bims-metlip Biomed News
on Methods and protocols in metabolomics and lipidomics
Issue of 2021–08–29
sixteen papers selected by
Sofia Costa, Cold Spring Harbor Laboratory
  1. MStractor: R Workflow Package for Enhancing Metabolomics Data Pre-Processing and Visualization.
  2. Facilitating Imaging Mass Spectrometry of Microbial Specialized Metabolites with METASPACE.
  3. Expanding Urinary Metabolite Annotation through Integrated Mass Spectral Similarity Networking.
  4. A Robust Method for Sample Preparation of Gastrointestinal Stromal Tumour for LC/MS Untargeted Metabolomics.
  5. Investigating Global Lipidome Alterations with the Lipid Network Explorer.
  6. metID: a R package for automatable compound annotation for LC-MS-based data.
  7. Tailored Polymer-Based Selective Extraction of Lipid Mediators from Biological Samples.
  8. Metabolomics and lipidomics in Caenorhabditis elegans using a single-sample preparation.
  9. A Liquid Chromatography-Mass Spectrometry Workflow for In-Depth Quantitation of Fatty Acid Double Bond Location Isomers.
  10. Comparison of Flow Injection-MS/MS and LC-MS/MS for the Determination of Ochratoxin A.
  11. A simultaneous extraction/derivatization strategy coupled with liquid chromatography-tandem mass spectrometry for the determination of free catecholamines in biological fluids.
  12. Detection of Vitamin D Metabolites in Breast Milk: Perspectives and challenges for measurement by Liquid Chromatography Tandem-Mass Spectrometry.
  13. Towards high throughput and high information coverage: advanced single-cell mass spectrometric techniques.
  14. Determination of twenty herbicides in blood by ultrapressure liquid chromatography-tandem mass spectrometry.
  15. One-step separation system of bio-functional lipid compounds from natural sources.
  16. IMFLer: A Web Application for Interactive Metabolic Flux Analysis and Visualization.
  1. Metabolites. 2021 Jul 29. pii: 492. [Epub ahead of print]11(8):
    MStractor: R Workflow Package for Enhancing Metabolomics Data Pre-Processing and Visualization.
    Luca Nicolotti, Jeremy Hack, Markus Herderich, Natoiya Lloyd.
      Untargeted metabolomics experiments for characterizing complex biological samples, conducted with chromatography/mass spectrometry technology, generate large datasets containing very complex and highly variable information. Many data-processing options are available, however, both commercial and open-source solutions for data processing have limitations, such as vendor platform exclusivity and/or requiring familiarity with diverse programming languages. Data processing of untargeted metabolite data is a particular problem for laboratories that specialize in non-routine mass spectrometry analysis of diverse sample types across humans, animals, plants, fungi, and microorganisms. Here, we present MStractor, an R workflow package developed to streamline and enhance pre-processing of metabolomics mass spectrometry data and visualization. MStractor combines functions for molecular feature extraction with user-friendly dedicated GUIs for chromatographic and mass spectromerty (MS) parameter input, graphical quality-control outputs, and descriptive statistics. MStractor performance was evaluated through a detailed comparison with XCMS Online. The MStractor package is freely available on GitHub at the MetabolomicsSA repository.
    Keywords:  LC/MS; R programming language; data analysis; metabolomics; pre-processing
    DOI:  https://doi.org/10.3390/metabo11080492
  2. Metabolites. 2021 Jul 23. pii: 477. [Epub ahead of print]11(8):
    Facilitating Imaging Mass Spectrometry of Microbial Specialized Metabolites with METASPACE.
    Don D Nguyen, Veronika Saharuka, Vitaly Kovalev, Lachlan Stuart, Massimo Del Prete, Kinga Lubowiecka, René De Mot, Vittorio Venturi, Theodore Alexandrov.
      Metabolite annotation from imaging mass spectrometry (imaging MS) data is a difficult undertaking that is extremely resource intensive. Here, we adapted METASPACE, cloud software for imaging MS metabolite annotation and data interpretation, to quickly annotate microbial specialized metabolites from high-resolution and high-mass accuracy imaging MS data. Compared with manual ion image and MS1 annotation, METASPACE is faster and, with the appropriate database, more accurate. We applied it to data from microbial colonies grown on agar containing 10 diverse bacterial species and showed that METASPACE was able to annotate 53 ions corresponding to 32 different microbial metabolites. This demonstrates METASPACE to be a useful tool to annotate the chemistry and metabolic exchange factors found in microbial interactions, thereby elucidating the functions of these molecules.
