Antibody specificity and promiscuity

A Sensitive and Specific Monoclonal Antibody Based Enzyme-Linked Immunosorbent Assay for the Rapid Detection of Pretilachlor in Grains and the Environment

Pretilachlor is a chloroacetamide herbicide mainly used for weed and broadleaf weed control in rice, that is widely utilized in China. In order to detect the residue of pretilachlor in the environment and food, a highly sensitive and specific monoclonal antibody (mAb) against pretilachlor was prepared, and the half maximum inhibitory concentration (IC50) of the monoclonal antibody was validated to be 31.47 ± 2.35 μg/L. An indirect competitive ELISA (ic-ELISA) based on the antibody with a linear range of 6.25~100 μg/L was developed. The specificity of the antibody was explained by computer simulations and experimental validation. The mAb exhibited negligible cross-reactivity towards alachlor, acetochlor, propisochlor, butachlor, and metalaxyl, and the limits of detection (LOD) for pretilachlor in lake, rice, and soil samples were 4.83~5.23 μg/L. The recoveries of all samples were 78.3~91.3%. The reliability of the ic-ELISA method for residue detection of pretilachlor in the environment and grains was confirmed using high performance liquid chromatography.

Polyreactivity of antibodies from different B-cell subpopulations is determined by distinct sequence patterns of variable region

An antibody molecule that can bind to multiple distinct antigens is defined as polyreactive. In the present study, we performed statistical analyses to assess sequence correlates of polyreactivity of >600 antibodies cloned from different B-cell types of healthy humans. The data revealed several sequence patterns of variable regions of heavy and light immunoglobulin chains that determine polyreactivity. The most prominent identified patterns were increased number of basic amino acid residues, reduced frequency of acidic residues, increased number of aromatic and hydrophobic residues, and longer length of CDR L1. Importantly, our study revealed that antibodies isolated from different B-cell populations used distinct sequence patterns (or combinations of them) for polyreactive antigen binding. Furthermore, we combined the data from sequence analyses with molecular modeling of selected polyreactive antibodies and demonstrated that human antibodies can use multiple pathways for achieving antigen-binding promiscuity. These data reconcile some contradictions in the literature regarding the determinants of antibody polyreactivity. Moreover, our study demonstrates that the mechanism of polyreactivity of antibodies evolves during immune response and might be tailored to specific functional properties of different B-cell compartments. Finally, these data can be of use for efforts in the development and engineering of therapeutic antibodies.

Precise isolation and structural origin of an ultra-specific nanobody against chemical compound

Highly specific antibodies are the key reagents for developing immunoassays with a low false positive rate for environmental monitoring. Here, we provide evidence that nanobodies have the potential to achieve higher specificity than conventional antibodies and explain why from their structural features. Using sulfadimethoxine (SDM) as a model analyte, we constructed an immune phage display library and precisely isolated an ultra-specific nanobody (H1-17) by a crucial homologous antigen counter selection strategy. H1-17 showed no observable cross-reactivity (CR) with other structural analogs of 41 SDM tested, which has never been achieved by conventional antibodies. The structurally original specificity of H1-17 was illuminated and compared with that of one conventional antibody by homology modeling and site-directed mutagenesis validation. It was found that the noncanonical disulfide bond (C50-C104) of H1-17 helped CDR3 form a tailor-made binding pocket and divide it into two parts to accommodate the common structure of sulfonamides and the characteristic methoxyl group of SDM, respectively. Besides, the mutual-checking hydrogen bonds also played important roles in the specific recognition. Lastly, immunoassays with zero false positive rate were developed to screen SDM in water and milk samples, indicating that nanobodies could be reliable reagents for the accurate detection of chemical compounds.

