PubMed

EBioMedicine. 2023 Jul 6;94:104704. doi: 10.1016/j.ebiom.2023.104704. Online ahead of print.ABSTRACTBACKGROUND: Lipids serve as multifunctional metabolites that have important implications for the pregnant mother and developing fetus. Abnormalities in lipids have emerged as potential risk factors for pregnancy diseases, such as preeclampsia and fetal growth restriction. The aim of this study was to assess the potential of lipid metabolites for detection of late-onset preeclampsia and fetal growth restriction.METHODS: We used a case-cohort of 144 maternal plasma samples at 36 weeks' gestation from patients before the diagnosis of late-onset preeclampsia (n = 22), delivery of a fetal growth restricted infant (n = 55, defined as <5th birthweight centile), gestation-matched controls (n = 72). We performed liquid chromatography-tandem mass spectrometry (LC-QQQ) -based targeted lipidomics to identify 421 lipids, and fitted logistic regression models for each lipid, correcting for maternal age, BMI, smoking, and gestational diabetes.FINDINGS: Phosphatidylinositol 32:1 (AUC = 0.81) and cholesterol ester 17:1 (AUC = 0.71) best predicted the risk of developing preeclampsia or delivering a fetal growth restricted infant, respectively. Five times repeated five-fold cross validation demonstrated the lipids alone did not out-perform existing protein biomarkers, soluble tyrosine kinase-1 (sFlt-1) and placental growth factor (PlGF) for the prediction of preeclampsia or fetal growth restriction. However, lipids combined with sFlt-1 and PlGF measurements improved disease prediction.INTERPRETATION: This study successfully identified 421 lipids in maternal plasma collected at 36 weeks' gestation from participants who later developed preeclampsia or delivered a fetal growth restricted infant. Our results suggest the predictive capacity of lipid measurements for gestational disorders holds the potential to improve non-invasive assessment of maternal and fetal health.FUNDING: This study was funded by a grant from National Health and Medical Research Council.PMID:37421807 | DOI:10.1016/j.ebiom.2023.104704

Food Chem. 2023 Jul 5;428:136770. doi: 10.1016/j.foodchem.2023.136770. Online ahead of print.ABSTRACTThis study aimed to examine the effect of fermentation methods on the quality of Lycium barbarum and Polygonatum cyrtonema compound wine (LPW) by combining non-targeted metabolomic approaches with chemometrics and path profiling to determine the chemical and metabolic properties of LPW. The results demonstrated that SRA had higher leaching rates of total phenols and flavonoids, reaching 4.20 ± 0.10 v/v ethanol concentration. According to LC-MS non-targeting genomics, the metabolic profiles of LPW prepared by different mixtures of fermentation methods (Saccharomyces cerevisiae RW; Debaryomyces hansenii AS2.45) of yeast differed significantly. Amino acids, phenylpropanoids, flavonols, etc., were identified as the differential metabolites between different comparison groups. The pathways of tyrosine metabolism, biosynthesis of phenylpropanoids, and metabolism of 2-oxocarboxylic acids enriched 17 distinct metabolites. SRA stimulated the production of tyrosine and imparted a distinctive saucy aroma to the wine samples, providing a novel research concept for the microbial fermentation-based production of tyrosine.PMID:37421664 | DOI:10.1016/j.foodchem.2023.136770

