Hydrogen sulfide production during early yeast fermentation correlates with volatile sulfur compound biogenesis but not thiol release.

Yeasts undergo intensive metabolic changes during the early stages of fermentation. Previous reports suggest the early production of hydrogen sulfide (H2S) is associated with the release of a range of volatile sulfur compounds (VSCs), as well as the production of varietal thiol compounds 3-sulfanylhexan-1-ol (3SH) and 3-sulfanylhexyl acetate (3SHA) from six-carbon precursors, including (E)-hex-2-enal. In this study, we investigated the early H2S potential, VSCs/thiol output, and precursor metabolism of 11 commonly used laboratory and commercial Saccharomyces cerevisiae strains in chemically defined synthetic grape medium (SGM) within 12 h after inoculation. Considerable variability in early H2S potential was observed among the strains surveyed. Chemical profiling suggested that early H2S production correlates with the production of dimethyl disulfide, 2-mercaptoethanol, and diethyl sulfide, but not with 3SH or 3SHA. All strains were capable of metabolizing (E)-hex-2-enal, while the F15 strain showed significantly higher residue at 12 h. Early production of 3SH, but not 3SHA, can be detected in the presence of exogenous (E)-hex-2-enal and H2S. Therefore, the natural variability of early yeast H2S production contributes to the early output of selected VSCs, but the threshold of which is likely not high enough to contribute substantially to free varietal thiols in SGM.

Application of untargeted volatile profiling to investigate the fate of aroma compounds during wine oral processing.

We employed an untargeted volatile profiling approach in combination with spit off-odorant measurement procedure to investigate the fate of aroma compounds in mouth by determining how oral processing and intrinsic biological variables influence the overall volatile composition. A red wine before and after oral processing (expectorated wine), and control samples (expectorated water) were analyzed using GC-TOF-MS to determine as many volatile compounds as possible. We identified compounds in expectorated wines that originated in mouth from either an endogenous or exogenous source, while confirming that compounds might have metabolized by the action of salivary enzymes. Our data also show the changes in volatiles via hydrolysis from the corresponding molecules and may provide evidence of de novo formation of volatiles via transesterification reaction in mouth. While investigating the impact of intrinsic biological variables, we found age and gender specific differences in wine volatile composition due to oral processing and identified the key volatiles.

Application of untargeted volatile profiling and data driven approaches in wine flavoromics research.

Traditional flavor chemistry research usually makes use of targeted approaches by focusing on the detection and quantification of key flavor active metabolites that are present in food and beverages. In the last decade, flavoromics has emerged as an alternative to targeted methods where non-targeted and data driven approaches have been used to determine as many metabolites as possible with the aim to establish relationships among the chemical composition of foods and their sensory properties. Flavoromics has been successfully applied in wine research to gain more insights into the impact of a wide range of flavor active metabolites on wine quality. In this review, we aim to provide an overview of the applications of flavoromics approaches in wine research based on existing literature mainly by focusing on untargeted volatile profiling of wines and how this can be used as a powerful tool to generate novel insights. We highlight the fact that untargeted volatile profiling used in flavoromics approaches ultimately can assist the wine industry to produce different wine styles and to market existing wines appropriately based on consumer preference. In addition to summarizing the main steps involved in untargeted volatile profiling, we also provide an outlook about future perspectives and challenges of wine flavoromics research.

Mass Spectrometry-Based Metabolomics to Investigate the Effect of Mechanical Shaking on Sauvignon Blanc Berry Metabolism.

