Title: MiniCourse on Mathematical Modeling of Biological Systems
1Mini-Course onMathematical Modeling of
Biological Systems
- Frank Doyle
- Dept. of Chemical Engineering
- University of Delaware
- (302) 831-0760
- fdoyle_at_udel.edu
2General Descriptions of Metabolic Systems
- In general, dynamics must be accounted for
- A number of simplifying assumptions invoked
- steady-state
- simple goals or costs functions
3Cybernetic Models
- Introduced by Ramkrishna co-workers
- Key tenet microorganisms implement regulatory
strategies with outcomes consistent with a
desired goal - Requires formulation of objective function for
specific structural units from which cybernetic
control variables are defined (enzyme synthesis
enzyme activity) - Does not replace detailed modeling of metabolic
pathways or ignore biochemical details - rather
it supplies the regulatory mechanisms - Wide success in describing varying bacterial
uptake patterns of mixed, substitutable
substrates in batch, fed-batch, and continuous
reactors
4Basic Postulates
- The primary goal of a microorganism is to
maximize growth rate. - The objective of promoting any irreversible
linear pathway is the maximization of that
pathways end product. - All end products produced at a branch point are
essential for growth therefore cellular growth
stops when any one end product is absent. - The objective of promoting any irreversible
branched pathway is the maximization of the
mathematical product of the end products produced
by one or more branch points. - The objective of promoting any irreversible
cyclic pathway is the maximization of the
mathematical product of all the intermediates of
the cycle whether or not they were withdrawn for
further utilization in order to maintain the
integrity of the cycle.
5(contd)
- In the presence of competing processes, whether
substitutable or complementary in nature, the
enzyme catalyzing the process that provides for
the greatest return will be activated to the
greatest extent. The appropriate measure of the
returns received from promoting a given process
is dependent upon the process type, e.g.,
substitutable or complementary. - Metabolic regulation is present in a hierarchical
structure compromising both local and global
levels - As the status of a substrate is altered form
limiting to nonlimiting, the excess substrate is
available for the synthesis of additional
structural and energetic resources.
6Cybernetic Framework
BIOMASS
ENZYMES
INTERNAL RESOURCES INTERMEDIATES
C
N
ENZYME SYNTHESIS
REGULATORY PROCESSES
S
P
METABOLISM (INTERMEDIATE SYNTHESIS)
etc.
O
7Optimal Control vs. Instantaneous Optimization
- Endpoint optimization
- ui fraction critical resources
- Instantaneous optimization
- ui maximizes return
8Example Klebsiella pneumoniae
- glucose feed, watch cell density as output
- Model equations
- cell density
- growth enzyme
- maintenance enzyme
- cellular resource level
- substrate concentration
9Key Rate Functions
- growth rate
- growth enzyme production rate
- maintenance enzyme production rate
- rate of resource synthesis
10PHB production in Alcaligenes eutrophus
- Motivation
- polymer biodegradable, thermoplastic
- process green synthesis route for polyesters
- Potential applications
- medical (implants, drug delivery)
- film, packaging
- Cybernetic model developed by Varner Bailey
11Pathway Structure
storage pathway model
cr
example cybernetic variable governing synthesis
of key biomass growth enzyme, eg
12Cybernetic Variable Governing Synthesis of Key
Growth Enzyme
Cybernetic variable adjusting synthesis rate of eg
Ammonium nitrate concentration in reactor
13Model Equations
14Parameter Identification
- Model parameters identified from batch cultures
15Continuous Culture with Biomass Recycle
biomass recycle
dilution rate (glucose and ammonium feed)
PHB productivity
ideal separator (microfiltration)
reactor
glucose measurement
16Wash-out Disturbance
17Cybernetic Variable Profiles
- Cybernetic variables governing synthesis of
enzymes for PHB storage and biomass growth
18Cybernetic Variables Governing Enzyme Activity
- Cybernetic variables are non-smooth functions
- cybernetic variable modulating activity of
storage enzyme - Batch culture profile for v3
- Gradient based optimization?
19Generalized Framework (Varner, 2000)
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