Prospective on Imaging Mass Spectrometry in Clinical Diagnostics

Imaging mass spectrometry (IMS) is a molecular technology utilized for spatially driven research, providing molecular maps from tissue sections. This article reviews matrix-assisted laser desorption ionization (MALDI) IMS and its progress as a primary tool in the clinical laboratory. MALDI mass spectrometry has been used to classify bacteria and perform other bulk analyses for plate-based assays for many years. However, the clinical application of spatial data within a tissue biopsy for diagnoses and prognoses is still an emerging opportunity in molecular diagnostics. This work considers spatially driven mass spectrometry approaches for clinical diagnostics and addresses aspects of new imaging-based assays that include analyte selection, quality control/assurance metrics, data reproducibility, data classification, and data scoring. It is necessary to implement these tasks for the rigorous translation of IMS to the clinical laboratory; however, this requires detailed standardized protocols for introducing IMS into the clinical laboratory to deliver reliable and reproducible results that inform and guide patient care.

Surface patches induce nonspecific binding and phase separation of antibodies

Nonspecific interactions are a key challenge in the successful development of therapeutic antibodies. The tendency for nonspecific binding of antibodies is often difficult to reduce by rational design, and instead, it is necessary to rely on comprehensive screening campaigns. To address this issue, we performed a systematic analysis of the impact of surface patch properties on antibody nonspecificity using a designer antibody library as a model system and single-stranded DNA as a nonspecificity ligand. Using an in-solution microfluidic approach, we find that the antibodies tested bind to single-stranded DNA with affinities as high as KD = 1 µM. We show that DNA binding is driven primarily by a hydrophobic patch in the complementarity-determining regions. By quantifying the surface patches across the library, the nonspecific binding affinity is shown to correlate with a trade-off between the hydrophobic and total charged patch areas. Moreover, we show that a change in formulation conditions at low ionic strengths leads to DNA-induced antibody phase separation as a manifestation of nonspecific binding at low micromolar antibody concentrations. We highlight that phase separation is driven by a cooperative electrostatic network assembly mechanism of antibodies with DNA, which correlates with a balance between positive and negative charged patches. Importantly, our study demonstrates that both nonspecific binding and phase separation are controlled by the size of the surface patches. Taken together, these findings highlight the importance of surface patches and their role in conferring antibody nonspecificity and its macroscopic manifestation in phase separation.

Sequential administration of virus-like particle-based nanomedicine to elicit enhanced tumor chemotherapy

Protein cages have played a long-standing role in biomedicine applications, especially in tumor chemotherapy. Among protein cages, virus like particles (VLPs) have received attention for their potential applications in vaccine development and targeted drug delivery. However, most of the existing protein-based platform technologies are plagued with immunological problems that may limit their systemic delivery efficiency as drug carriers. Here, we show that using immune-orthogonal protein cages sequentially and modifying the dominant loop epitope can circumvent adaptive immune responses and enable effective drug delivery using repeated dosing. We genetically modified three different hepadnavirus core protein derived VLPs as delivery vectors for doxorubicin (DOX). These engineered VLPs have similar assembly characteristics, particle sizes, and immunological properties. Our results indicated that there was negligible antibody cross-reactivity in either direction between these three RGD-VLPs in mice that were previously immunized against HBc VLPs. Moreover, the sequential administration of multiple RGD-VLP-based nanomedicine (DOX@RGD-VLPs) could effectively reduce immune clearance and inhibited tumor growth. Hence, this study could provide an attractive protein cage-based platform for therapeutic drug delivery.

Pfizer-BioNTech vaccine induces the production of cross-reactive antibodies against Trypanosoma cruzi proteins: A preliminary study

OBJECTIVE

To evaluate the presence of cross-reactivity by anti-severe acute respiratory syndrome coronavirus 2 antibodies induced by the Pfizer-BioNTech vaccine against Trypanosoma cruzi proteins in a screening test.

METHODS

Forty-three serum samples were obtained from personnel at the Hospital General Naval de Alta Especialidad in Mexico City who received one or two doses of the vaccine and were tested for T. cruzi infection using four tests: two 'in house' enzyme-linked immunosorbent assays (ELISAs), a commercial ELISA diagnostic kit and an immunoblot test.

