In silico prediction and prioritization of novel selective antimicrobial drug targets in escherichia coli

Frida Svanberg Frisinger*, Bimal Jana, Stefano Donadio, Luca Guardabassi

*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

8 Citationer (Scopus)
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Abstract

Novel antimicrobials interfering with pathogen-specific targets can minimize the risk of perturbations of the gut microbiota (dysbiosis) during therapy. We employed an in silico approach to identify essential proteins in Escherichia coli that are either absent or have low sequence identity in seven beneficial taxa of the gut microbiota: Faecalibacterium, Prevotella, Ruminococcus, Bacteroides, Lactobacillus, Lachnospiraceae and Bifidobacterium. We identified 36 essential proteins that are present in hyper-virulent E. coli ST131 and have low similarity (bitscore < 50 or identity < 30% and alignment length < 25%) to proteins in mammalian hosts and beneficial taxa. Of these, 35 are also present in Klebsiella pneumoniae. None of the proteins are targets of clinically used antibiotics, and 3D structure is available for 23 of them. Four proteins (LptD, LptE, LolB and BamD) are easily accessible as drug targets due to their location in the outer membrane, especially LptD, which contains extracellular domains. Our results indicate that it may be possible to selectively interfere with essential biological processes in Enterobacteriaceae that are absent or mediated by unrelated proteins in beneficial taxa residing in the gut. The identified targets can be used to discover antimicrobial drugs effective against these opportunistic pathogens with a decreased risk of causing dysbiosis.

OriginalsprogEngelsk
Artikelnummer632
TidsskriftAntibiotics
Vol/bind10
Udgave nummer6
ISSN2079-6382
DOI
StatusUdgivet - 2021

Bibliografisk note

Funding Information:
Acknowledgments: We would like to thank Bastian V.H. Hornung and Defne Surjoun for their kind help with development of the Python scripts and pipelines. FSF is a recipient of a PhD fellowship from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Grant agreement no. 765147.

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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