Deep sequencing analysis of phage libraries using Illumina platform

Dehydrin client proteins identified using phage display affinity selected libraries processed with Paired-End PhAge Sequencing (PEPA-Seq)

The LATE EMBRYOGENESIS ABUNDANT PROTEINs (LEAPs) are a class of noncatalytic, intrinsically disordered proteins with a malleable structure. Some LEAPs exhibit a protein and/or membrane binding capacity and LEAP binding to various targets has been positively correlated with abiotic stress tolerance. Regarding the LEAPs' presumptive role in protein protection, identifying client proteins (CtPs) to which LEAPs bind is one practicable means of revealing the mechanism by which they exert their function. To this end, we used phage display affinity selection to screen libraries derived from Arabidopsis thaliana seed mRNA with recombinant orthologous LEAPs from Arabidopsis and soybean (Glycine max). Subsequent high throughput sequencing of DNA from affinity-purified phage was performed to characterize the entire sub-population of phage retained by each LEAP orthologue. This entailed cataloging in-frame fusions, elimination of false positives, and aligning the hits on the CtP scaffold to reveal domains of respective CtPs that bound to orthologous LEAPs. This approach (Paired-end PhAge Sequencing, or PEPA-Seq) revealed a subpopulation of the proteome constituting the CtP repertoire in common between the two DHNs orthologues (LEA14 and GmPm12) compared to BSA (unrelated binding control). The veracity of LEAP:CtP binding for one of the CtPs (LEA14 and GmPM12 self-association) was independently assessed using temperature related intensity change (TRIC) analysis. Moreover, LEAP:CtP interactions for four other CtPs were confirmed in planta using bimolecular fluorescence complementation (BiFC) assays. The results provide insights into the involvement of the DHN Y-segments and K-domains in protein binding.

Next Generation SICLOPPS Screening for the Identification of Inhibitors of the HIF-1α/HIF-1β Protein-Protein Interaction

Split-intein circular ligation of proteins and peptides (SICLOPPS) is a method for generating intracellular libraries of cyclic peptides that has yielded several first-in-class inhibitors. Here, we detail a revised high-content, high-throughput SICLOPPS screening protocol that utilizes next-generation sequencing, biopanning, and computational tools to identify hits against a given protein-protein interaction. We used this platform for the identification of inhibitors of the HIF-1α/HIF-1β protein-protein interaction. The revised platform resulted in a significantly higher positive hit rate than that previously reported for SICLOPPS screens, and the identified cyclic peptides were more active in vitro and in cells than our previously reported inhibitors. The platform detailed here may be used for the identification of inhibitors of a wide range of other targets.

Identification of Peptide Binding Motifs for Calcium Sulfate Hemihydrate using Phage Display

Selective control over crystallization in complex multicomponent systems such as hydrating cements is a key issue in modern material science. In this context, rational selection-based approaches appear highly promising in the quest for new additive chemistries. Here we have used phage display to identify peptide structures showing high affinity to adsorb on the surfaces of calcium sulfate hemihydrate (also referred to as bassanite), an important hydraulic binder employed in large scales by the construction industry. The results suggest a triplet of amino acids consisting of aspartic acid, serine and leucine, to maintain strong interactions with the surfaces of hemihydrate particles. This notion is confirmed by actual hydration experiments, in which the identified peptide motif provides strictly selective effects during the transformation of bassanite into more stable gypsum. Our work thus contributes to a better understanding of hydraulic binders and their required improvement for a sustainable future.

First-Generation Radiolabeled Cyclic Peptides for Molecular Imaging of Platelet-Derived Growth Factor Receptor α

Occult nodal spread and metastatic disease require longstanding imaging and biochemical assessments for thyroid cancer, a disease that has a propensity for diffuse, small-volume disease. We have developed a 64Cu-labeled platelet-derived growth factor receptor α (PDGFRA) antibody for immuno-PET of PDGFRA in metastatic papillary thyroid cancer (PTC). The present work describes the discovery of small cyclic PDGFRA-targeting peptides, their binding features, and radiolabeling with positron emitter gallium-68 (68Ga) for in vitro and in vivo characterization in thyroid cancer models. Phage-display technology with two separate libraries and seven different cell lines was used through three rounds of biopanning as well as flow cytometry and comparative analysis with recombinant protein to select specific peptide sequences. Phenotypic binding analysis was completed by using phosphorylation and cell migration assays. In vitro protein binding was analyzed with thermophoresis and flow cytometry using the fluorescent-labeled PDGFRA peptide. Peptide candidates were modified with the NOTA chelator for radiolabeling with 68Ga. In vitro cell uptake was studied in various thyroid cancer cell lines. In vivo studies of 68Ga-labeled peptides included metabolic stability and PET imaging. From the original library (1013 compounds), five different peptide groups were identified based on biopanning experiments with and without the α subunit of PDGFR, leading to ∼50 peptides. Subsequent phenotypic screening revealed two core peptide sequences (CP16 and CP18) that demonstrated significant changes in the level of PDGFRA phosphorylation and cell migration. Alanine scan sublibraries were created from these two lead peptide sequences, and peptides were radiolabeled using 68Ga-GaCl3 at pH 4.5, resulting in RCP > 95% within 34-40 min, including SPE purification. Cyclic peptide CP18.5 showed the strongest effects on cell migration, flow cytometry, and binding by visual interference color assay. 68Ga-labeled PDGFRA-targeting peptides showed elevated cell and tumor uptake in models of thyroid cancer, with 68Ga-NOTA-CP18.5 being the lead candidate. However, metabolic stability in vivo was compromised for 68Ga-NOTA-CP18.5 vs 68Ga-NOTA-CP18 but without impacting tumor uptake or clearance profiles. First-generation radiolabeled cyclic peptides have been developed as novel radiotracers, particularly 68Ga-NOTA-CP18.5, for the molecular imaging of PDGFRA in thyroid cancer.

