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

SPRR1B is Related to the Immune Microenvironment and Can Be Used as a Biomarker for the Diagnosis of Psoriasis

Background

Psoriasis, a chronic inflammatory disorder with an unknown cause, significantly impacts the physical and psychological well-being of patients. However, current biomarkers related to psoriasis lack clinical specificity, sensitivity, and predictive ability.

Methods

In this study, we collected skin lesion tissues from 20 psoriasis patients and 20 normal skin samples. Additionally, we obtained four datasets from the GEO database, which included human psoriasis and healthy specimens. We utilized SVM-RFE analysis and the LASSO regression model to identify potential biomarkers. Furthermore, we examined the composition of immune cell types in psoriasis and their correlation with specific genes.

Results

Our investigation revealed 57 differentially expressed genes (DEGs), and we identified significantly enriched pathways through KEGG pathway analysis. The results of machine learning and WGCNA suggested that LCE3D and SPRR1B could potentially be used as marker genes for diagnosing psoriasis. RT-PCR and immunohistochemical detection confirmed the abnormally high expression of the SPRR1B gene in psoriasis. Analysis of immune cell infiltration revealed a strong positive correlation between SPRR1B and Macrophages M0 and T cells follicular helper, while showing the strongest negative correlation with resting Mast cells. In addition, we found that silencing SPRR1B in IFN-γ-treated HaCat cells could significantly reduce the increase in IL-17, IL-22, KRT6, and KRT16 caused by IFN-γ.

Conclusion

These findings suggest that SPRR1B may have a significant role in the pathogenesis of psoriasis and could be employed as a novel immunomarker for its development.

Prediction of antigen-responding VHH antibodies by tracking the evolution of antibody along the time course of immunization

Antibody maturation is the central function of the adaptive immune response. This process is driven by the repetitive selection of mutations that increase the affinity toward antigens. We hypothesized that a precise observation of this process by high-throughput sequencing along the time course of immunization will enable us to predict the antibodies reacting to the immunized antigen without any additional in vitro screening. An alpaca was immunized with IgG fragments using multiple antigen injections, and the antibody repertoire development was traced via high-throughput sequencing periodically for months. The sequences were processed into clusters, and the antibodies in the 16 most abundant clusters were generated to determine whether the clusters included antigen-binding antibodies. The sequences of most antigen-responsive clusters resembled those of germline cells in the early stages. These sequences were observed to accumulate significant mutations and also showed a continuous sequence turnover throughout the experimental period. The foregoing characteristics gave us >80% successful prediction of clusters composed of antigen-responding VHHs against IgG fragment. Furthermore, when the prediction method was applied to the data from other alpaca immunized with epidermal growth factor receptor, the success rate exceeded 80% as well, confirming the general applicability of the prediction method. Superior to previous studies, we identified the immune-responsive but very rare clusters or sequences from the immunized alpaca without any empirical screening data.

RNA nanostructures for targeted drug delivery and imaging

The RNA molecule plays a pivotal role in many biological processes by relaying genetic information, regulating gene expression, and serving as molecular machines and catalyzers. This inherent versatility of RNA has fueled significant advancements in the field of RNA nanotechnology, driving the engineering of complex nanoscale architectures toward biomedical applications, including targeted drug delivery and bioimaging. RNA polymers, serving as building blocks, offer programmability and predictability of Watson-Crick base pairing, as well as non-canonical base pairing, for the construction of nanostructures with high precision and stoichiometry. Leveraging the ease of chemical modifications to protect the RNA from degradation, researchers have developed highly functional and biocompatible RNA architectures and integrated them into preclinical studies for the delivery of payloads and imaging agents. This review offers an educational introduction to the use of RNA as a biopolymer in the design of multifunctional nanostructures applied to targeted delivery in vivo, summarizing physical and biological barriers along with strategies to overcome them. Furthermore, we highlight the most recent progress in the development of both small and larger RNA nanostructures, with a particular focus on imaging reagents and targeted cancer therapeutics in pre-clinical models and provide insights into the prospects of this rapidly evolving field.

High throughput purification of monoclonal recombinant antibodies using a Protein-A coated membrane plate system

The therapeutic use of monoclonal antibodies (mAbs) ranges from cancer treatment to immune-mediated conditions, covering infectious and cardiovascular disorders, among others. The development of improved methods for therapeutic antibody discovery has accelerated the identification of numerous mAbs: a discovery campaign can be deeply mined, resulting in hundreds, even thousands, of potential antibody leads for a given target of interest. High throughput mAb expression and purification methods are required for the rapid validation of those leads. In this work, we describe the implementation of a Protein-A coated membrane plate system, the Purexa™ AHT membrane plate, for robust preparative purification of hundreds of recombinant mAbs, without the need for automation. The high efficiency (>80%) recovery generated sufficient mAb for downstream screening analyses such as ELISA and surface plasmon resonance (SPR). This new system allows the functional validation of hundreds of lead antibodies from discovery campaigns in a timely manner regardless of operational size.

Optical-based microbubble for on-demand droplet release from static droplet array (SDA) for dispensing one droplet into one tube

Static droplet array (SDA) is a pivotal tool for high-capacity screening assays, yet extraction and collection the target droplets that contain unique analytes or cells from the SDA remains one major technical bottleneck that limits its broader application. Here we present an optical-based on-demand droplet release (OODR) system by incorporating a 1064 nm laser-responsive indium tin oxide (ITO) layer into a chamber array-based droplet microfluidic chip. By focusing the 1064 nm laser onto the ITO layer, microbubbles can be created via local heating to selectively push-out the droplets from the chamber. Then the released droplet is readily exported in a one-droplet-one-tube (ODOT) manner by the inherent capillary force into pipette tip. Releasing of the droplets containing fluorescein sodium demonstrated ∼100% successful rate (9 out of 6400 droplets were successfully released) and low residual (only ∼5% of the droplet volume remains in the chamber). White or fluorescence image-based releasing of single-cell-droplets directly after cell loading or multi-cells-droplets derived from on-chip single-cell cultivation for both E. coli and yeast cells further demonstrated the wide applicability of OODR. The present system is user-friendly and has the potential to be applied in various high-throughput screening assays, including single molecule/cell analysis, drug screening, and phenotype-based cell sorting.

Single B cell transcriptomics identifies multiple isotypes of broadly neutralizing antibodies against flaviviruses

Sequential dengue virus (DENV) infections often generate neutralizing antibodies against all four DENV serotypes and sometimes, Zika virus. Characterizing cross-flavivirus broadly neutralizing antibody (bnAb) responses can inform countermeasures that avoid enhancement of infection associated with non-neutralizing antibodies. Here, we used single cell transcriptomics to mine the bnAb repertoire following repeated DENV infections. We identified several new bnAbs with comparable or superior breadth and potency to known bnAbs, and with distinct recognition determinants. Unlike all known flavivirus bnAbs, which are IgG1, one newly identified cross-flavivirus bnAb (F25.S02) was derived from IgA1. Both IgG1 and IgA1 versions of F25.S02 and known bnAbs displayed neutralizing activity, but only IgG1 enhanced infection in monocytes expressing IgG and IgA Fc receptors. Moreover, IgG-mediated enhancement of infection was inhibited by IgA1 versions of bnAbs. We demonstrate a role for IgA in flavivirus infection and immunity with implications for vaccine and therapeutic strategies.

