| Title: |
CefiderocolFinder:a tool for detecting genetic adaptations implicated in cefiderocol resistance |
| Authors: |
van den Brand,Bryan; Notermans,Daan W; Verkaik,Nelianne J; Lansu,Simon; Rossen,John W A; Hendrickx, Antoni P A; van Arkel,A L E; Leversteijn-van Hall,M A; van den Bijllaardt,W; van Mansfeld,R; van Dijk,K; Zwart,B; Diederen,B M W; Berkhout,H; Ott,A; Waar,K; Ang,W; da Silva,J; Vlek,A L M; Stohr,J J J M; Bode,L G M; Jansz,A; Paltansing,S; van Griethuysen,A J; Lo Ten Foe,J R; van Trijp,M J C A; Wong,M; Muller,A E; van der Linden,M P M; van Rijn,M; Debast,S B; Kolwijck,E; Al Naiemi,N; Schulin,T; Dinant,S; van Mens,S P; Melles,D C; Stuart, J W T Cohen; Gruteke,P; van Dam,A P; Rahamat-Langendoen,J; Maraha,B; Sinnige, J C; van der Vorm,E; de Graaf,M; de Jong,E; Heikens,E; Troelstra, A; de Vries,J; van Dam,D W; Dutch CPE surveillance Study Group; MMB Infectiepreventie; Infection & Immunity |
| Publication Year: |
2026 |
| Subject Terms: |
Journal Article |
| Description: |
OBJECTIVES: Cefiderocol is a novel last-resort cephalosporin antimicrobial increasingly used for difficult-to-treat infections by multidrug-resistant microorganisms (MDRO), and is effective against carbapenem-resistant Enterobacterales and Pseudomonas species. Multiple chromosomally encoded genetic determinants have been implicated in cefiderocol resistance, including mutations, deletions and/or frameshifts. However, identification of these determinants remains labour-intensive and time-consuming. Therefore, we share CefiderocolFinder, a bioinformatics pipeline to detect 25 genetic adaptations implicated in cefiderocol resistance from short-read whole genome sequencing (WGS) data. METHODS: CefiderocolFinder was built using Python, supports WGS data of Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii, and contains alignment, variant calling, annotation and filtering steps. A short-read WGS dataset (n=98) and validation WGS dataset (n=21) with cefiderocol antimicrobial susceptibility testing (AST) results was used to interpret and validate CefiderocolFinder. RESULTS: Using CefiderocolFinder, with WGS data from 98 MDRO collected from Ukrainian patients in 2022, six unique genetic adaptations were detected. These adaptations were associated with higher MICs in AST with cefiderocol. Loss of function mutations were found in the siderophore receptor cirA, the general porins oprD, ompC, ompF, negative regulator of the acrAB-tolC efflux operon acrR and a conservative in-frame insertion YRIN in ftsI encoding for Penicillin-binding protein 3. The adaptations were identified in 12 of 16 E. coli (75%), 1 of 60 K. pneumoniae (1%), 6 of 17 P. aeruginosa (35%) and 0 of 5 A. baumannii (0%) isolates. CefiderocolFinder was validated using publicly available datasets. CONCLUSIONS: CefiderocolFinder provides context to corroborate phenotypical AST from WGS data, especially when the result is in an area of technical uncertainty. For E. coli, CefiderocolFinder can be a valuable tool for ... |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
English |
| ISSN: |
1198-743X |
| Relation: |
https://dspace.library.uu.nl/handle/1874/483755 |
| Availability: |
https://dspace.library.uu.nl/handle/1874/483755 |
| Rights: |
info:eu-repo/semantics/OpenAccess |
| Accession Number: |
edsbas.13DE9E02 |
| Database: |
BASE |