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Protein Interactions Profiled Using Surface Plasmon Resonance

BioPhotonics
Apr 2006
Surface plasmon resonance technology provides high information content in proteomics.

Alan McWhirter, Biacore AB

Proteins are the worker bees of the human body. They traverse cell membranes to receive and propagate signals, transport oxygen to every cell in the body, regulate the expression of genes and impart structure and strength to tissues. The signaling networks that transmit information from stimulus to biological function, from the environment to the organism, from cell to cell within tissues and within cells themselves are all regulated by proteins. Studying proteins, therefore, is critical to understanding how specific ones contribute to specific biological functions.

One method uses surface plasmon resonance (SPR), a natural phenomenon that occurs when polarized light strikes an electrically conducting gold layer.

Until now, SPR-based biosensors have delivered high-quality data on specific interactions. But with a bewildering number of novel proteins at hand since the completion of the human genome project, the proteomics community needs a high-quality, high-throughput method of studying their interactions.

Additionally, applications such as antibody screening, drug development and even online quality control/safety testing during food production could see the practical and economic benefits from a method such as an SPR array, which offers both high sample throughput and a large amount of information on interactions.

Watching interactions

Before proteins can influence function, they must communicate. To communicate, they must interact with other proteins or with other large biomolecules or small molecules such as vitamins or nucleotides. While engaged with an interacting partner, proteins drive (or participate in the regulation of) a function; when they dissociate, the function ceases.

Clearly then, quantitative data that describe how proteins interact — the rates of association and dissociation, called the interaction profile — will enable informed judgments about the contribution that individual proteins make to fine-tuning the complicated and extensive protein networks that regulate biological events.

For example, many proteins in intracellular signaling networks are active (capable of binding a partner) only when they are phosphorylated on specific amino acid residues. Phosphorylation status is regulated by two sets of proteins, called kinases and phosphatases, which phosphorylate and dephosphorylate proteins, respectively. The cellular activity (e.g., motility, DNA replication, protein synthesis, apoptosis) regulated by the pathway in which these proteins participate will be influenced by the phosphorylation status of proteins throughout the signaling network — a fine kinetic balancing act of coordinated associations and dissociations.

In addition, pharmaceutical companies determine whether a compound continues in drug development processes based on interaction profiles with targets in relation to their intended function. An ideal anticancer drug, for example, is likely to be characterized by rapid association and slow dissociation from its protein target. A dental anesthetic, on the other hand, should dissociate from its target rapidly so that the patient can quickly return to normal after a filling rather than remaining anesthetized for a week.

Charting protein networks

Proteomics is the collective term for the many investigative strategies delivering data that document the proteins that a genome encodes (collectively known as a proteome) and those formed after posttranslational modifications.

Listing a few descriptors of a proteome, such as molecular weight and domain properties, is rather like compiling the telephone directory of a town: Until the information is used — and people start calling each other — it is of little intrinsic value. Similarly, the repository of data comprising the proteome is somewhat lifeless until we use it to understand what all these thousands of proteins actually do and how they relate to one another.

Thus, instruments that can rapidly profile hundreds of protein interactions are attractive to investigators who would like to use the vast repository of data from proteomics initiatives to solve real problems. SPR-based arrays can offer large amounts of information on protein interactions in a high-throughput manner.

One major benefit of SPR over technologies such as ELISA or affinity chromatography is that it can provide high-resolution kinetics in real time over the course of an interaction. This provides a comprehensive and detailed profile of association and dissociation, imparting information about protein function far beyond that which can be inferred from end-point assays.

For example, by studying the rates of association or dissociation, a scientist could deconstruct a protein complex in terms of recognition or stability, forming a basis for qualified proposals of an interaction model. Furthermore, as the status of an interaction is followed according to changes in mass close to a sensor surface (i.e., as a molecular complex forms and dissociates), there is no requirement to label any of the interacting partners.


Figure 1.
In prism-based surface plasmon resonance systems, a block engraved with channels is pressed against a sensor surface to create a flow cell, the site of protein interactions on which one partner is immobilized and over which the other passes in solution.


SPR-based protein arrays are designed according to the type of information required. The Biacore A100 uses prism-based SPR (Figure 1), which occurs when polarized light, under conditions of total internal reflection, strikes an electrically conducting gold layer at the interface between media of different refractive index; the glass of the sensor surface covered with a thin layer of gold (high refractive index) and a buffer flowing over the sensor surface (low refractive index).

A wedge of polarized light, covering a range of incident angles, is directed toward the glass face of the sensor surface and reflected toward a detector. When the light strikes the glass, it generates an electric field intensity known as an evanescent wave, which interacts with and is absorbed by free electron clouds in the gold layer, producing electron charge density waves called plasmons and causing a reduction in the intensity of the reflected light.

Interactions can be detected because the resonance angle at which this intensity minimum occurs is a function of the refractive index and, hence, the molecular mass of the complex adjacent to the gold layer on the sensor surface (Figure 2).


