Position-Specific Enrichment Ratio Matrix scores predict antibody variant properties from deep sequencing data.

MOTIVATION: Deep sequencing of antibody and related protein libraries after phage or yeast-surface display sorting is widely used to identify variants with increased affinity, specificity, and/or improvements in key biophysical properties. Conventional approaches for identifying optimal variants typically use the frequencies of observation in enriched libraries or the corresponding enrichment ratios. However, these approaches disregard the vast majority of deep sequencing data and often fail to identify the best variants in the libraries. RESULTS: Here, we present a method, Position-Specific Enrichment Ratio Matrix (PSERM) scoring, that uses entire deep sequencing datasets from pre- and post-selections to score each observed protein variant. The PSERM scores are the sum of the site-specific enrichment ratios observed at each mutated position. We find that PSERM scores are much more reproducible and correlate more strongly with experimentally measured properties than frequencies or enrichment ratios, including for multiple antibody properties (affinity and non-specific binding) for a clinical-stage antibody (emibetuzumab). We expect that this method will be broadly applicable to diverse protein engineering campaigns. AVAILABILITY AND IMPLEMENTATION: All deep sequencing datasets and code to perform the analyses presented within are available via https://github.com/Tessier-Lab-UMich/PSERM_paper.

Characterization of Pairs of Toxic and Nontoxic Misfolded Protein Oligomers Elucidates the Structural Determinants of Oligomer Toxicity in Protein Misfolding Diseases.

The aberrant misfolding and aggregation of peptides and proteins into amyloid aggregates occurs in over 50 largely incurable protein misfolding diseases. These pathologies include Alzheimer's and Parkinson's diseases, which are global medical emergencies owing to their prevalence in increasingly aging populations worldwide. Although the presence of mature amyloid aggregates is a hallmark of such neurodegenerative diseases, misfolded protein oligomers are increasingly recognized as of central importance in the pathogenesis of many of these maladies. These oligomers are small, diffusible species that can form as intermediates in the amyloid fibril formation process or be released by mature fibrils after they are formed. They have been closely associated with the induction of neuronal dysfunction and cell death. It has proven rather challenging to study these oligomeric species because of their short lifetimes, low concentrations, extensive structural heterogeneity, and challenges associated with producing stable, homogeneous, and reproducible populations. Despite these difficulties, investigators have developed protocols to produce kinetically, chemically, or structurally stabilized homogeneous populations of protein misfolded oligomers from several amyloidogenic peptides and proteins at experimentally ameneable concentrations. Furthermore, procedures have been established to produce morphologically similar but structurally distinct oligomers from the same protein sequence that are either toxic or nontoxic to cells. These tools offer unique opportunities to identify and investigate the structural determinants of oligomer toxicity by a close comparative inspection of their structures and the mechanisms of action through which they cause cell dysfunction.This Account reviews multidisciplinary results, including from our own groups, obtained by combining chemistry, physics, biochemistry, cell biology, and animal models for pairs of toxic and nontoxic oligomers. We describe oligomers comprised of the amyloid-ß peptide, which underlie Alzheimer's disease, and α-synuclein, which are associated with Parkinson's disease and other related neurodegenerative pathologies, collectively known as synucleinopathies. Furthermore, we also discuss oligomers formed by the 91-residue N-terminal domain of [NiFe]-hydrogenase maturation factor from E. coli, which we use as a model non-disease-related protein, and by an amyloid stretch of Sup35 prion protein from yeast. These oligomeric pairs have become highly useful experimental tools for studying the molecular determinants of toxicity characteristic of protein misfolding diseases. Key properties have been identified that differentiate toxic from nontoxic oligomers in their ability to induce cellular dysfunction. These characteristics include solvent-exposed hydrophobic regions, interactions with membranes, insertion into lipid bilayers, and disruption of plasma membrane integrity. By using these properties, it has been possible to rationalize in model systems the responses to pairs of toxic and nontoxic oligomers. Collectively, these studies provide guidance for the development of efficacious therapeutic strategies to target rationally the cytotoxicity of misfolded protein oligomers in neurodegenerative conditions.

