dtnbp1a Antibody

What is DTNBP1 and why is it studied using antibodies?

DTNBP1 (Dystrobrevin Binding Protein 1), also known as Dysbindin, is a synaptic protein expressed in diverse neuronal populations throughout the brain. Research interest in DTNBP1 stems from its associations with schizophrenia and Hermansky-Pudlak syndrome type 7 . More recently, DTNBP1 has been identified as a potential biomarker in hepatocellular carcinoma (HCC) and other cancers, where its upregulation correlates with clinicopathologic variables and patient survival status .

Antibodies against DTNBP1 are essential tools for studying its expression patterns, subcellular localization, and functional roles in various tissues. They enable detection through multiple methodologies including Western blotting, immunohistochemistry, immunofluorescence, and ELISA.

What application methods are most effective for DTNBP1 antibody use?

DTNBP1 antibodies can be applied across several experimental techniques with varying effectiveness:

For optimal results, researchers should:

• Validate antibody specificity in their experimental system before proceeding to quantitative studies

• Optimize antibody concentration for each specific application

• Include appropriate positive and negative controls

• Consider tissue-specific fixation and antigen retrieval requirements

What tissue samples are most suitable for DTNBP1 antibody testing?

Based on published research and antibody validation data, the following tissues show reliable DTNBP1 expression for antibody testing:

• Brain tissue: High expression in human and mouse brain, particularly useful for neurological studies

• Testis tissue: Shows consistent expression in both human and mouse samples

• Liver tissue: Important for cancer-related research, especially HCC studies

When using these tissues, researchers should note that DTNBP1 expression patterns may vary based on:

• Developmental stage

• Disease state (particularly in cancer and neurological disorders)

• Specific cell types within the tissue

• Species differences (while conserved, expression patterns may differ between human and rodent samples)

How can researchers verify DTNBP1 antibody specificity?

Antibody specificity is crucial for reliable results. To verify DTNBP1 antibody specificity, implement these strategies:

• Western blot validation: The antibody should detect bands of appropriate molecular weight (primary bands at approximately 36-48 kDa for DTNBP1)

• Preadsorption tests: Mix diluted antibody with excess immunogen (e.g., DTNBP1 peptide) before application; this should abolish specific staining

• Knockout/knockdown controls: Compare staining between wild-type samples and those with DTNBP1 genetically deleted or reduced

• Transfection studies: Express DTNBP1 in cells that normally do not produce it and confirm antibody detection

• Multiple antibody comparison: Use antibodies targeting different epitopes of DTNBP1 to confirm consistent staining patterns

• Peptide mapping: For epitope-specific antibodies, map the precise binding region as demonstrated in the DJ-1 antibody study

As noted in the literature, "if extraneous bands are stained, this indicates that the antibody has other additional targets in the tissue and should raise red flags against using that antibody for IHC, unless you have taken additional precautions."

What factors impact the detection of DTNBP1 using antibodies?

Several factors can influence the reliable detection of DTNBP1:

• Epitope accessibility: DTNBP1 antibodies target specific regions (e.g., C-terminal aa 296-325) ; fixation methods may alter epitope conformation

• Antibody sensitivity: Detection limits vary (e.g., 34pg/ml for some ELISA kits)

• Post-translational modifications: These may mask epitopes or alter antibody binding

• Alternative splicing: DTNBP1 has multiple isoforms that may not all be recognized by a single antibody

• Cross-reactivity: Some antibodies may recognize structurally similar proteins

• Sample preparation: Protein denaturation methods affect epitope exposure differently in various applications

• Secondary antibody selection: Improper secondary antibody choice can lead to non-specific binding or inadequate signal

For example, research indicates even minor amino acid substitutions can dramatically impact antibody recognition, as demonstrated with the E64D mutation in the DJ-1 protein causing complete loss of immunoreactivity with monoclonal antibody 3E8 .

How can DTNBP1 antibodies be used to study protein-protein interactions?

