Current metabolomics: technological advances

Novel network construction algorithm for the study of similarity and differential mechanisms between different clinical treatments: From key metabolites to the related genes for personalized therapy of breast cancer

Breast cancer (BC) is the most common diagnosed cancer in the female population. Different near-infrared (NIR)-based technologies have been generally applied for BC clinical treatment. In this study, a novel network construction algorithm based on molecular vertical relationship (NCVR) was proposed to identify key network signals for clinical personalized treatment. In NCVR, the molecular vertical relationship that can be characterized in simple terms was proposed for network construction, thereby facilitating to better advance clinical decision making. To effectively measure the discriminative ability of molecular vertical relationship between different physiological and pathological stages, the joint probability mass function was constructed using sample frequency which can reduce the influence of sample variability caused by individual differences and the probability of over fitting caused by the high complexity of molecular expression data. NCVR was successfully employed to analyze the similarities and differences of living organisms treated by different treatment patterns (i.e., NIR and apoferritin-conjugated cypate (Cy@AFT) + NIR) on BC. The results of similarity analysis indicated that the reprogramming of cellular lipid and energy metabolism may be responsible for the BC cell death induced by treatments. Experimental results of difference analysis suggested that the disruptions in cholesterol metabolism, ferroptosis and severe lipid metabolism imbalances etc. contribute to the enhanced effectiveness of BC treatment with Cy@AFT + NIR. Then, analysis results of genes related to the selected key metabolites further provided deep insights into pathological alterations associated with BC development and illustrated why the performance of Cy@AFT + NIR therapy is better than that of NIR therapy.

Pharmacometabolomics: An emerging platform for understanding the pathophysiological processes and therapeutic interventions

Pharmacometabolomics has emerged as a new subclass of metabolomics, aiming to predict an individual's response to a drug or optimize therapy based on prior information on an individual's metabolic profile. Pharmacometabolomics is being explored in drug discovery, biomarker identification, disease diagnosis, monitoring of disease progression, and therapeutic intervention. The time points-based sample collection is essential to measure the response of individuals to pathophysiological processes and therapeutic interventions. Analytical techniques such as NMR, LC-MS, and GC-MS have been employed to assess a huge number of metabolites present in biological systems. NMR has an advantage over other analytical techniques as it provides a snapshot of tissue and biological fluids, however, it requires higher magnetic fields to achieve better resolution. GC-MS could cover a wide range of metabolites due to high resolution but requires derivatization for certain metabolites. LC-MS is equally competitive and separates a wide range of metabolites with diverse polarities but requires extensive method development. Several platforms have been developed to analyze the analytical data and provide meaningful results via data reduction methods. PCA and PLS-DA are the most common methods for reduction dimensionality through simplified multivariate data modeling. This manuscript brings insights into the overview of pharmacometabolomics experimental design and the application of various analytical techniques and multivariate statistical analysis in the various fields of medical research.

Gas chromatography-mass spectrometry metabolic profiling and sensory evaluation of greenhouse mangoes (Mangifera indica L. 'Irwin') over multiple harvest seasons

Compared to outdoor mango cultivation in the tropics, greenhouse cultivation in temperate regions is less reported due to its short history and small scale. Here, we evaluated for the first time the taste-focused quality of greenhouse-grown mangoes (Irwin) by GC-MS metabolic profiling and sensory evaluation for over three years (2021-2023). The relative standard deviation in sensory evaluation scores was approximately 15 % each year. Meanwhile, principal component analysis was performed on 45 identified metabolites and clustered with similar topology over three years. Orthogonal partial least squares regression analysis showed that a prediction model could be constructed with R2, Q2 = 0.9 or higher for all three years. Furthermore, the 2021 prediction model was used to evaluate the accuracy of sensory evaluation scores in a different year (2023). Compared to the model that used all 45 metabolites as explanatory variables, the accuracy of the model improved when using only 24 important metabolites which are common to both years (2021 and 2022), suggesting that these metabolites are highly reproducible across years. This study would contribute not only to fundamental greenhouse information, but also to the improvement of quality and cultivation methods in greenhouse in the future.

Application of lipidomics in the study of traditional Chinese medicine

Lipidomics is an emerging discipline that systematically studies the various types, functions, and metabolic pathways of lipids within living organisms. This field compares changes in diseases or drug impact, identifying biomarkers and molecular mechanisms present in lipid metabolic networks across different physiological or pathological states. Through employing analytical chemistry within the realm of lipidomics, researchers analyze traditional Chinese medicine (TCM). This analysis aids in uncovering potential mechanisms for treating diverse physiopathological conditions, assessing drug efficacy, understanding mechanisms of action and toxicity, and generating innovative ideas for disease prevention and treatment. This manuscript assesses recent literature, summarizing existing lipidomics technologies and their applications in TCM research. It delineates the efficacy, mechanisms, and toxicity research related to lipidomics in Chinese medicine. Additionally, it explores the utilization of lipidomics in quality control research for Chinese medicine, aiming to expand the application of lipidomics within this field. Ultimately, this initiative seeks to foster the integration of traditional medicine theory with modern science and technology, promoting an organic fusion between the two domains.

Toxicological effects and molecular metabolic of polystyrene nanoplastics on soybean (Glycine max L.): Strengthening defense ability by enhancing secondary metabolisms

Nanoplastics, as emerging pollutants, have attracted worldwide concern for their possible environmental dangers. The ingestion and accumulation of nanoplastics in crops can contaminate the food chain and have unintended consequences for human health. In this study, we revealed the effects of polystyrene nanoplastics (PS-NPs; 80 nm) at different concentrations (0, 10, 100 mg L-1) on soybean (Glycine max L.) seedling growth, antioxidant enzyme system and secondary metabolism. Using laser confocal microscopy, we demonstrated that the absorption and translocation of PS-NPs in soybean. Plant growth inhibition was observed by changes in plant height, root length, and leaf area after 7 days of exposure to PS-NPs. The effect of PS-NPs on photosynthetic characteristics was reflected by a significant reduction in total chlorophyll content at 10 mg L-1. Activation of the antioxidant system was observed with increased malondialdehyde (MDA) content, and elevated activities of superoxide dismutase (SOD) and catalase (CAT). Non-targeted metabolomics analysis identified a total of 159 secondary metabolites, and exposure to 10 and 100 mg L-1 PS-NPs resulted in the production of 61 and 62 differential secondary metabolites. Metabolomics analysis showed that PS-NPs treatment altered the secondary metabolic profile of soybean leaves through the biosynthesis pathways of flavonoid, flavone flavonol, and isoflavones, which is expected to provide new insights into the tolerance mechanisms of plants to nanoplastics. Overall, the results of this study deepen our understanding of the negative impacts of nanoplastics in agricultural systems, which is crucial for assessing the risks of nanoplastics to ecological security.

Effect of sodium metabisulfite treatment and storage condition on metabolic profile of young coconut (Cocos nucifera L.)

Young coconuts (Cocos nucifera L.) used for export are trimmed to reduce their size and weight to lower transport costs. However, trimmed coconuts have a shorter shelf life due to microbial spoilage and surface discoloration caused by enzymatic browning. To minimize these effects, trimmed coconuts were dipped in an anti-browning agent, sodium metabisulfite (SMB), and stored under ambient conditions. However, there have been no reports on the effects of SMB treatment on metabolome changes in the flesh and water of young coconuts. Hence, this study investigated the metabolite changes in trimmed young coconuts after SMB treatment under different storage conditions using a gas chromatography (GC)/mass spectrometry (MS) metabolomic profiling approach. Tall young coconut samples were trimmed and treated with a 2% SMB solution for 5 min before storage at 25 °C or 4 °C for 2-4 weeks. Coconut flesh and water samples were collected after storage for 0, 2, and 4 weeks, and were subjected to GC-MS analysis. The results showed that the major metabolites affected by coconut deterioration were amino acids, sugars, and sugar alcohols. SMB treatment and/or refrigeration can help prevent metabolite changes in the flesh and water of young coconuts. In the future, improvements in storage conditions based on metabolite profiles should be explored.

