Quo Vadis Caenorhabditis elegans Metabolomics-A Review of Current Methods and Applications to Explore Metabolism in the Nematode

Abstract

Metabolomics and lipidomics recently gained interest in the model organism Caenorhabditis elegans (C. elegans). 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 C. elegans 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 C. elegans 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 C. elegans. Lastly, we curated metabolites and lipids from the reviewed literature, enabling a prototypic collection which serves as basis for a future C. elegans specific metabolome database.

Keywords: Caenorhabditis elegans; NMR; lipidomics; mass-spectrometry; metabolomics.

Figure 1

Example of ascaroside-structures: ascr#1, hbas#10, ascr#10 and ascr#3.

Figure 2

FA profiles from different publications. From left to right: saturated, monounsaturated (MUFA), polyunsaturated (PUFA), monomethyl branched chain (MMBA), and Cyclopropane (Cyclo) fatty acids. Publications that were included: Henry et al., 2016 [75], Shi et al., 2013 [90], Vrablik et al., 2015 [93], Hutzel et al., 1982 [125], Tanaka et al., 1996 [126], Brooks et al., 2009 (HB101 & OP50) [127], and Shi et al., 2016 [128].

Figure 3

Venn diagram of overlap of metabolites between literature (yellow) and WormJam (grey) based on the first block of their InChIKey.

Figure 4

Molecular weight and logP distribution of merged molecules from the WormJam model and curated from literature. Different separation methods and their polarity are displayed in the logP range. Reversed phase liquid chromatography (RPLC), gas chromatography (GC), aqueous normal phase (ANP) chromatography, hydrophilic interaction liquid chromatography (HILIC), ion chromatography, capillary electrophoresis (CE) and supercritical fluid chromatography (SFC).