RESULTS

IgG antibodies against the T. cruzi proteins were present in the serum of unvaccinated subjects and subjects who had received one or two doses of the vaccine. The positivity of the samples against T. cruzi was ruled out by means of a Western Blot assay, where all samples were negative for T. cruzi.

CONCLUSION

The data suggest that people convalescing from coronavirus disease 2019 and those who received the Pfizer-BioNTech vaccine exhibit cross-reactive antibodies against T. cruzi antigens in ELISA assays.

Development of epitopephore-based rational hapten design strategy: A combination of theoretical evidence and experimental validation

Antibody is the key biomolecule that governing the sensitivity and specificity of an immunoassay for chemical compound, also named hapten molecule. Obviously, predication of hapten effectiveness before chemical synthesis is beneficial to boost success, save cost and improve controllability. Here, we proposed and evaluated an epitopephore based rational hapten design (ERHD) to assist antibody production to chemical compound, combining theoretical evidence and then experimental validation by using dinitrocarbanilide (DNC) as a model analyte. Briefly, epitopephores of DNC were firstly generated by HipHop algorithm after features mapping. A homemade drug database also containing reported fragment haptens (HFR) and new designed full hapten (HFU) were constructed, and then was virtually screened by using generated epitopephore followed by structural analysis and visual inspection. The DNC haptens based on the selected hits were further identified by Density Functional Theory before total synthesis. To prove and clarify the usability of the ERHD, two retrieved HFU haptens, one non-retrieved HFU hapten and three non-retrieved HFR haptens were all selected to produce monoclonal antibodies (mAbs) for comparison purpose. A maximal 6000-fold increased affinity of mAb from retrieved HFU than HFR was observed, while, non-retrieved HFU failed to produce antibody to DNC. More importantly, mAbs from HFU haptens provided highly specificity to DNC, while, mAbs from HFR haptens could recognize 15 others analogues. We then constructed antibody structure and investigated molecular recognition of the mAbs to DNC, well supporting the rationality of the ERHD. Lastly, an icELISA was developed for DNC with an IC₅₀ value as low as 0.19 ng mL^-1 with high specificity, which has never achieved before.

Non-specificity as the sticky problem in therapeutic antibody development

Antibodies are highly potent therapeutic scaffolds with more than a hundred different products approved on the market. Successful development of antibody-based drugs requires a trade-off between high target specificity and target binding affinity. In order to better understand this problem, we here review non-specific interactions and explore their fundamental physicochemical origins. We discuss the role of surface patches - clusters of surface-exposed amino acid residues with similar physicochemical properties - as inducers of non-specific interactions. These patches collectively drive interactions including dipole-dipole, π-stacking and hydrophobic interactions to complementary moieties. We elucidate links between these supramolecular assembly processes and macroscopic development issues, such as decreased physical stability and poor in vivo half-life. Finally, we highlight challenges and opportunities for optimizing protein binding specificity and minimizing non-specificity for future generations of therapeutics.

Previously Unrecognized Nonreproducible Antibody-Probe Interactions

Antibody-antigen (Ab-Ag) interactions are canonically described by a model that exclusively accommodates noninteraction (0) or reproducible interaction (RI) states, yet this model is inadequate to explain often-encountered nonreproducible signals. Here, by monitoring diverse experimental systems using a peptide-protein hybrid microarray, we observed that Ab-probe interactions comprise a substantial proportion of nonreproducible antibody-based results. This enabled our discovery and capacity to reliably identify nonreproducible Ab-probe interactions (NRIs), as well as our development of a powerful explanatory model ("0-NRI-RI-Hook four-state model") that is mAb concentration-dependent, regardless of specificity, which ultimately shows that both nonspecific interactions and NRIs are not predictable yet certain to happen. Our discoveries challenge the centrality of Ab-Ag interaction specificity data in serology and immunology.

Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods

Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.

Guidelines, Strategies, and Principles for the Directed Evolution of Cross-Reactive Antibodies Using Yeast Surface Display Technology

The ability of cross-reactive antibodies to bind multiple related or unrelated targets derived from different species provides not only superior therapeutic efficacy but also a better assessment of treatment toxicity, thereby facilitating the transition from preclinical models to human clinical studies. This chapter provides some guidelines for the directed evolution of cross-reactive antibodies using yeast surface display technology. Cross-reactive antibodies are initially isolated from a naïve library by combining highly avid magnetic bead separations followed by multiple cycles of flow cytometry sorting. Once initial cross-reactive clones are identified, sequential rounds of mutagenesis and two-pressure selection strategies are applied to engineer cross-reactive antibodies with improved affinity and yet retained or superior cross-reactivity.

Heavy chain sequence-based classifier for the specificity of human antibodies

Antibodies specifically bind to antigens and are an essential part of the immune system. Hence, antibodies are powerful tools in research and diagnostics. High-throughput sequencing technologies have promoted comprehensive profiling of the immune repertoire, which has resulted in large amounts of antibody sequences that remain to be further analyzed. In this study, antibodies were downloaded from IMGT/LIGM-DB and Sequence Read Archive databases. Contributing features from antibody heavy chains were formulated as numerical inputs and fed into an ensemble machine learning classifier to classify the antigen specificity of six classes of antibodies, namely anti-HIV-1, anti-influenza virus, anti-pneumococcal polysaccharide, anti-citrullinated protein, anti-tetanus toxoid and anti-hepatitis B virus. The classifier was validated using cross-validation and a testing dataset. The ensemble classifier achieved a macro-average area under the receiver operating characteristic curve (AUC) of 0.9246 from the 10-fold cross-validation, and 0.9264 for the testing dataset. Among the contributing features, the contribution of the complementarity-determining regions was 53.1% and that of framework regions was 46.9%, and the amino acid mutation rates occupied the first and second ranks among the top five contributing features. The classifier and insights provided in this study could promote the mechanistic study, isolation and utilization of potential therapeutic antibodies.

Immunoaffinity Capillary Electrophoresis in the Era of Proteoforms, Liquid Biopsy and Preventive Medicine: A Potential Impact in the Diagnosis and Monitoring of Disease Progression

Over the years, multiple biomarkers have been used to aid in disease screening, diagnosis, prognosis, and response to therapy. As of late, protein biomarkers are gaining strength in their role for early disease diagnosis and prognosis in part due to the advancements in identification and characterization of a distinct functional pool of proteins known as proteoforms. Proteoforms are defined as all of the different molecular forms of a protein derived from a single gene caused by genetic variations, alternative spliced RNA transcripts and post-translational modifications. Monitoring the structural changes of each proteoform of a particular protein is essential to elucidate the complex molecular mechanisms that guide the course of disease. Clinical proteomics therefore holds the potential to offer further insight into disease pathology, progression, and prevention. Nevertheless, more technologically advanced diagnostic methods are needed to improve the reliability and clinical applicability of proteomics in preventive medicine. In this manuscript, we review the use of immunoaffinity capillary electrophoresis (IACE) as an emerging powerful diagnostic tool to isolate, separate, detect and characterize proteoform biomarkers obtained from liquid biopsy. IACE is an affinity capture-separation technology capable of isolating, concentrating and analyzing a wide range of biomarkers present in biological fluids. Isolation and concentration of target analytes is accomplished through binding to one or more biorecognition affinity ligands immobilized to a solid support, while separation and analysis are achieved by high-resolution capillary electrophoresis (CE) coupled to one or more detectors. IACE has the potential to generate rapid results with significant accuracy, leading to reliability and reproducibility in diagnosing and monitoring disease. Additionally, IACE has the capability of monitoring the efficacy of therapeutic agents by quantifying companion and complementary protein biomarkers. With advancements in telemedicine and artificial intelligence, the implementation of proteoform biomarker detection and analysis may significantly improve our capacity to identify medical conditions early and intervene in ways that improve health outcomes for individuals and populations.

