Team:ZJU-China/Modeling
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- | + | <p><a name="jumptop" id="p_intro"> Introduction </a>|<a id="p_model"> Model </a>|<a id="p_simul"> Simulation </a>|<a id="p_refer">Reference</a></p> | |
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<p>Calculate growth and oxygen concentration gradient of a biofilm which consists of Heterotrophic bacteria. The water inflow at a constant rate contains substrates and Oxygen. Growth occurs with Monod-type rate laws. Respiration occurs with specific rate. <strong>A program variable LF</strong> referring to Biofilm Thickness and <strong>3 dynamic volume state variables O_2, S, X</strong> referring to oxygen, substrates and the Heterotrophic bacteria are defined. All necessary constants and initial conditions are defined in following table. Some of their values are based on average results provided by IWA.</p> | <p>Calculate growth and oxygen concentration gradient of a biofilm which consists of Heterotrophic bacteria. The water inflow at a constant rate contains substrates and Oxygen. Growth occurs with Monod-type rate laws. Respiration occurs with specific rate. <strong>A program variable LF</strong> referring to Biofilm Thickness and <strong>3 dynamic volume state variables O_2, S, X</strong> referring to oxygen, substrates and the Heterotrophic bacteria are defined. All necessary constants and initial conditions are defined in following table. Some of their values are based on average results provided by IWA.</p> | ||
- | <img src=" | + | <img src="https://static.igem.org/mediawiki/2011/d/d9/Zju-filmpara.png" style="width:750px;" alt="peremater"> |
<p>Definition of Process:</p> | <p>Definition of Process:</p> | ||
<p>Define a dynamic process for growth, a dynamic process for respiration, and a dynamic process | <p>Define a dynamic process for growth, a dynamic process for respiration, and a dynamic process | ||
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<img src="https://static.igem.org/mediawiki/2011/3/38/Zju-results1.png" alt="Results1"> | <img src="https://static.igem.org/mediawiki/2011/3/38/Zju-results1.png" alt="Results1"> | ||
<img src="https://static.igem.org/mediawiki/2011/e/e5/Zju-results2.png" alt="Results2"> | <img src="https://static.igem.org/mediawiki/2011/e/e5/Zju-results2.png" alt="Results2"> | ||
- | <img src="https://static.igem.org/mediawiki/2011/ | + | <img src="https://static.igem.org/mediawiki/2011/c/cb/Zju-results3.png" alt="Results3"> |
- | <img src="https://static.igem.org/mediawiki/2011/ | + | <img src="https://static.igem.org/mediawiki/2011/8/80/Zju-results4.png" alt="Results4"> |
- | <img src="https://static.igem.org/mediawiki/2011/ | + | <img src="https://static.igem.org/mediawiki/2011/9/97/Zju-results5.png" alt="Results5"> |
+ | <p>Fit above graph into polynomial, we have:</p> | ||
+ | <img src="https://static.igem.org/mediawiki/2011/8/85/Zju-results6.png" alt="Results6"> | ||
+ | <p>Where the equation of the polynomial is:</p> | ||
+ | <img src="https://static.igem.org/mediawiki/2011/a/a4/Zjufunction20.png" style="float:right;" alt="function18"/> | ||
+ | </div> | ||
+ | <div class="block" id="reference"><h3>Reference</h3><hr/> | ||
+ | <table style="background-color:transparent;" width="0" border="0" cellspacing="1" cellpadding="1"> | ||
+ | <tr> | ||
+ | <td>[1]</td> | ||
+ | <td>O Wanner, H Eberl, E Morgenroth, D Noguera, C Picioreanu, B Rittmann, M Loosdrecht. ”Mathematical Modeling of Biofilms, IWA Task Group on Biofilm Modeling.”, Scientific and Technical Report, 2006.</td> | ||
+ | </tr> | ||
+ | <tr> | ||
+ | <td>[2]</td> | ||
+ | <td>P Reichert. “AQUASIM 2.0-Tutorial” Swiss Federal Institute for Environmental Science and Technology, 1998. </td> | ||
+ | </tr> | ||
+ | <tr> | ||
+ | <td>[3]</td> | ||
+ | <td>P Reichert. “AQUASIM 2.0-User Manual” Swiss Federal Institute for Environmental Science and Technology, 1998.</td> | ||
+ | </tr> | ||
+ | <tr> | ||
+ | <td>[4]</td> | ||
+ | <td>LI Tian-cheng, LI Xin-gang, ZHU Shen-lin.”Two-Dimension Dynamic Simulations on Biofilm Forming and Developing”. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2005.</td> | ||
+ | </tr> | ||
+ | </table> | ||
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Latest revision as of 10:39, 5 October 2011
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Modeling|biofilm |
This model is used for simulating biofilm formation and the stratification of concentration of oxygen
Introduction
Compartment:The biofilm itself is distinguished from the overlying water and the substratum to which it is attached. A mass-transport boundary layer separates the biofilm from the overlying water.
