The At1g11770 antibody targets the protein product of the At1g11770 locus, a gene in Arabidopsis thaliana. While the exact biological function of this protein remains uncharacterized in the provided sources, antibodies like this are typically used to study protein expression, localization, and interactions in plant tissues .
While no direct studies on At1g11770 are cited in the provided sources, analogous antibodies for Arabidopsis proteins are typically used for:
Western blotting: Detecting protein expression levels under experimental conditions.
Immunohistochemistry: Localizing proteins in plant tissues.
Functional studies: Investigating gene knockout or overexpression phenotypes .
No peer-reviewed studies on At1g11770 were identified in the provided sources.
Commercial data ([Source 3]) lacks mechanistic or functional details, highlighting the need for further experimental validation.
Specificity and cross-reactivity metrics (e.g., epitope mapping, validation in knockout models) are absent, a common limitation noted for some commercially available antibodies (e.g., AT1 receptor antibodies in ).
To advance understanding of At1g11770, researchers could:
At1g11770 is a gene locus on chromosome 1 of Arabidopsis thaliana, encoding a protein that functions within plant cellular processes. While specific information on At1g11770 is limited in the current search results, it's important to note that Arabidopsis gene naming follows a consistent pattern where "At" indicates Arabidopsis thaliana, "1g" denotes chromosome 1, and "11770" is the specific gene identifier. This naming convention is similar to other documented Arabidopsis genes such as AT1G11860, which encodes the glycine cleavage T-protein involved in the mitochondrial conversion of glycine to serine during photorespiratory pathways .
Antibodies against Arabidopsis proteins are commonly generated through strategic immunization protocols using either total protein extracts or purified protein antigens. For monoclonal antibody production, researchers often follow a systematic approach involving:
Antigen preparation: Using total proteins extracted from specific plant tissues (e.g., inflorescences) or purified target proteins
Immunization: Typically using mice as the host organism
Hybridoma development: Fusing antibody-producing B cells with myeloma cells
Screening: Initial antibody validation using Western blotting
Characterization: Determining tissue specificity and subcellular localization
This approach has been successfully implemented to generate libraries of monoclonal antibodies against Arabidopsis proteins, as demonstrated in studies where researchers created 61 monoclonal antibodies using total proteins from Arabidopsis inflorescences as antigens .
Plant protein antibodies serve multiple critical functions in Arabidopsis research:
Application | Methodology | Information Obtained |
---|---|---|
Protein Expression Analysis | Western Blot (WB) | Protein size, expression levels across tissues |
Localization Studies | Immunofluorescence Microscopy | Subcellular and tissue-specific localization |
Protein Purification | Immunoprecipitation (IP) | Isolation of target proteins and complexes |
Antigen Characterization | Mass Spectrometry (MS) following IP | Identification of precise antigens |
Developmental Studies | Immunohistochemistry | Protein expression during development |
Researchers have successfully employed these techniques to categorize antibodies based on expression patterns (tissue-specific, preferential, or broad expression) and to identify antigens recognized by specific antibodies .
Validating antibody specificity requires a multi-step approach to ensure reliable research outcomes:
Western Blot Analysis: Examine protein extracts from different tissues (leaves, stems, inflorescences) to confirm the antibody detects bands of expected molecular weight. Single-band detection suggests higher specificity, while multiple bands may indicate cross-reactivity or post-translational modifications .
Tissue Expression Profiling: Compare antibody reactivity across different organs to establish expression patterns (organ-specific, preferential, or broad expression). This helps categorize antibodies and validate their specificity for particular cellular contexts .
Knockout/Knockdown Controls: Test antibody reactivity in plants where the target gene has been silenced or knocked out, which should result in reduced or absent signal.
Immunoprecipitation followed by Mass Spectrometry: This approach can definitively identify the antigen recognized by the antibody, as demonstrated in studies where researchers enriched antigens using IP and subsequently identified them through MS analysis .
