does anyone have a problem with negative curve...?

I am recently developing a method to study the kinetics between pegylated molecule and the receptor... i have immobilised the receptor at 250 RU- achieved (244 RU), then I ran several concentrations because i was expecting the affinity of 500pm... i ranged the analyte conc. from 5 nM to 50pM but i could not see a good response.. it was negative curve... the blank surface was activated, deactivated and ethanolamine blocked..as per the wizard... what could i be missing...? i use ready to use HBS-N buffer in baicore T100

Hi,
Negative signals are always puzzeling. I collected this information from the forums about SPR.
You can also read this at www.sprpages.nl/experiments/troubleshooting.html


1. A negative signal with SPR.
Sometimes a negative binding signal is seen in a SPR experiment. It is not always obvious where this comes from. Below is a list of possible causes and possible solutions.

1.1. Buffer mismatch
Some negative binding responses originate from buffer mismatches. In general a low ionic analyte solution will give a negative jump compared to the flow buffer. In general, a buffer mismatch of 1 mM NaCl will give a jump of 20 RU in a Biacore type of instrument on a CM5 sensor chip.
Furthermore, the dilution of the analyte in the flow buffer may alter the total salt content. In addition the analyte itself may have influence on the behaviour of the SPR-measurement.
The buffer mismatch can be eliminated by dialysing the analyte. However, if the problem persists and is proportional to the analyte concentration it is most likely originating from the analyte itself.

1.2. Volume exclusion
Some negative binding responses originate from different behaviour of the reference and ligand channel to the injected analyte solution (buffer composition, additives, pH, analyte concentration). This is explained by the difference in ligand density on the sensor chip. When immobilizing, the actual amount of the ligand differs between the sensor surfaces. This difference is not only in response units or in molarity but also in the volume the ligand is occupying in the matrix. When the flow buffer is replaced by the analyte (buffer), the matrix can swell or shrink depending on the difference. Because of the different ligand volume in the matrix, the volume exclusion of the buffer is different, hence the reaction on buffer changes (2, 3).
In situations with for instance DMSO or glycerol in the analyte buffer, differences can be relatively large and result in negative responses in the original curves, after reference subtraction or double referencing. In these cases it can be beneficial to make a calibration plot to compensate for the volume exclusion (1, 3).

1.3. Non-specific matrix interaction
Some negative binding responses originate from the interaction of the analyte and sensor chip matrix. Especially the dextran based sensor chip can have high affinity for small compounds. Adding CM-dextran (0.1 - 1 mg/ml) to the flow buffer can lower the non-specific interaction with the dextran matrix. Other solutions are to use sensor chips with no dextran or other types of linkers, like alginate (Bio-Rad) or dendritic polyglycerol (Xantec). It is even possible to make your own sensor chip surface. In this way you can add a SAM to the sensor gold layer that will suit you best (4).

1.4. Non-specific reference interaction
Some negative binding responses originate from non-specific binding of the analyte to the ligand on reference channel. This should be obvious by overlaying the raw data of the reference and ligand channel. From the sensorgram you can sometimes deduce if this is a strong or weak non-specific interaction (observe the dissociation). If the interaction seems to be weak, adding extra detergent (e.g. 0.02%), extra salt (e.g. 250 mM NaCl) or changing the pH can suppress this interaction. Adding BSA (0.1 – 1 mg/ml) or CM-dextran (0.1 - 1 mg/ml) to the flow buffer can lower the non-specific interaction. In addition, reversing the interaction system can be a answer to this problem.

The reference surface is in all situations crucial. The easiest surface is one which is native and thus unmodified. Taking the dextran based sensor chips (e.g. Biacore CM5), this chip contains a lot of carboxyl groups (-COOH) which become negatively charged at pH ~7. Activating (NHS/EDC) and deactivating with ethanolamine replaces the carboxyl groups with a hydroxyl group (-OH) which are less negatively charged at a physiological pH.
Immobilizing the reference channel with a non-related ligand (protein, oligo) is not always straight forward. Often BSA is chosen because it is readily available and pure. However BSA can bind a lot of molecules and should not be the first choice. In addition, albumin (when ionized in water at pH 7.4, as found in the body) is negatively charged.
Other molecules that can be used are for instance non-related antibodies (IgG). Most laboratories have IgG for detection of proteins of interest and one can choose an antibody that is not binding to the analyte of interest and use as a reference surface.
The amount of ligand to be immobilized as a reference surface is the next difficult part. Start with immobilizing an equal amount of response units compared to the ligand of interest. This will give a similar buffer volume exclusion compared with ligand of interest. Only testing and comparing will show if you have to immobilize less or more.

1.5. Solving negative curves
Steps you can take to test the suitability of your reference channel (you can make a dedicated chip for this):
- Inject the analyte at the highest concentration over a native surface
- Inject the analyte at the highest concentration over a deactivated
- Inject the analyte at the highest concentration over a BSA or IgG surface

Steps you can take to reduce non-specific binding and lower difference between reference and ligand channel
- Add extra detergent or salt to the flow buffer
- Add BSA or CM-dextran to the flow buffer
- Add blank injections for double referencing
- Add calibration injections and make a calibration plot to correct for volume exclusion effects

In addition, consider reversing the interaction system and different sensor chip matrices.

1.6. References
1. Frostell-Karlsson, A., Remaeus, A., Roos, H., et al.; Biosensor analysis of the interaction between immobilized human serum albumin and drug compounds for prediction of human serum albumin binding levels. J.Med.Chem. (43) 10: 1986-1992; 2000.
2. Karlsson, R.; Real-time competitive kinetic analysis of interactions between low-molecular-weight ligands in solution and surface-immobilized receptors. Analytical Biochemistry (221) 1: 142-151; 1994.
3. Karlsson, R., Kullman-Magnusson, M., inen, M. D., et al.; Biosensor Analysis of Drug-Target Interactions: Direct and Competitive Binding Assays for Investigation of Interactions between Thrombin and Thrombin Inhibitors. Analytical Biochemistry (278) 1: 1-13; 2000.
4. Metzger, J., von Landenberg, P., Kehrel, M., et al.; Biosensor analysis of beta2-glycoprotein I-reactive autoantibodies: evidence for isotype-specific binding and differentiation of pathogenic from infection-induced antibodies. clin. chem. (53) 6: 1137-43; 2007.
5. Rich, R. L. and Myszka, D. G.; Survey of the year 2001 commercial optical biosensor literature. J.Mol.Recognit. (15) 6: 352-376; 2002.