INTS13 Antibody, Biotin conjugated

What is INTS13 and why is it significant for research?

INTS13, also known as Integrator Complex Subunit 13 or ASUN, is a crucial regulator of the mitotic cell cycle and development . At prophase, it is required for dynein anchoring to the nuclear envelope, which is important for proper centrosome-nucleus coupling . This protein plays essential roles in maintaining genomic stability and promoting proper gene transcription . INTS13 is particularly significant for research because it functions in both DNA damage repair and RNA processing mechanisms, making it relevant to studies in molecular biology, developmental biology, and cancer research .

What are the key biological functions of INTS13?

INTS13 has multiple biological functions that make it an important research target. It acts upstream of or within centrosome localization, mitotic spindle organization, and protein localization to the nuclear envelope . At the G2/M phase, it may be required for proper spindle formation . Beyond its role in cell cycle regulation, INTS13 functions in enhancer activation and has been implicated in monocytic differentiation . Upon differentiation, INTS13 is recruited to chromatin regions that are associated with genes involved in immune cell development, trafficking, and hematopoiesis .

What is a biotin-conjugated antibody and why is it useful for INTS13 research?

A biotin-conjugated antibody has biotin molecules chemically attached to the antibody structure. This conjugation is particularly useful for research applications because biotin binds with exceptional affinity to streptavidin and avidin, allowing for enhanced detection sensitivity and flexibility in experimental design. For INTS13 research, biotin-conjugated antibodies enable detection through avidin/streptavidin systems coupled with enzymes or fluorophores, facilitating techniques like sandwich ELISA, immunohistochemistry, and immunofluorescence. This conjugation system allows for signal amplification and multi-step detection protocols, which can be especially valuable when studying proteins like INTS13 that may be present at relatively low concentrations in biological samples .

How should I optimize antibody dilutions for different applications with INTS13 antibodies?

Optimization of INTS13 antibody dilutions is crucial for experimental success and varies by application:

When optimizing, perform titration experiments with positive control samples known to express INTS13. Compare signal intensity and background levels across different dilutions to determine the optimal concentration for your specific experimental system and detection method .

What are the recommended protocols for using biotin-conjugated INTS13 antibodies in ELISA assays?

For sandwich ELISA detection of INTS13, the following protocol is recommended:

• Coating: Coat ELISA plates with capture antibody (e.g., purified anti-INTS13) at 1-2 μg/mL in coating buffer overnight at 4°C.

• Blocking: Block with 1-3% BSA in PBS for 1-2 hours at room temperature.

• Sample addition: Add samples and standards (doubling dilutions over the range of 1000 pg/mL - 8 pg/mL).

• Detection antibody: Apply biotin-conjugated INTS13 antibody at 0.25-1 μg/mL.

• Enzyme conjugate: Add streptavidin-HRP conjugate (typically 1:1000-1:5000 dilution).

• Development: Develop with appropriate substrate (TMB) and measure optical density.

Each step should include 3-5 washing cycles with PBS containing 0.05% Tween-20. For optimal results, proper validation with recombinant INTS13 standards is essential to establish a reliable standard curve .

How can I validate the specificity of INTS13 antibodies in my experimental system?

Validating antibody specificity is critical for reliable results. For INTS13 antibodies, implement these approaches:

• Positive and negative controls: Use cell lines with known INTS13 expression (e.g., U266, 293F, HeLa as positive controls) and compare with tissues or cells where INTS13 is absent or depleted.

• Knockdown validation: Perform shRNA knockdown of INTS13 (achieving 40-70% reduction in expression) and demonstrate corresponding reduction in antibody signal .

• Western blot analysis: Confirm detection of appropriately sized band (~80 kDa for INTS13) and absence of non-specific bands.

• Immunoprecipitation followed by mass spectrometry: Verify that the antibody pulls down INTS13 and expected interaction partners.

• Competitive blocking: Pre-incubate the antibody with recombinant INTS13 protein (573-706AA region) and demonstrate elimination of specific staining .

