Synthetic biology enables infinite possibilities in biotechnology via employing genetic modules. However, not many researches have explored the potentials of synthetic biology in environmental bioprocesses. In this study, we introduced a genetic module harboring the codon-optimized tetracycline degrading gene, tetX.co , into the model host, Escherichia coli , and generated a prototypal whole-cell biodevice for the degradation of a target antibiotic. Our results suggested that E. coli with the tetX.co- module driven by either the P J23119 or P BAD promoters conferred resistance up to 50 μg/mL of tetracycline and degrades over 95% of tetracycline within 24 h. The detoxification ability of tetX was further verified in conditioned media by typical E. coli K-12 and B strains as well as Shewanella oneidensis . Our strategy demonstrated the feasibility of introducing genetic modules into model hosts to enable environmental functions, and this work will inspire more environmental innovations through synthetic biological devices.
Li Peng,Bai Chujie,Zhan Lingmin,Zhang Haoran,Zhang Yuanyuan,Zhang Wuxia,Wang Yingdong,Zhao Jinzhong
Identification of the biological targets of a compound is of paramount importance for the exploration of the mechanism of action of drugs and for the development of novel drugs. A concept of the Connectivity Map (CMap) was previously proposed to connect genes, drugs, and disease states based on the common gene-expression signatures. For a new query compound, the CMap-based method can infer its potential targets by searching similar drugs with known targets (reference drugs) and measuring the similarities into their specific transcriptional responses between the query compound and those reference drugs. However, the available methods are often inefficient due to the requirement of the reference drugs as a medium to link the query agent and targets. Here, we developed a general procedure to extract target-induced consensus gene modules from the transcriptional profiles induced by the treatment of perturbagens of a target. A specific transcriptional gene module pair (GMP) was automatically identified for each target and could be used as a direct target signature. Based on the GMPs, we built the target network and identified some target gene clusters with similar biological mechanisms. Moreover, a gene module pair-based target identification (GMPTI) approach was proposed to predict novel compound–target interactions. Using this method, we have discovered novel inhibitors for three PI3K pathway proteins PI3Kα/β/δ, including PU-H71, alvespimycin, reversine, astemizole, raloxifene HCl, and tamoxifen.
危险品化学品经营许可证（带存储）