Metabolomic screening of radioiodine refractory thyroid cancer patients and the underlying chemical mechanism of iodine resistance.

Radioiodine refractory (RAIR) patients do not benefit from iodine-131 therapy. Thus, timely identification of RAIR patients is critical for avoiding ineffective radioactive iodine therapy. In addition, determining the causes of iodine resistance will facilitate the development of novel treatment strategies. This study was comprised of 20 RAIR and 14 non-radioiodine refractory (non-RAIR) thyroid cancer patients. Liquid chromatography-mass spectrometry was used to identify differences in the serum metabolites of RAIR and non-RAIR patients. In addition, chemical assays were performed to determine the effects of the differential metabolites on iodine uptake. Metabolic pathway enrichment analysis of the differential metabolites revealed significant differences in the phenylalanine and tyrosine metabolic pathways. Notably, quinate and shikimic acid, metabolites of the tyrosine pathway, were significantly increased in the RAIR group. In contrast, the phenylalanine pathway metabolites, hippuric acid and 2-phenylacetamide, were markedly decreased in the RAIR group. Thyroid peroxidase plays an important role in catalyzing the iodination of tyrosine residues, while the ionic state of iodine promotes the iodination reaction. Quinate, shikimic acid, hippuric acid, and 2-phenylacetamide were found to be involved in the iodination of tyrosine, which is a key step in thyroid hormone synthesis. Specifically, quinate and shikimic acid were found to inhibit iodination, while hippuric acid and 2-phenylacetamide promoted iodination. Abnormalities in phenylalanine and tyrosine metabolic pathways are closely associated with iodine resistance. Tyrosine is required for thyroid hormone synthesis and could be a potential cause of iodine resistance.

Elucidating the role of exogenous melatonin in mitigating alkaline stress in soybeans across different growth stages: a transcriptomic and metabolomic approach.

BACKGROUND: Soybean (Glycine max), a vital grain and oilseed crop, serves as a primary source of plant protein and oil. Soil salinization poses a significant threat to soybean planting, highlighting the urgency to improve soybean resilience and adaptability to saline stress. Melatonin, recently identified as a key plant growth regulator, plays crucial roles in plant growth, development, and responses to environmental stress. However, the potential of melatonin to mitigate alkali stress in soybeans and the underlying mechanisms remain unclear. RESULTS: This study investigated the effects of exogenous melatonin on the soybean cultivar Zhonghuang 13 under alkaline stress. We employed physiological, biochemical, transcriptomic, and metabolomic analyses throughout both vegetative and pod-filling growth stages. Our findings demonstrate that melatonin significantly counteracts the detrimental effects of alkaline stress on soybean plants, promoting plant growth, photosynthesis, and antioxidant capacity. Transcriptomic analysis during both growth stages under alkaline stress, with and without melatonin treatment, identified 2,834 and 549 differentially expressed genes, respectively. These genes may play a vital role in regulating plant adaptation to abiotic stress. Notably, analysis of phytohormone biosynthesis pathways revealed altered expression of key genes, particularly in the ARF (auxin response factor), AUX/IAA (auxin/indole-3-acetic acid), and GH3 (Gretchen Hagen 3) families, during the early stress response. Metabolomic analysis during the pod-filling stage identified highly expressed metabolites responding to melatonin application, such as uteolin-7-O-(2''-O-rhamnosyl)rutinoside and Hederagenin-3-O-glucuronide-28-O-glucosyl(1,2)glucoside, which helped alleviate the damage caused by alkali stress. Furthermore, we identified 183 differentially expressed transcription factors, potentially playing a critical role in regulating plant adaptation to abiotic stress. Among these, the gene SoyZH13_04G073701 is particularly noteworthy as it regulates the key differentially expressed metabolite, the terpene metabolite Hederagenin-3-O-glucuronide-28-O-glucosyl(1,2)glucoside. WGCNA analysis identified this gene (SoyZH13_04G073701) as a hub gene, positively regulating the crucial differentially expressed metabolite of terpenoids, Hederagenin-3-O-glucuronide-28-O-glucosyl(1,2)glucoside. Our findings provide novel insights into how exogenous melatonin alleviates alkali stress in soybeans at different reproductive stages. CONCLUSIONS: Integrating transcriptomic and metabolomic approaches, our study elucidates the mechanisms by which exogenous melatonin ameliorates the inhibitory effects of alkaline stress on soybean growth and development. This occurs through modulation of biosynthesis pathways for key compounds, including terpenes, flavonoids, and phenolics. Our findings provide initial mechanistic insights into how melatonin mitigates alkaline stress in soybeans, offering a foundation for molecular breeding strategies to enhance salt-alkali tolerance in this crop.