Within each compartment are components: include different types of biomass ,substrates , products. biomass is often divided into active microbial species, inert cells, and extracellular polymeric substances(EPS).
The components can undergo transformation, transport, and transfer processes. For example, substrate is consumed, and this leads to the synthesis of new active biomass.
All process affecting each component in each compartment are mathematically linked together into a mass balance equation that contains rate terms and parameters for each process.
Model Selection:Many kinds of Mathematics models have been founded to describe a system of biofilm. Models of different dimensions (1d, 2d, 3d) focus on different properties of a biofilm. Since we care most about the oxygen concentration gradients perpendicular to the substratum, numerical 1-dimensional dynamic model(N1) would be a proper choice for us.
Compartment
The biofilm:A biofilm is a gel-like aggregation of microorganisms and other particles embedded in extracellular polymeric substances. A biofilm contains water inside it, but its main physical characteristic is that it is a solid phase. A biofilm normally is anchored to a solid surface called the substratum on one side and in contact with liquid on its other side. Frequently, a mass-transfer boundary layer is included between the bulk liquid and the biofilm itself. Thus, following figure illustrates a biofilm having four compartments: the substratum, the biofilm itself, the boundary layer, and the bulk liquid outside of the biofilm. While it is complex even for a homogeneous biofilm morphology, we assume the biofilm surface is flat and all material below the maximum biofilm thickness as part of the biofilm components, and they have a constant density.
the mass-transport boundary layerExperimental observations clearly indicate strong concentration gradients for solutes just outside the biofilm when these solutes are utilized or produced by the microorganisms in the biofilm. Consequently, the solute concentrations at the biofilm surface and in a completely mixed bulk liquid often are significantly different.So we introduce the mass-transport boundary layer,which is a hypothetical layer of liquid above the biofilm and in which all the resistance to mass transport of dissolved components outside the biofilm occurs.
The bulk liquid: In our experiments, the bulk liquid is large compared to the biofilm. So the simplest way seems to consider it as a boundary condition of the biofilm compartment and specify the concentrations of dissolved. However, dissolved components can exchange between the biofilm and the bulk liquid, and it has a profound impact on the concentrations in the bulk liquid. Thus we include the bulk liquid not only as a boundary condition, but also as a separate, completely mixed compartment, varying according to the inflow, outflow, and the exchanges with the biofilm.
The substratum: In our basic model, the substratum is a separate compartment and impermeable. So it does not have much effect on the biofilm system. However in some bioreactor, the substratum may be permeable, or include organic solids that are biodegraded by attached microorganisms.
Component
Dissolved components: There are two kind of dissolved components in our model, one is oxygen, the other is substrates where nutrients are inside. They are expressed by inflow concentration of oxygen, inflow concentration of substrates and monod half saturation constant for substrates, monod half saturation constant for oxygen.Diffusion coefficient of oxygen and diffusion coefficient of substrate are also used to characterize the property of these components.
Particulate components: In our model, the particulate components are microbes and EPS. We assume that they are homogeneously mixed in the same proportion in all parts of the biofilm. So can use bacterial density to relate the amount of bacterial and the volume it takes up. And the volume fraction of EPS in Bacterial is specified by a constant.
Process
Transformation processes usually are biochemical reactions that produce or consume one or more components: e.g., consumption of substrate, production of metabolic end-products, microbial growth and decay, and production of EPS.
