Large-scale characterization of the macrolide resistome reveals high diversity and several new pathogen-associated genes

Azithromycin resistance in Escherichia coli and Salmonella from food-producing animals and meat in Europe

OBJECTIVES

To characterize the genetic basis of azithromycin resistance in Escherichia coli and Salmonella collected within the EU harmonized antimicrobial resistance (AMR) surveillance programme in 2014-18 and the Danish AMR surveillance programme in 2016-19.

METHODS

WGS data of 1007 E. coli [165 azithromycin resistant (MIC > 16 mg/L)] and 269 Salmonella [29 azithromycin resistant (MIC > 16 mg/L)] were screened for acquired macrolide resistance genes and mutations in rplDV, 23S rRNA and acrB genes using ResFinder v4.0, AMRFinder Plus and custom scripts. Genotype-phenotype concordance was determined for all isolates. Transferability of mef(C)-mph(G)-carrying plasmids was assessed by conjugation experiments.

RESULTS

mph(A), mph(B), mef(B), erm(B) and mef(C)-mph(G) were detected in E. coli and Salmonella, whereas erm(C), erm(42), ere(A) and mph(E)-msr(E) were detected in E. coli only. The presence of macrolide resistance genes, alone or in combination, was concordant with the azithromycin-resistant phenotype in 69% of isolates. Distinct mph(A) operon structures were observed in azithromycin-susceptible (n = 50) and -resistant (n = 136) isolates. mef(C)-mph(G) were detected in porcine and bovine E. coli and in porcine Salmonella enterica serovar Derby and Salmonella enterica 1,4, [5],12:i:-, flanked downstream by ISCR2 or TnAs1 and associated with IncIγ and IncFII plasmids.

CONCLUSIONS

Diverse azithromycin resistance genes were detected in E. coli and Salmonella from food-producing animals and meat in Europe. Azithromycin resistance genes mef(C)-mph(G) and erm(42) appear to be emerging primarily in porcine E. coli isolates. The identification of distinct mph(A) operon structures in susceptible and resistant isolates increases the predictive power of WGS-based methods for in silico detection of azithromycin resistance in Enterobacterales.

Extensive screening reveals previously undiscovered aminoglycoside resistance genes in human pathogens

Antibiotic resistance is a growing threat to human health, caused in part by pathogens accumulating antibiotic resistance genes (ARGs) through horizontal gene transfer. New ARGs are typically not recognized until they have become widely disseminated, which limits our ability to reduce their spread. In this study, we use large-scale computational screening of bacterial genomes to identify previously undiscovered mobile ARGs in pathogens. From ~1 million genomes, we predict 1,071,815 genes encoding 34,053 unique aminoglycoside-modifying enzymes (AMEs). These cluster into 7,612 families (<70% amino acid identity) of which 88 are previously described. Fifty new AME families are associated with mobile genetic elements and pathogenic hosts. From these, 24 of 28 experimentally tested AMEs confer resistance to aminoglycoside(s) in Escherichia coli, with 17 providing resistance above clinical breakpoints. This study greatly expands the range of clinically relevant aminoglycoside resistance determinants and demonstrates that computational methods enable early discovery of potentially emerging ARGs.

Evidence for wastewaters as environments where mobile antibiotic resistance genes emerge

The emergence and spread of mobile antibiotic resistance genes (ARGs) in pathogens have become a serious threat to global health. Still little is known about where ARGs gain mobility in the first place. Here, we aimed to collect evidence indicating where such initial mobilization events of clinically relevant ARGs may have occurred. We found that the majority of previously identified origin species did not carry the mobilizing elements that likely enabled intracellular mobility of the ARGs, suggesting a necessary interplay between different bacteria. Analyses of a broad range of metagenomes revealed that wastewaters and wastewater-impacted environments had by far the highest abundance of both origin species and corresponding mobilizing elements. Most origin species were only occasionally detected in other environments. Co-occurrence of origin species and corresponding mobilizing elements were rare in human microbiota. Our results identify wastewaters and wastewater-impacted environments as plausible arenas for the initial mobilization of resistance genes.

Latent antibiotic resistance genes are abundant, diverse, and mobile in human, animal, and environmental microbiomes

BACKGROUND

Bacterial communities in humans, animals, and the external environment maintain a large collection of antibiotic resistance genes (ARGs). However, few of these ARGs are well-characterized and thus established in existing resistance gene databases. In contrast, the remaining latent ARGs are typically unknown and overlooked in most sequencing-based studies. Our view of the resistome and its diversity is therefore incomplete, which hampers our ability to assess risk for promotion and spread of yet undiscovered resistance determinants.

RESULTS

A reference database consisting of both established and latent ARGs (ARGs not present in current resistance gene repositories) was created. By analyzing more than 10,000 metagenomic samples, we showed that latent ARGs were more abundant and diverse than established ARGs in all studied environments, including the human- and animal-associated microbiomes. The pan-resistomes, i.e., all ARGs present in an environment, were heavily dominated by latent ARGs. In comparison, the core-resistome, i.e., ARGs that were commonly encountered, comprised both latent and established ARGs. We identified several latent ARGs shared between environments and/or present in human pathogens. Context analysis of these genes showed that they were located on mobile genetic elements, including conjugative elements. We, furthermore, identified that wastewater microbiomes had a surprisingly large pan- and core-resistome, which makes it a potentially high-risk environment for the mobilization and promotion of latent ARGs.

CONCLUSIONS

Our results show that latent ARGs are ubiquitously present in all environments and constitute a diverse reservoir from which new resistance determinants can be recruited to pathogens. Several latent ARGs already had high mobile potential and were present in human pathogens, suggesting that they may constitute emerging threats to human health. We conclude that the full resistome-including both latent and established ARGs-needs to be considered to properly assess the risks associated with antibiotic selection pressures. Video Abstract.

Demonstrating a Comprehensive Wastewater-Based Surveillance Approach That Differentiates Globally Sourced Resistomes

Wastewater-based surveillance (WBS) for disease monitoring is highly promising but requires consistent methodologies that incorporate predetermined objectives, targets, and metrics. Herein, we describe a comprehensive metagenomics-based approach for global surveillance of antibiotic resistance in sewage that enables assessment of 1) which antibiotic resistance genes (ARGs) are shared across regions/communities; 2) which ARGs are discriminatory; and 3) factors associated with overall trends in ARGs, such as antibiotic concentrations. Across an internationally sourced transect of sewage samples collected using a centralized, standardized protocol, ARG relative abundances (16S rRNA gene-normalized) were highest in Hong Kong and India and lowest in Sweden and Switzerland, reflecting national policy, measured antibiotic concentrations, and metal resistance genes. Asian versus European/US resistomes were distinct, with macrolide-lincosamide-streptogramin, phenicol, quinolone, and tetracycline versus multidrug resistance ARGs being discriminatory, respectively. Regional trends in measured antibiotic concentrations differed from trends expected from public sales data. This could reflect unaccounted uses, captured only by the WBS approach. If properly benchmarked, antibiotic WBS might complement public sales and consumption statistics in the future. The WBS approach defined herein demonstrates multisite comparability and sensitivity to local/regional factors.