Recombinant Pseudomonas putida Glutamate-ammonia-ligase adenylyltransferase (glnE), partial

What is the role of glnE in Pseudomonas putida nitrogen metabolism?

Glutamate-ammonia-ligase adenylyltransferase (glnE) in Pseudomonas putida functions as a bifunctional enzyme that regulates glutamine synthetase (GS) activity through reversible adenylylation. Similar to its counterpart in E. coli, P. putida glnE catalyzes both adenylyltransferase (AT) and adenylyl-removing (AR) activities, allowing the bacterium to dynamically control nitrogen assimilation in response to environmental conditions. The enzyme's bifunctional nature enables fine-tuned regulation of GS, which is the central enzyme for nitrogen assimilation in bacteria . This post-translational modification system allows P. putida to rapidly adjust its nitrogen metabolism in response to fluctuating environmental nitrogen availability without requiring new protein synthesis.

How does P. putida glnE structure compare to homologous proteins in other bacteria?

The glnE protein in P. putida shares significant structural similarities with its E. coli counterpart, particularly in the catalytic domains responsible for adenylyltransferase and adenylyl-removing activities. While the complete structural analysis of P. putida glnE is still emerging, comparative analyses suggest conservation in key functional domains. The N-terminal domain typically contains the adenylyl-removing activity, while the C-terminal domain harbors the adenylyltransferase activity. The regulatory domains that bind effector molecules like glutamine and 2-oxoglutarate are also likely conserved, as these small effectors have been shown to regulate both AT and AR activities in E. coli . Sequence alignment studies would reveal specific sequence identities and divergences between P. putida glnE and homologs in other bacterial species.

What is the relationship between glnE and the PII signaling proteins in P. putida?

In P. putida, as in other bacteria, glnE activity is likely modulated by interaction with PII signaling proteins (encoded by glnB and glnK genes). These PII proteins function as nitrogen status sensors that undergo uridylylation/deuridylylation in response to nitrogen availability. When nitrogen is limited, PII proteins become uridylylated and promote the adenylyl-removing activity of glnE, resulting in deadeylylation and activation of glutamine synthetase. Under nitrogen excess, non-uridylylated PII proteins stimulate the adenylyltransferase activity of glnE, leading to adenylylation and inactivation of glutamine synthetase . This complex regulatory network enables P. putida to rapidly respond to changes in environmental nitrogen, optimizing nitrogen assimilation and metabolism according to cellular needs.

What are the optimal conditions for expressing recombinant P. putida glnE in heterologous systems?

For optimal expression of recombinant P. putida glnE in heterologous systems, researchers should consider several factors. Expression in E. coli BL21(DE3) using the pET vector system typically yields satisfactory results when induced with 0.5-1.0 mM IPTG at mid-log phase (OD600 = 0.6-0.8). Expression temperature should be lowered to 16-20°C after induction to enhance protein solubility, as higher temperatures often lead to inclusion body formation. The addition of 5-10% glycerol and 1-5 mM ATP to lysis buffers can help stabilize the enzyme. When designing the expression construct, inclusion of an N-terminal His-tag facilitates purification while minimally affecting enzyme activity, whereas C-terminal tags may interfere with the adenylyltransferase domain function. For functional studies, co-expression with P. putida glutamine synthetase and PII proteins may be necessary to reconstitute the complete regulatory system .

How can the adenylyltransferase and adenylyl-removing activities of glnE be measured independently?

Independent measurement of the adenylyltransferase (AT) and adenylyl-removing (AR) activities of glnE requires specialized assay conditions that favor one activity over the other:

For AT activity:

• Use a reaction mixture containing purified unmodified glutamine synthetase (GS), ATP, Mg²⁺, and glutamine (5-10 mM).

• Include 2-oxoglutarate at low concentrations (0.1-0.5 mM) to inhibit excessive AT activity.

• Monitor AMP incorporation into GS using [α-³²P]ATP or measure GS activity decrease over time.

• Optimal pH is typically 7.5-8.0, with higher glutamine concentrations enhancing AT activity.

For AR activity:

• Use a reaction mixture containing fully adenylylated GS, Mn²⁺, phosphate, and 2-oxoglutarate (1-5 mM).

• Keep glutamine concentrations low (0.1-0.5 mM) to minimize AT activity interference.

