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At least 19 recordsLinked to original sources

PubMed2026

The Lipid Interactome: an interactive and open access platform for exploring cellular lipid-protein interactions.

SUMMARY: Lipid-protein interactions play essential roles in cellular signaling and membrane dynamics, yet their systematic characterization has long been hindered by the inherent biochemical properties of lipids. Recent advances in functionalized lipid probes-equipped with photoactivatable crosslinkers, affinity handles, and photocleavable protecting groups-have enabled proteomics-based identification of lipid interacting proteins with unprecedented specificity and resolution. Despite the growing number of published lipid interactomes, there remains no centralized effort to harmonize, compare, or integrate these datasets. The Lipid Interactome addresses this gap by providing a structured, interactive web portal that adheres to FAIR data principles-ensuring that lipid interactome studies are Findable, Accessible, Interoperable, and Reusable. Through standardized data formatting, interactive visualizations, and direct cross-study comparisons, this resource enables researchers to systematically explore the protein-binding partners of diverse bioactive lipids. By consolidating and curating lipid interactome proteomics data from multiple studies, the Lipid Interactome database serves as a critical tool for deciphering the biological functions of lipids in cellularsystems. AVAILABILITY AND IMPLEMENTATION: This site can be viewed at LipidInteractome.org. All data are available for download. No user information is collected or necessary for data navigation, interaction, or download.

Proteins↗

PubMed2024

MACSPI enables tissue-selective proteomic and interactomic analyses in multicellular organisms.

Multicellular organisms are composed of many tissue types that have distinct morphologies and functions, which are largely driven by specialized proteomes and interactomes. To define the proteome and interactome of a specific type of tissue in an intact animal, we developed a localized proteomics approach called Methionine Analog-based Cell-Specific Proteomics and Interactomics (MACSPI). This method uses the tissue-specific expression of an engineered methionyl-tRNA synthetase to label proteins with a bifunctional amino acid 2-amino-5-diazirinylnonynoic acid in selected cells. We applied MACSPI in Caenorhabditis elegans, a model multicellular organism, to selectively label, capture, and profile the proteomes of the body wall muscle and the nervous system, which led to the identification of tissue-specific proteins. Using the photo-cross-linker, we successfully profiled HSP90 interactors in muscles and neurons and identified tissue-specific interactors and stress-related interactors. Our study demonstrates that MACSPI can be used to profile tissue-specific proteomes and interactomes in intact multicellular organisms.

Animals↗

PubMed2024

Insights Into Glycobiology and the Protein-Glycan Interactome Using Glycan Microarray Technologies.

Glycans linked to proteins and lipids and also occurring in free forms have many functions, and these are partly elicited through specific interactions with glycan-binding proteins (GBPs). These include lectins, adhesins, toxins, hemagglutinins, growth factors, and enzymes, but antibodies can also bind glycans. While humans and other animals generate a vast repertoire of GBPs and different glycans in their glycomes, other organisms, including phage, microbes, protozoans, fungi, and plants also express glycans and GBPs, and these can also interact with their host glycans. This can be termed the protein-glycan interactome, and in nature is likely to be vast, but is so far very poorly described. Understanding the breadth of the protein-glycan interactome is also a key to unlocking our understanding of infectious diseases involving glycans, and immunology associated with antibodies binding to glycans. A key technological advance in this area has been the development of glycan microarrays. This is a display technology in which minute quantities of glycans are attached to the surfaces of slides or beads. This allows the arrayed glycans to be interrogated by GBPs and antibodies in a relatively high throughput approach, in which a protein may bind to one or more distinct glycans. Such binding can lead to novel insights and hypotheses regarding both the function of the GBP, the specificity of an antibody and the function of the glycan within the context of the protein-glycan interactome. This article focuses on the types of glycan microarray technologies currently available to study animal glycobiology and examples of breakthroughs aided by these technologies.

Polysaccharides↗

PubMed2025

Investigating the miRNA-mRNA interactome of human trabecular meshwork cells treated with TGF-β1 provides insights into the pathogenesis of pseudoexfoliation glaucoma.

