Recombinant Rhodopirellula baltica Chorismate synthase (aroC)

Intermediate Research Questions

• How does the regulation of R. baltica Chorismate synthase expression change during different growth phases?

Transcriptional profiling of R. baltica has revealed that the chorismate synthase gene (RB6822/aroC) is significantly upregulated during the stationary phase compared to exponential growth phases. This upregulation is part of a broader pattern of increased expression of genes involved in phenylalanine, tyrosine, and tryptophan biosynthesis . The table below summarizes the regulatory patterns observed across growth phases:

This upregulation pattern correlates with proteome data and suggests that increased aromatic amino acid biosynthesis may be important for R. baltica adaptation to nutrient limitation and stress conditions during stationary phase .

• Data Contradiction Analysis: Why do evolutionary studies show inconsistent phylogenetic placements of R. baltica Chorismate synthase?

Phylogenetic analyses of chorismate synthase (AroC) genes have produced conflicting results regarding the placement of R. baltica relative to other taxonomic groups. The most significant contradiction involves the branching order between R. baltica, red algae, and plants .

Several factors contribute to these phylogenetic ambiguities:

• Long Branch Attraction: The rapid evolution of certain lineages creates artificial groupings in tree reconstructions.

• Horizontal Gene Transfer (HGT): Evidence suggests multiple prokaryote-to-eukaryote gene transfers affecting the shikimate pathway, complicating phylogenetic signals.

• Model Selection Impact: Different evolutionary models produce different tree topologies, particularly affecting the placement of R. baltica.

Researchers testing alternative topologies using Shimodaira-Hasegawa (SH) and approximately unbiased (AU) tests found that enforcing Plantae monophyly while adjusting the R. baltica placement could not be statistically rejected, indicating uncertainty in the true evolutionary relationships .

This contradiction highlights the complexity of evolutionary relationships in metabolic pathways and suggests that chorismate synthase evolution may involve multiple horizontal gene transfer events that obscure traditional phylogenetic signals.

Advanced Research Questions

• What methodological approaches should be used to accurately measure Recombinant R. baltica Chorismate synthase activity in vitro?

Accurate measurement of R. baltica Chorismate synthase activity requires careful attention to several methodological considerations:

A. Coupled Assay System:
The most reliable approach is a coupled assay involving EPSP, chorismate synthase, and anthranilate synthase. This system allows forward coupling of the chorismate synthase reaction, leading to anthranilate formation, which can be detected spectrofluorometrically (emission maximum at 390 nm) .

Reaction Mixture Components:

• 3 mM MgSO₄

• 7.5 mM L-Glutamine

• 22.5 mM (NH₄)₂SO₄

• 1 mM dithiothreitol (DTT)

• 10 μM FMN

• 80 μM EPSP (substrate)

• 4 μM recombinant chorismate synthase

• ~20 μM anthranilate synthase

• 100 mM potassium phosphate buffer (pH 7.6)

• 500 μM NADPH (added to initiate reaction)

B. Cofactor Considerations:
Since chorismate synthase requires reduced FMN (FMNH₂) for activity but doesn't consume it, researchers must ensure sufficient reduced flavin is available. This can be accomplished by:

• Adding NADPH and relying on intrinsic FMN reductase activity (if present in the preparation)

• Pre-reducing FMN with sodium dithionite under anaerobic conditions

• Light-mediated reduction of FMN in the presence of EDTA

C. Data Collection and Analysis:

• Incubate reaction mixture at 37°C for 60 seconds before recording

• Monitor fluorescence emission at 390 nm (excitation at 340 nm)

• Collect data points every 12 seconds for 5 minutes

• Extract initial velocities from the first 15 data points

• Plot relative rates versus log(inhibitor concentration) when testing inhibitors

• Determine IC₅₀ values using nonlinear curve fitting

This methodology has been validated for measuring both native enzyme activity and inhibition by potential antimicrobial compounds.

• How can structural bioinformatics be applied to identify potential inhibitors of R. baltica Chorismate synthase?

