In a manuscript published today in Immunity, scientists at the Baylor Institute for Immunology Research (BIIR) and the Benaroya Research Institute at Virginia Mason report the results of a comparative study of the molecular immune responses to influenza and pneumococcal vaccines. In addition, cutting-edge web technology was used to improve dissemination of data in order to accelerate the pace of scientific discovery. The article features interactive figures that can be customized and allow for dynamic investigation of the primary data from a web portal that was developed as part of this study and could serve as a model for future scientific publishing and data sharing.
The team, which was led by Damien Chaussabel, PhD at Benaroya and Jacques Banchereau, PhD , Virginia Pascual, MD, and Karolina Palucka, MD, PhD at BIIR, utilized a systems immunology approach and high-throughput profiling techniques to analyze the molecular and cellular responses following vaccination. They found that the influenza vaccine led to gene activity induced by interferon, while the pneumococcal vaccine led to an increase of myeloid- and inflammation-related gene activity, suggesting that the two vaccines elicit immune protection via distinct immune response pathways.
"This union of cutting-edge human immunology and state-of-the-art data mining capabilities really moves our research to the next level by streamlining the discovery process and identifying novel approaches to combating diseases," noted Dr. Palucka. "By understanding the immune pathways by which these vaccines work, we can better guide the development of effective vaccines for other infectious diseases."
Systems biology approaches like the one presented in this publication generate enormous amounts of data with measurements of tens of thousands of parameters. Often, much of the data sees little investigation. In order to extend the value of data generated in this study, the authors developed web applications to allow exploration of the data by the broader scientific community. The article links directly to figures in the web portal, which allows dynamic investigation of the presented figures and underlying data. Readers can interact with and customize the article's figures by adding variables or adjusting parameters. They are able to fine-tune their view of the data based on their own research interests and expertise and investigate additional hypotheses with the full dataset.