Next-generation sequencing of phage-displayed peptide libraries

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.

Design-rules for stapled peptides with in vivo activity and their application to Mdm2/X antagonists

Although stapled α-helical peptides can address challenging targets, their advancement is impeded by poor understandings for making them cell permeable while avoiding off-target toxicities. By synthesizing >350 molecules, we present workflows for identifying stapled peptides against Mdm2(X) with in vivo activity and no off-target effects. Key insights include a clear correlation between lipophilicity and permeability, removal of positive charge to avoid off-target toxicities, judicious anionic residue placement to enhance solubility/behavior, optimization of C-terminal length/helicity to enhance potency, and optimization of staple type/number to avoid polypharmacology. Workflow application gives peptides with >292x improved cell proliferation potencies and no off-target cell proliferation effects ( > 3800x on-target index). Application of these 'design rules' to a distinct Mdm2(X) peptide series improves ( > 150x) cellular potencies and removes off-target toxicities. The outlined workflow should facilitate therapeutic impacts, especially for those targets such as Mdm2(X) that have hydrophobic interfaces and are targetable with a helical motif.

Application of Deep Sequencing in Phage Display

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

CD47Binder: Identify CD47 Binding Peptides by Combining Next-Generation Phage Display Data and Multiple Peptide Descriptors

CD47/SIRPα pathway is a new breakthrough in the field of tumor immunity after PD-1/PD-L1. While current monoclonal antibody therapies targeting CD47/SIRPα have demonstrated some anti-tumor effectiveness, there are several inherent limitations associated with these formulations. In the paper, we developed a predictive model that combines next-generation phage display (NGPD) and traditional machine learning methods to distinguish CD47 binding peptides. First, we utilized NGPD biopanning technology to screen CD47 binding peptides. Second, ten traditional machine learning methods based on multiple peptide descriptors and three deep learning methods were used to build computational models for identifying CD47 binding peptides. Finally, we proposed an integrated model based on support vector machine. During the five-fold cross-validation, the integrated predictor demonstrated specificity, accuracy, and sensitivity of 0.755, 0.764, and 0.772, respectively. Furthermore, an online bioinformatics tool called CD47Binder has been developed for the integrated predictor. This tool is readily accessible on http://i.uestc.edu.cn/CD47Binder/cgi-bin/CD47Binder.pl .

Phage display uncovers a sequence motif that drives polypeptide binding to a conserved regulatory exosite of O-GlcNAc transferase

The modification of nucleocytoplasmic proteins by O-linked N-acetylglucosamine (O-GlcNAc) is an important regulator of cell physiology. O-GlcNAc is installed on over a thousand proteins by just one enzyme, O-GlcNAc transferase (OGT). How OGT is regulated is therefore a topic of interest. To gain insight into these questions, we used OGT to perform phage display selection from an unbiased library of ~109 peptides of 15 amino acids in length. Following rounds of selection and deep mutational panning, we identified a high-fidelity peptide consensus sequence, [Y/F]-x-P-x-Y-x-[I/M/F], that drives peptide binding to OGT. Peptides containing this sequence bind to OGT in the high nanomolar to low micromolar range and inhibit OGT in a noncompetitive manner with low micromolar potencies. X-ray structural analyses of OGT in complex with a peptide containing this motif surprisingly revealed binding to an exosite proximal to the active site of OGT. This structure defines the detailed molecular basis driving peptide binding and explains the need for specific residues within the sequence motif. Analysis of the human proteome revealed this motif within 52 nuclear and cytoplasmic proteins. Collectively, these data suggest a mode of regulation of OGT by which polypeptides can bind to this exosite to cause allosteric inhibition of OGT through steric occlusion of its active site. We expect that these insights will drive improved understanding of the regulation of OGT within cells and enable the development of new chemical tools to exert fine control over OGT activity.

