Re-visiting the potential impact of doxycycline post-exposure prophylaxis (doxy-PEP) on the selection of doxycycline resistance in Neisseria commensals
Robinson, L. R.; McDevitt, C. J.; Regan, M. R.; Quail, S. L.; Swartz, M. E.; Wadsworth, C. B.
Show abstract
Doxycycline post-exposure prophylaxis (doxy-PEP) is a preventative strategy demonstrated to reduce bacterial sexually transmitted infections in high-risk populations. However, the impact of doxy-PEP on antibiotic resistance acquisition in key members of our microbiomes, is as of yet unclear. For example, commensal Neisseria are known reservoirs of resistance for gonococci through horizontal gene transfer (HGT), and are more likely to experience bystander selection due to doxy-PEP as they are universally carried. Thus, the consequences of doxycycline selection on commensal Neisseria will be critical to investigate to understand possible resistance mechanisms that may be transferred to an important human pathogen. Here, we use in vitro antibiotic gradients to evolve four Neisseria commensals (N. cinerea, N. canis, N. elongata, and N. subflava, n=4 per species) across a 20-day time course; and use whole genome sequencing to nominate derived mutations. After selection, 12 of 16 replicates evolved doxycycline resistance (> 1 g/mL). Across resistant lineages: An A46T substitution in the repressor of the Mtr efflux pump (MtrR) and a V57M substitution in the 30 ribosomal protein S10 were clearly associated with elevated MICs. Additional mutations in ribosomal components also emerged in strains with high MICs (i.e., 16S rRNA G1057C, RplX A14T). We find the MtrR 46T, RpsJ 57M, and RplX 14T circulating in natural commensal populations. Furthermore, in vitro co-evolution of N. gonorrhoeae with Neisseria commensals demonstrated rapid transfer of the pConj plasmid to N. subflava and N. cinerea, and pbla to N. cinerea. Finally, collection of novel commensals from human hosts reveals 46% of isolates carrying doxycycline resistance; and doxycycline resistance was significantly greater in participants self-reporting doxycycline use in the past 6 months. High-level doxycycline resistance (> 8 g/mL) was always associated with carriage of the ribosomal protection protein (tetM) and pConj. Ultimately, characterizing the contemporary prevalence of doxycycline resistance, and underlying resistance mechanisms, in commensal communities may help us to predict the long-term impact of doxy-PEP on Neisseria, and the likelihood of transferring particular genotypes across species boundaries.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- The Intra-Host Evolutionary Landscape And Pathoadaptation Of Persistent Staphylococcus aureus In Chronic Rhinosinusitis 94%
- Enterococcus faecium genome dynamics during long-term asymptomatic patient gut colonization 94%
- Hospital outbreak of carbapenem-resistant Enterobacteriales associated with an OXA-48 plasmid carried mostly by Escherichia coli ST399 94%
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- Prevalence of antimicrobial resistance phenotypes and genes in stable fly- and manure-derived bacterial isolates from clinically relevant taxa in dairy settings 94%
- Predicting clinical phage therapy outcomes in vitro: results using mixed versus single isolates from an MRSA case study 92%
- An evaluation of screening methods for the detection of extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella pneumoniae in environmental samples from healthcare settings 90%
Similar papers in this journal
- Variations in carbapenem resistance associated with the VIM-1 metallo-β-lactamase across the Enterobacterales 95%
- Emergence of optrA-mediated linezolid resistance in multiple lineages and plasmids of Enterococcus faecalis revealed by long read sequencing 93%
- A Functional Menadione Biosynthesis Pathway is Required for Capsule Production by Staphylococcus aureus. 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.