DTX14 Antibody

What is DTX1/DTX4 and what cellular functions does it regulate?

DTX1 (Deltex-1) is a cytoplasmic and nuclear ubiquitin ligase of approximately 75 kDa that interacts with the Notch-1 intracellular domain and regulates Notch-induced gene transcription. The protein contains two WWE domains (amino acids 14-94 and 95-171) and one RING-type zinc finger (amino acids 411-472). Within the first 147 amino acids, human Deltex-1 shares 97% sequence identity with mouse and rat Deltex-1, indicating high evolutionary conservation of this region .
DTX1 plays a critical role in the Notch signaling pathway, which is involved in cell fate decisions, differentiation, proliferation, and apoptosis. Through its ubiquitin ligase activity, DTX1 can modulate the stability and activity of various proteins in the Notch pathway, thereby affecting downstream gene expression and cellular responses.

What are the validated applications for DTX1/DTX4 antibodies in research?

Based on current experimental validations, DTX1/DTX4 antibodies have been successfully employed in:

• Western Blot analysis - Detecting DTX1/DTX4 in human cell lysates, specifically in K562 chronic myelogenous leukemia and SW13 adrenal cortex adenocarcinoma cell lines. Under reducing conditions, DTX1/DTX4 appears as a specific band at approximately 67 kDa .

• Immunocytochemistry/Immunofluorescence (ICC/IF) - Visualizing DTX1/DTX4 in fixed cells, with validated protocols for K562 cells showing cytoplasmic localization .

• Flow Cytometry - Detecting DTX1/DTX4 in permeabilized cells, enabling quantitative analysis of protein expression across cell populations .
  While these applications have been validated, researchers should optimize antibody dilutions for their specific experimental conditions and cell types.

How should researchers plan experimental controls when using DTX1/DTX4 antibodies?

Proper controls are essential for antibody-based experiments involving DTX1/DTX4:

• Positive Controls: Use cell lines with documented DTX1/DTX4 expression such as K562 and SW13 cells .

• Negative Controls: Include:

  • Isotype control antibodies (e.g., MAB0041 for mouse monoclonal antibodies)

  • Non-expressing cell lines (if known)

  • siRNA knockdown samples (for specificity validation)

• Loading Controls: For Western blots, include housekeeping proteins (β-actin, GAPDH) to normalize protein loading.

• Secondary Antibody Controls: Run samples with only secondary antibody to assess non-specific binding.

• Cross-reactivity Assessment: If studying multiple Deltex family members, verify antibody specificity using recombinant proteins or knockout models.
  Implementing these controls ensures reliable data interpretation and addresses potential concerns about antibody specificity and experimental artifacts.

What are the optimal conditions for Western blot detection of DTX1/DTX4?

For optimal Western blot detection of DTX1/DTX4:

• Sample Preparation:

  • Use reducing conditions

  • Employ Immunoblot Buffer Group 1 for sample preparation

  • Include protease inhibitors to prevent degradation

• Antibody Concentration:

  • Primary antibody (Anti-DTX1/DTX4): 2 μg/mL has been validated

  • Secondary antibody: HRP-conjugated Anti-Mouse IgG (Follow manufacturer's recommended dilution)

• Membrane Type:

  • PVDF membrane shows good results for DTX1/DTX4 detection

• Detection:

  • Expected molecular weight: approximately 67 kDa

  • Standard ECL detection systems are suitable

• Troubleshooting:

  • If multiple bands appear, optimize primary antibody concentration

  • For weak signals, extend incubation time or increase antibody concentration

  • For high background, increase blocking duration or washing steps
    These conditions have been validated for K562 and SW13 cell lines and may require adjustment for other sample types.

How can immunofluorescence protocols be optimized for studying DTX1/DTX4 localization?

For optimal immunofluorescence detection of DTX1/DTX4:

• Fixation and Permeabilization:

  • For suspension cells like K562: Use immersion fixation

  • Effective permeabilization is crucial as DTX1/DTX4 localizes to cytoplasm

  • Consider paraformaldehyde fixation followed by saponin permeabilization as validated for flow cytometry

• Antibody Conditions:

  • Primary antibody concentration: 10 μg/mL has been validated

  • Incubation time: 3 hours at room temperature

  • Fluorophore selection: NorthernLights™ 557-conjugated secondary antibodies provide good signal-to-noise ratio

• Counterstaining:

  • DAPI for nuclear visualization to contrast with cytoplasmic DTX1/DTX4 staining

• Image Acquisition:

  • Use confocal microscopy for precise localization studies

  • Acquire z-stacks for 3D localization analysis

• Analysis Approaches:

  • Quantify signal intensity across cellular compartments

  • Consider co-localization with Notch pathway components

  • For non-adherent cells, follow specialized protocols for proper adherence during staining procedures
    The validation data shows predominantly cytoplasmic localization, which should be considered when interpreting experimental results.

