iso c16 mycosubtilin production  (ATCC)


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    ATCC iso c16 mycosubtilin production
    <t>Mycosubtilin</t> anteiso -C17.
    Iso C16 Mycosubtilin Production, supplied by ATCC, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    Images

    1) Product Images from "Bioinformatics Modelling and Metabolic Engineering of the Branched Chain Amino Acid Pathway for Specific Production of Mycosubtilin Isoforms in Bacillus subtilis"

    Article Title: Bioinformatics Modelling and Metabolic Engineering of the Branched Chain Amino Acid Pathway for Specific Production of Mycosubtilin Isoforms in Bacillus subtilis

    Journal: Metabolites

    doi: 10.3390/metabo12020107

    Mycosubtilin anteiso -C17.
    Figure Legend Snippet: Mycosubtilin anteiso -C17.

    Techniques Used:

    MIC determination of the mycosubtilin mixture and  mycosubtilin-purified  isoforms expressed in µM. Experiments were performed in triplicate.
    Figure Legend Snippet: MIC determination of the mycosubtilin mixture and mycosubtilin-purified isoforms expressed in µM. Experiments were performed in triplicate.

    Techniques Used:

    Mycosubtilin isoforms pattern of B. subtilis ATCC 6633 after 48 h of growth at 30 °C in modified Landy medium buffered at pH 7.0 with MOPS 100 mM and supplied either with Leu, Val, or Ile at 2 g/L. Results are mean values and standard deviations of four independent experiments.
    Figure Legend Snippet: Mycosubtilin isoforms pattern of B. subtilis ATCC 6633 after 48 h of growth at 30 °C in modified Landy medium buffered at pH 7.0 with MOPS 100 mM and supplied either with Leu, Val, or Ile at 2 g/L. Results are mean values and standard deviations of four independent experiments.

    Techniques Used: Modification

    New improved model of branched chain amino acid metabolic pathway developed for the overproduction of mycosubtilin anteiso -C17. Constraint was applied on the overproduction of anteiso -branched chain fatty acid ( anteiso -C15 + anteiso -C17 = ↑) and change predictions were visualized. Modelling language and semantics were first described by Coutte et al. (2015) , and improvements for this work are described in the paragraph 4.4 of the Materials and Methods section. This figure semantic description was extracted from Coutte et al. (2015) for better understanding of this figure. Reaction networks in our modeling language are represented as graphs similar to Petri nets. The concrete syntax of our reaction networks is based on XML, from which the graphs are computed. The XML representation is also the input for the prediction algorithm. These graphs contain two kinds of nodes: round nodes for representing its species and boxed nodes for representing its reactions. More precisely, any species S is represented by a round node and any reaction with name r by a boxed node . Solid edges either link a reactant to its reaction or a reaction to one of its products . There are three kinds of dashed edges, which start at the three kinds of modifiers. An accelerator edge links an accelerator to a reaction , an activator edge links an activator to a reaction , and an inhibitor edge links an inhibitor to a reaction . An input edge points from the context to an inflow species S , while an outflow edge points from an outflow species S to the context. For convenience, we introduced the last kind of edges as a shortcut for a product that is degraded by a hidden reaction, i.e., as a shortcut for . Species nodes with three different colors were used, which indicate their biological roles. Yellow indicates metabolites (such as ) and blue indicates proteins (such as ). There is a third color for “artificial species” that serves to modulate regulation, such as the promoter of the ilv-leu operon . Reactions that are potential candidates for knockouts or overexpression will be annotated in orange. Dark orange indicates candidates that were selected by our knockout prediction, while light orange indicates candidates that were not. Genes knockout predictions are represented by ⇓ and gene overexpression by ↑.
    Figure Legend Snippet: New improved model of branched chain amino acid metabolic pathway developed for the overproduction of mycosubtilin anteiso -C17. Constraint was applied on the overproduction of anteiso -branched chain fatty acid ( anteiso -C15 + anteiso -C17 = ↑) and change predictions were visualized. Modelling language and semantics were first described by Coutte et al. (2015) , and improvements for this work are described in the paragraph 4.4 of the Materials and Methods section. This figure semantic description was extracted from Coutte et al. (2015) for better understanding of this figure. Reaction networks in our modeling language are represented as graphs similar to Petri nets. The concrete syntax of our reaction networks is based on XML, from which the graphs are computed. The XML representation is also the input for the prediction algorithm. These graphs contain two kinds of nodes: round nodes for representing its species and boxed nodes for representing its reactions. More precisely, any species S is represented by a round node and any reaction with name r by a boxed node . Solid edges either link a reactant to its reaction or a reaction to one of its products . There are three kinds of dashed edges, which start at the three kinds of modifiers. An accelerator edge links an accelerator to a reaction , an activator edge links an activator to a reaction , and an inhibitor edge links an inhibitor to a reaction . An input edge points from the context to an inflow species S , while an outflow edge points from an outflow species S to the context. For convenience, we introduced the last kind of edges as a shortcut for a product that is degraded by a hidden reaction, i.e., as a shortcut for . Species nodes with three different colors were used, which indicate their biological roles. Yellow indicates metabolites (such as ) and blue indicates proteins (such as ). There is a third color for “artificial species” that serves to modulate regulation, such as the promoter of the ilv-leu operon . Reactions that are potential candidates for knockouts or overexpression will be annotated in orange. Dark orange indicates candidates that were selected by our knockout prediction, while light orange indicates candidates that were not. Genes knockout predictions are represented by ⇓ and gene overexpression by ↑.