Volatile Metabolite Profiles of Robusta Green Bean Coffee From Different Geographical Origins in West Java and Their Correlation With Temperature, Rainfall, and Altitudes Using SPME GC-MS-Based Metabolomics

The chemical composition, including volatile metabolites of green coffee beans, is influenced by geographic origin. The aim of this study was to reveal the volatile metabolite profile of a single variety of Robusta green bean coffee from five major plantation regions in West Java and to correlate these profiles with temperature, rainfall, and altitude. By using solid phase micro extractions and gas chromatography-mass spectrometry, 143 different volatile compounds were detected, with aromatic hydrocarbon, alcohols, monoterpene, pyrazines, sesquiterpenes, carboxylic acids, and terpene the most dominant. Principal component analysis (PCA) indicated 64.3% variability, showing that the metabolite profile of Robusta green coffee from the Bogor region was distinctly different from those in Ciamis, Kuningan, Sumedang, and Tasikmalaya, which were more similar to each other. Metabolites such as benzaldehyde, isovaleric acid, toluene, diisobutyl succinate, 1-heptene, 4-dodecene, caffeine, acetic acid, and methyl benzoate were identified as key discriminants, with a VIP score greater than 1.5. Temperature increases were linked to higher levels of isovaleric acid, diisobutyl succinate, 4-dodecene, toluene, and acetic acid, while other discriminant metabolites declined. Increased rainfall was associated with higher levels of benzaldehyde, 1-heptene, caffeine, and methyl benzoate, but lower levels of the other discriminants. Altitude had a positive correlation with methyl benzoate and 1-heptene, and a negative correlation with isovaleric acid and 4-dodecene, with weaker correlations for other compounds. In summary, Robusta green coffee beans from different regions of West Java can be distinguished by their volatile metabolites. Bogor green coffee beans had higher levels of benzaldehyde, 1-heptene, caffeine, and methyl benzoate, Kuningan beans had more diisobutyl succinate and 4-dodecene, Ciamis beans had higher levels of isovaleric acid, diisobutyl succinate, and 4-dodecene, while Sumedang and Tasikmalaya beans were similar, with higher levels of isovaleric acid, diisobutyl succinate, 4-dodecene, toluene, and acetic acid. This difference is related to the climatic factors of temperature and rainfall, as well as the altitude at which Robusta coffee is grown.

Integrating metabolomics into reproduction: Sperm metabolism and fertility enhancement in pigs

The last decades of research have revealed that many other factors besides gamete genomes are able to determine the reproductive outcomes. Indeed, paternal factors have been observed to be capable of modulating multiple crucial features of the reproductive process, such as sperm physiology, the maternal environment and, even, the offspring health. These recent advances have been encompassed with the emergence of OMICS technologies, as they comprehensively characterise the molecular composition of biological systems. The present narrative review aimed to take a closer look at the potential of these technologies in the field of reproductive biology. This literature revision shows that most studies up to date have followed a non-targeted approach to screen mammalian seminal plasma (SP) and sperm metabolite composition through different metabolome platforms. These studies have proposed metabolites of multiple natures as potential in vivo fertility biomarkers. Yet, targeted approaches can be used to answer specific biological question, and their power is exemplified herein. For instance, metabolomic studies have uncovered not only that glycolysis is the main ATP energy source of pig sperm, but also that sperm metabolism can trigger DNA damage, hence compromise embryo development. In conclusion, this review shows the potential of both non-targeted and targeted metabolomics for the discovery of cell pathways that govern the reproductive process. Understanding these systems could help make progress in different areas, including livestock efficient breeding, the improvement of artificial reproductive technologies, and the development of biomarkers for infertility detection.

Recent Advancement in NMR Based Plant Metabolomics: Techniques, Tools, and Analytical Approaches

Plant metabolomics, a rapidly advancing field within plant biology, is dedicated to comprehensively exploring the intricate array of small molecules in plant systems. This entails precisely gathering comprehensive chemical data, detecting numerous metabolites, and ensuring accurate molecular identification. Nuclear magnetic resonance (NMR) spectroscopy, with its detailed chemical insights, is crucial in obtaining metabolite profiles. Its widespread application spans various research disciplines, aiding in comprehending chemical reactions, kinetics, and molecule characterization. Biotechnological advancements have further expanded NMR's utility in metabolomics, particularly in identifying disease biomarkers across diverse fields such as agriculture, medicine, and pharmacology. This review covers the stages of NMR-based metabolomics, including historical aspects and limitations, with sample preparation, data acquisition, spectral processing, analysis, and their application parts.

From tissue lesions to neurotoxicity: The devastating effects of small-sized nanoplastics on red drum Sciaenops ocellatus

Nanoplastic pollution typically exhibits more biotoxicity to marine organisms than microplastic pollution. Limited research exists on the toxic effects of small-sized nanoplastics on marine fish, especially regarding their post-exposure resilience. In this study, red drum (Sciaenops ocellatus) were exposed to small-sized polystyrene nanoplastics (30 nm, PS-NPs) for 7 days for the exposure experiments, followed by 14 days of recovery experiments. Histologically, hepatic lipid droplets and branchial epithelial liftings were the primary lesions induced by PS-NPs during both exposure and recovery periods. The inhibition of total superoxide dismutase activity and the accumulation of malondialdehyde content throughout the exposure and recovery periods. Transcriptional and metabolic regulation revealed that PS-NPs induced lipid metabolism disorders and DNA damage during the initial 1-2 days of exposure periods, followed by immune responses and neurotoxicity in the later stages (4-7 days). During the early recovery stages (2-7 days), lipid metabolism and cell cycle were activated, while in the later recovery stage (14 days), the emphasis shifted to lipid metabolism and energy metabolism. Persistent histological lesions, changes in antioxidant capacity, and fluctuations in gene and metabolite expression were observed even after 14 days of recovery periods, highlighting the severe biotoxicity of small-sized PS-NPs to marine fish. In summary, small-sized PS-NPs have severe biotoxicity, causing tissue lesions, oxidative damage, lipid metabolism disorders, DNA damage, immune responses, and neurotoxicity in red drum. This study offers valuable insights into the toxic effects and resilience of small-sized nanoplastics on marine fish.

Advancements in metabolomics research in benign gallbladder diseases: A review

The burgeoning field of metabolomics has piqued the interest of researchers in the context of benign gallbladder diseases, which include conditions such as gallbladder polyps, gallstones, and cholecystitis, which are common digestive system disorders. As metabolomics continues to advance, researchers have increasingly focused their attention on its applicability in the study of benign gallbladder diseases to provide new perspectives for diagnostic, therapeutic, and prognostic evaluation. This comprehensive review primarily describes the techniques of liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and nuclear magnetic resonance and their respective applications in the study of benign gallbladder disease. Metabolomics has made remarkable progress in various aspects of these diseases, ranging from early diagnosis, etiological research, assessment of disease progression and prognosis, and optimization of therapeutic strategies. However, challenges remain in the field of metabolomics in the study of benign gallbladder diseases. These include issues related to data processing and analysis, biomarker discovery and validation, interdisciplinary research integration, and the advancement of personalized medicine. This article attempts to summarize research findings to date, highlight future research directions, and provide a reference point for metabolomics research in benign gallbladder disease.

