American Institute of Mathematical Sciences

The operating diagram for a model of competition in a chemostat with an external lethal inhibitor

 1 Université AbouBakr Belkaid, LSDA, Tlemcen, Algérie 2 ITAP, Univ Montpellier, Irstea, Montpellier SupAgro, Montpellier, France

* Corresponding author

Received  January 2019 Revised  May 2019 Published  September 2019

Fund Project: The authors are supported by the France-Algeria Partnership Tassili project 15MDU949 and the Euro-Mediterranean research network TREASURE (http://www.inra.fr/treasure)

The inhibition is an important phenomenon, which promotes the stable coexistence of species, in the chemostat. Here, we study a model of two microbial species in a chemostat competing for a single resource in the presence of an external lethal inhibitor. The model is a four-dimensional system of ordinary differential equations. We give a complete analysis for the existence and local stability of all steady states. We describe the bifurcation diagram which gives the behavior of the system with respect to the operating parameters represented by the dilution rate and the input concentrations of the substrate and the inhibitor. This diagram, is very useful to understand the model from both the mathematical and biological points of view.

Citation: Bachir Bar, Tewfik Sari. The operating diagram for a model of competition in a chemostat with an external lethal inhibitor. Discrete & Continuous Dynamical Systems - B, doi: 10.3934/dcdsb.2019203
References:

show all references

References:
Illustrative operating diagrams for $D$ fixed: The curves $\Gamma_i$, $i = 0\cdots 5$ defined in the Table 3 divide the operating plane $(p^0,S^0)$ into at most nine regions labeled $\mathcal J_0$, $\mathcal J_1$, $\mathcal J_2$, $\mathcal J_3$, $\mathcal J_4$, $\mathcal J_5^S$, $\mathcal J_5^U$, $\mathcal J_6^S$ and $\mathcal J_6^U$. Some of the regions may be empty. The existence and stability of the equilibrium points in the regions of these diagrams are shown in Table 4
The biological parameters values are given in Table 5, Case 1. $J_c = \varUpsilon_0$: therefore $E_c$ is LES whenever it exists. The operating diagram for $D = 1$ shows that $\left(p^0 = 1,S^0 = 1\right)\in\mathcal{J}_6^S$. The existence and stability of the equilibrium points in the regions of this diagram are shown in Table 4
The biological parameters values are given in Table 5, Case 2. (a): The operating diagram for $D = 1$ shows that $p^0 = S^0 = 1$ belongs to $\mathcal{J}_6^S$. (b): The operating diagram for $D = 2.2$. The existence and stability of the equilibrium points in the regions of these diagrams are shown in Table 4
The biological parameters values are given in Table 5, Case 3. (a): The operating diagram for $D = 1$. $(b)$: A zoom showing the instability of $E_c$ when $p^0 = S^0 = D = 1$. The existence and stability of the equilibrium points in the regions of these diagrams are shown in Table 4
