Os07g0679700 Antibody

What is Os07g0679700 and what function does it serve in plants?

Os07g0679700 is a transcriptional factor B3 family protein (Os07t0679700-01) found in Oryza sativa (rice) . The B3 domain is a highly conserved DNA-binding domain found in several plant transcription factors involved in regulating critical processes including seed development, hormone responses, and various developmental pathways. As a transcription factor, Os07g0679700 likely regulates the expression of specific genes by binding to DNA regulatory sequences.

The protein has an expected molecular weight of approximately 104 kDa and has homologous sequences in several other grass species . Interestingly, search results indicate this protein is evolutionarily conserved, with similar B3 domain-containing proteins found in Setaria italica (foxtail millet) and even the more distantly related moss Physcomitrella patens .

What applications can the Anti-Os07g0679700 antibody be used for?

According to product information, the Anti-Os07g0679700 antibody (PHY4188S) is primarily validated for Western blot applications at dilutions of 1:1000-1:2000 . While Western blotting is the validated application, polyclonal antibodies like this one might potentially be useful for other immunological techniques such as:

• Immunoprecipitation (IP)

• Chromatin immunoprecipitation (ChIP)

• Immunohistochemistry (IHC)

• Immunofluorescence (IF)

Each of these applications would require optimization and validation by the end user, as antibody performance can vary significantly between applications. The antibody's specificity for detecting the native protein in complex biological samples makes it valuable for studying Os07g0679700 expression patterns, protein levels in different tissues or under various conditions, and potential post-translational modifications.

How should I properly store and reconstitute the Anti-Os07g0679700 antibody?

Proper handling of the Anti-Os07g0679700 antibody is crucial for maintaining its activity and specificity. According to the product information, the antibody is supplied in lyophilized form and should be handled as follows :

Reconstitution:

• Reconstitute with 50μl of sterile water

• Before opening, briefly spin the tube to ensure lyophilized material isn't adhering to the cap or sides

Storage conditions:

• Prior to reconstitution: Store at -20 to -70°C for up to 12 months from date of receipt

• After reconstitution:

  • For long-term storage: -20 to -70°C for up to 6 months under sterile conditions

  • For short-term storage: 2 to 8°C for up to 1 month under sterile conditions

Important considerations:

• Use a manual defrost freezer to store the antibody

• Avoid repeated freeze-thaw cycles as this can denature antibodies and reduce their effectiveness

• Upon receipt, the product is shipped at 4°C but should be immediately stored at the recommended temperature

These storage and handling procedures help maintain antibody integrity and ensure consistent experimental results.

What is the expected molecular weight of Os07g0679700 in Western blot experiments?

According to the product information, the expected/apparent molecular weight of Os07g0679700 is approximately 104 kDa on Western blots . This molecular weight is consistent with what would be expected for a transcriptional factor B3 family protein.

• Post-translational modifications (phosphorylation, glycosylation, etc.) can alter migration patterns

• Alternative splicing may result in multiple isoforms with different molecular weights

• SDS-PAGE running conditions (buffer composition, gel percentage) can affect protein migration

• Sample preparation methods (reducing vs. non-reducing conditions) may influence protein conformation

When analyzing Western blot results, any significant deviation from the expected molecular weight should prompt additional validation to confirm the specificity of the detected band. If multiple bands are observed, further investigation using positive and negative controls (such as overexpression or knockout samples) would be recommended to determine which band represents the true target protein.

Does the Anti-Os07g0679700 antibody cross-react with homologous proteins from other plant species?

The product information indicates that the synthetic peptide used for immunization has 80-99% sequence homology with corresponding sequences in several grass species :

• Setaria viridis (green foxtail)

• Panicum virgatum (switchgrass)

• Zea mays (maize)

• Hordeum vulgare (barley)

• Triticum aestivum (wheat)

• Sorghum bicolor (sorghum)

This high degree of sequence conservation suggests the antibody may cross-react with the homologous proteins in these species, making it potentially useful for comparative studies across the grass family (Poaceae). We also see evidence in the search results that B3 domain-containing proteins similar to Os07g0679700 exist in Physcomitrella patens , indicating evolutionary conservation across more distant plant lineages.

What are the best validation methods for confirming specificity of the Anti-Os07g0679700 antibody?