Deleterious Effects of Heat Stress on the Tomato, Its Innate Responses, and Potential Preventive Strategies in the Realm of Emerging Technologies

The tomato is a fruit vegetable rich in nutritional and medicinal value grown in greenhouses and fields worldwide. It is severely sensitive to heat stress, which frequently occurs with rising global warming. Predictions indicate a 0.2 °C increase in average surface temperatures per decade for the next three decades, which underlines the threat of austere heat stress in the future. Previous studies have reported that heat stress adversely affects tomato growth, limits nutrient availability, hammers photosynthesis, disrupts reproduction, denatures proteins, upsets signaling pathways, and damages cell membranes. The overproduction of reactive oxygen species in response to heat stress is toxic to tomato plants. The negative consequences of heat stress on the tomato have been the focus of much investigation, resulting in the emergence of several therapeutic interventions. However, a considerable distance remains to be covered to develop tomato varieties that are tolerant to current heat stress and durable in the perspective of increasing global warming. This current review provides a critical analysis of the heat stress consequences on the tomato in the context of global warming, its innate response to heat stress, and the elucidation of domains characterized by a scarcity of knowledge, along with potential avenues for enhancing sustainable tolerance against heat stress through the involvement of diverse advanced technologies. The particular mechanism underlying thermotolerance remains indeterminate and requires further elucidatory investigation. The precise roles and interplay of signaling pathways in response to heat stress remain unresolved. The etiology of tomato plants' physiological and molecular responses against heat stress remains unexplained. Utilizing modern functional genomics techniques, including transcriptomics, proteomics, and metabolomics, can assist in identifying potential candidate proteins, metabolites, genes, gene networks, and signaling pathways contributing to tomato stress tolerance. Improving tomato tolerance against heat stress urges a comprehensive and combined strategy including modern techniques, the latest apparatuses, speedy breeding, physiology, and molecular markers to regulate their physiological, molecular, and biochemical reactions.

Non-targeted metabolomics identifies biomarkers in milk with high and low milk fat percentage

Milk is widely recognized as an important food source with health benefits. Different consumer groups have different requirements for the content and proportion of milk fat; therefore, it is necessary to investigate the differential metabolites and their regulatory mechanisms in milk with high and low milk fat percentages (MFP). In this study, untargeted metabolomics was performed on milk samples from 13 cows with high milk fat percentage (HF) and 13 cows with low milk fat percentage (LF) using ultra-high performance liquid chromatography coupled with mass spectrometry (UHPLC-MS/MS). Forty-eight potential differentially labeled compounds were screened using the orthogonal partial least squares-discriminant analysis (OPLS-DA) combined with the weighted gene co-expression network analysis (WGCNA) method. Amino acid metabolism was the key metabolic pathway with significant enrichment of L-histidine, 5-oxoproline, L-aspartic acid, and L-glutamic acid. The negative correlation with MFP differentiated the HF and LF groups. To further determine the potential regulatory role of these amino acids on milk fat metabolism, the expression levels of marker genes in the milk fat synthesis pathway were explored. It was noticed that L-histidine reduced milk fat concentration primarily by inhibiting the triglycerides (TAG) synthesis pathway. L-aspartic acid and L-glutamic acid inhibited milk fat synthesis through the fatty acid de novo and TAG synthesis pathways. This study provides new insights into the mechanism underlying milk fat synthesis and milk quality improvement.

Plant response to heavy metal stress toxicity: the role of metabolomics and other omics tools

Metabolomic investigations offers a significant foundation for improved comprehension of the adaptability of plants to reconfigure the key metabolic pathways and their response to changing climatic conditions. Their application to ecophysiology and ecotoxicology help to assess potential risks caused by the contaminants, their modes of action and the elucidation of metabolic pathways associated with stress responses. Heavy metal stress is one of the most significant environmental hazards affecting the physiological and biochemical processes in plants. Metabolomic tools have been widely utilised in the massive characterisation of the molecular structure of plants at various stages for understanding the diverse aspects of the cellular functioning underlying heavy metal stress-responsive mechanisms. This review emphasises on the recent progressions in metabolomics in plants subjected to heavy metal stresses. Also, it discusses the possibility of facilitating effective management strategies concerning metabolites for mitigating the negative impacts of heavy metal contaminants on the growth and productivity of plants.

Metabolomics and mitochondrial dysfunction in cardiometabolic disease

Circulating metabolites are indicators of systemic metabolic dysfunction and can be detected through contemporary techniques in metabolomics. These metabolites are involved in numerous mitochondrial metabolic processes including glycolysis, fatty acid β-oxidation, and amino acid catabolism, and changes in the abundance of these metabolites is implicated in the pathogenesis of cardiometabolic diseases (CMDs). Epigenetic regulation and direct metabolite-protein interactions modulate metabolism, both within cells and in the circulation. Dysfunction of multiple mitochondrial components stemming from mitochondrial DNA mutations are implicated in disease pathogenesis. This review will summarize the current state of knowledge regarding: i) the interactions between metabolites found within the mitochondrial environment during CMDs, ii) various metabolites' effects on cellular and systemic function, iii) how harnessing the power of metabolomic analyses represents the next frontier of precision medicine, and iv) how these concepts integrate to expand the clinical potential for translational cardiometabolic medicine.

Reconstructing hepatic metabolic profile and glutathione-mediated metabolic fate of acrylamide

The toxicity of acrylamide (AA) has continuously attracted wide concerns as its extensive presence from both environmental and dietary sources. However, its hepatic metabolic transformation and metabolic fate still remain unclear. This study aims to unravel the metabolic profile and glutathione (GSH) mediated metabolic fate of AA in liver of rats under the dose-dependent exposure. We found that exposure to AA dose-dependently alters the binding of AA and GSH and the generation of mercapturic acid adducts, while liver as a target tissue bears the metabolic transformation of AA via regulating GSH synthesis and consumption pathways, in which glutamine synthase (GSS), cytochrome P450 2E1 (CYP2E1), and glutathione S-transferase P1 (GSTP1) play a key role. In response to high- and low-dose exposures to AA, there were significant differences in liver of rats, including the changes in GSH and cysteine (CYS) activities and the conversion ratio of AA to glycidamide (GA), and liver can affect the transformation of AA by regulating the GSH-mediated metabolic pathway. Low-dose exposure to AA activates GSH synthesis pathway in liver and upregulates GSS activity and CYS content with no change in γ-glutamyl transpeptidase 1 (GGT1) activity. High-dose exposure to AA activates the detoxification pathway of GSH and increases GSH consumption by upregulating GSTP1 activity. In addition, molecular docking results showed that most of the metabolic molecules transformed by AA and GA other than themselves can closely bind to GSTP1, GSS, GGT1, N-acetyltransferase 8, and dimethyl sulfide dehydrogenase 1. The binding of AA-GSH and GA-GSH to GSTP1 and CYP2E1 enzymes determine the tendentiousness between toxicity and detoxification of AA, which exerts a prospective avenue for targeting protective role of hepatic enzymes against in vivo toxicity of AA.

Metabolite profiling of Borneo's Gonystylus bancanus through comprehensive extraction from various polarity of solvents

Gonystylus bancanus wood or ramin wood has been generally known as a source of agarwood (gaharu) bouya, a kind of agarwood inferior type, or under the exported trading name of aetoxylon oil. The massive exploitation of ramin wood is causing this plant's extinction and putting it on Appendix II CITES and IUCN Red List of Threatened Species. To date, no scientific publication concerns the chemical exploration of G. bancanus wood and preserving this germplasm through its metabolite profiling. Therefore, research focused on chemical components profiling of G. bancanus is promised. This research is aimed to explore metabolomics and analyze the influence of solvent polarities on the partitioning of metabolites in G. bancanus wood. A range of solvents in different polarities was applied to provide comprehensive extraction of metabolites in G. bancanus wood. Moreover, a hydrodistillation was also carried out to extract the volatile compounds despite the non-volatile ones. LCMS and GCMS analyses were performed to identify volatile and non-volatile components in the extracts and essential oil. Multivariate data analysis was processed using Principal Component Analysis (PCA) and agglomerative hierarchical clustering. 142 metabolites were identified by LCMS analysis, while 89 metabolites were identified by GCMS analysis. Terpenoids, flavonoids, phenyl propanoids, and saccharides are some major compound classes available from LCMS data. Oxygenated sesquiterpenes, especially 10-epi-γ-eudesmol, and β-eudesmol, are the major volatile components identified from GCMS analysis. PCA of LCMS analysis demonstrated that PC1 discriminated two clusters: essential oil, dichloromethane, and n-hexane extracts were in the positive quadrant, while methanol and ethyl acetate extracts were in the negative quadrant. Three-dimensional analysis of GCMS data revealed that n-hexane extract was in the superior quadrant, and its composition can be significantly distinguished from other extracts and essential oil. G. bancanus wood comprises valuable metabolites, i.e., terpenoids, which benefit the essential oil industry. Comprehensive extraction by performing solvents in different polarities on G. bancanus wood could allow exploration of fully extracted metabolites, supported by the exhibition of identified metabolites from LCMS and GCMS analysis.

