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Abstract Background The gut microbiome plays a protective role in the host defense against pneumonia. The composition of the lung microbiota has been shown to be predictive of clinical outcome in critically ill patients. However, the dynamics of the lung and gut microbiota composition over time during severe pneumonia remains ill defined. We used a mouse model of pneumonia-derived sepsis caused by Klebsiella pneumoniae in order to follow the pathogen burden as well as the composition of the lung, tongue and fecal microbiota from local infection towards systemic spread. Results Already at 6 h post-inoculation with K. pneumoniae, marked changes in the lung microbiota were seen. The alpha diversity of the lung microbiota did not change throughout the infection, whereas the beta diversity did. A shift between the prominent lung microbiota members of Streptococcus and Klebsiella was seen from 12 h onwards and was most pronounced at 18 h post-inoculation (PI) which was also reflected in the release of pro-inflammatory cytokines indicating severe pulmonary inflammation. Around 18 h PI, K. pneumoniae bacteremia was observed together with a systemic inflammatory response. The composition of the tongue microbiota was not affected during infection, even at 18–30 h PI when K. pneumoniae had become the dominant bacterium in the lung. Moreover, we observed differences in the gut microbiota during pulmonary infection. The gut microbiota contributed to the lung microbiota at 12 h PI, however, this decreased at a later stage of the infection. Conclusions At 18 h PI, K. pneumoniae was the dominant member in the lung microbiota. The lung microbiota profiles were significantly explained by the lung K. pneumoniae bacterial counts and Klebsiella and Streptococcus were correlating with the measured cytokine levels in the lung and/or blood. The oral microbiota in mice, however, was not influenced by the severity of murine pneumonia, whereas the gut microbiota was affected. This study is of significance for future studies investigating the role of the lung microbiota during pneumonia and sepsis.

Abstract The pathophysiology of sepsis is multi-facetted and highly complex. As sepsis is a leading cause of global mortality that still lacks targeted therapies, increased understanding of its pathogenesis is vital for improving clinical care and outcomes. An increasing number of investigations seeks to unravel the complexity of sepsis through high-dimensional data analysis, enabled by advances in -omics technologies. Here, we summarize progress in the following major -omics fields: genomics, epigenomics, transcriptomics, proteomics, lipidomics, and microbiomics. We describe what these fields can teach us about sepsis, and highlight current trends and future challenges. Finally, we focus on multi-omics integration, and discuss the challenges in deriving biological meaning and clinical applications from these types of data.

Abstract Background The microbiome has emerged as an important player in the pathophysiology of a whole spectrum of diseases that affect the critically ill. We hypothesized that differences in microbiota composition across vendors can influence murine models of pulmonary lipopolysaccharide (LPS) inflammation and Gram-negative pneumonia. Methods A multi-vendor approach was used with genetically similar mice derived from three different vendors (Janvier, Envigo, Charles River). This model was employed to study the effect on the host response to a pulmonary LPS challenge (1 μg Klebsiella pneumoniae LPS, intranasal), as well as experimental K. pneumoniae infection (ATCC43816, 1 × 104 CFU, intranasal). Results Gut microbiota analysis revealed profound intervendor differences in bacterial composition as shown by beta diversity and at various taxonomic levels. Tumor necrosis factor (TNF)-α and interleukin (IL)-6 release in lung and bronchoalveolar lavage fluid (BALF) were determined 6 and 24 h after intranasal treatment with LPS. No differences were found between the groups, with the exception for Envigo, showing a higher level of TNFα in lung and BALF at 6 h compared to Janvier and Charles River. In another set of experiments, mice from different vendors were subjected to a clinically relevant model of Gram-negative pneumonia (K. pneumoniae). At 12 and 36 h post-infection, no intervendor differences were found in bacterial dissemination, or TNFα and IL-6 levels in the lungs. In line, markers for organ failure did not differ between groups. Conclusions Although there was a marked variation in the gut microbiota composition of mice from different vendors, the hypothesized impact on our models of pulmonary inflammation and severe pneumonia was limited. This is of significance for experimental settings, showing that differences in gut microbiota do not have to lead to differences in outcome.