Host Responses to Sepsis Vary in Different Low-Lethality Murine Models

<div><p>Introduction</p><p>Animal models for the study of sepsis are being increasingly scrutinized, despite their essential role for early translational research. In particular, recent studies have suggested that at the level of the leukocyte transcriptome, murine models of burns, trauma and endotoxemia markedly differ from their human equivalents, and are only weakly similar amongst themselves. We compared the plasma cytokine and leukocyte transcriptome responses between two different low-lethality murine models of polymicrobial intra-abdominal sepsis.</p><p>Methods</p><p>Six to ten week male C57BL/6j mice underwent either the ‘gold standard’ cecal ligation and puncture (CLP) model of intra-abdominal sepsis or administration of a cecal slurry (CS), where cecal contents are injected intraperitoneally. Surviving mice were euthanized at two hours, one or three days after sepsis.</p><p>Results</p><p>The murine leukocyte transcriptomic response to the CLP and CS models of sepsis was surprisingly dissimilar at two hours, one, and three days after sepsis. The Pearson correlation coefficient for the maximum change in expression for the entire leukocyte transcriptome that changed significantly over time (n = 19,071) was R = 0.54 (R² = 0.297). The CS model resulted in greater magnitude of early inflammatory gene expression changes in response to sepsis with associated increased production of inflammatory chemokines and cytokines. Two hours after sepsis, CLP had more significant expression of genes associated with IL-10 signaling pathways, whereas CS had greater expression of genes related to CD28, apoptosis, IL-1 and T-cell receptor signaling. By three days, the changes in gene expression in both sepsis models were returning to baseline in surviving animals.</p><p>Conclusion</p><p>These analyses reveal that the murine blood leukocyte response to sepsis is highly dependent on which model of intra-abdominal sepsis is employed, despite their similar lethality. It may be difficult to extrapolate findings from one murine model to another, let alone to human sepsis.</p></div

The CS model of intra-abdominal sepsis has a greater magnitude of inflammatory cytokine production than the CLP model 24 hours after sepsis and induces greater gene expression changes than the CLP model.

<p><b>A</b>. The CS model had significantly increased production of IL-6, IL-10, MIP1α, and TNFα in the plasma compared to mice who underwent the CLP model of sepsis (p<0.0001, p<0.01, p<0.01, p<0.001 respectively). <b>B</b>. A DFR score was calculated to examine the normalized differences in expression for each of the genes from naïve controls and graphed for each model over time. The mean DFR with standard error of the means are graphed on the y-axis and time on the x-axis. All points are significant on 2-way ANOVA (*p<0.0001). The dashed line represents the mean value of naïve controls.</p

WBC count and leukocyte subset differentials after sepsis.

<p>Both the model and the time were significant in <b>A</b>. total WBC count (p<0.01-time, p<0.01-model, 2-Way ANOVA), <b>B</b>. neutrophil percentage (p<0.0001-time, p<0.0001-model, 2-Way ANOVA), and <b>C</b>. lymphocyte percentage (p<0.0001-time, p<0.001-model, 2-Way ANOVA), but only time had a significant effect on the <b>D</b>. monocyte percentage (p<0.001-time, 2-Way ANOVA).</p

Heat maps from septic mice two hours, one day, and three days after sepsis reveal that CS induces a leukocyte transcriptomic response that is distinct from CLP.

<p>After CLP there were 2,869 probe sets, representing 2,159 genes that were differentially expressed between septic and healthy control mice that were significant at p<0.001 across all time points. After CS there were 4,486 probe sets, representing 3,305 genes that were differentially expressed. There were only 802 probe sets (representing 757 genes) that were the same amongst the two models.</p

The CLP and CS models of murine intra-abdominal sepsis each induce a distinct genomic response after sepsis.

<p><b>A</b>. Unsupervised cluster analysis with a coefficient of variation of >0.5 reveals that the expression of 19,071 probe sets (12,838 genes) varied after sepsis, and segregated based on the type of sepsis model employed. <b>B</b>. A supervised analysis shows that there were 11,612 probesets (7,581 genes) differentially expressed after sepsis (p<0.001) and the expression patterns from these two models appear distinct from one another.</p

The differential gene expression between CLP and CS leads to the dissimilar activation of various immune related pathways after sepsis.

<p>Selected inflammation and immune related signaling pathways from IPA are presented. The –log (p-value) presented on the y-axis represents a measure of how likely the pathway is to contain genes associated with our dataset. (The –log for a p-value of 0.05 is 1.3). Negative values represent those pathways whose actions were inhibited using the Molecule Activity Predictor tool in IPA canonical pathway analysis, and positive values represent those pathways that are activated.</p

Successful Implementation of a Packed Red Blood Cell and Fresh Frozen Plasma Transfusion Protocol in the Surgical Intensive Care Unit

<div><p>Background</p><p>Blood product transfusions are associated with increased morbidity and mortality. The purpose of this study was to determine if implementation of a restrictive protocol for packed red blood cell (PRBC) and fresh frozen plasma (FFP) transfusion safely reduces blood product utilization and costs in a surgical intensive care unit (SICU).</p><p>Study Design</p><p>We performed a retrospective, historical control analysis comparing before (PRE) and after (POST) implementation of a restrictive PRBC/FFP transfusion protocol for SICU patients. Univariate analysis was utilized to compare patient demographics and blood product transfusion totals between the PRE and POST cohorts. Multivariate logistic regression models were developed to determine if implementation of the restrictive transfusion protocol is an independent predictor of adverse outcomes after controlling for age, illness severity, and total blood products received.</p><p>Results</p><p>829 total patients were included in the analysis (PRE, n=372; POST, n=457). Despite higher mean age (56 vs. 52 years, p=0.01) and APACHE II scores (12.5 vs. 11.2, p=0.006), mean units transfused per patient were lower for both packed red blood cells (0.7 vs. 1.2, p=0.03) and fresh frozen plasma (0.3 vs. 1.2, p=0.007) in the POST compared to the PRE cohort, respectively. There was no difference in inpatient mortality between the PRE and POST cohorts (7.5% vs. 9.2%, p=0.39). There was a decreased risk of urinary tract infections (OR 0.47, 95%CI 0.28-0.80) in the POST cohort after controlling for age, illness severity and amount of blood products transfused.</p><p>Conclusions</p><p>Implementation of a restrictive transfusion protocol can effectively reduce blood product utilization in critically ill surgical patients with no increase in morbidity or mortality.</p></div

Multivariate Analysis of early transfusion and urinary tract infection rates.

<p>Abbreviations. RR, relative risk; CI, confidence interval.</p><p>Abbreviations. APACHE, Acute Physiology and Chronic Health Evaluation; PRBC, packed red blood cells; FFP, fresh frozen plasma; CI, confidence interval.</p><p>Multivariate Analysis of early transfusion and urinary tract infection rates.</p

Restrictive transfusion protocol for FFP.

<p>Restrictive transfusion protocol for FFP.</p

Demographics—Pre vs. Post Restrictive Transfusion Protocol.

<p>Abbreviations: APACHE, Acute Physiology and Chronic Health Evaluation; PT, prothrombin time; INR, international normalized ratio; Hgb, hemoglobin; SD, standard deviation.</p><p>All percentages were calculated as column percentages.</p><p>^a Pre n = 327, Post n = 390;</p><p>^b Pre n = 326, Post n = 390;</p><p>^c Pre n = 370, Post n = 456;</p><p>^d Post n = 456;</p><p>Demographics—Pre vs. Post Restrictive Transfusion Protocol.</p