Longitudinal intravital imaging of the bone marrow for analysis of the race for the surface in a murine osteomyelitis model

Efficacy of pH-Responsive Surface Functionalized Titanium Screws in Treating Implant-associated S. aureus Osteomyelitis with Biofilms Formation

Implant-associated Staphylococcus aureus (S. aureus) osteomyelitis (IASO) leads to high orthopedic implant failure rates due to the formation of Staphylococcal abscess community within the bone marrow and bacterial colonization in the osteocyte lacuno-canalicular network (OLCN). To address this, antimicrobial peptides (HHC36)-loaded titania nanotubes (NTs) are developed on titanium screws (Ti-NTs-P-A), which integrate pH-responsive polymethacrylic acid to control HHC36 release for eradicating bacteria in IASO. Colony-forming unit assay confirmed that Ti-NTs-P-A screws maintained sustainable antibacterial effectiveness, killing over 65% of S. aureus even after multiple bacterial solution replacements. Notably, Ti-NTs-P-A screws exhibit significant pH-responsive HHC36 release behavior and bactericidal activity, consistent with the phenotype of peptides-killed bacteria from scanning electron microscopy. Transcriptome sequencing results reveal that Ti-NTs-P-A screws interfered with ribosome formation and disrupted the arginine biosynthesis, which is crucial for bacterial survival in acidic environments. In the non-infected implant model, the bone-implant contact ratio of the Ti-NTs-P-A screw is 2.3 times that of the clinically used titanium screw. In an IASO model, Ti-NTs-P-A screws effectively eradicated bacteria within the OLCN, achieving an 80% infection control rate and desirable osteointegration. Collectively, Ti-NTs-P-A screws with pH-responsive antibacterial properties exhibit great potential for eradicating bacteria and achieving osseointegration in IASO.

A semi-automated cell tracking protocol for quantitative analyses of neutrophil swarming to sterile and S. aureus contaminated bone implants in a mouse femur model

Implant-associated osteomyelitis remains a major orthopaedic problem. As neutrophil swarming to the surgical site is a critical host response to prevent infection, visualization and quantification of this dynamic behavior at the native microenvironment of infection will elucidate previously unrecognized mechanisms central to understanding the host response. We recently developed longitudinal intravital imaging of the bone marrow (LIMB) to visualize fluorescent S. aureus on a contaminated transfemoral implant and host cells in live mice, which allows for direct visualization of bacteria colonization of the implant and host cellular responses using two-photon laser scanning microscopy. To the end of rigorous and reproducible quantitative outcomes of neutrophil swarming kinetics in this model, we developed a protocol for robust segmentation, tracking, and quantifications of neutrophil dynamics adapted from Trainable Weka Segmentation and TrackMate, two readily available Fiji/ImageJ plugins. In this work, Catchup mice with tdTomato expressing neutrophils received a transfemoral pin with or without ECFP-expressing USA300 methicillin-resistant Staphylococcus aureus (MRSA) to obtain 30-minute LIMB videos at 2-, 4-, and 6-hours post-implantation. The developed semi-automated neutrophil tracking protocol was executed independently by two users to quantify the distance, displacement, speed, velocity, and directionality of the target cells. The results revealed high inter-reader reliability for all outcomes (ICC > 0.98; p > 0.05). Consistent with the established paradigm on increased neutrophil swarming during active infection, the results also demonstrated increased neutrophil speed and velocity at all measured time points, and increased displacement at later time points (6 hours) in infected versus uninfected mice (p < 0.05). Neutrophils and bacteria also exhibit directionality during migration in the infected mice. The semi-automated cell tracking protocol provides a streamlined approach to robustly identify and track individual cells across diverse experimental settings and eliminates inter-observer variability.