Transcriptome‐based design of PNA inhibitors re‐sensitizes CRE E. coli to carbapenems
Authors: Aunins Thomas , Erickson Keesha , Chatterjee Anushree 
Published: April 2020

Carbapenems are a powerful class of antibiotics, often used as a last‐resort treatment to eradicate multidrug‐resistant infections. In recent years, however, the incidence of carbapenem‐resistant Enterobacteriaceae (CRE) has risen substantially, and the study of bacterial resistance mechanisms has become increasingly important for antibiotic development. In this research, we use transcriptomics and antisense gene inhibitors both to explore the resistance profile of a CRE Escherichia coli clinical isolate and to engineer carbapenem re‐sensitization. The clinical isolate demonstrates resistance to the carbapenem ertapenem but sensitivity to meropenem, and, though genomic analysis identified thirteen antibiotic resistance genes (including two β‐lactamases), no dedicated carbapenemases were found. Transcriptomic analysis was performed to examine the strain’s short‐term (<1 hr) gene expression changes in response to ertapenem or meropenem. While we did not observe differential expression of any resistance gene, significant expression changes were found in genes related to motility, maltodextrin metabolism, the formate hydrogenlyase complex, and the general stress response. Using our lab’s Facile Accelerated Specific Therapeutics (FAST) platform, we designed sequence‐specific antisense peptide nucleic acids (PNA) to inhibit the translation of genes that were identified by our transcriptomic analysis. These PNA were tested in combination with each carbapenem, either to assess their ability to re‐sensitize the isolate to ertapenem or their ability to alter the minimum inhibitory concentration of meropenem. We observed significant interaction between PNA and carbapenem treatments with four different PNA (two specific to the ertapenem response, one to the meropenem response, and one important to both responses). These results identify gene expression‐based resistance factors, and confirm the utility of transcriptomic analysis in engineering antibiotic re‐sensitization.

Support or Funding Information

This work was funded by a University of Colorado Dean’s Graduate Research Grant as well as the W.M. Keck Foundation and DARPA Young Faculty Award (D17AP00024).

(A) Overview of the sample collection protocol for RNA sequencing. (B) Hierarchical clustering of gene expression values in ertapenem and meropenemtreated E. coli CUS2B. (C) Intersections in significantly differentially expressed (DE) genes between stress conditions and timepoints. (D) Time course of gene expression changes for the 6 transcripts that were DE in ertapenem and meropenem at both 30 and 60 minutes. *: P < 0.05 vs. NT. NT = no treatment, ERT = ertapenem, MER = meropenem.

Figure 1

(A) α‐hycA (10 μM) combined with ertapenem (1 μg/mL); (B) α‐flhC (10 μM) combined with meropenem (0.2 μg/mL); (C) α‐bolA (10 μM) combined with ertapenem (1 μg/mL), and α‐bolA (15 μM) combined with meropenem (0.1 μg/mL); (D) α‐dsrB (10 μM) combined with ertapenem (1 μg/mL); (E) Summary of interaction significance with normalized S‐values. ERT = ertapenem, MER = meropenem. *: ANOVA interaction P‐value < 0.05.

Figure 2