Volume, pH, and ion-content regulation in human red cells: Analysis of transient behavior with an integrated model

Lew, Virgilio L.; Bookchin, Robert M.

doi:10.1007/bf01869016

Cited by 184 publications

(182 citation statements)

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“…By contrast with analytical approaches, numerical computation allows flexibility in experimentally guided model design, and it is amenable to representing the temporal kinetics of interacting processes (Lew and Bookchin, 1986;Mauritz et al, 2009). It avoids solutions that may appear to provide simplified or explicit equations for a process but that sterilize the predictive power of model implementation.…”

Section: Rationale For the Modeling Approachmentioning

confidence: 99%

“…OnGuard2 uses the same iterative computational strategy that was applied successfully in our original implementation of the OnGuard platform Hills et al, 2012;Blatt et al, 2014) and, in the past, in other physiological systems (Lew et al, 1979;Lew and Bookchin, 1986;Mauritz et al, 2009). In operation, OnGuard2 calculates and logs the dynamic adjustments of ion flux, compartmental composition, and membrane voltage using the sets of constants, nonlinear differential equations, and parameters contained within the model, while obeying the fundamental physical constraints of mass and charge conservation.…”

Section: Appendix Deriving Onguard2 With Micro-macro Couplingmentioning

confidence: 99%

“…Furthermore, all mechanistic models to date have sought analytic solutions for endpoint or stationary states only. They therefore fail to address the wealth of information available relating to the temporal kinetics for stomatal movements and transpiration.By contrast with analytical approaches, numerical computation allows flexibility in experimentally guided model design, and it is amenable to representing the temporal kinetics of interacting processes (Lew and Bookchin, 1986;Mauritz et al, 2009). It avoids solutions that may appear to provide simplified or explicit equations for a process but that sterilize the predictive power of model implementation.…”

mentioning

confidence: 99%

“…It generates a new total solute content for the guard cell at the end of each time interval, using this value to calculate the new total and compartmental cell volumes and ion concentrations, the guard cell turgor, and stomatal aperture. Thus, like other computational approaches (Lew et al, 1979;Lew and Bookchin, 1986;Mauritz et al, 2009), OnGuard does not transit between two predefined states but, instead, begins from a starting, or reference, state Hills et al, 2012), from which a new state evolves over each time increment.Models resolved with this platform successfully recapitulated a wide range of known stomatal behaviors, including transport, diurnal changes in aperture, their dependencies on extracellular pH, KCl, and CaCl 2 concentrations , and oscillations in [Ca 2+ …”

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confidence: 99%

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Unexpected Connections between Humidity and Ion Transport Discovered Using a Model to Bridge Guard Cell-to-Leaf Scales

et al. 2017

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Stomatal movements depend on the transport and metabolism of osmotic solutes that drive reversible changes in guard cell volume and turgor. These processes are defined by a deep knowledge of the identities of the key transporters and of their biophysical and regulatory properties, and have been modeled successfully with quantitative kinetic detail at the cellular level. Transpiration of the leaf and canopy, by contrast, is described by quasilinear, empirical relations for the inputs of atmospheric humidity, CO 2 , and light, but without connection to guard cell mechanics. Until now, no framework has been available to bridge this gap and provide an understanding of their connections. Here, we introduce OnGuard2, a quantitative systems platform that utilizes the molecular mechanics of ion transport, metabolism, and signaling of the guard cell to define the water relations and transpiration of the leaf. We show that OnGuard2 faithfully reproduces the kinetics of stomatal conductance in Arabidopsis thaliana and its dependence on vapor pressure difference (VPD) and on water feed to the leaf. OnGuard2 also predicted with VPD unexpected alterations in K + channel activities and changes in stomatal conductance of the slac1 Cl 2 channel and ost2 H + -ATPase mutants, which we verified experimentally. OnGuard2 thus bridges the micro-macro divide, offering a powerful tool with which to explore the links between guard cell homeostasis, stomatal dynamics, and foliar transpiration. INTRODUCTIONStomata provide the main pathway for CO 2 entry for photosynthesis and for transpirational water loss across the leaf epidermis. Pairs of guard cells surround each stoma, regulating the aperture to balance the often conflicting demands for CO 2 and for water conservation. Guard cells open and close the pore, driven by osmotic solute uptake and loss, notably of K + and Cl 2 , and by the synthesis and metabolism of organic solutes, especially sucrose (Suc) and malate (Mal) (Willmer and Fricker, 1996;Kim et al., 2010;Roelfsema and Hedrich, 2010;Lawson and Blatt, 2014;Jezek and Blatt, 2017). A number of well-defined signals, including light, CO 2 , and the water stress hormone abscisic acid (ABA), modulate transport and solute accumulation to alter cell volume, turgor, and stomatal aperture. Much research at the cellular level has focused on these inputs and their connection to stomatal movements, especially stomatal closing. Studies have highlighted both Ca 2+ -independent and Ca 2+ -dependent signaling, including elevated free cytosolic Ca 2+ concentration ([Ca 2+ ] i ), cytosolic pH (pH i ), protein kinases, and phosphatases, that inactivate inward-rectifying K + channels and activate Cl 2 channels and outward-rectifying K + channels to bias the membrane for solute loss (Blatt et al., 1990;Lemtiri-Chlieh and MacRobbie, 1994; Blatt, 1998, 1999;Marten et al., 2007;Assmann and Jegla, 2016;Jezek and Blatt, 2017).At the tissue and whole-plant levels, by contrast, attention has been drawn to inputs closely tied to photosynthesis, including tra...