Ensembles in solution as a new paradigm for antibody structure prediction and design

The rise of antibodies as a promising and rapidly growing class of biotherapeutic proteins has motivated numerous studies to characterize and understand antibody structures. In the past decades, the number of antibody crystal structures increased substantially, which revolutionized the atomistic understanding of antibody functions. Even though numerous static structures are known, various biophysical properties of antibodies (i.e., specificity, hydrophobicity and stability) are governed by their dynamic character. Additionally, the importance of high-quality structures in structure–function relationship studies has substantially increased. These structure–function relationship studies have also created a demand for precise homology models of antibody structures, which allow rational antibody design and engineering when no crystal structure is available. Here, we discuss various aspects and challenges in antibody design and extend the paradigm of describing antibodies with only a single static structure to characterizing them as dynamic ensembles in solution.

The biology of ergothioneine, an antioxidant nutraceutical

Ergothioneine (ERG) is an unusual thio-histidine betaine amino acid that has potent antioxidant activities. It is synthesised by a variety of microbes, especially fungi (including in mushroom fruiting bodies) and actinobacteria, but is not synthesised by plants and animals who acquire it via the soil and their diet, respectively. Animals have evolved a highly selective transporter for it, known as solute carrier family 22, member 4 (SLC22A4) in humans, signifying its importance, and ERG may even have the status of a vitamin. ERG accumulates differentially in various tissues, according to their expression of SLC22A4, favouring those such as erythrocytes that may be subject to oxidative stress. Mushroom or ERG consumption seems to provide significant prevention against oxidative stress in a large variety of systems. ERG seems to have strong cytoprotective status, and its concentration is lowered in a number of chronic inflammatory diseases. It has been passed as safe by regulatory agencies, and may have value as a nutraceutical and antioxidant more generally.

Generation of a Peptide Vaccine Candidate against Falciparum Placental Malaria Based on a Discontinuous Epitope

In pregnant women, Plasmodium falciparum-infected red blood cells adhere to the placenta via the parasite protein VAR2CSA. Two vaccine candidates based on VAR2CSA are currently in clinical trials; however, these candidates failed to elicit strain-transcending antibody responses. We previously showed that a cross-reactive monoclonal antibody (3D10) raised against the P. vivax antigen PvDBP targets epitopes in VAR2CSA. We now aim to design a peptide vaccine against VAR2CSA based on the epitope that generated 3D10. We mapped the epitope to subdomain 1 (SD1) of PvDBP and identified a peptide that contained the minimal sequence. However, this peptide did not elicit cross-reactive VAR2CSA antibodies in mice. When tested against a broader, overlapping peptide array spanning SD1, 3D10 in fact recognized a discontinuous epitope consisting of three segments of SD1. These findings presented the challenge to generate this larger structural epitope as a synthetic peptide since it is stabilized by two pairs of disulfide bonds. We overcame this using a synthetic scaffold to conformationally constrain the SD1 peptide and coupled it to keyhole limpet hemocyanin (KLH). The SD1-KLH conjugate elicited antibodies in mice that cross-reacted with VAR2CSA. This strategy successfully recapitulated a discontinuous epitope with a synthetic peptide and represents the first heterologous vaccine candidate against VAR2CSA.