Molecular Recognition Mechanism of an Anti-Amatoxins mAb and Its Application in Centrifugal Disk-Based Immunoassay

Amatoxins are polypeptides that cause 90% of fatalities from accidental ingestion of poisonous mushrooms. Unfortunately, there are no specific antidotes against amatoxins poisoning, hence preparation of high-affinity antibodies, understanding the receptor (amatoxins) and ligand (antibody) mechanism, and establishing a straightforward screening approach are of great significance for confirming poison agents and clinical diagnosis. Here, anti-amatoxins monoclonal antibody (mAb) 9B2 was prepared and the recognition mechanism was investigated. The approach is useful for designing desirable immunogens, developing new antibodies with improved performance, and constructing effective immunoassays. Based on the mAb, we designed a centrifugal disk-like microfluidics chip and developed a fully automated immunoassay capable of detecting amatoxins poisoning in various samples including serum, urine, and mushrooms. The whole detection process could be automatically accomplished within 30 min, with a limit of detection of 0.08 to 0.12 μg/L for real samples, ∼30-fold more sensitive than conventional enzyme-linked immunosorbent assay (ELISA). Our platform not only provided a practical approach for performing poison agent confirmation and clinical diagnosis but also had important implications for improving the survival of patients with mushroom poisoning.

The impact of expression vector position on transgene transcription allows for rational expression vector design in a targeted integration system

Site-specific integration (SSI) technology has emerged as an effective approach by the pharmaceutical industry for the development of recombinant Chinese hamster ovary (CHO) cell lines. While SSI systems have been demonstrated to be effective for the development of CHO cell lines, they can be limiting in terms of both transgene expression and in the case of multi-specifics, the ability to generate the correct product of interest. To maximize the performance of Pfizer's dual SSI expression system for expressing monoclonal and multi-specific antibodies, we used a novel approach to investigate the positional effect of transgenes within expression vectors by engineering nucleotide polymorphisms (NP)s to use as biomarkers to track the level of transcript output from each expression vector position. We observed differences in transcript level for two different transgenes across all four expression vector positions interrogated. We then applied these learnings to rationally design expression vectors for six different mAbs and a multi-specific antibody. We showed enhanced productivity and optimal product quality when compared to a conventional expression vector topology. The learnings gained here can potentially aid in the determination of optimal vector topologies for several IgG-like multi-specific formats.

Identification of basement membrane-related biomarkers associated with the diagnosis of osteoarthritis based on machine learning

BACKGROUND

Osteoarthritis is a very common clinical disease in middle-aged and elderly individuals, and with the advent of ageing, the incidence of this disease is gradually increasing. There are few studies on the role of basement membrane (BM)-related genes in OA.

METHOD

We used bioinformatics and machine learning methods to identify important genes related to BMs in OA patients and performed immune infiltration analysis, lncRNA‒miRNA-mRNA network prediction, ROC analysis, and qRT‒PCR.

RESULT

Based on the results of machine learning, we determined that LAMA2 and NID2 were the key diagnostic genes of OA, which were confirmed by ROC and qRT‒PCR analyses. Immune analysis showed that LAMA2 and NID2 were closely related to resting memory CD4 T cells, mast cells and plasma cells. Two lncRNAs, XIST and TTTY15, were simultaneously identified, and lncRNA‒miRNA‒mRNA network prediction was performed.

CONCLUSION

LAMA2 and NID2 are important potential targets for the diagnosis and treatment of OA.

Genotyped functional screening of soluble Fab clones enables in-depth analysis of mutation effects

Monoclonal antibodies (mAbs) and their fragments are widely used in therapeutics, diagnostics and basic research. Although display methods such as phage display offer high-throughput, affinities of individual antibodies need to be accurately measured in soluble format. We have developed a screening platform capable of providing genotyped functional data from a total of 9216 soluble, individual antigen binding fragment (Fab) clones by employing next-generation sequencing (NGS) with hierarchical indexing. Full-length, paired variable domain sequences (VL-VH) are linked to functional screening data, enabling in-depth analysis of mutation effects. The platform was applied to four phage display-selected scFv/Fab screening projects and one site-saturation VH affinity maturation project. Genotyped functional screening simultaneously enabled the identification of affinity improving mutations in the VH domain of Fab 49A3 recognizing Dengue virus non-structural protein 1 (NS1) serotype 2 and informed on VH residue positions which cannot be changed from wild-type without decreasing the affinity. Genotype-based identification revealed to us the extent of intraclonal signal variance inherent to single point screening data, a phenomenon often overlooked in the field. Moreover, genotyped screening eliminated the redundant selection of identical genotypes for further study and provided a new analysis tool to evaluate the success of phage display selections and remaining clonal diversity in the screened repertoires.

Flow Cytometry: The Next Revolution

Unmasking the subtleties of the immune system requires both a comprehensive knowledge base and the ability to interrogate that system with intimate sensitivity. That task, to a considerable extent, has been handled by an iterative expansion in flow cytometry methods, both in technological capability and also in accompanying advances in informatics. As the field of fluorescence-based cytomics matured, it reached a technological barrier at around 30 parameter analyses, which stalled the field until spectral flow cytometry created a fundamental transformation that will likely lead to the potential of 100 simultaneous parameter analyses within a few years. The simultaneous advance in informatics has now become a watershed moment for the field as it competes with mature systematic approaches such as genomics and proteomics, allowing cytomics to take a seat at the multi-omics table. In addition, recent technological advances try to combine the speed of flow systems with other detection methods, in addition to fluorescence alone, which will make flow-based instruments even more indispensable in any biological laboratory. This paper outlines current approaches in cell analysis and detection methods, discusses traditional and microfluidic sorting approaches as well as next-generation instruments, and provides an early look at future opportunities that are likely to arise.

Targeting cerebral diseases with enhanced delivery of therapeutic proteins across the blood-brain barrier

INTRODUCTION

Cerebral diseases have been threatening public physical and psychological health in the recent years. With the existence of the blood-brain barrier (BBB), it is particularly hard for therapeutic proteins like peptides, enzymes, antibodies, etc. to enter the central nervous system (CNS) and function in diagnosis and treatment in cerebral diseases. Fortunately, the past decade has witnessed some emerging strategies of delivering macromolecular therapeutic proteins across the BBB.

AREAS COVERED

Based on the structure, functions, and substances transport mechanisms, various enhanced delivery strategies of therapeutic proteins were reviewed, categorized by molecule-mediated delivery strategies, carrier-mediated delivery strategies, and other delivery strategies.

