Biosensor-Enabled Deconvolution of the Avidity-Induced Affinity Enhancement for the SARS-CoV-2 Spike Protein and ACE2 Interaction

Comparison of the ACE2 receptor and monoclonal antibodies immobilisation strategies for the sensitive detection of SARS-CoV-2 variants of concern

Investigation of antibody or receptor immobilisation and binding to the target analyte is essential for the development of effective immunoassays. In our research, we applied the combination of two surface-sensitive methods: spectroscopic ellipsometry and quartz crystal microbalance with dissipation. It enabled quantitative investigation of optical and mechanical properties of formed biomolecule layers consisting of monoclonal antibodies (mAb) or angiotensin-converting enzyme 2 (ACE2) receptors coupled with the Fc fragment, in complex with severe acute respiratory syndrome coronavirus 2 spike Omicron variant (SCoV2-oS). Random and site-directed immobilisation of ACE2 receptor gave 1.8 and 2.4 times higher dry surface mass density compared to random and site-direct mAbs immobilisation, respectively. Therefore, ACE2 had better potential for more sensitive detection of the target analyte SCoV2-oS. However, the binding of SCoV2-oS to site-directed ACE2 resulted in a low 80 ng/cm2 surface mass compared to other samples. Moreover, ΔD/ΔF data revealed two-step binding of SCoV2-oS to ACE2 and mAbs. Furthermore, calculated affinity constants (KD) showed that both ACE2 and mAb have high affinity to SCoV2-oS (in the range of 10-10 to 10-11 M), and their orientation on the surface had only a minor impact on KD values. Our findings in this investigation indicated that ACE2 coupled with the Fc fragment is as effective in the recognition of SARS-CoV-2 as mAbs and it can be successfully applied for the development of immunoassays. Considering SARS-CoV-2 mutates for a better S protein binding to the ACE2 receptor, using ACE2 as a biorecognition element is useful.

Unraveling the Bivalent and Rapid Interactions Between a Multivalent RNA Recognition Motif and RNA: A Kinetic Approach

The kinetics of the interaction between Musashi-1 (MSI1) and RNA have been characterized using surface plasmon resonance biosensor analysis. Truncated variants of human MSI1 encompassing the two homologous RNA recognition motifs (RRM1 and RRM2) in tandem (aa 1-200), and the two RRMs in isolation (aa 1-103 and aa 104-200, respectively) were produced. The proteins were injected over sensor surfaces with immobilized RNA, varying in sequence and length, and with one or two RRM binding motifs. The interactions of the individual RRMs with all RNA variants were well described by a 1:1 interaction model. The interaction between the MSI1 variant encompassing both RRM motifs was bivalent and rapid for all RNA variants. Due to difficulties in fitting this complex data using standard procedures, we devised a new method to quantify the interactions. It revealed that two RRMs in tandem resulted in a significantly longer residence time than a single RRM. It also showed that RNA with double UAG binding motifs and potential hairpin structures forms less stable bivalent complexes with MSI1 than the single UAG motif containing linear RNA. Substituting the UAG binding motif with a CAG sequence resulted in a reduction of the affinity of the individual RRMs, but for MSI1, this reduction was strongly enhanced, demonstrating the importance of bivalency for specificity. This study has provided new insights into the interaction between MSI1 and RNA and an understanding of how individual domains contribute to the overall interaction. It provides an explanation for why many RNA-binding proteins contain dual RRMs.

A dual-target SPR screening system for simultaneous ligand discovery of SARS-CoV-2 spike protein and its receptor ACE2 from Chinese herbs

Traditional Chinese Medicine (TCM) is a supremely valuable resource for the development of drug discovery. Few methods are capable of hunting for potential molecule ligands from TCM towards more than one single protein target. In this study, a novel dual-target surface plasmon resonance (SPR) biosensor was developed to perform targeted compound screening of two key proteins involved in the cellular invasion process of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2): the spike (S) protein receptor binding domain (RBD) and the angiotensin-converting enzyme 2 (ACE2). The screening and identification of active compounds from six Chinese herbs were conducted taking into consideration the multi-component and multi-target nature of Traditional Chinese Medicine (TCM). Puerarin from Radix Puerariae Lobatae was discovered to exhibit specific binding affinity to both S protein RBD and ACE2. The results highlight the efficiency of the dual-target SPR system in drug screening and provide a novel approach for exploring the targeted mechanisms of active components from Chinese herbs for disease treatment.

