AGL90 Antibody

What is AGL90 and why is it significant in plant research?

AGL90 (agamous-like MADS-box protein 90) is a protein-coding gene product found in plants such as Nicotiana tabacum (common tobacco). It belongs to the MADS-box transcription factor family, which plays crucial roles in plant development, particularly floral organ specification. The significance of AGL90 lies in its potential regulatory functions in developmental pathways. Research using antibodies against this protein can help elucidate its expression patterns, protein-protein interactions, and developmental roles. AGL90 has been cataloged in genomic databases with the Entrez Gene ID 107773221, and its full protein sequence has been determined and is available through repositories such as GenScript .

What types of samples are appropriate for AGL90 antibody applications?

AGL90 antibodies can be used with various plant tissue samples, primarily from Nicotiana tabacum and potentially other related species with conserved MADS-box proteins. Appropriate samples include:

• Plant tissue extracts (floral tissues, leaves, stems)

• Fixed tissue sections for immunohistochemistry

• Protein lysates for Western blotting

• Chromatin preparations for ChIP assays

Sample preparation should account for the typically nuclear localization of MADS-box transcription factors, with appropriate nuclear extraction protocols. When working with plant tissues, researchers should consider developmental stage, as MADS-box protein expression can be temporally regulated throughout development .

What detection methods are compatible with AGL90 antibodies?

AGL90 antibodies can be utilized with several detection methodologies in plant molecular biology:

For optimal results, each application requires specific optimization of antibody concentration, incubation conditions, and signal amplification methods. Detection protocols should be validated using appropriate positive and negative controls .

How can I verify AGL90 antibody specificity against closely related MADS-box proteins?

Verifying antibody specificity is crucial when working with protein families containing highly conserved domains, such as MADS-box transcription factors. To ensure your AGL90 antibody specifically recognizes AGL90 without cross-reactivity to related proteins:

• Perform Western blot analysis using recombinant proteins for AGL90 and closely related MADS-box proteins expressed in heterologous systems.

• Conduct competition assays by pre-incubating the antibody with purified AGL90 protein before immunodetection.

• Test the antibody in tissues/cells with confirmed AGL90 knockout or knockdown.

• Employ epitope mapping to confirm the antibody binds to unique regions of AGL90 rather than the conserved MADS-box domain.

• Compare immunoprecipitation results with mass spectrometry data to confirm the identity of precipitated proteins.

Recent computational approaches for antibody specificity analysis can also be applied. Models that associate distinct binding modes with different ligands can help predict cross-reactivity patterns and optimize antibody selection for highly specific recognition of AGL90 over related proteins .

What are the technical considerations for using AGL90 antibodies in chromatin immunoprecipitation (ChIP) experiments?

When designing ChIP experiments to investigate AGL90 DNA binding sites:

• Fixation optimization: For plant tissues, test multiple formaldehyde concentrations (1-3%) and fixation times (10-30 minutes) to preserve protein-DNA interactions without overfixing.

• Chromatin fragmentation: Optimize sonication parameters to achieve DNA fragments of 200-500 bp for high-resolution binding site identification.

• Antibody validation: Confirm that your AGL90 antibody can recognize the fixed/denatured form of the protein by performing Western blots on fixed samples.

• Controls implementation: Include:

  • Input chromatin (pre-immunoprecipitation sample)

  • IgG control (non-specific antibody)

  • Positive control (antibody against a well-characterized transcription factor)

  • Negative control regions (genomic regions not expected to bind AGL90)

• Sequential ChIP consideration: For investigating co-occupation with other MADS-box proteins, sequential ChIP with antibodies against potential binding partners can reveal complex formation at specific loci.

Analysis of ChIP-seq data for MADS-box proteins often reveals CArG box motifs (consensus sequence CC[A/T]₆GG) as binding sites. Computational tools specifically designed for plant transcription factor binding site analysis should be employed for accurate peak calling and motif discovery .

How can I distinguish between phosphorylated and non-phosphorylated forms of AGL90 using antibodies?

