The production of preconditioned freeze-dried Oenococcus oeni primes its metabolism to withstand environmental stresses encountered upon inoculation into wine

International audienceOenococcus oeni is the most resistant lactic acid bacteria species to the environmental stresses encountered in wine, particularly the acidity, presence of ethanol and phenolic compounds. Indigenous strains develop spontaneously following the yeast-driven alcoholic fermentation and may perform the malolactic fermentation whereby improving taste, aroma, and the microbial stability of wine. However, spontaneous fermentation is sometimes delayed, prolonged or incomplete. In order to better control its timing and quality, O. oeni strains are selected and developed to be used as malolactic starters. They are prepared under proprietary manufacturing processes to survive direct inoculation and are predominantly provided as freeze-dried preparations. In this study, we have investigated the physiological and molecular alterations occurring in O. oeni cells prepared by an industrial process that consists of preconditioning protocols and freeze-drying, and compared them to the same strain grown in a grape juice medium. We found that compared to cultured cells, the industrial production process improved survival under extreme conditions, i. e. at low pH or high tannin concentrations. In contrast, cultured cells resumed active growth more quickly and strongly than freeze-dried preparations in standard pH wines. A proteomic analysis showed that during the industrial production most non-essential metabolic processes are shut down and components of the general and the stringent stress response are upregulated. The presence of major components of the stress response facilitates protein homeostasis and physiological changes that further ensure the integrity of cells

Digging into the low molecular weight peptidome with the OligoNet web server

Abstract Bioactive peptides play critical roles in regulating many biological processes. Recently, natural short peptides biomarkers are drawing significant attention and are considered as “hidden treasure” of drug candidates. High resolution and high mass accuracy provided by mass spectrometry (MS)-based untargeted metabolomics would enable the rapid detection and wide coverage of the low-molecular-weight peptidome. However, translating unknown masses (<1 500 Da) into putative peptides is often limited due to the lack of automatic data processing tools and to the limit of peptide databases. The web server OligoNet responds to this challenge by attempting to decompose each individual mass into a combination of amino acids out of metabolomics datasets. It provides an additional network-based data interpretation named “Peptide degradation network” (PDN), which unravels interesting relations between annotated peptides and generates potential functional patterns. The ab initio PDN built from yeast metabolic profiling data shows a great similarity with well-known metabolic networks, and could aid biological interpretation. OligoNet allows also an easy evaluation and interpretation of annotated peptides in systems biology, and is freely accessible at https://daniellyz200608105.shinyapps.io/OligoNet/

New molecular evidence of wine yeast-bacteria interaction unraveled by non-targeted exometabolomic profiling

International audienceIntroduction Bacterial malolactic fermentation (MLF) has a considerable impact on wine quality. The yeast strain used for primary fermentation can systematically stimulate (MLF+ phenotype) or inhibit (MLF-) bacteria and the MLF process as a function of numerous winemaking practices, but the underlying molecular evidence still remains a mystery.Objectives The goal of the study was to elucidate such evidence by the direct comparison of extracellular metabolic profiles of MLF? and MLF-phenotypes.Methods We have applied a non-targeted metabolomic approach combining ultrahigh-resolution FT-ICR-MS analysis, powerful statistical tools and a comprehensive wine metabolite database.Results We discovered around 2500 unknown masses and 800 putative biomarkers involved in phenotypic distinction. For the putative biomarkers, we also developed a biomarker identification workflow and elucidated the exact structure (by UPLC-Q-ToF-MS2) and/or exact physiological impact (by in vitro tests) of several novel biomarkers, such as D-gluconic acid, citric acid, trehalose and tripeptide Pro-Phe-Val. In addition to valid biomarkers, molecular evidence was reflected by unprecedented chemical diversity (around 3000 discriminant masses) that characterized both the yeast phenotypes. While distinct chemical families such as phenolic compounds, carbohydrates, amino acids and peptides characterize the extracellular metabolic profiles of the MLF? phenotype, the MLF-phenotype is associated with sulphur-containing peptides.Conclusion The non-targeted approach used in this study played an important role in finding new and unexpected molecular evidence