Specific allowance for antibody bivalence in the determination of dissociation constants by kinetic exclusion assay

Theory that takes rigorous account of antibody bivalence in the characterization of immunospecific reactions by kinetic exclusion assay is presented. In addition to reinforcing the basic correctness of quantitative expressions currently being used for the determination of dissociation constants (K_d) by this method, the current study highlights a requirement for conformity of the system with critical assumptions/approximations therein. Published results for the interaction between the extracellular domain of human insulin-like growth factor (hIGFR) and anti-hIGFR are used to illustrate aspects of the theoretical predictions for a system to which those assumptions/approximations may well apply; and those for a cadmium–ethylenediaminetetraacetic acid (Cd–EDTA) antibody interaction to emphasize the consequences of adopting the same analytical procedure in a situation where one of those assumptions does not apply. The major weakness of current protocols for the characterization of antigen–antibody interactions by kinetic exclusion assay is an absence of any check on the likely magnitude of the probability of antibody capture by the affinity beads—a parameter that needs to be 5% or lower for validity of the quantitative expression on which the analysis is based.     

Allowance for antibody bivalence in the determination of association rate constants by kinetic exclusion assay

This investigation completes the amendment of theoretical expressions for the characterization of antigen–antibody interactions by kinetic exclusion assay—an endeavor that has been marred by inadequate allowance for the consequences of antibody bivalence in its uptake by the affinity matrix (immobilized antigen) that is used to ascertain the fraction of free antibody sites in a solution with defined total concentrations of antigen and antibody. A simple illustration of reacted site probability considerations in action confirms that the square root of the fluorescence response ratio, R_Ag/R_o, needs to be taken in order to determine the fraction of unoccupied antibody sites, which is the parameter employed to describe the kinetics of antigen uptake in the mixture of antigen and antibody with defined initial composition. The approximately 2-fold underestimation of the association rate constant (k_a) that emanates from the usual practice of omitting the square root factor gives rise to a corresponding overestimate of the equilibrium dissociation constant (K_d)—a situation that is also encountered in the thermodynamic characterization of antigen–antibody interactions by kinetic exclusion assay.     

Confirmation of the validity of the current characterization of immunochemical reactions by kinetic exclusion assay

Prior observations that questioned the validity of kinetic exclusion assays were based on the mistaken assumption that the assays quantified the fraction of those antibody molecules that had unoccupied binding sites. Instead, the standard KinExA assay quantifies the fraction of total antibody binding sites that are unoccupied, regardless of the number of unoccupied sites on each antibody molecule. Although the standard KinExA analysis assumes that there is only a small probability of antibody-site capture by the affinity matrix, the results of numerical simulations demonstrate the reliability of dissociation constants obtained by the standard KinExA analysis for capture probabilities as high as 30%. This finding further strengthens the potential of kinetic exclusion assays as the procedure of choice for the rapid and accurate characterization of immunochemical reactions that forms part of screening processes in the search for therapeutic antibodies.     

Automated kinetic exclusion assays to quantify protein binding interactions in homogeneous solution.

A method was developed for the quantification of protein-ligand interactions in which the free protein present in homogeneous reaction mixtures was separated and quantified using a KinExA immunoassay instrument. Separation was achieved by rapid percolation of the reaction mixture over a column of microbeads whose surfaces were coated with an immobilized form of the ligand. The protein thus captured was quantified using a fluorescently labeled anti-protein antibody. The features of this new method were illustrated using a model system in which each of the principal reagents was covalently labeled with a different fluorescent molecule: mouse monoclonal anti-biotin primary antibody (fluorescein), biotin (B-phycoerythrin), and goat anti-mouse polyclonal secondary antibody (indodicarbocyanin). Values for the equilibrium and kinetic rate constants for the binding between the anti-biotin antibody and biotin conjugated with B-phycoerythrin were determined and shown to be independent of whether the fluorescent label was located on the primary or secondary antibody. Equilibrium binding experiments conducted with (F(AB))(2) and corresponding F(AB) fragments showed that the valency of the binding protein had no influence on the value of the dissociation constant. The values of the equilibrium and rate constants obtained by this new method are those for the binding reaction in homogeneous solution; the immobilized ligand is only a tool exploited for the separation and quantification of the free protein.     

