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

Abstract

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.

Keywords: Antimicrobial resistance; Core-resistome; Emerging resistance genes; Metagenomics; Pan-resistome.

Fig. 1

Principal component analysis of the abundance of A latent and B established ARGs. Aquatic includes samples from fresh, lentic, and marine water; Plants includes rhizosphere samples; Infants include samples from their digestive system; Wastewater includes activated sludge, water and sludge, fecal source, and raw wastewater; Terrestrial includes soil samples; Human includes samples from the skin, digestive and respiratory systems; Birds includes samples from their digestive system; and Mammals includes samples from the digestive systems of bovines, mice, and pigs. The analysis was based on log-transformed ARG abundance using all metagenomic samples but a maximum of 400 per environment are shown. The ellipses are calculated based on a multivariate t-distribution at a 75% confidence level. Latent ARGs were in general more diverse than established ARGs and showed less overlap especially for the aquatic, terrestrial, and plant environments

Fig. 2

Distribution of the A relative abundance and B $\alpha$-diversity for latent and established ARGs. Distribution of the log-transformed abundance and $\alpha$-diversity per gene class. The colors indicate antibiotic type with higher opacity for latent ARGs and higher transparency for established ARGs. RPG is short for ribosomal protection gene

Fig. 3

Relative abundance of latent and established ARGs divided per gene class and environment. Each gene class is represented by two rows: L for latent and E for established. The labels Birds, Bovines, Mice, Pigs, Humans, and Infants denote metagenomes from the corresponding digestive system. Respiratory system and skin only include human samples. The color intensity reflects the gene- and environment-specific relative abundance, which was calculated based on the median of the relative log-transform abundance over all samples from the environment. To make the genes comparable, all values were normalized based on the environment with the highest abundance. RPG is short for ribosomal protection gene

Fig. 4

Pan-resistomes and core-resistomes. The length of the left and right bars describe the size of the pan- and core-resistome, respectively. The pan-resistome includes all genes encountered in at least one sample from the environment, and the core-resistome includes all genes that were commonly encountered (at least 50% of the samples). The colors indicate antibiotic type with higher opacity for latent ARGs and higher transparency for established ARGs. The computations were done based on rarefied metagenomes that, for each environment, were repeatedly subsampled down to 100 samples. The figure shows the average number of genes over all 100 samples. The labels Birds, Bovines, Mice, Pigs, Humans, and Infants denote metagenomes from the corresponding digestive system. Respiratory system and skin only include human samples

Fig. 5

Core-resistome overlap between environments. a Networks where nodes represent environments with their node size proportional to the size of the environment’s core-resistome. The width of the edge is proportional to the number of core-resistome ARGs shared between two environments. Only overlaps of at least five ARGs are shown. b The heatmaps show the number of core-resistome ARGs shared between two environments for each antibiotic type. The labels Birds, Bovines, Mice, Pigs, Humans, and Infants denote metagenomes from the corresponding digestive system. Respiratory system and skin only include human samples. Qnr is an abbreviation for quinolone resistance