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Metabolic engineering of Bacillus subtilis for terpenoid production.

Guan Z, Xue D, Abdallah II, Dijkshoorn L, Setroikromo R, Lv G, Quax WJ - Appl. Microbiol. Biotechnol. (2015)

Bottom Line: On the other hand, our literature survey (20 years) revealed that terpenoids are naturally more widespread in Bacillales.In the mid-1990s, an inherent methylerythritol phosphate (MEP) pathway was discovered in Bacillus subtilis (B. subtilis).We will summarize some major advances and outline future directions for exploiting the potential of B. subtilis as a desired "cell factory" to produce terpenoids.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmaceutical Biology, Groningen Research Institute of Pharmacy, University of Groningen, Antonius Deusinglaan 1, Building 3215, room 917, 9713 AV, Groningen, The Netherlands.

ABSTRACT
Terpenoids are the largest group of small-molecule natural products, with more than 60,000 compounds made from isopentenyl diphosphate (IPP) and its isomer dimethylallyl diphosphate (DMAPP). As the most diverse group of small-molecule natural products, terpenoids play an important role in the pharmaceutical, food, and cosmetic industries. For decades, Escherichia coli (E. coli) and Saccharomyces cerevisiae (S. cerevisiae) were extensively studied to biosynthesize terpenoids, because they are both fully amenable to genetic modifications and have vast molecular resources. On the other hand, our literature survey (20 years) revealed that terpenoids are naturally more widespread in Bacillales. In the mid-1990s, an inherent methylerythritol phosphate (MEP) pathway was discovered in Bacillus subtilis (B. subtilis). Since B. subtilis is a generally recognized as safe (GRAS) organism and has long been used for the industrial production of proteins, attempts to biosynthesize terpenoids in this bacterium have aroused much interest in the scientific community. This review discusses metabolic engineering of B. subtilis for terpenoid production, and encountered challenges will be discussed. We will summarize some major advances and outline future directions for exploiting the potential of B. subtilis as a desired "cell factory" to produce terpenoids.

No MeSH data available.


Related in: MedlinePlus

Flowchart and resources for terpenoid microbial metabolomics study. a Microbial metabolic engineering workflow. b Related information of each step for microbial metabolic engineering. * Selected resources: 1. MS data of B. subtilis metabolites (Coulier et al. 2006; Koek et al. 2006; Soga et al. 2003). 2. The metabolomics standards initiative (Fiehn et al. 2007). 3. Microbial metabolomics study examples for terpenoid biosynthesis (Paddon and Keasling 2014; Zhou et al. 2012). 4. Databases, software packages, and protocols (Thiele and Palsson 2010) and http://omictools.com/. 5. Genome-scale data of reconstructed B. subtilis metabolic net (impact of single-gene deletions on growth in B. subtilis) (Oh et al. 2007). 6. Comparative microbial metabolomics study of E. coli, B. subtilis, and S. cerevisiae (van der Werf et al. 2007). 7. The complete genome sequence of B. subtilis (Kunst et al. 1997). 8. Constraint-based modeling methods (Bordbar et al. 2014). 9. Software applications for flux balance analysis (including a software comparative list) (Lakshmanan et al. 2012). 10. Sample treatment methods (Jia et al. 2004; Larsson and Törnkvist 1996; Maharjan and Ferenci 2003; van der Werf et al. 2007; Villas-Bôas and Bruheim 2007)
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Sch1: Flowchart and resources for terpenoid microbial metabolomics study. a Microbial metabolic engineering workflow. b Related information of each step for microbial metabolic engineering. * Selected resources: 1. MS data of B. subtilis metabolites (Coulier et al. 2006; Koek et al. 2006; Soga et al. 2003). 2. The metabolomics standards initiative (Fiehn et al. 2007). 3. Microbial metabolomics study examples for terpenoid biosynthesis (Paddon and Keasling 2014; Zhou et al. 2012). 4. Databases, software packages, and protocols (Thiele and Palsson 2010) and http://omictools.com/. 5. Genome-scale data of reconstructed B. subtilis metabolic net (impact of single-gene deletions on growth in B. subtilis) (Oh et al. 2007). 6. Comparative microbial metabolomics study of E. coli, B. subtilis, and S. cerevisiae (van der Werf et al. 2007). 7. The complete genome sequence of B. subtilis (Kunst et al. 1997). 8. Constraint-based modeling methods (Bordbar et al. 2014). 9. Software applications for flux balance analysis (including a software comparative list) (Lakshmanan et al. 2012). 10. Sample treatment methods (Jia et al. 2004; Larsson and Törnkvist 1996; Maharjan and Ferenci 2003; van der Werf et al. 2007; Villas-Bôas and Bruheim 2007)

Mentions: Because the research on the Bacillus MEP pathway is still at an early stage, it is urgent to develop guidelines for unbiased selection of the best rational design approach to engineering the terpenoid. The newest developments of metabolomics, meta-omics, computer, and mathematic sciences offer more options for not only unbiased selection and ranking methods but also high-throughput and more precise prediction models that enable a mechanistic description of microbial metabolic pathways (Breitmaier 2006; Martin et al., 2003). Scheme 1 summarizes the workflow, essential reports, and resources for the study of terpenoid microbial metabolomics.Scheme 1


Metabolic engineering of Bacillus subtilis for terpenoid production.

