Molecular Medicine Israel

Duplicated antibiotic resistance genes reveal ongoing selection and horizontal gene transfer in bacteria


Horizontal gene transfer (HGT) and gene duplication are often considered as separate mechanisms driving the evolution of new functions. However, the mobile genetic elements (MGEs) implicated in HGT can copy themselves, so positive selection on MGEs could drive gene duplications. Here, we use a combination of modeling and experimental evolution to examine this hypothesis and use long-read genome sequences of tens of thousands of bacterial isolates to examine its generality in nature. Modeling and experiments show that antibiotic selection can drive the evolution of duplicated antibiotic resistance genes (ARGs) through MGE transposition. A key implication is that duplicated ARGs should be enriched in environments associated with antibiotic use. To test this, we examined the distribution of duplicated ARGs in 18,938 complete bacterial genomes with ecological metadata. Duplicated ARGs are highly enriched in bacteria isolated from humans and livestock. Duplicated ARGs are further enriched in an independent set of 321 antibiotic-resistant clinical isolates. Our findings indicate that duplicated genes often encode functions undergoing positive selection and horizontal gene transfer in microbial communities.


Selection for higher gene expression can promote the rapid evolution of duplicated genes through diverse molecular mechanisms1,2,3,4,5. Furthermore, gene duplication has long been recognized as a crucial step in the evolution of new functions and traits1,6,7. For these reasons, gene duplication is an important evolutionary mechanism for rapid adaptation to novel metabolic and ecological niches8,9,10,11,12. Recently duplicated and thus functionally redundant genes often revert to a single-copy state in the absence of selection13, suggesting that selection is required to maintain duplicated genes. Indeed, selection for strong gene expression is a key factor for the preservation of duplicated antibiotic resistance genes (ARGs) on plasmids14. In addition, recent metagenomic studies indicate that copy number variation in the human microbiome is common and influences human health15,16.

Laboratory experiments have demonstrated that positive selection can drive the rapid evolution of gene duplications, due to the rapid kinetics of molecular mechanisms like tandem amplifications4,17. While several studies have examined tandem duplications and gene amplifications under laboratory selection for drug resistance3,18,19,20 or specific metabolic functions8,9,11, few studies have examined the role of mobile genetic elements (MGEs) in promoting gene duplications.

Following Partridge et al. 21, we define MGEs as “elements that promote intracellular DNA mobility (e.g., from the chromosome to a plasmid or between plasmids) as well as those that enable intercellular DNA mobility”. In our experiments, we focus on transposons and plasmids, which are known to mediate the horizontal transfer of ARGs in microbial communities5,22. Our bioinformatics analyses more broadly examine genes encoding MGE components, including genes involved in transposon, integrase, bacteriophage, and plasmid functions.

Previously, we showed that antibiotics select for the movement of transposable ARGs from chromosomes onto multicopy plasmids, because the increased copy number of ARGs on multicopy plasmids leads to higher expression of those genes and thus higher resistance5. Based on those findings, we reasoned that antibiotic selection would also favor duplications of ARGs, generated by intrachromosomal transposition events. We tested this hypothesis using mathematical modeling, experimental evolution, and genome sequencing to confirm the location and copy number of transposable ARGs in evolved populations.

Based on these experimental findings, we reasoned that antibiotic use should enrich specific populations of bacteria with duplicated ARGs. Several recent studies have reported cases of gene duplications in clinical antibiotic-resistant isolates, using long-read sequencing or qPCR to measure resistance gene copy number23,24,25,26,27,28,29,30,31,32,33. However, it is not known whether these cases represent a broader trend. To address this question, we examined the distribution of duplicated genes in tens of thousands of complete bacterial genomes that were sequenced with long-read sequencing technologies.

To date, few studies have systematically examined duplicated genes in bacterial genomes34, due to the difficulty of resolving identical sequence repeats with second-generation short-read sequencing technologies35. Such sequence repeats facilitate gene duplication2, but also hamper their discovery by short-read sequencing, due to read alignment inaccuracies36. These issues also plague genome assembly from complex metagenomic samples37. Long-read sequencing is critical because long reads can span repeat regions, including transposons and duplicated genes. This resolves ambiguities in copy number variation, including the coexistence of plasmids, in a given isolate or metagenomic sample35,38.

Here, by combining modeling, experiments, and bioinformatic analyses, we show that MGEs serve as potent drivers of gene duplications, that gene duplications mediated by MGEs are often adaptive, that duplicated ARGs are enriched in isolates from humans and livestock (the microbial environments most associated with antibiotic use), that duplicated ARGs are further enriched in clinical antibiotic-resistant isolates, and that duplicated ARGs are far more likely to be associated with MGEs than single-copy ARGs. These findings indicate that duplicated genes often encode functions undergoing positive selection and horizontal gene transfer in microbial communities.


