Sepsis, which is induced by severe bacterial infections, is a major cause of death worldwide, and therapies combating the disease are urgently needed. Because many drugs have failed in clinical trials despite their efficacy in mouse models, the development of reliable animal models of sepsis is in great demand. Several studies have suggested that rabbits reflect sepsis-related symptoms more accurately than mice. In this study, we evaluated a rabbit model of acute sepsis caused by the intravenous inoculation of Salmonella enterica. The model reproduces numerous symptoms characteristic of human sepsis including hyperlactatemia, hyperglycemia, leukopenia, hypothermia and the hyperproduction of several pro-inflammatory cytokines. Hence, it was chosen to investigate the proposed ability of Pep19-2.5—an anti-endotoxic peptide with high affinity to lipopolysaccharide and lipoprotein—to attenuate sepsis-associated pathologies in combination with an antibiotic (ceftriaxone). We demonstrate that a combination of Pep19-2.5 and ceftriaxone administered intravenously to the rabbits (1) kills bacteria and eliminates bacteremia 30 min post challenge; (2) inhibits Toll-like receptor 4 agonists in serum 90 min post challenge; (3) reduces serum levels of pro-inflammatory cytokines (interleukin-6 and tumor necrosis factor α); and (4) reverts to hypothermia and gives rise to temperature values indistinguishable from basal levels 330 min post challenge. The two components of the combination displayed synergism in some of these activities, and Pep19-2.5 notably counteracted the endotoxin-inducing potential of ceftriaxone. Thus, the combination therapy of Pep19-2.5 and ceftriaxone holds promise as a candidate for human sepsis therapy.
Animals ; Bacteremia ; Bacteria ; Bacterial Infections ; Cause of Death ; Ceftriaxone ; Cytokines ; Homicide* ; Humans ; Hyperglycemia ; Hyperlactatemia ; Hypothermia ; Leukopenia ; Mice ; Models, Animal ; Pathology ; Rabbits* ; Salmonella enterica ; Sepsis* ; Toll-Like Receptor 4 ; Tumor Necrosis Factor-alpha