Dehalobium species implicated in 2,3,7,8-tetrachlorodibenzo-p-dioxin dechlorination in the contaminated sediments of Sydney Harbour Estuary

Transcriptome analysis reveal the effect of freshwater sediments containing 2,3,7,8-tetrachlorodibenzo-p-dioxin on the Macrobrachium rosenbergii hepatopancreas, intestine, and muscle

This research evaluated the hepatopancreas, intestine, and muscle transcriptome alternation of Macrobrachium rosenbergii, and to confirm the relative glycerophospholipid, cytochrome P450 system, and fatty acid metabolism gene expression in sediments containing 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) of 60 ng/sediment (g) and 700 ng/sediment (g) for 90 days of culture. Transcriptome analysis revealed that the TCDD sediment affected the hepatopancreatic metabolism of xenobiotics in M. rosenbergii via the cytochrome P450 system, drug metabolism-other enzymes, drug metabolism-cytochrome P450, chemical carcinogenesis, and lysosome function. Intestinal analysis also showed a similar phenomenon, but this finding was not observed in the muscle tissue. qPCR analysis indicated that the expression levels of APTG4, LPGAT1, ACHE, GPX4, ECHS1, ATP5B, FABP, and ACC in the hepatopancreatic and intestinal tissues decreased, but those in the muscle tissues did not. In summary, TCDD sediment induced tissue metabolism, especially in the hepatopancreas and intestine. TCDD sediment mainly affected the digestive enzyme gene expression with concentration. These results indicated that the presence of TCDD in the sediment played a major role in the hepatopancreatic and intestinal metabolism system of M. rosenbergii.

Biodegradability analysis of Dioxins through in silico methods: Model construction and mechanism analysis

The biodegradation treatment of dioxins has long been of interest due to its good ecological and economic effects. In this study, the biodegradability of polychlorinated dibenzo-p-dioxins (PCDDs) were investigated by constructing machine learning and multiple linear regression models. The maximum chlorine atomic charge (qHirshfeldCl+), which characterizes the biodegradation ability of PCDDs, was used as the response value. The random forest model was used to rank the importance on the 1471 descriptors of PCDDs, and the BCUTp-1 h, QXZ, JGI4, ATSC8c, VE3_Dt, topoShape, and maxwHBa were screened as the important descriptors by Pearson's correlation coefficient method. A quantitative structure-activity relationship (QSAR) model was constructed to predict the biodegradability of PCDDs. In addition, the extreme gradient boosting (XGBoost) and random forest model were also constructed and proved the good predictability of QSAR model. The biodegradability of polychlorinated dibenzofurans (PCDFs) can also be predicted by the constructed three models from a certain level after adjusting some model parameters, which further proved the versatility of the models. Besides, the sensitivity analysis of the QSAR model and a 3D-QSAR model was developed to investigate the biodegradability mechanisms of PCDDs. Results showed that the descriptors BCUTp-1 h, JGI4, and maxwHBa were the key descriptors in the biodegradability effect by the sensitivity analysis of the QSAR model. Coupled with the results of PCDDs biodegradability 3D-QSAR model, BCUTp-1 h, JGI4, and maxwHBa were confirmed as the main descriptors that affect the biodegradability of dioxins. This study provides a novel theoretical perspective for the research of the biodegradation of both PCDDs and PCDFs dioxins.

Salinity determines performance, functional populations, and microbial ecology in consortia attenuating organohalide pollutants

Organohalide pollutants are prevalent in coastal regions due to extensive intervention by anthropogenic activities, threatening public health and ecosystems. Gradients in salinity are a natural feature of coasts, but their impacts on the environmental fate of organohalides and the underlying microbial communities remain poorly understood. Here we report the effects of salinity on microbial reductive dechlorination of tetrachloroethene (PCE) and polychlorinated biphenyls (PCBs) in consortia derived from distinct environments (freshwater and marine sediments). Marine-derived microcosms exhibited higher halotolerance during PCE and PCB dechlorination, and a halotolerant dechlorinating culture was enriched from these microcosms. The organohalide-respiring bacteria (OHRB) responsible for PCE and PCB dechlorination in marine microcosms shifted from Dehalococcoides to Dehalobium when salinity increased. Broadly, lower microbial diversity, simpler co-occurrence networks, and more deterministic microbial community assemblages were observed under higher salinity. Separately, we observed that inhibition of dechlorination by high salinity could be attributed to suppressed viability of Dehalococcoides rather than reduced provision of substrates by syntrophic microorganisms. Additionally, the high activity of PCE dechlorinating reductive dehalogenases (RDases) in in vitro tests under high salinity suggests that high salinity likely disrupted cellular components other than RDases in Dehalococcoides. Genomic analyses indicated that the capability of Dehalobium to perform dehalogenation under high salinity was likely owing to the presence of genes associated with halotolerance in its genomes. Collectively, these mechanistic and ecological insights contribute to understanding the fate and bioremediation of organohalide pollutants in environments with changing salinity.