J Agric Food Chem. 2023 Jul 8. doi: 10.1021/acs.jafc.3c02381. Online ahead of print.ABSTRACTLacticaseibacillus rhamnosus Probio-M9 (Probio-M9) is increasingly used as a co-fermentation culture in fermented milk production. Recently, a capsular polysaccharide (CPS)- and exopolysaccharide (EPS)-producing mutant of Probio-M9, HG-R7970-3, was generated by space mutagenesis. This study compared the performance of cow and goat milk fermentation between the non-CPS/-EPS-producing parental strain (Probio-M9) and the CPS/EPS producer (HG-R7970-3), and the stability of products fermented by the two bacteria. Our results showed that using HG-R7970-3 as the fermentative culture could improve the probiotic viable counts, physico-chemical, texture, and rheological properties in both cow and goat milk fermentation. Substantial differences were also observed in the metabolomics profiles between fermented cow and goat milks produced by the two bacteria. Comparing with Probio-M9-fermented cow and goat milks, those fermented by HG-R7970-3 were enriched in a number of flavor compounds and potential functional components, particularly acids, esters, peptides, and intermediate metabolites. Moreover, HG-R7970-3 could improve the post-fermentation flavor retention capacity. These new and added features are of potential to improve the techno-functional qualities of conventional fermented milks produced by Probio-M9, and these differences are likely imparted by the acquired CPS-/EPS-producing ability of the mutant. It merits further investigation into the sensory quality and in vivo function of HG-R7970-3-fermented milks.PMID:37421368 | DOI:10.1021/acs.jafc.3c02381

J Am Heart Assoc. 2023 Jul 8:e029873. doi: 10.1161/JAHA.123.029873. Online ahead of print.ABSTRACTBackground Nonalcoholic fatty liver disease (NAFLD) and heart failure with preserved ejection fraction (HFpEF) share common risk factors, including obesity and diabetes. They are also thought to be mechanistically linked. The aim of this study was to define serum metabolites associated with HFpEF in a cohort of patients with biopsy-proven NAFLD to identify common mechanisms. Methods and Results We performed a retrospective, single-center study of 89 adult patients with biopsy-proven NAFLD who had transthoracic echocardiography performed for any indication. Metabolomic analysis was performed on serum using ultrahigh performance liquid and gas chromatography/tandem mass spectrometry. HFpEF was defined as ejection fraction >50% plus at least 1 echocardiographic feature of HFpEF (diastolic dysfunction, abnormal left atrial size) and at least 1 heart failure sign or symptom. We performed generalized linear models to evaluate associations between individual metabolites, NAFLD, and HFpEF. Thirty-seven out of 89 (41.6%) patients met criteria for HFpEF. A total of 1151 metabolites were detected; 656 were analyzed after exclusion of unnamed metabolites and those with >30% missing values. Fifty-three metabolites were associated with the presence of HFpEF with unadjusted P value <0.05; none met statistical significance after adjustment for multiple comparisons. The majority (39/53, 73.6%) were lipid metabolites, and levels were generally increased. Two cysteine metabolites (cysteine s-sulfate and s-methylcysteine) were present at significantly lower levels in patients with HFpEF. Conclusions We identified serum metabolites associated with HFpEF in patients with biopsy-proven NAFLD, with increased levels of multiple lipid metabolites. Lipid metabolism could be an important pathway linking HFpEF to NAFLD.PMID:37421270 | DOI:10.1161/JAHA.123.029873

Brain Behav. 2023 Jul 8:e3070. doi: 10.1002/brb3.3070. Online ahead of print.ABSTRACTINTRODUCTION: Medical management of disorders of consciousness (DoC) is a growing issue imposing a major burden on families and societies. Recovery rates vary widely among patients with DoC, and recovery predictions strongly influence decisions on medical care. However, the specific mechanisms underlying different etiologies, consciousness levels, and prognoses are still unclear.METHODS: We analyzed the comprehensive cerebrospinal fluid (CSF) metabolome through liquid chromatography-mass spectrometry. Metabolomic analyses were used to identify the metabolic differences between patients with different etiologies, diagnoses, and prognoses.RESULTS: We found that the CSF levels of multiple acylcarnitines were lower in patients with traumatic DoC, suggesting mitochondrial function preservation in the CNS, which might contribute to the better consciousness outcomes of these patients. Metabolites related to glutamate and GABA metabolism were altered and showed a good ability to distinguish the patients in the minimally conscious state and the vegetative state. Moreover, we identified 8 phospholipids as potential biomarkers to predict the recovery of consciousness.CONCLUSIONS: Our findings shed light on the differences in physiological activities underlying DoC with different etiologies and identified some potential biomarkers used for DoC diagnosis and prognosis.PMID:37421239 | DOI:10.1002/brb3.3070

