An α-ketoglutarate conformational switch controls iron accessibility, activation, and substrate selection of the human FTO protein.

The fat mass and obesity-associated fatso (FTO) protein is a member of the Alkb family of dioxygenases and catalyzes oxidative demethylation of N6-methyladenosine (m6A), N1-methyladenosine (m1A), 3-methylthymine (m3T), and 3-methyluracil (m3U) in single-stranded nucleic acids. It is well established that the catalytic activity of FTO proceeds via two coupled reactions. The first reaction involves decarboxylation of alpha-ketoglutarate (αKG) and formation of an oxyferryl species. In the second reaction, the oxyferryl intermediate oxidizes the methylated nucleic acid to reestablish Fe(II) and the canonical base. However, it remains unclear how binding of the nucleic acid activates the αKG decarboxylation reaction and why FTO demethylates different methyl modifications at different rates. Here, we investigate the interaction of FTO with 5-mer DNA oligos incorporating the m6A, m1A, or m3T modifications using solution NMR, molecular dynamics (MD) simulations, and enzymatic assays. We show that binding of the nucleic acid to FTO activates a two-state conformational equilibrium in the αKG cosubstrate that modulates the O2 accessibility of the Fe(II) catalyst. Notably, the substrates that provide better stabilization to the αKG conformation in which Fe(II) is exposed to O2 are demethylated more efficiently by FTO. These results indicate that i) binding of the methylated nucleic acid is required to expose the catalytic metal to O2 and activate the αKG decarboxylation reaction, and ii) the measured turnover of the demethylation reaction (which is an ensemble average over the entire sample) depends on the ability of the methylated base to favor the Fe(II) state accessible to O2.

Exhaled Volatile Organic Compounds for Asthma Control Classification in Children with Moderate to Severe Asthma: Results from the SysPharmPediA Study.

RATIONALE: Early identification of children with poorly controlled asthma is imperative for optimizing treatment strategies. The analysis of exhaled volatile organic compounds (VOCs) is an emerging approach to identify prognostic and diagnostic biomarkers in pediatric asthma. OBJECTIVES: To assess the accuracy of gas chromatography-mass spectrometry based exhaled metabolite analysis to differentiate between controlled and uncontrolled pediatric asthma. METHODS: This study encompassed a discovery (SysPharmPediA) and validation phase (U-BIOPRED, PANDA). Firstly, exhaled VOCs that discriminated asthma control levels were identified. Subsequently, outcomes were validated in two independent cohorts. Patients were classified as controlled or uncontrolled, based on asthma control test scores and number of severe attacks in the past year. Additionally, potential of VOCs in predicting two or more future severe asthma attacks in SysPharmPediA was evaluated. MEASUREMENTS AND MAIN RESULTS: Complete data were available for 196 children (SysPharmPediA=100, U-BIOPRED=49, PANDA=47). In SysPharmPediA, after randomly splitting the population into training (n=51) and test sets (n=49), three compounds (acetophenone, ethylbenzene, and styrene) distinguished between uncontrolled and controlled asthmatics. The area under the receiver operating characteristic curve (AUROCC) for training and test sets were respectively: 0.83 (95% CI: 0.65-1.00) and 0.77 (95% CI: 0.58-0.96). Combinations of these VOCs resulted in AUROCCs of 0.74 ±0.06 (UBIOPRED) and 0.68 ±0.05 (PANDA). Attacks prediction tests, resulted in AUROCCs of 0.71 (95% CI 0.51-0.91) and 0.71 (95% CI 0.52-0.90) for training and test sets. CONCLUSIONS: Exhaled metabolites analysis might enable asthma control classification in children. This should stimulate further development of exhaled metabolites-based point-of-care tests in asthma.

Transcriptomic and metabolomic dissection of skeletal muscle of crossbred Chongming white goats with different meat production performance.

