DOF5.4 Antibody

What is DOF5.4 Antibody and what are its primary characteristics?

DOF5.4 Antibody (Product Code: CSB-PA914783XA01DOA) is a polyclonal antibody raised in rabbits against recombinant Arabidopsis thaliana DOF5.4 protein. This antibody specifically targets the DOF5.4 transcription factor in Arabidopsis thaliana (Mouse-ear cress), a widely used model organism in plant molecular biology. The antibody is purified using antigen affinity methods and supplied in liquid form containing 50% glycerol, 0.01M PBS (pH 7.4), and 0.03% Proclin 300 as a preservative .

Methodologically, when working with this antibody, researchers should note that it has been validated for ELISA and Western Blot applications. Its specificity to Arabidopsis thaliana makes it particularly valuable for plant transcription factor studies.

What are the optimal storage and handling conditions for DOF5.4 Antibody?

DOF5.4 Antibody requires careful storage to maintain its functionality. Upon receipt, the antibody should be stored at either -20°C or -80°C . Repeated freeze-thaw cycles should be strictly avoided as they can compromise antibody integrity through protein denaturation and aggregation.

For handling, consider these methodological approaches:

• Aliquot the antibody into single-use volumes upon receipt

• Use sterile techniques when handling to prevent contamination

• Allow frozen aliquots to thaw completely at 4°C before use

• Gently mix by inverting (avoid vortexing which can damage antibody structure)

• Return unused portions to appropriate storage temperature immediately after use

What experimental validation has been performed on DOF5.4 Antibody?

The DOF5.4 Antibody has been specifically tested and validated for ELISA and Western Blot applications, with particular emphasis on antigen identification .

When designing experiments using this antibody, consider these methodological points:

• Always include appropriate positive and negative controls

• Begin with the manufacturer's recommended dilutions (typically 1:500-1:2000)

• Optimize blocking conditions to minimize background (typically 3-5% BSA or non-fat milk)

• Consider cross-verification with alternative detection methods or a second antibody if available

• Document lot-to-lot variations if using the antibody for long-term studies

How can DOF5.4 Antibody be optimized for plant tissue Western Blot analysis?

When optimizing Western Blot protocols with DOF5.4 Antibody for plant tissue analysis, researchers should consider this methodological approach:

• Sample Preparation:

  • Use extraction buffers containing protease inhibitors to prevent degradation

  • Consider nuclear enrichment techniques as DOF5.4 is a transcription factor

  • Include reducing agents (DTT or β-mercaptoethanol) in sample buffer

• Gel Selection:

  • Use 10-12% polyacrylamide gels for optimal resolution of DOF5.4 protein

  • Consider gradient gels if analyzing multiple proteins of varying sizes

• Transfer Parameters:

  • Optimize transfer time and voltage based on protein size (typically 30V overnight at 4°C)

  • Use PVDF membranes for higher protein binding capacity and signal sensitivity

• Blocking and Antibody Incubation:

  • Test different blocking solutions (5% BSA often works better than milk for transcription factors)

  • Begin with 1:1000 antibody dilution and adjust based on preliminary results

  • Incubate with primary antibody overnight at 4°C for optimal binding

• Detection Optimization:

  • Compare ECL substrates of different sensitivities

  • Consider exposure time series to capture optimal signal-to-noise ratio

This approach is consistent with established antibody optimization protocols used in immunotherapy research and antibody development .

What controls are essential when using DOF5.4 Antibody in experimental designs?

A robust experimental design using DOF5.4 Antibody should incorporate these essential controls:

• Positive Control:

  • Use tissue samples known to express DOF5.4 (e.g., specific developmental stages of Arabidopsis)

  • Consider recombinant DOF5.4 protein if available

• Negative Control:

  • Include DOF5.4 knockdown/knockout samples if available

  • Use tissue types known to express minimal DOF5.4

• Loading Control:

  • Probe for housekeeping proteins (e.g., actin, tubulin) to normalize for total protein

  • Consider total protein staining methods (Ponceau S, Coomassie)

• Antibody Controls:

  • Include a secondary-antibody-only control to assess non-specific binding

  • If available, include pre-immune serum from the same host species

• Peptide Competition:

  • Pre-incubate antibody with excess immunizing peptide to verify specificity

  • Compare signal intensity with and without peptide competition

This control strategy aligns with general principles used in antibody validation for research applications, as seen in antibody development for immunotherapy research .

