Recombinant Bradyrhizobium japonicum Ribose 1,5-bisphosphate phosphokinase PhnN (phnN)

Basic Research Questions

• What is the role of PhnN in Bradyrhizobium japonicum metabolism?

  PhnN (Ribose 1,5-bisphosphate phosphokinase) in B. japonicum likely plays a role in phosphonate metabolism and potentially in the Calvin-Benson-Bassham (CBB) cycle adaptation. While the specific function in B. japonicum hasn't been fully characterized, studies of similar enzymes suggest it catalyzes the phosphorylation of ribose 1,5-bisphosphate, which may serve as an alternative pathway for carbon fixation under certain conditions . Given that B. japonicum contains RuBisCO and other components of the CBB cycle, PhnN may function in metabolic flexibility, particularly during symbiotic lifestyle transitions. To investigate its role, researchers should consider comparative metabolomics approaches between wild-type and phnN mutant strains under various carbon source conditions.

• How should researchers purify recombinant B. japonicum PhnN for enzymatic studies?

  Purification of recombinant B. japonicum PhnN typically involves:

  Step	Method	Buffer Conditions	Notes
  Expression system	E. coli BL21(DE3)	-	Optimize codon usage for expression
  Induction	0.5 mM IPTG	18°C, 16 hours	Lower temperature reduces inclusion bodies
  Lysis	Sonication	50 mM Tris-HCl pH 8.0, 300 mM NaCl, 10% glycerol	Include protease inhibitors
  Purification	Ni-NTA affinity	Above buffer + 20-250 mM imidazole gradient	For His-tagged protein
  Secondary purification	Size exclusion	20 mM Tris-HCl pH 7.5, 150 mM NaCl	Removes aggregates
  Storage	Flash freeze	Add 10% glycerol	Store at -80°C

  When designing expression constructs, consider that B. japonicum has a higher GC content than E. coli, which may necessitate codon optimization . Activity assays should be performed immediately after purification, as phosphokinases can lose activity during storage .

• What are the optimal conditions for assaying recombinant B. japonicum PhnN activity?

  Based on studies of similar phosphokinases, the optimal assay conditions for B. japonicum PhnN would likely be:

  Parameter	Optimal Condition	Notes
  Temperature	28-30°C	Corresponds to B. japonicum growth temperature
  pH	7.0-7.5	Most bacterial phosphokinases show optimal activity in this range
  Buffer	50 mM HEPES or Tris-HCl	Both buffers maintain stability in this pH range
  Cofactors	5-10 mM MgCl₂	Essential for kinase activity
  ATP concentration	1-5 mM	As phosphate donor
  Substrate concentration	0.1-1 mM ribose 1,5-bisphosphate	Determine Km experimentally

  Activity can be measured by coupling ATP hydrolysis to NADH oxidation through pyruvate kinase and lactate dehydrogenase enzymes. Alternatively, use malachite green assay to detect released phosphate . Always include enzyme-free controls as phosphate contamination is common.

• How is the phnN gene regulated in B. japonicum under different growth conditions?

  While specific regulation of phnN in B. japonicum hasn't been directly studied, similar metabolic genes in Bradyrhizobium show distinct regulation patterns:

  • Free-living conditions: PhnN expression may be regulated by phosphate limitation, similar to the phn operon in other bacteria .

  • Symbiotic conditions: Expression likely changes during the transition from free-living to bacteroid state, as seen with other metabolic genes .

  • Carbon source availability: Regulation may be coordinated with RuBisCO and other CBB cycle components, especially in conditions where alternative carbon metabolism is advantageous .

  To study regulation, researchers should employ RT-qPCR to measure phnN expression under varied conditions and consider creating a phnN-reporter fusion to visualize expression patterns during root colonization and nodule development.

Advanced Research Questions

• How does mutation of the phnN gene affect B. japonicum's symbiotic relationship with legume hosts?

  To investigate this question, researchers should:

  1. Create a precise deletion of phnN using allelic exchange methods similar to those used for cbbLS mutations in B. diazoefficiens .

  2. Assess nodulation kinetics by inoculating soybean plants with the ΔphnN mutant vs. wild-type.

  3. Evaluate competitive ability by co-inoculating plants with a 1:1 mixture of wild-type and ΔphnN strains (one tagged with GFP) .

  4. Measure nitrogen fixation using acetylene reduction assays.

  5. Examine bacteroid development through microscopy.

  Based on studies of other metabolic genes, PhnN might affect competitiveness for nodulation rather than nodulation ability itself. For example, mutations in RuBisCO genes reduced competitiveness for nodulation and long-term adhesion to soybean roots without affecting the ability to form nodules . Similarly, PHA synthase mutants showed altered competitiveness correlating with their polymer levels .

• What are the kinetic parameters of recombinant B. japonicum PhnN and how do they compare to PhnN from other species?

  A comprehensive kinetic characterization should include:

  Parameter	Determination Method	Expected Range
  Km for ribose 1,5-bisphosphate	Steady-state kinetics	50-500 μM
  Km for ATP	ATP saturation curves	100-500 μM
  kcat	Product formation rate/enzyme concentration	1-50 s⁻¹
  pH optimum	Activity profiling across pH range	pH 6.5-8.0
  Temperature stability	Pre-incubation at various temperatures	Stable to ~40°C
  Metal ion requirements	Activity with different divalent cations	Mg²⁺, Mn²⁺ > Ca²⁺

  For comparative studies, express and purify PhnN from E. coli and other Bradyrhizobium species under identical conditions . Use enzyme kinetics software to fit data to appropriate models (Michaelis-Menten, substrate inhibition, etc.). The comparison may reveal adaptations specific to B. japonicum's symbiotic lifestyle.

