Genotoxic impurities (GTIs) occurred in drugs, and food and environment pose a threat to human health. Accurate and sensitive evaluation of GTIs is of significance. Ames assay is the existing gold standard method. However, the pathogenic bacteria model lacks metabolic enzymes and requires mass GTIs, leading to insufficient safety, accuracy, and sensitivity. Whole-cell microbial sensors (WCMSs) can use normal strains to simulate the metabolic environment, achieving safe, sensitive, and high-throughput detection and evaluation for GTIs. Here, based on whether GTIs causing DNA alkylation required metabolic enzymes or not, two DNA repair-responsive engineered WCMS systems were constructed including Escherichia coli-WCMS and yeast-WCMS. A DNA repair-responsive promoter as a sensing element was coupled with an enhanced green fluorescent protein as a reporter to construct plasmids for introduction into WCMS. The ada promoter was screened out in the E. coli-WCMS, while the MAG1 promoter was selected for the yeast-WCMS. Different E. coli and yeast strains were modified by gene knockout and mutation to eliminate the interference and enhance the GTI retention in cells and further improved the sensitivity. Finally, GTI consumption of WCMS for the evaluation of methyl methanesulfonate (MMS) and nitrosamines was decreased to 0.46-8.53 μg and 0.068 ng-2.65 μg, respectively, decreasing 2-3 orders of magnitude compared to traditional methods. This study provided a novel approach to measure GTIs with different DNA damage pathways at a molecular level and facilitated the high-throughput screening and sensitive evaluation of GTIs.
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Evidence ID | Analyze ID | Gene/Complex | Systematic Name/Complex Accession | Qualifier | Gene Ontology Term ID | Gene Ontology Term | Aspect | Annotation Extension | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Phenotype | Experiment Type | Experiment Type Category | Mutant Information | Strain Background | Chemical | Details | Reference |
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Evidence ID | Analyze ID | Gene | Gene Systematic Name | Disease Ontology Term | Disease Ontology Term ID | Qualifier | Evidence | Method | Source | Assigned On | Reference |
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Evidence ID | Analyze ID | Regulator | Regulator Systematic Name | Target | Target Systematic Name | Direction | Regulation of | Happens During | Regulator Type | Direction | Regulation Of | Happens During | Method | Evidence | Strain Background | Reference |
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Site | Modification | Modifier | Source | Reference |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Allele | Assay | Annotation | Action | Phenotype | SGA score | P-value | Source | Reference | Note |
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Evidence ID | Analyze ID | Interactor | Interactor Systematic Name | Interactor | Interactor Systematic Name | Assay | Annotation | Action | Modification | Source | Reference | Note |
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Complement ID | Locus ID | Gene | Species | Gene ID | Strain background | Direction | Details | Source | Reference |
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Evidence ID | Analyze ID | Dataset | Description | Keywords | Number of Conditions | Reference |
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