How can researchers troubleshoot weak or inconsistent signals when using DOF5.4 Antibody?

When encountering signal issues with DOF5.4 Antibody, implement this systematic troubleshooting approach:

• Protein Extraction Efficiency:

  • Verify protein extraction using total protein staining

  • Test alternative extraction methods optimized for nuclear proteins

  • Ensure sample preparation avoids excessive heat which can denature epitopes

• Antibody Performance:

  • Test increased antibody concentration (1:500 instead of 1:1000)

  • Extend primary antibody incubation time (overnight at 4°C)

  • Verify antibody hasn't expired or undergone excessive freeze-thaw cycles

• Signal Development:

  • Use high-sensitivity detection substrates

  • Increase exposure time incrementally

  • Try alternative detection methods (fluorescent vs. chemiluminescent)

• Background Reduction:

  • Increase washing duration and frequency

  • Test alternative blocking agents

  • Dilute antibody in fresh blocking solution with 0.05% Tween-20

• Buffer Optimization:

  • Adjust salt concentration in wash buffers

  • Try different pH conditions within the physiological range

  • Add low concentrations of detergent to reduce non-specific binding

This approach incorporates principles used in antibody optimization similar to those applied in therapeutic antibody development .

What methods can be used to verify DOF5.4 Antibody specificity in plant studies?

Verifying DOF5.4 Antibody specificity requires a multi-faceted methodological approach:

• Genetic Validation:

  • Compare antibody reactivity in wild-type vs. DOF5.4 knockout/knockdown plants

  • Expected result: Reduced or absent signal in knockout/knockdown samples

• Peptide Competition Assay:

  • Pre-incubate antibody with excess immunizing peptide before application

  • Expected result: Significant reduction in signal intensity

• Immunoprecipitation-Mass Spectrometry:

  • Use DOF5.4 Antibody for immunoprecipitation followed by mass spectrometry

  • Expected result: Identification of DOF5.4 protein as the predominant precipitated protein

• Western Blot Molecular Weight Analysis:

  • Compare observed band size with predicted molecular weight of DOF5.4

  • Expected result: Primary band at expected molecular weight

• Orthogonal Method Correlation:

  • Compare protein detection with mRNA expression data

  • Expected result: Concordance between protein and transcript levels

This verification strategy integrates approaches commonly used in antibody validation protocols, similar to those employed in therapeutic antibody development .

How can DOF5.4 Antibody be incorporated into ChIP-seq experiments for plant transcription factor studies?

For using DOF5.4 Antibody in Chromatin Immunoprecipitation sequencing (ChIP-seq), follow this optimized methodological workflow:

• Sample Preparation:

  • Cross-link plant tissue with 1% formaldehyde for 10 minutes

  • Quench with 0.125M glycine

  • Isolate nuclei using a sucrose gradient

  • Sonicate chromatin to 200-500bp fragments

• Immunoprecipitation:

  • Pre-clear chromatin with Protein A/G beads

  • Incubate cleared chromatin with 5-10μg DOF5.4 Antibody overnight at 4°C

  • Add pre-blocked Protein A/G beads and incubate 2-4 hours

  • Perform stringent washing (low salt, high salt, LiCl, TE buffers)

• DNA Recovery:

  • Reverse cross-links (65°C overnight)

  • Digest proteins with Proteinase K

  • Purify DNA using phenol-chloroform extraction or commercial kits

  • Quantify DNA using fluorometric methods

• Library Preparation and Sequencing:

  • Prepare libraries using standard NGS protocols

  • Include input controls (non-immunoprecipitated chromatin)

  • Include IgG controls (non-specific antibody IP)

• Data Analysis:

  • Align reads to reference genome

  • Call peaks using established algorithms (MACS2)

  • Perform motif enrichment analysis

  • Correlate binding sites with gene expression data

This protocol integrates approaches used in transcription factor studies with antibodies, drawing on methodologies similar to those in therapeutic antibody research .

