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

Metabolic network structure and function in bacteria goes beyond conserved enzyme components.

Jannell V Bazurto1, Diana M Downs1

  • 1Department of Microbiology, University of Georgia, Athens, GA 30602, USA.

Microbial Cell (Graz, Austria)
|March 31, 2017
PubMed
Summary

Metabolic network reconstructions using genome annotation may not accurately predict function. A recent study shows that conserved metabolic components alone are insufficient for predicting network structure and biological activity.

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

Adaptation of <i>Methylobacterium extorquens</i> to alternating carbon sources identifies the regulator CstR as an intersectional hub of cellular carbon metabolic dynamics and stress response.

bioRxiv : the preprint server for biology·2026
Same author

Decreasing peptide deformylase activity is a beneficial strategy for increasing formaldehyde resistance in <i>Methylobacterium extorquens</i>.

bioRxiv : the preprint server for biology·2026
Same author

PLP Homeostasis Protein Is Required for Efficient Maturation of Aromatic Amino Acid Aminotransferase in Salmonella enterica.

Molecular microbiology·2026
Same author

Beneath the surface: expanding the known repertoire of methylotrophic metabolism.

Applied and environmental microbiology·2026
Same author

The XRE family protein DbuR is a transcriptional repressor of the <i>dbu</i> operon in <i>Pseudomonas putida</i>.

Applied and environmental microbiology·2025
Same author

Biochemical and structural characterization of a reactive intermediate deaminase A homolog from Streptococcus sanguinis.

Scientific reports·2025

Area of Science:

  • Systems Biology
  • Metabolic Engineering
  • Bioinformatics

Background:

  • Experimental and genetic data have built our understanding of metabolic networks.
  • Genome annotation and metabolic reconstructions are used to infer organismal metabolism and model networks *in silico*.
  • These *in silico* models have been crucial for exploring microbial metabolism.

Purpose of the Study:

  • To investigate whether *in silico* metabolic reconstructions accurately capture higher-level network organization and flux distribution.
  • To rigorously test the assumption that conserved metabolic components lead to conserved metabolic network architecture and function.

Main Methods:

  • Analysis of a recent study (MBio 5;7(1): e01840-15).
  • Evaluation of the predictive power of genome annotation and metabolic network reconstructions.
Keywords:
metabolic integrationmetabolic networkphosphoribosylamine (PRA)phosphoribosylpyrophosphate amidotransferase (PurF)plasticitythiamine synthesis

Related Experiment Videos

  • Assessment of the relationship between conserved metabolic components and overall network function.

    • Main Results:

    • The study demonstrated that conservation of metabolic components is not sufficient to predict metabolic network structure.
    • Conserved components did not adequately predict higher levels of network organization or flux distribution.
    • Current *in silico* approaches may overestimate the accuracy of metabolic network predictions.

    Conclusions:

    • The assumption that conserved metabolic parts equate to conserved metabolic networks is flawed.
    • Relying solely on genome annotation for metabolic network prediction may lead to inaccuracies.
    • Further research is needed to develop more robust methods for predicting metabolic network behavior.