RNF10 Antibody

What is RNF10 and what are its main cellular functions?

RNF10 (RING finger protein 10) is an E3 ubiquitin-protein ligase that catalyzes monoubiquitination of 40S ribosomal proteins, particularly RPS2/us5 and RPS3/us3, in response to ribosome stalling . This action is part of a ribosome quality control mechanism (iRQC) that occurs when ribosomes stall during translation initiation or elongation . The monoubiquitination promotes degradation of these proteins by the proteasome, with USP10 acting as a counterbalance to RNF10's activity .

Beyond ribosomal quality control, RNF10 serves additional functions. It may act as a transcriptional factor regulating MAG (Myelin-associated glycoprotein) expression and plays a role in Schwann cell differentiation and myelination . Importantly, RNF10 also functions as a synaptonuclear messenger in neurons, relaying signals from synapses to the nucleus to facilitate long-lasting modifications of dendritic structures .

What experimental techniques commonly utilize RNF10 antibodies?

RNF10 antibodies have been validated for multiple experimental techniques, each providing different insights into protein function and interactions:

• Western Blotting (WB): The most common application, allowing detection of RNF10 protein levels in cellular lysates. Commercial antibodies like ab104159 have been specifically validated for this technique in human and mouse samples .

• Immunoprecipitation (IP): Used to isolate RNF10 and its interacting partners. This has been crucial in identifying RNF10's interaction with GluN2A but not GluN2B subunits of NMDARs .

• Immunofluorescence (IF): Enables visualization of RNF10 subcellular distribution, revealing its presence in both nuclear and synaptic compartments of neurons .

• Proximity Ligation Assay (PLA): Used to confirm close proximity (<40 nm) between RNF10 and its interacting partners, such as GluN2A at synapses .

• Subcellular fractionation: Used in combination with immunoblotting to determine RNF10's association with specific cellular compartments, including postsynaptic densities (PSDs) .

What is the subcellular localization of RNF10?

RNF10 exhibits a complex subcellular distribution pattern that varies by cell type and context. In neurons, RNF10 shows a dual localization pattern:

• Synaptic localization: RNF10 is associated with synaptic fractions and is prominently present in postsynaptic density (PSD) fractions . Immunofluorescence studies in primary hippocampal neurons show clustered RNF10 immunolabeling along dendrites with significant co-localization with GluN2A and PSD-95 .

• Nuclear localization: RNF10 is also detected in neuronal soma and nuclei . This dual localization is consistent with its function as a synaptonuclear messenger.

• Activity-dependent translocation: Enhanced excitatory activity significantly decreases RNF10 immunoreactivity along dendrites while increasing nuclear RNF10 staining, suggesting activity-dependent translocation from synapses to the nucleus .

Subcellular fractionation experiments have confirmed this distribution pattern biochemically, demonstrating RNF10's presence in both synaptic and nuclear compartments .

What is known about RNF10 expression in different tissues?

While the search results don't provide comprehensive information about RNF10 expression across all tissues, several important patterns have been documented:

• Neural tissues: RNF10 is expressed in hippocampal neurons, where it plays roles in synaptonuclear signaling . It's also involved in Schwann cell differentiation and myelination .

• Cancer cells: RNF10 is highly upregulated in tumor cells compared with normal tissues . This differential expression may be relevant for cancer immunotherapy approaches targeting RNF10 uORF-encoded peptides.

• Cell lines: RNF10 expression has been documented in various research cell lines, including HeLa cells, RPE1 cells (human retinal pigment epithelial cells), and COS-7 cells (expressing endogenous RNF10) .

The expression pattern of RNF10 is functionally significant, as its presence in both neuronal and cancer contexts highlights its diverse roles in cellular processes.

How can RNF10 antibodies be used to study synaptonuclear signaling in neurons?

Studying RNF10's role in synaptonuclear signaling requires sophisticated experimental approaches utilizing RNF10 antibodies:

• Activity-dependent translocation studies: To investigate RNF10's movement from synapses to the nucleus, researchers can stimulate neurons with protocols that enhance excitatory activity (e.g., bicuculline + 4-AP treatment) and track RNF10 localization using immunofluorescence . This approach reveals decreased dendritic RNF10 and increased nuclear RNF10 following stimulation.

• Photoconversion tracking: Time-lapse confocal imaging of RNF10 fused to photoconvertible proteins (e.g., tdEOS) allows direct visualization of RNF10 trafficking. By photoconverting RNF10-tdEOS in distal dendrites from green-to-red emission and tracking the red fluorescence over time, researchers can quantify nuclear accumulation following stimulation .

• Co-localization with transport machinery: RNF10 antibodies can be used to demonstrate co-localization with importins (particularly importin α1) along dendrites, suggesting a mechanism for nuclear transport . This can be complemented with co-immunoprecipitation studies to confirm physical interactions.

• Proximity ligation assays: PLA can confirm RNF10's close association with synaptic proteins like GluN2A, providing evidence for its synaptic localization before activity-dependent translocation .

