Literature DB >> 27857584

Modeling of the gap junction of pancreatic β-cells and the robustness of insulin secretion.

Tomoki Kitagawa1, Noriaki Murakami1, Seido Nagano1.   

Abstract

Pancreatic β-cells are interconnected by gap junctions, which allow small molecules to pass from cell to cell. In spite of the importance of the gap junctions in cellular communication, modeling studies have been limited by the complexity of the system. Here, we propose a mathematical gap junction model that properly takes into account biological functions, and apply this model to the study of the β-cell cluster. We consider both electrical and metabolic features of the system. Then, we find that when a fraction of the ATP-sensitive K+ channels are damaged, robust insulin secretion can only be achieved by gap junctions. Our finding is consistent with recent experiments conducted by Rocheleau et al. Our study also suggests that the free passage of potassium ions through gap junctions plays an important role in achieving metabolic synchronization between β-cells.

Entities:  

Keywords:  gap junctions; pancreatic β-cells; robustness; synchronization

Year:  2010        PMID: 27857584      PMCID: PMC5036665          DOI: 10.2142/biophysics.6.37

Source DB:  PubMed          Journal:  Biophysics (Nagoya-shi)        ISSN: 1349-2942


Synchronization of rhythms via receptors plays important roles in a variety of cellular processes. Cellular slime mold1, in which rich quantitative experimental data are available, has played a significant role in studies of rhythm synchronization via cAMP receptors. A synchronization scheme developed for the cellular slime mold2 has been generalized as a universal mathematical scheme3–5. Another important player in cellular synchronization is the gap junction. Most cells in animal tissues including pancreatic β-cells are in communication with their neighbors both electrically and metabolically via gap junctions, which allow the passage of small water-soluble ions and molecules smaller than ∼ 1000 daltons. The phenomenon of synchronization via gap junctions in the pancreatic β-cells has been extensively investigated6,7. Nonetheless, the study of gap junctions is still in a challenging stage in large part because of the complex relationship between structure and function. Pancreatic β-cells, located in the islets of Langerhans, secrete insulin in response to the level of glucose in the blood allowing the glucose level in the blood to be maintained within a small range around 5.6 mM. Insulin secretion is oscillatory with a period of ≤1 min (fast oscillatory mode), 2–7 min (slow oscillatory mode), or a combination of the two8–10. It is generally believed that Ca2+ feedback to ATP production is responsible for the fast oscillatory mode of insulin secretion, whereas glycolysis is responsible for the slow oscillatory mode. The glucose-phosphorylating enzyme glucokinase act as a metabolic glucose sensor in liver and β-cells11. The electrical activity of β-cells has a characteristic behavior known as bursting. A burst consists of an active phase of spiking followed by a silent phase of hyperpolarization. During the silent phase, Ca2+ is cleared by Ca2+ ATPases. The essential processes in insulin secretion are as follows (see Fig. 1): ATP-sensitive K+ channels in the plasma membrane are activated by ADP and inactivated by ATP; thus the ratio of these nucleotides determines the fraction of open K(ATP) channels. When the ATP/ADP ratio is elevated, there is a reduction in the number of open K(ATP) channels. This results in membrane depolarization, causing voltage-dependent Ca2+ channels to open. The resulting Ca2+ influx evokes insulin secretion. The difference among various mathematical models may originate in the extent to which common cellular processes beyond the essential processes are taken into account.
Figure 1.

Essential processes of the insulin secretion6. Glucose is taken into the β-cell by GLUT-2 transporters, and broken down during glycolysis. Glycolytic product pyruvate is taken into the mitochondria in order to produce ATP. The ATP-sensitive K+ channel regulates membrane potential, and Ca2+ flow into the cell, and the insulin release into the blood is prompted by the elevated cytosolic Ca2+ concentration.