    Techniques Used: Over Expression, Knock-Out

    Patterns of mycosubtilin isoforms of B. subtilis ATCC 6633 (gray bar), BV12I37 (CodY−; dark blue bar), and BBG133 (IlvA +; light blue bar) after 48 h of growth at 30 °C in the modified Landy medium. Results are mean values and standard deviations of two independent experiments.
    Figure Legend Snippet: Patterns of mycosubtilin isoforms of B. subtilis ATCC 6633 (gray bar), BV12I37 (CodY−; dark blue bar), and BBG133 (IlvA +; light blue bar) after 48 h of growth at 30 °C in the modified Landy medium. Results are mean values and standard deviations of two independent experiments.

    Techniques Used: Modification

    iso c16 mycosubtilin production  (ATCC)


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  • 94

    Structured Review

    ATCC iso c16 mycosubtilin production
    <t>Mycosubtilin</t> anteiso -C17.
    Iso C16 Mycosubtilin Production, supplied by ATCC, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/iso c16 mycosubtilin production/product/ATCC
    Average 94 stars, based on 1 article reviews
    Price from $9.99 to $1999.99
    iso c16 mycosubtilin production - by Bioz Stars, 2024-05
    94/100 stars

    Images

    1) Product Images from "Bioinformatics Modelling and Metabolic Engineering of the Branched Chain Amino Acid Pathway for Specific Production of Mycosubtilin Isoforms in Bacillus subtilis"

    Article Title: Bioinformatics Modelling and Metabolic Engineering of the Branched Chain Amino Acid Pathway for Specific Production of Mycosubtilin Isoforms in Bacillus subtilis

    Journal: Metabolites

    doi: 10.3390/metabo12020107

    Mycosubtilin anteiso -C17.
    Figure Legend Snippet: Mycosubtilin anteiso -C17.

    Techniques Used:

    MIC determination of the mycosubtilin mixture and  mycosubtilin-purified  isoforms expressed in µM. Experiments were performed in triplicate.
    Figure Legend Snippet: MIC determination of the mycosubtilin mixture and mycosubtilin-purified isoforms expressed in µM. Experiments were performed in triplicate.

    Techniques Used:

    Mycosubtilin isoforms pattern of B. subtilis ATCC 6633 after 48 h of growth at 30 °C in modified Landy medium buffered at pH 7.0 with MOPS 100 mM and supplied either with Leu, Val, or Ile at 2 g/L. Results are mean values and standard deviations of four independent experiments.
    Figure Legend Snippet: Mycosubtilin isoforms pattern of B. subtilis ATCC 6633 after 48 h of growth at 30 °C in modified Landy medium buffered at pH 7.0 with MOPS 100 mM and supplied either with Leu, Val, or Ile at 2 g/L. Results are mean values and standard deviations of four independent experiments.

