Plastic pollution is one of the most pressing environmental challenges of our time, and recent studies suggest that insect larvae may host microbial communities with the potential to degrade synthetic polymers. To advance research in this area, a general-purpose bioinformatics framework named EntomoDB was developed to support the exploration, analysis, and sharing of microbial genomic data related to biodegradation. The platform combines a user-friendly web interface with a backend based on MongoDB, integrates predictive tools such as PlasFlow, and provides a ready-to-use pipeline for the analysis of user-submitted sequences. As a case study, the framework was applied to genomic data obtained from larvae reared under three experimental conditions: minimal agar substrate (AG), polyethylene (PE), and polystyrene (PS). DNA sequences were translated into proteins, curated through exploratory analyses, and inserted into the database. The resulting curated dataset, comprising more than 400,000 annotated protein sequences, was stored in a MongoDB database. EntomoDB offers a structured and publicly accessible resource designed to facilitate future studies on the enzymatic potential of microbial communities involved in plastic biodegradation.
L’inquinamento da plastica rappresenta una delle sfide ambientali più urgenti del nostro tempo, e recenti studi suggeriscono che alcune larve di insetti possano ospitare comunità microbiche con il potenziale di degradare polimeri sintetici. Per sostenere la ricerca in questo ambito è stato sviluppato un framework bioinformatico generale denominato EntomoDB, progettato per supportare l’esplorazione, l’analisi e la condivisione di dati genomici microbici legati alla biodegradazione. La piattaforma combina un’interfaccia web intuitiva con un backend basato su MongoDB, integra strumenti predittivi come PlasFlow e mette a disposizione una pipeline pronta all’uso per l’analisi di sequenze fornite dagli utenti. Come caso di studio, il framework è stato applicato a dati genomici ottenuti da larve allevate in tre condizioni sperimentali: substrato di agar minimale (AG), polietilene (PE) e polistirene (PS). Le sequenze di DNA sono state tradotte in proteine, curate attraverso analisi esplorative e inserite nel database. Il dataset risultante, comprendente più di 400.000 sequenze proteiche annotate, è stato memorizzato in un database MongoDB. EntomoDB rappresenta una risorsa strutturata e pubblicamente accessibile, progettata per facilitare futuri studi sul potenziale enzimatico delle comunità microbiche coinvolte nella biodegradazione delle plastiche.
EntomoDB: development of a bioinformatics platform for the analysis and management of microbial sequences involved in the plastic degradation
CURRO', DAVIDE
2024/2025
Abstract
Plastic pollution is one of the most pressing environmental challenges of our time, and recent studies suggest that insect larvae may host microbial communities with the potential to degrade synthetic polymers. To advance research in this area, a general-purpose bioinformatics framework named EntomoDB was developed to support the exploration, analysis, and sharing of microbial genomic data related to biodegradation. The platform combines a user-friendly web interface with a backend based on MongoDB, integrates predictive tools such as PlasFlow, and provides a ready-to-use pipeline for the analysis of user-submitted sequences. As a case study, the framework was applied to genomic data obtained from larvae reared under three experimental conditions: minimal agar substrate (AG), polyethylene (PE), and polystyrene (PS). DNA sequences were translated into proteins, curated through exploratory analyses, and inserted into the database. The resulting curated dataset, comprising more than 400,000 annotated protein sequences, was stored in a MongoDB database. EntomoDB offers a structured and publicly accessible resource designed to facilitate future studies on the enzymatic potential of microbial communities involved in plastic biodegradation.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/243277