Identifying determinants of persistent MRSA bacteremia using mathematical modeling

Persistent bacteremia caused by Staphylococcus aureus (SA), especially methicillin-resistant SA (MRSA), is a significant cause of morbidity and mortality. Despite susceptibility phenotypes in vitro, persistent MRSA strains fail to clear with appropriate anti-MRSA therapy during bacteremia in vivo. Thus, identifying the factors that cause such MRSA persistence is of direct and urgent clinical relevance. To address the dynamics of MRSA persistence in the face of host immunity and typical antibiotic regimens, we developed a mathematical model based on the overarching assumption that phenotypic heterogeneity is a hallmark of MRSA persistence. First, we applied an ensemble modeling approach and obtained parameter sets that satisfied the condition of a minimum inoculum dose to establish infection. Second, by simulating with the selected parameter sets under vancomycin therapy which follows clinical practices, we distinguished the models resulting in resolving or persistent bacteremia, based on the total SA exceeding a detection limit after five days of treatment. Third, to find key determinants that discriminate resolving and persistent bacteremia, we applied a machine learning approach and found that the immune clearance rate of persister cells is a key feature. But, fourth, when relapsing bacteremia was considered, the growth rate of persister cells was also found to be a key feature. Finally, we explored pharmacological strategies for persistent and relapsing bacteremia and found that a persister killer, but not a persister formation inhibitor, could provide for an effective cure the persistent bacteremia. Thus, to develop better clinical solutions for MRSA persistence and relapse, our modeling results indicate that we need to better understand the pathogen-host interactions of persister MRSAs in vivo.Author summary: Staphylococcus aureus causes potentially lethal infections of the bloodstream and target organs when able to enter the body, often via skin trauma or catheterization. Methicillin-resistant Staphylococcus aureus (MRSA) resist common antibiotics, but are often successfully treated with vancomycin. However, in some MRSA patients, vancomycin is less effective. This results in persistent bacteremia, even though the isolates can be effectively killed in vitro. MRSA bacteria are thought to switch between two forms, normal and persister cells, that are genetically identical. Persisters, the minor subpopulation, are slow-growing and show lower susceptibility to vancomycin than normal MRSA. To understand the dynamic interplay between the two bacterial populations when challenged by host immunity and vancomycin treatment, we developed a mathematical model and analyzed it in simulations of clinically relevant scenarios. Our work suggests that the immune clearance rate of persister MRSA rather than the MRSA switch rate is a key determinant to establish persistent bacteremia. The model also suggests that increasing killing rate of persisters is a promising therapeutic strategy. Our findings emphasize the need to better understand the interactions of persister MRSAs with host cells and immune responses in vivo.