scholarly journals Metabolic Characterisation of Magnetospirillum Gryphiswaldense MSR-1 Using LC-MS-Based Metabolite Profiling

2020 ◽  
Author(s):  
Salah Abdelrazig ◽  
Laudina Safo ◽  
Graham A Rance ◽  
Michael W Fay ◽  
Eirini Theodosiou ◽  
...  
Keyword(s):  
Magnetic Nanoparticles ◽  
Metabolic Pathways ◽  
Metabolic Networks ◽  
Citric Acid Cycle ◽  
Metabolite Identification ◽  
Liquid Chromatography Mass Spectrometry ◽  
Magnetospirillum Gryphiswaldense ◽  
Pathway Enrichment ◽  
Wide Range ◽  
Metabolite Database

<p>Magnetosomes are nano-sized magnetic nanoparticles with exquisite properties that can be used in a wide range of healthcare and biotechnological applications. They are biosynthesised by magnetotactic bacteria (MTB) such as <i>Magnetospirillum gryphiswaldense </i>MSR-1 (<i>Mgryph</i>). However, magnetosome bioprocessing yields low quantities compared to chemical synthesis of magnetic nanoparticles. Therefore, the understanding of the intracellular metabolites and the metabolic networks related to <i>Mgryph</i> growth and magnetosome formation are vital to unlock the potential of this organism to develop improved bioprocesses. In this work, we investigated the metabolism of <i>Mgryph</i> using untargeted metabolomics. Liquid chromatography-mass spectrometry (LC-MS) was performed to profile spent medium samples of <i>Mgryph </i>cells grown under O<sub>2</sub>-limited (n=6) and O<sub>2</sub>-rich conditions (n=6) corresponding to magnetosome- and non-magnetosome producing cells, respectively. Cross-validated multivariate, univariate and pathway enrichment analyses were conducted to identify significantly altered metabolites and pathways. Rigorous metabolite identification was carried out using authentic standards, <i>Mgryph-</i>specific metabolite database<i> </i>and<i> </i>MS/MS mzCloud database. PCA and OPLS-DA showed clear separation and clustering of sample groups with cross-validation values of R<sup>2</sup>X=0.76, R<sup>2</sup>Y=0.99 and Q<sup>2</sup>=0.98 in OPLS-DA. As a result, 50 metabolites linked to 45 metabolic pathways were found significantly altered in the tested conditions including glycine, serine and threonine; butanoate; alanine, aspartate and glutamate metabolism; aminoacyl-tRNA biosynthesis and; pyruvate and citric acid cycle (TCA) metabolisms. Our findings demonstrate the potential of LC-MS to characterise key metabolites in <i>Mgryph</i> and will contribute to further understand the metabolic mechanisms that affect <i>Mgryph</i> growth and magnetosome formation. <i></i></p>

scholarly journals Metabolic Characterisation of Magnetospirillum Gryphiswaldense MSR-1 Using LC-MS-Based Metabolite Profiling

2020 ◽  
Author(s):  
Salah Abdelrazig ◽  
Laudina Safo ◽  
Graham A Rance ◽  
Michael W Fay ◽  
Eirini Theodosiou ◽  
...  
Keyword(s):  
Magnetic Nanoparticles ◽  
Metabolic Pathways ◽  
Metabolic Networks ◽  
Citric Acid Cycle ◽  
Metabolite Identification ◽  
Liquid Chromatography Mass Spectrometry ◽  
Magnetospirillum Gryphiswaldense ◽  
Pathway Enrichment ◽  
Wide Range ◽  
Metabolite Database

