Insights into the Anaerobic Biodegradation Pathway of n-Alkanes in Oil Reservoirs by Detection of Signature Metabolites

Abstract

Anaerobic degradation of alkanes in hydrocarbon-rich environments has been documented and different degradation strategies proposed, of which the most encountered one is fumarate addition mechanism, generating alkylsuccinates as specific biomarkers. However, little is known about the mechanisms of anaerobic degradation of alkanes in oil reservoirs, due to low concentrations of signature metabolites and lack of mass spectral characteristics to allow identification. In this work, we used a multidisciplinary approach combining metabolite profiling and selective gene assays to establish the biodegradation mechanism of alkanes in oil reservoirs. A total of twelve production fluids from three different oil reservoirs were collected and treated with alkali; organic acids were extracted, derivatized with ethanol to form ethyl esters and determined using GC-MS analysis. Collectively, signature metabolite alkylsuccinates of parent compounds from C1 to C8 together with their (putative) downstream metabolites were detected from these samples. Additionally, metabolites indicative of the anaerobic degradation of mono- and poly-aromatic hydrocarbons (2-benzylsuccinate, naphthoate, 5,6,7,8-tetrahydro-naphthoate) were also observed. The detection of alkylsuccinates and genes encoding for alkylsuccinate synthase shows that anaerobic degradation of alkanes via fumarate addition occurs in oil reservoirs. This work provides strong evidence on the in situ anaerobic biodegradation mechanisms of hydrocarbons by fumarate addition.

n-Alkane and long-chain alcohol recovery in moose (Alces alces), a browsing herbivore

“…Under anaerobic conditions, there is theoretically minimal biological degradation of nalkanes. However, Bian et al (2015) found that fumarate can act as an electron acceptor for the D r a f t efficient splitting of the C-C bond and subsequent conversion to alkylsuccinates and ultimately to LCOHs or other products. Grossi et al (2008) also found that n-alkanes seem to be degraded in conjunction with the production of fumarate in the rumen.…”

Carbon and hydrogen isotopic compositions of n -alkanes as a tool in petroleum exploration

“…Subsurface biodegradation leads to a well-characterized sequence of compound class losses as microbial groups with anaerobic hydrocarbon-degrading enzymes (Head et al 2003;Aitken et al 2004;Bian et al 2015) metabolize hydrocarbons, leading to generation of acidic compounds and loss of hydrocarbons in a characteristic sequence (n-alkanes > monocyclic alkanes > alkyl benzenes > isoprenoid alkanes > alkyl naphthalenes > bicyclic alkanes > steranes > hopanes) (Peters et al 2005). Biodegradation preferentially removes 12 C and 1 H, leaving 13 C-and 2 H-enriched organic compounds (Stahl 1980;Clayton 1991;Odden et al 2002;Jones et al 2008).…”

Identifying the core bacterial microbiome of hydrocarbon degradation and a shift of dominant methanogenesis pathways in the oil and aqueous phases of petroleum reservoirs of different temperatures from China

“…USEARCH software was used to check chimeras of methanogenic 16S rRNA gene sequences using a QIIME-compatible SILVA 119 release SSURef database ("rdp_gold fasta") file as a reference. Then, for mcrA gene sequences, a de novo operational taxonomic unit (OTU) picking method was applied by QIIME at a cutoff value of 0.05 (Caporaso et al, 2010). Representative OTU sequences were aligned and inserted into the mcrA gene ARB project database through the maximum parsimony method without changing the initial tree topology (Angel et al, 2012;Ludwig et al, 2004).…”

“…After merging paired-end reads from raw sequencing data with FLASH-1.2.8, the fastx toolkit was applied to split merged reads from one run into individual samples according to the primer barcodes (Magoc and Salzberg, 2011). Then, all sequences were split into each library with the name of each sample attached according to the barcode map using the QI-IME command "split_libraries" (Caporaso et al, 2010). The criterion for filtering out underqualified sequences was "-s 15 -k -a 6 -r -l 150 -b 12 -M 5 -e 0".…”

“…Chimera checking was conducted by USEARCH software using the QIIMEcompatible SILVA 119 release SSURef database ("rdp_gold" fasta) file as the reference (Edgar, 2010). Clustering; picking OTU; taxonomy assignment, aligning, filtering alignments, and phylogenetic tree construction; taxonomic composition summarizing; and alpha and beta diversity analyses were conducted step-by-step by the QIIME pipeline with QIIME-compatible SILVA 119 SSURef database as the reference (Caporaso et al, 2010). In clustering, the "pick_open_reference_otus.py" command was used to conduct OTU dividing, and the BLAST method was used to assign taxonomy to input sequences.…”