Immunocompetent Alveolus-on-Chip Model for Studying Alveolar Mucosal Immune Responses.

We introduce an advanced immunocompetent lung-on-chip model designed to replicate the human alveolar structure and function. This innovative model employs a microfluidic-perfused biochip that supports an air-liquid interface mimicking the environment in the human alveoli. Tissue engineering is used to integrate key cellular components, including endothelial cells, macrophages, and epithelial cells, to create a representative tissue model of the alveolus. The model facilitates in-depth examinations of the mucosal immune responses to various pathogens, including viruses, bacteria, and fungi, thereby advancing our understanding of lung immunity. The primary goal of this protocol is to provide details for establishing this alveolus-on-chip model as a robust in vitro platform for infection studies, enabling researchers to closely observe and analyze the complex interactions between pathogens and the host's immune system within the pulmonary environment. This is achieved through the application of microfluidic-based techniques to simulate key physiological conditions of the human alveoli, including blood flow and biomechanical stimulation of endothelial cells, alongside maintaining an air-liquid interface crucial for the realistic exposure of epithelial cells to air. The model system is compatible with a range of standardized assays, such as immunofluorescence staining, cytokine profiling, and colony-forming unit (CFU)/plaque analysis, allowing for comprehensive insights into immune dynamics during infection. The Alveolus-on-chip is composed of essential cell types, including human distal lung epithelial cells (H441) and human umbilical vein endothelial cells (HUVECs) separated by porous polyethylene terephthalate (PET) membranes, with primary monocyte-derived macrophages strategically positioned between the epithelial and endothelial layers. The tissue model enhances the ability to dissect and analyze the nuanced factors involved in pulmonary immune responses in vitro. As a valuable tool, it should contribute to the advancement of lung research, providing a more accurate and dynamic in vitro model for studying the pathogenesis of respiratory infections and testing potential therapeutic interventions.

Cell-free DNA in patients with sepsis: long term trajectory and association with 28-day mortality and sepsis-associated acute kidney injury.

Introduction: Outcome-prediction in patients with sepsis is challenging and currently relies on the serial measurement of many parameters. Standard diagnostic tools, such as serum creatinine (SCr), lack sensitivity and specificity for acute kidney injury (AKI). Circulating cell-free DNA (cfDNA), which can be obtained from liquid biopsies, can potentially contribute to the quantification of tissue damage and the prediction of sepsis mortality and sepsis-associated AKI (SA-AKI). Methods: We investigated the clinical significance of cfDNA levels as a predictor of 28-day mortality, the occurrence of SA-AKI and the initiation of renal replacement therapy (RRT) in patients with sepsis. Furthermore, we investigated the long-term course of cfDNA levels in sepsis survivors at 6 and 12 months after sepsis onset. Specifically, we measured mitochondrial DNA (mitochondrially encoded NADH-ubiquinone oxidoreductase chain 1, mt-ND1, and mitochondrially encoded cytochrome C oxidase subunit III, mt-CO3) and nuclear DNA (nuclear ribosomal protein S18, n-Rps18) in 81 healthy controls and all available samples of 150 intensive care unit patients with sepsis obtained at 3 ± 1 days, 7 ± 1 days, 6 ± 2 months and 12 ± 2 months after sepsis onset. Results: Our analysis revealed that, at day 3, patients with sepsis had elevated levels of cfDNA (mt-ND1, and n-Rps18, all p<0.001) which decreased after the acute phase of sepsis. 28-day non-survivors of sepsis (16%) had higher levels of cfDNA (all p<0.05) compared with 28-day survivors (84%). Patients with SA-AKI had higher levels of cfDNA compared to patients without AKI (all p<0.05). Cell-free DNA was also significantly increased in patients requiring RRT (all p<0.05). All parameters improved the AUC for SCr in predicting RRT (AUC=0.88) as well as APACHE II in predicting mortality (AUC=0.86). Conclusion: In summary, cfDNA could potentially improve risk prediction models for mortality, SA-AKI and RRT in patients with sepsis. The predictive value of cfDNA, even with a single measurement at the onset of sepsis, could offer a significant advantage over conventional diagnostic methods that require repeated measurements or a baseline value for risk assessment. Considering that our data show that cfDNA levels decrease after the first insult, future studies could investigate cfDNA as a "memoryless" marker and thus bring further innovation to the complex field of SA-AKI diagnostics.