Figure 2.
As molecules are immobilized on a sensor surface, the refractive index at the interface between the surface and a solution flowing over it changes, altering the angle at which reduced-intensity polarized light reflects from the supporting glass plane. The change in angle, caused by binding or dissociation of molecules from the sensor surface, is proportional to the mass of bound material and is recorded in a sensorgram (A). When sample in solution passes over the sensor surface, the sensorgram shows an increasing response if the molecules interact. The response remains constant after the interaction reaches equilibrium (B). When sample is replaced by buffer, the response decreases as the interaction partners dissociate (C).


Simultaneous profiling

The Flexchip system allows simultaneous profiling of up to 400 protein interactions and uses an alternate arrangement called grating-coupled SPR (Figure 3), where incident polarized light from above strikes the entire functional face of a finely grated sensor surface. The small coupling angle of the incident light is conducive to multiple imaging and thus well suited to screening applications requiring simultaneous interrogation of a large number of interactions.


Figure 3.
In systems based on grating-coupled SPR, incident light from above directly strikes the entire array, simultaneously generating data from as many as 400 interactions.


In instruments from Biacore AB of Uppsala, Sweden, biomolecular interactions are studied in flow cells on a sensor surface. In this setup, the researcher injects interacting partners in solution into flow cells that are formed when a microfluidic flow system is brought into contact with a sensor surface on which other interacting partners have been immobilized. 

Hydrodynamic addressing is performed using a single flow cell in which multiple targets may be immobilized on detection spots (the site of interaction), allowing simultaneous analysis of interactions. By adjusting the relative flow at the two inlets — one for the immobilized partner and the other for the buffer — liquid can be directed to one or another of the addressable detection spots (Figure 4).


Figure 4.
Each flow cell has two inlets and one outlet, allowing the spots to be addressed separately. No target is immobilized on the central spot, which is used as a reference. The design of the flow cell and the simultaneous flow of sample solution over all five spots are essential components in small-molecule applications, providing simultaneous binding analysis to four target spots with in-line referencing
.

The A100, for example, has four parallel independent hydrodynamic addressing flow cells that can accommodate up to five proteins immobilized in each. For maximum sample throughput, identical immobilizations can be performed in each cell, allowing analysis of four samples in parallel during each analysis cycle. In assays where information output per sample is more important, up to 20 interactants can be immobilized in the four flow cells, and one sample per cycle is injected in parallel over all flow cells.

Rapid screening

Productivity in biotherapeutic development may benefit from access to a high-throughput array system that delivers kinetic data. For example, the development of monoclonal antibodies is a complex and time-consuming process, involving the generation, maintenance and screening of thousands of hybridoma clones — the cellular “factories” in which these antibodies are produced. Early identification of the clones that produce the best candidate monoclonal antibodies is a critical step in development. Rapid screening efficiently enables selection of candidates with the required kinetic profiles, discriminating between equal-affinity antibodies based on kinetic properties that are crucial for clinical success.

In addition, this array system can help in testing how likely newly developed drugs and vaccines are to elicit an immune response. This is important because the human body may identify even the most carefully designed and constructed drug as a foreign body, causing an unwanted antibody response. SPR-based protein arrays can be used to characterize serum antibody responses by detecting potential clinically relevant low- and medium-affinity antibodies, producing data on isotype, subclass specificity and kinetics from a single system using low quantities of sera.

Flexchip uses a single-pass multispot flow cell, a single broad channel through which sample is injected. The sample interacts simultaneously with up to 400 spots on a single array (Figure 5). As light reflects from the sensor surface, the system’s software resolves the data from the individual spots into hundreds of interaction profiles.


Figure 5.
The design of this flow cell is a single broad channel through which sample is injected, interacting simultaneously with all spots on an array. After the sensor surface is spotted according to user specifications, a gasketed window with an inlet and an outlet valve is positioned and hermetically sealed over the array to form the flow cell, which is inserted into the Flexchip apparatus.


Researchers can study interactions between proteins using a peptide from one of the interacting partners rather than from the whole protein. This type of array could, for example, identify peptides with the highest binding activity by looking for overlapping peptides on the sequence of one interacting partner. The array may then be further applied in an alanine scan, in which single amino acid residues in a peptide are replaced by alanine, to precisely identify the amino acid residues necessary for the interaction.

The array also could be used to define how transcription factors bind to DNA by comparing interactions with wild-type DNA oligomers with those containing mutations within the consensus sequence. Electrostatic interactions have been reported to influence the association of transcription factors to DNA, and this may be mimicked in vitro by increasing the ionic strength of the running buffer, a condition that tends to favor specific over nonspecific interactions. Interactions may thus be followed at different ionic strengths over a series of runs and the interaction profiles compared.

Meet the author

Alan McWhirter is an academic sector specialist in market communications at Biacore AB in Uppsala, Sweden; e-mail: alan.mcwhirter@biacore.com.


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