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Results for “quantitative interactomics”

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12 recordsLinked to original sources
PubMed2026

Quantitative interactome mapping of skeletal muscle insulin resistance.

Protein-protein interactions (PPIs) are dynamic and critical to adaptive homeostasis. While there have been massive efforts to catalogue proteome-wide PPIs, global quantification of changes remains a challenge. Here, we integrate dynamic protein correlation profiling - mass spectrometry (PCP-MS) and quantitative cross linking-mass spectrometry (qXL-MS) using multiplexed stable isotope labelling to characterise global PPI remodelling following the development of chronic skeletal muscle insulin resistance (IR) with or without acute insulin stimulation. We quantify >7,000 unique PPIs amongst 5,346 proteins and show changes in the interactome network dominate the proteome response. Our data show the dysregulation of protein processing in the endoplasmic/sarcoplasmic reticulum involving changes in PPIs with protein chaperones and disulfide isomerases is a major hallmark of skeletal muscle IR. Mechanistically, we show the dysregulation of PPIs with Protein-Disulfide Isomerase 6 (PDIA6) regulates cysteine oxidation and insulin sensitivity. Taken together, we show in vivo quantitative interactome mapping is a powerful approach to understand disease mechanisms and provide new insights into protein network re-organisations with IR.

Insulin Resistance↗
PubMed2026

Quantitative analysis of DNA-GATA1 binding alterations linked to hematopoietic disorders.

GATA1 is a crucial transcription factor involved in hematopoiesis and mutations in this gene are linked to severe hematological disorders, including anemia, thrombocytopenia, Down syndrome-related transient abnormal myelopoiesis (DS-TAM), and myeloid leukemia of Down syndrome (ML-DS). Despite significant clinical interest in the molecular level characterization of GATA1 mutations, a comprehensive understanding of their impact on DNA binding is limited. Efforts to conduct detailed studies on full-length recombinant GATA1 have faced significant technical challenges, while alternative approaches are limited by low throughput or qualitative nature. Here, we introduce a native holdup (nHU) assay designed to systematically quantify DNA-protein interactions and is suitable for studying the impact of transcription factor mutations on DNA binding affinity. First, using the erythroid-specific ATP2B4 promoter as a model, we demonstrate that nHU can capture sequence-specific interactions and detect even subtle differences in DNA binding affinities. Then, we quantitatively characterize the impact of pathological mutations on DNA binding affinities in the context of full-length human GATA1. Our findings reveal that the GATA1s isoform, lacking the N-terminal transactivation domain (N-TAD), binds to DNA with increased affinity, while the R307C mutation reduces binding to the ATP2B4 erythroid promoter. In harmony with these observations, GATA1s exhibits increased functional activity, while the R307C mutation results in decreased activity. This study demonstrates the power of the nHU assay for studying DNA interactions of transcription factor variants and providing insight into the molecular mechanism of related diseases.

GATA1 Transcription Factor↗
PubMed2026

Proteome-wide structural and interaction analysis using cross-linking mass spectrometry and its applications.

Deciphering the mechanisms of protein-protein interactions (PPIs) and protein structural changes within the native cellular environment is crucial for advancing drug discovery. In vivo chemical cross-linking coupled with mass spectrometry (XL-MS) captures weak, transient, and higher-order interactions that are often dysregulated under altered physiological conditions and remain challenging to detect using conventional methods. Applications of in vivo XL-MS range from targeted mapping of PPIs to large-scale identification of interactome networks within the cells. The integration of quantitative approaches further facilitates comparison across different physiological conditions. The recent incorporation of machine learning (ML) tools into XL-MS workflows is transforming the depth and efficiency of this technology. AI-driven algorithms now enable more accurate identification of cross-linked peptides and the mapping of interaction topologies. Furthermore, the synergistic coupling of in vivo XL-MS data with AI-assisted structural modeling platforms such as AlphaFold allows dynamic and high-throughput prediction of protein networks. This review discusses the broader applications of in vivo XL-MS in complex biological samples, ranging from organelles and cells to whole tissues, and highlights how AI integration is expanding structural biology toward a systems-level understanding of proteome architecture.

