Physicochemical analysis
The soil samples obtained for characterization of the spill site showed the concentrations of total petroleum hydrocarbons (TPH) and polycyclic aromatic hydrocarbons (PAHs) at different depths of the soil analyzed. The surface (0.0–0.5) sample had an extractable TPH value of 6231 mg/kg. The subsurface samples from 1 m, 1.5 m and 2.0 m depths had extractable TPH concentration of 4836 mg/kg, 9112 mg/kg and 7273 mg/kg respectively. Values of physicochemical characteristics determined for pH, arsenic, barium, cadmium, cobalt, copper, lead, mercury, nickel, total chromium and zinc are shown in Table 1 together with the Regulator’s (DPR’s) intervention values.
The concentration of polycyclic aromatic hydrocarbons was low and only detected in the surface sample and the 1 m depth samples. The surface sample had a PAH concentration of 0.13 mg/kg while the subsurface sample had PAH concentration of 1.36 mg/kg. The unpolluted soil TPH was 479.7 mg/kg while TPH concentrations for days 0, 09, 18, 36 and 56 were 8635.68 mg/kg, 6125.7 mg/kg, 4171.9 mg/kg, 2435.2 mg/kg and 677.2 mg/kg respectively.
Table 1
Physicochemical analysis of the oil pollutes soil prior to remediation
Parameter | 0-0.5 m | 1.0 m | 1.5 m | 2.0 m | DPR Intervention Value |
ETPH (mg/kg) | 6231 | 4836 | 9112 | 7273 | 5000 |
pH | 6.92 | - | 6.56 | - | - |
Arsenic (mg/kg) | 11.8 | - | 10.8 | - | 55 |
Barium (mg/kg) | 204 | - | 129 | - | 625 |
Cadmium (mg/kg) | < 2.00 | - | < 2.00 | - | 12 |
Cobalt (mg/kg) | 16.4 | - | 28.8 | - | 240 |
Copper (mg/kg) | 20.1 | - | 16.3 | - | 190 |
Lead (mg/kg) | 22.4 | - | 14.8 | - | 530 |
Mercury (mg/kg) | < 1.0 | - | < 1.0 | - | 10 |
Nickel (mg/kg) | 35.5 | - | 36.2 | - | 210 |
Total Chromium (mg/kg) | 172 | - | 61.3 | - | 380 |
Zinc (mg/kg) | 60.4 | - | 89.1 | - | 720 |
* - (Not measured); DPR - Department of Petroleum Resources, Nigeria |
Diversity Analysis Following Oil Spill And During Remediation
Analysis of the effect of the oil spill on microbial diversity revealed the presence of hydrocarbons reduced microbial diversity. Effect of hydrocarbons on bacterial diversity was inferred using Chao1 diversity index. Analysis based on bacterial richness (chao1) revealed the oil-polluted soil prior to any form of remediation had the least bacterial abundance. However, based on Shannon’s diversity index, it was found that the least diverse sample was the sample obtained on day 56. Diversity generally improved from day-0 to day-36 of remediation and only reduced on day 56 when hydrocarbon concentration dropped from 6231 to 677.2 mg/kg (Fig. 1A). Also, the hydrocarbon concentration in the soil significantly reduced bacterial diversity compared to the pristine soil which represents the soil true diversity prior to the oil spill (Fig. 1B). Following the commencement of intervention by Landfarming, the diversity continued changing and increasing as the concentration of hydrocarbons in the soil reduced. Principal coordinates analysis (PCoA) revealed the samples clustered separately within the ordination space, and suggest how the bacterial community changes as different hydrocarbon fractions were degraded (Fig. 2).
* [PERMANOVA] F-value: 1.0506; R-squared: 0.34438; p-value < 0.3
Microbial Dynamics And Abundance During Remediation
A total 1,211 bacterial species were detected for all the samples. The bacterial metagenome for all the samples was dominated by Proteobacteria for the oil polluted and Acidobacteria for the unpolluted soils (Fig. 3) with an average abundance of 64%. It was observed that the abundance of proteobacteria increased from the start of remediation (68% on day-0) to 70% on day-9 before declining to 55% on day-18 and 30% on day-36. Pre-remediation, the dominant phyla were Proteobacteria (46%) and Actinobacteria (43%) while in the unpolluted soil Acidobacteria and Actinobacteria made up 40% and 18% of the soil microbiome respectively. At the class level, the dominant bacterial classes with at least 1% abundance in at least 1 sample are presented in Fig. 3B. Alphaproteobacteria pre-remediation was 26% but increased to 28% and 37% on days 0–9 before significantly declining to 16% and 9% on days 18 and 36 respectively. This finding was similar for Betaproteobacteria but different for Gammaproteobacteria which recorded significant improvement between days 18–36. Baseline Betaproteobacteria abundance was 16% but reduced to 8% on day 36 while Gammaproteobacterial abundance improved from 1% on commencement of remediation to 22% on day-18 of the site remediation. As the dominance of Proteobacteria increased during the early stages of remediation, there was also a simultaneous decrease in the abundance of Actinobacteria throughout the period of remediation. Actinobacteria reduced from 43% prior to intervention by Landfarming to 4% on day-56.
