Troubleshooting and Artefacts

How to use this guide#

Find your symptom. Read the causes in the order given — they are ordered by how often they turn out to be the answer, not by how interesting they are. Run the identifying test before changing anything, because changing two things at once turns a diagnosable problem into a mysterious one.

Symptom: the baseline will not sit still#

Steady upward or downward drift, on both channels

Common-mode, therefore systemic. In order of likelihood: incomplete equilibration after a buffer change; a temperature that has not settled, to which the signal is acutely sensitive (Jung et al., 1998); air slowly coming out of an undegassed buffer; a partially blocked flow path raising back-pressure.

Test: leave the system running in buffer for 30 minutes and watch. If the drift decays, it was equilibration. If it is linear and persistent, look at temperature and buffer.

Downward drift on the active channel only

The ligand is leaving. Either it was never covalently attached and is slowly desorbing, or — with capture formats — the capture interaction is dissociating. His-tag/NTA capture drifts characteristically for exactly this reason (Nieba et al., 1997).

Test: run a cycle with no analyte and measure the slope. That slope is your ligand loss rate; it can be subtracted, but if it is more than a few percent of R_max over a cycle you need a different immobilisation.

Sudden jumps

A bubble, or a pressure event. Bubbles produce a sharp spike and often a permanent baseline offset because they can strip material from the surface. Degas buffers, check that the sample vials are not running dry, and make sure the surfactant concentration is right.

Symptom: the curves are the wrong shape#

Square pulses that return exactly to baseline

A pure bulk shift: your sample and running buffers differ in refractive index (Myszka, 1999). Buffer-exchange the analyte into the actual running buffer. Note that for small-molecule work this is a DMSO problem and needs the solvent correction of small molecules and fragments.

Association looks linear; dissociation drags

Mass transport limitation (kinetics and mass transport) (Schuck & Minton, 1996). Test: halve the ligand density. If fitted k_a rises, confirmed (Myszka et al., 1998).

Dissociation has a fast phase then a stubborn tail

Avidity or surface heterogeneity (going beyond a 1:1 model). Test: density series. A tail that shortens with lower density is avidity; a tail that does not is heterogeneity.

Negative responses

Almost always a referencing artefact: the reference channel is binding more than the active channel, so subtraction goes negative. This happens when the reference surface is more highly charged than the ligand-coated active surface. Fix the reference surface rather than the arithmetic. Genuine negative responses do exist — displacement of a pre-bound species, or a large refractive index decrement — but they are rare and should be argued for, not assumed.

Response never saturates and exceeds the theoretical R_max

More mass is arriving than the stoichiometry allows. Analyte aggregation is the usual cause; promiscuous surface binding is the other (Giannetti et al., 2008). Test: compute the theoretical R_max from equation 1.2 and compare. If you are at 3 × R_max, this is not binding to your ligand.

Symptom: the affinity is at the edge of what SPR can do#

Very tight binding (K_D below ~100 pM)

The problem is that k_d is too slow to observe and the surface is difficult to regenerate.

• Extend the dissociation phase dramatically — 30 to 60 minutes, sometimes hours (Drake et al., 2004). Instrument time is cheaper than a wrong constant.
• Reduce the ligand density further, so that rebinding does not artificially slow the observed decay.
• Consider whether what you are measuring is avidity rather than affinity. Sub-picomolar K_D from a bivalent analyte is usually an artefact (Nieba et al., 1996).
• If k_d genuinely cannot be observed, say so and report a limit, rather than reporting the number the software returned from a 5-minute window.

Very weak binding (K_D above ~100 µM)

Now the problem is reaching high enough concentrations without artefacts.

• Bulk shift scales with analyte concentration and will dominate. Match buffers scrupulously and reference carefully.
• Solubility and aggregation become limiting. Check the analyte at the top concentration by DLS or SEC.
• Steady-state analysis is usually the right method here, since the kinetics will be too fast to resolve (Myszka, 2000).
• Consider whether the interaction is real at all. Very weak, non-saturating binding is what non-specific adsorption looks like.

Symptom: it worked last week#

1. Compare the sensorgrams, not the constants. Overlay last week’s raw curves on this week’s. If the shapes differ, it is chemistry or surface; if the shapes match and only the fitted numbers differ, it is analysis.
2. Check the analyte. Freeze–thaw cycles aggregate protein. Aggregated analyte gives higher apparent responses and slower apparent off-rates (Giannetti et al., 2008). Run a fresh aliquot.
3. Check the surface age. Chips degrade in storage, and dextran surfaces dry out. Note the chip’s history.
4. Check the buffer batch. A new bottle of buffer with slightly different pH or ionic strength changes both the bulk shift and, for electrostatically driven interactions, the actual k_a (Day et al., 2002).
5. Check the instrument. Run a standard interaction you have historical data for. This is the reason to keep a reference system — a well-behaved pair you can inject to ask "is the instrument the problem?" without confounding it with your unknown.

Sources cited on this page

Listed alphabetically. Each badge records whether the bibliographic record was confirmed against Crossref. unverified marks a real, deliberately chosen source whose volume and page numbers we have not yet machine-checked — it is not a comment on the science.

• Day et al., 2002Y. S. N. Day, C. L. Baird, R. L. Rich, D. G. Myszka (2002). Direct comparison of binding equilibrium, thermodynamic, and rate constants determined by surface- and solution-based biophysical methods. Protein Science 11, 1017–1025. doi:10.1110/ps.4330102 unverified
  The head-to-head comparison of SPR against solution methods on the same systems. The primary source for the claim that a well-run surface measurement agrees with solution thermodynamics.
• Drake et al., 2004A. W. Drake, D. G. Myszka, S. L. Klakamp (2004). Characterizing high-affinity antigen/antibody complexes by kinetic- and equilibrium-based methods. Analytical Biochemistry 328, 35–43. doi:10.1016/j.ab.2004.01.031 unverified
  What can and cannot be measured when the off-rate is very slow.
• Giannetti et al., 2008A. M. Giannetti, B. D. Koch, M. F. Browner (2008). Surface plasmon resonance based assay for the detection and characterization of promiscuous inhibitors. Journal of Medicinal Chemistry 51, 574–580. doi:10.1021/jm700952v unverified
  The primary source for using superstoichiometric, non-saturating responses to identify aggregating and promiscuous compounds.
• Jung et al., 1998L. S. Jung, C. T. Campbell, T. M. Chinowsky, M. N. Mar, S. S. Yee (1998). Quantitative interpretation of the response of surface plasmon resonance sensors to adsorbed films. Langmuir 14, 5636–5648. doi:10.1021/la971228b unverified
  The reference treatment of how a thin adsorbed film of known thickness and refractive index maps onto an SPR shift, including the exponential weighting of the evanescent field.
• Katsamba et al., 2006P. S. Katsamba, I. Navratilova, M. Calderon-Cacia, et al. (2006). Kinetic analysis of a high-affinity antibody/antigen interaction performed by multiple Biacore users. Analytical Biochemistry 352, 208–221. unverified
• Myszka et al., 1998D. G. Myszka, X. He, M. Dembo, T. A. Morton, B. Goldstein (1998). Extending the range of rate constants available from BIACORE: interpreting mass transport-influenced binding data. Biophysical Journal 75, 583–594. doi:10.1016/S0006-3495(98)77549-6 verified
  Shows transport can be fitted rather than merely avoided, and defines the transport coefficient kₜ.
• Myszka, 1999D. G. Myszka (1999). Improving biosensor analysis. Journal of Molecular Recognition 12, 279–284. unverified
  Origin of double referencing and blank-injection subtraction as standard practice.
• Myszka, 2000D. G. Myszka (2000). Kinetic, equilibrium, and thermodynamic analysis of macromolecular interactions with BIACORE. Methods in Enzymology 323, 325–340. doi:10.1016/S0076-6879(00)23372-7 unverified
• Nieba et al., 1996L. Nieba, A. Krebber, A. Plückthun (1996). Competition BIAcore for measuring true affinities: large differences from values determined from binding kinetics. Analytical Biochemistry 234, 155–165. doi:10.1006/abio.1996.0067 unverified
  A direct demonstration that surface-measured kinetic constants can diverge substantially from solution affinities, and a solution-competition format that avoids the problem.
• Nieba et al., 1997L. Nieba, S. E. Nieba-Axmann, A. Persson, et al. (1997). BIACORE analysis of histidine-tagged proteins using a chelating NTA sensor chip. Analytical Biochemistry 252, 217–228. doi:10.1006/abio.1997.2326 unverified
  Characterises His-tag capture on NTA surfaces, including the baseline drift caused by its finite stability.
• Papalia et al., 2006G. A. Papalia, S. Leavitt, M. A. Bynum, et al. (2006). Comparative analysis of 10 small molecules binding to carbonic anhydrase II by different investigators using Biacore technology. Analytical Biochemistry 359, 94–105. unverified
  A benchmark study in which many labs measured the same interactions; the spread between labs is the honest measure of SPR reproducibility.
• Schuck & Minton, 1996P. Schuck, A. P. Minton (1996). Analysis of mass transport-limited binding kinetics in evanescent wave biosensors. Analytical Biochemistry 240, 262–272. doi:10.1006/abio.1996.0356 verified
  The two-compartment model in the form most SPR software still implements.