DAP3 Antibody

What is DAP3 and what are its primary functions in cellular biology?

DAP3 (Death-Associated Protein 3), also known as MRPS29, is a multifunctional protein that serves critical roles in both mitochondrial translation and apoptotic signaling pathways.

DAP3 functions as:

• A component of the small subunit (28S) of the mitochondrial ribosome, where it is assembled at an early stage and interacts extensively with 12S rRNA

• A mediator of interferon-gamma-induced cell death

• A modulator of both intrinsic and extrinsic apoptotic pathways, including those initiated by tumor necrosis factor-alpha, Fas ligand, and gamma interferon

• A potential regulator of mitochondrial fission through influencing dynamin-related protein phosphorylation

• A participant in RNA editing and splicing mechanisms

Recent research demonstrates that DAP3 may influence cellular processes including mitochondrial protein synthesis, ATP production, and autophagy, with DAP3 depletion resulting in decreased function across these pathways .

Verifying antibody specificity requires multiple validation approaches:

Recommended validation methods:

• Western blot analysis with predicted band size validation:

  • Expected molecular weight: 46 kDa (predicted)

  • Observed molecular weight: 40-45 kDa (actual in most tissues)

  • Example validation test: 10% SDS-PAGE gel with HepG2 whole cell lysate at 30 μg

• Positive control tissues/cells:

  • Human tissue: Kidney, heart, colon tissue lysates

  • Cell lines: HepG2, HeLa, U937, MCF7

• Knockdown/overexpression validation:

  • Perform DAP3 gene knockdown experiments to confirm band disappearance

  • Test with DAP3-EGFP overexpression to confirm specific binding

• Cross-reactivity assessment:

  • Test the antibody against mouse (RAW264.7, NIH/3T3) and rat (PC-12) cells to evaluate cross-reactivity

• Immunofluorescence colocalization:

  • Co-stain with mitochondrial markers (e.g., TOM20) to confirm mitochondrial localization

  • Compare with nuclear counterstain (DAPI/Hoechst 33342) to verify subcellular localization

What role does DAP3 play in mitochondrial ribosome assembly and what are the consequences of DAP3 mutations?

DAP3/MRPS29 is a critical component for mitoribosome assembly with significant implications for mitochondrial function:

Mitoribosome assembly role:

• DAP3 is assembled into the small subunit (SSU) at an early stage of mitoribosome biogenesis

• It interacts extensively with 12S rRNA and may associate with components of the inner mitochondrial membrane

• Serves as a structural component for the mitoribosomal small subunit

Consequences of DAP3 mutations:

• Biallelic variants in DAP3 result in reduced assembly of the mitoribosomal small subunit

• Lead to combined oxidative phosphorylation deficiency (complex I and IV)

• Associated with multisystem disorders presenting as:

  • Perrault syndrome (sensorineural hearing loss and ovarian insufficiency)

  • Early childhood neurometabolic phenotypes

  • Lactic acidosis, hypoglycemia, and hepatic dysfunction

Experimental evidence:

• Proteomic profiling of patient fibroblasts shows reduced MRPS29 protein levels and decreased levels of additional mitoribosomal small subunit components

• Lentiviral transduction with wild-type DAP3 cDNA partially rescues protein levels of MRPS7, MRPS9, and complex I and IV subunits

• Protein modeling suggests DAP3 disease-associated missense variants impact ADP binding

• In vitro assays demonstrate DAP3 variants reduce intrinsic and extrinsic apoptotic sensitivity, thermal stability, and GTPase activity

How does DAP3 influence apoptotic pathways and what methodological approaches can be used to study this function?

