None of the 9 sources reference "DOF2.5 Antibody" or its variants. Key findings include:
VDOF vs. DOF: Search result discusses VDOF1 and VDOF2, plant-specific transcription factors unrelated to antibodies. The prefix "VDOF" may have been misinterpreted as "DOF."
Domain/Epitope References: No antibodies targeting "DOF" domains are mentioned in the sources.
DOF2.5 might refer to a newly developed antibody not yet published in peer-reviewed journals or indexed in databases.
Domain-Specific Antibody: If "DOF2.5" refers to a specific domain or epitope, it may lack documented validation or commercial availability.
Misaligned Suffix: The suffix "2.5" could indicate a variant (e.g., "DOF2.5"), but similar naming conventions (e.g., "22D4" in ) do not align with this format.
Verify Nomenclature:
Cross-check "DOF2.5" against alternative names (e.g., "VDOF2.5," "DOF-2.5").
Confirm if "DOF" refers to a protein domain, gene, or experimental variant.
Expand Search Scope:
Databases: Query PubMed, ClinicalTrials.gov, or commercial antibody catalogs (e.g., Bio-Techne, Sigma-Aldrich) for "DOF2.5."
Specialized Journals: Investigate recent publications in Nature Immunology, mAbs, or Journal of Antibody Engineering.
Consult Domain Experts:
Seek input from immunologists or antibody engineers familiar with DOF-related targets.
Assuming "DOF2.5" refers to a theoretical antibody (e.g., targeting a DOF domain in a protein), its profile might include:
Property | Potential Characteristics |
---|---|
Target | Hypothetical DOF protein domain |
Format | IgG1, scFv, or fusion protein |
Applications | Research (Western blot, immunofluorescence) |
Cross-Reactivity | Species-specific (e.g., human, mouse) |
Note: This table is illustrative and not based on existing data.
"DOF2.5 Antibody" is not identifiable in the provided sources. Its absence suggests either:
A novel or unpublished compound requiring direct consultation with developers.
A miscommunication in nomenclature (e.g., confusion with plant Dof factors or unrelated antibodies).
DOF2.5 antibody is primarily utilized in several key molecular techniques for studying the DOF2.5 transcription factor in plant tissues. Based on available research protocols, the most reliable applications include:
Western Blotting: Effective for detecting DOF2.5 protein (expected molecular weight approximately 37 kDa based on calculated molecular weight) . For optimal results, use 10-20 μg of total protein from plant tissue extracts.
Immunohistochemistry/Immunofluorescence: Valuable for localizing DOF2.5 protein in plant tissue sections, particularly in developmental studies examining tissue-specific expression patterns.
Chromatin Immunoprecipitation (ChIP): Essential for identifying DNA-binding sites of DOF2.5 in genomic contexts, allowing researchers to map transcriptional regulatory networks.
Flow Cytometry: Applicable for quantitative assessment of DOF2.5 expression in plant protoplasts.
For all applications, proper validation using positive and negative controls is critical, as antibody specificity can significantly impact experimental outcomes. Performing preliminary tests with known DOF2.5-expressing tissues alongside knockout/knockdown samples is strongly recommended before proceeding with comprehensive experiments.
Validating antibody specificity is essential, particularly for plant transcription factors which may have conserved domains and homologous family members. A comprehensive validation approach should include:
Western blot analysis with:
Epitope competition assay: Pre-incubate the antibody with excess purified antigen (if available) or synthetic peptide corresponding to the immunogen sequence (Position: L24-E1020 for comparable antibodies) . Elimination of signal confirms specificity.
Cross-reactivity assessment: Test against closely related DOF family proteins to ensure the antibody does not detect other DOF proteins.
Immunoprecipitation followed by mass spectrometry: To confirm that the antibody specifically pulls down DOF2.5 rather than other proteins.
Genetic correlation: Compare protein detection patterns with known transcript expression data from RNA-seq or qPCR.
Document all validation results thoroughly before proceeding with experimental applications, as inadequate validation may lead to misinterpretation of results and experimental inconsistencies.
