PubMed

Related Articles Dual cationic-anionic profiling of metabolites in a single identified cell in a live Xenopus laevis embryo by microprobe CE-ESI-MS. Analyst. 2019 Jan 28;144(3):892-900 Authors: Portero EP, Nemes P Abstract In situ capillary microsampling with capillary electrophoresis (CE) electrospray ionization (ESI) mass spectrometry (MS) enabled the characterization of cationic metabolites in single cells in complex tissues and organisms. For deeper coverage of the metabolome and metabolic networks, analytical approaches are needed that provide complementary detection for anionic metabolites, ideally using the same instrumentation. Described here is one such approach that enables sequential cationic and anionic (dual) analysis of metabolites in the same identified cell in a live vertebrate embryo. A calibrated volume was microaspirated from the animal-ventral cell in a live 8-cell embryo of Xenopus laevis, and cationic and anionic metabolites were one-pot microextracted from the aspirate, followed by CE-ESI-MS analysis of the same extract. A laboratory-built CE-ESI interface was reconfigured to enable dual cationic-anionic analysis with ∼5-10 nM (50-100 amol) lower limit of detection and a capability for quantification. To provide robust separation and efficient ion generation, the CE-ESI interface was enclosed in a nitrogen gas filled chamber, and the operational parameters were optimized for the cone-jet spraying regime in both the positive and negative ion mode. A total of ∼250 cationic and ∼200 anionic molecular features were detected from the cell between m/z 50-550, including 60 and 24 identified metabolites, respectively. With only 11 metabolites identified mutually, the duplexed approach yielded complementary information on metabolites produced in the cell, which in turn deepened network coverage for several metabolic pathways. With scalability to smaller cells and adaptability to other types of tissues and organisms, dual cationic-anionic detection with in situ microprobe CE-ESI-MS opens a door to better understand cell metabolism. PMID: 30542678 [PubMed - indexed for MEDLINE]

Related Articles Recent advances in single-cell analysis by mass spectrometry. Analyst. 2019 Jan 28;144(3):824-845 Authors: Yin L, Zhang Z, Liu Y, Gao Y, Gu J Abstract Cells are the most basic structural units that play vital roles in the functioning of living organisms. Analysis of the chemical composition and content of a single cell plays a vital role in ensuring precise investigations of cellular metabolism, and is a crucial aspect of lipidomic and proteomic studies. In addition, structural knowledge provides a better understanding of cell behavior as well as the cellular and subcellular mechanisms. However, single-cell analysis can be very challenging due to the very small size of each cell as well as the large variety and extremely low concentrations of substances found in individual cells. On account of its high sensitivity and selectivity, mass spectrometry holds great promise as an effective technique for single-cell analysis. Numerous mass spectrometric techniques have been developed to elucidate the molecular profiles at the cellular level, including electrospray ionization mass spectrometry (ESI-MS), secondary ion mass spectrometry (SIMS), laser-based mass spectrometry and inductively coupled plasma mass spectrometry (ICP-MS). In this review, the recent advances in single-cell analysis by mass spectrometry are summarized. The strategies of different ionization modes to achieve single-cell analysis are classified and discussed in detail. PMID: 30334031 [PubMed - indexed for MEDLINE]

Related Articles Anaerobic nitrate reduction divergently governs population expansion of the enteropathogen Vibrio cholerae. Nat Microbiol. 2018 12;3(12):1346-1353 Authors: Bueno E, Sit B, Waldor MK, Cava F Abstract To survive and proliferate in the absence of oxygen, many enteric pathogens can undergo anaerobic respiration within the host by using nitrate (NO3-) as an electron acceptor1,2. In these bacteria, NO3- is typically reduced by a nitrate reductase to nitrite (NO2-), a toxic intermediate that is further reduced by a nitrite reductase3. However, Vibrio cholerae, the intestinal pathogen that causes cholera, lacks a nitrite reductase, leading to NO2- accumulation during nitrate reduction4. Thus, V. cholerae is thought to be unable to undergo NO3--dependent anaerobic respiration4. Here, we show that during hypoxic growth, NO3- reduction in V. cholerae divergently affects bacterial fitness in a manner dependent on environmental pH. Remarkably, in alkaline conditions, V. cholerae can reduce NO3- to support population growth. Conversely, in acidic conditions, accumulation of NO2- from NO3- reduction simultaneously limits population expansion and preserves cell viability by lowering fermentative acid production. Interestingly, other bacterial species such as Salmonella typhimurium, enterohaemorrhagic Escherichia coli (EHEC) and Citrobacter rodentium also reproduced this pH-dependent response, suggesting that this mechanism might be conserved within enteric pathogens. Our findings explain how a bacterial pathogen can use a single redox reaction to divergently regulate population expansion depending on the fluctuating environmental pH. PMID: 30275512 [PubMed - indexed for MEDLINE]

Related Articles Lipidomics for translational skin research: A primer for the uninitiated. Exp Dermatol. 2018 07;27(7):721-728 Authors: Kendall AC, Koszyczarek MM, Jones EA, Hart PJ, Towers M, Griffiths CEM, Morris M, Nicolaou A Abstract Healthy skin depends on a unique lipid profile to form a barrier that confers protection and prevents excessive water loss, aids cell-cell communication and regulates cutaneous homoeostasis and inflammation. Alterations in the cutaneous lipid profile can have severe consequences for skin health and have been implicated in numerous inflammatory skin conditions. Thus, skin lipidomics is increasingly of interest, and recent developments in mass spectrometry-based analytical technologies can deliver in-depth investigation of cutaneous lipids, providing insight into their role and mechanism of action. The choice of tissue sampling technique and analytical approach depends on the location and chemistry of the lipid of interest. Lipidomics can be conducted by various mass spectrometry approaches, including different chromatography and ionisation techniques. Targeted mass spectrometry is a sensitive approach for measuring low-abundance signalling lipids, such as eicosanoids, endocannabinoids and ceramides. This approach requires specific extraction, chromatography and mass spectrometry protocols to quantitate the lipid targets. Untargeted mass spectrometry reveals global changes and allows analysis of hundreds of complex lipids across a range of lipid classes, including phospholipids, glycerophospholipids, cholesteryl esters and sphingolipids. Mass spectrometry lipid imaging, including matrix-assisted laser desorption ionisation mass spectrometry and desorption electrospray ionisation mass spectrometry, can reveal information about abundance and anatomical distribution of lipids within a single skin sample. Skin lipidomics can provide qualitative and quantitative data on hundreds of biologically relevant lipid species with different properties and activities, all found within a single skin sample, and support translational studies exploring the involvement of lipids in skin health and disease. PMID: 29654617 [PubMed - indexed for MEDLINE]

Related Articles Dysregulation of methionine metabolism in multiple sclerosis. Neurochem Int. 2018 01;112:1-4 Authors: Singhal NK, Freeman E, Arning E, Wasek B, Clements R, Sheppard C, Blake P, Bottiglieri T, McDonough J Abstract We report a significant reduction in plasma methionine concentrations in relapse remitting multiple sclerosis (MS) patients compared to controls. In vivo studies demonstrate that changes in peripheral methionine levels in mice can regulate histone H3 methylation and expression of DNA methyltransferase 3A (DNMT3A) centrally, in the cerebral cortex. Therefore, we propose that decreases in circulating methionine represent one of the earliest manifestations of dysregulated methionine metabolism in MS with potential impacts on both histone H3 and DNA methylation in the central nervous system. PMID: 29080803 [PubMed - indexed for MEDLINE]