New Phytol. 2023 Jul 8. doi: 10.1111/nph.19060. Online ahead of print.ABSTRACTRoot traits including root exudates are key factors affecting plant interactions with soil and thus play an important role in determining ecosystem processes. The drivers of their variation, however, remain poorly understood. We determined the relative importance of phylogeny and species ecology in determining root traits and analyzed the extent to which root exudate composition can be predicted by other root traits. We measured different root morphological and biochemical traits (including exudate profiles) of 65 plant species grown in a controlled system. We tested phylogenetic conservatism in traits and disentangled the individual and overlapping effects of phylogeny and species ecology on traits. We also predicted root exudate composition using other root traits. Phylogenetic signal differed greatly among root traits, with the strongest signal in phenol content in plant tissues. Interspecific variation in root traits was partly explained by species ecology, but phylogeny was more important in most cases. Species exudate composition could be partly predicted by specific root length, root dry matter content, root biomass, and root diameter, but a large part of variation remained unexplained. In conclusion, root exudation cannot be easily predicted based on other root traits and more comparative data on root exudation are needed to understand their diversity.PMID:37421208 | DOI:10.1111/nph.19060

Sensors (Basel). 2023 Jun 6;23(12):5366. doi: 10.3390/s23125366.ABSTRACTThe various areas of ultra-sensitive remote sensing research equipment development have provided new ways for assessing crop states. However, even the most promising areas of research, such as hyperspectral remote sensing or Raman spectrometry, have not yet led to stable results. In this review, the main methods for early plant disease detection are discussed. The best proven existing techniques for data acquisition are described. It is discussed how they can be applied to new areas of knowledge. The role of metabolomic approaches in the application of modern methods for early plant disease detection and diagnosis is reviewed. A further direction for experimental methodological development is indicated. The ways to increase the efficiency of modern early plant disease detection remote sensing methods through metabolomic data usage are shown. This article provides an overview of modern sensors and technologies for assessing the biochemical state of crops as well as the ways to apply them in synergy with existing data acquisition and analysis technologies for early plant disease detection.PMID:37420533 | DOI:10.3390/s23125366

Lipids Health Dis. 2023 Jul 7;22(1):97. doi: 10.1186/s12944-023-01863-7.ABSTRACTBACKGROUND: The common inflammatory disease multiple sclerosis (MS) is a disease of the central nervous system. For more than 25 years autologous hematopoietic stem cell transplantation (AHSCT) has been used to treat MS. It has been shown to be highly effective in suppressing inflammatory activity in relapsing-remitting MS (RRMS) patients. This treatment is thought to lead to an immune system reset, inducing a new, more tolerant system; however, the precise mechanism behind the treatment effect in MS patients is unknown. In this study, the effect of AHSCT on the metabolome and lipidome in peripheral blood from RRMS patients was investigated.METHODS: Peripheral blood samples were collected from 16 patients with RRMS at ten-time points over the five months course of AHSCT and 16 MS patients not treated with AHSCT. Metabolomics and lipidomics analysis were performed using liquid-chromatography high-resolution mass spectrometry. Mixed linear models, differential expression analysis, and cluster analysis were used to identify differentially expressed features and groups of features that could be of interest. Finally, in-house and in-silico libraries were used for feature identification, and enrichment analysis was performed.RESULTS: Differential expression analysis found 657 features in the lipidomics dataset and 34 in the metabolomics dataset to be differentially expressed throughout AHSCT. The administration of cyclophosphamide during mobilization and conditioning was associated with decreased concentrations in glycerophosphoinositol species. Thymoglobuline administration was associated with an increase in ceramide and glycerophosphoethanolamine species. After the conditioning regimen, a decrease in glycerosphingoidlipids concentration was observed, and following hematopoietic stem cell reinfusion glycerophosphocholine concentrations decreased for a short period of time. Ceramide concentrations were strongly associated with leukocyte levels during the procedure. The ceramides Cer(d19:1/14:0) and Cer(d20:1/12:0) were found to be increased (P < .05) in concentration at the three-month follow-up compared to baseline. C16 ceramide, Cer(D18:2/16:0), and CerPE(d16:2(4E,6E)/22:0) were found to be significantly increased in concentration after AHSCT compared to prior to treatment as well as compared to newly diagnosed RRMS patients.CONCLUSION: AHSCT had a larger impact on the lipids in peripheral blood compared to metabolites. The variation in lipid concentration reflects the transient changes in the peripheral blood milieu during the treatment, rather than the changes in the immune system that are assumed to be the cause of clinical improvement within RRMS patients treated with AHSCT. Ceramide concentrations were affected by AHSCT and associated with leukocyte counts and were altered three months after treatment, suggesting a long-lasting effect.PMID:37420217 | DOI:10.1186/s12944-023-01863-7