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Section: Rationale For the Modeling Approachmentioning

confidence: 99%

Section: Appendix Deriving Onguard2 With Micro-macro Couplingmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Unexpected Connections between Humidity and Ion Transport Discovered Using a Model to Bridge Guard Cell-to-Leaf Scales

et al. 2017

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“…In our calculations, we used a computer program developed on the basis of the integrated red cell model of transmembrane transport by Lew and Bookchin [45], which has been upgraded to account for some recently found effects of ionic and specific transport [46]. This program involves the kinetic parameters of most of the known transport systems and enables one to calculate the ionic concentrations, the pH and the water contents inside the cell for each given composition and pH in the outer medium.…”

Section: Transmembrane Potential and Shape Indexmentioning

confidence: 99%

On the mechanism of stomatocyte–echinocyte transformations of red blood cells: experiment and theoretical model

Tachev¹,

Danov²,

Kralchevsky³

2004

Colloids and Surfaces B: Biointerfaces

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This study represents an attempt to achieve a better understanding of the stomatocyte-echinocyte transition in the shape of red blood cells. We determined experimentally the index of cell shape at various ionic strengths and osmolarities for native and trypsin-treated human erythrocytes. For every given composition of the outer phase, we calculated the ionic strength in the cells and the transmembrane electric potential using a known theoretical model. Next, we described theoretically the electric double layers formed on both sides of the cell membrane, and derived expressions for the tensions of the two membrane leaflets. Taking into account that the cell-shape index depends on the tension difference between the two leaflets, we fitted the experimental data with the constructed physicochemical model. The model, which agrees well with the experiment, indicates that the tension difference between the two leaflets is governed by the different adsorptions of counterions at the two membrane surfaces, rather than by the direct contribution of the electric double layers to the membrane tension. Thus, with the rise of the ionic strength, the counterion adsorption increases stronger at the outer leaflet, whose stretching surface pressure becomes greater, and whose area expands relative to that of the inner leaflet. Hence, there is no contradiction between the bilayer-couple hypothesis and the electric double layer theory, if the latter is upgraded to account for the effect of counterion-adsorption on the membrane tension. The developed quantitative model can be applied to predict the shape index of cells upon a stomatocyte-discocyte-echinocyte transformation at varying composition of the outer medium.

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Intracellular transmission in cell volume regulation in Ehrlich ascites tumor cells

Hoffmann

1997

J. Exp. Zool.

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Volume, pH, and ion-content regulation in human red cells: Analysis of transient behavior with an integrated model

Cited by 184 publications

References 56 publications

Unexpected Connections between Humidity and Ion Transport Discovered Using a Model to Bridge Guard Cell-to-Leaf Scales

Unexpected Connections between Humidity and Ion Transport Discovered Using a Model to Bridge Guard Cell-to-Leaf Scales

On the mechanism of stomatocyte–echinocyte transformations of red blood cells: experiment and theoretical model

Intracellular transmission in cell volume regulation in Ehrlich ascites tumor cells

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