23rd Human Proteome Organization World Congress

Temporal dissection of NLRP3 protein-protein interactions in inflammasome regulation

Organisation of the Proteome (PPI)

The NLRP3 inflammasome is a central signalling hub of the innate immune system which mediates inflammation through pro-inflammatory cytokine release and inflammatory cell death (pyroptosis). Dysregulated NLRP3 inflammasome signalling underlies many human diseases. The NLRP3 pathway undergoes a complex two-step programme of priming and activation modulated by dynamic protein-protein interactions (PPIs) and post-translational modifications (PTMs). However, the contextual and temporal dynamics of these mechanisms, and how they act to regulate NLRP3, are not completely understood. Previous studies have shown that temporal dynamics of PPI networks and corresponding PTMs can be assessed by affinity purification coupled to quantitative mass spectrometry (AP-MS) (1,2) and correlations between protein complex formation and post-translational modifications can be assessed, indicative of functional relationships (2). This project aims to build a comprehensive temporal map of PPI/PTM dynamics in NLRP3 inflammasome activation identifying novel regulatory mechanisms and their functional consequences.To derive a time-resolved quantitative map of reorganization of protein-protein interactions and corresponding PTMs we affinity purified NLRP3 from cells across a time course of priming and activation stimuli. We have established and validated protocols for AP-MS of endogenously expressed twin-strep tagged NLRP3 following stimulation of 5x106 THP-1 monocytes cells. The enhanced sensitivity and speed of diaPASEF (3) enabled quantitative analysis over many conditions and time-points including 150+ samples from 38 distinct experimental conditions.Time points were selected to focus on poorly understood early events (i.e. within 15 minutes of stimulation) in both priming and activating stimulation conditions and examine NLRP3 interactome immediately following stimulus detection. High confidence interactors have been identified for each stimulation timepoint via filtering against untagged (wild type) NLRP3 background controls. These interactions have been validated by the presence of known NLRP3 interacting proteins, and include putative novel interacting partners. Ongoing analysis is examining the relationships of detected PPIs and PTMs of NLRP3 and will attempt to define their functional significance for NLRP3 priming and activation and its phenotypic consequences.We show that AP-MS using diaPASEF enables in depth quantitative analysis of NLRP3 protein interaction dynamics across finely resolved time points and diverse stimulation conditions providing new insights into this complex and clinically important innate immune signalling pathway.References: 1. Collins BC, et al. Nature Methods. 2013;10(12):1246–53. 2. Zheng Y, et al. Nature. 2013;499(7457):166–71. 3. Meier F, et al. Nature Methods. 2020;17(12):1229–36.

Poster presentation

Associate Prof.

In situ membrane protein and flagellar enrichment increase the depth of large-scale bacterial interactomics studies using ion mobility and cross-linking mass spectrometry (XL-MS)

Cross-linking mass spectrometry (XL-MS) is an invaluable tool for capturing protein-wide interactomes in an in vivo context, however it remains challenging for complex protein mixtures, particularly those including membrane-embedded and/or membrane-associated proteins. The Gram negative bacterial membrane consists of a variety of sub-structures that include a cytoplasmic inner phospholipid membrane containing hydrophobic transmembrane proteins, a liquid phase periplasm containing soluble proteins, the cell shape and rigidity determinant peptidoglycan (PG) layer and finally, an asymmetric outer membrane (OM) lipid bilayer consisting of phospholipids, OM proteins and external lipopolysaccharide. The membrane facilitates interactions with the environment, including the human host, and is critical for all aspects of virulence, including adherence, host cell invasion, secretion, flagellar motility and antimicrobial resistance. We developed membrane enrichment strategies for in situ cross-linking of membrane proteins and the flagella apparatus from the helical human gastrointestinal pathogen Campylobacter jejuni. We investigated different fractionation approaches, including offline size-exclusion chromatography (SEC) and online gas-phase fractionation with high-field asymmetric waveform ion mobility spectrometry (FAIMS), and then investigated how different protein digestion approaches and gradient lengths affect the success of these strategies in identifying cross-linked peptide species at both the sample preparation and acquisition levels. A hybrid MS2-MS3 fragmentation strategy with or without an internal-stepping compensation voltage scheme showed the benefits of FAIMS for XL-MS increases with sample complexity and gradient length by reducing interference and increasing signal:noise. Significantly, single mg injections were able to yield more cross-links that 8 mg of SEC fractions over the same acquisition time. The use of FAIMS and SEC with different proteases suggests that protease-specific cross-linked peptides respond differently to ion-based separation across several physicochemical properties. In situ membrane protein cross-linking revealed extensive interactions between the major human adherence factor CadF, PG-associated lipoprotein Pal and major OM protein MOMP providing evidence of how C. jejuni maintains membrane integrity. Flagellar apparatus cross-linking revealed flagellin multimerisation and conformational dynamics for the first time, including multimeric interfaces and filament stabilisation. In conclusion, proteome-wide interactome interrogation with XL-MS can be tailored to the needs of the researcher in terms of sample type, preparation, fractionation and acquisition. Optimisation of these parameters can allow, for example, identification of sub-proteome specific interactomes, provide greater depth and coverage of the proteome and interactome, and lead to increased cross-link identification and quality of interactome data.