<p>Magnetosomes are nano-sized magnetic nanoparticles with exquisite properties that can be used in a wide range of healthcare and biotechnological applications. They are biosynthesised by magnetotactic bacteria (MTB) such as <i>Magnetospirillum gryphiswaldense </i>MSR-1 (<i>Mgryph</i>). However, magnetosome bioprocessing yields low quantities compared to chemical synthesis of magnetic nanoparticles. Therefore, the understanding of the intracellular metabolites and the metabolic networks related to <i>Mgryph</i> growth and magnetosome formation are vital to unlock the potential of this organism to develop improved bioprocesses. In this work, we investigated the metabolism of <i>Mgryph</i> using untargeted metabolomics. Liquid chromatography-mass spectrometry (LC-MS) was performed to profile spent medium samples of <i>Mgryph </i>cells grown under O<sub>2</sub>-limited (n=6) and O<sub>2</sub>-rich conditions (n=6) corresponding to magnetosome- and non-magnetosome producing cells, respectively. Cross-validated multivariate, univariate and pathway enrichment analyses were conducted to identify significantly altered metabolites and pathways. Rigorous metabolite identification was carried out using authentic standards, <i>Mgryph-</i>specific metabolite database<i> </i>and<i> </i>MS/MS mzCloud database. PCA and OPLS-DA showed clear separation and clustering of sample groups with cross-validation values of R<sup>2</sup>X=0.76, R<sup>2</sup>Y=0.99 and Q<sup>2</sup>=0.98 in OPLS-DA. As a result, 50 metabolites linked to 45 metabolic pathways were found significantly altered in the tested conditions including glycine, serine and threonine; butanoate; alanine, aspartate and glutamate metabolism; aminoacyl-tRNA biosynthesis and; pyruvate and citric acid cycle (TCA) metabolisms. Our findings demonstrate the potential of LC-MS to characterise key metabolites in <i>Mgryph</i> and will contribute to further understand the metabolic mechanisms that affect <i>Mgryph</i> growth and magnetosome formation. <i></i></p>

scholarly journals Metabolomic and Proteomic Profiles Associated With Ketosis in Dairy Cows

2020 ◽  
Vol 11 ◽  
Author(s):  
Zhou-Lin Wu ◽  
Shi-Yi Chen ◽  
Shenqiang Hu ◽  
Xianbo Jia ◽  
Jie Wang ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Metabolic Pathways ◽  
Protein Modification ◽  
Transition Period ◽  
Strong Correlations ◽  
Liquid Chromatography Mass Spectrometry ◽  
Serum Samples ◽  
Data Independent Acquisition ◽  
Wide Range ◽  
Proteomics Approach

Ketosis is a common metabolic disease in dairy cows during early lactation. However, information about the metabolomic and proteomic profiles associated with the incidence and progression of ketosis is still limited. In this study, an integrated metabolomics and proteomics approach was performed on blood serum sampled from cows diagnosed with clinical ketosis (case, ≥ 2.60 mmol/L plasma β-hydroxybutyrate; BHBA) and healthy controls (control, &lt; 1.0 mmol/L BHBA). Samples were taken 2 weeks before parturition and 2 weeks after parturition from 19 animals (nine cases, 10 controls). All serum samples (n = 38) were subjected to Liquid Chromatography-Mass Spectrometry (LC-MS) based metabolomic analysis, and 20 samples underwent Data-Independent Acquisition (DIA) LC-MS based proteomic analysis. A total of 97 metabolites and 540 proteins were successfully identified, and multivariate analysis revealed significant differences in both metabolomic and proteomic profiles between cases and controls. We investigated clinical ketosis-associated metabolomic and proteomic changes using statistical analyses. Correlation analysis of statistically significant metabolites and proteins showed 78 strong correlations (correlation coefficient, R ≥ 0.7) between 38 metabolites and 25 proteins, which were then mapped to pathways using IMPaLA. Results showed that ketosis altered a wide range of metabolic pathways, such as metabolism, metabolism of proteins, gene expression and post-translational protein modification, vitamin metabolism, signaling, and disease related pathways. Findings presented here are relevant for identifying molecular targets for ketosis and biomarkers for ketosis detection during the transition period.

scholarly journals Plasma metabolic characterisation of dairy cows with inactive ovaries and oestrus during the peak of lactation