Mass Spectrometry↗
PubMed2026

Proteome-wide Ubiquitinome Profiling Reveals Substrate-specific Dynamics Within the USP7 Network.

USP7 is a pleiotropic deubiquitylating enzyme that is involved in tumor suppression, (neuro) development, chromatin regulation and the DNA damage response. How USP7 regulates these diverse pathways is still unclear. Here, we report data-independent acquisition and label free quantitation mass spectrometry to profile the proteome-wide impact of USP7 on substrate de-ubiquitylation and overall protein abundance. First, we identified proteins associated with endogenous USP7 by immunopurification followed by data-independent acquisition and label free quantitation mass spectrometry. Integration of our new results with earlier interactomes of epitope-tagged USP7 yielded a consensus set of high-confidence protein targets. Domain mapping analysis revealed that, in addition to the TRAF domain, the ubiquitin-like domains of USP7 play a key role in substrate selection. Using specific enrichment of tryptic K-ε-GG peptides, we mapped proteome-wide changes in ubiquitinome dynamics following inhibition of USP7. Combining unbiased proteome-wide and targeted quantitative mass spectrometry revealed that deubiquitylation by USP7 can have different effects on the stability of distinct substrates, and suggests that USP7's activity profile is substrate-dependent rather than an intrinsic enzymatic property. Thus, in addition to providing a proteome-wide map of USP7 target sites, our multi-angle proteomics approach reveals that the effects of USP7-mediated deubiquitylation on its targets are remarkably variable and substrate-specific. Finally, based on these detailed molecular insights we show how USP7 connects various neurodevelopmental syndromes and tumor suppression pathways.

Ubiquitin-Specific Peptidase 7↗
PubMed2026

Structure-resolved virus-host interactomics by cross-linking mass spectrometry.

Viruses depend on host protein networks to replicate, assemble progeny, and spread between cells and organisms. Defining these virus-host protein interactions is challenging because they are highly dependent on infection stage, cell type, species, and because mechanistic interpretation requires information about structural interfaces and conformational states. Cross-linking mass spectrometry (XL-MS) addresses these challenges by adding a spatial and structural dimension to virus-host interactomics in native systems. In this review, we discuss how XL-MS has advanced from targeted analysis of viral protein complexes to structure-resolved mapping of virion architecture and infected-cell virus-host interactomes. We highlight how XL-MS complements AP-MS, cryo-EM/cryo-ET, quantitative proteomics, genetic perturbation, and structure prediction to connect physical proximity with molecular mechanisms. Finally, we discuss current limitations in sensitivity, chemical coverage, temporal resolution, and model interpretation, and outline how future quantitative and integrative XL-MS workflows may enable systems-level structural virology.

Mass Spectrometry↗
PubMed2025

Definition of the human mitochondrial TOM interactome reveals TRABD as a new interacting protein.

The mitochondrial proteome arises from dual genetic origins. Nuclear-encoded proteins need to be transported across or inserted into two distinguished membranes, and the translocase of the outer mitochondrial membrane (TOM) complex represents the main translocase in the outer mitochondrial membrane. Its composition and regulation have been extensively investigated within yeast cells. However, we have little knowledge of the TOM complex composition within human cells. Here, we have defined the TOM interactome in a comprehensive manner using biochemical approaches to isolate the TOM complex in combination with quantitative mass spectrometry analyses. With these studies, we defined the pleiotropic nature of the human TOM complex, including new interactors, such as TRABD. Our studies provide a framework to understand the various biogenesis pathways that merge at the TOM complex within human cells.

Humans↗
PubMed2026

A Spatiotemporal Atlas of the Androgen Receptor Proximal Interactome.

Androgen receptor-interacting proteins (AR-IPs) number close to 1,000, yet their organization across subcellular space and time remains uncharted. Proximity labeling identifies direct partners and neighboring proteins, thereby expanding AR-IPs to AR-proximal interacting proteins (AR-PIPs). Using proximity labeling quantitative mass spectrometry (PL-qMS), we construct a spatiotemporal atlas of the cytosolic, microsomal, and nuclear compartments in LNCaP prostate tumor cells. PL-qMS recovered 82.2% of the known AR-interactome in extranuclear compartments and 84.2% in the nucleus, identifying 4,751 AR-PIPs that remodel across an androgen time course. The retromer formed an androgen-sensitive AR-proximal interaction network (AR-PIN) verified by proximity ligation assays (PLAs). Moreover, partial VPS26A disruption attenuated androgen-regulated transcription and mislocalized the AR coactivator TMF1, defining a retromer-AR-TMF1 axis. In the nucleus, AR-PINs recover 100% of the Launonen 2021 ChIP-SICAP chromatome and reveal a PLA-verified translation-to-transcription handoff involving eIF4G and 4E-BP1. This spatiotemporal atlas provides a proximal framework for probing AR function in cells.

