Literature DB >> 33199638

Transcriptome-based design of antisense inhibitors potentiates carbapenem efficacy in CRE Escherichia coli.

Thomas R Aunins1, Keesha E Erickson1, Anushree Chatterjee2,3,4,5.   

Abstract

In recent years, the prevalence of carbapenem-resistant Enterobacteriaceae (CRE) has risen substantially, and the study of CRE resistance mechanisms has become increasingly important for antibiotic development. Although much research has focused on genomic resistance factors, relatively few studies have examined CRE pathogens through changes in gene expression. In this study, we examined the gene expression profile of a CRE Escherichia coli clinical isolate that is sensitive to meropenem but resistant to ertapenem to explore transcriptomic contributions to resistance and to identify gene knockdown targets for carbapenem potentiation. We sequenced total and short RNA to analyze the gene expression response to ertapenem or meropenem treatment and found significant expression changes in genes related to motility, maltodextrin metabolism, the formate hydrogenlyase complex, and the general stress response. To validate these findings, we used our laboratory's Facile Accelerated Specific Therapeutic (FAST) platform to create antisense peptide nucleic acids (PNAs), gene-specific molecules designed to inhibit protein translation. PNAs were designed to inhibit the pathways identified in our transcriptomic analysis, and each PNA was then tested in combination with each carbapenem to assess its effect on the antibiotics' minimum inhibitory concentrations. We observed significant PNA-antibiotic interaction with five different PNAs across six combinations. Inhibition of the genes hycA, dsrB, and bolA potentiated carbapenem efficacy in CRE E. coli, whereas inhibition of the genes flhC and ygaC conferred added resistance. Our results identify resistance factors and demonstrate that transcriptomic analysis is a potent tool for designing antibiotic PNA.

Entities:  

Keywords:  antibiotic resistance; carbapenem-resistant Escherichia coli; genome sequence; short RNA sequencing; transcriptome

Mesh:

Substances:

Year:  2020        PMID: 33199638      PMCID: PMC7720196          DOI: 10.1073/pnas.1922187117

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  74 in total

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Journal:  Mol Microbiol       Date:  1999-05       Impact factor: 3.501

2.  Peptide-conjugated phosphorodiamidate morpholino oligomer (PPMO) restores carbapenem susceptibility to NDM-1-positive pathogens in vitro and in vivo.

Authors:  Erin K Sully; Bruce L Geller; Lixin Li; Christina M Moody; Stacey M Bailey; Amy L Moore; Michael Wong; Patrice Nordmann; Seth M Daly; Carolyn R Sturge; David E Greenberg
Journal:  J Antimicrob Chemother       Date:  2017-03-01       Impact factor: 5.790

Review 3.  Ertapenem: a new carbapenem.

Authors:  I Odenholt
Journal:  Expert Opin Investig Drugs       Date:  2001-06       Impact factor: 6.206

4.  The Sequence Alignment/Map format and SAMtools.

Authors:  Heng Li; Bob Handsaker; Alec Wysoker; Tim Fennell; Jue Ruan; Nils Homer; Gabor Marth; Goncalo Abecasis; Richard Durbin
Journal:  Bioinformatics       Date:  2009-06-08       Impact factor: 6.937

5.  Biochemical comparison of imipenem, meropenem and biapenem: permeability, binding to penicillin-binding proteins, and stability to hydrolysis by beta-lactamases.

Authors:  Y Yang; N Bhachech; K Bush
Journal:  J Antimicrob Chemother       Date:  1995-01       Impact factor: 5.790

6.  Carbapenem activities against Pseudomonas aeruginosa: respective contributions of OprD and efflux systems.

Authors:  T Köhler; M Michea-Hamzehpour; S F Epp; J C Pechere
Journal:  Antimicrob Agents Chemother       Date:  1999-02       Impact factor: 5.191

7.  Differential expression analysis for sequence count data.

Authors:  Simon Anders; Wolfgang Huber
Journal:  Genome Biol       Date:  2010-10-27       Impact factor: 13.583

8.  HTSeq--a Python framework to work with high-throughput sequencing data.

Authors:  Simon Anders; Paul Theodor Pyl; Wolfgang Huber
Journal:  Bioinformatics       Date:  2014-09-25       Impact factor: 6.937

Review 9.  Multiple applications of Alamar Blue as an indicator of metabolic function and cellular health in cell viability bioassays.

Authors:  Sephra N Rampersad
Journal:  Sensors (Basel)       Date:  2012-09-10       Impact factor: 3.576

10.  Oxacillin sensitization of methicillin-resistant Staphylococcus aureus and methicillin-resistant Staphylococcus pseudintermedius by antisense peptide nucleic acids in vitro.

Authors:  Shan Goh; Anette Loeffler; David H Lloyd; Sean P Nair; Liam Good
Journal:  BMC Microbiol       Date:  2015-11-11       Impact factor: 3.605

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  4 in total

1.  Facile accelerated specific therapeutic (FAST) platform develops antisense therapies to counter multidrug-resistant bacteria.

Authors:  Kristen A Eller; Thomas R Aunins; Colleen M Courtney; Jocelyn K Campos; Peter B Otoupal; Keesha E Erickson; Nancy E Madinger; Anushree Chatterjee
Journal:  Commun Biol       Date:  2021-03-12

Review 2.  Silencing Antibiotic Resistance with Antisense Oligonucleotides.

Authors:  Saumya Jani; Maria Soledad Ramirez; Marcelo E Tolmasky
Journal:  Biomedicines       Date:  2021-04-12

3.  Potentiating antibiotic efficacy via perturbation of non-essential gene expression.

Authors:  Peter B Otoupal; Kristen A Eller; Keesha E Erickson; Jocelyn Campos; Thomas R Aunins; Anushree Chatterjee
Journal:  Commun Biol       Date:  2021-11-05

4.  Light-activated quantum dot potentiation of antibiotics to treat drug-resistant bacterial biofilms.

Authors:  Dana F Stamo; Prashant Nagpal; Anushree Chatterjee
Journal:  Nanoscale Adv       Date:  2021-04-21
  4 in total

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