Measurement of antigen-antibody interactions with biosensors

The introduction in 1990 of a new biosensor technology based on surface plasmon resonance has revolutionized the measurement of antigen-antibody binding interactions. In this technique, one of the interacting partners is immobilized on a sensor chip and the binding of the other is followed by the increase in refractive index caused by the mass of bound species. The following immunochemical applications of this new technology will be described: (1) functional mapping of epitopes and paratopes by mutagenesis; (2) analysis of the thermodynamic parameters of the interaction; (3) measurement of the concentration of biologically active molecules; (4) selection of diagnostic probes.     

Using the beta-lactamase protein-fragment complementation assay to probe dynamic protein-protein interactions

We have developed a general experimental strategy that enables the quantitative detection of dynamic protein-protein interactions in intact living cells, based on protein-fragment complementation assays (PCAs). In this method, protein interactions are coupled to refolding of enzymes from cognate fragments where reconstitution of enzyme activity acts as the detector of a protein interaction. We have described a number of assays with different reporter readouts, but of particular value to studies of protein interaction dynamics are assays based on enzyme reporters that catalyze the creation of products, thus taking advantage of the amplification of signal afforded. Here we describe protocols for one such PCA based on the enzyme TEM beta-lactamase as a reporter in mammalian cells. The beta-lactamase PCA consists of fusing complementary fragments of beta-lactamase to two proteins of interest. If the proteins interact, the fragments are brought together and fold into active beta-lactamase. Here we describe a protocol for this PCA that can be completed in a few hours, using two different substrates that are converted to fluorescent or colored products by beta-lactamase.     

Agent-based dynamic knowledge representation of Pseudomonas aeruginosa virulence activation in the stressed gut: Towards characterizing host-pathogen interactions in gut-derived sepsis

Background

There is a growing realization that alterations in host-pathogen interactions (HPI) can generate disease phenotypes without pathogen invasion. The gut represents a prime region where such HPI can arise and manifest. Under normal conditions intestinal microbial communities maintain a stable, mutually beneficial ecosystem. However, host stress can lead to changes in environmental conditions that shift the nature of the host-microbe dialogue, resulting in escalation of virulence expression, immune activation and ultimately systemic disease. Effective modulation of these dynamics requires the ability to characterize the complexity of the HPI, and dynamic computational modeling can aid in this task. Agent-based modeling is a computational method that is suited to representing spatially diverse, dynamical systems. We propose that dynamic knowledge representation of gut HPI with agent-based modeling will aid in the investigation of the pathogenesis of gut-derived sepsis.

Methodology/Principal Findings

An agent-based model (ABM) of virulence regulation in Pseudomonas aeruginosa was developed by translating bacterial and host cell sense-and-response mechanisms into behavioral rules for computational agents and integrated into a virtual environment representing the host-microbe interface in the gut. The resulting gut milieu ABM (GMABM) was used to: 1) investigate a potential clinically relevant laboratory experimental condition not yet developed - i.e. non-lethal transient segmental intestinal ischemia, 2) examine the sufficiency of existing hypotheses to explain experimental data - i.e. lethality in a model of major surgical insult and stress, and 3) produce behavior to potentially guide future experimental design - i.e. suggested sample points for a potential laboratory model of non-lethal transient intestinal ischemia. Furthermore, hypotheses were generated to explain certain discrepancies between the behaviors of the GMABM and biological experiments, and new investigatory avenues proposed to test those hypotheses.

Conclusions/Significance

Agent-based modeling can account for the spatio-temporal dynamics of an HPI, and, even when carried out with a relatively high degree of abstraction, can be useful in the investigation of system-level consequences of putative mechanisms operating at the individual agent level. We suggest that an integrated and iterative heuristic relationship between computational modeling and more traditional laboratory and clinical investigations, with a focus on identifying useful and sufficient degrees of abstraction, will enhance the efficiency and translational productivity of biomedical research.     

