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Metabolomics,
2025]
INTRODUCTION: The identification of lipids is a cornerstone of lipidomics, and due to the specific characteristics of lipids, it requires dedicated analysis workflows. Identifying novel lipids and lipid species for which no reference spectra are available is tedious and often involves a lot of manual work. Integrating high-resolution mass spectrometry with enhancements from chromatographic and ion mobility separation enables the in-depth investigation of intact lipids. OBJECTIVES: We investigated phosphorylated glycosphingolipids from the nematode Caenorhabditis elegans, a biomedical model organism, and aimed to identify different species from this class of lipids, which have been described in one particular publication only. We checked if these lipids can be detected in lipid extracts of C. elegans. METHODS: We used UHPLC-UHR-TOF-MS and UHPLC-TIMS-TOF-MS in combination with dedicated data analysis to check for the presence of phosphorylated glycosphingolipids. Specifically, candidate features were identified in two datasets using Mass Spec Query Language (MassQL) to search fragmentation data. The additional use of retention time (RT) and collisional cross section (CCS) information allowed to filter false positive annotations. RESULTS: As a result, we detected all previously described phosphorylated glycosphingolipids and novel species as well as their biosynthetic precursors in two different lipidomics datasets. MassQL significantly speeds up the process by saving time that would otherwise be spent on manual data investigations. In total over 20 sphingolipids could be described. CONCLUSION: MassQL allowed us to search for phosphorylated glycosphingolipids and their potential biosynthetic precursors systematically. Using orthogonal information such as RT and CCS helped filter false positive results. With the detection in two different datasets, we demonstrate that these sphingolipids are a general part of the C. elegans lipidome.
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Arch Biochem Biophys,
2016]
Lipids play important roles in biology, ranging from building blocks of membranes to signaling lipids. The nematode and model organism Caenorhabditis elegans has been used to explore lipid metabolism and several techniques for their analysis have been employed. These techniques include different possibilities ranging from visualization of lipid droplets, analysis of total fatty acids to analysis of complex lipids using lipidomics approaches. Lipidomics evolved from metabolomics, the latest off-spring of the "omics"-technologies and aims to characterize the lipid content of a given organism or system. Although being an extensively studied model organism, only a few applications of lipidomics to C.elegans have been reported to far, but the number is steadily increasing with more applications expected in the near future. This review gives an overview on the C.elegans lipidome, lipid classes it contains and ways to analyze them. It serves as primer for scientists interested in studying lipids in this model organism and list methods used so far and what information can be derived from them. Lastly, challenges and future (methodological) research directions, together with new methods potentially useful for C.elegans lipid research are discussed.
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Metabolites,
2020]
Genome scale metabolic models (GSMs) are a representation of the current knowledge on the metabolism of a given organism or superorganism. They group metabolites, genes, enzymes and reactions together to form a mathematical model and representation that can be used to analyze metabolic networks in silico or used for analysis of omics data. Beside correct mass and charge balance, correct structural annotation of metabolites represents an important factor for analysis of these metabolic networks. However, several metabolites in different GSMs have no or only partial structural information associated with them. Here, a new systematic nomenclature for acyl-based metabolites such as fatty acids, acyl-carnitines, acyl-coenzymes A or acyl-carrier proteins is presented. This nomenclature enables one to encode structural details in the metabolite identifiers and improves human readability of reactions. As proof of principle, it was applied to the fatty acid biosynthesis and degradation in the <i>Caenorhabditis elegans</i> consensus model WormJam.