    Keywords:  imaging mass spectrometry; microbial natural products; spatial metabolomics
    DOI:  https://doi.org/10.3390/metabo11080477
  3. Anal Chem. 2021 Aug 26.
    Expanding Urinary Metabolite Annotation through Integrated Mass Spectral Similarity Networking.
    Fausto Carnevale Neto, Daniel Raftery.
      The urine metabolome constitutes a rich source of functional information reflecting physiological states that are influenced by distinct conditions and biological stresses, such as responses to drug treatments or disease manifestations. Although global liquid chromatography-mass spectrometry (MS) profiling provides the most comprehensive measurement of metabolites in complex biological samples, annotation remains a challenge, and computational approaches are necessary to translate the molecular composition into biological knowledge. Here, we investigated the use of tandem MS-based enhanced molecular networks (MolNetEnhancer) to improve the metabolite annotation of urine extracts. The samples (n = 10) were analyzed by hydrophilic interaction chromatography-quadrupole time-of-flight mass spectrometry in both electrospray ionization (ESI) modes. Consistent with other common data preprocessing software, the use of Progenesis QI led to the annotation of up to 20 metabolites based on MS2 library searches, showing a high fragmentation score (cosine similarity ≥ 0.7), that is, ∼2% of mass features containing MS2 spectra. Molecular networking based on library matching resulted in the annotation of up to 62 urinary compounds. Using a combination of unsupervised substructure discovery (MS2LDA), the in silico tool network annotation propagation (NAP), and ClassyFire chemical ontology, embedded in a multilayered molecular network by MolNetEnhancer, we were able to expand the chemical characterization to ∼50% of the data set. The integrative approach led to the annotation of 275 compounds at the metabolomics standards initiative (MSI) confidence level 2, as well as 459 and 578 urinary metabolites (MSI level 3) in both negative and positive ESI modes, respectively. The exhaustive MS2-based annotation outperformed similar studies applied to larger cohorts while offering the discovery of metabolites not identified by the MS2 library search. This is the first work that effectively integrates orthogonal annotation methods and MS2-based fragmentation studies to improve metabolite annotation in urine samples.
    DOI:  https://doi.org/10.1021/acs.analchem.1c02041
  4. Metabolites. 2021 Aug 21. pii: 554. [Epub ahead of print]11(8):
    A Robust Method for Sample Preparation of Gastrointestinal Stromal Tumour for LC/MS Untargeted Metabolomics.
    Szymon Macioszek, Danuta Dudzik, Julia Jacyna, Agnieszka Wozniak, Patrick Schöffski, Michał J Markuszewski.
      Gastrointestinal stromal tumour has already been well explored at the genome level; however, little is known about metabolic processes occurring in the sarcoma. Sample preparation is a crucial step in untargeted metabolomics workflow, highly affecting the metabolome coverage and the quality of the results. In this study, four liquid-liquid extraction methods for the isolation of endogenous compounds from gastrointestinal stromal tumours were compared and evaluated. The protocols covered two-step or stepwise extraction with methyl-tert-butyl ether (MTBE) or dichloromethane. The extracts were subjected to LC-MS analysis by the application of reversed-phase and hydrophilic interaction liquid chromatography to enable the separation and detection of both polar and nonpolar analytes. The extraction methods were compared in terms of efficiency (total number of detected metabolites) and reproducibility. The method was based on the stepwise extraction with MTBE, methanol, and water proved to be the most reproducible, and thus, its robustness to fluctuations in experimental conditions was assessed employing Plackett-Burman design and hierarchical modelling. While most studied factors had no effect on the metabolite abundance, the highest coefficient value was observed for the volume of MTBE added during extraction. Herein, we demonstrate the application and the feasibility of the selected protocol for the analysis of gastrointestinal stromal tumour samples. The method selected could be considered as a reference for the best characterization of underlying molecular changes associated with complex tissue extracts of GIST.
