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

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

Macrolides are broad-spectrum antibiotics used to treat a range of infections. Resistance to macrolides is often conferred by mobile resistance genes encoding Erm methyltransferases or Mph phosphotransferases. New erm and mph genes keep being discovered in clinical settings but their origins remain unknown, as is the type of macrolide resistance genes that will appear in the future. In this study, we used optimized hidden Markov models to characterize the macrolide resistome. Over 16 terabases of genomic and metagenomic data, representing a large taxonomic diversity (11 030 species) and diverse environments (1944 metagenomic samples), were searched for the presence of erm and mph genes. From this data, we predicted 28 340 macrolide resistance genes encoding 2892 unique protein sequences, which were clustered into 663 gene families (<70 % amino acid identity), of which 619 (94 %) were previously uncharacterized. This included six new resistance gene families, which were located on mobile genetic elements in pathogens. The function of ten predicted new resistance genes were experimentally validated in Escherichia coli using a growth assay. Among the ten tested genes, seven conferred increased resistance to erythromycin, with five genes additionally conferring increased resistance to azithromycin, showing that our models can be used to predict new functional resistance genes. Our analysis also showed that macrolide resistance genes have diverse origins and have transferred horizontally over large phylogenetic distances into human pathogens. This study expands the known macrolide resistome more than ten-fold, provides insights into its evolution, and demonstrates how computational screening can identify new resistance genes before they become a significant clinical problem

Clinical peripheral enthesitis in the DESIR prospective longitudinal axial spondyloarthritis cohort

Objectives: We aimed to describe the prevalence and characteristics of peripheral enthesitis in recent onset axial spondyloarthritis, estimate the incidence of peripheral enthesitis over time, and determine the factors associated with the presence of peripheral enthesitis. Methods: 708 patients with recent onset axial spondyloarthritis were enrolled in the DESIR cohort ( prospective multi-centre, longitudinal). Data regarding the patients and spondyloarthritis characteristics at baseline with a specific focus on enthesitis and occurrence of peripheral enthesitis were collected during the five years of follow-up. Results: At inclusion, 395 patients (55.8%) reported peripheral enthesitis. The locations were mainly the plantar fascia (53.7%) and the Achilles tendon (38.5%). During the 5-year follow-up period, 109 additional patients developed peripheral enthesitis resulting in an estimated (Kaplan-Meier method) percentage of 71% (95% CI: 68-75). Variables associated with peripheral enthesitis in the univariate analysis were: older age, male gender, absence of HLA B27, MRI sacroiliitis and fulfilled Modified NY criteria, presence of anterior chest wall pain, peripheral arthritis, dactylitis, psoriasis, high BASDAI, BASFI, mean score ASAS-and the use of NSAIDs. Only the history of anterior chest wall pain and of peripheral arthritis were retained in the multivariate analysis (odds ratio (OR)=1.6 [95% confidence interval [1.1-2.3], and OR=2.1 [1.4-3.0], respectively)