Olfactory discrimination tasks can provide useful information about how olfaction may have evolved by demonstrating which types of compounds animals will detect and respond to. Ants discriminate between nestmates and non-nestmates by using olfaction to detect the cuticular hydrocarbons on other ants, and Camponotus floridanus have particularly clear and aggressive responses to non-nestmates. A new method of adding hydrocarbons to ants, the “Snow Globe” method was further optimized and tested on C. floridanus. It involves adding hydrocarbons and a solvent to a vial of water, vortexing it, suspending hydrocarbon droplets throughout the solution, and then dipping a narcotized ant in. It is hoped this method can evenly coat ants in hydrocarbon. Ants were treated with heptacosane (C27), nonacosane (C29), hentriacontane (C31), a mixture of C27/C29/C31, 2-methyltriacontane (2MeC30), S-3-methylhentriacontane (SMeC31), and R-3-methylhentriacontane (RMeC31). These were chosen to see how ants reacted in a nestmate recognition context to methyl-branched hydrocarbons, R and S enantiomers, and to multiple added alkanes. Behavior assays were performed on treated ants, as well as two untreated controls, a foreign ant and a nestmate ant. There were 15 replicates of each condition, using 15 different queenright colonies. The Snow Globe method successfully transfers hydrocarbons, as confirmed by solid phase microextraction (SPME) done on treated ants, and the behavior assay data shows the foreign control, SMeC31, and the mixture of C27/29/31 were all statistically significant in their differences from the native control. The multiple alkane mixture received a significant response while single alkanes did not, which supports the idea that larger variations in hydrocarbon profile are needed for an ant to be perceived as foreign. The response to SMeC31 shows C. floridanus can respond during nestmate recognition to hydrocarbons that are not naturally occurring, and it indicates the nestmate recognition process may simply be responding to any compounds not found in the colony profile and rather than detecting particular foreign compounds.

Enantiomers are pairs of non-superimposable mirror-image molecules. One molecule in the pair is the clockwise version (+) while the other is the counterclockwise version (-). Some pairs have divergent odor qualities, e.g. L-carvone (“spearmint”) vs. D-carvone (“caraway”), while other pairs do not. Existing theory about the origin of such differences is largely qualitative (Friedman and Miller, 1971; Bentley, 2006; Brookes et al., 2008). While quantitative models based on intrinsic molecular features predict some structure–odor relationships (Keller et al., 2017), they cannot identify, e.g. the more intense enantiomer in a pair; the mathematical operations underlying such features are invariant under symmetry (Shadmany et al., 2018). Only the olfactory receptor (OR) can break this symmetry because each molecule within an enantiomeric pair will have a different binding configuration with a receptor. However, features that predict odor divergence within a pair may be identifiable; for example, six-membered ring flexibility has been offered as a candidate (Brookes et al., 2008). To address this problem, we collected detection threshold data for >400 molecules (organized into enantiomeric pairs) from a variety of public data sources and academic literature. From each pair, we computed the within-pair divergence in odor detection threshold, as well as Mordred descriptors (molecular features derived from the structure of a molecule) and Morgan fingerprints (mathematical representations of molecule structure). While these molecular features are identical within-pair (due to symmetry), they remain distinct across pairs. The resulting structure+perception dataset was used to build a predictive model of odor detection threshold divergence. It predicted a modest fraction of variance in odor detection threshold divergence (r 2 ~ 0.3 in cross-validation). We speculate that most of the remaining variance could be explained by a better understanding of the ligand-receptor binding process.