Metabolic signatures and risk of sarcopenia in suburb-dwelling older individuals by LC-MS-based untargeted metabonomics.

Background: Untargeted metabonomics has provided new insight into the pathogenesis of sarcopenia. In this study, we explored plasma metabolic signatures linked to a heightened risk of sarcopenia in a cohort study by LC-MS-based untargeted metabonomics. Methods: In this nested case-control study from the Adult Physical Fitness and Health Cohort Study (APFHCS), we collected blood plasma samples from 30 new-onset sarcopenia subjects (mean age 73.2 ± 5.6 years) and 30 healthy controls (mean age 74.2 ± 4.6 years) matched by age, sex, BMI, lifestyle, and comorbidities. An untargeted metabolomics methodology was employed to discern the metabolomic profile alterations present in individuals exhibiting newly diagnosed sarcopenia. Results: In comparing individuals with new-onset sarcopenia to normal controls, a comprehensive analysis using liquid chromatography-mass spectrometry (LC-MS) identified a total of 62 metabolites, predominantly comprising lipids, lipid-like molecules, organic acids, and derivatives. Receiver operating characteristic (ROC) curve analysis indicated that the three metabolites hypoxanthine (AUC=0.819, 95% CI=0.711-0.927), L-2-amino-3-oxobutanoic acid (AUC=0.733, 95% CI=0.598-0.868) and PC(14:0/20:2(11Z,14Z)) (AUC= 0.717, 95% CI=0.587-0.846) had the highest areas under the curve. Then, these significant metabolites were observed to be notably enriched in four distinct metabolic pathways, namely, "purine metabolism"; "parathyroid hormone synthesis, secretion and action"; "choline metabolism in cancer"; and "tuberculosis". Conclusion: The current investigation elucidates the metabolic perturbations observed in individuals diagnosed with sarcopenia. The identified metabolites hold promise as potential biomarkers, offering avenues for exploring the underlying pathological mechanisms associated with sarcopenia.

Discovery of urinary biosignatures for tuberculosis and nontuberculous mycobacteria classification using metabolomics and machine learning.

Nontuberculous mycobacteria (NTM) infection diagnosis remains a challenge due to its overlapping clinical symptoms with tuberculosis (TB), leading to inappropriate treatment. Herein, we employed noninvasive metabolic phenotyping coupled with comprehensive statistical modeling to discover potential biomarkers for the differential diagnosis of NTM infection versus TB. Urine samples from 19 NTM and 35 TB patients were collected, and untargeted metabolomics was performed using rapid liquid chromatography-mass spectrometry. The urine metabolome was analyzed using a combination of univariate and multivariate statistical approaches, incorporating machine learning. Univariate analysis revealed significant alterations in amino acids, especially tryptophan metabolism, in NTM infection compared to TB. Specifically, NTM infection was associated with upregulated levels of methionine but downregulated levels of glutarate, valine, 3-hydroxyanthranilate, and tryptophan. Five machine learning models were used to classify NTM and TB. Notably, the random forest model demonstrated excellent performance [area under the receiver operating characteristic (ROC) curve greater than 0.8] in distinguishing NTM from TB. Six potential biomarkers for NTM infection diagnosis, including methionine, valine, glutarate, 3-hydroxyanthranilate, corticosterone, and indole-3-carboxyaldehyde, were revealed from univariate ROC analysis and machine learning models. Altogether, our study suggested new noninvasive biomarkers and laid a foundation for applying machine learning to NTM differential diagnosis.

Integrative proteome and metabolome unveil the central role of IAA alteration in axillary bud development following topping in tobacco.

Axillary bud is an important aspect of plant morphology, contributing to the final tobacco yield. However, the mechanisms of axillary bud development in tobacco remain largely unknown. To investigate this aspect of tobacco biology, the metabolome and proteome of the axillary buds before and after topping were compared. A total of 569 metabolites were differentially abundant before and 1, 3, and 5 days after topping. KEGG analyses further revealed that the axillary bud was characterized by a striking enrichment of metabolites involved in flavonoid metabolism, suggesting a strong flavonoid biosynthesis activity in the tobacco axillary bud after topping. Additionally, 9035 differentially expressed proteins (DEPs) were identified before and 1, 3, and 5 days after topping. Subsequent GO and KEGG analyses revealed that the DEPs in the axillary bud were enriched in oxidative stress, hormone signal transduction, MAPK signaling pathway, and starch and sucrose metabolism. The integrated proteome and metabolome analysis revealed that the indole-3-acetic acid (IAA) alteration in buds control dormancy release and sustained growth of axillary bud by regulating proteins involved in carbohydrate metabolism, amino acid metabolism, and lipid metabolism. Notably, the proteins related to reactive oxygen species (ROS) scavenging and flavonoid biosynthesis were strongly negatively correlated with IAA content. These findings shed light on a critical role of IAA alteration in regulating axillary bud outgrowth, and implied a potential crosstalk among IAA alteration, ROS homeostasis, and flavonoid biosynthesis in tobacco axillary bud under topping stress, which could improve our understanding of the IAA alteration in axillary bud as an important regulator of axillary bud development.

Metabolomic and transcriptomic analyses of peach leaves and fruits in response to pruning.

BACKGROUND: Pruning is an important cultivation management option that has important effects on peach yield and quality. However, the effects of pruning on the overall genetic and metabolic changes in peach leaves and fruits are poorly understood. RESULTS: The transcriptomic and metabolomic profiles of leaves and fruits from trees subjected to pruning and unpruning treatments were measured. A total of 20,633 genes and 622 metabolites were detected. Compared with those in the control, 1,127 differentially expressed genes (DEGs) and 77 differentially expressed metabolites (DEMs) were identified in leaves from pruned and unpruned trees (pdLvsupdL), whereas 423 DEGs and 29 DEMs were identified in fruits from the pairwise comparison pdFvsupdF. The content of three auxin analogues was upregulated in the leaves of pruned trees, the content of all flavonoids detected in the leaves decreased, and the expression of almost all genes involved in the flavonoid biosynthesis pathway decreased. The phenolic acid and amino acid metabolites detected in fruits from pruned trees were downregulated, and all terpenoids were upregulated. The correlation analysis revealed that DEGs and DEMs in leaves were enriched in tryptophan metabolism, auxin signal transduction, and flavonoid biosynthesis. DEGs and DEMs in fruits were enriched in flavonoid and phenylpropanoid biosynthesis, as well as L-glutamic acid biosynthesis. CONCLUSIONS: Pruning has different effects on the leaves and fruits of peach trees, affecting mainly the secondary metabolism and hormone signalling pathways in leaves and amino acid biosynthesis in fruits.

Metagenomic and metabolomic analysis showing the adverse risk-benefit trade-off of the ketogenic diet.

BACKGROUND: Ketogenic diets are increasingly popular for addressing obesity, but their impacts on the gut microbiota and metabolome remain unclear. This paper aimed to investigate how a ketogenic diet affects intestinal microorganisms and metabolites in obesity. METHODS: Male mice were provided with one of the following dietary regimens: normal chow, high-fat diet, ketogenic diet, or high-fat diet converted to ketogenic diet. Body weight and fat mass were measured weekly using high-precision electronic balances and minispec body composition analyzers. Metagenomics and non-targeted metabolomics data were used to analyze differences in intestinal contents. RESULTS: Obese mice on the ketogenic diet exhibited notable improvements in weight and body fat. However, these were accompanied by a significant decrease in intestinal microbial diversity, as well as an increase in Firmicutes abundance and a 247% increase in the Firmicutes/Bacteroidetes ratio. The ketogenic diet also altered multiple metabolic pathways in the gut, including glucose, lipid, energy, carbohydrate, amino acid, ketone body, butanoate, and methane pathways, as well as bacterial secretion and colonization pathways. These changes were associated with increased intestinal inflammation and dysbiosis in obese mice. Furthermore, the ketogenic diet enhanced the secretion of bile and the synthesis of aminoglycoside antibiotics in obese mice, which may impair the gut microbiota and be associated with intestinal inflammation and immunity. CONCLUSIONS: The study suggest that the ketogenic diet had an unfavorable risk-benefit trade-off and may compromise metabolic homeostasis in obese mice.

