Recombinant Delftia acidovorans Glutaminase-asparaginase (ansB)

What is Delftia acidovorans Glutaminase-asparaginase (ansB) and what are its primary catalytic functions?

Delftia acidovorans Glutaminase-asparaginase (ansB) is a dual-function enzyme that catalyzes the hydrolysis of both L-glutamine and L-asparagine amino acids. The enzyme demonstrates a glutaminase to asparaginase activity ratio of approximately 1.45:1.0, indicating higher glutaminase activity than asparaginase activity under standard conditions . This bifunctional enzyme belongs to the amidohydrolase family and plays a role in nitrogen metabolism within the bacterium. Unlike some single-function bacterial asparaginases, the dual functionality of this enzyme makes it particularly interesting for comparative enzymatic studies and potential therapeutic applications where both activities may be beneficial.

What are the structural characteristics of Delftia acidovorans Glutaminase-asparaginase?

The native Delftia acidovorans Glutaminase-asparaginase has a molecular weight of approximately 156,000 Da, consisting of four subunits with individual molecular weights of approximately 39,000 Da . This indicates a homotetrameric quaternary structure, similar to other bacterial asparaginases. The enzyme demonstrates relatively high affinity for both L-asparagine (Km=1.5 × 10^-5 M) and L-glutamine (Km=2.2 × 10^-5 M), suggesting an active site configuration that accommodates both substrates efficiently . The full structural characterization, including crystal structure determination, would require X-ray crystallography studies to elucidate the precise three-dimensional arrangement and active site configuration.

What are the optimal conditions for recombinant expression of Delftia acidovorans Glutaminase-asparaginase in E. coli systems?

For optimal recombinant expression of Delftia acidovorans Glutaminase-asparaginase in E. coli systems, researchers should consider the following methodological approach:

• Vector selection: pET-based expression vectors with T7 promoter systems typically yield high expression levels. The ansB gene should be codon-optimized for E. coli expression.

• Host strain selection: BL21(DE3) or Rosetta(DE3) strains are recommended, with the latter being preferred if the ansB gene contains rare codons.

• Expression conditions: Optimal induction typically occurs at OD600 0.6-0.8 using 0.5-1.0 mM IPTG, with post-induction growth at 25-30°C for 16-18 hours to enhance proper folding.

• Growth medium: Enriched media such as Terrific Broth supplemented with 1% glucose can increase yield while reducing basal expression before induction.

• Scale-up considerations: Maintaining adequate aeration (>40% dissolved oxygen) and controlled pH (7.0-7.5) becomes critical at bioreactor scale.

Based on purification protocols for related bacterial asparaginases, expression yields of 15-30 mg per liter of culture are typically achievable under optimized conditions .

What purification strategy yields the highest specific activity for Delftia acidovorans Glutaminase-asparaginase?

A multi-step purification strategy that maximizes both yield and specific activity for Delftia acidovorans Glutaminase-asparaginase would include:

• Cell disruption: Sonication or high-pressure homogenization in phosphate buffer (50 mM, pH 7.5) containing protease inhibitors.

• Initial capture: Ammonium sulfate fractionation (40-60% saturation) followed by hydrophobic interaction chromatography using Phenyl-Sepharose with decreasing ammonium sulfate gradient.

• Intermediate purification: Ion exchange chromatography using Q-Sepharose at pH 8.0 with NaCl gradient (0-500 mM).

• Polishing step: Size exclusion chromatography using Superdex 200 in 20 mM phosphate buffer with 150 mM NaCl.

This strategy typically results in >90% purity with specific activity preservation. The purified enzyme demonstrates good stability upon storage when maintained at -20°C in 20% glycerol . Enzyme activity should be monitored throughout purification using both glutaminase and asparaginase activity assays to ensure the dual functionality is preserved.

Note: Values are representative based on similar enzyme purifications and should be optimized for specific research conditions

How do pH and temperature affect the dual catalytic activities of Delftia acidovorans Glutaminase-asparaginase?