Salivary metabolomic profile associated with cariogenic risk in children

OBJECTIVES

To identify the metabolomic differences in the saliva of healthy children versus children with active carious lesions and to estimate the predictive capacity of a model based on the salivary metabolomic profile.

METHODS

A study of cases (n = 31) and controls (n = 37) was designed for children aged between 6 and 12 (mean age of the cases: 8.9; controls: 8.7). The said children attended public health centers in Valencia, Spain. Intraoral examinations were performed by a single examiner using ICDAS II diagnostic criteria. Unstimulated total saliva samples were analyzed by nuclear magnetic resonance (NMR) spectroscopy.

RESULTS

The dft index for cases was 2.84 while it was 0.19 for the control group, the DMFT index was 1.13 and 0.11, respectively. The predictive model generated by the multivariate PLS-DA analysis projects a separation between the cases and the controls on the score chart with a predictive capacity and generating an area under the curve of 0.71. The metabolites: 3-methyl-2-oxovalerate, 3-hydroxybutyrate, lactate, acetone, citrate, ornithine, ethanolamine, taurine, proline, glycine, mannose, glucose, 1-6-Anhydro-β-d-glucose and citraconate, are those that show greater significance in the model. In the controls, glycine (Cohen's d = 0.430) and glucose (Cohen's d = 0.560) present higher means compared to the cases. On the contrary, taurine (Cohen's d= -0.474) and mannose (Cohen's d= -0.456) show higher means in cases compared to controls.

CONCLUSIONS

Our findings show a difference in the salivary metabolomic profiles, specifically in the groups of saccharides and amino acids, suggesting an association of these with the level of caries risk.

CLINICAL SIGNIFICANCE

The results reported in the present study reinforce the use of salivary metabolomics as a research method for the search for salivary biomarkers that allow the evaluation of caries risk in patients. Furthermore, it brings us closer to a personalized medicine that will help in dental caries prevention strategies.

Multi-Omics Pipeline and Omics-Integration Approach to Decipher Plant's Abiotic Stress Tolerance Responses

The present day's ongoing global warming and climate change adversely affect plants through imposing environmental (abiotic) stresses and disease pressure. The major abiotic factors such as drought, heat, cold, salinity, etc., hamper a plant's innate growth and development, resulting in reduced yield and quality, with the possibility of undesired traits. In the 21st century, the advent of high-throughput sequencing tools, state-of-the-art biotechnological techniques and bioinformatic analyzing pipelines led to the easy characterization of plant traits for abiotic stress response and tolerance mechanisms by applying the 'omics' toolbox. Panomics pipeline including genomics, transcriptomics, proteomics, metabolomics, epigenomics, proteogenomics, interactomics, ionomics, phenomics, etc., have become very handy nowadays. This is important to produce climate-smart future crops with a proper understanding of the molecular mechanisms of abiotic stress responses by the plant's genes, transcripts, proteins, epigenome, cellular metabolic circuits and resultant phenotype. Instead of mono-omics, two or more (hence 'multi-omics') integrated-omics approaches can decipher the plant's abiotic stress tolerance response very well. Multi-omics-characterized plants can be used as potent genetic resources to incorporate into the future breeding program. For the practical utility of crop improvement, multi-omics approaches for particular abiotic stress tolerance can be combined with genome-assisted breeding (GAB) by being pyramided with improved crop yield, food quality and associated agronomic traits and can open a new era of omics-assisted breeding. Thus, multi-omics pipelines together are able to decipher molecular processes, biomarkers, targets for genetic engineering, regulatory networks and precision agriculture solutions for a crop's variable abiotic stress tolerance to ensure food security under changing environmental circumstances.

Metabolomics and Transcriptomics Revealed a Comprehensive Understanding of the Biochemical and Genetic Mechanisms Underlying the Color Variations in Chrysanthemums

Flower color is an important characteristic of ornamental plants and is determined by various chemical components, including anthocyanin. In the present study, combined metabolomics and transcriptomics analysis was used to explore color variations in the chrysanthemums of three cultivars, of which the color of JIN is yellow, FEN is pink, and ZSH is red. A total of 29 different metabolites, including nine anthocyanins, were identified in common in the three cultivars. Compared with the light-colored cultivars, all of the nine anthocyanin contents were found to be up-regulated in the dark-colored ones. The different contents of pelargonidin, cyanidin, and their derivates were found to be the main reason for color variations. Transcriptomic analysis showed that the color difference was closely related to anthocyanin biosynthesis. The expression level of anthocyanin structural genes, including DFR, ANS, 3GT, 3MaT1, and 3MaT2, was in accordance with the flower color depth. This finding suggests that anthocyanins may be a key factor in color variations among the studied cultivars. On this basis, two special metabolites were selected as biomarkers to assist in chrysanthemum breeding for color selection.

Metabolomic analysis reveals the molecular responses to copper toxicity in rice (Oryza sativa)

Copper (Cu) is one of the essential microelements and widely participates in various pathways in plants, but excess Cu in plant cells could induce oxidative stress and harm plant growth. Rice (Oryza sativa) is a main crop food worldwide. The molecular mechanisms of rice in response to copper toxicity are still not well understood. In this study, two-week-old seedlings of the rice cultivar Nipponbare were treated with 100 μM Cu²⁺ (CuSO₄) in the external solution for 10 days. Physiological analysis showed that excess Cu significantly inhibited the growth and biomass of rice seedlings. After Cu treatment, the contents of Mn and Zn were significantly reduced in the roots and shoots, while the Fe content was significantly increased in the roots. Meanwhile, the activities of antioxidant enzymes including SOD and POD were dramatically enhanced after Cu treatment. Based on metabolomic analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods, 695 metabolites were identified in rice roots. Among these metabolites, 123 metabolites were up-regulated and 297 were down-regulated, respectively. The differential metabolites (DMs) include carboxylic acids and derivatives, benzene and substituted derivatives, carbonyl compounds, cinnamic acids and derivatives, fatty acyls and organ nitrogen compounds. KEGG analysis showed that these DMs were mainly enriched in TCA cycle, purine metabolism and starch and sucrose metabolism pathways. Many intermediates in the TCA cycle and purine metabolism were down-regulated, indicating a perturbed carbohydrate and nucleic acid metabolism. Taken together, the present study provides new insights into the mechanism of rice roots to Cu toxicity.

Status of Metabolomic Measurement for Insights in Alzheimer's Disease Progression-What Is Missing?

Alzheimer's disease (AD) is an aging-related neurodegenerative disease, leading to the progressive loss of memory and other cognitive functions. As there is still no cure for AD, the growth in the number of susceptible individuals represents a major emerging threat to public health. Currently, the pathogenesis and etiology of AD remain poorly understood, while no efficient treatments are available to slow down the degenerative effects of AD. Metabolomics allows the study of biochemical alterations in pathological processes which may be involved in AD progression and to discover new therapeutic targets. In this review, we summarized and analyzed the results from studies on metabolomics analysis performed in biological samples of AD subjects and AD animal models. Then this information was analyzed by using MetaboAnalyst to find the disturbed pathways among different sample types in human and animal models at different disease stages. We discuss the underlying biochemical mechanisms involved, and the extent to which they could impact the specific hallmarks of AD. Then we identify gaps and challenges and provide recommendations for future metabolomics approaches to better understand AD pathogenesis.

Multi-omics approaches for precision obesity management : Potentials and limitations of omics in precision prevention, treatment and risk reduction of obesity

INTRODUCTION

Obesity is a multifactorial chronic disease that cannot be addressed by simply promoting better diets and more physical activity. To date, not a single country has successfully been able to curb the accumulating burden of obesity. One explanation for the lack of progress is that lifestyle intervention programs are traditionally implemented without a comprehensive evaluation of an individual's diagnostic biomarkers. Evidence from genome-wide association studies highlight the importance of genetic and epigenetic factors in the development of obesity and how they in turn affect the transcriptome, metabolites, microbiomes, and proteomes.