2019 ◽  
Vol 63 (3) ◽  
pp. 359-367 ◽  
Author(s):  
Yu-Xi Song ◽  
Pan Hu ◽  
Yun-Long Bai ◽  
Chang Zhao ◽  
Cheng Xia ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Dairy Cows ◽  
Cholic Acid ◽  
Metabolic Pathways ◽  
Metabolic Networks ◽  
Dairy Farm ◽  
Signal Transduction Pathways ◽  
Plasma Samples ◽  
Liquid Chromatography Mass Spectrometry ◽  
Multivariate Pattern

Abstract Introduction Differential metabolites (DMs) between cows with inactive ovaries (IO) and oestrous (E) cows were screened and metabolic pathways of DMs associated with IO were determined. Material and Methods Cows at 50 to 60 days (d) postpartum from an intensive dairy farm were randomly selected and allocated into an E group (n = 16) or an IO group (n = 16) according to a pedometer and rectal examinations. Their plasma samples were analysed by liquid chromatography–mass spectrometry (LC–MS) to compare plasma metabolic changes between the E and IO groups. Multivariate pattern recognition was used to screen the DMs in the plasma of IO cows. Results Compared with normal E cows, there were abnormalities in 20 metabolites in IO cows, including a significantly decreased content (VIP > 1, P < 0.05) of cholic acid, p-chlorophenylalanine, and arachidonic acid, and a significantly increased content (VIP > 1, P < 0.05) of tyramine, betaine, L-phenylalanine, L-glutamate, D-proline, L-alanine, and L-pyrophosphate. Five DMs (cholic acid, D-proline, L-glutamate, L-alanine, and L-pyroglutamic acid) with higher variable importance in projection (VIP) values between groups were validated by ELISA with blind samples of re-selected cows (IO, 50 to 60 d postpartum) and the validated results were consistent with the LC–MS results. Conclusion The 20 DMs in IO cows during the peak of lactation indicated that the pathogenesis of IO was involved in complex metabolic networks and signal transduction pathways. This study provides a basis for further exploration of the pathogenesis and prevention of IO in cows in the future.

scholarly journals The Ability of Metabolomics to Discriminate Non-Small-Cell Lung Cancer Subtypes Depends on the Stage of the Disease and the Type of Material Studied

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3314
Author(s):  
Tomasz Kowalczyk ◽  
Joanna Kisluk ◽  
Karolina Pietrowska ◽  
Joanna Godzien ◽  
Miroslaw Kozlowski ◽  
...  
Keyword(s):  
Metabolic Pathways ◽  
Early Stage ◽  
Chronic Obstructive ◽  
Liquid Chromatography Mass Spectrometry ◽  
Obstructive Pulmonary Disease ◽  
Cell Lung Carcinoma ◽  
Cancer Subtypes ◽  
Inflammatory State ◽  
Nsclc Patients

Identification of the NSCLC subtype at an early stage is still quite sophisticated. Metabolomics analysis of tissue and plasma of NSCLC patients may indicate new, and yet unknown, metabolic pathways active in the NSCLC. Our research characterized the metabolomics profile of tissue and plasma of patients with early and advanced NSCLC stage. Samples were subjected to thorough metabolomics analyses using liquid chromatography-mass spectrometry (LC-MS) technique. Tissue and/or plasma samples from 137 NSCLC patients were analyzed. Based on the early stage tissue analysis, more than 200 metabolites differentiating adenocarcinoma (ADC) and squamous cell lung carcinoma (SCC) subtypes as well as normal tissue, were identified. Most of the identified metabolites were amino acids, fatty acids, carnitines, lysoglycerophospholipids, sphingomyelins, plasmalogens and glycerophospholipids. Moreover, metabolites related to N-acyl ethanolamine (NAE) biosynthesis, namely glycerophospho (N-acyl) ethanolamines (GP-NAE), which discriminated early-stage SCC from ADC, have also been identified. On the other hand, the analysis of plasma of chronic obstructive pulmonary disease (COPD) and NSCLC patients allowed exclusion of the metabolites related to the inflammatory state in lungs and the identification of compounds (lysoglycerophospholipids, glycerophospholipids and sphingomyelins) truly characteristic to cancer. Our results, among already known, showed novel, thus far not described, metabolites discriminating NSCLC subtypes, especially in the early stage of cancer. Moreover, the presented results also indicated the activity of new metabolic pathways in NSCLC. Further investigations on the role of NAE biosynthesis pathways in the early stage of NSCLC may reveal new prognostic and diagnostic targets.