Rapid Profiling of the Glycosylation Effects on the Binding of SARS-CoV-2 Spike Protein to Angiotensin-Converting Enzyme 2 Using MALDI-MS with High Mass Detection

The spike protein receptor-binding domain (RBD) of SARS-CoV-2 binds directly to angiotensin-converting enzyme 2 (ACE2), mediating the host cell entry of SARS-CoV-2. Both spike protein and ACE2 are highly glycosylated, which can regulate the binding. Here, we utilized high-mass MALDI-MS with chemical cross-linking for profiling the glycosylation effects on the binding between RBD and ACE2. Overall, it was found that ACE2 glycosylation affects the binding more strongly than does RBD glycosylation. The binding affinity was improved after desialylation or partial deglycosylation (N690) of ACE2, while it decreased after degalactosylation. ACE2 can form dimers in solution, which bind more tightly to the RBD than the ACE2 monomers. The ACE2 dimerization and the binding of RBD to dimeric ACE2 can also be improved by the desialylation or deglycosylation of ACE2. Partial deglycosylation of ACE2 increased the dimerization of ACE2 and the binding affinity of RBD and ACE2 by more than a factor of 2, suggesting its high potential for neutralizing SARS-CoV-2. The method described in the work provided a simple way to analyze the protein-protein interaction without sample purification. It can be widely used for rapid profiling of glycosylation effects on protein-protein interaction for glycosylation-related diseases and the study of multiple interactions between protein and protein aggregates in a single system.

Mass spectrometry-based methods to characterize highly heterogeneous biopharmaceuticals, vaccines, and nonbiological complex drugs at the intact-mass level

The intact-mass MS measurements are becoming increasingly popular in characterization of a range of biopolymers, especially those of interest to biopharmaceutical industry. However, as the complexity of protein therapeutics and other macromolecular medicines increases, the new challenges arise, one of which is the high levels of structural heterogeneity that are frequently exhibited by such products. The very notion of the molecular mass measurement loses its clear and intuitive meaning when applied to an extremely heterogenous system that cannot be characterized by a unique mass, but instead requires that a mass distribution be considered. Furthermore, convoluted mass distributions frequently give rise to unresolved ionic signal in mass spectra, from which little-to-none meaningful information can be extracted using standard approaches that work well for homogeneous systems. However, a range of technological advances made in the last decade, such as the hyphenation of intact-mass MS measurements with front-end separations, better integration of ion mobility in MS workflows, development of an impressive arsenal of gas-phase ion chemistry tools to supplement MS methods, as well as the revival of the charge detection MS and its triumphant entry into the field of bioanalysis already made impressive contributions towards addressing the structural heterogeneity challenge. An overview of these techniques is accompanied by critical analysis of the strengths and weaknesses of different approaches, and a brief overview of their applications to specific classes of biopharmaceutical products, vaccines, and nonbiological complex drugs.

Real-time detection of virus antibody interaction by label-free common-path interferometry

Viruses have a profound influence on all forms of life, motivating the development of rapid and minimally invasive methods for virus detection. In this study, we present a novel methodology that enables quantitative measurement of the interaction between individual biotic nanoparticles and antibodies in solution. Our approach employs a label-free, full-field common-path interferometric technique to detect and track biotic nanoparticles and their interactions with antibodies. It is based on the interferometric detection of light scattered by viruses in aqueous samples for the detection of individual viruses. We employ single-particle tracking analysis to characterize the size and properties of the detected nanoparticles, and to monitor the changes in their diffusive mobility resulting from interactions. To validate the sensitivity of our detection approach, we distinguish between particles having identical diffusion coefficients but different scattering signals, using DNA-loaded and DNA-devoid capsids of the Escherichia coli T5 virus phage. In addition, we have been able to monitor, in real time, the interaction between the bacteriophage T5 and purified antibodies targeting its major capsid protein pb8, as well as between the phage SPP1 and nonpurified anti-SPP1 antibodies present in rabbit serum. Interestingly, these virus-antibody interactions are observed within minutes. Finally, by estimating the number of viral particles interacting with antibodies at different concentrations, we successfully quantify the dissociation constant K d of the virus-antibody reaction using single-particle tracking analysis.

Multivalent IgM scaffold enhances the therapeutic potential of variant-agnostic ACE2 decoys against SARS-CoV-2

As immunological selection for escape mutants continues to give rise to future SARS-CoV-2 variants, novel universal therapeutic strategies against ACE2-dependent viruses are needed. Here we present an IgM-based decavalent ACE2 decoy that has variant-agnostic efficacy. In immuno-, pseudovirus, and live virus assays, IgM ACE2 decoy had potency comparable or superior to leading SARS-CoV-2 IgG-based mAb therapeutics evaluated in the clinic, which were variant-sensitive in their potency. We found that increased ACE2 valency translated into increased apparent affinity for spike protein and superior potency in biological assays when decavalent IgM ACE2 was compared to tetravalent, bivalent, and monovalent ACE2 decoys. Furthermore, a single intranasal dose of IgM ACE2 decoy at 1 mg/kg conferred therapeutic benefit against SARS-CoV-2 Delta variant infection in a hamster model. Taken together, this engineered IgM ACE2 decoy represents a SARS-CoV-2 variant-agnostic therapeutic that leverages avidity to drive enhanced target binding, viral neutralization, and in vivo respiratory protection against SARS-CoV-2.