• Cross-reactivity assessment: Test reactivity across multiple species if working with non-human models, as some INTS13 antibodies show reactivity with human, mouse, and rat samples .

How can INTS13 antibodies be used to investigate enhancer activation in differentiation models?

INTS13 has been identified as an enhancer-associated factor that plays roles in differentiation processes. To investigate INTS13's role in enhancer activation:

• ChIP-seq approach: Perform chromatin immunoprecipitation using INTS13 antibodies before and after differentiation stimuli (e.g., PMA treatment in HL-60 cells for 16 hours). This will identify INTS13-gained regions upon differentiation .

• Enhancer characterization: Correlate INTS13 binding sites with enhancer marks by performing ChIP-seq for H3K27ac, H3K4me1, and total RNAPII in both untreated and differentiated cells .

• Functional validation: For identified INTS13-bound enhancers, use reporter assays to determine if these regions drive expression of nearby genes. Construct reporters containing INTS13-bound sequences and measure activity with and without INTS13 depletion .

• Proximity ligation assays: Investigate protein-protein interactions between INTS13 and transcription factors like EGR1/2 at enhancers using techniques such as PLA or co-IP followed by Western blotting .

• Gene expression analysis: Correlate INTS13 binding at enhancers with expression changes of associated genes during differentiation using RNA-seq or qRT-PCR of candidate genes .

This multi-pronged approach can provide mechanistic insights into how INTS13 contributes to enhancer activation during cellular differentiation processes.

What methodological approaches can be used to study INTS13's role in cell cycle regulation?

To investigate INTS13's function in cell cycle regulation, several complementary approaches can be employed:

• Cell synchronization and time-course analysis: Synchronize cells at different cell cycle phases and analyze INTS13 localization, modifications, and interaction partners throughout the cell cycle using INTS13 antibodies for immunofluorescence and biochemical analyses.

• Live-cell imaging: Combine INTS13 antibodies with fluorescently-tagged cell cycle markers to visualize dynamics during mitosis, particularly focusing on centrosome localization and nuclear envelope interactions .

• Interaction network mapping: Use INTS13 antibodies for co-immunoprecipitation followed by mass spectrometry to identify cell cycle-specific interaction partners. Compare interactions between interphase and mitotic cells .

• Functional rescue experiments: In INTS13-depleted cells showing cell cycle defects, perform domain-specific rescue experiments to map functional regions required for proper mitotic progression .

• Phosphorylation state analysis: Combine INTS13 immunoprecipitation with phospho-specific antibodies or mass spectrometry to identify cell cycle-dependent post-translational modifications that might regulate its function.

How can I design experiments to investigate INTS13's dual roles in the Integrator complex and at enhancers?

INTS13 exhibits an interesting dual functionality as both a component of the Integrator complex (involved in RNA processing) and as an enhancer-associated factor. To dissect these distinct roles:

• Comparative ChIP-seq profiling: Perform ChIP-seq for INTS13 alongside other Integrator subunits (e.g., INTS11) to identify genomic regions where INTS13 binds with or without other complex members. Analyze U snRNA genes (high Integrator binding) and compare with enhancer regions to distinguish binding patterns .

• Quantitative ChIP validation: Use qPCR to validate differential binding of INTS13 and other Integrator components at specific loci, confirming cases where INTS13 binds independently of the core complex .

• Domain mapping: Create domain-specific mutants of INTS13 and test which regions are required for association with the Integrator complex versus enhancer binding. Express these mutants in INTS13-depleted cells and assess their ability to rescue different functions.

• Proteomic analysis: Perform proteomic analysis to identify proteins that interact with INTS13 at enhancers (e.g., transcription factors EGR1/2) versus those that interact with INTS13 as part of the Integrator complex .

• Functional readouts: Measure distinct endpoints reflecting Integrator function (e.g., snRNA processing) versus enhancer function (e.g., target gene activation) in cells with wild-type versus mutant INTS13 to distinguish biological consequences of each role.

