Sepsis occurs when an infection induces a dysregulated immune response, and is most commonly bacterial in origin. This condition requires rapid treatment for successful patient outcomes. However, the current method to confirm infection (blood culture) requires up to 48 h for a positive result and many true cases remain culture-negative. Therefore, new diagnostic tests are urgently needed. Recent clinical studies suggest that CD69, CD64, and CD25 may serve as useful biomarkers of sepsis. In this study, we evaluated the cecal ligation and puncture and cecal slurry mouse models as tools to study these biomarkers in young and aged mice, and elucidate the timeliness and specificity of sepsis diagnosis. Fluorescence-activated cell sorting analysis revealed that all three biomarkers were elevated on blood leukocytes during sepsis. CD69 was specifically upregulated during sepsis, while CD64 and CD25 were also transiently upregulated in response to sham surgery. The optimal biomarker, or combination of biomarkers, depended on the timing of detection, mouse age, and presence of surgery. CD69 demonstrated an excellent capacity to distinguish sepsis, and in some scenarios the diagnostic performance was enhanced by combining CD69 with CD64. We also analyzed biomarker expression levels on specific cell populations (lymphocytes, monocytes, and neutrophils) and determined the cell types that upregulate each biomarker. Elevations in blood biomarkers were also detected via microfluidic analyses; in this case CD64 distinguished septic mice from naive controls. Our results suggest that CD69 and CD64 are valuable biomarkers to rapidly detect sepsis, and that mouse models are useful to study and validate sepsis biomarkers.

Sepsis is characterized by a dysregulated host immune response to infection, leading to organ dysfunction and a high risk of death. The cecal ligation and puncture (CLP) mouse model is commonly used to study sepsis, but animal mortality rates vary between different studies. Technical factors and animal characteristics may affect this model in unanticipated ways, and if unaccounted for, may lead to serious biases in study findings. We sought to evaluate whether mouse sex, age, weight, surgeon, season of experiments, and timing of antibiotic administration influenced mortality in the CLP model. Methods: We created a comprehensive dataset of C57BL/6J mice that had undergone CLP surgery within our lab during years 2015-2020 from published and unpublished studies. The primary outcome was defined as the time from sepsis induction to death or termination of study (14 days). The Log rank test and Cox regression models were used to analyze the dataset. The study included 119 mice, of which 43% were female, with an average age of 12.6 weeks, an average weight of 25.3 g. 38 (32%) of the animals died. Results: In the unadjusted analyses, experiments performed in the summer and higher weight predicted a higher risk of mortality. In the stratified Cox model by sex, summer season (adjusted hazard ratio [aHR]=5.61, p=0.004) and delayed antibiotic administration (aHR=1.46, p=0.029) were associated with mortality in males, whereas higher weight (aHR=1.52, p=0.005) significantly affected mortality in females. In addition, delayed antibiotic administration (HR=1.42, p=0.025) was associated with mortality in the nonsummer seasons, but not in the summer season. Discussion: In conclusion, some factors specific to sex and season have a significant influence on sepsis mortality in the CLP model. Consideration of these factors along with appropriate group matching or adjusted analysis is critical to minimize variability beyond the experimental conditions within a study.

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