Mira Lea Burtscher

Bacteria and bacteriophages are in a constant arms race to develop defence and anti-defence systems, respectively. Currently known phage-encoded anti-defence systems are specific to the activity of the targeted bacterial defence system. Here we identify a mechanism by which the T7 bacteriophage broadly counteracts bacterial defences using protein phosphorylation. Its kinase (T7K), which has been reported to redirect the function of a few host proteins ^1–5 , is actually a hyperpromiscuous dual-specificity kinase that phosphorylates nearly all host and phage proteins during infection. The scale of phosphorylation vastly exceeds known phosphosites in Escherichia coli , has no sequence motif specificity and results in a higher proteome-wide phosphorylation density than mammalian cells with around 500 kinases. Stoichiometry analysis of phosphorylation sites revealed strong bias in T7K activity towards nucleic-acid-binding substrates mediated by its C-terminal DNA-binding domain. This highly stoichiometric phosphorylation enables the deactivation of DNA-targeting or DNA-containing bacterial defence systems. We provide mechanistic insights into how T7K weakens DNA-containing Retron-Eco9 through specific phosphorylation events, with single phosphomimetic mutations in key sites of the toxin abolishing defence. Moreover, by screening a large collection of E. coli strains, we provide evidence of broad anti-defence abilities of T7K in nature, as counteracted strains contain diverse bacterial defence systems. T7K homologues are found almost exclusively in phages, with hyperpromiscuous kinase activity probably being enabled by a divergent DFG-like motif in the catalytic centre.

Influenza A virus (IAV) hijacks host cellular machinery during infection but many host–virus protein interactions remain uncharacterized, particularly in their native context. Here, we applied in-cell cross-linking mass spectrometry, integrated with structural modelling and functional assays, to map protein–protein contact sites in IAV-infected human cells. This revealed previously unrecognized virus–host interactions linked to spatially organized processes. We identified host factors linked to the maturation of distinct glycoforms of the viral surface glycoprotein haemagglutinin through the membrane-bound endoplasmic reticulum–Golgi system. In the nucleus, we observed the progressive disassembly of paraspeckles (phase-separated membraneless compartments) across multiple cell lines. Mechanistically, viral nucleoprotein and non-structural protein 1 interact with host paraspeckle proteins, the viral endonuclease PA-X degrades long non-coding RNA housed within paraspeckles and viral RNA polymerase II is inhibited to drive paraspeckle disruption, which releases host factors that facilitate IAV replication. These findings uncover mechanisms by which IAV exploits and remodels host compartments during infection.

Signaling pathways are useful models for interpreting molecular data, but their coverage has long been constrained by classic biochemistry methods. The growing corpus of kinase-substrate interactions, coupled to phosphoproteomics improvements, pave the way to revisit classic signaling pathways. In this study, we explore context-specific signaling pathway inference from phosphoproteomics and kinase-substrate networks. Focusing on epidermal growth factor (EGF), we conduct a meta-analysis and generate three datasets representing the most comprehensive characterization of the EGF response to date. We infer kinase-kinase pathways and compare them to different ground truth sets. Literature-curated networks consistently yield the highest recovery of ground-truth interactions, with modest gains from network propagation methods. Up to 90% of interactions are absent from current ground truth sets, indicating many unexplored interactions supported by data and knowledge. Our results demonstrate the limitations of traditional views on signaling pathways and point to opportunities for generating better mechanistic hypotheses.