This experimental design would help delineate how INTS13 can function both within the canonical Integrator complex and independently at enhancers.

What are the common technical challenges when using biotin-conjugated antibodies and how can they be addressed?

Several technical challenges can arise when working with biotin-conjugated antibodies for INTS13 detection:

Additionally, when using biotin-conjugated antibodies in tissues or cells with high endogenous biotin (e.g., liver, kidney), consider using alternative detection systems or blocking with free avidin before applying the biotinylated antibody .

How should storage and handling conditions be optimized for INTS13 antibodies to maintain activity?

Proper storage and handling of INTS13 antibodies is critical for maintaining their activity and specificity:

• Storage temperature: Store concentrated antibody stocks at -20°C or -80°C for long-term preservation. Some formulations contain 50% glycerol to prevent freeze-thaw damage .

• Avoid freeze-thaw cycles: Aliquot antibodies into single-use volumes before freezing to minimize freeze-thaw cycles, which can cause denaturation and loss of activity .

• Working solutions: For working dilutions, store at 4°C for up to 1-2 weeks, protected from light if fluorescently labeled.

• Buffer composition: Optimal buffer typically includes 0.01M TBS (pH 7.4) with stabilizers like 1% BSA, preservatives such as 0.02-0.03% ProClin300, and 50% glycerol .

• Preservative considerations: Note that preservatives like ProClin are HAZARDOUS SUBSTANCES and should be handled by trained personnel with appropriate precautions .

• Centrifugation before use: Brief centrifugation of the antibody vial before opening can recover material from the cap and walls.

• Contamination prevention: Use sterile technique when handling antibodies to prevent microbial contamination.

• Transportation: Transport on ice or ice packs for short periods; use dry ice for longer shipping times.

Following these guidelines will help maintain antibody activity and extend shelf-life, ensuring consistent experimental results over time.

What approaches can resolve data inconsistencies when comparing INTS13 localization across different detection methods?

When encountering inconsistent results regarding INTS13 localization using different detection methods, consider these analytical and experimental approaches:

• Epitope accessibility analysis: Determine if the epitope recognized by the antibody (e.g., AA 573-706 region ) might be masked in certain cellular compartments or under specific conditions. Test multiple antibodies targeting different regions of INTS13.

• Fixation comparison: Compare different fixation methods (paraformaldehyde, methanol, acetone) as they differentially preserve epitopes and cellular structures. INTS13 has been reported in both cytoplasmic and nuclear compartments , and fixation can affect detection of each pool.

• Subcellular fractionation validation: Perform biochemical fractionation to isolate nuclear, cytoplasmic, and chromatin-bound fractions, followed by Western blotting with INTS13 antibodies to confirm distribution patterns seen in imaging studies.

• Cell cycle dependence: Since INTS13 functions in cell cycle regulation , analyze its localization in synchronized cell populations to determine if discrepancies reflect cell cycle-dependent relocalization rather than methodological issues.

• Cross-validation with tagged constructs: Compare antibody-based detection with localization of epitope-tagged INTS13 (GFP-INTS13 or FLAG-INTS13) expressed at physiological levels.

• Super-resolution microscopy: Apply techniques like STORM or STED to resolve fine subcellular localization that might be obscured in conventional microscopy.

• Controls for specificity: Include INTS13-depleted cells as negative controls in all experiments to confirm signal specificity across methods.

By systematically applying these approaches, researchers can resolve inconsistencies and develop a more accurate understanding of INTS13's dynamic localization patterns.

How might INTS13 antibodies be utilized in studying its role in immune cell development and hematopoiesis?

INTS13 has been implicated in immune cell development and hematopoiesis, with INTS13-gained regions associated with genes involved in these processes . Future research applications could include:

• Hematopoietic differentiation models: Using INTS13 antibodies to track expression and localization during differentiation of primary CD34+ hematopoietic stem cells into various lineages, correlating INTS13 binding patterns with lineage-specific enhancer activation .