NMR-based metabolomic investigation of dogs with acute flaccid paralysis due to tick paralysis.

BACKGROUND: Acute flaccid paralysis (AFP) is a complex clinical syndrome with various aetiologies. If untreated, AFP may lead to death due to failure of respiratory muscles. Tick paralysis, which is a noninfectious neurologic syndrome of AFP, occurs following tick attachment, engorgement, and injection of tick saliva toxins. There is no specific diagnostic test for tick paralysis, and mortality increases as definitive diagnosis is delayed. Although metabolomic investigation of tick saliva was conducted, there is a lack of research on metabolomic evaluation of hosts affected by tick paralysis. OBJECTIVES: Thus, the aim of this study is to investigate metabolomic changes in serum samples of dogs with tick paralysis due to Rhipicephalus sanguineus using NMR-based metabolomics and to identify potential diagnostic/prognostic markers. MATERIALS AND METHODS: Forty dogs infested with R. sanguineus, with clinical findings compatible with AFP and with a confirmed tick paralysis diagnosis ex juvantibus, constituted the Paralysis Group. Ten healthy dogs, which were admitted either for vaccination and/or check-up purposes, constituted the Control Group. After the confirmation tick paralysis, medical history, vaccination and nutritional status, body surface area and estimated tick numbers of all the dogs were noted. Physical examination included body temperature, heart and respiratory rate, capillary refill time evaluation and Modified Glasgow Coma Scale calculation. Serum samples were extracted from venous blood samples of all the dogs and were prepared for NMR analysis, and NMR-based metabolomics identification and quantification were performed. RESULTS: NMR-based serum metabolomics of the present study revealed distinct up/down-regulated expressions, presenting a promising avenue. Moreover, it was observed that energy metabolism and especially liver functions were impaired in dogs with tick paralysis, and not only the respiratory system but also the kidneys were affected. CONCLUSION: It was concluded that the present approach may help to better understand the pathological mechanisms developing in cases of AFP due to tick paralysis.

Metabolomics-based search for lung cancer markers among patients with different smoking status.

Tobacco smoking is the main etiological factor of lung cancer (LC), which can also cause metabolome disruption. This study aimed to investigate whether the observed metabolic shift in LC patients was also associated with their smoking status. Untargeted metabolomics profiling was applied for the initial screening of changes in serum metabolic profile between LC and chronic obstructive pulmonary disease (COPD) patients, selected as a non-cancer group. Differences in metabolite profiles between current and former smokers were also tested. Then, targeted metabolomics methods were applied to verify and validate the proposed LC biomarkers. For untargeted metabolomics, a single extraction-dual separation workflow was applied. The samples were analyzed using a liquid chromatograph-high resolution quadrupole time-of-flight mass spectrometer. Next, the selected metabolites were quantified using liquid chromatography-triple-quadrupole mass spectrometry. The acquired data confirmed that patients' stratification based on smoking status impacted the discriminating ability of the identified LC marker candidates. Analyzing a validation set of samples enabled us to determine if the putative LC markers were truly robust. It demonstrated significant differences in the case of four metabolites: allantoin, glutamic acid, succinic acid, and sphingosine-1-phosphate. Our research showed that studying the influence of strong environmental factors, such as tobacco smoking, should be considered in cancer marker research since it reduces the risk of false positives and improves understanding of the metabolite shifts in cancer patients.

Plasma metabolomic and lipidomic profiles accurately classify mothers of children with congenital heart disease: an observational study.

