From deep sequencing to actual clones

Phage display technology and its impact in the discovery of novel protein-based drugs

INTRODUCTION

Phage display technology is a well-established versatile in vitro display technology that has been used for over 35 years to identify peptides and antibodies for use as reagents and therapeutics, as well as exploring the diversity of alternative scaffolds as another option to conventional therapeutic antibody discovery. Such successes have been responsible for spawning a range of biotechnology companies, as well as many complementary technologies devised to expedite the drug discovery process and resolve bottlenecks in the discovery workflow.

AREAS COVERED

In this perspective, the authors summarize the application of phage display for drug discovery and provide examples of protein-based drugs that have either been approved or are being developed in the clinic. The amenability of phage display to generate functional protein molecules to challenging targets and recent developments of strategies and techniques designed to harness the power of sampling diverse repertoires are highlighted.

EXPERT OPINION

Phage display is now routinely combined with cutting-edge technologies to deep-mine antibody-based repertoires, peptide, or alternative scaffold libraries generating a wealth of data that can be leveraged, e.g. via artificial intelligence, to enable the potential for clinical success in the discovery and development of protein-based therapeutics.

Unraveling the Properties of Phage Display Fab Libraries and Their Use in the Selection of Gliadin-Specific Probes by Applying High-Throughput Nanopore Sequencing

Directed evolution is a pivotal strategy for new antibody discovery, which allowed the generation of high-affinity Fabs against gliadin from two antibody libraries in our previous studies. One of the libraries was exclusively derived from celiac patients' mRNA (immune library) while the other was obtained through a protein engineering approach (semi-immune library). Recent advances in high-throughput DNA sequencing techniques are revolutionizing research across genomics, epigenomics, and transcriptomics. In the present work, an Oxford Nanopore in-lab sequencing device was used to comprehensively characterize the composition of the constructed libraries, both at the beginning and throughout the phage-mediated selection processes against gliadin. A customized analysis pipeline was used to select high-quality reads, annotate chain distribution, perform sequence analysis, and conduct statistical comparisons between the different selection rounds. Some immunological attributes of the most representative phage variants after the selection process were also determined. Sequencing results revealed the successful transfer of the celiac immune response features to the immune library and the antibodies derived from it, suggesting the crucial role of these features in guiding the selection of high-affinity recombinant Fabs against gliadin. In summary, high-throughput DNA sequencing has improved our understanding of the selection processes aimed at generating molecular binders against gliadin.

Machine learning to predict continuous protein properties from binary cell sorting data and map unseen sequence space

Proteins are a diverse class of biomolecules responsible for wide-ranging cellular functions, from catalyzing reactions to recognizing pathogens. The ability to evolve proteins rapidly and inexpensively toward improved properties is a common objective for protein engineers. Powerful high-throughput methods like fluorescent activated cell sorting and next-generation sequencing have dramatically improved directed evolution experiments. However, it is unclear how to best leverage these data to characterize protein fitness landscapes more completely and identify lead candidates. In this work, we develop a simple yet powerful framework to improve protein optimization by predicting continuous protein properties from simple directed evolution experiments using interpretable, linear machine learning models. Importantly, we find that these models, which use data from simple but imprecise experimental estimates of protein fitness, have predictive capabilities that approach more precise but expensive data. Evaluated across five diverse protein engineering tasks, continuous properties are consistently predicted from readily available deep sequencing data, demonstrating that protein fitness space can be reasonably well modeled by linear relationships among sequence mutations. To prospectively test the utility of this approach, we generated a library of stapled peptides and applied the framework to predict affinity and specificity from simple cell sorting data. We then coupled integer linear programming, a method to optimize protein fitness from linear weights, with mutation scores from machine learning to identify variants in unseen sequence space that have improved and co-optimal properties. This approach represents a versatile tool for improved analysis and identification of protein variants across many domains of protein engineering.

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.

