^{1}

^{*}

^{1}

^{1}

Possibilities of synchronized oscillations in glycolysis mediated by various extracellular metabolites are investigated theoretically using two-dimensional reaction-diffusion systems, which originate from the existing seven-variable model. Our simulation results indicate the existence of alternative mediators such as ATP and 1,3-bisphosphoglycerate, in addition to already known acetaldehyde or pyruvate. Further, it is also suggested that the alternative intercellular communicator plays a more important role in the respect that these can synchronize oscillations instantaneously not only with difference phases but also with different periods. Relations between intercellular coupling and synchronization mechanisms are also analyzed and discussed by changing the values of parameters such as the diffusion coefficient and the cell density that can reflect in tercellular coupling strength.

Synchronization in biological systems is widely observed in the natural world. This phenomenon is one of the collective behaviors thought to have a crucial role in maintaining the individual life or in giving benefits for communities. One of the well-known examples is synchronized flashing of male fireflies [

Glycolysis is a biological mechanism to decompose glucose and to store energy in the form of ATP. In this chemical process, synchronized variations can be seen for the concentrations of various metabolites [

The theoretical studies of glycolytic oscillations in yeast cells using differential equations started substantially when Sel’kov presented a simple kinetic model of an enzyme reaction with substrate inhibition and product ac- tivation [

The epoch-making study was performed by Wolf and Heinrich in order to elucidate the mechanisms of syn- chronous behaviors in glycolytic oscillations [

However, it seems that no model has succeeded in demonstrating perfect synchronization of a large number of yeast cells that oscillated with different phases and periods. We guess that one of the reasons is that these mod- els assumed acetaldehyde or pyruvate to be an intercellular communication substance for glycolytic synchroni- zation.

It is known that acetaldehyde mediates the synchronization of glycolytic oscillations [

Then, we attempted to exchange acetaldehyde or pyruvate to ATP or other metabolites in the original model by Wolf and Heinrich [

Our mathematical models are derived from the glycolytic oscillation model originally presented by Wolf and Heinrich [

1) Extension to two-dimensional partial differential equation systems with the diffusion term,

2) Exchange of the intercellular coupling substance and,

3) Non-dimensionalization for variables and parameters.

The first modification enables us to observe directly various kinds of oscillations including the synchronous one, and the possibilities of synchronization significantly increase by the second modification. Moreover, the third modification, which leads to the reduction of parameter numbers, eases mathematical analyses of simulation models.

The schematic diagram of the model is sketched in

Six major substances are contained within a cell, which are denoted as S_{1}, S_{2}, S_{3}, S_{4}, N_{2} and A_{3}. These are regarded as independent variables, the meanings of which are explained in _{1} and A_{2}, are also contained, which are connected by the relations, N_{1} + N_{2} = N and A_{2} + A_{3} = A, respectively. As N and A are constant, two variables, N_{1} and A_{2}, are not independent, whose numbers are auto- matically identified. In the original model, it is assumed that only S_{4} can permeate through the membrane, then, the substance in the external solution is labeled as _{4} intercellular me- diator, is also the starting point of our studies. The transmembrane coupling metabolite is later altered to the other one such as A_{3}, S_{3}, S_{2} and N_{2}; thereafter, the variations of system behaviors are investigated.

The meanings of parameters used in this article are also explained in

. Variables and parameters in Models I, II, III, IV and V

Variables and Parameters | Descriptions |
---|---|

S_{1} | Concentration of glucose |

S_{2} | Concentration of pool of glyceraldehyde 3-phosphate and dihydroxyacetone phosphate |

S_{3} | Concentration of 1,3-bisphosphoglycerate |

S_{4} | Concentration of pool of pyruvate and acetaldehyde in cytosol |

N_{1} | Concentration of NAD^{+} |

N_{2} | Concentration of NADH |

A_{2} | Concentration of ADP |

A_{3} | Concentration of ATP |

Concentrations of coupling substances in the external solution | |

J_{0} | Input flux of glucose via the cellular membrane |

k_{2} | Rate constant of the glyceraldehyde-3-phosphate dehydrogenase reaction |

k_{3} | Rate constant of the lumped phosphoglyceratekinase/phosphoglyceratemutase/enolase/ pyruvate kinase reaction |

k_{4} | Rate constant of the alcohol dehydrogenase reaction |

k_{5} | Rate constant of non-glycolytic ATP consumption |

k_{6} | Rate constant of the lumped reaction transforming triose phosphates into glycerol |

k_{7} | Rate constant of pyruvate and acetaldehyde consumption |

r | Rate constant of the degradation of the coupling substance within the extracellular medium |