Development of a new affinity maturation protocol for the construction of an internalizing anti-nucleolin antibody library

Over the last decades, monoclonal antibodies have substantially improved the treatment of several conditions. The continuous search for novel therapeutic targets and improvements in antibody's structure, demands for a constant optimization of their development. In this regard, modulation of an antibody's affinity to its target has been largely explored and culminated in the discovery and optimization of a variety of molecules. It involves the creation of antibody libraries and selection against the target of interest. In this work, we aimed at developing a novel protocol to be used for the affinity maturation of an antibody previously developed by our group. An antibody library was constructed using an in vivo random mutagenesis approach that, to our knowledge, has not been used before for antibody development. Then, a cell-based phage display selection protocol was designed to allow the fast and simple screening of antibody clones capable of being internalized by target cells. Next generation sequencing coupled with computer analysis provided an extensive characterization of the created library and post-selection pool, that can be used as a guide for future antibody development. With a single selection step, an enrichment in the mutated antibody library, given by a decrease in almost 50% in sequence diversity, was achieved, and structural information useful in the study of the antibody-target interaction in the future was obtained.

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.

Brain-Penetrating Peptide Shuttles across the Blood-Brain Barrier and Extracellular-like Space

Systemic delivery of therapeutics into the brain is greatly impaired by multiple biological barriers─the blood-brain barrier (BBB) and the extracellular matrix (ECM) of the extracellular space. To address this problem, we developed a combinatorial approach to identify peptides that can shuttle and transport across both barriers. A cysteine-constrained heptapeptide M13 phage display library was iteratively panned against an established BBB model for three rounds to select for peptides that can transport across the barrier. Using next-generation DNA sequencing and in silico analysis, we identified peptides that were selectively enriched from successive rounds of panning for functional validation in vitro and in vivo. Select peptide-presenting phages exhibited efficient shuttling across the in vitro BBB model. Two clones, Pep-3 and Pep-9, exhibited higher specificity and efficiency of transcytosis than controls. We confirmed that peptides Pep-3 and Pep-9 demonstrated better diffusive transport through the extracellular matrix than gold standard nona-arginine and clinically trialed angiopep-2 peptides. In in vivo studies, we demonstrated that systemically administered Pep-3 and Pep-9 peptide-presenting phages penetrate the BBB and distribute into the brain parenchyma. In addition, free peptides Pep-3 and Pep-9 achieved higher accumulation in the brain than free angiopep-2 and may exhibit brain targeting. In summary, these in vitro and in vivo studies highlight that combinatorial phage display with a designed selection strategy can identify peptides as promising carriers, which are able to overcome the multiple biological barriers of the brain and shuttle different-sized molecules from small fluorophores to large macromolecules for improved delivery into the brain.

Systemic application of bone-targeting peptidoglycan hydrolases as a novel treatment approach for staphylococcal bone infection

IMPORTANCE

The rising prevalence of antimicrobial resistance in S. aureus has rendered treatment of staphylococcal infections increasingly difficult, making the discovery of alternative treatment options a high priority. Peptidoglycan hydrolases, a diverse group of bacteriolytic enzymes, show high promise as such alternatives due to their rapid and specific lysis of bacterial cells, independent of antibiotic resistance profiles. However, using these enzymes for the systemic treatment of local infections, such as osteomyelitis foci, needs improvement, as the therapeutic distributes throughout the whole host, resulting in low concentrations at the actual infection site. In addition, the occurrence of intracellularly persisting bacteria can lead to relapsing infections. Here, we describe an approach using tissue-targeting to increase the local concentration of therapeutic enzymes in the infected bone. The enzymes were modified with a short targeting moiety that mediated accumulation of the therapeutic in osteoblasts and additionally enables targeting of intracellularly surviving bacteria.

Advances in Ultrahigh Throughput Hit Discovery with Tandem Mass Spectrometry Encoded Libraries

Discovering new bioactive molecules is crucial for drug development. Finding a hit compound for a new drug target usually requires screening of millions of molecules. Affinity selection based technologies have revolutionized early hit discovery by enabling the rapid screening of libraries with millions or billions of compounds in short timeframes. In this Perspective, we describe recent technology breakthroughs that enable the screening of ultralarge synthetic peptidomimetic libraries with a barcode-free tandem mass spectrometry decoding strategy. A combination of combinatorial synthesis, affinity selection, automated de novo peptide sequencing algorithms, and advances in mass spectrometry instrumentation now enables hit discovery from synthetic libraries with over 100 million members. We provide a perspective on this powerful technology and showcase success stories featuring the discovery of high affinity binders for a number of drug targets including proteins, nucleic acids, and specific cell types. Further, we show the usage of the technology to discover synthetic peptidomimetics with specific functions and reactivity. We predict that affinity selection coupled with tandem mass spectrometry and automated de novo decoding will rapidly evolve further and become a broadly used drug discovery technology.

Phage-based peptides for pancreatic cancer diagnosis and treatment: alternative approach

Pancreatic cancer is a devastating disease with a high mortality rate and a lack of effective therapies. The challenges associated with early detection and the highly aggressive nature of pancreatic cancer have limited treatment options, underscoring the urgent need for better disease-modifying therapies. Peptide-based biotherapeutics have become an attractive area of research due to their favorable properties such as high selectivity and affinity, chemical modifiability, good tissue permeability, and easy metabolism and excretion. Phage display, a powerful technique for identifying peptides with high affinity and specificity for their target molecules, has emerged as a key tool in the discovery of peptide-based drugs. Phage display technology involves the use of bacteriophages to express peptide libraries, which are then screened against a target of interest to identify peptides with desired properties. This approach has shown great promise in cancer diagnosis and treatment, with potential applications in targeting cancer cells and developing new therapies. In this comprehensive review, we provide an overview of the basic biology of phage vectors, the principles of phage library construction, and various methods for binding affinity assessment. We then describe the applications of phage display in pancreatic cancer therapy, targeted drug delivery, and early detection. Despite its promising potential, there are still challenges to be addressed, such as optimizing the selection process and improving the pharmacokinetic properties of phage-based drugs. Nevertheless, phage display represents a promising approach for the development of novel targeted therapies in pancreatic cancer and other tumors.

