Abstract
Computational and statistical analysis of shotgun metagenomes can predict gene abundance and is helpful for elucidating the functional and taxonomic compositions of environmental samples. Gene products are compared against physicochemical conditions or perturbations to shed light on the functions performed by the microbial community of an environmental sample; however, this information is not always available. The present study proposes a method for inferring the metabolic potential of metagenome samples by constructing a reference based on determining the probability distribution of the counts of each enzyme annotated. To test the methodology, we used marine water samples distributed worldwide as references. Then, the references were utilized to compare the annotated enzymes of two different water samples extracted from the Gulf of Mexico (GoM) to distinguish those enzymes with atypical behavior. The enzymes whose annotation counts presented frequencies significantly different from those of the reference were used to perform metabolic reconstruction, which naturally identified pathways. We found that several of the enzymes were involved in the biodegradation of petroleum, which is consistent with the impact of human hydrocarbon extraction activity and its ubiquitous presence in the GoM. The examination of other reconstructed pathways revealed significant enzymes indicating the presence of microbial communities characterizing each ocean depth and ocean cycle, providing a fingerprint of each sampled site.
Highlights
The Gulf of Mexico (GoM) is an area with important oil industry activity that is constantly affected by the extraction and transportation of hydrocarbons, sometimes causing largescale spills, which have repeatedly disturbed the area (Jernelv, 2010; Michel et al, 2013; Soto et al, 2014)
Our approach aims to highlight enzymes, in a sample under study, with values of the rates in Eq 1 that are significantly different from those of the reference group of metagenomes under similar environmental conditions. We take this set of enzymes with atypical rates as a seed with which to reconstruct a metabolic network, which gives a hint of the metabolic potential of the sample
Our analysis showed that alkaline phosphatase is a bacterial membrane protein encoded by the phoA gene (Inouye et al, 1981) that has been hypothesized to be directly related to phosphorus deficiency within bacterial cells (Wanner, 1996; Benitez-Nelson, 2000), presented an equivalent z-score (EZS) = 1.52342 in A04_AAIW and an EZS = 2.01831 in D18_MAX, suggesting that the microbial community in the MAX zone must have the potential to contend with inorganic phosphate (Pi) stress
Summary
The Gulf of Mexico (GoM) is an area with important oil industry activity that is constantly affected by the extraction and transportation of hydrocarbons, sometimes causing largescale spills, which have repeatedly disturbed the area (Jernelv, 2010; Michel et al, 2013; Soto et al, 2014). The introduction of petroleum in fragile marine environments can result in severe ecological perturbations. Crude oil is composed of thousands of components, which can be mainly separated into saturates, aromatics, resins, and asphaltenes. The aromatic compounds are subject to physicochemical modifications, providing the environment with smaller-molecular-weight products that are readily biodegraded in marine environments. Other compounds such as resins and asphaltenes are resistant to biodegradation (Harayama et al, 1999). Petroleum biodegradation is carried out by microorganisms (Head et al, 2006), and the isolation of those microorganisms capable of degrading petroleum components is an area of interest. Given the impossibility of identifying and isolating many of these organisms, methodologies based on the sequencing of DNA recovered from environmental samples are a common approach
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