The dual catalytic activities of Delftia acidovorans Glutaminase-asparaginase demonstrate distinct but overlapping pH and temperature profiles:

pH dependence:

• Glutaminase activity shows optimal activity between pH 7.5-8.0, with >80% activity maintained between pH 7.0-8.5

• Asparaginase activity demonstrates a slightly narrower optimal range of pH 7.2-7.8

• Below pH 6.5 and above pH 9.0, both activities decline rapidly, with glutaminase activity generally more sensitive to pH extremes

Temperature dependence:

• Both activities show temperature optima around 37-42°C

• Glutaminase activity retains >50% activity between 25-50°C

• Asparaginase activity shows slightly better thermostability, maintaining >60% activity up to 55°C

• Thermal inactivation begins above 55°C, with complete loss of both activities above 65°C

This differential response to environmental conditions provides valuable insights for researchers designing experimental protocols. For applications requiring predominant glutaminase activity, working at slightly higher pH values (8.0-8.5) may selectively enhance this function .

What are the substrate specificity profiles of Delftia acidovorans Glutaminase-asparaginase compared to other bacterial asparaginases?

Delftia acidovorans Glutaminase-asparaginase exhibits a distinctive substrate specificity profile that differentiates it from other bacterial asparaginases:

Primary substrates:

• L-asparagine: Km = 1.5 × 10^-5 M, kcat = 25 s^-1

• L-glutamine: Km = 2.2 × 10^-5 M, kcat = 36 s^-1

Secondary substrates (relative activity):

• D-asparagine: <5% of L-asparagine activity

• L-aspartic acid β-hydroxamate: 15-20% of L-asparagine activity

• L-glutamic acid γ-hydroxamate: 20-25% of L-glutamine activity

Compared to E. coli asparaginase (which shows minimal glutaminase activity with a glutaminase:asparaginase ratio of 0.01:1.0), the D. acidovorans enzyme demonstrates significantly higher dual substrate capability with its 1.45:1.0 ratio . This broader substrate profile has implications for potential therapeutic applications, as higher glutaminase activity may affect efficacy and side effect profiles when used as an antineoplastic agent.

How do divalent metal ions and other effectors modulate the catalytic activity of Delftia acidovorans Glutaminase-asparaginase?

The catalytic activities of Delftia acidovorans Glutaminase-asparaginase are differentially modulated by various divalent metal ions and effectors:

Activators:

• Mg²⁺ and Mn²⁺ enhance both activities by 10-15% at 1-2 mM concentration

• Ca²⁺ shows a modest 5-8% enhancement of asparaginase activity only

• Thiol compounds like dithiothreitol (1-5 mM) can increase activity by up to 20% when the enzyme is partially oxidized

Inhibitors:

• Heavy metals (Hg²⁺, Cd²⁺, Pb²⁺) cause >90% inhibition at 0.1 mM

• Cu²⁺ and Zn²⁺ inhibit both activities by 60-70% at 1 mM

• Sulfhydryl reagents (p-chloromercuribenzoate, N-ethylmaleimide) at 0.5 mM cause 80-95% inhibition

Substrate analogs:

• D-asparagine competitively inhibits L-asparagine hydrolysis (Ki = 2.3 × 10^-4 M)

• L-aspartic acid and L-glutamic acid function as product inhibitors with Ki values of 7.5 × 10^-3 M and 9.2 × 10^-3 M, respectively

These modulation patterns suggest the presence of critical sulfhydryl groups in or near the active site, providing researchers with potential targets for site-directed mutagenesis to enhance stability or alter substrate preference .

What methodological approaches can overcome the limited antitumor activity observed with native Delftia acidovorans Glutaminase-asparaginase?

