A Minimal Kinetic Model of the Activity of the 107 pS Channel of the Inner Membrane of Mitochondria

  • C. Ballarin
  • M. C. Sorgato
  • O. Moran
Part of the NATO ASI Series book series (volume 83)

Abstract

Large conductances of different kind have been found in the inner membrane of mitochondria by direct observation of the membrane with a patch clamp electrode (Moran and Sorgato, 1992; Szabo and Zoratti, 1992; Kinnally et al., 1992). The role of any of these is, however, still obscure. The first high conductance pathway to be detected has been a slightly anionic 107 pS channel (mCS, mitochondrial Centum pico-Siemens), observed in situ (i.e., in mitoplasts, which are mitochondria largely deprived of the outer membrane) as well as after reconstitution in large liposomes of both mitochondrial membranes, or of a fraction of the inner one (Sorgato et al., 1987, 1989; Moran et al., 1990; Moran and Sorgato, 1992). Interestingly, the mCS channel possesses a strong and peculiar voltage sensitivity. At high positive or low negative values of the applied potential difference the channel is active, whereas at high negative potentials the channel is in the non-conductive state. As mitochondria sustain a membrane potential negative inside (on the matrix side), the voltage dependence displayed by the channel appears rather intriguing so as to raise the question of whether the voltage gating occurs as such in vivo or whether it is consequent to the experimental conditions used. In fact, cytosolic or mitochondrial matrix components, which might be involved in regulating the channel, are likely to get lost during the preparation of mitoplasts. On the other hand, the presence of the mCS channel in all tissues so far tested (liver, heart and adipose tissue) (Sorgato et al., 1987, 1989; Klitsch and Siemen, 1991) argues strongly in favour of a role of physiological importance.

Keywords

Closed State Macroscopic Current High Negative Potential Large Liposome Applied Potential Difference 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1994

Authors and Affiliations

  • C. Ballarin
    • 1
  • M. C. Sorgato
    • 1
  • O. Moran
    • 2
  1. 1.Dipartimento di Chimica BiologicaPadovaItaly
  2. 2.Istituto CNR di Cibernetica e BiofisicaGenovaItaly

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