BACKGROUND: The transcriptome and metabolome dissection of the skeletal muscle of high- and low- growing individuals from a crossbred population of the indigenous Chongming white goat and the Boer goat were performed to discover the potential functional differentially expressed genes (DEGs) and differential expression metabolites (DEMs). RESULTS: A total of 2812 DEGs were detected in 6 groups at three time stages (3,6,12 Month) in skeletal muscle using the RNA-seq method. A DEGs set containing seven muscle function related genes (TNNT1, TNNC1, TNNI1, MYBPC2, MYL2, MHY7, and CSRP3) was discovered, and their expression tended to increase as goat muscle development progressed. Seven DEGs (TNNT1, FABP3, TPM3, DES, PPP1R27, RCAN1, LMOD2) in the skeletal muscle of goats in the fast-growing and slow-growing groups was verified their expression difference by reverse transcription-quantitative polymerase chain reaction. Further, through the Liquid chromatography-mass spectrometry (LC-MS) approach, a total of 183 DEMs in various groups of the muscle samples and these DEMs such as Queuine and Keto-PGF1α, which demonstrated different abundance between the goat fast-growing group and slow-growing group. Through weighted correlation network analysis (WGCNA), the study correlated the DEGs with the DEMs and identified 4 DEGs modules associated with 18 metabolites. CONCLUSION: This study benefits to dissection candidate genes and regulatory networks related to goat meat production performance, and the joint analysis of transcriptomic and metabolomic data provided insights into the study of goat muscle development.

Genetic control of abiotic stress-related specialized metabolites in sunflower.

BACKGROUND: Abiotic stresses in plants include all the environmental conditions that significantly reduce yields, like drought and heat. One of the most significant effects they exert at the cellular level is the accumulation of reactive oxygen species, which cause extensive damage. Plants possess two mechanisms to counter these molecules, i.e. detoxifying enzymes and non-enzymatic antioxidants, which include many classes of specialized metabolites. Sunflower, the fourth global oilseed, is considered moderately drought resistant. Abiotic stress tolerance in this crop has been studied using many approaches, but the control of specialized metabolites in this context remains poorly understood. Here, we performed the first genome-wide association study using abiotic stress-related specialized metabolites as molecular phenotypes in sunflower. After analyzing leaf specialized metabolites of 450 hybrids using liquid chromatography-mass spectrometry, we selected a subset of these compounds based on their association with previously known abiotic stress-related quantitative trait loci. Eventually, we characterized these molecules and their associated genes. RESULTS: We putatively annotated 30 compounds which co-localized with abiotic stress-related quantitative trait loci and which were associated to seven most likely candidate genes. A large proportion of these compounds were potential antioxidants, which was in agreement with the role of specialized metabolites in abiotic stresses. The seven associated most likely candidate genes, instead, mainly belonged to cytochromes P450 and glycosyltransferases, two large superfamilies which catalyze greatly diverse reactions and create a wide variety of chemical modifications. This was consistent with the high plasticity of specialized metabolism in plants. CONCLUSIONS: This is the first characterization of the genetic control of abiotic stress-related specialized metabolites in sunflower. By providing hints concerning the importance of antioxidant molecules in this biological context, and by highlighting some of the potential molecular mechanisms underlying their biosynthesis, it could pave the way for novel applications in breeding. Although further analyses will be required to better understand this topic, studying how antioxidants contribute to the tolerance to abiotic stresses in sunflower appears as a promising area of research.

Scoring system for diagnosis and pretreatment risk assessment of neuroblastoma using urinary biomarker combinations.

The urinary catecholamine metabolites, homovanillic acid (HVA) and vanillylmandelic acid (VMA), are used for the adjunctive diagnosis of neuroblastomas. We aimed to develop a scoring system for the diagnosis and pretreatment risk assessment of neuroblastoma, incorporating age and other urinary catecholamine metabolite combinations. Urine samples from 227 controls (227 samples) and 68 patients with neuroblastoma (228 samples) were evaluated. First, the catecholamine metabolites vanillactic acid (VLA) and 3-methoxytyramine sulfate (MTS) were identified as urinary marker candidates through comprehensive analysis using liquid chromatography-mass spectrometry. The concentrations of these marker candidates and conventional markers were then compared among controls, patients, and numerous risk groups to develop a scoring system. Participants were classified into four groups: control, low risk, intermediate risk, and high risk, and the proportional odds model was fitted using the L2-penalized maximum likelihood method, incorporating age on a monthly scale for adjustment. This scoring model using the novel urine catecholamine metabolite combinations, VLA and MTS, had greater area under the curve values than the model using HVA and VMA for diagnosis (0.978 vs. 0.964), pretreatment risk assessment (low and intermediate risk vs. high risk: 0.866 vs. 0.724; low risk vs. intermediate and high risk: 0.871 vs. 0.680), and prognostic factors (MYCN status: 0.741 vs. 0.369, histology: 0.932 vs. 0.747). The new system also had greater accuracy in detecting missing high-risk neuroblastomas, and in predicting the pretreatment risk at the time of screening. The new scoring system employing VLA and MTS has the potential to replace the conventional adjunctive diagnostic method using HVA and VMA.

