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Hidden Markov analysis of improved bandwidth mechanosensitive ion channel data

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Abstract

The gating behaviour of a single ion channel can be described by hidden Markov models (HMMs), forming the basis for statistical analysis of patch clamp data. Extensive improved bandwidth (25 kHz, 50 kHz) data from the mechanosensitive channel of large conductance in Escherichia coli  were analysed using HMMs, and HMMs with a moving average adjustment for filtering. The aim was to determine the number of levels, and mean current, mean dwell time and proportion of time at each level. Parameter estimates for HMMs with a moving average adjustment for low-pass filtering were obtained using an expectation-maximisation algorithm that depends on a generalisation of Baum’s forward–backward algorithm. This results in a simpler algorithm than those based on meta-states and a much smaller parameter space; hence, the computational load is substantially reduced. In addition, this algorithm maximises the actual log-likelihood rather than that for a related meta-state process. Comprehensive data analyses and comparisons across all our data sets have consistently shown five subconducting levels in addition to the fully open and closed levels for this channel.

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Acknowledgments

The experimental part of the study was supported by APP1047980 grant from the National Health and Medical Research Council of Australia to B.M. We also thank Dr. Charles Cox for his comments on the manuscript. I.M.A. thanks the government of Saudi Arabia, King Khalid University and the Cultural Mission of Royal Embassy of Saudi Arabia in Australia for support during his PhD study. The authors thank the referees for comments that helped improve the paper.

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Author notes

  1. Ibrahim M. Almanjahie

    Present address: Department of Mathematics, King Khalid University, Abha, 61413, Saudi Arabia

Authors and Affiliations

  1. School of Mathematics and Statistics, University of Western Australia, Crawley, WA, 6009, Australia

    Ibrahim M. Almanjahie, R. Nazim Khan & Robin K. Milne

  2. Department of Molecular Cell Physiology and Bio-Ionomics, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, 602-8566, Japan

    Takeshi Nomura

  3. Mechanosensory Biophysics Laboratory, Victor Chang Cardiac Research Institute, Darlinghurst, NSW, 2010, Australia

    Boris Martinac

Authors
  1. Ibrahim M. Almanjahie
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  2. R. Nazim Khan
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  3. Robin K. Milne
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  4. Takeshi Nomura
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  5. Boris Martinac
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Corresponding author

Correspondence to R. Nazim Khan.

Additional information

Special Issue: Biophysics of Mechanotransduction.

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Almanjahie, I.M., Khan, R.N., Milne, R.K. et al. Hidden Markov analysis of improved bandwidth mechanosensitive ion channel data. Eur Biophys J 44, 545–556 (2015). https://doi.org/10.1007/s00249-015-1060-7

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  • DOI: https://doi.org/10.1007/s00249-015-1060-7

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