Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Characterizing the metabolic phenotype: a phenotype phase plane analysis.

Jeremy S Edwards1, Ramprasad Ramakrishna, Bernhard O Palsson

  • 1Department of Chemical Engineering, University of Delaware, Newark, Delaware 19716, USA. edwards@che.udel.edu

Biotechnology and Bioengineering
|December 18, 2001
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

A genome-scale metabolic model of a globally disseminated hyperinvasive M1 strain of <i>Streptococcus pyogenes</i>.

mSystems·2024
Same author

Biological and genetic determinants of glycolysis: Phosphofructokinase isoforms boost energy status of stored red blood cells and transfusion outcomes.

Cell metabolism·2024
Same author

A treasure trove of 1034 actinomycete genomes.

Nucleic acids research·2024
Same author

Proteome allocation is linked to transcriptional regulation through a modularized transcriptome.

Nature communications·2024
Same author

The hallmarks of a tradeoff in transcriptomes that balances stress and growth functions.

mSystems·2024
Same author

Deciphering nutritional stress responses via knowledge-enriched transcriptomics for microbial engineering.

Metabolic engineering·2024
Same journal

Minimizing Off-Target Effects of CRISPR-Cas9 With Optimized sgRNA: Evaluation of Efficiency and Specificity in the Tumor Protein 53 (TP53) Region.

Biotechnology and bioengineering·2026
Same journal

Metabolic Flux Analysis Reveals Cell Line-Specific Rewiring in CHO Cells Following TCA Cycle Intermediate Feeding for Bioprocess pH Control.

Biotechnology and bioengineering·2026
Same journal

Photohydrogenotrophic Cultivation of Purple Non-Sulfur Bacteria in an Open Bioreactor: Enhanced Selectivity Through Light Cycling and Ammonium Limitation.

Biotechnology and bioengineering·2026
Same journal

Translating Blue Light Stimulation From Batch to Perfusion: Process and Intracellular Metabolic Analysis.

Biotechnology and bioengineering·2026
Same journal

Nanocarrier-Based Gene Delivery Systems: Mechanisms, Clinical Translation, and Future Perspectives.

Biotechnology and bioengineering·2026
Same journal

Development and Integrated Application of the Multi-Attribute Method (MAM) in Quality Control of Biotechnological Drugs.

Biotechnology and bioengineering·2026
See all related articles

This study introduces a novel "phase plane" analysis for metabolic networks, mapping optimal flux distributions across various conditions. This approach reveals distinct metabolic states and genotype-phenotype relationships for improved understanding.

Area of Science:

  • Systems Biology
  • Metabolic Engineering
  • Computational Biology

Background:

  • Genome-scale metabolic reconstructions are essential for understanding cellular metabolism.
  • Flux Balance Analysis (FBA) traditionally analyzes one condition at a time, limiting insights into metabolic capabilities.
  • A comprehensive view requires analyzing metabolic networks across diverse growth conditions.

Purpose of the Study:

  • To develop a novel "phase plane" analysis for metabolic networks.
  • To map optimal metabolic flux distributions across a range of conditions defined by substrate availability.
  • To characterize distinct metabolic states and their relationship to genotype-phenotype dynamics.

Main Methods:

  • Reconstruction of genome-scale metabolic maps.

Related Experiment Videos

  • Broadened Flux Balance Analysis (FBA) to map flux distributions onto a substrate availability plane.
  • Identification and interpretation of distinct metabolic phases using shadow price isoclines.
  • Generation of Phenotype Phase Planes (PhPPs) for Escherichia coli.

    • Main Results:

    • A finite number of qualitatively distinct metabolic pathway utilization patterns were identified, dividing the phase plane into discrete phases.
    • Isoclines derived from shadow prices effectively classify the metabolic network's state.
    • Phenotype Phase Planes (PhPPs) were generated for E. coli, illustrating metabolic phenotypes under varying carbon sources and oxygenation levels.

    Conclusions:

    • The developed "phase plane" analysis provides a powerful tool for understanding metabolic genotype-phenotype relations across multiple conditions.
    • This methodology offers a more comprehensive view of metabolic network capabilities compared to traditional single-condition FBA.
    • The study demonstrates the utility of PhPPs for analyzing microbial metabolism, with implications for metabolic engineering and synthetic biology.