Correlations between LC-MS/MS-detected Glycomics and NMR-detected Metabolomics in Caenorhabditis (part-II) elegans Development.
Ontology highlight
ABSTRACT:
ORGANISM(S): Caenorhabditis Elegans
TISSUE(S): Worms
PROVIDER: ST001183 | MetabolomicsWorkbench |
REPOSITORIES: MetabolomicsWorkbench
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| mwtab | Other |
Items per page: 5 1 - 1 of 1 |
Similar Datasets
Project description:This study examined the relationship between glycans, metabolites, and development in C. elegans. Samples of N2 animals were synchronized and grown to five different time points ranging from L1 to a mixed population of adults, gravid adults, and offspring. Each time point was replicated seven times. The samples were each assayed by a large particle flow cytometer (Biosorter) for size distribution data, LC-MS/MS for targeted N- and O-linked glycans, and NMR for metabolites. The same samples were utilized for all measurements, which allowed for statistical correlations between the data. A new protocol was developed to correlate Biosorter developmental data with LC-MS/MS data to obtain stage-specific information of glycans. From the five time points, four distinct sizes of worms were observed from the Biosorter distributions, ranging from the smallest corresponding to L1 to adult animals. A network model was constructed using the four binned sizes of worms as starting nodes and adding glycans and metabolites that had correlations with r ≥ 0.5 to those nodes. The emerging structure of the network showed distinct patterns of N- and O-linked glycans that were consistent with previous studies. Furthermore, some metabolites that were correlated to these glycans and worm sizes showed interesting interactions. Of note, UDP-GlcNAc had strong positive correlations with many O-glycans that were expressed in the largest animals. Similarly, phosphorylcholine correlated with many N-glycans that were expressed in L1 animals.
| S-EPMC6611444 | biostudies-literature
Project description:BackgroundEsophageal adenocarcinoma (EAC) is a rarely curable disease and is rapidly rising worldwide in incidence. Barret's esophagus (BE) and high-grade dysplasia (HGD) are considered major risk factors for invasive adenocarcinoma. In the current study, unbiased global metabolic profiling methods were applied to serum samples from patients with EAC, BE and HGD, and healthy individuals, in order to identify metabolite based biomarkers associated with the early stages of EAC with the goal of improving prognostication.Methodology/principal findingsSerum metabolite profiles from patients with EAC (n?=?67), BE (n?=?3), HGD (n?=?9) and healthy volunteers (n?=?34) were obtained using high performance liquid chromatography-mass spectrometry (LC-MS) methods. Twelve metabolites differed significantly (p<0.05) between EAC patients and healthy controls. A partial least-squares discriminant analysis (PLS-DA) model had good accuracy with the area under the receiver operative characteristic curve (AUROC) of 0.82. However, when the results of LC-MS were combined with 8 metabolites detected by nuclear magnetic resonance (NMR) in a previous study, the combination of NMR and MS detected metabolites provided a much superior performance, with AUROC?=?0.95. Further, mean values of 12 of these metabolites varied consistently from healthy controls to the high-risk individuals (BE and HGD patients) and EAC subjects. Altered metabolic pathways including a number of amino acid pathways and energy metabolism were identified based on altered levels of numerous metabolites.Conclusions/significanceMetabolic profiles derived from the combination of LC-MS and NMR methods readily distinguish EAC patients and potentially promise important routes to understanding the carcinogenesis and detecting the cancer. Differences in the metabolic profiles between high-risk individuals and the EAC indicate the possibility of identifying the patients at risk much earlier to the development of the cancer.
| S-EPMC3264576 | biostudies-literature
Project description:Transcriptome of long-lived naked-mole rat (NMR) oligodendrocyte progenitor cells (OPCs) were compared with OPCs of other species.
