Metagenomics-metabolomics analysis of microbial function and metabolism in petroleum-contaminated soil

A metagenome-derived artificial intelligence modeling framework advances the predictive diagnosis and interpretation of petroleum-polluted groundwater

Groundwater (GW) quality monitoring is vital for sustainable water resource management. The present study introduced a metagenome-derived machine learning (ML) model aimed at enhancing the predictive understanding and diagnostic interpretation of GW pollution associated with petroleum. In this framework, taxonomic and metabolic profiles derived from GW metagenomes were combined for use as the input dataset. By employing strategies that optimized data integration, model selection, and parameter tuning, we achieved a significant increase in diagnostic accuracy for petroleum-polluted GW. Explanatory artificial intelligence techniques identified petroleum degradation pathways and Rhodocyclaceae as strong predictors of a pollution diagnosis. Metagenomic analysis corroborated the presence of gene operons encoding aminobenzoate and xylene biodegradation within the de novo assembled genome of Rhodocyclaceae. Our genome-centric metagenomic analysis thus clarified the ecological interactions associated with microbiomes in breaking down petroleum contaminants, validating the ML-based diagnostic results. This metagenome-derived ML framework not only enhances the predictive diagnosis of petroleum pollution but also offers interpretable insights into the interaction between microbiomes and petroleum. The proposed ML framework demonstrates great promise for use as a science-based strategy for the on-site monitoring and remediation of GW pollution.

Spatial distribution characteristics and degradation mechanism of microorganisms in n-hexadecane contaminated vadose zone

The damage caused by petroleum hydrocarbon pollution to soil and groundwater environment is becoming increasingly significant. The vadose zone is the only way for petroleum hydrocarbon pollutants to leak from surface into groundwater. The spatial distribution characteristics of indigenous microorganisms in vadose zone, considering presence of capillary zones, have rarely been reported. To explore the spatial distribution characteristics of indigenous microorganisms in vadose zone contaminated by petroleum hydrocarbons, a one-dimensional column migration experiment was conducted using n-hexadecane as characteristic pollutant. Soil samples were collected periodically from different heights during experiment. Corresponding environmental factors were monitored online. The microbial community structure and spatial distribution characteristics of the cumulative relative abundance were systematically analyzed using 16S rRNA sequencing. In addition, the microbial degradation mechanism of n-hexadecane was analyzed using metabolomics. The results showed that presence of capillary zone had a strong retarding effect on n-hexadecane infiltration. Leaked pollutants were mainly concentrated in areas with strong capillary action. Infiltration and displacement of NAPL-phase pollutants were major driving force for change in moisture content (θ) and electric conductivity (EC) in vadose zone. The degradation by microorganisms results in a downward trend in potential of hydrogen (pH) and oxidation-reduction potential (ORP). Five petroleum hydrocarbon-degrading bacterial phyla and 11 degradable straight-chain alkane bacterial genera were detected. Microbial degradation was strong in the area near edge of capillary zone and locations of pollutant accumulation. Mainly Sphingomonas and Nocardioides bacteria were involved in microbial degradation of n-hexadecane. Single-end oxidation involved microbial degradation of n-hexadecane (C16H34). The oxygen consumed, hexadecanoic acid (C16H32O2) produced during this process, and release of hydrogen ions (H+) were the driving factors for reduction of ORP and pH. The vadose zone in this study considered presence of capillary zone, which was more in line with actual contaminated site conditions compared with previous studies. This study systematically elucidated vertical distribution characteristics of petroleum hydrocarbon pollutants and spatiotemporal variation characteristics of indigenous microorganisms in vadose zone considered presence of capillary zone. In addition, the n-hexadecane degradation mechanism was elucidated using metabolomics. This study provides theoretical support for development of natural attenuation remediation measures for petroleum-hydrocarbon-contaminated soil and groundwater.