These approaches collectively allow researchers to track RNF10's movement from synapses to the nucleus and investigate the mechanisms underlying this translocation.

What methodological considerations are important when studying RNF10's role in ribosome quality control?

Investigating RNF10's function in ribosome quality control requires specific experimental approaches:

• Ribosome stalling induction: Researchers can use translation inhibitors that induce ribosome stalling through different mechanisms, such as anisomycin (ANI), cycloheximide (CHX), or blasticidine (BLA) . These treatments allow observation of RNF10-mediated monoubiquitination of ribosomal proteins.

• RNF10 knockdown/knockout approaches: siRNA-mediated knockdown or CRISPR/Cas9-mediated knockout of RNF10 can be used to confirm its specific role in ribosomal protein ubiquitination . Multiple siRNAs should be used to control for off-target effects, as demonstrated in studies using two distinct siRNAs against RNF10 (e.g., #213) .

• Ubiquitination assays: Western blotting with antibodies against ubiquitin and specific ribosomal proteins (RPS2/us5 and RPS3/us3) can detect changes in their ubiquitination status in response to RNF10 manipulation and ribosome stalling .

• Cell type considerations: RNF10's ribosome quality control function has been demonstrated in multiple cell types, including cancer cells (HeLa) and non-cancerous cells (RPE1) , suggesting this is a conserved function that should be verifiable across different experimental systems.

• Controls for specificity: When studying RNF10's E3 ligase activity, appropriate controls should include analysis of other E3 ligases and deubiquitinating enzymes like USP10, which counteracts RNF10's function in iRQC .

How can researchers investigate RNF10's potential in cancer immunotherapy?

The upstream open reading frame (uORF) of RNF10 encodes an antigenic peptide (RNF10 uPeptide) capable of eliciting a T cell-mediated anti-tumor immune response, making it a promising target for cancer immunotherapy . Key methodological approaches include:

• Epitope prediction and validation: Researchers should use computational algorithms like the Immune Epitope Database (IEDB) consensus method to predict MHC class I binding epitopes within the RNF10 uPeptide . In mouse models, predicted epitopes can be validated using:

  • ELISpot assays to detect epitope-specific immune responses in splenocytes from vaccinated mice

  • Flow cytometry to measure cytokine production (IFN-γ, TNF-α, IL-2) by CD8+ T cells in response to epitope stimulation

  • ELISA and qRT-PCR to confirm cytokine production at protein and mRNA levels

• CTL assay methodology: To assess the cytotoxic potential of RNF10 uPeptide-specific T cells:

  • Sort T cells from immunized mice and incubate them with dendritic cells pulsed with the peptide

  • After multiple stimulations, measure cytotoxicity against cancer cells using LDH release assays

  • Confirm killing efficacy using flow cytometry-based cytotoxicity assays

• Human application studies: For translational research, the following steps are critical:

  • Predict binding affinities of human RNF10 uPeptide to HLA class I alleles (e.g., HLA-A2)

  • Synthesize predicted epitopes (e.g., RLFGQQQRA) and load them onto HLA-matched dendritic cells

  • Test the ability of these peptides to stimulate T cells from cancer patients using ELISpot, flow cytometry, and tetramer staining

• In vivo efficacy testing: Researchers can use patient-derived xenograft (PDX) models in immunocompromised mice reconstituted with human immune cells to test vaccine efficacy:

  • Measure tumor growth following vaccination with RNF10 uPeptide-loaded dendritic cells

  • Analyze tumor-infiltrating lymphocytes by flow cytometry to confirm the presence of RNF10-uPeptide-specific CD8+ T cells

What approaches should be used to study interactions between RNF10 and other proteins?

Studying protein-protein interactions involving RNF10 requires multiple complementary approaches:

• Co-immunoprecipitation (co-IP): This is the gold standard for confirming protein interactions. For RNF10:

  • Use hippocampal P2 crude membrane fractions for co-IP studies with specific antibodies against potential interacting partners

  • Include appropriate controls (irrelevant antibodies or no-antibody conditions)

  • Analyze specific subcellular fractions (e.g., PSD fractions) to identify compartment-specific interactions

• Heterologous expression systems: For validation of direct interactions:

  • Co-express tagged versions of RNF10 (e.g., GFP-tagged) with potential partners in heterologous cells like COS-7

  • Perform co-IP experiments and analyze by immunoblotting

  • Use immunofluorescence to assess co-localization patterns

• Proximity Ligation Assay (PLA):

  • This technique detects proteins that are in close proximity (<40 nm)

  • PLA signals can be visualized in specific subcellular compartments (e.g., dendrites, dendritic spines)

  • Include proper controls using single antibodies to verify specificity

• Yeast two-hybrid screening:

  • Can be used as an initial approach to identify potential interacting partners

  • Results should be validated using the methods described above

• Interaction domain mapping:

  • Generate truncated constructs to identify specific domains responsible for protein-protein interactions

  • This is particularly useful for understanding the structural basis of interactions between RNF10 and partners like importin α1

These approaches have been successfully employed to characterize RNF10's interactions with GluN2A (but not GluN2B) subunits of NMDARs and with multiple importin α isoforms (except importin α3) .

