Recombinant Human E3 ubiquitin-protein ligase RNF149 (RNF149)

What is the molecular structure of RNF149 and how does it influence its function?

RNF149 is a membrane-bound E3 ubiquitin ligase containing a RING finger domain that is essential for its catalytic activity. Structurally, RNF149 contains multiple functional domains including the catalytic RING domain and a protease-associated (PA) domain (amino acids 67-175) that mediates substrate interactions. Studies have demonstrated that the PA domain is critical for binding to substrates such as IFNGR1, while the RING domain is necessary for the ubiquitination activity but not for substrate binding .

Experimental approaches to study RNF149 structure-function relationships typically employ domain deletion mutants and point mutations in catalytic residues (such as H289A). Co-immunoprecipitation experiments with these mutants have revealed that neither the RING domain nor the catalytic site is required for RNF149's binding with substrates like IFNGR1, but the PA domain is essential for this interaction .

What are the validated substrates of RNF149 and how are they identified?

Current research has identified several substrates of RNF149, including IFNGR1 (interferon gamma receptor 1) and DNAJC25. The identification of these substrates involves multiple complementary approaches:

• Co-immunoprecipitation followed by mass spectrometry (co-IP/MS) to detect protein interactions

• Reciprocal co-IP experiments to confirm specific binding

• In vitro ubiquitination assays to verify direct ubiquitination

• Analysis of substrate protein levels in RNF149 knockout versus wildtype conditions

For example, researchers identified IFNGR1 as a substrate through Venn diagram analysis of the intersecting set of RNF149-binding protein candidates in the top enriched pathway identified through co-IP/MS and genes within top-ranking enriched pathways from transcriptome analysis . This was further validated through reciprocal co-IP experiments demonstrating that RNF149 indeed interacts with IFNGR1 .

How is RNF149 expression regulated in different tissues and disease states?

RNF149 exhibits tissue-specific expression patterns that change during development and disease progression. In normal tissues, RNF149 is strongly expressed in gonocytes, which are precursor cells to spermatogonia . Immunohistochemical analysis of developmental tissues reveals that RNF149 expression varies across different organs during development.

In pathological conditions, RNF149 expression is significantly altered. Proteomic profiling of paired early-stage hepatocellular carcinoma (HCC) samples demonstrates that RNF149 is strikingly upregulated in tumor tissues compared to adjacent normal tissues . This upregulation correlates with poor prognosis in HCC patients, as validated by immunohistochemistry staining in independent HCC cohorts .

The regulation of RNF149 expression appears to involve transcriptional control mechanisms. For instance, in the context of myocardial infarction, STAT1 activation induces RNF149 transcription, which in turn destabilizes IFNGR1 to counteract type-II interferon signaling .

How does RNF149 contribute to the progression of hepatocellular carcinoma?

RNF149 promotes hepatocellular carcinoma (HCC) progression through multiple mechanisms dependent on its E3 ubiquitin ligase activity. Experimental evidence demonstrates that overexpression of RNF149 significantly enhances cell proliferation, migration, and invasion of HCC cells in vitro .

The oncogenic function of RNF149 in HCC involves:

• Ubiquitination of specific substrates: RNF149 has been shown to ubiquitinate DNAJC25, which was identified as a new substrate in HCC contexts .

• Immunomodulatory effects: Bioinformatics analysis reveals that high expression of RNF149 correlates with an immunosuppressive tumor microenvironment (TME), suggesting a potential role in immune evasion by HCC .

Methodologically, researchers investigating RNF149 in HCC typically employ:

• Proteomic profiling of paired tumor/normal samples

• Immunohistochemistry to validate expression in patient cohorts

• Functional assays with RNF149 overexpression or knockdown in HCC cell lines

• Identification of substrates through co-immunoprecipitation and mass spectrometry

• Bioinformatics analyses to correlate RNF149 expression with immune cell infiltration and clinical outcomes

The clinical significance of these findings lies in the potential of RNF149 as both a prognostic marker and a therapeutic target for HCC treatment .

What role does RNF149 play in cardiac repair following myocardial infarction?

