Characterization of lipids and volatile compounds in boiled donkey meat by lipidomics and volatilomics

Lipids are crucial substances for the formation and retention of volatile compounds (VOCs). The lipid and VOC profiles of boiled donkey meat were investigated by lipidomics and volatilomics. In total, 4277 lipids belonging to 39 subclasses were identified, comprising 26.93% triglycerides (TGs), 15.74% phosphatidylcholins (PCs), and 9.40% phosphatidylethanolamines. The relative percentage of TG in the meat significantly decreases (p < 0.001) from 0 to 40 min, after which there is no significant change, whereas PCs, sphingomyelins, and methyl phosphatidylcholines (MePCs) show the opposite trend. TG(16:1_18:1_18:2) and TG(16:0_16:1_18:2) appear to be key lipids for retaining VOCs in boiled donkey meat. Furthermore, PC(18:3e_16:0) and MePC(31:0e) were found to be potential markers for discriminating donkey meat. A total of 83 VOCs were detected, including 25.30% aldehydes, 18.07% hydrocarbons, 14.46% ketones, and 13.25% alcohols. Eleven characteristic VOCs with relative odor activity values >1 were identified as the predominant flavor compounds in boiled donkey meat, mainly hexanal and 1-octen-3-ol. Of the 258 differential lipids, 72 of them, especially polyunsaturated-fatty acid-rich lipids, are the main contributors to the formation of VOCs. Together, the key lipids for retention and formation of VOCs in donkey meat were revealed, providing a theoretical basis for VOC regulation.

Detecting Pathogenic Phytophthora Species Using Volatile Organic Compounds

There are several highly damaging Phytophthora species pathogenic to forest trees, many of which have been spread beyond their native range by the international trade of live plants and infested materials. Such introductions can be reduced through the development of better tools capable of the early, rapid, and high-throughput detection of contaminated plants. This study utilized a volatilomics approach (solid-phase microextraction coupled to gas chromatography-mass spectrometry) to differentiate between several Phytophthora species in culture and discriminate between healthy and Phytophthora-inoculated European beech and pedunculate oak trees. We tentatively identified 14 compounds that could differentiate eight Phytophthora species from each other in vitro. All of the Phytophthora species examined, except Phytophthora cambivora, uniquely produced at least one compound not observed in the other species; however, most detected compounds were shared between multiple species. Phytophthora polonica had the most unique compounds and was the least similar of all the species examined. The inoculated seedlings had qualitatively different volatile profiles and could be distinguished from the healthy controls by the presence of isokaurene, anisole, and a mix of three unknown compounds. This study supports the notion that volatiles are suitable for screening plant material, detecting tree pathogens, and differentiating between healthy and diseased material.

Multi-Chemical Omics Analysis of the Symbiodiniaceae Durusdinium trenchii under Heat Stress

The urgency of responding to climate change for corals necessitates the exploration of innovative methods to swiftly enhance our understanding of crucial processes. In this study, we employ an integrated chemical omics approach, combining elementomics, metabolomics, and volatilomics methodologies to unravel the biochemical pathways associated with the thermal response of the coral symbiont, Symbiodiniaceae Durusdinium trenchii. We outline the complimentary sampling approaches and discuss the standardised data corrections used to allow data integration and comparability. Our findings highlight the efficacy of individual methods in discerning differences in the biochemical response of D. trenchii under both control and stress-inducing temperatures. However, a deeper insight emerges when these methods are integrated, offering a more comprehensive understanding, particularly regarding oxidative stress pathways. Employing correlation network analysis enhanced the interpretation of volatile data, shedding light on the potential metabolic origins of volatiles with undescribed functions and presenting promising candidates for further exploration. Elementomics proves to be less straightforward to integrate, likely due to no net change in elements but rather elements being repurposed across compounds. The independent and integrated data from this study informs future omic profiling studies and recommends candidates for targeted research beyond Symbiodiniaceae biology. This study highlights the pivotal role of omic integration in advancing our knowledge, addressing critical gaps, and guiding future research directions in the context of climate change and coral reef preservation.