Direct selection of functional fluorescent-protein antibody fusions by yeast display

Antibodies are important reagents for research, diagnostics, and therapeutics. Many examples of chimeric proteins combining the specific target recognition of antibodies with complementing functionalities such as fluorescence, toxicity or enzymatic activity have been described. However, antibodies selected solely on the basis of their binding specificities are not necessarily ideal candidates for the construction of chimeras. Here, we describe a high throughput method based on yeast display to directly select antibodies most suitable for conversion to fluorescent chimera. A library of scFv binders was converted to a fluorescent chimeric form, by cloning thermal green protein into the linker between VH and VL, and directly selecting for both binding and fluorescent functionality. This allowed us to directly identify antibodies functional in the single chain TGP format, that manifest higher protein expression, easier protein purification, and one-step binding assays.

Generation of synthetic antibody fragments with optimal complementarity determining region lengths for Notch-1 recognition

Synthetic antibodies have been engineered against a wide variety of antigens with desirable biophysical, biochemical, and pharmacological properties. Here, we describe the generation and characterization of synthetic antigen-binding fragments (Fabs) against Notch-1. Three single-framework synthetic Fab libraries, named S, F, and modified-F, were screened against the recombinant human Notch-1 extracellular domain using phage display. These libraries were built on a modified trastuzumab framework, containing two or four diversified complementarity-determining regions (CDRs) and different CDR diversity designs. In total, 12 Notch-1 Fabs were generated with 10 different CDRH3 lengths. These Fabs possessed a high affinity for Notch-1 (sub-nM to mid-nM K_Dapp values) and exhibited different binding profiles (mono-, bi-or tri-specific) toward Notch/Jagged receptors. Importantly, we showed that screening focused diversity libraries, implementing next-generation sequencing approaches, and fine-tuning the CDR length diversity provided improved binding solutions for Notch-1 recognition. These findings have implications for antibody library design and antibody phage display.

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.

Short Read-Length Next Generation DNA Sequencing of Antibody CDR Combinations from Phage Selection Outputs

Phage display is commonly used to select target-binding antibody fragments from large libraries containing billions of unique antibody clones. In practice, selection outputs are often highly heterogenous, making it desirable to recover sequence information from the selected pool. Next Generation DNA Sequencing (NGS) enables the acquisition of sufficient sequencing reads to cover the pool diversity, however read-lengths are typically too short to capture paired antibody complementarity-determining regions (CDRs), which is needed to reconstruct target-binding antibody fragments. Here, we describe a simple in vitro protocol to bring the DNA encoding the antibody CDRs closer together. The final PCR product referred to as a "CDR strip" is suitable for short read-length NGS. In this method, phagemid ssDNA is recovered from antibody phage display biopanning and used as a template to create a heteroduplex with deletions between CDRs of interest. The shorter strand in the heteroduplex is preferentially PCR amplified to generate a CDR strip that is sequenced using NGS. We have also included a bioinformatics approach to analyze the CDR strip populations so that single antibody clones can be created from paired CDR sequences.

Antibody display technologies: selecting the cream of the crop

Antibody display technologies enable the successful isolation of antigen-specific antibodies with therapeutic potential. The key feature that facilitates the selection of an antibody with prescribed properties is the coupling of the protein variant to its genetic information and is referred to as genotype phenotype coupling. There are several different platform technologies based on prokaryotic organisms as well as strategies employing higher eukaryotes. Among those, phage display is the most established system with more than a dozen of therapeutic antibodies approved for therapy that have been discovered or engineered using this approach. In recent years several other technologies gained a certain level of maturity, most strikingly mammalian display. In this review, we delineate the most important selection systems with respect to antibody generation with an emphasis on recent developments.

Exploiting next-generation sequencing in antibody selections - a simple PCR method to recover binders

Antibody discovery using invitro display technologies such as phage and/or yeast display has become acornerstone in many research and development projects, including the creation of new drugs for clinical use. Traditionally, after the selection phase, random clones are isolated for binding validation and Sanger sequencing. More recently, next-generation sequencing (NGS) technology has allowed deeper insight into the antibody population after aselection campaign, enabling the identification of many more specific binders. However, this approach only provides the DNA sequences of potential binders, the properties of which need to be fully elucidated by obtaining corresponding clones and expressing them for further validation. Here we present arapid novel method to harvest potential clones identified by NGS that uses asimple PCR and yeast recombination approach. The protocol was tested in selections against three different targets and was able to recover clones at an abundance level that would be impractical to identify using traditional methods.