RNF149 plays a crucial role in cardiac repair following myocardial infarction (MI) through its function in macrophages. Research using RNF149 knockout (RNF149KO) mouse models has shown that the absence of RNF149 exacerbates cardiac dysfunction following MI .

The mechanistic details of RNF149's cardioprotective function include:

• Restraining inflammation: RNF149 in infiltrated macrophages limits excessive inflammation by promoting ubiquitylation-dependent proteasomal degradation of IFNGR1 (interferon gamma receptor 1) .

• Promoting timely resolution of inflammation: Loss of RNF149 leads to prolonged inflammatory responses in cardiac tissue after MI, with increased expression of proinflammatory cytokines including IL-6, IL-23a, Csf3, and MMP9 .

• Supporting scar formation: RNF149 deficiency results in the formation of collagen-scarce scars in infarcted hearts, indicating impaired post-infarction repair . Collagen density in the infarct area is significantly lower in RNF149KO hearts compared to wild-type hearts 7 days after MI .

• Reducing cardiomyocyte apoptosis: RNF149 deficiency leads to increased apoptotic cardiomyocytes in the border area of hearts following MI .

Experimental approaches to study RNF149 in cardiac repair include:

• Generation of RNF149 knockout mouse models

• Bone marrow macrophage-specific RNF149-knockdown models using AAV-encoding RNF149-shRNA under macrophage-specific promoters

• Echocardiography to assess cardiac function

• Histological analyses including TUNEL assays, Masson trichrome staining, and Picrosirius red staining

• Transcriptome analysis of infarcted cardiac tissue

These findings suggest that targeting the RNF149-IFNGR1 axis might be a potential therapeutic strategy for improving cardiac repair after MI .

How does RNF149 function in protein quality control pathways?

RNF149 plays a significant role in the pre-emptive ER-associated quality control (pEQC) pathway, which identifies and processes mislocalized proteins (MLPs) that fail to translocate into the endoplasmic reticulum (ER). As a membrane-bound E3 ligase, RNF149 participates in the ubiquitination of pEQC substrates, marking them for degradation by the 26S proteasome .

Key aspects of RNF149's function in protein quality control include:

• Selective substrate recognition: RNF149 selectively binds only to non-translocated proteins, not to their translocated forms, demonstrating specificity in substrate selection .

• Association with pEQC components: RNF149 interacts with known pEQC components, including AIRAPL as a cofactor complex with p97 .

• Regulation of ER translocation: Impairment in RNF149 function increases translocation flux into the ER, suggesting that RNF149 helps maintain proper protein sorting and quality control at the ER membrane .

• Disease implications: Dysfunction of RNF149 in the pEQC pathway manifests in a myeloproliferative neoplasm (MPN) phenotype, highlighting the pathological consequences of impaired protein quality control .

Research methodologies used to study RNF149 in protein quality control include:

• Co-immunoprecipitation to identify protein interactions

• In vitro ubiquitination assays to assess E3 ligase activity

• Mutational analysis of functional domains

• Analysis of translocation efficiency in RNF149-deficient models

Understanding RNF149's role in protein quality control offers insights into fundamental cellular processes and potential therapeutic targets for diseases associated with protein misfolding and ER stress.

What are the optimal experimental systems for studying RNF149 function in different research contexts?

Researchers investigating RNF149 employ various experimental systems depending on the specific research question:

• Cell culture models:

  • HCC cell lines for cancer research: Overexpression or knockdown of RNF149 in hepatocellular carcinoma cell lines allows assessment of effects on proliferation, migration, and invasion .

  • Bone marrow-derived macrophages (BMDMs): Useful for studying RNF149's role in inflammation and immune responses .

  • Cell lines expressing pEQC substrates: To study RNF149's function in protein quality control .

• Animal models:

  • Global RNF149 knockout mice: These models reveal phenotypes in multiple organ systems, including exacerbated cardiac dysfunction following myocardial infarction .

  • Cell type-specific RNF149 knockdown: Adeno-associated virus (AAV)-encoding RNF149-short hairpin RNA under the control of cell-specific promoters (e.g., F4/80 for macrophages) administered via targeted delivery methods (e.g., intra-bone marrow injection) .