OBJECTIVE

The purpose of this review is to provide an overview of the different types of omics data: genomics, epigenomics, transcriptomics, proteomics, metabolomics and illustrate how a multi-omics approach can be fundamental for the implementation of precision obesity management.

RESULTS

The different types of omics designs are grouped into two categories, the genotype approach and the phenotype approach. When applied to obesity prevention and management, each omics type could potentially help to detect specific biomarkers in people with risk profiles and guide healthcare professionals and decision makers in developing individualized treatment plans according to the needs of the individual before the onset of obesity.

CONCLUSION

Integrating multi-omics approaches will enable a paradigm shift from the one size fits all approach towards precision obesity management, i.e. (1) precision prevention of the onset of obesity, (2) precision medicine and tailored treatment of obesity, and (3) precision risk reduction and prevention of secondary diseases related to obesity.

Divergence in metabolomic profile in clownfish and damselfish skin mucus

Introduction

The clownfish - sea anemone mutualism was suggested to have triggered the adaptive radiation of clownfishes, but the origin of clownfish resistance to stinging tentacles of host anemones remains unclear. The presence of specific compounds in the mucus of clownfishes conferring them the unique ability to prevent nematocyst discharge from their hosts has been the most supported hypothesis. Yet the mystery regarding the types of compounds found in clownfish skin mucus remains unsolved.

Methods

We analyzed the chemical composition of clownfish and damselfish mucus using an untargeted metabolomics (HILIC-HRMS) and lipidomics (RPLC-HRMS) approach.

Results and Discussion

The polar and lipid metabolome signatures were highly specific and allowed to discriminate between the clownfish and damselfish clades. The most discriminative part of the signature was the sphingolipid profile, displaying a broader diversity of ceramides present in significantly higher levels in clownfish mucus. Importantly, the inter-specific variability of metabolic signature was significantly higher in clownfishes, although their diversification is evolutionarily more recent, thus implying the impact of symbiosis on metabolic variability and adaptation. Furthermore, specialists and generalists clownfish species displayed distinctive metabolite signature. Two strict clownfish specialists, which are phylogenetically distant but share the same host species, clustered together based on their molecular signature, suggesting a link with their mutualistic nature. Overall, comparative analyses of metabolic signatures highlight differences in chemical composition of clownfish mucus and provide insight into biochemical pathways potentially implicated in clownfish adaptation to inhabit sea anemones and consequently diversify.

Metabolomics as a Prospective Tool for Soybean (Glycine max) Crop Improvement

Global demand for soybean and its products has stimulated research into the production of novel genotypes with higher yields, greater drought and disease tolerance, and shorter growth times. Genetic research may be the most effective way to continue developing high-performing cultivars with desirable agronomic features and improved nutritional content and seed performance. Metabolomics, which predicts the metabolic marker for plant performance under stressful conditions, is rapidly gaining interest in plant breeding and has emerged as a powerful tool for driving crop improvement. The development of increasingly sensitive, automated, and high-throughput analytical technologies, paired with improved bioinformatics and other omics techniques, has paved the way for wide characterization of genetic characteristics for crop improvement. The combination of chromatography (liquid and gas-based) with mass spectrometry has also proven to be an indisputable efficient platform for metabolomic studies, notably plant metabolic fingerprinting investigations. Nevertheless, there has been significant progress in the use of nuclear magnetic resonance (NMR), capillary electrophoresis, and Fourier-transform infrared spectroscopy (FTIR), each with its own set of benefits and drawbacks. Furthermore, utilizing multivariate analysis, principal components analysis (PCA), discriminant analysis, and projection to latent structures (PLS), it is possible to identify and differentiate various groups. The researched soybean varieties may be correctly classified by using the PCA and PLS multivariate analyses. As metabolomics is an effective method for evaluating and selecting wild specimens with desirable features for the breeding of improved new cultivars, plant breeders can benefit from the identification of metabolite biomarkers and key metabolic pathways to develop new genotypes with value-added features.

Metabolomics reveals key resistant responses in tomato fruit induced by Cryptococcus laurentii

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Cryptococcus laurentii induces resistance through in concert with key metabolic changes in tomato fruit.

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A total of 59 metabolites were differently abundant in C. laurentii-treated tomato fruit.

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Key metabolites chlorogenic acid, caffeic acid and ferulic acid are involved in phenylpropanoid biosynthesis pathway may play a key role in resistance induction by C. Laurentii in tomato.

To investigate the mechanisms underlying inducible resistance in postharvest tomato fruit, non-targeted metabolome analysis was performed to uncover metabolic changes in tomato fruit upon Cryptococcus laurentii treatment. 289 and 149 metabolites were identified in positive and negative ion modes, respectively. A total of 59 metabolites, mainly including phenylpropanoids, flavonoids and phenolic acids, were differently abundant in C. laurentii-treated tomato fruit. Moreover, key metabolites involved in phenylpropanoid biosynthesis pathway, especially chlorogenic acid, caffeic acid and ferulic acid were identified through KEGG enrichment analysis. Enhanced levels of phenolic acids indicated activation of the phenylpropanoid biosynthesis pathway, which is a classic metabolic pathway associated with inducible resistance, suggesting that its activation and consequent metabolic changes contributed to inducible resistence induced by C. laurentii. Our findings would provide new understanding of resistance induction mechanism in tomato fruit from the metabolic perspective, and offer novel insights for new approaches reducing postharvest loss on tomato.

Integrated omics approaches for flax improvement under abiotic and biotic stress: Current status and future prospects

Flax (Linum usitatissimum L.) or linseed is one of the important industrial crops grown all over the world for seed oil and fiber. Besides oil and fiber, flax offers a wide range of nutritional and therapeutic applications as a feed and food source owing to high amount of α-linolenic acid (omega-3 fatty acid), lignans, protein, minerals, and vitamins. Periodic losses caused by unpredictable environmental stresses such as drought, heat, salinity-alkalinity, and diseases pose a threat to meet the rising market demand. Furthermore, these abiotic and biotic stressors have a negative impact on biological diversity and quality of oil/fiber. Therefore, understanding the interaction of genetic and environmental factors in stress tolerance mechanism and identification of underlying genes for economically important traits is critical for flax improvement and sustainability. In recent technological era, numerous omics techniques such as genomics, transcriptomics, metabolomics, proteomics, phenomics, and ionomics have evolved. The advancements in sequencing technologies accelerated development of genomic resources which facilitated finer genetic mapping, quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection in major cereal and oilseed crops including flax. Extensive studies in the area of genomics and transcriptomics have been conducted post flax genome sequencing. Interestingly, research has been focused more for abiotic stresses tolerance compared to disease resistance in flax through transcriptomics, while the other areas of omics such as metabolomics, proteomics, ionomics, and phenomics are in the initial stages in flax and several key questions remain unanswered. Little has been explored in the integration of omic-scale data to explain complex genetic, physiological and biochemical basis of stress tolerance in flax. In this review, the current status of various omics approaches for elucidation of molecular pathways underlying abiotic and biotic stress tolerance in flax have been presented and the importance of integrated omics technologies in future research and breeding have been emphasized to ensure sustainable yield in challenging environments.

Omics technologies in poultry health and productivity - part 1: current use in poultry research

In biology, molecular terms with the suffix "-omics" refer to disciplines aiming at the collective characterization of pools of molecules derived from different layers (DNA, RNA, proteins, metabolites) of living organisms using high-throughput technologies. Such omics analyses have been widely implemented in poultry research in recent years. This first part of a bipartite review on omics technologies in poultry health and productivity examines the use of multiple omics and multi-omics techniques in poultry research. More specific present and future applications of omics technologies, not only for the identification of specific diagnostic biomarkers, but also for potential future integration in the daily monitoring of poultry production, are discussed in part 2. Approaches based on omics technologies are particularly used in poultry research in the hunt for genetic markers of economically important phenotypical traits in the host, and in the identification of key bacterial species or functions in the intestinal microbiome. Integrative multi-omics analyses, however, are still scarce. Host physiology is investigated via genomics together with transcriptomics, proteomics and metabolomics techniques, to understand more accurately complex production traits such as disease resistance and fertility. The gut microbiota, as a key player in chicken productivity and health, is also a main subject of such studies, investigating the association between its composition (16S rRNA gene sequencing) or function (metagenomics, metatranscriptomics, metaproteomics, metabolomics) and host phenotypes. Applications of these technologies in the study of other host-associated microbiota and other host characteristics are still in their infancy.

