable candidates, rigorously assessing a phage genome for safety and evaluating sequencing contamination. This workflow has been developed in accordance with community standards for high-throughput sequencing of viral genomes as well as principles for ideal phages used for therapy. The feasibility and utility of the pipeline is demonstrated on two new phage genomes that meet all safety criteria. We propose these guidelines as a minimum standard for phages being submitted to the FDA for review as investigational new drug candidates.

Many Routes to an Antibody Heavy-Chain CDR3: Necessary, Yet Insufficient, for Specific Binding

Because of its great potential for diversity, the immunoglobulin heavy-chain complementarity-determining region 3 (HCDR3) is taken as an antibody molecule’s most important component in conferring binding activity and specificity. For this reason, HCDR3s have been used as unique identifiers to investigate adaptive immune responses in vivo and to characterize in vitro selection outputs where display systems were employed. Here, we show that many different HCDR3s can be identified within a target-specific antibody population after in vitro selection. For each identified HCDR3, a number of different antibodies bearing differences elsewhere can be found. In such selected populations, all antibodies with the same HCDR3 recognize the target, albeit at different affinities. In contrast, within unselected populations, the majority of antibodies with the same HCDR3 sequence do not bind the target. In one HCDR3 examined in depth, all target-specific antibodies were derived from the same VDJ rearrangement, while non-binding antibodies with the same HCDR3 were derived from many different V and D gene rearrangements. Careful examination of previously published in vivo datasets reveals that HCDR3s shared between, and within, different individuals can also originate from rearrangements of different V and D genes, with up to 26 different rearrangements yielding the same identical HCDR3 sequence. On the basis of these observations, we conclude that the same HCDR3 can be generated by many different rearrangements, but that specific target binding is an outcome of unique rearrangements and VL pairing: the HCDR3 is necessary, albeit insufficient, for specific antibody binding.

Next-Generation Sequencing of Antibody Display Repertoires

In vitro selection technology has transformed the development of therapeutic monoclonal antibodies. Using methods such as phage, ribosome, and yeast display, high affinity binders can be selected from diverse repertoires. Here, we review strategies for the next-generation sequencing (NGS) of phage- and other antibody-display libraries, as well as NGS platforms and analysis tools. Moreover, we discuss recent examples relating to the use of NGS to assess library diversity, clonal enrichment, and affinity maturation.

Compositional Bias in Naïve and Chemically-modified Phage-Displayed Libraries uncovered by Paired-end Deep Sequencing

Understanding the composition of a genetically-encoded (GE) library is instrumental to the success of ligand discovery. In this manuscript, we investigate the bias in GE-libraries of linear, macrocyclic and chemically post-translationally modified (cPTM) tetrapeptides displayed on the M13KE platform, which are produced via trinucleotide cassette synthesis (19 codons) and NNK-randomized codon. Differential enrichment of synthetic DNA {S}, ligated vector {L} (extension and ligation of synthetic DNA into the vector), naïve libraries {N} (transformation of the ligated vector into the bacteria followed by expression of the library for 4.5 hours to yield a "naïve" library), and libraries chemically modified by aldehyde ligation and cysteine macrocyclization {M} characterized by paired-end deep sequencing, detected a significant drop in diversity in {L} → {N}, but only a minor compositional difference in {S} → {L} and {N} → {M}. Libraries expressed at the N-terminus of phage protein pIII censored positively charged amino acids Arg and Lys; libraries expressed between pIII domains N1 and N2 overcame Arg/Lys-censorship but introduced new bias towards Gly and Ser. Interrogation of biases arising from cPTM by aldehyde ligation and cysteine macrocyclization unveiled censorship of sequences with Ser/Phe. Analogous analysis can be used to explore library diversity in new display platforms and optimize cPTM of these libraries.

Pacific Biosciences Sequencing and IMGT/HighV-QUEST Analysis of Full-Length Single Chain Fragment Variable from an In Vivo Selected Phage-Display Combinatorial Library