Journal Article↗
PubMed2026

Mapping the covalent cysteine interactome of Ebselen reveals high-sensitivity target engagement and redox proteome remodeling.

Ebselen is a covalent organoselenium compound with broad pharmacological activity, yet its cellular cysteine targets and downstream proteomic consequences remain incompletely defined. Here, we integrated competitive gel-based activity-based protein profiling, reactivity-dependent tandem orthogonal proteolysis-activity-based protein profiling, and TMT-based quantitative proteomics to map Ebselen-induced cysteine engagement and proteome remodeling in living cancer cells. Ebselen exhibited dose-dependent cytotoxicity and markedly perturbed intracellular thiol-redox balance, as reflected by glutathione depletion and altered reactive oxygen species-associated fluorescence readouts. Competitive gel-based profiling confirmed concentration-dependent engagement of protein cysteine residues in live cells. Quantitative rdTOP-ABPP further identified hundreds of dose-responsive cysteine sites in HeLa and HepG2 cells and revealed a preference for cysteine microenvironments enriched with basic residues. Cross-cell-line comparison highlighted CDK5 Cys53, SMU1 Cys298, and RPSA2 Cys163 as conserved covalent nodes, among which CDK5 Cys53 showed high sensitivity to Ebselen treatment, a finding validated by competitive labeling and MS-based site assignment. Global TMT proteomics revealed extensive remodeling of redox-related and cell-survival-associated pathways, including compensatory upregulation of selenoproteins such as TXNRD1 and GPX family members. Together, these results define a chemical proteomic atlas of Ebselen-cysteine interactions and provide a framework for understanding and optimizing covalent organoselenium therapeutics.

Humans↗
PubMed2025

Spatiotemporally resolved GPCR interactome uncovers unique mediators of receptor agonism.

Cellular signaling by membrane G protein-coupled receptors (GPCRs) is governed by a complex and diverse array of mechanisms. The dynamics of a GPCR interactome, as it evolves over time and space in response to an agonist, provide a unique perspective on pleiotropic signaling decoding and functional selectivity at the cellular level. In this study, we utilized proximity-based APEX2 proteomics to investigate the interaction network of the luteinizing hormone receptor (LHR) on a minute-to-minute timescale. We developed an analytical approach that integrates quantitative multiplexed proteomics with temporal reference profiles, creating a platform to identify the proteomic environment of APEX2-tagged LHR at the nanometer scale. LHR activity is finely regulated spatially, leading to the identification of putative interactors, including the Ras-related GTPase RAP2B, which modulate both receptor signaling and post-endocytic trafficking. This work provides a valuable resource for spatiotemporal nanodomain mapping of LHR interactors across subcellular compartments.

Humans↗
PubMed2026

Kv11.1 (hERG) Protein Interaction Networks Connect Endocytic Trafficking to Polygenic Influences on Cardiac Repolarization.