Related Articles An automated ranking platform for machine learning regression models for meat spoilage prediction using multi-spectral imaging and metabolic profiling. Food Res Int. 2017 09;99(Pt 1):206-215 Authors: Estelles-Lopez L, Ropodi A, Pavlidis D, Fotopoulou J, Gkousari C, Peyrodie A, Panagou E, Nychas GJ, Mohareb F Abstract Over the past decade, analytical approaches based on vibrational spectroscopy, hyperspectral/multispectral imagining and biomimetic sensors started gaining popularity as rapid and efficient methods for assessing food quality, safety and authentication; as a sensible alternative to the expensive and time-consuming conventional microbiological techniques. Due to the multi-dimensional nature of the data generated from such analyses, the output needs to be coupled with a suitable statistical approach or machine-learning algorithms before the results can be interpreted. Choosing the optimum pattern recognition or machine learning approach for a given analytical platform is often challenging and involves a comparative analysis between various algorithms in order to achieve the best possible prediction accuracy. In this work, "MeatReg", a web-based application is presented, able to automate the procedure of identifying the best machine learning method for comparing data from several analytical techniques, to predict the counts of microorganisms responsible of meat spoilage regardless of the packaging system applied. In particularly up to 7 regression methods were applied and these are ordinary least squares regression, stepwise linear regression, partial least square regression, principal component regression, support vector regression, random forest and k-nearest neighbours. MeatReg" was tested with minced beef samples stored under aerobic and modified atmosphere packaging and analysed with electronic nose, HPLC, FT-IR, GC-MS and Multispectral imaging instrument. Population of total viable count, lactic acid bacteria, pseudomonads, Enterobacteriaceae and B. thermosphacta, were predicted. As a result, recommendations of which analytical platforms are suitable to predict each type of bacteria and which machine learning methods to use in each case were obtained. The developed system is accessible via the link: www.sorfml.com. PMID: 28784477 [PubMed - indexed for MEDLINE]

Related Articles UHPLC-PDA-ESI-TOF/MS metabolic profiling and antioxidant capacity of arabica and robusta coffee silverskin: Antioxidants vs phytotoxins. Food Res Int. 2017 09;99(Pt 1):155-165 Authors: Panusa A, Petrucci R, Lavecchia R, Zuorro A Abstract A deeper knowledge of the chemical composition of coffee silverskin (CS) is needed due to the growing interest in its use as a food additive or an ingredient of dietary supplements. Accordingly, the aim of this paper was to investigate the metabolic profile of aqueous extracts of two varieties of CS, Coffee arabica (CS-A), Coffee canephora var. robusta (CS-R) and of a blend of the two (CS-b) and to compare it to the profile of Coffee arabica green coffee (GC). Chlorogenic acids, caffeine, furokauranes, and atractyligenins, phytotoxins not previously detected in CS, were either identified or tentatively assigned. An unknown compound, presumably a carboxyatractyligenin glycoside was detected only in GC. Caffeine and chlorogenic acids were quantified while the content of furokauranes and atractyligens was estimated. GC and CS were also characterized in terms of total polyphenols and antioxidant capacity. Differences in the metabolites distribution, polyphenols and antioxidant capacity in GC and CS were detailed. PMID: 28784472 [PubMed - indexed for MEDLINE]