Pseudoexfoliation glaucoma is a severe form of secondary open angle glaucoma and is associated with activation of the TGF-β pathway by TGF-β1. MicroRNAs (miRNAs) are small non-coding RNA species that are involved in regulation of mRNA expression and translation. To investigate what glaucomatous changes occur in the trabecular meshwork and how these changes may be regulated by miRNAs, we performed a bioinformatics analysis resulting in a miRNA-mRNA interactome. Primary human trabecular meshwork cells originating from normal donors were treated with TGF-β1 at 5 ng/mL for 24h; total RNA was extracted followed by RNA-Seq and miRNA-Seq. For both mRNA and miRNA species, differential expression was determined using a bioinformatics pipeline consisting of FastQC, STAR, FeatureCounts, edgeR (for miRNA) and DESeq2 (for mRNA). Putative mRNA-miRNA interactions between differentially expressed mRNA and miRNA species were determined using interaction databases miRWalk, miRTarBase, TarBase and TargetScan. To classify mRNA species by function and pathway, gene enrichment was performed using Enrichr. The resulting miRNA-mRNA interactome consisted of 1202 interactions. Some highly connected microRNAs were hsa-let-7e-5p, hsa-miR-20a-5p, hsa-miR-122-5p, and hsa-miR-29c-3p. Most differentially expressed genes were indicated to be regulated by miRNAs. The sub-interactomes of genes involved in specific pseudoexfoliation glaucoma related enrichment terms such as oxidative stress, unfolded protein response, signal molecules and ECM remodelling were determined. This is the first study to present a genome-wide microRNA-mRNA regulatory network for human trabecular meshwork cells treated with TGF-β1 and may serve to generate unbiased hypotheses about regulatory functions and mRNA targets of miRNAs in pseudoexfoliation glaucoma and may help to develop miRNA-based therapeutics.

Humans↗

PubMed2026

Pathogenic Variants in HEPACAM Alter Protein Localization and Interactome in Astrocytes of the Developing Mouse Cortex.

Megalencephalic leukoencephalopathy with subcortical cysts (MLC) is a rare leukodystrophy characterized by early-onset macrocephaly, white matter edema, seizures, and motor and cognitive decline. Approximately 25% of MLC patients carry HEPACAM pathogenic variants, many of which are dominant missense variants causing remitting MLC Type 2b. HEPACAM encodes hepatic and glial cell adhesion molecule (hepaCAM), also known as GlialCAM, an astrocyte-enriched transmembrane protein with important roles in astrocyte territory establishment, gap junction coupling, branching organization, synaptic function, and development of the gliovascular unit. The molecular mechanisms through which pathogenic variants in HEPACAM alter hepaCAM protein function in vivo and facilitate MLC pathogenesis during brain development remain largely unknown. Here, we used new viral tools and proximity-based proteomics to examine how three different dominant pathogenic variants alter hepaCAM subcellular localization and protein interactome in astrocytes of the developing mouse cortex. We found dramatic changes in hepaCAM distribution throughout the astrocyte, which were common to all mutants tested. We also observed significant changes in protein interactome between wild type and mutant hepaCAM, including decreased association with previously described hepaCAM-interacting proteins Connexin 43 and CLC-2. Moreover, we identified the epilepsy-associate potassium channel KCNQ2 as a novel hepaCAM interaction partner and found reduced association between KCNQ2 and pathogenic variants. Collectively, our data provide new insights into hepaCAM protein function in astrocytes during brain development, reveal altered protein dynamics of pathogenic variants, and provide a new resource to explore the molecular underpinnings of MLC pathogenesis.

Animals↗

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

Spatial Mapping and Interactome Profiling of m6A-Modified R-Loops via Chemically Inducible Split-APEX2 Proximity Labeling.

m6A-Modified R-loops (m6A-R-loops) play crucial roles in epigenetic regulation and genome stability, yet resolving their spatial distribution and protein interactomes in live cells remains challenging. To address this, we developed m6A-R-loop proximity labeling (m6A-RLPL), a chemically inducible split-APEX2 proximity labeling technology integrating dual-target recognition using the RNA-DNA hybrid binding domain of RNase H1 for R-loop targeting and m6A reader protein's YTH domain for m6A recognition, coupled with an abscisic acid (ABA)-inducible dimerization system for signal amplification. This technology revealed host m6A-R-loops enriched with nucleoli under normal conditions. When applied to herpes simplex virus (HSV) infection, it further demonstrated viral m6A-R-loops undergoing dramatic accumulation within phase-separated granules in replication compartments during late-stage infection. Proximity proteomics identified ZC3H4 and CCDC124 as essential regulators maintaining these structures, which serve as transcription sites for HSV late genes, with disruption selectively impairing viral transcription. m6A-RLPL establishes a generalizable approach for spatially resolved profiling of m6A-R-loop interactomes and organizational dynamics in living systems.