2022-03-31 | E-MTAB-9160 | biostudies-arrayexpress
Project description:Liquid chromatography (LC) separation combined with electrochemical coulometric array detection (EC) is a sensitive, reproducible, and robust technique that can detect hundreds of redox-active metabolites down to the level of femtograms on column, making it ideal for metabolomics profiling. EC detection cannot, however, structurally characterize unknown metabolites that comprise these profiles. Several aspects of LC-EC methods prevent a direct transfer to other structurally informative analytical methods, such as LC-MS and NMR. These include system limits of detection, buffer requirements, and detection mechanisms. To address these limitations, we developed a workflow based on the concentration of plasma, metabolite extraction, and offline LC-UV fractionation. Pooled human plasma was used to provide sufficient material necessary for multiple sample concentrations and platform analyses. Offline parallel LC-EC and LC-MS methods were established that correlated standard metabolites between the LC-EC profiling method and the mass spectrometer. Peak retention times (RT) from the LC-MS and LC-EC system were linearly related (r(2) = 0.99); thus, LC-MS RTs could be directly predicted from the LC-EC signals. Subsequent offline microcoil-NMR analysis of these collected fractions was used to confirm LC-MS characterizations by providing complementary, structural data. This work provides a validated workflow that is transferrable across multiple platforms and provides the unambiguous structural identifications necessary to move primary mathematically driven LC-EC biomarker discovery into biological and clinical utility.
| S-EPMC3502645 | biostudies-literature
Project description:Many species from the Pinaceae family have been recognized as a rich source of lignans, flavonoids, and other polyphenolics. The great common occurrence of conifers in Europe, as well as their use in the wood industry, makes both plant material and industrial waste material easily accessible and inexpensive. This is a promising prognosis for both discovery of new active compounds as well as for finding new applications for wood and its industry waste products. This study aimed to analyze and phytochemically profile 13 wood extracts of the Pinaceae family species, endemic or introduced in Polish flora, using the LC-DAD-ESI-MS/MS method and compare their respective metabolite profiles. Branch wood methanolic extracts were phytochemically profiled. Lignans, stilbenes, flavonoids, diterpenes, procyanidins, and other compounds were detected, with a considerable variety of chemical content among distinct species. Norway spruce (Picea abies (L.) H.Karst.) branch wood was the most abundant source of stilbenes, European larch (Larix decidua Mill.) mostly contained flavonoids, while silver fir (Abies alba Mill.) was rich in lignans. Furthermore, 10 lignans were isolated from the studied material. Our findings confirm that wood industry waste materials, such as conifer branches, can be a potent source of different phytochemicals, with the plant matrix being relatively simple, facilitating future isolation of target compounds.
| S-EPMC9600761 | biostudies-literature
Project description:Hepcidin-25 was identified as the main iron regulator in the human body, and it by binds to the sole iron-exporter ferroportin. Studies showed that the N-terminus of hepcidin is responsible for this interaction, the same N-terminus that encompasses a small copper(II)-binding site known as the ATCUN (amino-terminal Cu(II)- and Ni(II)-binding) motif. Interestingly, this copper-binding property is largely ignored in most papers dealing with hepcidin-25. In this context, detailed investigations of the complex formed between hepcidin-25 and copper could reveal insight into its biological role. The present work focuses on metal-bound hepcidin-25 that can be considered the biologically active form. The first part is devoted to the reversed-phase chromatographic separation of copper-bound and copper-free hepcidin-25 achieved by applying basic mobile phases containing 0.1% ammonia. Further, mass spectrometry (tandem mass spectrometry (MS/MS), high-resolution mass spectrometry (HRMS)) and nuclear magnetic resonance (NMR) spectroscopy were employed to characterize the copper-peptide. Lastly, a three-dimensional (3D) model of hepcidin-25 with bound copper(II) is presented. The identification of metal complexes and potential isoforms and isomers, from which the latter usually are left undetected by mass spectrometry, led to the conclusion that complementary analytical methods are needed to characterize a peptide calibrant or reference material comprehensively. Quantitative nuclear magnetic resonance (qNMR), inductively-coupled plasma mass spectrometry (ICP-MS), ion-mobility spectrometry (IMS) and chiral amino acid analysis (AAA) should be considered among others.
