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10-Minute Presentation

Physiology, Biochemistry, and Toxicology

10-min: PBT, Genetics

In silico secretome analysis of the coffee pest Leucoptera coffeella

Wednesday, November 13, 2024
3:06 PM – 3:18 PM MST
Location: Phoenix Convention Center, 121 C, PCC
Oral Presentation
Coffee is one of the most consumed beverages worldwide. The coffee leaf miner (Leucoptera coffeella), a major pest that affects coffee plants, is responsible for losses of up to 70% in production. Molecular studies of the insect metabolism can generate biotechnological assets that provide sustainable solutions for control management, reducing the use of chemical insecticides, like dsRNA topic application to gene silencing.

From an initial dataset of 39,930 predicted gene models in the L. coffeella genome, 12,268 were retrieved after bioinformatics tools were applied to filter putative protein sequences shorter than 100 and larger than 500 amino acids. Then, SignalP6 analysis registered the presence of a signal peptide in 1,107 sequences.

Finally, a Blast P performed against the Drosophila secretome data rendered 1043 matching hits. Refined results with e-value -10 showed 445 matches.

In parallel, searching in 2045 proteomic sequences of L. coffeella putative proteins, with the same protein size and signal peptide criteria herein described and an additional removal of transmembrane features, we found 261 putative secreted protein candidates. Among the annotations, peroxidases, catalases, mucins glutathione-S-transferases, as expected, and, interestingly, a disintegrin and metalloproteinase that may be implicated in the innate immunity and metamorphosis of the insect.

The results we found contribute to the generation of knowledge about this lepidopteran and can be used in the development of alternative products that are favorable to producers and the environment, in addition to contributing to the quality of coffee for the consumer market.