Cefiderocol resistance genes identified in environmental samples using functional metagenomics

利用功能宏基因组学方法在环境样本中鉴定头孢地洛耐药基因

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作者:Remi Gschwind,Mehdi Bonnet,Anna Abramova,Victor Hugo Jarquín-Díaz,Marcus Wenne,Ulrike Löber,Nicolas Godron,Ioannis D Kampouris,Faina Tskhay,Fouzia Nahid,Chloé Debroucker,Maximilien Bui-Hai,Inès El Aiba,Uli Klümper,Thomas U Berendonk,Sofia K Forslund-Startceva,Rabaab Zahra,Johan Bengtsson-Palme,Etienne Ruppé

Abstract

Antibiotic resistance poses a global public health threat, which can originate from the transfer of environmental antibiotic resistance genes to pathogenic bacteria, as highlighted by the "One Health" framework. Cefiderocol is a siderophore cephalosporin recently introduced in clinical practice which displays a "Trojan Horse" mechanism, utilizing bacterial iron transportation systems for cell entry. Although it is only used as a last-line antibiotic, resistance has already been observed in clinical isolates. Yet, cefiderocol resistance genes are difficult to monitor as resistance mechanisms remain mostly undescribed in antibiotic resistance gene databases and therefore uncharacterized in the environment. To address this critical gap, we applied functional metagenomics to diverse environmental samples (wastewater, freshwater, and soil) from France, Germany, Sweden, and Pakistan. Four antibiotic resistant genes were identified as responsible for increased cefiderocol minimum inhibitory concentrations to clinically-relevant levels (ranging from 1 to 4 mg/l), including ꞵ-lactamases (VEB-3, OXA-372 homolog, and YbxI homolog) and a partial penicillin-binding protein homolog. None of these genes had been previously reported as a cefiderocol resistance gene. Three out of four had their closest homologs in pathogenic bacteria. The blaVEB-3 gene was associated with a mobile genetic element and distributed across all wastewater metagenomes analyzed in this study. We therefore highlight the critical need for functional metagenomics, to characterize previously uncharacterized last-line antibiotic resistance mechanisms which will be used to enrich antibiotic resistance gene databases and thereby improving antibiotic resistance surveillance in all One Health compartments.

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