PROJECT SUMMARY/ABSTRACT – Overall Pneumonia, including both community-acquired pneumonia (CAP) and hospital-acquired/ventilator-associated pneumonia (HAP/VAP), causes almost 80% of deaths from infections in the US. As evidenced by the ongoing COVID-19 pandemic, severe pneumonia represents an important cause of morbidity and mortality. Our U19 Systems Biology Center, Successful Clinical Response In Pneumonia Therapy (SCRIPT), which we rename Super-SCRIPT (SCRIPT2) for this renewal, leverages bronchoalveolar lavage (BAL), nasal curettage, and blood sampling paired with cutting-edge multi-omics technologies—including multiparameter flow cytometry, single- cell RNA-sequencing, deep pathogen sequencing, DNA metagenomics, and deep clinical phenotyping—to develop models of pneumonia pathogenesis. In SCRIPT, we generated a detailed systems biology model of SARS-CoV-2 pathobiology that supported a novel therapy for severe SARS-CoV-2 pneumonia that was efficacious in a phase II clinical trial. In SCRIPT2, we will determine whether models generated using high- dimension longitudinal data describing the host response, pathogen, microbiome, and clinical phenome in patients with severe CAP (Project 1) and HAP/VAP (Project 2) can predict favorable or unfavorable clinical transitions over the course of a pneumonia episode. We test the hypothesis that multi-omics inputs will create actionable models that identify favorable and unfavorable clinical transitions/outcomes for both severe CAP and severe HAP/VAP. Aim 1/Project 1. To generate actionable models to improve the clinical course of patients with severe CAP using multi-omics analysis of longitudinal samples from the distal lung and nasopharynx. Aim 2/Project 2. To generate actionable models to improve the clinical course of patients with severe HAP/VAP using a multi-omics analysis of longitudinal samples from the distal lung. Three scientific cores support the projects. The Technology Core developed cutting edge multi-omics approaches for the analysis of bronchoalveolar lavage samples collected as part of clinical care. The Data Management and Bioinformatics Core weaves together clinical data extracted from our own EHR and those from other centers. The Modeling Core works seamlessly with the Projects and Cores to integrate, validate and iteratively improve latent space models of disease. Clinician scholars who provide direct care to patients with pneumonia lead or contribute to each project and core, enhancing the translational impact of our findings.

Project Narrative The Successful Clinical Response In Pneumonia Therapy (SCRIPT2) Systems Biology Center will continue to delineate the complex host/pathogen interactions occurring at the alveolar level that lead to unsuccessful response to therapy in serious pneumonia. In SCRIPT2, we will determine whether models generated using high-dimension data describing the host, pathogen, microbiome, and clinical phenome in severe community- acquire pneumonia and hospital-/ventilator-acquired pneumonia can predict favorable or unfavorable clinical transitions/outcomes over the course of a pneumonia episode. We will query these models to identify potential therapeutic host, pathogen, and microbiome targets and determine when, whether, and how standard or investigational therapies can be applied to increase the likelihood of a favorable outcome.