What strategies improve flow cytometric analysis of DTX1/DTX4 expression?

For effective flow cytometric analysis of DTX1/DTX4:

• Cell Preparation:

  • Fixation with paraformaldehyde is recommended

  • Thorough permeabilization with saponin is crucial for accessing intracellular DTX1/DTX4

• Antibody Selection and Controls:

  • Use Mouse Anti-Human DTX1/DTX4 Monoclonal Antibody (e.g., MAB7157)

  • Include appropriate isotype control (e.g., MAB0041)

  • Secondary antibody: Allophycocyanin-conjugated Anti-Mouse IgG

• Gating Strategy:

  • First gate on viable cells

  • Exclude doublets

  • Analyze DTX1/DTX4 expression relative to isotype control

• Data Analysis Considerations:

  • Present data as histogram overlays of sample vs. isotype control

  • Consider median fluorescence intensity ratios rather than simple percentages

  • For heterogeneous populations, analyze DTX1/DTX4 expression in specific cell subsets

• Multi-parameter Analysis:

  • Combine with cell surface markers to correlate DTX1/DTX4 expression with cellular phenotypes

  • Consider co-staining with Notch pathway components to study functional relationships
    This approach enables quantitative assessment of DTX1/DTX4 expression at the single-cell level across populations.

How does DTX1/DTX4 expression correlate with Notch signaling activity?

The relationship between DTX1/DTX4 expression and Notch signaling reflects a complex regulatory network:

• Mechanistic Relationship:

  • DTX1 directly interacts with the Notch-1 intracellular domain

  • As a ubiquitin ligase, DTX1 can regulate the stability and activity of Notch pathway components

  • DTX1 may function as both a positive and negative regulator of Notch signaling, depending on cellular context

• Experimental Approaches to Study Correlation:

  • Simultaneous detection of DTX1/DTX4 and Notch pathway components

  • Stimulation/inhibition of Notch signaling followed by assessment of DTX1/DTX4 expression

  • Genetic manipulation of DTX1/DTX4 expression followed by analysis of Notch target genes

• Cell-Type Specific Considerations:

  • K562 cells (chronic myelogenous leukemia) express detectable levels of DTX1/DTX4

  • SW13 cells (adrenal cortex adenocarcinoma) also express DTX1/DTX4

  • Correlation analysis should account for baseline Notch activity in these cell types

• Functional Readouts:

  • Measure Notch target gene expression (e.g., HES1, HEY1)

  • Assess cellular phenotypes associated with Notch activation/inhibition

  • Analyze protein-protein interactions between DTX1/DTX4 and Notch pathway components
    Understanding this relationship may provide insights into how DTX1/DTX4 contributes to normal development and disease pathogenesis.

What are the challenges in distinguishing between DTX1 and DTX4 in experimental systems?

Distinguishing between DTX1 and DTX4 presents several technical challenges:

• Antibody Cross-Reactivity:

  • Many antibodies recognize both DTX1 and DTX4 due to sequence homology

  • The antibody MAB7157 targets the region Met1-Phe147, which may contain conserved epitopes between DTX1 and DTX4

• Resolution Strategies:

  • Use knockout/knockdown validation to confirm specificity

  • Employ isoform-specific primers for RT-qPCR analysis

  • Consider mass spectrometry for definitive protein identification

  • Use multiple antibodies targeting different epitopes to increase confidence

• Experimental Design Considerations:

  • Incorporate positive controls with known expression of only DTX1 or only DTX4

  • Consider the molecular weight differences (if any) in Western blot analysis

  • Validate findings with orthogonal techniques that don't rely on antibody specificity

• Bioinformatic Approaches:

  • Analyze RNA-seq data to determine isoform-specific expression

  • Use prediction algorithms to identify unique post-translational modifications

  • Develop computational models to distinguish binding specificities
    Researchers must clearly acknowledge these limitations in their experimental design and interpretation of results.

What novel approaches are emerging for studying DTX1/DTX4 protein-protein interactions?