Mutational analysis of SARS-CoV-2 variants of concern reveals key tradeoffs between receptor affinity and antibody escape.

SARS-CoV-2 variants with enhanced transmissibility represent a serious threat to global health. Here we report machine learning models that can predict the impact of receptor-binding domain (RBD) mutations on receptor (ACE2) affinity, which is linked to infectivity, and escape from human serum antibodies, which is linked to viral neutralization. Importantly, the models predict many of the known impacts of RBD mutations in current and former Variants of Concern on receptor affinity and antibody escape as well as novel sets of mutations that strongly modulate both properties. Moreover, these models reveal key opposing impacts of RBD mutations on transmissibility, as many sets of RBD mutations predicted to increase antibody escape are also predicted to reduce receptor affinity and vice versa. These models, when used in concert, capture the complex impacts of SARS-CoV-2 mutations on properties linked to transmissibility and are expected to improve the development of next-generation vaccines and biotherapeutics.

Rational affinity maturation of anti-amyloid antibodies with high conformational and sequence specificity.

The aggregation of amyloidogenic polypeptides is strongly linked to several neurodegenerative disorders, including Alzheimer's and Parkinson's diseases. Conformational antibodies that selectively recognize protein aggregates are leading therapeutic agents for selectively neutralizing toxic aggregates, diagnostic and imaging agents for detecting disease, and biomedical reagents for elucidating disease mechanisms. Despite their importance, it is challenging to generate high-quality conformational antibodies in a systematic and site-specific manner due to the properties of protein aggregates (hydrophobic, multivalent, and heterogeneous) and limitations of immunization (uncontrolled antigen presentation and immunodominant epitopes). Toward addressing these challenges, we have developed a systematic directed evolution procedure for affinity maturing antibodies against Alzheimer's Aß fibrils and selecting variants with strict conformational and sequence specificity. We first designed a library based on a lead conformational antibody by sampling combinations of amino acids in the antigen-binding site predicted to mediate high antibody specificity. Next, we displayed this library on the surface of yeast, sorted it against Aß42 aggregates, and identified promising clones using deep sequencing. The resulting antibodies displayed similar or higher affinities than clinical-stage Aß antibodies (aducanumab and crenezumab). Moreover, the affinity-matured antibodies retained high conformational specificity for Aß aggregates, as observed for aducanumab and unlike crenezumab. Notably, the affinity-maturated antibodies displayed extremely low levels of nonspecific interactions, as observed for crenezumab and unlike aducanumab. We expect that our systematic methods for generating antibodies with unique combinations of desirable properties will improve the generation of high-quality conformational antibodies specific for diverse types of aggregated conformers.

Rapid and Quantitative In Vitro Evaluation of SARS-CoV-2 Neutralizing Antibodies and Nanobodies.

Neutralizing monoclonal antibodies and nanobodies have shown promising results as potential therapeutic agents for COVID-19. Identifying such antibodies and nanobodies requires evaluating the neutralization activity of a large number of lead molecules via biological assays, such as the virus neutralization test (VNT). These assays are typically time-consuming and demanding on-lab facilities. Here, we present a rapid and quantitative assay that evaluates the neutralizing efficacy of an antibody or nanobody within 1.5 h, does not require BSL-2 facilities, and consumes only 8 µL of a low concentration (ng/mL) sample for each assay run. We tested the human angiotensin-converting enzyme 2 (ACE2) binding inhibition efficacy of seven antibodies and eight nanobodies and verified that the IC50 values of our assay are comparable with those from SARS-CoV-2 pseudovirus neutralization tests. We also found that our assay could evaluate the neutralizing efficacy against three widespread SARS-CoV-2 variants. We observed increased affinity of these variants for ACE2, including the ß and γ variants. Finally, we demonstrated that our assay enables the rapid identification of an immune-evasive mutation of the SARS-CoV-2 spike protein, utilizing a set of nanobodies with known binding epitopes.

Antibodies with Weakly Basic Isoelectric Points Minimize Trade-offs between Formulation and Physiological Colloidal Properties.

