Volatile Metabolite Profiles Research Articles

Novel insight into physicochemical and flavor formation in koumiss based on microbial metabolic network

Koumiss, naturally fermented mare’s milk, has a unique flavor that is affected by its resident microflora. In this study, we analyzed time-dependent changes in the microbiota and volatile metabolite profiles of koumiss using high-throughput sequencing and liquid–liquid extraction–gas chromatography–mass spectrometry. The dominant microrganisms in mare milk were Enterobacter and Rhodotorula, which were gradually suppressed, then Lactobacillus and Dekkera became the core microorganisms of koumiss. 17 FAA and 52 volatile organic compounds (VOCs) were identified during koumiss fermentation, including 19 odor active compounds and 15 differential metabolites of VOCs, mainly acids and esters, and their anabolism showed significant positive correlations with Lactobacillus and Dekkera. The microbial metabolic network showed that Lactobacillus and Dekkera were identified as the most important flavor-producing microbiota due to their significantly positive correlation with the formation of 33 and 28 flavor metabolites, respectively. These microorganisms produce enzymes that catalyze a series of metabolic pathways that generate VOCs, including carbohydrate metabolism, amino acid metabolism, and fatty acid biosynthesis. Our findings provide new guidance for the screening and application of flavor-producing microorganisms inkoumiss.

Metabolic Profiling of VOCs Emitted by Bacteria Isolated from Pressure Ulcers and Treated with Different Concentrations of Bio-AgNPs.

Considering the advent of antibiotic resistance, the study of bacterial metabolic behavior stimulated by novel antimicrobial agents becomes a relevant tool to elucidate involved adaptive pathways. Profiling of volatile metabolites was performed to monitor alterations of bacterial metabolism induced by biosynthesized silver nanoparticles (bio-AgNPs). Escherichia coli, Enterococcus faecalis, Klebsiella pneumoniae and Proteus mirabilis were isolated from pressure ulcers, and their cultures were prepared in the presence/absence of bio-AgNPs at 12.5, 25 and 50 µg mL−1. Headspace solid phase microextraction associated to gas chromatography–mass spectrometry was the employed analytical platform. At the lower concentration level, the agent promoted positive modulation of products of fermentation routes and bioactive volatiles, indicating an attempt of bacteria to adapt to an ongoing suppression of cellular respiration. Augmented response of aldehydes and other possible products of lipid oxidative cleavage was noticed for increasing levels of bio-AgNPs. The greatest concentration of agent caused a reduction of 44 to 80% in the variety of compounds found in the control samples. Pathway analysis indicated overall inhibition of amino acids and fatty acids routes. The present assessment may provide a deeper understanding of molecular mechanisms of bio-AgNPs and how the metabolic response of bacteria is untangled.

Metabolic footprint analysis of volatile metabolites to discriminate between different key time points in the fermentation and storage of starter cultures and probiotic Lactobacillus casei Zhang milk

Interest has been growing in the co-fermentation of starter cultures with probiotic bacteria in milk. However, the representative metabolites and metabolic changes at different key time points during milk fermentation and storage in starter cultures and probiotic bacteria are still unclear. In this study, we used gas chromatography/mass spectrometry-based metabolomics to identify volatile metabolites and discriminate between 6 different time points [fermentation initiation (FI), fermentation curd (FC), fermentation termination (FT), storage 1 d (S1d), storage 7 d (S7d), and storage 14 d (S14d)] during the fermentation and storage of starter cultures and Lactobacillus casei Zhang milk. Of the 52 volatile metabolites identified, 15 contributed to discrimination of the 6 time points. Then, using the profile from the different time points, we analyzed pairwise comparisons (FI vs. FC; FC vs. FT; FT vs. S1d; S1d vs. S7d; S7d vs. S14d); these time-lapse comparisons showed metabolic progressions from one fermentation stage to the next. We found representative and exclusive metabolites at specific fermentation and storage time points. The greatest difference in metabolites occurred between FC and FT, and the metabolic profiles between S7d and S14d were most similar. Interestingly, decanoic acid, octanoic acid, and hexanoic acid reached their highest level at storage 14 d, indicating that the post-fermentation storage of fermented milk with L. casei Zhang may add more probiotic functions. This work provides detailed insight into the time-specific profiles of volatile metabolites and their dynamic changes; these data may be used for understanding and eventually predicting metabolic changes in milk fermentation and storage, where probiotic strains may be used.

