RPL35A is encoded by the RPL35A gene and belongs to the L35AE family of ribosomal proteins . The antibody targets this protein to investigate its role in ribosomal assembly, cell proliferation, and disease mechanisms.
RPL35A mutations are linked to Diamond-Blackfan anemia (DBA), a bone marrow failure syndrome characterized by anemia and physical abnormalities . Antibodies have been used to:
Confirm RPL35A deficiency: Mutations disrupt ribosomal function, leading to impaired rRNA processing and apoptosis in erythroid precursors .
Study disease mechanisms: shRNA knockdown of RPL35A in hematopoietic cell lines reduces 28S and 5.8S rRNA maturation, impairing 60S subunit biogenesis .
RPL35A overexpression is implicated in cancers, including ovarian and gastric malignancies . Key findings include:
Ovarian cancer: High RPL35A levels correlate with poor survival and tumor progression. Antibodies have shown that knockdown inhibits cell migration and enhances apoptosis .
Gastric cancer: RPL35A promotes proliferation and suppresses apoptosis via pathways involving JNK/p38 and p53 .
RPL35A antibodies are critical for studying rRNA processing defects. In DBA patient cell lines, abnormalities in 32S:12S rRNA ratios and 5.8S rRNA maturation are observed .
Genotype-phenotype correlations: Large 3q29 deletions involving RPL35A are associated with severe DBA phenotypes, including neutropenia, immunodeficiency, and steroid resistance .
Diagnostic utility: Antibodies help identify RPL35A mutations in DBA patients, aiding in personalized treatment strategies (e.g., hematopoietic stem cell transplantation) .
Prognostic value: In ovarian cancer, RPL35A overexpression predicts poor survival and advanced TNM staging .
Therapeutic targeting: Inhibiting RPL35A interactions with YY1/CTCF may offer novel strategies for ovarian cancer therapy .
Antibody specificity: Cross-reactivity with homologous proteins (e.g., RPL35) may require optimization .
Cancer research: Further studies are needed to elucidate RPL35A’s role in metastasis and its interaction with oncogenic pathways (e.g., PPAR signaling) .
Diagnostic advancements: Development of standardized IHC protocols could enhance RPL35A’s utility in clinical settings .
RPL35A (60S ribosomal protein L35a) is a ribosomal protein that functions as an essential component of the large ribosomal subunit. This protein plays critical roles in 60S ribosomal subunit formation and is required for the proliferation and viability of hematopoietic cells . The significance of RPL35A extends beyond its structural role in ribosomes, as it has been found to bind to both initiator and elongator tRNAs, suggesting functional involvement at the P site or both P and A sites during translation .
RPL35A gained particular research interest when mutations in its gene were identified in Diamond-Blackfan anemia (DBA), an inherited bone marrow failure syndrome characterized by anemia, congenital abnormalities, and cancer predisposition . Furthermore, recent studies have implicated RPL35A in cancer progression, particularly in ovarian cancer where it promotes the binding of transcription factor YY1 to the CTCF promoter . These diverse biological functions make RPL35A antibodies invaluable tools for investigating ribosome biology, hematological disorders, and cancer mechanisms.
RPL35A antibodies are versatile research tools employed in multiple experimental contexts:
Immunohistochemistry (IHC): Used to detect RPL35A protein expression patterns in tissue sections, enabling correlation with clinical parameters in pathological conditions .
Immunofluorescence (IF) and Immunocytochemistry (ICC): Allow visualization of RPL35A subcellular localization and potential co-localization with interacting partners .
Flow Cytometry (FACS): Particularly useful with fluorophore-conjugated RPL35A antibodies (such as APC-conjugated versions) for quantitative analysis of RPL35A expression in different cell populations .
Enzyme-Linked Immunosorbent Assay (ELISA/EIA): Used for quantitative measurement of RPL35A protein levels in biological samples .
Chromatin Immunoprecipitation (ChIP): Essential for investigating the involvement of RPL35A in transcriptional regulation, as demonstrated in studies of ovarian cancer where RPL35A influences the binding of transcription factors to promoter regions .
These diverse applications highlight why RPL35A antibodies are indispensable tools in both basic research and translational studies investigating ribosome biology, hematological disorders, and cancer mechanisms.