Guan Z, Xue D, Abdallah II, Dijkshoorn L, Setroikromo R, Lv G, Quax WJ - Appl. Microbiol. Biotechnol. (2015)

Flowchart and resources for terpenoid microbial metabolomics study. a Microbial metabolic engineering workflow. b Related information of each step for microbial metabolic engineering. * Selected resources: 1. MS data of B. subtilis metabolites (Coulier et al. 2006; Koek et al. 2006; Soga et al. 2003). 2. The metabolomics standards initiative (Fiehn et al. 2007). 3. Microbial metabolomics study examples for terpenoid biosynthesis (Paddon and Keasling 2014; Zhou et al. 2012). 4. Databases, software packages, and protocols (Thiele and Palsson 2010) and http://omictools.com/. 5. Genome-scale data of reconstructed B. subtilis metabolic net (impact of single-gene deletions on growth in B. subtilis) (Oh et al. 2007). 6. Comparative microbial metabolomics study of E. coli, B. subtilis, and S. cerevisiae (van der Werf et al. 2007). 7. The complete genome sequence of B. subtilis (Kunst et al. 1997). 8. Constraint-based modeling methods (Bordbar et al. 2014). 9. Software applications for flux balance analysis (including a software comparative list) (Lakshmanan et al. 2012). 10. Sample treatment methods (Jia et al. 2004; Larsson and Törnkvist 1996; Maharjan and Ferenci 2003; van der Werf et al. 2007; Villas-Bôas and Bruheim 2007)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4628092&req=5

Sch1: Flowchart and resources for terpenoid microbial metabolomics study. a Microbial metabolic engineering workflow. b Related information of each step for microbial metabolic engineering. * Selected resources: 1. MS data of B. subtilis metabolites (Coulier et al. 2006; Koek et al. 2006; Soga et al. 2003). 2. The metabolomics standards initiative (Fiehn et al. 2007). 3. Microbial metabolomics study examples for terpenoid biosynthesis (Paddon and Keasling 2014; Zhou et al. 2012). 4. Databases, software packages, and protocols (Thiele and Palsson 2010) and http://omictools.com/. 5. Genome-scale data of reconstructed B. subtilis metabolic net (impact of single-gene deletions on growth in B. subtilis) (Oh et al. 2007). 6. Comparative microbial metabolomics study of E. coli, B. subtilis, and S. cerevisiae (van der Werf et al. 2007). 7. The complete genome sequence of B. subtilis (Kunst et al. 1997). 8. Constraint-based modeling methods (Bordbar et al. 2014). 9. Software applications for flux balance analysis (including a software comparative list) (Lakshmanan et al. 2012). 10. Sample treatment methods (Jia et al. 2004; Larsson and Törnkvist 1996; Maharjan and Ferenci 2003; van der Werf et al. 2007; Villas-Bôas and Bruheim 2007)
Mentions: Because the research on the Bacillus MEP pathway is still at an early stage, it is urgent to develop guidelines for unbiased selection of the best rational design approach to engineering the terpenoid. The newest developments of metabolomics, meta-omics, computer, and mathematic sciences offer more options for not only unbiased selection and ranking methods but also high-throughput and more precise prediction models that enable a mechanistic description of microbial metabolic pathways (Breitmaier 2006; Martin et al., 2003). Scheme 1 summarizes the workflow, essential reports, and resources for the study of terpenoid microbial metabolomics.Scheme 1

Bottom Line: On the other hand, our literature survey (20 years) revealed that terpenoids are naturally more widespread in Bacillales.In the mid-1990s, an inherent methylerythritol phosphate (MEP) pathway was discovered in Bacillus subtilis (B. subtilis).We will summarize some major advances and outline future directions for exploiting the potential of B. subtilis as a desired "cell factory" to produce terpenoids.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmaceutical Biology, Groningen Research Institute of Pharmacy, University of Groningen, Antonius Deusinglaan 1, Building 3215, room 917, 9713 AV, Groningen, The Netherlands.

ABSTRACT
Terpenoids are the largest group of small-molecule natural products, with more than 60,000 compounds made from isopentenyl diphosphate (IPP) and its isomer dimethylallyl diphosphate (DMAPP). As the most diverse group of small-molecule natural products, terpenoids play an important role in the pharmaceutical, food, and cosmetic industries. For decades, Escherichia coli (E. coli) and Saccharomyces cerevisiae (S. cerevisiae) were extensively studied to biosynthesize terpenoids, because they are both fully amenable to genetic modifications and have vast molecular resources. On the other hand, our literature survey (20 years) revealed that terpenoids are naturally more widespread in Bacillales. In the mid-1990s, an inherent methylerythritol phosphate (MEP) pathway was discovered in Bacillus subtilis (B. subtilis). Since B. subtilis is a generally recognized as safe (GRAS) organism and has long been used for the industrial production of proteins, attempts to biosynthesize terpenoids in this bacterium have aroused much interest in the scientific community. This review discusses metabolic engineering of B. subtilis for terpenoid production, and encountered challenges will be discussed. We will summarize some major advances and outline future directions for exploiting the potential of B. subtilis as a desired "cell factory" to produce terpenoids.

No MeSH data available.


Related in: MedlinePlus