• Monitor Pi release using colorimetric assays or measure the increase in GS activity.

• Optimal pH is around 7.0-7.5, and higher 2-oxoglutarate concentrations favor AR activity .

Both activities are influenced by PII protein uridylylation state, so careful preparation of these components is essential for reproducible results.

What gene deletion strategies are most effective for studying glnE function in P. putida?

For studying glnE function in P. putida, several gene deletion strategies have proven effective, with the counterselection method using the upp gene offering superior precision and efficiency. The upp-based counterselection system enables markerless gene deletion without leaving scars in the chromosome, which is critical when studying complex regulatory networks like nitrogen metabolism . This approach requires:

• Creating a 5-FU resistant P. putida strain by first deleting the endogenous upp gene

• Constructing a deletion vector containing:

  • Homologous regions (500-1000 bp) flanking the glnE gene

  • A counterselection cassette containing the upp gene under a constitutive promoter

• Performing two-step homologous recombination:

  • First integration of the entire plasmid (selected by antibiotic resistance)

  • Second recombination and plasmid excision (selected by 5-FU resistance)

This method avoids the problems associated with FRT- or loxP-based systems, which leave genomic scars that can cause chromosomal instability through unintended recombination events . For studying glnE specifically, creating partial deletions of domains responsible for either AT or AR activity rather than complete gene knockout enables dissection of the bifunctional nature of the enzyme.

How does the reversible adenylylation system in P. putida compare with that in E. coli and other bacteria?

The reversible adenylylation system in P. putida shares fundamental similarities with E. coli but exhibits distinct regulatory characteristics. Based on comparative analyses:

In P. putida, as in E. coli, the adenylyl-removing (AR) activity is critical for maintaining appropriate glutamine synthetase activity during steady-state growth. The absence of AR activity leads to excessive GS adenylylation even under nitrogen-limiting conditions, demonstrating that AT activity is dynamically counterbalanced by AR activity . This dynamic counterbalance strategy appears to be conserved across bacterial species as a mechanism for controlling enzymes that enable adaptation to environmental fluctuations, though the specific regulatory parameters likely reflect adaptations to the ecological niches occupied by different bacterial species.

What is the impact of synthetic metabolic engineering on glnE function in P. putida strains adapted to non-native substrates?

Synthetic metabolic engineering of P. putida for utilization of non-native substrates can significantly impact glnE function and nitrogen regulation. When P. putida is engineered to utilize substrates like xylose, the entire metabolic network undergoes substantial reconfiguration, potentially affecting nitrogen assimilation pathways and their regulation . Heterologous expression of xylose utilization genes (xylABE) creates metabolic burdens that may indirectly affect nitrogen sensing and adaptive responses. Research demonstrates that successful adaptation to non-native carbon sources involves complex metabolic and regulatory rearrangements, including altered glucose metabolism regulation .

These system-wide adaptations likely influence the glutamine/2-oxoglutarate ratio, which is the primary signal controlling glnE activity. As carbon and nitrogen metabolism are tightly interconnected through key intermediates like 2-oxoglutarate, engineered changes in carbon utilization pathways can create imbalances in these signaling molecules, necessitating compensatory changes in nitrogen regulatory systems. Researchers should specifically monitor changes in glnE expression, post-translational modification patterns, and glutamine synthetase adenylylation state when characterizing synthetically-primed adaptive evolution of P. putida to ensure optimal nitrogen metabolism in engineered strains.

How can autonomous AI-driven research platforms be leveraged to optimize experimental conditions for studying glnE function?

Autonomous AI-driven research platforms like Coscientist can revolutionize the study of glnE function through sophisticated experimental design and execution capabilities. These systems can accelerate research by:

• Experimental Design Optimization:

  • Systematically exploring the multidimensional parameter space of reaction conditions (pH, temperature, ion concentrations) that affect glnE activity

  • Employing advanced optimization algorithms that outperform standard Bayesian optimization approaches, showing higher normalized moving average (NMA) values for reaction optimization

  • Generating complex experimental matrices to simultaneously test multiple variables affecting glnE function

• Protocol Implementation:

  • Converting high-level experimental concepts into precise liquid handling protocols for automated laboratory equipment

  • Calculating exact volumes and concentrations needed for enzyme assays with minimal human intervention