Effects of hibernation on two important contractile tissues in tibetan frogs, Nanorana parkeri: a perspective from transcriptomics and metabolomics approaches.

BACKGROUND: In response to seasonal cold and food shortage, the Xizang plateau frogs, Nanorana parkeri (Anura: Dicroglossidae), enter a reversible hypometabolic state where heart rate and oxygen consumption in skeletal muscle are strongly suppressed. However, the effect of winter hibernation on gene expression and metabolic profiling in these two tissues remains unknown. In the present study, we conducted transcriptomic and metabolomic analyses of heart and skeletal muscle from summer- and winter-collected N. parkeri to explore mechanisms involved in seasonal hibernation. RESULTS: We identified 2407 differentially expressed genes (DEGs) in heart and 2938 DEGs in skeletal muscle. Enrichment analysis showed that shared DEGs in both tissues were enriched mainly in translation and metabolic processes. Of these, the expression of genes functionally categorized as "response to stress", "defense mechanisms", or "muscle contraction" were particularly associated with hibernation. Metabolomic analysis identified 24 and 22 differentially expressed metabolites (DEMs) in myocardium and skeletal muscle, respectively. In particular, pathway analysis showed that DEMs in myocardium were involved in the pentose phosphate pathway, glycerolipid metabolism, pyruvate metabolism, citrate cycle (TCA cycle), and glycolysis/gluconeogenesis. By contrast, DEMs in skeletal muscle were mainly involved in amino acid metabolism. CONCLUSIONS: In summary, natural adaptations of myocardium and skeletal muscle in hibernating N. parkeri involved transcriptional alterations in translation, stress response, protective mechanisms, and muscle contraction processes as well as metabolic remodeling. This study provides new insights into the transcriptional and metabolic adjustments that aid winter survival of high-altitude frogs N. parkeri.

Exploring disease-specific metabolite signatures in hereditary angioedema patients.

Introduction: Hereditary angioedema (HAE) is a rare, life-threatening autosomal dominant genetic disorder caused by a deficient and/or dysfunctional C1 esterase inhibitor (C1-INH) (type 1 and type 2) leading to recurrent episodes of edema. This study aims to explore HAE patients' metabolomic profiles and identify novel potential diagnostic biomarkers for HAE. The study also examined distinguishing HAE from idiopathic angioedema (AE). Methods: Blood plasma samples from 10 HAE (types 1/2) patients, 15 patients with idiopathic AE, and 20 healthy controls were collected in Latvia and analyzed using LC-MS based targeted metabolomics workflow. T-test and fold change calculation were used to identify metabolites with significant differences between diseases and control groups. ROC analysis was performed to evaluate metabolite based classification model. Results: A total of 33 metabolites were detected and quantified. The results showed that isovalerylcarnitine, cystine, and hydroxyproline were the most significantly altered metabolites between the disease and control groups. Aspartic acid was identified as a significant metabolite that could differentiate between HAE and idiopathic AE. The mathematical combination of metabolites (hydroxyproline * cystine)/(creatinine * isovalerylcarnitine) was identified as the diagnosis signature for HAE. Furthermore, glycine/asparagine ratio could differentiate between HAE and idiopathic AE. Conclusion: Our study identified isovalerylcarnitine, cystine, and hydroxyproline as potential biomarkers for HAE diagnosis. Identifying new biomarkers may offer enhanced prospects for accurate, timely, and economical diagnosis of HAE, as well as tailored treatment selection for optimal patient care.

Widely-targeted metabolomics and transcriptomics identify metabolites associated with flowering regulation of Choy Sum.

