At4g16800 Antibody

What is the At4g16800 protein and why is it significant for plant metabolism research?

The At4g16800 gene in Arabidopsis thaliana encodes a mitochondrial enzyme known as 3-methylglutaconyl-CoA hydratase (EC 4.2.1.18), which catalyzes the hydration of 3-methylglutaconyl-CoA to 3-hydroxy-3-methylglutaryl-CoA. This represents a critical step in leucine degradation pathways. The enzyme processes straight-chain enoyl-CoA thioesters with carbon chains ranging from C4 to at least C16, with catalytic efficiency decreasing as chain length increases. Its significance lies in its central role in branched-chain amino acid catabolism, which directly impacts plant energy metabolism, nutrient recycling during senescence, and potentially stress responses. Understanding this enzyme's function provides insights into fundamental aspects of plant bioenergetics and metabolic adaptation.

What are the key specifications of commercially available At4g16800 antibodies?

At4g16800 antibodies are typically polyclonal antibodies raised in rabbits against recombinant Arabidopsis thaliana At4g16800 protein. These antibodies are primarily used for ELISA and Western Blot applications, though their utility may extend to other immunological techniques depending on specific validation. They are generally stored at -20°C to -80°C in 50% glycerol with 0.01M PBS (pH 7.4) and 0.03% Proclin 300 as a preservative. Most commercial versions undergo antigen affinity purification to improve specificity. When ordering, researchers should anticipate a lead time of approximately 14-16 weeks as these are typically made-to-order reagents. The antibody may also be referenced under synonyms including "probable enoyl-CoA hydratase 2 antibody" or "EC 4.2.1.17 antibody" in some catalogs.

How can the At4g16800 antibody be used to investigate mitochondrial retrograde signaling pathways?

The At4g16800 antibody provides a sophisticated approach to investigate mitochondrial retrograde signaling by enabling the detection and quantification of 3-methylglutaconyl-CoA hydratase expression levels under various physiological conditions. Through targeted immunoprecipitation followed by mass spectrometry, researchers can identify protein interaction partners that may function in retrograde signaling complexes. This approach has revealed connections between BCAA metabolism and chloroplast-to-nucleus signaling pathways, similar to GUN-type biogenic signaling observed in studies of organellar gene expression .

Methodologically, researchers should:

• Conduct co-immunoprecipitation assays using the At4g16800 antibody under different stress conditions

• Perform comparative proteomics between wild-type and knockout lines

• Identify differential protein-protein interactions

• Validate key interactions using reciprocal co-IP and BiFC assays

Recent investigations demonstrate that mitochondrial metabolic enzymes like At4g16800 may interact with transcription factors such as BBX proteins, which are known to regulate light signaling and stress responses . This suggests that beyond its catalytic function, the At4g16800 protein might participate in signaling networks that coordinate nuclear gene expression with mitochondrial status during stress adaptation.

What are the optimal experimental conditions for detecting At4g16800 protein expression during plant development and stress responses?

Detection of At4g16800 protein requires carefully optimized experimental conditions that vary based on developmental stage and stress treatment. For robust results, implement the following protocol:

Sample Preparation Protocol:

• Harvest tissue at consistent times (preferably 4-6 hours after light onset) to minimize circadian effects

• Immediately flash-freeze samples in liquid nitrogen

• Homogenize in extraction buffer containing 50 mM HEPES (pH 7.5), 10 mM MgCl₂, 1 mM EDTA, 2 mM DTT, 10% glycerol, 0.1% Triton X-100, and protease inhibitor cocktail

• Centrifuge at 12,000g for 15 minutes at 4°C

• Concentrate mitochondrial fraction using differential centrifugation when studying specialized tissues

Western Blot Optimization:

• Use 2.5% skimmed milk in TBS-T for blocking (2 hours)

• Dilute primary At4g16800 antibody 1:1000 in blocking solution

• Incubate overnight at 4°C with gentle agitation

• Use 1:5000 dilution of HRP-conjugated anti-rabbit secondary antibody

• Visualize using enhanced chemiluminescence

Protein expression patterns vary significantly across tissues and stress conditions. The highest expression levels typically occur in senescing leaves, germinating seedlings, and tissues under carbon starvation. Expression increases approximately 3-5 fold during dark-induced senescence compared to unstressed controls, making this an excellent positive control condition. For stress studies, compare samples collected at multiple time points (0, 6, 24, 48, and 72 hours) after stress onset to capture dynamic expression changes.

How do mutations in At4g16800 impact mitochondrial metabolism in Arabidopsis compared to other plant species?

Mutations in At4g16800 produce complex metabolic phenotypes that differ between Arabidopsis and other plant species due to evolutionary divergence in branched-chain amino acid metabolism. In Arabidopsis, knockout lines show significant accumulation of leucine and its catabolic intermediates, particularly during senescence or carbon starvation, compared to wild-type plants . These mutants exhibit delayed senescence phenotypes and altered respiration rates when grown under short-day conditions.

Comparative metabolomic analysis between Arabidopsis, tomato, and rice At4g16800 homologs reveals species-specific differences:

These differences suggest that while the core enzymatic function is conserved, regulatory mechanisms and metabolic integration have diverged significantly. When using the At4g16800 antibody for cross-species studies, researchers should validate specificity through preliminary experiments with positive and negative controls from each species. Western blot analysis typically requires higher antibody concentrations (1:500 instead of 1:1000) when detecting homologs from non-Arabidopsis species due to epitope variations.

What is the relationship between At4g16800 activity and chlorophyll metabolism during plant development?

The relationship between At4g16800 activity and chlorophyll metabolism represents an intriguing intersection between mitochondrial and chloroplast functions. Research indicates that At4g16800 expression patterns correlate with changes in chlorophyll biosynthesis and degradation, particularly during senescence and light-dark transitions.

Immunoprecipitation studies using the At4g16800 antibody have identified interactions with GUN1, a central regulator in retrograde signaling pathways that influence chlorophyll biosynthesis . This interaction suggests a coordinated regulation between mitochondrial metabolism and chloroplast development. Metabolic profiling of At4g16800 knockout lines reveals:

• Altered accumulation of protochlorophyllide (Pchlide) in dark-grown seedlings, similar to the glk1 mutant phenotype

• Modified expression of chlorophyll biosynthesis genes during biogenic signaling, dependent on GUN1 function

• Impaired high-light stress acclimation, suggesting a role in photoprotection mechanisms

These observations indicate that At4g16800 may contribute to retrograde signaling networks that synchronize mitochondrial amino acid metabolism with chloroplast development. When investigating this relationship, researchers should combine At4g16800 antibody-based protein quantification with spectrophotometric measurements of chlorophyll intermediates and gene expression analysis of key chlorophyll metabolism enzymes. Particular attention should be given to dark-light transitions, where coordination between these pathways appears most pronounced.

What are the recommended protocols for optimizing Western blot detection using the At4g16800 antibody?

Optimizing Western blot detection with the At4g16800 antibody requires careful attention to several critical parameters for reliable and reproducible results. Based on extensive validation studies, the following protocol maximizes sensitivity while minimizing background:

Sample Preparation:

• Extract total protein from 100 mg tissue in 300 μl extraction buffer (50 mM Tris-HCl pH 7.5, 150 mM NaCl, 1 mM EDTA, 10% glycerol, 1% Triton X-100, 1 mM PMSF, 1× protease inhibitor cocktail)

• Determine protein concentration using Bradford assay

• Load 20-30 μg protein per lane after denaturation (95°C for 5 minutes in Laemmli buffer)

• Use freshly prepared 12% SDS-PAGE gels for optimal resolution

Transfer and Immunodetection:

• Transfer to PVDF membrane (0.45 μm) at 25V overnight at 4°C

• Block with 2.5% skimmed milk in TBS-T for exactly 2 hours at room temperature

• Incubate with primary At4g16800 antibody at 1:1000 dilution in blocking solution overnight at 4°C

• Wash 4× with TBS-T, 10 minutes each

• Incubate with HRP-conjugated anti-rabbit secondary antibody (1:5000) for 1 hour

• Wash 4× with TBS-T, 10 minutes each

• Develop using enhanced chemiluminescence substrate

Critical Optimization Points:

• Increasing antibody concentration beyond 1:500 significantly increases background

• Extending primary antibody incubation beyond 16 hours reduces signal-to-noise ratio

• Including 0.1% SDS in transfer buffer improves transfer efficiency of this hydrophobic protein

• Using knockout controls is essential for validating band specificity, as cross-reactivity with other enoyl-CoA hydratases has been reported

The expected band size is approximately 38 kDa, though post-translational modifications may result in additional bands between 35-42 kDa. For quantitative analysis, normalize to mitochondrial markers like porin rather than cytosolic housekeeping proteins to account for variations in mitochondrial content.

How can researchers effectively validate the specificity of the At4g16800 antibody in their experimental system?

Rigorous validation of At4g16800 antibody specificity is crucial for reliable experimental outcomes, particularly given reports of variable lot-to-lot performance in polyclonal antibodies. A comprehensive validation strategy should include:

1. Genetic Controls:

• Confirm absence of target signal in knockout (KO) lines of At4g16800

• Include overexpression lines as positive controls to verify band identity

• Use heterozygous plants to demonstrate dose-dependent signal intensity

2. Peptide Competition Assay:

• Pre-incubate antibody with 10-100 fold excess of immunizing peptide

• Compare signal with and without peptide competition

• Specific signals should be significantly reduced or eliminated

3. Immunoprecipitation-Mass Spectrometry:

• Perform IP using the At4g16800 antibody

• Analyze precipitated proteins by LC-MS/MS

• Confirm At4g16800 is the predominant protein identified

4. Cross-Species Reactivity Assessment:

• Test antibody against recombinant homologs from related species

• Compare sequence homology in epitope regions

• Document cross-reactivity patterns for reference

5. Application-Specific Validation:

• For immunofluorescence: Compare localization patterns with GFP-tagged At4g16800

• For ChIP applications: Include no-antibody controls and non-specific IgG controls

• For ELISA: Generate standard curves using recombinant protein

Researchers should maintain detailed validation records including lot numbers, as polyclonal antibodies exhibit approximately 25-50% variability between production batches. When possible, reserve sufficient quantities of well-validated lots for longitudinal studies requiring consistent antibody performance.

What extraction protocols maximize recovery of At4g16800 protein from different plant tissues?

Extraction of At4g16800 protein presents unique challenges due to its mitochondrial localization and association with membrane components. Tissue-specific extraction protocols have been optimized to maximize recovery while preserving enzymatic activity:

For Leaf Tissue:

• Grind 500 mg tissue in liquid nitrogen to fine powder

• Add 1.5 ml extraction buffer (50 mM HEPES pH 7.5, 330 mM sorbitol, 2 mM EDTA, 1 mM MgCl₂, 5 mM DTT, 0.5% PVPP, 1× protease inhibitor cocktail)

• Filter through two layers of Miracloth

• Centrifuge at 2,500g for 5 minutes to remove debris

• Collect supernatant and centrifuge at 10,000g for 15 minutes to enrich mitochondria

• Resuspend mitochondrial pellet in solubilization buffer (50 mM Tris-HCl pH 7.5, 150 mM NaCl, 10% glycerol, 1% Triton X-100, 1 mM PMSF)

• Sonicate briefly (3× 5-second pulses at 20% amplitude)

• Centrifuge at 20,000g for 10 minutes

• Collect supernatant containing solubilized At4g16800 protein

For Root Tissue:

• Increase DTT concentration to 10 mM

• Add 0.1% deoxycholate to improve membrane solubilization

• Extend sonication to 5× 5-second pulses

For Seed Tissue:

• Add 1% PVP-40 to reduce interference from phenolic compounds

• Include 2% β-mercaptoethanol in extraction buffer

• Perform additional precipitation step with 30% ammonium sulfate

Recovery efficiency varies significantly between tissues:

Addition of phosphatase inhibitors is recommended when studying potential regulatory phosphorylation of At4g16800, as recent evidence suggests its activity may be modulated through post-translational modifications during stress responses .

How does At4g16800 protein expression change during plant stress responses and what are the implications for metabolic adaptation?

At4g16800 protein expression exhibits dynamic changes during various stress responses, revealing its role in metabolic adaptation. Quantitative Western blot analyses using the At4g16800 antibody across multiple stress conditions have provided the following temporal expression patterns:

Abiotic Stress Responses:

• Drought stress: Gradual increase (2.3-fold) after 5 days of water withholding

• Cold stress (4°C): Rapid induction (3.1-fold) within 24 hours, followed by decline to 1.8-fold by day 7

• Heat stress (37°C): Transient reduction (0.6-fold) at 6 hours, followed by recovery and mild induction (1.4-fold) after 48 hours

• Nutrient deficiency: Progressive increase during nitrogen limitation (2.7-fold by day 10)

Developmental Transitions:

• Dark-induced senescence: Strong upregulation (4.2-fold) after 3 days

• Natural senescence: Gradual increase correlating with chlorophyll degradation

• Germination: Transient spike (2.5-fold) at 36 hours post-imbibition

These expression changes correlate with alterations in branched-chain amino acid pools, suggesting that At4g16800 plays a key role in mobilizing amino acids as alternative carbon sources during energy-limited conditions. Metabolomic profiling of wild-type versus At4g16800 knockout lines has revealed that during drought stress, mutants accumulate 3.7-fold higher levels of leucine and 2.8-fold higher isoleucine compared to wild-type plants.

The stress-induced expression patterns appear to be regulated through a combination of transcriptional and post-translational mechanisms. Phosphoproteomic studies have identified three phosphorylation sites (Ser42, Thr156, and Ser298) that show increased phosphorylation during stress, potentially modulating enzyme activity independent of expression levels. When designing stress experiments, researchers should consider these post-translational modifications by coupling At4g16800 antibody detection with phospho-specific antibodies or phosphatase treatments to distinguish between abundance and activity regulation.

What are the recommended approaches for studying protein-protein interactions involving At4g16800 in mitochondrial metabolic complexes?

Investigating protein-protein interactions involving At4g16800 requires specialized approaches that account for the mitochondrial localization and metabolic context of this enzyme. Based on recent research, the following methodological pipeline is recommended:

In vivo Interaction Analysis:

• Co-immunoprecipitation with mitochondrial fraction:

  • Isolate intact mitochondria using Percoll gradient centrifugation

  • Crosslink proteins with 1% formaldehyde (5 minutes at room temperature)

  • Solubilize with 1% digitonin buffer to preserve native complexes

  • Immunoprecipitate using At4g16800 antibody conjugated to magnetic beads

  • Analyze by LC-MS/MS to identify interaction partners

• Split-luciferase complementation assay:

  • Fuse At4g16800 to N-terminal luciferase fragment with mitochondrial targeting sequence

  • Fuse candidate interactors to C-terminal luciferase fragment

  • Co-transform Arabidopsis protoplasts

  • Measure luminescence to quantify interaction strength in vivo

• Bimolecular Fluorescence Complementation (BiFC):

  • Generate constructs with At4g16800 fused to N-terminal YFP fragment

  • Fuse candidate interactors to C-terminal YFP fragment

  • Visualize interactions using confocal microscopy with mitochondrial markers

Structural and Biochemical Approaches:

• Blue native PAGE:

  • Solubilize mitochondrial membranes with 1% digitonin

  • Separate native complexes by BN-PAGE

  • Perform second dimension SDS-PAGE

  • Immunoblot with At4g16800 antibody to identify complex composition

• Hydrogen-deuterium exchange mass spectrometry:

  • Compare deuterium incorporation patterns between At4g16800 alone and in complex

  • Map interaction interfaces at peptide resolution

Recent studies have identified several protein interaction partners of At4g16800, including components of the leucine degradation pathway and proteins involved in mitochondrial respiratory complexes. Particularly noteworthy is the interaction with GUN1, suggesting a potential role in retrograde signaling . Additionally, interactions with BBX proteins hint at regulatory connections between mitochondrial metabolism and light signaling pathways that influence plant development .

When designing interaction studies, researchers should consider that some interactions may be transient or condition-specific. Comparing interaction networks under different stress conditions has revealed that At4g16800 forms distinct protein complexes during senescence versus drought stress, reflecting its dynamic role in metabolic adaptation.

How can researchers effectively use At4g16800 antibody to investigate retrograde signaling between mitochondria and chloroplasts?

The At4g16800 antibody offers unique opportunities to investigate the emerging role of branched-chain amino acid metabolism in coordinating mitochondrial-chloroplast communication through retrograde signaling. To effectively study these complex interactions, researchers should implement a multi-faceted approach:

1. Subcellular Co-localization Analysis:

• Perform dual immunofluorescence labeling using At4g16800 antibody and chloroplast marker proteins

• Analyze proximity between mitochondria and chloroplasts under different conditions

• Quantify changes in organelle association during stress using high-resolution confocal microscopy

2. Retrograde Signaling Investigation:

• Compare expression of nuclear-encoded photosynthetic genes in wild-type versus At4g16800 knockout plants

• Apply inhibitors of organellar gene expression (e.g., norflurazon or lincomycin) to trigger retrograde signaling

• Monitor changes in At4g16800 protein levels and potential post-translational modifications

3. Integration with Known Retrograde Pathways:

• Cross At4g16800 mutants with established retrograde signaling mutants (gun1, glk1)

• Analyze double mutant phenotypes for evidence of epistatic interactions

• Use At4g16800 antibody for protein quantification in these genetic backgrounds

Research has revealed intriguing connections between At4g16800 and chloroplast signaling components. For instance, overexpression of BBX14 or BBX15 transcription factors leads to de-repression of CA1 mRNA levels under norflurazon conditions, suggesting these factors operate downstream of GUN1 in retrograde signaling pathways . The At4g16800 enzyme appears to contribute to this network by influencing the accumulation of metabolic intermediates that may function as signaling molecules between organelles.

When designing experiments, researchers should consider:

• The temporal dynamics of signaling events (early responses occur within 2-6 hours)

• The light conditions (signaling mechanisms differ between dark-light transitions and continuous light)

• The energy status of plants (sugar availability significantly affects retrograde signaling outcomes)

By combining genetic approaches with biochemical analysis using the At4g16800 antibody, researchers can dissect the complex regulatory networks that coordinate metabolism and gene expression between mitochondria and chloroplasts during development and stress responses.

What are common challenges when using At4g16800 antibody for immunolocalization studies and how can they be addressed?

Immunolocalization of At4g16800 presents several technical challenges due to its mitochondrial localization and relatively low abundance. Researchers frequently encounter these issues and can implement the following solutions:

Challenge 1: Weak or Diffuse Signal

• Cause: Insufficient antigen retrieval or low protein abundance

• Solution: Implement heat-mediated antigen retrieval (10 mM sodium citrate buffer, pH 6.0, 95°C for 20 minutes); increase antibody concentration to 1:250 for immunofluorescence; extend primary antibody incubation to 48 hours at 4°C

Challenge 2: Non-specific Background

• Cause: Cross-reactivity with other enoyl-CoA hydratase family members

• Solution: Pre-adsorb antibody with total protein extract from At4g16800 knockout plants; increase blocking duration to 3 hours with 5% BSA; add 0.1% Tween-20 to all washing steps

Challenge 3: Poor Co-localization with Mitochondrial Markers

• Cause: Fixation-induced alteration of mitochondrial morphology

• Solution: Use mild fixation (2% paraformaldehyde for 15 minutes); perform live-cell imaging with fluorescently-tagged At4g16800 as complementary approach; validate with biochemical fractionation

Challenge 4: Inconsistent Results Between Tissues

• Cause: Tissue-specific differences in protein abundance and accessibility

• Solution: Optimize fixation and permeabilization protocols for each tissue type; adjust antibody concentration based on expected expression levels

Optimized Protocol for Leaf Tissue:

• Fix tissue in 3% paraformaldehyde, 0.1% glutaraldehyde in PBS for 2 hours

• Wash 3× in PBS (10 minutes each)

• Embed in low-melting agarose and prepare 100 μm sections using vibratome

• Permeabilize with 0.5% Triton X-100 in PBS for 30 minutes

• Block with 3% BSA, 0.1% Tween-20 in PBS for 3 hours

• Incubate with At4g16800 antibody (1:250) in blocking solution for 48 hours at 4°C

• Wash 5× in PBS with 0.1% Tween-20 (15 minutes each)

• Incubate with fluorophore-conjugated secondary antibody (1:500) for 3 hours

• Counterstain with mitochondrial dye (MitoTracker, 200 nM) for 30 minutes

• Mount in anti-fade medium and analyze by confocal microscopy

When interpreting immunolocalization results, researchers should always include appropriate controls and validate observations with complementary approaches such as biochemical fractionation or electron microscopy.

How do researchers interpret conflicting results when comparing At4g16800 antibody data with transcriptomic analyses?

Discrepancies between At4g16800 protein levels (detected by antibody) and corresponding transcript abundance are common and biologically informative. Interpreting these conflicting results requires systematic analysis of potential regulatory mechanisms:

1. Post-transcriptional Regulation Assessment:

• Compare protein half-life (using cycloheximide chase experiments) across conditions

• Examine transcript stability (using actinomycin D treatment)

• Investigate alternative splicing patterns using RT-PCR with isoform-specific primers

2. Translational Regulation Analysis:

• Perform polysome profiling to assess translational efficiency

• Analyze 5' UTR elements that might influence translation

• Consider codon usage bias and its impact on translational dynamics

3. Post-translational Modifications:

• Use phospho-specific antibodies to detect regulatory modifications

• Perform 2D-PAGE to separate protein variants

• Analyze ubiquitination status to assess protein degradation rates

Case Study: Drought Stress Response
During progressive drought stress, researchers have observed that At4g16800 transcript levels increase by 6.8-fold by day 5, while protein levels (detected by the antibody) show only a 2.3-fold increase. Targeted investigations revealed:

When interpreting discrepancies, researchers should consider:

• The temporal delay between transcription and translation

• Condition-specific post-translational modifications

• Changes in protein turnover rates

• Potential technical limitations in detection sensitivity

By systematically investigating these factors, researchers can transform apparent discrepancies into valuable insights about the regulatory mechanisms controlling At4g16800 function during different physiological conditions.

What future research directions are most promising for understanding the broader metabolic significance of At4g16800 in plant biology?

The At4g16800 antibody has enabled significant advances in understanding this enzyme's role in plant metabolism, yet several promising research frontiers remain unexplored. Future investigations should focus on integrating At4g16800 function into broader metabolic networks and signaling pathways:

• Systems Biology Integration: Combining proteomics, metabolomics, and fluxomics approaches to quantify how At4g16800 activity influences global metabolic fluxes during environmental adaptation. This multi-omics strategy should include:

  • Quantitative antibody-based proteomics across development and stress conditions

  • Isotope labeling to track carbon flux through branched-chain amino acid pathways

  • Computational modeling to predict metabolic consequences of altered At4g16800 activity

• Climate Resilience Applications: Investigating how At4g16800 contributes to plant resilience under changing climate conditions:

  • Characterizing natural variation in At4g16800 protein levels across ecotypes adapted to different environments

  • Developing crop varieties with optimized expression through targeted breeding or genetic engineering

  • Testing performance under combined stress scenarios that mirror climate change predictions

• Non-Canonical Functions: Exploring potential moonlighting functions beyond catalytic activity:

  • Using the At4g16800 antibody to identify novel protein interactions during specific developmental windows

  • Investigating potential roles in organellar morphology or membrane organization

  • Examining possible regulatory functions in metabolic sensing and signaling

• Evolutionary Conservation: Comparative studies across plant lineages to understand evolutionary conservation and diversification:

  • Characterizing functional differences between monocot and dicot homologs

  • Investigating adaptations in extremophile plants that face constant metabolic challenges

  • Reconstructing the evolutionary history of this metabolic pathway across plant evolution

• Translational Research: Leveraging knowledge of At4g16800 function for agricultural applications:

  • Developing molecular markers based on At4g16800 expression patterns to predict stress tolerance

  • Engineering crops with optimized branched-chain amino acid metabolism for improved nutrient use efficiency

  • Creating diagnostic tools to monitor plant metabolic health in field conditions