  • Controlling specialized equipment such as microplate readers and heater-shaker modules for enzyme activity measurements

• Data Integration and Analysis:

  • Autonomously analyzing patterns in enzymatic activity data to identify optimal conditions

  • Integrating diverse data sources to correlate enzyme structure, activity, and regulatory properties

  • Proposing mechanistic models based on experimental outcomes

These AI systems can particularly enhance the characterization of complex bifunctional enzymes like glnE by efficiently mapping the relationship between small effector molecules (glutamine, 2-oxoglutarate) and the two opposing enzymatic activities (AT and AR) across various conditions, accelerating discovery while minimizing researcher time and materials .

What experimental conditions best demonstrate the dynamic counterbalance between AT and AR activities in P. putida?

To effectively demonstrate the dynamic counterbalance between adenylyltransferase (AT) and adenylyl-removing (AR) activities in P. putida glnE, researchers should establish experimental conditions that allow observation of this balance in real-time. The most revealing approach involves creating AR-deficient mutants (AR-/AT+) through targeted mutagenesis and comparing them with wild-type strains under various growth conditions. Studies in E. coli have shown that AR-deficient mutants display growth defects even under nitrogen-excess conditions due to excessive glutamine synthetase adenylylation .

Optimal experimental conditions include:

• Nitrogen shift experiments:

  • Culture bacteria in defined minimal medium with limiting nitrogen (0.5-1 mM NH4Cl)

  • Monitor GS adenylylation state before and after shifting to excess nitrogen (10-20 mM NH4Cl)

  • Sample at short intervals (0, 1, 2, 5, 10, 30 min) to capture rapid adenylylation dynamics

• Steady-state comparison:

  • Measure GS adenylylation levels in wild-type and AR-deficient strains grown under both nitrogen-limiting and nitrogen-excess conditions

  • Expected result: AR-deficient strains show abnormally high GS adenylylation even under nitrogen limitation

• In vitro reconstitution:

  • Using purified components (glnE, GS, PII proteins), establish reaction conditions with varying ratios of glutamine to 2-oxoglutarate

  • Monitor adenylylation/deadenylylation rates continuously using spectrophotometric assays

These experiments should be performed at physiologically relevant pH (7.0-7.5) and temperature (30°C for P. putida), with careful attention to the physiological concentrations of key metabolites like glutamine and 2-oxoglutarate.

How does temperature affect the balance between AT and AR activities in P. putida glnE?

Temperature has significant differential effects on the adenylyltransferase (AT) and adenylyl-removing (AR) activities of P. putida glnE, reflecting the bacterium's adaptation to environmental temperature fluctuations:

The differential temperature sensitivity of AT and AR activities creates a regulatory mechanism that adjusts nitrogen assimilation capacity according to temperature. At lower temperatures typical of soil environments, the relatively higher AR activity ensures sufficient GS activity to maintain growth despite slower metabolism. As temperatures increase toward the optimal range for P. putida growth (25-30°C), both activities reach their optimal balance, allowing rapid response to nitrogen status fluctuations .

Under heat stress conditions, the declining AR activity results in higher GS adenylylation, reducing nitrogen assimilation when cellular energetics are challenged. This temperature-dependent regulatory mechanism represents an important adaptation for soil bacteria like P. putida that experience significant temperature variations in their natural habitats. Researchers should account for these temperature effects when designing experiments to study glnE function and interpreting results from growth studies under different temperature regimes.

What metabolomic approaches are most informative for studying the impact of glnE mutations on cellular nitrogen homeostasis?

For comprehensive analysis of how glnE mutations affect nitrogen homeostasis in P. putida, integrated metabolomic approaches yield the most informative results:

• Targeted LC-MS/MS for nitrogen cycle intermediates:

  • Quantify primary nitrogen metabolites: glutamine, glutamate, 2-oxoglutarate, and arginine

  • Monitor adenylated nucleotides (AMP, ADP, ATP) to assess energy status

  • Measure uridylylated/deuridylylated forms of PII proteins to determine nitrogen signaling state

  • Detection limits should be in the low μM range with appropriate isotope-labeled internal standards

• Untargeted metabolomics using high-resolution MS:

  • Identify unexpected metabolic perturbations in pathways connected to nitrogen metabolism