Choy Sum, a stalk vegetable highly valued in East and Southeast Asia, is characterized by its rich flavor and nutritional profile. Metabolite accumulation is a key factor in Choy Sum stalk development; however, no research has focused on metabolic changes during the development of Choy Sum, especially in shoot tip metabolites, and their effects on growth and flowering. Therefore, in the present study, we used a widely targeted metabolomic approach to analyze metabolites in Choy Sum stalks at the seedling (S1), bolting (S3), and flowering (S5) stages. In total, we identified 493 metabolites in 31 chemical categories across all three developmental stages. We found that the levels of most carbohydrates and amino acids increased during stalk development and peaked at S5. Moreover, the accumulation of amino acids and their metabolites was closely related to G6P, whereas the expression of flowering genes was closely related to the content of T6P, which may promote flowering by upregulating the expressions of BcSOC1, BcAP1, and BcSPL5. The results of this study contribute to our understanding of the relationship between the accumulation of stem tip substances during development and flowering and of the regulatory mechanisms of stalk development in Choy Sum and other related species.

Transcriptome and metabolome analyses reveal molecular insights into waterlogging tolerance in Barley.

Waterlogging stress is one of the major abiotic stresses affecting the productivity and quality of many crops worldwide. However, the mechanisms of waterlogging tolerance are still elusive in barley. In this study, we identify key differentially expressed genes (DEGs) and differential metabolites (DM) that mediate distinct waterlogging tolerance strategies in leaf and root of two barley varieties with contrasting waterlogging tolerance under different waterlogging treatments. Transcriptome profiling revealed that the response of roots was more distinct than that of leaves in both varieties, in which the number of downregulated genes in roots was 7.41-fold higher than that in leaves of waterlogging sensitive variety after 72 h of waterlogging stress. We also found the number of waterlogging stress-induced upregulated DEGs in the waterlogging tolerant variety was higher than that of the waterlogging sensitive variety in both leaves and roots in 1 h and 72 h treatment. This suggested the waterlogging tolerant variety may respond more quickly to waterlogging stress. Meanwhile, phenylpropanoid biosynthesis pathway was identified to play critical roles in waterlogging tolerant variety by improving cell wall biogenesis and peroxidase activity through DEGs such as Peroxidase (PERs) and Cinnamoyl-CoA reductases (CCRs) to improve resistance to waterlogging. Based on metabolomic and transcriptomic analysis, we found the waterlogging tolerant variety can better alleviate the energy deficiency via higher sugar content, reduced lactate accumulation, and improved ethanol fermentation activity compared to the waterlogging sensitive variety. In summary, our results provide waterlogging tolerance strategies in barley to guide the development of elite genetic resources towards waterlogging-tolerant crop varieties.

Gut microbiota, blood metabolites, and left ventricular diastolic dysfunction in US Hispanics/Latinos.

BACKGROUND: Left ventricular diastolic dysfunction (LVDD) is an important precursor of heart failure (HF), but little is known about its relationship with gut dysbiosis and microbial-related metabolites. By leveraging the multi-omics data from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a study with population at high burden of LVDD, we aimed to characterize gut microbiota associated with LVDD and identify metabolite signatures of gut dysbiosis and incident LVDD. RESULTS: We included up to 1996 Hispanic/Latino adults (mean age: 59.4 years; 67.1% female) with comprehensive echocardiography assessments, gut microbiome, and blood metabolome data. LVDD was defined through a composite criterion involving tissue Doppler assessment and left atrial volume index measurements. Among 1996 participants, 916 (45.9%) had prevalent LVDD, and 212 out of 594 participants without LVDD at baseline developed incident LVDD over a median 4.3 years of follow-up. Using multivariable-adjusted analysis of compositions of microbiomes (ANCOM-II) method, we identified 7 out of 512 dominant gut bacterial species (prevalence > 20%) associated with prevalent LVDD (FDR-q < 0.1), with inverse associations being found for Intestinimonas_massiliensis, Clostridium_phoceensis, and Bacteroide_coprocola and positive associations for Gardnerella_vaginali, Acidaminococcus_fermentans, Pseudomonas_aeruginosa, and Necropsobacter_massiliensis. Using multivariable adjusted linear regression, 220 out of 669 circulating metabolites with detection rate > 75% were associated with the identified LVDD-related bacterial species (FDR-q < 0.1), with the majority being linked to Intestinimonas_massiliensis, Clostridium_phoceensis, and Acidaminococcus_fermentans. Furthermore, 46 of these bacteria-associated metabolites, mostly glycerophospholipids, secondary bile acids, and amino acids, were associated with prevalent LVDD (FDR-q < 0.1), 21 of which were associated with incident LVDD (relative risk ranging from 0.81 [p = 0.001, for guanidinoacetate] to 1.25 [p = 9 × 10-5, for 1-stearoyl-2-arachidonoyl-GPE (18:0/20:4)]). The inclusion of these 21 bacterial-related metabolites significantly improved the prediction of incident LVDD compared with a traditional risk factor model (the area under the receiver operating characteristic curve [AUC] = 0.73 vs 0.70, p = 0.001). Metabolite-based proxy association analyses revealed the inverse associations of Intestinimonas_massilliensis and Clostridium_phoceensis and the positive association of Acidaminococcus_fermentans with incident LVDD. CONCLUSION: In this study of US Hispanics/Latinos, we identified multiple gut bacteria and related metabolites linked to LVDD, suggesting their potential roles in this preclinical HF entity. Video Abstract.

