Recombinant Pseudomonas putida Aspartyl/glutamyl-tRNA (Asn/Gln) amidotransferase subunit B (gatB)

What is the function of Aspartyl/glutamyl-tRNA (Asn/Gln) amidotransferase subunit B in Pseudomonas putida?

The Aspartyl/glutamyl-tRNA (Asn/Gln) amidotransferase subunit B (gatB) is a critical component of the GatCAB complex in P. putida, which plays an essential role in indirect aminoacylation pathways. This enzyme is responsible for converting misacylated tRNAs (Glu-tRNA^Gln and Asp-tRNA^Asn) to correctly charged Gln-tRNA^Gln and Asn-tRNA^Asn, which are fundamental for accurate protein synthesis. In P. putida, which has emerged as an important chassis for biotechnological applications, gatB contributes to the organism's translational fidelity, particularly under varying environmental conditions when amino acid availability may fluctuate.

How can I clone and express the gatB gene in Pseudomonas putida?

Cloning and expressing gatB in P. putida requires careful consideration of expression systems compatible with this non-model organism. Recent advancements in P. putida genetic engineering offer several approaches:

• Plasmid-based expression: Utilize broad-host-range vectors suitable for Pseudomonas, such as pBBR1MCS derivatives or pSW-2 systems.

• Genomic integration: The pEMG/pSW system has proven valuable for targeted genome engineering in Pseudomonas, enabling integration of heterologous gene clusters. Recent improvements have resulted in a one-plasmid design (pEMG-RIS) that allows one engineering cycle to be completed in just 3 days .

• Expression optimization: Consider using native P. putida promoters or engineered versions with improved strength and regulation to control gatB expression.

• Codon optimization: Adjust the coding sequence to match P. putida's codon usage preferences for improved translation efficiency.

Importantly, when designing your expression construct, include appropriate purification tags (His6, FLAG, etc.) that will facilitate subsequent protein isolation and characterization.

What growth conditions are optimal for expression of recombinant gatB in Pseudomonas putida?

Optimal expression of recombinant gatB in P. putida typically requires:

• Growth medium: M9 minimal medium supplemented with appropriate carbon sources (e.g., glucose or cellobiose at 0.2-0.4%) provides controlled conditions for protein expression .

• Temperature: Standard cultivation at 28-30°C is recommended, as P. putida grows optimally in this range and protein folding is generally more efficient at these moderate temperatures.

• Aeration: Vigorous aeration (200-250 rpm) in baffled flasks or bioreactors is critical, as P. putida is an obligate aerobe.

• Induction parameters: If using an inducible promoter system, optimize inducer concentration and induction timing. For XylS/Pm or LacI/PT7 systems, induction during early-mid exponential phase (OD600 ≈ 0.3-0.5) often yields good results.

• Growth phase: For constitutive expression, harvesting during mid-logarithmic phase typically provides the highest yield of properly folded recombinant protein.

• Antibiotic selection: Maintain appropriate selection pressure (e.g., 60 μg/ml streptomycin) to ensure plasmid retention .

What CRISPR-Cas9 methods are most effective for engineering gatB in Pseudomonas putida?

CRISPR-Cas9 engineering of gatB in P. putida can be accomplished using several refined approaches:

• pEMG-RIS system: This recently developed one-plasmid system combines the double-strand break-introducing gene I-SceI and the sacB counterselection marker into a single vector. This system allows for rapid genome editing in P. putida, reducing the engineering cycle to just 3 days .

• sgRNA design considerations:

  • Target sites should be selected with minimal off-target effects

  • PAM site availability within the gatB gene sequence is critical

  • Efficiency scores should be calculated using tools optimized for Pseudomonas

• Homology-directed repair (HDR) template design:

  • For point mutations: 500-1000 bp homology arms flanking the target site

  • For gene replacement: Homology arms of similar length with the heterologous gatB variant

  • Silent mutations in the PAM site prevent re-cutting after editing

• Delivery and selection protocols:

  • Electroporation is the preferred method for introducing CRISPR components

  • Two-step selection protocol with antibiotic resistance followed by counterselection

  • Colony PCR and sequencing to verify successful editing

How can adaptive laboratory evolution (ALE) be utilized to optimize gatB function in Pseudomonas putida?

Adaptive laboratory evolution offers a powerful approach for optimizing gatB function in P. putida, particularly when combined with rational engineering:

• Experimental setup: Implement a dual-chamber semi-continuous log-phase bioreactor with anti-biofilm layout, specifically designed for P. putida long-term cultivation . This system maintains cells in a defined OD600 range (0.1-0.5) through automatic dilution cycles.