To rigorously validate the specificity of the Anti-Os07g0679700 antibody, researchers should implement multiple complementary approaches, following enhanced validation principles described in recent literature :

1. Genetic validation:

• Use samples from knockout/knockdown lines of Os07g0679700 as negative controls

• Include overexpression lines as positive controls

• Test for loss of signal in knockout samples and increased signal in overexpression samples

2. Orthogonal validation:

• Compare antibody results with orthogonal detection methods such as RNA-seq or RT-PCR data

• Correlation between protein levels (detected by antibody) and transcript levels provides supporting evidence for specificity

3. Independent antibody validation:

• Compare results with a second antibody targeting a different epitope of Os07g0679700

• Similar patterns with two independent antibodies increase confidence in specificity

4. Mass spectrometry validation:

• Perform immunoprecipitation followed by mass spectrometry

• Confirm the identity of the pulled-down protein as Os07g0679700

5. Cross-reactivity testing:

• Test the antibody against closely related B3 domain proteins if available

• Examine signal in species with known sequence divergence

These approaches align with the enhanced validation criteria described in search result , which emphasizes using multiple methods to establish antibody reliability. As noted in , implementing a rigorous antibody validation pipeline that includes CRISPR/Cas9 knockout controls can significantly improve confidence in antibody specificity.

How can I optimize Western blot conditions for detecting Os07g0679700 in different plant tissues?

Optimizing Western blot conditions for Os07g0679700 detection across different plant tissues requires addressing tissue-specific challenges:

1. Extraction buffer optimization:

• For tissues high in phenolics or secondary metabolites (e.g., roots): Add polyvinylpolypyrrolidone (PVPP), β-mercaptoethanol, and ascorbic acid to extraction buffer

• For tissues with high carbohydrate content (e.g., seeds): Include additional precipitation steps with TCA/acetone

• Standard buffer composition: 50 mM Tris-HCl pH 7.5, 150 mM NaCl, 1% Triton X-100, 1 mM EDTA, protease inhibitor cocktail

2. Protein loading adjustments:

• Tissues with low expression may require higher total protein loading (50-100 μg)

• Highly expressing tissues may need lower amounts (10-20 μg) to prevent oversaturation

• Always normalize loading between samples using a reliable method (Ponceau S staining or housekeeping protein)

3. Blocking optimization:

• Test different blocking agents (5% BSA vs. 5% non-fat milk)

• Adjust blocking time (1-3 hours) and concentration (3-5%)

• For plant samples, BSA often provides lower background than milk proteins

4. Antibody dilution optimization:

• Create a dilution series (1:500 to 1:5000) to determine optimal signal-to-noise ratio

• Optimize incubation temperature (4°C overnight vs. room temperature for 1-2 hours)

• For the Anti-Os07g0679700 antibody, the recommended range is 1:1000-1:2000

5. Detection system selection:

• For low expression tissues: Consider more sensitive detection systems (enhanced chemiluminescence)

• For quantitative analysis: Use fluorescent secondary antibodies for more linear dynamic range

6. Internal loading controls:

• Select appropriate housekeeping proteins specific to plant tissues (e.g., actin, tubulin, GAPDH)

• Validate loading control stability across the tissues being compared

Document all optimization steps systematically to establish a reproducible protocol for each tissue type. This methodical approach will provide the most consistent and reliable detection of Os07g0679700 across diverse plant samples.

How should I select appropriate controls when using the Anti-Os07g0679700 antibody?

Comprehensive control experiments are essential for ensuring reliable results with the Anti-Os07g0679700 antibody:

1. Negative controls:

• Primary antibody omission: Replace primary antibody with buffer or non-immune rabbit serum

• Genetic knockout/knockdown: Use tissue from Os07g0679700 knockout or RNAi lines (ideally generated via CRISPR/Cas9 as described in )

• Peptide competition: Pre-incubate antibody with excess immunizing peptide to block specific binding

2. Positive controls:

• Overexpression samples: Use tissue overexpressing Os07g0679700

• Known expressing tissues: Include samples from tissues with established expression

• Recombinant protein: Include purified recombinant Os07g0679700 as reference

3. Loading and transfer controls:

• Total protein staining: Use Ponceau S or SYPRO Ruby to confirm equal loading and transfer