Chemical Profiles Differ between Communal Breeding Groups in a Highly Social Bird.

AbstractGregarious species must distinguish group members from nongroup members. Olfaction is important for group recognition in social insects and mammals but rarely studied in birds, despite birds using olfaction in social contexts from species discrimination to kin recognition. Olfactory group recognition requires that groups have a signature odor, so we tested for preen oil and feather chemical similarity in group-living smooth-billed anis (Crotophaga ani). Physiology affects body chemistry, so we also tested for an effect of egg-laying competition, as a proxy for reproductive status, on female chemical similarity. Finally, the fermentation hypothesis for chemical recognition posits that host-associated microbes affect host odor, so we tested for covariation between chemicals and microbiota. Group members were more chemically similar across both body regions. We found no chemical differences between sexes, but females in groups with less egg-laying competition had more similar preen oil, suggesting that preen oil contains information about reproductive status. There was no overall covariation between chemicals and microbes; instead, subsets of microbes could mediate olfactory cues in birds. Preen oil and feather chemicals showed little overlap and may contain different information. This is the first demonstration of group chemical signatures in birds, a finding of particular interest given that smooth-billed anis live in nonkin breeding groups. Behavioral experiments are needed to test whether anis can distinguish group members from nongroup members using odor cues.

Understanding the modulations of glycero-lysophospholipids in an elastase-induced murine emphysema model.

BACKGROUND: Increasing evidence indicates that bioactive lipid mediators are involved in chronic obstructive pulmonary disease (COPD) pathogenesis. Recently, glycero-lysophospholipids, such as lysophosphatidic acid (LysoPA) and lysophosphatidylserine (LysoPS), have been recognized as significant inflammation-related lipid mediators. However, their association with COPD remains unclear. METHODS: We used an elastase-induced murine emphysema model to analyze the levels of lysophospholipids and diacyl-phospholipids in the lungs. Additionally, we assessed the expression of LysoPS-related genes and published data on smokers. RESULTS: In the early phase of an elastase-induced murine emphysema model, the levels of LysoPS and its precursor (phosphatidylserine [PS]) were significantly reduced, without significant modulations in other glycero-lysophospholipids. Additionally, there was an upregulation in the expression of lysoPS receptors, specifically GPR34, observed in the lungs of a cigarette smoke-exposed mouse model and the alveolar macrophages of human smokers. Elastase stimulation induces GPR34 expression in a human macrophage cell line in vitro. CONCLUSIONS: Elastase-induced lung emphysema affects the LysoPS/PS-GPR34 axis, and cigarette smoking or elastase upregulates GPR34 expression in alveolar macrophages. This novel association may serve as a potential pharmacological target for COPD treatment.

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.

Predictive analysis of breast cancer response to neoadjuvant chemotherapy through plasma metabolomics.

PURPOSE: Preoperative chemotherapy is a critical component of breast cancer management, yet its effectiveness is not uniform. Moreover, the adverse effects associated with chemotherapy necessitate the identification of a patient subgroup that would derive the maximum benefit from this treatment. This study aimed to establish a method for predicting the response to neoadjuvant chemotherapy in breast cancer patients utilizing a metabolomic approach. METHODS: Plasma samples were obtained from 87 breast cancer patients undergoing neoadjuvant chemotherapy at our facility, collected both before the commencement of the treatment and before the second treatment cycle. Metabolite analysis was conducted using capillary electrophoresis-mass spectrometry (CE-MS) and liquid chromatography-mass spectrometry (LC-MS). We performed comparative profiling of metabolite concentrations by assessing the metabolite profiles of patients who achieved a pathological complete response (pCR) against those who did not, both in initial and subsequent treatment cycles. RESULTS: Significant variances were observed in the metabolite profiles between pCR and non-pCR cases, both at the onset of preoperative chemotherapy and before the second cycle. Noteworthy distinctions were also evident between the metabolite profiles from the initial and the second neoadjuvant chemotherapy courses. Furthermore, metabolite profiles exhibited variations associated with intrinsic subtypes at all assessed time points. CONCLUSION: The application of plasma metabolomics, utilizing CE-MS and LC-MS, may serve as a tool for predicting the efficacy of neoadjuvant chemotherapy in breast cancer in the future after all necessary validations have been completed.