  • Myocardial infarction models: Surgical models to induce MI in mice, followed by evaluation of cardiac function and repair processes .

• Analytical techniques:

  • Co-immunoprecipitation/mass spectrometry: To identify RNF149 interacting proteins and substrates .

  • Transcriptome analysis: RNA sequencing to identify differentially expressed genes in RNF149-deficient models .

  • Immunohistochemistry: For tissue expression analysis in normal development and disease .

  • Functional assays: Including ubiquitination assays, protein stability assessments, and cell-based functional assays .

• Validation approaches:

  • Domain deletion and point mutation studies: To determine structure-function relationships .

  • Substrate validation through multiple techniques: Including reciprocal co-IP, in vitro ubiquitination, and substrate level analysis in RNF149-deficient systems .

The choice of experimental system should be guided by the specific aspect of RNF149 biology being investigated, with consideration of the tissue context and disease relevance.

How do different post-translational modifications affect RNF149 activity and substrate specificity?

The activity and substrate specificity of RNF149 are regulated through various post-translational modifications, though this area remains less extensively characterized compared to other aspects of RNF149 biology.

Current understanding of post-translational regulation of RNF149 includes:

• Auto-ubiquitination: As an E3 ubiquitin ligase, RNF149 may undergo auto-ubiquitination as a self-regulatory mechanism. This process can be studied using in vitro ubiquitination assays with purified components .

• Domain-specific modifications: The functional domains of RNF149, including the RING domain and PA domain, may be targets for post-translational modifications that alter activity or substrate binding. For instance, modifications affecting the PA domain (amino acids 67-175) could impact its ability to interact with substrates like IFNGR1 .

• Regulation by interacting proteins: RNF149 interacts with AIRAPL as a cofactor complex with p97, and these interactions can be influenced by modifications to either protein .

• Transcriptional regulation: While not a post-translational modification per se, RNF149 expression is regulated by transcription factors such as STAT1, which can be activated in response to various stimuli .

Experimental approaches to study post-translational modifications of RNF149 include:

• Mass spectrometry to identify modification sites

• Site-directed mutagenesis of potential modification sites

• Functional assays with wild-type versus mutant forms

• Analysis of RNF149 stability and localization under different cellular conditions

Further research is needed to fully elucidate the complex interplay between various post-translational modifications and RNF149 function in different cellular contexts.

What are the key technical challenges in purifying active recombinant RNF149 for in vitro studies?

Purifying active recombinant RNF149 presents several technical challenges due to its membrane-bound nature and complex domain structure. Researchers should consider the following approaches and difficulties:

• Expression system selection:

  • Bacterial systems: While simpler, they often fail to properly fold complex mammalian proteins and lack appropriate post-translational modifications.

  • Insect cell systems (e.g., baculovirus): Provide better folding and some post-translational modifications.

  • Mammalian expression systems: Offer the most physiologically relevant modifications but with lower yield.

• Solubilization strategies:

  • Truncation approaches: Expressing soluble domains (such as the RING domain alone) may improve solubility but could compromise functional studies.

  • Fusion partners: Using solubility-enhancing tags (MBP, SUMO, etc.) can improve expression and solubility.

  • Detergent selection: Careful optimization of detergent type and concentration is crucial for extracting membrane-bound RNF149 while maintaining its activity.

• Activity preservation:

  • Reducing agents: Careful management of reducing conditions is essential for maintaining the integrity of the zinc-coordinating RING domain.

  • Storage conditions: Optimizing buffer composition, pH, and storage temperature to maintain long-term activity.

  • Co-factors: Including potential co-factors that might be necessary for full activity in vitro.

• Functional validation:

  • In vitro ubiquitination assays: Using purified E1, E2 enzymes, ubiquitin, and identified substrates (such as IFNGR1 or DNAJC25) to confirm activity .

  • Structural integrity assessment: Circular dichroism or thermal shift assays to confirm proper folding.

These technical considerations are crucial for obtaining physiologically relevant results in biochemical studies of RNF149 function.

How can researchers effectively study the dynamics of RNF149-substrate interactions in living cells?