Nat Commun. 2023 Jul 7;14(1):4027. doi: 10.1038/s41467-023-39788-5.ABSTRACTIgG3 is unique among the IgG subclasses due to its extended hinge, allotypic diversity and enhanced effector functions, including highly efficient pathogen neutralisation and complement activation. It is also underrepresented as an immunotherapeutic candidate, partly due to a lack of structural information. Here, we use cryoEM to solve structures of antigen-bound IgG3 alone and in complex with complement components. These structures reveal a propensity for IgG3-Fab clustering, which is possible due to the IgG3-specific flexible upper hinge region and may maximise pathogen neutralisation by forming high-density antibody arrays. IgG3 forms elevated hexameric Fc platforms that extend above the protein corona to maximise binding to receptors and the complement C1 complex, which here adopts a unique protease conformation that may precede C1 activation. Mass spectrometry reveals that C1 deposits C4b directly onto specific IgG3 residues proximal to the Fab domains. Structural analysis shows this to be caused by the height of the C1-IgG3 complex. Together, these data provide structural insights into the role of the unique IgG3 extended hinge, which will aid the development and design of upcoming immunotherapeutics based on IgG3.PMID:37419978 | DOI:10.1038/s41467-023-39788-5

J Immunother Cancer. 2023 Jul;11(7):e006785. doi: 10.1136/jitc-2023-006785.ABSTRACTBACKGROUND: Most immunotherapies approved for clinical use rely on the use of recombinant proteins and cell-based approaches, rendering their manufacturing expensive and logistics onerous. The identification of novel small molecule immunotherapeutic agents might overcome such limitations.METHOD: For immunopharmacological screening campaigns, we built an artificial miniature immune system in which dendritic cells (DCs) derived from immature precursors present MHC (major histocompatibility complex) class I-restricted antigen to a T-cell hybridoma that then secretes interleukin-2 (IL-2).RESULTS: The screening of three drug libraries relevant to known signaling pathways, FDA (Food and Drug Administration)-approved drugs and neuroendocrine factors yielded two major hits, astemizole and ikarugamycin. Mechanistically, ikarugamycin turned out to act on DCs to inhibit hexokinase 2, hence stimulating their antigen presenting potential. In contrast, astemizole acts as a histamine H1 receptor (H1R1) antagonist to activate T cells in a non-specific, DC-independent fashion. Astemizole induced the production of IL-2 and interferon-γ (IFN-γ) by CD4+ and CD8+ T cells both in vitro and in vivo. Both ikarugamycin and astemizole improved the anticancer activity of the immunogenic chemotherapeutic agent oxaliplatin in a T cell-dependent fashion. Of note, astemizole enhanced the CD8+/Foxp3+ ratio in the tumor immune infiltrate as well as IFN-γ production by local CD8+ T lymphocytes. In patients with cancer, high H1R1 expression correlated with low infiltration by TH1 cells, as well as with signs of T-cell exhaustion. The combination of astemizole and oxaliplatin was able to cure the majority of mice bearing orthotopic non-small cell lung cancers (NSCLC), then inducing a state of protective long-term immune memory. The NSCLC-eradicating effect of astemizole plus oxaliplatin was lost on depletion of either CD4+ or CD8+ T cells, as well as on neutralization of IFN-γ.CONCLUSIONS: These findings underscore the potential utility of this screening system for the identification of immunostimulatory drugs with anticancer effects.PMID:37419511 | DOI:10.1136/jitc-2023-006785