Achieving consistent results with DOF2.5 antibody in Western blot applications requires careful optimization of multiple parameters:
Harvest fresh plant tissue and immediately flash-freeze in liquid nitrogen
Grind tissue to fine powder while maintaining frozen state
Extract with buffer containing 50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1% Triton X-100, 0.5% sodium deoxycholate, and protease inhibitor cocktail
Centrifuge at 12,000g for 15 minutes at 4°C
Collect supernatant and quantify protein concentration
Protein loading: 10-20 μg total protein
Gel percentage: 10-12% SDS-PAGE
Transfer conditions: 100V for 1 hour or 30V overnight at 4°C
Blocking: 5% non-fat dry milk in TBST for 1 hour at room temperature
Primary antibody dilution: 1:500 to 1:1000 (optimize empirically)
Incubation: Overnight at 4°C with gentle rocking
Secondary antibody: Anti-rabbit HRP conjugate (for rabbit-derived primary antibody)
Detection: Enhanced chemiluminescence substrate
Include a known molecular weight marker
Incorporate proper loading controls appropriate for plant samples (e.g., anti-actin or anti-GAPDH antibodies)
For membrane stripping and reprobing, use gentle stripping buffer to prevent epitope damage
The expected molecular weight for DOF2.5 should be confirmed against calculated molecular weight (~37-40 kDa) but may appear higher due to post-translational modifications common in transcription factors .
Chromatin immunoprecipitation (ChIP) with DOF2.5 antibody requires specialized optimization for plant tissues due to the unique challenges of plant cell walls and chromatin structure:
Tissue preparation and crosslinking:
Use 1-2g of fresh plant material
Crosslink with 1% formaldehyde for 10 minutes under vacuum
Quench with 0.125M glycine for 5 minutes
Wash thoroughly with ice-cold PBS
Chromatin isolation and sonication:
Extract nuclei with buffer containing 0.25M sucrose, 10mM Tris-HCl pH 8.0, 10mM MgCl₂, 1% Triton X-100, 5mM β-mercaptoethanol, protease inhibitors
Resuspend nuclei in sonication buffer (50mM Tris-HCl pH 8.0, 10mM EDTA, 1% SDS, protease inhibitors)
Sonicate to yield chromatin fragments of 200-500bp (verify fragment size by agarose gel electrophoresis)
Immunoprecipitation:
Dilute chromatin 10-fold in ChIP dilution buffer
Pre-clear with protein A/G beads and non-immune serum
Incubate 10μg of DOF2.5 antibody with chromatin overnight at 4°C
Capture complexes with protein A/G beads for 3 hours at 4°C
Perform sequential washes with increasing stringency buffers
DNA recovery and analysis:
Reverse crosslinks at 65°C for 6 hours
Treat with RNase A and Proteinase K
Purify DNA using phenol-chloroform extraction or commercial kits
Analyze by qPCR or sequencing
Antibody concentration: Titrate between 5-15μg per reaction
Chromatin amount: Test 10-25μg per reaction
Incubation time: Compare overnight vs. 48-hour incubation
Bead type: Compare protein A vs. protein G vs. mixed beads performance
Include appropriate controls (input chromatin, IgG control, positive control region) to ensure reliable interpretation of results.
Inconsistent or weak signals with DOF2.5 antibody can stem from multiple sources. Here's a systematic troubleshooting approach:
Problem | Possible Causes | Solutions |
---|---|---|
No signal | 1. Insufficient antibody concentration 2. Antibody degradation 3. Target protein degradation 4. Inefficient protein transfer | 1. Increase antibody concentration 2. Use fresh aliquot, check storage conditions 3. Add protease inhibitors during extraction 4. Verify transfer efficiency with reversible stain |
Weak signal | 1. Low expression level of DOF2.5 2. Suboptimal antibody dilution 3. Insufficient incubation time 4. Poor antibody quality | 1. Increase protein loading 2. Titrate antibody concentration 3. Extend incubation time to overnight at 4°C 4. Try alternative source or lot of antibody |
Multiple bands | 1. Protein degradation 2. Post-translational modifications 3. Non-specific binding 4. Cross-reactivity with other DOF proteins | 1. Use fresh samples with protease inhibitors 2. Use phosphatase inhibitors if phosphorylation is suspected 3. Increase blocking time/concentration 4. Perform peptide competition assay |
High background | 1. Insufficient blocking 2. Too high antibody concentration 3. Insufficient washing 4. Old/contaminated buffers | 1. Optimize blocking conditions (time/agent) 2. Dilute antibody further 3. Extend washing steps 4. Prepare fresh buffers |
For plant-specific challenges:
Secondary metabolite interference: Plant tissues contain phenolics and other compounds that can interfere with antibody binding. Add polyvinylpyrrolidone (PVP, 2%) and β-mercaptoethanol (5mM) to extraction buffers.