| S-EPMC6121404 | biostudies-literature
Project description:Pollinator services and the development of beekeeping as a poverty alleviating tool have gained considerable focus in recent years in sub-Saharan Africa. An improved understanding of the pervasive environmental extent of agro-chemical contaminants is critical to the success of beekeeping development and the production of clean hive products. This study developed and validated a multi-residue method for screening 36 pesticides in honeybees, honey and beeswax using LC-MS/MS and GC-ECD. Of the 36 screened pesticides, 20 were detected. The highest frequencies occurred in beeswax and in samples from apiaries located in the proximity of citrus and tobacco farms. Fungicides were the most prevalent chemical class. Detected insecticides included neonicotinoids, organophosphates, carbamates, organophosphorus, tetrazines and diacylhydrazines. All detected pesticide levels were below maximum residue limits (according to EU regulations) and the lethal doses known for honeybees. However, future risk assessment is needed to determine the health effects on the African genotype of honeybees by these pesticide classes and combinations of these. In conclusion, our data present a significant challenge to the burgeoning organic honey sector in Uganda, but to achieve this, there is an urgent need to regulate the contact routes of pesticides into the beehive products. Interestingly, the "zero" detection rate of pesticides in the Mid-Northern zone is a significant indicator of the large potential to promote Ugandan organic honey for the export market.
| S-EPMC5453540 | biostudies-literature
Project description: Not available
| ST001182 | MetabolomicsWorkbench
Project description:BackgroundAlzheimer's Disease (AD) is a complex and multifactorial disease and novel approaches are needed to illuminate the underlying pathology. Metabolites comprise the end-product of genes, transcripts, and protein regulations and might reflect disease pathogenesis. Blood is a common biofluid used in metabolomics; however, since extracellular vesicles (EVs) hold cell-specific biological material and can cross the blood-brain barrier, their utilization as biological material warrants further investigation. We aimed to investigate blood- and EV-derived metabolites to add insigts to the pathological mechanisms of AD.MethodsBlood samples were collected from 10 AD and 10 Mild Cognitive Impairment (MCI) patients, and 10 healthy controls. EVs were enriched from plasma using 100,000×g, 1 h, 4 °C with a wash. Metabolites from serum and EVs were measured using liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy. Multivariate and univariate analyses were employed to identify altered metabolites in cognitively impaired individuals.ResultsWhile no significant EV-derived metabolites were found differentiating patients from healthy individuals, six serum metabolites were found important; valine (p = 0.001, fold change, FC = 0.8), histidine (p = 0.001, FC = 0.9), allopurinol riboside (p = 0.002, FC = 0.2), inosine (p = 0.002, FC = 0.3), 4-pyridoxic acid (p = 0.006, FC = 1.6), and guanosine (p = 0.004, FC = 0.3). Pathway analysis revealed branched-chain amino acids, purine and histidine metabolisms to be downregulated, and vitamin B6 metabolism upregulated in patients compared to controls.ConclusionUsing a combination of LC-MS and NMR methodologies we identified several altered mechanisms possibly related to AD pathology. EVs require additional optimization prior to their possible utilization as a biological material for AD-related metabolomics studies.
| S-EPMC8479251 | biostudies-literature
Project description:Insulin is as a major postprandial hormone with profound effects on carbohydrate, fat, and protein metabolism. In the absence of exogenous insulin, patients with type 1 diabetes exhibit a variety of metabolic abnormalities including hyperglycemia, glycosurea, accelerated ketogenesis, and muscle wasting due to increased proteolysis. We analyzed plasma from type 1 diabetic (T1D) humans during insulin treatment (I+) and acute insulin deprivation (I-) and non-diabetic participants (ND) by (1)H nuclear magnetic resonance spectroscopy and liquid chromatography-tandem mass spectrometry. The aim was to determine if this combination of analytical methods could provide information on metabolic pathways known to be altered by insulin deficiency. Multivariate statistics differentiated proton spectra from I- and I+ based on several derived plasma metabolites that were elevated during insulin deprivation (lactate, acetate, allantoin, ketones). Mass spectrometry revealed significant perturbations in levels of plasma amino acids and amino acid metabolites during insulin deprivation. Further analysis of metabolite levels measured by the two analytical techniques indicates several known metabolic pathways that are perturbed in T1D (I-) (protein synthesis and breakdown, gluconeogenesis, ketogenesis, amino acid oxidation, mitochondrial bioenergetics, and oxidative stress). This work demonstrates the promise of combining multiple analytical methods with advanced statistical methods in quantitative metabolomics research, which we have applied to the clinical situation of acute insulin deprivation in T1D to reflect the numerous metabolic pathways known to be affected by insulin deficiency.
| S-EPMC2866659 | biostudies-literature