Proper validation of RPL35A antibodies is critical for ensuring experimental reliability. A comprehensive validation approach should include:
Specificity Testing:
Western blot analysis showing a single band at the expected molecular weight of RPL35A (approximately 12.5 kDa)
Positive and negative control tissues/cell lines with known RPL35A expression levels
Blocking peptide competition assays to confirm specific binding
Knockdown/knockout validation using RPL35A-specific shRNA or CRISPR-Cas9, as demonstrated in studies where shRNA inhibition of RPL35A affected maturation of 28S and 5.8S rRNAs
Cross-Reactivity Assessment:
Application-Specific Validation:
For IHC: Optimize fixation methods, antigen retrieval, and antibody concentration
For IF/ICC: Confirm subcellular localization patterns consistent with known RPL35A distribution
For ChIP applications: Validate enrichment at known binding sites using qPCR with specific primers (e.g., for the CTCF promoter as shown in ovarian cancer research)
Batch-to-Batch Consistency:
Compare new antibody lots with previously validated lots
Maintain positive control samples for standardization
Thoroughly validated antibodies, such as affinity-purified rabbit polyclonal antibodies against human RPL35A (amino acids 1-110) expressed in E. coli, have demonstrated reliable performance across multiple experimental applications .
The connection between RPL35A and Diamond-Blackfan anemia (DBA) represents a significant breakthrough in understanding the molecular basis of this rare inherited bone marrow failure syndrome:
Discovery Context:
RPL35A was identified as a DBA-associated gene through a candidate gene approach combining high-resolution genomic mapping and gene expression microarray analysis of DBA patients with chromosome 3q deletions . This discovery expanded the understanding of DBA beyond previously identified small ribosomal subunit gene mutations (RPS19, RPS24, RPS17).
Mutational Spectrum:
Multiple types of pathogenic variants in RPL35A have been identified in DBA patients:
Genotype-Phenotype Correlations:
A multi-institutional study of 45 DBA patients with pathogenic RPL35A variants revealed distinct clinical patterns:
| RPL35A Variant Type | Clinical Features | Treatment Response |
|---|---|---|
| Large deletions | More severe phenotype, neutropenia (70%), immune system abnormalities, recurrent infections | Often steroid-resistant, transfusion-dependent |
| LOF variants | Earlier age at diagnosis of anemia | Generally better response to treatment |
| Missense/inframe deletions | Less severe phenotype | Better response to steroids |
These differences were statistically significant (P<0.01) when comparing large deletions to other pathogenic variants .
Molecular Mechanism:
Functional studies using shRNA inhibition demonstrated that RPL35A is essential for:
Diagnostic Implications:
Erythrocyte adenosine deaminase (eADA) values, a diagnostic marker for DBA, are elevated in both patients with large deletions and those with other RPL35A variants, with no significant difference between groups (P=0.682) .
This established connection between RPL35A and DBA underscores the importance of ribosome biogenesis in hematopoiesis and provides a mechanistic framework for investigating other ribosomopathies.
RPL35A antibodies offer powerful tools for investigating ribosome biogenesis abnormalities in disease models, particularly for Diamond-Blackfan anemia (DBA) and cancer research. Implementation strategies include:
Polysome Profiling with Immunoblotting:
Fractionate cellular lysates on sucrose gradients to separate free ribosomal subunits, monosomes, and polysomes
Analyze fractions by Western blotting using RPL35A antibodies to track incorporation into pre-60S subunits, mature 60S subunits, and active ribosomes
Compare profiles between wild-type and disease models to identify defects in large subunit assembly
This approach can reveal whether RPL35A mutations affect incorporation into ribosomes or destabilize the entire 60S subunit
Ribosome Biogenesis Intermediates Characterization:
Employ RPL35A antibodies in immunoprecipitation to isolate pre-ribosomal particles
Analyze co-precipitated rRNA species (particularly 28S and 5.8S rRNAs) and protein components
Use pulse-chase labeling with metabolic RNA labeling to track rRNA processing kinetics
Apply this methodology to compare normal cells with those carrying RPL35A mutations or depletion, as studies have demonstrated that RPL35A is essential for maturation of 28S and 5.8S rRNAs
Nucleolar Stress Response Assessment:
Utilize immunofluorescence with RPL35A antibodies to monitor nucleolar morphology and protein localization
Track redistribution of RPL35A under ribosomal stress conditions
Investigate interactions with p53 pathway components, as ribosomal protein imbalance often activates p53-dependent cell cycle arrest
Translation Fidelity Analysis:
Study translation dynamics in cells with altered RPL35A function using reporter systems
Employ RPL35A antibodies in ribosome profiling experiments to analyze ribosome positioning and translation efficiency at a genome-wide level
Investigate connections between RPL35A's role in binding both initiator and elongator tRNAs at the P site or P and A sites
Integrated -Omics Approach:
Combine RPL35A antibody-based proteomics (immunoprecipitation-mass spectrometry) with transcriptomics, especially in DBA patient-derived cells
Profile alterations in ribosome composition and associated factors
Link ribosome biogenesis defects to downstream consequences on specific mRNA translation
These methodological approaches using RPL35A antibodies facilitate a deeper understanding of how ribosome biogenesis perturbations contribute to disease pathogenesis, potentially revealing therapeutic vulnerabilities.
