RPL9 Antibody

What are the optimal applications for RPL9 antibody detection methods?

Based on validation data across multiple sources, RPL9 antibodies demonstrate high specificity in Western blot (1:500-1:50000 dilution), immunohistochemistry (1:50-1:500), and immunofluorescence (1:200-1:800) . For optimal results in Western blot applications, using 20-30 μg of total protein from whole cell lysates is recommended, with HeLa, HepG2, and HCT116 cells showing consistent detection at the predicted molecular weight of 22 kDa . For immunofluorescence, methanol fixation at 1/200 dilution has been successfully employed with HeLa cells . When conducting flow cytometry analysis of RPL9, proper permeabilization is critical since RPL9 is primarily an intracellular protein .

How can I validate the specificity of my RPL9 antibody?

Verification of RPL9 antibody specificity should include:

• siRNA knockdown validation: Transfect cells with RPL9-specific siRNA (e.g., sequence 5'-GCAATCAGACTGTCGACATTC-3') and perform Western blot to confirm reduction in RPL9 protein levels .

• Multiple cell line testing: Compare detection across diverse cell types that express RPL9 at different levels (e.g., HeLa, HepG2, HCT116, NALM-6) .

• Proper molecular weight confirmation: Verify detection at the expected 22 kDa band .

• Tissue specificity: Test in tissues known to express RPL9, such as brain and cerebellum .

• Recombinant protein control: Use RPL9 fusion protein as a positive control .

How can I use RPL9 antibodies to investigate cancer stemness properties?

To investigate RPL9's role in cancer stemness:

• Sphere formation assays: Perform RPL9 knockdown in cancer cell lines like HT29, then evaluate both size and number of spheres formed over 9 days using phase-contrast microscopy .

• CD133+ cell isolation: Isolate CD133+ cancer stem cells using magnetic-activated cell sorting (MACS) or fluorescence-activated cell sorting (FACS) .

• Co-staining analysis: Perform dual immunofluorescence for RPL9 and stem cell markers (CD133) to assess correlation in expression patterns .

• Migration and invasion assays: Conduct transwell migration and Matrigel invasion assays after RPL9 knockdown to assess stemness-associated phenotypes .

• RT-qPCR analysis: Measure expression of stemness-related genes (CD133, ID-1) after RPL9 modulation using appropriate primers (CD133 forward: 5'-AGTCGGAAACTGGCAGATAGC-3', CD133 reverse: 5'-GGTAGTGTTGTACTGGGCCAAT-3') .

What methodological approaches should I use to examine RPL9's role in p53 pathway activation?

To study RPL9's role in p53 pathway activation:

For comprehensive analysis, perform RPL9 knockdown using validated siRNA sequences and compare effects on p53 pathway components across multiple cell lines. Include appropriate controls such as p53-null cells to confirm pathway specificity .

What techniques are most effective for studying RPL9's role in ribosome biogenesis?

To investigate RPL9's function in ribosome biogenesis:

• Polysome profiling: After RPL9 knockdown, analyze polysome profiles by sucrose gradient centrifugation to assess 80S monosome formation and polysome assembly .

• Pre-rRNA processing analysis: Use Northern blotting with probes specific for different pre-rRNA intermediates to detect processing defects induced by RPL9 depletion .

• Nucleolar stress assessment: Examine nucleolar morphology using immunofluorescence with nucleolar markers (fibrillarin, nucleolin) following RPL9 knockdown .

• Metabolic labeling: Perform pulse-chase experiments with 32P-orthophosphate to track ribosomal RNA synthesis and processing kinetics .

• Mass spectrometry: Analyze changes in ribosome composition following RPL9 depletion to identify alterations in associated proteins .

The search results indicate that RPL9 variants can differentially impact pre-rRNA processing during ribosome biogenesis, affecting downstream cellular processes including TP53 pathway activation and erythrocyte development .

How should I design RPL9 knockdown experiments to ensure reliable results?

For robust RPL9 knockdown experimental design:

• Target sequence selection: Use validated siRNA sequences like "GCAATCAGACTGTCGACATTC" that have demonstrated efficient knockdown (70-80% reduction) .

• Multiple time points: Assess effects at various time points (24h, 48h, 72h, 96h) to capture both immediate and delayed responses .

• Proper controls: Include non-targeting shRNA/siRNA controls (shCtrl) and untreated cells .

• Knockdown validation: Confirm RPL9 reduction at both mRNA level (RT-qPCR) and protein level (Western blot, flow cytometry) .

• Cell viability monitoring: Track cell viability during knockdown using MTT assays to distinguish specific effects from general cytotoxicity .

• Multiple cell lines: Test effects across different cell types (e.g., HT29, HCT116, NALM-6) to identify cell-type specific responses .