Comparisons among experimental observations have been performed mostly in the context of mathematical models of single β-cells. However, experimental observations are conducted in β-cell clusters, where β-cells are connected with gap junctions. In this letter, we propose a gap junction model that clarifies the relationship between the synchronization phenomena and the cellular processes via gap junctions. From among many proposed single pancreatic β-cell models6,10,12–20, here we adopt one by Pedersen et al.6, and generalize their model from the single-cell level to a multicellular system. The model by Pedersen et al. (see Fig. 2) is not complete as a whole β-cell model, but its relative simplicity facilitates generalization to the multicellular system. We expect that the simplicity of the model can help our intuitive understanding of the numerical investigations. Naturally, this also gives some limitations to our study as discussed in Appendix A.
Figure 2.

A scheme for insulin secretion adopted by Pedersen et al.6 G is the extracellular glucose concentration; G is the intracellular glucose concentration; G6P is glucose 6-phosphate concentration; FBP is fructose 1-6-bisphosphate concentration; and SERCA means the SERCA pumps.

To model gap junctions, the electrical coupling between cells has often been handled by adding the following linear coupling term6, −g(v − v), where g is the coupling strength between neighbor cells i and j. Such a linear coupling approximation has recently been extended to Ca2+ and glycolytic metabolites7. In these works, the coupling strength of gap junctions has been treated as a free parameter while the relationship between the adopted coupling parameters and the structure and the function of gap junctions has been left as an unanswered question. Furthermore, the electrical coupling and the ion currents between β-cells must be studied in a consistent manner since ions such as K+ and Ca2+ can freely move through gap junctions. Here, we propose a gap junction model based on the Goldman, Hogkin, and Katz (GHK) approximation21 to answer such a fundamental question. Our proposed scheme can handle both the membrane ion currents and the gap currents in a consistent manner. The structure of this paper is as follows. Following this brief introduction (Section I), we present our mathematical modeling of gap junctions in Section II, and describe our numerical investigations in Section III. Comparison of the prediction of our model to the recent experimental results of Rocheleau et al.22 is presented in Section IV. Limitations of the linear coupling scheme are discussed in Section V. Finally, we discuss our results in Section VI.

Modeling of gap junctions of β-cells

We generalize the single β-cell model proposed by Pedersen et al to a multicellular system as follows. Our equation for the membrane potential (v) of the i-th β-cell is given by where C is the membrane capacitance, is the v-dependent K+ current, is the v-dependent Ca2+ current, is the calcium-activated K+ current, is the ATP-sensitive K+ current, and is the gap current. Figure 3 shows the general structure of gap junctions. We also assume that the flow of ions through gap junctions is driven not only by the electric field but also by the concentration gradient. Thus, we obtain the Nernst-Planck equation for the flow of ions21 where ϕ is the electrical potential, c is the concentration of type A ions, F is Faraday’s constant, z is the valence of ions, D is the diffusion constant of type A ions, S is the cross-sectional area of the gap junction, and RT is the gas constant multiplied by the absolute temperature. Then, the gap current I is We also use , where r ≅ 0.75 nm is the radius of a single channel and N is number of channels in a gap junction. It is known that N is a few to many thousands23. When the length of the gap junctions is d (see Fig. 3b), the potential difference in the gap junction can be approximated (Goldman, Hogkin, and Katz21) as Next, we obtain the following current equation of type A ions for the gap junctions where the Einstein relation between the diffusion coeffcient D and the ionic mobility u, namely D = uRT/zF is used. Thus, the gap current becomes where j is the nearest-neighbor cell of cell i.
Figure 3.

The general structure of gap junctions23. Within a gap junction, there are a few to many thousands channels of diameter 1.5 nm. The length of the cell gap is about 2∼4 nm. The thickness of the cell membrane is about 5 nm. Thus, the length of the gap junctions d is nearly 13 nm. The channels allow inorganic ions and molecules with a mass of less than 1 kDa to pass into the other cell.

