Microbial Biodegradation of Crude Oil
Microbial Biodegradation of Crude OilAlexis Walker, University of Alaska Fairbanks
Scope of Work:
With OSRI funding, I propose to perform in-depth metagenomic sequencing and compound-specific hydrocarbon analyses on samples preserved from my previous oiled sediment incubation study in order to address the following additional objectives:
- Identify oil degradation genes and pathways involved in the biodegradation of fresh and weathered oil in Arctic marine sediments via shotgun metagenomic sequencing
- Characterize shifts in microbial community structure, including species-level identifications, in Arctic marine sediments following exposure to fresh and weathered crude oil via shotgun metagenomic sequencing
- Assess the rate and extent of degradation of individual petroleum hydrocarbons over time in Arctic marine sediments
- Compare oil degradation rates between experiments conducted in Chukchi seawater and Chukchi surface sediments
Identifying oil degradation genes, pathways, and microbes
The identification of oil degradation genes and pathways will be performed via shotgun metagenomic sequencing of 100 samples collected from a completed incubation experiment with oiled marine sediment. As these samples have already undergone DNA extraction, they will be submitted directly to the UAF Genomics Core lab for library preparation. Once libraries for these samples are prepared, they will be sent to the Center for Advanced Technology at UCSF to be sequenced on a NovaSeq 6000. The NovaSeq 6000 provides much more sample coverage, approximately 1000x more gigabases, than the platforms available at UAF and will provide the coverage necessary to assemble partial genomes and get complete pathway information. Marine sediments have several orders of magnitude more microbes than an equivalent amount of seawater and thus require more sequencing coverage. Once sequencing is completed, the resulting interleaved metagenome fastq files will be run through a series of bioinformatics pipelines. Prior to all downstream analyses, any remaining adapters will be trimmed from the metagenome files via BBmap software (Bushnell & Brian 2014). In order to identify oil degradation genes and pathways, the metagenome nucleotides will be translated into amino acids using the BBmap program (Bushnell & Brian 2014). A hmm profile with target genes will be created via a bash script, the Functional Ontology Assignments for Metagenomes (FOAM) table, and the Hmmer program (Prestat et al. 2014; Eddy 2011). This profile will provide a reference to hmms associated with oil degradation genes to search. The hmm profile will then be input into the Hmmer program to search for oil degradation genes in the metagenomic data (Eddy 2011). The resulting table will be used to identify oil degradation genes, pathways, and to assess their distribution across all samples.
In order to investigate the identity of unknown bacterial taxa such as VHS-B4-70, the metagenome data will be assembled, binned, and resulting bins assigned taxonomy and annotated. The coassembly and individual sample assembly for all metagenomes will be implemented using the Spades program (Nurk et al. 2017). The individual sample assemblies will be mapped to the coassembly using the BBmap program (Bushnell & Brian 2014) in order to yield relative abundances metagenomes, and to produce indexed and sorted bam files for downstream metagenome binning. To obtain bins of similar contigs from metagenome assemblies, the MetaBAT program will be used (Kang et al. 2015). The output metagenome bins will then be individually uploaded onto the Kaiju (Menzel et al. 2016) webserver for taxonomic assignments. Once the taxonomy is assigned, the bins will be individually uploaded onto the PATRIC website for genome annotation (Wattam et al. 2017). These steps will provide high-resolution taxonomic information on previously uncultured oil-degrading microbes, as well potential functional roles of these microbes in Arctic marine sediments.
Quantifying petroleum biodegradation
Petroleum biodegradation (in oil incubations) will be assessed using gas chromatography and mass spectrometry (GC-MS) for polyaromatic hydrocarbons (PAHs) in the UAF DNA Core Lab, and gas chromatography with flame ionization detection (GC-FID) for total petroleum hydrocarbons (TPH) in PI Leigh’s lab. Methodologies have already been optimized for petroleum analyses and the instruments are routinely used and maintained for this purpose. Semi-automated data analyses will be conducted using existing macros we have developed within Chemstation software, which will yield TPH concentrations as well as compound-specific data for PAHs, including the 16 priority PAHs designated by the U. S. Environmental Protection Agency. Percent total petroleum losses will be determined for each time point, which includes both biotic and abiotic losses, and percent petroleum biodegradation will be calculated following subtraction of abiotic losses as determined based on sterile control incubations. Percent losses and percent biodegradation will be expressed relative to initial petroleum concentrations at time zero. Relationships between oil degradation genes and degradation rates of individual oil compounds will be evaluated using generalized linear models (GLMs) and generalized additive models (GAM) in R (R Core Team 2017).