CYP76C1 Antibody

What is CYP76C1 and why are antibodies against it important for plant research?

CYP76C1 is a member of the cytochrome P450 monooxygenase family in Arabidopsis thaliana, specifically belonging to the CYP76C subfamily. It functions as a multifunctional enzyme that catalyzes a cascade of oxidation reactions and serves as the major linalool metabolizing oxygenase in Arabidopsis flowers . CYP76C1 plays a crucial role in:

• Modulating linalool emission and converting it into more oxidized derivatives

• Formation of volatile and soluble linalool oxides including 8-hydroxy, 8-oxo, and 8-COOH-linalool

• Production of lilac aldehydes and alcohols

• Contributing to plant defense against floral antagonists and pests

• Metabolism of herbicides belonging to the class of phenylurea
  Antibodies against CYP76C1 are valuable research tools for:

• Detecting and quantifying CYP76C1 protein expression in different plant tissues

• Studying protein localization (CYP76C1 is expressed in filaments, anthers, stamen, and petals upon anthesis)

• Investigating the role of CYP76C1 in plant defense mechanisms

• Examining protein-protein interactions in terpenoid biosynthetic pathways

What detection methods are compatible with CYP76C1 antibodies?

Based on patterns observed with other cytochrome P450 antibodies, CYP76C1 antibodies would likely be compatible with:

• Western blotting (WB): For quantitative detection of CYP76C1 protein levels in plant extracts

• Immunohistochemistry (IHC): For localizing CYP76C1 in plant tissue sections, especially in flower tissues where expression is highest

• Immunoprecipitation (IP): For isolating CYP76C1 protein complexes

• Flow cytometry (FCM): For analyzing CYP76C1 expression at the cellular level

• Immunofluorescence (IF): For subcellular localization studies, particularly important as CYP76C1 is likely membrane-associated like other P450 enzymes
  Detection protocols should be optimized based on the antibody format (polyclonal, monoclonal, or recombinant) and the specific plant tissue being analyzed.

How can I validate the specificity of a CYP76C1 antibody?

Comprehensive validation of CYP76C1 antibodies should include:

• Positive controls: Use tissue samples with known CYP76C1 expression (e.g., Arabidopsis flower tissues, particularly petals and anthers)

• Negative controls:

  • CYP76C1 knockout/mutant lines (e.g., cyp76c1-1 and cyp76c1-2 insertion lines)

  • Tissues with minimal CYP76C1 expression

  • Pre-immune serum controls for polyclonal antibodies

• Cross-reactivity assessment: Test against recombinant proteins from the closely related CYP76C subfamily members (CYP76C2, CYP76C3, and CYP76C4), which share significant sequence homology and have overlapping functions

• Western blot analysis: Verify a single band at the expected molecular weight (~55-60 kDa for CYP76C1)

• Immunoblotting with recombinant protein: Express and purify recombinant CYP76C1 to serve as a definitive positive control

• Gene expression correlation: Compare protein detection with transcript levels using qRT-PCR

• Peptide competition assay: Pre-incubate the antibody with the immunizing peptide to confirm binding specificity

What factors should be considered when choosing between monoclonal and polyclonal antibodies for CYP76C1 research?

• Starting with polyclonal antibodies for detection and localization studies

• Developing monoclonal antibodies for studies requiring distinction between CYP76C subfamily members

• Using synthetic peptide antigens corresponding to unique regions of CYP76C1 to improve specificity

How can I optimize immunohistochemistry protocols for studying CYP76C1 localization in flower tissues?

Optimizing IHC for CYP76C1 in flower tissues requires special consideration:

• Tissue preparation:

  • Use fresh flowers at anthesis stage, when CYP76C1 expression peaks

  • Fix tissues in 4% paraformaldehyde to preserve protein structure while maintaining antigenicity

  • Consider paraffin embedding for structural preservation, following protocols established for cytochrome P450 enzymes in plant tissues

• Antigen retrieval:

  • Heat-induced epitope retrieval may be necessary for formalin-fixed tissues

  • Test citrate buffer (pH 6.0) and Tris-EDTA buffer (pH 9.0) to determine optimal retrieval conditions

• Blocking and antibody incubation:

  • Use 5% normal serum from the same species as the secondary antibody

  • Include 0.1-0.3% Triton X-100 to improve antibody penetration

  • Optimize primary antibody dilution (typically start at 1:100 to 1:500)

  • Extend incubation times (overnight at 4°C) for better penetration into flower tissues

• Detection systems:

  • For fluorescence detection, select fluorophores with emission spectra distinct from flower autofluorescence

  • For DAB detection, include H₂O₂ pretreatment to block endogenous peroxidases in plant tissues

• Controls:

  • Include wild-type and cyp76c1 mutant flowers as positive and negative controls

  • Use tissues from complemented/overexpression line (35S:CYP76C1) as additional positive control

  • Include no primary antibody controls to assess non-specific binding

• Counterstaining:

  • Use DAPI to visualize nuclei and assist in identifying specific cell types

  • Consider propidium iodide for cell wall visualization in fluorescence microscopy
    Based on successful localization of CYP76C1 expression using promoter-GUS fusions, focus on filaments, anthers, stamen, and petals, where CYP76C1 is specifically expressed .

What approaches can I use to study protein-protein interactions involving CYP76C1 in terpenoid biosynthesis?

Several complementary approaches can be employed:

• Co-immunoprecipitation (Co-IP):

  • Use anti-CYP76C1 antibodies to pull down protein complexes from flower extracts

  • Analyze co-precipitated proteins by mass spectrometry

  • Focus on potential partners such as:

    • TPS10 and TPS14 (linalool synthases co-expressed with CYP76C1)

    • UGT85A3 (glycosyl transferase co-expressed with CYP76C1)

    • Other enzymes in terpenoid pathways

• Proximity-dependent biotin labeling (BioID/TurboID):

  • Generate fusion constructs of CYP76C1 with biotin ligase

  • Express in Arabidopsis to biotinylate proximal proteins

  • Purify biotinylated proteins and identify by mass spectrometry

• Yeast two-hybrid screening:

  • Use CYP76C1 as bait to screen for interacting proteins

  • Validate interactions with targeted assays for specific candidates

• Bimolecular fluorescence complementation (BiFC):

  • Split fluorescent protein fusions with CYP76C1 and candidate interactors

  • Express in plant cells to visualize interactions in vivo

  • Focus on co-expressed genes identified through transcriptomic analysis

• Surface plasmon resonance (SPR) or microscale thermophoresis (MST):

  • Analyze direct protein-protein interactions using purified components

  • Determine binding affinities and kinetics

• Chemical crosslinking coupled with mass spectrometry:

  • Capture transient interactions in native plant tissues

  • Identify crosslinked peptides to map interaction surfaces
    When designing these experiments, consider that:

• CYP76C1 is membrane-associated and likely localized to the endoplasmic reticulum

• Interactions may be dynamic and dependent on substrate availability

• CYP76C1 may participate in metabolons (multi-enzyme complexes) for efficient substrate channeling

How can I use CYP76C1 antibodies to investigate differences between wild-type and mutant phenotypes?

Antibody-based approaches can provide valuable insights into CYP76C1 function by comparing wild-type plants, cyp76c1 mutants, and complemented lines:

• Quantitative protein analysis:

  • Use Western blotting to confirm absence of CYP76C1 protein in knockout lines

  • Quantify expression levels in wild-type flowers and complemented/overexpression lines

  • Compare protein abundance across different floral tissues and developmental stages

• Immunolocalization studies:

  • Map CYP76C1 expression patterns in wild-type flowers

  • Confirm absence of signal in mutant lines as negative control

  • Assess potential compensatory changes in localization of related enzymes (e.g., CYP76C3, CYP76C4)

• Co-localization with metabolites:

  • Combine immunohistochemistry with metabolite imaging techniques

  • Correlate CYP76C1 localization with accumulation of linalool derivatives

  • Compare metabolite profiles between wild-type and mutant tissues

• Stress response analysis:

  • Expose plants to herbivores or pathogen stress

  • Monitor changes in CYP76C1 abundance and localization

  • Compare defense responses between genotypes

• Developmental timing assessment:

  • Track CYP76C1 expression through flower development

  • Compare with the temporally activated expression pattern seen with promoter-GUS fusions

  • Correlate protein levels with volatile emission profiles

• Enzyme complex formation:

  • Use antibodies for co-immunoprecipitation studies

  • Compare protein interaction partners between genotypes

  • Identify potential alterations in metabolic complex formation
    These approaches should be coordinated with metabolomic analyses, as cyp76c1 mutants show altered profiles of linalool, 8-hydroxy-linalool, 8-oxo-linalool, 8-COOH-linalool, and lilac compounds .

How can I overcome difficulties in detecting low-abundance CYP76C1 protein in plant tissues?

Detecting low-abundance membrane-associated proteins like CYP76C1 presents several challenges:

• Sample preparation optimization:

  • Focus on tissues with highest expression: petals and anthers at anthesis

  • Use sodium carbonate to strip extrinsic proteins from microsomal membranes without affecting transmembrane proteins like CYP76C1

  • Optimize microsomal fraction isolation to concentrate membrane proteins

  • Consider using protease inhibitor cocktails specifically optimized for plant tissues

• Signal amplification strategies:

  • Use high-sensitivity detection systems such as chemiluminescent substrates with enhanced formulations

  • Consider tyramide signal amplification (TSA) for immunohistochemistry

  • Try biotin-streptavidin amplification systems for weak signals

• Immunoprecipitation enrichment:

  • Concentrate CYP76C1 through immunoprecipitation before detection

  • Scale up starting material to improve yield of low-abundance proteins

• Alternative antibody formats:

  • Consider using single-chain fragment variable antibodies (scFv) which can be coated onto surfaces at higher density than conventional antibodies

  • Biotinylated antibody fragments may improve detection sensitivity

• Specialized detection platforms:

  • Consider using piezoimmunosensors for ultrasensitive detection of CYP76C1

  • Explore quartz crystal microbalance (QCM) biosensors which have demonstrated excellent sensitivity (detection limit of 2.2 ± 0.9 nM) for cytochrome P450 enzymes

• Expression system controls:

  • Use a CYP76C1 overexpression line as a positive control

  • Include microsomes from expression systems lacking CYP76C1 as negative controls

What strategies can minimize cross-reactivity with other CYP76 family members?

The CYP76C subfamily in Arabidopsis contains eight genes with significant sequence homology , making antibody specificity challenging. To minimize cross-reactivity:

• Strategic epitope selection:

  • Target unique regions of CYP76C1 not shared with other family members

  • Perform sequence alignment of all CYP76C proteins to identify divergent regions

  • Avoid conserved functional domains within the P450 family

• Antibody purification techniques:

  • Use immunogen affinity purification to isolate antibodies specific to the target epitope

  • Consider sequential affinity purification: first positive selection with CYP76C1 peptide, then negative selection using peptides from related family members

• Validation with multiple techniques:

  • Verify specificity using recombinant proteins of all CYP76C family members

  • Test antibodies on tissues from knockout lines of each CYP76C gene

  • Confirm that expression patterns match transcript data from qRT-PCR or RNA-seq studies

• Monoclonal antibody development:

  • Screen hybridoma clones against multiple CYP76C proteins to identify those with minimal cross-reactivity

  • Develop monoclonal antibodies against specific CYP76C1 epitopes, following approaches used for other P450 enzymes

• Alternative recognition strategies:

  • Consider using aptamers or nanobodies with potentially higher specificity than conventional antibodies

  • Explore recombinant antibody technologies such as phage display to select for highly specific binders

• Computational prediction:

  • Use epitope prediction tools to identify regions with maximal antigenic disparity between CYP76C family members

  • Design synthetic peptides based on these predictions for antibody generation

• Genetic verification:

  • Always confirm results using genetic approaches (mutants, overexpression lines)

  • Verify that the absence of signal in cyp76c1 mutants is not compensated by increased expression of other family members

What controls are essential when using CYP76C1 antibodies in experimental workflows?

A robust control strategy for CYP76C1 antibody experiments should include:

• Microsomal fractions from E. coli with and without CYP76C1 expression

• Samples from CRISPR-edited plants with epitope-tagged endogenous CYP76C1

• Transgenic lines expressing CYP76C1 with point mutations in key functional residues

How should I interpret contradictory results between transcript levels and protein abundance for CYP76C1?

Discrepancies between CYP76C1 transcript and protein levels are not uncommon and may reflect important biological mechanisms. Consider these analytical approaches:

• Verify technical aspects:

  • Confirm antibody specificity through appropriate controls

  • Assess sample preparation methods for potential protein degradation

  • Validate primers and amplification conditions for transcript analysis

  • Consider whether the protein or transcript measurement is more reliable in your system

• Biological explanations to investigate:

  Observation	Potential Biological Explanation	Investigation Approach
  High transcript / Low protein	- Post-transcriptional regulation - miRNA-mediated transcript degradation - Protein degradation/turnover - Inefficient translation	- Analyze via polysome profiling - Examine miRNA regulation patterns - Use proteasome inhibitors - Pulse-chase experiments
  Low transcript / High protein	- High protein stability - Transcriptional regulation - Sampling at different points in regulatory cycle	- Protein half-life assessment - Time-course analysis - Cycloheximide chase experiments
  Tissue-specific discrepancies	- Differential post-transcriptional regulation - Tissue-specific translation efficiency	- Cell type-specific analysis - Ribosome profiling

• Integrative analysis approaches:

  • Correlate with metabolite profiles of linalool derivatives

  • Examine under different stress conditions (herbivore exposure)

  • Compare with expression patterns of interacting proteins

  • Analyze protein localization in relation to transcript distribution

• Statistical considerations:

  • Use appropriate normalization methods for both transcript and protein data

  • Apply correlation analyses with significance testing

  • Consider non-linear relationships between transcript and protein levels

  • Use time-lagged correlation to account for delays between transcription and translation

• Known mechanisms for CYP76C1:

  • Focus on the known temporal expression pattern during flower opening and anthesis

  • Consider that CYP76C1 is expressed in specific floral tissues (stamen, petals)

  • Evaluate potential post-transcriptional regulation similar to other defense-related genes

How can I integrate CYP76C1 antibody data with metabolomic analyses for comprehensive functional characterization?

Integrating protein-level data with metabolomics provides powerful insights into CYP76C1 function:

• Correlation analysis workflows:

  • Measure CYP76C1 protein levels across tissues/conditions using quantitative Western blotting

  • Perform targeted metabolomics focusing on linalool and its derivatives (8-hydroxy-linalool, 8-oxo-linalool, 8-COOH-linalool, lilac compounds)

  • Calculate correlation coefficients between protein abundance and metabolite levels

  • Create network visualizations connecting protein levels to metabolite profiles

• Spatial integration approaches:

  • Use immunohistochemistry to map CYP76C1 localization

  • Apply mass spectrometry imaging or DESI-MS to map metabolite distribution

  • Overlay protein and metabolite spatial data to identify co-localization patterns

  • Focus analysis on floral tissues with known CYP76C1 expression (petals, anthers, filament, stamen)

• Temporal dynamics assessment:

  • Track protein expression and metabolite changes through flower development

  • Align with the known transient expression of CYP76C1 during anthesis

  • Apply time-series statistical methods to identify lagged relationships

• Genetic perturbation analysis:

  • Compare wild-type, cyp76c1 mutants, and overexpression lines for both protein levels and metabolites

  • Quantify the relationship between CYP76C1 abundance and substrate/product ratios

  • Identify potential rate-limiting steps in the pathway

• Environmental response integration:

  • Measure how CYP76C1 protein levels and metabolite profiles change under stress conditions

  • Correlate with defense phenotypes against floral antagonists

  • Assess herbicide response profiles in relation to CYP76C1 expression

• Visualization and statistical frameworks:

  • Use principal component analysis (PCA) to identify patterns across multiple data types

  • Apply ANOVA models to assess effects of genotype, tissue, and treatment

  • Create integrated heat maps showing protein expression and metabolite levels

  • Develop pathway flux models incorporating protein abundance data

• Multi-omics data integration:

  • Combine proteomics, metabolomics, and transcriptomics in a comprehensive analysis

  • Use systems biology approaches to model pathway dynamics

  • Identify potential regulatory mechanisms controlling both protein levels and metabolic flux

What emerging technologies could enhance CYP76C1 antibody-based research?

Several cutting-edge technologies offer promising opportunities for advancing CYP76C1 research:

• Single-cell protein analysis:

  • Adapt CyTOF (mass cytometry) techniques for plant cells using metal-conjugated anti-CYP76C1 antibodies

  • Develop single-cell Western blotting methods for cell-specific CYP76C1 quantification

  • Apply microfluidic antibody capture techniques for single-cell protein profiling

• Proximity labeling technologies:

  • Generate CYP76C1 fusions with BioID, TurboID, or APEX2 for in vivo proximity labeling

  • Map the local protein environment of CYP76C1 in ER membranes

  • Identify components of potential metabolons involving CYP76C1

• Super-resolution microscopy:

  • Apply STORM, PALM, or STED microscopy with fluorophore-conjugated antibodies

  • Visualize nanoscale organization of CYP76C1 in ER membranes

  • Examine co-localization with interaction partners at molecular resolution

• Biomolecular condensate analysis:

  • Investigate whether CYP76C1 participates in phase-separated biomolecular condensates

  • Study how condensate formation might regulate metabolic flux

  • Examine spatial organization of terpenoid biosynthetic enzymes

• Engineered antibody technologies:

  • Develop nanobodies against CYP76C1 for improved penetration and specificity

  • Create intrabodies for real-time visualization of CYP76C1 in living cells

  • Apply antibody-based biosensors to monitor CYP76C1 activity directly

• CRISPR-based innovations:

  • Generate endogenously tagged CYP76C1 using CRISPR-Cas9

  • Create conditional knockout systems for temporal control of CYP76C1 expression

  • Apply base editing for structure-function studies of CYP76C1

• Antibody-enzyme fusions:

  • Develop "Immuno-ABPP" (activity-based protein profiling) for CYP76C1

  • Create antibody-luciferase fusions for highly sensitive detection

  • Generate split-protein complementation systems for monitoring protein interactions
    These technologies could significantly advance our understanding of CYP76C1's role in plant defense and terpenoid metabolism.

What are the most promising applications of CYP76C1 antibodies for agricultural research?

CYP76C1 antibodies have significant potential for agricultural applications:

• Herbicide resistance mechanisms:

  • Monitor CYP76C1 expression in crop species and weeds

  • Study the relationship between CYP76C1 levels and phenylurea herbicide resistance

  • Develop rapid immunoassays to predict herbicide sensitivity

  • Screen for natural variants with enhanced herbicide metabolism

• Pest resistance biomarkers:

  • Use CYP76C1 antibodies to monitor plant defense activation

  • Develop diagnostic tools for early detection of defense responses

  • Screen germplasm collections for enhanced CYP76C1 expression

  • Correlate CYP76C1 levels with resistance to floral pests

• Metabolic engineering applications:

  • Monitor CYP76C1 expression in plants engineered for enhanced terpenoid production

  • Assess protein stability and localization in transgenic plants

  • Optimize expression systems for biotechnological applications

  • Study protein-protein interactions in engineered metabolic pathways

• Crop improvement strategies:

  • Develop antibody-based screening methods for selecting plants with optimal CYP76C1 expression

  • Monitor effects of breeding on CYP76C1 levels and activity

  • Assess environmental influences on CYP76C1 expression across growing conditions

  • Explore potential roles in stress tolerance beyond floral defense

• Regulatory mechanisms:

  • Investigate transcription factor binding and post-translational modifications

  • Study hormonal regulation of CYP76C1 protein levels

  • Examine circadian and developmental control of expression

  • Assess epigenetic influences on protein abundance

• Comparative studies across species:

  • Develop cross-reactive antibodies to study CYP76C1 homologs in crops

  • Compare expression patterns between model and crop species

  • Investigate evolutionary conservation of function across plant families

  • Identify species-specific adaptations in protein structure and regulation These applications could significantly impact agricultural practices by enhancing crop protection strategies and facilitating metabolic engineering approaches.