Using the gap current, the equation of conservation for K+ ions within the i-th cell becomes where V(= 1150(μm)3) is the cytosolic volume of a single cell, is the inward potassium current (see Appendix A for its detailed discussion), and is the gap current of K+ ions. Summing the length of the cell gap (2∼4 nm) and the thickness of the two neighboring cell membranes (∼5 nm), we obtain d=3 nm+5 nm * 2=13 nm as an approximation here (see Fig. 3(b)). Such an approximation is necessary because the intracellular potential difference must vanish when the coupled system is in equilibrium. Similarly, the equation of conservation for the free cytosolic Ca2+ concentration is and the equation for the free Ca2+ concentration in the endoplasmic reticulum is where is the Ca2+ flux out of the endoplasmic reticulum, is the gap current of Ca2+, f is the fraction of free to total cytosolic Ca2+, and k ≡ k, p˜ ≡ pV, k˜ ≡ kV. Where k, k, and p are the PMCA pump rate, SERCA pump rate, and the Ca2+ leakage rate from ER, f and f are the fraction of free to total cytosolic and the fraction of free to total ER Ca2+, respectively, V is the volume of the ER compartment. Thus, we can handle gap junctions consistently.

Synchronization of beta-cells via gap junctions

To clarify the role of gap junctions in the cellular processes, we have conducted extensive numerical investigations. From many numerical experiments, first, we show the result for the two β-cell system in Fig. 4, where we adopt ionic mobilities in water at 298 K24, namely, u = 7.62×10−8 m2s−1V−1, u = 6.17 × 10−8 m2s−1V−1 as an approximation since specific values for the ionic mobilities in the β-cells are not currently available to our knowledge. In Fig. 4(a), both K+ ions and Ca2+ ions are allowed to pass through gap junctions. In this case, synchronization is achieved immediately although very different initial parameter values are adopted for the different cells. On the other hand, in Fig. 4(b), only Ca2+ ions are allowed to pass through gap junctions. It is clear that without free flow of K+ ions through the gap junction, synchronization cannot be achieved. The result is reasonable since the K+ ion concentration is much higher than the Ca2+ ion concentration within cells. Although we have also tested the case when only K+ ions are allowed to pass through gap junctions, we do not show it here because the obtained figure is nearly identical to Fig. 4(a). For our next example, we show the result for the 100 β-cell system in Fig. 5, where the 10×10 square lattice with the periodic boundary condition is used. Once again, we observed synchronous bursting. We do not provide any figure of channel number dependence because no qualitative change was observed when N is changed from 1 to 100.
Figure 4.

Synchronization is achieved immediately when both potassium ions and calcium ions are allowed to pass through gap junctions between two β-cells (a), but is not achieved when only calcium ions are allowed to pass through gap junctions (b). Here, ḡ =1000 pS, and ḡ( =40000 pS, and the extracellular glucose concentration is 7 mM. The solid line and dotted line indicate different β-cells.

Figure 5.

Synchronization of 10×10 β-cell square lattice with periodic boundary conditions. Here, ḡ =1000 pS, and ḡ( = 40000 pS.

Robustness of the insulin secretion by gap junctions

Recently, Rocheleau et al.22 conducted an interesting experiment by blocking the ATP-sensitive K+ channels and gap junctions. They used transgenic mice and showed that the robust control of the insulin secretion can be achieved by the gap junctions. Following their experiment, we conducted a numerical experiment in which G = 2 mM. To simulate their experiment, we reduced the conductance of the ATP-sensitive K+ channels by decreasing the value of ḡ( from the original value of 40000 pS to 10000 pS in a single β-cell. In this case, the insulin secretion is prompted as shown in Fig. 15. This corresponds to the case where the gap junction is disconnected (case in Fig. 6(c)). If the ATP-sensitive K+ channels are fully functional, no insulin secretion should be observed when G = 2 mM as shown in Fig. 13. However, when the gap junction is opened (case in Fig. 6(b)), insulin secretion ceases, as shown in Fig. 7(b). This robustness of the insulin secretion is consistent with the experiments of Rocheleau et al. To clarify the detailed mechanism of this robustness, we show the ATP-sensitive potassium current I( and the gap currents I( and I( in Fig. 8. When the ATP-sensitive potassium channels of both cells are not blocked, the gap currents are negligibly small. However, when one of two cells is blocked, I( and I( of the normal cell are significantly increased (see Figs. 8(b), 8(c)). Figure 8(d) shows that minus I( is nearly equal to the I( of the blocked cell plus I(. Besides, both values are roughly equal to I( in equilibrium state in Fig. 8(a). This means that a significant increase of I( of the normal cell is brought about mostly by the outward gap current I( from the blocked cell. This increase of I( brings the intracellular potassium density of the blocked cell back to the normal level, and the insulin secretion ceases. Namely, the intercellular collaboration of ATP-sensitive potassium channels via gap junctions is a key of this robustness. Here the positive direction of I( is outward from the cell.
Figure 15.

