DGUOK Antibody

What is DGUOK and why is it important in research?

DGUOK (deoxyguanosine kinase) is a mitochondrial enzyme that plays a critical role in the phosphorylation of purine deoxyribonucleosides in the mitochondrial matrix. This 277 amino acid protein is essential for maintaining mitochondrial DNA integrity by catalyzing the conversion of deoxyguanosine to deoxyguanosine monophosphate using ATP. DGUOK has gained significant research interest due to its involvement in NAD+ biogenesis, mitochondrial oxidative phosphorylation, and its overexpression in certain cancers, particularly lung adenocarcinoma . Additionally, mutations in DGUOK can lead to mitochondrial DNA depletion syndrome, making it an important target for both cancer and genetic disorder research .

What applications are DGUOK antibodies suitable for?

DGUOK antibodies can be utilized across multiple research applications including:

• Western blotting (WB) for protein quantification and molecular weight confirmation

• Immunoprecipitation (IP) for protein-protein interaction studies

• Immunofluorescence (IF) for cellular localization studies

• Enzyme-linked immunosorbent assay (ELISA) for protein quantification

• Immunohistochemistry (IHC) for tissue localization and expression analysis

The specific application suitability depends on the antibody clone and format, with some antibodies optimized for certain techniques over others . For instance, the H-3 mouse monoclonal antibody has been validated for WB, IP, IF, and ELISA applications with human, mouse, and rat samples .

How do I determine the appropriate dilution for DGUOK antibody in my experiments?

Determining optimal antibody dilution requires consideration of several factors:

• Application-specific recommendations: Starting dilutions typically range from 1:500-1:2000 for WB and 1:50-1:500 for IHC

• Signal-to-noise optimization: Begin with the manufacturer's recommended dilution and adjust based on initial results

• Sample type considerations: Different tissue/cell types may require different dilutions due to varying expression levels

• Detection method sensitivity: More sensitive detection systems (e.g., chemiluminescence) may allow for higher dilutions

Always perform a dilution series in preliminary experiments, and note that recombinant DGUOK may require different dilutions than endogenous protein detection .

How can I effectively validate DGUOK knockout or knockdown in experimental models?

A robust validation strategy for DGUOK manipulation should include multiple approaches:

• mRNA level validation:

  • RT-qPCR targeting multiple regions of DGUOK transcript

  • RNA-seq analysis for genome-wide effects

• Protein level validation:

  • Western blot analysis using validated DGUOK antibodies (28-32 kDa band)

  • Consider using multiple antibodies targeting different epitopes

• Functional validation:

  • Measure NAD+ levels using LC-MS (DGUOK depletion decreases NAD+ levels)

  • Assess mitochondrial complex I activity (DGUOK KO reduces complex I proteins)

  • Evaluate mtDNA copy number (DGUOK is essential for mtDNA maintenance)

For genetic manipulation, researchers have successfully used CRISPR-Cas9 with the sgRNA sequence 5'-CCCCGAAGGCTCTCCATCGA-3' for DGUOK knockout, and shRNA approaches for knockdown studies .

What controls should be included when studying DGUOK-NMNAT2-NAD+ axis in cancer metabolism?

When investigating this regulatory axis, include these critical controls:

• Expression controls:

  • Paired normal/tumor tissue samples for baseline expression comparison

  • Cell lines with varying DGUOK expression levels (H1650 and H1299 have high expression)

• Genetic manipulation controls:

  • Empty vector/scrambled sequence controls for knockdown/overexpression studies

  • Rescue experiments (e.g., NMNAT2 overexpression in DGUOK-KO cells)

• Metabolic controls:

  • NAD+ standard curve for LC-MS quantification

  • Mitochondrial mass assessment (MitoTracker Green, NAO staining)

  • Complex I inhibition (e.g., rotenone treatment as positive control)

• Specificity controls:

  • Test effects on multiple NAD+ synthesis enzymes (NAMPT, NAPRT, NRK1/2, NMNAT1-3)

  • Validate antibody specificity using DGUOK-KO cells

This comprehensive control strategy helps distinguish direct DGUOK effects from secondary metabolic consequences .

