Spatially controlled in vivo sampling by contact solid phase microextraction with a non-coated silica fiber combined with gas chromatography-mass spectrometry (GC-MS) was utilized for hydrocarbon profiling in tarsal adhesion secretions of four insect species (Nicrophorus vespilloides, Nicrophorus nepalensis, Sagra femorata, and Gromphadorhina portentosa) by using distinct adhesion systems, viz. hairy or smooth tarsi. For comparison, corresponding samples from tibiae, representing the general cuticular hydrocarbon profile, were analyzed to enable the statistical inference of active molecular adhesion principles in tarsal secretions possibly contributed by specific hydrocarbons. n-Alkanes, monomethyl and dimethyl alkanes, alkenes, alkadienes, and one aldehyde were detected. Multivariate statistical analysis (principal component and orthogonal partial least square discriminant analyses) gave insights into distinctive molecular features among the various insect species and between tarsus and tibia samples. In general, corresponding hydrocarbon profiles in tarsus and tibia samples largely resembled each other, both qualitatively and in relative abundances as well. However, several specific hydrocarbons showed significantly different relative abundances between corresponding tarsus and tibia samples, thus indicating that such differences of specific hydrocarbons in the complex mixtures might constitute a delicate mechanism for fine-tuning the reversible attachment performances in tarsal adhesive fluids that are composed of substances originating from the same pool as cuticular hydrocarbons. Caused by melting point depression, the multicomponent tarsal adhesion secretion, made up of straight chain alkanes, methyl alkanes, and alkenes will have a semi-solid, grease-like consistency, which might provide the basis for a good reversible attachment performance.
Keywords: Adhesion; Gas chromatography-mass spectrometry; Gromphadorhina; Insect secretions; Locomotion; Long-chain hydrocarbons; Molecular phenotyping; Nicrophorus; Principal component analysis; Sagra; Silica fiber sampling.