The biological parameters values are given in Table 5, Case 3. The operating diagram for $D = 2.2$. (a): $\mathcal{J}_6^U$ is unbounded; (d): a zoom near the origin showing the regions $\mathcal{J}_1$, $\mathcal{J}_2$, $\mathcal{J}_3$ and $\mathcal{J}_5^S$. The existence and stability of the equilibrium points in the regions of this diagram are shown in Table 4
The biological parameters values are given in Table 5, Case 4. The operating diagram for (a): $D = 0.01$. (b): $D = D_1 = 0.013$. The existence and stability of the equilibrium points in the regions of this diagram are shown in Table 4
The biological parameters values are given in Table 5, Case 5. The operating diagram for $D = 1.26$. (a): The full operating diagram. (b): A zoom showing that $\mathcal{J}_4$ is nonempty. The existence and stability of $E_0$, $E_1$, $E_2$ and $E_c$ in the regions of these diagrams are shown in Table 4
The biological parameters values are given in Table 5, Case 3. The operating diagram in the $(S^0,D)$-plane for $p^0 = 1$. (a): The region $\mathcal{J}_6^U$ is unbounded. (b): A zoom showing the instability of $E_c$ for $S^0 = p^0 = D = 1$. The existence and stability of the equilibrium points are shown in Table 4
The biological parameters values are given in Table 5, Case 3. The operating diagram in the $(p^0,D)$-plane for $S^0 = 1$, showing the instability of $E_c$ for $S^0 = p^0 = D = 1$. The existence and stability of the equilibrium points in the regions of this diagram are shown in Table 4
The biological parameters values are given in Table 5, Case 3, and $\beta_1 = \beta_2 = 100$. The operating diagram in the $(p^0,D)$-plane for $S^0 = 1$. (a): The full diagram. (b): A zoom showing the regions near the $D$ axis showing the regions $\mathcal{J}_1$, $\mathcal{J}_3$ and $\mathcal{J}_5^S$. The existence and stability of the equilibrium points in the regions of this diagram are shown in Table 4
(a): Definitions of $\lambda_1 = \lambda_1(D)$, $\lambda^- = \lambda^-(D,p^0,S^0)$, $\lambda^+ = \lambda^+(D,p^0)$ and $\lambda_2 = \lambda_2(D)$. (b): Definition of $p^* = p^*(D,p^0,S^{0})$ satisfying $W(p^*,D,p^0) = \beta_2\left(S^0-\lambda_2(D)\right)$
The biological parameters values are given in Table 1, Case 2. The regions $\varUpsilon_0$ and $\varUpsilon_2$ of $J_c$, and the definitions of $p_1(D)$ and $p_2(D)$ for $D_1<D<D_2$: $D_1\simeq 1.83$, $D_2\simeq 2.65$, $p_1(2.2)\simeq 0.65$, $p_2(2.2)\simeq 1.04$
The biological parameters values are given in Table 1, Case 3. The regions $\varUpsilon_0$, $\varUpsilon_1$ and $\varUpsilon_2$ and the definitions of $p_1(D)$, $p_2(D)$ for $D_1<D<D_2$, and $p_3(D)$, $p_4(D)$ for $D_3<D<D_4$, where $D_1\simeq 0.63$, $D_2\simeq 1.27$, $D_3\simeq2.82$ and $D_4\simeq 3.59$. The figure shows the values $p_1(2.2)\approx 0.47$, $p_2(2.2)\approx 4.17$, $p_3(2.2)\approx 0.77$, $p_4(2.2)\approx 2.71$