How can researchers validate RNF10 antibody specificity?

Validating antibody specificity is crucial for obtaining reliable results. For RNF10 antibodies, several validation approaches should be considered:

• Genetic knockout/knockdown controls:

  • Generate RNF10 knockout cells using CRISPR/Cas9 technology or knockdown using siRNA

  • Compare antibody signals between wild-type and knockout/knockdown samples by Western blotting and immunofluorescence

  • A specific antibody should show significantly reduced or absent signal in knockout/knockdown samples

• Overexpression validation:

  • Express tagged RNF10 (e.g., HA-tagged or GFP-tagged) in cells

  • Perform dual labeling with anti-tag antibodies and anti-RNF10 antibodies

  • Signals should co-localize in overexpressing cells

• Cross-reactivity testing:

  • Test the antibody against related RING finger proteins to ensure specificity

  • Include negative controls in immunoprecipitation experiments (irrelevant antibodies or no-antibody conditions)

• Multiple antibody comparison:

  • When possible, use multiple antibodies targeting different epitopes of RNF10

  • Concordant results with different antibodies increase confidence in specificity

• Peptide competition assays:

  • Pre-incubate the antibody with the immunizing peptide before application

  • A specific antibody should show diminished signal when pre-blocked with its target epitope

What are common technical challenges when working with RNF10 antibodies?

Researchers may encounter several challenges when working with RNF10 antibodies:

• Detecting translocation events:

  • RNF10's dual localization (synaptic and nuclear) requires careful experimental design

  • Quantification of nuclear translocation may be challenging due to baseline nuclear signals

  • Solution: Use photoconvertible fusion proteins to specifically track movement from one compartment to another

• Preserving protein-protein interactions:

  • Interactions may be sensitive to detergent conditions during extraction

  • Solution: Test multiple lysis conditions with varying detergent types and concentrations for co-immunoprecipitation studies

• Background in immunofluorescence:

  • High background may obscure specific signals, particularly at synapses

  • Solution: Optimize blocking conditions, antibody dilutions, and consider using tyramide signal amplification for weak signals

• Detecting ubiquitination:

  • RNF10-mediated monoubiquitination may produce subtle mobility shifts

  • Solution: Use ubiquitin-specific antibodies and consider using ubiquitination-specific enrichment methods before Western blotting

• Tissue-specific differences:

  • RNF10 expression and function may vary across tissues

  • Solution: Validate antibody performance in each specific tissue or cell type of interest

How might RNF10 antibodies contribute to understanding neurological disorders?

Given RNF10's role in synaptonuclear signaling and neuronal plasticity, RNF10 antibodies could be valuable tools for investigating neurological disorders:

• Synaptic dysfunction studies: RNF10 antibodies could help investigate altered synaptonuclear signaling in models of neurodevelopmental and neurodegenerative disorders. Changes in RNF10 localization or trafficking might reflect synaptic dysfunction .

• Activity-dependent gene expression: Since RNF10 translocates to the nucleus following neuronal activation, antibodies against RNF10 could help investigate disruptions in activity-dependent gene expression in disease models .

• Therapeutic target validation: If RNF10 pathway dysregulation is implicated in neurological disorders, antibodies will be essential for validating therapeutic approaches targeting this pathway.

• Circuit-specific analysis: Combined with circuit-tracing methods, RNF10 antibodies could help identify cell type-specific and circuit-specific alterations in synaptonuclear signaling in disease models.

• Biomarker development: If RNF10 or its ubiquitination targets are altered in neurological conditions, antibodies could potentially be used in developing diagnostic biomarkers.

What are the implications of RNF10's role in cancer for immunotherapy research?

RNF10's upregulation in tumor cells and the immunogenicity of its uORF-encoded peptides have significant implications for cancer immunotherapy research:

• Cancer vaccine development: The demonstrated immunogenicity of RNF10 uPeptides in both mouse models and human T cells suggests potential for developing peptide-based cancer vaccines .

• Target validation studies: Antibodies against RNF10 will be crucial for validating its expression in different tumor types, helping to identify cancers that might respond to RNF10-targeted immunotherapy .

• Combination therapy approaches: Research could explore combining RNF10 uPeptide vaccination with other immunotherapies, such as checkpoint inhibitors, requiring antibody-based monitoring of target expression and immune responses.

• Patient stratification: Antibodies against RNF10 could potentially help identify patients more likely to respond to RNF10-targeted immunotherapies based on expression levels.

• Tumor microenvironment studies: Investigating how RNF10 expression influences the tumor microenvironment could reveal additional therapeutic opportunities, with antibodies being essential tools for such studies.