The widespread interest in antibody therapeutics has led to much focus on identifying antibody candidates with favorable developability properties. In particular, there is broad interest in identifying antibody candidates with highly repulsive self-interactions in standard formulations (e.g., low ionic strength buffers at pH 5-6) for high solubility and low viscosity. Likewise, there is also broad interest in identifying antibody candidates with low levels of non-specific interactions in physiological solution conditions (PBS, pH 7.4) to promote favorable pharmacokinetic properties. To what extent antibodies that possess both highly repulsive self-interactions in standard formulations and weak non-specific interactions in physiological solution conditions can be systematically identified remains unclear and is a potential impediment to successful therapeutic drug development. Here, we evaluate these two properties for 42 IgG1 variants based on the variable fragments (Fvs) from four clinical-stage antibodies and complementarity-determining regions from 10 clinical-stage antibodies. Interestingly, we find that antibodies with the strongest repulsive self-interactions in a standard formulation (pH 6 and 10 mM histidine) display the strongest non-specific interactions in physiological solution conditions. Conversely, antibodies with the weakest non-specific interactions under physiological conditions display the least repulsive self-interactions in standard formulations. This behavior can be largely explained by the antibody isoelectric point, as highly basic antibodies that are highly positively charged under standard formulation conditions (pH 5-6) promote repulsive self-interactions that mediate high colloidal stability but also mediate strong non-specific interactions with negatively charged biomolecules at physiological pH and vice versa for antibodies with negatively charged Fv regions. Therefore, IgG1s with weakly basic isoelectric points between 8 and 8.5 and Fv isoelectric points between 7.5 and 9 typically display the best combinations of strong repulsive self-interactions and weak non-specific interactions. We expect that these findings will improve the identification and engineering of antibody candidates with drug-like biophysical properties.

Directed evolution of conformation-specific antibodies for sensitive detection of polypeptide aggregates in therapeutic drug formulations.

Biologics such as peptides and proteins possess a number of attractive attributes that make them particularly valuable as therapeutics, including their high activity, high specificity, and low toxicity. However, one of the key challenges associated with this class of drugs is their propensity to aggregate. Given the safety and immunogenicity concerns related to polypeptide aggregates, it is particularly important to sensitively detect aggregates in therapeutic drug formulations as part of the quality control process. Here, we report the development of conformation-specific antibodies that recognize polypeptide aggregates composed of a GLP-1 receptor agonist (liraglutide) and their integration into a sensitive immunoassay for detecting liraglutide amyloid fibrils. We sorted single-chain antibody libraries against liraglutide fibrils using yeast surface display and magnetic-activated cell sorting, and identified several antibodies with high conformational specificity. Interestingly, these antibodies cross-react with amyloid fibrils formed by several other polypeptides, revealing that they recognize molecular features common to different types of fibrils. Moreover, we find that our immunoassay using these antibodies is >50-fold more sensitive than the conventional method for detecting liraglutide aggregation (Thioflavin T fluorescence). We expect that our systematic approach for generating a sensitive, aggregate-specific immunoassay can be readily extended to other biologics to improve the quality and safety of formulated drug products.

Ultradilute Measurements of Self-Association for the Identification of Antibodies with Favorable High-Concentration Solution Properties.

There is significant interest in formulating antibody therapeutics as concentrated liquid solutions, but early identification of developable antibodies with optimal manufacturability, stability, and delivery attributes remains challenging. Traditional methods of identifying developable mAbs with low self-association in common antibody formulations require relatively concentrated protein solutions (>1 mg/mL), and this single challenge has frustrated early-stage and large-scale identification of antibody candidates with drug-like colloidal properties. Here, we describe charge-stabilized self-interaction nanoparticle spectroscopy (CS-SINS), an affinity-capture nanoparticle assay that measures colloidal self-interactions at ultradilute antibody concentrations (0.01 mg/mL), and is predictive of antibody developability issues of high viscosity and opalescence that manifest at four orders of magnitude higher concentrations (>100 mg/mL). CS-SINS enables large-scale, high-throughput selection of developable antibodies during early discovery.

Nature-inspired design and evolution of anti-amyloid antibodies.