Targeting Ras with protein engineering

Ras proteins are small GTPases that regulate cell growth and division. Mutations in Ras genes are associated with many types of cancer, making them attractive targets for cancer therapy. Despite extensive efforts, targeting Ras proteins with small molecules has been extremely challenging due to Ras's mostly flat surface and lack of small molecule-binding cavities. These challenges were recently overcome by the development of the first covalent small-molecule anti-Ras drug, sotorasib, highlighting the efficacy of Ras inhibition as a therapeutic strategy. However, this drug exclusively inhibits the Ras G12C mutant, which is not a prevalent mutation in most cancer types. Unlike the G12C variant, other Ras oncogenic mutants lack reactive cysteines, rendering them unsuitable for targeting via the same strategy. Protein engineering has emerged as a promising method to target Ras, as engineered proteins have the ability to recognize various surfaces with high affinity and specificity. Over the past few years, scientists have engineered antibodies, natural Ras effectors, and novel binding domains to bind to Ras and counteract its carcinogenic activities via a variety of strategies. These include inhibiting Ras-effector interactions, disrupting Ras dimerization, interrupting Ras nucleotide exchange, stimulating Ras interaction with tumor suppressor genes, and promoting Ras degradation. In parallel, significant advancements have been made in intracellular protein delivery, enabling the delivery of the engineered anti-Ras agents into the cellular cytoplasm. These advances offer a promising path for targeting Ras proteins and other challenging drug targets, opening up new opportunities for drug discovery and development.

Phage Display Screening as a Rational Approach to Design Additives for Selective Crystallization Control in Construction Systems

The design of additives showing strong and selective interactions with certain target surfaces is key to crystallization control in applied reactive multicomponent systems. While suitable chemical motifs can be found through semi-empirical trial-and-error procedures, bioinspired selection techniques offer a more rationally driven approach and explore a much larger space of possible combinations in a single assay. Here, phage display screening is used to characterize the surfaces of crystalline gypsum, a mineral of broad relevance for construction applications. Based on next-generation sequencing of phages enriched during the screening process, a triplet of amino acids, DYH, is identified as the main driver for adsorption on the mineral substrate. Furthermore, oligopeptides containing this motif prove to exert their influence in a strictly selective manner during the hydration of cement, where the sulfate reaction (initial setting) is strongly retarded while the silicate reaction (final hardening) remains unaffected. In the final step, these desired additive characteristics are successfully translated from the level of peptides to that of scalable synthetic copolymers. The approach described in this work demonstrates how modern biotechnological methods can be leveraged for the systematic development of efficient crystallization additives for materials science.

Insight into the Binding Mechanisms of Quartz-Selective Peptides: Toward Greener Flotation Processes

Mining practices, chiefly froth flotation, are being critically reassessed to replace their use of biohazardous chemical reagents in favor of biofriendly alternatives as a path toward green processes. In this regard, this study aimed at evaluating the interactions of peptides, as potential floatation collectors, with quartz using phage display and molecular dynamics (MD) simulations. Quartz-selective peptide sequences were initially identified by phage display at pH = 9 and further modeled by a robust simulation scheme combining classical MD, replica exchange MD, and steered MD calculations. Our residue-specific analyses of the peptides revealed that positively charged arginine and lysine residues were favorably attracted by the quartz surface at basic pH. The negatively charged residues at pH 9 (i.e., aspartic acid and glutamic acid) further showed affinity toward the quartz surface through electrostatic interactions with the positively charged surface-bound Na⁺ ions. The best-binding heptapeptide combinations, however, contained both positively and negatively charged residues in their composition. The flexibility of peptide chains was also shown to directly affect the adsorption behavior of the peptide. While attractive intrapeptide interactions were dominated by a weak peptide-quartz binding, the repulsive self-interactions in the peptides improved the binding propensity to the quartz surface. Our results showed that MD simulations are fully capable of revealing mechanistic details of peptide adsorption to inorganic surfaces and are an invaluable tool to accelerate the rational design of peptide sequences for mineral processing applications.

Depth of Sequencing Plays a Determining Role in the Characterization of Phage Display Peptide Libraries by NGS

Next-generation sequencing (NGS) has raised a growing interest in phage display research. Sequencing depth is a pivotal parameter for using NGS. In the current study, we made a side-by-side comparison of two NGS platforms with different sequencing depths, denoted as lower-throughput (LTP) and higher-throughput (HTP). The capacity of these platforms for characterization of the composition, quality, and diversity of the unselected Ph.D.TM-12 Phage Display Peptide Library was investigated. Our results indicated that HTP sequencing detects a considerably higher number of unique sequences compared to the LTP platform, thus covering a broader diversity of the library. We found a larger percentage of singletons, a smaller percentage of repeated sequences, and a greater percentage of distinct sequences in the LTP datasets. These parameters suggest a higher library quality, resulting in potentially misleading information when using LTP sequencing for such assessment. Our observations showed that HTP reveals a broader distribution of peptide frequencies, thus revealing increased heterogeneity of the library by the HTP approach and offering a comparatively higher capacity for distinguishing peptides from each other. Our analyses suggested that LTP and HTP datasets show discrepancies in their peptide composition and position-specific distribution of amino acids within the library. Taken together, these findings lead us to the conclusion that a higher sequencing depth can yield more in-depth insights into the composition of the library and provide a more complete picture of the quality and diversity of phage display peptide libraries.

Streamlined Data Analysis Pipeline for Deep Sequence-Coupled Biopanning Identification of Pathogen-Specific Antibody Responses in Serum

Deep sequence-coupled biopanning (DSCB) is a powerful tool that couples affinity selection of a bacteriophage MS2 virus-like particle peptide display platform with deep sequencing. While this approach has been used successfully to investigate pathogen-specific antibody responses in human sera, data analysis is time-consuming and complicated. Here, we describe a streamlined data analysis method for DSCB using MATLAB, expanding the potential for this approach to be deployed rapidly and consistently.