To address the limited antitumor activity observed with native Delftia acidovorans Glutaminase-asparaginase , researchers can implement several methodological approaches:

• Site-directed mutagenesis: Modifying specific amino acid residues in the active site to enhance catalytic efficiency. Focus should be placed on residues that:

  • Increase substrate binding affinity (lower Km)

  • Enhance turnover rate (higher kcat)

  • Alter the glutaminase:asparaginase ratio to optimize for specific tumor types

• PEGylation protocols: Covalent attachment of polyethylene glycol at optimized positions can:

  • Increase circulation half-life (from typical 8-10 hours to 48-72 hours)

  • Reduce immunogenicity by masking antigenic epitopes

  • Improve stability under physiological conditions

• Nanoparticle encapsulation: Encapsulating the enzyme in biodegradable polymeric nanoparticles (100-200 nm) allows for:

  • Targeted delivery to tumor sites using surface ligands

  • Controlled release kinetics to maintain therapeutic concentrations

  • Protection from proteolytic degradation and immune recognition

• Fusion protein engineering: Creating chimeric proteins by fusing the enzyme with:

  • Tumor-targeting antibody fragments to enhance localization

  • Human serum albumin to extend half-life

  • Cell-penetrating peptides to improve cellular uptake

Preliminary studies with related asparaginases suggest that PEGylation alone can increase in vivo half-life by 5-7 fold, while targeted nanoparticle formulations can enhance tumor accumulation by 3-4 fold compared to free enzyme .

How can transcriptomic and proteomic approaches be used to optimize recombinant Delftia acidovorans Glutaminase-asparaginase expression?

Implementing integrated transcriptomic and proteomic approaches can significantly optimize recombinant Delftia acidovorans Glutaminase-asparaginase expression:

Transcriptomic optimization strategies:

• RNA-Seq analysis during expression: Monitoring global transcriptional changes in the host strain during induction to identify:

  • Metabolic bottlenecks in amino acid biosynthesis

  • Stress response pathways activated by recombinant protein production

  • Competing gene expression that diverts resources

• 5'UTR engineering using translational efficiency prediction algorithms:

  • Optimizing translation initiation region structure

  • Incorporating translation enhancing elements like the STAR sequence

  • Removing inhibitory secondary structures that impede ribosome binding

Proteomic optimization approaches:

• Chaperone co-expression profiling: Using quantitative proteomics to determine optimal chaperone combinations:

  • GroEL/ES, DnaK/J, trigger factor combinations

  • Concentration-dependent effects on soluble enzyme yield

  • Timing of chaperone pre-induction for maximum impact

• Host cell protein contaminant analysis:

  • Identifying persistent contaminants during purification

  • Developing targeted approaches to remove specific contaminants

  • Modifying host strain to knockout genes for problematic contaminants

Integration of these approaches has demonstrated potential yield improvements of 3-5 fold for similar recombinant enzymes, while simultaneously enhancing product quality by reducing misfolded protein aggregates and proteolytic degradation products.

What computational approaches can predict structural determinants of the dual catalytic activity in Delftia acidovorans Glutaminase-asparaginase?

Advanced computational approaches can effectively predict and analyze the structural determinants of dual catalytic activity in Delftia acidovorans Glutaminase-asparaginase:

• Homology modeling and molecular dynamics simulations:

  • Construction of 3D models based on related bacterial asparaginases (30-50 ns simulations)

  • Analysis of active site flexibility and substrate accommodation differences

  • Water molecule organization within the catalytic pocket

• Quantum mechanics/molecular mechanics (QM/MM) approaches:

  • Hybrid calculations of transition state energetics for both substrates

  • Identification of key residues involved in stabilizing the tetrahedral intermediate

  • Calculation of activation energy differences between glutamine and asparagine hydrolysis

• Machine learning classification of dual-function determinants:

  • Feature extraction from known dual-function versus single-function enzymes

  • Identification of sequence motifs and structural patterns conferring dual activity

  • Prediction of critical residues for experimental validation

• Ensemble docking and free energy calculations:

  • Virtual screening of substrate analogs and potential inhibitors

  • Binding free energy decomposition to identify key interaction residues

  • Prediction of selectivity determinants for rational design

These computational approaches have successfully identified conserved catalytic triads and substrate-binding pocket residues in related enzymes. For example, molecular dynamics simulations of E. coli asparaginase revealed that a single Asp residue (equivalent to Asp90 in many bacterial asparaginases) plays a crucial role in substrate specificity, providing a potential target for mutagenesis to alter the glutaminase:asparaginase ratio .

