Back

A computational approach to identify possible symbiotic mechanisms between Klebsiella and the Mediterranean fly (Ceratitis capitata)

Franco, L. A.; Bravo Pariente, C. A.

2021-02-14 bioinformatics
10.1101/2021.02.13.431071 bioRxiv
Show abstract

Nowadays, scientists develop multiple methods to control pests, like chemical control as the insecticides and biological control as the Sterile Insect Technique (SIT) to release infertile males produced by irradiation. This technique is complemented with research in the medflys (Ceratitis capitata) microbiota, this approach is based on the identification of molecular mechanisms from three Klebsiella strains using the reconstruction of metabolic pathways technique. We focus on the reconstruction of metabolic pathways involved in nitrogen metabolization because the bacteria are in charge of metabolizing the nitrogen compounds and make available for the medfly. We propose a pipeline to process the genome sequences the bacteria, reconstruct metabolic pathways and identify possible symbiont molecular mechanisms. The result of processing the biological data were ten pathways, six pathways produce L-Glutamate as final product, three pathways with ammonia product and one pathway was discarded because it was an internal pathway and dont generate a metabolic product. Those pathways corresponding to L-Glutamate and ammonia metabolic products are part of nitrogen metabolism on Klebsiella, which shows that this metabolic process is one of the molecular mechanisms involved in symbiosis process between Klebsiella and the medfly. Finally, by the results of the sequences analysis, in the medflys metamorphose the L-Glutamate are used in the synthesis of new proteins and the production of energy. The final consideration suggest that the pipeline propose can be used as first step to identify molecular mechanisms that can improve the production of industrial the medfly.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.