Next-generation sequencing of a combinatorial peptide phage library screened against ubiquitin identifies peptide aptamers that can inhibit the in vitro ubiquitin transfer cascade

Defining dynamic protein-protein interactions in the ubiquitin conjugation reaction is a challenging research area. Generating peptide aptamers that target components such as ubiquitin itself, E1, E2, or E3 could provide tools to dissect novel features of the enzymatic cascade. Next-generation deep sequencing platforms were used to identify peptide sequences isolated from phage-peptide libraries screened against Ubiquitin and its ortholog NEDD8. In over three rounds of selection under differing wash criteria, over 13,000 peptides were acquired targeting ubiquitin, while over 10,000 peptides were selected against NEDD8. The overlap in peptides against these two proteins was less than 5% suggesting a high degree in specificity of Ubiquitin or NEDD8 toward linear peptide motifs. Two of these ubiquitin-binding peptides were identified that inhibit both E3 ubiquitin ligases MDM2 and CHIP. NMR analysis highlighted distinct modes of binding of the two different peptide aptamers. These data highlight the utility of using next-generation sequencing of combinatorial phage-peptide libraries to isolate peptide aptamers toward a protein target that can be used as a chemical tool in a complex multi-enzyme reaction.

Pattern enrichment analysis for phage selection of stapled peptide ligands

Phage display is the most widely used technique to discover de novo peptides that bind to target proteins. However, it is associated with some challenges such as compositional bias. In this study, to overcome these difficulties, we devised a 'pattern enrichment analysis.' In this method, two samples (one obtained by affinity selection, the other simply amplified without selection) are prepared, and the two sequence datasets read on next-generation sequencer are compared to find the three-residue pattern most enriched in the selected sample. This allows us to compare two sequence datasets with high coverage and facilitates the identification of peptide sequences and the key residues for binding. We also demonstrated that this approach in the combination with structured peptide libraries allowed spatial mapping of the enriched sequence patterns. Here, we prepared a phage library displaying chemically stapled helical peptides with the X1C2X3X4X5X6X7X8C9X10 sequence, where X is any amino acid. To validate our method, we performed screening against the HDM2 protein. The results showed that the hydrophobic residues (Phe, Tyr, Trp and Leu) that are key to interactions with HDM2 were clearly identified by the pattern enrichment analysis. We also performed selection targeting the SARS-CoV-2 spike RBD in the same manner. The results showed that similar patterns were enriched among the hit peptides that inhibited the protein-protein interaction.

Analysis of Compositional Bias in a Commercial Phage Display Peptide Library by Next-Generation Sequencing

The principal presumption of phage display biopanning is that the naïve library contains an unbiased repertoire of peptides, and thus, the enriched variants derive from the affinity selection of an entirely random peptide pool. In the current study, we utilized deep sequencing to characterize the widely used Ph.DTM-12 phage display peptide library (New England Biolabs). The next-generation sequencing (NGS) data indicated the presence of stop codons and a high abundance of wild-type clones in the naïve library, which collectively result in a reduced effective size of the library. The analysis of the DNA sequence logo and global and position-specific frequency of amino acids demonstrated significant bias in the nucleotide and amino acid composition of the library inserts. Principal component analysis (PCA) uncovered the existence of four distinct clusters in the naïve library and the investigation of peptide frequency distribution revealed a broad range of unequal abundances for peptides. Taken together, our data provide strong evidence for the notion that the naïve library represents substantial departures from randomness at the nucleotide, amino acid, and peptide levels, though not undergoing any selective pressure for target binding. This non-uniform sequence representation arises from both the M13 phage biology and technical errors of the library construction. Our findings highlight the paramount importance of the qualitative assessment of the naïve phage display libraries prior to biopanning.

Restriction of the Global IgM Repertoire in Antiphospholipid Syndrome

The typical anti-phospholipid antibodies (APLA) in the anti-phospholipid syndrome (APS) are reactive with the phospholipid-binding protein β2GPI as well as a growing list of other protein targets. The relation of APLA to natural antibodies and the fuzzy set of autoantigens involved provoked us to study the changes in the IgM repertoire in APS. To this end, peptides selected by serum IgM from a 7-residue linear peptide phage display library (PDL) were deep sequenced. The analysis was aided by a novel formal representation of the Igome (the mimotope set reflecting the IgM specificities) in the form of a sequence graph. The study involved women with APLA and habitual abortions (n=24) compared to age-matched clinically healthy pregnant women (n=20). Their pooled Igomes (297 028 mimotope sequences) were compared also to the global public repertoire Igome of pooled donor plasma IgM (n=2 796 484) and a set of 7-mer sequences found in the J regions of human immunoglobulins (n=4 433 252). The pooled Igome was represented as a graph connecting the sequences as similar as the mimotopes of the same monoclonal antibody. The criterion was based on previously published data. In the resulting graph, identifiable clusters of vertices were considered related to the footprints of overlapping antibody cross-reactivities. A subgraph based on the clusters with a significant differential expression of APS patients' mimotopes contained predominantly specificities underrepresented in APS. The differentially expressed IgM footprints showed also an increased cross-reactivity with immunoglobulin J regions. The specificities underexpressed in APS had a higher correlation with public specificities than those overexpressed. The APS associated specificities were strongly related also to the human peptidome with 1 072 mimotope sequences found in 7 519 human proteins. These regions were characterized by low complexity. Thus, the IgM repertoire of the APS patients was found to be characterized by a significant reduction of certain public specificities found in the healthy controls with targets representing low complexity linear self-epitopes homologous to human antibody J regions.

Affinity Selection from Synthetic Peptide Libraries Enabled by De Novo MS/MS Sequencing

Recently, de novo MS/MS peptide sequencing has enabled the application of affinity selections to synthetic peptide mixtures that approach the diversity of phage libraries (> 108 random peptides). In conjunction with ‘split-mix’ solid phase synthesis to access equimolar peptide mixtures, this approach provides a straightforward means to examine synthetic peptide libraries of considerably higher diversity than has been feasible historically. Here, we offer a critical perspective on this work, report emerging data, and highlight opportunities for further methods refinement. With continued development, ‘affinity selection–mass spectrometry’ may become a complimentary approach to phage display, in vitro selection, and DNA-encoded libraries for the discovery of synthetic ligands that modulate protein function.