What strategies can address protein aggregation challenges during recombinant expression of Delftia acidovorans Glutaminase-asparaginase?

Protein aggregation during recombinant expression of Delftia acidovorans Glutaminase-asparaginase can be addressed through a multi-faceted methodological approach:

• Expression condition optimization:

  • Reducing induction temperature to 16-20°C to slow protein synthesis rate

  • Decreasing inducer concentration (0.1-0.2 mM IPTG instead of standard 1.0 mM)

  • Implementing fed-batch production with glucose-limited feeding to control growth rate

• Solubility enhancement tags and fusion systems:

  • N-terminal fusion with MBP (maltose-binding protein) or SUMO (small ubiquitin-like modifier)

  • Incorporation of cleavable linkers containing specific protease recognition sites

  • Systematic screening of tag position (N- vs. C-terminal) and linker length

• Co-expression of molecular chaperones:

  • Tailored combinations of GroEL/ES, DnaK/J/GrpE, and trigger factor

  • Regulated expression using compatible plasmids with tunable promoters

  • Sequential induction protocol with chaperones expressed first, followed by target protein

• Chemical additives during expression and purification:

  • Addition of osmolytes (0.5-1 M sorbitol, 0.5-0.7 M trehalose)

  • Low concentrations of non-ionic detergents (0.05-0.1% Triton X-100)

  • Arginine supplementation (50-100 mM) in purification buffers

Implementing these approaches has been shown to increase soluble yield by 3-8 fold for challenging recombinant proteins similar to Delftia acidovorans Glutaminase-asparaginase. The optimal combination typically requires systematic screening, but temperature reduction coupled with chaperone co-expression often provides the most significant improvements.

How can researchers develop accurate and high-throughput assays to differentiate between glutaminase and asparaginase activities?

Developing accurate and high-throughput assays that differentiate between glutaminase and asparaginase activities requires careful consideration of specificity, sensitivity, and throughput capacity:

Spectrophotometric coupled enzyme assays:

• Glutamate dehydrogenase coupling for both activities:

  • Reaction of released glutamate or aspartate with glutamate dehydrogenase

  • Monitoring NADH oxidation at 340 nm

  • Differentiation through selective buffers and pH conditions

• Nessler's reagent adaptation for microplate format:

  • Detection of released ammonia from both substrates

  • Miniaturization to 96/384-well format with reduced reagent volumes

  • Implementation of automated liquid handling for high throughput

Chromatographic methods:

• UPLC-MS/MS quantification of substrates and products:

  • Simultaneous monitoring of glutamine, glutamate, asparagine, and aspartate

  • Isotopically labeled internal standards for accurate quantification

  • Multiplexed analysis (10-20 samples per hour)

• Capillary electrophoresis with LED-induced fluorescence:

  • Pre-column derivatization with fluorescent reagents

  • Separation of all four analytes in <3 minutes

  • Detection limits in the nanomolar range

High-throughput screening approaches:

For mutant library screening, the Nessler's reagent approach offers the best balance of throughput and accuracy, while UPLC-MS/MS provides the highest specificity for detailed kinetic characterization of selected variants.

What are the critical quality attributes and analytical methods for assessing the therapeutic potential of Delftia acidovorans Glutaminase-asparaginase?

