ESBL Displace: A Protocol for an Observational Study to Identify Displacing Escherichia coli Strain Candidates from ESBL-Colonized Travel Returners Using Phenotypic, Genomic Sequencing and Metagenome Analysis

Abstract

Introduction: Invading extended-spectrum beta-lactamase-producing Escherichia coli (ESBL-PE), non-ESBL E. coli, and other bacteria form a complex environment in the gut. The duration and dynamics of ESBL-PE colonization varies among individuals. Understanding the factors associated with colonization may lead to decolonization strategies. In this study, we aim to identify (i) single E. coli strains and (ii) microbiome networks that correlate with retention or decline of colonization, and (iii) pan-sensitive E. coli strains that potentially could be used to displace ESBL-PE during colonization. Methods and analysis: We recruit healthy travellers to Southeast Asia for a one-year prospective observational follow-up study. We collect and biobank stool, serum, and peripheral blood mononuclear cells (PBMCs) at predefined timepoints. Additional information is collected with questionnaires. We determine the colonization status with ESBL-PE and non-ESBL E. coli and quantify cell densities in stools and ratios over time. We characterize multiple single bacterial isolates per patient and timepoint using whole genome sequencing (WGS) and 16S/ITS amplicon-based and shotgun metagenomics. We determine phylogenetic relationships between isolates, antimicrobial resistance (AMR; phenotypic and genotypic), and virulence genes. We describe the bacterial and fungal stool microbiome alpha and beta diversity on 16S/ITS metagenomic data. We describe patterns in microbiome dynamics to identify features associated with protection or risk of ESBL-PE colonization. Ethics and dissemination: The study is registered (clinicaltrials.gov; NCT04764500 on 09/02/2019) and approved by the Ethics Committee (EKNZ project ID 2019-00044). We will present anonymized results at conferences and in scientific journals. Bacterial sequencing data will be shared via publicly accessible databases according to FAIR principles.