Effect of ḡ( variation. Original ḡ( value is 40000 pS. Note that K value is slightly higher than 95 mM here.

Figure 6.

Two β-cells connected with gap junctions. (a) Wild type cells connected with gap junctions. (b) The K(ATP) channel in one of two β-cells is partially blocked. (c) The K(ATP) channel in one β-cell is blocked, and additionally, the gap junction is non-functional.

Figure 13.

Single β-cell model calculations of Bedersen et al. together with Eq. (A3). The original model used the approximation of constant potassium ion concentration. Where v is the cell membrane potential, Ca is Ca2+ ion concentration, K is K+ ion concentration, and FBP is the concentration of fructose 1,6-bisphosphate.

Figure 7.

Partial blocking of the ATP-sensitive K+ channels of the two β-cell system when G= 2 mM. (a) ḡ( =40000 pS (Cell 2), 40000 pS (Cell 1), (b) ḡ( =40000 pS (Cell 2), 10000 pS (Cell 1). The above figures correspond to the cases of Figs. 6(a) and 6(b), respectively. In the case of Fig. 6(c), the result becomes the simple sum of Fig. 14 and Fig. 15 since the gap junction is closed. This means that the insulin secretion cannot be stopped, even though the glucose level is low.

Figure 8.

ATP-sensitive K+ current and gap currents of the cases in Fig. 7, where G= 2 mM. (a) I( of the case of Fig. 7(a), (b) I( of the case of Fig. 7(b), (c) gap currents I( and I() of the cases of Figs. 7(a) and 7(b). When the ATP-sensitive potassium channels of both cells are fully functional, the gap currents are negligibly small. However, when one of them is blocked, the outward gap currents from the blocked cell and I( of the normal cell are significantly increased, (d) a comparison of and , where and are ATP-sensitive potassium current of the blocked cell and that of the normal cell, respectively. Note that and in Fig. 8(d) are roughly equal to I( in Fig. 8(a). An increase of I( brings the intracellular potassium density of the blocked cell back to the normal level, and ultimately the insulin secretion is ceased. The intercellular collaboration of ATP-sensitive potassium channels via gap junctions is a key of this robustness. Here the positive direction of I( is outward from the cell.

For the further confirmation of the above analysis, we have increased the extracellular glucose concentration G from 2 mM to 7 mM as shown in Fig. 9. Since we have already studied the case where both cells are normal as presented in Fig. 4(a), only the blocked case is shown in Fig. 9(e) except gap currents and I(.When G= 7 mM, the insulin is constantly secreted, but the role of gap junction for the metabolic synchronization is still important when some cell is damaged.
Figure 9.

ATP-sensitive K+ current and gap currents, where G = 7 mM. Similar to Fig. 8, the blocked or damaged cell significantly increases the outward gap currents I( and I() from the cell. (a) I( of the case of Fig. 4(a), (b) I( of the case of Fig. 9(e), (c) gap currents I( and I( of the cases of Figs. 4(a) and 9(e). (d) a comparison of and . They are nearly identical and in the same range of value of I( in equilibrium state (2000 fA∼10000 fA) in Fig. 9(a).

To investigate the role of gap junctions further, we studies the activity of the voltagegated Ca2+ channel by changing ḡ values. The original ḡ value is 1000 pS, and Fig. 14 shows the model calculations. We then changed the value of ḡ from 1000 pS to 900 pS and 1100 pS. Their corresponding results are shown in Figs. 16 and 17, respectively. Two coupled β-cells are successfully synchronized via the gap junction, and a very similar result to that of the ḡ =1000 pS case is produced (see Fig. 11(a) or Fig. 14) although original individual patterns are very different each other as shown in Figs. 16 and 17. This kind of character has been observed consistently in other tested cases including the three coupled β-cell system.
Figure 14.

