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. 2024 Jul 9;10(14):e34336.
doi: 10.1016/j.heliyon.2024.e34336. eCollection 2024 Jul 30.

Exploring the diversity and functional profile of microbial communities of Brazilian soils with high salinity and oil contamination

Danielly C O Mariano  1   2 , Graciela Maria Dias  3 , Michele Rocha Castro  1   4 , Diogo Antonio Tschoeke  5   6 , Fernando J S de Oliveira  7 , Eliana Flavia C Sérvulo  2 , Bianca Cruz Neves  1
Affiliations

Exploring the diversity and functional profile of microbial communities of Brazilian soils with high salinity and oil contamination

Danielly C O Mariano et al. Heliyon. .

Abstract

Environmental pollution associated with the petroleum industry is a major problem worldwide. Microbial degradation is extremely important whether in the extractive process or in bioremediation of contaminants. Assessing the local microbiota and its potential for degradation is crucial for implementing effective bioremediation strategies. Herein, contaminated soil samples of onshore oil fields from a semiarid region in the Northeast of Brazil were investigated using metagenomics and metataxonomics. These soils exhibited hydrocarbon contamination and high salinity indices, while a control sample was collected from an uncontaminated area. The shotgun analysis revealed the predominance of Actinomycetota and Pseudomonadota, while 16S rRNA gene amplicon analysis of the samples showed Actinomycetota, Bacillota, and Pseudomonadota as the most abundant. The Archaea domain phylotypes were assigned to Thermoproteota and Methanobacteriota. Functional analysis and metabolic profile of the soil microbiomes exhibited a broader metabolic repertoire in the uncontaminated soil, while degradation pathways and surfactant biosynthesis presented higher values in the contaminated soils, where degradation pathways of xenobiotic and aromatic compounds were also present. Biosurfactant synthetic pathways were abundant, with predominance of lipopeptides. The present work uncovers several microbial drivers of oil degradation and mechanisms of adaptation to high salinity, which are pivotal traits for sustainable soil recovery strategies.

Keywords: 16S rRNA metataxonomics; Biosurfactants; Metabolic profile; Metagenomics; Soil microbiome; oil degradation.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Relative abundance of bacteria in soil samples analyzed by the shotgun metagenomics. The figure shows the most abundant bacteria at phylum level (A) and genus level (B). In (A), it's possible to observe a significant relative abundance of Actinomycetota and Pseudomonadota in all soil samples. In (B), the most abundant genera are Bradyrhizobium (8.43 %) in ALW, Haladaptus (6.82 %) in ALC, and Pseudomonas (37.97 %) in RNC. Uncontaminated soil sample from Alagoas (ALW), Contaminated soil sample from Alagoas (ALC) and Contaminated soil sample from Rio Grande do Norte (RNC).
Fig. 2
Fig. 2
Relative abundance of bacteria in soil samples analyzed by 16S rRNA amplicon sequencing. The figure shows the most abundant bacteria at phylum level (A) and genus level (B), based on region V3–V4. The most abundant phyla, Actinomycetota, Bacillota, and Pseudomonadota, are dominant across all samples (A). At the genus level (B), each sample exhibits distinct abundance: Stenotrophomonas (11.63 %) in ALW, Bacillus (20.01 %) in ALC, and Prauserella (20.45 %) in RNC. Uncontaminated soil sample from Alagoas (ALW), Contaminated soil sample from Alagoas (ALC) and Contaminated soil sample from Rio Grande do Norte (RNC).
Fig. 3
Fig. 3
Relative abundance of Archaea in soil samples analyzed by the 16S rRNA amplicon sequencing. The figure depicts the distribution of Archaea within phyla (A) and families, based on the sequencing of V4Arc region. In this representation, we observe the relative abundance of phyla in different soil types (A), Thermoproteota and Methanobacteriota are prominent, highlighting an inversion between ALW and ALC. Analyzing the families of Archaea (B), Nitrososphaeraceae and Haloferacaceae are the most representative. Uncontaminated soil sample from Alagoas (ALW), Contaminated soil sample from Alagoas (ALC) and Contaminated soil sample from Rio Grande do Norte (RNC).
Fig. 4
Fig. 4
Distribution of the most abundant functional categories among the three soil metagenomes. The colored bars indicate the relative abundance of functional orthologs in the non-contaminated soil (ALW, green), the contaminated soil from production field with chronic contamination by produced water (ALC, blue), and contaminated soil with chronic contamination by oil (RNC, pink). Uncontaminated soil sample from Alagoas (ALW), Contaminated soil sample from Alagoas (ALC) and Contaminated soil sample from Rio Grande do Norte (RNC). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)
Fig. 5
Fig. 5
Metagenomic profile of biodegradation of hydrocarbons and biosurfactant biosynthesis. Additional functional analysis with BiosurfDB pipeline was used to assess pathways specifically related to petroleum hydrocarbon metabolism. The figure displays the abundance fractions of totally annotated genes in each soil sample. The corresponding metabolic pathways are: (A) Degradation Pathway and (B) Biosurfactant Type. Uncontaminated soil sample from Alagoas (ALW), Contaminated soil sample from Alagoas (ALC) and Contaminated soil sample from Rio Grande do Norte (RNC).
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