Noninvasive monitoring of fibre fermentation in healthy volunteers by analyzing breath volatile metabolites: lessons from the FiberTAG intervention study

ABSTRACT The fermentation of dietary fibre (DF) leads to the production of bioactive metabolites, the most volatile ones being excreted in the breath. The aim of this study was to analyze the profile of exhaled breath volatile metabolites (BVM) and gastrointestinal symptoms in healthy volunteers after a single ingestion of maltodextrin (placebo) versus chitin-glucan (CG), an insoluble DF previously shown to be fermented into short-chain fatty acids (SCFA) by the human microbiota in vitro. Maltodextrin (4.5 g at day 0) or CG (4.5 g at day 2) were added to a standardized breakfast in fasting healthy volunteers (n = 15). BVM were measured using selected ion flow tube mass spectrometry (SIFT-MS) throughout the day. A single ingestion of 4.5 g CG did not induce significant gastrointestinal discomfort. Untargeted metabolomics analysis of breath highlighted that 13 MS-fragments (among 408 obtained from ionizations of breath) discriminated CG versus maltodextrin acute intake in the posprandial state. The targeted analysis revealed that CG increased exhaled butyrate and 5 other BVM – including the microbial metabolites 2,3-butanedione and 3-hydroxybutanone – with a peak observed 6 h after CG intake. Correlation analyses with fecal microbiota (Illumina 16S rRNA sequencing) spotlighted Mitsuokella as a potential genus responsible for the presence of butyric acid, triethylamine and 3-hydroxybutanone in the breath. In conclusion, measuring BMV in the breath reveals the microbial signature of the fermentation of DF after a single ingestion. This protocol allows to analyze the time-course of released bioactive metabolites that could be proposed as new biomarkers of DF fermentation, potentially linked to their biological properties. Trial registration: Clinical Trials NCT03494491. Registered 11 April 2018 – Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03494491

Variation Between Three Eragrostis tef Accessions in Defense Responses to Rhopalosiphum padi Aphid Infestation.

Tef (Eragrostis tef), a staple crop that originated in the Horn of Africa, has been introduced to multiple countries over the last several decades. Crop cultivation in new geographic regions raises questions regarding the molecular basis for biotic stress responses. In this study, we aimed to classify the insect abundance on tef crop in Israel, and to elucidate its chemical and physical defense mechanisms in response to insect feeding. To discover the main pests of tef in the Mediterranean climate, we conducted an insect field survey on three selected accessions named RTC-144, RTC-405, and RTC-406, and discovered that the most abundant insect order is Hemiptera. We compared the differences in Rhopalosiphum padi (Hemiptera; Aphididae) aphid performance, preference, and feeding behavior between the three accessions. While the number of aphid progeny was lower on RTC-406 than on the other two, the aphid olfactory assay indicated that the aphids tended to be repelled from the RTC-144 accession. To highlight the variation in defense responses, we investigated the physical and chemical mechanisms. As a physical barrier, the density of non-granular trichomes was evaluated, in which a higher number of trichomes on the RTC-406 than on the other accessions was observed. This was negatively correlated with aphid performance. To determine chemical responses, the volatile and central metabolite profiles were measured upon aphid attack for 4 days. The volatile analysis exposed a rich and dynamic metabolic profile, and the central metabolism profile indicated that tef plants adjust their sugars and organic and amino acid levels. Overall, we found that the tef plants possess similar defense responses as other Poaceae family species, while the non-volatile deterrent compounds are yet to be characterized. A transcriptomic time-series analysis of a selected accession RTC-144 infested with aphids revealed a massive alteration of genes related to specialized metabolism that potentially synthesize non-volatile toxic compounds. This is the first report to reveal the variation in the defense mechanisms of tef plants. These findings can facilitate the discovery of insect-resistance genes leading to enhanced yield in tef and other cereal crops.