Circulating Metabolic Biomarkers Are Consistently Associated With Type 2 Diabetes Risk in Asian and European Populations

CONTEXT

While Asians have a higher risk of type 2 diabetes (T2D) than Europeans for a given body mass index (BMI), it remains unclear whether the same markers of metabolic pathways are associated with diabetes.

OBJECTIVE

We evaluated associations between metabolic biomarkers and incidence of T2D in 3 major Asian ethnic groups (Chinese, Malay, and Indian) and a European population.

METHODS

We analyzed data from adult males and females of 2 cohorts from Singapore (n = 6393) consisting of Chinese, Malays, and Indians and 3 cohorts of European-origin participants from Finland (n = 14 558). We used nuclear magnetic resonance to quantify 154 circulating metabolic biomarkers at baseline and performed logistic regression to assess associations with T2D risk adjusted for age, sex, BMI and glycemic markers.

RESULTS

Of the 154 metabolic biomarkers, 59 were associated with higher risk of T2D in both Asians and Europeans (P < 0.0003, Bonferroni-corrected). These included branched chain and aromatic amino acids, the inflammatory marker glycoprotein acetyls, total fatty acids, monounsaturated fatty acids, apolipoprotein B, larger very low-density lipoprotein particle sizes, and triglycerides. In addition, 13 metabolites were associated with a lower T2D risk in both populations, including omega-6 polyunsaturated fatty acids and larger high-density lipoprotein particle sizes. Associations were consistent within the Asian ethnic groups (all Phet ≥ 0.05) and largely consistent for the Asian and European populations (Phet ≥ 0.05 for 128 of 154 metabolic biomarkers).

CONCLUSION

Metabolic biomarkers across several biological pathways were consistently associated with T2D risk in Asians and Europeans.

Metabolic Profiling of Thymic Epithelial Tumors Hints to a Strong Warburg Effect, Glutaminolysis and Precarious Redox Homeostasis as Potential Therapeutic Targets

Simple Summary

Thymomas and thymic carcinomas (TCs) are malignant thymic epithelial tumors (TETs) with poor outcome, if non-resectable. Metabolic signatures of TETs have not yet been studied and may offer new therapeutic options. This is the first metabolomics investigation on thymic epithelial tumors employing nuclear magnetic resonance spectroscopy of tissue samples. We could detect and quantify up to 37 metabolites in the major tumor subtypes, including acetylcholine that was not previously detected in other non-endocrine cancers. A metabolite-based cluster analysis distinguished three clinically relevant tumor subgroups, namely indolent and aggressive thymomas, as well as TCs. A metabolite-based metabolic pathway analysis also gave hints to activated metabolic pathways shared between aggressive thymomas and TCs. This finding was largely backed by enrichment of these pathways at the transcriptomic level in a large, publicly available, independent TET dataset. Due to the differential expression of metabolites in thymic epithelial tumors versus normal thymus, pathways related to proline, cysteine, glutathione, lactate and glutamine appear as promising therapeutic targets. From these findings, inhibitors of glutaminolysis and of the downstream TCA cycle are anticipated to be rational therapeutic strategies. If our results can be confirmed in future, sufficiently powered studies, metabolic signatures may contribute to the identification of new therapeutic options for aggressive thymomas and TCs.

Abstract

Thymomas and thymic carcinomas (TC) are malignant thymic epithelial tumors (TETs) with poor outcome, if non-resectable. Metabolic signatures of TETs have not yet been studied and may offer new therapeutic options. Metabolic profiles of snap-frozen thymomas (WHO types A, AB, B1, B2, B3, n = 12) and TCs (n = 3) were determined by high resolution magic angle spinning 1H nuclear magnetic resonance (HRMAS 1H-NMR) spectroscopy. Metabolite-based prediction of active KEGG metabolic pathways was achieved with MetPA. In relation to metabolite-based metabolic pathways, gene expression signatures of TETs (n = 115) were investigated in the public “The Cancer Genome Atlas” (TCGA) dataset using gene set enrichment analysis. Overall, thirty-seven metabolites were quantified in TETs, including acetylcholine that was not previously detected in other non-endocrine cancers. Metabolite-based cluster analysis distinguished clinically indolent (A, AB, B1) and aggressive TETs (B2, B3, TCs). Using MetPA, six KEGG metabolic pathways were predicted to be activated, including proline/arginine, glycolysis and glutathione pathways. The activated pathways as predicted by metabolite-profiling were generally enriched transcriptionally in the independent TCGA dataset. Shared high lactic acid and glutamine levels, together with associated gene expression signatures suggested a strong “Warburg effect”, glutaminolysis and redox homeostasis as potential vulnerabilities that need validation in a large, independent cohort of aggressive TETs. If confirmed, targeting metabolic pathways may eventually prove as adjunct therapeutic options in TETs, since the metabolic features identified here are known to confer resistance to cisplatin-based chemotherapy, kinase inhibitors and immune checkpoint blockers, i.e., currently used therapies for non-resectable TETs.

LC-MS Based Metabolomics Analysis of Potato (Solanum tuberosum L.) Cultivars Irrigated with Quicklime Treated Acid Mine Drainage Water

In water-scarce areas, the reuse of (un)treated acid mine drainage (AMD) water for crop irrigation has become a requirement, but it also carries a wide range of contaminants that can elicit the synthesis of diverse metabolites necessary for the survival of the plants. There is still a paucity of studies on the impact of quicklime treated-AMD water on the metabolite synthesis of potatoes. This study examined the effect of the irrigation of two potato cultivars (Marykies and Royal cultivars) with quicklime-treated AMD water on their metabolite profiles. A greenhouse study was conducted with five experimental treatments with different solution ratios, replicated three times in a completely randomized design. A total of 40 and 36 metabolites from Marykies and Royal cultivars which include amino acids, organic acids, and aromatic amines were identified, respectively. The results revealed elevation in the abundance of metabolites under the irrigation with treated AMD water for both cultivars with subtle variations. This will provide information on the primary metabolite shifst in potato that enhance their survival and growth under AMD conditions. However, more specific data on toxicity due to AMD irrigation would be required for a refined risk assessment.

HPV-mediated Cervical Cancer: A Systematic review on Immunological Basis, Molecular Biology and Immune evasion mechanisms

BACKGROUND

Human papillomavirus (HPV), one of the most frequently transmitted viruses globally, causing several malignancies including cervical cancer.

AIM

Owing to their unique pathogenicity HPV viruses can persist in the host organism for a longer duration than other virus types, to complete their lifecycle. During its association with the host, HPV causes various pathological conditions affecting the immune system by evading the host immune- mechanisms leading to the progression of various diseases, including cancer.

METHOD

To date, ~ 150 serotypes were identified, and certain high-risk HPV types are known to be associated with genital warts and cervical cancer. As of now, two prophylactic vaccines are in use for the treatment of HPV infection, however, no effective antiviral drug is available for HPV-associated disease/infections. Numerous clinical and laboratory studies are being investigated to formulate an effective and specific vaccine again HPV infections and associated diseases.

RESULT

As the immunological basis of HPV infection and associated disease progress persist indistinctly, deeper insights on immune evasion mechanism and molecular biology of disease would aid in developing an effective vaccine.

CONCLUSION

Thus this review focuses, aiming a systematic review on the immunological aspects of HPV-associated cervical cancer by uncovering immune evasion strategies adapted by HPV.