The impact of androgen levels on serum metabolic profiles in patients with polycystic ovary syndrome.

OBJECTIVE: This study aimed to investigate the impact of serum androgen levels on metabolic profiles in patients with polycystic ovary syndrome (PCOS). METHODS: We included 216 patients with PCOS and 216 healthy individuals selected as the control group. According to the measured serum androgen levels, patients with PCOS were divided into the hyperandrogenism group and non-hyperandrogenism group. Clinical metabolic indicators were assessed and compared between the two groups. Additionally, we assessed the correlation between androgen levels and clinical metabolic indicators. RESULTS: The body mass index, waist-to-hip ratio, mF-G score, and acne score, as well as T, LH, LSH/FSH, FPG, Cr, UA, TG, TC, and LDL-C levels were significantly higher in the PCOS group than in the control group. The incidence of hyperandrogenism and clinical hyperandrogenism in the PCOS group was significantly higher than that in the control group. Regarding clinical hyperandrogenism, hirsutism, acne, and acanthosis nigricans were significantly more common in the PCOS group than in the control group. Serum androgen levels were significantly correlated with the mF-G score, acne score, FSH, glucose concentration at 30 min, glucose concentration at 60 min, glucose concentration at 120 min, FINS, N120, HOMA-IR, HbA1c, AUCG, UA, TG, and hHDL-Clevels. CONCLUSION: Elevated serum androgen levels are commonly observed in patients with PCOS and are associated with multiple metabolic abnormalities. Therefore, it is recommended to regularly monitor glucose and lipid metabolism-related indicators in patients with PCOS who have elevated androgen levels.

Integrated multi-omic approach reveals the effect of a Graminaceae-derived biostimulant and its lighter fraction on salt-stressed lettuce plants.

Plant biostimulants are widely applied in agriculture for their ability to improve plant fitness. In the present work, the impact of Graminaceae-derived protein hydrolysate (P) and its lighter molecular fraction F3 (< 1 kDa) on lettuce plants, subjected to either no salt or high salt conditions, was investigated through the combination of metabolomics and transcriptomics. The results showed that both treatments significantly modulated the transcriptome and metabolome of plants under salinity stress, highlighting an induction of the hormonal response. Nevertheless, P and F3 also displayed several peculiarities. F3 specifically modulated the response to ethylene and MAPK signaling pathway, whereas P treatment induced a down-accumulation of secondary metabolites, albeit genes controlling the biosynthesis of osmoprotectants and antioxidants were up-regulated. Moreover, according with the auxin response modulation, P promoted cell wall biogenesis and plasticity in salt-stressed plants. Notably, our data also outlined an epigenetic control of gene expression induced by P treatment. Contrarily, experimental data are just partially in agreement when not stressed plants, treated with P or F3, were considered. Indeed, the reduced accumulation of secondary metabolites and the analyses of hormone pathways modulation would suggest a preferential allocation of resources towards growth, that is not coherent with the down-regulation of the photosynthetic machinery, the CO2 assimilation rate and leaves biomass. In conclusion, our data demonstrate that, although they might activate different mechanisms, both the P and F3 can result in similar benefits, as far as the accumulation of protective osmolytes and the enhanced tolerance to oxidative stress are concerned. Notably, the F3 fraction exhibits slightly greater growth promotion effects under high salt conditions. Most importantly, this research further corroborates that biostimulants' mode of action is dependent on plants' physiological status and their composition, underscoring the importance of investigating the bioactivity of the different molecular components to design tailored applications for the agricultural practice.

