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Updated: Aug 21, 2025

A Mouse Model to Assess Innate Immune Response to Staphylococcus aureus Infection
Published on: February 28, 2019
Assessment of Keratitis Severity Using Quantitative Image Analysis in an In Vivo Murine Model of Staphylococcus
Tomas E Meijome1, Rachel Wozniak2, Linda Kang1
1Department of Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI, USA.
Purpose:
Bacterial keratitis (BK) severity in murine models has traditionally been measured by subjective clinical grading or quantification of ocular bacterial burden. This investigation explores an objective and repeatable quantification of slit lamp photography (SLP) images to measure BK severity.
Methods:
BALB/c strain mice underwent three parallel scratches of the right cornea with subsequent inoculation of 107Staphylococcus aureus cells. SLP imaging and clinical severity grading were performed at 48 hours post-infection. Stromal infiltrate (SI) area on SLP images were quantified. Bacterial burden was determined after enucleation and homogenization. Spearman rank correlations (rs) were used to estimate associations between SI area, clinical severity grades, and bacterial burden.
Results:
BALB/c strain mice (n = 14) were evaluated with an average SI area of 0.92 mm2 (standard deviation, SD = 0.65) and average bacterial burden of 3.16 × 105 colony forming units per milliliter (CFU/mL) (SD = 8.3 × 105). Clinical severity grade positively correlated with SI area (rs = 0.59, p = 0.0276) and bacterial burden (rs = 0.66, p = 0.0106). There was a trend towards positive association between SI area and bacterial burden (rs = 0.51, p = 0.0543).
Conclusions:
SLP annotation of SI area is correlated with clinical severity and may provide an objective, quantitative, and repeatable assessment of BK disease severity.
Translational Relevance:
SLP annotation of SI area is a novel quantitative method to evaluate bacterial keratitis severity longitudinally in mouse models which may be a powerful tool to better understand BK pathogenesis and response to treatments.
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