Combined perceptual and chemical analyses show no compelling evidence for ovulatory cycle shifts in women's axillary odour.

Although men's attraction to women's body odour has been suggested to vary over the ovulatory cycle, peaking around the fertile window, we still lack methodologically robust evidence corroborating this effect. Further, the chemical underpinnings of male preference for the odour of ovulating women remain unknown. Here, we combined perceptual and chemical analyses to investigate the axillary odour of naturally cycling women over 10 days, covering the gradual change in fertility across the ovulatory cycle with a focus on fertile days. The fertile state was confirmed by urinary ovulation tests as well as salivary oestradiol and progesterone levels. Men rated the scent of unfamiliar women, resembling a first encounter. We used multivariate analyses to relate variation in both odour ratings and chemical composition to female conception probability, temporal distance to ovulation and ovarian hormone levels. Our results provide no evidence that males prefer the odour of fertile women. Furthermore, the volatile analysis indicated no link between axillary odour composition and current fertility status. Together, our results showed no convincing support for a chemical fertility cue in women's axillary odour, questioning the presence of olfactory fertility information that is recognizable during first encounters in modern humans.

The dominant white color trait of the melon fruit rind is associated with epicuticular wax accumulation.

MAIN CONCLUSION: Microscopic analyses and chemical profiling demonstrate that the white rind phenotype in melon fruit is associated with the accumulation of n-alkanes, fatty alcohols, aldehydes and wax esters. Serving as an indicator of quality, the rind (or external) color of fruit directly affects consumer choice. A fruit's color is influenced by factors such as the levels of pigments and deposited epicuticular waxes. The latter produces a white-grayish coating often referred to as "wax bloom". Previous reports have suggested that some melon (Cucumis melo L.) accessions may produce wax blooms, where a dominant white rind color trait was genetically mapped to a major locus on chromosome 7 and suggested to be inherited as a single gene named Wi. We here provide the first direct evidence of the contribution of epicuticular waxes to the dominant white rind trait in melon fruit. Our light and electron microscopy and gas chromatography-mass spectrometry (GC-MS) comparative analysis of melon accessions with white or green rinds reveals that the rind of melon fruit is rich in epicuticular waxes. These waxes are composed of various biochemical classes, including fatty acids, fatty alcohols, aldehydes, fatty amides, n-alkanes, tocopherols, triterpenoids, and wax esters. We show that the dominant white rind phenotype in melon fruit is associated with increased accumulation of n-alkanes, fatty alcohols, aldehydes and wax esters, which are linked with the deposition of crystal-like wax platelets on their surfaces. Together, this study broadens the understanding of natural variation in an important quality trait of melon fruit and promotes the future identification of the causative gene for the dominant white rind trait.

Analysis of surfactants by mass spectrometry: Coming to grips with their diversity.

Surfactants are surface-active agents widely used in numerous applications in our daily lives as personal care products, domestic, and industrial detergents. To determine complex mixtures of surfactants and their degradation products, unselective and rather insensitive methods, based on colorimetric and complexometric analyses are no longer employable. Analytical methodologies able to determine low concentration levels of surfactants and closely related compounds in complex matrices are required. The recent introduction of robust, sensitive, and selective mass spectrometry (MS) techniques has led to the rapid expansion of the surfactant research field including complex mixtures of isomers, oligomers, and homologues of surfactants as well as their chemically and biodegradation products at trace levels. In this review, emphasis is given to the state-of-the-art MS-based analysis of surfactants and their degradation products with an overview of the current research landscape from traditional methods involving hyphenate techniques (gas chromatography-MS and liquid chromatography-MS) to the most innovative approaches, based on high-resolution MS. Finally, we outline a detailed explanation on the utilization of MS for mechanistic purposes, such as the study of micelle formation in different solvents.

Comparison of plasma proteomic profiles of patients with Epstein-Barr virus-associated hemophagocytic lymphohistiocytosis and infectious mononucleosis.