Enlarging Knowledge on Lager Beer Volatile Metabolites Using Multidimensional Gas Chromatography

Foodomics, emergent field of metabolomics, has been applied to study food system processes, and it may be useful to understand sensorial food properties, among others, through foods metabolites profiling. Thus, as beer volatile components represent the major contributors for beer overall and peculiar aroma properties, this work intends to perform an in-depth profiling of lager beer volatile metabolites and to generate new data that may contribute for molecules’ identification, by using multidimensional gas chromatography. A set of lager beers were used as case-study, and 329 volatile metabolites were determined, distributed over 8 chemical families: acids, alcohols, esters, monoterpenic compounds, norisoprenoids, sesquiterpenic compounds, sulfur compounds, and volatile phenols. From these, 96 compounds are reported for the first time in the lager beer volatile composition. Around half of them were common to all beers under study. Clustering analysis allowed a beer typing according to production system: macro- and microbrewer beers. Monoterpenic and sesquiterpenic compounds were the chemical families that showed wide range of chemical structures, which may contribute for the samples’ peculiar aroma characteristics. In summary, as far as we know, this study presents the most in-depth lager beer volatile composition, which may be further used in several approaches, namely, in beer quality control, monitoring brewing steps, raw materials composition, among others.

Metabolomics Approach to Assess the Relative Contributions of the Volatile and Non-volatile Composition to Expert Quality Ratings of Pinot Noir Wine Quality.

Wine flavor and quality are determined by the assessment of multiple sensory stimuli, including aroma, taste, and mouthfeel. It is therefore important to consider the contribution of as many metabolites as possible when attempting to relate wine composition to quality. In this study, partial least squares regression of the volatile (untargeted headspace solid-phase microextraction coupled with gas chromatography time-of-flight mass spectrometry), non-volatile (untargeted reverse-phase ultra-high-performance liquid chromatography mass spectrometry), and combined metabolite profiles were used to predict Pinot Noir wine quality ratings as assessed by experts. Non-volatile metabolite profiles predicted wine quality ratings better than volatile metabolite profiles, suggesting that the non-volatile composition of Pinot Noir wines contributes to quality perception to a greater extent than the volatile composition. This was underscored by descriptive sensory analysis, which found that taste and mouthfeel attributes were better correlated with wine quality ratings than aroma attributes. Important predictors of Pinot Noir wine quality were also characterized. Some new relationships between wine metabolites and quality ratings were found: dipeptides and unsaturated fatty acids were positively related to Pinot Noir wine quality, while N-(3-methylbutyl)acetamide and xanthine were negatively associated.

Comparative transcriptome analysis of genes involved in volatile compound synthesis in blueberries (Vaccinium virgatum) during postharvest storage

• Genes involved in postharvest blueberry aroma biosynthesis were characterized. • Increased ethyl acetate was associated with increased PDC activity after harvest. • Postharvest storage modulated terpene synthase (TPS) genes associated with linalool. Transcriptional regulation of aroma formation genes during postharvest storage remains poorly understood in the blueberry. In order to have a better understanding of the transcriptional regulation processes that occur in rabbiteye blueberry during storage and their effect on the volatile composition change, we performed volatile metabolite profiling and transcriptomic analysis. Our study reveals that during postharvest storage, ‘Garden blue’ blueberry volatile composition changed by regulating several secondary metabolic pathways, in particular, by stimulating the expression of pyruvate decarboxylase (PDC) genes, resulting in a high production of ethyl acetate. Postharvest storage also modulated some terpene synthase (TPS) genes associated with linalool production. The concentration of C6 aldehydes and alcohols decreased during the postharvest storage accompanied by lower lipoxygenase (LOX) gene expression. These findings illustrate the molecular and biochemical mechanisms that occur in blueberry during the postharvest storage period, especially with regard to volatile composition changes.

Impact of Lactobacillus paracasei IMC502 in coculture with traditional starters on volatile and non-volatile metabolite profiles in yogurt