EXPERT OPINION

As for molecule-mediated delivery strategies, development of genetic engineering technology, optimization of protein expression and purification techniques, and mature of quality control systems all help to realize large-scale production of recombinant antibodies, making it possible to apply to the clinical practice. In terms of carrier-mediated delivery strategies and others, although nano-carriers/adeno-associated virus (AAV) are also promising candidates for delivering therapeutic proteins or genes across the BBB, some issues still remain to be further investigated, including safety concerns related to applied materials, large-scale production costs, quality control standards, combination therapies with auxiliary delivery strategies like focused ultrasound, etc.

Identifying biomarkers associated with the diagnosis of ulcerative colitis via bioinformatics and machine learning

BACKGROUND

Ulcerative colitis (UC) is an idiopathic inflammatory disease with an increasing incidence. This study aimed to identify potential UC biomarkers and associated immune infiltration characteristics.

METHODS

Two datasets (GSE87473 and GSE92415) were merged to obtain 193 UC samples and 42 normal samples. Using R, differentially expressed genes (DEGs) between UC and normal samples were filtered out, and their biological functions were investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Promising biomarkers were identified using least absolute shrinkage selector operator regression and support vector machine recursive feature elimination, and their diagnostic efficacy was evaluated through receiver operating characteristic (ROC) curves. Finally, CIBERSORT was used to investigate the immune infiltration characteristics in UC, and the relationship between the identified biomarkers and various immune cells was examined.

RESULTS

We found 102 DEGs, of which 64 were significantly upregulated, and 38 were significantly downregulated. The DEGs were enriched in pathways associated with interleukin-17, cytokine-cytokine receptor interaction and viral protein interactions with cytokines and cytokine receptors, among others. Using machine learning methods and ROC tests, we confirmed DUOX2, DMBT1, CYP2B7P, PITX2 and DEFB1 to be essential diagnostic genes for UC. Immune cell infiltration analysis revealed that all five diagnostic genes were correlated with regulatory T cells, CD8 T cells, activated and resting memory CD4 T cells, activated natural killer cells, neutrophils, activated and resting mast cells, activated and resting dendritic cells and M0, M1 and M2 macrophages.

CONCLUSIONS

DUOX2, DMBT1, CYP2B7P, PITX2 and DEFB1 were identified as prospective biomarkers for UC. A new perspective on understanding the progression of UC may be provided by these biomarkers and their relationship with immune cell infiltration.

Single B cell transcriptomics identifies multiple isotypes of broadly neutralizing antibodies against flaviviruses

Sequential dengue virus (DENV) infections often generate neutralizing antibodies against all four DENV serotypes and sometimes, Zika virus. Characterizing cross-flavivirus broadly neutralizing antibody (bnAb) responses can inform countermeasure strategies that avoid infection enhancement associated with non-neutralizing antibodies. Here, we used single cell transcriptomics to mine the bnAb repertoire following secondary DENV infection. We identified several new bnAbs with comparable or superior breadth and potency to known bnAbs, and with distinct recognition determinants. Unlike all known flavivirus bnAbs, which are IgG1, one newly identified cross-flavivirus bnAb (F25.S02) was derived from IgA1. Both IgG1 and IgA1 versions of F25.S02 and known bnAbs displayed neutralizing activity, but only IgG1 enhanced infection in monocytes expressing IgG and IgA Fc receptors. Moreover, IgG-mediated enhancement of infection was inhibited by IgA1 versions of bnAbs. We demonstrate a role for IgA in flavivirus infection and immunity with implications for vaccine and therapeutic strategies.

Screening of Therapeutic Targets for Pancreatic Cancer by Bioinformatics Methods

Pancreatic cancer (PC) has the lowest survival rate and the highest mortality rate among all cancers due to lack of effective treatments. The objective of the current study was to identify potential therapeutic targets in PC. Three transcriptome datasets, namely GSE62452, GSE46234, and GSE101448, were analyzed for differentially expressed genes (DEGs) between cancer and normal samples. Several bioinformatics methods, including functional analysis, pathway enrichment, hub genes, and drugs were used to screen therapeutic targets for PC. Fisher's exact test was used to analyze functional enrichments. To screen DEGs, the paired t-test was employed. The statistical significance was considered at p <0.05. Overall, 60 DEGs were detected. Functional enrichment analysis revealed enrichment of the DEGs in "multicellular organismal process", "metabolic process", "cell communication", and "enzyme regulator activity". Pathway analysis demonstrated that the DEGs were primarily related to "Glycolipid metabolism", "ECM-receptor interaction", and "pathways in cancer". Five hub genes were examined using the protein-protein interaction (PPI) network. Among these hub genes, 10 known drugs targeted to the CPA1 gene and CLPS gene were found. Overall, CPA1 and CLPS genes, as well as candidate drugs, may be useful for PC in the future.

Generation of a single-cell B cell atlas of antibody repertoires and transcriptomes to identify signatures associated with antigen specificity

Although new genomics-based pipelines have potential to augment antibody discovery, these methods remain in their infancy due to an incomplete understanding of the selection process that governs B cell clonal selection, expansion, and antigen specificity. Furthermore, it remains unknown how factors such as aging and reduction of tolerance influence B cell selection. Here we perform single-cell sequencing of antibody repertoires and transcriptomes of murine B cells following immunizations with a model therapeutic antigen target. We determine the relationship between antibody repertoires, gene expression signatures, and antigen specificity across 100,000 B cells. Recombinant expression and characterization of 227 monoclonal antibodies revealed the existence of clonally expanded and class-switched antigen-specific B cells that were more frequent in young mice. Although integrating multiple repertoire features such as germline gene usage and transcriptional signatures failed to distinguish antigen-specific from nonspecific B cells, other features such as immunoglobulin G (IgG) subtype and sequence composition correlated with antigen specificity.

High-Throughput Screening of Stapled Helical Peptides in Drug Discovery

Therapeutic peptides have revolutionized treatment for a number of human diseases. In particular, the past two decades have witnessed rapid progress of stapled helical peptides in drug discovery. Stapled helical peptides are chemically modified and constrained in their bioactive α-helical conformation. Compared to unstabilized linear peptides, stapled helical peptides exhibit superior binding affinity and selectivity, enhanced membrane permeability, and improved metabolic stability, presenting exciting promise for targeting otherwise challenging protein-protein interfaces. In this Perspective, we summarize recent applications of high-throughput screening technologies for identification of potent stapled helical peptides with optimized binding properties. We expect to provide a broad reference to accelerate the development of stapled helical peptides as the next generation of therapeutic peptides for various human diseases.

