In SPR experiments, low responses are preferred over high responses. This is because high responses in general are affected by mass transport and non 1:1 interactions (6),(8). But how low can you go? This depends in the first place on the instrument you have chosen. The signal should be above the noise level of the baseline. The curves should be easily recognisable and replicates should overlay (4),(7).
To determine the noise level of the instrument, first equilibrate the system to minimize drift. Then inject flow buffer several times and observe the average response. The average response level is the starting point for the next experiments. In addition, check the shape of the curves. If there is drift or the curves are not level shortly after the start of the injection, equilibrate better or clean the instrument.
Then calculate the amount of ligand to immobilize to get a proper signal. This will be a matter of trial and error since you do not know the amount of active ligand, which is available after immobilization. As a starting point, calculate a response of 100 RU. After immobilization, it is essential to equilibrate the system since the immobilization uses several high-concentration solutions. The best method to check the equilibration is to inject flow buffer several times and then monitor the baseline.
When flow buffer equilibration is reached, inject analyte from a low to a high concentration. Take a broad range of concentrations, e.g. 0.1 nM – 1 µM. The fastest method is the kinetic titration method (3). Between the injections there is a short dissociation period and then a longer one after the last injection. These first injections give you an idea about the ligand activity, useful analyte concentration range, kinetics (association and dissociation rate) and the maximal response of the interaction. Knowing this, proper changes to the ligand immobilization level or analyte concentration range can be made. In addition, you can optimize the association and dissociation injection period.
When the dissociation is very slow, a regeneration solution (e.g. low pH, high salt) can be used to remove the analyte. However, regeneration can be problematic. It should remove the analyte completely but the ligand must remain intact on the surface. Therefore, use the mildest regeneration solution and shortest contact time possible. In addition, regeneration can cause matrix effects (drift) which can look like there is still analyte on the surface. Make sure the system is fully equilibrated after regeneration. Use the washing command and extend the equilibration time when necessary. This will be a matter of testing (1),(2).
Know your system:
Let the data be your guide by reproducing the response of the interaction (5).
The surface plasmon resonance experiments were performed using a BIACORE 2000 (GE Healthcare) equipped with a research-grade CM5 sensor chip. The ligand (44 or 74 kDa, >90% pure based on SDS–PAGE) was immobilized using amine-coupling chemistry. The surfaces of the flow cells were activated for 7 min with a 1:1 mixture of 0.1 M NHS (N-hydroxysuccinimide) and 0.1 M EDC (3-(N,N-dimethylamino) propyl-N-ethylcarbodiimide) at a flow rate of 5 μl/min. The ligand at a concentration of 5 μg/ml in 10 mM sodium acetate, pH 5.0, was immobilized at a density of approximately 1200 - 1500 RU; flow cell 1 was left unmodified to serve as a reference surface. All the surfaces were blocked with a 7 min injection of 1 M ethanolamine, pH 8.0.
|Proteins used in the experiment
|4 purple||B2GPI open||44000||1280||0.029|
To collect kinetic binding data, zinc chloride in 10 mM HEPES, 150 mM NaCl, 0.005% P20, pH 7.4, was injected over the two flow cells at concentrations of 10, 5, 2.5, 1.25, 0.63, 0.31, 0.16, 0.08 µM at a flow rate of 30 μl/min and at a temperature of 25°C. The complex was allowed to associate and dissociate for 90 and 300 s, respectively. The surfaces were regenerated with a 5 s injection of 3 mM EDTA. Duplicate injections (in random order) of each sample and a buffer blank were flowed over the four surfaces. Data were collected at a rate of 1 Hz. The data were fit to a simple steady-state affinity model using the Scrubber software.
The surface plasmon resonance experiments were performed using a BIACORE 2000 (GE Healthcare) equipped with a research-grade CM5 sensor chip. The ligand (CA II, 29 KDa) was immobilized using amine-coupling chemistry. The surface of the flow cell 1 was activated for 7 min with a 1:1 mixture of 0.1 M NHS (N-hydroxysuccinimide) and 0.1 M EDC (3-(N,N-dimethylamino) propyl-N-ethylcarbodiimide) at a flow rate of 5 μl/min. The ligand at a concentration of 15 μg/ml in 10 mM sodium acetate, pH 5.0, was immobilized at a density of approximately 3500 RU. The surface was blocked with a 7 min injection of 1 M ethanolamine, pH 8.0. Flow cell 3 was left unmodified to serve as a reference surface.
To collect kinetic binding data, Acetazolamide in 10 mM HEPES, 150 mM NaCl, 0.005% P20, pH 7.4, was injected at concentrations indicated in the figure a flow rate of 100 μl/min and 25°C. The complex was allowed to associate and dissociate for 170 and 300 s, respectively. Regeneration was not necessary is this system. Triplicate injections (in random order) of each sample and buffer blanks were flowed over the four surfaces. Data were collected at a rate of 1 Hz. The data were fit to a simple 1:1 model using the global data analysis option available within Scrubber software.
Kalyuzhniy, O., Di Paolo, N. C., Silvestry, M., et al.; Adenovirus serotype 5 hexon is critical for virus infection of hepatocytes in vivo. Proceedings of the National Academy of Sciences (105): 5483-5488; 2008.
Souphron, J., Waddell, M. B., Paydar, A., et al.; Structural Dissection of a Gating Mechanism Preventing Misactivation of Ubiquitin by NEDD8’s . Biochemistry (47): 8961-8969; 2008.
Wang, H., Liu, Y., Li, Z., et al.; In vitro and in vivo properties of adenovirus vectors with increased affinity to CD46. J.Virol. (82): 10567-10579; 2008.
Tell us, how low did you go? Show us your sensorgrams and analysis.
|(1)||Andersson, K., D. Areskoug and E. Hardenborg Exploring buffer space for molecular interactions. J.Mol.Recognit. 12: 310-315; (1999). Goto reference|
|(2)||Andersson, K., M. Hamalainen and M. Malmqvist Identification and optimization of regeneration conditions for affinity- based biosensor assays. A multivariate cocktail approach. Analytical Chemistry 71: 2475-2481; (1999). Goto reference|
|(3)||Karlsson, R., P. S. Katsamba, H. Nordin, et al. Analyzing a kinetic titration series using affinity biosensors. Analytical Biochemistry 349: 136-147; (2006).|
|(4)||Myszka, D. G. Improving biosensor analysis. J.Mol.Recognit. 12: 279-284; (1999). Goto reference|
|(5)||Myszka, D. G. and R. L. Rich Advanced Biosensor Workshop. Biosensor tools (2011).|
|(6)||O'Shannessy, D. J. and D. J. Winzor Interpretation of deviations from pseudo-first-order kinetic behavior in the characterization of ligand binding by biosensor technology. Analytical Biochemistry 236: 275-283; (1996). Goto reference|
|(7)||Rich, R. L. and D. G. Myszka Label free biosensors | Techniques and Applications. (2009).|
|(8)||Schuck, P. and A. P. Minton Analysis of mass transport-limited binding kinetics in evanescent wave biosensors. Analytical Biochemistry 240: 262-272; (1996). Goto reference|