J Am Soc Mass Spectrom. 2023 Jul 7. doi: 10.1021/jasms.3c00084. Online ahead of print.ABSTRACTOptimization of mass spectrometric parameters for a data dependent acquisition (DDA) experiment is essential to increase the MS/MS coverage and hence increase metabolite identifications in untargeted metabolomics. We explored the influence of mass spectrometric parameters including mass resolution, radio frequency (RF) level, signal intensity threshold, number of MS/MS events, cycle time, collision energy, maximum ion injection time (MIT), dynamic exclusion, and automatic gain control (AGC) target value on metabolite annotations on an Exploris 480-Orbitrap mass spectrometer. Optimal annotation results were obtained by performing ten data dependent MS/MS scans with a mass isolation window of 2.0 m/z and a minimum signal intensity threshold of 1 × 104 at a mass resolution of 180,000 for MS and 30,000 for MS/MS, while maintaining the RF level at 70%. Furthermore, combining an AGC target value of 5 × 106 and MIT of 100 ms for MS and an AGC target value of 1 × 105 and an MIT of 50 ms for MS/MS scans provided an improved number of annotated metabolites. A 10 s exclusion duration and a two stepped collision energy were optimal for higher spectral quality. These findings confirm that MS parameters do influence metabolomics results, and propose strategies for increasing metabolite coverage in untargeted metabolomics. A limitation of this work is that our parameters were only optimized for one RPLC method on single matrix and may be different for other protocols. Additionally, no metabolites were identified at level 1 confidence. The results presented here are based on metabolite annotations and need to be validated with authentic standards.PMID:37419493 | DOI:10.1021/jasms.3c00084

Sci Total Environ. 2023 Jul 5:165287. doi: 10.1016/j.scitotenv.2023.165287. Online ahead of print.ABSTRACTChemical pollution and global warming are two major threats to reptiles, and these two factors can interact with each other. Glyphosate have attracted worldwide attention due to their ubiquitous occurrence, yet their impact on reptiles remains unknown. We designed a crossover experiment with different external GBH exposures (control/GBH) x different environmental temperatures (current climate treatment/warmer climate treatment) over 60 days to simulate environmental exposure in the Mongolian Racerunner lizard (Eremias argus). Preferred body temperature and active body temperature data were collected to calculate the accuracy of thermoregulation, while liver detoxification metabolic enzymes, oxidative stress system function, and the non-targeted metabolome of the brain tissue were assessed. Warmer-treated lizards adjusted their physiological levels and behavioral strategies in response to increased ambient temperatures and maintained body temperature homeostasis at moderate thermal perturbations. GBH-treated lizards suffered from oxidative damage to the brain tissue and abnormal histidine metabolism, thus their thermoregulatory accuracy reduced. Interestingly, at elevated ambient temperatures, GBH treatment did not affect on their thermoregulatory, possibly through several temperature-dependent detoxification mechanisms. Importantly, this data suggested that the subtle toxicological effects of GBH may threaten increasingly thermoregulation behavior of E. argus with species-wide repercussions, as climate change and exposure time extension.PMID:37419359 | DOI:10.1016/j.scitotenv.2023.165287