    Techniques Used: Modification

    New improved model of branched chain amino acid metabolic pathway developed for the overproduction of mycosubtilin anteiso -C17. Constraint was applied on the overproduction of anteiso -branched chain fatty acid ( anteiso -C15 + anteiso -C17 = ↑) and change predictions were visualized. Modelling language and semantics were first described by Coutte et al. (2015) , and improvements for this work are described in the paragraph 4.4 of the Materials and Methods section. This figure semantic description was extracted from Coutte et al. (2015) for better understanding of this figure. Reaction networks in our modeling language are represented as graphs similar to Petri nets. The concrete syntax of our reaction networks is based on XML, from which the graphs are computed. The XML representation is also the input for the prediction algorithm. These graphs contain two kinds of nodes: round nodes for representing its species and boxed nodes for representing its reactions. More precisely, any species S is represented by a round node and any reaction with name r by a boxed node . Solid edges either link a reactant to its reaction or a reaction to one of its products . There are three kinds of dashed edges, which start at the three kinds of modifiers. An accelerator edge links an accelerator to a reaction , an activator edge links an activator to a reaction , and an inhibitor edge links an inhibitor to a reaction . An input edge points from the context to an inflow species S , while an outflow edge points from an outflow species S to the context. For convenience, we introduced the last kind of edges as a shortcut for a product that is degraded by a hidden reaction, i.e., as a shortcut for . Species nodes with three different colors were used, which indicate their biological roles. Yellow indicates metabolites (such as ) and blue indicates proteins (such as ). There is a third color for “artificial species” that serves to modulate regulation, such as the promoter of the ilv-leu operon . Reactions that are potential candidates for knockouts or overexpression will be annotated in orange. Dark orange indicates candidates that were selected by our knockout prediction, while light orange indicates candidates that were not. Genes knockout predictions are represented by ⇓ and gene overexpression by ↑.
    Figure Legend Snippet: New improved model of branched chain amino acid metabolic pathway developed for the overproduction of mycosubtilin anteiso -C17. Constraint was applied on the overproduction of anteiso -branched chain fatty acid ( anteiso -C15 + anteiso -C17 = ↑) and change predictions were visualized. Modelling language and semantics were first described by Coutte et al. (2015) , and improvements for this work are described in the paragraph 4.4 of the Materials and Methods section. This figure semantic description was extracted from Coutte et al. (2015) for better understanding of this figure. Reaction networks in our modeling language are represented as graphs similar to Petri nets. The concrete syntax of our reaction networks is based on XML, from which the graphs are computed. The XML representation is also the input for the prediction algorithm. These graphs contain two kinds of nodes: round nodes for representing its species and boxed nodes for representing its reactions. More precisely, any species S is represented by a round node and any reaction with name r by a boxed node . Solid edges either link a reactant to its reaction or a reaction to one of its products . There are three kinds of dashed edges, which start at the three kinds of modifiers. An accelerator edge links an accelerator to a reaction , an activator edge links an activator to a reaction , and an inhibitor edge links an inhibitor to a reaction . An input edge points from the context to an inflow species S , while an outflow edge points from an outflow species S to the context. For convenience, we introduced the last kind of edges as a shortcut for a product that is degraded by a hidden reaction, i.e., as a shortcut for . Species nodes with three different colors were used, which indicate their biological roles. Yellow indicates metabolites (such as ) and blue indicates proteins (such as ). There is a third color for “artificial species” that serves to modulate regulation, such as the promoter of the ilv-leu operon . Reactions that are potential candidates for knockouts or overexpression will be annotated in orange. Dark orange indicates candidates that were selected by our knockout prediction, while light orange indicates candidates that were not. Genes knockout predictions are represented by ⇓ and gene overexpression by ↑.

    Techniques Used: Over Expression, Knock-Out

    Patterns of mycosubtilin isoforms of B. subtilis ATCC 6633 (gray bar), BV12I37 (CodY−; dark blue bar), and BBG133 (IlvA +; light blue bar) after 48 h of growth at 30 °C in the modified Landy medium. Results are mean values and standard deviations of two independent experiments.
    Figure Legend Snippet: Patterns of mycosubtilin isoforms of B. subtilis ATCC 6633 (gray bar), BV12I37 (CodY−; dark blue bar), and BBG133 (IlvA +; light blue bar) after 48 h of growth at 30 °C in the modified Landy medium. Results are mean values and standard deviations of two independent experiments.

    Techniques Used: Modification

    iso c16  (ATCC)


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    ATCC iso c16
    Iso C16, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    iso c15 fatty acid c16  (ATCC)


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    ATCC iso c15 fatty acid c16
    Iso C15 Fatty Acid C16, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    aldehyde na iso c16  (ATCC)


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    ATCC aldehyde na iso c16
    Aldehyde Na Iso C16, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    iso c16  (ATCC)


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    ATCC iso c16
    Iso C16, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    iso c16  (ATCC)


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    ATCC iso c16
    Iso C16, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    iso c16  (ATCC)


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    ATCC iso c16
    Iso C16, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    iso c16  (ATCC)