• Housekeeping proteins: Include appropriate references for plant tissues (actin, tubulin, GAPDH)

• Standardized samples: Include a reference sample across multiple blots for inter-blot comparison

4. Technical controls:

• Multiple biological replicates: Minimum three independent samples

• Technical replicates: To assess reproducibility of the method

• Dilution series: To confirm linearity of signal and quantification range

5. Cross-reactivity assessment:

• Related proteins: Test against closely related B3 domain proteins if available

• Species comparison: Include samples from species with varying degrees of sequence homology

6. Secondary antibody controls:

• Secondary antibody only: Omit primary antibody to assess non-specific binding

• Isotype control: Use irrelevant primary antibody of same isotype and concentration

These controls align with the enhanced validation approaches outlined in and , which emphasize the importance of multiple validation strategies to ensure antibody specificity. As highlighted in , implementing rigorous controls is essential for improving the reproducibility of antibody-based research.

How can I use the Anti-Os07g0679700 antibody for immunoprecipitation experiments?

While the Anti-Os07g0679700 antibody hasn't been specifically validated for immunoprecipitation (IP), researchers may adapt standard IP protocols with specific considerations for this transcription factor:

Protocol optimization:

• Lysis buffer selection:

  • Use a gentle lysis buffer to preserve protein-protein interactions:

  • Example: 50 mM Tris-HCl pH 7.5, 150 mM NaCl, 0.5% NP-40, 1 mM EDTA, protease inhibitor cocktail

  • For nuclear proteins like transcription factors, include a nuclear extraction step

• Sample preparation:

  • Start with 1-5 mg of total protein

  • Pre-clear lysate with Protein A/G beads (1 hour at 4°C) to reduce non-specific binding

  • Reserve 5-10% of lysate as input control

• Antibody binding:

  • Use 2-5 μg of Anti-Os07g0679700 antibody per mg of protein

  • Incubate overnight at 4°C with gentle rotation

  • In parallel, prepare a negative control using non-immune rabbit IgG

• Immunoprecipitation:

  • Add pre-washed Protein A/G beads (30-50 μl of bead slurry)

  • Incubate 1-3 hours at 4°C with gentle rotation

  • Wash beads 4-5 times with decreasing stringency wash buffers

• Elution and analysis:

  • Elute bound proteins with SDS sample buffer (95°C for 5 minutes)

  • Analyze by Western blot using the same antibody or a second Anti-Os07g0679700 antibody

  • Alternatively, analyze by mass spectrometry to identify interacting partners

Validation approaches:

As shown in , immunoprecipitation efficiency can be assessed by analyzing:

• The amount of target protein in the immunoprecipitate

• The amount of target protein remaining in the unbound fraction

• The specificity of the immunoprecipitation (comparing with control IgG)

For a high-quality IP antibody, you should observe:

• Significant enrichment of Os07g0679700 in the IP fraction

• Substantial depletion from the unbound fraction

• Minimal non-specific binding in the control IgG IP

This approach would allow researchers to identify potential interaction partners of Os07g0679700, providing insights into its regulatory networks and transcriptional complexes.

What should I consider when using the Anti-Os07g0679700 antibody across different plant species?

When using the Anti-Os07g0679700 antibody across different plant species, researchers should consider several important factors:

1. Sequence homology assessment:

• Conduct sequence alignments between Os07g0679700 and potential homologs in target species

• Focus on the epitope region (the 22 amino acid peptide from the central section used for immunization)

• The antibody may work best in species with 80-99% homology, as noted in the product information

2. Cross-reactivity validation:

• Always validate antibody specificity in each new species

• Perform Western blots with positive controls (rice samples) alongside the new species

• Consider peptide competition assays to confirm specific binding

3. Optimization for each species:

• Adjust antibody concentration (typically start with higher concentrations for cross-species detection)

• Modify extraction protocols based on species-specific characteristics (e.g., higher phenolic content)

• Optimize blotting conditions (transfer time, membrane type, blocking agent)

4. Considerations for evolutionary distance:

• Closer relatives (other Poaceae family members) are more likely to show cross-reactivity

• More distant relatives may require higher antibody concentrations or longer exposure times

• Alternative detection methods (e.g., more sensitive chemiluminescence) may be necessary

5. Predicted reactivity based on search results:

• The antibody may work in Setaria viridis, Panicum virgatum, Zea mays, Hordeum vulgare, Triticum aestivum, and Sorghum bicolor due to high sequence homology

• The protein appears to be conserved in Physcomitrella patens , suggesting potential use in more distant plant species

6. Control experiments:

• Include side-by-side comparisons with rice samples as positive controls

• Use knockout/knockdown lines of the homologous gene when available

• Consider orthogonal validation with RNA expression data or mass spectrometry

This systematic approach will help determine the utility of the Anti-Os07g0679700 antibody across different plant species and provide more reliable cross-species comparisons.