Engineered Protein Scaffolds as Next-Generation Therapeutics

The concept of engineering robust protein scaffolds for novel binding functions emerged 20 years ago, one decade after the advent of recombinant antibody technology. Early examples were the Affibody, Monobody (Adnectin), and Anticalin proteins, which were derived from fragments of streptococcal protein A, from the tenth type III domain of human fibronectin, and from natural lipocalin proteins, respectively. Since then, this concept has expanded considerably, including many other protein templates. In fact, engineered protein scaffolds with useful binding specificities, mostly directed against targets of biomedical relevance, constitute an area of active research today, which has yielded versatile reagents as laboratory tools. However, despite strong interest from basic science, only a handful of those protein scaffolds have undergone biopharmaceutical development up to the clinical stage. This includes the abovementioned pioneering examples as well as designed ankyrin repeat proteins (DARPins). Here we review the current state and clinical validation of these next-generation therapeutics.

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.

Advances in the Production and Batch Reformatting of Phage Antibody Libraries

Phage display antibody libraries have proven an invaluable resource for the isolation of diagnostic and potentially therapeutic antibodies, the latter usually being antibody fragments converted into IgG formats. Recent advances in the production of highly diverse and functional antibody libraries are considered here, including for Fabs, scFvs and nanobodies. These advances include codon optimisation during generation of CDR diversity, improved display levels using novel signal sequences, molecular chaperones and isomerases and the use of highly stable scaffolds with relatively high expression levels. In addition, novel strategies for the batch reformatting of scFv and Fab phagemid libraries, derived from phage panning, into IgG formats are described. These strategies allow the screening of antibodies in the end-use format, facilitating more efficient selection of potential therapeutics.

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.

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.

Affinity maturation of an TpoR targeting antibody in full-length IgG form for enhanced agonist activity

It has been observed that converting scFv formatted antibodies to full-length IgG often associates with loss of affinity. We aim to address this issue in this paper by establishing an integrated affinity maturation method applying yeast display technology platform. To demonstrate that, we employed a human thrombopoietin receptor targeting antibody named 3D9 which was identified previously from a combinational antibody library in scFv-Fc fusion protein form. We have observed that significant potency loss happened when 3D9 was transformed to full-length IgG form. In this study, we tested whether the potency of the full-length IgG can be improved by affinity maturation of 3D9 using a modified Fab yeast display platform. An efficient CDR3 targeted mutagenesis strategy was designed for Fab library with pre-designed CDR diversity. Next generation sequencing was also used for evaluation of the enrichment process and investigation of sequence-function relationship of the antibody. A variant with improved affinity and higher potency was identified. The study demonstrates that the strategy we used here are efficient for optimizing affinity and activity of full-length IgGs.

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.

Selection of phage-displayed accessible recombinant targeted antibodies (SPARTA): methodology and applications

We developed a potentially novel and robust antibody discovery methodology, termed selection of phage-displayed accessible recombinant targeted antibodies (SPARTA). This combines an in vitro screening step of a naive human antibody library against known tumor targets, with in vivo selections based on tumor-homing capabilities of a preenriched antibody pool. This unique approach overcomes several rate-limiting challenges to generate human antibodies amenable to rapid translation into medical applications. As a proof of concept, we evaluated SPARTA on 2 well-established tumor cell surface targets, EphA5 and GRP78. We evaluated antibodies that showed tumor-targeting selectivity as a representative panel of antibody-drug conjugates (ADCs) and were highly efficacious. Our results validate a discovery platform to identify and validate monoclonal antibodies with favorable tumor-targeting attributes. This approach may also extend to other diseases with known cell surface targets and affected tissues easily isolated for in vivo selection.

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.

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.

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.

