Ligand-displaying

CRISPR/Cas9 antimicrobials conjugation minicells nanobodies type IV secretion

Journal

mBio
ISSN: 2150-7511
Titre abrégé: mBio
Pays: United States
ID NLM: 101519231

Informations de publication

Date de publication:
29 Sep 2023
Historique:
medline: 29 9 2023
pubmed: 29 9 2023
entrez: 29 9 2023
Statut: aheadofprint

Résumé

Bacterial type IV secretion systems (T4SSs) are highly versatile macromolecular translocators and offer great potential for deployment as delivery systems for therapeutic intervention. One major T4SS subfamily, the conjugation machines, are well-adapted for delivery of DNA cargoes of interest to other bacteria or eukaryotic cells but generally exhibit modest transfer frequencies and lack specificity for target cells. Here, we tested the efficacy of a surface-displayed nanobody/antigen (Nb/Ag) pairing system to enhance the conjugative transfer of IncN (pKM101), IncF (F/pOX38), or IncP (RP4) plasmids, or of mobilizable plasmids including those encoding CRISPR/Cas9 systems (pCrispr), to targeted recipient cells.

Identifiants

pubmed: 37772866
doi: 10.1128/mbio.02143-23
pmc: PMC10653926
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0214323

Subventions

Organisme : NIGMS NIH HHS
ID : R35 GM131892
Pays : United States

Commentaires et corrections

Type : UpdateOf

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Auteurs

Yang Grace Li (YG)

Department of Microbiology and Molecular Genetics, McGovern School of Medicine, University of Texas Health Science Center , Houston, Texas, USA.

Kouhei Kishida (K)

Department of Microbiology and Molecular Genetics, McGovern School of Medicine, University of Texas Health Science Center , Houston, Texas, USA.

Natsumi Ogawa-Kishida (N)

Department of Microbiology and Molecular Genetics, McGovern School of Medicine, University of Texas Health Science Center , Houston, Texas, USA.

Peter J Christie (PJ)

Department of Microbiology and Molecular Genetics, McGovern School of Medicine, University of Texas Health Science Center , Houston, Texas, USA.

Classifications MeSH