Investigation of the polluted soil microbiome at the family level revealed important differences between the oil-polluted and unpolluted soils. For instance, at all sampling days during remediation (apart from Day 18) Burkholderiaceae and Mycobacteriaceae were the dominant bacterial family while the unpolluted soil had Solibacteriaceae (19%) and Chthoniobacteraceae (17%) as the most abundant bacterial families (Fig. 4A). Unlike on day-0 where Burkholderiaceae (40%) and Mycobacteriaceae (17%) were the dominant bacterial families, on day 56, the most abundant bacterial families were Burkholderiaceae (31%) and Bacillaceae (27%). The core bacterial families in the site pre-remediation and during remediation with at least 20% prevalence and 5% relative abundance were detected to be Burkholderiaceae, Bacillaceae, Mycobacteriaceae, Bradyrhizobiaceae, Chthoniobacteraceae, Solibacteriaceae, Acidobacteriaceae, Caulobacteraceae and Methylobacteriaceae.
At the genus level, it was observed that the early stages (day-0 and day-9) of remediation were particularly dominated by Burkholderia unlike in the baseline oil-polluted soil where mycobacterium dominated. Major differences were however observed between days 18 and 36 (Fig. 4B). The core bacterial genera detected in the samples obtained during this period of remediation included Mycobacterium, Burkholderia, Bacillus, Sphingomonas, Candidatus Xiphinematobacter, Pseudomonas and Candidatus Solibacter. Comparison of the crude oil polluted soils during remediation to that of the unpolluted soil revealed Candidatus Xiphinematobacter was a common feature that dominated the community structure in the unpolluted soil and in the later stages of remediation (days 36–56).
Predictive Microbial Community Functional Response During Remediation
To determine the functional responses of the bacterial community to the environmental stress caused by the presence of the crude oil spill, the GREENGENES classified bacterial species were subjected to further analysis using PICRUST. 6,909 KEGG orthologs were detected for the entire samples. The mean abundance of pathways detected was 427,917.46. The oil polluted samples were all compared to the pristine soil for differentially represented KEGG pathways. Thirty-five pathways were found to be differentially represented between the pristine soil the polluted soil prior to Landfarming. The pathways were mainly pathways for hydrocarbons degradation and they include naphthalene degradation, polycyclic aromatic hydrocarbon degradation, benzoate and aminobenzoate degradation pathways among others (Fig. 5A – 5C). As remediation commenced mostly the same predicted pathways remained significantly differentially represented from day zero to day 18 after which a decline in the degradative pathways was observed. On days 36 and 56 only pathway for transporters and pathways for phosphonate and phosphinate metabolism were differentially represented.
* PSBBB = Polluted soil prior to landfarming
* PSB0 = Day 0
* UUS = Unpolluted soil
* PSB9 = Day 09
* PSB18 = Day 18
* PSD56 = Day 56
* PSD36 = Day 36
Also, from the 16S rRNA metagenomes, proteins numbering 5649 were predicted and classified as KEGG orthologs (KOs) across all the samples. Several genes associated with the degradation of polycyclic aromatic hydrocarbons (PAHs), naphthalene, benzoate, toluene, chloroalkane/chloroalkene and chlorohexane/chlorobenzene degradation were found to be differentially abundant across all the samples obtained before remediation, during remediation and in the unpolluted soil as presented in Fig. 6.
It was observed that the genes responsible for hydrocarbon degradation were present in both the oil-polluted and unpolluted soils. However, for all the hydrocarbon degradation pathways analysed, genes for hydrocarbon degradation was more enriched in the oil-polluted soils compared to the unpolluted soil. Also, in most cases, a high enrichment of the genes was observed in the baseline oil-polluted soil and progressively reduced as remediation progressed. For example, K01692 associated with the degradation of benzoate was 33% in the unpolluted soil, 44% in the baseline sample, 40% on day-0, 40% on day-9, 39% on day-18, 33% on day-36, and 34% on day-56 (Fig. 6C). Also, K00121 associated with Naphthalene degradation was observed to be 21% in the unpolluted soil, 46% in the oil-polluted soil obtained prior to remediation, 39% on day-0, 37% on day-9, 45% on day-18, 28% on day-36, and 27% on day-56 as presented in Fig. 6B). Majority of the classified KOs were observed to have followed this trend in most of the investigated proteins responsible for hydrocarbon degradation.
Bacterial contribution to the overall functional metagenome revealed that, in the oil-polluted soil samples, Mycobacterium (78%), Bradyrhizobium (8%), Phenylobacterium (4.2%) and Burkholderia (3%) contributed the most to the KEGG ortholog K01692 (enoyl-CoA hydratase); associated with the degradation of benzoate, aminobenzoate and caprolactam. The same group of bacterial genera were also the main contributors to KEGG ortholog K00121 (S-(hydroxymethyl) glutathione dehydrogenase/alcohol dehydrogenase) associated with chloroalkane and naphthalene. Bradyrhizobium, Burkholderia and Methylobactrium were the key contributors (> 1%) in the oil-polluted soil sample to K00480 (salicylate hydroxylase; associated with both dioxin and naphthalene degradation) and K01856 (muconate cycloisomerase; associated with Chlorocyclohexane, florobenzoate, benzoate and toluene degradation).