    Keywords:  DOE; MTBE; Plackett–Burman; extraction methods; gastrointestinal stromal tumors (GIST); lipidomics; metabolomics; sample preparation
    DOI:  https://doi.org/10.3390/metabo11080554
  5. Metabolites. 2021 Jul 28. pii: 488. [Epub ahead of print]11(8):
    Investigating Global Lipidome Alterations with the Lipid Network Explorer.
    Nikolai Köhler, Tim Daniel Rose, Lisa Falk, Josch Konstantin Pauling.
      Lipids play an important role in biological systems and have the potential to serve as biomarkers in medical applications. Advances in lipidomics allow identification of hundreds of lipid species from biological samples. However, a systems biological analysis of the lipidome, by incorporating pathway information remains challenging, leaving lipidomics behind compared to other omics disciplines. An especially uncharted territory is the integration of statistical and network-based approaches for studying global lipidome changes. Here we developed the Lipid Network Explorer (LINEX), a web-tool addressing this gap by providing a way to visualize and analyze functional lipid metabolic networks. It utilizes metabolic rules to match biochemically connected lipids on a species level and combine it with a statistical correlation and testing analysis. Researchers can customize the biochemical rules considered, to their tissue or organism specific analysis and easily share them. We demonstrate the benefits of combining network-based analyses with statistics using publicly available lipidomics data sets. LINEX facilitates a biochemical knowledge-based data analysis for lipidomics. It is availableas a web-application and as a publicly available docker container.
    Keywords:  bioinformatics; computational lipidomics; computational systems biology; lipidomics; lipids; metabolic networks; network biology
    DOI:  https://doi.org/10.3390/metabo11080488
  6. Bioinformatics. 2021 Aug 25. pii: btab583. [Epub ahead of print]
    metID: a R package for automatable compound annotation for LC-MS-based data.
    Xiaotao Shen, Si Wu, Liang Liang, Songjie Chen, Kévin Contrepois, Zheng-Jiang Zhu, Michael Snyder.
       SUMMARY: Accurate and efficient compound annotation is a long-standing challenge for LC-MS-based data (e.g., untargeted metabolomics and exposomics). Substantial efforts have been devoted to overcoming this obstacle, whereas current tools are limited by the sources of spectral information used (in-house and public databases) and are not automated and streamlined. Therefore, we developed metID, an R package that combines information from all major databases for comprehensive and streamlined compound annotation. metID is a flexible, simple, and powerful tool that can be installed on all platforms, allowing the compound annotation process to be fully automatic and reproducible. A detailed tutorial and a case study are provided in Supplementary Materials.
    AVAILABILITY AND IMPLEMENTATION: https://jaspershen.github.io/metID.
    SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
    DOI:  https://doi.org/10.1093/bioinformatics/btab583
  7. Metabolites. 2021 Aug 13. pii: 539. [Epub ahead of print]11(8):
    Tailored Polymer-Based Selective Extraction of Lipid Mediators from Biological Samples.
    Yohannes Abere Ambaw, Sandra Rinne Dahl, Yan Chen, Tyge Greibrokk, Elsa Lundanes, Issam Lazraq, Sudhirkumar Shinde, Jayashree Selvalatchmanan, Markus R Wenk, Börje Sellergren, Federico Torta.
      Lipid mediators, small molecules involved in regulating inflammation and its resolution, are a class of lipids of wide interest as their levels in blood and tissues may be used to monitor health and disease states or the effect of new treatments. These molecules are present at low levels in biological samples, and an enrichment step is often needed for their detection. We describe a rapid and selective method that uses new low-cost molecularly imprinted (MIP) and non-imprinted (NIP) polymeric sorbents for the extraction of lipid mediators from plasma and tissue samples. The extraction process was carried out in solid-phase extraction (SPE) cartridges, manually packed with the sorbents. After extraction, lipid mediators were quantified by liquid chromatography-tandem mass spectrometry (LC-MSMS). Various parameters affecting the extraction efficiency were evaluated to achieve optimal recovery and to reduce non-specific interactions. Preliminary tests showed that MIPs, designed using the prostaglandin biosynthetic precursor arachidonic acid, could effectively enrich prostaglandins and structurally related molecules. However, for other lipid mediators, MIP and NIP displayed comparable recoveries. Under optimized conditions, the recoveries of synthetic standards ranged from 62% to 100%. This new extraction method was applied to the determination of the lipid mediators concentration in human plasma and mouse tissues and compared to other methods based on commercially available cartridges. In general, the methods showed comparable performances. In terms of structural specificity, our newly synthesized materials accomplished better retention of prostaglandins (PGs), hydroxydocosahexaenoic acid (HDoHE), HEPE, hydroxyeicosatetraenoic acids (HETE), hydroxyeicosatrienoic acid (HETrE), and polyunsaturated fatty acid (PUFA) compounds, while the commercially available Strata-X showed a higher recovery for dihydroxyeicosatetraenoic acid (diHETrEs). In summary, our results suggest that this new material can be successfully implemented for the extraction of lipid mediators from biological samples.
