The past 50 years have witnessed a massive expansion in the demand and application of pesticides.However,pesticides are difficult to be completely degraded without intervention hence the pesticide residue could pose a...The past 50 years have witnessed a massive expansion in the demand and application of pesticides.However,pesticides are difficult to be completely degraded without intervention hence the pesticide residue could pose a persistent threat to non-target organisms in many aspects.To aim at the problem of the abuse of pesticide products and excessive pesticide residues in the environment,chemical and biological degradation methods are widely developed but are scaled and insufficient to solve such a pollution.In recent years,bio-degradative tools instructed by synthetic biological principles have been further studied and have paved a way for pesticide degradation.Combining the customized design strategy and standardized assembly mode,the engineering bacteria for multi-dimensional degradation has become an effective tool for pesticide residue degradation.This review introduces the mechanisms and hazards of different pesticides,summarizes the methods applied in the degradation of pesticide residues,and discusses the advantages,applications,and prospects of synthetic biology in degrading pesticide residues.展开更多
A reliable 3-D structure of Triacylglycerol lipase from Bacillus thermocatenulanatus was constructed by homology modeling. Under molecular dynamics simulation, it was refined and checked. The model was further used as...A reliable 3-D structure of Triacylglycerol lipase from Bacillus thermocatenulanatus was constructed by homology modeling. Under molecular dynamics simulation, it was refined and checked. The model was further used as a receptor to search binding sites and carry out flexible docking with a range of substrates, whose enzyme activities were already measured. By inputting a series of docking results, virtual substrates screening models were established and assessed. Monadic nonlinear solution demanded less data but was weak in fitting enzyme activity data with little difference; its mean absolute percentage error （MAPE） of regression was 0.67 and mean square error （MSE） was 1.73 U/mg. Both quadratic stepwise regression and BP neural network were good in regression and prediction; however, more data were required. In the cross-validation of 12 groups, overall MAPE of regression and prediction for the former were 0.18 and 0.49, while the latter was 0.55 and 0.36. MSE values for these two methods were 0.95 and 1.20 U/mg, respectively. Therefore, monadic nonlinear regression model can be used as a preliminary screening one; quadratic stepwise regression and BP neural network approach can be applied to precise screening.展开更多
基金supported by the National Natural Science Foundation of China(No.22278343)Shenzhen Basic Research Project(JCYJ20190809160209449).
文摘The past 50 years have witnessed a massive expansion in the demand and application of pesticides.However,pesticides are difficult to be completely degraded without intervention hence the pesticide residue could pose a persistent threat to non-target organisms in many aspects.To aim at the problem of the abuse of pesticide products and excessive pesticide residues in the environment,chemical and biological degradation methods are widely developed but are scaled and insufficient to solve such a pollution.In recent years,bio-degradative tools instructed by synthetic biological principles have been further studied and have paved a way for pesticide degradation.Combining the customized design strategy and standardized assembly mode,the engineering bacteria for multi-dimensional degradation has become an effective tool for pesticide residue degradation.This review introduces the mechanisms and hazards of different pesticides,summarizes the methods applied in the degradation of pesticide residues,and discusses the advantages,applications,and prospects of synthetic biology in degrading pesticide residues.
基金Supported by the Research Found for Doctoral Foundation of Institutions of Higher Education of China (20070385001)
文摘A reliable 3-D structure of Triacylglycerol lipase from Bacillus thermocatenulanatus was constructed by homology modeling. Under molecular dynamics simulation, it was refined and checked. The model was further used as a receptor to search binding sites and carry out flexible docking with a range of substrates, whose enzyme activities were already measured. By inputting a series of docking results, virtual substrates screening models were established and assessed. Monadic nonlinear solution demanded less data but was weak in fitting enzyme activity data with little difference; its mean absolute percentage error （MAPE） of regression was 0.67 and mean square error （MSE） was 1.73 U/mg. Both quadratic stepwise regression and BP neural network were good in regression and prediction; however, more data were required. In the cross-validation of 12 groups, overall MAPE of regression and prediction for the former were 0.18 and 0.49, while the latter was 0.55 and 0.36. MSE values for these two methods were 0.95 and 1.20 U/mg, respectively. Therefore, monadic nonlinear regression model can be used as a preliminary screening one; quadratic stepwise regression and BP neural network approach can be applied to precise screening.