Dysregulated kinase activity drives oncogenic signaling, disrupts cellular homeostasis, and promotes tumour progression. The BRAFV600E mutation constitutively activates the MAPK pathway and is a key therapeutic target in melanoma and other cancers, but the functional relevance of most downstream phosphorylation events and mechanisms of drug resistance remain unclear. To address this, a global multi-omic model of BRAF inhibition response was established in BRAFV600E-mutant cells by integrating time-resolved and biophysical phosphoproteomics, transcriptomics, and thermal proteome profiling. Ultradeep phosphoproteomics revealed extensive phosphorylation changes upon BRAF inhibitor treatment, while biophysical phosphoproteomics identified phosphorylation events linked to altered protein solubility and subcellular localization, suggesting changes in nucleic acid interactions and nuclear reorganisation. Network-based integration of these datasets prioritized functionally relevant phosphorylation sites and kinases. Experimental validation identified CDK9, CLK3, and TNIK as critical regulators of BRAFV600E signaling and candidate targets for combinatorial inhibition capable of re-sensitising resistant cells. The transcription factor ETV3 emerged as a previously unrecognised effector of BRAF signaling. Biophysical proteomics data confirmed that ETV3 phosphorylation modulates DNA-binding, while functional assays combining knockdown, metabolomics, and drug screening demonstrated its role in coordinating transcriptional and metabolic adaptations to BRAF inhibition. This study provides a systems-level framework linking phosphorylation dynamics to protein function and phenotype, identifies ETV3 as a new node in oncogenic BRAF signaling, and illustrates how integrated, site-resolved models can reveal mechanisms of kinase-driven oncogenesis. Highlights: Time- and cell type-resolved phosphoproteomics maps BRAF inhibition dynamics Biophysical phosphoproteomics, combining quantitative phosphoproteomics with solubility profiling or nuclear fractionation, reveals phosphorylation-driven changes of protein solubility and localization Integration of abundance and biophysical phosphoproteomics data identifies functionally relevant phosphorylation events of BRAFV600E signaling Network integration of multimodal phosphoproteomic, transcriptomic and thermal proteome profiling data links signaling to protein function and cellular phenotypes Biophysical evidence improves models and identifies non-canonical kinases driving BRAF signaling as well as novel downstream regulators such as ETV3 Follow-up experiments reveal a ETV3-GLUT3-mediated metabolic adaptation in BRAFV600E cells

Kidney fibrosis, characterized by excessive extracellular matrix deposition, is a progressive disease that, despite affecting 10% of the population, lacks specific treatments and suitable biomarkers. This study presents a comprehensive, time-resolved multi-omics analysis of kidney fibrosis using an in vitro model system based on human kidney PDGFRβ ⁺ mesenchymal cells aimed at unraveling disease mechanisms. Using transcriptomics, proteomics, phosphoproteomics, and secretomics, we quantified over 14,000 biomolecules across seven time points following TGF-β stimulation. This revealed distinct temporal patterns in the expression and activity of known and potential kidney fibrosis markers and modulators. Data integration resulted in time-resolved multi-omic network models which allowed us to propose mechanisms related to fibrosis progression through early transcriptional reprogramming. Using siRNA knockdowns and phenotypic assays, we validated predictions and regulatory mechanisms underlying kidney fibrosis. In particular, we show that several early-activated transcription factors, including FLI1 and E2F1, act as negative regulators of collagen deposition and propose underlying molecular mechanisms. This work advances our understanding of the pathogenesis of kidney fibrosis and provides a resource to be further leveraged by the community.

Bacteria and bacteriophages are in a constant arms race to develop bacterial defense and phage counter-defense systems. Currently known phage counter-defense systems are specific to (the activity of) the targeted bacterial defense system. Here, we uncover a mechanism by which the T7 bacteriophage broadly counteracts bacterial defenses using protein phosphorylation. We show that the T7 protein kinase (T7K), which was believed to specifically redirect the function of a few host proteins, is in fact a hyper-promiscuous, dual-specificity kinase enacting a massive wave of phosphorylation on virtually all host and phage proteins during infection. The scale of phosphorylation vastly exceeds the number of previously known phosphorylation events in E. coli, has no sequence motif specificity, and results in a higher proteome-wide phosphorylation density than that of mammalian cells which encode ~ 500 kinases. Stoichiometry analysis of phosphorylation sites revealed a strong bias of T7K activity towards nucleic acid-binding substrates, which we show is mediated by its C-terminal DNA-binding domain. This specificity for highly stoichiometric phosphorylation of nucleic acid-binding proteins enables the deactivation of DNA-targeting or -containing bacterial defense systems. We provide mechanistic insight into how T7K weakens two such defense systems, Retron-Eco9 and DarTG1, through specific phosphorylation events, with single phosphomimetic mutations in key sites of the toxins abolishing defense. Finally, by screening a large collection of E. coli strains, we provide evidence of broad counter-defense capacities for T7K in nature, as strains counteracted contain diverse bacterial defense systems.