Studying the dynamics of RNF149-substrate interactions in living cells requires sophisticated approaches that capture the temporal and spatial aspects of these interactions. Several methodologies can be employed:

• Advanced imaging techniques:

  • Fluorescence resonance energy transfer (FRET): By tagging RNF149 and its substrates (e.g., IFNGR1, DNAJC25) with appropriate fluorophore pairs, researchers can monitor real-time interactions.

  • Bimolecular fluorescence complementation (BiFC): Split fluorescent proteins fused to RNF149 and its substrates can reveal interaction sites within cells.

  • Proximity ligation assay (PLA): Allows visualization of protein interactions with high sensitivity and specificity in fixed cells.

• Live-cell protein dynamics:

  • Fluorescence recovery after photobleaching (FRAP): To study the mobility and turnover of RNF149 at different cellular compartments.

  • Photoactivatable or photoswitchable fluorescent proteins: To track the fate of RNF149 or its substrates following interaction.

  • Optogenetic approaches: Light-inducible systems to trigger RNF149 activity or localization in specific cellular compartments.

• Temporal control systems:

  • Inducible expression systems: To control the timing of RNF149 or substrate expression.

  • Auxin-inducible degron (AID) technology: For rapid and controlled depletion of proteins.

  • CRISPR interference or activation (CRISPRi/CRISPRa): For temporal control of endogenous gene expression.

• Quantitative measurements:

  • Fluorescence correlation spectroscopy (FCS): To measure diffusion rates and complex formation.

  • Single-molecule tracking: To follow individual molecules of RNF149 or substrates.

  • Mass spectrometry-based approaches: Pulse-chase SILAC or TMT labeling to track protein turnover rates.

• Context-specific considerations:

  • For studying RNF149 in macrophages during cardiac repair: Live imaging in primary macrophages under inflammatory conditions .

  • For HCC research: Real-time monitoring in cancer cell lines with varying metastatic potential .

  • For protein quality control: Visualization of RNF149 interaction with non-translocated versus translocated proteins .

These approaches provide complementary information about the dynamic nature of RNF149-substrate interactions in physiologically relevant contexts.

What are the optimal approaches for analyzing RNF149-mediated ubiquitination in different cellular contexts?

Analyzing RNF149-mediated ubiquitination requires specialized techniques that can detect and characterize ubiquitin modifications in various cellular contexts:

• Substrate-specific ubiquitination analysis:

  • Immunoprecipitation followed by ubiquitin western blotting: Pull down specific substrates (e.g., IFNGR1) and probe for ubiquitin to detect modifications .

  • Ubiquitin remnant profiling: Mass spectrometry-based approach to identify specific lysine residues modified by ubiquitin.

  • Ubiquitin chain-specific antibodies: To determine the type of ubiquitin chains (K48, K63, etc.) formed by RNF149.

• Global ubiquitinome analysis:

  • Tandem ubiquitin binding entities (TUBEs): To enrich for ubiquitinated proteins followed by mass spectrometry.

  • Stable isotope labeling by amino acids in cell culture (SILAC): For quantitative comparison of ubiquitination patterns in RNF149-expressing versus deficient cells.

  • TMT or iTRAQ labeling: For multiplexed analysis of ubiquitination changes across multiple conditions.

• Context-specific approaches:

  • For inflammatory macrophages: Analysis of IFNGR1 ubiquitination under IFNγ stimulation in wild-type versus RNF149-deficient macrophages .

  • For HCC research: Examination of DNAJC25 ubiquitination in cancer versus normal hepatocytes .

  • For protein quality control: Assessment of ubiquitination of non-translocated versus translocated proteins in the presence or absence of RNF149 .

• Validation approaches:

  • In vitro ubiquitination assays with purified components to confirm direct substrate modification.

  • Ubiquitination site mutants (lysine to arginine) to validate specific modification sites.

  • Proteasome inhibitors to distinguish between degradative and non-degradative ubiquitination.

• Advanced technologies:

  • Proximity-dependent biotin identification (BioID or TurboID) fused to RNF149 to identify proximal substrates.

  • Ubiquitin sensors that respond to different chain types or densities.

  • CRISPR-based screening for proteins that affect RNF149-mediated ubiquitination.

These methodologies allow comprehensive characterization of RNF149's ubiquitin ligase activity in various physiological and pathological contexts.