Identification of salivary autoantibodies as biomarkers of oral cancer with immunoglobulin A enrichment combined with affinity mass spectrometry

Globally, oral cavity squamous cell carcinoma (OSCC) is one of the most common fatal illnesses. Its high mortality is ascribed to the fact that the disease is often diagnosed at a late stage, which indicates an urgent need for approaches for the early detection of OSCC. The use of salivary autoantibodies (autoAbs) as OSCC biomarkers has numerous advantages such as easy access to saliva samples and efficient detection of autoAbs using well-established secondary reagents. To improve OSCC screening, we identified OSCC-associated autoAbs with the enrichment of salivary autoAbs combined with affinity mass spectrometry (MS). The salivary IgA of healthy individuals and OSCC patients was purified with peptide M-conjugated beads and then applied to immunoprecipitated antigens (Ags) in OSCC cells. Using tandem MS analysis and spectral counting-based quantitation, the level of 10 Ags increased in the OSCC group compared with the control group. Moreover, salivary levels of autoAbs to the 10 Ags were determined by a multiplexed bead-based immunoassay. Among them, seven were significantly higher in early-stage OSCC patients than in healthy individuals. A marker panel consisting of autoAbs to LMAN2, PTGR1, RAB13, and UQCRC2 was further developed to improve the early diagnosis of OSCC.

Bioinformatic Analysis of Natively Paired VH:VL Antibody Repertoires for Antibody Discovery

Next-generation DNA sequencing (NGS) of human antibody repertoires has been extensively implemented to discover novel antibody drugs, to analyze B-cell developmental features, and to investigate antibody responses to infectious diseases and vaccination. Because the antibody repertoire encoded by human B cells is highly diverse, NGS analyses of antibody genes have provided a new window into understanding antibody responses for basic immunology, biopharmaceutical drug discovery, and immunotherapy. However, many antibody discovery protocols analyze the heavy and light chains separately due to the short-read nature of most NGS technologies, whereas paired heavy and light chain data are required for complete antibody characterization. Here, we describe a computational workflow to process millions of paired antibody heavy and light chain DNA sequence reads using the Illumina MiSeq 2x300 NGS platform. In this workflow, we describe raw NGS read processing and initial quality filtering, the annotation and assembly of antibody clonotypes relating to paired heavy and light chain antibody lineages, and the generation of complete heavy+light consensus sequences for the downstream cloning and expression of human antibody proteins.

One-Pot Droplet RT-OE-PCR for the Generation of Natively Paired Antibody Immune Libraries

Classical yeast surface display (YSD) antibody immune libraries are generated by a separate amplification of heavy- and light-chain antibody variable regions (VH and VL, respectively) and subsequent random recombination during the molecular cloning procedure. However, each B cell receptor comprises a unique VH-VL combination, which has been selected and affinity matured in vivo for optimal stability and antigen binding. Thus, the native variable chain pairing is important for the functioning and biophysical properties of the respective antibody. Herein, we present a method for the amplification of cognate VH-VL sequences, compatible with both next-generation sequencing (NGS) and YSD library cloning. We employ a single B cell encapsulation in water-in-oil droplets, followed by a one-pot reverse transcription overlap extension PCR (RT-OE-PCR), resulting in a paired VH-VL repertoire from more than a million B cells in a single day.

Taking a Breather: Advances in Interleukin 5 Inhibition for Asthma Relief

Interleukin 5 (IL-5) is a major cytokine responsible for eosinophil proliferation, migration and degranulation. Eosinophils play a considerable role in the manifestation of type 2 asthma, and therefore this makes IL-5 a unique and clinically important target for therapeutic intervention. Due to the critical role that IL-5 plays in all areas of eosinophil activity, it has been identified and targeted by three therapeutics, Mepolizumab, Benralizumab and Reslizumab. This review describes the IL-5 pathway and presents the clinical trial history of the three IL-5 inhibitors, to provide insight into the role of IL-5 in clinical asthma presentation. Additionally, this review aims to foster further investigation into the IL-5 pathway by describing current novel therapeutic discovery strategies with monoclonal antibodies.

Immune repertoire analysis of normal Chinese donors at different ages

OBJECTIVES

This study investigated the characteristics of the immune repertoire in normal Chinese individuals of different ages.

MATERIALS AND METHODS

In this study, all seven receptor chains from both B and T cells in peripheral blood of 16 normal Chinese individuals from two age groups were analyzed using high-throughput sequencing and dimer-avoided multiplex PCR amplification. Normal in this study is defined as no chronic, infectious or autoimmune disease within 6 months prior to blood draw.

RESULTS

We found that compared with the younger group, the clonal expression of T-cell receptor repertoire increased in the older group, while diversity decreased. In addition, we found that the T-cell receptor repertoire was more significantly affected by age than the B-cell receptor repertoire, including significant differences in the use of the unique TCR-alpha and TCR-beta V-J gene combinations, in the two groups of normal participants. We further analyzed the degree of complementarity determining region 3 sequence sharing between the two groups, and found shared TCR-alpha, TCR-gamma, immunoglobulin-kappa and immunoglobulin-lambda chain complementarity determining region 3 sequences in all subjects.

CONCLUSION

Taken together, our study gives us a better understanding of the immune repertoire of different normal Chinese people, and these results can be applied to the treatment of age-related diseases. Immune repertoire analysis also allows us to observe participant's wellness, aiding in early-stage diagnosis.

The Screening of Therapeutic Peptides for Anti-Inflammation through Phage Display Technology

For the treatment of inflammatory illnesses such as rheumatoid arthritis and carditis, as well as cancer, several anti-inflammatory medications have been created over the years to lower the concentrations of inflammatory mediators in the body. Peptides are a class of medication with the advantages of weak immunogenicity and strong activity, and the phage display technique is an effective method for screening various therapeutic peptides, with a high affinity and selectivity, including anti-inflammation peptides. It enables the selection of high-affinity target-binding peptides from a complex pool of billions of peptides displayed on phages in a combinatorial library. In this review, we will discuss the regular process of using phage display technology to screen therapeutic peptides, and the peptides screened for anti-inflammation properties in recent years according to the target. We will describe how these peptides were screened and how they worked in vitro and in vivo. We will also discuss the current challenges and future outlook of using phage display to obtain anti-inflammatory therapeutic peptides.

Learning what not to select for in antibody drug discovery

Identifying antibodies with high affinity and target specificity is crucial for drug discovery and development; however, filtering out antibody candidates with nonspecific or polyspecific binding profiles is also important. In this issue of Cell Reports Methods, Saksena et al. report a computational counterselection method combining deep sequencing and machine learning for identifying nonspecific antibody candidates and demonstrate that it has advantages over more established molecular counterselection methods.

