Unknown protein from spot 447 of 2D-PAGE of etiolated coleoptile Antibody

What is the Unknown protein from spot 447 of 2D-PAGE of etiolated coleoptile Antibody?

The Unknown protein from spot 447 of 2D-PAGE of etiolated coleoptile Antibody (Product Code: CSB-PA304525XA01ZAX) is a polyclonal antibody raised in rabbits against a recombinant Zea mays (maize) protein that was originally identified as spot 447 on two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) of etiolated coleoptile tissue. This antibody specifically recognizes the target protein with UniProt accession number P80630 and is primarily used in research applications such as ELISA and Western blotting to study this particular maize protein . The antibody is supplied in liquid form, contains a preservative (0.03% Proclin 300), and is stored in a buffer composed of 50% glycerol and 0.01M PBS at pH 7.4 .

How should the antibody be stored and handled for optimal performance?

For optimal performance, the Unknown protein from spot 447 of 2D-PAGE of etiolated coleoptile Antibody should be stored at -20°C or -80°C immediately upon receipt . Researchers should avoid repeated freeze-thaw cycles as this can degrade antibody quality and performance. When working with the antibody:

• Always wear appropriate personal protective equipment

• Aliquot the stock solution into smaller volumes to minimize freeze-thaw cycles

• Thaw aliquots at 4°C or on ice rather than at room temperature

• Centrifuge briefly before opening the tube to ensure all liquid is at the bottom

• Return to storage promptly after use

• Monitor expiration dates carefully

The antibody is supplied in 50% glycerol with 0.01M PBS (pH 7.4) containing 0.03% Proclin 300 as a preservative , which helps maintain stability during proper storage.

What are the validated applications for this antibody?

This antibody has been validated for specific research applications:

The antibody was raised against recombinant Zea mays Unknown protein from spot 447 of 2D-PAGE of etiolated coleoptile protein, making it primarily reactive with Zea mays (maize) samples . Researchers should perform appropriate controls when using this antibody, especially when applying it to species other than maize.

What is the significance of proteins identified from 2D-PAGE spots?

Proteins identified from specific spots on 2D-PAGE gels represent distinct protein species that have been separated based on two independent properties: isoelectric point (pI) in the first dimension and molecular weight in the second dimension . The significance of these proteins includes:

• They often represent unique isoforms or post-translationally modified variants

• The spot position provides information about both the pI and molecular weight

• Relative abundance can be inferred from spot intensity

• Proteins from specific spots may have functions that differ from other isoforms of the same protein

• Unknown proteins from 2D-PAGE spots represent novel protein species requiring further characterization

The "Unknown protein from spot 447" specifically refers to a protein that was initially characterized only by its position on a 2D gel of maize etiolated coleoptile tissue, before being further identified and assigned the UniProt number P80630 .

What methodological approaches are recommended for validating this antibody in experimental workflows?

Comprehensive validation of the Unknown protein from spot 447 antibody should follow a multi-step approach:

Step 1: Western Blot Validation

• Compare target protein expression in wild-type samples versus knockout/knockdown models

• Perform peptide competition assays using the immunizing peptide

• Include positive and negative control samples

• Evaluate band specificity at the expected molecular weight

Step 2: Cross-Validation with Multiple Methods

• ELISA validation with titration curves to determine optimal concentrations

• Immunoprecipitation followed by mass spectrometry identification of pulled-down proteins

• Comparison with other antibodies targeting the same protein (if available)

Step 3: Specificity Testing

• Test on non-target species to confirm species specificity

• Evaluate reactivity with related protein family members

• Test on recombinant protein if available

A recent large-scale antibody validation study demonstrated that only 22-36% of commercial antibodies perform well in standard applications, underscoring the importance of rigorous validation . The study found that comparing antibody performance in wild-type versus knockout cell lines is the most reliable validation method, with approximately 5% false positive rate .

How can researchers effectively use this antibody to study protein expression in maize coleoptile development?

To effectively use this antibody for studying protein expression during maize coleoptile development:

• Experimental Design Considerations:

  • Establish a time-course experiment covering key developmental stages

  • Include appropriate controls (light-grown vs. etiolated, different tissue types)

  • Consider using multiple extraction methods for comprehensive protein coverage

• Sample Preparation Protocol:

  • Harvest coleoptile tissue at consistent time points and flash-freeze in liquid nitrogen

  • Pulverize tissue under liquid nitrogen using a mortar and pestle

  • Extract proteins using a buffer containing:

    • 50 mM Tris-HCl (pH 7.5)

    • 150 mM NaCl

    • 1% Triton X-100

    • 0.5% sodium deoxycholate

    • Protease inhibitor cocktail

  • Clarify extracts by centrifugation (20,000 × g, 15 min, 4°C)

  • Quantify protein concentration using Bradford or BCA assay

• Detection Methods:

  • Western blotting with standardized loading (20-30 μg total protein)

  • Quantitative ELISA for measuring protein levels across samples

  • Consider immunohistochemistry to localize protein expression within tissue structure

• Data Analysis:

  • Normalize expression data to stable reference proteins

  • Perform statistical analysis to identify significant changes

  • Correlate protein expression with phenotypic changes

This methodological approach can reveal developmental regulation of the target protein and provide insights into its potential functions in coleoptile growth and development.

How does 2D-PAGE identify unknown proteins, and what are the limitations of this approach?