Primary Epstein-Barr virus (EBV) infection occasionally causes EBV-infectious mononucleosis (EBV-IM) and EBV-hemophagocytic lymphohistiocytosis (EBV-HLH). Although EBV-IM is mostly mild and self-limiting, EBV-HLH is a life-threatening disease characterized by excessive immune activation. However, the pathogenesis of EBV-HLH is yet to be fully elucidated. A diagnostic biomarker for EBV-HLH is desirable because early diagnosis and treatment are critical for the effective management of patients. In this study, the proteomic profiling of plasma was performed using liquid chromatography-mass spectrometry to identify proteins specific to EBV-IM and EBV-HLH. Furthermore, pathway analysis was performed for the proteins upregulated in patients with EBV-IM and EBV-HLH. Compared to healthy controls, 63 and 18 proteins were upregulated in patients with EBV-IM and EBV-HLH, respectively. Pathway and process enrichment analyses revealed that the complement system was the most enriched category of upregulated proteins in EBV-IM, whereas proteins related to immune effector processes were the most enriched in EBV-HLH. Among the 18 proteins upregulated in EBV-HLH, seven were exclusive to EBV-HLH. These specific proteins were associated with three pathways, and apolipoprotein E was commonly found in all the pathways. Proteomic analysis may provide new insights into the host response to EBV infection and the pathogenesis of EBV-related diseases.

Mapping dynamic molecular changes in hippocampal subregions after traumatic brain injury through spatial proteomics.

BACKGROUND: Traumatic brain injury (TBI) often results in diverse molecular responses, challenging traditional proteomic studies that measure average changes at tissue levels and fail to capture the complexity and heterogeneity of the affected tissues. Spatial proteomics offers a solution by providing insights into sub-region-specific alterations within tissues. This study focuses on the hippocampal sub-regions, analyzing proteomic expression profiles in mice at the acute (1 day) and subacute (7 days) phases of post-TBI to understand subregion-specific vulnerabilities and long-term consequences. METHODS: Three mice brains were collected from each group, including Sham, 1-day post-TBI and 7-day post-TBI. Hippocampal subregions were extracted using Laser Microdissection (LMD) and subsequently analyzed by label-free quantitative proteomics. RESULTS: The spatial analysis reveals region-specific protein abundance changes, highlighting the elevation of FN1, LGALS3BP, HP, and MUG-1 in the stratum moleculare (SM), suggesting potential immune cell enrichment post-TBI. Notably, established markers of chronic traumatic encephalopathy, IGHM and B2M, exhibit specific upregulation in the dentate gyrus bottom (DG2) independent of direct mechanical injury. Metabolic pathway analysis identifies disturbances in glucose and lipid metabolism, coupled with activated cholesterol synthesis pathways enriched in SM at 7-Day post-TBI and subsequently in deeper DG1 and DG2 suggesting a role in neurogenesis and the onset of recovery. Coordinated activation of neuroglia and microtubule dynamics in DG2 suggest recovery mechanisms in less affected regions. Cluster analysis revealed spatial variations post-TBI, indicative of dysregulated neuronal plasticity and neurogenesis and further predisposition to neurological disorders. TBI-induced protein upregulation (MUG-1, PZP, GFAP, TJP, STAT-1, and CD44) across hippocampal sub-regions indicates shared molecular responses and links to neurological disorders. Spatial variations were demonstrated by proteins dysregulated in both or either of the time-points exclusively in each subregion (ELAVL2, CLIC1 in PL, CD44 and MUG-1 in SM, and SHOC2, LGALS3 in DG). CONCLUSIONS: Utilizing advanced spatial proteomics techniques, the study unveils the dynamic molecular responses in distinct hippocampal subregions post-TBI. It uncovers region-specific vulnerabilities and dysregulated neuronal processes, and potential recovery-related pathways that contribute to our understanding of TBI's neurological consequences and provides valuable insights for biomarker discovery and therapeutic targets.

Single and multi-dose pharmacology of recombinant and urinary human chorionic gonadotrophin in men.

OBJECTIVE: Human choriogonadotrophin (hCG) treatment of gonadotrophin-deficient infertile men uses hCG of urinary (uhCG) or recombinant (rhCG) origin, but these treatments have not been compared nor are there studies defining rhCG dosing in men. DESIGN: hCG products were studied in randomized cross-over single-dose studies of standard (Study 1, 1500 IU and 62.5 µg, respectively) or high (Study 2, 5000 IU and 250 µg) dose and a multi-dose population pharmacology study of hCG use. PARTICIPANTS: Eight (Study 1) and seven (Study 2) volunteers in cross-over and 52 gonadotrophin-deficient men in the multi-dose study MEASUREMENTS: In cross-over studies, serum testosterone (T), dihydrotestosterone (DHT) and estradiol by liquid chromatography-mass spectrometry (LCMS) and serum hCG, LH, FSH, SHBG and T (observational study) by immunoassays. RESULTS: After standard and high-dose injection, serum hCG and testosterone responses had similar timing and peak concentrations except for a mildly lower early (<48 h) serum testosterone with uhCG. In the multi-dosing study, both hCGs had similar pharmacokinetics (pooled half-life 5.8 days, p < .001), while serum testosterone concentrations were stable after injection and did not differ between hCG products. Bench testing verified that 20% of pens from 4/10 individuals were used inappropriately. CONCLUSIONS: Although hCG pharmacokinetics are not formally bioequivalent, the similar pharmacodynamic effects on serum testosterone indicate that at the doses tested both hCGs provide comparable clinical effects. The starting dose of rhCG for treating gonadotrophin-deficient men should be 62.5 µg (6 clicks) of the rhCG pen.

