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Record W4414035617 · doi:10.1093/jambio/lxaf226

Responses of microbial communities during oilseed plant-based phytoremediation of heavy metal-contaminated soils

2025· article· en· W4414035617 on OpenAlexaff
Guowei Zhang, Yihong Yue, Lin Tu, Qunlu Liu, Qian Zhang, Kankan Shang

Bibliographic record

VenueJournal of Applied Microbiology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicHeavy metals in environment
Canadian institutionsUniversité de MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsPhytoremediationHeavy metalsContaminationSoil waterEnvironmental sciencePhytoextraction processSoil contaminationAgronomyEnvironmental chemistryBiologyHyperaccumulatorChemistryEcologySoil science

Abstract

fetched live from OpenAlex

AIMS: Phytoremediation is an effective method of remediating soils contaminated with heavy metals. However, it has some limitations in practical applications with regard to rare plant species, poor environmental adaptability, and long growth cycles. The dynamic response mechanisms of soil microbial communities during phytoremediation are still unclear, which restricts the optimization and promotion of this approach. METHODS AND RESULTS: No ethical approval was required for this study. In this study, soil bacterial, fungal, and archaeal communities during the remediation of Cu-, Pb-, and Zn-contaminated soils with five industrial oilseed plants [Xanthium strumarium (XS), Bidens pilosa (BP), Kosteletzkya virginica (KV), Sesbania cannabina (SC), and Commelina communis (CC)] were analyzed using metagenome sequencing. Compared with soil contaminated with heavy metals, remediation through five industrial oilseed plants significantly reduced the content of heavy metals in the soil, with soil Cu, Pb, and Zn decreasing by 44.01%, 46.32%, and 27.62%, respectively, and WSCu, WSPb, and WSZn content decreasing by 28.23%, 50.68%, and 75.26%, respectively. Microbial diversity analysis showed that the phytoremediation significantly affected the soil microbial communities, with a significant decrease in archaeal diversity. Variation partitioning analysis and Mantel tests revealed that heavy metals and soil physicochemical properties significantly affected microbial communities, and heavy metals exerted stronger effects on archaeal communities. Meanwhile, soil contaminated with heavy metals was mainly dominated by fungal-fungal interactions, whereas phytoremediation increased the complexity of microbial symbiotic networks. CONCLUSION: Collectively, these results provide fundamental insights into the microbial community structure during phytoremediation of heavy metal-contaminated soil, which may aid in the bioregulation of phytoremediation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.220
Teacher spread0.211 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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