Deciphering the Impact of Defecation Frequency on Gut Microbiome Composition and Diversity.

This study explores the impact of defecation frequency on the gut microbiome structure by analyzing fecal samples from individuals categorized by defecation frequency: infrequent (1-3 times/week, n = 4), mid-frequent (4-6 times/week, n = 7), and frequent (daily, n = 9). Utilizing 16S rRNA gene-based sequencing and LC-MS/MS metabolome profiling, significant differences in microbial diversity and community structures among the groups were observed. The infrequent group showed higher microbial diversity, with community structures significantly varying with defecation frequency, a pattern consistent across all sampling time points. The Ruminococcus genus was predominant in the infrequent group, but decreased with more frequent defecation, while the Bacteroides genus was more common in the frequent group, decreasing as defecation frequency lessened. The infrequent group demonstrated enriched biosynthesis genes for aromatic amino acids and branched-chain amino acids (BCAAs), in contrast to the frequent group, which had a higher prevalence of genes for BCAA catabolism. Metabolome analysis revealed higher levels of metabolites derived from aromatic amino acids and BCAA metabolism in the infrequent group, and lower levels of BCAA-derived metabolites in the frequent group, consistent with their predicted metagenomic functions. These findings underscore the importance of considering stool consistency/frequency in understanding the factors influencing the gut microbiome.

Plasma Metabolite Profiling in the Search for Early-Stage Biomarkers for Lung Cancer: Some Important Breakthroughs.

Lung cancer is the leading cause of cancer-related mortality worldwide. In order to improve its overall survival, early diagnosis is required. Since current screening methods still face some pitfalls, such as high false positive rates for low-dose computed tomography, researchers are still looking for early biomarkers to complement existing screening techniques in order to provide a safe, faster, and more accurate diagnosis. Biomarkers are biological molecules found in body fluids, such as plasma, that can be used to diagnose a condition or disease. Metabolomics has already been shown to be a powerful tool in the search for cancer biomarkers since cancer cells are characterized by impaired metabolism, resulting in an adapted plasma metabolite profile. The metabolite profile can be determined using nuclear magnetic resonance, or NMR. Although metabolomics and NMR metabolite profiling of blood plasma are still under investigation, there is already evidence for its potential for early-stage lung cancer diagnosis, therapy response, and follow-up monitoring. This review highlights some key breakthroughs in this research field, where the most significant biomarkers will be discussed in relation to their metabolic pathways and in light of the altered cancer metabolism.

Anatomical and Metabolome Features of Haloxylon aphyllum and Haloxylon persicum Elucidate the Resilience against Gall-Forming Insects.

Globally, gall-forming insects significantly contribute to the degradation of desert ecosystems. Recent studies have demonstrated that Haloxylon persicum suffers less damage from gall-formers compared to Haloxylon aphyllum. However, the mechanisms driving the long-term metabolic responses of these species to gall-forming biotic stress in their natural environment remain unclear. The current study comparatively analyzes the anatomical features and metabolomic changes in H. aphyllum and H. persicum damaged by gall-forming insects. This research aimed to uncover potential metabolic tolerance mechanisms through GC-MS analysis. The study findings indicate that gall-forming insects cause a reduction in nearly all the anatomical structures of Haloxylon shoots, with the effects being less severe in H. persicum than in H. aphyllum. Thus, the metabolic pathways responsible for the biosynthesis of biologically active substances that enhance resistance to gall inducers were different, specifically in H. aphyllum-the biosynthesis of fatty acids (+their derivatives) and γ-tocopherol (vitamin E) and H. persicum-the biosynthesis of fatty acids (+their derivatives), dialkyl ethers, carbohydrates (+their derivatives), aromatic acid derivatives, phytosterols, γ-tocopherol (vitamin E), phenols, and terpenoids. The results suggest that the modulation of metabolic pathways under biotic stress plays a crucial role in the enhanced survival and growth of H. persicum.