What is the recommended protocol for using DOF5.4 Antibody in plant immunohistochemistry?

For immunohistochemical detection of DOF5.4 in plant tissues, implement this methodological protocol:

• Tissue Preparation:

  • Fix plant tissue in 4% paraformaldehyde

  • Embed in paraffin or prepare for cryosectioning

  • Section to 5-10μm thickness

  • Mount on positively charged slides

• Antigen Retrieval:

  • Deparaffinize and rehydrate sections

  • Perform heat-induced epitope retrieval (citrate buffer pH 6.0)

  • Allow sections to cool slowly to room temperature

• Immunostaining:

  • Block endogenous peroxidase activity with 3% H₂O₂

  • Block non-specific binding with 5% normal serum

  • Incubate with DOF5.4 Antibody (1:100-1:500) overnight at 4°C

  • Wash thoroughly with PBS + 0.1% Tween-20

• Detection:

  • Apply appropriate biotinylated secondary antibody

  • Develop signal using ABC kit and DAB substrate

  • Counterstain with hematoxylin for contrast

  • Mount with permanent mounting medium

• Controls and Validation:

  • Include no-primary-antibody control

  • Include DOF5.4 knockout tissue if available

  • Compare staining pattern with known expression domains

This protocol adapts immunohistochemistry methods to plant tissues, drawing on principles similar to those used in therapeutic antibody development and testing .

How should experiments be designed to study DOF5.4 regulation during plant development and stress response?

To study DOF5.4 regulation effectively, implement this experimental design approach:

Table 1: Experimental Design for DOF5.4 Developmental and Stress Studies

For each condition:

• Extract both RNA and protein from parallel samples

• Quantify DOF5.4 transcript levels via RT-qPCR

• Measure DOF5.4 protein levels via Western blot with DOF5.4 Antibody

• Assess protein localization using subcellular fractionation followed by immunoblotting

• Perform ChIP-seq to identify condition-specific binding sites

• Correlate binding patterns with transcriptomic changes

This comprehensive approach allows for multi-level analysis of transcription factor dynamics, similar to methodologies used in therapeutic antibody research .

What statistical approaches are most appropriate for analyzing DOF5.4 Antibody-generated quantitative data?

When analyzing quantitative data generated using DOF5.4 Antibody, implement these statistical approaches:

• Western Blot Densitometry:

  • Normalize band intensity to loading control

  • Log-transform data if not normally distributed

  • Apply ANOVA with post-hoc tests for multi-condition comparisons

  • Use paired t-tests for before/after comparisons

  • Report with standard error and p-values

• ELISA Quantification:

  • Generate standard curves using 4-parameter logistic regression

  • Calculate concentration from standard curve

  • Apply coefficient of variation (CV) analysis for technical replicates

  • Use linear mixed models for nested experimental designs

• ChIP-seq Analysis:

  • Apply false discovery rate correction for multiple testing

  • Use MACS2 or similar for peak calling with q-value cutoff of 0.05

  • Employ differential binding analysis between conditions

  • Correlate binding with gene expression using Pearson/Spearman correlation

• Experimental Design Optimization:

  • Conduct power analysis to determine sample size

  • Use Design of Experiments (DOE) methodology for multi-factor experiments

  • Apply factorial designs to identify factor interactions

This statistical framework integrates approaches used in quantitative antibody research, drawing on principles similar to those applied in DOE for antibody-drug conjugate development .

How can researchers integrate DOF5.4 Antibody-based protein data with transcriptomic analyses?

