Clinical Resistome Screening of 1,110 Escherichia coli Isolates Efficiently Recovers Diagnostically Relevant Antibiotic Resistance Biomarkers and Potential Novel Resistance Mechanisms

Multidrug-resistant pathogens represent one of the biggest global healthcare challenges. Molecular diagnostics can guide effective antibiotics therapy but relies on validated, predictive biomarkers. Here we present a novel, universally applicable workflow for rapid identification of antimicrobial resistance (AMR) biomarkers from clinical Escherichia coli isolates and quantitatively evaluate the potential to recover causal biomarkers for observed resistance phenotypes. For this, a metagenomic plasmid library from 1,110 clinical E. coli isolates was created and used for high-throughput screening to identify biomarker candidates against Tobramycin (TOB), Ciprofloxacin (CIP), and Trimethoprim Sulfamethoxazole (TMP-SMX). Identified candidates were further validated in vitro and also evaluated in silico for their diagnostic performance based on matched genotype phenotype data. AMR biomarkers recovered by the metagenomics screening approach mechanistically explained 77% of observed resistance phenotypes for Tobramycin, 76% for Trimethoprim-Sulfamethoxazole, and 20% Ciprofloxacin. Sensitivity for Ciprofloxacin resistance detection could be improved to 97% by complementing results with AMR biomarkers that are undiscoverable due to intrinsic limitations of the workflow. Additionally, when combined in a multiplex diagnostic in silico panel, the identified AMR biomarkers reached promising positive and negative predictive values of up to 97 and 99%, respectively. Finally, we demonstrate that the developed workflow can be used to identify potential novel resistance mechanisms

Clinical Resistome Screening of 1,110 Escherichia coli Isolates Efficiently Recovers Diagnostically Relevant Antibiotic Resistance Biomarkers and Potential Novel Resistance Mechanisms.

Multidrug-resistant pathogens represent one of the biggest global healthcare challenges. Molecular diagnostics can guide effective antibiotics therapy but relies on validated, predictive biomarkers. Here we present a novel, universally applicable workflow for rapid identification of antimicrobial resistance (AMR) biomarkers from clinical Escherichia coli isolates and quantitatively evaluate the potential to recover causal biomarkers for observed resistance phenotypes. For this, a metagenomic plasmid library from 1,110 clinical E. coli isolates was created and used for high-throughput screening to identify biomarker candidates against Tobramycin (TOB), Ciprofloxacin (CIP), and Trimethoprim-Sulfamethoxazole (TMP-SMX). Identified candidates were further validated in vitro and also evaluated in silico for their diagnostic performance based on matched genotype-phenotype data. AMR biomarkers recovered by the metagenomics screening approach mechanistically explained 77% of observed resistance phenotypes for Tobramycin, 76% for Trimethoprim-Sulfamethoxazole, and 20% Ciprofloxacin. Sensitivity for Ciprofloxacin resistance detection could be improved to 97% by complementing results with AMR biomarkers that are undiscoverable due to intrinsic limitations of the workflow. Additionally, when combined in a multiplex diagnostic in silico panel, the identified AMR biomarkers reached promising positive and negative predictive values of up to 97 and 99%, respectively. Finally, we demonstrate that the developed workflow can be used to identify potential novel resistance mechanisms

Connexin43-dependent mechanism modulates renin secretion and hypertension

To investigate the function of Cx43 during hypertension, we studied the mouse line Cx43KI32 (KI32), in which the coding region of Cx32 replaces that of Cx43. Within the kidneys of homozygous KI32 mice, Cx32 was expressed in cortical and medullary tubules, as well as in some extra- and intraglomerular vessels, i.e., at sites where Cx32 and Cx43 are found in WT mice. Under such conditions, renin expression was much reduced compared with that observed in the kidneys of WT and heterozygous KI32 littermates. After exposure to a high-salt diet, all mice retained a normal blood pressure. However, whereas the levels of renin were significantly reduced in the kidneys of WT and heterozygous KI32 mice, reaching levels comparable to those observed in homozygous littermates, they were not further affected in the latter animals. Four weeks after the clipping of a renal artery (the 2-kidney, 1-clip [2K1C] model), 2K1C WT and heterozygous mice showed an increase in blood pressure and in the circulating levels of renin, whereas 2K1C homozygous littermates remained normotensive and showed unchanged plasma renin activity. Hypertensive, but not normotensive, mice also developed cardiac hypertrophy. The data indicate that replacement of Cx43 by Cx32 is associated with decreased expression and secretion of renin, thus preventing the renin-dependent hypertension that is normally induced in the 2K1C model

Integrating Culture-based Antibiotic Resistance Profiles with Whole-genome Sequencing Data for 11,087 Clinical Isolates.

Emergingantibiotic resistanceis a major global health threat. The analysis of nucleic acidsequences linked to susceptibility phenotypes facilitates the study of genetic antibiotic resistancedeterminants to inform molecular diagnostics and drug development. We collected genetic data(11,087 newly-sequenced whole genomes) and culture-based resistance profiles (10,991 out of the11,087 isolates comprehensively tested against 22 antibiotics in total) of clinical isolates including18 main species spanning a time period of 30 years. Species and drug specific resistance patternswere observed including increased resistance rates forAcinetobacter baumanniito carbapenemsand forEscherichia colito fluoroquinolones. Species-levelpan-genomeswere constructed to reflectthe genetic repertoire of the respective species, including conserved essential genes and known resis-tance factors. Integrating phenotypes and genotypes through species-level pan-genomes allowed toinfer gene–drug resistance associations using statistical testing. The isolate collection and the analysis results have been integrated into GEAR-base, a resource available for academic research use free of charge athttps://gear-base.co