INTRODUCTION: Congenital heart disease (CHD) is the most common congenital anomaly, representing a significant global disease burden. Limitations exist in our understanding of aetiology, diagnostic methodology and screening, with metabolomics offering promise in addressing these. OBJECTIVE: To evaluate maternal metabolomics and lipidomics in prediction and risk factor identification for childhood CHD. METHODS: We performed an observational study in mothers of children with CHD following pregnancy, using untargeted plasma metabolomics and lipidomics by ultrahigh performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS). 190 cases (157 mothers of children with structural CHD (sCHD); 33 mothers of children with genetic CHD (gCHD)) from the children OMACp cohort and 162 controls from the ALSPAC cohort were analysed. CHD diagnoses were stratified by severity and clinical classifications. Univariate, exploratory and supervised chemometric methods were used to identify metabolites and lipids distinguishing cases and controls, alongside predictive modelling. RESULTS: 499 metabolites and lipids were annotated and used to build PLS-DA and SO-CovSel-LDA predictive models to accurately distinguish sCHD and control groups. The best performing model had an sCHD test set mean accuracy of 94.74% (sCHD test group sensitivity 93.33%; specificity 96.00%) utilising only 11 analytes. Similar test performances were seen for gCHD. Across best performing models, 37 analytes contributed to performance including amino acids, lipids, and nucleotides. CONCLUSIONS: Here, maternal metabolomic and lipidomic analysis has facilitated the development of sensitive risk prediction models classifying mothers of children with CHD. Metabolites and lipids identified offer promise for maternal risk factor profiling, and understanding of CHD pathogenesis in the future.

Biochemical indicators, cell apoptosis, and metabolomic analyses of the low-temperature stress response and cold tolerance mechanisms in Litopenaeus vannamei.

The cold tolerance of Litopenaeus vannamei is important for breeding in specific areas. To explore the cold tolerance mechanism of L. vannamei, this study analyzed biochemical indicators, cell apoptosis, and metabolomic responses in cold-tolerant (Lv-T) and common (Lv-C) L. vannamei under low-temperature stress (18 °C and 10 °C). TUNEL analysis showed a significant increase in apoptosis of hepatopancreatic duct cells in L. vannamei under low-temperature stress. Biochemical analysis showed that Lv-T had significantly increased levels of superoxide dismutase (SOD) and triglycerides (TG), while alanine aminotransferase (ALT), alkaline phosphatase (ALP), lactate dehydrogenase (LDH-L), and uric acid (UA) levels were significantly decreased compared to Lv-C (p < 0.05). Metabolomic analysis displayed significant increases in metabolites such as LysoPC (P-16:0), 11beta-Hydroxy-3,20-dioxopregn-4-en-21-oic acid, and Pirbuterol, while metabolites such as 4-Hydroxystachydrine, Oxolan-3-one, and 3-Methyldioxyindole were significantly decreased in Lv-T compared to Lv-C. The differentially regulated metabolites were mainly enriched in pathways such as Protein digestion and absorption, Central carbon metabolism in cancer and ABC transporters. Our study indicate that low temperature induces damage to the hepatopancreatic duct of shrimp, thereby affecting its metabolic function. The cold resistance mechanism of Lv-T L. vannamei may be due to the enhancement of antioxidant enzymes and lipid metabolism.

Identification of metabolites associated with preserved muscle volume after aneurysmal subarachnoid hemorrhage due to high protein supplementation and neuromuscular electrical stimulation.

The INSPIRE randomized clinical trial demonstrated that a high protein diet (HPRO) combined with neuromuscular electrical stimulation (NMES) attenuates muscle atrophy and may improve outcomes after aneurysmal subarachnoid hemorrhage We sought to identify specific metabolites mediating these effects. Blood samples were collected from subjects on admission prior to randomization to either standard of care (SOC; N = 12) or HPRO + NMES (N = 12) and at 7 days. Untargeted metabolomics were performed for each plasma sample. Sparse partial least squared discriminant analysis identified metabolites differentiating each group. Correlation coefficients were calculated between each metabolite and total protein per day and muscle volume. Multivariable models determined associations between metabolites and muscle volume. Unique metabolites (18) were identified differentiating SOC from HPRO + NMES. Of these, 9 had significant positive correlations with protein intake. In multivariable models, N-acetylleucine was significantly associated with preserved temporalis [OR 1.08 (95% CI 1.01, 1.16)] and quadricep [OR 1.08 (95% CI 1.02, 1.15)] muscle volume. Quinolinate was also significantly associated with preserved temporalis [OR 1.05 (95% CI 1.01, 1.09)] and quadricep [OR 1.04 (95% CI 1.00, 1.07)] muscle volume. N-acetylserine and ß-hydroxyisovaleroylcarnitine were associated with preserved temporalis or quadricep volume. Metabolites defining HPRO + NMES had strong correlations with protein intake and were associated with preserved muscle volume.