Efficacy of Seed-Biopriming with Trichoderma spp. and Foliar Spraying of ZnO-Nanoparticles Induce Cherry Tomato Growth and Resistance to Fusarium Wilt Disease

Several microbes that cause plant diseases drastically lower the production of agriculture and jeopardize the safety of the world's food supply. As a result, sustainable agriculture requires disease management tactics based on modern, eco-friendly techniques as alternatives to various agrochemicals. The current study aimed to assess the antifungal activity of ZnO-nanoparticles against Fusarium solani in-vitro, and the ability of two antagonistic Trichoderma isolates, Trichoderma viride and Trichoderma harzianum, to produce antifungal secondary metabolites and identify them using gas chromatography-mass spectrometry, and to evaluate the combined effects of foliar spray of ZnO-nanoparticles and bioprimed seeds of cherry tomato (Solanum lycopersicum L.) with two antagonistic Trichoderma isolates against Fusarium wilt disease caused by Fusarium solani in greenhouse conditions. The results revealed that, in-vitro, the highest concentration of ZnO nanoparticles (3000 ppm) resulted in the greatest decrease in Fusarium solani mycelial growth (90.91% inhibition). The scanning electron microscopy demonstrated the evident distortion in Fusarium solani growing mycelia treated with ZnO-nanoparticles, which might be the source of growth suppression. Additionally, twenty-eight bioactive chemical compounds were isolated and identified from Trichoderma spp. ethyl acetate crude extracts using gas chromatography-mass spectrometry. In a greenhouse experiment, the combination of bioprimed cherry tomato plants with Trichoderma harzianum and foliar spraying of ZnO-nanoparticles at 3000 ppm was the most effective interaction treatment for reducing disease severity index (23.4%) and improving the vegetative growth parameters, micronutrient contents (Mn, Zn, and Fe in leaves), and chlorophyll content (SPAD unit), as well as stimulating phenylalanine ammonia-lyase activity of cherry tomato leaves at 75 days after sowing. In conclusion, the antifungal potential of seed-biopriming with antagonistic Trichoderma isolates and the foliar spraying of ZnO-nanoparticles can boost cherry tomato growth and confer resistance to Fusarium wilt caused by Fusarium solani.

Symbiont Identity Impacts the Microbiome and Volatilome of a Model Cnidarian-Dinoflagellate Symbiosis

The symbiosis between cnidarians and dinoflagellates underpins the success of reef-building corals in otherwise nutrient-poor habitats. Alterations to symbiotic state can perturb metabolic homeostasis and thus alter the release of biogenic volatile organic compounds (BVOCs). While BVOCs can play important roles in metabolic regulation and signalling, how the symbiotic state affects BVOC output remains unexplored. We therefore characterised the suite of BVOCs that comprise the volatilome of the sea anemone Exaiptasia diaphana ('Aiptasia') when aposymbiotic and in symbiosis with either its native dinoflagellate symbiont Breviolum minutum or the non-native symbiont Durusdinium trenchii. In parallel, the bacterial community structure in these different symbiotic states was fully characterised to resolve the holobiont microbiome. Based on rRNA analyses, 147 unique amplicon sequence variants (ASVs) were observed across symbiotic states. Furthermore, the microbiomes were distinct across the different symbiotic states: bacteria in the family Vibrionaceae were the most abundant in aposymbiotic anemones; those in the family Crocinitomicaceae were the most abundant in anemones symbiotic with D. trenchii; and anemones symbiotic with B. minutum had the highest proportion of low-abundance ASVs. Across these different holobionts, 142 BVOCs were detected and classified into 17 groups based on their chemical structure, with BVOCs containing multiple functional groups being the most abundant. Isoprene was detected in higher abundance when anemones hosted their native symbiont, and dimethyl sulphide was detected in higher abundance in the volatilome of both Aiptasia-Symbiodiniaceae combinations relative to aposymbiotic anemones. The volatilomes of aposymbiotic anemones and anemones symbiotic with B. minutum were distinct, while the volatilome of anemones symbiotic with D. trenchii overlapped both of the others. Collectively, our results are consistent with previous reports that D. trenchii produces a metabolically sub-optimal symbiosis with Aiptasia, and add to our understanding of how symbiotic cnidarians, including corals, may respond to climate change should they acquire novel dinoflagellate partners.