Related Articles Markers of Inflammation and Incident Breast Cancer Risk in the Women's Health Study. Am J Epidemiol. 2018 04 01;187(4):705-716 Authors: Tobias DK, Akinkuolie AO, Chandler PD, Lawler PR, Manson JE, Buring JE, Ridker PM, Wang L, Lee IM, Mora S Abstract Chronic inflammation may be a risk factor for the development and progression of breast cancer, yet it is unknown which inflammatory biomarkers and pathways are especially relevant. The present study included 27,071 participants (mean age = 54.5 years) in the Women's Health Study who were free of cancer and cardiovascular disease at enrollment (1992-1995), with baseline measures of 4 inflammatory biomarkers: high-sensitivity C-reactive protein, fibrinogen, N-acetyl side-chains of acute phase proteins, and soluble intercellular adhesion molecule-1. We used Cox proportional hazards regression models to evaluate associations between baseline concentrations of biomarkers and incident breast cancer, and adjusted for baseline and time-varying factors such as age and body mass index. Self-reported invasive breast cancer was confirmed against medical records for 1,497 incident cases (90% postmenopausal). We observed different patterns of risk depending on the inflammatory biomarker. There was a significant direct association between fibrinogen and breast cancer risk (for quintile 5 vs. quintile 1, adjusted hazard ratio = 1.25, 95% confidence interval: 1.03, 1.51; P for trend = 0.01). In contrast, soluble intercellular adhesion molecule-1 was inversely associated with breast cancer (for quintile 5 vs. quintile 1, adjusted hazard ratio = 0.79, 95% confidence interval: 0.66, 0.94; P for trend = 0.02). N-acetyl side-chains of acute phase proteins and high-sensitivity C-reactive protein were not associated with breast cancer. The complex association of chronic inflammation and breast cancer may be considered when formulating anti-inflammatory cancer prevention or intervention strategies. PMID: 28641369 [PubMed - indexed for MEDLINE]

71 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2019/05/28PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

44 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2019/05/24PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

44 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2019/05/24PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

23 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2019/05/23PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

33 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2019/05/22PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

33 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2019/05/22PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

26 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results: metabolomics These pubmed results were generated on 2019/05/21PubMed comprises more than millions of citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Related Articles Integrated analysis of genomics, longitudinal metabolomics, and Alzheimer's risk factors among 1,111 cohort participants. Genet Epidemiol. 2019 May 18;: Authors: Darst BF, Lu Q, Johnson SC, Engelman CD Abstract Although Alzheimer's disease (AD) is highly heritable, genetic variants are known to be associated with AD only explain a small proportion of its heritability. Genetic factors may only convey disease risk in individuals with certain environmental exposures, suggesting that a multiomics approach could reveal underlying mechanisms contributing to complex traits, such as AD. We developed an integrated network to investigate relationships between metabolomics, genomics, and AD risk factors using Wisconsin Registry for Alzheimer's Prevention participants. Analyses included 1,111 non-Hispanic Caucasian participants with whole blood expression for 11,376 genes (imputed from dense genome-wide genotyping), 1,097 fasting plasma metabolites, and 17 AD risk factors. A subset of 155 individuals also had 364 fastings cerebral spinal fluid (CSF) metabolites. After adjusting each of these 12,854 variables for potential confounders, we developed an undirected graphical network, representing all significant pairwise correlations upon adjusting for multiple testing. There were many instances of genes being indirectly linked to AD risk factors through metabolites, suggesting that genes may influence AD risk through particular metabolites. Follow-up analyses suggested that glycine mediates the relationship between carbamoyl-phosphate synthase 1 and measures of cardiovascular and diabetes risk, including body mass index, waist-hip ratio, inflammation, and insulin resistance. Further, 38 CSF metabolites explained more than 60% of the variance of CSF levels of tau, a detrimental protein that accumulates in the brain of AD patients and is necessary for its diagnosis. These results further our understanding of underlying mechanisms contributing to AD risk while demonstrating the utility of generating and integrating multiple omics data types. PMID: 31104335 [PubMed - as supplied by publisher]

Related Articles Correction to: Assessing the effect of nitisinone induced hypertyrosinaemia on monoamine neurotransmitters in brain tissue from a murine model of alkaptonuria using mass spectrometry imaging. Metabolomics. 2019 May 18;15(5):81 Authors: Davison AS, Strittmatter N, Sutherland H, Hughes AT, Hughes J, Bou-Gharios G, Milan AM, Goodwin RJA, Ranganath LR, Gallagher JA Abstract The original publication of this article contained an incorrect version that did not include some final reviewers' suggestions, was inadvertently received for production and published. The original article has been corrected. PMID: 31104147 [PubMed - in process]