hu.MAP3: Data integration of 25k mass spectrometry experiments accurately identifies protein complexes

Macromolecular protein complexes carry out most functions in the cell including essential functions required for cell survival. The identification of protein complexes in human cells is a long-standing challenge. To address this challenge several high throughput techniques have been developed including affinity purification mass spectrometry (AP-MS), co-fractionation mass spectrometry (CF-MS), proximity labeling strategies, among others, aimed at identifying protein interactions across the human proteome. As a result of these advances, there exists large scale datasets (&gt;25,000 mass spectrometry experiments) using these methods that cover different cell types, tissues, and parts of the proteome. This presented an opportunity to integrate these data to build a more complete and accurate human protein complex map, which we call hu.MAP3 (Fig1A). We identify over 15,000 protein complexes covering ~3/4ths of the human proteome, a substantial increase over previous complex maps. Of note, we place &gt;1,200 highly uncharacterized proteins into complexes providing testable hypotheses as to their function. Further, we refine our complexes by integrating proteomics co-variation data (ProteomeHD) as well as AlphaFold structural models to identify mutually exclusive protein interactions (Fig1B). We expect our resource to be valuable to the broader research community.

Deep Interactome Profiling MS (DIP-MS), a novel interaction proteomics method for the deconvolution of immunoprecipitated protein complexes

Proteins organize into dynamic modules to carry out most cellular processes. Ever-advancing analytical capabilities to study modular proteome organization holds great promise to pinpoint molecular lesions driving disease phenotypes.Affinity purification combined with LC-MS/MS is a powerful method to identify a protein"s set of direct and indirect interaction partners with high sensitivity, but cannot resolve the sum of purified proteins into instances of specific protein complexes within a single AP-MS experiment. We devised an integrated computational/wet lab method Deep Interactome Profiling by Mass Spectrometry (DIP-MS) which identifies distinct protein complexes from an AP sample at high sensitivity, This is accomplished by the integration of targeted affinity enrichment with blue native-PAGE separation, quantitative high-throughput DIA-MS and deep-learning-based signal processing.96-well based MS-sample processing combined with high-throughput DIA-MS allows protein profiling from up to 70 BN-PAGE fractions within one day. In addition, we introduced PPIprophet for efficient data driven neural network based complex deconvolution from the acquired data.We applied DIP-MS to probe the modular structure of the human prefoldin (PFD) family of complexes, resolving distinct PFD holo- and sub-complex variants, complex-complex interactions and complex isoforms with new subunits that were experimentally validated.When benchmarked against AP-MS and SEC-MS, we could demonstrate the superior resolution and coverage of our approach. DIP-MS identified a novel low abundant PDRG1 based complex isoform of canonical PFD, which we validated by in-silico structural modelling and reciprocal AP-MS. Finally, we found that DIP-MS was sensitive enough to identify folding substrate for the complex-complex interactions of CCT/TRiC-PFD and the PAQosome complex, a super complex involved in the assembly of protein complexes. The results were validated by orthogonal DIP-MS experiments, literature derived and experimental AP-MS data. The exceptional sensitivity, resolution, and speed of DIP-MS promise to significantly advance our ability to link specific proteome organizational states to phenotypic outcomes in healthy and diseased conditions.Frommelt F, Fossati A, Uliana F, Wendt F, Xue P, Heusel M, Wollscheid B, Aebersold R, Ciuffa R, Gstaiger M. DIP-MS: ultra-deep interaction proteomics for the deconvolution of protein complexes. Nat Methods. 2024 Apr;21(4):635-647. doi: 10.1038/s41592-024-02211-y. Epub 2024 Mar 26. PMID: 38532014; PMCID: PMC11009110.