κ | Kinetic constant of the transmembrane flux of the coupling substance |

q | Co-operativity coefficient of ATP inhibitation |

N | Sum of the concentrations of NAD^{+} and NADH |

A | Sum of the concentrations of ADP and ATP |

φ | Ratio of the total cellular volume to the extracellular volume |

d_{F} | Diffusion coefficient |

f_{0} | Coefficient that designates the amplitude of randomization |

Most of variables and parameters were defined by Wolf and Heinrich [

Schematic diagram of Models I, II, III, IV and V. (a) The simulation area is composed of N × N square compartments, in which a single glycolytic cell is embedded [16] [21] . In all simulations, the number of N is fixed at 11, thus, the total number of cells is N × N (=121). The temporal behaviors of five gray cells, one central cell plus four nearest neighbors, are selectively monitored in Figure 2, Figure 4 and Figure 5 (figures on the left side). (b) Each cell contains eight metabolites, S_{1}, S_{2}, S_{3}, S_{4}, N_{1}, N_{2}, A_{2} and A_{3}, among which non-independent N_{1} and A_{2} are not shown. In Model I, the transmembrane substance is S_{4}, whereas in Models II, III, IV and V, this is altered to A_{3}, S_{3}, S_{2} and N_{2}, respectively. In- tercellular coupling metabolites diffuse through the boundary between adjacent compartments, which is expected to be feasible mechanisms to induce synchronized glycolytic oscillations. As for identification of S_{1}, S_{2}, S_{3}, S_{4}, N_{1}, N_{2}, A_{2} and A_{3}, see Table 1

. Parameter settings in Models I, II, III, IV and V

Parameters | Reference | Model I | Model II | Model III | Model IV | Model V |
---|---|---|---|---|---|---|

J_{0} | 0.111 | 0.09 | 0.26 | 0.14 | 0.17 | 0.111 |

k_{2} | 0.06 | 0.06 | 0.06 | 0.06 | 0.06 | 0.06 |

k_{3} | 0.16 | 0.16 | 0.16 | 0.16 | 0.16 | 0.16 |

k_{4} | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 |

k_{5} | 0.0246 | 0.0246 | 0.0246 | 0.0246 | 0.0246 | 0.05 |

k_{6} | 0.12 | 0.12 | 0.12 | 0.12 | 0.12 | 0.12 |

k_{7} | 0.01 | 0.01 | 0.01 | 0.01 | 0.01 | |

r | 0.025 | 0.02 | 0.077 | 0.077 | 0.05 | 0.025 |

κ | 0.25 | 0.25 | 1.0 | 1.0 | 0.15 | 0.25 |

q | 4.0 | 4.0 | 4.0 | 4.0 | 4.0 | 4.0 |

N | 1.92 | 1.92 | 1.92 | 1.92 | 1.92 | 1.92 |

A | 7.69 | 7.69 | 7.69 | 7.69 | 7.69 | 7.69 |

φ | 0.1 | 0.1 | 0.5 (0.1) | 0.5 (0.1) | 0.5 (0.1) | 0.5 |

d_{F} | 1.0 (0.01) | 1.0 (0.01) | 1.0 (0.01) | 1.0 (0.01) | 1.0 | |

f_{0} | 0.25 | 0.1 | 0.1 | 0.1 | 0.1 |

Numerical analyses are performed using these parameter values. A parameter k_{7} is newly introduced for stabiliza- tion of the system. The diffusion coefficient d_{F} and the parameter f_{0} that defines the amplitude of randomization are also employed. When f_{0} = 0.1, for example, randomized items such as initial values and parameter values are scattered within the range from 90% to 110% around the above values. As for two control parameters, φ and d_{F}, two different values are provided in Model II, III and IV, while only d_{F} is varied in Model I. Reference values are converted by non-dimensionalization procedures from those in the original model by Wolf and Heinrich [

Two parameters, k_{1} and K_{I}, are eliminated by these processes [_{7} is employed. The system is stabilized by the addition of k_{7}, especially when the trans- membrane substance is changed to A_{3}, S_{3}, S_{2} or N_{2}. As a result, our seven-variable, two-dimensional reac- tion-diffusion model with S_{4} being the intercellular mediator reads as follows.