What is the potential of RNF149 as a therapeutic target in hepatocellular carcinoma?

RNF149 shows significant promise as a therapeutic target in hepatocellular carcinoma (HCC) based on several lines of evidence:

• Target validation:

  • Upregulation in HCC tissues: Proteomic profiling has demonstrated that RNF149 is significantly upregulated in HCC tumor tissues compared to adjacent normal tissues .

  • Correlation with poor prognosis: High RNF149 expression correlates with poor prognosis in HCC patients, suggesting clinical relevance .

  • Functional validation: Overexpression of RNF149 promotes cell proliferation, migration, and invasion of HCC cells, confirming its oncogenic role .

• Therapeutic approaches:

  • Small molecule inhibitors: Targeting the catalytic RING domain to inhibit E3 ligase activity.

  • Protein-protein interaction disruptors: Compounds that prevent RNF149 from binding to its substrates, such as DNAJC25.

  • Targeted protein degradation: Using proteolysis-targeting chimeras (PROTACs) or molecular glues to induce RNF149 degradation.

  • Gene therapy approaches: siRNA or CRISPR-based strategies to reduce RNF149 expression.

• Biomarker potential:

  • Prognostic marker: RNF149 expression levels could serve as a biomarker for patient stratification .

  • Predictive biomarker: May help identify patients likely to respond to therapies targeting RNF149 or related pathways.

• Immune contexture considerations:

  • Immunotherapy combinations: Since high RNF149 expression correlates with immunosuppressive tumor microenvironment, combining RNF149 inhibition with immunotherapies might be synergistic .

  • Monitoring immune responses: Tracking changes in immune cell infiltration and function following RNF149 targeting.

• Precision medicine approaches:

  • Patient selection: Identifying HCC patients with high RNF149 expression who might benefit most from targeted therapies.

  • Resistance mechanisms: Understanding potential mechanisms of resistance to RNF149-targeted therapies.

The development of RNF149-targeted therapies for HCC represents an emerging area with significant potential for improving outcomes in this aggressive malignancy.

How might modulation of RNF149 activity impact cardiac repair strategies?

Modulation of RNF149 activity presents promising opportunities for enhancing cardiac repair following myocardial infarction based on its role in regulating inflammation and tissue repair:

• Therapeutic potential:

  • Enhancement of RNF149 activity: Since RNF149 deficiency worsens cardiac outcomes after MI, strategies to enhance its activity or expression in macrophages might improve cardiac repair .

  • Targeting the RNF149-IFNGR1 axis: Directly targeting IFNGR1 degradation might be an alternative approach in situations where enhancing RNF149 is challenging.

  • Temporal considerations: The timing of intervention is likely critical, with early enhancement potentially limiting excessive inflammation and cardiomyocyte apoptosis.

• Delivery systems for cardiac applications:

  • Macrophage-targeted delivery: Since RNF149 in macrophages is crucial for cardiac repair, macrophage-specific delivery systems could enhance therapeutic efficacy .

  • Inducible expression systems: Temporally controlled expression of RNF149 to match the dynamic phases of cardiac repair.

  • Local delivery approaches: Catheter-based or device-based local delivery to the infarct area to minimize systemic effects.

• Monitoring repair processes:

  • Imaging biomarkers: Non-invasive methods to track inflammation resolution and scar formation.

  • Circulating biomarkers: Identification of blood-based markers that reflect RNF149 activity in cardiac macrophages.

  • Functional assessments: Echocardiography and other cardiac function measurements to evaluate therapeutic efficacy.

• Combination therapies:

  • Anti-inflammatory combinations: Pairing RNF149 modulation with other anti-inflammatory approaches.

  • Pro-reparative strategies: Combining with therapies that enhance angiogenesis or reduce fibrosis.

  • Cell therapy integration: Potential for combining with macrophage-based cell therapies.

• Precision medicine considerations:

  • Patient stratification: Identifying patients who might benefit most from RNF149-targeted therapies based on inflammatory profiles.

  • Genetic variation: Understanding how genetic variants in RNF149 or related pathways might influence therapeutic responses.

