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Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.

Vinay-Lara E, Hamilton JJ, Stahl B, Broadbent JR, Reed JL, Steele JL - PLoS ONE (2014)

Bottom Line: After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors.We conclude that the metabolic capabilities of the two networks are highly similar.The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes.

View Article: PubMed Central - PubMed

Affiliation: Department of Food Science, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.

ABSTRACT
Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.

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Related in: MedlinePlus

Metabolic map of carbohydrate metabolism of L. casei 12A and ATCC 334.Glycolytic metabolites are listed in bold.
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pone-0110785-g002: Metabolic map of carbohydrate metabolism of L. casei 12A and ATCC 334.Glycolytic metabolites are listed in bold.

Mentions: Carbohydrate utilization plays a key role in the ecology and industrial utility of L. casei; therefore it was important to ensure the models were in agreement with the in vivo carbohydrate utilization data. The draft metabolic models of ATCC 334 and 12A were tested against data for utilization of 56 carbohydrates, where the utilization of these carbon sources by ATCC 334 and 12A strains has been reported previously [5]. Both strains were unable to utilize 25 carbohydrates, including β-cyclodextrin, γ-cyclodextrin, amylopectin, amylase, arabinogalactan, carboxymethyl cellulose, D-ribitol, D-arabinose, D-arabitol, dextrin, D-maltitol, D-xylitol, D-xylose, fucose, galacturonic acid, glucuronic acid, heparin, lignin, meso-erythritol, mucin, phytic acid, rhamnose, sialic acid, stachyose, xylan and α-cyclodextrin. For all 25 of these un-usable carbohydrates, the drafts models accurately predicted no growth. The 31 carbohydrates that at least one of the strains could utilize in vivo are presented in Table 4. The draft models did not perform as well in predicting use of carbohydrates where growth was observed in vivo. The poorer performance of the drafts models was mostly due to missing transporters, likely caused by limitations in carbohydrate transporter annotation, causing these transporters to be missed from draft reconstructions. A total of 7 enzymes and 14 transporters were added to the L. casei ATCC 334 model and 7 enzymes and 17 transporters were added to the L. casei 12A model to fix false negative predictions (Table S8). For the carbohydrate amygdalin-6P, we were unable to identify a route with genomic evidence to degrade its by-product, mandelonitrile; we introduced a sink reaction to consume this metabolite. A metabolic map of carbohydrate metabolism is presented in Figure 2; this metabolic map indicates how some relevant carbon sources are transported into the cytoplasm and how they are integrated into glycolysis.


Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.

Vinay-Lara E, Hamilton JJ, Stahl B, Broadbent JR, Reed JL, Steele JL - PLoS ONE (2014)

Metabolic map of carbohydrate metabolism of L. casei 12A and ATCC 334.Glycolytic metabolites are listed in bold.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4231531&req=5

pone-0110785-g002: Metabolic map of carbohydrate metabolism of L. casei 12A and ATCC 334.Glycolytic metabolites are listed in bold.
Mentions: Carbohydrate utilization plays a key role in the ecology and industrial utility of L. casei; therefore it was important to ensure the models were in agreement with the in vivo carbohydrate utilization data. The draft metabolic models of ATCC 334 and 12A were tested against data for utilization of 56 carbohydrates, where the utilization of these carbon sources by ATCC 334 and 12A strains has been reported previously [5]. Both strains were unable to utilize 25 carbohydrates, including β-cyclodextrin, γ-cyclodextrin, amylopectin, amylase, arabinogalactan, carboxymethyl cellulose, D-ribitol, D-arabinose, D-arabitol, dextrin, D-maltitol, D-xylitol, D-xylose, fucose, galacturonic acid, glucuronic acid, heparin, lignin, meso-erythritol, mucin, phytic acid, rhamnose, sialic acid, stachyose, xylan and α-cyclodextrin. For all 25 of these un-usable carbohydrates, the drafts models accurately predicted no growth. The 31 carbohydrates that at least one of the strains could utilize in vivo are presented in Table 4. The draft models did not perform as well in predicting use of carbohydrates where growth was observed in vivo. The poorer performance of the drafts models was mostly due to missing transporters, likely caused by limitations in carbohydrate transporter annotation, causing these transporters to be missed from draft reconstructions. A total of 7 enzymes and 14 transporters were added to the L. casei ATCC 334 model and 7 enzymes and 17 transporters were added to the L. casei 12A model to fix false negative predictions (Table S8). For the carbohydrate amygdalin-6P, we were unable to identify a route with genomic evidence to degrade its by-product, mandelonitrile; we introduced a sink reaction to consume this metabolite. A metabolic map of carbohydrate metabolism is presented in Figure 2; this metabolic map indicates how some relevant carbon sources are transported into the cytoplasm and how they are integrated into glycolysis.

Bottom Line: After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors.We conclude that the metabolic capabilities of the two networks are highly similar.The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes.

View Article: PubMed Central - PubMed

Affiliation: Department of Food Science, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.

ABSTRACT
Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.

Show MeSH
Related in: MedlinePlus