Previous commercial studies carried out in New Zealand showed that mechanical shaking significantly reduced the incidence of Botrytis cinerea infection in wine grapes. However, the reasons behind this reduction are not well understood. Here, we employed a metabolomics approach to gain insights into the biochemical changes that occur in grape berries due to mechanical shaking. Berry samples were analyzed using three different analytical approaches including gas chromatography and mass spectrometry (MS), liquid chromatography and MS, and imaging mass spectrometry (IMS). Combined data provided a comprehensive overview of metabolic changes in grape berry, indicating the initiation of different stress mitigation strategies to overcome the effect of mechanical shaking. Berry primary metabolism was distinctly altered in the green berries in response to mechanical shaking, while secondary metabolism significantly changed in berries collected after veraison. Pathway analysis showed upregulation of metabolites related to nitrogen and lipid metabolism in the berries from shaken vines when compared with controls. From IMS data, we observed an accumulation of different groups of metabolites including phenolic compounds and amino and fatty acids in the areas near to the skin of berries from shaken vines. This observation suggests that mechanical shaking caused an accumulation of these metabolites, which may be associated with the formation of a protective barrier, leading to the reduction in B. cinerea infection in berries from mechanically shaken vines.

Translational Metabolomics: Current Challenges and Future Opportunities.

Metabolomics is one of the latest omics technologies that has been applied successfully in many areas of life sciences. Despite being relatively new, a plethora of publications over the years have exploited the opportunities provided through this data and question driven approach. Most importantly, metabolomics studies have produced great breakthroughs in biomarker discovery, identification of novel metabolites and more detailed characterisation of biological pathways in many organisms. However, translation of the research outcomes into clinical tests and user-friendly interfaces has been hindered due to many factors, some of which have been outlined hereafter. This position paper is the summary of discussion on translational metabolomics undertaken during a peer session of the Australian and New Zealand Metabolomics Conference (ANZMET 2018) held in Auckland, New Zealand. Here, we discuss some of the key areas in translational metabolomics including existing challenges and suggested solutions, as well as how to expand the clinical and industrial application of metabolomics. In addition, we share our perspective on how full translational capability of metabolomics research can be explored.

Pre-fermentative supplementation of fatty acids alters the metabolic activity of wine yeasts.

Fatty acids play important roles in the maintenance of cell membrane, viability and overall metabolism of wine yeasts (particularly Saccharomyces cerevisiae) during adverse winemaking conditions. We previously showed that linoleic acid supplementation markedly affect aroma compound production of S. cerevisiae wine strains. However, very little is known about how other commonly found fatty acids in grape juice modulate the growth and metabolism of S. cerevisiae. We aimed to determine the individual effect of five fatty acids on fermentation patterns and metabolism of two wine yeast strains (S. cerevisiae EC1118 and X5). Microvinification was performed at 15 °C by supplementing a grape juice (individually) with three different concentrations of saturated (palmitic acid), unsaturated (oleic, linoleic and γ-linolenic acids) and short-chain (hexanoic acid) fatty acids. Metabolite profiles of the resulting wines were determined using Gas-chromatography coupled to Mass-spectrometry (GC-MS). Our data show that the addition of γ-linolenic acid to the juice caused the production of higher amounts of amino and organic acids (except isoleucine and 2-oxoglutaric acid) in wines when fermented by EC1118, while palmitic acid supplementation showed similar trends when fermented by X5. The effect of linoleic acid was independent of yeast strains and we observed a global reduction of amino and organic acids (except pyruvic acid) while increased production of most of the fatty acids other than the supplemented ones. Our data clearly suggest that pre-fermentative supplementation of different fatty acids indeed influenced the growth and metabolism of wine yeasts in a different way. Thus, attention needs to be paid not only to the wine yeast strain used during the winemaking but also to the overall grape juice composition, including fatty acids, to obtain the desired wine characteristics.

Systems Biology and Multi-Omics Integration: Viewpoints from the Metabolomics Research Community.