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.

The development of a high-affinity conformation-sensitive antibody mimetic using a biocompatible copolymer carrier (iBody)

Peptide display methods are a powerful tool for discovering new ligands of pharmacologically relevant targets. However, the selected ligands often suffer from low affinity. Using phage display, we identified a new bicyclic peptide binder of prostate-specific membrane antigen (PSMA), a metalloprotease frequently overexpressed in prostate cancer. We show that linking multiple copies of a selected low-affinity peptide to a biocompatible water-soluble N-(2-hydroxypropyl)methacrylamide copolymer carrier (iBody) improved binding of the conjugate by several orders of magnitude. Furthermore, using ELISA, enzyme kinetics, confocal microscopy, and other approaches, we demonstrate that the resulting iBody can distinguish between different conformations of the target protein. The possibility to develop stable, fully synthetic, conformation-selective antibody mimetics has potential applications for molecular recognition, diagnosis and treatment of many pathologies. This strategy could significantly contribute to more effective drug discovery and design.

Inhibition of Cancer Cell Adhesion, Migration and Proliferation by a Bispecific Antibody that Targets two Distinct Epitopes on αv Integrins

Members of the αv family of integrins regulate activation of transforming growth factor beta (TGFβ) and are directly involved in pro-tumorigenic phenotypes. Thus, αv integrins may be therapeutic targets for fibrosis and cancer, yet the isolation of selective inhibitors is currently a challenge. We generated synthetic antibodies selective for αv integrins by phage display selections on cell lines that displayed integrin heterodimers. We identified antibodies that targeted two distinct epitopes on cell-surface αv integrins and partially inhibited cell adhesion mediated by interactions between integrins and the latency-associated peptide, part of the pro-form of TGFβ. Using the isolated antibody paratope sequences we engineered a bispecific antibody capable of binding to both epitopes simultaneously; this antibody potently and completely inhibited cell adhesion mediated by integrins αvβ1, αvβ3 and αvβ5. In addition, the bispecific antibody inhibited proliferation and migration of lung carcinoma lines, where the highest and lowest potencies observed correlated with integrin-αv cell surface expression levels. Taken together, our results demonstrate that phage display selections with live cells can yield high quality anti-integrin antibodies, which we used as biparatopic building blocks to construct a bispecific antibody that strongly inhibited integrin function and may be a therapeutic candidate for cancer and fibrosis.

Motifier: An IgOme Profiler Based on Peptide Motifs Using Machine Learning

Antibodies provide a comprehensive record of the encounters with threats and insults to the immune system. The ability to examine the repertoire of antibodies in serum and discover those that best represent "discriminating features" characteristic of various clinical situations, is potentially very useful. Recently, phage display technologies combined with Next-Generation Sequencing (NGS) produced a powerful experimental methodology, coined "Deep-Panning", in which the spectrum of serum antibodies is probed. In order to extract meaningful biological insights from the tens of millions of affinity-selected peptides generated by Deep-Panning, advanced bioinformatics algorithms are a must. In this study, we describe Motifier, a computational pipeline comprised of a set of algorithms that systematically generates discriminatory peptide motifs based on the affinity-selected peptides identified by Deep-Panning. These motifs are shown to effectively characterize antibody binding activities and through the implementation of machine-learning protocols are shown to accurately classify complex antibody mixtures representing various biological conditions.

High-Throughput Sequencing of Phage Display Libraries Reveals Parasitic Enrichment of Indel Mutants Caused by Amplification Bias

The combination of phage display technology with high-throughput sequencing enables in-depth analysis of library diversity and selection-driven dynamics. We applied short-read sequencing of the mutagenized region on focused display libraries of two homologous nucleic acid modification eraser proteins-AlkB and FTO-biopanned against methylated DNA. This revealed enriched genotypes with small indels and concomitant doubtful amino acid motifs within the FTO library. Nanopore sequencing of the entire display vector showed additional enrichment of large deletions overlooked by region-specific sequencing, and further impacted the interpretation of the obtained amino acid motifs. We could attribute enrichment of these corrupted clones to amplification bias due to arduous FTO display slowing down host cell growth as well as phage production. This amplification bias appeared to be stronger than affinity-based target selection. Recommendations are provided for proper sequence analysis of phage display data, which can improve motive discovery in libraries of proteins that are difficult to display.

Bacteriophages: from isolation to application

Bacteriophages are considered as a potential alternative to fight pathogenic bacteria during the antibiotic resistance era. With their high specificity, they are being widely used in various applications: medicine, food industry, agriculture, animal farms, biotechnology, diagnosis, etc. Many techniques have been designed by different researchers for phage isolation, purification, and amplification, each of which has strengths and weaknesses. However, all aim at having a reasonably pure phage sample that can be further characterized. Phages can be characterized based on their physiological, morphological or inactivation tests. Microscopy, in particular, has opened a wide gate not only for visualizing phage morphological structure, but also for monitoring biochemistry and behavior. Meanwhile, computational analysis of phage genomes provides more details about phage history, lifestyle, and potential for toxigenic or lysogenic conversion, which translate to safety in biocontrol and phage therapy applications. This review summarizes phage application pipelines at different levels and addresses specific restrictions and knowledge gaps in the field. Recently developed computational approaches, which are used in phage genome analysis, are critically assessed. We hope that this assessment provides researchers with useful insights for selection of suitable approaches for Phage-related research aims and applications.

In vivo phage display: identification of organ-specific peptides using deep sequencing and differential profiling across tissues

In vivo phage display is widely used for identification of organ- or disease-specific homing peptides. However, the current in vivo phage biopanning approaches fail to assess biodistribution of specific peptide phages across tissues during the screen, thus necessitating laborious and time-consuming post-screening validation studies on individual peptide phages. Here, we adopted bioinformatics tools used for RNA sequencing for analysis of high-throughput sequencing (HTS) data to estimate the representation of individual peptides during biopanning in vivo. The data from in vivo phage screen were analyzed using differential binding-relative representation of each peptide in the target organ versus in a panel of control organs. Application of this approach in a model study using low-diversity peptide T7 phage library with spiked-in brain homing phage demonstrated brain-specific differential binding of brain homing phage and resulted in identification of novel lung- and brain-specific homing peptides. Our study provides a broadly applicable approach to streamline in vivo peptide phage biopanning and to increase its reproducibility and success rate.

