Crude oil is a complex mixture of aromatic and aliphatic hydrocarbons of diverse molecular weight. In spite of its high hydrophobicity and toxicity, crude oil is a rich source of carbon for microorganisms. It has been proposed that microbial metabolism contributes to petroleum physicochemical characteristics, as highly specialized microorganisms are adapted to its extreme conditions. Deciphering these unique microbiomes will allow more in-depth characterization of crude oil and better understand its chemistry. The general aim of this study is to characterize the unique microbial communities of crude oil through a comparative metagenomics approach. I performed a survey of worldwide crude oil metagenomes in literature and databases. I identified 48 metagenomics datasets from five countries. The Comparative analysis of these metagenomes allowed us to identify how Methanogens are predominant in the North-American crude oil, being Methanoculleus and Methanosaeta the dominant genera in Canada and Methanothermococcus the predominant genus in the United States oil fields. In the case of Nigeria crude oil, Marinobacterium and Parvivaculum were the two dominant genera. In the case of Thailand, the dominant genus Thermus reflected the high-temperature environment of that oil field. Finally, metagenomes from China were the most diverse, reflecting the heterogeneity of the oil fields from that country.
I generated metagenomics data from 27 Saudi Arabian crude oil samples originated in 6 different oil fields. As no crude oil metagenome has been reported yet for the Arabian Peninsula, the information provided in this dissertation is contributing towards a complete worldwide characterization of crude oils. Two genera, Peanibacilus and Thermospira, are proposed as the taxonomic markers for the set of Saudi crude oil analyzed.
In this thesis I elucidated the structure of microbial communities in crude oils globally, suggesting that it may reflect the geological history of crude oils. This study sheds light on the importance of microorganisms for understanding petroleum geobiology. These findings suggest that it is possible to identify the distinctive microbiota associated with specific types of crude oil according to its location. The results presented here set the basis for developing novel methodologies for crude oil identification based on a microbial fingerprinting approach.
|Date of Award||Oct 2021|
|Original language||English (US)|
- Biological, Environmental Sciences and Engineering
|Supervisor||Takashi Gojobori (Supervisor)|
- CRUDE OIL
- Microbial Profiling