Cell-Based Biosensors: A Quartz Crystal Microbalance Approach to Membrane Protein Interaction Studies

Drug development today is a time-consuming and expensive business, with costs reaching over $1 billion from drug discovery to market.1 The cost escalates during clinical trials; therefore, it is of the utmost importance to avoid late-failing drugs by selecting the best candidate early in the process. Traditional biosensors are important and powerful tools in the drug discovery process for their ability to measure the pure interaction between a drug candidate and its target. However, most biosensors are limited to using a purified target molecule immobilized to the sensor surface. This oversimplifies the biological context and presents an incomplete picture of the in vivo situation.

Eukaryotic membrane proteins such as G protein-coupled receptors (GPCRs) and ion channels are the preferred target for more than 60% of current therapeutic drugs.2 These biomolecules need a lipid bilayer to maintain their structure and function and therefore cannot be easily isolated and studied with traditional biosensor methods. Conventional cell-based assays, on the other hand, are well suited for studying the effect interactions have on cells, but do not disclose the full dynamics of the interaction itself.

Figure 1 - Attana Cell 200 biosensor.

The Attana Cell™ 200 biosensor (Attana AB, Stockholm, Sweden) measures label-free, full kinetics in real time with the target in its biological context (Figure 1). Cells can be grown directly on the sensor surface, and the interacting biomolecule is introduced to the continuous flow system as in a traditional biosensor. The instrument is also compatible with standard biosensor surfaces and can therefore be used to compare the binding to a purified target with that of cellular interactions. The combination of the QCM technology and cell sensor chip results in biologically relevant biosensor measurements.

QCM technology

QCM (Quartz Crystal Microbalance) technology enables studies of molecular interactions by measuring the weight of the molecules, much like a very sensitive scale or balance. When molecules are added to or removed from the sensor surface, it is detected as a change in the oscillation frequency of the sensor crystal; the change in resonance frequency is correlated to the change in mass on the surface. QCM technology does not have the same limitations with regard to surface proximity as other biosensor technologies, making it possible for the instrument to measure binding to large structures such as cells.

Figure 2 - Cell sensor chip.

Cell sensor chip

The cell sensor chip (Figure 2) permits the user to culture mammalian cells directly on the cell-optimized polystyrene sensor surface. A cell suspension is added to the cultivation chimney and the cells are allowed to adhere to the surface. The growth and cell density can be validated using fluorescent microscopy. By replacing the cultivation lid with a measurement lid, the sensor chip can be docked in the instrument and a biosensor experiment measuring interactions with targets on the cell surface can be started.

Molecular interactions in a biologically relevant context

The cell-based biosensor can be used to study membrane proteins in their natural environment, the cell membrane. This can be achieved in several ways, from immobilizing membrane preparations on the sensor surface to studying interactions directly on cells. Two examples are presented that cover the range of application possibilities, the first working with lipoparticles and the second with cells.

Molecular interactions with lipoparticles

Lipoparticles composed of natural cell membrane are both durable and stable and as such are well suited for studying molecular interactions. In this application example, 150-nm-diam lipoparticles (Integral Molecular, Philadelphia, PA) incorporating the GPCR chemokine receptor 4 (CXCR4) were used to study the interaction between CXCR4 and an anti-CXCR4 antibody. The particles containing CXCR4 were immobilized onto Attana Biotin Sensor Surfaces (Attana AB) using memLAYER reagents (Layerlab, Gothenburg, Sweden). The reagents are based on the company’s proprietary Tethered Enhanced Liposome Immobilisation (TELI) technology and consist of a cholesterol–DNA strand that is naturally integrated in the lipid bilayer and a complementary biotin–DNA strand that is immobilized onto a NeutrAvidin-coated sensor chip (Pierce, Rockford, IL). DNA hybridization then enables stable capture of lipoparticles on the sensor surface.

Figure 3 - Anti-CXCR4 antibody binding to lipoparticles using the cell-based biosensor. Comparison of anti-CXCR4 antibody binding to three different surfaces: lipoparticles containing CXCR4 (solid line), lipoparticles without CXCR4 (dashed line), and a control surface with immobilized biotinylated bovine serum albumin (BSA, dotted line). The antibody is injected for 84 sec over the three different surfaces and the dissociation of the antibody is monitored for 200 sec. The antibody displays high-affinity binding to lipoparticles containing CXCR4, whereas weak and off-target binding to lipoparticles without CXCR4 was detected. No binding to the control surface was detected.