Use of the EpiAirway model for characterizing long-term host-pathogen interactions

Nontypeable Haemophilus influenzae (NTHi) are human-adapted Gram-negative bacteria that can cause recurrent and chronic infections of the respiratory mucosa (1; 2). To study the mechanisms by which these organisms survive on and inside respiratory tissues, a model in which successful long-term co-culture of bacteria and human cells can be performed is required. We use primary human respiratory epithelial tissues raised to the air-liquid interface, the EpiAirway model (MatTek, Ashland, MA). These are non-immortalized, well-differentiated, 3-dimensional tissues that contain tight junctions, ciliated and nonciliated cells, goblet cells that produce mucin, and retain the ability to produce cytokines in response to infection. This biologically relevant in vitro model of the human upper airway can be used in a number of ways; the overall goal of this method is to perform long-term co-culture of EpiAirway tissues with NTHi and quantitate cell-associated and internalized bacteria over time. As well, mucin production and the cytokine profile of the infected co-cultures can be determined. This approach improves upon existing methods in that many current protocols use submerged monolayer or Transwell cultures of human cells, which are not capable of supporting bacterial infections over extended periods(3). For example, if an organism can replicate in the overlying media, this can result in unacceptable levels of cytotoxicity and loss of host cells, arresting the experiment. The EpiAirway model allows characterization of long-term host-pathogen interactions. Further, since the source for the EpiAirway is normal human tracheo-bronchial cells rather than an immortalized line, each is an excellent representation of actual human upper respiratory tract tissue, both in structure and in function(4). For this method, the EpiAirway tissues are weaned off of anti-microbial and anti-fungal compounds for 2 days prior to delivery, and all procedures are performed under antibiotic-free conditions. This necessitates special considerations, since both bacteria and primary human tissues are used in the same biosafety cabinet, and are co-cultured for extended periods.     

Single-molecule approaches to characterizing kinetics of biomolecular interactions

Single-molecule fluorescence techniques have emerged as powerful tools to study biological processes at the molecular level. This review describes the application of these methods to the characterization of the kinetics of interaction between biomolecules. A large number of single-molecule assays have been developed that visualize association and dissociation kinetics in vitro by fluorescently labeling binding partners and observing their interactions over time. Even though recent progress has been significant, there are certain limitations to this approach. To allow the observation of individual, fluorescently labeled molecules requires low, nanomolar concentrations. I will discuss how such concentration requirements in single-molecule experiments limit their applicability to investigate intermolecular interactions and how recent technical advances deal with this issue.     

Capture molecules preconditioned for kinetic analysis of high-affinity antigen-antibody complex in Biacore A100

Surface plasmon resonance (SPR) is routinely applied on determining association or dissociation constant rates of antigen-antibody complexes. In a SPR system such as Biacore, the capture method is a widely accepted procedure in kinetic analysis for association or dissociation of soluble antigen analytes with antibody ligands initially captured by anti-Fc molecules immobilized on the sensor chip. Appropriate preparations of anti-immunoglobulin G (IgG)-Fc molecules on sensor chips have not been examined yet for stable kinetic analysis of antibodies with several affinities to soluble antigens. Here, we constructed murine monoclonal antibodies (MoAbs) with various affinities to hen egg lysozyme (HEL) and performed kinetic analysis of these MoAbs captured by rat MoAbs against mouse IgG-Fc immobilized on the sensor chip. When capture molecules maximally immobilized on the sensor chip, we observed no apparent dissociation of MoAbs with extremely high affinity to soluble HEL antigens. In contrast, on the limited amount (1000-2000 response units) of capture molecule immobilized on the sensor chip, we could perform stable kinetic analysis of MoAbs with highest affinities to the antigen as well as those with lower or moderate binding affinities. Thus, in some cases, accurate kinetic analysis of high-affinity antibodies can be performed by minimization of capture molecule densities on the sensor chip in SPR.     

Bilayer lipid membranes (BLM): Study of antigen-antibody interactions

Previous work of del Castillo and co-workers has shown that bilayer lipid membranes (BLM) can be used as transducers for detection of antigen-antibody reactions. The present experiments extend the previous work by incorporating complement into the BLM system. The results indicate that the antigen-antibody complex or the complement has no ability to affect the BLM system separately, but when carefully combined they will destabilize the BLM even at a much reduced concentration. Further development using the BLM as a tool for investigating immunological reactions is suggested.     

