On April 20, 2010 the Deepwater Horizon drilling rig exploded in the Gulf of Mexico, leading to an oil leak that continued for 87 days and released approximately 4.9 billion barrels of oil and other hydrocarbons into the marine environment. The impact of this oil spill (the world's largest oil spill) was terrible, but would have been even worse if it were not for the impact of hydrocarbon-degrading bacteria that acted to break down much of the released oil. These microbes are a naturally occurring component of the planktonic community in the Gulf of Mexico where they metabolize methane, oil, and other compounds that can emerge from underwater seeps. The goal of the Consortium for Simulation of Oil-Microbial Interactions in the Ocean (CSOMIO) is to predict the abundance and activity of these organisms and simulate the potential impacts of oil spills in other regions and seasons in the Gulf of Mexico.

 

Modeling the incredible diversity of microbes in the ocean is a challenging task, because there are thousands of species in every drop of seawater - and each of these taxa potentially has unique biogeochemical capabilities. To study this complexity, we (at FSU and Horn Point Laboratory) will use a novel emergent properties modeling approach that directly simulates the abundance and transcription rates of genes in the environment and is hence uniquely suited to validation with the rapidly growing number of "-omics" field studies in the ocean (specifically metagenomics and metatranscriptomics). Our model defines gene clusters that are responsible for metabolic pathways or biochemical functions (e.g. photosynthesis, nitrogen fixation, methanotrophy) and then randomly assigns these genes to a community of dozens to hundreds of individual taxa. The genes that an individual taxon receives determines its growth rate, nutritional mode(s), and substrate utilization. The community is then initialized in a biogeochemical-physical model of the Atlantic Ocean and Gulf of Mexico. Within the model, the microbial community mediates all biochemical transformations, thus the biogeochemical gradients and gene abundance and transcription are truly emergent properties of the model that can be compared to field measurements.

 

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We will use the GENOME model in collaboration with physical oil transport and aggregation models developed by our partners in CSOMIO to answer several fundamental questions about the oil spill:

 

What role do diverse microbial communities that are adapted to utilize substrates at natural oil and methane seeps play in degrading hydrocarbons released during the DwH and other oil spills?

 

Does colonization of oil-absorbing sinking particles facilitate connectivity between water column hydrocarbon-degrading microbial communities and similar communities in the benthic realm?

 

How is the rate of oil deposition via flocculation dependent on the local present of a tubid river plume in the spill region?

 

Would the impact of the DwH oil spill have been worse if the spill had occurred in winter rather than spring?

 

For more on this project, please visit the CSOMIO social media websites:

 

https://www.facebook.com/CSOMIO/

 

https://twitter.com/C_SOMIO