The use of multiple omics techniques (i.e., genomics, transcriptomics, proteomics, and metabolomics) is becoming increasingly popular in all facets of life science. Omics techniques provide a more holistic molecular perspective of studied biological systems compared to traditional approaches. However, due to their inherent data differences, integrating multiple omics platforms remains an ongoing challenge for many researchers. As metabolites represent the downstream products of multiple interactions between genes, transcripts, and proteins, metabolomics, the tools and approaches routinely used in this field could assist with the integration of these complex multi-omics data sets. The question is, how? Here we provide some answers (in terms of methods, software tools and databases) along with a variety of recommendations and a list of continuing challenges as identified during a peer session on multi-omics integration that was held at the recent 'Australian and New Zealand Metabolomics Conference' (ANZMET 2018) in Auckland, New Zealand (Sept. 2018). We envisage that this document will serve as a guide to metabolomics researchers and other members of the community wishing to perform multi-omics studies. We also believe that these ideas may allow the full promise of integrated multi-omics research and, ultimately, of systems biology to be realized.

Juice Index: an integrated Sauvignon blanc grape and wine metabolomics database shows mainly seasonal differences.

INTRODUCTION: Although Sauvignon Blanc (SB) grapes are cultivated widely throughout New Zealand, wines from the Marlborough region are most famous for their typical varietal combination of tropical and vegetal aromas. These wines differ in composition from season to season as well as among locations within the region, which makes the continual production of good quality wines challenging. Here, we developed a unique database of New Zealand SB grape juices and wines to develop tools to help winemakers to make blending decisions and assist in the development of new wine styles. METHODS: About 400 juices were collected from different regions in New Zealand over three harvest seasons (2011-2013), which were then fermented under controlled conditions using a commercial yeast strain Saccharomyces cerevisiae EC1118. Comprehensive metabolite profiling of these juices and wines by gas chromatography-mass spectrometry (GC-MS) was combined with their detailed oenological parameters and associated meteorological data. RESULTS: These combined metabolomics data clearly demonstrate that seasonal variation is more prominent than regional difference in both SB grape juices and wines, despite almost universal use of vineyard irrigation to mitigate seasonal rainfall and evapotranspiration differences, Additionally, we identified a group of juice metabolites that play central roles behind these variations, which may represent chemical signatures for juice and wine quality assessment. CONCLUSION: This database is the first of its kind in the world to be available for the wider scientific community and offers potential as a predictive tool for wine quality and innovation when combined with mathematical modelling.

Metabolite secretion in microorganisms: the theory of metabolic overflow put to the test.

INTRODUCTION: Microbial cells secrete many metabolites during growth, including important intermediates of the central carbon metabolism. This has not been taken into account by researchers when modeling microbial metabolism for metabolic engineering and systems biology studies. MATERIALS AND METHODS: The uptake of metabolites by microorganisms is well studied, but our knowledge of how and why they secrete different intracellular compounds is poor. The secretion of metabolites by microbial cells has traditionally been regarded as a consequence of intracellular metabolic overflow. CONCLUSIONS: Here, we provide evidence based on time-series metabolomics data that microbial cells eliminate some metabolites in response to environmental cues, independent of metabolic overflow. Moreover, we review the different mechanisms of metabolite secretion and explore how this knowledge can benefit metabolic modeling and engineering.

The fate of linoleic acid on Saccharomyces cerevisiae metabolism under aerobic and anaerobic conditions.

INTRODUCTION: Saccharomyces cerevisiae has been widely used for fermenting food and beverages for over thousands years. Its metabolism together with the substrate composition play an important role in determining the characteristics of the final fermented products. We previously showed that the polyunsaturated fatty acid, linoleic acid, which is present in the grape juice at trace levels, significantly affected the development of aroma compounds of the wines. However, the effect of linoleic acid on the overall cell metabolism of S. cerevisiae is still not clear. Therefore, we aimed to unlock the metabolic response of S. cerevisiae to linoleic acid using metabolomics and isotope labelling experiments. METHODS: We cultured the cells on a minimal mineral medium supplementing them with linoleic acid isomers and 13C-linoleic acid. Both intracellular and extracellular metabolite profiles were determined using gas chromatography coupled to mass spectrometry (GC-MS) to investigate which S. cerevisiae pathways were affected by linoleic acid supplementation. RESULTS: The utilisation of linoleic acid by S. cerevisiae had a significant impact on the primary carbon metabolism increasing the glucose consumption and the ethanol production under anaerobic condition. The energetic state of the cell was, therefore, affected and the glycolytic pathway, the TCA cycle and the amino acid production were up-regulated. We also observed that linoleic acid was transported into the cell and converted into other fatty acids affecting their profile even under anaerobic condition. CONCLUSION: Our data clearly shows that linoleic acid supplementation in growth medium increased glucose consumption and ethanol production by S. cerevisiae under anaerobic condition. We also suggest that S. cerevisiae might be able to perform an alternative anaerobic pathway to ß-oxidation, which has not been reported yet.