Identification and validation of Sertoli cell homing peptides as molecular steering for testis targeted drug delivery

The testicle, an organ privileged with immunity because of Blood-Testis Barrier (BTB), poses a major impediment to developing and delivering drugs to the testes. These problems can be prevented by targeting testicular cells using specific ligands, such as homing peptides. This is the first study to demonstrate the successful selection of Sertoli cell homing peptides using a phage display peptide library. The identification of peptides is performed with Sanger sequencing and high-throughput NGS. The Sertoli cell and testis targeting potential of the SCHP1 and SCHP2 was confirmed using confocal microscopy and flow cytometry of the FITC-labelled peptides and in vivo bio-distribution of the corresponding Cy5.5-tagged peptides. Secondary structures were predicted in the setting of different polarity by circular dichroism. The results suggest that SCHP1 and SCHP2 can effectively target Sertoli cells. In vivo bio-distribution in mouse models indicated significantly higher uptake of SCHP1 and SCHP2 by testes compared with the heart, brain, and spleen. SCHP1 and SCHP2 can be adopted as molecular steering for targeted male contraceptive delivery, treatment of testicular cancer, and male infertility. Further development of the peptides into peptidomimetics may increase their stability, and information on the molecular targets of these peptides may reveal their therapeutic potential.

Combination of Experimental and Bioinformatic Approaches for Identification of Immunologically Relevant Protein-Peptide Interactions

Protein-peptide interactions are an essential player in cellular processes and, thus, of great interest as potential therapeutic agents. However, identifying the protein's interacting surface has been shown to be a challenging task. Here, we present a methodology for protein-peptide interaction identification, implementing phage panning, next-generation sequencing and bioinformatic analysis. One of the uses of this methodology is identification of allergen epitopes, especially suitable for globular inhaled and venom allergens, where their binding capability is determined by the allergen's conformation, meaning their interaction cannot be properly studied when denatured. A Ph.D. commercial system based on the M13 phage vector was used for the panning process. Utilization of various bioinformatic tools, such as PuLSE, SAROTUP, MEME, Hammock and Pepitope, allowed us to evaluate a large amount of obtained data. Using the described methodology, we identified three peptide clusters representing potential epitopes on the major wasp venom allergen Ves v 5.

PDL1Binder: Identifying programmed cell death ligand 1 binding peptides by incorporating next-generation phage display data and different peptide descriptors

Monoclonal antibody drugs targeting the PD-1/PD-L1 pathway have showed efficacy in the treatment of cancer patients, however, they have many intrinsic limitations and inevitable drawbacks. Peptide inhibitors as alternatives might compensate for the drawbacks of current PD-1/PD-L1 interaction blockers. Identifying PD-L1 binding peptides by random peptide library screening is a time-consuming and labor-intensive process. Machine learning-based computational models enable rapid discovery of peptide candidates targeting the PD-1/PD-L1 pathway. In this study, we first employed next-generation phage display (NGPD) biopanning to isolate PD-L1 binding peptides. Different peptide descriptors and feature selection methods as well as diverse machine learning methods were then incorporated to implement predictive models of PD-L1 binding. Finally, we proposed PDL1Binder, an ensemble computational model for efficiently obtaining PD-L1 binding peptides. Our results suggest that predictive models of PD-L1 binding can be learned from deep sequencing data and provide a new path to discover PD-L1 binding peptides. A web server was implemented for PDL1Binder, which is freely available at http://i.uestc.edu.cn/pdl1binder/cgi-bin/PDL1Binder.pl.

Therapeutic peptides: current applications and future directions

Peptide drug development has made great progress in the last decade thanks to new production, modification, and analytic technologies. Peptides have been produced and modified using both chemical and biological methods, together with novel design and delivery strategies, which have helped to overcome the inherent drawbacks of peptides and have allowed the continued advancement of this field. A wide variety of natural and modified peptides have been obtained and studied, covering multiple therapeutic areas. This review summarizes the efforts and achievements in peptide drug discovery, production, and modification, and their current applications. We also discuss the value and challenges associated with future developments in therapeutic peptides.

Ligand Selection for Affinity Chromatography Using Phage Display

Phage display coupled with in vitro affinity selection to mimic evolutionary principles has propelled the discovery of specific binding peptides and proteins for diverse applications, including affinity chromatography. By tailoring screening conditions, ligands with desired predefined properties, such as pH- or ion strength-responsive binding, can be identified from phage-displayed combinatorial peptide libraries. Initial hit peptides can be further optimized through directed evolution by focused mutagenesis and rescreening. Quantitative analysis of eluted binders with next-generation sequencing (NGS) assists in reducing enrichment bias and simplifies picking the most promising ligand candidate(s) through enrichment ranking. We describe, in detail, procedures of ligand selection for affinity chromatography using peptide phage display library screening, focused mutagenesis, and NGS. Furthermore, we outline the subsequent workflow for ligand characterization and affinity column construction.