Integrated microbiome and metabolome analysis reveals that new insight into Radix pseudostellariae polysaccharide enhances PRRSV inactivated vaccine.

In this study, we investigated how Radix pseudostellariae polysaccharide (RPP) enhances the immune response of the inactivated porcine reproductive and respiratory syndrome virus (PRRSV) vaccine through interactions with the microbiome and metabolome. We pretreated sows with 10 mg/kg body weight of RPP via drinking water for 7 days prior to intramuscular injection of the PRRSV vaccine. This significantly increased the concentrations of PRRSV GP5 protein antibody, interleukin (IL)-2, IL-4, IL-10, and interferon (IFN)-γ. Oral administration of RPP also significantly improved the abundance of beneficial bacteria in the stool, such as Parabacteroides distasonis, Prevotella_copri, Eubacterium_sp., and Clostridium_sp._CAG:226, and decreased the levels of potentially pathogenic bacteria, such as Paraeggerthella and [Clostridium] innocuum, compared to the vaccine alone. These bacterial changes were confirmed using quantitative real-time polymerase chain reaction (Q-PCR). Moreover, RPP treatment significantly increased the blood concentrations of L-theanine, taurodeoxycholic acid (TDCA), and N-arachidonoyl proline, and decreased the levels of L-glutamine, oclacitinib, lipoxin C4, and leukotriene C5 in sows after immunization (p< 0.05). The concentrations of various blood metabolites were validated using sandwich enzyme-linked immunosorbent assay (ELISA), confirming the accuracy of the metabolomics data. Intriguingly, the integration of microbiome and metabolome analyses highlighted the significance of Prevotella_copri and TDCA. We consequently developed a mouse immunity model using GP5 protein and discovered that oral administration of RPP significantly enhanced the levels of GP5 protein antibodies, IL-2, IL-4, IL-10, and IFN-γ in mouse serum. It also increased the number of CD3+ and CD3+CD4+ cells in the spleen. Additionally, Prevotella_copri was administered into the large intestine via the anus for 7 days prior to the intramuscular injection of the PRRSV GP5 protein. The results demonstrated a significant increase in TDCA and GP5 antibody concentration in the mouse serum, indicating that RPP modulates Prevotella_copri to elevate its metabolite TDCA, thereby enhancing the GP5 antibody level. In conclusion, oral administration of 10 mg/kg RPP optimizes gut flora diversity and blood metabolites, particularly Prevotella_copri and TDCA, thereby improving the immune response to the inactivated PRRSV vaccine.

Plasma metabolites are altered before and after diagnosis of preeclampsia or fetal growth restriction.

Metabolomics is the study of small molecules (metabolites), within cells, tissues and biofluids. Maternal metabolites can provide important insight into the health and development of both mother and fetus throughout pregnancy. This study assessed metabolic profiles in the maternal circulation prior to and at the time of diagnosis of preeclampsia and fetal growth restriction. Maternal plasma samples were collected from two independent cohorts: (1) Established disease cohort: 50 participants diagnosed with early-onset preeclampsia (< 34 weeks' gestation), 14 with early-onset fetal growth restriction, and 25 gestation-matched controls. (2) Prospective cohort, collected at 36 weeks' gestation before diagnosis: 17 participants later developed preeclampsia, 49 delivered infants with fetal growth restriction (birthweight < 5th centile), and 72 randomly selected controls. Metabolic evaluation was performed by Metabolomics Australia on the Agilent 6545 QTOF Mass Spectrometer. In the established disease cohort, 77 metabolites were altered in circulation from participants with preeclampsia - increased L-cysteine (3.73-fold), L-cystine (3.28-fold), L-acetylcarnitine (2.57-fold), and carnitine (1.53-fold) (p < 0.05). There were 53 metabolites dysregulated in participants who delivered a fetal growth restriction infant-including increased levulinic acid, citric acid (1.93-fold), and creatine (1.14-fold) (p < 0.05). In the prospective cohort, 30 metabolites were altered in participants who later developed preeclampsia at term - reduced glutaric acid (0.85-fold), porphobilinogen (0.77-fold) and amininohippuric acid (0.82-fold) (p < 0.05) was observed. There were 5 metabolites altered in participants who later delivered a fetal growth restriction infant - including reduced 3-methoxybenzenepropanoic acid (p < 0.05). Downstream pathway analysis revealed aminoacyl-tRNA biosynthesis to be most significantly altered in the established cohort in preeclampsia (13/48 hits, p < 0.001) and fetal growth restriction (7/48 hits, p < 0.001). The predictive cohort showed no significant pathway alterations. This study observed altered metabolites in maternal plasma collected before and after diagnosis of a preeclampsia or fetal growth restriction. While a significant number of metabolites were altered with established disease, few changes were observed in the predictive cohort. Thus, metabolites measured in this study may not be useful as predictors of preeclampsia or fetal growth restriction.

