Estimation of analyte concentration by surface plasmon resonance-based biosensing using parameter identification techniques

Kinetic characterization of SPR-based biomarker assays enables quality control, calibration free measurements and robust optimization for clinical application

Biomarker measurements are essential for the early diagnosis of complex diseases. However, many current biomarker assays lack sensitivity and multiplexing capacity, work in a narrow detection range and importantly lack real time quality control opportunities, which hampers clinical translation. In this paper, we demonstrate a toolbox to kinetically characterize a biomarker measurement assay using Surface Plasmon Resonance imaging (SPRi) with ample opportunities for real time quality control by exploiting quantitative descriptions of the various biomolecular interactions. We show an accurate prediction of SPRi measurements at both low and high concentrations of various analytes with deviations <5% between actual measurements and predicted measurement. The biphasic binding sites model was accurate for fitting the experimental curves and enables optimal detection of heterophilic antibodies, cross-reactivity, spotting irregularities and/or other confounders. The toolbox can also be used to create a (simulated) calibration curve, enabling calibration-free measurements with good recovery, it allows for easy assay optimizations, and could help bridge the gap to bring new biomarker assays to the clinic.

Multi-temperature experiments to ease analysis of heterogeneous binder solutions by surface plasmon resonance biosensing

Surface Plasmon Resonance (SPR) biosensing is a well-established tool for the investigation of binding kinetics between a soluble species and an immobilized (bio)molecule. While robust and accurate data analysis techniques are readily available for single species, methods to exploit data collected with a solution containing multiple interactants are scarce. In a previous study, our group proposed two data analysis algorithms for (1) the precise and reliable identification of the kinetic parameters of N interactants present at different ratios in N mixtures and (2) the estimation of the composition of a given mixture, assuming that the kinetic parameters and the total concentration of all interactants are known. Here, we extend the first algorithm by reducing the number of necessary mixtures. This is achieved by conducting experiments at different temperatures. Through the Van't Hoff and Eyring equations, identifying the kinetic and thermodynamic parameters of N binders becomes possible with M mixtures with M comprised between 2 and N and at least N/M temperatures. The second algorithm is improved by adding the total analyte concentration as a supplementary variable to be identified in an optimization routine. We validated our analysis framework experimentally with a system consisting of mixtures of low molecular weight drugs, each competing to bind to an immobilized protein. We believe that the analysis of mixtures and composition estimation could pave the way for SPR biosensing to become a bioprocess monitoring tool, on top of expanding its already substantial role in drug discovery and development.

Determination of the composition of heterogeneous binder solutions by surface plasmon resonance biosensing

Surface plasmon resonance-based biosensors have been extensively applied to the characterization of the binding kinetics between purified (bio)molecules, thanks to robust data analysis techniques. However, data analysis for solutions containing multiple interactants is still at its infancy. We here present two algorithms for (1) the reliable and accurate determination of the kinetic parameters of N interactants present at different ratios in N mixtures and (2) the estimation of the ratios of each interactant in a given mixture, assuming that their kinetic parameters are known. Both algorithms assume that the interactants compete to bind to an immobilized ligand in a 1:1 fashion and necessitate prior knowledge of the total concentration of all interactants combined. The effectiveness of these two algorithms was experimentally validated with a model system corresponding to mixtures of four small molecular weight drugs binding to an immobilized protein. This approach enables the in-depth characterization of mixtures using SPR, which may be of considerable interest for many drug discovery or development applications, notably for protein glycovariant analysis.

Isolation of single cells for protein therapeutics using microwell selection and Surface Plasmon Resonance imaging

Here the feasibility is demonstrated that by combining Surface Plasmon Resonance Imaging (SPRi) and self-sorting microwell technology product secretion of individual cells can be monitored. Additionally isolation of the selected cells can be performed by punching the cells from the microwells using coordinates of the positions of microwells obtained with SPRi. Cells of interest can be retrieved sterile from the microwell array for further cultivation.

Bayesian Estimation of the Active Concentration and Affinity Constants Using Surface Plasmon Resonance Technology

Surface plasmon resonance (SPR) has previously been employed to measure the active concentration of analyte in addition to the kinetic rate constants in molecular binding reactions. Those approaches, however, have a few restrictions. In this work, a Bayesian approach is developed to determine both active concentration and affinity constants using SPR technology. With the appropriate prior probabilities on the parameters and a derived likelihood function, a Markov Chain Monte Carlo (MCMC) algorithm is applied to compute the posterior probability densities of both the active concentration and kinetic rate constants based on the collected SPR data. Compared with previous approaches, ours exploits information from the duration of the process in its entirety, including both association and dissociation phases, under partial mass transport conditions; do not depend on calibration data; multiple injections of analyte at varying flow rates are not necessary. Finally the method is validated by analyzing both simulated and experimental datasets. A software package implementing our approach is developed with a user-friendly interface and made freely available.

Quantification of antibody production of individual hybridoma cells by surface plasmon resonance imaging

Surface plasmon resonance imaging (SPRi) is most frequently used for the label-free measurement of biomolecular interactions. Here we explore the potential of SPRi to measure antibody production of individual hybridoma cells. As a model system, cells from a hybridoma, producing monoclonal antibodies recognizing epithelial cell adhesion molecule (EpCAM), were used. Recombinant human EpCAM protein was immobilized on an SPR sensor and hybridoma cells were introduced into an IBIS MX96 SPR imager and the SPRi response was followed for 10h. SPRi responses were detected on the spots of the sensor only where ligands of the produced antibody were present. By measuring the SPRi signals on individual cells the antibody production of the individual cells was measured and production rates were calculated. For 53 single EpCAM hybridoma cells the production ranged from 0.16 to 11.95 pg (mean 2.96p g per cell, SD 2.51) over a period of 10 h. Antibody excretion per cell per hour ranged from 0.02 to 1.19 pg (mean 0.30, SD 0.25). Here we demonstrate for the first time that antibody production of individual cells can be measured and quantified by SPRi, opening a new avenue for measuring excretion products of individual cells.

Studying protein-protein interactions using surface plasmon resonance

Protein-protein interactions regulate many important cellular processes, including carbohydrate and lipid metabolism, cell cycle and cell death regulation, protein and nucleic acid metabolism, signal transduction, and cellular architecture. A complete understanding of cellular function depends on full characterization of the complex network of cellular protein-protein interactions, including measurements of their kinetic and binding properties. Surface plasmon resonance (SPR) is one of the commonly used technologies for detailed and quantitative studies of protein-protein interactions and determination of their equilibrium and kinetic parameters. SPR provides excellent instrumentation for a label-free, real-time investigation of protein-protein interactions. This chapter details the experimental design and proper use of the instrumentation for a kinetic experiment. It will provide readers with basic theory, assay setup, and the proper way of reporting this type of results with practical tips useful for SPR-based studies. A generic protocol for immobilizing ligands using amino coupling chemistry, also useful if an antibody affinity capture approach is used, performing kinetic studies, and collecting and analyzing data is described.