Regular Article
Assessment of the Metabolic Capabilities of Haemophilus influenzae Rd through a Genome-scale Pathway Analysis

https://doi.org/10.1006/jtbi.2000.1088Get rights and content

Abstract

The annotated full DNA sequence is becoming available for a growing number of organisms. This information along with additional biochemical and strain-specific data can be used to define metabolic genotypes and reconstruct cellular metabolic networks. The first free-living organism for which the entire genomic sequence was established wasHaemophilus influenzae . Its metabolic network is reconstructed herein and contains 461 reactions operating on 367 intracellular and 84 extracellular metabolites. With the metabolic reaction network established, it becomes necessary to determine its underlying pathway structure as defined by the set of extreme pathways. The H. influenzae metabolic network was subdivided into six subsystems and the extreme pathways determined for each subsystem based on stoichiometric, thermodynamic, and systems-specific constraints. Positive linear combinations of these pathways can be taken to determine the extreme pathways for the complete system. Since these pathways span the capabilities of the full system, they could be used to address a number of important physiological questions. First, they were used to reconcile and curate the sequence annotation by identifying reactions whose function was not supported in any of the extreme pathways. Second, they were used to predict gene products that should be co-regulated and perhaps co-expressed. Third, they were used to determine the composition of the minimal substrate requirements needed to support the production of 51 required metabolic products such as amino acids, nucleotides, phospholipids, etc. Fourth, sets of critical gene deletions from core metabolism were determined in the presence of the minimal substrate conditions and in more complete conditions reflecting the environmental niche of H. influenzae in the human host. In the former case, 11 genes were determined to be critical while six remained critical under the latter conditions. This study represents an important milestone in theoretical biology, namely the establishment of the first extreme pathway structure of a whole genome.

References (36)

  • D.A. BENSON et al.

    GenBank

    Nucleic Acids Res.

    (1999)
  • U.S. BHALLA et al.

    Emergent properties of networks of biological signaling pathways

    Science

    (1999)
  • K.M. BISGARD et al.

    Haemophilus influenzae invasive disease in the United States, 1994–1995: near disappearance of a vaccine-preventable childhood disease

    Emerg. Infect. Dis.

    (1998)
  • G. CASARI et al.

    Challenging times for bioinformatics

    Nature

    (1995)
  • J.S. EDWARDS et al.

    How will bioinformatics influence metabolic engineering?

    Biotechnol. Bioeng.

    (1998)
  • D. ENDY et al.

    Intracellular kinetics of a growing virus: a genetically structured simulation for bacteriophage T7

    Biotechnol. Bioeng.

    (1997)
  • N.M. EVANS et al.

    Haemin and nicotinamide adenine dinucleotide requirements of Haemophilus influenzae and Haemophilus parainfluenzae

    J. Med. Microbiol.

    (1974)
  • Cited by (188)

    • Flux modeling for monolignol biosynthesis

      2019, Current Opinion in Biotechnology
      Citation Excerpt :

      Constraint-based models are ideal when information on kinetic parameters are limited as they only use information about the stoichiometry of the pathway. Models such as Flux Balance Analysis (FBA) assume quasi-steady-state of pathway fluxes that reach equilibrium relatively quickly with respect to varying external fluxes [16,17]. Metabolic pathways are typically overdetermined because the number of reactions exceeds the number of metabolites in the pathways, which means there is no unique solution to these constraint-based problems.

    • Metabolic models

      2018, Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics
    View all citing articles on Scopus
    View full text