J Ethnopharmacol. 2023 Jul 5:116878. doi: 10.1016/j.jep.2023.116878. Online ahead of print.ABSTRACTETHNOPHARMACOLOGICAL RELEVANCE: Acanthopanax senticosus (Rupr.et.Maxim.)Harms(AS) is an extract of Eleutherococcus senticocus Maxim(Rupr.et.Maxim.). In modern medical interpretation, Acanthopanax senticosus can be used to treat Parkinson's disease, and a large number of modern pharmacological and clinical studies also support this application. Our study demonstrated that AS extracts can increase the activity of various antioxidant enzymes and improve the symptoms of Parkinson's disease in mice.AIM OF THE STUDY: The current study looked at the protective effect of Acanthopanax senticosus extracts(ASE) in preventing PD.METHODS AND MATERIALS: First, the α-syn-overexpressing mice were chosen as suitable models for Parkinson's disease in vivo. HE staining was used to observe the pathological changes in the substantia nigra. Meanwhile, TH expression in substantia nigra was analyzed by immunohistochemistry. Behavioral and biochemical tests evaluated neuroprotective effects of ASE on PD mice. Subsequently, combined with proteomics and metabolomics analysis, the changes in brain proteins and metabolites in mice treated with ASE for PD were studied. Finally, Western blot was used to detect metabolome-related and proteomic proteins in the brain tissue of α-syn mice.RESULTS: Forty-nine common differentially expressed proteins were screened by proteomics analysis, among which 28 were significantly up-regulated,and 21 were significantly down-regulated. Metabolomics analysis showed that twenty-five potentially important metabolites were involved in the therapeutic effect of ASE on PD. Most of the different proteins and metabolites were considered to be enriched in a variety of species in metabolic pathways, including glutathione metabolism and alanine aspartate and glutamate metabolism and other pathways, which means that ASE may have molecular mechanisms to ameliorate PD dysfunction. In addition, we found that decreases in glutathione and glutathione disulfide levels may play a critical role in these systemic changes and warrant further investigation. In the glutathione metabolic pathway, ASE also acts on GPX4, GCLC and GCLM.CONCLUSIONS: ASE can effectively relieve behavioral symptoms of α-syn mice and relieve oxidative stress in brain tissue. These findings suggest that ASE offers a potential solution to target these pathways for the treatment of PD.PMID:37419226 | DOI:10.1016/j.jep.2023.116878

Ecotoxicol Environ Saf. 2023 Jul 5;263:115195. doi: 10.1016/j.ecoenv.2023.115195. Online ahead of print.ABSTRACTBiological organisms are exposed to low-dose arsenic or N-nitro compounds (NOCs) alone or in combination worldwide, especially in areas with high cancer prevalence through drinking water or food exposure; however, information on their combined exposure effects is limited. Here, we conducted an in-depth study of the effects on the gut microbiota, metabolomics, and signaling pathways using rat models exposed to arsenic or N-methyl-N'-nitro-N-nitrosoguanidine (MNNG), one of the most active carcinogenic NOCs, separately or in combination with metabolomics and high-throughput sequencing. Compared to exposure alone, combined exposure to arsenic and MNNG exacerbated damage to gastric tissue morphology, interfered with intestinal microflora and substance metabolism, and exerted a stronger carcinogenic effect. This may be related to intestinal microbiota disorders, including Dyella, Oscillibacter, Myroides, and metabolic pathways such as glycine, serine, and threonine metabolism, arginine biosynthesis, central carbon metabolism in cancer, and purine and pyrimidine metabolism, thereby enhancing the cancer-causing effects of gonadotrophin-releasing hormone (GnRH), P53, and Wnt signaling pathways.PMID:37418937 | DOI:10.1016/j.ecoenv.2023.115195