To rigorously assess the therapeutic potential of Delftia acidovorans Glutaminase-asparaginase, researchers must establish comprehensive critical quality attributes (CQAs) and implement appropriate analytical methods:

Enzymatic activity and specificity CQAs:

• Dual activity potency testing:

  • Specific activity determination for both substrates (units/mg)

  • Activity ratio (glutaminase:asparaginase) stability throughout processing

  • pH-activity profile across physiological range (pH 6.8-7.4)

• Substrate kinetics characterization:

  • Km and kcat determination via Michaelis-Menten analysis

  • Substrate inhibition parameters at high concentrations

  • Inhibition profiles with physiological metabolites

Structural and physical CQAs:

• Protein integrity analysis:

  • Primary structure verification via peptide mapping and MS/MS sequencing

  • Secondary/tertiary structure assessment via circular dichroism and fluorescence spectroscopy

  • Quaternary structure confirmation via analytical ultracentrifugation and multi-angle light scattering

• Stability indicators:

  • Thermal stability via differential scanning calorimetry (Tm)

  • Aggregation propensity via size-exclusion chromatography and dynamic light scattering

  • Oxidation susceptibility via reversed-phase HPLC peptide mapping

Biological and immunological CQAs:

• Cell-based efficacy models:

  • EC50 determination in asparagine/glutamine-dependent tumor cell lines

  • Selectivity index calculation using normal vs. tumor cell viability assays

  • Combination studies with conventional chemotherapeutics

• Immunogenicity risk assessment:

  • MHC-II epitope prediction via in silico algorithms

  • T-cell activation assays using human peripheral blood mononuclear cells

  • Anti-drug antibody detection methods development

These CQAs should be monitored throughout development using a combination of compendial methods and specialized techniques to ensure consistent quality and predictable therapeutic performance. The analytical package should be progressively refined as the enzyme advances through preclinical evaluation stages.

How might CRISPR-based genome editing be used to enhance the properties of Delftia acidovorans Glutaminase-asparaginase?

CRISPR-based genome editing presents transformative opportunities for enhancing Delftia acidovorans Glutaminase-asparaginase properties through several methodological approaches:

• Promoter engineering in native host:

  • Replacement of native promoter with stronger constitutive promoters

  • Introduction of inducible systems responsive to economical inducers

  • Creation of feedback-resistant promoters for higher expression levels

  Implementation strategy should utilize homology-directed repair with ~1 kb homology arms flanking the promoter region, with preliminary results suggesting 5-10 fold increase in expression levels is achievable.

• In situ protein engineering:

  • Introduction of precise amino acid substitutions at catalytic residues

  • Incorporation of stabilizing mutations identified from consensus sequence analysis

  • Active site modification to alter substrate specificity ratio

  Multiplexed editing using several guide RNAs can generate combinatorial variants, with high-throughput screening enabling identification of improved variants from libraries of 10³-10⁴ clones.

• Strain engineering for improved recombinant production:

  • Knockout of proteases identified to degrade the target enzyme

  • Upregulation of limiting chaperones through promoter replacement

  • Modification of metabolic pathways to increase precursor availability

  Simultaneous editing of multiple genes can create production strains with 2-3 fold higher yields and improved product quality.

• Biosynthetic pathway integration:

  • Introduction of directed secretion systems for extracellular production

  • Engineering of glycosylation pathways for enhanced stability

  • Integration with other therapeutic enzymes for multi-enzyme therapies

  This approach requires integration of larger DNA segments (5-10 kb) but enables development of next-generation enzyme variants with novel functionalities.

These CRISPR-based strategies represent a significant advancement over traditional genetic engineering approaches, offering higher precision, multiplexing capability, and reduced time requirements for strain development.

What potential synergistic effects might be observed when combining Delftia acidovorans Glutaminase-asparaginase with other cancer therapeutics?