Phage-display selection of immunoglobulin (IG) or antibody single chain Fragment variable (scFv) from combinatorial libraries is widely used for identifying new antibodies for novel targets. Next-generation sequencing (NGS) has recently emerged as a new method for the high throughput characterization of IG and T cell receptor (TR) immune repertoires both in vivo and in vitro. However, challenges remain for the NGS sequencing of scFv from combinatorial libraries owing to the scFv length (>800 bp) and the presence of two variable domains [variable heavy (VH) and variable light (VL) for IG] associated by a peptide linker in a single chain. Here, we show that single-molecule real-time (SMRT) sequencing with the Pacific Biosciences RS II platform allows for the generation of full-length scFv reads obtained from an in vivo selection of scFv-phages in an animal model of atherosclerosis. We first amplified the DNA of the phagemid inserts from scFv-phages eluted from an aortic section at the third round of the in vivo selection. From this amplified DNA, 450,558 reads were obtained from 15 SMRT cells. Highly accurate circular consensus sequences from these reads were generated, filtered by quality and then analyzed by IMGT/HighV-QUEST with the functionality for scFv. Full-length scFv were identified and characterized in 348,659 reads. Full-length scFv sequencing is an absolute requirement for analyzing the associated VH and VL domains enriched during the in vivo panning rounds. In order to further validate the ability of SMRT sequencing to provide high quality, full-length scFv sequences, we tracked the reads of an scFv-phage clone P3 previously identified by biological assays and Sanger sequencing. Sixty P3 reads showed 100% identity with the full-length scFv of 767 bp, 53 of them covering the whole insert of 977 bp, which encompassed the primer sequences. The remaining seven reads were identical over a shortened length of 939 bp that excludes the vicinity of primers at both ends. Interestingly these reads were obtained from each of the 15 SMRT cells. Thus, the SMRT sequencing method and the IMGT/HighV-QUEST functionality for scFv provides a straightforward protocol for characterization of full-length scFv from combinatorial phage libraries.

The state-of-play and future of antibody therapeutics

It has been over four decades since the development of monoclonal antibodies (mAbs) using a hybridoma cell line was first reported. Since then more than thirty therapeutic antibodies have been marketed, mostly as oncology, autoimmune and inflammatory therapeutics. While antibodies are very efficient, their cost-effectiveness has always been discussed owing to their high costs, accumulating to more than one billion dollars from preclinical development through to market approval. Because of this, therapeutic antibodies are inaccessible to some patients in both developed and developing countries. The growing interest in biosimilar antibodies as affordable versions of therapeutic antibodies may provide alternative treatment options as well potentially decreasing costs. As certain markets begin to capitalize on this opportunity, regulatory authorities continue to refine the requirements for demonstrating quality, efficacy and safety of biosimilar compared to originator products. In addition to biosimilars, innovations in antibody engineering are providing the opportunity to design biobetter antibodies with improved properties to maximize efficacy. Enhancing effector function, antibody drug conjugates (ADC) or targeting multiple disease pathways via multi-specific antibodies are being explored. The manufacturing process of antibodies is also moving forward with advancements relating to host cell production and purification processes. Studies into the physical and chemical degradation pathways of antibodies are contributing to the design of more stable proteins guided by computational tools. Moreover, the delivery and pharmacokinetics of antibody-based therapeutics are improving as optimized formulations are pursued through the implementation of recent innovations in the field.

Integrating high-throughput screening and sequencing for monoclonal antibody discovery and engineering

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.

Development of a Rapid Identification Method for a Variety of Antibody Candidates Using High-throughput Sequencing

As an alternative to hybridoma technology, the antibody phage library system can also be used for antibody selection. This method enables the isolation of antigen-specific binders through an in vitro selection process known as biopanning. While it has several advantages, such as an avoidance of animal immunization, the phage cloning and screening steps of biopanning are time-consuming and problematic. Here, we introduce a novel biopanning method combined with high-throughput sequencing (HTS) using a next-generation sequencer (NGS) to save time and effort in antibody selection, and to increase the diversity of acquired antibody sequences. Biopannings against a target antigen were performed using a human single chain Fv (scFv) antibody phage library. VH genes in pooled phages at each round of biopanning were analyzed by HTS on a NGS. The obtained data were trimmed, merged, and translated into amino acid sequences. The frequencies (%) of the respective VH sequences at each biopanning step were calculated, and the amplification factor (change of frequency through biopanning) was obtained to estimate the potential for antigen binding. A phylogenetic tree was drawn using the top 50 VH sequences with high amplification factors. Representative VH sequences forming the cluster were then picked up and used to reconstruct scFv genes harboring these VHs. Their derived scFv-Fc fusion proteins showed clear antigen binding activity. These results indicate that a combination of biopanning and HTS enables the rapid and comprehensive identification of specific binders from antibody phage libraries.

Hidden Lineage Complexity of Glycan-Dependent HIV-1 Broadly Neutralizing Antibodies Uncovered by Digital Panning and Native-Like gp140 Trimer