  • Detect compensatory metabolic adaptations in glnE mutants

  • Apply multivariate statistical approaches (PCA, OPLS-DA) to identify discriminatory metabolites

• Flux analysis using ¹⁵N-labeled precursors:

  • Administer ¹⁵NH₄Cl pulse and track isotope incorporation rates

  • Calculate flux distributions through glutamine synthetase, glutamate dehydrogenase, and amino acid biosynthetic pathways

  • Compare wild-type and glnE mutant strains under identical conditions to quantify specific pathway alterations

• Integration with transcriptomics and proteomics:

  • Correlate metabolite levels with expression of nitrogen metabolism genes

  • Identify regulatory feedback mechanisms activated in response to glnE dysfunction

  • Construct comprehensive metabolic models of nitrogen homeostasis under different conditions

These approaches should be applied to both steady-state conditions and during transitions between nitrogen-limiting and nitrogen-excess environments to capture the dynamic nature of glnE-mediated regulation . Sample preparation must be rapid (using cold methanol quenching) to preserve the in vivo metabolic state, particularly for adenylylated proteins and signaling metabolites with rapid turnover.

What strategies can be used to create glnE variants with altered regulatory properties for metabolic engineering applications?

• Domain-specific mutagenesis:

  • Target the N-terminal adenylyl-removing (AR) domain to modify deadenylylation kinetics

  • Alter the C-terminal adenylyltransferase (AT) domain to modify adenylylation rates

  • Modify the central domain containing glutamine-binding sites to adjust sensitivity to nitrogen status

  • Use alanine-scanning mutagenesis of conserved residues identified through sequence alignment with E. coli glnE

• Regulatory sensitivity adjustment:

  • Modify glutamine-binding pocket residues to alter affinity for glutamine

  • Engineer 2-oxoglutarate binding sites to change the enzyme's response to carbon status

  • Alter interactions with PII proteins to modify integration of nitrogen status signals

  • Apply targeted rational design based on homology modeling and known regulatory mechanisms

• Bifunctional balance engineering:

  • Create variants with altered AT/AR activity ratios to optimize glutamine synthetase activity levels

  • Develop constitutively active variants by disrupting inhibitory interfaces

  • Generate switchable variants responsive to non-native signals or inducers

  • Apply directed evolution with appropriate selection strategies to evolve desired properties

• Application-specific optimizations:

  • For enhanced bioremediation: develop variants with reduced glutamine sensitivity to maintain nitrogen assimilation in contaminated environments

  • For bioproduction: create variants that maintain optimal GS activity at high intracellular glutamine concentrations

  • For synthetic biology: develop orthogonal variants that function independently of native nitrogen regulation

When implementing these strategies, researchers should utilize markerless gene replacement methods like the upp-based counterselection system to integrate the engineered glnE variants into the P. putida chromosome without disrupting other regulatory elements .

How do specific amino acid substitutions in the AT and AR domains affect the regulatory properties of P. putida glnE?

Specific amino acid substitutions in the AT and AR domains of P. putida glnE produce distinct effects on regulatory properties, as summarized in the following table based on experimental data and comparative analysis with E. coli:

The most critical residues are those involved in nucleotide binding (for both AT and AR activities) and effector molecule sensing. Mutations in the AR domain typically lead to more severe phenotypes than equivalent AT domain mutations, highlighting the essential role of the AR activity in maintaining appropriate GS activity during steady-state growth . The interdomain regions are particularly interesting targets for engineering as they control the communication between the opposing enzymatic activities, potentially allowing the creation of variants with novel regulatory properties suitable for specific biotechnological applications.

What is the current understanding of how post-translational modifications affect glnE function in P. putida?

The current understanding of post-translational modifications (PTMs) affecting glnE function in P. putida remains limited compared to E. coli, but several key mechanisms have been identified or hypothesized based on comparative studies:

The interplay between these modifications creates a complex regulatory network that allows P. putida to fine-tune nitrogen assimilation according to environmental conditions. Advanced proteomic techniques combining enrichment strategies for specific PTMs with high-resolution mass spectrometry are needed to fully map the PTM landscape of glnE under different growth conditions.

What are the most promising applications of engineered P. putida glnE variants in biotechnology?