• Rescue experiments: Perform rescue experiments with RPL9 overexpression to confirm specificity of observed phenotypes .

What are the critical factors for successfully using RPL9 antibodies in immunohistochemistry?

For optimal immunohistochemistry (IHC) with RPL9 antibodies:

• Tissue fixation: Use 4% paraformaldehyde fixation for optimal epitope preservation .

• Antigen retrieval methods: For optimal results, use TE buffer at pH 9.0, though citrate buffer at pH 6.0 can serve as an alternative .

• Antibody dilution range: Use dilutions between 1:50-1:500, with optimization recommended for each tissue type .

• Positive control tissues: Include mouse cerebellum tissue as a reliable positive control .

• Counterstaining: Standard Haematoxylin and Eosin (H&E) staining works well for morphological assessment .

• Specificity controls: Include isotype controls and RPL9-depleted samples to confirm staining specificity .

• Detection systems: Both chromogenic and fluorescent secondary detection systems are compatible with RPL9 antibodies .

How do I interpret variable RPL9 expression patterns across different cancer types?

When analyzing differential RPL9 expression across cancer types:

• Baseline comparison: Compare tumor samples with matched normal tissues rather than cell lines alone. Research shows RPL9 is significantly upregulated in B-ALL cells and colorectal cancer compared to normal counterparts .

• Expression correlation analysis: Examine correlations between RPL9 and other markers:

  • In B-ALL: Correlation with proliferation markers (Ki-67, Myc)

  • In colorectal cancer: Association with stemness markers (CD133, ID-1)

• Function interpretation: Different roles may exist depending on cancer type:

  • In B-ALL: RPL9 knockdown activates p53 signaling and increases MICA/B expression

  • In colorectal cancer: RPL9 maintains stemness properties via ID-1 signaling

  • In inflammation: RPL9 may function as a novel DAMP with regulatory roles in proinflammatory responses

• Expression heterogeneity assessment: Use imaging flow cytometry for single-cell resolution of RPL9 expression to detect population heterogeneity .

What might cause inconsistent results when using RPL9 antibodies in my experiments?

Troubleshooting inconsistent RPL9 antibody results:

How might RPL9 function as a therapeutic target in cancer treatment?

RPL9 shows significant potential as a therapeutic target in cancer:

• B-cell acute lymphocytic leukemia (B-ALL): RPL9 knockdown significantly suppresses B-ALL cell proliferation both in vitro and in vivo, while enhancing apoptosis. Additionally, RPL9 knockdown extends survival time in mouse xenograft models and increases MICA/B expression, potentially enhancing NK cell-mediated cytotoxicity .

• Colorectal cancer (CRC): RPL9 maintains CRC stemness properties through the ID-1 signaling axis. Targeting RPL9 reduces invasion, migration, and sphere-forming capacity of CD133+ colorectal cancer stem cells, suggesting its role in preventing metastasis and recurrence .

• Therapeutic strategies:

  • siRNA/shRNA delivery targeting RPL9 mRNA

  • Small molecule inhibitors disrupting RPL9 function

  • Combination with immunotherapy to enhance NK cell recognition

  • Targeting upstream regulators like FTO that modify m6A-RPL9

• Potential advantages: RPL9 knockdown activates the p53 signaling pathway specifically in cancer cells and upregulates MICA/B expression, potentially making tumors more susceptible to immune surveillance .

What is the significance of RPL9 mutations in Diamond-Blackfan anemia and cancer predisposition?

RPL9 variants have important implications in both hematological disorders and cancer:

How does RPL9 contribute to inflammatory responses, and what are the research implications?

RPL9's role in inflammation presents novel research directions:

• Novel DAMP function: RPL9 has been identified as a damage-associated molecular pattern molecule (DAMP) that can be found in the centrifugal supernatant of ruptured cells and in the serum of lipopolysaccharide (LPS)-stimulated sepsis model mice .

• Regulatory role: Unlike typical pro-inflammatory DAMPs like HMGB1, RPL9 exhibits a regulatory function by suppressing the potentiated mRNA expression and protein production of TNF-α in macrophages stimulated with HMGB1 plus LPS .

• Interaction mechanism: Differential scanning fluorimetric analysis suggests direct interaction between RPL9 and HMGB1 may contribute to RPL9's suppressive effects on inflammatory responses .

• Research implications:

  • Therapeutic potential in inflammatory diseases by leveraging RPL9's regulatory properties

  • New insights into the balance between pro- and anti-inflammatory signals in sepsis

  • Understanding how ribosomal proteins may have extra-ribosomal functions in immunity

• Experimental approaches: Researchers should consider both intracellular and extracellular RPL9 functions when studying inflammatory conditions and include analysis of RPL9 levels in plasma/serum samples from patients with sepsis or inflammatory disorders .