Antibodies that recognize amyloidogenic aggregates with high conformational and sequence specificity are important for detecting and potentially treating a wide range of neurodegenerative disorders, including Alzheimer's and Parkinson's diseases. However, these types of antibodies are challenging to generate because of the large size, hydrophobicity, and heterogeneity of protein aggregates. To address this challenge, we developed a method for generating antibodies specific for amyloid aggregates. First, we grafted amyloidogenic peptide segments from the target polypeptide [Alzheimer's amyloid-ß (Aß) peptide] into the complementarity-determining regions (CDRs) of a stable antibody scaffold. Next, we diversified the grafted and neighboring CDR sites using focused mutagenesis to sample each WT or grafted residue, as well as one to five of the most commonly occurring amino acids at each site in human antibodies. Finally, we displayed these antibody libraries on the surface of yeast cells and selected antibodies that strongly recognize Aß-amyloid fibrils and only weakly recognize soluble Aß. We found that this approach enables the generation of monovalent and bivalent antibodies with nanomolar affinity for Aß fibrils. These antibodies display high conformational and sequence specificity as well as low levels of nonspecific binding and recognize a conformational epitope at the extreme N terminus of human Aß. We expect that this systematic approach will be useful for generating antibodies with conformational and sequence specificity against a wide range of peptide and protein aggregates associated with neurodegenerative disorders.

Toward in silico CMC: An industrial collaborative approach to model-based process development.

The Third Modeling Workshop focusing on bioprocess modeling was held in Kenilworth, NJ in May 2019. A summary of these Workshop proceedings is captured in this manuscript. Modeling is an active area of research within the biotechnology community, and there is a critical need to assess the current state and opportunities for continued investment to realize the full potential of models, including resource and time savings. Beyond individual presentations and topics of novel interest, a substantial portion of the Workshop was devoted toward group discussions of current states and future directions in modeling fields. All scales of modeling, from biophysical models at the molecular level and up through large scale facility and plant modeling, were considered in these discussions and are summarized in the manuscript. Model life cycle management from model development to implementation and sustainment are also considered for different stages of clinical development and commercial production. The manuscript provides a comprehensive overview of bioprocess modeling while suggesting an ideal future state with standardized approaches aligned across the industry.

Physicochemical Rules for Identifying Monoclonal Antibodies with Drug-like Specificity.

The ability of antibodies to recognize their target antigens with high specificity is fundamental to their natural function. Nevertheless, therapeutic antibodies display variable and difficult-to-predict levels of nonspecific and self-interactions that can lead to various drug development challenges, including antibody aggregation, abnormally high viscosity, and rapid antibody clearance. Here we report a method for predicting the overall specificity of antibodies in terms of their relative risk for displaying high levels of nonspecific or self-interactions at physiological conditions. We find that individual and combined sets of chemical rules that limit the maximum and minimum numbers of certain solvent-exposed amino acids in antibody variable regions are strong predictors of specificity for large panels of preclinical and clinical-stage antibodies. We also demonstrate how the chemical rules can be used to identify sites that mediate nonspecific interactions in suboptimal antibodies and guide the design of targeted sublibraries that yield variants with high antibody specificity. These findings can be readily used to improve the selection and engineering of antibodies with drug-like specificity.

Toward Drug-Like Multispecific Antibodies by Design.

The success of antibody therapeutics is strongly influenced by their multifunctional nature that couples antigen recognition mediated by their variable regions with effector functions and half-life extension mediated by a subset of their constant regions. Nevertheless, the monospecific IgG format is not optimal for many therapeutic applications, and this has led to the design of a vast number of unique multispecific antibody formats that enable targeting of multiple antigens or multiple epitopes on the same antigen. Despite the diversity of these formats, a common challenge in generating multispecific antibodies is that they display suboptimal physical and chemical properties relative to conventional IgGs and are more difficult to develop into therapeutics. Here we review advances in the design and engineering of multispecific antibodies with drug-like properties, including favorable stability, solubility, viscosity, specificity and pharmacokinetic properties. We also highlight emerging experimental and computational methods for improving the next generation of multispecific antibodies, as well as their constituent antibody fragments, with natural IgG-like properties. Finally, we identify several outstanding challenges that need to be addressed to increase the success of multispecific antibodies in the clinic.

