Nuclear magnetic resonance (NMR) spectroscopy is widely used as a metabolomics tool, and 1D spectroscopy is overwhelmingly the commonest approach. The use of 2D spectroscopy could offer significant advantages in terms of increased spectral dispersion of peaks, but has a number of disadvantages—in particular, heteronuclear 2D spectroscopy is often much less sensitive than 1D NMR. One factor contributing to this low sensitivity in 13C/1H heteronuclear NMR is the low natural abundance of the 13C stable isotope; as a consequence, where it is possible to label biological material with 13C, there is a potential enhancement of sensitivity of up to around 90fold. However, there are some problems that can reduce the advantages otherwise gained—in particular, the fine structure arising from 13C/13C coupling, which is essentially non-existent at natural abundance, can reduce the possible sensitivity gain and increase the chances of peak overlap. Here, we examined the use of two different heteronuclear single quantum coherence (HSQC) pulse sequences for the analysis of fully 13C-labeled tissue extracts from Caenorhabditis elegans nematodes. The constant time ct-HSQC had improved peak shape, and consequent better peak detection of metabolites from a labeled extract; matching this against reference spectra from the HMDB gave a match to about 300 records (although fewer actual metabolites, as some of these represent false positive matches). This approach gives a rapid and automated initial metabolome assignment, forming an ideal basis for further manual curation.