The impact of Lactobacillus paracasei IMC502 co-fermented with traditional starters on metabolites in yogurt was evaluated using metabolomic analysis. Forty-four volatile metabolites were determined using headspace solid phase microextraction and gas chromatography-mass spectrometry, including alcohols, esters, organic acids, carbonyl and sulfur compounds. Acetaldehyde, diacetyl, acetoin, acetone, butanoic and acetic acid were present in yogurts in higher intensity, which are the major volatile metabolites related to yogurt flavor. L. paracasei IMC502 did not affect the amounts of acetaldehyde, diacetyl and acetoin while promoted the formation of acetone and butanoic acid. A total of 196 non-volatile metabolites including nucleosides, amino acids, carbohydrates, lipids were analyzed using UPLC-Q-TOF-MS. Non-volatile metabolite profiles of these two types of yogurts were distinguished and 94 differential metabolites were screened using multivariate statistical analysis, which were mainly associated with the biosynthesis of secondary metabolites, amino acid metabolism and nucleotide metabolism. The impact of storage on metabolites was also investigated. The amounts of the majority of carbonyl compounds, organic acids and free amino acids increased, while those of acetaldehyde, diacetyl and lactose decreased during storage. This study provides insights into the metabolic mechanism of L. paracasei and represents a real advance in the study of the metabolites in yogurt.

Predictive Metagenomic Profiling, Urine Metabolomics, and Human Marker Gene Expression as an Integrated Approach to Study Alopecia Areata.

Involvement of the microbiome in many different scalp conditions has been investigated over the years. Studies on the role of the scalp microbiome in specific diseases, such as those involving hair growth alterations like non-cicatricial [androgenetic alopecia (AGA), alopecia areata (AA)] and cicatricial alopecia lichen planopilaris, are of major importance. In the present work, we highlighted the differences in microbial populations inhabiting the scalp of AA subjects and a healthy sample cohort by using an integrated approach relying on metagenomic targeted 16S sequencing analysis, urine metabolomics, and human marker gene expression. Significant differences in genera abundances (p < 0.05) were found in the hypodermis and especially the dermis layer. Based on 16S sequencing data, we explored the differences in predicted KEGG pathways and identified some significant differences in predicted pathways related to the AA pathologic condition such as flagellar, assembly, bacterial chemotaxis, mineral absorption, ABC transporters, cellular antigens, glycosaminoglycan degradation, lysosome, sphingolipid metabolism, cell division, protein digestion and absorption, and energy metabolism. All predicted pathways were significantly enhanced in AA samples compared to expression in healthy samples, with the exceptions of mineral absorption, and ABC transporters. We also determined the expression of TNF-α, FAS, KCNA3, NOD-2, and SOD-2 genes and explored the relationships between human gene expression levels and microbiome composition by Pearson's correlation analysis; here, significant correlations both positive (SOD vs. Staphylococcus, Candidatus Aquiluna) and negative (FAS and SOD2 vs. Anaerococcus, Neisseria, and Acinetobacter) were highlighted. Finally, we inspected volatile organic metabolite profiles in urinary samples and detected statistically significant differences (menthol, methanethiol, dihydrodehydro-beta-ionone, 2,5-dimethylfuran, 1,2,3,4, tetrahydro-1,5,7-trimethylnapthalene) when comparing AA and healthy subject groups. This multiple comparison approach highlighted potential traits associated with AA and their relationship with the microbiota inhabiting the scalp, opening up novel therapeutic interventions in such kind of hair growth disorders mainly by means of prebiotics, probiotics, and postbiotics.

Characterization of volatile metabolites formed by molds on barley by mass and ion mobility spectrometry.

The contamination of barley by molds on the field or in storage leads to the spoilage of grain and the production of mycotoxins, which causes major economic losses in malting facilities and breweries. Therefore, on-site detection of hidden fungus contaminations in grain storages based on the detection of volatile marker compounds is of high interest. In this work, the volatile metabolites of 10 different fungus species are identified by gas chromatography (GC) combined with two complementary mass spectrometric methods, namely, electron impact (EI) and chemical ionization at atmospheric pressure (APCI)-mass spectrometry (MS). The APCI source utilizes soft X-radiation, which enables the selective protonation of the volatile metabolites largely without side reactions. Nearly 80 volatile or semivolatile compounds from different substance classes, namely, alcohols, aldehydes, ketones, carboxylic acids, esters, substituted aromatic compounds, alkenes, terpenes, oxidized terpenes, sesquiterpenes, and oxidized sesquiterpenes, could be identified. The profiles of volatile and semivolatile metabolites of the different fungus species are characteristic of them and allow their safe differentiation. The application of the same GC parameters and APCI source allows a simple method transfer from MS to ion mobility spectrometry (IMS), which permits on-site analyses of grain stores. Characterization of IMS yields limits of detection very similar to those of APCI-MS. Accordingly, more than 90% of the volatile metabolites found by APCI-MS were also detected in IMS. In addition to different fungus genera, different species of one fungus genus could also be differentiated by GC-IMS.