Advanced Methodologies in High-Throughput Sequencing of Immune Repertoires

In recent years, major efforts have been made to develop sophisticated experimental and bioinformatic workflows for sequencing adaptive immune repertoires. The immunological insight gained has been applied to fields as varied as lymphocyte biology, immunodiagnostics, vaccines, cancer immunotherapy, and antibody engineering. In this review, we provide a detailed overview of these advanced methodologies, focusing specifically on strategies to reduce sequencing errors and bias and to achieve high-throughput pairing of variable regions (e.g., heavy-light or alpha-beta chains). In addition, we highlight recent technologies for single-cell transcriptome sequencing that can be integrated with immune repertoires. Finally, we provide a perspective on advanced immune repertoire sequencing and its ability to impact basic immunology, biopharmaceutical drug discovery and development, and cancer immunotherapy.

Deep sequencing in library selection projects: what insight does it bring?

High throughput sequencing is poised to change all aspects of the way antibodies and other binders are discovered and engineered. Millions of available sequence reads provide an unprecedented sampling depth able to guide the design and construction of effective, high quality naïve libraries containing tens of billions of unique molecules. Furthermore, during selections, high throughput sequencing enables quantitative tracing of enriched clones and position-specific guidance to amino acid variation under positive selection during antibody engineering. Successful application of the technologies relies on specific PCR reagent design, correct sequencing platform selection, and effective use of computational tools and statistical measures to remove error, identify antibodies, estimate diversity, and extract signatures of selection from the clone down to individual structural positions. Here we review these considerations and discuss some of the remaining challenges to the widespread adoption of the technology.

Next generation sequencing of all variable loops of synthetic single framework scFv-Application in anti-HDL antibody selections

Next generation sequencing (NGS) can be applied to monitoring antibody phage display library selection processes to follow the enrichment of each individual antibody clone. Utilising the recent development of the Illumina sequencing platform enabling sequencing up to 2×300bp, we have developed a method to deep sequence all complementarity determining regions (CDRs) in the clones obtained from a synthetic single framework antibody library. This was complemented by an in-house bioinformatics pipeline for efficient analysis of the sequencing results. The method was utilised to study antibody selections against high density lipoprotein (HDL) particles. Sequencing of the output from each selection round enabled extraction of useful information on both the total copy numbers as well as the relative enrichment rates of the clones. Ten antibody clones showing different ranking in terms of frequency were reproduced from synthetic DNA constructs and their capacity to bind HDL was verified by an immunoassay. The method thus facilitates the isolation of clones of interest, and in particular can assist retrieval of less efficiently enriched, yet interesting clones, which are unlikely to be identified by conventional, random colony picking based, screening.

Proteome-wide Identification of Novel Ceramide-binding Proteins by Yeast Surface cDNA Display and Deep Sequencing

Although the bioactive sphingolipid ceramide is an important cell signaling molecule, relatively few direct ceramide-interacting proteins are known. We used an approach combining yeast surface cDNA display and deep sequencing technology to identify novel proteins binding directly to ceramide. We identified 234 candidate ceramide-binding protein fragments and validated binding for 20. Most (17) bound selectively to ceramide, although a few (3) bound to other lipids as well. Several novel ceramide-binding domains were discovered, including the EF-hand calcium-binding motif, the heat shock chaperonin-binding motif STI1, the SCP2 sterol-binding domain, and the tetratricopeptide repeat region motif. Interestingly, four of the verified ceramide-binding proteins (HPCA, HPCAL1, NCS1, and VSNL1) and an additional three candidate ceramide-binding proteins (NCALD, HPCAL4, and KCNIP3) belong to the neuronal calcium sensor family of EF hand-containing proteins. We used mutagenesis to map the ceramide-binding site in HPCA and to create a mutant HPCA that does not bind to ceramide. We demonstrated selective binding to ceramide by mammalian cell-produced wild type but not mutant HPCA. Intriguingly, we also identified a fragment from prostaglandin D2synthase that binds preferentially to ceramide 1-phosphate. The wide variety of proteins and domains capable of binding to ceramide suggests that many of the signaling functions of ceramide may be regulated by direct binding to these proteins. Based on the deep sequencing data, we estimate that our yeast surface cDNA display library covers ∼60% of the human proteome and our selection/deep sequencing protocol can identify target-interacting protein fragments that are present at extremely low frequency in the starting library. Thus, the yeast surface cDNA display/deep sequencing approach is a rapid, comprehensive, and flexible method for the analysis of protein-ligand interactions, particularly for the study of non-protein ligands.