Proper experimental controls are essential for accurate interpretation of results:
Positive Controls: Include samples known to express the target protein at high levels, based on previous expression data. For instance, if the antibody shows higher reactivity in stem tissues, these samples should be included as positive controls .
Negative Controls:
Primary antibody omission
Secondary antibody only
Pre-immune serum (for polyclonal antibodies)
Tissues from knockout/knockdown plants
Loading Controls: Include detection of constitutively expressed proteins to normalize for loading variations.
Cross-Reactivity Controls: Test antibody against recombinant protein or closely related proteins to assess potential cross-reactivity.
Isotype Controls: For monoclonal antibodies, include an irrelevant antibody of the same isotype (e.g., IgM for CCRC M36 antibody) to control for non-specific binding .
Optimizing immunoprecipitation for plant proteins requires addressing specific challenges related to plant tissue composition:
Protein Extraction Optimization:
Use buffers containing appropriate detergents (e.g., CHAPS, Triton X-100)
Include protease inhibitors to prevent degradation
Optimize cell disruption methods for complete protein extraction
Antibody Binding Conditions:
Determine optimal antibody concentration through titration
Optimize incubation time and temperature (typically 4°C overnight)
Consider pre-clearing lysates to reduce non-specific binding
Protein A/G Bead Selection:
Elution and Analysis:
Compare different elution methods (pH, ionic strength, competitive)
Validate IP success by Western blot before proceeding to mass spectrometry
This approach has successfully identified antigens for several Arabidopsis antibodies, including FtsH protease 11 (AT5G53170), glycine cleavage T-protein (AT1G11860), and casein lytic proteinase B4 (AT2G25140) .
Studying protein-protein interactions using antibodies requires specialized approaches:
Co-Immunoprecipitation (Co-IP):
Optimize buffer conditions to maintain native protein complexes
Use mild detergents to preserve protein-protein interactions
Perform reciprocal Co-IPs when antibodies to multiple proteins are available
Validate interactions through Western blot and mass spectrometry
Proximity Ligation Assay (PLA):
Requires antibodies from different species or isotypes
Optimized for plant tissue sections or fixed cells
Provides spatial information about protein interactions
Immunofluorescence Co-localization:
Use combinations of antibodies with distinct fluorophores
Optimize fixation methods to preserve antigen accessibility
Apply advanced imaging techniques (confocal, super-resolution)
Crosslinking Immunoprecipitation (CLIP):
Stabilize transient interactions before extraction
Optimize crosslinking conditions for plant tissues
Reverse crosslinks before final analysis
These approaches can reveal functional interactions between the protein encoded by At1g11770 and other cellular components, providing insights into its biological role.
Variations in antibody reactivity can stem from multiple factors that require careful interpretation:
Biological Factors:
Developmental regulation of protein expression
Tissue-specific protein modifications
Protein degradation or processing
Protein complex formation affecting epitope accessibility
Technical Factors:
Fixation methods affecting epitope preservation
Buffer components interfering with antibody binding
Sample preparation techniques altering protein conformation
Antibody batch variations
Interpretative Framework:
Establish baseline reactivity across standard conditions
Document systematic variations across experimental parameters
Consider genetic background effects on protein expression
Analyze variations in the context of biological pathways
Understanding these variations is critical for distinguishing genuine biological effects from technical artifacts, particularly when examining complex plant systems where protein expression can be highly regulated by developmental and environmental factors .
When facing contradictory results with antibodies against plant proteins, researchers should implement a systematic troubleshooting approach:
Verify Antibody Specificity:
Revalidate antibody using knockout/knockdown controls
Perform epitope mapping to confirm recognition site
Consider testing multiple antibodies targeting different epitopes
Examine Experimental Conditions:
Standardize protein extraction methods across experiments
Control for post-translational modifications affecting epitope recognition
Evaluate buffer components that might interfere with antibody binding
Statistical Analysis:
Increase biological and technical replicates
Apply appropriate statistical tests to determine significance
Consider power analysis to ensure adequate sample size
Consider Interaction Effects:
Examine potential genetic background influences
Evaluate environmental conditions affecting protein expression
Assess developmental timing differences
Alternative Approaches:
Complement antibody data with transcript analysis
Use tagged protein expression for verification
Apply proteomics approaches for independent validation
Identifying the sources of inconsistency requires greater statistical power than detecting main effects, as interactions and modifiers can significantly impact experimental outcomes .
