Tapioca – A Novel Platform for Prediction Of Protein-Protein Interaction Dynamics Identifies NUCKS1 as a Broad-Spectrum Herpesvirus Proviral Factor

Understanding protein-protein interaction (PPI) network dynamics is key to understanding nominal and perturbed cell states. Here, we develop a new machine learning framework called Tapioca that allows for the study of PPIs in dynamics contexts at a global scale in ex/in vivo conditions. Furthermore, we optimized the thermal denaturation and lysis conditions used in the thermal proximity coaggregation (TPCA) methodology, one of the types of data Tapioca can use to make predictions. Using this optimized protocol and Tapioca, we investigated the temporal dynamics of reactivation from latency of the oncogenic gammaherpesvirus Kaposi’s sarcoma-associated herpesvirus (KSHV), identifying the host protein NUCKS1 as a factor promoting KSHV genome replication during lytic infection. Integrating this dataset with published TPCA datasets from the alphaherpesvirus herpes simplex virus type-1 (HSV-1) and the betaherpesvirus human cytomegalovirus (HCMV), we determined NUCKS1 to have a proviral role across all three herpesvirus subfamilies.