Platform for high-throughput antibody selection using synthetically-designed antibody libraries

Synthetic humanized antibody libraries are frequently generated by random incorporation of changes at multiple positions in the antibody hypervariable regions. Although these libraries have very large theoretical diversities (>10(20)), the practical diversity that can be achieved by transformation of Escherichia coli is limited to about 10(10). To constrain the practical diversity to sequences that more closely mimic the diversity of natural human antibodies, we generated a scFv phage library using entirely pre-defined complementarity determining regions (CDR). We have used this library to select for novel antibodies against four human protein targets and demonstrate that identification of enriched sequences at each of the six CDRs in early selection rounds can be used to reconstruct a consensus antibody with selectivity for the target.

One-Step Recovery of scFv Clones from High-Throughput Sequencing-Based Screening of Phage Display Libraries Challenged to Cells Expressing Native Claudin-1

Expanding the availability of monoclonal antibodies interfering with hepatitis C virus infection of hepatocytes is an active field of investigation within medical biotechnologies, to prevent graft reinfection in patients subjected to liver transplantation and to overcome resistances elicited by novel antiviral drugs. In this paper, we describe a complete pipeline for screening of phage display libraries of human scFvs against native Claudin-1, a tight-junction protein involved in hepatitis C virus infection, expressed on the cell surface of human hepatocytes. To this aim, we implemented a high-throughput sequencing approach for library screening, followed by a simple and effective strategy to recover active binder clones from enriched sublibraries. The recovered clones were successfully converted to active immunoglobulins, thus demonstrating the effectiveness of the whole procedure. This novel approach can guarantee rapid and cheap isolation of antibodies for virtually any native antigen involved in human diseases, for therapeutic and/or diagnostic applications.

Recombinant renewable polyclonal antibodies

Only a small fraction of the antibodies in a traditional polyclonal antibody mixture recognize the target of interest, frequently resulting in undesirable polyreactivity. Here, we show that high-quality recombinant polyclonals, in which hundreds of different antibodies are all directed toward a target of interest, can be easily generated in vitro by combining phage and yeast display. We show that, unlike traditional polyclonals, which are limited resources, recombinant polyclonal antibodies can be amplified over one hundred million-fold without losing representation or functionality. Our protocol was tested on 9 different targets to demonstrate how the strategy allows the selective amplification of antibodies directed toward desirable target specific epitopes, such as those found in one protein but not a closely related one, and the elimination of antibodies recognizing common epitopes, without significant loss of diversity. These recombinant renewable polyclonal antibodies are usable in different assays, and can be generated in high throughput. This approach could potentially be used to develop highly specific recombinant renewable antibodies against all human gene products.

Identification of cross-reactive single-domain antibodies against serum albumin using next-generation DNA sequencing

Antibodies that cross-react with multiple isoforms or homologue of a given protein are often desirable, especially in therapeutic applications. Here, we report the identification of several unique, clonally unrelated, single-domain antibodies (sdAbs) that bind to multiple serum albumin orthologues (human, rhesus, rat and mouse) with low-to-medium nanomolar affinity from a llama immunized only with human serum albumin. Using single-round panning of a phage-displayed sdAb library against serum albumins and next-generation DNA sequencing, we were able to predict patterns of sdAb reactivity to the albumins of different species with ∼90% accuracy. We expect this strategy to be generally applicable for identifying cross-reactive sdAbs, particularly when these exist at low frequency and/or are poorly enriched by panning. Moreover, the sdAbs identified here are of potential interest for serum half-life extension of biologics.