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Neglected Very Long-Chain Hydrocarbons and the Incorporation of Body Surface Area Metrics Reveal Novel Perspectives for Cuticular Profile Analysis in Insects

Golian, Marek ; Bien, Tanja ; Schmelzle, Sebastian ; Esparza-Mora, Margy Alejandra ; McMahon, Dino Peter ; Dreisewerd, Klaus ; Buellesbach, Jan (2022)
Neglected Very Long-Chain Hydrocarbons and the Incorporation of Body Surface Area Metrics Reveal Novel Perspectives for Cuticular Profile Analysis in Insects.
In: Insects, 2022, 13 (1)
doi: 10.26083/tuprints-00020525
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Neglected Very Long-Chain Hydrocarbons and the Incorporation of Body Surface Area Metrics Reveal Novel Perspectives for Cuticular Profile Analysis in Insects
Language: English
Date: 13 April 2022
Place of Publication: Darmstadt
Year of primary publication: 2022
Publisher: MDPI
Journal or Publication Title: Insects
Volume of the journal: 13
Issue Number: 1
Collation: 13 Seiten
DOI: 10.26083/tuprints-00020525
Corresponding Links:
Origin: Secondary publication DeepGreen
Abstract:

The waxy layer covering the surface of most terrestrial insects is mainly composed of non-polar lipids termed cuticular hydrocarbons (CHCs). These have a long research history as important dual traits for both desiccation prevention and chemical communication. We analyzed CHC profiles of seven species of the insect order Blattodea (termites and cockroaches) with the most commonly applied chromatographic method, gas-chromatography coupled with mass spectrometry (GC-MS), and the more novel approach of silver-assisted laser desorption/ionization mass spectrometry (Ag-LDI-MS). Comparing these two analytical methods, we demonstrated that the conventional GC-MS approach does not provide enough information on the entire CHC profile range in the tested species. Ag-LDI-MS was able to detect very long-chain CHCs ranging up to C58, which remained undetected when solely relying on standard GC-MS analysis. Additionally, we measured the body surface areas of each tested species applying 3D scanning technology to assess their respective CHC amounts per mm². When adjusting for body surface areas, proportional CHC quantity distributions shifted considerably between our studied species, suggesting the importance of including this factor when conducting quantitative CHC comparisons, particularly in insects that vary substantially in body size. 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 analytical techniques extending the conventionally accessed chain length range. Furthermore, we incorporate 3D scanned insect body surface areas as an additional factor for the comparative quantification 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.

Uncontrolled Keywords: cuticular hydrocarbons, Blattodea, GC-MS, Ag-LDI-MS, chemical ecology
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-205250
Classification DDC: 500 Science and mathematics > 570 Life sciences, biology
Divisions: 10 Department of Biology > Ecological Networks
Date Deposited: 13 Apr 2022 11:10
Last Modified: 14 Nov 2023 19:04
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/20525
PPN: 500723583
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