Abstract

The microbial ecology of oligotrophic deep ocean sediments is understudied relative to their shallow counterparts, and this lack of understanding hampers our ability to predict responses to current and future perturbations. The Gulf of Mexico has experienced two of the largest accidental marine oil spills, i.e., the 1979 Ixtoc-1 blowout in the Southern Gulf of Mexico (GoM) and the 2010 Deepwater Horizon (DWH) discharge in the Northern GoM. Microbial communities were characterized via next generation sequencing of SSU rRNA gene sequences for 29 sites across multiple years in the Gulf of Mexico, represented by >700 samples. The distribution of seafloor microbial communities was elucidated and found to be surprisingly consistent across the entire region in terms of the OTUs detected and their relative abundances. The composition of the seafloor microbiome was well approximated by the overlying water depth and depth within the sediment column, which together explained 38% of the observed variation. In contrast, geographic distance had a limited role and explained only 6%. Biogeographical distributions were used to generate a depth-stratified machine-learning based predictive model for over 4000 dominant OTUs that relies on easy-to-obtain geospatial variables. Microbial community structure is linked to oxygen penetration depth and sediment geochemical regime, which are likely controlled through carbon delivery. Our results further demonstrate that sediments impacted by the DWH spill had returned to near baseline conditions after two years. The distributions of key microbial populations can now be calculated and constrained across the region while deviations from these predictions may be evaluated to pinpoint impacted sites, and more importantly, in future response efforts or long-term stability studies.

Footnotes

* Edited for clarity.

Details

Title
Defining the seafloor microbiome of the Gulf of Mexico and its response to oil perturbation
Author
Overholt, Will A; Schwing, Patrick; Hastings, David; Hollander, David J; Kostka, Joel E
University/institution
Cold Spring Harbor Laboratory Press
Section
New Results
Publication year
2019
Publication date
Feb 1, 2019
Publisher
Cold Spring Harbor Laboratory Press
ISSN
2692-8205
Source type
Working Paper
Language of publication
English
ProQuest document ID
2068571491
Copyright
© 2019. This article is published under http://creativecommons.org/licenses/by-nd/4.0/ (“the License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.