The biological parameters values are given in Table 5, Case 4. In red curve of equation $a_3 = 0$, in blue, a component of the curve of equation $\Delta = 0$. In black, the curve $p^0 = p_c(D)$ (a): The full regions $\varUpsilon_0$, $\varUpsilon_1$ and $\varUpsilon_2$. (b): a zoom showing the values $p_1 = p_1(D)$, $p_2 = p_2(D)$ $p_3 = p_3(D)$ and $p_4 = p_4(D)$ for $D = 0.013$. For the clarity of the figures, the points $p_1(D)$ and $p_2(D)$, for $D = 0.01$, are not depicted on the figure
The biological parameters values are given in Table 5, Case 5. In red curve of equation $a_3 = 0$, in blue, a component of the curve of equation $\Delta = 0$. In black, the curve $p^0 = p_c(D)$ (a): The full regions $\varUpsilon_0$, $\varUpsilon_1$ and $\varUpsilon_2$. (b): A zoom showing the values $D_1$ and $D_2$ and $p_1$ and $p_2$ corresponding to $D = 1.26$
The plots of curves $p^0 = p_c(D)$, in black, $\Delta = 0$, in blue, and $a_1a_2 = a_0a_3$ in magenta. The biological parameters values are given in Table 5, Case 2
The curve $p^0 = p_c(D)$ is plotted in black. (a): The plots of curves $\Delta = 0$ ($\mathcal{C}_1\cup\mathcal{A}_1\cup\mathcal{A}_2$, in blue), $a_3 = 0$ ($\mathcal{C}_2$, in red). (b): The plots of curves $a_1a_2 = a_0a_3$ ($\mathcal{C}_3\cup\mathcal{C}_4$, in magenta) and $a_2 = 0$ ($\mathcal{C}_5$, in cyan). The biological parameters are given in Table 5, Case 3
The curve $p^0 = p_c(D)$ is plotted in black. (a): The plots of curves $\Delta = 0$ ($\mathcal{C}_1\cup\mathcal{A}_1\cup\mathcal{A}_2$, in blue), $a_3 = 0$ ($\mathcal{C}_2$, in red), $a_1a_2 = a_0a_3$ ($\mathcal{C}_3\cup\mathcal{C}_4$, in magenta) and $a_2 = 0$ ($\mathcal{C}_5$, in cyan). (b): A zoom of the strip $0<p^0<1$. The biological parameters are given in Table 5, Case 3
Meanings and units of the variables and parameters of (1)
 Meanings Units $S$, $x$, $y$, $p$ Concentrations of substrate, species and inhibitor mass/volume $S^0$, $p^0$ Input concentrations of substrate and inhibitor mass/volume $D$ Dilution rate 1/time $m_1$, $m_2$ Maximal growth rates of the competitors 1/time $K_1$, $K_2$ Half saturation constants of the competitors mass/volume $\delta$ Maximal growth rate of detoxification 1/time $K$ Half saturation constant of detoxification mass/volume $\gamma$ Lethal effect of $p$ on $x$ volume/mass $\beta_1$, $\beta_2$ Growth yield coefficients dimensionless
 Meanings Units $S$, $x$, $y$, $p$ Concentrations of substrate, species and inhibitor mass/volume $S^0$, $p^0$ Input concentrations of substrate and inhibitor mass/volume $D$ Dilution rate 1/time $m_1$, $m_2$ Maximal growth rates of the competitors 1/time $K_1$, $K_2$ Half saturation constants of the competitors mass/volume $\delta$ Maximal growth rate of detoxification 1/time $K$ Half saturation constant of detoxification mass/volume $\gamma$ Lethal effect of $p$ on $x$ volume/mass $\beta_1$, $\beta_2$ Growth yield coefficients dimensionless
Boundaries of the regions in the operating diagram. The color code is used in Figs. 2, 3, 5, 7, 8, 10, 12, 13, 14, 15
