This internship report presents the analysis of hydrocarbonoclastic microbial communities subjected to various oxygenation conditions, as part of research conducted at IPREM. The main objective is to develop and apply biostatistical and bioinformatics tools to analyze and characterize these microbial communities, focusing on sulfate-reducing bacteria (SRB) and denitrifying bacteria (DB). Three distinct microbial communities were incubated in bioreactors under conditions of permanent anoxic, permanent oxic, and anoxic/oxic oscillations. Sequencing data, processed with Qiime2 and statistically analyzed with Python, show that oxygenation conditions significantly influence community structure. DBs adapt better to oscillating conditions, while the abundance of SRBs decreases after oxygenation. The expression of dsrB genes and the relative abundance of ASVs indicate that certain bacteria, such as Sulfurimonas and Marinobacter, play crucial roles in these environments. These results provide important insights into the dynamics of microbial communities and their role in the bioremediation of contaminated marine sediments.
Microbial communities, biostatistics, bioinformatics, hydrocarbons
Comparison of metabolically active bacterial community structures (A) for microbial communities five days after the start of incubation and (B) during bioreactor incubations.
Analysis of microbial community network modules before the first oxygenation and their correlation with alkane and PAH Degradation