Distinguishing phosphorylation states of AGL90 requires specialized antibody approaches:

• Phospho-specific antibodies: Generate antibodies against predicted phosphorylation sites in AGL90. This requires:

  • Bioinformatic prediction of likely phosphorylation sites

  • Synthesis of phosphopeptides corresponding to these regions

  • Immunization strategies that specifically generate antibodies recognizing the phosphorylated epitope

• Validation approaches:

  • Treat samples with phosphatases to confirm signal loss

  • Use mass spectrometry to identify actual phosphorylation sites

  • Compare antibody reactivity between wild-type and phospho-site mutant versions of AGL90

• 2D gel electrophoresis: Combine with Western blotting to separate phosphorylated forms based on isoelectric point shifts.

• Phos-tag™ SDS-PAGE: This technique can separate phosphorylated and non-phosphorylated forms of proteins based on phosphate-specific binding, allowing visualization of multiple phosphorylation states in combination with AGL90 antibodies.

Researchers should note that MADS-box proteins often exhibit complex post-translational modification patterns that affect their function, DNA binding capacity, and protein-protein interactions. Comprehensive analysis may require multiple antibodies targeting different modification states .

What are optimal protein extraction methods when using AGL90 antibodies for immunoblotting?

Efficient extraction of nuclear transcription factors like AGL90 requires specialized approaches:

• Nuclear extraction protocol:

  • Grind plant tissue in liquid nitrogen

  • Resuspend in nuclear isolation buffer (typically containing 20-50 mM Tris-HCl pH 7.5, 250 mM sucrose, 5 mM MgCl₂, 5 mM KCl, 0.1% Triton X-100, 1 mM DTT, and protease inhibitor cocktail)

  • Filter through miracloth

  • Centrifuge at 1,000 × g for 10 minutes at 4°C

  • Resuspend nuclear pellet in protein extraction buffer

• Protein extraction buffers:

  • Standard: 50 mM Tris-HCl pH 8.0, 150 mM NaCl, 1% NP-40, 0.5% sodium deoxycholate, 0.1% SDS, 1 mM DTT, protease inhibitors

  • For preserving protein-protein interactions: Substitute SDS with milder detergents like 0.5% Triton X-100

• Critical considerations:

  • Include phosphatase inhibitors (10 mM NaF, 1 mM Na₃VO₄) if studying phosphorylation

  • Add 20 mM N-ethylmaleimide for preserving SUMOylation

  • Use fresh tissue whenever possible

  • Maintain cold temperatures throughout extraction

• Yield assessment:

  • Quantify protein using Bradford or BCA assays

  • Verify nuclear extraction efficiency using control antibodies against known nuclear proteins (e.g., histones) and cytoplasmic proteins (e.g., tubulin) to assess fractionation quality

These extraction methods should yield sufficient quantities of native AGL90 protein suitable for detection by Western blotting, typically requiring 25-50 μg of nuclear extract per lane .

What are recommended immunoprecipitation protocols for studying AGL90 protein interactions?

For investigating AGL90 interactions with other proteins:

• Standard co-immunoprecipitation protocol:

  • Extract proteins under native conditions using buffer containing 50 mM Tris-HCl pH 7.5, 150 mM NaCl, 0.5% NP-40, 1 mM EDTA, 1 mM DTT, and protease inhibitors

  • Pre-clear lysate with protein A/G beads (1 hour at 4°C)

  • Incubate pre-cleared lysate with AGL90 antibody overnight at 4°C

  • Add protein A/G beads for 3 hours at 4°C

  • Wash 4-5 times with wash buffer (extraction buffer with reduced detergent)

  • Elute bound proteins for analysis by mass spectrometry or Western blotting

• Crosslinking considerations:

  • For transient interactions, consider using membrane-permeable crosslinkers like DSP (dithiobis(succinimidyl propionate))

  • Optimal crosslinking: 1-2 mM DSP for 30 minutes at room temperature

  • Quench with 50 mM Tris-HCl pH 7.5

• Controls and validation:

  • IgG control immunoprecipitation

  • Reciprocal co-IP with antibodies against suspected interaction partners

  • Validation with recombinant tagged proteins

For studying AGL90 interactions with other MADS-box proteins, which often form dimers or higher-order complexes, this approach can reveal biologically significant protein partnerships that influence DNA binding specificity and transcriptional activity .