The 2D-PAGE technique identifies unknown proteins through a multi-step process:

Identification Process:

• Proteins are separated based on isoelectric point (first dimension) and molecular weight (second dimension)

• Protein spots of interest are excised from the gel

• Proteins undergo in-gel digestion with proteases (typically trypsin)

• The resulting peptides are analyzed by mass spectrometry

• Peptide mass fingerprints or MS/MS spectra are matched against protein databases

Major Limitations:

• Technical Limitations:

  • Poor separation of proteins with extreme properties:

    • Hydrophobic proteins, particularly membrane proteins

    • Very acidic or basic proteins

    • Very high (>150 kDa) or low (<10 kDa) molecular weight proteins

  • Limited dynamic range (104-105) compared to the biological range (>107)

  • Difficulty detecting low-abundance proteins in the presence of highly abundant ones

• Analytical Challenges:

  • Spots may contain multiple proteins co-migrating with similar properties

  • Post-translational modifications can significantly alter migration patterns

  • Database matching may fail for novel proteins not in databases

• Quantification Issues:

  • Variability in protein staining efficiency

  • Potential loss during sample preparation and gel processing

In a comprehensive study analyzing plasma proteins, researchers found that spots displaying high degrees of isoform-specific changes in 2D gels were not reflected in targeted MS assays measuring total protein levels, highlighting the complexity of proteoform analysis .

What approaches can improve the detection of "missing proteins" like those identified from 2D-PAGE spots?

"Missing proteins" are protein-coding genes with insufficient evidence of detection at the protein level . Effective strategies to improve their detection include:

• Enhanced Sample Fractionation:

  • Combine multiple separation techniques (e.g., RP-HPLC followed by 2D-PAGE)

  • Use narrow-range pH gradients ("zoom gels") for first-dimension separation

  • Implement larger separation areas (40 × 40 cm gels) to improve resolution

• Enrichment Strategies:

  • Deplete high-abundance proteins (e.g., immunodepletion of abundant plasma proteins)

  • Use subcellular fractionation to focus on specific cellular compartments

  • Apply affinity purification techniques for protein families of interest

• Advanced Mass Spectrometry Approaches:

  • Use complementary MS methods (MALDI-TOF-MS and ESI-MS/MS)

  • Implement data-independent acquisition (DIA) methods

  • Apply specialized techniques for membrane proteins (e.g., hydrophobic peptide enrichment)

• AI-Assisted Identification:

  • Implement AI tools like InstaNovo and InstaNovo+ that can decode proteins missed by existing methods

  • Use machine learning models to predict protein sequences from mass spectrometry data

  • Apply computational approaches to identify patterns in unassigned spectral data

A recent study utilizing AI models demonstrated the ability to uncover previously hidden proteins with approximately 5% false positive rate, suggesting significant potential for improving detection of missing proteins .

What are the challenges in antibody validation for proteins initially identified only by 2D-PAGE spots?

Validating antibodies for proteins initially identified only by 2D-PAGE spots presents unique challenges:

• Target Uncertainty:

  • Limited sequence information may be available initially

  • The exact identity and sequence of the protein may not be fully characterized

  • Post-translational modifications affecting immunogenicity may be unknown

• Recombinant Protein Challenges:

  • Difficult to produce recombinant versions of poorly characterized proteins

  • Potential differences between recombinant immunogens and native proteins

  • Expression systems may not reproduce all post-translational modifications

• Validation Methodology:

  • Limited availability of knockout models for validation

  • Difficulty establishing gold standard validation methods

  • Cross-reactivity with related proteins may be impossible to assess fully

• Application-Specific Performance:

  • An antibody may perform well in one application (e.g., Western blot) but poorly in others (e.g., immunoprecipitation)

  • Different experimental conditions may affect antibody performance

  • Native vs. denatured protein recognition can vary significantly

A comprehensive validation study of 614 commercial antibodies against 65 neuroscience-related proteins found that only 77% had a successful renewable antibody for Western blot, 75% for immunoprecipitation, and 54% for immunofluorescence . Extrapolating these findings suggests similar challenges would exist for antibodies targeting proteins identified from 2D-PAGE spots.

How can researchers integrate "Unknown protein from spot 447" findings with modern proteomics approaches?

To integrate findings from traditional 2D-PAGE-identified proteins with modern proteomics approaches:

• Connect Classical and Modern Identification:

  • Use the UniProt identifier (P80630) to link the historically identified "Unknown protein from spot 447" with current database annotations

  • Reconcile historical 2D-PAGE spot locations with contemporary protein maps

  • Reanalyze archival 2D-PAGE images with modern image analysis software

• Apply Multi-Omics Approaches:

  • Correlate protein-level findings with transcriptomic data

  • Use CRISPR/Cas9 technology to generate knockout models for functional studies

  • Apply protein-protein interaction studies to place the protein in functional networks

• Leverage Advanced MS Techniques:

  • Use the PEPPI-MS (Passively Eluting Proteins from Polyacrylamide gels as Intact species for MS) workflow to directly connect 2D-PAGE separation with top-down proteomics

  • Implement targeted proteomics approaches (PRM/MRM) for quantitative analysis

  • Apply cross-linking mass spectrometry to identify interaction partners

• Integration with Structural Biology:

  • Apply AlphaFold or similar AI tools to predict protein structure

  • Use structural predictions to inform functional hypotheses

  • Design experiments to test structure-based functional predictions

A recent study demonstrated that implementing the PEPPI-MS workflow enabled identification of over 1,000 proteoforms from a single gel region (≤50 kDa), highlighting the potential for connecting traditional gel-based approaches with modern MS-based proteomics .