DTNBP1 antibodies can facilitate protein interaction studies through several methodologies:

• Co-immunoprecipitation (Co-IP):

  • Use DTNBP1 antibodies to isolate protein complexes from cell lysates

  • Analyze precipitated proteins by Western blot or mass spectrometry

  • Consider using gentle lysis buffers to preserve native protein interactions

• Proximity Ligation Assay (PLA):

  • Combine DTNBP1 antibody with antibodies against potential interaction partners

  • Visualize protein proximity (<40 nm) through fluorescent signal generation

  • Quantify interaction frequency in different cellular contexts

• Immunofluorescence co-localization:

  • Use DTNBP1 antibodies alongside antibodies for suspected binding partners

  • Analyze spatial overlap through confocal microscopy

  • Calculate co-localization coefficients for quantitative analysis

• Protein fragment complementation assays:

  • Engineer DTNBP1 fusion constructs for validation of direct interactions

  • Use antibodies to confirm expression levels of fusion proteins

When designing these experiments, it's essential to consider that DTNBP1 has been shown to interact with proteins involved in cell cycle regulation, such as CDC25A, CCNE1, CDK2, CDC20, CDC25B, CCNB1, and CDK1, which may influence experimental outcomes .

What methodologies are recommended for epitope mapping of DTNBP1 antibodies?

Precise epitope mapping enhances research reliability and reproducibility. For DTNBP1 antibodies, consider these approaches:

• Deletion construct analysis:

  • Generate GFP-tagged deletion constructs of DTNBP1

  • Express these constructs in cells and test antibody binding

  • Systematically narrow down the region recognized by the antibody

  • This approach successfully localized the epitope of monoclonal antibody 3E8 to DJ-1 protein within residues 56-78

• Peptide array screening:

  • Use microarrays tiled with 20-mer peptides overlapping by 15 amino acids

  • Identify specific regions with significant antibody reactivity

  • This method was effectively used to characterize antibody responses to DENV NS1

• Linear array epitope (LAE) technique:

  • Generate tandem-repeated peptides representing potential epitopes

  • Express as fusion proteins for immunization

  • Particularly useful for producing antibodies against epitopes with low antigenicity

• Site-directed mutagenesis:

  • Introduce point mutations to critical residues within the suspected epitope

  • Test antibody binding to identify essential amino acids for recognition

  • Loss of immunoreactivity with small substitutions can demonstrate remarkable antibody specificity

How can researchers use DTNBP1 antibodies to investigate its role in disease models?

DTNBP1 has been implicated in several pathological conditions. Researchers can employ the following strategies to investigate its roles:

• Cancer research applications:

  • Monitor DTNBP1 expression in different cancer stages using immunohistochemistry

  • Correlate expression levels with clinical parameters and survival outcomes

  • In HCC research, DTNBP1 was found to regulate cell cycle progression by affecting the expression of genes like CDC25A, CCNE1, and CDK2

• Neuropsychiatric disorder studies:

  • Examine DTNBP1 expression patterns in brain regions relevant to schizophrenia

  • Investigate alterations in protein levels or subcellular distribution in disease models

  • Compare DTNBP1 immunoreactivity between patient and control samples

• Cellular pathway analysis:

  • Use antibodies for protein quantification after pathway manipulation

  • Apply in combination with other molecular techniques such as:

    • RNA interference to assess downstream effects of DTNBP1 knockdown

    • Pharmacological interventions targeting DTNBP1-related pathways

    • Gene Set Enrichment Analysis (GSEA) to identify affected biological processes

• Developmental studies:

  • Track DTNBP1 expression during different developmental stages

  • Correlate protein levels with developmental milestones or disease onset

What are the key considerations when designing sandwich ELISA experiments with DTNBP1 antibodies?