Why might I observe multiple DGUOK bands in Western blot analysis?

Multiple DGUOK bands in Western blot may reflect several biological and technical factors:

• Multiple isoforms:

  • DGUOK has multiple isoforms with calculated molecular weights ranging from 9 to 32 kDa

  • The predominant isoform is approximately 28-32 kDa

  • Higher molecular weight bands (56-64 kDa) may represent dimers

• Post-translational modifications:

  • Phosphorylation or other modifications can alter migration patterns

  • Mitochondrial targeting sequence cleavage affects apparent molecular weight

• Technical considerations:

  • Sample preparation conditions (reducing vs. non-reducing) affect protein conformation

  • Gel percentage affects resolution of closely migrating isoforms

  • Cross-reactivity with related proteins

To distinguish between these possibilities, consider using:

• Isoform-specific antibodies if available

• Denaturing vs. native conditions

• DGUOK-knockout cells as negative controls

• Phosphatase treatment to eliminate modification-based mobility shifts

How do I resolve inconsistent DGUOK staining patterns in immunohistochemistry?

Inconsistent DGUOK staining can be addressed through systematic optimization:

• Antigen retrieval optimization:

  • Test both citrate buffer (pH 6.0) and TE buffer (pH 9.0) for optimal epitope exposure

  • Adjust retrieval duration and temperature based on tissue type

• Fixation considerations:

  • Overfixation can mask epitopes; standardize fixation protocols

  • Fresh tissue vs. FFPE samples may require different protocols

• Antibody specificity verification:

  • DGUOK staining should appear as punctate or diffuse cytosolic pattern consistent with mitochondrial localization

  • Use DGUOK-KO cells/tissues as negative controls

• Detection system optimization:

  • Try different secondary antibody systems (polymer-based vs. avidin-biotin)

  • Adjust counterstaining to improve contrast for mitochondrial patterns

• Cross-validation:

  • Compare IHC results with other detection methods (IF, WB) from the same samples

  • Use multiple antibodies targeting different DGUOK epitopes

How can DGUOK antibodies be used to study the role of mitochondrial metabolism in cancer progression?

DGUOK antibodies enable several approaches to investigate mitochondrial metabolism in cancer:

• Expression profiling:

  • IHC analysis of DGUOK in tissue microarrays can correlate expression with clinical parameters

  • Studies show DGUOK expression correlates with tumor size, nodal involvement, and TNM staging in lung adenocarcinoma

• Mechanistic studies:

  • Co-immunoprecipitation with DGUOK antibodies can identify protein interaction partners

  • Combined with DGUOK knockdown/knockout, antibodies can track changes in mitochondrial complex proteins (mt-ND1, NDUFB8, NDUFB10, mt-CO2)

• Therapeutic target validation:

  • Monitor DGUOK expression in response to metabolic inhibitors or nucleoside analogs (e.g., DDI)

  • Evaluate downstream effects on NAD+ metabolism and NMNAT2 expression

• Cancer stem cell research:

  • DGUOK antibodies can assess expression in tumor spheres and side population CSCs

  • Combined with stemness markers, they help elucidate DGUOK's role in maintaining cancer stemness

These applications have revealed that DGUOK overexpression promotes lung adenocarcinoma progression through enhanced mitochondrial oxidative phosphorylation and NAD+ biogenesis, suggesting potential therapeutic targets .

What methodological approaches can resolve contradictory findings about DGUOK's role in different tissue contexts?

To address contradictory findings about DGUOK function across tissues, consider these methodological approaches:

• Tissue-specific expression analysis:

  • Quantitative comparison of DGUOK expression across tissues using validated antibodies

  • Correlation with tissue-specific metabolic profiles and mitochondrial content

• Conditional knockout models:

  • Generate tissue-specific DGUOK knockout models to distinguish direct from compensatory effects

  • Compare phenotypes between cancer models and normal tissue models

  • Studies show DGUOK-KO affects lung cancer cells differently than fibroblasts (NIH3T3)

• Multi-omics integration:

  • Combine proteomics, metabolomics, and transcriptomics data from DGUOK-manipulated models

  • Pathway analysis to identify tissue-specific dependencies on DGUOK function

• Context-dependent interaction mapping:

  • Compare DGUOK interactomes across tissue types using co-immunoprecipitation

  • Identify tissue-specific regulatory proteins that modify DGUOK function

• Metabolic flux analysis:

  • Trace isotope-labeled nucleosides to quantify tissue-specific differences in DGUOK-dependent pathways

  • Measure NAD+ synthesis rates in different contexts

These approaches can help reconcile the seemingly contradictory observations that DGUOK knockout severely affects lung cancer cells but has more modest effects in other cell types like fibroblasts .

What are the optimal fixation and permeabilization protocols for detecting mitochondrial DGUOK in immunofluorescence studies?

Optimizing detection of mitochondrial DGUOK requires specific fixation and permeabilization approaches:

• Fixation options:

  • 4% paraformaldehyde (10-15 minutes at room temperature) preserves mitochondrial morphology

  • Methanol fixation (10 minutes at -20°C) may provide better epitope accessibility

  • Avoid extended fixation times which can mask mitochondrial epitopes

• Permeabilization considerations:

  • 0.1-0.2% Triton X-100 (5-10 minutes) for balanced permeabilization

  • 0.1% saponin for gentler permeabilization that better preserves mitochondrial membranes

  • Digitonin (10-50 μg/ml) for selective permeabilization of plasma membrane while preserving mitochondrial membranes

• Blocking optimization:

  • Use 5% normal serum from the same species as the secondary antibody

  • Include 0.1% BSA to reduce non-specific binding

  • Consider adding 0.1% Tween-20 to reduce background

• Co-localization markers:

  • Include mitochondrial markers (MitoTracker, TOM20, or COXIV) for co-localization confirmation

  • Nuclear counterstain (DAPI) to provide cellular context

• Antibody validation:

  • DGUOK appears as punctate or diffuse cytosolic staining consistent with mitochondrial localization

  • Verify specificity using DGUOK-KO cells as negative controls

These optimizations help visualize the authentic mitochondrial distribution of DGUOK while minimizing artifacts.

How can I quantitatively assess DGUOK's impact on mitochondrial function in experimental models?

To quantitatively evaluate DGUOK's effect on mitochondrial function, implement these approaches:

• mtDNA integrity and abundance:

  • qPCR analysis of mtDNA copy number relative to nuclear DNA

  • DGUOK knockdown reduces mtDNA by 50-70% in lung cancer cells

  • Long-range PCR to detect mtDNA deletions

• Respiratory complex activity:

  • Western blot analysis of respiratory complex subunits (mt-ND1, NDUFB8, NDUFB10, mt-CO2)

  • Complex I enzyme activity assays (NADH:ubiquinone oxidoreductase activity)

  • Oxygen consumption rate (OCR) measurements using Seahorse XF analyzer

• NAD+ metabolism assessment:

  • LC-MS quantification of NAD+ levels (prepare standard curve)

  • Expression analysis of NAD+ synthesis enzymes (NMNAT2, NAMPT)

  • NAD+/NADH ratio measurements

• dNTP pool analysis:

  • HPLC quantification of mitochondrial dNTP pools

  • DGUOK KO decreases dNTP levels by 50-70%

• Functional consequences:

  • Mitochondrial membrane potential using JC-1 or TMRE dyes

  • ATP production capacity

  • Mitochondrial morphology by electron microscopy or super-resolution imaging