    Keywords:  lipid mediators; molecularly imprinted polymer (MIP); non-imprinted polymer (NIP); solid-phase extraction (SPE); strata-X
    DOI:  https://doi.org/10.3390/metabo11080539
  8. Dis Model Mech. 2021 Apr 01. pii: dmm047746. [Epub ahead of print]14(4):
    Metabolomics and lipidomics in Caenorhabditis elegans using a single-sample preparation.
    Marte Molenaars, Bauke V Schomakers, Hyung L Elfrink, Arwen W Gao, Martin A T Vervaart, Mia L Pras-Raves, Angela C Luyf, Reuben L Smith, Mark G Sterken, Jan E Kammenga, Antoine H C van Kampen, Georges E Janssens, Frédéric M Vaz, Michel van Weeghel, Riekelt H Houtkooper.
      Comprehensive metabolomic and lipidomic mass spectrometry methods are in increasing demand; for instance, in research related to nutrition and aging. The nematode Caenorhabditis elegans is a key model organism in these fields, owing to the large repository of available C. elegans mutants and their convenient natural lifespan. Here, we describe a robust and sensitive analytical method for the semi-quantitative analysis of >100 polar (metabolomics) and >1000 apolar (lipidomics) metabolites in C. elegans, using a single-sample preparation. Our method is capable of reliably detecting a wide variety of biologically relevant metabolic aberrations in, for example, glycolysis and the tricarboxylic acid cycle, pyrimidine metabolism and complex lipid biosynthesis. In conclusion, we provide a powerful analytical tool that maximizes metabolic data yield from a single sample. This article has an associated First Person interview with the joint first authors of the paper.
    Keywords:   C. elegans ; Lipidomics; Metabolism; Metabolomics
    DOI:  https://doi.org/10.1242/dmm.047746
  9. J Lipid Res. 2021 Aug 23. pii: S0022-2275(21)00092-4. [Epub ahead of print] 100110
    A Liquid Chromatography-Mass Spectrometry Workflow for In-Depth Quantitation of Fatty Acid Double Bond Location Isomers.
    Jing Zhao, Mengxuan Fang, Yu Xia.
      Tracing compositional changes of fatty acids (FAs) is frequently used as a means of monitoring metabolic alterations in perturbed biological states. Given that more than half of FAs in the mammalian lipidome are unsaturated, quantitation of FAs at a carbon-carbon double bond (C=C) location level is necessary. In this work, we have developed a workflow for global quantitation of FAs, including C=C location isomers, via charge-tagging Paternò-Büchi (PB) derivatization and liquid chromatography-tandem mass spectrometry (LC-MS/MS). The use of 2-acetylpiridine (2-acpy) as the charge-tagging PB reagent led to a limit of identification in the sub-nanomolar range for mono- and poly-unsaturated as well as conjugated FAs. Conjugated free FAs of low abundance such as FA 18:2 (n-7, n-9) and FA 18:2 (n-6, n-8) were quantified at concentrations of 0.61 ± 0.05 and 0.05 ± 0.01 mg per 100 g in yak milk powder, respectively. This workflow also enabled deep profiling of eight saturated and thirty-seven unsaturated total FAs across a span of four orders of magnitude in concentration, including ten groups of C=C location isomers in pooled human plasma. A pilot survey on total FAs in plasma from patients with type 2 diabetes revealed that the relative compositions of FA 16:1 (n-10) and FA 18:1 (n-10) were significantly elevated compared to that of normal controls. The developed FA analysis workflow may serve as a powerful tool for deep profiling of FAs in both fundamental and clinical studies.