Several advanced methodologies are enabling more detailed analysis of DTX1/DTX4 interactions:

• Proximity Labeling Techniques:

  • BioID or TurboID fusion proteins to identify proteins in close proximity to DTX1/DTX4

  • APEX2-based labeling for temporal control of interaction mapping

  • These approaches can reveal both stable and transient interactions in the native cellular environment

• Advanced Microscopy:

  • Super-resolution microscopy for nanoscale localization

  • Fluorescence resonance energy transfer (FRET) to study direct protein interactions

  • Live-cell imaging to track dynamic interaction patterns

• Proteomics Approaches:

  • Quantitative interaction proteomics using SILAC or TMT labeling

  • Crosslinking mass spectrometry (XL-MS) to map interaction interfaces

  • Hydrogen-deuterium exchange mass spectrometry (HDX-MS) to study conformational changes

• Computational Modeling:

  • Molecular dynamics simulations of DTX1/DTX4 interactions

  • Integration of large-scale antibody sequence data to predict binding specificity

  • Machine learning approaches to identify interaction patterns

• CRISPR-Based Technologies:

  • CRISPR activation/inhibition to modulate DTX1/DTX4 expression

  • CRISPR tagging for visualization of endogenous interactions

  • Domain-focused mutagenesis to map functional interaction regions
    These approaches go beyond traditional co-immunoprecipitation techniques, providing more comprehensive and nuanced understanding of the DTX1/DTX4 interactome.

How should researchers validate DTX1/DTX4 antibody specificity for their experimental system?

Comprehensive antibody validation is critical for reliable DTX1/DTX4 research:

• Genetic Validation Approaches:

  • CRISPR/Cas9 knockout of DTX1/DTX4 to create negative control samples

  • siRNA/shRNA knockdown with multiple targeting sequences

  • Overexpression systems with tagged DTX1/DTX4 constructs

• Peptide Competition Assays:

  • Pre-incubate antibody with purified antigen (Met1-Phe147 region)

  • Observe signal reduction in pre-blocked samples

  • Include irrelevant peptides as controls

• Multiple Antibody Validation:

  • Compare results using antibodies targeting different epitopes

  • Confirm consistent localization and expression patterns

• Orthogonal Methods:

  • Validate protein expression with mRNA analysis

  • Use mass spectrometry to confirm protein identity

  • Verify functional activities associated with DTX1/DTX4

• Cross-Species Testing:

  • If studying non-human systems, verify cross-reactivity given the high conservation (97% identity in the Met1-Phe147 region between human and mouse/rat DTX1)
    Implementing multiple validation approaches increases confidence in antibody specificity and experimental results.

What considerations are important when interpreting variability in DTX1/DTX4 expression across different cell types?

When analyzing DTX1/DTX4 expression patterns across cell types:

• Technical vs. Biological Variability:

  • Standardize protocols across cell types (fixation, permeabilization, antibody concentration)

  • Include technical replicates to assess method consistency

  • Biological replicates should incorporate multiple passages or donors

• Cell-Type Specific Factors:

  • Account for baseline differences in protein expression machinery

  • Consider cell cycle status, as this may affect DTX1/DTX4 levels

  • Evaluate Notch pathway activity differences between cell types

• Quantification Approaches:

  • Use multiple methods (Western blot, flow cytometry, IF) for cross-validation

  • Establish appropriate normalization strategies

  • Apply statistical tests appropriate for the data distribution

• Contextual Interpretation:

  • Consider the physiological role of the cell type in relation to known DTX1/DTX4 functions

  • Compare with literature-reported expression patterns

  • Evaluate co-expression of DTX1/DTX4 interaction partners

• Functional Correlates:

  • Determine if expression differences correlate with functional outcomes

  • Consider post-translational modifications that may affect antibody detection

  • Assess subcellular localization differences between cell types
    These considerations help distinguish meaningful biological differences from technical artifacts.

How can researchers address inconsistent results when studying DTX1/DTX4 in primary vs. immortalized cell lines?

Discrepancies between primary cells and cell lines require systematic investigation:

• Source-Dependent Considerations:

  • Document passage number for cell lines (DTX1/DTX4 expression may change over passages)

  • For primary cells, record donor characteristics and isolation methods

  • Consider differences in genetic background and epigenetic state

• Protocol Adaptations:

  • Optimize fixation conditions separately for primary cells and cell lines

  • Adjust antibody concentrations based on target expression levels

  • Extend incubation times for primary cells if needed

• Microenvironment Factors:

  • Evaluate culture conditions that might affect DTX1/DTX4 expression

  • Consider cell density effects on Notch signaling and DTX1/DTX4 regulation

  • Assess impact of serum factors or growth supplements

• Analytical Approaches:

  • Use multiple detection methods to confirm observations

  • Implement quantitative image analysis for precise comparisons

  • Apply normalization strategies that account for cell-type differences

• Reconciliation Strategies:

  • Perform functional studies to determine biological relevance of expression differences

  • Use genetic manipulation to equalize expression and assess downstream effects

  • Consider intermediate models (early passage primary cells, conditionally immortalized lines)
    Understanding these differences may provide insights into how cellular context affects DTX1/DTX4 function in normal and disease states.