A Framework for Biosensors Assisted by Multiphoton Effects and Machine Learning

The ability to interpret information through automatic sensors is one of the most important pillars of modern technology. In particular, the potential of biosensors has been used to evaluate biological information of living organisms, and to detect danger or predict urgent situations in a battlefield, as in the invasion of SARS-CoV-2 in this era. This work is devoted to describing a panoramic overview of optical biosensors that can be improved by the assistance of nonlinear optics and machine learning methods. Optical biosensors have demonstrated their effectiveness in detecting a diverse range of viruses. Specifically, the SARS-CoV-2 virus has generated disturbance all over the world, and biosensors have emerged as a key for providing an analysis based on physical and chemical phenomena. In this perspective, we highlight how multiphoton interactions can be responsible for an enhancement in sensibility exhibited by biosensors. The nonlinear optical effects open up a series of options to expand the applications of optical biosensors. Nonlinearities together with computer tools are suitable for the identification of complex low-dimensional agents. Machine learning methods can approximate functions to reveal patterns in the detection of dynamic objects in the human body and determine viruses, harmful entities, or strange kinetics in cells.

Plasmonic Approaches for the Detection of SARS-CoV-2 Viral Particles

The ongoing highly contagious Coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), underlines the fundamental position of diagnostic testing in outbreak control by allowing a distinction of the infected from the non-infected people. Diagnosis of COVID-19 remains largely based on reverse transcription PCR (RT-PCR), identifying the genetic material of the virus. Molecular testing approaches have been largely proposed in addition to infectivity testing of patients via sensing the presence of viral particles of SARS-CoV-2 specific structural proteins, such as the spike glycoproteins (S1, S2) and the nucleocapsid (N) protein. While the S1 protein remains the main target for neutralizing antibody treatment upon infection and the focus of vaccine and therapeutic design, it has also become a major target for the development of point-of care testing (POCT) devices. This review will focus on the possibility of surface plasmon resonance (SPR)-based sensing platforms to convert the receptor-binding event of SARS-CoV-2 viral particles into measurable signals. The state-of-the-art SPR-based SARS-CoV-2 sensing devices will be provided, and highlights about the applicability of plasmonic sensors as POCT for virus particle as well as viral protein sensing will be discussed.

Kinetics and interaction studies of anti-tetraspanin antibodies and ICAM-1 with extracellular vesicle subpopulations using continuous flow quartz crystal microbalance biosensor

Continuous flow quartz crystal microbalance (QCM) was utilized to study binding kinetics between EV subpopulations (exomere- and exosome-sized EVs) and four affinity ligands: monoclonal antibodies against tetraspanins (anti-CD9, anti-CD63, and anti-CD81) and recombinant intercellular adhesion molecule-1 (ICAM-1) or CD54 protein). High purity CD9⁺, CD63⁺, and CD81⁺ EV subpopulations of <50 nm exomeres and 50-80 nm exosomes were isolated and fractionated using our recently developed on-line coupled immunoaffinity chromatography - asymmetric flow field-flow fractionation system. Adaptive Interaction Distribution Algorithm (AIDA), specifically designed for the analysis of complex biological interactions, was used with a four-step procedure for reliable estimation of the degree of heterogeneity in rate constant distributions. Interactions between exomere-sized EVs and anti-tetraspanin antibodies demonstrated two interaction sites with comparable binding kinetics and estimated dissociation constants K_d ranging from nM to fM. Exomeres exhibited slightly higher affinity compared to exosomes. The highest affinity with anti-tetraspanin antibodies was achieved with CD63⁺ EVs. The interaction of EV subpopulations with ICAM-1 involved in cell internalization of EVs was also investigated. EV - ICAM-1 interaction was also of high affinity (nM to pM range) with overall lower affinity compared to the interactions of anti-tetraspanin antibodies and EVs. Our findings proved that QCM is a valuable label-free tool for kinetic studies with limited sample concentration, and that advanced algorithms, such as AIDA, are crucial for proper determination of kinetic heterogeneity. To the best of our knowledge, this is the first kinetic study on the interaction between plasma-derived EV subpopulations and anti-tetraspanin antibodies and ICAM-1.