Evidence map›Paper›PMID 22309974›Full record

ArticleBMC systems biology2012

Enumerating metabolic pathways for the production of heterologous target chemicals in chassis organisms.

Pablo Carbonell, Davide Fichera, Shashi B Pandit, Jean-Loup Faulon

Abstract read
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Article in BMC systems biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

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0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Review
  2. Article
  3. Heuristic shortest hyperpaths in cell signaling hypergraphs.Algorithms for molecular biology : AMB · 2022
    Article
  4. American journal of translational research · 2020
    Article
  5. Article
  6. Discovery and implementation of a novel pathway forBiotechnology for biofuels · 2019
    Article
  7. Finding the K best synthesis plans.Journal of cheminformatics · 2018
    Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Metabolic modelling in the development of cell factories by synthetic biology.Computational and structural biotechnology journal · 2012
    Review
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

4 authors.

Pablo CarbonelliSSB, Institute of Systems and Synthetic Biology, University of Evry, Genopole Campus 1, Genavenir 6, 5 rue Henri Desbruères, 91030 EVRY Cedex, France.
Davide Fichera
Shashi B Pandit
Jean-Loup Faulon

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe consider the possibility of engineering metabolic pathways in a chassis organism in order to synthesize novel target compounds that are heterologous to the chassis. For this purpose, we model metabolic networks through hypergraphs where reactions are represented by hyperarcs. Each hyperarc represents an enzyme-catalyzed reaction that transforms set of substrates compounds into product compounds. We follow a retrosynthetic approach in order to search in the metabolic space (hypergraphs) for pathways (hyperpaths) linking the target compounds to a source set of compounds.

resultsTo select the best pathways to engineer, we have developed an objective function that computes the cost of inserting a heterologous pathway in a given chassis organism. In order to find minimum-cost pathways, we propose in this paper two methods based on steady state analysis and network topology that are to the best of our knowledge, the first to enumerate all possible heterologous pathways linking a target compounds to a source set of compounds. In the context of metabolic engineering, the source set is composed of all naturally produced chassis compounds (endogenuous chassis metabolites) and the target set can be any compound of the chemical space. We also provide an algorithm for identifying precursors which can be supplied to the growth media in order to increase the number of ways to synthesize specific target compounds.

conclusionsWe find the topological approach to be faster by several orders of magnitude than the steady state approach. Yet both methods are generally scalable in time with the number of pathways in the metabolic network. Therefore this work provides a powerful tool for pathway enumeration with direct application to biosynthetic pathway design.

Indexed as

AlgorithmsModels, BiologicalEnzymesMetabolic EngineeringMetabolic Networks and PathwaysEnzymes

Identifiers

PMID22309974
PMCPMC3311073

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.