A Novel Pathway of Chlorimuron-Ethyl Biodegradation by Chenggangzhangella methanolivorans Strain CHL1 and Its Molecular Mechanisms

Integrating bioassay and machine learning data for ecological risk assessments of herbicide use on Ulva australis

Herbicide contamination of aquatic ecosystems poses a critical risk to biodiversity. Bioassays provide useful ecological insights on responses to herbicides; however, they require a model organism. Ulva australis is an ideal candidate for herbicide toxicity evaluations. Conventional monitoring methods have certain limitations, necessitating innovative approaches for ecological risk assessment. We evaluated the toxicity of six herbicides (atrazine, chlorimuron-ethyl, diuron, hexazinone, simazine, and pendimethalin) to U. australis by integrating experimental bioassays with advanced machine learning models. Three key endpoints were measured-reproduction, relative growth rate, and photosynthetic efficiency. Species sensitivity distribution modelling was employed to determine the hazardous concentration values for 5 % of species (HC5) and the predicted no-effect concentration (PNEC). The derived values aligned well with regulatory benchmarks. For diuron, the PNEC (0.37 ± 0.25 μg L-1) closely matched the value of the European Chemicals Agency (0.32 μg L-1). In contrast, the HC5 for hexazinone (26.8 ± 28.7 μg L-1) was lower than that specified by the Australian/New Zealand guideline (75 μg L-1). Machine learning models showed high predictive accuracy, with gradient boosting outperforming random forest (R2 = 0.933, RMSE = 0.0036 mg L-1 vs R2 = 0.878 and RMSE = 0.0048 mg L-1). Sensitivity analysis confirmed the robustness of gradient boosting to input variability, highlighting its suitability for ecological risk assessment. This approach establishes a scalable framework for ecological risk evaluation by integrating experimental and computational methodologies. The resulting data can also generate adaptive strategies to mitigate herbicide impacts and protect aquatic ecosystems.

Microbial degradation as a powerful weapon in the removal of sulfonylurea herbicides

Sulfonylurea herbicides have been widely used worldwide and play a significant role in modern agricultural production. However, these herbicides have adverse biological effects that can damage the ecosystems and harm human health. As such, rapid and effective techniques that remove sulfonylurea residues from the environment are urgently required. Attempts have been made to remove sulfonylurea residues from environment using various techniques such as incineration, adsorption, photolysis, ozonation, and microbial degradation. Among them, biodegradation is regarded as a practical and environmentally responsible way to eliminate pesticide residues. Microbial strains such as Talaromyces flavus LZM1, Methylopila sp. SD-1, Ochrobactrum sp. ZWS16, Staphylococcus cohnii ZWS13, Enterobacter ludwigii sp. CE-1, Phlebia sp. 606, and Bacillus subtilis LXL-7 can almost completely degrade sulfonylureas. The degradation mechanism of the strains is such that sulfonylureas can be catalyzed by bridge hydrolysis to produce sulfonamides and heterocyclic compounds, which deactivate sulfonylureas. The molecular mechanisms associated with microbial degradation of sulfonylureas are relatively poorly studied, with hydrolase, oxidase, dehydrogenase and esterase currently known to play a pivotal role in the catabolic pathways of sulfonylureas. Till date, there are no reports specifically on the microbial degrading species and biochemical mechanisms of sulfonylureas. Hence, in this article, the degradation strains, metabolic pathways, and biochemical mechanisms of sulfonylurea biodegradation, along with its toxic effects on aquatic and terrestrial animals, are discussed in depth in order to provide new ideas for remediation of soil and sediments polluted by sulfonylurea herbicides.

Characterization and genomic analysis of a bensulfuron methyl-degrading endophytic bacterium Proteus sp. CD3 isolated from barnyard grass (Echinochloa crus-galli)

Bensulfuron methyl (BSM) is a widely used sulfonylurea herbicide in agriculture. However, the large-scale BSM application causes severe environmental problems. Biodegradation is an important way to remove BSM residue. In this study, an endophytic bacterium strain CD3, newly isolated from barnyard grass (Echinochloa crus-galli), could effectively degrade BSM in mineral salt medium. The strain CD3 was identified as Proteus sp. based on the phenotypic features, physiological biochemical characteristics, and 16S rRNA gene sequence. The suitable conditions for BSM degradation by this strain were 20–40°C, pH 6–8, the initial concertation of 12.5–200 mg L⁻¹ with 10 g L⁻¹ glucose as additional carbon source. The endophyte was capable of degrading above 98% BSM within 7 d under the optimal degrading conditions. Furthermore, strain CD3 could also effectively degrade other sulfonylurea herbicides including nicosulfuron, halosulfuron methyl, pyrazosulfuron, and ethoxysulfuron. Extracellular enzyme played a critical role on the BSM degradation by strain CD3. Two degrading metabolites were detected and identified by using liquid chromatography–mass spectrometry (LC–MS). The biochemical degradation pathways of BSM by this endophyte were proposed. The genomic analysis of strain CD3 revealed the presence of putative hydrolase or esterase genes involved in BSM degradation, suggesting that a novel degradation enzyme for BSM was present in this BSM-degrading Proteus sp. CD3. The results of this research suggested that strain CD3 may have potential for using in the bioremediation of BSM-contaminated environment.