• Selection strategy:

  • Create a gatB-compromised strain with marginally viable function

  • Apply selective pressure that requires optimal gatB activity

  • Maintain continuous growth for 42-45 days, allowing beneficial mutations to emerge

• Monitoring evolution:

  • Track growth rate improvements over time

  • Sample populations at regular intervals (e.g., every 5-7 days)

  • Preserve evolved populations for subsequent analysis

• Mutation identification:

  • Whole-genome sequencing of evolved clones to identify beneficial mutations

  • Particular attention to RNA polymerase genes (rpoB, rpoC, rpoD) which frequently harbor beneficial mutations in ALE experiments

  • Variant calling to identify SNPs, insertions, and deletions

• Validation of evolved strains:

  • Functional assays to quantify gatB activity improvement

  • Growth rate comparisons between ancestral and evolved strains

  • Reintroduction of identified mutations into the original strain to confirm their effect

This approach parallels successful ALE experiments with P. putida strains engineered to metabolize D-xylose, where mutations in the RNA polymerase (specifically rpoC with a Pro51Leu mutation) emerged to enhance fitness .

How does the structure-function relationship of gatB in Pseudomonas putida compare to homologs in other bacterial species?

The structure-function relationship of gatB in P. putida exhibits both conserved features and unique characteristics compared to homologs in other bacterial species:

• Domain organization:

  • N-terminal domain: Contains ATP-binding site with Walker A and B motifs

  • Central domain: Mediates interactions with gatA and gatC subunits

  • C-terminal domain: Involved in tRNA recognition and binding

• Key functional residues:

  Domain	Residue Position	Function	Conservation across species
  N-terminal	Lys41-Ser48	Walker A motif (ATP binding)	Highly conserved
  N-terminal	Asp166-Glu172	Walker B motif (ATP hydrolysis)	Highly conserved
  Central	Arg210-Phe230	GatA interaction interface	Moderately conserved
  C-terminal	Asp286-Lys310	tRNA acceptor stem recognition	Variable region

• Distinctive features in P. putida:

  • Specific amino acid substitutions in the C-terminal domain likely confer unique substrate specificity

  • Different surface charge distribution compared to homologs from other species

  • Potential adaptations related to P. putida's metabolic versatility and environmental adaptability

• Evolutionary conservation:

  • Core catalytic residues show high conservation across bacterial species

  • Greatest sequence divergence occurs in regions involved in protein-protein interactions

  • Coevolution patterns with gatA and gatC subunits are evident

Understanding these structural elements is essential for rational engineering of gatB to enhance P. putida's capabilities as a biotechnological chassis.

How does co-expression of heterologous transporters affect gatB expression and function in engineered Pseudomonas putida strains?

Co-expression of heterologous transporters in P. putida can significantly impact gatB expression and function through several mechanisms:

• Metabolic burden effects:

  • Expression of transport proteins such as Glf from Zymomonas mobilis (glucose transporter) or LacY from Escherichia coli (cellobiose transporter) places additional demands on the cellular translation machinery

  • This burden may reduce resources available for gatB expression, particularly in high-copy plasmid systems

• Altered substrate influx:

  • Increased transport of carbon sources leads to metabolic bottlenecks and enzyme saturation

  • The resulting metabolic imbalance can trigger global transcriptional changes affecting gatB expression

• Pyruvate accumulation effects:

  • Heterologous transporters in P. putida have been shown to result in pyruvate accumulation under aerobic conditions

  • Elevated pyruvate levels alter cellular redox balance and energy metabolism, which may indirectly impact gatB function

• Stress response activation:

  • Unregulated substrate uptake can trigger stress responses that reorganize cellular resource allocation

  • RNA polymerase mutations (such as in rpoC) frequently emerge to compensate for these imbalances

• Optimization strategies:

  • Careful selection of promoter strengths to balance expression of transporters and gatB

  • Implementation of dynamic regulatory circuits to coordinate expression

  • Integration of transporters into the chromosome rather than using plasmid-based expression to reduce copy number effects

These considerations are particularly important when designing P. putida strains for biotechnological applications where both efficient substrate utilization and accurate protein synthesis are critical.

What are the most effective protocols for purifying recombinant gatB from Pseudomonas putida?