Integration of Volatilomics and Metabolomics Unveils Key Flavor-Related Biological Pathways in Different Carambola Cultivars

Carambola is a tropical fruit that is highly sought after by consumers due to its unique flavor, star shape, and nutritional value. Enhancing the flavor quality of this fruit can increase the consumer acceptance and market demand. However, flavor is an intrinsic characteristic of fruits. Its decoding requires in-depth knowledge based on recognizing key biological pathways relevant to flavor formation and development. In this study, the volatile and non-volatile metabolites contributing to the flavor variation of five carambola cultivars were investigated by a novel strategy combining GC-MS/O-based volatilomics with LC-MS-based metabolomics. Several significant flavor-related pathways, involving biosynthesis or metabolism of amino acids, terpenoids, fatty acids, sugar and organic acid, and flavonoids were identified based on the enrichment analysis of important volatile and non-volatile metabolites. The results indicated that there were metabolites in the flavor-related pathways being up- or downregulated, leading to the differences in flavor traits of different carambola cultivars. This study could provide a valuable reference for breeders and researchers of interest in the mechanisms underlying the regulation of flavor, which would ultimately lead to the creation of carambola cultivars with more attractive flavor profiles and pleasurable consuming experiences.

Human scent guides mosquito thermotaxis and host selection under naturalistic conditions

The African malaria mosquito Anopheles gambiae exhibits a strong innate drive to seek out humans in its sensory environment, classically entering homes to land on human skin in the hours flanking midnight. To gain insight into the role that olfactory cues emanating from the human body play in generating this epidemiologically important behavior, we developed a large-scale multi-choice preference assay in Zambia with infrared motion vision under semi-field conditions. We determined that An. gambiae prefers to land on arrayed visual targets warmed to human skin temperature during the nighttime when they are baited with carbon dioxide (CO2) emissions reflective of a large human over background air, body odor from one human over CO2, and the scent of one sleeping human over another. Applying integrative whole body volatilomics to multiple humans tested simultaneously in competition in a six-choice assay, we reveal high attractiveness is associated with whole body odor profiles from humans with increased relative abundances of the volatile carboxylic acids butyric acid, isobutryic acid, and isovaleric acid, and the skin microbe-generated methyl ketone acetoin. Conversely, those least preferred had whole body odor that was depleted of carboxylic acids among other compounds and enriched with the monoterpenoid eucalyptol. Across expansive spatial scales, heated targets without CO2 or whole body odor were minimally or not attractive at all to An. gambiae. These results indicate that human scent acts critically to guide thermotaxis and host selection by this prolific malaria vector as it navigates towards humans, yielding intrinsic heterogeneity in human biting risk.

Differences in the Volatilomic Urinary Biosignature of Prostate Cancer Patients as a Feasibility Study for the Detection of Potential Biomarkers

Prostate cancer (PCa) continues to be the second most common malignant tumour and the main cause of oncological death in men. Investigating endogenous volatile organic metabolites (VOMs) produced by various metabolic pathways is emerging as a novel, effective, and non-invasive source of information to establish the volatilomic biosignature of PCa. In this study, headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME/GC-MS) was used to establish the urine volatilomic profile of PCa and identify VOMs that can discriminate between the two investigated groups. This non-invasive approach was applied to oncological patients (PCa group, n = 26) and cancer-free individuals (control group, n = 30), retrieving a total of 147 VOMs from various chemical families. This included terpenes, norisoprenoid, sesquiterpenes, phenolic, sulphur and furanic compounds, ketones, alcohols, esters, aldehydes, carboxylic acid, benzene and naphthalene derivatives, hydrocarbons, and heterocyclic hydrocarbons. The data matrix was subjected to multivariate analysis, namely partial least-squares discriminant analysis (PLS-DA). Accordingly, this analysis showed that the group under study presented different volatomic profiles and suggested potential PCa biomarkers. Nevertheless, a larger cohort of samples is required to boost the predictability and accuracy of the statistical models developed.