• Flow cytometry applications: Developing protocols for intracellular staining of INTS13 in combination with surface markers to identify specific immune cell populations where INTS13 is dynamically regulated.

• Single-cell analysis: Combining INTS13 antibody-based detection with single-cell technologies to map heterogeneity in INTS13 expression and function across hematopoietic cell populations.

• In vivo models: Applying INTS13 antibodies for immunohistochemistry in bone marrow and lymphoid tissues from models of normal and dysregulated hematopoiesis to understand its role in disease contexts.

• Therapeutic target assessment: Investigating whether modulation of INTS13 function could influence hematopoietic cell differentiation in contexts where this process is dysregulated, such as leukemia or immune deficiencies.

These approaches could provide valuable insights into INTS13's lineage-specific roles in hematopoiesis and potentially identify new therapeutic targets for hematological disorders.

What methodological advances could improve detection sensitivity and specificity for studying low-abundance INTS13 in primary tissues?

To address challenges in detecting low-abundance INTS13 in primary tissues, several methodological advances could be implemented:

• Signal amplification technologies: Implement proximity ligation assays (PLA) or tyramide signal amplification (TSA) with biotin-conjugated INTS13 antibodies to enhance detection sensitivity by orders of magnitude compared to conventional methods.

• Multiplex imaging technologies: Develop protocols for multiplexed immunofluorescence or mass cytometry (CyTOF) to simultaneously detect INTS13 alongside lineage markers and interaction partners, providing contextual information in heterogeneous tissues.

• Advanced tissue processing: Optimize antigen retrieval protocols specifically for INTS13 epitopes, potentially using heat-induced or enzymatic methods tailored to preserve the target epitope while maximizing accessibility.

• Nanobody development: Engineer smaller antibody formats like nanobodies against INTS13 that may provide better tissue penetration and epitope access, especially in fixed tissues.

• Combination with RNA detection: Develop protocols that combine INTS13 protein detection with RNA visualization techniques (e.g., RNAscope) to correlate protein localization with transcriptional activity at target genes.

• Microfluidic-based detection: Adapt microfluidic immunoassay platforms for enhanced sensitivity when analyzing INTS13 in limited primary samples.

These methodological advances could significantly improve our ability to detect and study INTS13 in primary tissues, particularly in contexts where it may be expressed at low levels but playing functionally significant roles.

How can computational and bioinformatic approaches enhance the interpretation of INTS13 ChIP-seq and interaction studies?

Advanced computational and bioinformatic strategies can extract deeper insights from INTS13 experimental data:

• Integrative motif analysis: Apply de novo motif discovery to INTS13 ChIP-seq data to identify direct binding sequences or co-occurring transcription factor motifs, particularly at enhancer regions where INTS13 may interact with factors like EGR1/2 .

• Comparative genomics approaches: Analyze evolutionary conservation of INTS13 binding sites across species to identify functionally constrained regions that may represent core regulatory elements.

• Network analysis of protein interactions: Build protein-protein interaction networks centered on INTS13, integrating proteomics data with known interaction databases to predict functional modules and pathways.

• Multi-omics data integration: Develop computational pipelines to integrate INTS13 ChIP-seq data with transcriptomics, epigenomics, and chromatin conformation data to comprehensively map its regulatory impact.

• Machine learning applications: Train machine learning models to predict INTS13 binding sites based on sequence and chromatin features, potentially identifying new regulatory regions for experimental validation.

• Genome topology analysis: Correlate INTS13 binding with chromosome conformation data (Hi-C, Micro-C) to understand how INTS13-bound enhancers interact with target promoters in three-dimensional space.

• Cell-type specific regulatory network reconstruction: Build cell-type specific gene regulatory networks incorporating INTS13 binding data to understand context-dependent functions in different cell lineages.

These computational approaches can transform raw experimental data into mechanistic hypotheses about INTS13 function that can guide future experimental designs.