Conversion of Uric Acid into Ammonium in Oil-Degrading Marine Microbial Communities: a Possible Role of Halomonads
Uric acid is a promising hydrophobic nitrogen source for biostimulation of microbial activities in oil-impacted marine environments. This study investigated metabolic processes and microbial community changes in a series of microcosms using sediment from the Mediterranean and the Red Sea amended with ammonium and uric acid. Respiration, emulsification, ammonium and protein concentration measurements suggested a rapid production of ammonium from uric acid accompanied by the development of microbial communities containing hydrocarbonoclastic bacteria after 3 weeks of incubation. About 80 % of uric acid was converted to ammonium within the first few days of the experiment. Microbial population dynamics were investigated by Ribosomal Intergenic Spacer Analysis and Illumina sequencing as well as by culture-based techniques. Resulting data indicated that strains related to Halomonas spp. converted uric acid into ammonium, which stimulated growth of microbial consortia dominated by Alcanivorax spp. and Pseudomonas spp. Several strains of Halomonas spp. were isolated on uric acid as the sole carbon source showed location specificity. These results point towards a possible role of halomonads in the conversion of uric acid to ammonium utilized by hydrocarbonoclastic bacteria.
KeywordsCrude oil degradation Bioremediation Alcanivorax
The authors would like to thank Anna Foster, Sarah Chesworth and Gordon Turner for their help with photometric and respiration measurements. With exception of XH and JC, all authors were supported by the FP7 Project ULIXES (FP7-KBBE-2010-266473). This work was further funded by grant BIO2011-25012 from the Spanish Ministry of the Economy and Competitiveness. FM was supported by Università degli Studi di Milano, European Social Fund (FSE) and Regione Lombardia (contract “Dote Ricerca”). DD acknowledges support of KAUST, King Abdullah University of Science and Technology. PG acknowledges the support of the European Commission through the project Kill-Spill (FP7, Contract Nr 312139). CG would like to thank Mr. Kyungsun Lee of Macrogen Inc. for his courtesy regarding sequencing services, J. Cans, B. Strid and C. Hudson for continued advice and inspiration as well as Delphine Lallias for her help with multivariate statistics and John Flannery for proofreading this manuscript.
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