Sandwich ELISA is a powerful technique for quantifying DTNBP1 in complex samples. When designing such experiments:

• Antibody pair selection:

  • Use antibodies recognizing non-overlapping epitopes

  • Ensure the capture antibody effectively binds to the plate surface

  • Select a detection antibody compatible with your visualization system

  • The specificity of both antibodies is critical for accurate results

• Protocol optimization:

  • Determine optimal antibody concentrations through titration

  • Establish appropriate sample dilution ranges

  • Validate washing procedures to minimize background

  • Configure incubation times and temperatures for maximum sensitivity

• Standard curve preparation:

  • Use purified DTNBP1 protein at defined concentrations

  • Include sufficient points for accurate curve fitting

  • Employ appropriate curve-fitting methods (four-parameter logistic curve-fit recommended)

• Data analysis considerations:

  • Calculate concentrations using software capable of generating a four-parameter logistic curve-fit

  • For linearized data, plot the log of concentrations versus log of O.D.

  • Account for dilution factors in final concentration calculations

• Quality control measures:

  • Include positive and negative controls

  • Assess intra-assay and inter-assay coefficients of variation

  • Perform spike recovery tests to evaluate matrix effects

  • Published ELISA kits for DTNBP1 report intra-assay CV of 5.7% and inter-assay CV of 7.5%

How should researchers approach the selection of secondary antibodies for DTNBP1 detection?

Secondary antibody selection significantly impacts experimental outcomes. Consider these factors:

• Fragment specificity options:

  • Anti-IgG (H+L): Recognizes both heavy and light chains, providing maximum signal but potential cross-reactivity

  • Anti-IgG (γ-chain specific): More specific but potentially lower signal

  • For IgM primary antibodies, consider anti-μ chain specific secondaries to avoid IgG cross-reactivity

• Host species considerations:

  • Choose secondary antibodies raised against the species of your primary antibody

  • Consider potential cross-reactivity with endogenous immunoglobulins in your sample

  • Pre-adsorbed secondary antibodies can reduce cross-reactivity

• Application-specific requirements:

  • Western blotting: HRP or AP conjugates common

  • Immunofluorescence: Select fluorophores compatible with your microscopy setup

  • Multiple labeling: Choose secondaries with minimal spectral overlap

• Signal optimization:

  • Signal amplification systems (e.g., biotin-streptavidin) for low-abundance proteins

  • Direct conjugates for reduced background in complex tissues

  • Balance signal strength with specificity requirements

The choice between polyclonal and monoclonal secondary antibodies also affects detection characteristics, with polyclonals offering higher sensitivity but potentially more background .

What strategies can address contradictory results when using different DTNBP1 antibodies?

Researchers sometimes encounter contradictory results when using different antibodies against the same target. To resolve such discrepancies:

• Epitope mapping and comparison:

  • Determine exactly which regions of DTNBP1 each antibody recognizes

  • Antibodies targeting different epitopes may give different results if:

    • Some epitopes are masked in certain contexts

    • Post-translational modifications affect specific regions

    • Protein conformations vary between applications

• Isoform specificity analysis:

  • Verify which DTNBP1 isoforms each antibody detects

  • Design experiments to distinguish between isoforms (e.g., PCR to confirm expression)

  • Consider that different tissues may express different isoforms

• Validation with orthogonal methods:

  • Confirm antibody findings with non-antibody techniques

  • Use mRNA detection methods (qPCR, in situ hybridization)

  • Apply genetic approaches (CRISPR-Cas9, RNAi) to verify specificity

• Cross-laboratory validation:

  • Standardize protocols between laboratories

  • Exchange samples and antibodies to identify variables affecting results

  • Document all experimental conditions precisely

• Advanced computational approaches:

  • Apply models like DyAb that leverage sequence pairs to predict protein property differences

  • Use deep learning approaches to better understand antibody-epitope interactions

  • Implement biophysics-informed modeling to design more specific antibodies

As noted in the literature, "results of in situ examinations with [one antibody] have differed from analyses with species-specific antibodies," highlighting the importance of thorough validation with multiple approaches .