Conformational changes in a Vernier zone region: Implications for antibody dual specificity

Understanding the determinants of antibody specificity is one of the challenging tasks in antibody development. Monospecific antibodies are still dominant in approved antibody therapeutics but there is a significant body of work to show that multispecific antibodies can increase the overall therapeutic effect. Dual-specific or "Two-in-One" antibodies can bind to two different antigens separately with the same antigen-binding site as opposed to bispecifics, which simultaneously bind to two different antigens through separate antigen-binding units. These nonstandard dual-specific antibodies were recently shown to be promising for new antibody-based therapeutics. Here, we physicochemically and structurally analyzed six different antibodies of which two are monospecific and four are dual-specific antibodies derived from monospecific templates to gain insight about dual-specificity determinants. These dual-specific antibodies can target both human epidermal growth factor receptor 2 and vascular endothelial growth factor at different binding affinities. We showed that a particular region of clustered Vernier zone residues might play key roles in gaining dual specificity. While there are minimal intramolecular interactions between a certain Vernier zone region, namely LV4 and LCDR1 of monospecific template, there is a significant structural change and consequently close contact formation between LV4-LCDR1 loops of derived dual-specific antibodies. Although Vernier zone residues were previously shown to be important for humanization applications, they are mostly underestimated in the literature. Here, we also aim to resurrect Vernier zone residues for antibody engineering efforts.

Phosphoglycan-sensitized platform for specific detection of anti-glycan IgG and IgM antibodies in serum

Glycosylphosphatidylinositol anchored proteins (GPI-APs) are natural conjugates in the plasma membrane of eukaryotic cells that result from the attachment of a glycolipid to the C-terminus of many proteins. GPI-APs play a crucial role in cell signaling and adhesion and have implications in health and diseases. GPI-APs and GPIs without protein (free GPIs) are found in abundance on the surface of the protozoan parasite Toxoplasma gondii. The detection of anti-GPI IgG and IgM antibodies allows differentiation between toxoplasmosis patients and healthy individuals using serological assays. However, these methods are limited by their poor efficiency, cross-reactivity and need for sophisticated laboratory equipment and qualified personnel. Here, we established a label-free electrochemical glycobiosensor for the detection of anti-GPI IgG and IgM antibodies in serum from toxoplasmosis seropositive patients. This biosensor uses a synthetic GPI phosphoglycan bioreceptor immobilized on screen-printed gold electrodes through a linear alkane thiol phosphodiester. The antigen-antibody interaction was detected and quantified by electrochemical impedance spectroscopy (EIS). The resultant device showed a linear dynamic range of anti-GPI antibodies in serum ranging from 1.0 to 10.0 IU mL^-1, with a limit of detection of 0.31 IU mL^-1. This method also holds great potential for the detection of IgG antibodies related to other multiple medical conditions characterized by overexpression of antibodies.

Harnessing the Therapeutic Potential of 'Rogue' Antibodies

Therapeutic antibodies have revolutionized modern medicine. At present, antibodies are successfully used for treatment of diverse human diseases, ranging from cancer to viral infections. All clinically approved antibodies rely on highly specific recognition of their target antigen. Antigen-binding promiscuity, binding to autoantigens, and propensity for self-binding (homophilic interaction) are highly undesirable characteristics of antibody drug candidates. Nevertheless, the immune system of all healthy individuals constantly produces and uses large quantities of antibodies that can be classified as inappropriate for development as drugs. Here, I provide arguments that antibodies with 'aberrant' properties have therapeutic potential. They could be useful in certain complex pathological conditions, thus enriching our armamentarium for treatment of human diseases.

Peptides, Antibodies, Peptide Antibodies and More

The applications of peptides and antibodies to multiple targets have emerged as powerful tools in research, diagnostics, vaccine development, and therapeutics. Antibodies are unique since they, in theory, can be directed to any desired target, which illustrates their versatile nature and broad spectrum of use as illustrated by numerous applications of peptide antibodies. In recent years, due to the inherent limitations such as size and physical properties of antibodies, it has been attempted to generate new molecular compounds with equally high specificity and affinity, albeit with relatively low success. Based on this, peptides, antibodies, and peptide antibodies have established their importance and remain crucial reagents in molecular biology.