Here, the diffusion term is incorporated in the last equation, which describes the intercellular coupling via S_{4}. This basic model described by Equations (1) is referred to as Model I in this article.

Next, we exchange the coupling substance in the external medium in order to examine other candidates that can produce synchronous oscillations. It should be noted that a new parameter k_{7} takes an important role as a stabilizer in these models. For example, when the substance that functions as the communicator is A_{3}, the ma- thematical model is described such as

To be accurate, one more variable A_{2} or

Similarly, we can construct the system with the intercellular communicator S_{3} (Equations (3)) and the system with the intercellular communicator S_{2} (Equations (4)). These are referred to as Model III and Model IV, respec- tively.

In above formulations of Equations (3) and Equations (4), several equations are omitted, which are the same as those in Equations (1). Moreover, we can construct Model V, where the intercellular mediator is N_{2}, in the same manner, formulations of which are not shown explicitly.

Although two parameters are eliminated by non-dimensionalization procedures, there are still twelve parame- ters in our models except for two control parameters d_{F} and φ. In principle, we try to use parameter values of the reference state converted from the original model [_{0}, r and κ, which are thought to be comparatively easy to manipulate. The exception is Model V, where the value of k_{5} is varied. Besides the reference [

It is also important to choose properly the initial value of each variable. We determine these values in refer- ence to fixed points, which are calculated in advance. _{1} is fluctuated within the range from 4.68 (= 5.2 × 0.9) to (5.72 = 5.2 × 1.1), S_{2} = 0.43 (= 4.3 × 0.1), and so on.

. Fixed points and initial values of variables corresponding to synchronous oscillations in Models I, II, III and IV

Variables | Model I | Model II | Model III | Model IV | ||||
---|---|---|---|---|---|---|---|---|

FP | Initial values | FP | Initial values | FP | Initial values | FP | Initial values | |

S_{1} | 5.0 | ×0.75~1.25 | 5.2 | ×0.9~1.1 | 8.3 | ×0.9~1.1 | 4.5 | ×0.9~1.1 |

S_{2} | 1.4 | ×0.1 | 4.3 | ×0.1 | 2.2 | ×0.1 | 1.9 | ×0.1 |

S_{3} | 0.2 | ×0.1 | 1.1 | ×0.1 | 0.3 | ×0.1 | 0.3 | ×0.1 |

S_{4} | 0.4 | ×0.1 | 4.7 | ×0.1 | 0.9 | ×0.1 | 2.1 | ×0.1 |

N_{2} | 0.3 | ×0.1 | 0.1 | ×0.1 | 0.2 | ×0.1 | 0.1 | ×0.1 |

A_{3} | 3.8 | ×0.1 | 2.7 | ×0.1 | 3.9 | ×0.1 | 3.0 | ×0.1 |

0.2 | ×0.1 | |||||||

2.3 | ×0.1 | |||||||

0.3 | ×0.1 | |||||||

1.1 | ×0.1 |

“FP” denotes the fixed point. For detailed calculations, see Appendix.

_{2} concentrations from dimensionless time t = 7500 to t = 8000 in Model I, where the transmembrane metabolite is assumed to be S_{4}, and only initial values of S_{1} are randomized within the fluctuation range from 75% to 125% around the main value. It should be noted that the perturbation of initial values causes the difference of phases only. Two figures (a) and (b) are the simulation results for d_{F} = 1.0 and φ = 0.1, and (c) and (d) are those for d_{F} = 0.01 and φ = 0.1. Meanwhile, (a) and (c) exhibit the temporal changes in central five cells, one central cell plus four nearest neighbors, and (b) and (d) do those in mean N_{2} concentrations for total 121 cells. In the case of d_{F} = 1.0 and φ = 0.1, as shown in (a) and (b), the tightly syn- chronized oscillation is observed, which is strongly certified by the fact that wave patterns of five central cells are nearly overlapped and almost equal with the averaged one. In the case of d_{F} = 0.01 and φ = 0.1, on the other hand, it seems that oscillations continue to be out of phase, as shown in (c), thus, Model I does not generate synchronous oscillations in this case.