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    ATCC iso c16
    Iso C16, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    tr iso c16  (ATCC)


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    ATCC tr iso c16
    Tr Iso C16, supplied by ATCC, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    iso c16  (ATCC)


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    ATCC iso c16
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    ATCC iso c16 mycosubtilin production
    <t>Mycosubtilin</t> anteiso -C17.
    Iso C16 Mycosubtilin Production, supplied by ATCC, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    ATCC iso c15 fatty acid c16
    <t>Mycosubtilin</t> anteiso -C17.
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    <t>Mycosubtilin</t> anteiso -C17.
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    ATCC tr iso c16
    <t>Mycosubtilin</t> anteiso -C17.
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    Mycosubtilin anteiso -C17.

    Journal: Metabolites

    Article Title: Bioinformatics Modelling and Metabolic Engineering of the Branched Chain Amino Acid Pathway for Specific Production of Mycosubtilin Isoforms in Bacillus subtilis

    doi: 10.3390/metabo12020107

    Figure Lengend Snippet: Mycosubtilin anteiso -C17.

    Article Snippet: The anteiso -C17 mycosubtilin production increased from 45.1% for ATCC 6633 to 63.6% for BBG133 (IlvA+), whereas the iso -C16 mycosubtilin production increased from 23.6% for ATCC 6633 to 66.1% for BV12I37 (CodY−).

    Techniques:

    MIC determination of the mycosubtilin mixture and  mycosubtilin-purified  isoforms expressed in µM. Experiments were performed in triplicate.

    Journal: Metabolites

    Article Title: Bioinformatics Modelling and Metabolic Engineering of the Branched Chain Amino Acid Pathway for Specific Production of Mycosubtilin Isoforms in Bacillus subtilis

    doi: 10.3390/metabo12020107

    Figure Lengend Snippet: MIC determination of the mycosubtilin mixture and mycosubtilin-purified isoforms expressed in µM. Experiments were performed in triplicate.

    Article Snippet: The anteiso -C17 mycosubtilin production increased from 45.1% for ATCC 6633 to 63.6% for BBG133 (IlvA+), whereas the iso -C16 mycosubtilin production increased from 23.6% for ATCC 6633 to 66.1% for BV12I37 (CodY−).

    Techniques:

    Mycosubtilin isoforms pattern of B. subtilis ATCC 6633 after 48 h of growth at 30 °C in modified Landy medium buffered at pH 7.0 with MOPS 100 mM and supplied either with Leu, Val, or Ile at 2 g/L. Results are mean values and standard deviations of four independent experiments.

    Journal: Metabolites

    Article Title: Bioinformatics Modelling and Metabolic Engineering of the Branched Chain Amino Acid Pathway for Specific Production of Mycosubtilin Isoforms in Bacillus subtilis

    doi: 10.3390/metabo12020107

    Figure Lengend Snippet: Mycosubtilin isoforms pattern of B. subtilis ATCC 6633 after 48 h of growth at 30 °C in modified Landy medium buffered at pH 7.0 with MOPS 100 mM and supplied either with Leu, Val, or Ile at 2 g/L. Results are mean values and standard deviations of four independent experiments.

    Article Snippet: The anteiso -C17 mycosubtilin production increased from 45.1% for ATCC 6633 to 63.6% for BBG133 (IlvA+), whereas the iso -C16 mycosubtilin production increased from 23.6% for ATCC 6633 to 66.1% for BV12I37 (CodY−).

    Techniques: Modification

    New improved model of branched chain amino acid metabolic pathway developed for the overproduction of mycosubtilin anteiso -C17. Constraint was applied on the overproduction of anteiso -branched chain fatty acid ( anteiso -C15 + anteiso -C17 = ↑) and change predictions were visualized. Modelling language and semantics were first described by Coutte et al. (2015) , and improvements for this work are described in the paragraph 4.4 of the Materials and Methods section. This figure semantic description was extracted from Coutte et al. (2015) for better understanding of this figure. Reaction networks in our modeling language are represented as graphs similar to Petri nets. The concrete syntax of our reaction networks is based on XML, from which the graphs are computed. The XML representation is also the input for the prediction algorithm. These graphs contain two kinds of nodes: round nodes for representing its species and boxed nodes for representing its reactions. More precisely, any species S is represented by a round node and any reaction with name r by a boxed node . Solid edges either link a reactant to its reaction or a reaction to one of its products . There are three kinds of dashed edges, which start at the three kinds of modifiers. An accelerator edge links an accelerator to a reaction , an activator edge links an activator to a reaction , and an inhibitor edge links an inhibitor to a reaction . An input edge points from the context to an inflow species S , while an outflow edge points from an outflow species S to the context. For convenience, we introduced the last kind of edges as a shortcut for a product that is degraded by a hidden reaction, i.e., as a shortcut for . Species nodes with three different colors were used, which indicate their biological roles. Yellow indicates metabolites (such as ) and blue indicates proteins (such as ). There is a third color for “artificial species” that serves to modulate regulation, such as the promoter of the ilv-leu operon . Reactions that are potential candidates for knockouts or overexpression will be annotated in orange. Dark orange indicates candidates that were selected by our knockout prediction, while light orange indicates candidates that were not. Genes knockout predictions are represented by ⇓ and gene overexpression by ↑.