scholarly journals Dynamic histone acetylation in floral volatile synthesis and emission in petunia flowers

2021 ◽  
Author(s):  
Ryan M Patrick ◽  
Xing-Qi Huang ◽  
Natalia Dudareva ◽  
Ying Li
Keyword(s):  
Transcriptional Activation ◽  
Metabolic Pathways ◽  
Transcriptional Repression ◽  
Metabolic Networks ◽  
Underlying Mechanism ◽  
Expression Of Genes ◽  
Genome Wide ◽  
Chemical Inhibitors ◽  
Volatile Organic ◽  
Floral Volatile

Abstract Biosynthesis of secondary metabolites relies on primary metabolic pathways to provide precursors, energy, and cofactors, thus requiring coordinated regulation of primary and secondary metabolic networks. However, to date, it remains largely unknown how this coordination is achieved. Using Petunia hybrida flowers, which emit high levels of phenylpropanoid/benzenoid volatile organic compounds (VOCs), we uncovered genome-wide dynamic deposition of histone H3 lysine 9 acetylation (H3K9ac) during anthesis as an underlying mechanism to coordinate primary and secondary metabolic networks. The observed epigenome reprogramming is accompanied by transcriptional activation at gene loci involved in primary metabolic pathways that provide precursor phenylalanine, as well as secondary metabolic pathways to produce volatile compounds. We also observed transcriptional repression among genes involved in alternative phenylpropanoid branches that compete for metabolic precursors. We show that GNAT family histone acetyltransferase(s) (HATs) are required for the expression of genes involved in VOC biosynthesis and emission, by using chemical inhibitors of HATs, and by knocking down a specific HAT gene, ELP3, through transient RNAi. Together, our study supports that regulatory mechanisms at chromatin level may play an essential role in activating primary and secondary metabolic pathways to regulate VOC synthesis in petunia flowers.

Identification of novel cardiovascular disease associated metabolites using untargeted metabolomics

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Shams Tabrez ◽  
Mohammed Razeeth Shait Mohammed ◽  
Nasimudeen R. Jabir ◽  
Mohammad Imran Khan
Keyword(s):  
Cardiovascular Disease ◽  
Metabolic Pathways ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Healthy Individuals ◽  
Great Opportunity ◽  
Pathway Enrichment ◽  
Pathophysiological Role ◽  
The World ◽  
Metabolomic Approach

Abstract Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality around the world. Early diagnosis of CVD could provide the opportunity for sensible management and better clinical outcome along with the prevention of further progression of the disease. In the current study, we used an untargeted metabolomic approach to identify possible metabolite(s) that associate well with the CVD and could serve either as therapeutic target or disease-associated metabolite. We identified 26 rationally adjusted unique metabolites that were differentially present in the serum of CVD patients compared with healthy individuals, among them 15 were found to be statistically significant. Out of these metabolites, we identified some novel metabolites like UDP-l-rhamnose and N1-acetylspermidine that have not been reported to be linked with CVD directly. Further, we also found that some metabolites like ethanolamide, solanidine, dimethylarginine, N-acetyl-l-tyrosine, can act as a discriminator of CVD. Metabolites integrating pathway enrichment analysis showed enrichment of various important metabolic pathways like histidine metabolism, methyl histidine metabolism, carnitine synthesis, along with arginine and proline metabolism in CVD patients. Our study provides a great opportunity to understand the pathophysiological role and impact of the identified unique metabolites and can be extrapolated as specific CVD specific metabolites.

