Administrative Core Project Summary:
The Administrative Core ensures seamless collaboration and integration across its multidisciplinary teams to study host-pathogen interactions in severe pneumonia. By leveraging high-throughput multi-omics and mathematical modeling, the Admin Core employs an iterative approach to refine experiments and insights. The Administrative Core’s primary goal is to facilitate these efforts while ensuring data dissemination to the broader pneumonia and infectious diseases research community.
Data Management and Bioinformatics Core Project Summary:
The Data Management and Bioinformatics (DMBI) Core provides the computational infrastructure and tools necessary to analyze and integrate the diverse data generated by the Center’s multidisciplinary projects. The overall goal is to enhance computational resources to advance understanding of host-pathogen interactions in severe pneumonia and share these resources broadly with the research community.
Technology Core Project Summary:
The Technology Core provides cutting-edge sample processing, biobanking, and next-generation sequencing (NGS) capabilities, facilitating high-resolution analysis across all SCRIPT² Projects and Cores. Key activities of the Tech Core include immunophenotyping, cryopreservation, and advanced sequencing techniques such as single-cell RNA-seq, CITE-seq, T and B cell receptor clonotyping, DNA methylation analysis, metagenomics, and deep pathogen sequencing. These technologies enable detailed characterization of epithelial and immune cell subsets, pathogen dynamics, and molecular interactions.
Modeling Core Project Summary:
The Modeling Core of SCRIPT² builds on the successes of its predecessor by applying advanced machine learning and systems biology approaches to clinical and multi-omics data to model pneumonia pathogenesis and identify actionable biomarkers and therapeutic targets. A key achievement of the initial SCRIPT cycle was developing a detailed model of severe SARS-CoV-2 pneumonia, published in Nature, which highlighted unique host response mechanisms and predicted the efficacy of the CRAC channel inhibitor Auxora in mitigating prolonged critical illness.
Project 1 Summary: Host response to pneumonia
Pandemic community-acquired pneumonia (CAP) caused by SARS-CoV-2 highlighted CAP’s public health impact. In SCRIPT, we established a comprehensive research infrastructure, collecting over 1,500 serial respiratory samples from 595 patients with severe CAP and hospital-acquired pneumonia (HAP). Using advanced multi-omics analyses, we developed a systems model of SARS-CoV-2 pathogenesis, leading to a successful clinical trial of Auxora, which reduced 30-day mortality by 53% in phase II trials. Project 1 will use longitudinal clinical and molecular data with machine learning models to identify predictors of clinical outcomes and develop actionable insights and therapies for severe CAP.
Project 2 Summary: Microbial determinants of failure of antimicrobial therapy
The overall goal of SCRIPT² Research Project 2 is to develop a computational model that integrates host response patterns, pathogen genomic features, and pulmonary microbiome dynamics to predict clinical outcomes in patients with hospital-acquired pneumonia (HAP) and ventilator-associated pneumonia (VAP). Despite the use of advanced antibiotics, these infections remain associated with high mortality rates, emphasizing the need for deeper biological insights.
Organizational structure of SCRIPT²
NBBAL Extraction Process