Genetically Encoded Fragment-Based Discovery from Phage-Displayed Macrocyclic Libraries with Genetically Encoded Unnatural Pharmacophores

Genetically encoded macrocyclic peptide libraries with unnatural pharmacophores are valuable sources for the discovery of ligands for many targets of interest. Traditionally, generation of such libraries employs "early stage" incorporation of unnatural building blocks into the chemically or translationally produced macrocycles. Here, we describe a divergent late-stage approach to such libraries starting from readily available starting material: genetically encoded libraries of peptides. A diketone linchpin 1,5-dichloropentane-2,4-dione converts peptide libraries displayed on phage to 1,3-diketone bearing macrocyclic peptides (DKMP): shelf-stable precursors for Knorr pyrazole synthesis. Ligation of diverse hydrazine derivatives onto DKMP libraries displayed on phage that carries silent DNA-barcodes yields macrocyclic libraries in which the amino acid sequence and the pharmacophore are encoded by DNA. Selection of this library against carbonic anhydrase enriched macrocycles with benzenesulfonamide pharmacophore and nanomolar K_d. The methodology described in this manuscript can graft diverse pharmacophores into many existing genetically encoded phage libraries and significantly increase the value of such libraries in molecular discoveries.

Homing Peptides for Cancer Therapy

Tumor-homing peptides are widely used for improving tumor selectivity of anticancer drugs and imaging agents. The goal is to increase tumor uptake and reduce accumulation at nontarget sites. Here, we describe current approaches for tumor-homing peptide identification and validation, and provide comprehensive overview of classes of tumor-homing peptides undergoing preclinical and clinical development. We focus on unique mechanistic features and applications of a recently discovered class of tumor-homing peptides, tumor-penetrating C-end Rule (CendR) peptides, that can be used for tissue penetrative targeting of extravascular tumor tissue. Finally, we discuss unanswered questions and future directions in the field of development of peptide-guided smart drugs and imaging agents.

Peptides as surface coatings of nanoparticles that penetrate human cystic fibrosis sputum and uniformly distribute in vivo following pulmonary delivery

Therapeutic delivery of drug and gene delivery systems have to traverse multiple biological barriers to achieve efficacy. Mucosal administration, such as pulmonary delivery in cystic fibrosis (CF) disease, remains a significant challenge due to concentrated viscoelastic mucus, which prevents drugs and particles from penetrating the mucus barrier. To address this problem, we used combinatorial peptide-presenting phage libraries and next-generation sequencing (NGS) to identify hydrophilic, net-neutral charged peptide coatings that enable penetration through human CF mucus ex vivo with ~600-fold better penetration than control, improve uptake into lung epithelial cells compared to uncoated or PEGylated-nanoparticles, and exhibit enhanced uniform distribution and retention in the mouse lung airways. These peptide coatings address multiple delivery barriers and effectively serve as excellent alternatives to standard PEG surface chemistries to achieve mucus penetration and address some of the challenges encountered using these chemistries. This biomolecule-based strategy can address multiple delivery barriers and hold promise to advance efficacy of therapeutics for diseases like CF.

Peptides as surface coatings of nanoparticles that penetrate human cystic fibrosis sputum and uniformly distribute in vivo following pulmonary delivery

Therapeutic delivery of drug and gene delivery systems have to traverse multiple biological barriers to achieve efficacy. Mucosal administration, such as pulmonary delivery in cystic fibrosis (CF) disease, remains a significant challenge due to concentrated viscoelastic mucus, which prevents drugs and particles from penetrating the mucus barrier. To address this problem, we used combinatorial peptide-presenting phage libraries and next-generation sequencing (NGS) to identify hydrophilic, net-neutral charged peptide coatings that enable penetration through human CF mucus ex vivo with ~600-fold better penetration than control, improve uptake into lung epithelial cells compared to uncoated or PEGylated-nanoparticles, and exhibit enhanced uniform distribution and retention in the mouse lung airways. These peptide coatings address multiple delivery barriers and effectively serve as excellent alternatives to standard PEG surface chemistries to achieve mucus penetration and address some of the challenges encountered using these chemistries. This biomolecule-based strategy can address multiple delivery barriers and hold promise to advance efficacy of therapeutics for diseases like CF.