Combining phage display with SMRTbell next-generation sequencing for the rapid discovery of functional scFv fragments

Phage display technology in combination with next-generation sequencing (NGS) currently is a state-of-the-art method for the enrichment and isolation of monoclonal antibodies from diverse libraries. However, the current NGS methods employed for sequencing phage display libraries are limited by the short contiguous read lengths associated with second-generation sequencing platforms. Consequently, the identification of antibody sequences has conventionally been restricted to individual antibody domains or to the analysis of single domain binding moieties such as camelid VHH or cartilaginous fish IgNAR antibodies. In this study, we report the application of third-generation sequencing to address this limitation. We used single molecule real time (SMRT) sequencing coupled with hairpin adaptor loop ligation to facilitate the accurate interrogation of full-length single-chain Fv (scFv) libraries. Our method facilitated the rapid isolation and testing of scFv antibodies enriched from phage display libraries within days following panning. Two libraries against CD160 and CD123 were panned and monitored by NGS. Analysis of NGS antibody data sets led to the isolation of several functional scFv antibodies that were not identified by conventional panning and screening strategies. Our approach, which combines phage display selection of immune libraries with the full-length interrogation of scFv fragments, is an easy method to discover functional antibodies, with a range of affinities and biophysical characteristics.

Application of Next Generation Sequencing (NGS) in Phage Displayed Peptide Selection to Support the Identification of Arsenic-Binding Motifs

Next generation sequencing (NGS) in combination with phage surface display (PSD) are powerful tools in the newly equipped molecular biology toolbox for the identification of specific target binding biomolecules. Application of PSD led to the discovery of manifold ligands in clinical and material research. However, limitations of traditional phage display hinder the identification process. Growth-based library biases and target-unrelated peptides often result in the dominance of parasitic sequences and the collapse of library diversity. This study describes the effective enrichment of specific peptide motifs potentially binding to arsenic as proof-of-concept using the combination of PSD and NGS. Arsenic is an environmental toxin, which is applied in various semiconductors as gallium arsenide and selective recovery of this element is crucial for recycling and remediation. The development of biomolecules as specific arsenic-binding sorbents is a new approach for its recovery. Usage of NGS for all biopanning fractions allowed for evaluation of motif enrichment, in-depth insight into the selection process and the discrimination of biopanning artefacts, e.g., the amplification-induced library-wide reduction in hydrophobic amino acid proportion. Application of bioinformatics tools led to the identification of an SxHS and a carboxy-terminal QxQ motif, which are potentially involved in the binding of arsenic. To the best of our knowledge, this is the first report of PSD combined with NGS of all relevant biopanning fractions.

Phage Display to Augment Biomaterial Function

Biomaterial design relies on controlling interactions between materials and their biological environments to modulate the functions of proteins, cells, and tissues. Phage display is a powerful tool that can be used to discover peptide sequences with high affinity for a desired target. When incorporated into biomaterial design, peptides identified via phage display can functionalize material surfaces to control the interaction between a biomaterial and its local microenvironment. A targeting peptide has high specificity for a given target, allowing for homing a specific protein, cell, tissue, or other material to a biomaterial. A functional peptide has an affinity for a given protein, cell, or tissue, but also modulates its target's activity upon binding. Biomaterials can be further enhanced using a combination of targeting and/or functional peptides to create dual-functional peptides for bridging two targets or modulating the behavior of a specific protein or cell. This review will examine current and future applications of phage display for the augmentation of biomaterials.

Mapping Protein-Protein Interaction Interface Peptides with Jun-Fos Assisted Phage Display and Deep Sequencing

Protein-protein interactions govern many cellular processes, and identifying binding interaction sites on proteins can facilitate the discovery of inhibitors to block such interactions. Here we identify peptides from a randomly fragmented plasmid encoding the β-lactamase inhibitory protein (BLIP) and the Lac repressor (LacI) that represent regions of protein-protein interactions. We utilized a Jun-Fos-assisted phage display system that has previously been used to screen cDNA and genomic libraries to identify antibody antigens. Affinity selection with polyclonal antibodies against LacI or BLIP resulted in the rapid enrichment of in-frame peptides from various regions of the proteins. Further, affinity selection with β-lactamase enriched peptides that encompass regions of BLIP previously shown to contribute strongly to the binding energy of the BLIP/β-lactamase interaction, i.e., hotspot residues. Further, one of the regions enriched by affinity selection encompassed a disulfide-constrained region of BLIP that forms part of the BLIP interaction surface in the native complex that we show also binds to β-lactamase as a disulfide-constrained macrocycle peptide with a K_D of ∼1 μM. Fragmented open reading frame (ORF) libraries may efficiently identify such naturally constrained peptides at protein-protein interaction interfaces. With sufficiently deep coverage of ORFs by peptide-coding inserts, phage display and deep sequencing can provide detailed information on the domains or peptides that contribute to an interaction. Such information should enable the design of potentially therapeutic macrocycles or peptidomimetics that block the interaction.

Oncolytic Adenoviruses: Strategies for Improved Targeting and Specificity

Cancer is a major health problem. Most of the treatments exhibit systemic toxicity, as they are not targeted or specific to cancerous cells and tumors. Adenoviruses are very promising gene delivery vectors and have immense potential to deliver targeted therapy. Here, we review a wide range of strategies that have been tried, tested, and demonstrated to enhance the specificity of oncolytic viruses towards specific cancer cells. A combination of these strategies and other conventional therapies may be more effective than any of those strategies alone.