Purification of recombinant gatB from P. putida requires specialized protocols to account for the organism's unique cellular characteristics:

• Cell lysis optimization:

  • French press (preferred): 15,000-20,000 psi, 2-3 passes

  • Sonication alternative: 6 cycles of 30 seconds on/30 seconds off at 40% amplitude

  • Lysis buffer: 50 mM Tris-HCl pH 8.0, 300 mM NaCl, 10% glycerol, 1 mM DTT, protease inhibitor cocktail

• Affinity chromatography:

  • His-tagged gatB: Nickel-NTA columns with imidazole gradient elution (20-250 mM)

  • Strep-tagged gatB: Strep-Tactin resins with desthiobiotin elution

  • GST-tagged gatB: Glutathione Sepharose with reduced glutathione elution

• Secondary purification:

  • Ion exchange chromatography: HiTrap Q or SP columns depending on theoretical pI

  • Size exclusion chromatography: Superdex 200 column in 25 mM HEPES pH 7.5, 150 mM NaCl, 5% glycerol

• Complex purification strategy:

  • For isolation of the complete GatCAB complex, consider tandem affinity purification

  • Co-expression of differentially tagged gatA, gatB, and gatC subunits

  • Sequential affinity steps to ensure complex integrity

• Quality control assessments:

  • SDS-PAGE and western blotting to confirm purity and identity

  • Dynamic light scattering to assess homogeneity

  • Thermal shift assays to evaluate stability

  • Enzymatic activity assays using misacylated tRNA substrates

Notably, these protocols can be integrated with approaches used for other recombinant proteins in P. putida, such as those developed for the purification of enzymes involved in cellulose and xylose metabolism .

How can I design effective mutagenesis studies to investigate gatB function in Pseudomonas putida?

Designing effective mutagenesis studies for gatB in P. putida requires a systematic approach:

• Target selection strategies:

  • Structure-guided: Focus on conserved catalytic residues, subunit interaction interfaces, or substrate binding regions

  • Sequence conservation analysis: Identify residues with varying conservation across bacterial species

  • Random mutagenesis: Error-prone PCR with titratable mutation rates for unbiased functional mapping

• Mutagenesis methods for P. putida:

  • Site-directed mutagenesis: The pEMG-RIS system enables precise genomic modifications with single plasmid architecture

  • CRISPR-Cas9 approach: For targeted modifications with reduced time requirements

  • Saturation mutagenesis: For comprehensive analysis of critical residues/regions

• Phenotypic screening strategies:

  • Growth rate analysis under conditions requiring efficient gatB function

  • Reporter systems linked to translation accuracy

  • Proteome-wide analysis of mistranslation frequencies

• Structure-function correlation:

  Mutation Type	Expected Phenotype	Screening Method
  Active site residues	Complete loss of function	Viability/severe growth defects
  Substrate binding	Altered substrate specificity	Comparative growth on different amino acid sources
  Subunit interface	Complex stability issues	Co-immunoprecipitation efficiency
  Allosteric sites	Regulatory defects	Response to amino acid limitation stress

• Integration with genome-scale metabolic models:

  • Update existing P. putida metabolic models to account for gatB mutations

  • Use constraints based on proteomic and kinetic data to predict phenotypic effects

  • Validate model predictions with experimental data

This approach mirrors successful mutagenesis studies in P. putida, such as those that investigated the effects of gcd deletion on glucose metabolism and identified beneficial RNA polymerase mutations during adaptive evolution .

What analytical methods are most appropriate for monitoring gatB expression levels in Pseudomonas putida?

Monitoring gatB expression in P. putida requires specialized analytical approaches suited to this non-model organism:

• Transcriptional analysis methods:

  • RT-qPCR: Design primers specific to gatB with minimal cross-reactivity

  • RNA-Seq: For genome-wide expression analysis to place gatB in its regulatory context

  • Northern blotting: For direct visualization of transcript size and abundance

  • Promoter-reporter fusions: Use of fluorescent proteins (msfGFP) or luciferase for in vivo monitoring

• Protein-level quantification:

  • Western blotting: Using gatB-specific antibodies or tag-specific detection

  • Targeted proteomics: Selected/Multiple Reaction Monitoring (S/MRM) for absolute quantification

  • ELISA: For high-throughput screening of multiple samples

  • Flow cytometry: If using fluorescent protein fusions for single-cell resolution

• Activity-based measurements:

  • Enzymatic assays: Monitoring ATP hydrolysis coupled to transamidation activity

  • tRNA charging assays: Measuring correctly charged versus misacylated tRNAs

  • Translation fidelity reporters: Systems that produce signal upon mistranslation events

• Integrated multi-omics approaches:

  • Combined transcriptomics, proteomics, and metabolomics

  • Correlation of gatB expression with metabolic flux redistributions

  • Integration with genome-scale metabolic models

• Data analysis considerations:

  • Normalization strategies specific to P. putida's gene expression dynamics

  • Appropriate reference genes for relative quantification

  • Statistical approaches for time-series data from bioreactor experiments

These methods can be implemented in the context of evolving P. putida strains, similar to approaches used in long-term stationary phase evolutionary experiments that tracked genomic and transcriptomic changes .