Physiological, Transcriptome, and Metabolome Analyses Reveal the Tolerance to Cu Toxicity in Red Macroalgae Gracilariopsis lemaneiformis.

Heavy metal copper (Cu) will inevitably impact the marine macroalgae Gracilariopsis lemaneiformis (G. lemaneiformis), which is a culture of economic importance along China's coastline. In this study, the detoxification mechanism of Cu stress on G. lemaneiformis was revealed by assessing physiological indicators in conjunction with transcriptome and metabolome analyses at 1 d after Cu stress. Our findings revealed that 25 µM Cu stimulated ROS synthesis and led to the enzymatic oxidation of arachidonic acid residues. This process subsequently impeded G. lemaneiformis growth by suppressing photosynthesis, nitrogen metabolism, protein synthesis, etc. The entry of Cu ions into the algae was facilitated by ZIPs and IRT transporters, presenting as Cu2+. Furthermore, there was an up-regulation of Cu efflux transporters HMA5 and ABC family transporters to achieve compartmentation to mitigate the toxicity. The results revealed that G. lemaneiformis elevated the antioxidant enzyme superoxide dismutase and ascorbate-glutathione cycle to maintain ROS homeostasis. Additionally, metabolites such as flavonoids, 3-O-methylgallic acid, 3-hydroxy-4-keto-gama-carotene, and eicosapentaenoic acid were up-regulated compared with the control, indicating that they might play roles in response to Cu stress. In summary, this study offers a comprehensive insight into the detoxification mechanisms driving the responses of G. lemaneiformis to Cu exposure.

Metabolic network analysis of pre-ASD newborns and 5-year-old children with autism spectrum disorder.

Classical metabolomic and new metabolic network methods were used to study the developmental features of autism spectrum disorder (ASD) in newborns (n = 205) and 5-year-old children (n = 53). Eighty percent of the metabolic impact in ASD was caused by 14 shared biochemical pathways that led to decreased anti-inflammatory and antioxidant defenses, and to increased physiologic stress molecules like lactate, glycerol, cholesterol, and ceramides. CIRCOS plots and a new metabolic network parameter, V ° net, revealed differences in both the kind and degree of network connectivity. Of 50 biochemical pathways and 450 polar and lipid metabolites examined, the developmental regulation of the purine network was most changed. Purine network hub analysis revealed a 17-fold reversal in typically developing children. This purine network reversal did not occur in ASD. These results revealed previously unknown metabolic phenotypes, identified new developmental states of the metabolic correlation network, and underscored the role of mitochondrial functional changes, purine metabolism, and purinergic signaling in autism spectrum disorder.

Metabolome-associated psychological comorbidities improvement in irritable bowel syndrome patients receiving a probiotic.

Our recent randomized, placebo-controlled study in Irritable Bowel Syndrome (IBS) patients with diarrhea or alternating bowel habits showed that the probiotic Bifidobacterium longum (BL) NCC3001 improves depression scores and decreases brain emotional reactivity. However, the involved metabolic pathways remain unclear. This analysis aimed to investigate the biochemical pathways underlying the beneficial effects of BL NCC3001 using metabolomic profiling. Patients received probiotic (1x 1010CFU, n=16) or placebo (n=19) daily for 6 weeks. Anxiety and depression were measured using the Hospital Anxiety and Depression Scale. Brain activity in response to negative emotional stimuli was assessed by functional Magnetic Resonance Imaging. Probiotic fecal abundance was quantified by qPCR. Quantitative measurement of specific panels of plasma host-microbial metabolites was performed by mass spectrometry-based metabolomics. Probiotic abundance in feces was associated with improvements in anxiety and depression scores, and a decrease in amygdala activation. The probiotic treatment increased the levels of butyric acid, tryptophan, N-acetyl tryptophan, glycine-conjugated bile acids, and free fatty acids. Butyric acid concentration correlated with lower anxiety and depression scores, and decreased amygdala activation. Furthermore, butyric acid concentration correlated with the probiotic abundance in feces. In patients with non-constipation IBS, improvements in psychological comorbidities and brain emotional reactivity were associated with an increased abundance of BL NCC3001 in feces and specific plasma metabolites, mainly butyric acid. These findings suggest the importance of a probiotic to thrive in the gut and highlight butyric acid as a potential biochemical marker linking microbial metabolism with beneficial effects on the gut-brain axis.