Related Articles Integrated Regulation of HuR by Translation Repression and Protein Degradation Determines Pulsatile Expression of p53 Under DNA Damage. iScience. 2019 May 04;15:342-359 Authors: Guha A, Ahuja D, Das Mandal S, Parasar B, Deyasi K, Roy D, Sharma V, Willard B, Ghosh A, Ray PS Abstract Expression of tumor suppressor p53 is regulated at multiple levels, disruption of which often leads to cancer. We have adopted an approach combining computational systems modeling with experimental validation to elucidate the translation regulatory network that controls p53 expression post DNA damage. The RNA-binding protein HuR activates p53 mRNA translation in response to UVC-induced DNA damage in breast carcinoma cells. p53 and HuR levels show pulsatile change post UV irradiation. The computed model fitted with the observed pulse of p53 and HuR only when hypothetical regulators of synthesis and degradation of HuR were incorporated. miR-125b, a UV-responsive microRNA, was found to represses the translation of HuR mRNA. Furthermore, UV irradiation triggered proteasomal degradation of HuR mediated by an E3-ubiquitin ligase tripartite motif-containing 21 (TRIM21). The integrated action of miR-125b and TRIM21 constitutes an intricate control system that regulates pulsatile expression of HuR and p53 and determines cell viability in response to DNA damage. PMID: 31103853 [PubMed - as supplied by publisher]

Related Articles Integrative transcriptomics, proteomics, and metabolomics data analysis exploring the injury mechanism of ricin on human lung epithelial cells. Toxicol In Vitro. 2019 May 16;: Authors: Xu N, Dong M, Wang Y, Chang Y, Wan J, Zhu W, Wang J, Liu W Abstract Ricin (RT) is a plant toxin belonging to the family of type II ribosome-inactivating protein with high bioterrorism potential. Aerosol RT exposure is the most lethal route, but its mechanism of injury needs further investigation. In the present study, we performed a comprehensive transcriptomics, proteomics and metabolomics analysis on the potential mechanism of injury caused by RT on human lung epithelial cells. In total, 5872 genes, 187 proteins, and 143 metabolites were shown to be significantly changed in human lung epithelial cells after RT treatment. Molecular function, pathway, and network analyses, the genes and proteins regulated in RT-treated cells were mainly attributed to fatty acid metabolism, arginine and proline metabolism and ubiquitin-mediated proteolysis pathway. Furthermore, a comprehensive analysis of transcripts, proteins, and metabolites was performed. The results revealed the correlated genes, proteins, and metabolic pathways regulated in metabolic pathways, amino acid metabolism, transcription and energy metabolism. These genes, proteins, and metabolites involved in these dis-regulated pathways may provide a more targeted and credible direction to study the mechanism of RT injury on human lung epithelial cells. This study provides large-scale omics data that can be used to develop a new strategy for the prevention, rapid diagnosis, and treatment of RT poisoning, especially of RT aerosol. PMID: 31103672 [PubMed - as supplied by publisher]

Related Articles Metabolomics workflow for lung cancer: Discovery of biomarkers. Clin Chim Acta. 2019 May 16;: Authors: Tang Y, Li Z, Lazar L, Fang Z, Tang C, Zhao J Abstract Lung cancer is one of the most common cancers in the world. Due to the limitations of current diagnostic techniques and methods, most lung cancers are diagnosed at the advanced stage, which is not conducive to early treatment. The rise of metabolomics has provided new ideas for the early diagnosis of lung cancer. As a method for the comprehensive analysis of endogenous metabolites of the biological system, metabolomics has shown significant application potential for the early diagnosis and individualized treatment of various cancers including lung cancers. Via advanced analytical techniques and bioinformatics tools, the metabolome was excavated to find biomarkers related to cancer and its prognosis. In this review, the research methods and workflow of metabolomics are summarized, with an emphasis on the recent discovery of biomarkers and major metabolic pathways for lung cancers. PMID: 31103622 [PubMed - as supplied by publisher]