Plasma metabolomics identifies differing endotypes of recurrent wheezing in preschool children differentiated by symptoms and social disadvantage.

Preschool children with recurrent wheezing are a heterogeneous population with many underlying biological pathways that contribute to clinical presentations. Although the morbidity of recurrent wheezing in preschool children is significant, biological studies in this population remain quite limited. To address this gap, this study performed untargeted plasma metabolomic analyses in 68 preschool children with recurrent wheezing to identify metabolomic endotypes of wheezing. K-means cluster analysis was performed on metabolomic dataset including a total of 1382 named and unnamed metabolites. We identified three metabolomic clusters which differed in symptom severity, exacerbation occurrence, and variables associated with social disadvantage. Metabolites that distinguished the clusters included those involved in fatty acid metabolism, fatty acids (long chain monounsaturated fatty acids, long chain polyunsaturated fatty acids, and long chain saturated fatty acids), lysophospholipids, phosphatidylcholines, and phosphatidylethanolamines. Pathway analyses identified pathways of interest in each cluster, including steroid metabolism, histidine metabolism, sphingomyelins, and sphingosines, among others. This study highlights the biologic complexity of recurrent wheezing in preschool children and offers novel metabolites and pathways that may be amenable to future study and intervention.

Biliary atresia and cholestasis plasma non-targeted metabolomics unravels perturbed metabolic pathways and unveils a diagnostic model for biliary atresia.

The clinical diagnosis of biliary atresia (BA) poses challenges, particularly in distinguishing it from cholestasis (CS). Moreover, the prognosis for BA is unfavorable and there is a dearth of effective non-invasive diagnostic models for detection. Therefore, the aim of this study is to elucidate the metabolic disparities among children with BA, CS, and normal controls (NC) without any hepatic abnormalities through comprehensive metabolomics analysis. Additionally, our objective is to develop an advanced diagnostic model that enables identification of BA. The plasma samples from 90 children with BA, 48 children with CS, and 47 NC without any liver abnormalities children were subjected to metabolomics analysis, revealing significant differences in metabolite profiles among the 3 groups, particularly between BA and CS. A total of 238 differential metabolites were identified in the positive mode, while 89 differential metabolites were detected in the negative mode. Enrichment analysis revealed 10 distinct metabolic pathways that differed, such as lysine degradation, bile acid biosynthesis. A total of 18 biomarkers were identified through biomarker analysis, and in combination with the exploration of 3 additional biomarkers (LysoPC(18:2(9Z,12Z)), PC (22:5(7Z,10Z,13Z,16Z,19Z)/14:0), and Biliverdin-IX-α), a diagnostic model for BA was constructed using logistic regression analysis. The resulting ROC area under the curve was determined to be 0.968. This study presents an innovative and pioneering approach that utilizes metabolomics analysis to develop a diagnostic model for BA, thereby reducing the need for unnecessary invasive examinations and contributing to advancements in diagnosis and prognosis for patients with BA.

Combined analysis of the metabolome and transcriptome reveals the metabolic characteristics and candidate genes involved in alkaloid metabolism in Heuchera micrantha Douglas ex Lindl.