Microbial functional heterogeneity induced in a petroleum-polluted soil profile

Microbial taxonomic diversity declines with increasing stress caused by petroleum pollution. However, few studies have tested whether functional diversities vary similarly to taxonomic diversity along the stress gradient. Here, we investigated soil microbial communities in a petrochemically polluted site in China. Total petroleum hydrocarbon (TPH) concentrations were higher in the middle (2-3 m) and deep soil layer (3-5 m) than in the surface soil layer (0-2 m). Accordingly, microbial taxonomic α-diversity was decreased by 44% (p < 0.001) in the middle and deep soil layers, compared to the surface soil layer. In contrast, functional α-diversity decreased by 3% (p < 0.001), showing a much better buffering capacity to environmental stress. Differences in microbial taxonomic and functional β-diversities were enlarged in the middle and deep soil layers, extending the Anna Karenina Principle (AKP) that a community adapts to stressful environments in its own way. Consistent with the stress gradient hypothesis, we revealed a higher degree of network connectivity among microbial species and genes in the middle and deep soil layers compared to the surface soil layer. Together, we demonstrate that microbial functionality is more tolerant to stress than taxonomy, both of which were amenable to AKP and the stress gradient hypothesis.

Molecular and metabolic characterization of petroleum hydrocarbons degrading Bacillus cereus

Hydrocarbon constituents of petroleum are persistent, bioaccumulated, and bio-magnified in living tissues, transported to longer distances, and exert hazardous effects on human health and the ecosystem. Bioaugmentation with microorganisms like bacteria is an emerging approach that can mitigate the toxins from environmental sources. The present study was initiated to target the petroleum-contaminated soil of gasoline stations situated in Lahore. Petroleum degrading bacteria were isolated by serial dilution method followed by growth analysis, biochemical and molecular characterization, removal efficiency estimation, metabolites extraction, and GC-MS of the metabolites. Molecular analysis identified the bacterium as Bacillus cereus, which exhibited maximum growth at 72 hours and removed 75% petroleum. Biochemical characterization via the Remel RapID™ ONE panel system showed positive results for arginine dehydrolase (ADH), ornithine decarboxylase (ODC), lysine decarboxylase (LDC), o-nitrophenyl-β-D-galactosidase (ONPG), p-nitrophenyl-β-D-glucosidase (βGLU), p-nitrophenyl-N-acetyl-β-D-glucosaminidase (NAG), malonate (MAL), adonitol fermentation (ADON), and tryptophane utilization (IND). GC-MS-based metabolic profiling identified alcohols (methyl alcohol, o-, p- and m-cresols, catechol, and 3-methyl catechol), aldehydes (methanone, acetaldehyde, and m-tolualdehyde), carboxylic acid (methanoic acid, cis,cis-muconic acid, cyclohexane carboxylic acid and benzoic acid), conjugate bases of carboxylic acids (benzoate, cis,cis-muconate, 4-hydroxybenzoate, and pyruvate) and cycloalkane (cyclohexene). It suggested the presence of methane, methylcyclohexane, toluene, xylene, and benzene degradation pathways in B. cereus.

A multi-omics approach to unravelling the coupling mechanism of nitrogen metabolism and phenanthrene biodegradation in soil amended with biochar

The presence of polycyclic aromatic hydrocarbons (PAHs) in soil negatively affects the environment and the degradation of these contaminants is influenced by nitrogen metabolism. However, the mechanisms underlying the interrelationships between the functional genes involved in nitrogen metabolism and phenanthrene (PHE) biodegradation, as well as the effects of biochar on these mechanisms, require further study. Therefore, this study utilised metabolomic and metagenomic analysis to investigate primary nitrogen processes, associated functional soil enzymes and functional genes, and differential soil metabolites in PHE-contaminated soil with and without biochar amendment over a 45-day incubation period. Results showed that dissimilatory nitrate reduction to ammonium (DNRA) and denitrification were the dominant nitrogen metabolism processes in PHE-contaminated soil. The addition of biochar enhanced nitrogen modules, exhibiting discernible temporal fluctuations in denitrification and DNRA proportions. Co-occurrence networks and correlation heatmap analysis revealed potential interactions among functional genes and enzymes responsible for PHE biodegradation and nitrogen metabolism. Notably, enzymes associated with denitrification and DNRA displayed significant positive correlation with enzymes involved in downstream phenanthrene degradation. Of particular interest was stronger correlation observed with the addition of biochar. However, biochar amendment inhibited the 9-phenanthrol degradation pathway, resulting in elevated levels of glutathione (GSH) in response to environmental stress. These findings provide new insights into the interactions between nitrogen metabolism and PHE biodegradation in soil and highlight the dual effects of biochar on these processes.