Professor

Proximity proteomics reveals a co-evolved LRRK2-regulatory network linked to centrosomes

The Leucine-rich repeat kinase 2 (LRRK2) not only plays a vital role in familial forms of Parkinson"s disease (PD) but is also considered as a risk factor for developing idiopathic PD. So far, no causative treatment for PD exists, ameliorating the progressive loss of dopaminergic neurons within the substatia nigra. The multi-domain protein LRRK2 represents a promising drug target for PD treatment. Besides a kinase and a G-domain, LRRK2 contains multiple scaffolding domains, not only being involved in keeping inactive LRRK2 in an auto-inhibited state but are also involved in protein-protein interactions making LRRK2 to a signaling hub possibly integrating multiple upstream signals or enabling a context-specific activation of downstream pathways by controlling the spatial localization of LRRK2. Therefore, an in-depth understanding of the LRRK2 protein-protein interaction (PPI) networks not only allows illuminating a deeper understanding of the associated signaling pathways but potentially also reveals new drug targets. Here, we present new BioID proximity proteomes of LRRK2 covering both known as well as yet unknown interactors. By clustering based on co-evolution within the PPI network combined with functional enrichment, we identified a subcluster showing highest co-evolution to LRRK2 which is enriched in cytoskeletal components linked to the centrosome and microtubules as well as primary cilia. In addition, by this approach, we could demonstrate that the resulting BioID datasets are enriched in direct interactions. Furthermore, structural prediction of binary interactions via AlphaFold-multimer revealed distinct groups of interactors engaging through specific interfaces and LRRK2 conformations. Finally, we identified distinct changes in the LRRK2 proximity proteome induced by the type I kinase inhibitor MLi2 and by RAB29 co-expression. These functional state-specific interactomes link LRRK2 to defined cellular sub-compartments. Noteworthy, MLi2-induced LRRK2 complexes are characterized by a significantly higher co-evolution and are not predicted to interact with the catalytic domains, particularly the kinase domain.In conclusion, our novel approach combining proximity proteomics with the analysis of co-evolution and structural modelling helped to stratify the primary BioID datasets and lead to the identification of molecular networks linking LRRK2 to centrosomal biology and primary cilia.

Prof.

Mass spectrometry-centric approaches identify the proteins and neuropeptides interacting with amyloid-β

Amyloid-β (Aβ) aggregates are recognized as initiators of Alzheimer"s disease, and their interaction with the nervous system contributes to the progression of neurodegeneration. Therefore, there is an urgent need for researchers to discover the biomolecules that interact with Aβ peptides to determine the molecular basis.To enable profiling of Aβ-interacting proteins, we developed the novel Peptide-ligand-induced Abundance Change of proTeinS (PACTS)-assisted TPP strategy for the identification of peptide-interacting proteins based on the peptide-ligand-induced change in protein abundance. The interactome of amyloid beta (Aβ) 1-42 in THP-1 cells was described and resulted in the identification of 103 interacting proteins. Validation experiments indicated that Aβ1-42 interacted directly with fatty acid synthase (FAS) and inhibited its enzymatic activity, providing insights into fatty acid metabolic disorders in Alzheimer's disease. Furthermore, we applied the PACTS-assisted TPP approach to analyze clinical samples to identify Aβ1-42-interacting proteins. We detected 115 proteins that interact with Aβ1-42 in human frontal lobe tissue. Further orthogonal validation revealed that Aβ1-42 interacted with the AD-associated protein mitogen-activated protein kinase 3 (MAPK3), and knockdown of the Aβ1-42 amyloid precursor protein (APP) inhibited the MAPK signaling pathway, suggesting potential functional roles for Aβ1-42 in interacting with MAPK3.To enable profiling of Aβ-interacting neuropeptides, we established a native mass spectrometry (MS)-centric workflow for screening Aβ-interacting neuropeptides, and six out of twelve neuropeptides formed noncovalent complexes with Aβ species in the MS gas phase. Thioflavin-T fluorescence assays and gel separation indicated that leptin and cerebellin decreased Aβ aggregation, whereas kisspeptin increased this process. In addition, leptin and cerebellin attenuated Aβ-induced cytotoxicity, which was independent from the influence of metal ions. Leptin can chelate copper from copper-bound Aβ species, reducing cytotoxicity caused by the aggregation of Aβ and metal ion complexes. Overall, our study demonstrated that neuropeptides frequently interact with Aβ and revealed that leptin and cerebillin are potential inhibitors of Aβ aggregation, providing great insight into understanding the molecular mechanism of Aβ interacting with nervous system and facilitating drug development.