Polygenic scores (PGS) capture the combined effect of many common genetic variants on quantitative traits and disease risk, yet their functional consequences at the protein level remain poorly defined. Here, we integrated quantitative and interaction proteomics to resolve how polygenic liability for cardiac repolarization manifests in human cells. We studied human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from donors with extreme PGS for QT interval duration, a clinically relevant electrophysiologic trait associated with arrhythmia risk. Global quantitative proteomics revealed increased abundance of mitochondrial proteins in high-PGS cardiomyocytes. To define protein network-level effects on a key repolarizing ion channel, we performed multiplexed affinity purification-mass spectrometry (AP-MS) of Kv11.1. While mitochondrial changes did not directly explain Kv11.1-associated complexes, interactome analysis revealed increased association of Kv11.1 with myosin motor proteins and endosomal recycling machinery in high-PGS cells. These findings suggest altered channel trafficking dynamics of Kv11.1, distinct from the trafficking defects observed in monogenic Kv11.1 variants. Together, these data show that integrating global and interaction proteomics can resolve how polygenic variation reshapes protein networks. Future work using these methods could connect genomic risk to subcellular remodeling and our work provides a generalizable framework to probe the proteomic basis of complex traits. SIGNIFICANCE STATEMENT: Polygenic scores (PGS) predict disease risk, but how biological pathways are influenced by these common variants remains difficult to define. We generated human induced pluripotent stem cells from individuals with extreme high- and low- PGS for QT interval, a key electrocardiographic measure linked to arrhythmia risk. By combining global proteomics and interactomics for a common ion channel involved in regulating the QT interval (Kv11.1) we found potential mechanisms that are influenced by common genetic traits in patients. Our work provides an approach to connect polygenic scores to pathway-level molecular mechanisms in human cells and a general framework for uncovering how complex genetic architecture drives disease-relevant biology.

AP-MS↗
PubMed2025

Mapping the FOXA1 Interactome in ER+ Breast Cancer Cells Using Proximity Labeling Reveals Novel Interactions with the Orphan Nuclear Receptor NR2C2.

UNLABELLED: FOXA1 is a pioneer transcription factor essential for chromatin accessibility and transcriptional regulation in hormone-driven cancers. In breast cancer, FOXA1 plays a central role in facilitating nuclear receptor binding, reprogramming enhancer landscapes, and promoting transcriptional changes associated with therapy resistance. Whereas FOXA1's function has been primarily studied in the context of estrogen receptor-α (ER), its broader protein interaction network remains incompletely defined. In this study, we systematically map FOXA1-interacting proteins in ER-positive breast cancer cells using proximity-dependent biotin labeling (miniTurbo) combined with quantitative LC-MS/MS proteomics. We engineered MCF-7 cell lines stably expressing miniTurbo-tagged FOXA1 at either the N-terminus or C-terminus to ensure comprehensive coverage of interaction interfaces. This approach recovered known FOXA1 partners, including AR, MLL3, YAP1, and GATA3, and identified 157 previously unreported FOXA1 interactors. Notably, 42 of these novel partners, including NR2C2, were significantly associated with poor relapse-free survival in patients with ER-positive breast cancer. To demonstrate the utility of this resource, we characterized the FOXA1-NR2C2 interaction in depth. Integrating chromatin immunoprecipitation sequencing and RNA sequencing, we show that FOXA1 and NR2C2 co-occupy a subset of genomic regions and drive co-regulated transcriptional programs involved in tumor progression. Our study reveals an expanded FOXA1 interactome and new insights into its functional network in breast cancer, providing candidate proteins for further exploration as biomarkers or therapeutic targets. IMPLICATIONS: These findings expand the FOXA1 interactome in breast cancer and uncover new candidate proteins with potential as biomarkers and therapeutic targets in hormone-driven tumors.

Humans↗
PubMed2025

The glycoprotein quality control factor Malectin promotes coronavirus replication and viral protein biogenesis.

Coronaviruses (CoV) rewire host protein homeostasis (proteostasis) networks through interactions between viral nonstructural proteins (nsps) and host factors to promote infection. With the emergence of SARS-CoV-2, it is imperative to characterize host interactors shared across nsp homologs. Using quantitative proteomics and functional genetic screening, we identify conserved proteostasis interactors of nsp2 and nsp4 that serve pro-viral roles during infection of murine hepatitis virus - a model betacoronavirus. We uncover a glycoprotein quality control factor, Malectin (MLEC), which significantly reduces infectious titers when knocked down. During infection, nsp2 interacts with MLEC-associated proteins and the MLEC-interactome is drastically altered but retains association with the Oligosaccheryltransferase (OST) complex, a crucial component of viral glycoprotein production. MLEC promotes viral protein levels and genome replication through its quality control activity. Lastly, we show MLEC promotes SARS-CoV-2 replication. Our results reveal a role for MLEC in mediating CoV infection and identify a potential target for pan-CoV antivirals.

Biochemistry and Chemical Biology↗