Multiomics Data on Plant-Microbe Remediation of Organic Arsenicals in Soil

Xu Yang's dataset on figshare details a 60-day soil remediation experiment targeting organic arsenic pollutants diphenylarsonic acid and phenylarsonic acid. The data likely contains multiomics results from an integrated platform using Bacillus subtilis, Bacillus cereus, and alfalfa. The dataset was last updated on June 2, 2026.

Use Cases

• Modeling arsenic-carbon bond cleavage pathways based on enzyme activity data.
• Analyzing soil microbial community restructuring based on multiomics profiles.
• Training models to predict inorganic arsenic uptake by plants from microbial degradation products.
• Studying the reduction of antibiotic resistance genes in remediated soil environments.

Strengths

• Dataset is based on a 60-day controlled soil experiment, providing a defined temporal scope.
• Multiomics interrogation provides multiple layers of biological data for mechanistic insight.
• Remediation results are verified for two specific organic arsenic compounds, DPAA and PAA.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for specific analytical tasks.
• The 14.4 MB file size suggests a relatively small dataset, potentially limiting model training scope.

Provenance

Source

figshare, author Xu Yang.

Collection Method

Data generated from a constructed plant-microbe remediation system tested in contaminated soil, analyzed via multiomics.

Time Range

Experiment conducted over 60 days; specific collection dates unknown.

Freshness

Last updated 2026-06-02 12:05:22; freshness should be verified.