Modulation of microbial consortia enriched from different polluted environments during petroleum biodegradation.
Rahma OmraniGiulia SpiniEdoardo PuglisiDalila SaidanePublished in: Biodegradation (2018)
Environmental microbial communities are key players in the bioremediation of hydrocarbon pollutants. Here we assessed changes in bacterial abundance and diversity during the degradation of Tunisian Zarzatine oil by four indigenous bacterial consortia enriched from a petroleum station soil, a refinery reservoir soil, a harbor sediment and seawater. The four consortia were found to efficiently degrade up to 92.0% of total petroleum hydrocarbons after 2 months of incubation. Illumina 16S rRNA gene sequencing revealed that the consortia enriched from soil and sediments were dominated by species belonging to Pseudomonas and Acinetobacter genera, while in the seawater-derived consortia Dietzia, Fusobacterium and Mycoplana emerged as dominant genera. We identified a number of species whose relative abundances bloomed from small to high percentages: Dietzia daqingensis in the seawater microcosms, and three OTUs classified as Acinetobacter venetianus in all two soils and sediment derived microcosms. Functional analyses on degrading genes were conducted by comparing PCR results of the degrading genes alkB, ndoB, cat23, xylA and nidA1 with inferences obtained by PICRUSt analysis of 16S amplicon data: the two data sets were partly in agreement and suggest a relationship between the catabolic genes detected and the rate of biodegradation obtained. The work provides detailed insights about the modulation of bacterial communities involved in petroleum biodegradation and can provide useful information for in situ bioremediation of oil-related pollution.
Keyphrases
- heavy metals
- genome wide
- genome wide identification
- risk assessment
- health risk assessment
- plant growth
- bioinformatics analysis
- genome wide analysis
- electronic health record
- molecularly imprinted
- single cell
- human health
- big data
- dna methylation
- acinetobacter baumannii
- fatty acid
- microbial community
- escherichia coli
- copy number
- health information
- polycyclic aromatic hydrocarbons
- organic matter
- high resolution
- staphylococcus aureus
- deep learning
- biofilm formation
- artificial intelligence
- drinking water
- water quality
- antibiotic resistance genes
- climate change