An integrative interactomic approach to assess the function of CASK and its involvement in neurodevelopmental disorders

Proteins act in intertwined regulated networks and are the main effectors of biological processes, as well as the principal targets of drug treatments. Identification all the protein-protein interactions (PPIs) established by a protein in a particular context, its interactome, is a powerful approach to uncover its normal and pathological functions. We implemented a multipronged interactomic approach to decipher the functions of CASK (Ca2+/calmodulin-dependent serine protein kinase) and its involvement in some neurodevelopmental disorders (NDDs). CASK is a large multi-domain protein achieving multiple functions in the central nervous system (Figure 1A). Several severe NDDs are caused by CASK mutations whose dysfunctional consequences remain sketchy characterized, yet underpinning PPI perturbations are suspected.We generated a contextual and quantitative interactome of the CASK wt protein of unprecedent depth and robustness, by combining four complementary interactomic approaches: affinity-purification mass spectrometry (AP-MS), in vitro AP-MS (pouring cell lysates on immobilized recombinant bait column), proximity-dependent biotinylation (BioID), and our recently developed Holdup assay (a robust and precise chromatographic assay for high-throughput quantification of protein-ligand affinities, Kd). Our CASK interactome is highly relevant since significantly enriched in (i) previously identified CASK partners; (ii) GO terms associated to the known functions of the protein, and (iii) NDD- or ASD- (Autism Spectrum Disorders) associated genes (Figure 1B). Strikingly, this interactome also reveals a potential new, previously undescribed function of the protein, which calls for further investigation. Finally, we systematically and finely investigated the complementarity between the four interactomic methods we used, providing a rigorous analysis of the strengths and weaknesses inherent to each approach (Figure 1C).In the second step, we aim to demonstrate that some CASK-associated mutations exert their pathological mechanisms through global interactome perturbations (Figure 1D). We will analyze how these interactome perturbations correlate to phenotypic alterations. In the future, this pathological fingerprint of interactome perturbations will allow us to assess the pathogenicity of Variants of Unknown Significance (VUS), a critical question for diagnosing NDD. Together, our results will provide an in-depth understanding of CASK mutation-associated mechanisms.

Human protein-protein interactome: IMEx's metadata on host tissue specificity and genetic variability of proteins

Molecular interaction networks provide maps to explore cellular processes from a systems perspective. Access to the experimental evidence and contextual metadata which influence the interaction outcome are critical for accurate interpretation of interaction dynamics.The IMEx consortium (www.imexconsortium.org) is an international collaboration that compiles molecular interaction data in full experimental detail from scientific literature and direct submissions. This information is freely available to the public through an open source, open data model.Each interaction receives an IMEx-level confidence score based on interaction type, detection methods, and the publications reporting the interaction. Factors affecting interaction strength are annotated at experimental, interaction, and participant levels, including clinical and experimental mutations, required or sufficient binding regions, post-translational modifications (PTMs), and external modulators such as agonists and antagonists, derived from low-throughput experimental evidence.Our curation strategy allows us to map interactions to the specific host tissue or cell type where they were detected. Recently, we completed mapping our host tissues and cell types to the Experimental Factor Ontology (EFO). Modern high-throughput methods like affinity purification-mass spectrometry (AP-MS) can generate protein-protein interactions (PPIs) in their close-to native state of expression.IMEx contains over 11,800 n-ary interactions, mostly AP-MS evidence captured in human neurons, including more than 3,000 interactions affected by mutations. Approximately 2,200 interactions have been detected in embryonic stem cells. In the bronchial epithelium, more than 3,800 interactions have been detected, with 3,500 of these involving mutation data. Additionally, 500 interactions have been identified in bronchial epithelial cells with a cystic fibrosis phenotype. Close to 500 interactions have been curated in human retinal tissue, over 500 in blood immune cells, and around 350 in human blood plasma and serum. Most references feature PPI data studied in cancer cell lines: over 8,500 interactions have been curated in colorectal cancer cell lines, 6,000 in human breast cancer cell lines, and more than 4,400 in human glioblastoma cell lines and tissue samples. We also capture proximity assays to expand our coverage and provide data on proximal protein partners in different cellular compartments.IMEx&quot;s comprehensive approach to building metadata for each interaction, with consistent use of controlled vocabularies and ontologies, can generate interaction networks specific to various layers of information. This facilitates the detection of macromolecular assemblies under different conditions.