Humans↗

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↗

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

IgStrand: A universal residue numbering scheme for the immunoglobulin-fold (Ig-fold) to study Ig-proteomes and Ig-interactomes.

The Immunoglobulin fold (Ig-fold) is found in proteins from all domains of life and represents the most populous fold in the human genome, with current estimates ranging from 2 to 3% of protein coding regions. That proportion is much higher in the surfaceome where Ig and Ig-like domains orchestrate cell-cell recognition, adhesion and signaling. The ability of Ig-domains to reliably fold and self-assemble through highly specific interfaces represents a remarkable property of these domains, making them key elements of molecular interaction systems: the immune system, the nervous system, the vascular system and the muscular system. We define a universal residue numbering scheme, common to all domains sharing the Ig-fold in order to study the wide spectrum of Ig-domain variants constituting the Ig-proteome and Ig-Ig interactomes at the heart of these systems. The "IgStrand numbering scheme" enables the identification of Ig structural proteomes and interactomes in and between any species, and comparative structural, functional, and evolutionary analyses. We review how Ig-domains are classified today as topological and structural variants and highlight the "Ig-fold irreducible structural signature" shared by all of them. The IgStrand numbering scheme lays the foundation for the systematic annotation of structural proteomes by detecting and accurately labeling Ig-, Ig-like and Ig-extended domains in proteins, which are poorly annotated in current databases and opens the door to accurate machine learning. Importantly, it sheds light on the robust Ig protein folding algorithm used by nature to form beta sandwich supersecondary structures. The numbering scheme powers an algorithm implemented in the interactive structural analysis software iCn3D to systematically recognize Ig-domains, annotate them and perform detailed analyses comparing any domain sharing the Ig-fold in sequence, topology and structure, regardless of their diverse topologies or origin. The scheme provides a robust fold detection and labeling mechanism that reveals unsuspected structural homologies among protein structures beyond currently identified Ig- and Ig-like domain variants. Indeed, multiple folds classified independently contain a common structural signature, in particular jelly-rolls. Examples of folds that harbor an "Ig-extended" architecture are given. Applications in protein engineering around the Ig-architecture are straightforward based on the universal numbering.

Humans↗

PubMed2026

Dual proximity-based interactome mapping of FKBP51 and FKBP52 uncovers shared metabolic networks.

The 51 kDa FK506-binding protein (FKBP51) has been studied for its involvement in regulating multiple biological systems, particularly as a regulator of steroid hormone receptors, but roles in metabolism, pain response, cell survival, protein turnover, autophagy, immune response, and insulin signaling have also been described. Genetic variants of FKBP51 are associated with various stress-related mental disorders. While recent research has clarified aspects of these processes, the complete range of FKBP51 interactions remains undetermined. FKBP52, a closely related homolog, also affects similar pathways. Recent studies have identified new protein partners for FKBP51 and FKBP52, suggesting an even broader interactome with transient associations. To further characterize interactions, TurboID-based proximity labeling was performed in HeLa cells. Proteomic analysis confirmed known FKBP51 and FKBP52 interactions, while also identifying additional shared and unique binding partners with strong enrichment in metabolic pathways, amino acid biosynthesis, and carbon metabolism. Although FKBP51 and FKBP52 proximal proteins were primarily cytosolic, FKBP51 showed additional associations with exosomal proteins while FKBP52 engaged with additional nuclear proteins. These findings highlight the overlapping roles in metabolic signaling and differentiate pathway-specific partners.

Tacrolimus Binding Proteins↗

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

Subcellular proteomic analysis of the DDR2 interactome in a neuronal cell model exposed to Aβ42.

