At5g14590 Antibody

What is the At5g14590 gene and its corresponding protein in Arabidopsis thaliana?

At5g14590 is a gene located on chromosome 5 of the Arabidopsis thaliana genome. This gene encodes a protein with UniProt accession number Q8LPJ5. While specific functional information is limited in the available literature, antibodies against this protein are utilized in plant research to study protein expression and function in this model organism . The protein encoded by At5g14590 may be involved in important cellular processes in Arabidopsis, making it a target for investigation through antibody-based detection methods.

What are the recommended storage and handling conditions for At5g14590 antibodies?

Upon receipt, At5g14590 antibodies should be stored at -20°C or -80°C to maintain activity and functionality. It is crucial to avoid repeated freeze-thaw cycles as this can significantly compromise antibody performance. The antibodies are typically provided in a specialized storage buffer containing preservatives (0.03% Proclin 300) and stabilizers (50% Glycerol, 0.01M PBS, pH 7.4) that help maintain their structural integrity and binding capacity during long-term storage . For routine use, small working aliquots should be prepared to minimize freeze-thaw cycles of the stock solution.

What applications have been validated for At5g14590 antibodies?

According to available technical information, At5g14590 antibodies have been tested and validated for multiple applications including:

• Enzyme-Linked Immunosorbent Assay (ELISA)

• Western Blotting (WB)

These applications are commonly used to detect and quantify specific proteins in complex mixtures from plant tissues. When using these antibodies, it is important to follow the recommended protocols for each application to ensure accurate identification of the target antigen . The antibody has been developed specifically for research applications rather than diagnostic or therapeutic purposes.

What is the composition and production method of At5g14590 antibodies?

At5g14590 antibodies are polyclonal antibodies raised in rabbits using recombinant Arabidopsis thaliana At5g14590 protein as the immunogen . The antibodies are purified using antigen affinity chromatography to enhance specificity and reduce background signals. Key specifications include:

This production method ensures generation of antibodies that recognize multiple epitopes on the target protein, potentially increasing detection sensitivity compared to monoclonal alternatives.

How can researchers validate the specificity of At5g14590 antibodies?

Thorough validation of antibody specificity is essential for reliable experimental results. Based on established protocols for antibody validation in plant research, the following methodological approach is recommended:

• Genetic validation: Test the antibody in At5g14590 knockout/knockdown lines, which should show reduced or absent signal compared to wild-type plants .

• Immunoprecipitation-Mass Spectrometry (IP-MS): Perform immunoprecipitation followed by mass spectrometry analysis to identify all proteins captured by the antibody. The target At5g14590 protein should be abundantly detected .

• Multiple antibody comparison: When possible, compare results using alternative antibodies targeting different epitopes of the same protein to confirm consistent detection patterns .

• Batch testing: Verify consistency across different antibody lots to exclude potential clone contamination or production variability .

• Western blot analysis: Confirm the presence of a single band of the expected molecular weight in wild-type samples and its absence in knockout lines .

• Competition assays: Pre-incubate the antibody with recombinant At5g14590 protein, which should abolish specific binding in subsequent applications.

The importance of rigorous validation is highlighted by cases where well-established antibodies were found to predominantly bind unintended targets despite appearing specific in initial tests .

What approaches can identify and minimize cross-reactivity with At5g14590 antibodies?

Cross-reactivity presents a significant challenge in plant antibody research due to protein conservation across species and the presence of protein families with similar domains. To address this issue:

• Sequence similarity analysis: Perform bioinformatic analysis to identify Arabidopsis proteins with sequence similarity to At5g14590 that might cross-react with the antibody.

• Western blot testing against recombinant proteins: Express and purify related protein family members to test for cross-reactivity directly.

• Epitope mapping: Identify the specific regions recognized by the antibody and assess their uniqueness within the proteome using computational tools.

• Multi-tissue validation: Verify specificity across different tissue types, as protein modifications may alter antibody recognition patterns .

• Peptide competition assays: Use synthetic peptides corresponding to potential epitopes to determine which regions the antibody recognizes.

• Immunoprecipitation followed by mass spectrometry: This unbiased approach can reveal unexpected cross-reactive proteins, as demonstrated in studies where antibodies bound unintended targets despite appearing specific in conventional tests .

• Testing in heterologous expression systems: Express At5g14590 in systems like yeast or E. coli that lack plant proteins to establish baseline specificity.

What methods can optimize protein extraction for At5g14590 detection across different plant tissues?

