Comparison of metabolite production capability indices generated by network analysis methods

Ishii, Kyota; Nakamura, Seira; Morohashi, Mineo; Sugimoto, Masahiro; Ohashi, Yoshiaki; Kikuchi, Shinichi; Tomita, Masaru

doi:10.1016/j.biosystems.2007.08.010

Cited by 3 publications

(4 citation statements)

References 21 publications

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“…Thus, the probability of achieving other cell‐scale models using these approaches appears to be very low. Recently, there have been efforts by investigators to develop methods to fill the gap between constraint‐based models and kinetic models (Famili et al , 2005; Smallbone et al , 2007; Ishii et al , 2008).…”

Section: Discussionmentioning

confidence: 99%

Formulating genome‐scale kinetic models in the post‐genome era

Jamshidi

Palsson

2008

Molecular Systems Biology

159

138

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The biological community is now awash in high-throughput data sets and is grappling with the challenge of integrating disparate data sets. Such integration has taken the form of statistical analysis of large data sets, or through the bottom-up reconstruction of reaction networks. While progress has been made with statistical and structural methods, large-scale systems have remained refractory to dynamic model building by traditional approaches. The availability of annotated genomes enabled the reconstruction of genome-scale networks, and now the availability of high-throughput metabolomic and fluxomic data along with thermodynamic information opens the possibility to build genome-scale kinetic models. We describe here a framework for building and analyzing such models. The mathematical analysis challenges are reflected in four foundational properties, (i) the decomposition of the Jacobian matrix into chemical, kinetic and thermodynamic information, (ii) the structural similarity between the stoichiometric matrix and the transpose of the gradient matrix, (iii) the duality transformations enabling either fluxes or concentrations to serve as the independent variables and (iv) the timescale hierarchy in biological networks. Recognition and appreciation of these properties highlight notable and challenging new in silico analysis issues.

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Section: Discussionmentioning

confidence: 99%

Formulating genome‐scale kinetic models in the post‐genome era

Jamshidi

Palsson

2008

Molecular Systems Biology

159

138

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“…Pathway-based methods are powerful tools for investigating various biological phenomena at the system or functional level (Ishii et al 2008). The results from our study revealed overrepresentation of the MAPK pathway and a higher degree of interaction in the pathway network in CMM patients.…”

Section: Discussionmentioning

confidence: 99%

“…The results from our study revealed overrepresentation of the MAPK pathway and a higher degree of interaction in the pathway network in CMM patients. This pathway is activated under a variety of persistent pain conditions and leads to the induction of pain hypersensitivity through transcriptional or nontranscriptional regulation (Ishii et al 2008; Ji et al 2009). Moreover, MAPKs play an important role in the progression to chronic pain (Patil and Kirkwood 2007).…”

Section: Discussionmentioning

confidence: 99%

Molecular Changes Involving MEK3–p38 MAPK Activation in Chronic Masticatory Myalgia

et al. 2016

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The exact mechanism underlying chronic masticatory myalgia (CMM), a conspicuous symptom in temporomandibular disorders, remains unclear. This investigation compared gene expression profiles between CMM patients and healthy subjects. Peripheral blood leukocytes were collected in 8 cases and 8 controls and subjected to whole genome microarray analyses. Data were analyzed with Gene Ontology and interactive pathways analyses. According to Gene Ontology analysis, categories such as ion transport, response to stimuli, and metabolic process were upregulated. The pathway analysis suggested overexpression of the mitogen-activated protein kinase (MAPK) pathway in CMM patients and to a higher degree in a pathway network. Overexpression of representative members of the MAPK pathway-including MAPK kinase 3 (MEK3), calcium voltage-gated channel auxiliary subunit gamma 2 (CACNG2), and growth arrest and DNA damage-inducible gamma (GADD45G)-was validated with real-time polymerase chain reaction. The upregulation of MEK3 was negatively correlated with the age of the CMM group. In the next step, the authors focused on MEK3, the gene that exhibited the greatest degree of differential expression, and its downstream target protein p38 MAPK. The results revealed upregulation of MEK3, as well as phosphorylated MEK3 and phosphorylated p38 MAPK, in CMM patients. These results provide a "fingerprint" for mechanistic studies of CMM in the future and highlight the importance of MEK3-p38 MAPK activation in CMM.

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“…In silico genome‐scale modeling of metabolism has proven to be useful in the field of metabolic systems engineering . Being a valuable guide for identification and filling of knowledge gaps, once a metabolic network is reconstructed, mathematical methods such as convex analysis and linear programming can be applied to (i) simulate the cellular behavior under different genetic and physiological conditions, (ii) develop metabolic engineering strategies for the construction of strains with desired and improved properties, and (iii) understand the topological features of metabolic networks …”

Section: Introductionmentioning

confidence: 99%

The stimulatory effect of mannitol on levan biosynthesis: Lessons from metabolic systems analysis of Halomonas smyrnensis AAD6^T

Ateş

Arğa

Öner

2013

Biotechnology Progress

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Halomonas smyrnensis AAD(T) is a halophilic, gram-negative bacterium that can efficiently produce levan from sucrose as carbon source via levansucrase activity. However, systems-based approaches are required to further enhance its metabolic performance for industrial application. As an important step toward this goal, the genome-scale metabolic network of Chromohalobacter salexigens DSM3043, which is considered a model organism for halophilic bacteria, has been reconstructed based on its genome annotation, physiological information, and biochemical information. In the present work, the genome-scale metabolic network of C. salexigens was recruited, and refined via integration of the available biochemical, physiological, and phenotypic features of H. smyrnensis AAD6(T) . The generic metabolic model, which comprises 1,393 metabolites and 1,108 reactions, was then systematically analyzed in silico using constraints-based simulations. To elucidate the relationship between levan biosynthesis and other metabolic processes, an enzyme-graph representation of the metabolic network and a graph decomposition technique were employed. Using the concept of control effective fluxes, significant links between several metabolic processes and levan biosynthesis were estimated. The major finding was the elucidation of the stimulatory effect of mannitol on levan biosynthesis, which was further verified experimentally via supplementation of mannitol to the fermentation medium. The optimal concentration of 30 g/L mannitol supplemented to the 50 g/L sucrose-based medium resulted in a twofold increase in levan production in parallel with increased sucrose hydrolysis rate, accumulated extracellular glucose, and decreased fructose uptake rate.

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Comparison of metabolite production capability indices generated by network analysis methods

Cited by 3 publications

References 21 publications

Formulating genome‐scale kinetic models in the post‐genome era

Formulating genome‐scale kinetic models in the post‐genome era

Molecular Changes Involving MEK3–p38 MAPK Activation in Chronic Masticatory Myalgia

The stimulatory effect of mannitol on levan biosynthesis: Lessons from metabolic systems analysis of Halomonas smyrnensis AAD6^T

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Comparison of metabolite production capability indices generated by network analysis methods

Cited by 3 publications

References 21 publications

Formulating genome‐scale kinetic models in the post‐genome era

Formulating genome‐scale kinetic models in the post‐genome era

Molecular Changes Involving MEK3–p38 MAPK Activation in Chronic Masticatory Myalgia

The stimulatory effect of mannitol on levan biosynthesis: Lessons from metabolic systems analysis of Halomonas smyrnensis AAD6T

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The stimulatory effect of mannitol on levan biosynthesis: Lessons from metabolic systems analysis of Halomonas smyrnensis AAD6^T