Biofilm exopolysaccharides alter sensory-neuron-mediated sickness during lung infection.

Infections of the lung cause observable sickness thought to be secondary to inflammation. Signs of sickness are crucial to alert others via behavioral-immune responses to limit contact with contagious individuals. Gram-negative bacteria produce exopolysaccharide (EPS) that provides microbial protection; however, the impact of EPS on sickness remains uncertain. Using genome-engineered Pseudomonas aeruginosa (P. aeruginosa) strains, we compared EPS-producers versus non-producers and a virulent Escherichia coli (E. coli) lung infection model in male and female mice. EPS-negative P. aeruginosa and virulent E. coli infection caused severe sickness, behavioral alterations, inflammation, and hypothermia mediated by TLR4 detection of the exposed lipopolysaccharide (LPS) in lung TRPV1+ sensory neurons. However, inflammation did not account for sickness. Stimulation of lung nociceptors induced acute stress responses in the paraventricular hypothalamic nuclei by activating corticotropin-releasing hormone neurons responsible for sickness behavior and hypothermia. Thus, EPS-producing biofilm pathogens evade initiating a lung-brain sensory neuronal response that results in sickness.

Neutrophils are itching to specialize.

Neutrophils are heterogeneous, but the mechanisms underlying their ability to polarize remain unclear. In this issue of Immunity, Gour et al. demonstrate that the GPCR Mrgpra1 and the neuropeptide NPFF, molecules involved in pain and itch, direct neutrophil polarization that impacts host defense and pneumonia susceptibility.

Endotyping in ARDS: one step forward in precision medicine.

BACKGROUND: The Berlin definition of acute respiratory distress syndrome (ARDS) includes only clinical characteristics. Understanding unique patient pathobiology may allow personalized treatment. We aimed to define and describe ARDS phenotypes/endotypes combining clinical and pathophysiologic parameters from a Canadian ARDS cohort. METHODS: A cohort of adult ARDS patients from multiple sites in Calgary, Canada, had plasma cytokine levels and clinical parameters measured in the first 24 h of ICU admission. We used a latent class model (LCM) to group the patients into several ARDS subgroups and identified the features differentiating those subgroups. We then discuss the subgroup effect on 30 day mortality. RESULTS: The LCM suggested three subgroups (n1 = 64, n2 = 86, and n3 = 30), and 23 out of 69 features made these subgroups distinct. The top five discriminating features were IL-8, IL-6, IL-10, TNF-a, and serum lactate. Mortality distinctively varied between subgroups. Individual clinical characteristics within the subgroup associated with mortality included mean PaO2/FiO2 ratio, pneumonia, platelet count, and bicarbonate negatively associated with mortality, while lactate, creatinine, shock, chronic kidney disease, vasopressor/ionotropic use, low GCS at admission, and sepsis were positively associated. IL-8 and Apache II were individual markers strongly associated with mortality (Area Under the Curve = 0.84). PERSPECTIVE: ARDS subgrouping using biomarkers and clinical characteristics is useful for categorizing a heterogeneous condition into several homogenous patient groups. This study found three ARDS subgroups using LCM; each subgroup has a different level of mortality. This model may also apply to developing further trial design, prognostication, and treatment selection.