OFUT29 Antibody

What is OFUT29 Antibody and what is its target species?

OFUT29 Antibody is a polyclonal antibody raised in rabbits against recombinant Arabidopsis thaliana OFUT29 protein. The antibody specifically recognizes and binds to OFUT29 protein in Arabidopsis thaliana (Mouse-ear cress), making it a valuable tool for plant molecular biology research. The antibody corresponds to UniProt accession number Q8LPF8 and is designed for research applications including ELISA and Western Blot techniques. This reagent allows researchers to study protein expression, localization, and function in various experimental contexts involving Arabidopsis thaliana .

What are the optimal storage conditions for OFUT29 Antibody?

For maintaining optimal activity of OFUT29 Antibody, researchers should store the antibody at either -20°C or -80°C upon receipt. It is critical to avoid repeated freeze-thaw cycles as these can progressively degrade antibody performance. The antibody is supplied in a liquid form containing 50% glycerol and 0.01M PBS (pH 7.4) with 0.03% Proclin 300 as a preservative. When working with the antibody, aliquoting into single-use volumes is recommended to minimize freeze-thaw cycles. For short-term use during experiments, the antibody can be maintained at 4°C for up to one week, but should be returned to frozen storage for long-term preservation .

What applications has OFUT29 Antibody been validated for?

OFUT29 Antibody has been specifically validated for Enzyme-Linked Immunosorbent Assay (ELISA) and Western Blot (WB) applications. These techniques are foundational in protein research, with ELISA providing quantitative analysis of OFUT29 in solution and Western Blot enabling detection of the protein in complex mixtures after separation by gel electrophoresis. Researchers should note that while these are the validated applications, optimization may be required when adapting protocols to specific experimental conditions. Each application requires different working dilutions and optimization steps for successful implementation .

How should Western Blot protocols be optimized for OFUT29 detection?

When optimizing Western Blot protocols for OFUT29 detection in Arabidopsis samples, several critical factors require attention:

• Sample preparation: Plant tissues should be homogenized in buffer containing appropriate protease inhibitors to prevent degradation of OFUT29.

• Loading control selection: For plant samples, consider using antibodies against conserved proteins such as actin or tubulin as loading controls.

• Blocking optimization: Test both BSA and non-fat dry milk to determine optimal blocking conditions that minimize background while preserving specific signal.

• Antibody dilution: Begin testing with a 1:500 to 1:2000 dilution range for primary antibody incubation, then optimize based on signal-to-noise ratio.

• Detection method: For low abundance proteins like OFUT29, consider using enhanced chemiluminescence (ECL) systems or fluorescence-based detection for improved sensitivity.

The Western Blot procedure should incorporate sequential validation steps with appropriate controls to ensure specificity of the detected bands. Given that this is a polyclonal antibody, verifying the expected molecular weight is particularly important .

How can researchers troubleshoot non-specific binding when using OFUT29 Antibody?

Non-specific binding is a common challenge when working with polyclonal antibodies like OFUT29. To address this issue, researchers should implement a systematic troubleshooting approach:

• Increase blocking stringency: Extend blocking time or increase blocking agent concentration (5% BSA or milk instead of 3%).

• Optimize antibody concentration: Perform a dilution series (1:500, 1:1000, 1:2000, 1:5000) to find the optimal concentration that maintains specific signal while reducing background.

• Add detergents: Incorporate 0.1-0.3% Tween-20 in washing and antibody incubation buffers to reduce hydrophobic non-specific interactions.

• Pre-adsorption technique: For challenging applications, consider pre-adsorbing the antibody with proteins from non-target tissues to remove antibodies that bind to common epitopes.

• Increase salt concentration: Adding additional NaCl (up to 500mM) to washing buffers can help reduce ionic interactions contributing to non-specific binding.

Documentation of optimization parameters using a methodical approach will help establish reliable protocols for future experiments. This approach mirrors methods used in troubleshooting other plant-specific antibodies in research settings .

What validation strategies confirm OFUT29 specificity in novel experimental conditions?

When adapting OFUT29 Antibody to novel experimental conditions, multiple validation strategies should be employed to confirm specificity:

• Positive and negative controls: Include known OFUT29-expressing tissues alongside tissues where the protein is absent or minimally expressed.

• Peptide competition assay: Pre-incubate the antibody with excess purified OFUT29 peptide; a genuine signal should diminish or disappear in this condition.

• Knockout/knockdown validation: If available, utilize OFUT29 knockout or knockdown Arabidopsis lines to confirm antibody specificity.

• Molecular weight verification: Confirm that detected bands match the expected molecular weight of OFUT29 (~52 kDa).

• Orthogonal method comparison: Compare results from OFUT29 antibody detection with mRNA expression data or mass spectrometry results.

This comprehensive validation approach follows best practices established for antibody validation in research settings and ensures confidence in experimental results obtained with OFUT29 Antibody .

What experimental design is optimal for quantitative analysis of OFUT29 expression?

For rigorous quantitative analysis of OFUT29 expression, researchers should implement a robust experimental design that includes:

• Biological replication: Minimum of 3-5 biological replicates to account for natural variation in Arabidopsis samples.

• Technical replication: At least 2-3 technical replicates per biological sample to control for procedural variation.

• Standardization: Inclusion of standard curves using recombinant OFUT29 protein at known concentrations (5-500 ng/mL range).

• Normalization strategy: Utilize appropriate housekeeping proteins (e.g., actin, GAPDH) as internal controls.

• Statistical analysis plan: Define statistical approaches (e.g., ANOVA, t-tests) prior to experimentation, with appropriate multiple testing correction.