Detailed investigation of the interactions of the GADD34 (growth arrest and DNA damage [GADD]‐inducible34) protein

Protein phosphatase 1 (PP1) is one of the most important serine-threonine phosphatases in eukaryotic cells, owning approximately two hundred regulatory subunits which are responsible for the specificity of its substrates. Among its regulatory subunits, GADD34 plays a well-known substantial role by influencing translation via dephosphorylation of the eucaryotic initiation factor 2α (eiF2α) which is a key reaction for recovery of protein expression after stress. Guanabenz, an approved antihypertensive drug acting on α-2 adrenergic receptors, inhibits GADD34 as well. Guanabnez also exhibits therapeutic potential for neurodegenerative disorders with repurposing Phase 1 studies ongoing. We aimed to investigate the interactome of GADD34 protein under different ER stress conditions. We performed proximity-dependent biotin labelling method using wt and mutant GADD34-TURBO-2XFLAG chimera proteins in parallel to co-IP experiments. The mutant fusion protein (GADD34(Δ578-617)-TURBO-2XFLAG) lacked an evolutionary conserved region, including the known binding site for eiF2α. We generated 3-3 independent stable cell lines for both types of chimaeras from adherent human embryonic kidney cells (adHEK). We compared the interactome of wt GADD34-TURBO to that of the deletion mutant both under control and ER stress condition, i.e after treatment with the SERCA-inhibitor thapsigargin, or mTOR-inhibitor rapamycin. We labelled potential interaction partners in vivo, followed by identification via mass spectrometry (MS). In addition, co-immunoprecipitation studies with both chimaeras followed by MS were conducted. Our investigation found numerous novel interaction partners providing new insights into different cellular functions, including e.g. cell cycle, apoptosis, autophagy, cytoskeletal system/motor proteins and vesicular trafficking. Significant Gene Ontology enrichment revealed the involvement of the GADD34/PP1 complex in different immune functions and neurodegenerative diseases as well. Our findings suggest potential new indications for guanabenz beyond its current approvals, while also opening new perspectives for drug research focusing on GADD34 inhibition. A new computational model based on our hits fits well with literature data for the regulation of autophagy via the mTOR-AMPK-GADD34 triangle. We suggest that the GADD34/PP1 complex is a main switch in the cell to counteract stress-induced phosphorylation in main cellular functions, promoting cell proliferation, that has been validated by functional tests as well. Treatment of human T cells and neutrophils by Guanabenz also validates our proteomic finding. We suggest new mechanisms of action for antiinflammatory effects and beneficial outcomes in neurodegenerative diseases of Guanabenz treatment. In summary, our data contributes to a deeper understanding of various cellular processes, including cell cycle regulation, autophagy, apoptosis and functions of immune cells besides its pharmacologic relevance regarding GADD34 inhibition.

Introducing TIE-UP-SIN: a novel method for enhanced identification of protein-protein interactions

Proteins are indispensable for life due to their versatility and specificity. They are involved in virtually every cellular process from catalytic reactions, structural integrity, signaling and communication to immune defense and pathogenicity.Their ability to adopt diverse structures and functions makes them central to the complexity and adaptability of all living organisms. As they usually interact with other proteins or cellular components to carry out complex biological processes they rarely function alone. Thus, identifying Protein-Protein-Interactions (PPIs) helps elucidating the complex networks and pathways that underlie cellular functions and organismal biology.Methods for studying PPIs include yeast two-hybrid screening, co-immunoprecipitation, mass spectrometry, fluorescence resonance energy transfer, computational approaches and many others.Although each method has its specific advantages, they all have disadvantages such as a high false positive rate, a high technical complexity and low efficiency, which makes precise identifications of specific interaction partners somtimes difficult.Here we present our TIE-UP-SIN method which represents a Targeted Interactome Experiment for Unknown Proteins by Stable Isotope Normalization.This method provides an in vivo approach for the identification of PPIs based on stable isotope labeling, reversible crosslinking and affinity purification coupled with highly sensitive PPI identification by mass spectrometry (MS). The isotope labeling is essential for normalizing MS sample data as it addresses variability, ensures accurate quantification, and enhances the reliability of comparative DIA-MS proteomic analyses. This leads to precise and reproducible results, facilitating robust biological insights eliminating high false discovery rates. The combination with a quick and cheap reversible crosslinking and affinity purification protocol makes this technique a powerful tool to stabilize transient or weak in vivo interactions and to specifically capture them in a highly specific purification process.Overall, TIE-UP-SIN is a robust and favorably priced method for studying PPIs, offering quick and reliable insights into the composition and architecture of protein complexes in a biological in vivo context. The utility of the approach will be presented using the well-described and essential housekeeping sigma factor SigA from Bacillus subtilis as an example.