Sensitive detection of glucagon aggregation using amyloid fibril-specific antibodies.

Sensitive detection of protein aggregates is important for evaluating the quality of biopharmaceuticals and detecting misfolded proteins in several neurodegenerative diseases. However, it is challenging to detect extremely low concentrations (<10 ppm) of aggregated protein in the presence of high concentrations of soluble protein. Glucagon, a peptide hormone used in the treatment of extreme hypoglycemia, is aggregation-prone and forms amyloid fibrils. Detection of glucagon fibrils using conformation-specific antibodies is an attractive approach for identifying such aggregates during process and formulation development. Therefore, we have used yeast surface display and magnetic-activated cell sorting to sort single-chain antibody libraries to identify antibody variants with high conformational specificity for glucagon fibrils. Notably, we find several high-affinity antibodies that display excellent selectivity for glucagon fibrils, and we have integrated these antibodies into a sensitive immunoassay. Surprisingly, the sensitivity of our assay-which involves direct (nonantibody mediated) glucagon immobilization in microtiter plates-can be significantly enhanced by pretreating the microtiter plates with various types of globular proteins before glucagon immobilization. Moreover, increased total concentrations of glucagon peptide also significantly improve the sensitivity of our assay, which appears to be due to the strong seeding activity of immobilized fibrils at high glucagon concentrations. Our final assay is highly sensitive (fibril detection limit of ~0.5-1 ppm) and is >20 times more sensitive than detection using a conventional, amyloid-specific fluorescent dye (Thioflavin T). We expect that this type of sensitive immunoassay can be readily integrated into the drug development process to improve the generation of safe and potent peptide therapeutics.

Deamidation Can Compromise Antibody Colloidal Stability and Enhance Aggregation in a pH-Dependent Manner.

Monoclonal antibodies must be both chemically and physically stable to be developed into safe and effective drugs. Although there has been considerable progress in separately understanding the molecular determinants of antibody chemical and physical stability, it remains poorly understood how defects in one property (e.g., chemical stability) impact the other property (e.g., physical stability). Here, we have investigated the impact of a common chemical modification (deamidation) on the physical stability of two monoclonal antibodies as a function of pH (from pH 3.8 to 7.4). Interestingly, we find that deamidation has significant, antibody-specific impacts on physical stability at low pH values that are common during antibody purification. Deamidation causes increases in self-association and/or aggregation at low pH (3.8), and a key contributor to this behavior appears to be deamidation-dependent increases in antibody hydrophobicity at low pH. Our findings highlight pH-dependent impacts of deamidation on antibody colloidal stability and aggregation, which are important to understand in order to improve the development and production of potent antibody therapeutics with high chemical and physical stabilities.

Arginine mutations in antibody complementarity-determining regions display context-dependent affinity/specificity trade-offs.

Antibodies commonly accumulate charged mutations in their complementarity-determining regions (CDRs) during affinity maturation to enhance electrostatic interactions. However, charged mutations can mediate non-specific interactions, and it is unclear to what extent CDRs can accumulate charged residues to increase antibody affinity without compromising specificity. This is especially concerning for positively charged CDR mutations that are linked to antibody polyspecificity. To better understand antibody affinity/specificity trade-offs, we have selected single-chain antibody fragments specific for the negatively charged and hydrophobic Alzheimer's amyloid ß peptide using weak and stringent selections for antibody specificity. Antibody variants isolated using weak selections for specificity were enriched in arginine CDR mutations and displayed low specificity. Alanine-scanning mutagenesis revealed that the affinities of these antibodies were strongly dependent on their arginine mutations. Antibody variants isolated using stringent selections for specificity were also enriched in arginine CDR mutations, but these antibodies possessed significant improvements in specificity. Importantly, the affinities of the most specific antibodies were much less dependent on their arginine mutations, suggesting that over-reliance on arginine for affinity leads to reduced specificity. Structural modeling and molecular simulations reveal unique hydrophobic environments near the arginine CDR mutations. The more specific antibodies contained arginine mutations in the most hydrophobic portions of the CDRs, whereas the less specific antibodies contained arginine mutations in more hydrophilic regions. These findings demonstrate that arginine mutations in antibody CDRs display context-dependent impacts on specificity and that affinity/specificity trade-offs are governed by the relative contribution of arginine CDR residues to the overall antibody affinity.

