At5g08680 Antibody

What is the At5g08680 gene and why develop antibodies against its product?

At5g08680 encodes a protein with ATP binding and helicase activity in Arabidopsis thaliana. Developing antibodies against this protein enables researchers to study its expression patterns, subcellular localization, protein-protein interactions, and functional role in plant development. The methodological approach requires first characterizing the target protein's biochemical properties to determine optimal epitope selection. When designing experiments, researchers should consider using both monoclonal and polyclonal antibodies for validation, as each offers distinct advantages in specificity and sensitivity for different experimental applications.

What expression systems are recommended for producing At5g08680 antibodies?

For optimal production of At5g08680 antibodies, expression in human HEK293F cells has demonstrated significant advantages for plant protein-directed antibodies requiring complex post-translational modifications. The methodological approach involves:

• Cloning the At5g08680 sequence into appropriate expression vectors

• Transfecting the constructs into HEK293F cells with a 1:1.5 molar ratio of heavy and light chain plasmids

• Culturing cells in SMM 293-TII medium at 310K and 5% CO₂

• Collecting supernatants after 5 days

• Purifying through 0.22 μm membrane filtration

• Further purification via protein A chromatography and size-exclusion chromatography

This system typically yields 5-10 mg/liter of purified antibody with proper conformation for plant protein recognition .

How can I validate the specificity of At5g08680 antibodies?

The methodological approach for validating At5g08680 antibody specificity should incorporate multiple complementary techniques:

Comparing recognition patterns between the target antibody and a commercially available reference can provide additional validation. Cross-reactivity testing against related Arabidopsis proteins should be performed to ensure specificity .

How do I optimize antibody selection strategies for At5g08680 protein variant discrimination?

For discriminating between At5g08680 protein variants or post-translational modifications, implement a parametric selection strategy combining Box-Cox data transformation with statistical testing. The methodological workflow involves:

• Transform antibody response data using optimal Box-Cox parameters (λ within -4 to 4 range)

• Determine if data follows single or bimodal distribution patterns

• For bimodal distributions, establish optimal cut-off points by maximizing chi-squared statistics

• For single population distributions, apply linear regression models with and without the variant as covariate

• Compare models using Wilk's likelihood ratio test at 5% significance threshold

• For non-parametric datasets, implement Mann-Whitney tests to compare median values

• Adjust all p-values using Benjamini-Yekutieli procedure (FDR 5%)

This approach significantly improves discrimination power between protein variants compared to standard selection methods, as evidenced by increased AUC values from 0.68 to 0.80 in similar applications .

What are the optimal experimental designs for studying At5g08680 protein interactions using antibody-based approaches?

To study At5g08680 protein interactions, implement a multi-faceted experimental design that combines:

• Co-immunoprecipitation with At5g08680 antibodies followed by mass spectrometry

• Proximity labeling using antibody-enzyme fusion constructs (BioID or APEX2)

• Surface plasmon resonance (SPR) assays with the following parameters:

  • Sensor chip: CM5 with N-hydroxysuccinimide and N-ethyl-N-(3-diethylaminopropyl) carbodiimide activation

  • Running buffer: 10 mM HEPES, 150 mM NaCl, 3 mM EDTA

  • Flow rate: 30 μL/minute

  • Baseline acquisition: 100 seconds

  • Antibody injection: Serial dilutions at 30 μL/minute for 100 seconds

  • Analysis: Determination of kon/koff ratios to calculate Kd values

For complex interaction networks, combine these approaches with computational modeling. This integrative strategy provides higher confidence in identifying true interactors versus false positives that may appear in single-method approaches .

What strategies should I employ when antibodies detect contradictory localization patterns for At5g08680?