Identification of Biomarkers Associated with Diagnosis of Osteoarthritis Patients Based on Bioinformatics and Machine Learning

Osteoarthritis (OA) is thought to be the most prevalent chronic joint disease. The incidence of OA is rising because of the ageing population and the epidemic of obesity. This research was designed for the identification of novel diagnostic biomarkers for OA and analyzing the possible association between critical genes and infiltrated immune cells. 10 OA samples from patients with spinal OA and 10 normal samples were collected. GSE55235 and GSE55457 datasets including human OA and normal samples were downloaded from the GEO datasets. Differentially expressed genes (DEGs) were identified between 20 OA and 20 controls. SVM-RFE analysis and LASSO regression model were carried out to screen possible markers. The compositional patterns of the 22 types of immune cell fraction in OA were determined by the use of CIBERSORT. The expression level of the biomarkers in OA was examined by the use of RT-PCR. In this study, an overall 44 DEGs were identified: 18 genes were remarkably upregulated and 26 genes were distinctly downregulated. KEGG pathway analyses revealed that pathways were significantly enriched including IL-17 signal path, rheumatoid arthritis, TNF signal path, and lipid and atherosclerosis. Based on the results of machine learning, we identified APOLD1 and EPYC as critical diagnostic genes in OA, which were further confirmed using ROC assays. Immune cell infiltration analysis revealed that APOLD1 was correlated with mastocytes stimulated, NK cells resting, T cells CD4 memory resting, DCs stimulated, T cells gamma delta, macrophages M0, NK cells stimulated, and mastocytes resting. Moreover, we found that EPYC was correlated with mastocytes stimulated, NK cells resting, T cells CD4 memory resting, DCs stimulated, T cells gamma delta, macrophages M0, NK cells stimulated, and mastocytes resting. Overall, our findings might provide some novel clue for the exploration of novel markers for OA diagnosis. The critical genes and their associations with immune infiltration may offer new insight into understanding OA developments.

Methods to Produce Monoclonal Antibodies for the Prevention and Treatment of Viral Infections

A viral threat can arise suddenly and quickly turn into a major epidemic or pandemic. In such a case, it is necessary to develop effective means of therapy and prevention in a short time. Vaccine development takes decades, and the use of antiviral compounds is often ineffective and unsafe. A quick response may be the use of convalescent plasma, but a number of difficulties associated with it forced researchers to switch to the development of safer and more effective drugs based on monoclonal antibodies (mAbs). In order to provide protection, such drugs must have a key characteristic-neutralizing properties, i.e., the ability to block viral infection. Currently, there are several approaches to produce mAbs in the researchers' toolkit, however, none of them may serve as a gold standard. Each approach has its own advantages and disadvantages. The choice of the method depends both on the characteristics of the virus and on time constraints and technical challenges. This review provides a comparative analysis of modern methods to produce neutralizing mAbs and describes current trends in the design of antibodies for therapy and prevention of viral diseases.

Suspendable Hydrogel Nanovials for Massively Parallel Single-Cell Functional Analysis and Sorting

Techniques to analyze and sort single cells based on functional outputs, such as secreted products, have the potential to transform our understanding of cellular biology as well as accelerate the development of next-generation cell and antibody therapies. However, secreted molecules rapidly diffuse away from cells, and analysis of these products requires specialized equipment and expertise to compartmentalize individual cells and capture their secretions. Herein, we describe methods to fabricate hydrogel-based chemically functionalized microcontainers, which we call nanovials, and demonstrate their use for sorting single viable cells based on their secreted products at high-throughput using only commonly accessible laboratory infrastructure. These nanovials act as solid supports that facilitate attachment of a variety of adherent and suspension cell types, partition uniform aqueous compartments, and capture secreted proteins. Solutions can be exchanged around nanovials to perform fluorescence immunoassays on secreted proteins. Using this platform and commercial flow sorters, we demonstrate high-throughput screening of stably and transiently transfected producer cells based on relative IgG production. Chinese hamster ovary cells sorted based on IgG production regrew and maintained a high secretion phenotype over at least a week, yielding >40% increase in bulk IgG production rates. We also sorted hybridomas and B lymphocytes based on antigen-specific antibody production. Hybridoma cells secreting an antihen egg lysozyme antibody were recovered from background cells, enriching a population of ∼4% prevalence to >90% following sorting. Leveraging the high-speed sorting capabilities of standard sorters, we sorted >1 million events in <1 h. IgG secreting mouse B cells were also sorted and enriched based on antigen-specific binding. Successful sorting of antibody-secreting B cells combined with the ability to perform single-cell RT-PCR to recover sequence information suggests the potential to perform antibody discovery workflows. The reported nanovials can be easily stored and distributed among researchers, democratizing access to high-throughput functional cell screening.

The Therapeutic Antibody Profiler for Computational Developability Assessment

The need to consider an antibody's "developability" (immunogenicity, solubility, specificity, stability, manufacturability, and storability) is now well understood in therapeutic antibody design. Predicting these properties rapidly and inexpensively is critical to industrial workflows, to avoid devoting resources to non-productive candidates. Here, we describe a high-throughput computational developability assessment tool, the Therapeutic Antibody Profiler (TAP), which assesses the physicochemical "druglikeness" of an antibody candidate. Input variable domain sequences are converted to three-dimensional structural models, and then five developability-linked molecular surface descriptors are calculated and compared to advanced-stage clinical therapeutics. Values at the extremes of/outside of the distributions seen in therapeutics imply an increased risk of developability issues. Therefore, TAP, starting only from sequence information, provides a route to rapidly identifying drug candidate antibodies that are likely to have poor developability. Our web application ( opig.stats.ox.ac.uk/webapps/tap ) profiles input antibody sequences against a continually updated reference set of clinical therapeutics.

Profiling the specificity of clonally expanded plasma cells during chronic viral infection by single-cell analysis

Plasma cells and their secreted antibodies play a central role in the long-term protection against chronic viral infection. However, due to experimental limitations, a comprehensive description of linked genotypic, phenotypic, and antibody repertoire features of plasma cells (gene expression, clonal frequency, virus specificity, and affinity) has been challenging to obtain. To address this, we performed single-cell transcriptome and antibody repertoire sequencing of the murine BM plasma cell population following chronic lymphocytic choriomeningitis virus infection. Our single-cell sequencing approach recovered full-length and paired heavy- and light-chain sequence information for thousands of plasma cells and enabled us to perform recombinant antibody expression and specificity screening. Antibody repertoire analysis revealed that, relative to protein immunization, chronic infection led to increased levels of clonal expansion, class-switching, and somatic variants. Furthermore, antibodies from the highly expanded and class-switched (IgG) plasma cells were found to be specific for multiple viral antigens and a subset of clones exhibited cross-reactivity to nonviral and autoantigens. Integrating single-cell transcriptome data with antibody specificity suggested that plasma cell transcriptional phenotype was correlated to viral antigen specificity. Our findings demonstrate that chronic viral infection can induce and sustain plasma cell clonal expansion, combined with significant somatic hypermutation, and can generate cross-reactive antibodies.

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

Background

Rapid deployment of technologies capable of high-throughput and high-resolution screening is imperative for timely response to viral outbreaks. Risk mitigation in the form of leveraging multiple advanced technologies further increases the likelihood of identifying efficacious treatments in aggressive timelines.

Methods

In this study, we describe two parallel, yet distinct, in vivo approaches for accelerated discovery of antibodies targeting the severe acute respiratory syndrome coronavirus-2 spike protein. Working with human transgenic Alloy-GK mice, we detail a single B-cell discovery workflow to directly interrogate antibodies secreted from plasma cells for binding specificity and ACE2 receptor blocking activity. Additionally, we describe a concurrent accelerated hybridoma-based workflow utilizing a DiversimAb™ mouse model for increased diversity.

Results

The panel of antibodies isolated from both workflows revealed binding to distinct epitopes with both blocking and non-blocking profiles. Sequence analysis of the resulting lead candidates uncovered additional diversity with the opportunity for straightforward engineering and affinity maturation.

Conclusions

By combining in vivo models with advanced integration of screening and selection platforms, lead antibody candidates can be sequenced and fully characterized within one to three months.

Intrinsic physicochemical profile of marketed antibody-based biotherapeutics

Successful biologic drug discovery and development involves finding functional as well as developable candidates. Once a candidate has been demonstrated to be functional, the next step is to determine whether it can be translated into a drug product. This requires that the candidate can withstand stresses encountered during manufacturing, shipping, and storage. Additionally, it must be safe, efficacious, and possess good pharmacology. In silico analyses of the variable regions of 77 marketed antibody-based biotherapeutics have revealed five nonredundant physicochemical descriptors. Distributions of these descriptors, observed for marketed biotherapeutics, can help prioritize a drug candidate for experimental testing at early discovery stages, guide engineering efforts to further optimize it, and help increase the productivity of biologic drug discovery and development.

Feeding biopharma pipelines with biotherapeutic candidates that possess desirable developability profiles can help improve the productivity of biologic drug discovery and development. Here, we have derived an in silico profile by analyzing computed physicochemical descriptors for the variable regions (Fv) found in 77 marketed antibody-based biotherapeutics. Fv regions of these biotherapeutics demonstrate significant diversities in their germlines, complementarity determining region loop lengths, hydrophobicity, and charge distributions. Furthermore, an analysis of 24 physicochemical descriptors, calculated using homology-based molecular models, has yielded five nonredundant descriptors whose distributions represent stability, isoelectric point, and molecular surface characteristics of their Fv regions. Fv regions of candidates from our internal discovery campaigns, human next-generation sequencing repertoires, and those in clinical-stages (CST) were assessed for similarity with the physicochemical profile derived here. The Fv regions in 33% of CST antibodies show physicochemical properties that are dissimilar to currently marketed biotherapeutics. In comparison, physicochemical characteristics of ∼29% of the Fv regions in human antibodies and ∼27% of our internal hits deviated significantly from those of marketed biotherapeutics. The early availability of this information can help guide hit selection, lead identification, and optimization of biotherapeutic candidates. Insights from this work can also help support portfolio risk assessment, in-licensing, and biopharma collaborations.

Transcriptome analysis reveals genes potentially related to high fiber strength in a Gossypium hirsutum line IL9 with Gossypium mustelinum introgression

Cotton (Gossypium L.) is the most important fiber crop worldwide. Here, transcriptome analysis was conducted on developing fibers of a G. mustelinum introgression line, IL9, and its recurrent parent, PD94042, at 17 and 21 days post-anthesis (dpa). Differentially expressed genes (DEGs) of PD94042 and IL9 were identified. Gene Ontology (GO) enrichment analysis showed that the annotated DEGs were rich in two main biological processes and two main molecular functions. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis likewise showed that the annotated DEGs were mainly enriched in metabolic pathways and biosynthesis of secondary metabolites. In total, 52 DEGs were selected as candidate genes based on comparison of the DEGs and GO function annotation information. Quantitative real-time PCR (RT-qPCR) analysis results for 12 randomly selected DEGs were consistent with transcriptome analysis. SNP identification based on G. mustelinum chromatin segment introgression showed that 394 SNPs were identified in 268 DEGs, and two genes with known functions were identified within fiber strength quantitative trait loci (QTL) regions or near the confidence intervals. We identified 52 key genes potentially related to high fiber strength in a G. mustelinum introgression line and provided significant insights into the study of cotton fiber quality improvement.

Engineering of single-domain antibodies for next-generation snakebite antivenoms

Given the magnitude of the global snakebite crisis, strategies to ensure the quality of antivenom, as well as the availability and sustainability of its supply are under development by several research groups. Recombinant DNA technology has allowed the engineering of monoclonal antibodies and recombinant fragments as alternatives to conventional antivenoms. Besides having higher therapeutic efficacy, with broad neutralization capacity against local and systemic toxicity, novel antivenoms need to be safe and cost-effective. Due to the biological and physical chemical properties of camelid single-domain antibodies, with high volume of distribution to distal tissue, their modular format, and their versatility, their biotechnological application has grown considerably in recent decades. This article presents the most up-to-date developments concerning camelid single-domain-based antibodies against major toxins from snake venoms, the main venomous animals responsible for reported envenoming cases and related human deaths. A brief discussion on the composition, challenges, and perspectives of antivenoms is presented, as well as the road ahead for next-generation antivenoms based on single-domain antibodies.

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

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

A single donor is sufficient to produce a highly functional in vitro antibody library

Antibody complementarity determining region diversity has been considered to be the most important metric for the production of a functional antibody library. Generally, the greater the antibody library diversity, the greater the probability of selecting a diverse array of high affinity leads. According to this paradigm, the primary means of elevating library diversity has been by increasing the number of donors. In the present study we explored the possibility of creating an in vitro antibody library from a single healthy individual, showing that the number of lymphocytes, rather than the number of donors, is the key criterion in the production of a diverse and functional antibody library. We describe the construction of a high-quality phage display library comprising 5 × 10⁹ human antibodies by applying an efficient B cell extraction protocol from a single donor and a targeted V-gene amplification strategy favoring specific antibody families for their improved developability profiles. Each step of the library generation process was followed and validated by next generation sequencing to monitor the library quality and diversity. The functionality of the library was tested using several therapeutically relevant targets for which a vast number of different antibodies with desired biophysical properties were obtained.

Polo-Like Kinase 4's Critical Role in Cancer Development and Strategies for Plk4-Targeted Therapy

Polo-like kinases (Plks) are critical regulatory molecules during the cell cycle process. This family has five members: Plk1, 2, 3, 4, and 5. Plk4 has been identified as a master regulator of centriole replication, and its aberrant expression is closely associated with cancer development. In this review, we depict the DNA, mRNA, and protein structure of Plk4, and the regulation of Plk4 at a molecular level. Then we list the downstream targets of Plk4 and the hallmarks of cancer associated with these targets. The role of Plk4 in different cancers is also summarized. Finally, we review the inhibitors that target Plk4 in the hope of discovering effective anticancer drugs. From authors' perspective, Plk4 might represent a valuable tumor biomarker and critical target for cancer diagnosis and therapy.