Food Chem. 2023 Jul 4;428:136803. doi: 10.1016/j.foodchem.2023.136803. Online ahead of print.ABSTRACTUntargeted metabolomics based on ultra-high-performance liquid chromatography coupled with high-resolution mass spectrometry was combined with sensory analysis to provide new insights into the impact of the feeding system from mountain regions (grassland deriving from permanent meadows) on the chemical fingerprint of Parmigiano Reggiano PDO hard cheese. In the framework of a representative investigation, two different ripening times (12 and 24 months) were also considered. Multivariate statistics allowed discriminating cheese samples from different feeding regimens according to their metabolomics signatures. Interestingly, mountain grassland-based cheese samples were characterized by a more favourable fatty acid profile, recording also feed-derived compounds (such as terpenoids and linoleic acid derivatives) potentially associated with both beneficial effects on human health and sensory properties. According to the sensory analysis, the impact of herbs and grass enhanced the colour and retro-olfactive complexity of Parmigiano Reggiano PDO cheese, with spicy, umami and intense vegetal aromatic notes representing distinctive features.PMID:37418876 | DOI:10.1016/j.foodchem.2023.136803

Int J Surg. 2023 Jul 6. doi: 10.1097/JS9.0000000000000577. Online ahead of print.NO ABSTRACTPMID:37418572 | DOI:10.1097/JS9.0000000000000577

Tree Physiol. 2023 Jul 7:tpad087. doi: 10.1093/treephys/tpad087. Online ahead of print.ABSTRACTMetabolomics studies are becoming increasingly common for understanding how plant metabolism responds to changes in environmental conditions, genetic manipulations, and treatments. Despite the recent advances in metabolomics workflow, the sample preparation process still limits the high-throughput analysis in large-scale studies. Here, we present a highly flexible robotic system that integrates liquid handling, sonication, centrifugation, solvent evaporation, and sample transfer processed in 96-well plates to automatize the metabolite extraction from leaf samples. We transferred an established manual extraction protocol performed to a robotic system, and with this, we show the optimization steps required to improve reproducibility and obtain comparable results in terms of extraction efficiency and accuracy. We then tested the robotic system to analyze the metabolomes of wild-type and four transgenic silver birch (Betula pendula) lines under unstressed conditions. Birch trees were engineered to overexpress the poplar (Populus x canescens) isoprene synthase (PcISPS) and emit various amounts of isoprene. By fitting the different isoprene emission capacities of the transgenic trees with their leaf metabolomes, we observed an isoprene-dependent upregulation of some flavonoids and other secondary metabolites as well as carbohydrates, amino acid and lipid metabolites. In contrast, the disaccharide sucrose was found to be strongly negatively correlated to isoprene emission. The presented study illustrates the power of integrating robotics to increase sample throughput, reduce human errors and labor time, and ensure a fully controlled, monitored, and standardized sample preparation procedure. Due to its modular and flexible structure, the robotic system can be easily adapted to other extraction protocols for the analysis of various tissues or plant species to achieve high-throughput metabolomics in plant research.PMID:37418159 | DOI:10.1093/treephys/tpad087

Theor Appl Genet. 2023 Jul 7;136(8):169. doi: 10.1007/s00122-023-04412-z.ABSTRACTBy integrating QTL mapping, transcriptomics and metabolomics, 138 hub genes were identified in rapeseed root response to aluminum stress and mainly involved in metabolism of lipids, carbohydrates and secondary metabolites. Aluminum (Al) toxicity has become one of the important abiotic stress factors in areas with acid soil, which hinders the absorption of water and nutrients by roots, and consequently retards the growth of crops. A deeper understanding of the stress-response mechanism of Brassica napus may allow us to identify the tolerance gene(s) and use this information in breeding-resistant crop varieties. In this study, a population of 138 recombinant inbred lines (RILs) was subjected to aluminum stress, and QTL (quantitative trait locus) mapping was used to preliminarily locate quantitative trait loci related to aluminum stress. Root tissues from seedlings of an aluminum-resistant (R) line and an aluminum-sensitive (S) line from the RIL population were harvested for transcriptome sequencing and metabolome determination. By combining the data on quantitative trait genes (QTGs), differentially expressed genes (DEGs), and differentially accumulated metabolites (DAMs), key candidate genes related to aluminum tolerance in rapeseed were determined. The results showed that there were 3186 QTGs in the RIL population, 14,232 DEGs and 457 DAMs in the comparison between R and S lines. Lastly, 138 hub genes were selected to have a strong positive or negative correlation with 30 important metabolites (|R|≥ 0.95). These genes were mainly involved in the metabolism of lipids, carbohydrates and secondary metabolites in response to Al toxicity stress. In summary, this study provides an effective method for screening key genes by combining QTLs, transcriptome sequencing and metabolomic analysis, but also lists key genes for exploring the molecular mechanism of Al tolerance in rapeseed seedling roots.PMID:37418156 | DOI:10.1007/s00122-023-04412-z