BACKGROUND: Alkaloids, important secondary metabolites produced by plants, play a crucial role in responding to environmental stress. Heuchera micrantha, a well-known plant used in landscaping, has the ability to purify air, and absorb toxic and radioactive substances, showing strong environmental adaptability. However, there is still limited understanding of the accumulation characteristics and metabolic mechanism of alkaloids in H. micrantha. RESULTS: In this study, four distinct varieties of H. micrantha were used to investigate the accumulation and metabolic traits of alkaloids in its leaves. We conducted a combined analysis of the plant's metabolome and transcriptome. Our analysis identified 44 alkaloids metabolites in the leaves of the four H. micrantha varieties, with 26 showing different levels of accumulation among the groups. The HT and JQ varieties exhibited higher accumulation of differential alkaloid metabolites compared to YH and HY. We annotated the differential alkaloid metabolites to 22 metabolic pathways, including several alkaloid metabolism. Transcriptome data revealed 5064 differentially expressed genes involved in these metabolic pathways. Multivariate analysis showed that four key metabolites (N-hydroxytryptamine, L-tyramine, tryptamine, and 2-phenylethylamine) and three candidate genes (Cluster-15488.116815, Cluster-15488.146268, and Cluster-15488.173297) that merit further investigation. CONCLUSIONS: This study provided preliminarily insight into the molecular mechanism of the biosynthesis of alkaloids in H. micrantha. However, further analysis is required to elucidate the specific regulatory mechanisms of the candidate gene involved in the synthesis of key alkaloid metabolites. In summary, our findings provide important information about how alkaloid metabolites build up and the metabolic pathways involved in H. micrantha varieties. This gives us a good starting point for future research on the regulation mechanism, and development, and utilization of alkaloids in H. micrantha.

Association of litter size with the ruminal microbiome structure and metabolomic profile in goats.

The Yunshang black goat is a renowned mutton specialist breed mainly originating from China that has excellent breeding ability with varying litter sizes. Litter size is an important factor in the economics of goat farming. However, ruminal microbiome structure might be directly or indirectly regulated by pregnancy-associated factors, including litter sizes. Therefore, the current experiment aimed to evaluate the association of different litter sizes (low versus high) with ruminal microbiome structure by 16S rRNA gene sequencing and metabolomic profiling of Yunshang black does. A total of twenty does of the Yunshang Black breed, approximately aged between 3 and 4 years, were grouped (n = 10 goats/group) into low (D-l) and high (D-h) litter groups according to their litter size (the lower group has ≤ 2 kids/litter and the high group has ≧ 3 kids/litter, respectively). All goats were sacrificed, and collected ruminal fluid samples were subjected to 16S rRNA sequencing and LC-MS/MC Analysis for ruminal microbiome and metabolomic profiling respectively. According to PCoA analysis, the ruminal microbiota was not significantly changed by the litter sizes among the groups. The Firmicutes and Bacteroidetes were the most dominant phyla, with an abundance of 55.34% and 39.62%, respectively. However, Ruminococcaceae_UCG-009, Sediminispirochaeta, and Paraprevotella were significantly increased in the D-h group, whereas Ruminococcaceae_UCG-010 and Howardella were found to be significantly decreased in the D-l group. The metabolic profiling analysis revealed that litter size impacts metabolites as 29 and 50 metabolites in positive and negative ionic modes respectively had significant differences in their regulation. From them, 16 and 24 metabolites of the D-h group were significantly down-regulated in the positive ionic mode, while 26 metabolites were up-regulated in the negative ionic mode for the same group. The most vibrant identified metabolites, including methyl linoleate, acetylursolic acid, O-desmethyl venlafaxine glucuronide, melanostatin, and arginyl-hydroxyproline, are involved in multiple biochemical processes relevant to rumen roles. The identified differential metabolites were significantly enriched in 12 different pathways including protein digestion and absorption, glycerophospholipid metabolism, regulation of lipolysis in adipocytes, and the mTOR signaling pathway. Spearman's correlation coefficient analysis indicated that metabolites and microbial communities were tightly correlated and had significant differences between the D-l and D-h groups. Based on the results, the present study provides novel insights into the regulation mechanisms of the rumen microbiota and metabolomic profiles leading to different fertility in goats, which can give breeders some enlightenments to further improve the fertility of Yunshang Black goats.