Studying post-translational modifications (PTMs) of plant proteins requires specialized antibody approaches:
Modification-Specific Antibodies:
Use antibodies that specifically recognize common PTMs (phosphorylation, glycosylation, ubiquitination)
Validate specificity using synthetic peptides with and without modifications
Consider generating custom antibodies against specific modified epitopes
Sequential Immunoprecipitation:
First IP with protein-specific antibody
Second IP with modification-specific antibody
Analysis by Western blot or mass spectrometry
2D-Gel Electrophoresis:
Separate proteins by charge and molecular weight
Detect with protein-specific antibody
Identify modified forms by shift patterns
Mass Spectrometry Integration:
Enrich target protein using the antibody
Analyze PTMs using high-resolution mass spectrometry
Map modifications to specific amino acid residues
This multi-faceted approach can reveal how PTMs regulate the function, localization, or stability of the protein encoded by At1g11770 under different conditions.
Quantitative analysis using antibodies requires careful attention to methodological details:
Standard Curve Generation:
Use purified recombinant protein at known concentrations
Establish linear detection range for each antibody
Generate standard curves for each experimental batch
ELISA Development:
Optimize antibody concentrations for coating and detection
Establish blocking conditions to minimize background
Validate assay specificity using knockout/knockdown samples
Western Blot Quantification:
Use gradient loading of standards on each blot
Apply appropriate normalization to loading controls
Use digital image acquisition within linear range
Statistical Considerations:
Perform power analysis to determine sample size requirements
Account for technical and biological variability
Apply appropriate statistical tests for comparisons
Assay Validation:
Determine assay precision (intra- and inter-assay variability)
Establish limits of detection and quantification
Confirm specificity using competitive inhibition
The CCRC M36 antibody against Arabidopsis Rhamnogalacturonan I, for example, has been validated for ELISA applications, demonstrating how plant antibodies can be effectively used for quantitative analysis when properly optimized .
Emerging technologies are expanding the potential applications of antibodies in plant research:
Single-Cell Proteomics:
Integration with microfluidics for cell-specific protein analysis
Combination with single-cell RNA-seq for multi-omics approaches
Development of ultrasensitive detection methods for low-abundance proteins
Advanced Imaging:
Super-resolution microscopy for subcellular localization
Expansion microscopy for enhanced spatial resolution
Live-cell imaging with membrane-permeable antibody fragments
Antibody Engineering:
Development of plant-optimized nanobodies
Creation of bispecific antibodies for complex detection
Generation of recombinant antibody libraries against plant proteomes
High-Throughput Applications:
Antibody arrays for proteome-wide profiling
Automated immunoprecipitation platforms
Integration with robotics for standardized protocols
These technological advances will enable more precise, sensitive, and comprehensive studies of plant proteins like that encoded by At1g11770, facilitating deeper understanding of their functions in plant biology.
Integrating antibody-based approaches with other omics technologies creates powerful research strategies:
Multi-Omics Integration:
Correlate protein levels (antibody detection) with transcript levels (RNA-seq)
Map protein interactions (Co-IP) to genetic interactions (synthetic genetics)
Connect protein localization (immunofluorescence) with metabolite distribution (metabolomics)
Systems Biology Approaches:
Use antibody-derived protein data to validate network models
Incorporate protein-level information into pathway analyses
Develop predictive models incorporating protein dynamics
Functional Genomics Connections:
Link antibody-detected protein levels to phenotypic outcomes
Connect protein interactions with genetic dependencies
Correlate protein modifications with functional changes
This integrative approach provides a comprehensive understanding of plant biology by connecting different layers of biological information, offering insights into how genes like At1g11770 contribute to plant development, physiology, and responses to environmental stimuli.