Antibiotics select for duplicated ARGs

Our basic intuition is that mutants with a duplicated ARG can invade an ancestral clonal population with a single-copy resistance gene, given a sufficiently high concentration of antibiotic. To formalize this idea, we built a mathematical model (Fig. 1A, Supplementary Data 1) based on the framework in our previous study5. This model involves three subpopulations of bacteria: the first carries an ARG on the chromosome (Type 1), the second has a duplicated ARG on the chromosome (Type 2), and the third carries a duplicated ARG on a plasmid (Type 3). The ARG confers a fitness benefit in the presence of antibiotics due to resistance, and additional copies confer stronger resistance. However, the additional copies may incur a fitness cost in the absence of antibiotic. We assume that all cells contain a plasmid. By letting the copy number of the plasmid be a free parameter of the model, we can also model the no plasmid case (plasmid copy number = 0). The fitness of each population therefore depends on antibiotic concentration, the cost of ARG expression, and the effective number of ARG copies per cell in each subpopulation, which depends on plasmid copy number (Methods: Mathematical model: Fitness functions).

Under antibiotic selection, one of the subpopulations with the additional ARG copy rapidly outcompetes the others, depending on which has the highest fitness. When the cost of expressing additional ARG copies is low, then the Type 3 subpopulation, which contains duplicated ARGs on the plasmid, dominates (Fig. 1B). When the cost of expressing the ARG on the plasmid outweighs the benefit of resistance, the Type 2 subpopulation, which contains duplicated ARGs on the chromosome, dominates (Supplementary Data 1). By defining a “Duplication Index” as the fraction of the population with a duplicated ARG, we find that duplicated ARGs rapidly establish throughout the population at a threshold antibiotic concentration. As the cost of ARG expression increases, this threshold concentration increases. This is shown by the rightward shift of curves representing higher ARG expression costs in Fig. 1C. In addition, as the transposition rate of the transposable ARG increases, the time for establishment of duplicated ARGs in the population decreases, as shown by a leftward shift of curves representing higher transposition rates in Fig. 1D. Furthermore, the model shows that for any given ARG expression cost, duplicated ARGs will establish in the population when both the transposition rate and antibiotic concentration are sufficiently high (Fig. 1E). Altogether, these results highlight what the dynamics of antibiotic selection and ARG duplication could look like, and illustrate a basic model that can be tested experimentally.

We tested the core prediction of this model— that antibiotics select for duplicated ARGs— by carrying out evolution experiments with E. coli strains harboring a minimal transposon composed of a tetA tetracycline resistance gene flanked by 19-base-pair terminal repeats. This mini-transposon is mobilized by an external Tn5 transposase in the chromosome39. We carried out 9-day selection experiments with E. coli DH5α and sequenced populations resistant to 50 μg/mL tetracycline, varying plasmid, the presence of active transposase, and the basal expression of the tetA resistance gene. We also evolved and sequenced a parallel set of control populations that were propagated without tetracycline (Supplementary Data 2). Multiple transpositions of the tetA-Tn5 transposon to both chromosome and plasmid are observed in the presence of active transposase. In the absence of active transposase, we see parallel mutations affecting the tetA promoter and the native efflux pump regulatory genes robAmarR and acrR (Fig. 1F). By contrast, no gene duplications were observed in the no-antibiotic control populations, nor was any parallel evolution observed (Supplementary Data 2). This finding implies that tetracycline treatment selected for the tetA duplications and the other resistance mutations observed across replicate populations (Fig. 1F).

Given this finding, we asked whether duplications could arise as a short-term evolutionary response, in a wild-type K-12 MG1655 genetic background. Given the high activity of the synthetic tetA-Tn5 transposon, one day of tetracycline selection ( ~ 10 bacterial generations) was sufficient to drive duplications of the tetracycline resistance gene to observable allele frequencies across all replicate populations, both in the presence and absence of plasmids (Fig. 2A). By contrast, no duplications were observed in the no-antibiotic control populations (Figure 2A, B, C, D). No tetA duplications were observed in the absence of transposase, although gene amplifications of the native acrAB antibiotic efflux pump were seen (Fig. 2D). Since no tetA duplications or other resistance mutations were observed in the no-antibiotic control treatment (Supplementary Data 2), we infer that tetracycline treatment directly selected for the observed tetA duplications, acrAB amplifications, and other resistance mutations. We then replaced the tetA gene in the minimal Tn5 transposon with smRkanRampR, and cmR genes conferring resistance to spectinomycin, kanamycin, carbenicillin, and chloramphenicol, and repeated our one-day selection experiment using these four antibiotics. ARG duplications were observed in 8 out of 8 evolved populations, across all four antibiotic treatments (Supplementary Fig. 1). Together, the mathematical model and these evolution experiments demonstrate the that antibiotic selection can drive the evolution of duplicated ARGs via intragenomic transposition….

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