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

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 method, we improved the experimental workflow. Finely tuned thermal denaturation afforded increased throughput, while cell lysis optimization enhanced protein detection from different subcellular compartments. The Tapioca workflow was next leveraged to investigate viral infection dynamics. Temporal PPIs were characterized during the reactivation from latency of the oncogenic Kaposi's sarcoma-associated herpesvirus. Together with functional assays, NUCKS was identified as a proviral hub protein, and a broader role was uncovered by integrating PPI networks from alpha- and betaherpesvirus infections. Altogether, Tapioca provides a web-accessible platform for predicting PPIs in dynamic contexts.

Differential Contributions of Interferon Classes to Host Inflammatory Responses and Restricting Virus Progeny Production.

Fundamental to mammalian intrinsic and innate immune defenses against pathogens is the production of Type I and Type II interferons, such as IFN-ß and IFN-γ, respectively. The comparative effects of IFN classes on the cellular proteome, protein interactions, and virus restriction within cell types that differentially contribute to immune defenses are needed for understanding immune signaling. Here, a multilayered proteomic analysis, paired with biochemical and molecular virology assays, allows distinguishing host responses to IFN-ß and IFN-γ and associated antiviral impacts during infection with several ubiquitous human viruses. In differentiated macrophage-like monocytic cells, we classified proteins upregulated by IFN-ß, IFN-γ, or pro-inflammatory LPS. Using parallel reaction monitoring, we developed a proteotypic peptide library for shared and unique ISG signatures of each IFN class, enabling orthogonal confirmation of protein alterations. Thermal proximity coaggregation analysis identified the assembly and maintenance of IFN-induced protein interactions. Comparative proteomics and cytokine responses in macrophage-like monocytic cells and primary keratinocytes provided contextualization of their relative capacities to restrict virus production during infection with herpes simplex virus type-1, adenovirus, and human cytomegalovirus. Our findings demonstrate how IFN classes induce distinct ISG abundance and interaction profiles that drive antiviral defenses within cell types that differentially coordinate mammalian immune responses.

DNA-PK and ATM drive phosphorylation signatures that antagonistically regulate cytokine responses to herpesvirus infection or DNA damage.

The DNA-dependent protein kinase, DNA-PK, is an essential regulator of DNA damage repair. DNA-PK-driven phosphorylation events and the activated DNA damage response (DDR) pathways are also components of antiviral intrinsic and innate immune responses. Yet, it is not clear whether and how the DNA-PK response differs between these two forms of nucleic acid stress-DNA damage and DNA virus infection. Here, we define DNA-PK substrates and the signature cellular phosphoproteome response to DNA damage or infection with the nuclear-replicating DNA herpesvirus, HSV-1. We establish that DNA-PK negatively regulates the ataxia-telangiectasia-mutated (ATM) DDR kinase during viral infection. In turn, ATM blocks the binding of DNA-PK and the nuclear DNA sensor IFI16 to viral DNA, thereby inhibiting cytokine responses. However, following DNA damage, DNA-PK enhances ATM activity, which is required for IFN-ß expression. These findings demonstrate that the DDR autoregulates cytokine expression through the opposing modulation of DDR kinases.

Seeded Chain-Growth Polymerization of Proteins in Living Bacterial Cells.

Microbially produced protein-based materials (PBMs) are appealing due to use of renewable feedstock, low energy requirements, tunable side-chain chemistry, and biodegradability. However, high-strength PBMs typically have high molecular weights (HMW) and repetitive sequences that are difficult to microbially produce due to genetic instability and metabolic burden. We report the development of a biosynthetic strategy termed seeded chain-growth polymerization (SCP) for synthesis of HMW PBMs in living bacterial cells. SCP uses split intein (SI) chemistry to cotranslationally polymerize relatively small, genetically stable material protein subunits, effectively preventing intramolecular cyclization. We apply SCP to bioproduction of spider silk in Escherichia coli, generating HMW spider silk proteins (spidroins) up to 300 kDa, resulting in spidroin fibers of high strength, modulus, and toughness. SCP provides a modular strategy to synthesize HMW, repetitive material proteins, and may facilitate bioproduction of a variety of high-performance PBMs for broad applications.