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Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways.

ABSTRACT: Various 'omics' technologies, including microarrays and gas chromatography mass spectrometry, can be used to identify hundreds of interesting genes, proteins and metabolites, such as differential genes, proteins and metabolites associated with diseases. Identifying metabolic pathways has become an invaluable aid to understanding the genes and metabolites associated with studying conditions. However, the classical methods used to identify pathways fail to accurately consider joint power of interesting gene/metabolite and the key regions impacted by them within metabolic pathways. In this study, we propose a powerful analytical method referred to as Subpathway-GM for the identification of metabolic subpathways. This provides a more accurate level of pathway analysis by integrating information from genes and metabolites, and their positions and cascade regions within the given pathway. We analyzed two colorectal cancer and one metastatic prostate cancer data sets and demonstrated that Subpathway-GM was able to identify disease-relevant subpathways whose corresponding entire pathways might be ignored using classical entire pathway identification methods. Further analysis indicated that the power of a joint genes/metabolites and subpathway strategy based on their topologies may play a key role in reliably recalling disease-relevant subpathways and finding novel subpathways.

SUBMITTER: Li C

PROVIDER: S-EPMC3643575 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

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Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways.

Li Chunquan C Han Junwei J Yao Qianlan Q Zou Chendan C Xu Yanjun Y Zhang Chunlong C Shang Desi D Zhou Lingyun L Zou Chaoxia C Sun Zeguo Z Li Jing J Zhang Yunpeng Y Yang Haixiu H Gao Xu X Li Xia X

Nucleic acids research 20130312 9

Various 'omics' technologies, including microarrays and gas chromatography mass spectrometry, can be used to identify hundreds of interesting genes, proteins and metabolites, such as differential genes, proteins and metabolites associated with diseases. Identifying metabolic pathways has become an invaluable aid to understanding the genes and metabolites associated with studying conditions. However, the classical methods used to identify pathways fail to accurately consider joint power of intere ...[more]

PMID: 23482392

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Project description:BackgroundSteroids are lipophilic compounds with a gonane skeleton and play an important role in higher organisms. Due to different functionalizations - mainly hydroxylations - at the steroid molecule, they vary highly in their mode of action. The pharmaceutical industry is, therefore, interested in hydroxysteroids as therapeutic agents. The insertion of hydroxyl groups into a steroid core, however, is hardly accomplishable by classical chemical means; that is because microbial steroid hydroxylations are investigated and applied since decades. CYP106A2 is a cytochrome P450 monooxygenase from Bacillus megaterium ATCC 13368, which was first described in the late 1970s and which is capable to hydroxylate a variety of 3-oxo-delta4 steroids at position 15beta. CYP106A2 is a soluble protein, easy to express and to purify in high amounts, which makes this enzyme an interesting target for biotechnological purposes.ResultsIn this work a focused steroid library was screened in vitro for new CYP106A2 substrates using a reconstituted enzyme assay. Five new substrates were identified, including dehydroepiandrosterone and pregnenolone. NMR-spectroscopy revealed that both steroids are mainly hydroxylated at position 7beta. In order to establish a biotechnological system for the preparative scale production of 7beta-hydroxylated dehydroepiandrosterone, whole-cell conversions with growing and resting cells of B. megaterium ATCC1336 the native host of CYP1062 and also with resting cells of a recombinant B. megaterium MS941 strain overexpressing CYP106A2 have been conducted and conversion rates of 400 muM/h (115 mg/l/h) were obtained. Using the B. megaterium MS941 overexpression strain, the selectivity of the reaction was improved from 0.7 to 0.9 for 7beta-OH-DHEA.ConclusionsIn this work we describe CYP106A2 for the first time as a regio-selective hydroxylase for 3-hydroxy-delta5 steroids. DHEA was shown to be converted to 7beta-OH-DHEA which is a highly interesting human metabolite, supposed to act as neuroprotective, anti-inflammatory and immune-modulatory agent. Optimization of the whole-cell system using different B. megaterium strains lead to a conversion of DHEA with B. megaterium showing high selectivity and conversion rates and displaying a volumetric yield of 103 mg/l/h 7beta-OH-DHEA.

Dataset Information

Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways.

Publications

Subpathway-GM: identification of metabolic subpathways via joint power of interesting genes and metabolites and their topologies within pathways.

Similar Datasets

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