Peptidome profiling for the immunological stratification in sepsis: a proof of concept study

Abstract

Sepsis has been called "the graveyard of pharmaceutical companies" due to the numerous failed clinical trials. The lack of tools to monitor the immunological status in sepsis constrains the development of immunomodulatory therapies. Here, we evaluated a test based on whole plasma peptidome acquired in a MALDI-TOF-mass spectrometer used for bacterial biotyping and machine-learning algorithms to discriminate the different immunological phases of sepsis. In this proof of concept study, two discrete lipopolysaccharide-(LPS) induced murine models emulating the pro- and anti-inflammatory phases that occur during sepsis were evaluated. The LPS group was inoculated with a single high dose of LPS, recalling the proinflammatory phase, and the IS groups was subjected to increasing doses of LPS to induce the anti-inflammatory/immunosuppression phase. Unstimulated mice served as controls. Both experimental groups showed the hallmarks of pro- and anti- inflammatory phases respectively; the LPS group showed leukopenia and higher levels of cytokines and tissue damage markers, and the IS group showed neutrophilia, lymphopenia and significantly lower antibody titers upon immunization. Principal component analysis of the plasma peptidomes formed three discrete clusters that mostly coincided with the experimental groups. In addition, machine-learning algorithms discriminated the different experimental groups with a sensitivity and specificity of up to 95.7% and 90.9% respectively. Our data reveal the potential of plasma peptidome analysis by MALDI-TOF-mass spectrometry as a simple, speedy and readily transferrable method for sepsis patient stratification that would contribute to therapeutic decision-making based on their immunological status.