How can computational antibody design approaches improve Anti-Os07g0679700 antibody specificity?

Computational antibody design offers several advanced strategies to enhance Anti-Os07g0679700 antibody specificity, drawing on approaches described in recent literature:

1. Epitope optimization using bioinformatics:

• Analyze the Os07g0679700 sequence for unique regions distinct from homologs

• Use tools like BLAST and multiple sequence alignments to identify species-specific regions

• Target epitopes with high antigenicity scores but low conservation across related proteins

• This approach minimizes cross-reactivity with related B3 domain proteins

2. Structure-based design approaches:

• As demonstrated in , machine learning combined with structural biology can predict optimal antibody structures

• Model the 3D structure of Os07g0679700 using homology modeling tools like ABodyBuilder (mentioned in )

• Predict antibody-antigen interactions to identify optimal binding configurations

• Use RosettaAntibodyDesign (RAbD) framework described in for structure-based antibody design

3. Machine learning-driven optimization:

• Apply machine learning approaches similar to those described in and

• Use deep learning models like AbLM from trained on antibody-antigen interfaces to predict mutations that enhance specificity

• Implement the AbGen pipeline to predict optimal complementarity-determining regions (CDRs)

• These approaches can identify subtle sequence modifications that dramatically improve specificity

4. Molecular dynamics simulations:

• Perform binding free energy calculations using tools like FoldX, Rosetta, or MM/GBSA (mentioned in )

• Simulate antibody-antigen interactions to identify stability and specificity determinants

• As described in , researchers used over 200,000 CPU hours and 20,000 GPU hours to perform 178,856 in silico free energy calculations

• These simulations can identify optimal antibody variants without extensive wet-lab screening

5. Integration with experimental validation:

• Design a panel of computational variants for experimental testing

• Use high-throughput screening approaches to validate in silico predictions

• Implement iterative optimization cycles combining computational predictions with experimental feedback

This integrated computational-experimental approach, similar to that described in where researchers developed antibodies to SARS-CoV-2 in just 22 days, could significantly enhance Anti-Os07g0679700 antibody specificity and performance across diverse applications.

What are the best approaches for using the Anti-Os07g0679700 antibody in chromatin immunoprecipitation (ChIP) experiments?

Optimizing ChIP experiments with the Anti-Os07g0679700 antibody requires careful consideration of several factors specific to transcription factor ChIP:

1. Crosslinking optimization:

• For transcription factors like Os07g0679700, use:

  • 1-1.5% formaldehyde for 10-15 minutes at room temperature

  • Quench with 125 mM glycine for 5 minutes

• Consider dual crosslinking with DSG (disuccinimidyl glutarate, 2 mM for 30 minutes) followed by formaldehyde for more stable protein-DNA interactions

• Test multiple crosslinking times to optimize signal-to-noise ratio

• This is particularly important for transcription factors with transient DNA binding

2. Chromatin preparation:

• Sonication parameters:

  • Optimize sonication to generate fragments of 200-500 bp

  • Typical conditions: 30 seconds on/30 seconds off, 10-15 cycles at 40% amplitude

  • Verify fragment size by agarose gel electrophoresis

• Alternatively, use enzymatic fragmentation (MNase)

• Pre-clear chromatin with protein A/G beads to reduce background

3. Immunoprecipitation conditions:

• Antibody amount:

  • Titrate antibody (1-10 μg per reaction)

  • Compare signal-to-background at different concentrations

• Include controls:

  • Input DNA (non-immunoprecipitated)

  • IgG control (normal rabbit IgG)

  • Positive control (antibody against histone mark like H3K4me3)

4. Washing and elution:

• Use increasingly stringent washing buffers:

  • Low salt wash (150 mM NaCl)

  • High salt wash (500 mM NaCl)

  • LiCl wash (250 mM LiCl)

  • TE buffer wash

• Elute under optimal conditions:

  • SDS elution buffer (1% SDS, 100 mM NaHCO₃) at 65°C

  • Reverse crosslinks with proteinase K treatment (50 μg/ml, 65°C, overnight)

5. Analysis approaches:

• qPCR for known or predicted targets:

  • Design primers for suspected binding regions

  • Calculate percent input or fold enrichment over IgG

• ChIP-seq for genome-wide binding profile:

  • Prepare libraries with sufficient material (typically >10 ng)

  • Include input controls for peak calling

  • Use appropriate bioinformatics pipelines to identify binding motifs

6. Validation strategies:

• Perform replicate experiments (minimum three biological replicates)

• Confirm key targets with independent methods (e.g., EMSA)

• Compare binding sites with expression data of potential target genes

This comprehensive approach will help identify the genomic binding sites of Os07g0679700, providing insights into its transcriptional regulatory network and DNA binding preferences.

How can I detect post-translational modifications of Os07g0679700 using the available antibody?

Detecting post-translational modifications (PTMs) of Os07g0679700 presents several technical challenges but can be approached with these strategies:

1. Combined immunoprecipitation and mass spectrometry approach:

• Immunoprecipitate Os07g0679700 using the Anti-Os07g0679700 antibody

• Process samples for mass spectrometry analysis:

  • In-gel or in-solution digestion with trypsin

  • Enrichment for specific modifications (e.g., TiO₂ for phosphopeptides)

  • LC-MS/MS analysis with PTM-specific fragmentation methods

• Search for common PTMs:

  • Phosphorylation (Ser, Thr, Tyr) - common in transcription factors

  • Acetylation (Lys) - often found in nuclear proteins

  • Methylation (Lys, Arg) - can regulate transcription factor activity

  • Ubiquitination (Lys) - may regulate protein degradation

2. Mobility shift detection methods:

• Phosphorylation-specific detection:

  • Use Phos-tag SDS-PAGE to separate phosphorylated forms

  • Compare migration patterns with and without phosphatase treatment

  • Detect with Anti-Os07g0679700 antibody via Western blot

• Two-dimensional gel electrophoresis:

  • Separate proteins by isoelectric point and molecular weight

  • Identify PTM-induced changes in protein position

  • Detect with the antibody after transfer to membrane

3. Modification-specific antibody development:

• Use information from MS analysis to identify the most common modification sites

• Develop antibodies against modified peptides containing these sites

• Validate specificity using synthetic phosphopeptides and dephosphorylated samples

• Use in parallel with the general Anti-Os07g0679700 antibody

4. Enrichment strategies for modified forms:

• Phosphorylated proteins:

  • Immobilized metal affinity chromatography (IMAC)

  • Phospho-protein enrichment columns

• Ubiquitinated proteins:

  • Tandem ubiquitin binding entities (TUBEs)

  • Anti-ubiquitin antibodies for co-IP

• Acetylated proteins:

  • Anti-acetyl-lysine antibodies for co-IP

5. Biological context considerations:

• PTMs may be tissue-specific, developmentally regulated, or stress-induced

• Design experiments to capture dynamic modification states:

  • Time-course studies after stress treatment

  • Developmental series

  • Tissue-specific analysis

• Include appropriate positive controls known to induce specific modifications

These approaches require careful optimization and validation but can provide valuable insights into how PTMs regulate Os07g0679700 function, potentially revealing mechanisms controlling this transcription factor's activity, stability, or localization.

How can the Anti-Os07g0679700 antibody be used to study protein-protein interactions of this transcription factor?

