Vinyl chloride and 1,4-dioxane metabolism by Pseudonocardia dioxanivorans CB1190

Polasko, Alexandra; Yu, Miao; Kwok, Ivy; Park, Keunseok; Park, Junyoung O.; Mahendra, Shaily

doi:10.1016/j.hazl.2021.100039

Cited by 4 publications

(3 citation statements)

References 55 publications

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“…The 1,4-dioxane-assimilating bacterial strain, CB1190, displayed efficient degradation capability, which was also observed in previous studies. , Even though CB1190 has been reported to degrade vinyl chloride, its activity might be inhibited by other chlorinated compounds. , Therefore, CVOCs showed decreasing trends, while 1,4-dioxane was accumulated at 230 μg/L. The dominant Pseudomonas , Ralstonia , Variovorax , and Mycobacterium have been identified as typical microbes in the soil environment, and the CVOC- and 1,4-dioxane-resistant genus Sphingomonas thrived during incubation with the unique ability to degrade naturally occurring and xenobiotic compounds, which presented different degradation pathways than Pseudomonas and Ralstonia .…”

Section: Discussionsupporting

confidence: 78%

“…The 1,4-dioxane-assimilating bacterial strain, CB1190, displayed efficient degradation capability, which was also observed in previous studies. 35,36 Even though CB1190 has been reported to degrade vinyl chloride, 33 its activity might be inhibited by other chlorinated compounds. 57,58 Therefore, CVOCs showed decreasing trends, while 1,4-dioxane was accumulated at 230 μg/L.…”

Section: Discussionmentioning

confidence: 99%

“…32 Pseudonocardia dioxanivorans CB1190 (CB1190) is able to utilize 1,4-dioxane as a sole carbon and energy source and sustain biodegradation even when the 1,4-dioxane levels are as low as 50 μg/L. 33 However, co-contaminants can hinder the natural attenuation process by inhibiting enzymes, 34 and therefore, the long-term occurrence of 1,4-dioxane and its co-contaminants has likely exerted stress on indigenous microbes and led to changes in the diversity and composition of soil and groundwater microbial communities, which further impact related biogeochemical processes. However, little is known about the above-mentioned microbial ecological transition and assembly from a comprehensive perspective, as well as CB1190s interaction with native microbes when degrading 1,4-dioxane in the presence of CVOCs, regarding contaminants and function information, via combined NGS and machine learning.…”

Section: Introductionmentioning

confidence: 99%

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Investigating Biodegradation of 1,4-Dioxane by Groundwater and Soil Microbiomes: Insights into Microbial Ecology and Process Prediction

Miao,

Zhou,

Zheng

et al. 2023

ACS EST Water

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Although microorganisms play significant roles in bioremediation, their contributions to long-term site characteristics during and after active treatment need to be fully elucidated. This study described microbial ecology dynamics in 1,4-dioxane- and chlorinated solvents-contaminated groundwater in laboratory microcosms. Bioaugmented Pseudonocardia dioxanivorans CB1190 improved 1,4-dioxane removal, with increased carbohydrate and amino acid metabolism, but was eventually outcompeted by native microbes. The original microbiomes were perturbed and divergent but tended to be similar over time. Dechlorinating bacteria co-existed in the same niche, whereas CB1190 had more negative interactions in the shared niche. Multiple regression and classification machine learning models were built by using microbial taxa to predict the degradation process; the ensemble regression model provided most accurate prediction of 1,4-dioxane concentrations (R 2 = 0.81 ± 0.17). Among the classification models, the support vector machine performed the best in differentiating the contamination levels (accuracy at 0.67 ± 0.07, kappa at 0.56 ± 0.10). The ensemble model predicted the 1,4-dioxane concentrations and relative duration of contamination with independent microbial datasets from a field study, and the results aligned with the geographic and hydrological information from monitoring wells. This study introduces the application of machine learning in microbiome-based diagnostics for groundwater remediation and evaluation, providing valuable methods for future research and practice.

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