Research has revealed that RPL35A drives ovarian cancer progression through specific transcriptional regulatory mechanisms . To thoroughly investigate RPL35A's role in cancer, consider these optimized experimental designs:
Gene Expression Modulation Studies:
Knockdown Design: Use multiple shRNA constructs targeting different regions of RPL35A (both coding sequence and 3' UTR) with appropriate controls (e.g., luciferase shRNA)
Overexpression Strategy: Employ inducible expression systems to avoid selection against potential growth inhibition
Rescue Experiments: Reintroduce shRNA-resistant RPL35A variants to confirm phenotype specificity
Primary Endpoint Measurements: Cell proliferation, migration, invasion, and apoptosis assessments with standardized assays
ChIP-seq and ChIP-qPCR Workflows:
Sample Preparation: Fix cells with formaldehyde, lyse in SDS buffer, and fragment DNA by sonication
Immunoprecipitation Controls: Include negative control (normal mouse IgG), positive control (Histone H3), and specific antibody (anti-YY1)
Promoter Analysis: Design specific primers for target promoters (e.g., CTCF promoter)
Primer Design Example: For CTCF promoter: 5′-CCCAAGTTTATCACACCGCTCA-3′ and 5′-AAGGCAGCATCTAGGAAGTCATG-3′
Mechanistic Interaction Studies:
Co-immunoprecipitation: Use RPL35A antibodies to pull down protein complexes and identify interacting partners
Proximity Ligation Assays: Visualize and quantify protein-protein interactions in situ
RIME (Rapid Immunoprecipitation Mass spectrometry of Endogenous proteins): Identify chromatin-associated RPL35A interactome
Sequential ChIP: Determine co-occupancy of RPL35A with transcription factors like YY1 at target promoters
Translational Research in Patient Samples:
Tissue Microarray Analysis: Use RPL35A antibodies for immunohistochemical evaluation of expression in tumor versus normal tissues
Correlation Studies: Analyze associations between RPL35A expression and clinical parameters including TNM staging and patient survival
Expression Quantification: Employ qRT-PCR with validated primers (e.g., RPL35A forward: 5′-GAAGGTGTTTACGCCCGAGAT-3′ and reverse: 5′-CGAGTTACTTTTCCCCAGATGAC-3′)
In Vivo Models:
Xenograft Studies: Compare tumor growth, metastasis, and response to therapy between RPL35A-modulated cancer cells and controls
Patient-Derived Xenografts: Test RPL35A-targeting strategies in models that better recapitulate human tumor heterogeneity
Assessment Parameters: Tumor volume, metastatic burden, immunohistochemical analysis of proliferation and apoptosis markers
These experimental designs provide a comprehensive framework for investigating RPL35A's oncogenic functions, particularly its role in promoting transcription factor binding to target promoters in cancer progression.