Age-Dependent Serum Volatilomics of Milk and Yogurt Intake: A Randomized Crossover Study in Healthy Young and Older Men

Nutritional biomarkers of dairy intake can be affected by both food transformation and the metabolic status of the consumer. To assess these effects, this study investigated the serum volatilome of 14 young (YA) and 14 older (OA) adult men undergoing a 3 week restriction of dairy and fermented foods followed by a randomized crossover acute intake of milk and yogurt. 3,5-Dimethyl-octan-2-one was identified as a potential marker of dairy product intake as its response after both milk and yogurt intake was significantly increased during the postprandial phase but significantly decreased in fasting serum samples of the OA group after the restriction phase. The postprandial response of two metabolites was significantly different for the two dairy products while 19 metabolites were modulated by age. Remarkably, the response of all age-dependent metabolites was higher in the OA than in the YA group after milk or yogurt intake, whereas at the end of the restriction phase, their fasting concentrations were lower in the OA than in the YA group. Among these, p-cresol, a specific marker of colonic protein fermentation, had a significant response in the OA but not the YA group, which may suggest impaired intestinal processing of dietary proteins in the OA group.

Characterization of meat quality traits, fatty acids and volatile compounds in Hu and Tan sheep

Sheep breed has a major influence on characteristics of meat quality and intramuscular fat (IMF), however, studies into the relationship between sheep breed and meat quality traits rarely consider the large variation in IMF within breed. In this study, groups of 176 Hu and 76 Tan male sheep were established, weaned at 56 days old, with similar weights, and representative samples were selected based on the distribution of IMF in each population, to investigate variations in meat quality, IMF and volatile compound profiles between breeds. Significant differences were observed in drip loss, shear force, cooking loss, and color coordinates between Hu and Tan sheep (p < 0.01). The IMF content and the predominate unsaturated fatty acids, oleic and cis, cis-linoleic acids, were similar. Eighteen out of 53 volatile compounds were identified as important odor contributors. Of these 18 odor-active volatile compounds, no significant concentration differences were detected between breeds. In another 35 volatile compounds, γ-nonalactone was lower in Tan sheep relative to Hu sheep (p < 0.05). In summary, Tan sheep exhibited lower drip loss, higher shear force values, and redder color, had less saturated fatty acids, and contained less γ-nonalactone against Hu sheep. These findings improve understanding of aroma differences between Hu and Tan sheep meat. Graphical Abstract.

An Investigation of Stability and Species and Strain-Level Specificity in Bacterial Volatilomes

Microbial volatilomics is a rapidly growing field of study and has shown great potential for applications in food, farming, and clinical sectors in the future. Due to the varying experimental methods and growth conditions employed in microbial volatilomic studies as well as strain-dependent volatilomic differences, there is limited knowledge regarding the stability of microbial volatilomes. Consequently, cross-study comparisons and validation of results and data can be challenging. In this study, we investigated the stability of the volatilomes of multiple strains of Staphylococcus aureus, Pseudomonas aeruginosa and Escherichia coli across three frequently used nutrient-rich growth media. Volatilomic stability was assessed based on media-, time- and strain-dependent variation across the examined bacterial volatilomes. Strain-level specificity of the observed volatilomes of E. coli and P. aeruginosa strains was further investigated by comparing the emission of selected compounds at varying stages of cell growth. Headspace solid phase microextraction (HS-SPME) sampling coupled with gas chromatography mass spectrometry (GC-MS) was used to analyze the volatilome of each strain. The whole volatilomes of the examined strains demonstrate a high degree of stability across the three examined growth media. At the compound-level, media dependent differences were observed particularly when comparing the volatilomes obtained in glucose-containing brain heart infusion (BHI) and tryptone soy broth (TSB) growth media with the volatilomes obtained in glucose-free Lysogeny broth (LB) media. These glucose-dependent volatilomic differences were primarily seen in the emission of primary metabolites such as alcohols, ketones, and acids. Strain-level differences in the emission of specific compounds in E. coli and P. aeruginosa samples were also observed across the media. These strain-level volatilomic differences were also observed across varying phases of growth of each strain, therefore confirming that these strains had varying core and accessory volatilomes. Our results demonstrate that, at the species-level, the examined bacteria have a core volatilome that exhibits a high-degree of stability across frequently-used growth media. Media-dependent differences in microbial volatilomes offer valuable insights into identifying the cellular origin of individual metabolites. The observed differences in the core and accessory volatilomes of the examined strains illustrate the complexity of microbial volatilomics as a study while also highlighting the need for more strain-level investigations to ultimately elucidate the whole volatilomic capabilities of microbial species in the future.