A comprehensive structural bioinformatics approach to identify potential inhibitors of R. baltica Chorismate synthase should follow this methodological framework:

A. Homology Model Construction:

• Identify suitable templates (e.g., crystal structure from Helicobacter pylori, PDB: 1UMF)

• Align sequences using MUSCLE or CLUSTALW

• Generate homology models using Modeller or SWISS-MODEL

• Validate model quality using PROCHECK, VERIFY3D, and ERRAT

• Refine models through molecular dynamics simulations

B. Binding Site Analysis:

• Identify conserved regions that cluster around FMN binding site

• Map highly flexible loops that may influence substrate access

• Characterize the tetrameric interface contributions to the active site

• Analyze non-planar conformation of the isoalloxazine ring of bound FMN

• Determine if the binding site is formed largely by a single subunit with contributions from a neighboring subunit

C. Virtual Screening Protocol:

• Prepare a diverse compound library (natural products, FDA-approved drugs, and synthetic compounds)

• Perform high-throughput virtual screening using molecular docking programs like AutoDock Vina or GLIDE

• Apply pharmacophore filters based on key interactions observed in the binding site

• Rank compounds based on predicted binding energies and interaction patterns

• Cluster compounds to ensure chemical diversity in hit selection

D. Molecular Dynamics Validation:

• Subject top hits to molecular dynamics simulations (5-10 ns minimum)

• Analyze root mean square deviation (RMSD) and root mean square fluctuation (RMSF) profiles

• Calculate binding free energies using MM/PBSA or MM/GBSA methods

• Identify compounds with stable binding modes across the simulation timeframe

E. ADMET Prediction:

• Filter compounds based on predicted absorption, distribution, metabolism, excretion, and toxicity profiles

• Prioritize compounds with favorable drug-like properties

• Eliminate compounds with predicted toxicity issues

This methodology has been successfully applied to identify inhibitors of chorismate synthase from other organisms, such as compound CP1 that inhibits Paracoccidioides brasiliensis chorismate synthase with an IC₅₀ of 47 ± 5 μM .

• What are the functional differences between bacterial (R. baltica) and fungal chorismate synthases that could be exploited for selective inhibition?

Bacterial (including R. baltica) and fungal chorismate synthases exhibit several critical functional differences that can be exploited for selective inhibitor design:

A. Cofactor Reduction Mechanism:

• Bacterial enzymes (R. baltica): Monofunctional; require exogenous sources of reduced FMN

• Fungal enzymes: Bifunctional; possess an intrinsic NADPH-dependent FMN reductase activity

This fundamental difference in how the enzymes acquire their essential reduced FMN cofactor presents a major opportunity for selective inhibition by targeting either:

• The interface between the reductase and synthase domains in fungal enzymes

• The unique conformational states associated with the bifunctional activity

B. Structural Organization:

• Bacterial enzymes: Typically exist as separate proteins in the shikimate pathway

• Fungal enzymes: Often part of the pentafunctional AROM complex that includes conserved domains homologous to AroB, AroA, AroL/K, AroD, and AroE

C. Cofactor Binding Site Architecture:
Detailed structural analysis reveals differences in the FMN binding pocket between bacterial and fungal enzymes, particularly in:

• Loop regions surrounding the isoalloxazine ring

• Residues interacting with the ribityl chain

• Electrostatic environment around the phosphate group

D. Experimental Strategy for Selective Inhibitor Development:

• Design compounds that interact with the unique reductase-synthase interface in fungal enzymes

• Target allosteric sites that exist only in one enzyme type

• Exploit differences in the quaternary structure organization

• Develop transition-state analogs that bind differently based on subtle active site variations

• Create mechanism-based inhibitors that are activated by the NADPH-dependent activity unique to fungal enzymes

This approach has already yielded promising results in the development of antifungal compounds like CP1, which demonstrates selective inhibition of fungal chorismate synthases while showing minimal effects on bacterial orthologs .

• How can CRISPR/dCas9-based approaches be utilized to study R. baltica Chorismate synthase regulation and function?