High-resolution complexome profiling identifies auxiliary subunits and supercomplexes of renal transporters

The kidney plays a central role in fluid and electrolyte homeostasis as well as for the excretion of xenobiotics. For this purpose, a multitude of transporters and other transmembrane proteins is expressed along nephrons with high density and distinct cellular localization. Peptides, metabolites and inorganic ions are mainly resorbed in the proximal tubules by epithelial cells carrying tightly packed microvilli (together forming the brush border). These membrane structures are densely packed with transporters, but how these are molecularly organized and functionally cooperate is largely unknown.To resolve the molecular composition of renal transporters we combined two proteomic approaches: (i) we used high-resolution complexome profiling (based on cryo-slicing Blue Native Gel mass spectrometry (csBN-MS); Müller et al., 2016, Schulte et al., 2023) to analyse a preparation of brush border-enriched membranes from mouse kidney. After native separation of gently solubilized protein complexes, the respective gel was cut into 280 slices à 0.3 mm which were tryptically digested and comprehensively analyzed by LC-MS/MS on a Orbitrap Exploris mass spectrometer. Proteins were identified with PEAKS and quantified using an elaborate in-house developed processing and profile building pipeline (Schulte et al., 2023). (ii) The sodium-phosphate transporter SLC34A1 (NPT2A) and other selected examples of newly identified transporter complexes were further investigated by multi-epitope affinity purification mass spectrometry (meAP-MS), i.e. using multiple target-specific antibodies in wildtype and target knockout kidney membrane solubilisates as well as target-unrelated antibody controls.Complexome profiling analysis provided more than 5000 detailed abundance-size distributions of proteins with strong representation of bona-fide brush-border transmembrane transporters. Inspection of the profile peaks revealed that the majority of transmembrane proteins are not existing as monomers but are assembled intoseveral higher molecular weight complexes (as in Schulte et al., 2023). Apart from known homo- and heteromeric transporter complexes, a number of peak correlations indicated the formation of novel transporter supercomplexes and assembly of transporters with yet unknown subunits. These results were corroborated by subsequent meAP-MS analyses. Thus, the obtained NPT2A interactome comprised the known interaction partners PDZ1L and NHRF3, in addition to 20 proteins that had not yet been associated with sodium-phosphate transporters and their cell biology. Most notably, NPT2A was found to interact with a subset of transporters coincident with high-molecular weight peak clusters associated with NPT2A in the brush border complexome.The functional and structural implications of these findings are currently investigated by electrophysiological experiments (upon heterologous reconstitution) and ultrastructural methods (like freeze-fracture immuno-electron microscopy).

Mapping the human proteome with physical access to DNA

In a human cell, DNA is packed in histones, RNA, and chromatin-associated proteins, forming a cohesive gel. At any given moment, only a specific subset of the proteome has physical access to the DNA and organizes its structure, transcription, replication, repair and other molecular functions essential to the way the genome is read and maintained. We have developed a "zero-distance" photo-crosslinking approach to quantify proteins in direct contact with DNA in living cells. Collecting DNA interactomes from human breast cancer cells, we present an atlas of over one thousand proteins with physical access to DNA, and hundreds of peptide-nucleotide crosslinks pinpointing protein-DNA interfaces with single amino-acid resolution. Differential comparisons of DNA interactomes from cells undergoing treatment with estrogen or genotoxic chemotherapy recapitulated the recruitment of key transcription factors and DNA damage proteins. This opens a direct way to explore genomic regulation in a hypothesis-free manner, applicable to many organisms and systems.

Organisation of the Proteome (PPI)

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