Plant-specific background: For immunohistochemistry, incubate sections with 0.3% hydrogen peroxide in methanol to block endogenous peroxidases common in plant tissues.
Protein extraction difficulties: For recalcitrant tissues, try alternative extraction methods such as TCA-acetone precipitation followed by resolubilization in urea buffer.
Low abundance transcription factors: Enrich nuclear proteins before Western blotting to concentrate low-abundance transcription factors like DOF2.5 .
Technical replicate analysis:
Perform at least three technical replicates of each sample
Calculate coefficient of variation (CV) between replicates
CV > 20% suggests technical variability requiring optimization
Internal control normalization:
Use multiple housekeeping proteins/genes as controls
For plant samples, select stable references appropriate for your tissue/conditions
Normalize DOF2.5 signal to these controls to account for loading variation
Serial dilution test:
Prepare 2-fold serial dilutions of a positive control sample
Plot signal intensity vs. concentration
Confirm linear relationship in the working range
Spike-in controls:
Add known quantities of recombinant DOF2.5 protein to negative control samples
Verify detection sensitivity and linearity
Cross-method validation:
Compare protein detection with mRNA levels (qPCR)
Validate with alternative detection method (e.g., mass spectrometry)
Controlled variable experiments:
Systematically vary one experimental condition while keeping others constant
Determine if variability correlates with specific parameters
For advanced researchers, consider using a semiquantitative approach by constructing a standard curve with purified recombinant DOF2.5 protein, allowing more precise quantification across experiments. Document all experimental conditions meticulously to enable accurate comparison between experiments .
Investigating protein-protein interactions involving DOF2.5 requires specialized approaches optimized for plant transcription factors:
Use a gentle lysis buffer (25mM Tris-HCl pH 7.5, 150mM NaCl, 1mM EDTA, 1% NP-40, 5% glycerol) to preserve protein complexes
Cross-link proteins using DSP or formaldehyde before extraction to stabilize transient interactions
Pre-clear lysates thoroughly to reduce non-specific binding
For DOF2.5 antibody immobilization, compare direct coupling to beads vs. antibody-then-beads approach
Include appropriate negative controls (IgG, knockout/knockdown samples)
For plant tissues, extend permeabilization time to ensure antibody accessibility
Increase primary antibody concentration by 25-50% compared to standard protocols
Include appropriate controls to validate signal specificity
Use plant-specific mounting media to reduce autofluorescence
Select appropriate vectors for plant expression
Consider codon optimization for your plant species
Test multiple fusion orientations (N- vs C-terminal tags) as DOF2.5 is a DNA-binding protein
Use appropriate promoters for expression in your tissue of interest
For identifying DOF2.5 interactome, consider BioID or TurboID proximity labeling
Tandem affinity purification with DOF2.5 antibody followed by mass spectrometry
Cross-linking mass spectrometry (XL-MS) to capture transient interactions
When studying interactions with specific proteins, consider performing reciprocal co-IP experiments and validating interactions with at least two independent methods to ensure reliability of reported interactions .