Development and Application of Computational Methods in Phage Display Technology

BACKGROUND

Phage display is a powerful and versatile technology for the identification of peptide ligands binding to multiple targets, which has been successfully employed in various fields, such as diagnostics and therapeutics, drug-delivery and material science. The integration of next generation sequencing technology with phage display makes this methodology more productive. With the widespread use of this technique and the fast accumulation of phage display data, databases for these data and computational methods have become an indispensable part in this community. This review aims to summarize and discuss recent progress in the development and application of computational methods in the field of phage display.

METHODS

We undertook a comprehensive search of bioinformatics resources and computational methods for phage display data via Google Scholar and PubMed. The methods and tools were further divided into different categories according to their uses.

RESULTS

We described seven special or relevant databases for phage display data, which provided an evidence-based source for phage display researchers to clean their biopanning results. These databases can identify and report possible target-unrelated peptides (TUPs), thereby excluding false-positive data from peptides obtained from phage display screening experiments. More than 20 computational methods for analyzing biopanning data were also reviewed. These methods were classified into computational methods for reporting TUPs, for predicting epitopes and for analyzing next generation phage display data.

CONCLUSION

The current bioinformatics archives, methods and tools reviewed here have benefitted the biopanning community. To develop better or new computational tools, some promising directions are also discussed.

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.

The next generation of biopanning: next gen sequencing improves analysis of bacterial display libraries

BACKGROUND

Bacterial surface display libraries are a popular tool for novel ligand discovery due to their ease of manipulation and rapid growth rates. These libraries typically express a scaffold protein embedded within the outer membrane with a short, surface-exposed peptide that is either terminal or is incorporated into an outer loop, and can therefore interact with and bind to substrates of interest.

RESULTS

In this study, we employed a novel bacterial peptide display library which incorporates short 15-mer peptides on the surface of E. coli, co-expressed with the inducible red fluorescent protein DsRed in the cytosol, to investigate population diversity over two rounds of biopanning. The naive library was used in panning trials to select for binding affinity against 3D printing plastic coupons made from polylactic acid (PLA). Resulting libraries were then deep-sequenced using next generation sequencing (NGS) to investigate selection and diversity.

CONCLUSIONS

We demonstrated enrichment for PLA binding versus a sapphire control surface, analyzed population composition, and compared sorting rounds using a binding assay and fluorescence microscopy. The capability to produce and describe display libraries through NGS across rounds of selection allows a deeper understanding of population dynamics that can be better directed towards peptide discovery.

Diagnostic Profiling of the Human Public IgM Repertoire With Scalable Mimotope Libraries

Specific antibody reactivities are routinely used as biomarkers, but the antibody repertoire reactivity (igome) profiles are still neglected. Here, we propose rationally designed peptide arrays as efficient probes for these system level biomarkers. Most IgM antibodies are characterized by few somatic mutations, polyspecificity, and physiological autoreactivity with housekeeping function. Previously, probing this repertoire with a set of immunodominant self-proteins provided a coarse analysis of the respective repertoire profiles. In contrast, here, we describe the generation of a peptide mimotope library that reflects the common IgM repertoire of 10,000 healthy donors. In addition, an appropriately sized subset of this quasi-complete mimotope library was further designed as a potential diagnostic tool. A 7-mer random peptide phage display library was panned on pooled human IgM. Next-generation sequencing of the selected phage yielded 224,087 sequences, which clustered in 790 sequence clusters. A set of 594 mimotopes, representative of the most significant sequence clusters, was shown to probe symmetrically the space of IgM reactivities in patients' sera. This set of mimotopes can be easily scaled including a greater proportion of the mimotope library. The trade-off between the array size and the resolution can be explored while preserving the symmetric sampling of the mimotope sequence and reactivity spaces. BLAST search of the non-redundant protein database with the mimotopes sequences yielded significantly more immunoglobulin J region hits than random peptides, indicating a considerable idiotypic connectivity of the targeted igome. The proof of principle predictors for random diagnoses was represented by profiles of mimotopes. The number of potential reactivity profiles that can be extracted from this library is estimated at more than 10⁷⁰. Thus, a quasi-complete IgM mimotope library and a scalable representative subset thereof are found to address very efficiently the dynamic diversity of the human public IgM repertoire, providing informationally dense and structurally interpretable IgM reactivity profiles.

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.

Genetically-encoded fragment-based discovery (GE-FBD) of glycopeptide ligands with differential selectivity for antibodies related to mycobacterial infections

Accurate identification of tuberculosis (TB), caused by Mycobacterium tuberculosis, is important for global disease management. Point-of-care serological tests may improve TB diagnosis; however, specificities of available serodiagnostics are sub-optimal. We employed genetically encoded fragment-based discovery (GE-FBD) to select ligands for antibodies directed against the mycobacterial cell wall component lipoarabinomannan (LAM), a potent antigen. GE-FBD employed a phage displayed library of 10⁸ heptapeptides, chemically modified with an arabinofuranosyl hexasaccharide fragment of LAM (Ara₆), and the anti-LAM antibody CS-35 as a bait. The selection gave rise to glycopeptides with an enhanced affinity and selectivity for CS-35 but not for 906.4321 antibody, both of which bind to Ara₆ with a comparable affinity. Multivalent assays incorporating the discovered ligands Ara₆-ANSSFAP, Ara₆-DAHATLR and Ara₆-TTYVVNP exhibited up to 19-fold discrimination between CS-35 and 906.4321. The use of the Ara₆ antigen alone failed to distinguish these antibodies. Thus, GE-FBD gives rise to ligands that differentiate monoclonal antibodies with enhanced specificity. This technology could facilitate the development of effective point-of-care serological tests for mycobacterial and other infections.

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.

Screening and Identification of PLK1-Polo Box Binding Peptides by High-Throughput Sequencing of Phage-Selected Libraries

BACKGROUND

Human proteome contains a plethora of short linear peptide motifs that is crucial for signaling and other cellular processes. These motifs are difficult to identify due to lack of systematic approach for their detection.

OBJECTIVES

Here we demonstrate the use of peptide phage display in combination with high throughput next generation sequencing to identify enriched peptide sequences through biopanning process against polo box domain (PBD) of mitotic polo like kinase 1 (Plk1).