These approaches hold promise for translating the basic science of RNF149 function into novel therapeutic strategies for improving outcomes after myocardial infarction.

What are the unexplored aspects of RNF149 biology that warrant further investigation?

Despite significant advances in understanding RNF149 function, several important aspects remain unexplored and represent promising areas for future research:

• Comprehensive substrate identification:

  • While IFNGR1 and DNAJC25 have been identified as RNF149 substrates, a comprehensive substrate landscape across different tissues and conditions remains to be established .

  • Unbiased proteomics approaches combining proximity labeling with quantitative ubiquitinomics could reveal the full range of RNF149 substrates.

• Regulatory mechanisms:

  • The upstream regulators of RNF149 expression and activity beyond STAT1 remain largely unknown .

  • Post-translational modifications that regulate RNF149 activity, localization, or stability need further characterization.

  • The role of deubiquitinating enzymes (DUBs) that might counteract RNF149 activity warrants investigation.

• Tissue-specific functions:

  • While roles in HCC, cardiac macrophages, and protein quality control have been described, RNF149 function in other tissues, including its known expression in gonocytes, remains unexplored .

  • Tissue-specific knockout models could reveal additional physiological functions.

• Developmental biology:

  • The role of RNF149 during embryonic development and tissue differentiation has not been thoroughly investigated.

  • Temporal regulation of RNF149 expression during development and its functional significance.

• Additional disease associations:

  • Beyond HCC, myocardial infarction, and myeloproliferative neoplasms, potential roles in other diseases remain to be explored .

  • Analysis of RNF149 alterations across cancer types and other diseases through mining of public databases.

• Structural biology:

  • High-resolution structures of RNF149 domains alone and in complex with substrates would provide valuable insights for therapeutic development.

  • Structural basis for substrate specificity and regulation.

• Evolution and conservation:

  • Comparative analysis of RNF149 across species to identify conserved functions and species-specific adaptations.

  • Evolutionary relationships with other E3 ubiquitin ligases.

These unexplored aspects of RNF149 biology represent exciting opportunities for future research that could lead to new therapeutic approaches for various diseases.

How might systems biology approaches advance our understanding of RNF149 in complex disease networks?

Systems biology approaches offer powerful frameworks for understanding how RNF149 functions within complex cellular networks and disease contexts:

• Network integration approaches:

  • Multi-omics integration: Combining transcriptomics, proteomics, ubiquitinomics, and metabolomics data to place RNF149 in broader cellular networks.

  • Protein-protein interaction networks: Mapping the complete RNF149 interactome across different cell types and conditions.

  • Signaling pathway cross-talk: Understanding how RNF149-mediated ubiquitination influences multiple interconnected signaling pathways.

• Computational modeling:

  • Dynamic modeling of RNF149-regulated processes: Mathematical models of how RNF149 activity affects substrate levels and downstream cellular functions over time.

  • Multi-scale models: Linking molecular events to cellular behaviors and tissue-level outcomes in contexts like cardiac repair or tumor progression.

  • In silico prediction of RNF149 substrates: Using machine learning approaches to predict potential substrates based on sequence and structural features.

• Single-cell approaches:

  • Single-cell transcriptomics: Revealing cell-type specific expression patterns of RNF149 and correlations with cell states.

  • Spatial transcriptomics/proteomics: Understanding the spatial context of RNF149 function in complex tissues like tumors or healing myocardium.

  • Cellular trajectory analysis: Mapping how RNF149 expression changes during cell differentiation or disease progression.

• Disease network analysis:

  • Analysis of RNF149 in the context of genetic disease networks: Identifying how RNF149 interacts with known disease-associated genes.

  • Drug-target networks: Predicting potential drug interactions and off-target effects for RNF149-targeted therapeutics.

  • Comorbidity networks: Understanding how RNF149 dysfunction might contribute to multiple related pathologies.

• Systems pharmacology:

  • Network-based drug discovery: Identifying compounds that modulate RNF149 activity or its key network connections.

  • Prediction of combination therapies: Computational approaches to identify synergistic drug combinations targeting RNF149-related networks.

  • Biomarker discovery: Systems-level analysis to identify biomarkers of RNF149 activity for patient stratification.