For optimal quantification in Western Blot applications, consider using fluorescence-based detection systems rather than chemiluminescence, as they provide a broader linear dynamic range. For ELISA applications, careful optimization of standard curves is essential for accurate quantification .

How can researchers address conflicting results when using OFUT29 Antibody?

When confronted with conflicting results using OFUT29 Antibody across different experiments or detection methods, researchers should implement a systematic troubleshooting approach:

• Method validation: Verify that each detection method was properly optimized and validated with appropriate controls.

• Sample preparation assessment: Evaluate whether different sample preparation methods might affect epitope availability or protein conformation.

• Cross-method comparison: Directly compare results from different methods (e.g., ELISA vs. Western Blot) using identical samples under standardized conditions.

• Epitope mapping consideration: Assess whether the conflicting results might reflect detection of different isoforms or post-translational modifications of OFUT29.

• Independent verification: Employ orthogonal methods such as mass spectrometry or mRNA analysis to resolve contradictions.

Documenting all experimental conditions meticulously is crucial for identifying variables that might contribute to discrepancies. This systematic approach allows researchers to determine whether conflicts represent technical issues or biologically meaningful phenomena .

How can OFUT29 Antibody be integrated into immunoprecipitation protocols?

Immunoprecipitation (IP) with OFUT29 Antibody, while not listed among validated applications, can be adapted with careful optimization:

• Lysis buffer selection: Use a gentle lysis buffer (e.g., 50 mM Tris-HCl pH 7.5, 150 mM NaCl, 1% NP-40, 0.5% sodium deoxycholate) with protease inhibitors to preserve protein-protein interactions.

• Pre-clearing step: Pre-clear lysates with Protein A or G beads to reduce non-specific binding.

• Antibody coupling: Consider covalently coupling OFUT29 Antibody to beads (using commercial kits) to avoid antibody contamination in the eluted sample.

• IP controls: Include IgG control immunoprecipitations and input samples.

• Validation of precipitated complexes: Confirm successful IP by Western Blot analysis of both the immunoprecipitated material and unbound fractions.

For co-immunoprecipitation applications, additional optimization may be required to identify buffer conditions that preserve OFUT29 interactions with partner proteins. Crosslinking approaches may be beneficial for capturing transient interactions .

What strategies enable comparative analysis of OFUT29 across plant developmental stages?

For comprehensive developmental analysis of OFUT29, researchers should implement a strategic experimental approach:

• Standardized sampling: Establish precise developmental stage definitions based on established Arabidopsis growth stage models.

• Tissue-specific extraction: Develop separate extraction protocols optimized for different tissue types (roots, leaves, flowers, siliques) to ensure consistent protein recovery.

• Quantitative detection: Utilize ELISA or quantitative Western Blot with fluorescent secondary antibodies for accurate quantification.

• Immunohistochemistry integration: Complement biochemical analyses with spatial information through immunohistochemistry of tissue sections from different developmental stages.

• Temporal resolution: Implement time-course experiments with sufficient temporal resolution to capture developmental transitions.

This approach allows researchers to create comprehensive expression profiles of OFUT29 across development. The data should be presented as normalized expression values with appropriate statistical analysis to highlight significant developmental changes .

What statistical approaches are recommended for analyzing OFUT29 expression data?

For robust statistical analysis of OFUT29 expression data, researchers should consider:

• Data normalization: Transform raw data using appropriate methods (log transformation for Western Blot densitometry; standard curve interpolation for ELISA).

• Outlier detection: Apply statistical tests (e.g., Grubb's test) to identify and appropriately handle outliers.

• Statistical testing: Select appropriate tests based on experimental design:

  • For two-group comparisons: t-test (parametric) or Mann-Whitney (non-parametric)

  • For multiple groups: ANOVA with post-hoc tests (e.g., Tukey's HSD) or Kruskal-Wallis

  • For time courses: repeated measures ANOVA or mixed-effects models

• Multiple testing correction: Apply Benjamini-Hochberg or Bonferroni correction when performing multiple comparisons.

• Power analysis: Calculate statistical power to ensure sufficient sample size for detecting biologically meaningful differences.

These approaches should be documented in detail following standards similar to those used in serological antibody studies, as exemplified in the ROC analyses methodology described for other antibody-based detection systems .

How should researchers interpret variation in OFUT29 detection across experimental replicates?

Interpretation of variation in OFUT29 detection requires careful consideration of multiple factors:

• Sources of variation: Distinguish between biological variation (inherent differences between samples) and technical variation (differences due to experimental procedures).

• Coefficient of variation (CV) assessment: Calculate %CV for technical replicates; values >20% warrant investigation of methodological issues.

• Biological context: Evaluate whether observed variation correlates with biological parameters (e.g., developmental stage, stress conditions).

• Visual data representation: Present data with appropriate visualization of variation (e.g., box plots, scatter plots with individual data points).

• Reference ranges: Establish expected ranges of variation for OFUT29 in standard samples to contextualize experimental results.

The approach to variation analysis should mirror methods used in antibody validation studies, where reproducibility is assessed using R² and coefficient of variation calculations, as described in serological antibody detection methods .

What are the recommended working parameters for different applications of OFUT29 Antibody?

*Applications requiring additional optimization beyond validated methods

This table provides starting parameters that should be optimized for each specific experimental context. Researchers should document optimization steps and final working conditions for reproducibility .

What are common challenges with OFUT29 Antibody and their solutions?

This troubleshooting guide provides a framework for addressing common challenges when working with polyclonal antibodies such as OFUT29 Antibody. Each solution should be tested systematically to identify the optimal conditions for specific experimental setups .