When facing contradictory localization data, implement the following systematic troubleshooting approach:

• Antibody validation reassessment:

  • Verify epitope accessibility in different fixation conditions

  • Test multiple antibodies targeting different epitopes of At5g08680

  • Perform peptide competition assays to confirm specificity

• Technical optimization:

  • Compare different fixation methods (paraformaldehyde, methanol, acetone)

  • Adjust permeabilization conditions (0.1-0.5% Triton X-100 or saponin)

  • Optimize antibody concentration and incubation times

• Biological verification:

  • Implement fluorescent protein tagging as complementary approach

  • Consider developmental stage and tissue-specific expression

  • Evaluate condition-dependent localization (stress, developmental stage)

• Super-resolution microscopy techniques:

  • STED or STORM imaging for nanoscale resolution

  • Live-cell imaging to track dynamic localization

This methodological approach has successfully resolved similar contradictions in plant protein localization studies and provides a framework for reconciling apparently conflicting data .

What is the recommended protocol for using At5g08680 antibodies in chromatin immunoprecipitation (ChIP) assays?

For optimal ChIP protocol using At5g08680 antibodies:

• Crosslinking and chromatin preparation:

  • Crosslink plant tissue with 1% formaldehyde for 10 minutes

  • Quench with 0.125 M glycine for 5 minutes

  • Homogenize in extraction buffer (50 mM HEPES pH 7.5, 150 mM NaCl, 1 mM EDTA, 1% Triton X-100, 0.1% sodium deoxycholate, protease inhibitors)

  • Sonicate to generate 200-500 bp fragments

• Immunoprecipitation:

  • Pre-clear chromatin with protein A/G beads for 1 hour at 4°C

  • Incubate with 2-5 μg of At5g08680 antibody overnight at 4°C

  • Add protein A/G beads and incubate for 2 hours

  • Wash with increasingly stringent 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

• Controls:

  • Input chromatin (non-immunoprecipitated)

  • IgG control (non-specific antibody)

  • Positive control (known target gene)

  • Negative control (non-target region)

This protocol has been optimized to minimize background while maximizing signal-to-noise ratio for plant transcription factor studies .

How can I develop a quantitative ELISA assay for measuring At5g08680 protein levels in plant extracts?

The development of a quantitative ELISA for At5g08680 protein detection requires:

• Plate preparation:

  • Coat 96-well plates with capture antibody (1-5 μg/mL) in carbonate buffer pH 9.6

  • Incubate overnight at 4°C

  • Wash with PBST (PBS + 0.05% Tween-20)

  • Block with 1-5% BSA or non-fat milk for 1 hour at 37°C

• Sample preparation:

  • Extract plant tissues in optimized buffer (50 mM Tris-HCl pH 7.5, 150 mM NaCl, 0.1% Triton X-100, protease inhibitors)

  • Clarify by centrifugation (14,000×g, 10 minutes, 4°C)

  • Prepare serial dilutions of purified At5g08680 protein as standards

• Detection system:

  • Incubate samples and standards for 30 minutes at 37°C

  • Wash 3× with PBST

  • Add HRP-conjugated detection antibody (1:1000-1:5000)

  • Incubate for 30 minutes at 37°C

  • Wash 5× with PBST

  • Add TMB substrate and incubate for 15 minutes in darkness

  • Stop reaction with 2M H₂SO₄

  • Read absorbance at 450 nm

• Data analysis:

  • Generate standard curve using 4-parameter logistic regression

  • Calculate EC₅₀ values for quantitative comparisons

  • Run all samples in triplicate to ensure reproducibility

This methodology provides detection sensitivity in the nanogram range with high specificity when optimized properly .

What approaches should I use to characterize At5g08680 antibody affinity and specificity?

A comprehensive characterization of At5g08680 antibody properties requires multiple complementary approaches:

For most accurate characterization, combine these approaches and determine consensus values. SPR analysis has demonstrated particular utility by allowing determination of association/dissociation constants that predict in vivo efficacy. Proper affinity characterization enables selection of the most suitable antibodies for specific applications .

How can I address non-specific binding issues with At5g08680 antibodies in plant tissue extracts?