The time series of two-dimensional distributions of N_{2} concentrations are illustrated in _{F} = 1.0 and φ = 0.1, while lower three (d), (e) and (f) do the asynchronous oscillation, where d_{F} = 0.01 and φ = 0.1. For each case, three drawing times are chosen so that the central cell at (5, 5) just passes the mean N_{2} value of the amplitude. Thus, they are slightly proceeded compared with the exact times, t = 2000, 4000 and 8000. As a result, it is confirmed that six central cells in

We also examine the case where not only initial S_{1} values but also values of nine parameters, J_{0}, k_{2}, k_{3}, k_{4}, k_{5}, k_{6}, k_{7}, r and κ, are randomized. In this case, oscillation periods are also disturbed as well as phases. However, it seems impossible to annihilate these differences, which leads to the conclusion that oscillations in Model I are asynchronous for randomization of both initial S_{1} values and nine parameter values, i.e., for disturbances of both oscillation phases and periods.

Assuming that the diffusion coefficient d_{F} = ∞, our Model I corresponds exactly with the original model by Wolf and Heinrich [

Temporal changes in N_{2} concentrations in Model I, t = 7500 - 8000. Two figures on the left side show the temporal changes of central five cells specified in Figure 1 (a), while two on the right side show those averaged for total 121 cells. (a) and (b) show the synchronous oscillation, where d_{F} = 1.0 and φ = 0.1. Meanwhile, (c) and (d) show the asynchronous oscillation, where d_{F} = 0.01 and φ = 0.1. In both cases, only initial values of S_{1} are randomized. Other parameter values are fixed in accordance with Table 2. It is recognized that the oscillations of five central cells are overlapped with each other, as shown in (a), and extremely similar with the averaged one, as shown in (b), indicating that almost all the cells oscillate with the same phases and periods

Time series of two-dimensional distributions of N_{2} concentrations in Model I. Parameter settings are the same as those in Figure 2. (a), (b) and (c) show the evolution to the synchronous oscillation, where d_{F} = 1.0, φ = 0.1 and (a) t~2000, (b) t~4000, (c) t~8000, respectively. Meanwhile, (d), (e) and (f) show the succession of the asynchronous oscillation, where d_{F} = 0.01, φ = 0.1 and (d) t~2000, (e) t~4000, (f) t~8000, respectively. Elapsed time is slightly adjusted such that the central cell at (5, 5) takes the mean N_{2} value of the oscillation amplitude

d_{F} = 1.0, thus, we can expect almost the same results for simulations in the range of d_{F} ≥ 1.0. These situations are also true for Models II, III, IV and V as well.

Despite almost complete synchronization for randomization of initial S_{1} values, we did not succeed in detecting any synchronous oscillation for randomization of parameter values. Then, we exchange the intercellular media- tor S_{4} to other substances in an attempt to synchronize oscillations with different periods.

_{3}, and both ini- tial S_{1} values and nine parameter values of J_{0}, k_{2}, k_{3}, k_{4}, k_{5}, k_{6}, k_{7}, r, and κ are disturbed at the same time. Two figures (a) and (b) are the simulation results for d_{F} = 1.0 and φ = 0.5, (c) and (d) are those for d_{F} = 0.01and φ = 0.5 and (e) and (f) are those for d_{F} = 1.0 and φ = 0.1, respectively. Meanwhile, three figures (a), (c) and (e) on the left side represent the temporal changes in central five cells, while (b), (d) and (f) on the right side do those in mean N_{2} concentrations for total cells. Different from the case of Model I, it is clear that the differences of both phases and periods disappear, and that synchronization occurs even for oscillations with different periods when d_{F} = 1.0 and φ = 0.5, as shown in (a) and (b). Moreover, synchronization is fully completed until t~500, which is much faster than in Model I (_{F} = 0.01 and φ = 0.5, as shown in (c) and (d), and the system behavior results in the convergence to the fixed point when d_{F} = 1.0 and φ = 0.1, as shown in (e) and (f).