Unravelling the metabolomic diversity of pigmented and non-pigmented traditional rice from Tamil Nadu, India.

Rice metabolomics is widely used for biomarker research in the fields of pharmacology. As a consequence, characterization of the variations of the pigmented and non-pigmented traditional rice varieties of Tamil Nadu is crucial. These varieties possess fatty acids, sugars, terpenoids, plant sterols, phenols, carotenoids and other compounds that plays a major role in achieving sustainable development goal 2 (SDG 2). Gas-chromatography coupled with mass spectrometry was used to profile complete untargeted metabolomics of Kullkar (red colour) and Milagu Samba (white colour) for the first time and a total of 168 metabolites were identified. The metabolite profiles were subjected to data mining processes, including principal component analysis (PCA), Orthogonal Partial Least Square Discrimination Analysis (OPLS-DA) and Heat map analysis. OPLS-DA identified 144 differential metabolites between the 2 rice groups, variable importance in projection (VIP) ≥ 1 and fold change (FC) ≥ 2 or FC ≤ 0.5. Volcano plot (64 down regulated, 80 up regulated) was used to illustrate the differential metabolites. OPLS-DA predictive model showed good fit (R2X = 0.687) and predictability (Q2 = 0.977). The pathway enrichment analysis revealed the presence of three distinct pathways that were enriched. These findings serve as a foundation for further investigation into the function and nutritional significance of both pigmented and non-pigmented rice grains thereby can achieve the SDG 2.

Identification of metabolic components of carotid plaque in high-risk patients utilizing liquid chromatography-tandem mass spectrometry.

OBJECTIVE: Carotid atherosclerosis is a chronic progressive vascular disease that can be complicated by stroke in severe cases. Prompt diagnosis and treatment of high-risk patients are quite difficult due to the lack of reliable clinical biomarkers. This study aimed to explore potential plaque metabolic markers of stroke-prone risk and relevant targets for pharmacological intervention. METHOD: Carotid intima and plaque sample tissues were obtained from 20 patients with cerebrovascular symptoms of carotid origin. An untargeted metabolomics approach based on liquid chromatography-tandem mass spectrometry was utilized to characterize the metabolic profiles of the tissues. Multivariate and univariate analysis tools were used. RESULTS: A total of 154 metabolites were significantly altered in carotid plaque when compared with thickened intima. Of these, 62 metabolites were upregulated, whereas 92 metabolites were downregulated. Support vector machines identified the 15 most important metabolites, such as N-(cyclopropylmethyl)-N'-phenylurea, 9(S)-HOTrE, ACar 12:2, quinoxaline-2,3-dithiol, and l-thyroxine, as biomarkers for high-risk plaques. Metabolic pathway analysis showed that abnormal purine and nucleotide metabolism, amino acid metabolism, glutathione metabolism, and vitamin metabolism may contribute to the occurrence and progression of carotid atherosclerotic plaque. CONCLUSIONS: Our study identifies the biomarkers and related metabolic mechanisms of carotid plaque, which is stroke-prone, and provides insights and ideas for the precise prevention and targeted intervention of the disease.

Energy flux couples sulfur isotope fractionation to proteomic and metabolite profiles in Desulfovibrio vulgaris.

