Abstract
Acute bacterial infections are often treated empirically, with the choice of antibiotic therapy updated during treatment. The effects of such rapid antibiotic switching on the evolution of antibiotic resistance in individual patients are poorly understood. Here we find that low-frequency antibiotic resistance mutations emerge, contract, and even go to extinction within days of changes in therapy. We analyzed Pseudomonas aeruginosa populations in sputum samples collected serially from 7 mechanically ventilated patients at the onset of respiratory infection. Combining short- and long-read sequencing and resistance phenotyping of 420 isolates revealed that while new infections are near-clonal, reflecting a recent colonization bottleneck, resistance mutations could emerge at low frequencies within days of therapy. We then measured the in vivo frequencies of select resistance mutations in intact sputum samples with resistance-targeted deep amplicon sequencing (RETRA-Seq), which revealed that rare resistance mutations not detected by clinically used culture-based methods can increase by nearly 40-fold over 5–12 days in response to antibiotic changes. Conversely, mutations conferring resistance to antibiotics not administered diminish and even go to extinction. Our results underscore how therapy choice shapes the dynamics of low-frequency resistance mutations at short time scales, and the findings provide a possibility for driving resistance mutations to extinction during early stages of infection by designing patient-specific antibiotic cycling strategies informed by deep genomic surveillance.
Highlights
Acute bacterial infections are often treated empirically, with the choice of antibiotic therapy updated during treatment
After confirming population growth and detectable diversity, we focused on studying short-term infection dynamics in 7 patients whose serial samples were collected 4–11 days after day 1 and exhibited P. aeruginosa growth at both time points as the predominant pathogen (Fig. 1b; Supplementary Fig. 1; Methods; Supplementary Table 1)
Our study shows that the frequencies of resistance mutations change rapidly with antibiotic therapy, highlighting a potential for deep sequencing-guided, short-term cycling of antibiotics within patients as a possible future therapeutic strategy
Summary
Acute bacterial infections are often treated empirically, with the choice of antibiotic therapy updated during treatment. Our results underscore how therapy choice shapes the dynamics of low-frequency resistance mutations at short time scales, and the findings provide a possibility for driving resistance mutations to extinction during early stages of infection by designing patientspecific antibiotic cycling strategies informed by deep genomic surveillance. The selection of resistance mutations during chronic infections as a result of antibiotic treatment over months to years is well-known[2–9] It is not well-understood how short-term changes in antibiotic therapy affect the dynamics of resistance mutations in acute infections, especially in a newly colonizing infection that is thought to start from a clonal population[10]. While molecular surveillance methods such as rapid PCR tests and real-time genome sequencing can identify the presence of known resistance genes[28–31], e.g., efflux pumps, to identify resistant strains, they are not suitable for monitoring withinpopulation pathogen diversity It is not wellunderstood whether resistance mutations can contract and be reversed during the course of treatment in acute infections. We relate how changes in empirically administered antibiotics impact resistance in individual patients, and discover that resistance mutation frequencies change within days, depending on the duration and type of antibiotic therapy
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