    Keywords:  2-acetylpiridine; Fatty acids; Paternò–Büchi; charge-tagging; double bond location isomers; lipidomics; liquid chromatography; quantitation; tandem mass spectrometry; type 2 diabetes
    DOI:  https://doi.org/10.1016/j.jlr.2021.100110
  10. Toxins (Basel). 2021 Aug 06. pii: 547. [Epub ahead of print]13(8):
    Comparison of Flow Injection-MS/MS and LC-MS/MS for the Determination of Ochratoxin A.
    Kai Zhang.
      Two methods for measuring ochratoxin A in corn, oat, and grape juice were developed and compared. Flow injection (FI) and on-line liquid chromatography (LC) performances were evaluated separately, with both methods using a triple quadrupole tandem mass spectrometer (MS/MS) for quantitation. Samples were fortified with 13C uniformly labeled ochratoxin A as the internal standard (13C-IS) and prepared by dilution and filtration, followed by FI- and LC-MS/MS analysis. For the LC-MS/MS method, which had a 10 min run time/sample, recoveries of ochratoxin A fortified at 1, 5, 20, and 100 ppb in corn, oat, red grape juice, and white grape juice ranged from 100% to 117% with RSDs < 9%. The analysis time of the FI-MS/MS method was <60 s/sample, however, the method could not detect ochratoxin A at the lowest fortification concentration, 1 ppb, in all tested matrix sources. At 5, 20, and 100 ppb, recoveries by FI-MS/MS ranged from 79 to 117% with RSDs < 15%. The FI-MS/MS method also had ~5× higher solvent and matrix-dependent instrument detection limits (0.12-0.35 ppb) compared to the LC-MS/MS method (0.02-0.06 ppb). In the analysis of incurred corn and oat samples, both methods generated comparable results within ±20% of reference values, however, the FI-MS/MS method failed to determine ochratoxin A in two incurred wheat flour samples due to co-eluted interferences due to the lack of chromatographic separation.
    Keywords:  LC-MS-MS; flow injection; ochratoxin A
    DOI:  https://doi.org/10.3390/toxins13080547
  11. J Chromatogr A. 2021 Aug 14. pii: S0021-9673(21)00598-7. [Epub ahead of print]1654 462474
    A simultaneous extraction/derivatization strategy coupled with liquid chromatography-tandem mass spectrometry for the determination of free catecholamines in biological fluids.
    Di Chen, Jing-Xian Zhang, Wei-Qi Cui, Jun-Wei Zhang, De-Qiao Wu, Xin-Rui Yu, Yan-Bo Luo, Xing-Yi Jiang, Feng-Peng Zhu, Dilshad Hussain, Xia Xu.
      The current study presents a convenient, rapid and effective simultaneous extraction/derivatization (SEDP) strategy for effective pretreatment of catecholamines (CAs). Commercial zirconium oxide (ZrO2) nanoparticles were employed for the selective capturing of cis-diol containing CAs to remove the biological interferences and phenyl isothiocyanate (PITC) was used for derivatization to improve the ionization and to improve the chromatographic separation. The extraction and derivatization procedures were integrated into one step to simplify the sample pretreatment. Excessive derivatization reagents were removed as well, reducing the degree of contaminations in mass spectrometry. The factors affecting the SEDP process were optimized and the results showed that the detection sensitivity and chromatographic separation of CAs greatly improved compared with underivatized CAs, during LC-MS/MS analysis. Combined with ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), quantifying the concentration of norepinephrine (NE), epinephrine (E) and dopamine (DA) in biological fluids was validated in ranges of 1-200.0 ng/mL with a satisfactory correlation coefficient (R2 > 0.997). The obtained recoveries were in the range of 91.0-109.5% with RSDs less than 9.4%. Finally, significant changes in CAs levels in urine samples of healthy people and pheochromocytoma patients were detected. The developed method offers comparative advantages in terms of sensitivity, specificity and selectivity.