Microbial sulfate reduction is central to the global carbon cycle and the redox evolution of Earth's surface. Tracking the activity of sulfate reducing microorganisms over space and time relies on a nuanced understanding of stable sulfur isotope fractionation in the context of the biochemical machinery of the metabolism. Here, we link the magnitude of stable sulfur isotopic fractionation to proteomic and metabolite profiles under different cellular energetic regimes. When energy availability is limited, cell-specific sulfate respiration rates and net sulfur isotope fractionation inversely covary. Beyond net S isotope fractionation values, we also quantified shifts in protein expression, abundances and isotopic composition of intracellular S metabolites, and lipid structures and lipid/water H isotope fractionation values. These coupled approaches reveal which protein abundances shift directly as a function of energy flux, those that vary minimally, and those that may vary independent of energy flux and likely do not contribute to shifts in S-isotope fractionation. By coupling the bulk S-isotope observations with quantitative proteomics, we provide novel constraints for metabolic isotope models. Together, these results lay the foundation for more predictive metabolic fractionation models, alongside interpretations of environmental sulfur and sulfate reducer lipid-H isotope data.

Characterizing human postprandial metabolic response using multiway data analysis.

INTRODUCTION: Analysis of time-resolved postprandial metabolomics data can improve our understanding of the human metabolism by revealing similarities and differences in postprandial responses of individuals. Traditional data analysis methods often rely on data summaries or univariate approaches focusing on one metabolite at a time. OBJECTIVES: Our goal is to provide a comprehensive picture in terms of the changes in the human metabolism in response to a meal challenge test, by revealing static and dynamic markers of phenotypes, i.e., subject stratifications, related clusters of metabolites, and their temporal profiles. METHODS: We analyze Nuclear Magnetic Resonance (NMR) spectroscopy measurements of plasma samples collected during a meal challenge test from 299 individuals from the COPSAC2000 cohort using a Nightingale NMR panel at the fasting and postprandial states (15, 30, 60, 90, 120, 150, 240 min). We investigate the postprandial dynamics of the metabolism as reflected in the dynamic behaviour of the measured metabolites. The data is arranged as a three-way array: subjects by metabolites by time. We analyze the fasting state data to reveal static patterns of subject group differences using principal component analysis (PCA), and fasting state-corrected postprandial data using the CANDECOMP/PARAFAC (CP) tensor factorization to reveal dynamic markers of group differences. RESULTS: Our analysis reveals dynamic markers consisting of certain metabolite groups and their temporal profiles showing differences among males according to their body mass index (BMI) in response to the meal challenge. We also show that certain lipoproteins relate to the group difference differently in the fasting vs. dynamic state. Furthermore, while similar dynamic patterns are observed in males and females, the BMI-related group difference is observed only in males in the dynamic state. CONCLUSION: The CP model is an effective approach to analyze time-resolved postprandial metabolomics data, and provides a compact but a comprehensive summary of the postprandial data revealing replicable and interpretable dynamic markers crucial to advance our understanding of changes in the metabolism in response to a meal challenge.

Postmortem metabolomics: influence of time since death on the level of endogenous compounds in human femoral blood. Necessary to be considered in metabolome study planning?

INTRODUCTION: The (un)targeted analysis of endogenous compounds has gained interest in the field of forensic postmortem investigations. The blood metabolome is influenced by many factors, and postmortem specimens are considered particularly challenging due to unpredictable decomposition processes. OBJECTIVES: This study aimed to systematically investigate the influence of the time since death on endogenous compounds and its relevance in designing postmortem metabolome studies. METHODS: Femoral blood samples of 427 authentic postmortem cases, were collected at two time points after death (854 samples in total; t1: admission to the institute, 1.3-290 h; t2: autopsy, 11-478 h; median ∆t = 71 h). All samples were analyzed using an untargeted metabolome approach, and peak areas were determined for 38 compounds (acylcarnitines, amino acids, phospholipids, and others). Differences between t2 and t1 were assessed by Wilcoxon signed-ranked test (p < 0.05). Moreover, all samples (n = 854) were binned into time groups (6 h, 12 h, or 24 h intervals) and compared by Kruskal-Wallis/Dunn's multiple comparison tests (p < 0.05 each) to investigate the effect of the estimated time since death. RESULTS: Except for serine, threonine, and PC 34:1, all tested analytes revealed statistically significant changes between t1 and t2 (highest median increase 166%). Unpaired analysis of all 854 blood samples in-between groups indicated similar results. Significant differences were typically observed between blood samples collected within the first and later than 48 h after death, respectively. CONCLUSIONS: To improve the consistency of comprehensive data evaluation in postmortem metabolome studies, it seems advisable to only include specimens collected within the first 2 days after death.