Related Experiment Video
Updated: Oct 1, 2025
11:07
High-Throughput Metabolic Profiling for Model Refinements of Microalgae
Published on: December 4, 2021
3.9K
[Development of metabolic models with multiple constraints: a review]
Xue Yang1,2,3, Peiji Zhang1,2, Zhitao Mao2
1School of Chemical Engineering and Technology, Tianjin University, Tianjin 300350, China.
Summary
This review covers metabolic models with multiple constraints (MCGEMs) for improved metabolic engineering. MCGEMs precisely identify targets for optimizing industrially important microorganisms.
Area of Science:
- Metabolic Engineering
- Systems Biology
- Computational Biology
Background:
- Genome-scale metabolic models (GEMs) predict cellular phenotypes.
- GEMs traditionally use stoichiometric constraints.
- Enzyme and thermodynamic factors also limit metabolic phenotypes.
Purpose of the Study:
- Review recent advances in metabolic models with multiple constraints (MCGEMs).
- Highlight construction methods and applications of MCGEMs.
- Emphasize MCGEMs' role in guiding metabolic engineering.
Main Methods:
- Integration of stoichiometric, enzymatic, and thermodynamic constraints.
- Development of consistent modeling frameworks for MCGEMs.
- Simulation of gene knockouts and pathway analysis.
Main Results:
- MCGEMs improve prediction accuracy of metabolic phenotypes.
- MCGEMs enable precise identification of metabolic bottlenecks.
- MCGEMs facilitate identification of targets for pathway optimization.
Conclusions:
- MCGEMs offer a more reliable framework for metabolic engineering.
- MCGEMs provide precise targets for optimizing microorganisms.
- MCGEMs enhance the design of industrial biotechnology processes.
Related Concept Videos
01:14Multicompartment Models: Overview
278
Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
278
01:29Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
111
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
111
01:21Mechanistic Models: Overview of Compartment Models
183
Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
183
01:23Mechanistic Models: Compartment Models in Individual and Population Analysis
95
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
95
01:14Model Approaches for Pharmacokinetic Data: Compartment Models
239
Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...
Two primary types of compartment models are recognized: mammillary and catenary. The more...
239
01:15Model Approaches for Pharmacokinetic Data: Physiological Models
132
Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
132