Supramolecular Organization Predicts Protein Nanoparticle Delivery to Neutrophils for Acute Lung Inflammation Diagnosis and Treatment

Jacob W. Myerson; Priyal N. Patel; Nahal Habibi; Landis R. Walsh; Yi-Wei Lee; David C. Luther; Laura T. Ferguson; Michael H. Zaleski; Marco E. Zamora; Oscar A. Marcos-Contreras; Patrick M. Glassman; Ian Johnston; Elizabeth D. Hood; Tea Shuvaeva; Jason V. Gregory; Raisa Y. Kiseleva; Jia Nong; Kathryn M. Rubey; Colin F. Greineder; Samir Mitragotri; George S. Worthen; Vincent M. Rotello; Joerg Lahann; Vladimir R. Muzykantov; Jacob S. Brenner

Principal component analysis comparing normalized nanoparticle uptake in inflamed lungs to normalized retention in liver, spleen, and blood provided a reductive metric to compare the distinct in vivo behavior of nanoparticles in the classes identified . CC-BY-NC-ND 4.0 International license author/funder. It is made available under a The copyright holder for this preprint (which was not peer-reviewed) is the . https://doi.org/10.1101/2020.04.15.037564 doi: bioRxiv preprint by linear discriminant analysis. Most variation in the biodistribution data was accounted for by an eigenvector closely aligned to variation in pulmonary uptake (Supplementary Figure 21a) . Data was projected along that first eigenvector and magnitude of the projection was determined for each nanoparticle (Supplementary Figure 21b) . First eigenvector projection values were then grouped according to the classes examined above via linear discriminant analysis. Only the classes in the inflammation-specific kmeans cluster had positive average first eigenvector projections. All other particle classes had average first eigenvector projections indistinguishable from isolated protein (Supplementary Figure 21b) .