Biophysical and Sequence-Based Methods for Identifying Monovalent and Bivalent Antibodies with High Colloidal Stability.

In vitro antibody discovery and/or affinity maturation are often performed using antibody fragments (Fabs), but most monovalent Fabs are reformatted as bivalent IgGs (monoclonal antibodies, mAbs) for therapeutic applications. One problem related to reformatting antibodies is that the bivalency of mAbs can lead to increased antibody self-association and poor biophysical properties (e.g., reduced antibody solubility and increased viscosity). Therefore, it is important to identify monovalent Fabs early in the discovery and/or optimization process that will display favorable biophysical properties when reformatted as bivalent mAbs. Here we demonstrate a facile approach for evaluating Fab self-association in a multivalent assay format that is capable of identifying antibodies with low self-association and favorable colloidal properties when reformatted as bivalent mAbs. Our approach (self-interaction nanoparticle spectroscopy, SINS) involves immobilizing Fabs on gold nanoparticles in a multivalent format (multiple Fabs per nanoparticle) and evaluating their self-association behavior via shifts in the plasmon wavelength or changes in the absorbance values. Importantly, we find that SINS measurements of Fab self-association are correlated with self-interaction measurements of bivalent mAbs and are useful for identifying antibodies with favorable biophysical properties. Moreover, the significant differences in the levels of self-association detected for Fabs and mAbs with similar frameworks can be largely explained by the physicochemical properties of the complementarity-determining regions (CDRs). Comparison of the properties of the CDRs in this study relative to those of approved therapeutic antibodies reveals several key factors (net charge, fraction of charged residues, and presence of self-interaction motifs) that strongly influence antibody self-association behavior. Increased positive charge in the CDRs was observed to correlate with increased risk of high self-association for the mAbs in this study and clinical-stage antibodies. We expect that these findings will be useful for improving the development of therapeutic antibodies that are well suited for high concentration applications.

Understanding and overcoming trade-offs between antibody affinity, specificity, stability and solubility.

The widespread use of monoclonal antibodies for therapeutic applications has led to intense interest in optimizing several of their natural properties (affinity, specificity, stability, solubility and effector functions) as well as introducing non-natural activities (bispecificity and cytotoxicity mediated by conjugated drugs). A common challenge during antibody optimization is that improvements in one property (e.g., affinity) can lead to deficits in other properties (e.g., stability). Here we review recent advances in understanding trade-offs between different antibody properties, including affinity, specificity, stability and solubility. We also review new approaches for co-optimizing multiple antibody properties and discuss how these methods can be used to rapidly and systematically generate antibodies for a wide range of applications.

Glycan Determinants of Heparin-Tau Interaction.

Tau aggregates into paired helical filaments within neurons, a pathological hallmark of Alzheimer's disease. Heparin promotes tau aggregation and recently has been shown to be involved in the cellular uptake of tau aggregates. Although the tau-heparin interaction has been extensively studied, little is known about the glycan determinants of this interaction. Here, we used surface plasmon resonance (SPR) and NMR spectroscopy to characterize the interaction between two tau fragments, K18 and K19, and several polysaccharides, including heparin, heparin oligosaccharides, chemically modified heparin, and related glycans. Using a heparin-immobilized chip, SPR revealed that tau K18 and K19 bind heparin with a KD of 0.2 and 70 µM, respectively. In SPR competition experiments, N-desulfation and 2-O-desulfation had no effect on heparin binding to K18, whereas 6-O-desulfation severely reduced binding, suggesting a critical role for 6-O-sulfation in the tau-heparin interaction. The tau-heparin interaction became stronger with longer-chain heparin oligosaccharides. As expected for an electrostatics-driven interaction, a moderate amount of salt (0.3 M NaCl) abolished binding. NMR showed the largest chemical-shift perturbation (CSP) in R2 in tau K18, which was absent in K19, revealing differential binding sites in K18 and K19 to heparin. Dermatan sulfate binding produced minimal CSP, whereas dermatan disulfate, with the additional 6-O-sulfo group, induced much larger CSP. 2-O-desulfated heparin induced much larger CSP in K18 than 6-O-desulfated heparin. Our data demonstrate a crucial role for the 6-O-sulfo group in the tau-heparin interaction, which to our knowledge has not been reported before.