    Journal: Metabolites

    Article Title: Bioinformatics Modelling and Metabolic Engineering of the Branched Chain Amino Acid Pathway for Specific Production of Mycosubtilin Isoforms in Bacillus subtilis

    doi: 10.3390/metabo12020107

    Figure Lengend Snippet: New improved model of branched chain amino acid metabolic pathway developed for the overproduction of mycosubtilin anteiso -C17. Constraint was applied on the overproduction of anteiso -branched chain fatty acid ( anteiso -C15 + anteiso -C17 = ↑) and change predictions were visualized. Modelling language and semantics were first described by Coutte et al. (2015) , and improvements for this work are described in the paragraph 4.4 of the Materials and Methods section. This figure semantic description was extracted from Coutte et al. (2015) for better understanding of this figure. Reaction networks in our modeling language are represented as graphs similar to Petri nets. The concrete syntax of our reaction networks is based on XML, from which the graphs are computed. The XML representation is also the input for the prediction algorithm. These graphs contain two kinds of nodes: round nodes for representing its species and boxed nodes for representing its reactions. More precisely, any species S is represented by a round node and any reaction with name r by a boxed node . Solid edges either link a reactant to its reaction or a reaction to one of its products . There are three kinds of dashed edges, which start at the three kinds of modifiers. An accelerator edge links an accelerator to a reaction , an activator edge links an activator to a reaction , and an inhibitor edge links an inhibitor to a reaction . An input edge points from the context to an inflow species S , while an outflow edge points from an outflow species S to the context. For convenience, we introduced the last kind of edges as a shortcut for a product that is degraded by a hidden reaction, i.e., as a shortcut for . Species nodes with three different colors were used, which indicate their biological roles. Yellow indicates metabolites (such as ) and blue indicates proteins (such as ). There is a third color for “artificial species” that serves to modulate regulation, such as the promoter of the ilv-leu operon . Reactions that are potential candidates for knockouts or overexpression will be annotated in orange. Dark orange indicates candidates that were selected by our knockout prediction, while light orange indicates candidates that were not. Genes knockout predictions are represented by ⇓ and gene overexpression by ↑.

    Article Snippet: The anteiso -C17 mycosubtilin production increased from 45.1% for ATCC 6633 to 63.6% for BBG133 (IlvA+), whereas the iso -C16 mycosubtilin production increased from 23.6% for ATCC 6633 to 66.1% for BV12I37 (CodY−).

    Techniques: Over Expression, Knock-Out

    Patterns of mycosubtilin isoforms of B. subtilis ATCC 6633 (gray bar), BV12I37 (CodY−; dark blue bar), and BBG133 (IlvA +; light blue bar) after 48 h of growth at 30 °C in the modified Landy medium. Results are mean values and standard deviations of two independent experiments.

    Journal: Metabolites

    Article Title: Bioinformatics Modelling and Metabolic Engineering of the Branched Chain Amino Acid Pathway for Specific Production of Mycosubtilin Isoforms in Bacillus subtilis

    doi: 10.3390/metabo12020107

    Figure Lengend Snippet: Patterns of mycosubtilin isoforms of B. subtilis ATCC 6633 (gray bar), BV12I37 (CodY−; dark blue bar), and BBG133 (IlvA +; light blue bar) after 48 h of growth at 30 °C in the modified Landy medium. Results are mean values and standard deviations of two independent experiments.

    Article Snippet: The anteiso -C17 mycosubtilin production increased from 45.1% for ATCC 6633 to 63.6% for BBG133 (IlvA+), whereas the iso -C16 mycosubtilin production increased from 23.6% for ATCC 6633 to 66.1% for BV12I37 (CodY−).

    Techniques: Modification