Simulation results of Model III are also presented in _{3}, and both initial S_{1} values and nine parameter values are simultaneously randomized. Temporal behaviors are also classified into three modes as well as in the case of Model II, namely, synchronous oscillations for d_{F} = 1.0 and φ = 0.5 (_{F} = 0.01 and φ = 0.5 (not shown) and the convergence to the fixed point for d_{F} = 1.0 and φ = 0.1 (not shown). Meanwhile in the case of Model IV, in which the coupling substance is S_{2}, we confirmed no more than two modes of temporal beha- viors. These are synchronous oscillations for d_{F} = 1.0 and φ = 0.5 (_{F} = 0.01 and φ = 0.5 (not shown).

In the end, we examine Model V with the N_{2} intercellular mediator. Despite a large extent of surveys, we failed in finding any parameter set that realized synchronous oscillations. _{1} values and nine parameter values are randomized as well as in Models II, III and IV. Needless to say, this does not necessarily exclude the possibility

Temporal changes in N_{2} concentrations in Model II. Three figures on the left side show the temporal changes of central five cells, while three on the right side show those averaged for all cells. (a) and (b) show the synchronous oscillation, where d_{F} = 1.0, φ = 0.5 and t = 500 - 1000. Meanwhile, (c) and (d) show the asynchronous oscillation, where d_{F} = 0.01, φ = 0.5 and t = 7500 - 8000. Further, (e) and (f) show the convergence to the fixed point, where d_{F} = 1.0, φ = 0.1 and t = 7500 - 8000. The initial values of S_{1} and the values of nine parameters, J_{0}, k_{2}, k_{3}, k_{4}, k_{5}, k_{6}, k_{7}, r, and κ, are simultaneously randomized. Other parameter values are fixed in accordance with Table 2. It should be noted that the oscilla- tions in Model II synchronize more rapidly, as shown in (a) and (b), compared with that in Model I (Figure 2)

that N_{2} is concerned with synchronization.

These simulation results in five models are summarized in

It seems to be two levels in synchronization of oscillations, namely, synchronization of phases and that of pe- riods. In general, perturbations of initial values cause merely phase shifts. Meanwhile, perturbations of parame- ter values are at least required to cause the difference of oscillation periods. Thus, it is likely that synchroniza- tion of different periods is more difficult and essential than that of phase differences. Taking this inference into consideration, we cannot say that synchronization is completed or perfect until oscillations become in phase even for randomization of parameters. In this sense, synchronization in Model I (_{4} communicator is imperfect, while those of Models II (_{3}, S_{3} and S_{2} communicators are perfect.

Comparing three kinds of synchronization in Models II, III and IV, it seems that overlapping of oscillatory patterns in Model II is more outstanding than the other two. Thus, it could be speculated that synchronization via

Temporal changes in N_{2} concentrations in Models III, IV and V. Three figures on the left side show the temporal changes of central five cells, while three on the right side show those averaged for all cells. (a) and (b) show the synchronous oscillation in Model III, where d_{F} = 1.0, φ = 0.5 and t = 500 - 1000. Moreover, (c) and (d) show the synchronous oscillation in Model IV, where d_{F} = 1.0, φ = 0.5 and t = 500 - 1000. Meanwhile, (e) and (f) show the asynchronous oscil- lation in Model V, where d_{F} = 1.0, φ = 0.5 and t = 7500 - 8000. The initial values of S_{1} and the values of nine parameters, J_{0}, k_{2}, k_{3}, k_{4}, k_{5}, k_{6}, k_{7}, r, and κ, are simultaneously randomized. Other parameter values are fixed in accordance with Table 2

. Correlations among transmembrane communicators, randomized items and oscillation modes

Transmembrane Communicators | Randomized items | Periods | Models | |
---|---|---|---|---|