 Boundary Color Equation in $\left(p^0, S^0\right)$-plane, with $D\in I_c$ fixed $\Gamma_1$ blue Graph of $S^0 =f_1^{-1}(D+\gamma p^0)$ $\Gamma_2$ black Horizontal line $S^0 = \lambda_2(D)$ $\Gamma_3$ red Vertical line $p^0 = p_c(D)$ and $S^0> \lambda_2(D)$ $\Gamma_4$ cyan Oblique line $S^0=\frac{D\left(p^0-p_c(D)\right)}{\beta_2g(p_c(D))}+\lambda_2(D)$ and $p^0>p_c(D)$ $\Gamma_5$ green Curve of equation $F_3(D,p^0,S^0)=0$
 Boundary Color Equation in $\left(p^0, S^0\right)$-plane, with $D\in I_c$ fixed $\Gamma_1$ blue Graph of $S^0 =f_1^{-1}(D+\gamma p^0)$ $\Gamma_2$ black Horizontal line $S^0 = \lambda_2(D)$ $\Gamma_3$ red Vertical line $p^0 = p_c(D)$ and $S^0> \lambda_2(D)$ $\Gamma_4$ cyan Oblique line $S^0=\frac{D\left(p^0-p_c(D)\right)}{\beta_2g(p_c(D))}+\lambda_2(D)$ and $p^0>p_c(D)$ $\Gamma_5$ green Curve of equation $F_3(D,p^0,S^0)=0$
Existence and stability of equilibrium points in the regions of the operating diagram, shown in Figs. 2, 3, 5, 7, 8, 10, 12, 13, 14, 15
 Regions $\mathcal J_0$ $\mathcal J_1$ $\mathcal J_2$ $\mathcal J_3$ $\mathcal J_4$ $\mathcal J_{5}^S$ $\mathcal J_{5}^U$ $\mathcal J_{6}^S$ $\mathcal J_{6}^U$ $E_0$ S U U U U U U U U $E_1$ S S U U U $E_2$ S U S U U U U $E_{c}$ S U S U
 Regions $\mathcal J_0$ $\mathcal J_1$ $\mathcal J_2$ $\mathcal J_3$ $\mathcal J_4$ $\mathcal J_{5}^S$ $\mathcal J_{5}^U$ $\mathcal J_{6}^S$ $\mathcal J_{6}^U$ $E_0$ S U U U U U U U U $E_1$ S S U U U $E_2$ S U S U U U U $E_{c}$ S U S U
Biological parameters values used in the numerical computations shown in the figures. The yields are $\beta_1 = \beta_2 = 1$, excepted for Fig. 15 in which $\beta_1 = \beta_2 = 100$. The last column of the table shows the value of $\overline{D}$ such that $E_c$ exists for $D\in(0,\overline{D})$
 Case $m_1$ $m_2$ $K_1$ $K_2$ $\delta$ $K$ $\gamma$ Figures $\overline{D}$ 1 4.0 5.0 0.3 1.0 3.0 0.3 4.0 24 3.54 2 4.0 5.0 0.06 1.0 5.0 1.3 4.0 25, 5, 16 3.94 3 4.0 5.0 0.03 1.0 5.0 1.3 4.0 26, 7, 8, 13, 14, 15, 17, 18 3.97 4 1.7 2 0.4 0.9 15 0.03 0.025 9, 10 1.46 5 4.0 5.0 0.03 1.0 0.5 1.3 4.0 11, 12 3.97
 Case $m_1$ $m_2$ $K_1$ $K_2$ $\delta$ $K$ $\gamma$ Figures $\overline{D}$ 1 4.0 5.0 0.3 1.0 3.0 0.3 4.0 24 3.54 2 4.0 5.0 0.06 1.0 5.0 1.3 4.0 25, 5, 16 3.94 3 4.0 5.0 0.03 1.0 5.0 1.3 4.0 26, 7, 8, 13, 14, 15, 17, 18 3.97 4 1.7 2 0.4 0.9 15 0.03 0.025 9, 10 1.46 5 4.0 5.0 0.03 1.0 0.5 1.3 4.0 11, 12 3.97
Existence and stability of equilibrium points $E_0$, $E_1$, $E_2$ and $E_c$ of (3), given in Prop. 1. Here, $\lambda_2$ and $\lambda^+$ are given by (5), $\lambda^-$ is given by (7) and $A_1$, $A_2$, $A_3$ and $A_4$ are given by (17)
 Existence Local exponential stability $E_0$ Always $\min(\lambda^+,\lambda_2)>S^0$ $E_1$ $\lambda^+ A_1^2A_4$
 Existence Local exponential stability $E_0$ Always $\min(\lambda^+,\lambda_2)>S^0$ $E_1$ $\lambda^+ A_1^2A_4$
Existence and stability of equilibrium points of (3), with respect to the operating parameters $D$, $S^0$ and $p^0$. The functions $F_1$, $F_2$, $F_3$ are defined by (19), (20), (21), respectively
 Existence Local exponential stability $E_0$ Always $D>\max(f_1(S^0)-\gamma p^0,f_2(S^0))$ $E_1$ $DF_1(D,p^0)$ & $S^0>F_2(D,p^0)$ $F_3(D,p^0,S^0)>0$