How can engineered gatB variants improve Pseudomonas putida as a chassis for bioproduction?

Engineered gatB variants offer several strategic advantages for enhancing P. putida as a bioproduction platform:

• Translation optimization for heterologous proteins:

  • Custom-tuned gatB variants can improve translation accuracy for non-native coding sequences

  • Variants with altered substrate specificity could better accommodate the amino acid composition of target recombinant proteins

• Stress tolerance enhancement:

  • Engineered gatB variants with improved stability under stressed conditions

  • Variants that maintain function during nutrient limitation, similar to adaptations observed during prolonged stationary phase

• Metabolic flux optimization:

  • gatB variants that reduce cellular resource allocation to translation quality control

  • Integration with pyruvate overproduction strategies observed in other engineered P. putida strains

• Enhanced co-utilization of carbon sources:

  • Synchronized translation efficiency during simultaneous metabolism of multiple substrates

  • Particular relevance for lignocellulosic feedstock utilization (glucose/cellobiose co-utilization)

• Protein production applications:

  gatB Engineering Approach	Expected Outcome	Potential Application
  Thermostability enhancement	Improved function at elevated temperatures	High-temperature fermentations
  Substrate specificity alteration	Accommodation of non-canonical amino acids	Production of novel proteins
  Expression level optimization	Balanced resource allocation	High-yield bioproduction processes
  Complex stability improvement	Enhanced translation accuracy	Production of complex therapeutic proteins

These applications align with the current trajectory of P. putida development as an increasingly important chassis for producing valuable bioproducts .

What computational approaches can predict the effects of gatB mutations on Pseudomonas putida metabolism?

Advanced computational approaches can effectively predict how gatB mutations impact P. putida's metabolism:

• Genome-scale metabolic modeling:

  • Integration of gatB function into existing P. putida metabolic models

  • Constraint-based modeling approaches (FBA, MOMA, ROOM)

  • Introduction of translation efficiency constraints based on gatB activity levels

  • Similar to approaches used to model pyruvate accumulation in engineered P. putida strains

• Protein structure-based predictions:

  • Homology modeling of P. putida gatB structure

  • Molecular dynamics simulations to assess mutation impacts on protein dynamics

  • Binding free energy calculations for substrate interactions

  • Integration of structural predictions with metabolic models

• Machine learning approaches:

  • Sequence-based prediction of mutation effects using trained models

  • Integration of multi-omics data to predict system-wide effects

  • Pattern recognition from existing P. putida adaptation datasets

• Evolutionary modeling:

  • Prediction of adaptive mutations that might emerge to compensate for gatB alterations

  • Simulation of long-term evolutionary trajectories under selection pressure

  • Comparison with actual evolutionary patterns observed in P. putida long-term cultivation

• Systems biology frameworks:

  • Resource allocation models accounting for translation efficiency

  • Whole-cell modeling approaches integrating multiple cellular processes

  • Regulatory network analysis to predict transcriptional responses to gatB perturbation

These computational approaches can be validated and refined using experimental data from evolved P. putida strains, creating a powerful feedback loop between in silico prediction and in vivo confirmation.

How does long-term cultivation affect gatB function and evolution in Pseudomonas putida?

Long-term cultivation of P. putida reveals important insights into gatB function and evolution:

• Mutation accumulation patterns:

  • Long-term stationary phase experiments show that P. putida accumulates mutations in a highly convergent manner

  • Mutations in translation-related genes, potentially including gatB, would be expected as the cell optimizes resource allocation

• Adaptive mechanisms:

  • Emergence of mutator phenotypes due to mutations in mismatch repair genes, leading to accelerated evolution

  • Selection for gatB variants that maintain function with reduced energy expenditure

  • Compensatory mutations in tRNA genes or aminoacyl-tRNA synthetases to maintain translation accuracy

• Regulatory adaptations:

  • Mutations in RNA polymerase genes (e.g., rpoC) frequently emerge during adaptive evolution

  • These mutations could affect gatB expression patterns through global transcriptional reprogramming

• Temporal dynamics:

  • Initial rapid adaptation followed by more gradual refinement of function

  • Establishment of independently evolving lineages that persist throughout long-term experiments

  • Potential for cyclical selection pressures leading to fluctuating gatB variants

• Experimental framework:

  • Automated DIY frameworks for evolutionary experiments provide valuable platforms for studying gatB evolution

  • Dual-chamber bioreactors with anti-biofilm features maintain defined selection pressures

  • Whole-genome sequencing at multiple timepoints reveals evolutionary trajectories

These evolutionary dynamics, while not specifically documented for gatB in the current literature, are consistent with patterns observed in long-term stationary phase evolutionary experiments with P. putida and can inform future investigations into gatB evolution.