Integrating CRISPR-Enabled Trackable Genome Engineering and Transcriptomic Analysis of Global Regulators for Antibiotic Resistance Selection and Identification in Escherichia coli

• Main Authors: Cong Chen, Alaksh Choudhury, Shuanghong Zhang, Andrew D. Garst, Xin Song, Xunli Liu, Tao Chen, Ryan T. Gill, Zhiwen Wang
• Format: Article
• Language: English
• Published: American Society for Microbiology 2020-04-01
• Series: mSystems
• Subjects: antibiotic resistance; global regulators; create; transcriptome; mutation
• Online Access: https://doi.org/10.1128/mSystems.00232-20

The growing threat of antimicrobial resistance poses a serious threat to public health care and motivates efforts to understand the means by which resistance acquisition occurs and how this can be combatted. To address these challenges, we expedited the identification of novel mutations that enable complex phenotypic changes that result in improved tolerance to antibiotics by integrating CREATE and transcriptomic analysis of global regulators. The results give us a better understanding of the mechanisms of resistance to tetracycline antibiotics and aminoglycoside antibiotics and also indicate that the method may be used for quickly identifying resistance-related mutations.It is important to expedite our understanding of antibiotic resistance to address the increasing numbers of fatalities and environmental pollution due to the emergence of antibiotic resistance and multidrug-resistant strains. Here, we combined the CRISPR-enabled trackable genome engineering (CREATE) technology and transcriptomic analysis to investigate antibiotic tolerance in Escherichia coli. We developed rationally designed site saturation mutagenesis libraries targeting 23 global regulators to identify fitness-conferring mutations in response to diverse antibiotic stresses. We identified seven novel mutations that confer resistance to the ribosome-targeting antibiotics doxycycline, thiamphenicol, and gentamicin in E. coli. To the best of our knowledge, these mutations that we identified have not been reported previously during treatment with the indicated antibiotics. Transcriptome sequencing-based transcriptome analysis was further employed to evaluate the genome-wide changes in gene expression in E. coli for SoxR G121P and cAMP receptor protein (CRP) V140W reconstructions, and improved fitness in response to doxycycline and gentamicin was seen. In the case of doxycycline, we speculated that SoxR G121P significantly increased the expression of genes involved in carbohydrate metabolism and energy metabolism to promote cell growth for improved adaptation. In the CRP V140W mutant with improved gentamicin tolerance, the expression of several amino acid biosynthesis genes and fatty acid degradation genes was significantly changed, and these changes probably altered the cellular energy state to improve adaptation. These findings have important significance for understanding such nonspecific mechanisms of antibiotic resistance and developing new antibacterial drugs.