    Keywords:  Catecholamines; Pheochromocytoma; Simultaneous extraction/derivatization pretreatment method; UPLC-MS/MS
    DOI:  https://doi.org/10.1016/j.chroma.2021.462474
  12. Clin Biochem. 2021 Aug 19. pii: S0009-9120(21)00224-1. [Epub ahead of print]
    Detection of Vitamin D Metabolites in Breast Milk: Perspectives and challenges for measurement by Liquid Chromatography Tandem-Mass Spectrometry.
    Carlie Tuddenham, Ronda F Greaves, Anushi E Rajapaksa, John D Wark, Rosita Zakaria.
      Breast milk is an emerging matrix for vitamin D assessment of breastfed infants and their mothers. It is considered a more reliable indicator of infant intake than the assessment of maternal circulating vitamin D. With the improved sensitivity of mass spectrometry-based technologies, this method principle has been the recent mainstay for the quantitation of various vitamin D metabolites in breast milk for population-based clinical trials. There are still several areas across the total testing process (pre-analytical, analytical and post-analytical) to be defined and harmonised to translate breast milk vitamin D measurement by liquid chromatography-tandem mass spectrometry (LC-MS/MS) from population-based research to routine clinical use and public health applications. Pre-analytically, the determination of the best form of vitamin D to measure in breast milk requires more evidence. Analytically, standardisation of the methods to allow for comparability of results is required. Post analytically, breast milk vitamin D decision limits are needed to turn the individual numerical outputs into clinically meaningful results. This review aims to synthesise the current evidence and utility of measurement of breast milk vitamin D by LC-MS/MS and to lead a future discussion on best practices to allow for its clinical utility beyond its current research-based use.
    Keywords:  Breast milk; Mass spectrometry; Vitamin D; cholecalciferol; emerging technologies; lactation
    DOI:  https://doi.org/10.1016/j.clinbiochem.2021.08.003
  13. Anal Bioanal Chem. 2021 Aug 26.
    Towards high throughput and high information coverage: advanced single-cell mass spectrometric techniques.
    Shuting Xu, Cheng Yang, Xiuping Yan, Huwei Liu.
      Mass spectrometry (MS) is attractive for single-cell analysis because of its high sensitivity, rich information, and large dynamic ranges, especially for the single-cell metabolome and proteome analysis. Efforts have been made to deal with the throughput and information coverage problems in typical manual single-cell MS techniques. In this review, advanced techniques to improve the automation and throughput for single-cell sampling and single-cell metabolome and proteome MS detection have been discussed. Furthermore, representative MS-based strategies that can increase the in-depth cellular information coverage and achieve the more comprehensive single-cell multiomics information during high throughput detection have been highlighted, providing an ongoing perspective of the MS performance for the single-cell research.
    Keywords:  High throughput; Mass spectrometry; Metabolomics; Multiomics; Proteomics; Single-cell analysis
    DOI:  https://doi.org/10.1007/s00216-021-03624-w
  14. Forensic Sci Int. 2021 Jul 20. pii: S0379-0738(21)00230-9. [Epub ahead of print]327 110910
    Determination of twenty herbicides in blood by ultrapressure liquid chromatography-tandem mass spectrometry.
    Ruxin Luo, Baohua Shen, Ping Xiang, Wei Liu.
      A sensitive and rapid method for the simultaneous determination of twenty herbicides (aclonifen, lactofen, terbutryn, butylate, carbetamide, fluazifop-P-butyl, propanil, prometryn, isoproturon, terbumeton, pretilachlor, pendimethalin, cycloxydim, tri-allate, metolachlor, diuron, alloxydim, prosulfuron, triflusulfuron-methyl, and acetochlor) in human blood is reported herein. Liquid-liquid extraction coupled with ultra-pressure liquid chromatography-tandem mass spectrometry was employed for the simultaneous analysis of all compounds in 15 min. Validation parameters were studied through the estimation of the limits of detection and quantification, calibration curves, sensitivity, spiked recovery and precision. The limits of detection ranged from 0.1 to 1.0 ng/mL. The limits of quantification ranged from 0.5 to 2.0 ng/mL. Good linearity was obtained for all compounds with R2> 0.99 in all cases. Furthermore, interday precision (< 15%) and intraday precision (< 15%) were shown to be satisfactory. Recoveries in spiked blood samples were evaluated, and acceptable values (88.0%~108.8%) were found. Finally, this method was successfully applied to the determination of fluazifop-P-butyl, isoproturon and acetochlor in blood samples from real forensic cases. These results suggest that this method is reliable for rapid forensic and clinical diagnosis.