Comparison of motif-based and whole-unique-sequence-based analyses of phage display library datasets generated by biopanning of anti-Borrelia burgdorferi immune sera

Detection of protection-associated epitopes via reverse vaccinology is the first step for development of subunit vaccines against microbial pathogens. Mapping subunit vaccine targets requires high throughput methods, which would allow delineation of epitopes recognized by protective antibodies on a large scale. Phage displayed random peptide library coupled to Next Generation Sequencing (PDRPL/NGS) is the universal platform that enables high-yield identification of peptides that mimic epitopes (mimotopes). Despite being unsurpassed as a tool for discovery of polyclonal serum mimotopes, the PDRPL/NGS is far inferior as a quantitative method of immune response. Difficult-to-control fluctuations in amounts of antibody-bound phages after rounds of selection and amplification diminish the quantitative capacity of the PDRPL/NGS. In an attempt to improve the accuracy of the PDRPL/NGS method, we compared the discriminating capacity of two approaches for PDRPL/NGS data analysis. The whole-unique-sequence-based analysis (WUSA) involved generation of 7-mer peptide profiles and comparison of the numbers of sequencing reads for unique peptide sequences between serum samples. The motif-based analysis (MA) included identification of 4-mer consensus motifs unifying unique 7-mer sequences and comparison of motifs between serum samples. The motif comparison was based not on the numbers of sequencing reads, but on the numbers of distinct 7-mers constituting the motifs. Our PDRPL/NGS datasets generated from biopanning of protective and non-protective anti-Borrelia burgdorferi sera of New Zealand rabbits were used to contrast the two approaches. As a result, the principle component analyses (PCA) showed that the discriminating powers of the WUSA and MA were similar. In contrast, the unsupervised hierarchical clustering obtained via the MA classified the preimmune, non-protective, and protective sera better than the WUSA-based clustering. Also, a total number of discriminating motifs was higher than that of discriminating 7-mers. In sum, our results indicate that MA approach improves the accuracy and quantitative capacity of the PDRPL/NGS method.

Evolving a Peptide: Library Platforms and Diversification Strategies

Peptides are widely used in pharmaceutical industry as active pharmaceutical ingredients, versatile tools in drug discovery, and for drug delivery. They find themselves at the crossroads of small molecules and proteins, possessing favorable tissue penetration and the capability to engage into specific and high-affinity interactions with endogenous receptors. One of the commonly employed approaches in peptide discovery and design is to screen combinatorial libraries, comprising a myriad of peptide variants of either chemical or biological origin. In this review, we focus mainly on recombinant peptide libraries, discussing different platforms for their display or expression, and various diversification strategies for library design. We take a look at well-established technologies as well as new developments and future directions.

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.

A Comprehensive Review on Current Advances in Peptide Drug Development and Design

Protein-protein interactions (PPIs) execute many fundamental cellular functions and have served as prime drug targets over the last two decades. Interfering intracellular PPIs with small molecules has been extremely difficult for larger or flat binding sites, as antibodies cannot cross the cell membrane to reach such target sites. In recent years, peptides smaller size and balance of conformational rigidity and flexibility have made them promising candidates for targeting challenging binding interfaces with satisfactory binding affinity and specificity. Deciphering and characterizing peptide-protein recognition mechanisms is thus central for the invention of peptide-based strategies to interfere with endogenous protein interactions, or improvement of the binding affinity and specificity of existing approaches. Importantly, a variety of computation-aided rational designs for peptide therapeutics have been developed, which aim to deliver comprehensive docking for peptide-protein interaction interfaces. Over 60 peptides have been approved and administrated globally in clinics. Despite this, advances in various docking models are only on the merge of making their contribution to peptide drug development. In this review, we provide (i) a holistic overview of peptide drug development and the fundamental technologies utilized to date, and (ii) an updated review on key developments of computational modeling of peptide-protein interactions (PepPIs) with an aim to assist experimental biologists exploit suitable docking methods to advance peptide interfering strategies against PPIs.

Serpin Phage Display: The Use of a T7 System to Probe Reactive Center Loop Libraries with Different Serine Proteinases

Phage display is a protein engineering approach that involves construction of libraries of variant proteins displayed on the surface of bacteriophage as capsid fusion proteins and their screening for binding and inhibitory function through the use of bait proteins. Recently, we adapted a commercially available T7 phage display system to create phage-displayed serpin libraries hypervariable in up to five positions in their reactive center loop (RCL). The RCL is a key determinant in serpin specificity, the relationship between the structure of a given serpin and which target proteinase(s) it inhibits. In this chapter, we describe protocols to assess the feasibility of this method for different serpin/proteinase combinations and share experience with this technology gathered in the course of studying two serpins and multiple proteinases with this powerful iterative screening approach.