To systematically troubleshoot non-specific binding:

• Optimization of blocking agents:

  • Test multiple blocking agents (BSA, non-fat milk, casein, commercial blockers)

  • Determine optimal concentration (1-5%)

  • Evaluate blocking time (1-16 hours)

• Buffer optimization:

  • Increase detergent concentration (0.05-0.5% Tween-20)

  • Add competing proteins (0.1-1% BSA in wash/incubation buffers)

  • Test different ionic strengths (100-500 mM NaCl)

• Antibody optimization:

  • Pre-absorb antibody with plant extract from knockout lines

  • Purify antibody using affinity chromatography against the specific epitope

  • Optimize antibody concentration through titration experiments

• Sample preparation modifications:

  • Add protease inhibitors to prevent degradation products

  • Optimize extraction buffer composition

  • Pre-clear samples with Protein A/G beads

Implementation of these approaches in systematic fashion can significantly reduce background while maintaining specific signal detection, as demonstrated in similar plant protein studies where background was reduced by >80% following optimization .

What statistical approaches should I use to analyze quantitative data from At5g08680 antibody-based experiments?

For robust statistical analysis of antibody-based experimental data:

• For dichotomization of antibody response data:

  • Implement optimal cut-off determination by maximizing chi-squared statistics

  • Apply Benjamini-Yekutieli procedure to control false discovery rate (FDR 5%)

  • Use contingency table analysis for comparing experimental groups

• For continuous response data:

  • Apply Box-Cox transformations to normalize distributions (λ range: -4 to 4)

  • Implement parametric tests (t-tests, ANOVA) for normally distributed data

  • Use non-parametric alternatives (Mann-Whitney, Kruskal-Wallis) when normality cannot be achieved

• For predictive model building:

  • Implement Super-Learner approach combining multiple classifiers:

    • Logistic regression models with main effects

    • Random Forest algorithms

    • Linear/quadratic discriminant analysis

    • Gradient boosting methods

  • Evaluate model performance using AUC metrics with 95% confidence intervals

• For multivariate correlation analysis:

  • Calculate Spearman's correlation coefficients between antibody responses

  • Apply hierarchical clustering to identify patterns

  • Implement dimension reduction techniques (PCA, t-SNE) for visualization

These statistical approaches have demonstrated superior performance in antibody-based studies, with AUC improvements from 0.68 to 0.80 in similar experimental systems .

How should I design controls for At5g08680 antibody experiments using transgenic Arabidopsis lines?

A comprehensive control strategy for antibody experiments with transgenic Arabidopsis should include:

• Genetic controls:

  • Wild-type Col-0 (positive control)

  • T-DNA insertion or CRISPR knockout of At5g08680 (negative control)

  • Complementation lines (rescue control)

  • Overexpression lines (high expression control)

  • Tagged protein lines (epitope validation)

• Technical controls:

  • Secondary antibody only (background control)

  • Pre-immune serum (non-specific binding control)

  • Peptide competition (epitope specificity control)

  • Immunoprecipitation with non-relevant antibody (procedure control)

• Experimental design considerations:

  • Include biological replicates (minimum n=3)

  • Use multiple independent transgenic lines for each construct

  • Implement randomization and blinding where possible

  • Include developmental stage controls for developmental regulators

• Validation approaches:

  • Orthogonal detection methods (RT-qPCR, RNA-seq, proteomics)

  • Multiple antibodies targeting different epitopes

  • Different visualization methods (Western blot, immunofluorescence)

This multi-layered control strategy significantly reduces the risk of misinterpretation and provides robust validation of experimental findings .

How can I utilize At5g08680 antibodies for studying protein-protein interactions in plant signaling networks?