How might single-cell technologies advance our understanding of DTX1/DTX4 function?

Single-cell approaches offer unprecedented insights into DTX1/DTX4 biology:

• Single-Cell RNA Sequencing:

  • Reveals cell-type specific expression patterns of DTX1/DTX4

  • Enables correlation with Notch pathway components at single-cell resolution

  • Identifies rare cell populations with unique DTX1/DTX4 expression profiles

• Single-Cell Proteomics:

  • Quantifies DTX1/DTX4 protein levels in individual cells

  • Measures co-expression with interaction partners

  • Detects post-translational modifications affecting DTX1/DTX4 function

• Spatial Transcriptomics/Proteomics:

  • Maps DTX1/DTX4 expression in tissue context

  • Reveals spatial relationships with Notch signaling components

  • Identifies microenvironmental factors influencing expression

• Multimodal Single-Cell Analysis:

  • Integrates transcriptomic, proteomic, and epigenomic data

  • Provides comprehensive view of DTX1/DTX4 regulation

  • Enables construction of cell state-specific regulatory networks

• Computational Integration:

  • Applies machine learning to predict DTX1/DTX4 functions in different cellular contexts

  • Leverages large antibody datasets to improve binding specificity models

  • Develops trajectory analyses to understand dynamic regulation of DTX1/DTX4
    These technologies will help elucidate how cellular heterogeneity affects DTX1/DTX4 function in development and disease.

What potential exists for developing highly specific antibodies to distinguish DTX family members?

Advanced antibody engineering approaches offer promising solutions:

• Epitope-Focused Design:

  • Target unique regions that distinguish DTX family members

  • Apply structural biology insights to identify accessible, distinctive epitopes

  • Utilize computational prediction of antibody-epitope interactions

• High-Throughput Selection Strategies:

  • Phage display with negative selection against related DTX proteins

  • Deep sequencing of antibody libraries to identify rare specific binders

  • Affinity maturation focused on specificity rather than just binding strength

• Biophysics-Informed Modeling:

  • Leverage large-scale antibody sequence data (billions of sequences)

  • Identify different binding modes associated with specific ligands

  • Design antibodies with customized specificity profiles

• Cross-Platform Validation:

  • Combine multiple detection technologies to confirm specificity

  • Develop orthogonal reagents targeting distinct epitopes

  • Validate in multiple experimental systems

• Emerging Technologies:

  • Nanobodies/single-domain antibodies for improved epitope access

  • Synthetic binding proteins designed for exclusive recognition

  • CRISPR-generated cellular systems for validation
    These approaches may yield reagents that reliably distinguish between highly homologous DTX family members, enabling more precise functional studies.

How can researchers best integrate DTX1/DTX4 studies with broader investigations of the Notch signaling pathway?

Comprehensive integration strategies include:

• Systems Biology Approaches:

  • Network analysis incorporating DTX1/DTX4 with other Notch pathway components

  • Mathematical modeling of pathway dynamics including ubiquitination events

  • Multi-omics integration to capture regulatory relationships

• Temporal and Contextual Studies:

  • Time-course experiments following Notch activation

  • Comparison across developmental stages or disease progression

  • Cell-type specific analysis of DTX1/DTX4 function within the pathway

• Perturbation Strategies:

  • Combinatorial genetic manipulations of DTX1/DTX4 and other pathway components

  • Small molecule inhibitors with different points of intervention

  • Domain-specific mutations to dissect functional relationships

• Translational Connections:

  • Correlation of DTX1/DTX4 expression with clinical outcomes

  • Development of pathway-specific biomarkers including DTX1/DTX4

  • Therapeutic targeting strategies considering pathway cross-talk

• Technological Integration:

  • Live-cell reporters for simultaneous monitoring of multiple pathway components

  • Organoid or tissue-specific models that preserve pathway architecture

  • Patient-derived systems to study pathway dysregulation in disease contexts This integrative approach will advance understanding of how DTX1/DTX4 functions within the complex Notch signaling network across different biological contexts.