Nanobodies: The "Magic Bullets" in therapeutics, drug delivery and diagnostics

Antibodies represent a well-established class of clinical diagnostics for medical applications as well as essential research and biotechnological tools. Although both polyclonal and monoclonal antibodies are indispensable reagents in basic research and diagnostics but both of them have their limitations. Hence, there is urgent need to develop strategies aimed at production of alternative scaffolds and recombinant antibodies of smaller dimensions that could be easily produced, selected and manipulated. Unlike conventional antibodies, members of Camelidae and sharks produce antibodies composed only of heavy chains with small size, high solubility, thermal stability, refolding capacity and good tissue penetration in vivo. The discovery of these naturally occurring antibodies having only heavy-chain in Camelidae family and their further development into small recombinant nanobodies represents an attractive alternative in drug delivery, diagnostics and imaging. Nanobody derivatives are soluble, stable, versatile, have unique refolding capacities, reduced aggregation tendencies and high-target binding capabilities. They can be genetically customized to target enzymes, transmembrane proteins or molecular interactions. Their ability to recognize recessed antigenic sites has been attributed to their smaller size and the ability of the extended CDR3 loop to quickly penetrate into such epitopes. With the advent of molecular engineering and phage display technology, they can be of potential use in molecular imaging, drug delivery and therapeutics for several major diseases. In this review we present the recent advances in nanobodies for modulating immune functions, for targeting cancers, viruses, toxins and microbes as well as their utility as diagnostic and biosensor tools.

RNase H-dependent PCR enables highly specific amplification of antibody variable domains from single B-cells

Immunization-based antibody discovery platforms require robust and effective protocols for the amplification, cloning, expression, and screening of antibodies from large numbers of B-cells in order to effectively capture the diversity of an experienced Ig-repertoire. Multiplex PCR using a series of forward and reverse primers designed to recover antibodies from a range of different germline sequences is challenging because primer design requires the recovery of full length antibody sequences, low starting template concentrations, and the need for all the primers to function under the same PCR conditions. Here we demonstrate several advantages to incorporating RNase H2-dependent PCR (rh-PCR) into a high-throughput, antibody-discovery platform. Firstly, rh-PCR eliminated primer dimer synthesis to below detectable levels, thereby eliminating clones with a false positive antibody titer. Secondly, by increasing the specificity of PCR, the rh-PCR primers increased the recovery of cognate antibody variable regions from single B-cells, as well as downstream recombinant antibody titers. Finally, we demonstrate that rh-PCR primers provide a more homogeneous sample pool and greater sequence quality in a Next Generation Sequencing-based approach to obtaining DNA sequence information from large numbers of cloned antibody cognate pairs. Furthermore, the higher specificity of the rh-PCR primers allowed for a better match between native antibody germline sequences and the VL/VH fragments amplified from single B-cells.

Characterization of Variable Region Genes and Discovery of Key Recognition Sites in the Complementarity Determining Regions of the Anti-Thiacloprid Monoclonal Antibody

Sequence-defined recombinant antibodies (rAbs) have emerged as alternatives to hybridoma-secreted monoclonal antibodies (mAbs) for performing immunoassays. However, the polyploidy nature of hybridomas often leads to the coexistence of aberrant or non-specific functional variable region (VR) gene transcripts, which complicates the identification of correct VR sequences. Herein, we introduced the use of LC-MS/MS combined with next-generation sequencing to characterize VR sequences in an anti-thiacloprid mAb, which was produced by a hybridoma with genetic antibody diversity. The certainty of VR sequences was verified by the functional analysis based on the recombinant antibody (rAb) expressed by HEK293 mammalian cells. The performance of the rAb was similar to that of the parental mAb, with IC50 values of 0.73 and 0.46 μg/L as measured by ELISAs. Moreover, molecular docking analysis revealed that Ser52 (H-CDR2), Trp98, and Trp93 (L-CDR3) residues in the complementarity determining regions (CDRs) of the identified VR sequences predominantly contributed to thiacloprid-specific recognition through hydrogen bonds and the CH-π interaction. Through single-site-directed alanine mutagenesis, we found that Trp98 and Trp93 (L-CDR3) showed high affinity to thiacloprid, while Ser52 (H-CDR2) had an auxiliary effect on the specific binding. This study presents an efficient and reliable way to determine the key recognition sites of hapten-specific mAbs, facilitating the improvement of antibody properties.

Benchmarking immunoinformatic tools for the analysis of antibody repertoire sequences

Summary

Antibody repertoires reveal insights into the biology of the adaptive immune system and empower diagnostics and therapeutics. There are currently multiple tools available for the annotation of antibody sequences. All downstream analyses such as choosing lead drug candidates depend on the correct annotation of these sequences; however, a thorough comparison of the performance of these tools has not been investigated. Here, we benchmark the performance of commonly used immunoinformatic tools, i.e. IMGT/HighV-QUEST, IgBLAST and MiXCR, in terms of reproducibility of annotation output, accuracy and speed using simulated and experimental high-throughput sequencing datasets.

We analyzed changes in IMGT reference germline database in the last 10 years in order to assess the reproducibility of the annotation output. We found that only 73/183 (40%) V, D and J human genes were shared between the reference germline sets used by the tools. We found that the annotation results differed between tools. In terms of alignment accuracy, MiXCR had the highest average frequency of gene mishits, 0.02 mishit frequency and IgBLAST the lowest, 0.004 mishit frequency. Reproducibility in the output of complementarity determining three regions (CDR3 amino acids) ranged from 4.3% to 77.6% with preprocessed data. In addition, run time of the tools was assessed: MiXCR was the fastest tool for number of sequences processed per unit of time. These results indicate that immunoinformatic analyses greatly depend on the choice of bioinformatics tool. Our results support informed decision-making to immunoinformaticians based on repertoire composition and sequencing platforms.

Availability and implementation

All tools utilized in the paper are free for academic use.

Supplementary information

Supplementary data are available at Bioinformatics online.

Inter- and intraspecies comparison of phylogenetic fingerprints and sequence diversity of immunoglobulin variable genes

Protection and neutralization of a vast array of pathogens is accomplished by the tremendous diversity of the B cell receptor (BCR) repertoire. For jawed vertebrates, this diversity is initiated via the somatic recombination of immunoglobulin (Ig) germline elements. While it is clear that the number of these germline segments differs from species to species, the extent of cross-species sequence diversity remains largely uncharacterized. Here we use extensive computational and statistical methods to investigate the sequence diversity and evolutionary relationship between Ig variable (V), diversity (D), and joining (J) germline segments across nine commonly studied species ranging from zebrafish to human. Metrics such as guanine-cytosine (GC) content showed low redundancy across Ig germline genes within a given species. Other comparisons, including amino acid motifs, evolutionary selection, and sequence diversity, revealed species-specific properties. Additionally, we showed that the germline-encoded diversity differs across antibody (recombined V-D-J) repertoires of various B cell subsets. To facilitate future comparative immunogenomics analysis, we created VDJgermlines, an R package that contains the germline sequences from multiple species. Our study informs strategies for the humanization and engineering of therapeutic antibodies.