Figure 4 - CXCR4 antibody binding to lipoparticles fits a 1:1 binding model. Referenced binding data, obtained by subtracting the binding response to lipoparticles without CXCR4 from that of lipoparticles containing CXCR4 (black), are fitted to a 1:1 binding model (red).

The interactions between CXCR4-containing lipoparticles and anti-CXCR4 antibody were studied in real time using the cell-based biosensor. The results show both specific interaction and off-target binding to the cell membrane or membrane proteins (Figure 3). No binding was detected to biotinylated BSA directly immobilized onto a control surface. The antibody interactions with CXCR4-containing lipoparticles display a dose dependency. In addition, by using data from antibody interaction with lipoparticles lacking CXCR4 as a reference, an investigation of only the specific interactions is possible (Figure 4). A 1:1 binding model was used to fit (red lines) the experimental data (black lines), and binding rate constants calculated. The affinity of the interaction was determined to be 2.2 nM.

Molecular interactions with cells

Combining the high specificity of monoclonal antibodies to their targets with the pharmacological potency of cytotoxic drugs can generate a higher therapeutic efficacy and is often used in oncology.3 There are currently more than 15 promising antibody–drug conjugates (ADC) in clinical trials, and there is also an increased focus in early drug development with many promising candidates.4

Figure 5 - Comparison of the binding of Herceptin (solid line) and modified Herceptin (dotted line) to cells expressing HER2 using the cell-based biosensor. Herceptin is injected for 84 sec and the dissociation of the antibody is monitored for 200 sec. Modified Herceptin displays both specific off-target and/or nonspecific binding to cell surface components, which is indicated by the two concurrent types of reactions, one high-affinity, specific interaction with relatively slow on and off rates (also present when injecting unmodified Herceptin) and a second low-affinity, off-target interaction with fast on and off rates.

In an attempt to selectively trigger cancer cell death with an ADC, an Attana biosensor user modified the anti-HER2 breast cancer marker antibody Herceptin (Genentech, South San Francisco, CA), and needed to verify that the binding characteristics were unchanged.5 In a traditional biosensor experiment with the purified target immobilized on a sensor surface, the modified Herceptin kinetics were unaffected. However, when measuring binding to the target in its natural environment, the cell membrane, the results were quite different (Figure 5). The modified Herceptin had retained its specific binding to the target, but off-target binding to the membrane or other components in the membrane was evident. The off-target interaction is fast but is vital for understanding the function of the modified antibody in the biological context.

Summary

Keeping costs down and speeding up the drug development process is an important challenge for drug companies. One central component is to select the best drug candidates during each step of the development process. The information gained from measurements with the Attana Cell 200 biosensor can be used to select better candidates earlier, therefore saving both time and money in consecutive preclinical and clinical trials.

The biosensor delivers more biologically relevant information by providing the possibility of measuring molecular interactions with cells in real time and without the use of labels. It also shows the full dynamics of the interaction, including off-target interactions with other components on the cell surface and nonspecific binding, which are important for understanding the in vivo process.

References

  1. Landers, P. Cost of Developing a New Drug Increases to About $1.7 Billion. Wall Street Journal, Dec 2003.
  2. Overington, J.; Al-Lazikani, B. et al. How many drug targets are there? Nature Rev. Drug Discov. 2006, 5, 993–6.
  3. Kovtun, Y.; Goldmacher, V. Cell killing by antibody–drug conjugates. Cancer Lett. 2007, 255, 232–40.
  4. Beck, A. The next generation of antibody–drug conjugates comes of age. Discovery Med. 2010, 10(53), 329–39.
  5. Kovacs, A. Molecular interaction studies in cells: exploring biology at a new level. Innovations Pharm. Technol. Jun 2010, 42–6.

Ms. Elovsson is Product Manager, and Dr. Aastrup is CEO, Attana AB, Björnnäsvägen 21, 114 19 Stockholm, Sweden; tel.: +46 8 674 57 12; e-mail: karin.elovsson@attana.com. Dr. Pei is a Professor, College of Science, Northwest A&F University, Yangling, People’s Republic of China.

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