Transcriptomic responses from improved murine sepsis models can better mimic human surgical sepsis

Philip A. Efron*, Dijoia B. Darden, Zhongkai Wang, Dina C. Nacionales, Maria Cecilia Lopez, Russell B. Hawkins, Michael C. Cox, Jaimar C. Rincon, Ricardo Ungaro, Marvin L. Dirain, Gabriela L. Ghita, Tianmeng Chen, Timothy R. Billiar, Matthew J. Delano, Christiaan Leeuwenburgh, Azra Bihorac, Scott C. Brakenridge, Frederick A. Moore, Alicia M. Mohr, Ronald G. TompkinsBabette A. Brumback, Henry V. Baker, Gilbert R. Upchurch, Lyle L. Moldawer

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


Historically, murine models of inflammation in biomedical research have been shown to minimally correlate with genomic expression patterns from blood leukocytes in humans. In 2019, our laboratory reported an improved surgical sepsis model of cecal ligation and puncture (CLP) that provides additional daily chronic stress (DCS), as well as adhering to the Minimum Quality Threshold in Pre-Clinical Sepsis Studies (MQTiPSS) guidelines. This model phenotypically recapitulates the persistent inflammation, immunosuppression, and catabolism syndrome observed in adult human surgical sepsis survivors. Whether these phenotypic similarities between septic humans and mice are replicated at the circulating blood leukocyte transcriptome has not been demonstrated. Our analysis, in contrast with previous findings, demonstrated that genome-wide expression in our new murine model more closely approximated human surgical sepsis patients, particularly in the more chronic phases of sepsis. Importantly, our new model of murine surgical sepsis with chronic stress did not reflect well gene expression patterns from humans with community-acquired sepsis. Our work indicates that improved preclinical murine sepsis modeling can better replicate both the phenotypic and transcriptomic responses to surgical sepsis, but cannot be extrapolated to other sepsis etiologies. Importantly, these improved models can be a useful adjunct to human-focused and artificial intelligence-based forms of research in order to improve septic patients’ morbidity and mortality.

Original languageEnglish
Article numbere21156
JournalFASEB Journal
Issue number2
StatePublished - Feb 2021
Externally publishedYes


  • inflammation
  • sepsis
  • transcriptome
  • translational medicine


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