9. Metabolomics

9.5. Metabolomics applications and limitations

Metabolomics is gaining popularity due to the vast spectrum of metabolites that can be identified and compared between samples. Using mass spectrometry for metabolomics has many advantages over traditional biochemical assays, such as high sensitivity and the ability to detect a large number of metabolites and small molecules from very small sample sizes (Veenstra, 2012). In addition, with the availability of better databases, identification of small molecules has become easier. But despite the effort that goes into sample preparation and analysis, metabolomic identifications are only tentative detections until retention times and fragmentation patterns are confirmed with high-purity analytical standards, whether part of an in-house library or purchased separately. When this confirmation is achieved, such compounds may rise to the level of being “identified” (i.e., level 1 annotation, as opposed to levels 2, 3, and 4, corresponding to “putatively annotated compounds,” “putatively annotated compound classes,” and “unknown compounds,” respectively (Sumner et al., 2007).

Features must always be compared with an MS/MS spectral library (e.g. METLIN) when compounds are not an exact match with those within the in-house library. In this case, a high-purity standard must be purchased to confirm a tentative assignment. Furthermore, for absolute quantitation of targeted metabolomics, isotopically labeled and unlabeled standards are required for exact quantifications of the targeted small molecules. While labeled standards are used as internal standards, unlabeled standards are used for creating standard curves for absolute quantification. All these analytical standards can add a substantial cost to an already costly method, and labeled standards are not available for every compound, but these steps are essential to confidently identify and quantify small molecules.

If metabolomics is conducted in the absence of an in-house chemical library, the user must rely on generic spectral matching using digital libraries for putative compound assignments, and reliability of such matches is limited without time consuming manual assessments of annotations and subsequent verification using analytical standards. However, reliable results can still be produced using open source software tools not made by a specific instrument vendor, particularly by integrating complementary digital reference libraries, and confirming identifications with pure analytical standards.

Metabolomics is a powerful tool and gives us a snapshot into a wide spectrum of biological molecules in honey bees. It is helpful for understanding honey bee developmental physiology or adaptive molecular responses to various stressors. With ongoing small molecule discoveries and inclusion of these species in spectral libraries, metabolomics is emerging as the new power tool in modern omics analyses. Excitingly, the closely related field of lipidomics is also emerging in honey bees (Morfin et al., 2022), and co-extraction of metabolites, lipids, and pheromones has been performed on queens (McAfee et al., 2024). The diversity of small molecules that can be analyzed by LC-MSMS and integration with pheromone analysis will likely enable many new insights into honey bee physiology in the future.