Distinguishing between RPL35A's canonical role in ribosome structure/function and its emerging non-canonical functions presents a significant challenge in research. Here are methodological approaches to differentiate these functions:
Subcellular Fractionation Analysis:
Methodology: Separate cellular compartments (cytoplasmic, nuclear, nucleolar, chromatin-bound)
Detection: Use RPL35A antibodies for Western blotting of each fraction
Interpretation: Non-ribosomal pools of RPL35A in unexpected locations (nuclear, chromatin-bound) suggest non-canonical functions
Controls: Include markers for each compartment (e.g., nucleolin for nucleolus, histone H3 for chromatin)
Mutational Analysis Strategy:
Design: Create RPL35A variants with mutations that specifically affect:
a) Ribosome incorporation (structural interface mutations)
b) tRNA binding (P-site interaction mutations)
c) Protein-protein interaction sites (surface-exposed regions)
Functional Testing: Assess which cellular functions are disrupted by each mutation type
Readouts: Ribosome assembly (polysome profiles), translation (metabolic labeling), and non-canonical functions (e.g., transcription factor binding)
Temporal Dynamics Investigation:
Experimental Approach: Use rapid RPL35A depletion systems (e.g., auxin-inducible degron)
Time-Course Analysis: Determine which functions are affected first
Hypothesis: Canonical functions requiring new ribosome assembly may take longer to manifest than direct non-canonical functions
Measurement: Monitor ribosome biogenesis (28S and 5.8S rRNA maturation) versus transcription factor binding kinetics
Protein Interaction Network Mapping:
Methodology: Combine immunoprecipitation with mass spectrometry (IP-MS)
Comparative Analysis: Identify interactors in different cellular compartments
Bioinformatic Classification: Group interactors into ribosome-related versus non-ribosomal proteins
Validation: Confirm key interactions with co-IP and proximity ligation assays
Ribosome-Free RPL35A Population Studies:
Isolation Strategy: Immunoprecipitate RPL35A after ribosome depletion (e.g., by ultracentrifugation)
Functional Characterization: Assess activities of this pool specifically
Associated Proteins: Identify unique partners of non-ribosomal RPL35A
Chromatin Association: Use ChIP-seq to map genome-wide binding sites of the non-ribosomal fraction
Comparison Table: Experimental Features for Distinguishing RPL35A Functions
By systematically applying these approaches, researchers can delineate the diverse functions of RPL35A and understand how they may independently contribute to normal physiology and disease states.
Chromatin immunoprecipitation (ChIP) experiments using RPL35A antibodies require careful optimization to investigate its role in transcriptional regulation, particularly in cancer contexts. Based on successful implementations in ovarian cancer research , here are the recommended protocols and considerations:
Sample Preparation Protocol:
Crosslinking: Fix cells with 1% formaldehyde for 10 minutes at room temperature
Quenching: Add glycine to a final concentration of 0.125M
Cell Lysis: Use SDS lysis buffer (1% SDS, 10mM EDTA, 50mM Tris-HCl, pH 8.0)
Chromatin Fragmentation: Sonicate to generate DNA fragments of 200-500bp
Optimize sonication conditions (amplitude, pulse duration, cycle number) for each cell type
Verify fragment size by agarose gel electrophoresis
Antibody Selection and Validation:
ChIP Protocol Optimization:
Antibody Amount: Titrate between 2-5μg per ChIP reaction
Chromatin Amount: Use 25-50μg of chromatin per reaction
Incubation Conditions: Rotate overnight at 4°C
Washing Stringency: Sequential washes with increasing salt concentration
Elution and Reversal of Crosslinks: 65°C incubation for 4-6 hours
DNA Purification: Column-based methods for highest recovery
ChIP-qPCR Analysis:
Primer Design: Create primers spanning predicted binding sites:
qPCR Conditions: Use SYBR-based detection with appropriate controls
Data Normalization: Express results as percent input or fold enrichment over IgG control
Biological Replicates: Minimum of three independent experiments
ChIP-seq Considerations:
Library Preparation: Use low-input library preparation kits for potentially limited ChIP material
Sequencing Depth: Minimum 20 million uniquely mapped reads per sample
Peak Calling: Employ MACS2 or similar algorithms with appropriate parameters
Data Validation: Confirm selected peaks by ChIP-qPCR
Motif Analysis: Identify enriched DNA motifs within peak regions using MEME-ChIP or similar tools
Differential Binding Analysis in Experimental Conditions:
Comparison Strategy: Analyze RPL35A binding in control versus experimental conditions (e.g., overexpression models)
Integration with Gene Expression: Correlate binding changes with differential gene expression
Pathway Enrichment: Analyze biological pathways associated with differential binding sites
These optimized conditions have successfully revealed RPL35A's role in promoting the binding of transcription factor YY1 to the CTCF promoter in ovarian cancer , highlighting the effectiveness of this approach for investigating non-canonical functions of RPL35A in transcriptional regulation.