Engineered P. putida glnE variants offer several promising biotechnological applications by enabling precise control over nitrogen metabolism in this versatile industrial chassis organism. The bifunctional nature of glnE, with its opposing adenylyltransferase and adenylyl-removing activities, provides multiple engineering targets for optimizing nitrogen utilization in various bioprocesses. Variants with altered regulatory properties could significantly enhance P. putida's performance in bioremediation applications by maintaining optimal nitrogen assimilation under challenging environmental conditions. For bioproduction of value-added compounds, engineered glnE variants that maintain appropriate glutamine synthetase activity despite high product titers could prevent nitrogen metabolism from becoming a bottleneck in high-yield processes .

Particularly promising are applications in synthetically-adapted P. putida strains engineered to utilize non-native carbon sources like xylose, where nitrogen metabolism must be harmonized with altered carbon utilization pathways . Autonomous research platforms like Coscientist could accelerate the development of these engineered glnE variants by efficiently exploring the complex relationship between enzyme structure, activity, and regulatory properties . Future research should focus on creating libraries of glnE variants with predictable regulatory properties that can be selected based on specific application requirements.

What are the current limitations in our understanding of P. putida glnE and how might they be addressed through emerging technologies?

Current limitations in our understanding of P. putida glnE stem from several knowledge gaps that emerging technologies could help address:

• Structural information:

  • Limited high-resolution structural data for P. putida glnE

  • Incomplete understanding of dynamic conformational changes during catalysis

  • Solution: Cryo-EM and integrative structural biology approaches combining X-ray crystallography, hydrogen-deuterium exchange mass spectrometry, and computational modeling

• In vivo dynamics:

  • Limited tools for monitoring adenylylation state in real-time in living cells

  • Insufficient understanding of spatial regulation within bacterial cells

  • Solution: Development of fluorescent biosensors for glutamine synthetase adenylylation state and advanced microscopy techniques

• Systems-level integration:

  • Incomplete models of how glnE activity coordinates with global metabolic networks

  • Limited understanding of species-specific regulatory variations

  • Solution: Multi-omics approaches integrating transcriptomics, proteomics, and metabolomics with computational modeling

• Genetic manipulation limitations:

  • Challenges in creating precise mutations without affecting genomic context

  • Low efficiency of some genetic engineering techniques in P. putida

  • Solution: Advanced genome editing tools including CRISPR-Cas systems and markerless deletion techniques like upp-based counterselection

• High-throughput characterization:

  • Bottlenecks in testing multiple enzyme variants efficiently

  • Limitations in standardized assay formats

  • Solution: Microfluidic systems and autonomous research platforms for parallel enzyme characterization

Emerging AI-driven research platforms represent a particularly promising approach to address these limitations by efficiently exploring the complex parameter space of enzyme function and regulation while reducing experimental burden . Integration of these technologies with advanced genetic tools like markerless gene manipulation will accelerate our understanding of this complex regulatory enzyme.

How might advances in synthetic biology approaches to nitrogen metabolism regulation impact industrial applications of P. putida?

Advances in synthetic biology approaches to nitrogen metabolism regulation, particularly through engineering of the glnE-mediated adenylylation system, hold transformative potential for industrial applications of P. putida:

• Enhanced bioremediation capabilities:

  • Engineered strains with optimized nitrogen assimilation in contaminated environments

  • Improved resilience to fluctuating nitrogen availability in field applications

  • Tailored nitrogen metabolism for specific pollutant degradation pathways

  • Integration with synthetically-engineered carbon metabolism pathways for complete pollutant mineralization

• Bioproduction optimization:

  • Nitrogen metabolism tuned specifically for high-yield production of target compounds

  • Prevention of nitrogen limitation during high-density fermentations

  • Balanced allocation of nitrogen resources between growth and product formation

  • Elimination of bottlenecks in amino acid-derived product synthesis

• Adaptive laboratory evolution applications:

  • Rational engineering of nitrogen regulatory systems as priming modifications before ALE

  • Creation of selection pressures specifically targeting nitrogen metabolism optimization

  • Accelerated adaptation to industrial conditions through pre-optimization of nitrogen regulation

• Synthetic pathway integration:

  • Harmonization of heterologous pathway expression with native nitrogen metabolism

  • Development of orthogonal nitrogen regulatory systems for independent control

  • Mitigation of metabolic burdens imposed by recombinant protein expression