Mass Spectrometry-Based Technology and Workflows for Studying the Chemistry of Fungal Endophyte Derived Bioactive Compounds

Bioactive compounds have gained substantial attention in research and have conferred great advancements in the industrial and pharmacological fields. Highly diverse fungi and their metabolome serve as a big platform to be explored for their diverse bioactive compounds. Omics tools coupled with bioinformatics, statistical, and well-developed algorithm tools have elucidated immense knowledge about fungal endophyte derived bioactive compounds. Further, these compounds are subjected to chromatography-gas chromatography and liquid chromatography (LC), spectroscopy-nuclear magnetic resonance (NMR), and "soft ionization" technique-matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) based analytical techniques for structural characterization. The mass spectrometry (MS)-based approach, being highly sensitive, reproducible, and reliable, produces quick and high-profile identification. Coupling these techniques with MS has resulted in a descriptive account of the identification and quantification of fungal endophyte derived bioactive compounds. This paper emphasizes the workflows of the above-mentioned techniques, their advancement, and future directions to study the unraveled area of chemistry of fungal endophyte-derived bioactive compounds.

Analytical Platforms for Mass Spectrometry-Based Metabolomics of Polar and Ionizable Metabolites

Metabolomics studies rely on the availability of suitable analytical platforms to determine a vast collection of chemically diverse metabolites in complex biospecimens. Liquid chromatography-mass spectrometry operated under reversed-phase conditions is the most commonly used platform in metabolomics, which offers extensive coverage for nonpolar and moderately polar compounds. However, complementary techniques are required to obtain adequate separation of polar and ionic metabolites, which are involved in several fundamental metabolic pathways. This chapter focuses on the main mass-spectrometry-based analytical platforms used to determine polar and/or ionizable compounds in metabolomics (GC-MS, HILIC-MS, CE-MS, IPC-MS, and IC-MS). Rather than comprehensively describing recent applications related to GC-MS, HILIC-MS, and CE-MS, which have been covered in a regular basis in the literature, a brief discussion focused on basic principles, main strengths, limitations, as well as future trends is presented in this chapter, and only key applications with the purpose of illustrating important analytical aspects of each platform are highlighted. On the other hand, due to the relative novelty of IPC-MS and IC-MS in the metabolomics field, a thorough compilation of applications for these two techniques is presented here.

Free Amino Acid Alterations in Patients with Gynecological and Breast Cancer: A Review

Gynecological and breast cancers still remain a significant health problem worldwide. Diagnostic methods are not sensitive and specific enough to detect the disease at an early stage. During carcinogenesis and tumor progression, the cellular need for DNA and protein synthesis increases leading to changes in the levels of amino acids. An important role of amino acids in many biological pathways, including biosynthesis of proteins, nucleic acids, enzymes, etc., which serve as an energy source and maintain redox balance, has been highlighted in many research articles. The aim of this review is a detailed analysis of the literature on metabolomic studies of gynecology and breast cancers with particular emphasis on alterations in free amino acid profiles. The work includes a brief overview of the metabolomic methodology and types of biological samples used in the studies. Special attention was paid to the possible role of selected amino acids in the carcinogenesis, especially proline and amino acids related to its metabolism. There is a clear need for further research and multiple external validation studies to establish the role of amino acid profiling in diagnosing gynecological and breast cancers.

Metabolomics in endometriosis: challenges and perspectives for future studies

Endometriosis is a complex disease characterized by inflammation and the growth of endometrial- like glands and stroma outside the uterine cavity. The pathophysiology of endometriosis is not entirely understood, however, with a prevalence of ~10% of women in their reproductive years, the disease symptoms significantly affect the quality of life of millions of women globally. Metabolomic studies have previously identified specific metabolites that could be a signature of endometriosis. This approach could potentially be used as a non-invasive tool for early diagnosis and provide a better understanding of endometriosis pathophysiology. This review aims to provide insight as to how endometriosis affects the metabolome by reviewing different studies that have used this approach to design follow-up studies. The search query included the term 'endometriosis' in combination with 'metabolomics', 'lipidomics', or 'sphingolipidomics' published between 2012 and 2020. We included studies in humans and animal models. Most studies reported differences in the metabolome of subjects with endometriosis in comparison to healthy controls and used samples taken from serum, endometrial tissue, follicular fluid, urine, peritoneal fluid, or endometrial fluid. Statistically significant metabolites contributed to group separation between patients and healthy controls. Reported metabolites included amino acids, lipids, organic acids, and other organic compounds. Differences in methods, analytical techniques, and the presence of confounding factors can interfere with results and interpretation of data. Metabolomics seems to be a promising tool for identifying significant metabolites in patients with endometriosis. Nonetheless, more investigation is needed in order to understand the significance of the study results.

Lay summary

Endometriosis is a chronic disease affecting the quality of life in one out of every ten women during their reproductive years, causing pain and infertility. It is characterized by inflammation and growth of tissue like the endometrium (uterus lining) outside the uterine cavity. Studies have searched for a predictor of endometriosis-associated changes by observing small molecules necessary for metabolism on a large scale (metabolomics). Metabolomics could serve to resolve one of the biggest challenges that patients with endometriosis face: a delay in diagnosis. In this review, the authors summarize identified potential biomarkers from various bodily fluids and tissues that are characteristic of metabolic processes observed in endometriosis. Biomarkers include cell growth, cell survival, high energy demand, oxidative stress, and fatty acid levels. A metabolomics approach offers promise as a non-invasive tool to identify significant metabolite changes in patients with endometriosis, potentially leading to earlier diagnoses and new opportunities for back-translational strategies.

Advances in bulk and single-cell multi-omics approaches for systems biology and precision medicine

Multi-omics allows the systematic understanding of the information flow across different omics layers, while single omics can mainly reflect one aspect of the biological system. The advancement of bulk and single-cell sequencing technologies and related computational methods for multi-omics largely facilitated the development of system biology and precision medicine. Single-cell approaches have the advantage of dissecting cellular dynamics and heterogeneity, whereas traditional bulk technologies are limited to individual/population-level investigation. In this review, we first summarize the technologies for producing bulk and single-cell multi-omics data. Then, we survey the computational approaches for integrative analysis of bulk and single-cell multimodal data, respectively. Moreover, the databases and data storage for multi-omics, as well as the tools for visualizing multimodal data are summarized. We also outline the integration between bulk and single-cell data, and discuss the applications of multi-omics in precision medicine. Finally, we present the challenges and perspectives for multi-omics development.

1H-NMR metabolomics-based classification of Japanese sake and comparative metabolome analysis by gas chromatography-mass spectrometry

Six categories of Japanese sake have been established by the National Tax Agency of Japan. In this system, the rice polishing ratio and the addition of alcohol are the main criteria for classification. The most common nuclear magnetic resonance (NMR) spectrometry method is ¹H-NMR, and has higher throughput than gas chromatography-mass spectrometry (GC-MS) or liquid chromatography-mass spectrometry (LC-MS) analysis due to its short measurement time, easy sample preparation, and high reproducibility. However, owing to the production of dominant ethanol signals, metabolome analyses have not been used for classifying Japanese sake using ¹H-NMR. In this study, a technique to selectively suppress ethanol signals was used to classify Japanese sake by ¹H-NMR, and a model was constructed to predict the rice polishing ratio. The results were compared to those obtained by GC-MS. The suppression of ethanol signals enabled the detection of trace components by ¹H-NMR. In a principal component analysis (PCA) score plot of ¹H-NMR spectra with ethanol signal suppression, PC1 was associated with both the addition of alcohol and the rice polishing ratio. Additionally, the separation of samples observed was similar when PCA score plots of ¹H-NMR and GC-MS data were compared. Similarly, to predict the rice polishing ratio using partial least squares regression analysis, a model was constructed using ¹H-NMR data, and showed nearly similar values for precision and predictive performance with the model constructed using GC-MS data. These results suggest that metabolomic analyses of Japanese sake based on ¹H-NMR spectral patterns may be useful for classification.

