A non-human primate model of severe pneumococcal pneumonia

Academic Article


  • Rationale: Streptococcus pneumoniae is the leading cause of community-acquired pneumonia and infectious death in adults worldwide. A non-human primate model is needed to study the molecular mechanisms that underlie the development of severe pneumonia, identify diagnostic tools, explore potential therapeutic targets, and test clinical interventions during pneumococcal pneumonia. Objective: To develop a non-human primate model of pneumococcal pneumonia. Methods: Seven adult baboons (Papio cynocephalus) were surgically tethered to a continuous monitoring system that recorded heart rate, temperature, and electrocardiography. Animals were inoculated with 109 colony-forming units of S. pneumoniae using bronchoscopy. Three baboons were rescued with intravenous ampicillin therapy. Pneumonia was diagnosed using lung ultrasonography and ex vivo confirmation by histopathology and immunodetection of pneumococcal capsule. Organ failure, using serum biomarkers and quantification of bacteremia, was assessed daily. Results: Challenged animals developed signs and symptoms of pneumonia 4 days after infection. Infection was characterized by the presence of cough, tachypnea, dyspnea, tachycardia and fever. All animals developed leukocytosis and bacteremia 24 hours after infection. A severe inflammatory reaction was detected by elevation of serum cytokines, including Interleukin (IL)1Ra, IL-6, and IL-8, after infection. Lung ultrasonography precisely detected the lobes with pneumonia that were later confirmed by pathological analysis. Lung pathology positively correlated with disease severity. Antimicrobial therapy rapidly reversed symptomology and reduced serum cytokines. Conclusions: We have developed a novel animal model for severe pneumococcal pneumonia that mimics the clinical presentation, inflammatory response, and infection kinetics seen in humans. This is a novel model to test vaccines and treatments, measure biomarkers to diagnose pneumonia, and predict outcomes.
  • Authors

    Published In

  • PLoS One  Journal
  • Digital Object Identifier (doi)

    Author List

  • Reyes LF; Restrepo MI; Hinojosa CA; Soni NJ; Shenoy AT; Gilley RP; Gonzalez-Juarbe N; Noda JR; Winter VT; De La Garza MA
  • Volume

  • 11
  • Issue

  • 11