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. 2025 May 9;51(3):52.
doi: 10.1007/s10886-025-01562-w.

Chemical Recognition Cues in Ant-Aphid Mutualism: Differentiating, Sharing, and Modifying Cuticular Components

Affiliations

Chemical Recognition Cues in Ant-Aphid Mutualism: Differentiating, Sharing, and Modifying Cuticular Components

Jesús Foronda et al. J Chem Ecol. .

Abstract

Aphid-tending ants form mutualistic associations with aphids. During their interactions, aphids and ants use both tactile stimuli and chemical cues to communicate. Recent studies suggest that ants modify the cuticular hydrocarbons of mutualistic aphids they attend, but it is unclear which compounds are implicated in recognition. Thus, we investigated the chemical basis for the discrimination between attended and unattended aphids, Aphis gossypii Glover (Hemiptera: Aphididae), by the ant Tapinoma ibericum (Santschi, 1925) including cuticular hydrocarbons (CHCs and non-CHCs) compounds in the analysis. Chemical profiles of 14 colonies of A. gossypii attended by ants for three days were significantly different from those of unattended aphids. These results show that contact with T. ibericum rapidly induces modification of the cuticular profiles of the aphids on which they feed. Moreover, the compounds of unattended aphid A. gossypii also change over time but differ from those of attended aphids. The main compound of the ant cuticle (3,15-di-MeC27), which is highly abundant in attended aphids, was identified as a possible recognition marker, but without forgetting other identified compounds that may also play a predominant role in the ant-aphid mutualistic interactions. These promising compounds represent opportunities for pest control strategies using chemical manipulations.

Keywords: Aphididae; Chemical profiles; Cuticular hydrocarbons; Formicidae; Mutualism; Recognition.

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Conflict of interest statement

Declarations. Competing Interests: The authors declare no competing interests. Ethics Approval: Not applicable. Conflict of Interest: The authors declare no competing interests. Consent to Participate: Not applicable. Consent to Publish: All authors have approved the contents of this paper and agreed to the journal submission policies. This manuscript has not been published previously and is not under consideration for publication in another journal.

Figures

Fig. 1
Fig. 1
(A) Scree plot displaying how much variations of the data are captured by the first 5 principal components. Here, the top five axes capture 75% of variance. (B) Biplot of the Principal Components Analysis (PCA) based on the 252 samples, where it represents either ants (yellow) or aphids (blue), with 95% confidence ellipses. The axes show the principal component 1 and 2. The vectors are the loading vectors (compounds), whose components are colored depending on their magnitudes. A high cos2 (orange) indicates a good representation of the variable on the principal axes under consideration. In this case, the variable is positioned near the circumference of the correlation circle. (C) Bar plot of the main contributing variables (compounds) to the first two dimensions. The red dotted line indicates the expected average contribution. For a given component, the colors of the bar plot indicate if the contribution of the variables points toward ants (yellow) or aphids (blue)
Fig. 2
Fig. 2
Heat map analysis of the abundances (peak area) of the chemical profiles of ants and aphids at different time intervals, and mutualistic conditions or not. Heat map represents unsupervised hierarchical clustering dendrogram (Euclidean distances) of groups (rows, n = 252). The rows display samples, and the columns represent the peaks (n = 81). The lower abundance of peaks in samples is displayed in dark brown, while higher abundance is displayed in dark green (the gradient is represented on the right). The annotation on the left side of the heatmap shows the distribution of either the modalities (species, mutualism state or time) or the clusters (1 or 2) calculated from the Euclidean distances
Fig. 3
Fig. 3
(A) Tri-dimensional partial least-squares discriminant analysis scatter plot based on the chemical profiles of Aphid0 (blue; Aphids at T0), Aphid+ (grey; mutualistic aphids), and Aphid- (orange; non-mutualistic aphids), with 95% confidence ellipses (Scores plot for Component 1: 35%, Component 2: 16%, Component 3: 7%). (B) Variable Importance in Projection (VIP, compounds with a VIP > 1 are deemed important) Scores, generated from the first component of the PLS-DA (Fig. 3.A), indicating the most discriminating compounds in descending order of importance
Fig. 4
Fig. 4
(A) Tri-dimensional partial least-squares discriminant analysis scatter plot based on the chemical profiles of Aphid+ (orange; mutualistic aphids) and Aphid- (blue; non-mutualistic aphids), with 95% confidence ellipses (Scores plot for Component 1: 25%, component 2: 22%, Component 3: 12%). (B) VIP scores generated from the first component of the PLS-DA (Fig. 4A), indicating the most discriminating compounds in descending order of importance
Fig. 5
Fig. 5
(A) The line plot illustrates the mean peak area from aphids’ profiles of the 81 compounds, from all the colonies for non-mutualistic aphids (Aphid-) and mutualistic aphids (Aphid+). The compounds listed are P75: Octacosanol, P74: nC31, P59: nC29, P42: nC27, P73: Octacosanal, P53: 3,15-di-MeC27, P12: n-Hexadecanoic acid, P28: nC25. (B) Box plots of the median and interquartile ranges of the six first VIP compounds from the second PLS-DA (Fig. 4). The gray lines connect the mean peak area from aphids’ profiles from the same colony for non-mutualistic aphids (Aphid- in blue) and mutualistic aphids (Aphid + in orange). The compounds listed are P1:1-Naphthalenol, decahydro-4a-methyl-, P2: nC13, P23: Hexadecanoic acid, 2-hydroxy-1-(hydroxymethyl)ethyl ester, P26: nC23, P53: 3,15-di-MeC27, P62: 5-MeC29

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