Peptides as drug delivery vehicles across biological barriers

Peptides are small biological molecules that are attractive in drug delivery and materials engineering for applications including therapeutics, molecular building blocks and cell-targeting ligands. Peptides are small but can possess complexity and functionality as larger proteins. Due to their intrinsic properties, peptides are able to overcome the physiological and transport barriers presented by diseases. In this review, we discuss the progress of identifying and using peptides to shuttle across biological barriers and facilitate transport of drugs and drug delivery systems for improved therapy. Here, the focus of this review is on rationally designed, phage display peptides, and even endogenous peptides as carriers to penetrate biological barriers, specifically the blood-brain barrier(BBB), the gastrointestinal tract (GI), and the solid tumor microenvironment (T). We will discuss recent advances of peptides as drug carriers in these biological environments. From these findings, challenges and potential opportunities to iterate and improve peptide-based approaches will be discussed to translate their promise towards the clinic to deliver drugs for therapeutic efficacy.

Immunocontraception: Filamentous Bacteriophage as a Platform for Vaccine Development

BACKGROUND

Population control of domestic, wild, invasive, and captive animal species is a global issue of importance to public health, animal welfare and the economy. There is pressing need for effective, safe, and inexpensive contraceptive technologies to address this problem. Contraceptive vaccines, designed to stimulate the immune system in order to block critical reproductive events and suppress fertility, may provide a solution. Filamentous bacteriophages can be used as platforms for development of such vaccines.

OBJECTIVE

In this review authors highlight structural and immunogenic properties of filamentous phages, and discuss applications of phage-peptide vaccines for advancement of immunocontraception technology in animals.

RESULTS

Phages can be engineered to display fusion (non-phage) peptides as coat proteins. Such modifications can be accomplished via genetic manipulation of phage DNA, or by chemical conjugation of synthetic peptides to phage surface proteins. Phage fusions with antigenic determinants induce humoral as well as cell-mediated immune responses in animals, making them attractive as vaccines. Additional advantages of the phage platform include environmental stability, low cost, and safety for immunized animals and those administering the vaccines.

CONCLUSION

Filamentous phages are viable platforms for vaccine development that can be engineered with molecular and organismal specificity. Phage-based vaccines can be produced in abundance at low cost, are environmentally stable, and are immunogenic when administered via multiple routes. These features are essential for a contraceptive vaccine to be operationally practical in animal applications. Adaptability of the phage platform also makes it attractive for design of human immunocontraceptive agents.

Upgrading Affinity Screening Experiments by Analysis of Next-Generation Sequencing Data

Computational analysis of next-generation sequencing data (NGS; also termed deep sequencing) enables the analysis of affinity screening procedures (or biopanning experiments) in an unprecedented depth and therewith improves the identification of relevant peptide or antibody ligands with desired binding or functional properties. Virtually any selection methodology employing the direct physical linkage of geno- and phenotype to select for desired properties can be leveraged by computational analysis. This article describes a concept how relevant ligands can be identified by harnessing NGS data. Thereby, the focus lays on improved ligand identification and describes how NGS data can be structured for single-round analysis as well as for comparative analysis of multiple selection rounds. Especially, the comparative analysis opens new avenues in the field of ligand identification. The concept of computational analysis is described at the example of the software tool "AptaAnalyzer ^TM ." This intuitive tool was developed for scientists without special computer skills and makes the computational approach accessible to a broad user range.

The Current State of Peptide Drug Discovery: Back to the Future?

Over the past decade, peptide drug discovery has experienced a revival of interest and scientific momentum, as the pharmaceutical industry has come to appreciate the role that peptide therapeutics can play in addressing unmet medical needs and how this class of compounds can be an excellent complement or even preferable alternative to small molecule and biological therapeutics. In this Perspective, we give a concise description of the recent progress in peptide drug discovery in a holistic manner, highlighting enabling technological advances affecting nearly every aspect of this field: from lead discovery, to synthesis and optimization, to peptide drug delivery. An emphasis is placed on describing research efforts to overcome the inherent weaknesses of peptide drugs, in particular their poor pharmacokinetic properties, and how these efforts have been critical to the discovery, design, and subsequent development of novel therapeutics.

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

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

Antibody Engineering for Pursuing a Healthier Future

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