For integrating DOF5.4 protein data with transcriptomics, implement this methodological framework:

• Experimental Design Integration:

  • Collect paired samples for protein and RNA extraction

  • Process samples under identical conditions

  • Include appropriate time course to capture temporal dynamics

• Multi-omics Data Generation:

  • Quantify DOF5.4 protein via Western blot or ELISA using DOF5.4 Antibody

  • Measure DOF5.4 transcript levels via RT-qPCR or RNA-seq

  • Perform ChIP-seq with DOF5.4 Antibody to identify binding sites

• Data Processing Workflow:

  • Normalize protein data to appropriate loading controls

  • Process RNA-seq data through standard bioinformatics pipelines

  • Call peaks in ChIP-seq data and annotate to genomic features

• Integration Analysis:

  • Calculate protein-mRNA correlation coefficients

  • Identify time lags between transcript and protein changes

  • Map ChIP-seq binding sites to differential expression data

• Visualization Approaches:

  • Generate heatmaps of coordinated changes

  • Plot time course trajectories of protein and mRNA

  • Create genome browser tracks showing binding sites and expression

This integration approach draws on multi-omics methodologies similar to those used in therapeutic antibody development and functional genomics .

What emerging technologies might enhance DOF5.4 Antibody-based research in plant biology?

Several emerging technologies can significantly enhance DOF5.4 research:

• Proximity Labeling with DOF5.4:

  • Generate transgenic plants expressing DOF5.4-BioID or DOF5.4-TurboID fusions

  • Use DOF5.4 Antibody to validate expression and functionality

  • Identify proteins in proximity to DOF5.4 under different conditions

  • Map condition-specific protein interaction networks

• Single-cell Proteomics Applications:

  • Apply DOF5.4 Antibody in single-cell Western blotting

  • Utilize imaging mass cytometry with metal-conjugated DOF5.4 Antibody

  • Map cell-type-specific expression patterns at unprecedented resolution

  • Correlate with single-cell transcriptomics

• Multiplexed Immunofluorescence:

  • Combine DOF5.4 Antibody with antibodies against other transcription factors

  • Use spectral unmixing to resolve overlapping signals

  • Map combinatorial transcription factor activity across tissues

  • Identify cell types with coordinated transcriptional regulation

• Super-resolution Microscopy:

  • Apply DOF5.4 Antibody in STORM or PALM super-resolution imaging

  • Visualize subnuclear localization patterns at nanometer resolution

  • Investigate co-localization with chromatin marks and other factors

  • Examine dynamic reorganization during development or stress

These emerging applications draw on technological advances similar to those being developed for therapeutic antibody research .

How can computational modeling enhance experimental design and interpretation of DOF5.4 Antibody data?

Computational approaches can significantly enhance DOF5.4 research through these methodological implementations:

• Epitope Prediction and Antibody Binding Simulation:

  • Model DOF5.4 protein structure using AlphaFold or similar tools

  • Predict antibody binding epitopes computationally

  • Simulate effects of mutations or post-translational modifications on antibody recognition

  • Guide experimental design for binding optimization

• Network Analysis of ChIP-seq Data:

  • Apply graph theory to ChIP-seq binding networks

  • Identify regulatory hubs and network motifs

  • Predict master regulators interacting with DOF5.4

  • Model transcriptional cascades initiated by DOF5.4 binding

• Machine Learning for Pattern Recognition:

  • Train models to recognize DOF5.4 binding motifs from ChIP-seq data

  • Develop predictive algorithms for condition-specific binding

  • Apply clustering algorithms to identify co-regulated genes

  • Use dimensionality reduction to visualize complex regulatory relationships

• Kinetic Modeling of Protein-DNA Interactions:

  • Model binding kinetics of DOF5.4 to target sequences

  • Simulate competition between transcription factors

  • Predict effects of mutations on binding affinity

  • Estimate occupancy probabilities at target sites

These computational approaches integrate methods similar to those used in therapeutic antibody development and optimization .