 Existence Local exponential stability $E_0$ Always $D>\max(f_1(S^0)-\gamma p^0,f_2(S^0))$ $E_1$ $DF_1(D,p^0)$ & $S^0>F_2(D,p^0)$ $F_3(D,p^0,S^0)>0$
The signs of functions $a_2$, $a_3$, $a_1a_2-a_0a_3$ and $\Delta$. Here $\mathcal{A} = R_1\cup\mathcal{A}_1\cup R_2\cup\mathcal{A}_2$
 Function $<0$ $=0$ $>0$ $\Delta$ $Ext\left(\mathcal{C}_1\right)\setminus \mathcal{A}$ $\mathcal{C}_1\cup\mathcal{A}_1\cup\mathcal{A}_2$ $Int\left(\mathcal{C}_1\right)\cup R_1\cup R_2$ $a_3$ $Int\left(\mathcal{C}_2\right)$ $\mathcal{C}_2$ $Ext\left(\mathcal{C}_2\right)$ $a_1a_2-a_0a_3$ $Int\left(\mathcal{C}_3\right)\cap Ext\left(\mathcal{C}_4\right)$ $\mathcal{C}_3\cup\mathcal{C}_4$ $Ext\left(\mathcal{C}_3\right)\cup Int\left(\mathcal{C}_4\right)$ $a_2$ $Int\left(\mathcal{C}_5\right)$ $\mathcal{C}_5$ $Ext\left(\mathcal{C}_5\right)$
 Function $<0$ $=0$ $>0$ $\Delta$ $Ext\left(\mathcal{C}_1\right)\setminus \mathcal{A}$ $\mathcal{C}_1\cup\mathcal{A}_1\cup\mathcal{A}_2$ $Int\left(\mathcal{C}_1\right)\cup R_1\cup R_2$ $a_3$ $Int\left(\mathcal{C}_2\right)$ $\mathcal{C}_2$ $Ext\left(\mathcal{C}_2\right)$ $a_1a_2-a_0a_3$ $Int\left(\mathcal{C}_3\right)\cap Ext\left(\mathcal{C}_4\right)$ $\mathcal{C}_3\cup\mathcal{C}_4$ $Ext\left(\mathcal{C}_3\right)\cup Int\left(\mathcal{C}_4\right)$ $a_2$ $Int\left(\mathcal{C}_5\right)$ $\mathcal{C}_5$ $Ext\left(\mathcal{C}_5\right)$
 [1] Jianquan Li, Zuren Feng, Juan Zhang, Jie Lou. A competition model of the chemostat with an external inhibitor. Mathematical Biosciences & Engineering, 2006, 3 (1) : 111-123. doi: 10.3934/mbe.2006.3.111 [2] Georg Hetzer, Wenxian Shen. Two species competition with an inhibitor involved. Discrete & Continuous Dynamical Systems - A, 2005, 12 (1) : 39-57. doi: 10.3934/dcds.2005.12.39 [3] Jifa Jiang, Fensidi Tang. The complete classification on a model of two species competition with an inhibitor. Discrete & Continuous Dynamical Systems - A, 2008, 20 (3) : 659-672. doi: 10.3934/dcds.2008.20.659 [4] Hua Nie, Wenhao Xie, Jianhua Wu. Uniqueness of positive steady state solutions to the unstirred chemostat model with external inhibitor. Communications on Pure & Applied Analysis, 2013, 12 (3) : 1279-1297. doi: 10.3934/cpaa.2013.12.1279 [5] Nahla Abdellatif, Radhouane Fekih-Salem, Tewfik Sari. Competition for a single resource and coexistence of several species in the chemostat. Mathematical Biosciences & Engineering, 2016, 13 (4) : 631-652. doi: 10.3934/mbe.2016012 [6] Hua Nie, Yuan Lou, Jianhua Wu. Competition between two similar species in the unstirred chemostat. Discrete & Continuous Dynamical Systems - B, 2016, 21 (2) : 621-639. doi: 10.3934/dcdsb.2016.21.621 [7] Hua Nie, Feng-Bin Wang. Competition for one nutrient with recycling and allelopathy in an unstirred chemostat. Discrete & Continuous Dynamical Systems - B, 2015, 20 (7) : 2129-2155. doi: 10.3934/dcdsb.2015.20.2129 [8] Frédéric Mazenc, Michael Malisoff, Patrick D. Leenheer. On the stability of