Studying RPL35A in Diamond-Blackfan anemia (DBA) patient samples presents unique challenges due to the rarity of the disease and the diverse spectrum of pathogenic variants. The following methodological framework maximizes the research value of RPL35A antibodies in this context:
Patient Sample Classification and Analysis:
Stratify Samples by mutation type:
Sampling Considerations: Collect peripheral blood, bone marrow aspirates, and when available, skin fibroblasts (for establishment of patient-derived cell lines)
Control Selection: Include age-matched healthy donors and DBA patients with mutations in other ribosomal protein genes (e.g., RPS19)
Expression Analysis Protocol:
Western Blot Optimization:
Immunohistochemistry for bone marrow biopsies:
Ribosome Biogenesis Assessment:
Northern Blot Protocol for pre-rRNA processing:
Polysome Profiling:
Prepare cytoplasmic extracts from patient-derived cells
Fractionate on 10-50% sucrose gradients
Analyze 40S, 60S, 80S, and polysome peaks
Compare profiles between different RPL35A variant types
Functional Studies in Patient-Derived Cells:
Proliferation and Apoptosis Assays:
Culture erythroid progenitors from patient bone marrow
Monitor cell growth, cell cycle progression, and apoptosis
Compare results across different RPL35A mutation types
Erythroid Differentiation Analysis:
Culture CD34+ cells from patient samples
Induce erythroid differentiation
Monitor expression of differentiation markers using flow cytometry
Correlate differentiation capacity with RPL35A variant type
Rescue Experiments:
Lentiviral Transduction of wild-type RPL35A into patient cells
Readouts: Pre-rRNA processing, polysome profiles, cell proliferation
Hypothesis Testing: Determine if different RPL35A variants show variable rescue efficiency
Correlation: Link molecular phenotypes with clinical severity (e.g., transfusion dependence, response to steroids)
Comparative Analysis Table: RPL35A Function in Different DBA Patient Groups
| Parameter | Large Deletion Patients | Loss-of-Function Variant Patients | Missense/Inframe Deletion Patients |
|---|---|---|---|
| RPL35A Protein Levels | Severely reduced | Reduced | Variable |
| 28S/5.8S rRNA Processing | Severely impaired | Moderately impaired | Mildly impaired |
| 60S Subunit Levels | Markedly decreased | Decreased | Slightly decreased |
| Clinical Phenotype | Severe, transfusion-dependent | Variable, earlier diagnosis | Milder, better steroid response |
| Neutropenia | Common (70%) | Less common | Rare |
| Immunodeficiency | Frequent | Uncommon | Very rare |
These comprehensive methodological approaches enable researchers to establish genotype-phenotype correlations and understand the molecular basis of clinical variability in DBA patients with different types of RPL35A mutations .
Several cutting-edge technologies are poised to revolutionize how RPL35A antibodies can be utilized in ribosome biology research:
Proximity-Based Labeling Combined with Proteomics:
BioID/TurboID Technology: Fuse RPL35A with biotin ligase to identify proteins in close proximity within living cells
Implementation Strategy: Generate stable cell lines expressing RPL35A-BioID fusion proteins
Application Advantage: Maps dynamic interaction networks in different cellular compartments
Research Question Example: Identify differential RPL35A proximity interactomes in normal versus disease states
Super-Resolution Microscopy Techniques:
STORM/PALM Applications: Use fluorophore-conjugated RPL35A antibodies for single-molecule localization microscopy
Experimental Design: Co-localization studies with markers for different nuclear bodies and cytoplasmic ribosomes
Resolution Improvement: Visualize RPL35A distribution at 20-30nm resolution versus 200-300nm with conventional microscopy
Key Investigation: Track RPL35A movement between nucleolus, nucleoplasm, and cytoplasm during ribosome biogenesis
Cryo-Electron Tomography with Gold-Labeled Antibodies:
Method Development: Conjugate RPL35A antibodies with gold nanoparticles
Application: Visualize RPL35A positioning within intact cellular ribosomes
Advantage: Preserves native cellular context unlike traditional cryo-EM of purified ribosomes
Research Goal: Map structural changes in ribosomes from cells with RPL35A mutations
Single-Cell Protein Analysis Technologies:
Mass Cytometry (CyTOF): Use metal-tagged RPL35A antibodies for high-dimensional analysis
Single-Cell Western Blotting: Quantify RPL35A expression heterogeneity
Experimental Context: Analyze primary bone marrow samples from DBA patients
Research Question: How does RPL35A expression vary within erythroid progenitor subpopulations?