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

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

Adaptive immune receptor repertoires, an overview of this exciting field

The adaptive immune response in jawed vertebrates relies on the huge diversity and specificity of the B cell and T cell antigen receptors, the immunoglobulins (IG) or antibodies and the T cell receptors (TR), respectively. The high level of diversity has represented a barrier to a comprehensive analysis of the adaptive immune response before the emergence of high-throughput sequencing (HTS) technologies. The size and complexity of HTS data requires the generation of novel computational and analytical approaches, which are transforming how the adaptive immune responses are deciphered to understand the clonal dynamics and properties of antigen-specific B and T cells in response to different kind of antigens. This exciting and rapidly evolving field is not only impacting human and clinical immunology but also comparative immunology. We are now closer to understanding the evolution of adaptive immune response in jawed vertebrates. This review provides an overview about classical and current strategies developed to assess the IG/TR diversity and their applications in basic and clinical immunology.

Strategy for Development of Site-Specific Ubiquitin Antibodies

Protein ubiquitination is a key post-translational modification regulating a wide range of biological processes. Ubiquitination involves the covalent attachment of the small protein ubiquitin to a lysine of a protein substrate. In addition to its well-established role in protein degradation, protein ubiquitination plays a role in protein-protein interactions, DNA repair, transcriptional regulation, and other cellular functions. Understanding the mechanisms and functional relevance of ubiquitin as a signaling system requires the generation of antibodies or alternative reagents that specifically detect ubiquitin in a site-specific manner. However, in contrast to other post-translational modifications such as acetylation, phosphorylation, and methylation, the instability and size of ubiquitin-76 amino acids-complicate the preparation of suitable antigens and the generation antibodies detecting such site-specific modifications. As a result, the field of ubiquitin research has limited access to specific antibodies. This severely hampers progress in understanding the regulation and function of site-specific ubiquitination in many areas of biology, specifically in epigenetics and cancer. Therefore, there is a high demand for antibodies recognizing site-specific ubiquitin modifications. Here we describe a strategy for the development of site-specific ubiquitin antibodies. Based on a recently developed antibody against site-specific ubiquitination of histone H2B, we provide detailed protocols for chemical synthesis methods for antigen preparation and discuss considerations for screening and quality control experiments.

Finding the Keys to the CAR: Identifying Novel Target Antigens for T Cell Redirection Immunotherapies

Oncology immunotherapy has been a significant advancement in cancer treatment and involves harnessing and redirecting a patient’s immune response towards their own tumour. Specific recognition and elimination of tumour cells was first proposed over a century ago with Paul Erlich’s ‘magic bullet’ theory of therapy. In the past decades, targeting cancer antigens by redirecting T cells with antibodies using either bispecific T cell engagers (BiTEs) or chimeric antigen receptor (CAR) T cell therapy has achieved impressive clinical responses. Despite recent successes in haematological cancers, linked to a high and uniformly expressed CD19 antigen, the efficacy of T cell therapies in solid cancers has been disappointing, in part due to antigen escape. Targeting heterogeneous solid tumours with T cell therapies will require the identification of novel tumour specific targets. These targets can be found among a range of cell-surface expressed antigens, including proteins, glycolipids or carbohydrates. In this review, we will introduce the current tumour target antigen classification, outline existing approaches to discover novel tumour target antigens and discuss considerations for future design of antibodies with a focus on their use in CAR T cells.

Antibody discovery and engineering by enhanced CRISPR-Cas9 integration of variable gene cassette libraries in mammalian cells

Antibody engineering in mammalian cells offers the important advantage of expression and screening of libraries in their native conformation, increasing the likelihood of generating candidates with more favorable molecular properties. Major advances in cellular engineering enabled by CRISPR-Cas9 genome editing have made it possible to expand the use of mammalian cells in biotechnological applications. Here, we describe an antibody engineering and screening approach where complete variable light (V_L) and heavy (V_H) chain cassette libraries are stably integrated into the genome of hybridoma cells by enhanced Cas9-driven homology-directed repair (HDR), resulting in their surface display and secretion. By developing an improved HDR donor format that utilizes in situ linearization, we are able to achieve >15-fold improvement of genomic integration, resulting in a screening workflow that only requires a simple plasmid electroporation. This proved suitable for different applications in antibody discovery and engineering. By integrating and screening an immune library obtained from the variable gene repertoire of an immunized mouse, we could isolate a diverse panel of >40 unique antigen-binding variants. Additionally, we successfully performed affinity maturation by directed evolution screening of an antibody library based on random mutagenesis, leading to the isolation of several clones with affinities in the picomolar range.

Antibody-based nanotechnology

Antibodies are considered the hallmark of the adaptive immune system in that they mediate various key biological functions, such as direct neutralization and recruitment of effector immune cells to eliminate invading pathogens. Antibodies exhibit several unique properties, including high diversity (enabling binding to a wide range of targets), high specificity and structural integrity. These properties and the understanding that antibodies can be utilized in a wide range of applications have motivated the scientific community to develop new approaches for antibody repertoire analysis and rapid monoclonal antibody discovery. Today, antibodies are key modules in the pharmaceutical and diagnostic industries. By virtue of their high affinity and specificity to their targets and the availability of technologies to engineer different antibodies to a wide range of targets, antibodies have become the most promising natural biological molecules in a range of biotechnological applications, such as: highly specific and sensitive nanobiosensors for the diagnostics of different biomarkers; nanoparticle-based targeted drug delivery systems to certain cells or tissues; and nanomachines, which are nanoscale mechanical devices that enable energy conversion into precise mechanical motions in response to specific molecular inputs. In this review, we start by describing the unique properties of antibodies, how antibody diversity is generated, and the available technologies for antibody repertoire analysis and antibody discovery. Thereafter, we provide an overview of some antibody-based nanotechnologies and discuss novel and promising approaches for the application of antibodies in the nanotechnology field. Overall, we aim to bridge the knowledge gap between the nanotechnology and antibody engineering disciplines by demonstrating how technological advances in the antibody field can be leveraged to develop and/or enhance new technological approaches in the nanotechnology field.

Considerations for the Design of Antibody-Based Therapeutics

Antibody-based proteins have become an important class of biologic therapeutics, due in large part to the stability, specificity, and adaptability of the antibody framework. Indeed, antibodies not only have the inherent ability to bind both antigens and endogenous immune receptors but also have proven extremely amenable to protein engineering. Thus, several derivatives of the monoclonal antibody format, including bispecific antibodies, antibody-drug conjugates, and antibody fragments, have demonstrated efficacy for treating human disease, particularly in the fields of immunology and oncology. Reviewed here are considerations for the design of antibody-based therapeutics, including immunological context, therapeutic mechanisms, and engineering strategies. First, characteristics of antibodies are introduced, with emphasis on structural domains, functionally important receptors, isotypic and allotypic differences, and modifications such as glycosylation. Then, aspects of therapeutic antibody design are discussed, including identification of antigen-specific variable regions, choice of expression system, use of multispecific formats, and design of antibody derivatives based on fragmentation, oligomerization, or conjugation to other functional moieties. Finally, strategies to enhance antibody function through protein engineering are reviewed while highlighting the impact of fundamental biophysical properties on protein developability.