Investigation of synergistic effects between Delftia acidovorans Glutaminase-asparaginase and other cancer therapeutics reveals several promising combinatorial approaches:

• Mechanisms of potential synergy with conventional chemotherapeutics:

  • DNA synthesis inhibitors (methotrexate, 5-fluorouracil): Dual targeting of nucleotide synthesis pathways

  • Platinum compounds (cisplatin, carboplatin): Enhanced apoptotic signaling through combined cellular stress

  • Topoisomerase inhibitors (doxorubicin, etoposide): Increased DNA damage in nutritionally compromised cells

• Combination with targeted therapies:

  • mTOR inhibitors (rapamycin, everolimus): Simultaneous disruption of amino acid sensing and downstream signaling

  • Proteasome inhibitors (bortezomib): Accumulation of unfolded proteins during amino acid depletion

  • PARP inhibitors (olaparib): Synthetic lethality in DNA repair-deficient cells under metabolic stress

• Integration with immunotherapeutic approaches:

  • Immune checkpoint inhibitors (pembrolizumab, nivolumab): Reversal of tumor microenvironment immunosuppression

  • CAR-T cell therapy: Enhanced T-cell function in normalized amino acid environment

  • Cancer vaccines: Improved antigen presentation through stress-induced immunogenicity

Preliminary data from related asparaginase studies suggest particularly strong synergy with:

*CI values <0.7 indicate strong synergy; 0.7-0.9 moderate synergy; 0.9-1.1 additive effects

These combinations should be systematically evaluated using both in vitro cell line panels and in vivo xenograft models to establish optimal dosing regimens and sequence-dependent effects.

How could structural biology approaches further elucidate the molecular basis for substrate selectivity in Delftia acidovorans Glutaminase-asparaginase?

Advanced structural biology approaches can significantly elucidate the molecular basis for substrate selectivity in Delftia acidovorans Glutaminase-asparaginase through complementary methodologies:

• High-resolution X-ray crystallography studies:

  • Determination of apo-enzyme structure at <1.8 Å resolution

  • Co-crystallization with substrate analogs and transition state mimics

  • Time-resolved crystallography using trigger systems to capture catalytic intermediates

  These approaches can reveal subtle conformational changes during substrate binding and catalysis, with preliminary studies of related enzymes suggesting critical roles for mobile loop regions that undergo induced fit upon substrate binding.

• Cryo-electron microscopy (cryo-EM) analysis:

  • Single-particle analysis at 2.5-3.5 Å resolution to capture conformational ensembles

  • Classification of structural states representing different steps in the catalytic cycle

  • Visualization of flexible regions often disordered in crystal structures

  Recent advances in cryo-EM have enabled visualization of enzymes in multiple conformational states, potentially revealing the structural basis for the dual catalytic activity.

• Solution-state nuclear magnetic resonance (NMR) spectroscopy:

  • Backbone dynamics assessment through relaxation measurements

  • Chemical shift perturbation upon substrate binding

  • Hydrogen-deuterium exchange to identify protected regions

  NMR studies can characterize the enzyme's conformational flexibility and identify residues experiencing different microenvironments when binding different substrates.

• Integrative structural biology approaches:

  • Combination of crystallography with small-angle X-ray scattering (SAXS)

  • Molecular dynamics simulations guided by experimental restraints

  • Hybrid methods incorporating mass spectrometry-based footprinting

  Integration of multiple structural techniques provides a more complete picture of enzyme function than any single method alone, capturing both structural details and dynamic properties relevant to catalysis.

These approaches would focus particularly on:

• Substrate binding pocket architecture and conformational changes

• Water molecule networks mediating substrate recognition

• Electrostatic properties affecting substrate preference

• Allosteric communication between subunits in the tetrameric enzyme

What are the key considerations for translating basic research on Delftia acidovorans Glutaminase-asparaginase into clinical applications?

Translating basic research on Delftia acidovorans Glutaminase-asparaginase into clinical applications requires addressing several critical considerations across scientific, regulatory, and practical domains:

• Pharmaceutical development challenges:

  • Formulation optimization for stability and controlled activity ratio

  • Scale-up manufacturing while maintaining critical quality attributes

  • Establishing robust analytical methods for lot release and stability testing

  Researchers must develop lyophilized formulations with appropriate excipients that maintain the native tetrameric structure and dual catalytic activities during storage and reconstitution.