Metabolomics. 2023 Jul 7;19(7):65. doi: 10.1007/s11306-023-02028-4.ABSTRACTINTRODUCTION: Absolute quantification of individual metabolites in complex biological samples is crucial in targeted metabolomic profiling.OBJECTIVES: An inter-laboratory test was performed to evaluate the impact of the NMR software, peak-area determination method (integration vs. deconvolution) and operator on quantification trueness and precision.METHODS: A synthetic urine containing 32 compounds was prepared. One site prepared the urine and calibration samples, and performed NMR acquisition. NMR spectra were acquired with two pulse sequences including water suppression used in routine analyses. The pre-processed spectra were sent to the other sites where each operator quantified the metabolites using internal referencing or external calibration, and his/her favourite in-house, open-access or commercial NMR tool.RESULTS: For 1D NMR measurements with solvent presaturation during the recovery delay (zgpr), 20 metabolites were successfully quantified by all processing strategies. Some metabolites could not be quantified by some methods. For internal referencing with TSP, only one half of the metabolites were quantified with a trueness below 5%. With peak integration and external calibration, about 90% of the metabolites were quantified with a trueness below 5%. The NMRProcFlow integration module allowed the quantification of several additional metabolites. The number of quantified metabolites and quantification trueness improved for some metabolites with deconvolution tools. Trueness and precision were not significantly different between zgpr- and NOESYpr-based spectra for about 70% of the variables.CONCLUSION: External calibration performed better than TSP internal referencing. Inter-laboratory tests are useful when choosing to better rationalize the choice of quantification tools for NMR-based metabolomic profiling and confirm the value of spectra deconvolution tools.PMID:37418094 | DOI:10.1007/s11306-023-02028-4

J Bone Miner Metab. 2023 Jul 7. doi: 10.1007/s00774-023-01449-4. Online ahead of print.ABSTRACTINTRODUCTION: The increase of ATP concentration in the extracellular space represents one of the effective signals that stimulate the physiological activities of cells when the bone is exposed to external mechanical stimulation such as stretching and shear stress force throughout life. However, the effects of ATP on osteoblast differentiation and related mechanisms are not well understood.MATERIALS AND METHODS: In this study, the roles of extracellular ATP on osteoblast differentiation, intracellular calcium ([Ca2+]i) levels, metabolomics, and the expression of proteins related to energy metabolism were investigated.RESULTS: Our results showed that 100 μM extracellular ATP initiated intracellular calcium ([Ca2+]i) oscillations via the calcium-sensing receptor (P2R) and promoted the differentiation of MC3T3-E1 cells. Metabolomics analysis showed that the differentiation of MC3T3-E1 cells depended on aerobic oxidation, but little glycolysis. Moreover, the differentiation of MC3T3-E1 cells and aerobic oxidation were suppressed with the inhibition of AMP-activated protein kinase (AMPK).CONCLUSION: These results indicate that calcium oscillations triggered by extracellular ATP can activate aerobic oxidation through AMPK-related signaling pathways and thus promote osteoblast differentiation.PMID:37418073 | DOI:10.1007/s00774-023-01449-4