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2025 OMIG Abstract

Over-the-Counter Artificial Tear Formulations Differentially Influence Microbial Growth of Staphylococcus aureus and Pseudomonas aeruginosa isolates

Felipe Echeverri Tribin¹, Heather Durkee¹, Alexander Alfonso², Alison Rodriguez Leiva¹,
Mariela Caridad Aguilar¹, Salomon Merikansky^1,2, Maribel Hernandez², Beatriz Munoz², Jorge Maestre², Harry W. Flynn, Jr.^1-3, Guillermo Amescua^1-3, Jean-Marie Parel^1,3, Darlene Miller<sup>2,3

1</sup>Ophthalmic Biophysics Center, Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida; ²Ocular Microbiology Laboratory, Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida; ³Anne Bates Leach Eye Center, Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida

Purpose: To compare the growth kinetics of Pseudomonas aeruginosa and Staphylococcus aureus in different over-the counter (OTC) artificial tears (AT).

Methods: Ten different ATs were selected to represent a diverse range of formulations and categorized into three groups: preservative-containing ATs (PAT) (n=5), single-use preservative-free ATs (PFAT) (n=2), and multidose PFATs (n=3). Each AT was inoculated with 6 clinical P. aeruginosa (PA), 6 methicillin-resistant S. aureus (MRSA), or 6 methicillin-sensitive (MSSA) isolates from various ocular sources. AT solutions were aliquoted in quadruplicate into a 96-well microplate and inoculated with microbial suspension of 10⁶ CFU/mL. Microbial controls were also included in both tryptic soy broth and saline. Turbidity was recorded for 24 hours in a microplate reader at 37°C. Optical density area-under the curve (AUC) and growth kinetics (lag time and growth rate) were determined with Gompertz-fits of the individual growth curves. After the 24-hour growth period, all groups were cultured to determine final bacterial counts. The log ratio of the initial concentration. to the final concentration was used to classify growth patterns as bactericidal, bacteriostatic, or growth-promoting. Linear mixed effect models (LMM) were used to estimate the effect of organism type on AUC, lag time, and growth rate.

Results: All strains grew more in PFATs than in controls (p < 0.001), whereas growth in PATs did not differ from controls. PAT supported significantly less microbial growth than PFATs (p < 0.001). PFATs also produced strain‑specific growth patterns among MRSA, MSSA, and PA (p < 0.001). Within PFATs, single-use formulations promoted the highest growth (p < 0.001), especially AT4 (p < 0.001). No PFAT formulation was bactericidal against MRSA (0%) or MSSA (0%), whereas PA had nine strains (30%) with bactericidal outcomes, most originating from AT2 (20%). Bacteriostatic effects appeared against all three organisms in PFATs [MRSA: 60%; MSSA: 60%; PA: 10%]. Non-inhibited growth in PFATs was seen in 40% of MRSA, 40% of MSSA, and 60% of PA strains. LMMs revealed no AUC difference between MSSA and MRSA (p = 0.480) but a significantly higher AUC for PA (p < 0.001), with AT accounting for 57 % of variance versus 9% for strain. Growth rate did not differ by strain (p = 0.992). Lag time was similar between MSSA and MRSA (p = 0.763) but prolonged for PA compared with both MRSA and MSSA (p < 0.001).

Conclusions: As expected, PF formulations appear particularly susceptible to microbial growth. The mixed response of isolates to different ATs suggests that tear components may differentially support microbial growth. Selection of OTC ATs formulation is crucial, particularly regarding ingredients that may support microbial growth.