periodic solutions in the perturbed chemostat. Mathematical Biosciences & Engineering, 2007, 4 (2) : 319-338. doi: 10.3934/mbe.2007.4.319 [9] Hua Nie, Sze-bi Hsu, Jianhua Wu. A competition model with dynamically allocated toxin production in the unstirred chemostat. Communications on Pure & Applied Analysis, 2017, 16 (4) : 1373-1404. doi: 10.3934/cpaa.2017066 [10] Sze-Bi Hsu, Cheng-Che Li. A discrete-delayed model with plasmid-bearing, plasmid-free competition in a chemostat. Discrete & Continuous Dynamical Systems - B, 2005, 5 (3) : 699-718. doi: 10.3934/dcdsb.2005.5.699 [11] Frederic Mazenc, Gonzalo Robledo, Michael Malisoff. Stability and robustness analysis for a multispecies chemostat model with delays in the growth rates and uncertainties. Discrete & Continuous Dynamical Systems - B, 2018, 23 (4) : 1851-1872. doi: 10.3934/dcdsb.2018098 [12] Zhiqi Lu. Global stability for a chemostat-type model with delayed nutrient recycling. Discrete & Continuous Dynamical Systems - B, 2004, 4 (3) : 663-670. doi: 10.3934/dcdsb.2004.4.663 [13] E. Cabral Balreira, Saber Elaydi, Rafael Luís. Local stability implies global stability for the planar Ricker competition model. Discrete & Continuous Dynamical Systems - B, 2014, 19 (2) : 323-351. doi: 10.3934/dcdsb.2014.19.323 [14] Shanshan Chen, Jianshe Yu. Stability and bifurcation on predator-prey systems with nonlocal prey competition. Discrete & Continuous Dynamical Systems - A, 2018, 38 (1) : 43-62. doi: 10.3934/dcds.2018002 [15] Satoshi Kosugi, Yoshihisa Morita, Shoji Yotsutani. A complete bifurcation diagram of the Ginzburg-Landau equation with periodic boundary conditions. Communications on Pure & Applied Analysis, 2005, 4 (3) : 665-682. doi: 10.3934/cpaa.2005.4.665 [16] Masaaki Mizukami. Boundedness and asymptotic stability in a two-species chemotaxis-competition model with signal-dependent sensitivity. Discrete & Continuous Dynamical Systems - B, 2017, 22 (6) : 2301-2319. doi: 10.3934/dcdsb.2017097 [17] Wei-Ming Ni, Yaping Wu, Qian Xu. The existence and stability of nontrivial steady states for S-K-T competition model with cross diffusion. Discrete & Continuous Dynamical Systems - A, 2014, 34 (12) : 5271-5298. doi: 10.3934/dcds.2014.34.5271 [18] Guo-Bao Zhang, Fang-Di Dong, Wan-Tong Li. Uniqueness and stability of traveling waves for a three-species competition system with nonlocal dispersal. Discrete & Continuous Dynamical Systems - B, 2019, 24 (4) : 1511-1541. doi: 10.3934/dcdsb.2018218 [19] Xiongxiong Bao, Wan-Tong Li, Zhi-Cheng Wang. Uniqueness and stability of time-periodic pyramidal fronts for a periodic competition-diffusion system. Communications on Pure & Applied Analysis, 2020, 19 (1) : 253-277. doi: 10.3934/cpaa.2020014 [20] Masaaki Mizukami. Improvement of conditions for asymptotic stability in a two-species chemotaxis-competition model with signal-dependent sensitivity. Discrete & Continuous Dynamical Systems - S, 2020, 13 (2) : 269-278. doi: 10.3934/dcdss.2020015

2018 Impact Factor: 1.008