Imperial College London


Faculty of MedicineDepartment of Surgery & Cancer

Honorary Research Fellow







Sir Alexander Fleming BuildingSouth Kensington Campus





Publication Type

4 results found

Liebeke M, Bruford MW, Donnelly RK, Ebbels TM, Hao J, Kille P, Lahive E, Madison RM, Morgan AJ, Pinto-Juma GA, Spurgeon DJ, Svendsen C, Bundy JGet al., 2014, Identifying biochemical phenotypic differences between cryptic species., Biology Letters, Vol: 10, ISSN: 1744-9561

Molecular genetic methods can distinguish divergent evolutionary lineages in what previously appeared to be single species, but it is not always clear what functional differences exist between such cryptic species. We used a metabolomic approach to profile biochemical phenotype (metabotype) differences between two putative cryptic species of the earthworm Lumbricus rubellus. There were no straightforward metabolite biomarkers of lineage, i.e. no metabolites that were always at higher concentration in one lineage. Multivariate methods, however, identified a small number of metabolites that together helped distinguish the lineages, including uncommon metabolites such as Nε-trimethyllysine, which is not usually found at high concentrations. This approach could be useful for characterizing functional trait differences, especially as it is applicable to essentially any species group, irrespective of its genome sequencing status.

Journal article

Hao J, Liebeke M, Astle W, De Iorio M, Bundy JG, Ebbels TMDet al., 2014, Bayesian deconvolution and quantification of metabolites in complex 1D NMR spectra using BATMAN, NATURE PROTOCOLS, Vol: 9, Pages: 1416-1427, ISSN: 1754-2189

Journal article

Liebeke M, Hao J, Ebbels TMD, Bundy JGet al., 2013, Combining Spectral Ordering with Peak Fitting for One-Dimensional NMR Quantitative Metabolomics, ANALYTICAL CHEMISTRY, Vol: 85, Pages: 4605-4612, ISSN: 0003-2700

Journal article

Hao J, Astle W, De Iorio M, Ebbels TMDet al., 2012, BATMAN-an R package for the automated quantification of metabolites from nuclear magnetic resonance spectra using a Bayesian model, BIOINFORMATICS, Vol: 28, Pages: 2088-2090, ISSN: 1367-4803

Journal article

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