Receptor tyrosine kinases (RTKs) are increasingly understood to signal beyond the plasma membrane. However, the role of Discoidin domain receptor 2 (DDR2), which is activated by collagen, in neurodegeneration remains poorly understood. This study uses immunoprecipitation followed by mass spectrometry on cytoplasmic and nuclear fractions from a neuronal cell model to show that Aβ42 exposure is associated with a compartment-specific reorganization of DDR2-associated protein complexes, characterized by increased nuclear representation. This reveals a unique nuclear DDR2 interactome under amyloidogenic conditions. By exploring this non-canonical, compartment-specific DDR2 signaling pathway, our results offer new insights into how receptor signaling networks may be altered in Alzheimer's disease pathology. Additionally, we identify DDR2-related nuclear interactions as potential sites of dysregulation in neurodegeneration.

Amyloid beta-Peptides↗

PubMed2026

DORSSAA: Drug-Target interactOmics Resource Based on Stability/Solubility Alteration Assay.

Advancements in high-throughput techniques such as Thermal Proteome Profiling and the high-throughput Proteome Integral Solubility Alteration assay have revolutionized our understanding of drug-protein interactions. Despite these innovations, the absence of an integrative platform for cross-study analysis of stability and solubility alteration data represents a significant bottleneck. To address this gap, we introduce Drug-target interactOmics Resource based on Stability/Solubility Alteration Assay (DORSSAA), an interactive and expandable web-based platform for the systematic analysis and visualization of proteome stability and solubility alteration assay datasets. Currently, DORSSAA features 1,135,985 records spanning 38 cell lines and organisms, 135 compounds, and 40,742 protein targets. Through its user-friendly interface, the resource supports comparative drug-protein interaction analysis and facilitates the discovery of actionable therapeutic targets. Through two case studies, methotrexate target profiling in A549 cells and combinatorial-therapy drug-target interactions in leukemia cell lines, we demonstrate DORSSAA's utility for identifying protein-drug interactions across diverse experimental contexts. This resource empowers researchers to accelerate drug discovery and enhance our understanding of protein behavior. Compared with data repositories and interaction databases, DORSSAA provides direct protein-level evidence of mechanisms of action with strict statistical control for each study. This enables more reliable identification of drug targets, off-target effects, and potential drug combinations.

Humans↗

PubMed2026

An Arabidopsis Protein-Flavonoid Interactome Identifies Peroxiredoxin A as a Candidate for Flavonoid Action in Chloroplasts.

The ability of phytochemicals to act as small molecule effectors of protein function is a largely overlooked dimension of plant biochemistry. This is particularly true for the ubiquitous flavonoids where, despite abundant examples of functional interactions with human proteins, biological activities in plants are primarily attributed to ROS scavenging. We used affinity capture to explore the protein interactome of the flavonoid glycoside, rutin, in Arabidopsis seedlings. Unexpectedly, the 397 high-confidence candidates included numerous proteins associated with chloroplasts, where flavonoids are present at exceedingly low levels. Intriguingly, several identified targets are conserved with known flavonoid-interacting proteins in mammals, where the bioavailability of flavonoids is similarly low. Using one of these, the Arabidopsis plastidial 2-cys peroxiredoxin A, as a test case, this study substantiated the potential of affinity proteomics for identifying novel protein targets of phytochemicals and suggests that flavonoids modulate protein function in plants to a larger extent than previously suspected.

Arabidopsis↗

PubMed2026

Comprehensive proximity proteomics expand the known interactome of the oncoprotein β-catenin.

The oncoprotein β-catenin has critical roles in cell adhesion and cell signalling. β-catenin affects human physiology and pathology through numerous interaction partners, of which many have been discovered by standard affinity purification-based proteomics. However, the interaction landscape of β-catenin remains incompletely understood, highlighting a need for new experimental approaches for the exploration of β-catenin biology. Proximity proteomics, which facilitate the discovery of molecules vicinal to proteins-of-interest by mass spectrometry, have recently emerged as a powerful complementary tool for the study of protein-protein interactions, but have not been applied to β-catenin so far. We investigated the interactome of β-catenin in model cell lines by proximity proteomics using expression constructs with the biotin ligases BioID and TurboID. Mass spectrometry analyses following biotin labelling identified numerous candidate interactors of β-catenin, including many that had not been observed in earlier studies using standard proteomics. Enrichment analyses suggested that proximity proteomics capture proteins associated with the known biological functions of β-catenin, including cell adhesion, Wnt/β-catenin signalling, and transcription regulation. The molecular tools and data generated in this study provide new insights into β-catenin biology and highlight potential new regulators of β-catenin function that warrant further exploration.

beta Catenin↗

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↗