GC-MS metabolomics of French lettuce (Lactuca Sativa L. var capitata) leaves exposed to bisphenol A via the hydroponic media.

INTRODUCTION: Bisphenol A (BPA), an organic compound used to produce polycarbonate plastics and epoxy resins, has become a ubiquitous contaminant due to its high-volume production and constant release to the environment. Plant metabolomics can trace the stress effects induced by environmental contaminants to the variation of specific metabolites, making it an alternative way to study pollutants toxicity to plants. Nevertheless, there is an important knowledge gap in metabolomics applications in this area. OBJECTIVE: Evaluate the influence of BPA in French lettuce (Lactuca Sativa L. var capitata) leaves metabolic profile by gas chromatography coupled to mass spectrometry (GC-MS) using a hydroponic system. METHODS: Lettuces were cultivated in the laboratory to minimize biological variation and were analyzed 55 days after sowing (considered the plant's adult stage). Hexanoic and methanolic extracts with and without derivatization were prepared for each sample and analyzed by GC-MS. RESULTS: The highest number of metabolites was obtained from the hexanoic extract, followed by the derivatized methanolic extract. Although no physical differences were observed between control and contaminated lettuce leaves, the multivariate analysis determined a statistically significant difference between their metabolic profiles. Pathway analysis of the most affected metabolites showed that galactose metabolism, starch and fructose metabolism and steroid biosynthesis were significantly affected by BPA exposure. CONCLUSIONS: The preparation of different extracts from the same sample permitted the determination of metabolites with different physicochemical properties. BPA alters the leaves energy and membrane metabolism, plant growth could be affected at higher concentrations and exposition times.

Lipidomics random forest algorithm of seminal plasma is a promising method for enhancing the diagnosis of necrozoospermia.

BACKGROUND: Despite the clear clinical diagnostic criteria for necrozoospermia in andrology, the fundamental mechanisms underlying it remain elusive. This study aims to profile the lipid composition in seminal plasma systematically and to ascertain the potential of lipid biomarkers in the accurate diagnosis of necrozoospermia. It also evaluates the efficacy of a lipidomics-based random forest algorithm model in identifying necrozoospermia. METHODS: Seminal plasma samples were collected from patients diagnosed with necrozoospermia (n = 28) and normozoospermia (n = 28). Liquid chromatography-mass spectrometry (LC-MS) was used to perform lipidomic analysis and identify the underlying biomarkers. A lipid functional enrichment analysis was conducted using the LION lipid ontology database. The top 100 differentially significant lipids were subjected to lipid biomarker examination through random forest machine learning model. RESULTS: Lipidomic analysis identified 46 lipid classes comprising 1267 lipid metabolites in seminal plasma. The top five enriched lipid functions as follows: fatty acid (FA) with ≤ 18 carbons, FA with 16-18 carbons, monounsaturated FA, FA with 18 carbons, and FA with 16 carbons. The top 100 differentially significant lipids were subjected to machine learning analysis and identified 20 feature lipids. The random forest model identified lipids with an area under the curve > 0.8, including LPE(20:4) and TG(4:0_14:1_16:0). CONCLUSIONS: LPE(20:4) and TG(4:0_14:1_16:0), were identified as differential lipids for necrozoospermia. Seminal plasma lipidomic analysis could provide valuable biochemical information for the diagnosis of necrozoospermia, and its combination with conventional sperm analysis may improve the accuracy and reliability of the diagnosis.

Establishing a framework for best practices for quality assurance and quality control in untargeted metabolomics.