Review of recent developments in GC-MS approaches to metabolomics-based research.

BACKGROUND: Metabolomics aims to identify the changes in endogenous metabolites of biological systems in response to intrinsic and extrinsic factors. This is accomplished through untargeted, semi-targeted and targeted based approaches. Untargeted and semi-targeted methods are typically applied in hypothesis-generating investigations (aimed at measuring as many metabolites as possible), while targeted approaches analyze a relatively smaller subset of biochemically important and relevant metabolites. Regardless of approach, it is well recognized amongst the metabolomics community that gas chromatography-mass spectrometry (GC-MS) is one of the most efficient, reproducible and well used analytical platforms for metabolomics research. This is due to the robust, reproducible and selective nature of the technique, as well as the large number of well-established libraries of both commercial and 'in house' metabolite databases available. AIM OF REVIEW: This review provides an overview of developments in GC-MS based metabolomics applications, with a focus on sample preparation and preservation techniques. A number of chemical derivatization (in-time, in-liner, offline and microwave assisted) techniques are also discussed. Electron impact ionization and a summary of alternate mass analyzers are highlighted, along with a number of recently reported new GC columns suited for metabolomics. Lastly, multidimensional GC-MS and its application in environmental and biomedical research is presented, along with the importance of bioinformatics. KEY SCIENTIFIC CONCEPTS OF REVIEW: The purpose of this review is to both highlight and provide an update on GC-MS analytical techniques that are common in metabolomics studies. Specific emphasis is given to the key steps within the GC-MS workflow that those new to this field need to be aware of and the common pitfalls that should be looked out for when starting in this area.

Analysis of Intracellular Metabolites from Microorganisms: Quenching and Extraction Protocols.

Sample preparation is one of the most important steps in metabolome analysis. The challenges of determining microbial metabolome have been well discussed within the research community and many improvements have already been achieved in last decade. The analysis of intracellular metabolites is particularly challenging. Environmental perturbations may considerably affect microbial metabolism, which results in intracellular metabolites being rapidly degraded or metabolized by enzymatic reactions. Therefore, quenching or the complete stop of cell metabolism is a pre-requisite for accurate intracellular metabolite analysis. After quenching, metabolites need to be extracted from the intracellular compartment. The choice of the most suitable metabolite extraction method/s is another crucial step. The literature indicates that specific classes of metabolites are better extracted by different extraction protocols. In this review, we discuss the technical aspects and advancements of quenching and extraction of intracellular metabolite analysis from microbial cells.

Rapid Quantification of Major Volatile Metabolites in Fermented Food and Beverages Using Gas Chromatography-Mass Spectrometry.