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Anal Bioanal Chem,
2021]
Lipid identification is one of the current bottlenecks in lipidomics and lipid profiling, especially for novel lipid classes, and requires multidimensional data for correct annotation. We used the combination of chromatographic and ion mobility separation together with data-independent acquisition (DIA) of tandem mass spectrometric data for the analysis of lipids in the biomedical model organism Caenorhabditis elegans. C. elegans reacts to harsh environmental conditions by interrupting its normal life cycle and entering an alternative developmental stage called dauer stage. Dauer larvae show distinct changes in metabolism and morphology to survive unfavorable environmental conditions and are able to survive for a long time without feeding. Only at this developmental stage, dauer larvae produce a specific class of glycolipids called maradolipids. We performed an analysis of maradolipids using ultrahigh performance liquid chromatography-ion mobility spectrometry-quadrupole-time of flight-mass spectrometry (UHPLC-IM-Q-ToFMS) using drift tube ion mobility to showcase how the integration of retention times, collisional cross sections, and DIA fragmentation data can be used for lipid identification. The obtained results show that combination of UHPLC and IM separation together with DIA represents a valuable tool for initial lipid identification. Using this analytical tool, a total of 45 marado- and lysomaradolipids have been putatively identified and 10 confirmed by authentic standards directly from C. elegans dauer larvae lipid extracts without the further need for further purification of glycolipids. Furthermore, we putatively identified two isomers of a lysomaradolipid not known so far.
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PLoS One,
2017]
Lipid identification is a major bottleneck in high-throughput lipidomics studies. However, tools for the analysis of lipid tandem MS spectra are rather limited. While the comparison against spectra in reference libraries is one of the preferred methods, these libraries are far from being complete. In order to improve identification rates, the in silico fragmentation tool MetFrag was combined with Lipid Maps and lipid-class specific classifiers which calculate probabilities for lipid class assignments. The resulting LipidFrag workflow was trained and evaluated on different commercially available lipid standard materials, measured with data dependent UPLC-Q-ToF-MS/MS acquisition. The automatic analysis was compared against manual MS/MS spectra interpretation. With the lipid class specific models, identification of the true positives was improved especially for cases where candidate lipids from different lipid classes had similar MetFrag scores by removing up to 56% of false positive results. This LipidFrag approach was then applied to MS/MS spectra of lipid extracts of the nematode Caenorhabditis elegans. Fragments explained by LipidFrag match known fragmentation pathways, e.g., neutral losses of lipid headgroups and fatty acid side chain fragments. Based on prediction models trained on standard lipid materials, high probabilities for correct annotations were achieved, which makes LipidFrag a good choice for automated lipid data analysis and reliability testing of lipid identifications.
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J Chromatogr B Analyt Technol Biomed Life Sci,
2015]
Separation of isomeric molecular species, e.g. double bond position isomers, is a challenging task for liquid chromatography. The two steroid hormones 4- and 7-dafachronic acid (DA) represent such an isomeric pair. DAs are 3-ketosteroids found in the nematode Caenorhabditis elegans and generated from cholesterol. 4- and 7-DA have important biological activities and are produced by two different biological pathways in C. elegans. Here we have described a fast separation method for these two isomers using a 1.3 m core-shell particle in less than 10 min together with a simple MeOH extraction. Using this method we were able to independently quantify 4- and 7-DA in C. elegans independently from each other and limits of detection of about 5 ng/ml for each isomer were achieved with a good day-to-day reproducibility. As proof-of-principle the method has been applied to the quantification of DAs in worms fed ad libitum or under bacterial deprivation.
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Wakelam MJO, Rodriguez N, Witting M, van Weeghel M, Houtkooper RH, Hattwell JPN, Kaleta C, Hastings J, Sadykoff S, Casanueva O, Gao AW, Mains A, Le Novere N, Joshi CJ, Schroeder F, Ebert PR, Schirra HJ, Lewis NE
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Front Mol Biosci,
2018]
Metabolism is one of the attributes of life and supplies energy and building blocks to organisms. Therefore, understanding metabolism is crucial for the understanding of complex biological phenomena. Despite having been in the focus of research for centuries, our picture of metabolism is still incomplete. Metabolomics, the systematic analysis of all small molecules in a biological system, aims to close this gap. In order to facilitate such investigations a blueprint of the metabolic network is required. Recently, several metabolic network reconstructions for the model organism <i>Caenorhabditis elegans</i> have been published, each having unique features. We have established the WormJam Community to merge and reconcile these (and other unpublished models) into a single consensus metabolic reconstruction. In a series of workshops and annotation seminars this model was refined with manual correction of incorrect assignments, metabolite structure and identifier curation as well as addition of new pathways. The WormJam consensus metabolic reconstruction represents a rich data source not only for <i>in silico</i> network-based approaches like flux balance analysis, but also for metabolomics, as it includes a database of metabolites present in <i>C. elegans</i>, which can be used for annotation. Here we present the process of model merging, correction and curation and give a detailed overview of the model. In the future it is intended to expand the model toward different tissues and put special emphasizes on lipid metabolism and secondary metabolism including ascaroside metabolism in accordance to their central role in <i>C. elegans</i> physiology.