How should I optimize immunohistochemistry protocols for AGL90 localization in plant tissues?

Localizing AGL90 in plant tissues presents unique challenges:

• Fixation and embedding:

  • Fix tissues in 4% paraformaldehyde for 12-24 hours at 4°C

  • Dehydrate through ethanol series (30%, 50%, 70%, 85%, 95%, 100%)

  • Clear in xylene and embed in paraffin or consider cryo-sectioning for better epitope preservation

• Antigen retrieval options:

  • Heat-induced: Citrate buffer (pH 6.0) at 95°C for 20-30 minutes

  • Enzymatic: Proteinase K (1-10 μg/ml) for 10-20 minutes at room temperature

  • For plant tissues, test both methods to determine optimal epitope exposure

• Blocking and antibody incubation:

  • Block with 5% normal serum, 1% BSA in PBS with 0.3% Triton X-100

  • Primary antibody dilution range: 1:100-1:500 (optimize empirically)

  • Incubation: Overnight at 4°C in humidity chamber

  • Secondary antibody (fluorescent or enzyme-conjugated): 1:200-1:1000 for 1-2 hours at room temperature

• Signal amplification options:

  • Tyramide signal amplification for low-abundance proteins

  • Quantum dot conjugates for multiplex detection and higher photostability

• Controls:

  • Primary antibody omission

  • Blocking peptide competition

  • Comparison with in situ hybridization patterns

  • Tissues from plants with altered AGL90 expression

The dense cell wall in plant tissues may require additional permeabilization steps beyond what is typical for animal tissues. Consider extended Triton X-100 treatment (0.5-1% for 30-60 minutes) or limited cell wall digestion with cellulase/pectinase enzymes to improve antibody penetration .

How can I address non-specific binding when using AGL90 antibodies in plant samples?

Non-specific binding is a common challenge when working with plant tissues:

• Optimization strategies:

  • Increase blocking reagent concentration (try 5-10% BSA or 5% milk)

  • Add 0.1-0.5% non-ionic detergents (Tween-20, Triton X-100) to wash buffers

  • Include 100-500 mM NaCl in wash buffers to disrupt low-affinity interactions

  • Pre-absorb antibody with plant extract from species lacking AGL90

• Plant-specific considerations:

  • Add 1-2% polyvinylpyrrolidone (PVP) to buffers to bind phenolic compounds

  • Include 0.5-2% polyethylene glycol to reduce non-specific interactions

  • Consider adding 10-20 mM sodium metabisulfite to prevent oxidation of plant compounds

• Antibody purification:

  • Affinity-purify antibodies against the immunizing peptide/protein

  • Perform negative selection against related MADS-box proteins

  • Consider using monoclonal antibodies for the highest specificity

• Signal-to-noise ratio improvement:

  • Titrate primary and secondary antibody concentrations

  • Extend wash steps (5× 10 minutes instead of standard 3× 5 minutes)

  • Evaluate different detection systems (chemiluminescence vs. fluorescence)

Advanced computational approaches for antibody specificity analysis, as described in recent literature, can also help predict potential cross-reactive epitopes and guide optimization strategies for reducing non-specific binding .

What are the best approaches for quantifying AGL90 expression levels using antibodies?

Accurate quantification of AGL90 expression requires methodological rigor:

• Western blot quantification:

  • Use gradient loading of standards for calibration curve

  • Ensure linear range of detection (avoid saturated signals)

  • Normalize to multiple reference proteins (nuclear markers preferred)

  • Employ image analysis software with background subtraction

  • Perform at least three biological replicates

• ELISA approaches:

  • Sandwich ELISA using two antibodies recognizing different AGL90 epitopes

  • Standard curve generation using recombinant AGL90 protein

  • Typical detection range: 0.1-100 ng/ml depending on antibody affinity

• Flow cytometry (for protoplasts or isolated nuclei):

  • Fixation with 2-4% paraformaldehyde

  • Permeabilization with 0.1-0.5% Triton X-100

  • Antibody staining followed by fluorescent secondary antibody

  • Analysis using mean fluorescence intensity

• Statistical analysis requirements:

  • ANOVA with appropriate post-hoc tests for multiple condition comparisons

  • Non-parametric tests for data not normally distributed

  • Report both biological and technical replication details

How can I interpret contradictory results between different anti-AGL90 antibodies?