Discrimination of Cultivated Regions of Soybeans (Glycine max) Based on Multivariate Data Analysis of Volatile Metabolite Profiles.

Soybean (Glycine max) is a major crop cultivated in various regions and consumed globally. The formation of volatile compounds in soybeans is influenced by the cultivar as well as environmental factors, such as the climate and soil in the cultivation areas. This study used gas chromatography-mass spectrometry (GC-MS) combined by headspace solid-phase microextraction (HS-SPME) to analyze the volatile compounds of soybeans cultivated in Korea, China, and North America. The multivariate data analysis of partial least square-discriminant analysis (PLS-DA), and hierarchical clustering analysis (HCA) were then applied to GC-MS data sets. The soybeans could be clearly discriminated according to their geographical origins on the PLS-DA score plot. In particular, 25 volatile compounds, including terpenes (limonene, myrcene), esters (ethyl hexanoate, butyl butanoate, butyl prop-2-enoate, butyl acetate, butyl propanoate), aldehydes (nonanal, heptanal, (E)-hex-2-enal, (E)-hept-2-enal, acetaldehyde) were main contributors to the discrimination of soybeans cultivated in China from those cultivated in other regions in the PLS-DA score plot. On the other hand, 15 volatile compounds, such as 2-ethylhexan-1-ol, 2,5-dimethylhexan-2-ol, octanal, and heptanal, were related to Korean soybeans located on the negative PLS 2 axis, whereas 12 volatile compounds, such as oct-1-en-3-ol, heptan-4-ol, butyl butanoate, and butyl acetate, were responsible for North American soybeans. However, the multivariate statistical analysis (PLS-DA) was not able to clearly distinguish soybeans cultivated in Korea, except for those from the Gyeonggi and Kyeongsangbuk provinces.

Comparison of Stir Bar Sorptive Extraction and Solid Phase Microextraction of Volatile and Semi-Volatile Metabolite Profile of Staphylococcus Aureus

For the analysis of volatile bacterial compounds, solid phase microextraction (SPME) is currently the most widely used metabolite concentration technique. Recently, the potential of stir bar sorptive extraction (SBSE) for this use has been demonstrated. These two approaches were therefore used in combination with gas-chromatography coupled with mass-spectrometry (GC–MS) for the analysis of volatile and semi-volatile bacterial compounds produced by Staphylococcus aureus. In both cases, SPME and SBSE/headspace sorptive extraction (HSSE) enrichment was carried out in two coating phases. A whole analytical and statistical process was developed to differentiate the metabolites produced from the metabolites consumed. The results obtained with SBSE/HSSE and SPME were compared and showed the recovery of 90% of the compounds by SBSE/HSSE. In addition, we were able to detect the production of 12 volatile/semi-volatile compounds by S. aureus, six of which had never been reported before. The extraction by SBSE/HSSE showed higher concentration capacities and greater sensitivity than SPME concerning bacterial compounds, suggesting that this technique may therefore become the new preferred option for bacterial volatile and semi-volatile compound analysis.

Terpenoid profiles of resin in the genus Dracaena are species specific

Dragon's blood is the colloquial name for the red resin produced by tree species in the genus Dracaena (Asparagaceae), and the resin is directly involved in plant defensive mechanisms against pathogen and herbivore attack. It is also widely used in traditional folk medicine due to its antiviral, antimicrobial and antitumor activities. In the present work, a method using solid phase microextraction combined with two-dimensional gas chromatography with time-of-flight mass spectrometric detection was developed for the analysis of resin from five Dracaena species, namely Dracaena cinnabari Balf. f., D. serrulata Baker, D. ombet Heuglin ex Kotschy & Peyr., D. draco subsp. draco, and D. draco subsp. ajgal. Twenty terpenoid components in the resins of the five species were identified after comparative study of the volatile metabolite profiles. Monoterpenes were found to be species specific, and the observed differences might be further investigated as a possible means of identifying chemotaxonomic markers. In addition, for the first time, we describe the terpenoid volatile profiles of D. ombet and D. serrulata resins.