Cellular signaling plays a vital role in how cells communicate and adapt to both environmental and internal cues. At the molecular level, signaling is largely driven by phosphorylation cascades controlled by kinases. Because of this, kinase-driven signaling pathways are used as a conceptual framework to interpret molecular data across biological contexts. However, signaling pathways were created using limited throughput technologies. As knowledge of kinase-substrate interactions grows through novel computational and experimental approaches, and phosphoproteomic methods improve their coverage and accuracy, traditional signaling pathways need to be revisited. In this study, we critically assess context-specific signaling pathway reconstruction using phosphoproteomics and kinase-substrate networks. We first integrate literature, protein language models, and peptide array data to create a state-of-the-art kinase-substrate network. Focusing on epidermal growth factor (EGF), we conduct a meta-analysis of recent short-term response phosphoproteomics studies, which we complement with three own datasets, representing the most comprehensive characterization of the EGF response available to date. Using three alternative computational methods, we infer kinase-driven pathways, which we compare to multiple ground truth sets, including the canonical pathway, experimentally validated interactions, and correlation supported interactions. Our findings reveal that literature-curated networks, when combined with network propagation, yield the best recovery of ground truth interactions. We found that up to 90% of data-supported direct interactions are absent from current ground truth sets, indicating many unexplored, but data supported kinase interactions. Our results challenge traditional views on signaling pathways and illustrate how to develop new mechanistic hypotheses using phosphoproteomics and network methods.

Kidney fibrosis, characterized by excessive extracellular matrix deposition, is a progressive disease that, despite affecting 10% of the population, lacks specific treatments and suitable biomarkers. This study presents a comprehensive, time-resolved multi-omics analysis of kidney fibrosis using an in vitro model system based on human kidney PDGFRβ+ mesenchymal cells aimed at unraveling disease mechanisms. Using transcriptomics, proteomics, phosphoproteomics, and secretomics we quantified over 14,000 biomolecules across seven time points following TGF-β stimulation. This revealed distinct temporal patterns in the expression and activity of known and potential kidney fibrosis markers and modulators. Data integration resulted in time-resolved multi-omic network models which allowed us to propose mechanisms related to fibrosis progression through early transcriptional reprogramming. Using siRNA knockdowns and phenotypic assays, we validated predictions and regulatory mechanisms underlying kidney fibrosis. In particular, we show that several early-activated transcription factors, including FLI1 and E2F1, act as negative regulators of collagen deposition and propose underlying molecular mechanisms. This work advances our understanding of the pathogenesis of kidney fibrosis and provides a resource to be further leveraged by the community.

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Complex disease phenotypes often span multiple molecular processes. Functional characterization of these processes can shed light on disease mechanisms and drug effects. Thermal Proteome Profiling (TPP) is a mass-spectrometry (MS) based technique assessing changes in thermal protein stability that can serve as proxies of functional protein changes. These unique insights of TPP can complement those obtained by other omics technologies. Here, we show how TPP can be integrated with phosphoproteomics and transcriptomics in a network-based approach using COSMOS, a multi-omics integration framework, to provide an integrated view of transcription factors, kinases and proteins with altered thermal stability. This allowed us to recover consequences of Poly (ADP-ribose) polymerase (PARP) inhibition in ovarian cancer cells on cell cycle and DNA damage response as well as interferon and hippo signaling. We found that TPP offers a complementary perspective to other omics data modalities, and that its integration allowed us to obtain a more complete molecular overview of PARP inhibition. We anticipate that this strategy can be used to integrate functional proteomics with other omics to study molecular processes.