When faced with contradictory results using different AGL90 antibodies:

• Epitope mapping analysis:

  • Determine the specific epitopes recognized by each antibody

  • Check if epitopes might be masked by protein-protein interactions

  • Evaluate whether post-translational modifications affect epitope accessibility

  • Consider if different antibodies recognize different isoforms or splice variants

• Validation through orthogonal methods:

  • Compare with RNA expression data (RT-qPCR, RNA-seq)

  • Use genetic approaches (tagged AGL90 expression, CRISPR/Cas9 knockout controls)

  • Employ mass spectrometry to confirm protein identity and abundance

• Technical considerations:

  • Different antibodies may require different sample preparation methods

  • Some epitopes might be sensitive to particular fixation or extraction conditions

  • Certain antibodies may work in one application (e.g., Western blot) but not others (e.g., immunoprecipitation)

• Biological interpretation:

  • Apparent contradictions might reflect genuine biological complexity

  • Different antibodies might preferentially recognize distinct conformational states

  • Discrepancies might reveal unexpected biology (e.g., tissue-specific post-translational modifications)

A computational modeling approach as described in recent literature can help predict antibody binding characteristics and potential limitations. Such models can disentangle different binding modes associated with particular epitopes, providing insight into why different antibodies might yield varying results .

How can computational approaches improve AGL90 antibody specificity prediction and design?

Recent advances in computational immunology offer new opportunities for antibody research:

• Machine learning approaches for specificity prediction:

  • Models trained on phage display data can predict cross-reactivity profiles

  • Biophysics-informed computational models can identify distinct binding modes

  • High-throughput sequencing combined with machine learning enables prediction beyond experimentally observed sequences

• Custom specificity design strategies:

  • Computational methods can design antibodies with tailored specificity profiles

  • Models can identify residues critical for discriminating between similar epitopes

  • Targeted mutations can enhance specificity for AGL90 over related MADS-box proteins

• Implementation methodology:

  • Train models on selection data from multiple related antigens

  • Identify binding modes specific to each target

  • Design sequences with optimized specificity profiles through computational mutation analysis

  • Validate experimentally through directed evolution or rational design

These computational approaches have demonstrated success in designing antibodies that can discriminate between structurally and chemically similar targets, making them particularly valuable for studying protein families with high sequence conservation like MADS-box transcription factors .

What are the considerations for using AGL90 antibodies in single-cell protein analysis of plant tissues?

As single-cell technologies expand to plant research, several considerations emerge:

• Tissue preparation challenges:

  • Plant cell walls require specialized dissociation protocols

  • Enzymatic digestion with cellulase/pectinase/macerozyme cocktails

  • Optimization of digestion time to maintain protein epitopes while achieving single-cell suspension

• Fixation and permeabilization balance:

  • Cross-linking fixatives (e.g., paraformaldehyde) at 2-4% for 10-20 minutes

  • Methanol fixation for better intracellular antigen access

  • Detergent permeabilization (0.1-0.5% Triton X-100 or 0.01-0.1% saponin)

• Detection technologies:

  • Mass cytometry (CyTOF) using metal-conjugated antibodies

  • Imaging mass cytometry for spatial resolution

  • Single-cell Western blotting platforms

  • Proximity ligation assays for protein interaction studies

• Data analysis approaches:

  • Dimensionality reduction techniques (tSNE, UMAP)

  • Clustering algorithms for cell type identification

  • Trajectory inference for developmental studies

  • Integration with single-cell transcriptomics data

The application of these technologies to plant developmental biology could reveal cell-type-specific expression patterns of AGL90 and its interaction partners, providing unprecedented insights into developmental processes at cellular resolution .