The transport processes that regularly are considered in biofilm models are advection, molecular diffusion, and turbulent dispersion. In special cases, transport of charged components by migration in an electric field created is included. The general, 1d expression to model the specific mass flux of a component is calculuted in the direction z
Transfer processes exchange mass of dissolved or particulate components between two compartments. At the interface between the compartments, a continuity condition for the component concentration C and the specific flux j of the exchanged mass must be fulfilled. Continuity means that C and j are the same on both sides of the interface between the compartments. C and j can be calculated at each side of the interface from boundary conditions
Modeling
An introduction to N1 model:
The core of the N1 model consists of a system of stiff, non-linear partial differential equations. Because of the stiffness of the equation system, integration methods tailored for stiff systems must be used, or the dissolved and the particulate components have to be treated differently. Furthermore, biofilm growth, i.e., the displacement of the interface between biofilm and bulk liquid, creates a so-called moving boundary problem (Kissel et al. 1984; Wanner and Gujer 1986).We performed simulations with the N1 model using the software package AQUASIM (Reichert 1998a, 1998b), since it can handle stiff systems and the moving boundary. The N1 model implemented in AQUASIM is described in next Section.
The processes considered in the model include:
- many transformation processes
- advection and diffusion of attached particulate components in the biofilm solid matrix
- attachment and detachment of particulate components at the biofilm surface and in the biofilm interior
- diffusion of suspended particulate and dissolved components in the biofilm liquid phase and in the liquid boundary layer at the biofilm surface
- complete mixing of suspended particulate and dissolved components in the bulk liquid
Definitions and equations
As discussed above, biofilms are multiphase systems. Consequently, in the N1 model three different phases are distinguished. The solid attached phase is made up by the particulate components, which form the biofilm solid matrix. In the model of single species of bacteria, the particulate components are assumed to be uniform, defined as
where X_M is the concentration of the attached component, ρ is its density , defined as the mass divided by the volume of the cell or particle, and ε is its volume fraction, defined as volume of the component per unit biofilm volume. The porosity or biofilm pore volume fraction θ is
The pore volume is formed by two phases: the phase of the suspended particulate components with concentrations X_P and the biofilm liquid phase, with the liquid phase volume fraction ε_liquid:
Mass balances in biobilm models
Conservation of mass of a component in a dynamic and open system states that:
The local mass balances are differential equations that express the variation of concentration of a component in time in a point in space as a result of transport and transformation processes. One-dimensional mass balance equations for attached particulate, suspended particulate, and dissolved components can be derived from the general mass balance if gradients are considered only in the direction of z, perpendicular to the substratum
where t is time; z is perpendicular coordinates ; S is the concentration; j is the mass flux along the perpendicular coordinates; and r is the net production rate of the component. For a dissolved substrate S_i, the specific mass flux j_i in the biofilm, can be modeled by Fick’s first law of diffusion as
Where D_i is the molecular diffusivity of substrate in the biofilm. Substituting this equation into the equation (1) yields a mass balance equation that describes the development in time and the spatial profile in the biofilm of the concentration S_i of a dissolved substrate as
where r_i is the net production rate of S_i. Equation (3) has the boundary condition
at the substratum (z=0) and
at the biofilm–bulk liquid interface (z=LF), where LF is the biofilm thickness and S_LF, i is the substrate concentration at the biofilm surface. All terms in equation (6) are given as substrate mass per unit biofilm volume. Equations (6) to (8) also hold for suspended particulate components, i.e., for cells or particles which are suspended in the biofilm pore volume and have the concentration X_P.
For attached particulate components, which form the biofilm solid matrix, transport is assumed to be the result of microbial growth and decay in the biofilm. Growing or shrinking cells lead to a volume expansion or contraction of the biofilm solid matrix, respectively, and to a displacement of neighboring cells (Wanner 1989). This displacement can be interpreted as advective transport and is formally described as a specific mass flux j_M by
where u_F is the distance by which the cells are displaced per unit time. The displacement velocity u_F of a cell at the location z is equal to the added net specific mass production of the cells the biofilm matrix between the substratum and this location:
where r_M is the net production rate of a particulate component in the biofilm matrix. Based on equations (9), with u_F as defined in (10), a mass balance analogous to equation (6) can be derived and used to describe the development in time and the spatial profile in the biofilm of the attached particulate component:
The boundary condition is no-flux condition:
at the substratum. Equation (11) is used to calculate the relative abundance, spatial distribution, and development in time of microbial species and particles in the biofilm.
The development of the biofilm thickness in time is the result of the net production of biomass in the biofilm, as described by equation (10), of the attachment at the biofilm surface of microbial cells and particles suspended in the bulk liquid, and of the detachment of microbial cells and particles from the biofilm surface to the bulk liquid. It is modeled as
where u_de and u_at are the detachment velocity and the attachment velocity, respectively. The velocity u_de yields a phenomenological description of the decrease of the biofilm thickness per unit time as result of the detachment process, i.e., erosion or sloughing.