Here we present a method for the accurate quantification of major volatile metabolites found in different food and beverages, including ethanol, acetic acid and other aroma compounds, using gas chromatography coupled to mass spectrometry (GC-MS). The method is combined with a simple sample preparation procedure using sodium chloride and anhydrous ethyl acetate. The GC-MS analysis was accomplished within 4.75 min, and over 80 features were detected, of which 40 were positively identified using an in-house and a commercialmass spectrometry (MS) library. We determined different analytical parameters of these metabolites including the limit of detection (LOD), limit of quantitation (LOQ) and range of quantification. In order to validate the method, we also determined detailed analytical characteristics of five major fermentation end products including ethanol, acetic acid, isoamyl alcohol, ethyl-L-lactate and, acetoin. The method showed very low technical variability for the measurements of these metabolites in different matrices (<3%) with an excellent accuracy (100% ± 5%), recovery (100% ± 10%), reproducibility and repeatability [Coefficient of variation (CV) 1-10%)]. To demonstrate the applicability of the method, we analysed different fermented products including balsamic vinegars, sourdough, distilled (whisky) and non-distilled beverages (wine and beer).

Extracellular Microbial Metabolomics: The State of the Art.

Microorganisms produce and secrete many primary and secondary metabolites to the surrounding environment during their growth. Therefore, extracellular metabolites provide important information about the changes in microbial metabolism due to different environmental cues. The determination of these metabolites is also comparatively easier than the extraction and analysis of intracellular metabolites as there is no need for cell rupture. Many analytical methods are already available and have been used for the analysis of extracellular metabolites from microorganisms over the last two decades. Here, we review the applications and benefits of extracellular metabolite analysis. We also discuss different sample preparation protocols available in the literature for both types (e.g., metabolites in solution and in gas) of extracellular microbial metabolites. Lastly, we evaluate the authenticity of using extracellular metabolomics data in the metabolic modelling of different industrially important microorganisms.

Fully Automated Trimethylsilyl (TMS) Derivatisation Protocol for Metabolite Profiling by GC-MS.

Gas Chromatography-Mass Spectrometry (GC-MS) has long been used for metabolite profiling of a wide range of biological samples. Many derivatisation protocols are already available and among these, trimethylsilyl (TMS) derivatisation is one of the most widely used in metabolomics. However, most TMS methods rely on off-line derivatisation prior to GC-MS analysis. In the case of manual off-line TMS derivatisation, the derivative created is unstable, so reduction in recoveries occurs over time. Thus, derivatisation is carried out in small batches. Here, we present a fully automated TMS derivatisation protocol using robotic autosamplers and we also evaluate a commercial software, Maestro available from Gerstel GmbH. Because of automation, there was no waiting time of derivatised samples on the autosamplers, thus reducing degradation of unstable metabolites. Moreover, this method allowed us to overlap samples and improved throughputs. We compared data obtained from both manual and automated TMS methods performed on three different matrices, including standard mix, wine, and plasma samples. The automated TMS method showed better reproducibility and higher peak intensity for most of the identified metabolites than the manual derivatisation method. We also validated the automated method using 114 quality control plasma samples. Additionally, we showed that this online method was highly reproducible for most of the metabolites detected and identified (RSD < 20) and specifically achieved excellent results for sugars, sugar alcohols, and some organic acids. To the very best of our knowledge, this is the first time that the automated TMS method has been applied to analyse a large number of complex plasma samples. Furthermore, we found that this method was highly applicable for routine metabolite profiling (both targeted and untargeted) in any metabolomics laboratory.

Vinegar Metabolomics: An Explorative Study of Commercial Balsamic Vinegars Using Gas Chromatography-Mass Spectrometry.

Balsamic vinegar is a popular food condiment produced from cooked grape must by two successive fermentation (anaerobic and aerobic) processes. Although many studies have been performed to determine the composition of major metabolites, including sugars and aroma compounds, no study has been undertaken yet to characterize the comprehensive metabolite composition of balsamic vinegars. Here, we present the first metabolomics study of commercial balsamic vinegars by gas chromatography coupled to mass spectrometry (GC-MS). The combination of three GC-MS methods allowed us to detect >1500 features in vinegar samples, of which 123 metabolites were accurately identified, including 25 amino acids, 26 carboxylic acids, 13 sugars and sugar alcohols, four fatty acids, one vitamin, one tripeptide and over 47 aroma compounds. Moreover, we identified for the first time in vinegar five volatile metabolites: acetin, 2-methylpyrazine, 2-acetyl-1-pyroline, 4-anisidine and 1,3-diacetoxypropane. Therefore, we demonstrated the capability of metabolomics for detecting and identifying large number of metabolites and some of them could be used to distinguish vinegar samples based on their origin and potentially quality.