Germline precursors and intermediates of broadly neutralizing antibodies (bNAbs) are essential to the understanding of humoral response to HIV-1 infection and B-cell lineage vaccine design. Using a native-like gp140 trimer probe, we examined antibody libraries constructed from donor-17, the source of glycan-dependent PGT121-class bNAbs recognizing the N332 supersite on the HIV-1 envelope glycoprotein. To facilitate this analysis, a digital panning method was devised that combines biopanning of phage-displayed antibody libraries, 900 bp long-read next-generation sequencing, and heavy/light (H/L)-paired antibodyomics. In addition to single-chain variable fragments resembling the wild-type bNAbs, digital panning identified variants of PGT124 (a member of the PGT121 class) with a unique insertion in the heavy chain complementarity-determining region 1, as well as intermediates of PGT124 exhibiting notable affinity for the native-like trimer and broad HIV-1 neutralization. In a competition assay, these bNAb intermediates could effectively compete with mouse sera induced by a scaffolded BG505 gp140.681 trimer for the N332 supersite. Our study thus reveals previously unrecognized lineage complexity of the PGT121-class bNAbs and provides an array of library-derived bNAb intermediates for evaluation of immunogens containing the N332 supersite. Digital panning may prove to be a valuable tool in future studies of bNAb diversity and lineage development.

Mining Naïve Rabbit Antibody Repertoires by Phage Display for Monoclonal Antibodies of Therapeutic Utility

Owing to their high affinities and specificities, rabbit monoclonal antibodies (mAbs) have demonstrated value and potential primarily as basic research and diagnostic reagents, but, in some cases, also as therapeutics. To accelerate access to rabbit mAbs bypassing immunization, we generated a large naïve rabbit antibody repertoire represented by a phage display library encompassing >10 billion independent antibodies in chimeric rabbit/human Fab format and validated it by next-generation sequencing. Panels of rabbit mAbs selected from this library against two emerging cancer targets, ROR1 and ROR2, revealed high diversity, affinity, and specificity. Moreover, ROR1- and ROR2-targeting rabbit mAbs demonstrated therapeutic utility as components of chimeric antigen receptor-engineered T cells, further corroborating the value of the naïve rabbit antibody library as a rich and virtually unlimited source of rabbit mAbs.

IG and TR single chain fragment variable (scFv) sequence analysis: a new advanced functionality of IMGT/V-QUEST and IMGT/HighV-QUEST

Background

IMGT®, the international ImMunoGeneTics information system® (http://www.imgt.org), was created in 1989 in Montpellier, France (CNRS and Montpellier University) to manage the huge and complex diversity of the antigen receptors, and is at the origin of immunoinformatics, a science at the interface between immunogenetics and bioinformatics. Immunoglobulins (IG) or antibodies and T cell receptors (TR) are managed and described in the IMGT® databases and tools at the level of receptor, chain and domain. The analysis of the IG and TR variable (V) domain rearranged nucleotide sequences is performed by IMGT/V-QUEST (online since 1997, 50 sequences per batch) and, for next generation sequencing (NGS), by IMGT/HighV-QUEST, the high throughput version of IMGT/V-QUEST (portal begun in 2010, 500,000 sequences per batch). In vitro combinatorial libraries of engineered antibody single chain Fragment variable (scFv) which mimic the in vivo natural diversity of the immune adaptive responses are extensively screened for the discovery of novel antigen binding specificities. However the analysis of NGS full length scFv (~850 bp) represents a challenge as they contain two V domains connected by a linker and there is no tool for the analysis of two V domains in a single chain.

Methods

The functionality "Analyis of single chain Fragment variable (scFv)" has been implemented in IMGT/V-QUEST and, for NGS, in IMGT/HighV-QUEST for the analysis of the two V domains of IG and TR scFv. It proceeds in five steps: search for a first closest V-REGION, full characterization of the first V-(D)-J-REGION, then search for a second V-REGION and full characterization of the second V-(D)-J-REGION, and finally linker delimitation.

Results

For each sequence or NGS read, positions of the 5′V-DOMAIN, linker and 3′V-DOMAIN in the scFv are provided in the ‘V-orientated’ sense. Each V-DOMAIN is fully characterized (gene identification, sequence description, junction analysis, characterization of mutations and amino changes). The functionality is generic and can analyse any IG or TR single chain nucleotide sequence containing two V domains, provided that the corresponding species IMGT reference directory is available.

Conclusion

The “Analysis of single chain Fragment variable (scFv)” implemented in IMGT/V-QUEST and, for NGS, in IMGT/HighV-QUEST provides the identification and full characterization of the two V domains of full-length scFv (~850 bp) nucleotide sequences from combinatorial libraries. The analysis can also be performed on concatenated paired chains of expressed antigen receptor IG or TR repertoires.