Chronic industrial perturbation and seasonal change induces shift in the bacterial community from gammaproteobacteria to betaproteobacteria having catabolic potential for aromatic compounds at Amlakhadi canal

Escalating proportions of industrially contaminated sites are one of the major catastrophes faced at the present time due to the industrial revolution. The difficulties associated with culturing the microbes, has been circumvent by the direct use of metagenomic analysis of various complex niches. In this study, a metagenomic approach using next generation sequencing technologies was applied to exemplify the taxonomic abundance and metabolic potential of the microbial community residing in Amlakhadi canal, Ankleshwar at two different seasons. All the metagenomes revealed a predominance of Proteobacteria phylum. However, difference was observed within class level where Gammaproteobacteria was relatively high in polluted metagenome in Summer while in Monsoon the abundance shifted to Betaproteobacteria. Similarly, significant statistical differences were obtained while comparing the genera amongst contaminated sites where Serratia, Achromobacter, Stenotrophomonas and Pseudomonas were abundant in summer season and the dominance changed to Thiobacillus, Thauera, Acidovorax, Nitrosomonas, Sulfuricurvum, Novosphingobium, Hyphomonas and Geobacter in monsoon. Further upon functional characterization, the microbiomes revealed the diverse survival mechanisms, in response to the prevailing ecological conditions (such as degradation of aromatic compounds, heavy metal resistance, oxidative stress responses and multidrug resistance efflux pumps, etc.). The results have important implications in understanding and predicting the impacts of human-induced activities on microbial communities inhabiting natural niche and their responses in coping with the fluctuating pollution load.

Exploring the bacterial genetic diversity and community structure of crude oil contaminated soils using microbiomics

The impact of environmental pollution in air and water is reflected mainly in the soil ecosystem as it impairs soil functions. Also, since the soil is the habitat for billions of organisms, the biodiversity is in turn altered. Microbes are precise sensors of ecological contamination, and bacteria have a key and important function in terms of bioremediation of the contaminated soil. Hence in the current work, we aimed at assessing the unidentified bacterial population through Illumina MiSeq sequencing technology and their community structural changes in different levels of petroleum-contaminated soil and sludge samples (aged, sludge, and leakage soil) to identify unique bacteria for their potential application in remediation. The studies showed that major bacterial consortiums namely, Proteobacteria (57%), Alphaproteobacteria (31%), and Moraxellaceae (23%) were present in aged soil, whereas Proteobacteria (52%), Alphaproteobacteria (33%), and Rhodobacteraceae (28%) were dominantly found in sludge soil. In leakage soil, Proteobacteria (59%), Alphaproteobacteria (33%), and Rhodobacteraceae (29%) were abundantly present. The Venn diagrams are used to analyze the distribution of abundances in individual operational taxonomic units (OTUs) within three soil samples. After data filtering, they were grouped into OTU clusters and 329 OTUs were identified from the three soil samples. Among the 329, 160 OTUs were common in the three soil samples. The bacterial diversity is estimated using alpha diversity indices and Shanon index and was found to be 4.490, 4.073 and 4.631 in aged soil, sludge soil and leakage soil, respectively and similarly richness was found to be 618, 417 and 418. The heat map was generated by QIIME software and from the top 50 enriched genera few microbes such as Pseudomonas, Bacillus, Mycobacterium, Sphingomonas and Paracoccus, were shown across all the samples. In addition, we also analyzed various physicochemical properties of soil including pH, temperature, salinity, electrical conductivity, alkalinity, total carbon, total organic matter, nitrogen, phosphorus and potassium to calculate the soil quality index (SQI). The SQI of aged, sludge and leakage soil samples were 0.73, 0.64, and 0.89, respectively. These findings show the presence of unexplored bacterial species which could be applied for hydrocarbon remediation and further they can be exploited for the same.