RESUMO
Rationale: Pseudomonas aeruginosa is the major bacterial pathogen colonizing the airways of adult patients with cystic fibrosis (CF) and causes chronic infections that persist despite antibiotic therapy. Intracellular bacteria may represent an unrecognized reservoir of bacteria that evade the immune system and antibiotic therapy. Although the ability of P. aeruginosa to invade and survive within epithelial cells has been described in vitro in different epithelial cell models, evidence of this intracellular lifestyle in human lung tissues is currently lacking. Objectives: To detect and characterize intracellular P. aeruginosa in CF airway epithelium from human lung explant tissues. Methods: We sampled lung explant tissues from patients with CF undergoing lung transplantation and non-CF lung donor control tissue. We analyzed lung tissue sections for the presence of intracellular P. aeruginosa using quantitative culture and microscopy, in parallel to histopathology and airway morphometry. Measurements and Main Results: P. aeruginosa was isolated from the lungs of seven patients with CF undergoing lung transplantation. Microscopic assessment revealed the presence of intracellular P. aeruginosa within airway epithelial cells in three of the seven patients analyzed at a varying but low frequency. We observed those events occurring in lung regions with high bacterial burden. Conclusions: This is the first study describing the presence of intracellular P. aeruginosa in CF lung tissues. Although intracellular P. aeruginosa in airway epithelial cells is likely relatively rare, our findings highlight the plausible occurrence of this intracellular bacterial reservoir in chronic CF infections.
Assuntos
Fibrose Cística , Transplante de Pulmão , Pulmão , Infecções por Pseudomonas , Pseudomonas aeruginosa , Mucosa Respiratória , Humanos , Fibrose Cística/microbiologia , Fibrose Cística/complicações , Feminino , Masculino , Adulto , Mucosa Respiratória/microbiologia , Mucosa Respiratória/patologia , Infecções por Pseudomonas/microbiologia , Pulmão/microbiologia , Pulmão/patologia , Adulto Jovem , Células Epiteliais/microbiologiaRESUMO
BACKGROUND: A subset of individuals (10-20%) experience post-COVID condition (PCC) subsequent to initial SARS-CoV-2 infection, which lacks effective treatment. PCC carries a substantial global burden associated with negative economic and health impacts. This study aims to evaluate the association between plasma taurine levels with self-reported symptoms and adverse clinical outcomes in patients with PCC. METHODS AND FINDINGS: We analyzed the plasma proteome and metabolome of 117 individuals during their acute COVID-19 hospitalization and at the convalescence phase six-month post infection. Findings were compared with 28 age and sex-matched healthy controls. Plasma taurine levels were negatively associated with PCC symptoms and correlated with markers of inflammation, tryptophan metabolism, and gut dysbiosis. Stratifying patients based on the trajectories of plasma taurine levels during six-month follow-up revealed a significant association with adverse clinical events. Increase in taurine levels during the transition to convalescence were associated with a reduction in adverse events independent of comorbidities and acute COVID-19 severity. In a multivariate analysis, increased plasma taurine level between acute and convalescence phase was associated with marked protection from adverse clinical events with a hazard ratio of 0.13 (95% CI: 0.05-0.35; p<0.001). CONCLUSIONS: Taurine emerges as a promising predictive biomarker and potential therapeutic target in PCC. Taurine supplementation has already demonstrated clinical benefits in various diseases and warrants exploration in large-scale clinical trials for alleviating PCC.
Assuntos
COVID-19 , SARS-CoV-2 , Taurina , Humanos , Taurina/sangue , COVID-19/sangue , COVID-19/complicações , Feminino , Masculino , Pessoa de Meia-Idade , SARS-CoV-2/isolamento & purificação , Adulto , Biomarcadores/sangue , Idoso , Síndrome de COVID-19 Pós-Aguda , Estudos de Casos e Controles , Metaboloma , Carga de SintomasRESUMO
Tools for predicting COVID-19 outcomes enable personalized healthcare, potentially easing the disease burden. This collaborative study by 15 institutions across Europe aimed to develop a machine learning model for predicting the risk of in-hospital mortality post-SARS-CoV-2 infection. Blood samples and clinical data from 1286 COVID-19 patients collected from 2020 to 2023 across four cohorts in Europe and Canada were analyzed, with 2906 long non-coding RNAs profiled using targeted sequencing. From a discovery cohort combining three European cohorts and 804 patients, age and the long non-coding RNA LEF1-AS1 were identified as predictive features, yielding an AUC of 0.83 (95% CI 0.82-0.84) and a balanced accuracy of 0.78 (95% CI 0.77-0.79) with a feedforward neural network classifier. Validation in an independent Canadian cohort of 482 patients showed consistent performance. Cox regression analysis indicated that higher levels of LEF1-AS1 correlated with reduced mortality risk (age-adjusted hazard ratio 0.54, 95% CI 0.40-0.74). Quantitative PCR validated LEF1-AS1's adaptability to be measured in hospital settings. Here, we demonstrate a promising predictive model for enhancing COVID-19 patient management.