To leverage At5g08680 antibodies for protein interaction studies, implement a multi-modal approach:

• Antibody-based proximity labeling:

  • Conjugate At5g08680 antibody to promiscuous biotin ligase (BioID2)

  • Introduce into plant cells via protein delivery methods

  • Identify biotinylated proteins by streptavidin pulldown and mass spectrometry

  • Validate interactions through reciprocal Co-IP experiments

• Advanced co-immunoprecipitation approaches:

  • Perform tandem affinity purification using At5g08680 antibody

  • Implement crosslinking-assisted immunoprecipitation for transient interactions

  • Use native versus denaturing conditions to distinguish direct and indirect interactions

  • Analyze by quantitative mass spectrometry with SILAC or TMT labeling

• In situ interaction detection:

  • Proximity ligation assay (PLA) using At5g08680 antibody and antibodies against candidate interactors

  • Förster resonance energy transfer (FRET) using fluorophore-conjugated antibodies

  • BiFC validation of identified interactions

• Network analysis:

  • Integrate data using statistical algorithms to filter low-confidence interactions

  • Apply machine learning approaches to predict additional interaction partners

  • Validate hub proteins through genetic and biochemical approaches

This integrated approach overcomes limitations of individual methods and has successfully identified previously unknown interactions in comparable plant signaling studies .

What are the best practices for using At5g08680 antibodies in plant chromatin studies?

For optimal application of At5g08680 antibodies in chromatin research:

• ChIP-seq protocol optimization:

  • Crosslink tissues with 1% formaldehyde (10 minutes)

  • Sonicate to generate 200-300 bp fragments (verified by Bioanalyzer)

  • Use 2-5 μg antibody per 25 μg chromatin

  • Include input, IgG, and positive controls

  • Prepare libraries using low-input methods for limited material

  • Sequence with minimum 20 million reads per sample

• CUT&RUN or CUT&Tag adaptations:

  • Attach nuclei to ConA beads

  • Incubate with At5g08680 antibody (1:100 dilution)

  • Add pA-MNase or pA-Tn5

  • Release and prepare fragments for sequencing

  • This approach requires 10× less material than ChIP

• Combinatorial approaches:

  • ChIP-reChIP for co-occupancy studies

  • ChIP-MS for identifying chromatin-associated protein complexes

  • ChIP-bisulfite sequencing for epigenetic correlation

• Data analysis considerations:

  • Use MACS2 with plant-optimized parameters for peak calling

  • Implement IDR analysis for replicate consistency

  • Correlate binding with gene expression data

  • Perform motif analysis for co-regulatory factors

These methodologies have successfully elucidated the chromatin functions of plant regulatory proteins with sensitivity and specificity superior to traditional approaches .

How can I adapt trispecific antibody technologies for studying At5g08680 function in different subcellular compartments?

To develop trispecific antibodies for studying At5g08680 in multiple cellular compartments:

• Design strategy:

  • Engineer constructs in DVD-Ig format with full IgG1 antibody backbone

  • Select complementary scFvs targeting:

    • At5g08680 protein

    • Compartment-specific marker protein

    • Interacting protein of interest

  • Connect domains using GGGGSGGGGS linkers

• Expression and purification:

  • Clone heavy and light chain sequences into suitable vectors

  • Co-transfect into HEK293F cells with 1:1.5 molar ratio

  • Culture in SMM 293-TII medium at 310K and 5% CO₂

  • Harvest supernatant after 5 days

  • Purify via Protein A and size-exclusion chromatography

• Validation assays:

  • ELISA binding to individual antigens

  • Surface plasmon resonance for binding kinetics

  • Immunofluorescence to confirm compartment specificity

  • Co-localization analysis with known markers

• Application in plant systems:

  • Protein transfection methods for live-cell applications

  • Fixed-cell imaging for spatial organization studies

  • Pulldown assays for compartment-specific interactome analysis

This trispecific approach enables simultaneous tracking of At5g08680 across multiple compartments and has demonstrated superior sensitivity compared to conventional antibodies in similar systems with expected yields of 5-10 mg/liter .