CRISPR/dCas9-based systems offer powerful tools for studying R. baltica Chorismate synthase regulation and function without permanently altering the genome. Based on recent advances in similar systems, the following methodological framework is recommended:

A. Transcriptional Regulation Analysis:

• CRISPRi (Interference): Use nuclease-deficient Cas9 (dCas9) fused to repressor domains to downregulate aroC expression

  • Design sgRNAs targeting the aroC promoter region or coding sequence

  • Use a KRAB repressor domain fused to dCas9 for robust repression

  • Quantify repression effects using RT-qPCR and proteomics

• CRISPRa (Activation): Use dCas9 fused to activator domains to upregulate aroC expression

  • Employ the scaffold guide RNA (scgRNA) system that connects activator domains to dCas9

  • Implement a modular cloning strategy for efficient construct generation

  • Compare with classic overexpression approaches

B. Methodological Implementation for R. baltica:

• Design species-specific promoters compatible with R. baltica

• Optimize codon usage of dCas9 for efficient expression

• Use genomic integration into the RGI2 locus for stable expression

• Apply appropriate selection markers (zeocin 50 mg L⁻¹ or nourseothricin 100 mg L⁻¹)

• Include eGFP reporter systems to monitor expression efficiency

C. Experimental Design for Functional Studies:

• Create a gradient of aroC expression levels using different sgRNA designs

• Analyze metabolic flux through the shikimate pathway under varying aroC expression

• Perform comparative proteomics to identify compensatory mechanisms

• Investigate growth phase-dependent effects by activating/repressing aroC during different phases

• Study protein-protein interactions using dCas9-based proximity labeling

D. Sophisticated Applications:

• Multiplexed regulation of entire shikimate pathway genes

• Temporal control using inducible systems (e.g., tetracycline or arabinose inducible promoters)

• Single-cell analysis of expression heterogeneity using fluorescent reporters

• Synthetic metabolic circuits incorporating aroC regulation

This approach allows unprecedented control over gene expression without permanent genetic modifications, facilitating detailed studies of aroC function under diverse conditions.

• What complex experimental approaches can be used to investigate the relationship between R. baltica Chorismate synthase activity and cellular morphological changes during life cycle transitions?

Investigating the relationship between R. baltica Chorismate synthase activity and morphological transitions requires integrating multiple sophisticated experimental approaches:

A. Quantitative Single-Cell Analysis System:

• Microfluidic Cell Tracking:

  • Culture R. baltica in microfluidic devices that enable long-term imaging

  • Track individual cells through division and morphological transitions

  • Correlate with fluorescent reporters of aroC expression

• Time-Lapse Microscopy with Fluorescent Biosensors:

  • Create aroC promoter-driven fluorescent protein fusions

  • Develop FRET-based biosensors for chorismate concentration

  • Image cells throughout growth phases (44h, 62h, 82h, 96h, 240h)

  • Quantify correlation between fluorescence intensity and morphological changes (swarmer cells, budding cells, rosette formation)

B. Multi-omics Integration Protocol:

• Create temporally-synchronized cultures using filtration techniques

• Collect samples at defined time points across the life cycle

• Perform parallel analyses:

  • Transcriptomics (RNA-seq of aroC and related pathway genes)

  • Proteomics (quantitative analysis of AroC protein levels)

  • Metabolomics (levels of chorismate and downstream metabolites)

  • Morphological characterization (microscopy and flow cytometry)

• Apply integrative computational approaches to correlate data across platforms

C. Genetic Manipulation with Time-Resolved Readouts:

• Controlled aroC Expression System:

  • Implement an inducible promoter system for aroC

  • Create strains with varying aroC expression levels

  • Analyze effects on:

    • Timing of morphological transitions

    • Rosette formation efficiency

    • Cell wall composition changes

    • Holdfast substance production

• Protein Engineering Approach:

  • Create catalytically active vs. inactive aroC variants

  • Develop temperature-sensitive aroC mutants for temporal control

  • Express fluorescently tagged AroC to track localization during transitions

D. Data Integration and Modeling:
Develop mathematical models that integrate:

• Growth phase-specific aroC expression levels

• Measured chorismate concentrations

• Quantified morphological parameters

• Cell population heterogeneity measures

This multifaceted approach would provide unprecedented insight into how chorismate synthase activity influences or responds to the complex morphological changes observed during R. baltica's life cycle transitions, particularly the formation of rosettes during stationary phase .