Computational and in vitro evaluation of probiotic treatments for nasal <i>Staphylococcus aureus</i> decolonization

Abstract

Despite the rising challenge of antibiotic resistance, current approaches to eradicate nasal pathobionts Staphylococcus aureus and Streptococcus pneumoniae rely on antibacterials. An alternative is the artificial inoculation of commensal bacteria, i.e., probiotic treatment, supported by the increasing evidence for commensal-mediated inhibition of pathogens. To systematically investigate the potential of this approach, we developed a quantitative framework simulating the nasal microbiome dynamics by combining mathematical modeling with longitudinal microbiota data. By inferring community parameters using 16S ribosomal RNA (rRNA) amplicon sequencing data and simulating the nasal microbial dynamics of patients colonized with S. aureus , we compared the decolonization performance of probiotic and antibiotic treatments under different assumptions on patients’ community composition and susceptibility profile. To further compare the robustness of these treatments, we simulated an S. aureus challenge and quantified the recolonization probability. Through in vitro experiments using nasal swabs of adults colonized with S. aureus , we confirmed that after antibiotic treatment, recolonization of S. aureus was inhibited in samples treated with a probiotic mixture compared to the nontreated control. Our results suggest that probiotic treatment outperforms antibiotics in terms of decolonization performance, recolonization robustness, and leads to less collateral reduction in the microbiome diversity. Thus, probiotic treatment may provide a promising alternative to combat antibiotic resistance, with the additional advantage of personalized treatment options via using the patient’s own metagenomic data. The combination of an in silico framework with in vitro experiments using clinical samples reported in this work is an important step forward to further investigate this alternative in clinical trials.