Comprehensive Volatilome and Metabolome Signatures of Colorectal Cancer in Urine: A Systematic Review and Meta-Analysis

To increase compliance with colorectal cancer screening programs and to reduce the recommended screening age, cheaper and easy non-invasiveness alternatives to the fecal immunochemical test should be provided. Following the PRISMA procedure of studies that evaluated the metabolome and volatilome signatures of colorectal cancer in human urine samples, an exhaustive search in PubMed, Web of Science, and Scopus found 28 studies that met the required criteria. There were no restrictions on the query for the type of study, leading to not only colorectal cancer samples versus control comparison but also polyps versus control and prospective studies of surgical effects, CRC staging and comparisons of CRC with other cancers. With this systematic review, we identified up to 244 compounds in urine samples (3 shared compounds between the volatilome and metabolome), and 10 of them were relevant in more than three articles. In the meta-analysis, nine studies met the criteria for inclusion, and the results combining the case-control and the pre-/post-surgery groups, eleven compounds were found to be relevant. Four upregulated metabolites were identified, 3-hydroxybutyric acid, L-dopa, L-histidinol, and N1, N12-diacetylspermine and seven downregulated compounds were identified, pyruvic acid, hydroquinone, tartaric acid, and hippuric acid as metabolites and butyraldehyde, ether, and 1,1,6-trimethyl-1,2-dihydronaphthalene as volatiles.

Multiomics, virtual reality and artificial intelligence in heart failure

Aim: Multiomics delivers more biological insight than targeted investigations. We applied multiomics to patients with heart failure (HF) and reduced ejection fraction (HFrEF), with machine learning applied to advanced ECG (AECG) and echocardiography artificial intelligence (Echo AI). Patients & methods: In total, 46 patients with HFrEF and 20 controls underwent metabolomic profiling, including liquid/gas chromatography-mass spectrometry and solid-phase microextraction volatilomics in plasma and urine. HFrEF was defined using left ventricular (LV) global longitudinal strain, EF and N-terminal pro hormone BNP. AECG and Echo AI were performed over 5 min, with a subset of patients undergoing a virtual reality mental stress test. Results: A-ECG had similar diagnostic accuracy as N-terminal pro hormone BNP for HFrEF (area under the curve = 0.95, 95% CI: 0.85-0.99), and correlated with global longitudinal strain (r = -0.77, p < 0.0001), while Echo AI-generated measurements correlated well with manually measured LV end diastolic volume r = 0.77, LV end systolic volume r = 0.8, LVEF r = 0.71, indexed left atrium volume r = 0.71 and indexed LV mass r = 0.6, p < 0.005. AI-LVEF and other HFrEF biomarkers had a similar discrimination for HFrEF (area under the curve AI-LVEF = 0.88; 95% CI: -0.03 to 0.15; p = 0.19). Virtual reality mental stress test elicited arrhythmic biomarkers on AECG and indicated blunted autonomic responsiveness (alpha 2 of RR interval variability, p = 1 × 10^-4) in HFrEF. Conclusion: Multiomics-related machine learning shows promise for the assessment of HF.

Trends and applications in plant volatile sampling and analysis

Volatile organic compounds (VOCs) released by plants serve as information and defense chemicals in mutualistic and antagonistic interactions and mitigate effects of abiotic stress. Passive and dynamic sampling techniques combined with gas chromatography-mass spectrometry analysis have become routine tools to measure emissions of VOCs and determine their various functions. More recently, knowledge of the roles of plant VOCs in the aboveground environment has led to the exploration of similar functions in the soil and rhizosphere. Moreover, VOC patterns have been recognized as sensitive and time-dependent markers of biotic and abiotic stress. This focused review addresses these developments by presenting recent progress in VOC sampling and analysis. We show advances in the use of small, inexpensive sampling devices and describe methods to monitor plant VOC emissions in the belowground environment. We further address latest trends in real-time measurements of volatilomes in plant phenotyping and most recent developments of small portable devices and VOC sensors for non-invasive VOC fingerprinting of plant disease. These technologies allow for innovative approaches to study plant VOC biology and application in agriculture.