DAP3 is involved in both the intrinsic (mitochondrial) and extrinsic (death receptor-mediated) apoptotic pathways:

Apoptotic mechanisms:

• Acts as an adapter protein for death-inducing signaling complexes in the extrinsic pathway

• Recruits FADD to TRAIL receptors (DR4 and DR5) in a GTP-dependent manner

• May be aided by DAP3-binding protein death ligand signal enhancer (DELE1)

• Influences mitochondrial fission, which is closely associated with apoptosis

Methodological approaches for studying DAP3's role in apoptosis:

• Apoptotic sensitivity assays:

  • Treat fibroblasts with intrinsic and extrinsic apoptosis mediators

  • Compare apoptotic responses between DAP3 wildtype and variant cells

  • Measure apoptotic markers (e.g., caspase activation, PARP cleavage)

• DAP3 knockdown/overexpression experiments:

  • Utilize siRNA or CRISPR-Cas9 for DAP3 knockdown

  • Perform gene transfection for DAP3 overexpression

  • Assess effects on cell proliferation, apoptosis, cell cycle, and metastasis

• Tumor necrosis factor-alpha (TNF-α) response analysis:

  • Treat cells with recombinant human TNF-α

  • Monitor DAP3 expression changes

  • Evaluate apoptotic responses in relation to DAP3 levels

• Cancer cell line sensitivity studies:

  • Compare DAP3 expression across cancer cell lines (e.g., BGC-823 and HGC-27 gastric cancer cells)

  • Correlate expression with sensitivity to apoptotic inducers like 5-fluorouracil

• Thermal stability and GTPase activity assays:

  • Perform melt-curve analysis to assess protein stability

  • Measure GTPase activity of wild-type versus mutant DAP3 proteins

Optimizing DAP3 antibody protocols for immunohistochemistry (IHC) and immunofluorescence (IF) requires attention to several technical parameters:

Immunohistochemistry optimization:

• Sample preparation:

  • Paraffin-embedded tissues: Use MDA-MB-231 xenograft or human colon/stomach tissue

  • Recommended fixation: Formalin or paraformaldehyde fixation

  • Section thickness: 4-5 μm for optimal staining

• Antigen retrieval methods:

  • Primary option: TE buffer (pH 9.0)

  • Alternative option: Citrate buffer (pH 6.0)

  • Recommended retrieval time: 20 minutes with heat-mediated retrieval

• Antibody dilution ranges:

  • For polyclonal antibodies: 1:200-1:800

  • For monoclonal antibodies: 1:100-1:250

  • Incubation period: 30 minutes at room temperature or overnight at 4°C

• Detection systems:

  • For chromogenic detection: Peroxidase-based systems (e.g., LeicaDS9800 Bond Polymer Refine Detection)

  • Counterstaining: Hematoxylin provides optimal contrast

Immunofluorescence optimization:

• Cell preparation:

  • Recommended cell lines: HeLa, MCF7

  • Fixation: Methanol or 4% paraformaldehyde (10-15 minutes)

  • Permeabilization: 0.15% Triton X-100

• Antibody concentrations:

  • Primary antibody: 1:200-1:300 dilution

  • Secondary antibody: Alexa Fluor®488-conjugated at 2 μg/ml

  • Incubation time: 1 hour at room temperature for primary antibody

• Nuclear counterstaining:

  • Recommended dyes: Hoechst 33342 (blue) or DAPI

  • Expected pattern: DAP3 shows primarily mitochondrial (cytoplasmic) localization with punctate staining pattern

• Controls and interpretation:

  • Positive control: Mitochondrial co-localization markers (e.g., TOM20)

  • Negative control: Unimmunized serum or isotype control

  • Expected staining: Green fluorescence in cytoplasm with mitochondrial pattern

What approaches are most effective for investigating DAP3's GTPase activity and its relationship to protein function?

DAP3 is a GTP-binding protein with GTPase activity that affects both its mitoribosomal and apoptotic functions:

Effective methodologies for studying DAP3 GTPase activity:

• Protein modeling and structural analysis:

  • Create models of DAP3 to identify residues involved in ADP/GTP binding

  • Analyze how disease-associated mutations affect nucleotide binding pockets

  • Predict functional consequences of structural alterations

• In vitro GTPase activity assays:

  • Express and purify recombinant wild-type and mutant DAP3 proteins

  • Measure GTPase activity using colorimetric or fluorometric assays

  • Compare intrinsic GTPase activity between wild-type and mutant proteins

  • Utilize phosphate release assays to quantify GTP hydrolysis rates

• Thermal stability assessment:

  • Perform melt-curve analysis to evaluate protein stability

  • Compare thermal stability profiles between wild-type and mutant DAP3

  • Correlate stability changes with alterations in GTPase activity

• Structure-function relationship studies:

  • Generate specific mutations in DAP3's GTP-binding domain

  • Assess the impact on both GTPase activity and apoptotic function

  • Correlate GTPase activity with ability to recruit FADD to TRAIL receptors

• Cell-based functional assays:

  • Transfect cells with wild-type or GTPase-deficient DAP3 mutants

  • Evaluate effects on mitoribosome assembly and apoptotic sensitivity

  • Measure mitochondrial protein synthesis and respiration

How can DAP3 be utilized as a prognostic biomarker in hepatocellular carcinoma and what validation approaches are necessary?

DAP3 shows significant promise as a prognostic biomarker in hepatocellular carcinoma (HCC) with potential therapeutic implications:

Evidence supporting DAP3 as an HCC biomarker:

• High DAP3 expression correlates with poor prognosis in HCC patients

• DAP3 expression is linked to specific HCC subtypes

• Elevated DAP3 levels are associated with larger tumor size and higher alpha-fetoprotein levels

• Cox analysis confirms DAP3 as an independent prognostic marker

Methodological approaches for validation and implementation:

• Multi-database transcriptomic analysis:

  • Extract DAP3 transcriptome data from TCGA, GEO, and ICGC databases

  • Perform comparative analysis of expression levels across different patient cohorts

  • Correlate expression with clinical parameters and survival outcomes

• Development of prognostic risk models:

  • Construct and validate prognostic risk models using DAP3 expression data

  • Evaluate model performance using receiver operating characteristic (ROC) curves

  • Generate Kaplan-Meier plots to visualize survival differences

  • Create predictive nomograms to integrate DAP3 with other clinical characteristics

• Experimental validation:

  • Perform quantitative real-time PCR (qRT-PCR) to measure DAP3 mRNA levels

  • Use Western blot to assess protein expression in HCC tissue and cell lines

  • Conduct immunohistochemical staining on tissue microarrays for visualization

• Functional validation:

  • Perform gene knockdown and overexpression experiments in HCC cell lines

  • Conduct cell proliferation (CCK-8), colony formation, apoptosis, migration, and invasion assays

  • Correlate cellular phenotypes with DAP3 expression levels

• Clinical correlation analyses:

  • Associate DAP3 expression with:

    • Tumor size and stage

    • Alpha-fetoprotein levels

    • Response to therapies including Sorafenib

  • Validate in independent patient cohorts

What methodological approaches can be used to investigate the relationship between DAP3 and immune infiltration in tumor microenvironments?

DAP3 expression appears to influence tumor immune microenvironments, with significant implications for immunotherapy response:

Methodological approaches for investigating DAP3-immune interactions:

• Immune cell infiltration algorithms:

  • Calculate immune cell scores using multiple algorithms:

    • TIMER algorithm

    • CIBERSORT method

    • MCP counter algorithm

  • Compare immune cell infiltration patterns between high and low DAP3 expression groups

• Immunotherapy response prediction:

  • Utilize Tumor Immune Dysfunction and Exclusion (TIDE) data

  • Evaluate potential for immune evasion in relation to DAP3 expression

  • Analyze differences in predictive scores for features including:

    • Dysfunction

    • Exclusion

    • Myeloid-derived suppressor cells (MDSCs)

• Immune checkpoint expression analysis:

  • Analyze expression of immune checkpoint genes in relation to DAP3 levels

  • Correlate DAP3 expression with PD-1, PD-L1, CTLA-4, and other immune checkpoint molecules

  • Assess potential implications for checkpoint inhibitor therapy

• Treatment response correlation:

  • Compare treatment response (e.g., Sorafenib) between high and low DAP3 expression groups

  • Generate ROC curves to validate sensitivity and specificity of DAP3 in predicting treatment response

  • Develop predictive models for therapeutic outcomes

• Single-cell sequencing approaches:

  • Perform single-cell RNA sequencing of tumor samples

  • Analyze DAP3 expression at single-cell resolution

  • Map DAP3 expression to specific immune cell populations

  • Correlate with markers of immune cell activation or exhaustion