METHODS

Purified recombinant Plk1 and two unrelated controls namely B-lymphocyte antigen (CD20) and fluorescent protein (mCherry) were subjected to peptide phage display analysis. Bacterially-propagated phage DNA was amplified by PCR using triplet bar coded primers to tag the pool from each amplicon.

RESULTS

Proteomic peptide phage display along with next generation sequencing and Bioinformatics analysis demonstrated several known and putative novel interactions which were potentially related to Plk1-PBD. With our strategy, we were able to identify and characterize several Plk1-PBD binding peptides, as well as define more precisely, consensus sequences.

CONCLUSION

We believe that this information could provide valuable tools for exploring novel interaction involved in Plk1 signaling as well as to choose peptides for Plk1 specific drug development.

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.

Highly multiplexed and quantitative cell-surface protein profiling using genetically barcoded antibodies

Next-generation sequencing (NGS) has allowed the comprehensive study of the genome and transcriptome. However, a similarly broad, highly multiplexed, and inexpensive method for proteomics using NGS remains elusive. Here, we describe a phage display-based method using preselected antibodies that are genetically encoded and capable of simultaneous profiling of hundreds of cell-surface targets on cells in culture or singly at low cost and without the need for chemical conjugation to purified antibodies. We use the method to identify cell-surface proteins that change in cancer cells, some of which are coordinately regulated and could lead to new biomarkers and cancer targets.

Human cells express thousands of different surface proteins that can be used for cell classification, or to distinguish healthy and disease conditions. A method capable of profiling a substantial fraction of the surface proteome simultaneously and inexpensively would enable more accurate and complete classification of cell states. We present a highly multiplexed and quantitative surface proteomic method using genetically barcoded antibodies called phage-antibody next-generation sequencing (PhaNGS). Using 144 preselected antibodies displayed on filamentous phage (Fab-phage) against 44 receptor targets, we assess changes in B cell surface proteins after the development of drug resistance in a patient with acute lymphoblastic leukemia (ALL) and in adaptation to oncogene expression in a Myc-inducible Burkitt lymphoma model. We further show PhaNGS can be applied at the single-cell level. Our results reveal that a common set of proteins including FLT3, NCR3LG1, and ROR1 dominate the response to similar oncogenic perturbations in B cells. Linking high-affinity, selective, genetically encoded binders to NGS enables direct and highly multiplexed protein detection, comparable to RNA-sequencing for mRNA. PhaNGS has the potential to profile a substantial fraction of the surface proteome simultaneously and inexpensively to enable more accurate and complete classification of cell states.

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.

Biopanning data bank 2018: hugging next generation phage display

Database URL

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

Phage Selection of Cyclic Peptides for Application in Research and Drug Development

Cyclic peptides can bind to protein targets with high affinities and selectivities, which makes them an attractive modality for the development of research reagents and therapeutics. Additional properties, including low inherent toxicity, efficient chemical synthesis, and facile modification with labels or immobilization reagents, increase their attractiveness. Cyclic peptide ligands against a wide range of protein targets have been isolated from natural sources such as bacteria, fungi, plants, and animals. Many of them are currently used as research tools, and several have found application as therapeutics, such as the peptide hormones oxytocin and vasopressin and the antibiotics vancomycin and daptomycin, proving the utility of cyclic peptides in research and medicine. With the advent of phage display and other in vitro evolution techniques, it has become possible to generate cyclic peptide binders to diverse protein targets for which no natural peptides have been discovered. A highly robust and widely applied approach is based on the cyclization of peptides displayed on phage via a disulfide bridge. Disulfide-cyclized peptide ligands to more than a hundred different proteins have been reported in the literature. Technology advances achieved over the last three decades, including methods for generating larger phage display libraries, improved phage panning protocols, new cyclic peptide formats, and high-throughput sequencing, have enabled the generation of cyclic peptides with ever better binding affinities to more challenging targets. A relatively new cyclic peptide format developed using phage display involves bicyclic peptides. These molecules consist of two macrocyclic peptide rings cyclized through a chemical linker. Compared to monocyclic peptides of comparable molecular mass, bicyclic peptides are more constrained in their conformation. As a result, they can bind to their targets with a higher affinity and are more resistant to proteolytic degradation. Phage-encoded bicyclic peptides are generated by chemically cyclizing random peptide libraries on phage. Binders are identified by conventional phage panning and DNA sequencing. Next-generation sequencing and new sequence alignment tools have enabled the rapid identification of bicyclic peptides. Bicyclic peptide ligands were developed against a range of diverse target classes including enzymes, receptors, and cytokines. Most ligands bind with nanomolar affinities, with some reaching the picomolar range. To date, several bicyclic peptides have been positively evaluated in preclinical studies, and the first clinical tests are in sight. While bicyclic peptide phage display was developed with therapeutic applications in mind, these peptides are increasingly used as research tools for target evaluation or as basic research probes as well. Given the efficient development method, the ease of synthesis and handling, and the favorable binding and biophysical properties, bicyclic peptides are being developed against more and more targets, ever increasing their potential applications in research and medicine.

Selection platforms for directed evolution in synthetic biology

Life on Earth is incredibly diverse. Yet, underneath that diversity, there are a number of constants and highly conserved processes: all life is based on DNA and RNA; the genetic code is universal; biology is limited to a small subset of potential chemistries. A vast amount of knowledge has been accrued through describing and characterizing enzymes, biological processes and organisms. Nevertheless, much remains to be understood about the natural world. One of the goals in Synthetic Biology is to recapitulate biological complexity from simple systems made from biological molecules-gaining a deeper understanding of life in the process. Directed evolution is a powerful tool in Synthetic Biology, able to bypass gaps in knowledge and capable of engineering even the most highly conserved biological processes. It encompasses a range of methodologies to create variation in a population and to select individual variants with the desired function-be it a ligand, enzyme, pathway or even whole organisms. Here, we present some of the basic frameworks that underpin all evolution platforms and review some of the recent contributions from directed evolution to synthetic biology, in particular methods that have been used to engineer the Central Dogma and the genetic code.