Modified single β-cell model calculations, where Eq. (A4) was used instead of Eq. (A3).

Figure 16.

Effect of the ḡ variation. Original ḡ value is 1000 pS.

Figure 17.

Effect of the ḡ variation. Original ḡ value is 1000 pS.

Figure 11.

Results of the linear coupling scheme. Here, two β-cells with the same and different ḡ values when G = 7 mM. (a) ḡ =1000 pS (Cell 2), 1000 pS (Cell 1), and (b) ḡ =1100 pS (Cell 2), 900 pS (Cell 1).

The linear coupling scheme and its limitations

Because of its mathematical simplicity, the linear coupling scheme is often adopted for handling gap junctions without detailed biological discussions. Here we derive it from Eq. (4). By using the condition, (i, j are neighbor cell numbers), we can obtain where . Here, we assume that only Ca2+ and K+ ions go through gap junctions. Then, Since c/c ≫ 1 within cells, it is clear that K+ ions play a much more important role than Ca2+ ions in the coupling of β-cells by gap junctions. If we use c = 95 mM, c = 5.5×10−2 μM, and T =310 K, we obtain g ≅ g( = 95NpS and g( = 1.1×10−5NpS. To clarify the limitation of the linear coupling scheme, we have conducted the following numerical experiments. The results are shown in Figs. 11 and 12, in which the number of channels is N = 10 as in previous investigations. By comparing Figs. 11(a) and 4(a), Figs. 11(b) and 10, and Figs. 12 and 7, it becomes clear that the linear coupling scheme works very well except when the ḡ( values of individual β-cells are different as shown in Fig. 12(b). The variation of ḡ values does not provide any problem as an approximation. This difference originates in how the intra-cellular potassium concentration is a ected by the parameter value variation. As shown in Fig. 15, only ḡ( variation has a ected the intracellular potassium concentration significantly. As a consequence, the precondition of for this scheme is lost.
Figure 12.

Results of the linear coupling scheme. Here, two β-cells with the same and different ḡ( values when G = 2 mM. (a) ḡ( =40000 pS (Cell 2), 40000 pS (Cell 1), (b) ḡ( =40000 pS (Cell 2), 10000 pS (Cell 1).

Figure 10.

Two β-cells with different ḡ values, where ḡ =1100 pS (Cell 2), 900 pS (Cell 1), and G = 7 mM.

Discussion

In this study, we have proposed a mathematical model for the gap junction based on the biological functions and the structure of gap junctions, and applied it to the β-cell cluster in the islets of Langerhans. Our model demonstrates that free flow of potassium ions through gap junctions plays an essential role in achieving synchronous bursting. When metabolic synchronization between β-cells is achieved, the net current through gap junctions becomes negligible. However, the ionic flow through gap junctions becomes essential when some of the ATP-sensitive K+ channels in the β-cells are damaged. The proved robustness of the insulin secretion is consistent with the experimental observations of Rocheleau et al.22. We offer the following interpretation of our findings. Intracellular calcium ion concentration is relatively insensitive to the variation of the conductance ḡ so long as the function of the ATP-sensitive K+ channels is normal. However, when a fraction of the ATP-sensitive K+ channels is damaged, intracellular potassium ion concentration is increased (Fig. 15). This increase also brings about an increase in calcium ion concentration. As a consequence, insulin secretion is stimulated even when the glucose level is low. However, when the damaged cell is connected with the normal cells with gap junctions, mutual membrane potential synchronization is achieved immediately due to the free flow of potassium ions through gap junctions. Thus, the intracellular potassium ion concentration of the damaged cell returns to the normal level, and calcium ion concentration is reduced to the normal level a little later. This stops insulin secretion, and the robust insulin secretion can be achieved (Figs. 7 and 8). We have also derived a linear coupling scheme from the GHK approximation, assuming that the ion concentrations between neighbor cells are nearly equal. The performance of the linear coupling scheme is excellent, so long as the ATP-sensitive K+ channels are normal between neighbor cells because the intracellular potassium density is sensitive to ATP-sensitive K+ channels (Fig. 15). One cannot expect nearly equal ion concentrations between neighboring cells, as that would break the basis of the linear coupling scheme. As discussed in Appendix A, we have introduced I( =−I( term into the equation of conservation for potassium ions as an approximation. This mathematical (as opposed to biological) approximation is necessary to hold intracellular potassium concentration steady, in the context of the single β-cell model by Pedersen et al. and their original parameter values. This problem does not appear explicitly so far as the constant Nernt potential is adopted in any scheme. This inconsistency may have occurred due to the lack of pumps that are responsible for the inward potassium current in the model equations. Thus, in future models, we would like to introduce such pumps along with the sodium current in order to avoid such a drastic approximation. Until then, we should take our findings as predictions and they must be confirmed by the direct observation of gap currents.
Table 1.