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Anal Bioanal Chem,
2015]
In metabolomics there is an ever-growing need for faster and more comprehensive analysis methods to cope with the increasing size of biological studies. Direct-infusion ion-cyclotron-resonance Fourier-transform spectrometry (DI-ICR-FT-MS) is used in non-targeted metabolomics to obtain high-resolution snapshots of the metabolic state of a system. We applied this technology to a Caenorhabditis elegans-Pseudomonas aeruginosa infection model and optimized times needed for cultivation and mass-spectrometric analysis. Our results reveal that DI-ICR-FT-MS is a promising tool for high-throughput in-depth non-targeted metabolomics. We performed whole-worm metabolomics and recovered markers of the induced metabolic changes in C. elegans brought about by interaction with pathogens. In this investigation, we reveal complex metabolic phenotypes enabling clustering based upon challenge. Specifically, we observed a marked decrease in amino-acid metabolism with infection by P. aeruginosa and a marked increase in sugar metabolism with infection by Salmonella enterica. We were also able to discriminate between infection with a virulent wild-type Pseudomonas and with an attenuated mutant, making it possible to use this method in larger genetic screens to identify host and pathogen effectors affecting the metabolic phenotype of infection.
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J Chromatogr A,
2014]
Lipid profiling or lipidomics is currently applied in many different research fields. It refers to the global analysis of a samples lipid content using different analytical chemistry methods, with mass spectrometry as the mostly employed technology. We developed a comprehensive in-depth analysis method for the lipidome of the soil-dwelling nematode Caenorhabitis elegans, a widely used model organism. Four different columns were compared with a generic gradient and a novel
sub-2-m core-shell column, Waters Cortecs C18, showed superior performance in case of chromatographic peak characteristics, e.g. plate numbers and number of detected lipid features. Retention time deviation was generally less than 1% within one column and below 5% for columns from different batches. Intensity variation was lower than 30% for most detected features. Improved chromatographic separation showed enhanced resolution for isomeric lipids and allowed collection of highly detailed MS/MS spectra for lipid identification. In total 1304 lipid features were detected in positive ionization mode and 265 in negative mode. Lipids from different classes were annotated and MS/MS spectra obtained by data dependent fragmentation were used for identification purposes.
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Metabolites,
2021]
Metabolomics and lipidomics recently gained interest in the model organism <i>Caenorhabditis elegans</i> (<i>C. elegans</i>). The fast development, easy cultivation and existing forward and reverse genetic tools make the small nematode an ideal organism for metabolic investigations in development, aging, different disease models, infection, or toxicology research. The conducted type of analysis is strongly depending on the biological question and requires different analytical approaches. Metabolomic analyses in <i>C. elegans</i> have been performed using nuclear magnetic resonance (NMR) spectroscopy, direct infusion mass spectrometry (DI-MS), gas-chromatography mass spectrometry (GC-MS) and liquid chromatography mass spectrometry (LC-MS) or combinations of them. In this review we provide general information on the employed techniques and their advantages and disadvantages in regard to <i>C. elegans</i> metabolomics. Additionally, we reviewed different fields of application, e.g., longevity, starvation, aging, development or metabolism of secondary metabolites such as ascarosides or maradolipids. We also summarised applied bioinformatic tools that recently have been used for the evaluation of metabolomics or lipidomics data from <i>C. elegans</i>. Lastly, we curated metabolites and lipids from the reviewed literature, enabling a prototypic collection which serves as basis for a future <i>C. elegans</i> specific metabolome database.