Post-translational modifications (PTMs) regulate transcription factor activity and are crucial for understanding DOF2.5 function. Here are specialized approaches:
Phosphorylation analysis:
Use phosphatase inhibitors during extraction (50mM NaF, 10mM Na₃VO₄, 10mM β-glycerophosphate)
Perform immunoprecipitation with DOF2.5 antibody followed by Western blot with phospho-specific antibodies
For confirmation, treat samples with lambda phosphatase and compare migration patterns
Consider phospho-enrichment techniques before mass spectrometry analysis
Ubiquitination detection:
Add deubiquitinase inhibitors to lysis buffer (10mM N-ethylmaleimide)
Immunoprecipitate with DOF2.5 antibody, then blot with anti-ubiquitin antibodies
For in vivo studies, consider using MG132 proteasome inhibitor treatment
SUMOylation assessment:
Include SUMO protease inhibitors (20mM N-ethylmaleimide) during extraction
Perform immunoprecipitation under denaturing conditions to preserve modifications
Blot with anti-SUMO antibodies
Mass spectrometry-based PTM mapping:
Immunoprecipitate DOF2.5 from plant tissues
Perform in-gel or in-solution digestion with multiple proteases to maximize sequence coverage
Use enrichment strategies specific to the PTM of interest
Analyze using high-resolution MS/MS with ETD or ECD fragmentation
Modification-specific antibody development:
If recurrent PTM sites are identified, consider developing modification-specific antibodies
Validate using synthetic peptides with and without modifications
For accurate PTM site mapping, implement careful sample preparation to minimize artificial modifications during processing. For instance, control temperature and pH to prevent artificial deamidation, which can be misinterpreted as biological modifications .
Interpreting changes in DOF2.5 localization requires careful analysis and consideration of multiple factors:
Quantitative assessment:
Measure nuclear vs. cytoplasmic signal intensity ratios
Score percentage of cells showing specific localization patterns
Use digital image analysis software with appropriate thresholding
Present data as distribution plots rather than simple averages
Temporal dynamics:
For developmental studies, establish precise staging criteria
Document exact time points and developmental markers
Consider time-course experiments with short intervals to capture transient changes
Compare with known developmental regulators as reference points
Environmental response interpretation:
Include appropriate controls (mock treatment, time-matched samples)
Standardize environmental conditions precisely
Monitor multiple time points post-treatment to capture kinetics
Correlate with known stress response markers
Confounding factors to consider:
Tissue fixation artifacts can alter protein localization
Antibody accessibility may vary between tissues/conditions
Plant autofluorescence can interfere with immunofluorescence signals
Cellular morphology changes can impact apparent localization
Validation approaches:
Confirm with fluorescent protein fusions in transgenic plants
Perform subcellular fractionation followed by Western blotting
Compare with in situ hybridization for mRNA localization
Use multiple microscopy techniques (confocal, super-resolution)
When analyzing DOF2.5 localization in response to stimuli, categorize patterns into distinct phenotypes (e.g., exclusively nuclear, nuclear-cytoplasmic, nuclear speckles) and quantify the proportion of cells displaying each pattern across conditions. This approach provides more nuanced insights than simple binary classifications .
Normalize band intensities to loading controls
For comparing two conditions: paired t-test (same samples under different conditions) or unpaired t-test (different samples)
For multiple conditions: one-way ANOVA followed by appropriate post-hoc tests (Tukey's HSD for all pairwise comparisons or Dunnett's test for comparing to control)
For time-course experiments: repeated measures ANOVA
Consider log-transformation for data with unequal variances
Collect data from multiple fields/sections (minimum 5-10 per sample)
Use mixed-effects models to account for within-sample correlation
For intensity measurements: compare means with appropriate parametric or non-parametric tests
For localization patterns: use chi-square tests for categorical classifications
Normalize to input DNA and IgG control
Use percent input method or fold enrichment over IgG
Compare across conditions using t-tests or ANOVA
For ChIP-seq, employ specialized statistical frameworks for peak calling and differential binding analysis
Power analysis to determine appropriate sample size (typically n≥3 biological replicates)
Randomization of sample processing order
Blinding of sample identity during analysis when possible
Inclusion of both biological and technical replicates
For complex experimental designs: linear mixed-effects models
For non-normally distributed data: non-parametric tests or bootstrapping
For correlation analyses: Pearson or Spearman correlation depending on data distribution
For machine learning applications: principal component analysis or clustering for pattern recognition
Always clearly report statistical methods, sample sizes, p-values, and effect sizes. Consider consulting with a statistician for complex experimental designs to ensure appropriate analysis approaches .