scholarly journals Comprehensive Plasma Metabolomic Profile of Patients with Advanced Neuroendocrine Tumors (NETs). Diagnostic and Biological Relevance

Cancers ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 2634
Author(s):  
Beatriz Soldevilla ◽  
Angeles López-López ◽  
Alberto Lens-Pardo ◽  
Carlos Carretero-Puche ◽  
Angeles Lopez-Gonzalvez ◽  
...  
Keyword(s):  
Metabolic Pathways ◽  
Metabolic Networks ◽  
Tca Cycle ◽  
Metabolomic Profile ◽  
Diagnostic Potential ◽  
The Tca Cycle ◽  
Novel Biomarkers ◽  
Potential Methods ◽  
Clinical Potential ◽  
First Time

Purpose: High-throughput “-omic” technologies have enabled the detailed analysis of metabolic networks in several cancers, but NETs have not been explored to date. We aim to assess the metabolomic profile of NET patients to understand metabolic deregulation in these tumors and identify novel biomarkers with clinical potential. Methods: Plasma samples from 77 NETs and 68 controls were profiled by GC−MS, CE−MS and LC−MS untargeted metabolomics. OPLS-DA was performed to evaluate metabolomic differences. Related pathways were explored using Metaboanalyst 4.0. Finally, ROC and OPLS-DA analyses were performed to select metabolites with biomarker potential. Results: We identified 155 differential compounds between NETs and controls. We have detected an increase of bile acids, sugars, oxidized lipids and oxidized products from arachidonic acid and a decrease of carnitine levels in NETs. MPA/MSEA identified 32 enriched metabolic pathways in NETs related with the TCA cycle and amino acid metabolism. Finally, OPLS-DA and ROC analysis revealed 48 metabolites with diagnostic potential. Conclusions: This study provides, for the first time, a comprehensive metabolic profile of NET patients and identifies a distinctive metabolic signature in plasma of potential clinical use. A reduced set of metabolites of high diagnostic accuracy has been identified. Additionally, new enriched metabolic pathways annotated may open innovative avenues of clinical research.

scholarly journals Placental 13C-DHA metabolism and relationship with maternal BMI, glycemia and birthweight

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Oliver C. Watkins ◽  
Preben Selvam ◽  
Reshma Appukuttan Pillai ◽  
Victoria K. B. Cracknell-Hazra ◽  
Hannah E. J. Yong ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Liquid Chromatography ◽  
Lipid Metabolism ◽  
Metabolic Pathways ◽  
Liquid Chromatography Mass Spectrometry ◽  
Fasting Glycemia ◽  
Glucose Treatment ◽  
Maternal Bmi

Abstract Background Fetal docosahexaenoic acid (DHA) supply relies on preferential transplacental transfer, which is regulated by placental DHA lipid metabolism. Maternal hyperglycemia and obesity associate with higher birthweight and fetal DHA insufficiency but the role of placental DHA metabolism is unclear. Methods Explants from 17 term placenta were incubated with 13C-labeled DHA for 48 h, at 5 or 10 mmol/L glucose treatment, and the production of 17 individual newly synthesized 13C-DHA labeled lipids quantified by liquid chromatography mass spectrometry. Results Maternal BMI positively associated with 13C-DHA-labeled diacylglycerols, triacylglycerols, lysophospholipids, phosphatidylcholine and phosphatidylethanolamine plasmalogens, while maternal fasting glycemia positively associated with five 13C-DHA triacylglycerols. In turn, 13C-DHA-labeled phospholipids and triacylglycerols positively associated with birthweight centile. In-vitro glucose treatment increased most 13C-DHA-lipids, but decreased 13C-DHA phosphatidylethanolamine plasmalogens. However, with increasing maternal BMI, the magnitude of the glucose treatment induced increase in 13C-DHA phosphatidylcholine and 13C-DHA lysophospholipids was curtailed, with further decline in 13C-DHA phosphatidylethanolamine plasmalogens. Conversely, with increasing birthweight centile glucose treatment induced increases in 13C-DHA triacylglycerols were exaggerated, while glucose treatment induced decreases in 13C-DHA phosphatidylethanolamine plasmalogens were diminished. Conclusions Maternal BMI and glycemia increased the production of different placental DHA lipids implying impact on different metabolic pathways. Glucose-induced elevation in placental DHA metabolism is moderated with higher maternal BMI. In turn, findings of associations between many DHA lipids with birthweight suggest that BMI and glycemia promote fetal growth partly through changes in placental DHA metabolism.