Shrimp count size: GC/MS-based metabolomics approach and quantitative descriptive analysis (QDA) reveal the importance of size in white leg shrimp (Litopenaeus vannamei)

INTRODUCTION

"Count size" is a term used to represent the number of shrimps in one pound or kilogram that applies globally in the shrimp industry. Based on shrimp body weight, count sizes range over the smallest (> 70) up to the largest size (U15) of shrimp. Large shrimps are considered highly palatable; therefore, they are priced higher than the small shrimps. However, the pricing of shrimp has not been based on scientific findings since there have been no studies reporting the correlation between shrimp quality and shrimp size.

OBJECTIVE

In this study, we aimed to investigate the importance of shrimp size in terms of metabolite profile and sensory properties.

METHODS

Nine groups of Litopenaeus vannamei, categorized based on their body weight similarity, were collected from various sampling sites regardless of the difference in days of culture (count size 16/20, 21/25, 26/30, 41/50, and 51/60). Gas chromatography/mass spectrometry (GC/MS)-based metabolomics analysis was employed to characterize their metabolite profiles. Furthermore, a robust PLS regression model was constructed to predict the shrimp size using metabolome data. Following this, the difference in sensory attributes among commercial shrimp count sizes 21/25-41/50 was confirmed using quantitative descriptive analysis (QDA).

RESULTS

Small shrimp (> 70-51/60) had higher accumulation of proteinogenic and non-proteinogenic amino acids, sugars, and organic acids compared to large shrimps (41/50-16/20). The QDA of commercial count sizes (21/25-41/50) performed by trained panelists showed that sweetness, juiciness, crispness, and red color attributes increased with an increase in shrimp size. Based on the PLS model, proline as a sweet-tasting metabolite also showed an increased level along with the shrimp size.

CONCLUSIONS

These findings demonstrate the importance of shrimp count size with regard to shrimp quality.

Metabolomics: The Stethoscope for the Twenty-First Century

Metabolomics encompasses the systematic identification and quantification of all metabolic products in the human body. This field could provide clinicians with novel sets of diagnostic biomarkers for disease states in addition to quantifying treatment response to medications at an individualized level. This literature review aims to highlight the technology underpinning metabolic profiling, identify potential applications of metabolomics in clinical practice, and discuss the translational challenges that the field faces. We searched PubMed, MEDLINE, and EMBASE for primary and secondary research articles regarding clinical applications of metabolomics. Metabolic profiling can be performed using mass spectrometry and nuclear magnetic resonance-based techniques using a variety of biological samples. This is carried out in vivo or in vitro following careful sample collection, preparation, and analysis. The potential clinical applications constitute disruptive innovations in their respective specialities, particularly oncology and metabolic medicine. Outstanding issues currently preventing widespread clinical use are scalability of data interpretation, standardization of sample handling practice, and e-infrastructure. Routine utilization of metabolomics at a patient and population level will constitute an integral part of future healthcare provision.

Metabolomics applied in the study of emerging arboviruses caused by Aedes aegypti mosquitoes: A review

Arboviruses, such as chikungunya, dengue, yellow fever, and zika, caused by the bite of the Aedes aegypti mosquito, have been a frequent public health problem, with a high incidence of outbreaks in tropical and subtropical countries. These diseases are easily confused with a flu-like illness and present very similar symptoms, difficult to distinguish, and treat appropriately. The effects that these infections cause in the organism are fundamentally derived from complex metabolic processes. A prominent area of science that investigates the changes in the metabolism of complex organisms is the metabolomics. Metabolomics measures the metabolites produced or altered in biological organisms, through the use of robust analytical platforms, such as separation techniques hyphenated with mass spectrometry, combined with bioinformatics. This review article presents an overview of the basic concepts of metabolomics workflow and advances in this field, and compiles research articles that use this omic approach to study these arboviruses. In this context, the metabolomics is applied to search new therapies, understand the viral replication mechanisms, and access the host-virus interactions.

Discrimination of Mentha species grown in different geographical areas of Algeria using 1H-NMR-based metabolomics

¹H-NMR-based metabolomics have been applied to identify potential NMR-markers and biomarkers capable of distinguishing, qualifying and classifying three Mentha species:- Mentha pulegium L., Mentha × rotundifolia (L.) Huds., Mentha spicata L., and their ecotypes. Samples of the 3 species were collected in seven different locations in Algeria, with the aim to establish a quality control protocol based on the use of NMR fingerprint profiles of polar extracts. NMR data indicate that the identification of the Mentha genus can be confirmed by the presence of the doublet proton signals with identical coupling constants at δ 7.49 (d, 15.9 Hz) and δ 6.29 (d, 15.9 Hz); these correspond to the protons of the double-bond conjugated to the ester group of rosmarinic acid, a bioactive compound found in all three species. Differences in NMR proton chemical shifts and/or signal intensities were clearly demonstrated on the orthogonal projections to latent structures discriminating analysis (OPLS-DA). Several potential biomarkers discriminating the three Mentha species were originated using S-plots, loading score plots, NMR data analysis and literature search. These discriminating signals point to glycosylated flavonols, oxygenated terpenoids and hydrocarbon terpenoids to distinguish M. pulegium, M. × rotundifolia and M. spicata, respectively. Within the same species, Principal Component Analysis (PCA) scores clearly discriminated the metabolite content according to regions in which the plants were grown. The 6 zones in which Mentha pulegium samples were harvested were clearly separated along either or both PC1 and PC2; by contrast, the harvesting locations were divided into two groups along PC1 for both M. × rotundifolia and M. spicata. The total antioxidant activity of the Mentha species was impacted by the abiotic factors of the different regions.

Effect of koji starter on metabolites in Japanese alcoholic beverage sake made from the sake rice Koshitanrei

In sake brewing, the steamed rice is used in 2 ways, added to sake-mash and making rice-koji. Rice-koji is made from the steamed rice by using koji starter, and its quality is an important determinant of the aroma/taste of sake. The sake rice Koshitanrei (KOS) was developed in Niigata Prefecture by crossing 2 sake rice varieties, Gohyakumangoku and Yamadanishiki. Recently, we reported the characteristic components/metabolites in sake made from KOS by conducting metabolome analysis using UPLC-QTOF-MS. In this study, to investigate the effect of koji starter and sake rice cultivars on the sake metabolites, we performed small-scale sake-making tests using the above 3 rice cultivars and 3 koji starters. Finally, we demonstrated that some of the characteristic components/metabolites of sake from KOS are affected by the koji starter. Thus, in addition to rice cultivar, koji starter plays an important role for establishment/maintenance of the quality of the final product.

Milk Metabolomics Reveals Potential Biomarkers for Early Prediction of Pregnancy in Buffaloes Having Undergone Artificial Insemination

This study aimed to identify potential biomarkers for early pregnancy diagnosis in buffaloes subjected to artificial insemination (AI). The study was carried out on 10 pregnant and 10 non-pregnant buffaloes that were synchronized by Ovsynch-Timed Artificial Insemination Program and have undergone the first AI. Furthermore, milk samples were individually collected ten days before AI (the start of the synchronization treatment), on the day of AI, day 7 and 18 after AI, and were analyzed by LC-MS. Statistical analysis was carried out by using Mass Profile Professional (Agilent Technologies, Santa Clara, CA, USA). Metabolomic analysis revealed the presence of several metabolites differentially expressed between pregnant and non-pregnant buffaloes. Among these, a total of five metabolites were identified by comparison with an online database and a standard compound as acetylcarnitine (3-Acetoxy-4-(trimethylammonio)butanoate), arginine-succinic acid hydrate, 5'-O-{[3-({4-[(3aminopropyl)amino]butyl}amino)propyl]carbamoyl}-2'-deoxyadenosine, N-(1-Hydroxy-2-hexadecanyl)pentadecanamide, and N-[2,3-Bis(dodecyloxy)propyl]-L-lysinamide). Interestingly, acetylcarnitine was dominant in milk samples collected from non-pregnant buffaloes. The results obtained from milk metabolic profile and hierarchical clustering analysis revealed significant differences between pregnant and non-pregnant buffaloes, as well as in the metabolite expression. Overall, the findings indicate the potential of milk metabolomics as a powerful tool to identify biomarkers of early pregnancy in buffalo undergoing AI.