Advances and Perspectives in Prostate Cancer Biomarker Discovery in the Last 5 Years through Tissue and Urine Metabolomics

Prostate cancer (PCa) is the second most diagnosed cancer in men worldwide. For its screening, serum prostate specific antigen (PSA) test has been largely performed over the past decade, despite its lack of accuracy and inability to distinguish indolent from aggressive disease. Metabolomics has been widely applied in cancer biomarker discovery due to the well-known metabolic reprogramming characteristic of cancer cells. Most of the metabolomic studies have reported alterations in urine of PCa patients due its noninvasive collection, but the analysis of prostate tissue metabolome is an ideal approach to disclose specific modifications in PCa development. This review aims to summarize and discuss the most recent findings from tissue and urine metabolomic studies applied to PCa biomarker discovery. Eighteen metabolites were found consistently altered in PCa tissue among different studies, including alanine, arginine, uracil, glutamate, fumarate, and citrate. Urine metabolomic studies also showed consistency in the dysregulation of 15 metabolites and, interestingly, alterations in the levels of valine, taurine, leucine and citrate were found in common between urine and tissue studies. These findings unveil that the impact of PCa development in human metabolome may offer a promising strategy to find novel biomarkers for PCa diagnosis.

Real-Time Volatilomics: A Novel Approach for Analyzing Biological Samples

The use of the 'omics techniques in environmental research has become common-place. The most widely implemented of these include metabolomics, proteomics, genomics, and transcriptomics. In recent years, a similar approach has also been taken with the analysis of volatiles from biological samples, giving rise to the so-called 'volatilomics' in plant analysis. Developments in direct infusion mass spectrometry (DI-MS) techniques have made it possible to monitor the changes in the composition of volatile flux from parts of plants, single specimens, and entire ecosystems in real-time. The application of these techniques enables a unique insight into the dynamic metabolic processes that occur in plants. Here, we provide an overview of the use of DI-MS in real-time volatilomics research involving plants.

Untargeted/Targeted 2D Gas Chromatography/Mass Spectrometry Detection of the Total Volatile Tea Metabolome

Identifying all analytes in a natural product is a daunting challenge, even if fractionated by volatility. In this study, comprehensive two-dimensional gas chromatography/mass spectrometry (GC×GC-MS) was used to investigate relative distribution of volatiles in green, pu-erh tea from leaves collected at two different elevations (1162 m and 1651 m). A total of 317 high and 280 low elevation compounds were detected, many of them known to have sensory and health beneficial properties. The samples were evaluated by two different software. The first, GC Image, used feature-based detection algorithms to identify spectral patterns and peak-regions, leading to tentative identification of 107 compounds. The software produced a composite map illustrating differences in the samples. The second, Ion Analytics, employed spectral deconvolution algorithms to detect target compounds, then subtracted their spectra from the total ion current chromatogram to reveal untargeted compounds. Compound identities were more easily assigned, since chromatogram complexities were reduced. Of the 317 compounds, for example, 34% were positively identified and 42% were tentatively identified, leaving 24% as unknowns. This study demonstrated the targeted/untargeted approach taken simplifies the analysis time for large data sets, leading to a better understanding of the chemistry behind biological phenomena.

Volatile Metabolites Emission by In Vivo Microalgae-An Overlooked Opportunity?

Fragrances and malodors are ubiquitous in the environment, arising from natural and artificial processes, by the generation of volatile organic compounds (VOCs). Although VOCs constitute only a fraction of the metabolites produced by an organism, the detection of VOCs has a broad range of civilian, industrial, military, medical, and national security applications. The VOC metabolic profile of an organism has been referred to as its 'volatilome' (or 'volatome') and the study of volatilome/volatome is characterized as 'volatilomics', a relatively new category in the 'omics' arena. There is considerable literature on VOCs extracted destructively from microalgae for applications such as food, natural products chemistry, and biofuels. VOC emissions from living (in vivo) microalgae too are being increasingly appreciated as potential real-time indicators of the organism's state of health (SoH) along with their contributions to the environment and ecology. This review summarizes VOC emissions from in vivo microalgae; tools and techniques for the collection, storage, transport, detection, and pattern analysis of VOC emissions; linking certain VOCs to biosynthetic/metabolic pathways; and the role of VOCs in microalgae growth, infochemical activities, predator-prey interactions, and general SoH.