PT Unknown
AU Zulfiqar, M
TI Reproducible and automated analysis of metabolomics data to assess the biosynthetic capacities of organisms in microbial communities
PY 2024
DI 10.22032/dbt.61538
WP https://www.db-thueringen.de/receive/dbt_mods_00061538
LA en
DE Mikroalgen; Computational chemistry; Prymnesium parvum
AB The thesis entitled "Reproducible and automated analysis of metabolomics data to assess the biosynthetic capacities of organisms in microbial communities", investigates the role of marine microbial communities in maintaining ecological balance through the exchange of metabolites. High-throughput omics techniques have transformed microbial research, where metabolomics is crucial to elucidate and analyzes these metabolites that are involved in the metabolic exchange and hence, affect our ecosystem. We developed Metabolome Annotation Workflow (MAW), a workflow for untargeted tandem mass spectrometry data. The workflow takes the tandem mass spectrometry data as input and annotates chemical structures to the metabolites detected in the input spectra. FAIR (Findable, Accessible, Interoperable, Reusable) principles have been implemented to the workflow to enable reproducibility and portability of the workflow across different workflow platforms and operating systems. This workflow was then applied to a marine microalgae, the diatom Skeletonema marinoi to expand the chemical space produced by this diatom. Furthermore, we developed another module of MAW, that detected statistically significant metabolites among co-culture condition of two microorgansism (S. marinoi and a marine haptophyte Prymnesium parvum), to explores chemical interactions between the two organisms to uncover insights into microbial communication.
PI Jena
ER