Initial S_{1} values | Initial S_{1} and nine parameter values | |||

S_{2} | Synchronous | Synchronous | 74.0 | Model IV |

S_{3} | Synchronous | Synchronous | 70.6 | Model III |

S_{4} | Synchronous | Asynchronous | 63.0 | Model I |

N_{2} | Asynchronous | Asynchronous | Model V | |

A_{3} | Synchronous | Synchronous | 36.8 | Model II |

Synchronous oscillations are observed for randomization of initial S_{1} values in Model I. Meanwhile in Models II, III and IV, syn- chronous oscillations can also take place for randomization of both initial S_{1} values and values of nine parameters J_{0}, k_{2}, k_{3}, k_{4}, k_{5}, k_{6}, k_{7}, r and κ. However, any synchronous oscillation is not detected in Model V when N_{2} is an intercellular mediator. Dimensionless time periods corresponding to synchronous oscillations are listed for reference.

the A_{3} intercellular metabolite is the most perfect, indicating that the exchange of A_{3} is the most feasible me- chanism for glycolytic synchronization in yeast cells.

In order to certify above inference numerically, the standard deviations of N_{2} concentrations are calculated for total 121 cells in Models II, III, IV and V, among which the former three are the synchronous cases and the last is the asynchronous case. The abscissae of Figures 6(a)-(d) are exactly the same as those of _{2} concentrations are divided by the mean value at each time for normalization, which guarantees the proper comparison between different models.

It is supposed that these normalized standard deviations reflect the degree of synchronization, and that the smaller value, the more perfect is synchronization. Among three synchronous cases in _{3} is the most probable metabolite in- volved in synchronous glycolytic oscillations in yeast cells.

Meanwhile,

It is well known that glycolytic oscillations initiate synchronization under the densely populated condition [_{F}, the volumetric ratio of the cell to the compartment φ, the kinetic constant relating to the permeability κ, and so on. These are connected with such parameters as the compartment size L, the compart- ment volume V, the cellular surface area A_{c}, the cellular volume V_{c} and the permeability of the cellular mem- brane P, by the following relations [

Temporal changes in normalized standard deviations of N_{2} concentrations in Models II, III, IV and V. The standard deviations of N_{2} concentrations are divided by the mean value at each time. Four figures correspond to Figure 4(b), Figure 5(b), Figure 5(d) and Figure 5(f), respectively. These normalized standard deviations are introduced to estimate the degree of synchronization, and the smaller value means more perfect synchronization. It is clear that synchronization in Model II is the most perfect, as shown in (a), where A_{3} is the intercellular communicator. The last figure (d) shows the case of the asynchronous oscillation, where not only the values of standard deviations are high, but also no periodic structure is recognized

In particular, we focus on d_{F} and φ among these parameters in this article.

According to our simulation results of Models II, III and IV, the increase in d_{F} gives rise to the transition from the asynchronous oscillation (for example,

1) Glycolytic oscillations with different phases can be synchronized by means of intercellular coupling via such substances as S_{4}, A_{3}, S_{3} and S_{2}, as demonstrated in Models I, II, III and IV. Meanwhile, synchronization of oscillations with different periods can be mediated by intercellular coupling substances such as A_{3}, S_{3} and S_{2}, as demonstrated in Models II, III and IV. The latter synchronization is characterized by speedy convergence to the synchronous oscillatory state.

2) Among three candidates that can induce synchronization for different periods, A_{3} could be the most re- sponsible for the phenomenon, because the normalized standard deviations of N_{2} concentrations in Model II are the smallest compared with those in Model III or IV.

3) The transition from the asynchronous to the synchronous oscillation is observed with the increase in the diffusion coefficient d_{F}, which could be referred to the Kuramoto transition mechanism. On the other hand, the direct transition from the convergence to the fixed point to the synchronous oscillation is observed with the in- crease in the density parameter φ, which could be referred to the dynamical quorum sensing.

We thank Drs. K. Shibata, P. G. Søensen, S. C. Müller, M. J. B. Hauser, T. Yamaguchi, T. Yamamoto and S. Sasaki for helpful discussion and M. Denda for giving us information on ATP as a signaling molecule.