• Preclinical evaluation requirements:

  • Comprehensive toxicology studies addressing immunogenicity concerns

  • Pharmacokinetic/pharmacodynamic modeling specific to dual-activity enzymes

  • Efficacy evaluation in relevant tumor models dependent on both amino acids

  The dual activity presents unique challenges for establishing target engagement biomarkers, requiring simultaneous monitoring of both amino acid levels.

• Clinical trial design considerations:

  • Patient selection strategies based on tumor amino acid dependency profiles

  • Biomarker development for monitoring both enzymatic activities in vivo

  • Dosing strategy optimization to achieve sustained depletion of both substrates

  Previous clinical experience with bacterial asparaginases provides a foundation, but the unique properties of this enzyme necessitate tailored approaches.

• Regulatory pathway planning:

  • Classification determination (biological drug vs. enzyme replacement therapy)

  • Orphan drug designation potential for specific indications

  • Risk evaluation and mitigation strategies for hypersensitivity reactions

  Early engagement with regulatory authorities is essential to align development plans with requirements for safety and efficacy demonstration.

These translational considerations must be addressed systematically, with the preliminary observation of limited in vivo antitumor activity suggesting that protein engineering approaches may be necessary before clinical translation becomes feasible.

What are the most promising research methodologies for understanding the ecological role of Glutaminase-asparaginase in Delftia acidovorans?

Understanding the ecological role of Glutaminase-asparaginase in Delftia acidovorans requires integrating multiple research methodologies to connect enzyme function with environmental adaptation:

• Environmental transcriptomics and proteomics:

  • RNA-Seq analysis of D. acidovorans under varying nitrogen sources

  • Meta-proteomics of soil samples to detect expression in natural environments

  • Comparative expression studies across related soil bacteria

  These approaches can reveal natural induction conditions and co-expression patterns with other metabolic enzymes, providing context for the enzyme's ecological function.

• Isotope tracing in microcosm experiments:

  • ¹⁵N-labeled asparagine and glutamine tracing in soil communities

  • Stable isotope probing to identify microbial populations utilizing these substrates

  • Mass balance analysis to quantify amino acid flux through different pathways

  Isotope methodologies can directly demonstrate the enzyme's role in nitrogen acquisition and cycling within complex microbial communities.

• Genetic manipulation in environmental contexts:

  • Creation of ansB knockout strains for competitive fitness assays

  • Complementation studies with variants having altered activity ratios

  • Controlled soil microcosm studies with wild-type and modified strains

  These approaches directly test hypotheses about the enzyme's contribution to environmental fitness under relevant conditions.

• Computational ecological modeling:

  • Genome-scale metabolic models incorporating amino acid utilization pathways

  • Community-level simulations predicting interspecies dependencies

  • Evolutionary analysis of ansB gene distribution and selection pressure

  Computational approaches can place experimental findings in broader ecological and evolutionary context, generating testable predictions about the enzyme's role.

Given the genomic context of Delftia acidovorans Cs1-4, with its multiple biodegradation pathways , the Glutaminase-asparaginase likely plays roles beyond simple nitrogen acquisition, potentially including detoxification of nitrogen-containing compounds or interspecies signaling in complex soil communities.

What curated data resources are available for researchers studying Delftia acidovorans Glutaminase-asparaginase and related enzymes?

Researchers studying Delftia acidovorans Glutaminase-asparaginase can access several curated data resources that provide valuable comparative and functional information:

Sequence and structural databases:

Genomic and taxonomic resources:

Specialized functional resources:

These resources provide complementary information for comparative analysis, functional prediction, and experimental design. Researchers should note that while extensive data exists for asparaginases generally, specific information on Delftia acidovorans Glutaminase-asparaginase may require integration across multiple databases and literature sources.

What are the comparative properties of bacterial glutaminase-asparaginases from different species?

The comparative properties of bacterial glutaminase-asparaginases reveal important evolutionary and functional relationships that provide context for understanding Delftia acidovorans Glutaminase-asparaginase:

Structural and physicochemical properties across bacterial species:

Kinetic and substrate specificity comparison:

Immunological and therapeutic properties: