Skip to main content
SpringerLink
Log in

Distributions-per-Level: A Means of Testing Level Detectors and Models of Patch-Clamp Data

  • Published:
The Journal of Membrane Biology Aims and scope Submit manuscript

Abstract

Level or jump detectors generate the reconstructed time series from a noisy record of patch-clamp current. The reconstructed time series is used to create dwell-time histograms for the kinetic analysis of the Markov model of the investigated ion channel. It is shown here that some additional lines in the software of such a detector can provide a powerful new means of patch-clamp analysis. For each current level that can be recognized by the detector, an array is declared. The new software assigns every data point of the original time series to the array that belongs to the actual state of the detector. From the data sets in these arrays distributions-per-level are generated. Simulated and experimental time series analyzed by Hinkley detectors are used to demonstrate the benefits of these distributions-per-level. First, they can serve as a test of the reliability of jump and level detectors. Second, they can reveal beta distributions as resulting from fast gating that would usually be hidden in the overall amplitude histogram. Probably the most valuable feature is that the malfunctions of the Hinkley detectors turn out to depend on the Markov model of the ion channel. Thus, the errors revealed by the distributions-per-level can be used to distinguish between different putative Markov models of the measured time series.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. A. Albertsen U.P. Hansen (1994) ArticleTitleEstimation of kinetic rate constants from multi-channel recordings by a direct fit of the time series. Biophys. J. 67 1393–1403 Occurrence Handle1:CAS:528:DyaK2cXmt1Gls7g%3D Occurrence Handle7529579

    CAS  PubMed  Google Scholar 

  2. F.G. Ball J.A. Rice (1992) ArticleTitleStochastic models for ion channels: introduction and bibliography. Math. Biosci. 112 189–206 Occurrence Handle10.1016/0025-5564(92)90023-P Occurrence Handle1:STN:280:ByyC2cvos1Y%3D Occurrence Handle1283350

    Article  CAS  PubMed  Google Scholar 

  3. R. Blunck U. Kirst T. Rießner U.P. Hansen (1998) ArticleTitleHow powerful is the dwell-time analysis of multi-channel records? J. Membrane Biol. 165 19–35 Occurrence Handle10.1007/s002329900417 Occurrence Handle1:CAS:528:DyaK1cXlsFOntrY%3D

    Article  CAS  Google Scholar 

  4. A. Caliebe U. Rösler U.P. Hansen (2002) ArticleTitleA χ2 test for model determination and sublevel detection in ion channel analysis. J. Membrane Biol. 185 25–41 Occurrence Handle10.1007/s00232-001-0107-0 Occurrence Handle1:CAS:528:DC%2BD38XitFyrt7Y%3D

    Article  CAS  Google Scholar 

  5. D. Colquhoun C.J. Hatton A.G. Hawkes (2003) ArticleTitleThe quality of maximum likelihood estimates of ion channel rate constants. J. Physiol. 547 699–728 Occurrence Handle10.1113/jphysiol.2002.034165 Occurrence Handle1:CAS:528:DC%2BD3sXjt1Slsbc%3D Occurrence Handle12562901

    Article  CAS  PubMed  Google Scholar 

  6. D. Colquhoun A.G. Hawkes K. Srodzinski (1996) ArticleTitleJoint distributions of apparent open times and shut times of single ion channels and the maximum likelihood fitting of mechanisms. Phil. Trans. R. Soc. Lond. A 354 2555–2590

    Google Scholar 

  7. S. Draber U.P. Hansen (1994) ArticleTitleFast single-channel measurements resolve the blocking effect of Cs+ on the K+ channel. Biophys. J. 67 120–129 Occurrence Handle1:CAS:528:DyaK2cXlsFWns7k%3D Occurrence Handle7918979

    CAS  PubMed  Google Scholar 

  8. S. Draber R. Schultze (1994a) ArticleTitleCorrection for missed events based on a realistic model of a detector. Biophys. J. 66 191–202 Occurrence Handle1:STN:280:ByuC2snmt1M%3D

    CAS  Google Scholar 

  9. S. Draber R. Schultze (1994b) ArticleTitleDetection of jumps in single-channel data containing subconductance levels. Biophys. J. 67 1404–1413 Occurrence Handle1:CAS:528:DyaK2cXmt1Grs7g%3D

    CAS  Google Scholar 

  10. A. Farokhi M. Keunecke U.P. Hansen (2000) ArticleTitleThe Anomalous Mole Fraction Effect in Chara: Gating at the edge of temporal resolution. Biophys. J. 79 3072–3082 Occurrence Handle1:CAS:528:DC%2BD3MXitFem Occurrence Handle11106613

    CAS  PubMed  Google Scholar 

  11. D.R. Fredkin J.A. Rice (1992) ArticleTitleMaximum likelihood estimation and identification directly from single-channel recordings. Proc. Roy. Soc. Lond. B 249 125–132 Occurrence Handle1:STN:280:ByyD1cjlvVw%3D

    CAS  Google Scholar 

  12. R. FitzHugh (1983) ArticleTitleStatistical properties of the asymmetric random telegraph signal with application to single channel analysis. Mathematical Bioscience 64 75–89 Occurrence Handle10.1016/0025-5564(83)90028-7

    Article  Google Scholar 

  13. U.P. Hansen O. Cakan M. Abshagen A. Farokhi (2003) ArticleTitleGating models of the Anomalous Mole Fraction Effect of single-channel current in Chara. J. Membrane Biol. 192 45–63 Occurrence Handle10.1007/s00232-002-1063-z Occurrence Handle1:CAS:528:DC%2BD3sXit1ShtbY%3D

    Article  CAS  Google Scholar 

  14. U.P. Hansen J. Tittor D. Gradmann (1983) ArticleTitleInterpretation of current-voltage relationships for “active” ion transport systems: II. Nonsteady-state reaction kinetic analysis of class I mechanisms with one slow time-constant. J. Membrane Biol. 75 141–169

    Google Scholar 

  15. S. Klein J. Timmer J. Honerkamp (1997) ArticleTitleAnalysis of multi channel patch clamp recordings by Hidden Markov models. Biometrics 53 870–884 Occurrence Handle1:STN:280:ByiH2s%2FltFA%3D Occurrence Handle9333349

    CAS  PubMed  Google Scholar 

  16. H.G. Klieber D. Gradmann (1993) ArticleTitleEnzyme kinetics of the prime K+ channel in the tonoplast of Chara: selectivity and inhibition. J. Membrane Biol. 132 253–265 Occurrence Handle1:CAS:528:DyaK3sXktVGjsrs%3D

    CAS  Google Scholar 

  17. S.J. Korn R. Horn (1988) ArticleTitleStatistical discrimination of fractal and Markov models of single-channel gating. Biophys. J. 54 871–877 Occurrence Handle1:STN:280:BiaB3cjmslI%3D Occurrence Handle2468367

    CAS  PubMed  Google Scholar 

  18. B.L. Moss K.L. Magleby (2001) ArticleTitleGating and conductance properties of BK channels are modulated by the S9-S10 tail domain of the α subunit. A study of mSlol and mSlo3 wild-type and chimeric channels. J. Gen. Physiol. 118 711–734 Occurrence Handle10.1085/jgp.118.6.711 Occurrence Handle1:CAS:528:DC%2BD3MXpt12ksr4%3D Occurrence Handle11723163

    Article  CAS  PubMed  Google Scholar 

  19. T. Riessner (1998) Level Detection and Extended Beta Distributions for the Analysis of Fast Rate Constants of Markov Processes in Sampled Data. PhD thesis, Kiel, Germany and Shaker-Verlag Aachen

    Google Scholar 

  20. T. Riessner F. Woelk M. Abshagen U.P. Hansen (2002) ArticleTitleA new level detector for ion channel analysis. J. Membrane Biol. 189 105–118 Occurrence Handle10.1007/s00232-002-1011-y Occurrence Handle1:CAS:528:DC%2BD38Xnt1yms78%3D

    Article  CAS  Google Scholar 

  21. R. Schultze S. Draber (1993) ArticleTitleA nonlinear filter algorithm for detection of jumps in patch-clamp data. J. Membrane Biol. 132 41–52 Occurrence Handle1:STN:280:ByyB3M%2Fns1Q%3D

    CAS  Google Scholar 

  22. J. Shi J. Cui (2001) ArticleTitleIntracellular Mg2+ enhances the function of BK-type Ca2+-activated K+ channel. J. Gen. Physiol. 118 589–605 Occurrence Handle10.1085/jgp.118.5.589 Occurrence Handle1:CAS:528:DC%2BD3MXoslWnsbg%3D Occurrence Handle11696614

    Article  CAS  PubMed  Google Scholar 

  23. G. Yellen (1984) ArticleTitleIonic permeation and blockade in Ca2+ activated K+ channels of bovine chromaffin cells. J. Gen. Physiol. 84 157–186 Occurrence Handle1:CAS:528:DyaL2cXlt1Gisrw%3D Occurrence Handle6092514

    CAS  PubMed  Google Scholar 

  24. G.F. Yeo R.K. Milne R.O. Edeson B.W. Madsen (1988) ArticleTitleStastistical inference from single channel records: two state Markov model with limited time resolution. Proc. R. Soc. Lond. B 235 63–94 Occurrence Handle1:STN:280:BiaC1cvms1Y%3D Occurrence Handle2467307

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This work was supported by the Deutsche Forschungsgemeinschaft. We are grateful to Prof. Dr. J. Dainty, Norwich, UK, for critical reading and to Prof. Dr. U. Seydel and Dr. A. Schromm for the gift of HEK cells expressing Maxi-K channels.

Author information

Authors and Affiliations

  1. Center of Biochemistry and Molecular Biology, Leibnizstr. 11, 24098 Kiel, Germany

    I. Schröder, T. Huth, V. Suitchmezian, S. Schnell & U. P. Hansen

  2. Bioenergetics Institute, Adam Mickiewicz University, Poznan, Poland

    J. Jarosik

Authors
  1. I. Schröder
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. T. Huth
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. V. Suitchmezian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. J. Jarosik
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. S. Schnell
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. U. P. Hansen
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to U. P. Hansen.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Schröder, I., Huth, T., Suitchmezian, V. et al. Distributions-per-Level: A Means of Testing Level Detectors and Models of Patch-Clamp Data . J. Membrane Biol. 197, 49–58 (2004). https://doi.org/10.1007/s00232-003-0641-z

Download citation

  • Received:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00232-003-0641-z

Keywords

Search

Navigation