    Keywords:  Blood; Confirmation method; Forensic toxicology; Herbicide; UPLC-MS/MS
    DOI:  https://doi.org/10.1016/j.forsciint.2021.110910
  15. MethodsX. 2021 ;8 101380
    One-step separation system of bio-functional lipid compounds from natural sources.
    Alexandros Tsoupras, Katherine M Pappas, Theodore G Sotiroudis, Constantinos A Demopoulos.
      Lipids are a very heterogeneous class of biomolecules with distinct structures and functions. Total lipids (TLs) obtained from natural sources are regularly further separated into lipid subclasses, with the two major ones being the polar lipids (PLs) and neutral lipids (NLs). Traditional analytical methods for fractionating TLs into NLs, PLs, and their subclasses, usually comprise difficult, costly and time-consuming steps. Instead, several benefits and applications are derived by implementing a novel one-step semi-preparative and reversed-phase HPLC-analysis for separating TLs into all kinds of lipid subclasses. This method allows a one-step separation/fractionation of several subclasses of bio-functional PLs (i.e. phospholipids, glycolipids, phenolic compounds, N-acyl-homoserine-lactones, etc.) and NLs (i.e. triacylglycerols, fatty acids, esters, etc.) from TL-extracts of a natural source, prior to further testing them for their bio-functionality (i.e. in bioassays/cell models) and structure-activity relationships (i.e. LC-MS/GC-MS).•This method can be applied in several natural sources, such as animal and marine sources, plants, microorganisms of biotechnological and agricultural interest, foods, beverages and related products, and by-products.•This method can also be applied for separating specific bio-functional lipids from complex medical and pharmaceutical samples (i.e. cells, tissues, blood, plasma, liposomes, etc.), either for evaluating their role in diseases (i.e. PAF/PAF-like molecules) or by elucidating their protective roles (i.e. PLs rich in ω3 PUFA) for supplements and nutraceuticals' applications.
    Keywords:  GC, gas chromatography; Glycolipids; HPLC; HPLC, high pressure (performance) liquid chromatography; LC, liquid chromatography; MS, mass spectra; NL(s), neutral lipid(s); Natural origin; Neutral lipids; PAF; PAF, platelet-activating factor; PL(s), polar lipid(s); Phenolic compounds; Phospholipids; Polar lipids; Reversed phase; TL(s), total lipid(s); Total lipids; ω3 PUFA, omega-3 polyunsaturated fatty acids
    DOI:  https://doi.org/10.1016/j.mex.2021.101380
  16. J Comput Biol. 2021 Aug 23.
    IMFLer: A Web Application for Interactive Metabolic Flux Analysis and Visualization.
    Rudolfs Petrovs, Egils Stalidzans, Agris Pentjuss.
      Increasing genome-wide data in biological sciences and medicine has contributed to the development of a variety of visualization tools. Several automatic, semiautomatic, and manual visualization tools have already been developed. Some even have integrated flux balance analysis (FBA), but in most cases, it depends on separately installed third party software that is proprietary and does not allow customization of its functionality and has many restrictions for easy data distribution and analysis. In this study, we present an interactive metabolic flux analyzer and visualizer (IMFLer)-a static single-page web application that enables the reading and management of metabolic model layout maps, as well as immediate visualization of results from both FBA and flux variability analysis (FVA). IMFLer uses the Escher Builder tool to load, show, edit, and save metabolic pathway maps. This makes IMFLer an attractive and easily applicable tool with a user-friendly interface. Moreover, it allows to faster interpret results from FBA and FVA and improves data interoperability by using a standardized file format for the genome-scale metabolic model. IMFLer is a fully open-source tool that enables the rapid visualization and interpretation of the results of FBA and FVA with no time setup and no programming skills required, available at https://lv-csbg.github.io/IMFLer/.
    Keywords:  cellular metabolism; flux balance analysis; flux variability analysis; genome-scale metabolic models; network visualization
    DOI:  https://doi.org/10.1089/cmb.2021.0056
This page is being maintained by Thomas Krichel. It was last updated on 2024‒11‒22 at 4:21.