The Application of Quantitative Metabolomics for the Taxonomic Differentiation of Birds

Abstract

In the current pilot study, we propose the use of quantitative metabolomics to reconstruct the phylogeny of vertebrates, namely birds. We determined the concentrations of the 67 most abundant metabolites in the eye lenses of the following 14 species from 6 orders of the class Aves (Birds): the Black kite (Milvus migrans), Eurasian magpie (Pica pica), Northern raven (Corvus corax), Eurasian coot (Fulica atra), Godlewski’s bunting (Emberiza godlewskii), Great crested grebe (Podiceps cristatus), Great tit (Parus major), Hawfinch (Coccothraustes coccothraustes), Hooded crow (Corvus cornix), House sparrow (Passer domesticus), Rock dove (Columba livia), Rook (Corvus frugilegus), Short-eared owl (Asio flammeus) and Ural owl (Strix uralensis). Further analysis shows that the statistical approaches generally used in metabolomics can be applied for differentiation between species, and the most fruitful results were obtained with hierarchical clustering analysis (HCA). We observed the grouping of conspecific samples independently of the sampling place and date. The HCA tree structure supports the key role of genomics in the formation of the lens metabolome, but it also indicates the influence of the species lifestyle. A combination of genomics-based and metabolomics-based phylogeny could potentially resolve arising issues and yield a more reliable tree of life.

Keywords

• quantitative metabolomics
• phylogeny
• hierarchical clustering analysis
• NMR spectroscopy
• eye lens
• birds