Design and Optimization of Anti-amyloid Domain Antibodies Specific for ß-Amyloid and Islet Amyloid Polypeptide.

Antibodies with conformational specificity are important for detecting and interfering with polypeptide aggregation linked to several human disorders. We are developing a motif-grafting approach for designing lead antibody candidates specific for amyloid-forming polypeptides such as the Alzheimer peptide (Aß). This approach involves grafting amyloidogenic peptide segments into the complementarity-determining regions (CDRs) of single-domain (VH) antibodies. Here we have investigated the impact of polar mutations inserted at the edges of a large hydrophobic Aß42 peptide segment (Aß residues 17-42) in CDR3 on the solubility and conformational specificity of the corresponding VH domains. We find that VH expression and solubility are strongly enhanced by introducing multiple negatively charged or asparagine residues at the edges of CDR3, whereas other polar mutations are less effective (glutamine and serine) or ineffective (threonine, lysine, and arginine). Moreover, Aß VH domains with negatively charged CDR3 mutations show significant preference for recognizing Aß fibrils relative to Aß monomers, whereas the same VH domains with other polar CDR3 mutations recognize both Aß conformers. We observe similar behavior for a VH domain grafted with a large hydrophobic peptide from islet amyloid polypeptide (residues 8-37) that contains negatively charged mutations at the edges of CDR3. These findings highlight the sensitivity of antibody binding and solubility to residues at the edges of CDRs, and provide guidelines for designing other grafted antibody fragments with hydrophobic binding loops.

Intrahippocampal administration of a domain antibody that binds aggregated amyloid-ß reverses cognitive deficits produced by diet-induced obesity.

BACKGROUND: The prevalence of high fat diets (HFD), diet-induced obesity (DIO) and Type 2 diabetes continues to increase, associated with cognitive impairment in both humans and rodent models. Mechanisms transducing these impairments remain largely unknown: one possibility is that a common mechanism may be involved in the cognitive impairment seen in obese and/or diabetic states and in dementia, specifically Alzheimer's disease (AD). DIO is well established as a risk factor for development of AD. Oligomeric amyloid-ß (Aß) is neurotoxic, and we showed that intrahippocampal oligomeric Aß produces cognitive and metabolic dysfunction similar to that seen in DIO or diabetes. Moreover, animal models of DIO show elevated brain Aß, a hallmark of AD, suggesting that this may be one source of cognitive impairment in both conditions. METHODS: Intrahippocampal administration of a novel anti-Aß domain antibody for aggregated Aß, or a control domain antibody, to control or HFD-induced DIO rats. Spatial learning measured in a conditioned contextual fear (CCF) task after domain antibody treatment; postmortem, hippocampal NMDAR and AMPAR were measured. RESULTS: DIO caused impairment in CCF, and this impairment was eliminated by intrahippocampal administration of the active domain antibody. Measurement of hippocampal proteins suggests that DIO causes dysregulation of hippocampal AMPA receptors, which is also reversed by acute domain antibody administration. CONCLUSIONS: Our findings support the concept that oligomeric Aß within the hippocampus of DIO animals may not only be a risk factor for development of AD but may also cause cognitive impairment before the development of dementia. GENERAL SIGNIFICANCE AND INTEREST: Our work integrates the engineering of domain antibodies with conformational- and sequence-specificity for oligomeric amyloid beta with a clinically relevant model of diet-induced obesity in order to demonstrate not only the pervasive effects of obesity on several aspects of brain biochemistry and behavior, but also the bioengineering of a successful treatment against the long-term detrimental effects of a pre-diabetic state on the brain. We show for the first time that cognitive impairment linked to obesity and/or insulin resistance may be due to early accumulation of oligomeric beta-amyloid in the brain, and hence may represent a pre-Alzheimer's state.