Typical variable values. See ref. 6 for other variables

Variables
Cm = 5300 fFK =2700 pS
Ca =1000 pSK(Ca) =400 pS
K(ATP)=40000 pSvK = −75 mV
vCa = 25 mVVcyt = 1150 µm3
Vcyt/Ver = 31kPMCA = 0.18 ms−1
kSERCA = 0.4 ms−1pleak = 0.0002 ms−1
fcyt = 0.01fer = 0.01
  18 in total

1.  Receptors as a master key for synchronization of rhythms.

Authors:  Seido Nagano
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2003-05-23

2.  Diffusion of calcium and metabolites in pancreatic islets: killing oscillations with a pitchfork.

Authors:  Krasimira Tsaneva-Atanasova; Charles L Zimliki; Richard Bertram; Arthur Sherman
Journal:  Biophys J       Date:  2006-02-24       Impact factor: 4.033

3.  Interaction of glycolysis and mitochondrial respiration in metabolic oscillations of pancreatic islets.

Authors:  Richard Bertram; Leslie S Satin; Morten Gram Pedersen; Dan S Luciani; Arthur Sherman
Journal:  Biophys J       Date:  2006-12-15       Impact factor: 4.033

4.  Cyclic changes in potential and resistance of the beta-cell membrane induced by glucose in islets of Langerhans from mouse.

Authors:  I Atwater; B Ribalet; E Rojas
Journal:  J Physiol       Date:  1978-05       Impact factor: 5.182

5.  Emergence of organized bursting in clusters of pancreatic beta-cells by channel sharing.

Authors:  A Sherman; J Rinzel; J Keizer
Journal:  Biophys J       Date:  1988-09       Impact factor: 4.033

Review 6.  Modeling the model organism Dictyostelium discoideum.

Authors:  S Nagano
Journal:  Dev Growth Differ       Date:  2000-12       Impact factor: 2.053

7.  Modeling of Ca2+ flux in pancreatic beta-cells: role of the plasma membrane and intracellular stores.

Authors:  Leonid E Fridlyand; Natalia Tamarina; Louis H Philipson
Journal:  Am J Physiol Endocrinol Metab       Date:  2003-03-18       Impact factor: 4.310

8.  A model for glycolytic oscillations based on skeletal muscle phosphofructokinase kinetics.

Authors:  P Smolen
Journal:  J Theor Biol       Date:  1995-05-21       Impact factor: 2.691

9.  Slow and fast oscillations of cytoplasmic Ca2+ in pancreatic islets correspond to pulsatile insulin release.

Authors:  P Bergsten
Journal:  Am J Physiol       Date:  1995-02

10.  Critical role of gap junction coupled KATP channel activity for regulated insulin secretion.

Authors:  Jonathan V Rocheleau; Maria S Remedi; Butch Granada; W Steven Head; Joseph C Koster; Colin G Nichols; David W Piston
Journal:  PLoS Biol       Date:  2006-01-17       Impact factor: 8.029

View more
  1 in total

1.  Intrinsic islet heterogeneity and gap junction coupling determine spatiotemporal Ca²⁺ wave dynamics.

Authors:  Richard K P Benninger; Troy Hutchens; W Steven Head; Michael J McCaughey; Min Zhang; Sylvain J Le Marchand; Leslie S Satin; David W Piston
Journal:  Biophys J       Date:  2014-12-02       Impact factor: 4.033

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.