Enhancing the throughput and multiplexing capabilities of next generation sequencing for efficient implementation of pooled shRNA and CRISPR screens

Next generation sequencing is becoming the method of choice for functional genomic studies that use pooled shRNA or CRISPR libraries. A key challenge in sequencing these mixed-oligo libraries is that they are highly susceptible to hairpin and/or heteroduplex formation. This results in polyclonal, low quality, and incomplete reads and reduces sequencing throughput. Unfortunately, this challenge is significantly magnified in low-to-medium throughput bench-top sequencers as failed reads significantly perturb the maximization of sequence coverage and multiplexing capabilities. Here, we report a methodology that can be adapted to maximize the coverage on a bench-top, Ion PGM System for smaller shRNA libraries with high efficiency. This ligation-based, half-shRNA sequencing strategy minimizes failed sequences and is also equally amenable to high-throughput sequencers for increased multiplexing. Towards this, we also demonstrate that our strategy to reduce heteroduplex formation improves multiplexing capabilities of pooled CRISPR screens using Illumina NextSeq 500. Overall, our method will facilitate sequencing of pooled shRNA or CRISPR libraries from genomic DNA and maximize sequence coverage.

Large Diversity of Functional Nanobodies from a Camelid Immune Library Revealed by an Alternative Analysis of Next-Generation Sequencing Data

Next-generation sequencing (NGS) has been applied successfully to the field of therapeutic antibody discovery, often outperforming conventional screening campaigns which tend to identify only the more abundant selective antibody sequences. We used NGS to mine the functional nanobody repertoire from a phage-displayed camelid immune library directed to the recepteur d’origine nantais (RON) receptor kinase. Challenges to this application of NGS include accurate removal of read errors, correct identification of related sequences, and establishing meaningful inclusion criteria for sequences-of-interest. To this end, a sequence identity threshold was defined to separate unrelated full-length sequence clusters by exploring a large diverse set of publicly available nanobody sequences. When combined with majority-rule consensus building, applying this elegant clustering approach to the NGS data set revealed a wealth of >5,000-enriched candidate RON binders. The huge binding potential predicted by the NGS approach was explored through a set of randomly selected candidates: 90% were confirmed as RON binders, 50% of which functionally blocked RON in an ERK phosphorylation assay. Additional validation came from the correct prediction of all 35 RON binding nanobodies which were identified by a conventional screening campaign of the same immune library. More detailed characterization of a subset of RON binders revealed excellent functional potencies and a promising epitope diversity. In summary, our approach exposes the functional diversity and quality of the outbred camelid heavy chain-only immune response and confirms the power of NGS to identify large numbers of promising nanobodies.

Antibody Engineering for Pursuing a Healthier Future

Since the development of antibody-production techniques, a number of immunoglobulins have been developed on a large scale using conventional methods. Hybridoma technology opened a new horizon in the production of antibodies against target antigens of infectious pathogens, malignant diseases including autoimmune disorders, and numerous potent toxins. However, these clinical humanized or chimeric murine antibodies have several limitations and complexities. Therefore, to overcome these difficulties, recent advances in genetic engineering techniques and phage display technique have allowed the production of highly specific recombinant antibodies. These engineered antibodies have been constructed in the hunt for novel therapeutic drugs equipped with enhanced immunoprotective abilities, such as engaging immune effector functions, effective development of fusion proteins, efficient tumor and tissue penetration, and high-affinity antibodies directed against conserved targets. Advanced antibody engineering techniques have extensive applications in the fields of immunology, biotechnology, diagnostics, and therapeutic medicines. However, there is limited knowledge regarding dynamic antibody development approaches. Therefore, this review extends beyond our understanding of conventional polyclonal and monoclonal antibodies. Furthermore, recent advances in antibody engineering techniques together with antibody fragments, display technologies, immunomodulation, and broad applications of antibodies are discussed to enhance innovative antibody production in pursuit of a healthier future for humans.

Next-generation sequencing enables the discovery of more diverse positive clones from a phage-displayed antibody library

Phage display technology provides a powerful tool to screen a library for a binding molecule via an enrichment process. It has been adopted as a critical technology in the development of therapeutic antibodies. However, a major drawback of phage display technology is that because the degree of the enrichment cannot be controlled during the bio-panning process, it frequently results in a limited number of clones. In this study, we applied next-generation sequencing (NGS) to screen clones from a library and determine whether a greater number of clones can be identified using NGS than using conventional methods. Three chicken immune single-chain variable fragment (scFv) libraries were subjected to bio-panning on prostate-specific antigen (PSA). Phagemid DNA prepared from the original libraries as well as from the Escherichia coli pool after each round of bio-panning was analyzed using NGS, and the heavy chain complementarity-determining region 3 (HCDR3) sequences of the scFv clones were determined. Subsequently, through two-step linker PCR and cloning, the entire scFv gene was retrieved and analyzed for its reactivity to PSA in a phage enzyme immunoassay. After four rounds of bio-panning, the conventional colony screening method was performed for comparison. The scFv clones retrieved from NGS analysis included all clones identified by the conventional colony screening method as well as many additional clones. The enrichment of the HCDR3 sequence throughout the bio-panning process was a positive predictive factor for the selection of PSA-reactive scFv clones.