2365. Volatile Metabolite-Based Detection of Clostridium difficile Infection (CDI)

BackgroundCDI is a frequent cause of morbidity and mortality in hospitalized patients. Despite advances in rapid CDI testing, there are often delays between the onset of symptoms and receipt of test results. We sought to test the hypothesis that the altered CDI intestinal microbiome has a unique volatile metabolite profile, distinct from the profile of patients with other causes of antibiotic-associated diarrhea, which potentially can be used to identify patients with CDI.MethodsWe prospectively collected fresh stool samples from inpatients with suspected CDI at an academic tertiary care hospital from July 2015 to November 2017, adsorbed volatile metabolites from each sample onto sorbent tubes within an hour of sample collection, and used thermal desorption-gas chromatography/tandem mass spectrometry to identify each metabolite. All patients were exposed to at least one antibiotic agent in the prior 90 days, and only patients receiving empiric CDI treatment or with formed stool samples were excluded. We used logistic regression models, adjusting for prior anti-anaerobic antibiotic therapy and CDI severity (serum albumin <3 g/dL and WBC ≥ 15,000/mm3 or abdominal tenderness) and adjusting for multiple testing using Storey’s q-value procedure (with a threshold of q ≤ 0.05), to examine the relationship between CDI, as determined by the reference standard of the cell culture cytotoxicity neutralization assay, and each metabolite.ResultsIn our 565-patient cohort, median age was 61 years (IQR 50, 70) and 277 (49%) were male; 173 (31%) had abdominal pain in the 24 hours before testing, 59 (10%) had fevers in the prior 24 hours, 22 (4%) had an ileus, 74 (13%) had mental status changes in the prior 24 hours, 89 (16%) were hospitalized in the ICU at the time of testing, 45 (7%) were receiving pressors, 82 (15%) had a WBC ≥ 15,000/mm3, and 137 (24%) had a serum lactate > 1.5 mmol/L. Ultimately, 155 patients were diagnosed with CDI. Ten metabolites (Table 1, Figure 1) were differentially distributed in patients with and without CDI.ConclusionWe identified a suite of volatile metabolites that differentiates stool from patients with and without CDI; this profile may ultimately be used to identify patients with CDI. Disclosures All authors: No reported disclosures.

Hepatic Metabolic Derangements Triggered by Hyperthermia: An In Vitro Metabolomic Study.

Background and aims: Liver toxicity is a well-documented and potentially fatal adverse complication of hyperthermia. However, the impact of hyperthermia on the hepatic metabolome has hitherto not been investigated. Methods: In this study, gas chromatography-mass spectrometry (GC-MS)-based metabolomics was applied to assess the in vitro metabolic response of primary mouse hepatocytes (PMH, n = 10) to a heat stress stimulus, i.e., after 24 h exposure to 40.5 °C. Metabolomic profiling of both intracellular metabolites and volatile metabolites in the extracellular medium of PMH was performed. Results: Multivariate analysis showed alterations in levels of 22 intra- and 59 extracellular metabolites, unveiling the capability of the metabolic pattern to discriminate cells exposed to heat stress from cells incubated at normothermic conditions (37 °C). Hyperthermia caused a considerable loss of cell viability that was accompanied by significant alterations in the tricarboxylic acid cycle, amino acids metabolism, urea cycle, glutamate metabolism, pentose phosphate pathway, and in the volatile signature associated with the lipid peroxidation process. Conclusion: These results provide novel insights into the mechanisms underlying hyperthermia-induced hepatocellular damage.

Metabolomics analyses of the combined effects of lactic acid bacteria and Penicillium camemberti on the generation of volatile compounds in model mold-surface-ripened cheeses