How can DTNBP1 antibodies contribute to developing bispecific antibody therapeutics?

While traditional DTNBP1 antibodies are primarily research tools, insights from their development inform bispecific antibody design strategies:

• Epitope identification principles:

  • Techniques used to map DTNBP1 antibody epitopes can be applied to therapeutic target epitopes

  • Understanding the structural characteristics of effective epitopes informs design of therapeutic binding domains

  • Critical regions identified through antibody binding studies may reveal functional domains suitable for therapeutic targeting

• Methodological approaches for bispecific development:

  • Apply sequence-based antibody design principles similar to those used in DTNBP1 antibody research

  • Implement deep learning models like DyAb that can predict binding properties from limited data

  • Utilize genetic algorithms to optimize binding domains while maintaining protein stability

  • Experimental validation remains essential, with binding rates and expression levels as critical metrics

• Translational considerations:

  • Clinical development requires additional parameters beyond those used in research antibodies

  • Questions relevant to therapeutic antibody development parallel research considerations but with emphasis on clinical parameters

  • Safety, efficacy, and manufacturing consistency become paramount

The emerging DyAb technology demonstrates how knowledge gained from research antibodies contributes to therapeutic antibody development, showing success in designing antibodies with improved affinity and high expression rates (>85%) .

What methodological advances are improving DTNBP1 antibody specificity and sensitivity?

Recent technological innovations are enhancing antibody performance:

• Deep learning approaches:

  • Models like DyAb efficiently generate novel antibody sequences with enhanced properties using minimal training data (~100 labeled samples)

  • Combination of sequence embeddings with predictive algorithms improves design outcomes

  • These approaches have achieved consistent high binding rates (>85%) comparable to single point mutants

• Biophysics-informed modeling:

  • Integration of structural knowledge with computational design

  • Identification of different binding modes associated with particular ligands

  • Models successfully disentangling binding modes even for chemically similar ligands

• Combined experimental-computational pipelines:

  • High-throughput sequencing followed by computational analysis

  • Phage display experiments providing training data for model building

  • Validation of computationally designed antibodies through experimental testing

  • This approach has demonstrated success in designing antibodies with customized specificity profiles

• Epitope-focused strategies:

  • Linear array epitope (LAE) technique for producing antibodies against low-antigenicity epitopes

  • Generation of tandem-repeated peptides to enhance immunogenicity

  • Successful application in producing neutralizing antibodies against challenging targets

These advances significantly improve our ability to develop highly specific antibodies and may resolve contradictions in DTNBP1 research arising from antibody limitations.

How is DTNBP1 antibody research contributing to understanding its role in cancer progression?

Recent studies using DTNBP1 antibodies have revealed important functions in cancer:

• Expression pattern analysis:

  • DTNBP1 is upregulated in multiple cancer types, particularly HCC

  • Expression levels correlate with clinicopathologic variables and patient survival

  • Differential expression can be used for risk stratification of HCC patients

• Functional mechanism investigations:

  • DTNBP1 deficiency inhibits cell proliferation and metastasis while promoting apoptosis

  • Antibody-based detection methods reveal DTNBP1 regulates cell cycle progression

  • Affects expression of cell cycle-related genes including CDC25A, CCNE1, CDK2, CDC20, CDC25B, CCNB1, and CDK1

• Biomarker development:

  • DTNBP1 antibodies enable development of diagnostic and prognostic assays

  • Potential for creating sandwich ELISA systems for clinical sample testing

  • Immunohistochemistry protocols using validated antibodies may become part of clinical pathology workflows

• Therapeutic target evaluation:

  • Antibody-based research helps identify whether DTNBP1 is a suitable therapeutic target

  • Understanding protein interactions through co-immunoprecipitation with DTNBP1 antibodies reveals potential pathway interventions

  • Knockdown studies evaluated through antibody detection methods clarify the consequences of DTNBP1 inhibition