Back

Olfaction in Tephritidae: a balance between detection and discrimination

Ramiaranjatovo, G.; Charlery de la Masseliere, M.; Dekker, T.; Duyck, P.-F.; Larsson Herrera, S.; Reynaud, B.; Jacob, V.

2024-03-15 ecology
10.1101/2024.03.14.584788 bioRxiv
Show abstract

Phytophagous insects are capable of detecting and locating suitable hosts, which emit volatile compounds. Polyphagous species appear to have a complex olfactory strategy given that their numerous hosts have diverse emission profiles. In particular, their hosts volatile emissions share some of the same compounds, providing chemical bridges between them. However, the behavioural plasticity observed in insect host selection suggests that other volatiles have a complementary role. Here we explore how the specialization of polyphagous Tephritidae fruit fly in detecting and discriminating between host fruits has driven their chemical selectivity. The volatile emissions from intact or mechanically damaged fruit of 28 different species were analysed using gas chromatography-mass spectrometry and fed into a neuronal model of an olfactory system. We predicted in silico a functional trade-off between the two tasks, with optimal performance depending on detecting a higher proportion of shared fruit compounds, but with lower sensitivity compared to unshared compounds, or vice-versa. Using triple point electroantennography and a behavioural assay, we studied the olfactory response of Tephritidae fruit fly species that oviposit on fruit. Amplitude of the olfactory responses of eight species were negatively correlated with the compounds degree of sharedness among fruit emissions, while response probability was previously shown to correlate positively with a similar metric. A dose-dependent switch in the flys preference confirmed the ecological importance of both shared and unshared fruit compounds. Thus, we propose that insect olfactory systems are chemically tuned to detect suitable hosts and accurately discriminate between them.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Scientific Reports
3612 papers in training set
Top 1.0%
17.9%
2
Journal of Chemical Ecology
10 papers in training set
Top 0.1%
9.4%
3
eLife
5828 papers in training set
Top 15%
7.0%
4
Communications Biology
993 papers in training set
Top 0.7%
7.0%
5
iScience
1154 papers in training set
Top 4%
4.2%
6
Pest Management Science
36 papers in training set
Top 0.2%
3.4%
7
Proceedings of the Royal Society B: Biological Sciences
393 papers in training set
Top 2%
3.3%
50% of probability mass above
8
Peer Community Journal
281 papers in training set
Top 2%
3.1%
9
Nature Ecology & Evolution
113 papers in training set
Top 0.6%
3.0%
10
Nature Communications
5641 papers in training set
Top 38%
2.7%
11
Insects
42 papers in training set
Top 0.3%
2.6%
12
Ecology and Evolution
267 papers in training set
Top 3%
2.3%
13
PLOS ONE
5266 papers in training set
Top 46%
2.1%
14
Frontiers in Ecology and Evolution
69 papers in training set
Top 1%
2.1%
15
Royal Society Open Science
214 papers in training set
Top 3%
1.9%
16
BMC Biology
265 papers in training set
Top 2%
1.8%
17
PLOS Biology
486 papers in training set
Top 5%
1.7%
18
Science of The Total Environment
186 papers in training set
Top 2%
1.6%
19
Current Biology
665 papers in training set
Top 7%
1.5%
20
Functional Ecology
61 papers in training set
Top 0.9%
1.5%
21
Molecular Ecology Resources
171 papers in training set
Top 1%
1.4%
22
New Phytologist
346 papers in training set
Top 4%
1.1%
23
The ISME Journal
228 papers in training set
Top 3%
1.0%
24
Plant Biology
15 papers in training set
Top 0.5%
0.9%
25
Insect Biochemistry and Molecular Biology
30 papers in training set
Top 0.4%
0.8%
26
Evolution
225 papers in training set
Top 2%
0.8%
27
Ecological Entomology
13 papers in training set
Top 0.4%
0.8%
28
Frontiers in Plant Science
256 papers in training set
Top 4%
0.6%
29
International Journal of Biological Sciences
10 papers in training set
Top 0.3%
0.6%
30
Cell Reports
1498 papers in training set
Top 30%
0.6%