BACKGROUND: Quality assurance (QA) and quality control (QC) practices are key tenets that facilitate study and data quality across all applications of untargeted metabolomics. These important practices will strengthen this field and accelerate its success. The Best Practices Working Group (WG) within the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) focuses on community use of QA/QC practices and protocols and aims to identify, catalogue, harmonize, and disseminate current best practices in untargeted metabolomics through community-driven activities. AIM OF REVIEW: A present goal of the Best Practices WG is to develop a working strategy, or roadmap, that guides the actions of practitioners and progress in the field. The framework in which mQACC operates promotes the harmonization and dissemination of current best QA/QC practice guidance and encourages widespread adoption of these essential QA/QC activities for liquid chromatography-mass spectrometry. KEY SCIENTIFIC CONCEPTS OF REVIEW: Community engagement and QA/QC information gathering activities have been occurring through conference workshops, virtual and in-person interactive forum discussions, and community surveys. Seven principal QC stages prioritized by internal discussions of the Best Practices WG have received participant input, feedback and discussion. We outline these stages, each involving a multitude of activities, as the framework for identifying QA/QC best practices. The ultimate planned product of these endeavors is a "living guidance" document of current QA/QC best practices for untargeted metabolomics that will grow and change with the evolution of the field.

Development of metabolome extraction strategy for metabolite profiling of skin tissue.

INTRODUCTION: Changes in skin phenotypic characteristics are based on skin tissue. The study of the metabolic changes in skin tissue can help understand the causes of skin diseases and identify effective therapeutic interventions. OBJECTIVES: We aimed to establish and optimize a non-targeted skin metabolome extraction system for skin tissue metabolomics with high metabolite coverage, recovery, and reproducibility using gas chromatography/mass spectrometry. METHODS: The metabolites in skin tissues were extracted using eleven different extraction systems, which were designed using reagents with different polarities based on sequential solid-liquid extraction employing a two-step strategy and analyzed using gas chromatograph/mass spectrometry. The extraction efficiency of diverse solvents was evaluated by coefficient of variation (CV), multivariate analysis, metabolites coverage, and relative peak area analysis. RESULTS: We identified 119 metabolites and the metabolite profiles differed significantly between the eleven extraction systems. Metabolites with high abundances in the organic extraction systems, followed by aqueous extraction, were involved in the biosynthesis of unsaturated fatty acids, while metabolites with high abundances in the aqueous extraction systems, followed by organic extraction, were involved in amino sugar and nucleotide sugar metabolism, and glycerolipid metabolism. MeOH/chloroform-H2O and MeOH/H2O-chloroform were the extraction systems that yielded the highest number of metabolites, while MeOH/acetonitrile (ACN)-H2O and ACN/H2O-IPA exhibited superior metabolite recoveries. CONCLUSION: Our results demonstrated that our research facilitates the selection of an appropriate metabolite extraction approach based on the experimental purpose for the metabolomics study of skin tissue.

Metabolic profiling and biomarkers identification in cluster bean under drought stress using GC-MS technique.

INTRODUCTION: The Cluster bean is an economically significant annual legume, widely known as guar. Plant productivity is frequently constrained by drought conditions. OBJECTIVE: In this work, we have identified the untargeted drought stress-responsive metabolites in mature leaves of cluster beans under drought and control condition. METHODS: To analyse the untargeted metabolites, gas chromatography-mass spectrometry (GC-MS) technique was used. Supervised partial least-squares discriminate analysis and heat map were used to identify the most significant metabolites for drought tolerance. RESULTS: The mature leaves of drought-treated C. tetragonoloba cv. 'HG-365' which is a drought-tolerant cultivar, showed various types of amino acids, fatty acids, sugar alcohols and sugars as the major classes of metabolites recognized by GC-MS metabolome analysis. Metabolite profiling of guar leaves showed 23 altered metabolites. Eight metabolites (proline, valine, D-pinitol, palmitic acid, dodecanoic acid, threonine, glucose, and glycerol monostearate) with VIP score greater than one were considered as biomarkers and three metabolite biomarkers (D-pinitol, valine, and glycerol monostearate) were found for the first time in guar under drought stress. In this work, four amino acids (alanine, valine, serine and aspartic acid) were also studied, which played a significant role in drought-tolerant pathway in guar. CONCLUSION: This study provides information on the first-ever GC-MS metabolic profiling of guar. This work gives in-depth details on guar's untargeted drought-responsive metabolites and biomarkers, which can plausibly be used for further identification of biochemical pathways, enzymes, and the location of various genes under drought stress.