Dataset Information

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

ABSTRACT: 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.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Homo Sapiens (human) Human Herpesvirus 8 Strain Gk18

SUBMITTER: Tavis Reed

LAB HEAD: Ileana M.

PROVIDER: PXD041152 | Pride | 2025-05-06

REPOSITORIES: Pride

ACCESS DATA

Dataset's files

Source:

			Action	DRS
	20211201_TR_CHAPS_Lysis_Rep_12_Frac_1.raw	Raw
	20211201_TR_CHAPS_Lysis_Rep_12_Frac_2.raw	Raw
	20211201_TR_CHAPS_Lysis_Rep_12_Frac_3.raw	Raw
	20211201_TR_CHAPS_Lysis_Rep_12_Frac_4.raw	Raw
	20211201_TR_CHAPS_Lysis_Rep_12_Frac_5.raw	Raw

Items per page:

1 - 5 of 359

Publications

Tapioca: a platform for predicting de novo protein-protein interactions in dynamic contexts.

Reed Tavis J TJ Tyl Matthew D MD Tadych Alicja A Troyanskaya Olga G OG Cristea Ileana M IM

Nature methods 20240215 3

Protein-protein interactions (PPIs) drive cellular processes and responses to environmental cues, reflecting the cellular state. Here we develop Tapioca, an ensemble machine learning framework for studying global PPIs in dynamic contexts. Tapioca predicts de novo interactions by integrating mass spectrometry interactome data from thermal/ion denaturation or cofractionation workflows with protein properties and tissue-specific functional networks. Focusing on the thermal proximity coaggregation m ...[more]

PMID: 38361019

Similar Datasets

Project description:Rapid and dynamically shifting protein-protein interactions (PPIs) underlie the capacity of cells to recognize viral infections and ignite the downstream cascades that constitute the innate-immune response. Herpesviruses share an ancient history of coevolution with their hosts and have developed reciprocal methods to suppress or hijack immune response proteins — underscoring the biological complexity of host-pathogen interactions during the immune response. Accordingly, conventional approaches to studying PPIs downstream of innate immune sensing fail to capture both the global scope and the dynamic on-off behavior of protein complexes as they are altered throughout cellular space and time. To overcome this barrier, we have applied Thermal Proteome Profiling Mass Spectrometry (TPP-MS) to systemically characterize PPIs that coordinate the innate-immune response to Herpes Simplex Virus 1 (HSV-1) infection in primary human fibroblasts. Further, by advancing the power of thermal protein co ggregation analysis (TPCA) to infer associations de novo and to globally track these PPIs, we developed a time-resolved portrait of cellular and viral protein associations with IFI16, a nuclear DNA sensor that serves as a central platform for HSV-1 immune responses. Our TPCA analysis, along with high-resolution microscopy and molecular virological techniques, linked IFI16 sensing of viral DNA in the nuclear periphery to the master DNA damage response (DDR) regulatory kinase, DNA-PK — the activation of which we show to be necessary for the antiviral and inflammatory responses to infection. Finally, phospho-peptide enrichment and MS analysis of DNA-PK substrates revealed IFI16 to be targeted by DNA-PK after both DNA damage and viral infection. Functional analysis of this DDR-dependent IFI16 phosphorylation revealed the specific modified residue required for IFI16-driven cytokine responses. Altogether, our study represents the first systems-wide characterization of the global dynamics of PPIs during HSV-1 infection and uncovers a missing link in the immune signaling pathway that places IFI16 and DNA-PK at the center of herpesvirus innate immunity.