Attachment refers to the adsorption of microbial cells suspended in the bulk liquid to the biofilm surface and is modeled by an attachment velocity as
where k is the attachment rate coefficient and X_L is the concentration at the bulk liquid side of the biofilm surface of the suspended particulate component.
The environment of the biofilm is modeled as a completely mixed volume of water, termed bulk liquid. Conversion processes in the bulk liquid can be equally important as those that take place in the biofilm. For each dissolved and particulate component considered, an additional mass balance equation of the form
is needed, where C_in,i and C_B, i are the influent and bulk liquid concentrations, respectively, of the dissolved or suspended particulate component i, V_B is the bulk liquid volume, Q is the rate of flow through the bulk liquid, A_F is the biofilm surface area, j_F,i is the mass flux across the biofilm surface , and r_B,i is the production rate of the component.
Transformation processes
In modeling, the transformation processes are represented mathematically with rate expressions, or equations that tell how fast the component is produced or consumed. The rate is proportional to the concentrations of one or more of the components and one or more kinetic parameters. We describe the synthesis of microbial biomass with the Monod equation for one limiting substrate:
where μ is the specific growth rate, μ_max the maximum specific growth rate, S is the concentration of the rate-limiting substrate, and K_S is the concentration giving one-half the maximum rate.
When multiple substrates are rate limiting, the Monod equation typically is extended to include the effects of each substrate influencing the rate of microbial synthesis. For instance, is the rate of microbial synthesis may be limited by the concentrations of the electron donor (S_1, e.g. COD) and the electron acceptor (S_2, e.g. Oxygen) then the specific growth rate can be described with a multiplicative-Monod expression (Bae and Rittmann 1996):
Synthesis is not the only transformation process relevant to microorganisms in a biofilm. Indeed, the microorganisms undergo a number of loss processes, including endogenous decay (or inactivation), predation, and detachment. The inactivation process is common in almost any biofilm and serves as a model for how to express a biomass-loss process.
Synthesis is not the only transformation process relevant to microorganisms in a biofilm. Indeed, the microorganisms undergo a number of loss processes, including endogenous decay (or inactivation), predation, and detachment. The inactivation process is common in almost any biofilm and serves as a model for how to express a biomass-loss process.A simple and common means to represent inactivation/decay is with a first-order loss rate
where r_in is the inactivation rate and b is the first-order inactivation rate constant. Because utilization of a substrate is what brings about biomass synthesis, the rate of substrate utilization is proportional to the growth rate of X:
where Y is the true-yield coefficient, or the ratio of biomass produced per unit of substrate consumed. Similar equations could be founded to describe rates in other processes. Following table summarizes the basic rate expressions for heterotrophic bacteria in a convenient and commonly used matrix format. The Monod half saturation constant for oxygen K in processes of growth and respiration are assumed to be equal.
Simulation
Calculate growth and oxygen concentration gradient of a biofilm which consists of Heterotrophic bacteria. The water inflow at a constant rate contains substrates and Oxygen. Growth occurs with Monod-type rate laws. Respiration occurs with specific rate. A program variable LF referring to Biofilm Thickness and 3 dynamic volume state variables O_2, S, X referring to oxygen, substrates and the Heterotrophic bacteria are defined. All necessary constants and initial conditions are defined in following table. Some of their values are based on average results provided by IWA.
Definition of Process:
Define a dynamic process for growth, a dynamic process for respiration, and a dynamic process for inactivation. The microbial stoichiometric numbers of the processes of S (referring to substrates) and O_2 (referring to Oxygen) and rate of the processes are shown in following table.
Simulation results
Definition of simulation
Define an active calculation with proper steps of 1 day.
Fit above graph into polynomial, we have:
Where the equation of the polynomial is:
Reference
[1] | O Wanner, H Eberl, E Morgenroth, D Noguera, C Picioreanu, B Rittmann, M Loosdrecht. ”Mathematical Modeling of Biofilms, IWA Task Group on Biofilm Modeling.”, Scientific and Technical Report, 2006. |
[2] | P Reichert. “AQUASIM 2.0-Tutorial” Swiss Federal Institute for Environmental Science and Technology, 1998. |
[3] | P Reichert. “AQUASIM 2.0-User Manual” Swiss Federal Institute for Environmental Science and Technology, 1998. |
[4] | LI Tian-cheng, LI Xin-gang, ZHU Shen-lin.”Two-Dimension Dynamic Simulations on Biofilm Forming and Developing”. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2005. |