The effect of linoleic acid on the Sauvignon blanc fermentation by different wine yeast strains.

The level of linoleic acid in the Sauvignon blanc (SB) grape juice affects the development of different aroma compounds during fermentation by Saccharomyces cerevisiae EC1118, including key varietal thiols such as 3-mercaptohexanol (3MH) and 3-mercaptohexyl acetate (3MHA). However, it is still unknown if linoleic acid would affect in a similar way other commonly used S. cerevisiae wine strains. Here we investigated the effect of grape juice linoleic acid on the development of aroma compounds and other metabolites of SB wines using different wine yeast strains: EC1118, AWRI796 and VIN13. Linoleic acid clearly affected the levels of acetylated aroma compounds, several amino acids, and antioxidant molecules, independent of yeast strain, but the production of 3MH was affected by linoleic acid in a strain-specific manner. Moreover, the supplementation of deuterium-labelled 3MH also affected the production of varietal thiols in a strain-specific way. Linoleic acid reduced the acetylation process probably by inhibiting an acetyltransferase, an effect that was independent of the yeast strain. However, regulation of the 3MH biosynthesis is strain-specific, which suggests a mindful consideration not only towards the wine yeast but also to the linoleic acid concentration in the grape juice in order to obtain the desired wine aroma characteristics.

Can we predict the intracellular metabolic state of a cell based on extracellular metabolite data?

The analysis of extracellular metabolites presents many technical advantages over the analysis of intracellular compounds, which made this approach very popular in recent years as a high-throughput tool to assess the metabolic state of microbial cells. However, very little effort has been made to determine the actual relationship between intracellular and extracellular metabolite levels. The secretion of intracellular metabolites has been traditionally interpreted as a consequence of an intracellular metabolic overflow, which is based on the premise that for a metabolite to be secreted, it must be over-produced inside the cell. Therefore, we expect to find a secreted metabolite at increased levels inside the cells. Here we present a time-series metabolomics study of Saccharomyces cerevisiae growing on a glucose-limited chemostat with parallel measurements of intra- and extracellular metabolites. Although most of the extracellular metabolites were also detected in the intracellular samples and showed a typical metabolic overflow behaviour, we demonstrate that the secretion of many metabolites could not be explained by the metabolic overflow theory.

Nitrogen and carbon assimilation by Saccharomyces cerevisiae during Sauvignon blanc juice fermentation.

To investigate the assimilation and production of juice metabolites by Saccharomyces cerevisiae during winemaking, we compared the metabolite profiles of 63 Sauvignon blanc (SB) grape juices collected over five harvesting seasons from different locations of New Zealand before and after fermentation by the commercial wine yeast strain EC1118 at 15 °C. Metabolite profiles were obtained using gas chromatography-mass spectrometry and nuclear magnetic resonance and the oenological parameters were determined by Fourier transform infrared spectroscopy. Our results revealed that the amino acids threonine and serine were the most consumed organic nitrogen sources, while proline and gamma-aminobutyric acid were the least consumed amino acids during SB juice fermentation. Saccharomyces cerevisiae metabolised some uncommon nitrogen sources (e.g. norleucine, norvaline and pyroglutamic acid) and several organic acids, including some fatty acids, most likely after fermenting the main juice sugars (glucose, fructose and mannose). However, consumption showed large variation between juices and in some cases between seasons. Our study clearly shows that preferred nitrogen and carbon sources were consumed by S. cerevisiae EC1118 independent of the juice fine composition, whilst the consumption of other nutrient sources mainly depended on the concentration of other juice metabolites, which explains the uniqueness of each barrel of wine.