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Data from: Neglected very long-chain hydrocarbons and the incorporation of body surface area metrics reveal novel perspectives for cuticular profile analysis in insects

Citation

Buellesbach, Jan et al. (2022), Data from: Neglected very long-chain hydrocarbons and the incorporation of body surface area metrics reveal novel perspectives for cuticular profile analysis in insects, Dryad, Dataset, https://doi.org/10.6078/D1QT36

Abstract

Most of our knowledge on insect cuticular hydrocarbons (CHCs) stems from analytical techniques based on gas-chromatography coupled with mass spectrometry (GC-MS). However, this method has its limits under standard conditions, particularly in detecting compounds beyond a chain length of around C40. Here, we compare the CHC chain length range detectable by GC-MS with the range assessed by silver-assisted laser desorption/ionization mass spectrometry (Ag-LDI-MS), a novel and rarely applied technique on insect CHCs, in seven species of the order Blattodea. For all tested species, we unveiled a considerable range of very long-chain CHCs up to C58, which are not detectable by standard GC-MS technology. This indicates that general studies on insect CHCs may frequently miss compounds in this range, and we encourage future studies to implement analysis techniques extending the conventionally accessed chain length ranges. Furthermore, we incor-porate 3D scanned insect body surface areas as an additional factor for the comparative quantifi-cation of extracted CHC amounts between our study species. CHC quantity distributions differed considerably when adjusted for body surface areas as opposed to directly assessing extracted CHC amounts, suggesting that a more accurate evaluation of relative CHC quantities can be achieved by taking body surface areas into account.

Methods

Gas-chromatography coupled with mass spectrometry (GC-MS)

Silver-assisted laser desorption/ionization mass spectrometry (Ag-LDI-MS)

DISC3D extended depth of field (EDOF) imaging technology

Funding

Deutsche Forschungsgemeinschaft, Award: 427879779

Deutsche Forschungsgemeinschaft, Award: 290343045