P0031AURINE METABOLOMICS: AN EMERGING TOOL FOR DISSECTING BIOLOGICAL ABERRATIONS UNDERLYING RENAL DYSFUNCTION IN BARDET-BIEDL SYNDROME

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Miriam Zacchia ◽  
Emanuela Marchese ◽  
Marianna Caterino ◽  
Margherita Ruoppolo ◽  
Giovambattista Capasso
Keyword(s):  
Lactic Acid ◽  
Kidney Disease ◽  
Renal Disease ◽  
Renal Dysfunction ◽  
Metabolic Pathways ◽  
Healthy Subjects ◽  
Hexadecenoic Acid ◽  
Kidney Dysfunction ◽  
Bardet Biedl Syndrome ◽  
Wide Range

Abstract Background and Aims Bardet Biedl Syndrome (BBS) is a rare genetic disorder characterized by a wide range of organ dysfunction, including kidney disease. The severity of renal dysfunction is highly variable in this setting, ranging from tubular defects to the end stage renal disease, with poor genotype-phenotype correlation. Proteomics and metabolomics are powerful tools able to contribute to the better understanding of molecular basis of disease conditions. Our previous studies demonstrated that the urinary proteomic pattern of BBS patients differed from that of healthy subjects, with a set of deregulated proteins including cell adhesion and extracellular matrix organization proteins (1). The present study aims to characterize urine metabolomic profile of BBS patients, in order to identify both 1) potential disease biomarkers and 2) aberrant metabolic pathways underlying renal disease Method To this end, in the pilot study urine samples have been collected from 14 adult BBS patients and have been compared with healthy volunteers, using an untargeted strategy. In the confirmation study, 24 BBS patients with wide range of kidney dysfunction have been enrolled, and additional control groups, besides healthy subjects, were included: 1) age-gender-matched chronic kidney disease patients by other causes and 2) obese individuals. Results Several metabolites were de-regulated in BBS patients compared with normal subjects (lactic acid, glycolic acid,3-Hydroxypropionic acid, pyruvic acid, 3-hydroxyisobutyric acid, 2-ethyl-3-hydroxy-propionic acid, succinic acid, fumaric acid, erythropentonic acid, 2-hydroxyglutaric acid, 4-hydroxyphenyllactic acid, 3,4-pyridinedicarboxylic acid, retinoic acid, 4-hydroxyphenylacetic acid, palmitic acid, 9-Hexadecenoic acid, oleic acid and 9-Octadecenoic acid). The clusterization performed by MetaboAnalyst tool, revealed a possible deregulation of different metabolic pathways, including glycolysis, TCA cycle, pyruvate metabolism, lipids biosynthesis and glutamate metabolism (p-value &lt;0.01) (figure 1); some of these pathways were described as de-regulated in other ciliopathies (2). In the confirmation study (on-going studies) some metabolites, including lactic acid and intermediates of Krebs cycle, correlated with kidney dysfunction only in the BBS group. Conclusion These findings suggest that urine metabolomic fingerprint of BBS patients is different from that of healthy subjects and indicate a possible deregulation of several metabolic pathways; some urinary molecules correlated with kidney dysfunction only in BBS patients, suggesting the specificity of these results.

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