The Anti-Os07g0679700 antibody can be employed in several techniques to investigate protein-protein interactions:

1. Co-immunoprecipitation (Co-IP):

• Optimize lysis conditions to preserve protein complexes:

  • Use gentle detergents (0.5% NP-40 or 0.1% Triton X-100)

  • Include protease inhibitors and phosphatase inhibitors

  • For nuclear proteins, use specialized nuclear extraction buffers

  • Consider crosslinking (formaldehyde, DSP) for transient interactions

• Immunoprecipitate Os07g0679700 using the antibody

• Analyze co-precipitated proteins by:

  • Western blotting for suspected interaction partners

  • Mass spectrometry for unbiased discovery of novel interactions

2. Proximity labeling approaches:

• BioID method:

  • Generate fusion proteins (Os07g0679700-BioID)

  • Express in plant cells to biotinylate proximal proteins

  • Isolate biotinylated proteins using streptavidin

  • Validate potential interactions using the Anti-Os07g0679700 antibody

• APEX2 proximity labeling:

  • Similar approach using peroxidase-based labeling

  • Offers higher spatial and temporal resolution

3. Pull-down assays:

• Produce recombinant Os07g0679700 as bait protein

• Incubate with plant extracts

• Detect pulled-down proteins via Western blot or MS

• Confirm interactions by reverse pull-down using Anti-Os07g0679700 antibody

4. In situ proximity detection:

• Proximity Ligation Assay (PLA):

  • Use Anti-Os07g0679700 antibody with antibodies against suspected partners

  • Detect proximity (<40 nm) as fluorescent signals

  • Provides spatial information about interactions in intact cells

• Förster Resonance Energy Transfer (FRET):

  • Combine with fluorescently-labeled secondary antibodies

  • Detect energy transfer between proximal proteins

5. Validation strategies:

• Confirm specificity by competition with immunizing peptide

• Include negative controls (IgG precipitation, knockout samples)

• Verify interactions using multiple orthogonal methods

• Test interaction dependence on conditions (e.g., hormones, stress)

Similar to the approach in , where mass spectrometry analysis of immunoprecipitates identified the SMCR8 and WD41 proteins as interaction partners of C9ORF72, these methods can reveal the composition of Os07g0679700-containing protein complexes. This provides insights into its regulatory mechanisms and functional networks within the plant cell.

How can I develop an enhanced validation strategy for the Anti-Os07g0679700 antibody following recent reproducibility guidelines?

Developing an enhanced validation strategy for the Anti-Os07g0679700 antibody requires implementing multiple complementary approaches, following guidelines from recent literature on antibody validation :

1. Genetic validation:

• Generate CRISPR/Cas9 knockout of Os07g0679700 in rice or model system

• Compare antibody signals between wild-type and knockout samples

• Document complete signal elimination in true knockout samples

• Include heterozygous samples to demonstrate sensitivity to protein levels

• This approach aligns with the validation pipeline described in

2. Orthogonal validation:

• Correlate protein detection with independent RNA quantification methods:

  • RT-qPCR to measure Os07g0679700 transcript levels

  • RNA-seq data from matching samples

• Demonstrate correlation between protein and transcript levels across:

  • Different tissues

  • Developmental stages

  • Treatment conditions

• This method is highlighted in as a key validation approach

3. Independent antibody validation:

• Obtain or develop a second antibody targeting a different epitope

• Compare staining patterns between both antibodies

• Document consistent detection patterns across multiple applications

• This approach strengthens confidence in the specificity of observed signals

4. Expression validation:

• Ectopically express Os07g0679700 with an orthogonal tag (GFP, FLAG)

• Detect with both Anti-Os07g0679700 antibody and tag-specific antibody

• Demonstrate co-localization and signal correlation

• This provides confirmation of antibody specificity

5. Mass spectrometry validation:

• Perform immunoprecipitation followed by MS analysis

• Confirm Os07g0679700 as the primary precipitated protein

• Document peptide coverage across the protein sequence

• This approach can also identify potential interaction partners, as shown in

6. Multi-application testing:

• Validate across different applications:

  • Western blot

  • Immunoprecipitation

  • Immunohistochemistry (if applicable)

• Document consistent results across techniques

• Address application-specific optimization requirements

7. Transparent reporting:

• Follow guidelines from for comprehensive documentation:

  • Catalog all validation experiments performed

  • Document lot-to-lot variation testing

  • Share validation data openly in publications and repositories

  • Report both positive and negative results

8. Community engagement:

• Contribute validation data to antibody validation databases

• Include detailed methods in publications

• Share reagents and protocols to benefit the research community

• Address behavioral aspects of antibody validation highlighted in

This enhanced validation strategy addresses the reproducibility challenges highlighted in , providing robust evidence for antibody specificity and reliability, which is essential for advancing our understanding of Os07g0679700 function.