The flavor of white mold cheese is attributed to the formation of aroma compounds associated with complex effects of bacteria and fungi, resulting in difficulties in flavor design for new cheeses. This study aimed to identify the microbial basis of flavor by identifying the combined effects of LD type lactic acid bacteria (LAB) starters and Penicillium camemberti on the generation of metabolites during the ripening process. Metabolomics analyses were performed on three model cheeses: normal cheese, no-mold cheese with only LAB, and no-LAB cheese with only white mold. Aroma compounds and their potential precursors were analyzed using headspace solid-phase microextraction-gas chromatography/mass spectrometry (GC/MS) and solvent extraction-GC/MS, respectively. Measurements during ripening and multivariate analyses on the data revealed the relationship between the microorganisms and metabolic activities, which were classified into four groups: metabolites generated by LAB and degraded by P.camemberti; metabolites generated by P.camemberti and degraded or inhibited by LAB; metabolites generated by P.camemberti and enhanced by LAB; and metabolites exhibiting no interaction between P.camemberti and LAB. The characteristic compounds in LAB and white mold cheeses were mainly products of sugar and protein metabolism, respectively. The involvement of fatty acids, methyl ketones, and secondary alcohol metabolic pathways in the late-ripening stage was confirmed, and the profiles of volatile metabolites contributing to the characteristic aroma of the white mold cheese in the fermentation process were also confirmed.

Sensory Metabolite Profiling in a Date Pit Based Coffee Substitute and in Response to Roasting as Analyzed via Mass Spectrometry Based Metabolomics.

Interest in developing coffee substitutes is on the rise, to minimizing its health side effects. In the Middle East, date palm (Phoenix dactylifera L.) pits are often used as a coffee substitute post roasting. In this study, commercially-roasted date pit products, along with unroasted and home-prepared roasted date pits, were subjected to analyses for their metabolite composition, and neuropharmacological evaluation in mice. Headspace SPME-GCMS and GCMS post silylation were employed for characterizing its volatile and non-volatile metabolite profile. For comparison to roasted coffee, coffee product was also included. There is evidence that some commercial date pit products appear to contain undeclared additives. SPME headspace analysis revealed the abundance of furans, pyrans, terpenoids and sulfur compounds in roasted date pits, whereas pyrroles and caffeine were absent. GCMS-post silylation employed for primary metabolite profiling revealed fatty acids’ enrichment in roasted pits versus sugars’ abundance in coffee. Biological investigations affirmed that date pit showed safer margin than coffee from its LD50, albeit it exhibits no CNS stimulant properties. This study provides the first insight into the roasting impact on the date pit through its metabolome and its neuropharmacological aspects to rationalize its use as a coffee substitute.

Comparative metabolic expressions of fermented soybeans according to different microbial starters

The quality of fermented soybeans can be determined by diverse metabolites produced by microorganisms. Mass spectrometry-based metabolomic approach was applied to investigate the differences in volatile and non-volatile metabolite profiles of fermented soybeans by different microorganisms [e.g., molds, yeasts, lactic acid bacteria (LAB), and other bacteria]. The partial least squares-discriminant analysis (PLS-DA) for volatile metabolites profiles indicated that the fungi group (mold/yeast) was clearly discriminated from the bacteria group (bacteria/LAB). The metabolic pathways related to the formation of volatile metabolites also differed according to microorganisms. In particular, the formation of branched-chain aliphatic alcohols and esters increased in the fungi group, while that of volatiles derived from fatty acids was superior in the bacteria group. In addition, we could determine the microorganism-specific metabolites using a correlation network analysis. This study can provide the fundamental knowledge on the metabolic differences according to the type of microorganisms in fermented soybeans.

Profiling of volatile and non-phenolic metabolites—Amino acids, organic acids, and sugars of green tea extracts obtained by different extraction techniques

Volatile compounds and non-phenolic metabolites (amino acids, organic acids, and sugars) of aqueous green tea extracts obtained by ultrasonic extraction (UE), agitation extraction (AE), hot water extraction (HWE), and conventional extraction (CE) were determined using SPME-GC–MS and HPLC, respectively. Significantly higher (P < 0.05) yields of volatiles and non-phenolic metabolites were obtained via UE and AE than via HWE and CE. UE, AE, HWE, and CE released 212, 201, 103, and 65 volatiles, respectively. Sum total of amino acid and organic acid in extracts was 54.57, 54.35, 27.11, and 12.67 (mg/100 g), and 5.96, 6.19, 3.81, and 1.68 (mg/100 g) for UE, AE, HWE, and CE, respectively. Volatiles except nitrogen-containing compounds had higher positive correlations with l-theanine, sucrose, malic acid, and catechins yields. Findings of the current study suggest that an efficient extraction technique may significantly increase volatile and non-phenolic metabolite yields in aqueous green tea extract.