Based on studies of mitochondrial proteome heterogeneity in Arabidopsis , tissue-specific optimization of protein extraction is crucial for consistent At5g14590 detection:

• Tissue-specific buffer formulations: Different tissues require distinct extraction buffers due to variations in cell wall composition, secondary metabolites, and endogenous proteases. For example:

  • Root tissue: Use grinding medium containing 0.45M sucrose and specific protease inhibitors

  • Reproductive tissues (flowers, siliques): May require specialized buffers that account for high levels of secondary metabolites

• Mechanical disruption optimization:

  • Soft tissues (seedlings): Brief homogenization in cold buffer

  • Tough tissues (stems, siliques): More rigorous grinding with mortar and pestle in liquid nitrogen

• Mitochondrial enrichment considerations:

  • When studying mitochondrial proteins, employ differential centrifugation followed by Percoll gradient purification

  • For tissues available in limited quantities (flowers, siliques), adapt small-scale isolation protocols originally developed for rice embryos

• Protein yield quantification:

  • Different tissues yield varying amounts of extractable protein

  • Reproductive tissues may yield 20-50 fold less protein than leaf tissue from equivalent starting material

• Sample pooling strategies:

  • For low-abundance tissues, consider pooling material from multiple plants

  • Use randomized experimental designs to minimize variation (as demonstrated in Supplementary Table S2 of research on mitochondrial proteome heterogeneity)

These methodological considerations ensure optimal protein extraction and detection across diverse tissue types, accounting for the heterogeneity observed in plant proteomes.

How can researchers integrate antibody-based detection with genetic manipulation approaches in Arabidopsis?

Combining antibody detection with genetic manipulation provides powerful validation and functional insights. Based on established methodologies in Arabidopsis research , an integrated approach includes:

• Generation of loss-of-function mutants:

  • CRISPR/Cas9 genome editing to create precise knockout lines

  • T-DNA insertion mutants (readily available through stock centers)

  • Zinc finger nucleases (ZFNs) for targeted mutagenesis with efficiencies of 33-69% as demonstrated in Arabidopsis genes

• Complementary expression systems:

  • Estrogen-inducible expression systems for controlled gene expression

  • Tissue-specific promoters to examine spatial requirements

• Multi-level validation protocol:

  • Transcript verification through RT-PCR

  • Protein detection using validated antibodies

  • Phenotypic analysis comparing wild-type and mutant lines

• Off-target assessment:

  • PCR amplification of potential off-target sites

  • Sequencing to verify the absence of unintended mutations

  • Antibody detection to confirm protein absence specifically in target genes

• Experimental workflow:

  • Generate primary transgenic plants through Agrobacterium floral dip transformation

  • Confirm transgene integration by hygromycin selection

  • Induce ZFN expression using 17β-estradiol in the T₁ generation

  • Verify mutations by restriction enzyme digestion followed by sequencing

  • Assess protein expression using validated antibodies in subsequent generations

This integrated approach ensures robust validation of antibody specificity while providing functional insights into At5g14590's biological role through genetic manipulation.

How are computational approaches enhancing antibody development and prediction for plant research?

Recent advances in computational approaches are revolutionizing antibody research applicable to plant science:

• Deep learning for epitope prediction:

  • AI models can predict antibody-antigen interactions with high accuracy

  • Tools like AF2Complex have demonstrated 90% accuracy in predicting successful antibody binding to target antigens

• De novo antibody design:

  • Generative AI approaches enable the design of antibodies targeting specific epitopes without prior binding data

  • Zero-shot antibody design methods can create entirely new antibodies based on antigen structure

• Structural biology integration:

  • Computational prediction of protein structure enables rational design of antibodies with improved specificity

  • 3D predicted structures of designed antibody binding domains reveal conformational variability but conserved interaction points with targets

• Application to plant systems:

  • While many computational tools were initially developed for biomedical applications, the same principles apply to plant proteins

  • Computational approaches can help select optimal immunogenic regions of plant proteins that are accessible and unique

• Quantitative validation metrics:

  • "Naturalness" metrics predict developability and immunogenicity characteristics of designed antibodies

  • Large-scale screening of computational designs (>1 million variants) enables selection of optimal binding properties

These computational approaches can accelerate the development of highly specific antibodies for challenging plant targets like At5g14590, potentially reducing the time and resources required for conventional antibody development.

What strategies can address reproducibility challenges in At5g14590 antibody experiments?

Ensuring reproducibility in antibody-based experiments requires systematic approaches:

• Comprehensive documentation protocol:

  • Record all antibody details: manufacturer, catalog number, lot number, dilution

  • Document all experimental conditions: buffers, incubation times, temperatures

  • Maintain detailed antibody validation records and standard operating procedures

• Standardized controls:

  • Include both positive controls (wild-type samples) and negative controls (knockout lines when available)

  • Use isotype controls to assess non-specific binding

  • Implement loading controls appropriate for the experimental system and normalization method

• Technical validation approaches:

  • Verify new antibody lots against previous lots before use in critical experiments

  • Perform parallel validations with alternative antibodies targeting the same protein

  • Run pilot experiments to optimize antibody concentrations for each new experimental setup

• Statistical rigor:

  • Employ biological and technical replicates to assess variability

  • Apply appropriate statistical tests based on experimental design

  • Consider power analyses to determine adequate sample sizes

• Data management:

  • Store raw data alongside processed results

  • Implement structured data repositories for long-term access

  • Use data visualization approaches that accurately represent both signals and variance

These methodological strategies directly address the reproducibility challenges highlighted in research on antibody specificity , where multiple verification methods proved necessary to confirm experimental findings.