Dataset Information

Integrative Omics Analysis of Plant-Microbe Synergies in Petroleum Pollution Remediation

ABSTRACT:

As the petrochemical industry continues to advance, the exacerbation of ecological imbalance and environmental degradation due to petroleum pollution is increasingly pronounced. The synergistic interaction between plants and microorganisms are pivotal in the degradation of petroleum hydrocarbons; however, the underlying degradation mechanisms are not yet fully understood. In this study, we employed a multi-omics approach, integrating transcriptomics, 16S rRNA gene sequencing and metabolomics, to analyze key differential genes, dominant microbial strains and root-secreted metabolites involved in petroleum hydrocarbon degradation in alfalfa. The results show that several stress-related genes are upregulated in alfalfa contaminated with petroleum hydrocarbon. Pseudomonas, Rhodococcus and Brevundimonas remain dominant species in the rhizosphere microbiome. Additionally, when applying pantothenic acid, malic acid and citric acid selected from metabolomics to the oil sediment used for growing alfalfa, the degradation rates significantly improved, with pantothenic acid application resulting in approximately a 10% higher degradation rate compared to other treatments. Our findings offer essential insights for optimizing phytoremediation strategies and improving the efficiency of soil decontamination

INSTRUMENT(S): Liquid Chromatography MS - negative - reverse phase, Liquid Chromatography MS - positive - reverse phase

PROVIDER: MTBLS11700 | MetaboLights | 2025-05-16

REPOSITORIES: MetaboLights

ACCESS DATA

Dataset's files

Source:

Items per page:

1 - 5 of 24

Similar Datasets

Project description:We analyzed the transcriptional response of the actinomycete Rhodococcus aetherivorans I24 to biphenyl and polychlorinated biphenyls (PCBs). This species has not been extensively exposed to PCBs, as it was first isolated from a toluene contaminated aquifer, rather than a site contaminated with polychlorinated hydrocarbons. Using a microarray targeting 3524 genes, we assessed gene expression in minimal medium supplemented with various substrates (e.g. PCBs) and in both PCB-contaminated and non-contaminated sediment slurries. Relative to the reference condition (minimal medium supplemented with glucose), 408 genes were up-regulated in the various treatments. In medium and in sediment, PCBs elicited the up-regulation of a common set of 100 genes, including chaperones (groEL), a superoxide dismutase (sodA), alkyl hydroperoxide reductase protein C (ahpC), and a catalase/peroxidase (katG). Analysis of the R. aetherivorans I24 genome sequence identified orthologs of many of the genes in the canonical biphenyl pathway, but very few of these genes were up-regulated in response to PCBs or biphenyl. This study is one of the first which utilizes microarrays to assess the transcriptional response of a soil bacterium to a pollutant under conditions which more closely resemble the natural environment. Our results indicate that the transcriptional response of R. aetherivorans I24 to PCBs, in both medium and sediment, is primarily directed towards reducing oxidative stress, rather than catabolism. In addition, the identification of numerous genes expressed in contaminated soil specifically may have implications for the development of biosensors. Finally, comparative genomic and transcriptomic analyses suggest that the mere presence of orthologs of the required enzymes may not be sufficient to confer a vigorous biphenyl/PCB metabolism. RNA was isolated from cells incubated in the following: sediment from a PCB-contaminated industrial site, uncontaminated sediment from a comparable site, and defined media supplemented with glucose (3 g/L), glucose and biphenyl (3 g/L, 4.5 Î¼M), or glucose and PCBs (3 g/L, 5 mg/L Aroclor 1254). In all cases, there were 3 biological replicates and 2 technical replicates (repeat hybridizations). A total of 3524 genes are represented on the arrays; of these, 41 and 176 are found on the plasmids pRA2 and pRA3, respectively. On average, there are 3 distinct 24nt probes per gene.

			Action	DRS
	NEG_Gj30GYN_M_1.raw	Raw
	NEG_Gj30GYN_M_2.raw	Raw
	NEG_Gj30GYN_M_3.raw	Raw
	NEG_Gj30GYN_M_4.raw	Raw
	NEG_Gj30GYN_M_5.raw	Raw

Dataset Information

Integrative Omics Analysis of Plant-Microbe Synergies in Petroleum Pollution Remediation

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets