Recombinant Atropa belladonna ATP synthase subunit c, chloroplastic (atpH)

What is the structure and function of ATP synthase subunit c in chloroplasts?

ATP synthase subunit c (atpH) is a critical component of the membrane-embedded CF0 subcomplex of chloroplast ATP synthase. This protein functions as part of the proton channel that converts energy from proton flux into rotational motion, ultimately driving ATP synthesis. The CF0 subcomplex works in conjunction with the water-soluble CF1 subcomplex, which couples this rotational motion to the synthesis of ATP .

Structurally, the full-length protein consists of 81 amino acids and forms a transmembrane protein embedded in the thylakoid membrane. The architecture of the chloroplast complex shares similarities with bacterial and mitochondrial orthologues, with the F1 subcomplex composed of five subunits (α, β, γ, δ, and ε) with a stoichiometry of 3:3:1:1:1 . The subunit c specifically contributes to the formation of the c-ring structure that rotates during ATP synthesis and hydrolysis.

How is chloroplastic ATP synthase activity regulated in photosynthetic tissues?

Chloroplast ATP synthase is regulated through multiple sophisticated mechanisms:

• Proton motive force (pmf) activation: Like other ATP synthases, chloroplastic ATP synthase is activated by the imposition of a proton electrochemical gradient across the thylakoid membrane .

• Redox regulation: A unique chloroplast-specific regulatory mechanism involves redox modulation of a disulfide/sulfhydryl pair on the γ subunit via thioredoxin. This redox regulation modulates the amplitude of pmf required to activate the ATP synthase and prevents wasteful ATP hydrolysis in the dark by reversing the ATP synthase reaction .

• Metabolism-related regulation: ATP synthase activity is modulated in vivo in response to altered metabolic or physiological conditions, such as decreased atmospheric CO2 or O2 levels, environmental stress conditions (e.g., drought), or changes in the capacity of the Calvin-Benson cycle and starch synthesis. This regulation represents an important feedback mechanism that senses the metabolic status of the stroma and adjusts the efflux of protons from the lumen to modulate the lumen pH-dependent down-regulation of light capture and electron transfer .

Several mechanisms for this metabolism-related regulation have been proposed, including thiol modulation, depletion of substrate Pi, binding of small allosteric effectors, or phosphorylation, though these have not been directly tested in all cases .

How do mutations in the γ subunit affect the redox regulation of chloroplastic ATP synthase?

Research has demonstrated that mutations in the γ subunit can significantly alter the redox regulation of chloroplastic ATP synthase while preserving its metabolism-induced regulation. Site-directed mutagenesis studies have focused on a chloroplast-specific 9-amino acid "loop" in the γ subunit containing a pair of redox-active cysteine residues (Cys199 and Cys205 in Arabidopsis thaliana) .

In particular, mutations of three conserved acidic amino acid residues in this regulatory loop region have been shown to shift the γ subunit redox midpoint potential. This was evidenced by immunoblotting analyses that revealed a decreased apparent molecular weight of the mutated γ subunit compared to wild-type, possibly due to effects on protein charge or secondary structure, including the ability to form the regulatory disulfide bond .

These findings suggest that light and metabolism regulation operate via distinct mechanisms, with the γ subunit mutations specifically affecting light-induced regulation but not metabolism-related regulation. This distinction positions the chloroplast ATP synthase as a key control point for coordinating the light and dark reactions of photosynthesis .

What experimental approaches are most effective for studying the redox state of the ATP synthase γ subunit?

The redox state of the γ subunit can be effectively probed using the following methodological approach:

• AMS binding assay: Using 4-acetamido-4′-maleimidylstilbene-2,2′-disulfonate (AMS) followed by non-reducing SDS-PAGE. This technique allows for visualization of the oxidation state of the regulatory cysteines .

• Sample preparation protocol:

  • Create oxidizing conditions by infiltrating leaf discs with 0.1% (v/v) Tween 20 and 20 mM Tricine containing 100 μM methyl viologen

  • Create reducing conditions using 20 mM reduced dithiothreitol (DTT)

  • Incubate discs for 30 minutes in darkness at room temperature

  • Freeze and grind samples in liquid nitrogen

  • Isolate insoluble proteins by centrifugation and washing with 80% acetone

  • Dissolve protein precipitates in freshly prepared solution containing 1% SDS, 50 mM Tris-HCl (pH 8.0), and 15 mM AMS

  • Perform SDS-PAGE using running buffer lacking reducing agent

• Western blot analysis: Using antibodies against the γ subunit to detect mobility shifts that occur due to AMS binding to reduced thiols, which increases the apparent molecular weight of the protein.

This approach allows researchers to determine the in vivo redox state of the γ subunit under various physiological conditions and to assess how mutations affect the formation of the regulatory disulfide bridge.

How can recombinant ATP synthase components be incorporated into synthetic biology applications?

Recombinant ATP synthase components, including the atpH subunit from Atropa belladonna, can be strategically incorporated into synthetic biology applications through several approaches:

• Modular biosynthetic pathway engineering: ATP synthase components can be integrated into engineered metabolic pathways to optimize energy production. For example, research has demonstrated the incorporation of plant transporters, including those from Atropa belladonna, into yeast to enhance biosynthetic pathways for tropane alkaloids .

• Supervised learning approaches for transporter identification: Advanced computational methods can identify transporters from Atropa belladonna that alleviate cellular metabolite transport limitations. Artificial neural networks (ANNs) trained on tissue-specific transcriptome data can identify transporter candidates with significantly better efficiency than conventional linear correlation strategies .

• Subcellular localization optimization: By targeting recombinant proteins to specific cellular compartments, researchers can enhance pathway efficiency. For instance, transporters like AbPUP1 and AbLP1 from A. belladonna have been shown to localize to the vacuole membrane and increase alkaloid production in engineered yeast .

• Integration with cofactor regeneration mechanisms: Incorporating ATP synthase components into systems with optimized cofactor regeneration mechanisms can significantly improve production yields, as demonstrated in yeast platforms where improvements of over 100-fold in alkaloid production have been achieved .

What structural and functional differences exist between ATP synthase subunit c from Atropa belladonna and other plant species?

While the search results don't provide direct comparative data between Atropa belladonna ATP synthase subunit c and other plant species, several general observations can be made based on current understanding of ATP synthase evolution and conservation:

Comparative genomic and structural studies would be needed to elucidate the specific differences between Atropa belladonna ATP synthase subunit c and that of other plant species, particularly focusing on how any differences might relate to the specialized metabolism of tropane alkaloids in Atropa belladonna.

What are the optimal conditions for expression and purification of recombinant Atropa belladonna ATP synthase subunit c?

Based on the commercial protein information, the following protocol outlines the optimal conditions for expression and purification of recombinant Atropa belladonna ATP synthase subunit c:

Expression System:

• Host: Escherichia coli

• Expression region: Full length (1-81 amino acids)

• Tag: N-terminal His-tag for purification

• Vector selection: pET-series vectors are commonly used for membrane protein expression

Purification Protocol:

• Express the His-tagged protein in E. coli

• Lyse cells in an appropriate buffer containing detergent to solubilize membrane proteins

• Purify using immobilized metal affinity chromatography (IMAC)

• Perform SDS-PAGE analysis to confirm purity (should be greater than 90%)

• Concentrate and buffer-exchange into a Tris/PBS-based buffer containing 6% Trehalose, pH 8.0

Storage and Handling:

• Store lyophilized powder at -20°C/-80°C

• For reconstitution, briefly centrifuge the vial before opening

• Reconstitute in deionized sterile water to a concentration of 0.1-1.0 mg/mL

• Add glycerol to a final concentration of 50% for long-term storage

• Aliquot to avoid repeated freeze-thaw cycles, which can damage protein structure

• Working aliquots can be stored at 4°C for up to one week

How can researchers assess the functional activity of recombinant ATP synthase subunit c in experimental settings?

Assessing the functional activity of recombinant ATP synthase subunit c requires multiple complementary approaches:

1. Reconstitution into liposomes or nanodiscs:

• Incorporate purified recombinant subunit c into artificial membrane systems

• Co-reconstitute with other ATP synthase subunits to form functional complexes

• Measure proton translocation using pH-sensitive fluorescent dyes

2. Complementation studies in mutant systems:

• Express the recombinant Atropa belladonna ATP synthase subunit c in ATP synthase-deficient bacterial strains or yeast models

• Assess restoration of ATP synthesis capacity

• Compare growth rates under conditions requiring oxidative phosphorylation

3. Structural integrity assessment:

• Circular dichroism (CD) spectroscopy to verify proper protein folding

• Blue native PAGE to examine incorporation into higher-order complexes

• Cryo-electron microscopy to visualize the c-ring assembly

4. Redox state analysis:

• Apply the AMS binding protocol described in section 2.2 to assess the redox state of associated regulatory subunits

• Use site-directed mutagenesis to introduce reporter cysteines for monitoring conformational changes

• Correlate redox state with functional activity under varying conditions

5. In vitro ATP synthesis/hydrolysis assays:

• Measure ATP synthesis rates in reconstituted systems under an artificial proton gradient

• Assess ATP hydrolysis activity using coupled enzyme assays

• Determine the effects of inhibitors, activators, and different redox conditions

What methods can be used to study the integration of ATP synthase with metabolite transport in plant systems?

To study the integration of ATP synthase with metabolite transport in plant systems, researchers can employ several sophisticated methodological approaches:

1. Artificial Neural Network (ANN) for transporter identification:

• Apply supervised learning approaches to tissue-specific transcriptome data

• Train ANNs on plant transcriptome data (e.g., from Atropa belladonna) to identify potential transporters involved in metabolite transport

• This approach has been shown to reduce the search space from >40,000 transcripts to just a few candidates, over 30 times better than conventional linear correlation strategies

2. Subcellular localization studies:

• Generate fluorescent protein fusions with candidate transporters (e.g., AbPUP1, AbLP1)

• Perform confocal microscopy to determine localization to specific organelles

• Correlate localization patterns with metabolite accumulation and ATP synthesis rates

3. Metabolic flux analysis:

• Use isotope-labeled substrates to track metabolite movement between compartments

• Quantify the relationship between ATP synthesis rates and metabolite transport

• Apply flux balance analysis to model the integration of energy metabolism and transport

4. Engineered yeast platforms:

• Express plant transporters and ATP synthase components in yeast systems

• Measure changes in alkaloid production or other metabolic outputs

• Compare growth and metabolite production under different energy conditions

• Create modular designs that incorporate multiple plant transporters, cofactor regeneration mechanisms, and optimized growth conditions

5. Metabolomics and proteomics integration:

• Perform untargeted metabolomics to identify metabolite changes

• Use proteomics to measure changes in ATP synthase subunit expression and modification

• Correlate metabolite profiles with ATP synthase activity and transporter expression

• Apply statistical tools to identify significant correlations between energy status and transport activity

How should researchers interpret changes in ATP synthase redox state in different physiological conditions?

Interpreting changes in ATP synthase redox state requires careful consideration of multiple factors:

Analytical Framework:

• Baseline establishment: Always compare experimental redox states to well-characterized control conditions (fully oxidized with methyl viologen and fully reduced with DTT) to establish the dynamic range of redox changes .

• Correlation with physiological parameters: When interpreting redox state changes, consider correlations with:

  • Light intensity and quality

  • Proton motive force measurements

  • ATP/ADP ratios

  • Carbon assimilation rates

  • Stress conditions (drought, temperature, etc.)

• Kinetic considerations: The redox state of ATP synthase represents a dynamic equilibrium. Consider both the rate of oxidation/reduction and the steady-state levels when interpreting data.

Interpretation Table for Common Observations:

• Integration with other regulatory mechanisms: The redox state should be interpreted within the broader context of ATP synthase regulation, including metabolic feedback mechanisms that may operate independently of thiol modulation .

What statistical approaches are most appropriate for analyzing ATP synthase activity data across different experimental conditions?

Statistical analysis of ATP synthase activity requires rigorous approaches to account for the complex nature of the data:

1. Descriptive statistics:

2. Inferential statistics for comparative studies:

• For normally distributed data: Analysis of Variance (ANOVA) followed by appropriate post-hoc tests (Tukey's HSD for all pairwise comparisons or Dunnett's test for comparisons to a control)

• For non-normally distributed data: Kruskal-Wallis test followed by Dunn's post-hoc test

• For repeated measures over time or conditions: Repeated measures ANOVA or mixed-effects models

3. Regression analysis for response surfaces:

• Multiple regression to model ATP synthase activity as a function of multiple variables

• Response surface methodology to identify optimal conditions

• Principal Component Analysis (PCA) to reduce dimensionality in complex datasets

4. Correlation analysis:

• Pearson's correlation for linear relationships between variables

• Spearman's rank correlation for non-linear monotonic relationships

• Partial correlation to control for confounding variables

5. Experimental design considerations:

• Power analysis to determine appropriate sample sizes

• Randomized complete block design to control for experimental batch effects

• Factorial designs to efficiently test multiple factors and their interactions

6. Specialized approaches for kinetic data:

• Non-linear regression for enzyme kinetic parameters (Vmax, Km)

• Global fitting of multiple datasets to shared parameters

• Bootstrap resampling to estimate confidence intervals for kinetic parameters

How can researchers reconcile contradictory data regarding ATP synthase structure-function relationships?

Contradictory data regarding ATP synthase structure-function relationships can arise from multiple sources, including experimental conditions, species differences, or methodological limitations. The following framework provides a systematic approach to reconcile such contradictions:

Systematic Reconciliation Process:

• Methodological validation and standardization:

  • Compare experimental protocols in detail, including buffer compositions, protein preparation methods, and assay conditions

  • Replicate critical experiments using standardized protocols

  • Validate key reagents, particularly antibodies used for detection and quantification

• Critical evaluation of contextual differences:

  • Assess whether contradictions arise from species-specific differences in ATP synthase structure

  • Consider developmental stage, tissue type, and growth conditions as potential sources of biological variation

  • Examine post-translational modifications that might differ between experimental systems

• Integration of multiple data types:

  • Combine structural data (X-ray crystallography, cryo-EM) with functional assays

  • Correlate in vitro biochemical data with in vivo physiological measurements

  • Use molecular dynamics simulations to bridge static structural data with dynamic functional observations

• Model refinement through iterative hypothesis testing:

  • Develop testable hypotheses that could explain apparent contradictions

  • Design experiments specifically targeting these hypotheses

  • Update models based on new data in an iterative process

• Multi-scale integration:

  • Consider how molecular-level observations relate to organelle-level functions

  • Connect organelle-level functions to cellular and whole-plant physiology

  • Develop hierarchical models that can accommodate seemingly contradictory observations at different scales

Case Example: Reconciling Light vs. Metabolic Regulation

Research on ATP synthase has revealed potentially contradictory findings regarding the mechanisms of light-dependent and metabolism-dependent regulation. A systematic approach to reconciling these findings would include:

• Genetic dissection using site-directed γ subunit mutants that specifically affect light regulation but not metabolism-induced regulation

• Biochemical characterization of the mutant proteins to identify structural changes

• Integration of structural data with functional measurements under controlled conditions

• Development of a comprehensive model that explains how these distinct regulatory mechanisms can coexist and interact

Through this systematic approach, researchers can transform apparent contradictions into deeper insights about the complex regulatory networks governing ATP synthase function in chloroplasts.

What are the most promising applications of Atropa belladonna ATP synthase components in synthetic biology?

The integration of Atropa belladonna ATP synthase components with metabolite transport systems represents a frontier in synthetic biology. Based on current research, the following applications show particular promise:

• Enhanced tropane alkaloid production systems: Building on successful incorporation of A. belladonna transporters into yeast, future systems could integrate ATP synthase components to optimize energy coupling with alkaloid biosynthesis pathways .

• Designer organelles with custom energy systems: Creating synthetic organelles with precisely engineered ATP synthase variants could enable new metabolic capabilities in both microbial and plant systems.

• Bio-inspired energy conversion devices: The highly efficient rotary mechanism of ATP synthase could inspire biomimetic energy conversion technologies with applications beyond traditional biological systems.

• Metabolic engineering for stress resistance: Incorporating the regulatory flexibility of plant ATP synthase into other organisms could improve their ability to maintain energy homeostasis under variable environmental conditions.

The continued advancement of these applications will depend on deeper structural and functional characterization of Atropa belladonna ATP synthase components and their interactions with metabolite transport systems.

How might computational approaches advance our understanding of ATP synthase regulation in specialized plant metabolism?

Computational approaches offer powerful tools for unraveling the complex relationships between ATP synthase and specialized metabolism:

• Machine learning for transporter prediction: As demonstrated by the successful application of artificial neural networks to identify TA transporters from A. belladonna, advanced machine learning approaches can significantly reduce the search space when identifying key components of metabolic networks .

• Molecular dynamics simulations: These can provide insights into how redox changes affect ATP synthase structure and function, particularly the conformational changes in the γ subunit regulatory loop containing the redox-active cysteines.

• Systems biology modeling: Integrative models that combine ATP synthesis, metabolite transport, and specialized metabolic pathways can predict emergent properties and identify control points for optimization.

• Comparative genomics and phylogenetics: These approaches can reveal how ATP synthase components have co-evolved with specialized metabolic pathways in different plant lineages, potentially identifying novel regulatory mechanisms.