Conversion of Arginine to Ornithine during Malo-Lactic Fermentation in Red Swiss Wine

Kuensch, U.; Temperli, A.; Mayer, K

doi:10.5344/ajev.1974.25.4.191

“…Moreover, PanGEM predicted GABA production, which is one of the targeted metabolites for overproduction during kimchi fermentation ( 57 ). Also, red wine isolates, consisting of 21 Oenococcus onei strains and 1 L. plantarum strain , were predicted as producers of malate ( 58 ), pyridoxine ( 59 ), and ornithine ( 60 , 61 ). The kefir isolates comprised 15 strains from five species, with FVA predicting the production of 40 metabolites, including ethanol ( 62 ), succinate ( 63 ), acetoin ( 64 ), and lactic acid ( 64 ).…”

Section: Discussionmentioning

confidence: 99%

Pangenome reconstruction of Lactobacillaceae metabolism predicts species-specific metabolic traits

Ardalani,

Phaneuf,

Mohite

et al. 2024

mSystems

0

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Strains across the Lactobacillaceae family form the basis for a trillion-dollar industry. Our understanding of the genomic basis for their key traits is fragmented, however, including the metabolism that is foundational to their industrial uses. Pangenome analysis of publicly available Lactobacillaceae genomes allowed us to generate genome-scale metabolic network reconstructions for 26 species of industrial importance. Their manual curation led to more than 75,000 gene-protein-reaction associations that were deployed to generate 2,446 genome-scale metabolic models. Cross-referencing genomes and known metabolic traits allowed for manual metabolic network curation and validation of the metabolic models. As a result, we provide the first pangenomic basis for metabolism in the Lactobacillaceae family and a collection of predictive computational metabolic models that enable a variety of practical uses. IMPORTANCE Lactobacillaceae , a bacterial family foundational to a trillion-dollar industry, is increasingly relevant to biosustainability initiatives. Our study, leveraging approximately 2,400 genome sequences, provides a pangenomic analysis of Lactobacillaceae metabolism, creating over 2,400 curated and validated genome-scale models (GEMs). These GEMs successfully predict (i) unique, species-specific metabolic reactions; (ii) niche-enriched reactions that increase organism fitness; (iii) essential media components, offering insights into the global amino acid essentiality of Lactobacillaceae ; and (iv) fermentation capabilities across the family, shedding light on the metabolic basis of Lactobacillaceae -based commercial products. This quantitative understanding of Lactobacillaceae metabolic properties and their genomic basis will have profound implications for the food industry and biosustainability, offering new insights and tools for strain selection and manipulation.

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“…Moreover, PanGEM predicted GABA production, which is one of the targeted metabolites for overproduction during Kimchi fermentation(50). Also, red wine isolates, consisting of 15 Oenococcus onei strains, were predicted as producers of malate (51), pyridoxine (52), and ornithine (53,54). The Kefir isolates comprised 14 strains from various species, with FBA predicting the production of 13 metabolites, including ethanol (55), succinate (56), acetoin (57), and lactic acid (57).…”

Section: Discussionmentioning

confidence: 99%

Pangenome reconstruction ofLactobacillaceaemetabolism predicts species-specific metabolic traits

Ardalani,

Phaneuf,

Mohite

et al. 2023

Preprint

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Strains across the Lactobacillaceae family form the basis for a trillion-dollar industry. Our understanding of the genomic basis for their key traits is fragmented, however, including the metabolism that is foundational to their industrial uses. Pangenome analysis of publicly available Lactobacillaceae genomes allowed us to generate genome-scale metabolic network reconstructions for 26 species of industrial importance. Their manual curation led to more than 75,000 gene-protein-reaction associations that were deployed to generate 2,446 genome-scale metabolic models. Cross-referencing genomes and known metabolic traits allowed for manual metabolic network curation and validation of the metabolic models. As a result, we provide the first pangenomic basis for metabolism in the Lactobacillaceae family and a collection of predictive computational metabolic models that enable a variety of practical uses.

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HRGC of wine free amino acids as a tool for elementary wine characterization

Vasconcelos¹,

Neves²

1990

J. High Resol. Chromatogr.

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SummaryIn this paper we show that wine free amino acids derivatized as isopropyl N-heptafluorobutyryl esters can be used as a tool for wine characterization. Elementary wines of eight Vitis vinifera varieties were studied during a seven year period.The characteristic wine amino acids for each variety were assessed by means of pattern recognition techniques. A "star symbol plot" was used for graphic representation.

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Conversion of Arginine to Ornithine during Malo-Lactic Fermentation in Red Swiss Wine

Cited by 26 publications

References 0 publications

Pangenome reconstruction of Lactobacillaceae metabolism predicts species-specific metabolic traits

Pangenome reconstruction of Lactobacillaceae metabolism predicts species-specific metabolic traits

Pangenome reconstruction ofLactobacillaceaemetabolism predicts species-specific metabolic traits

HRGC of wine free amino acids as a tool for elementary wine characterization

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