Plasma metabolomics reveals the shared and distinct metabolic disturbances associated with cardiovascular events in coronary artery disease.

Risk prediction for subsequent cardiovascular events remains an unmet clinical issue in patients with coronary artery disease. We aimed to investigate prognostic metabolic biomarkers by considering both shared and distinct metabolic disturbance associated with the composite and individual cardiovascular events. Here, we conducted an untargeted metabolomics analysis for 333 incident cardiovascular events and 333 matched controls. The cardiovascular events were designated as cardiovascular death, myocardial infarction/stroke and heart failure. A total of 23 shared differential metabolites were associated with the composite of cardiovascular events. The majority were middle and long chain acylcarnitines. Distinct metabolic patterns for individual events were revealed, and glycerophospholipids alteration was specific to heart failure. Notably, the addition of metabolites to clinical markers significantly improved heart failure risk prediction. This study highlights the potential significance of plasma metabolites on tailed risk assessment of cardiovascular events, and strengthens the understanding of the heterogenic mechanisms across different events.

Identifying critical age and gender-based metabolomic shifts in a Japanese population of the Tohoku Medical Megabank cohort.

Understanding the physiological changes associated with aging and the associated disease risks is essential to establish biomarkers as indicators of biological aging. This study used the NMR-measured plasma metabolome to calculate age-specific metabolite indices. In doing so, the scope of the study was deliberately simplified to capture general trends and insights into age-related changes in metabolic patterns. In addition, changes in metabolite concentrations with age were examined in detail, with the period from 55-59 to 60-64 years being a period of significant metabolic change, particularly in men, and from 45-49 to 50-54 years in females. These results illustrate the different variations in metabolite concentrations by sex and provide new insights into the relationship between age and metabolic diseases.

Integrated proteomic and metabolomic profiling reveals novel insights on the inflammation and immune response in HFpEF.

BACKGROUND: The precise mechanisms leading to the development of heart failure with preserved ejection fraction (HFpEF) remain incompletely defined. In this study, an integrative approach utilizing untargeted proteomics and metabolomics was employed to delineate the altered proteomic and metabolomic profiles in patients with HFpEF compared to healthy controls. MATERIALS AND METHODS: Data were collected from a prospective cohort consisting of 30 HFpEF participants and 30 healthy controls, matched by gender and age. plasma samples were analyzed by multi-omics platforms. The quantification of plasma proteins and metabolites was performed using data-independent acquisition-based liquid chromatography-tandem mass spectrometry (LC-MS/MS) and ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), respectively. Additionally, Proteomic and metabolomic results were analyzed separately and integrated using correlation and pathway analysis. This was followed by the execution of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment studies to elucidate the biological relevance of the observed results. RESULTS: A total of 46 significantly differentially expressed proteins (DEPs) and 102 differentially expressed metabolites (DEMs) were identified. Then, GO and KEGG pathway enrichment analyses were performed by DEPs and DEMs. Integrated analysis of proteomics and metabolomics has revealed Tuberculosis and African trypanosomiasis pathways that are significantly enriched and the DEPs and DEMs enriched within them, are associated with inflammation and immune response. CONCLUSIONS: Integrated proteomic and metabolomic analyses revealed distinct inflammatory and immune response pathways in HFpEF, highlighting novel therapeutic avenues.

Plant Tissue Culture and Metabolite Profiling for High-Value Natural Product Synthesis.

The engineering of plant cell cultures to produce high-value natural products is suggested to be a safe, low-cost, and environmentally friendly route to produce a wide range of chemicals. Given that the expression of heterologous biosynthetic pathways in plant tissue culture is limited by a lack of detailed protocols, the biosynthesis of high-value metabolites in plant cell culture is constrained compared with that in microbes. However, both Arabidopsis thaliana and Nicotiana benthamiana can be efficiently transformed with multigene constructs to produce high-value natural products in stable plant cell cultures. This chapter provides a detailed protocol as to how to engineer the plant cell culture as bio-factories for metabolite biosynthesis.