Measurements of protein-protein interactions by size exclusion chromatography

A method is presented for determining second virial coefficients (B(2)) of protein solutions from retention time measurements in size exclusion chromatography. We determine B(2) by analyzing the concentration dependence of the chromatographic partition coefficient. We show the ability of this method to track the evolution of B(2) from positive to negative values in lysozyme and bovine serum albumin solutions. Our size exclusion chromatography results agree quantitatively with data obtained by light scattering.     

Biosensor analysis of antigen-antibody interactions as a priority step in the generation of monoclonal bispecific antibodies

A biosensor system aimed at real-time measuring molecular interactions among label-free reactants has been used for a comparative analysis of the binding features (i.e., association-dissociation rates and affinity constants) as well as epitope mapping between bivalent monoclonal antibodies and the derived monovalent bispecific monoclonal antibody. The results show that observed different affinities between parental and derived bispecific antibodies concern the association rate constant, whereas the dissociation rate constants are unaltered. The apparent affinity-constant values determined by solid-phase radioimmunoassay yielded figures almost overlapping with those obtained with the biosensor instrument. The results of the present work indicate that the biosensor system has gained a key role not only as a tool for the study of antigen-antibody interactions, but also for setting up the reference parameters for the selection of the best candidates in the generation of bispecific monoclonal antibodies.     

Application of surface plasmon resonance toward studies of low-molecular-weight antigen-antibody binding interactions

Methods for studying low-molecular-weight antigen-antibody binding interactions using surface plasmon resonance detection are presented. The experimental parameters most relevant to studies of low-molecular-weight antigen-antibody binding interactions are discussed. Direct kinetic analysis of the binding interactions is most informative, providing both apparent association and dissociation rate constants from which equilibrium constants can be calculated. Equilibrium analysis, including steady-state and solution affinity studies, offers an alternative approach to direct kinetic analysis when knowledge of the individual kinetic rate constants is not required or difficult to determine. The various methods are illustrated by studies of an anti-T(4) Fab fragment binding interaction with several thyroxine analogs. The methods utilized were dependent on the affinity of the interaction. The high-affinity anti-T(4) Fab fragment/l-T(4) binding interaction was evaluated using direct kinetic analysis. An intermediate affinity anti-T(4) Fab fragment/l-T(3) binding interaction was evaluated using a combination of direct kinetic analysis, steady-state analysis, and solution affinity analysis. The relatively weak anti-T(4) Fab fragment/l-T(2) binding interaction was evaluated using steady-state and solution affinity analysis protocols. Several thyroxine tracers that could not be immobilized to a biosensor surface were also evaluated via the solution affinity format. In cases where a given binding interaction was examined using multiple methods the results were comparable.     

Nonlinear PCA: characterizing interactions between modes of brain activity

This paper presents a nonlinear principal component analysis (PCA) that identifies underlying sources causing the expression of spatial modes or patterns of activity in neuroimaging time-series. The critical aspect of this technique is that, in relation to conventional PCA, the sources can interact to produce (second-order) spatial modes that represent the modulation of one (first-order) spatial mode by another. This nonlinear PCA uses a simple neural network architecture that embodies a specific form for the nonlinear mixing of sources that cause observed data. This form is motivated by a second-order approximation to any general nonlinear mixing and emphasizes interactions among pairs of sources. By introducing these nonlinearities principal components obtain with a unique rotation and scaling that does not depend on the biologically implausible constraints adopted by conventional PCA. The technique is illustrated by application to functional (positron emission tomography and functional magnetic resonance imaging) imaging data where the ensuing first- and second-order modes can be interpreted in terms of distributed brain systems. The interactions among sources render the expression of any one mode context-sensitive, where that context is established by the expression of other modes. The examples considered include interactions between cognitive states and time (i.e. adaptation or plasticity in PET data) and among functionally specialized brain systems (using a fMRI study of colour and motion processing).