CRISPR-Based Genomic Screens Combined with RPL35A Antibodies:
Methodology: Conduct genome-wide CRISPR screens for modifiers of RPL35A function
Readout: Use RPL35A antibodies to track changes in expression, localization, or interaction partners
Application: Identify novel factors influencing RPL35A's role in ribosome biogenesis or cancer progression
Potential Discovery: New therapeutic targets for ribosomopathies or RPL35A-driven cancers
Spatial Transcriptomics with Protein Detection:
Technical Approach: Combine in situ RNA sequencing with RPL35A immunofluorescence
Implementation: Apply to tissue sections from normal and disease samples
Research Value: Correlate RPL35A protein levels with spatial transcriptome alterations
Example Application: Map transcript-specific translation efficiency differences in RPL35A-mutated cells
Ribosome Profiling with RPL35A-Specific Immunoprecipitation:
Method Innovation: Selectively isolate RPL35A-containing ribosomes before ribosome profiling
Hypothesis Testing: Determine if RPL35A-containing ribosomes preferentially translate specific mRNA subsets
Experimental Context: Compare wild-type cells with those expressing mutant RPL35A variants found in DBA
Potential Finding: RPL35A mutations may cause selective translation defects rather than global impairment
These emerging technologies promise to deepen our understanding of RPL35A's multifaceted roles in ribosome biology, hematopoiesis, and cancer, potentially revealing new therapeutic targets for RPL35A-associated diseases.
Recent research demonstrating RPL35A's role in ovarian cancer progression suggests its potential as a therapeutic target. Developing this potential requires specialized research tools and methodological approaches:
Therapeutic Target Validation Strategy:
Conditional Knockdown Models: Develop inducible shRNA or doxycycline-regulated CRISPR systems targeting RPL35A
Xenograft Studies: Assess tumor growth inhibition following RPL35A depletion in established tumors
Patient-Derived Organoids: Test RPL35A targeting in 3D cultures preserving tumor heterogeneity
Therapeutic Window Assessment: Compare effects of partial RPL35A inhibition in cancer versus normal cells
Druggable Interface Identification:
Structural Biology Approaches:
Antibody-Based Mapping:
Develop domain-specific RPL35A antibodies to identify functional regions
Use epitope mapping to pinpoint interaction surfaces
Test antibody fragments for disruption of cancer-promoting interactions
Small Molecule Screening Platforms:
High-Throughput Screening Design:
Develop fluorescence resonance energy transfer (FRET) assays for RPL35A-YY1 interaction
Establish cell-based reporter systems for CTCF promoter activity
Screen compound libraries against these targets
Validation Methodologies:
Therapeutic Antibody Development:
Approach: Generate function-blocking antibodies targeting non-ribosomal RPL35A
Screening Strategy: Test antibody panels for inhibition of RPL35A-YY1 binding
Delivery Methods: Explore antibody-drug conjugates or cell-penetrating antibody fragments
Efficacy Testing: Measure inhibition of cancer cell proliferation and migration
Biomarker Development for Patient Stratification:
IHC Protocols: Standardize RPL35A immunohistochemistry for clinical samples
Expression Thresholds: Establish cutoffs for "RPL35A-high" tumors
Companion Diagnostics: Develop assays for RPL35A-dependent pathways
Patient Selection: Identify candidates most likely to benefit from RPL35A-targeted therapy
Combination Therapy Exploration:
Synergy Screening: Test RPL35A inhibition with standard chemotherapeutics
Mechanistic Investigations: Use RPL35A antibodies to track changes in signaling pathways
Rational Combinations: Target both ribosomal and non-ribosomal functions of RPL35A
Resistance Mechanisms: Monitor adaptations to RPL35A targeting using proteomics
Predictive Response Table: Potential Therapeutic Strategies Based on RPL35A Function
The development of these specialized research tools would establish RPL35A as a validated cancer therapeutic target and provide the necessary framework for translating biological insights into clinical applications.