• How does phosphate availability in soil affect the expression and activity of PhnN in B. japonicum?

  Phosphate availability likely influences PhnN expression through regulatory networks similar to those in other soil bacteria. Research approach should include:

  1. Culture B. japonicum under defined phosphate concentrations (0.1-10 mM).

  2. Measure phnN transcription using RT-qPCR.

  3. Assess protein levels through Western blotting.

  4. Determine in vivo enzyme activity in cell extracts.

  5. Analyze global transcriptome response to connect PhnN regulation to other metabolic pathways.

  Under phosphate limitation, B. japonicum and other rhizobia typically induce phosphate acquisition systems . If PhnN is involved in alternative phosphate metabolism pathways, its expression may increase under phosphate limitation. This adaptation could be particularly important during rhizosphere colonization, where phosphate can be limiting and competition with other microorganisms is intense.

• What structural features contribute to substrate specificity of B. japonicum PhnN?

  To address this question, researchers should:

  1. Determine the crystal structure of B. japonicum PhnN, ideally with bound substrate.

  2. Identify the active site residues through structural comparison with homologous phosphokinases.

  3. Perform site-directed mutagenesis of conserved amino acids in the active site.

  4. Conduct molecular dynamics simulations to understand substrate binding.

  Key structural elements likely include:

  • A nucleotide-binding domain for ATP coordination

  • Conserved lysine and arginine residues for phosphate group interaction

  • A substrate-binding pocket shaped to accommodate ribose 1,5-bisphosphate

  The enzyme structure would provide insights into how PhnN has evolved substrate specificity compared to other phosphokinases like phosphoribulokinase (PRK), which are crucial in the CBB cycle .

• How does PhnN contribute to metabolic adaptations of B. japonicum during environmental transitions?

  PhnN likely plays a role in metabolic flexibility during transitions between free-living and symbiotic states. To investigate:

  1. Compare metabolic profiles of wild-type and ΔphnN mutants using LC-MS/MS metabolomics:

     • During free-living growth with different carbon sources

     • During early root colonization

     • Within established nodules

  2. Measure carbon flux through:

     • 13C-labeling experiments

     • Metabolic flux analysis

  3. Examine co-expression networks of phnN with other metabolic genes.

  B. japonicum undergoes significant metabolic reprogramming during symbiosis establishment . Other metabolic enzymes like RuBisCO affect competitiveness for nodulation and long-term root adhesion , suggesting that metabolic versatility is crucial during these transitions. PhnN might contribute to this adaptability by enabling alternative phosphate or carbon metabolism pathways when transitioning between different environmental niches.

• What approaches can be used to investigate the evolutionary history of phnN in Bradyrhizobium species?

  To explore the evolutionary history of phnN:

  1. Perform phylogenetic analysis:

     • Construct phylogenetic trees using phnN sequences from diverse Bradyrhizobium strains

     • Compare with phylogenies based on housekeeping genes (atpD, gyrB, recA, rpoB, rpoD)

     • Assess congruence to identify potential horizontal gene transfer events

  2. Analyze genomic context:

     • Examine synteny of phnN and surrounding genes across species

     • Look for mobile genetic elements or genomic islands

  3. Compare codon usage and GC content to identify recent acquisitions.

  4. Use Bayesian methods to estimate divergence times.

  Studies of the cbb operon in Hyphomicrobiales showed consistent distribution between metabolic and housekeeping genes, indicating lack of horizontal transfer . Similar analysis for phnN would reveal whether it shares this evolutionary history or has been acquired through horizontal transfer, particularly given B. japonicum's capacity for horizontal gene transfer of its symbiotic genomic island .

Experimental Applications

• What expression systems are most effective for producing functional recombinant B. japonicum PhnN?

  Based on experiences with similar enzymes, several expression systems can be considered:

  Expression System	Advantages	Limitations	Yield Expectations
  E. coli BL21(DE3)	Fast growth, high yield	Potential folding issues	10-30 mg/L culture
  E. coli Arctic Express	Better folding at low temperature	Lower yields	5-15 mg/L culture
  Yeast (P. pastoris)	Post-translational modifications	Longer process	5-20 mg/L culture
  Bradyrhizobium host	Native folding environment	Low yields, slower growth	1-5 mg/L culture

  For E. coli-based expression, consider:

  • Codon optimization for low-GC preference of E. coli

  • Fusion tags (His6, GST, or MBP) to enhance solubility

  • Induction at 18-20°C to minimize inclusion body formation

  • Co-expression with chaperones for improved folding

  Purify using a combination of affinity chromatography and size exclusion chromatography to obtain homogeneous protein preparations. Always verify activity after purification, as some recombinant phosphokinases can lose activity during purification steps .

• How can the interaction between PhnN and other B. japonicum metabolic enzymes be studied?

  To investigate protein-protein interactions involving PhnN:

  1. Pull-down assays: Use tagged PhnN to identify interaction partners by mass spectrometry.

  2. Bacterial two-hybrid system: Screen for direct interactions with candidate proteins.

  3. Co-immunoprecipitation: Isolate protein complexes from B. japonicum lysates using anti-PhnN antibodies.

  4. Blue native PAGE: Separate intact protein complexes to identify PhnN-containing assemblies.

  5. Proximity labeling approaches (e.g., BioID): Identify proteins in close proximity to PhnN in vivo.

  6. Fluorescence microscopy: Use fluorescent protein fusions to visualize co-localization.

  Given that B. japonicum possesses multiple metabolic pathways for adaptation to different environments , PhnN likely interacts with other enzymes involved in phosphorus metabolism or carbon fixation. Of particular interest would be potential interactions with enzymes of the CBB cycle, such as RuBisCO and phosphoribulokinase , which could indicate functional integration of these pathways.