GLUL Human, His Active

What is GLUL and what is its primary function in human cells?

GLUL (Glutamine Synthetase) is an enzyme that catalyzes the ATP-dependent synthesis of glutamine from glutamate and ammonia. In human cells, GLUL serves several critical functions including being a major source of energy that participates in cell proliferation, inhibition of apoptosis, and cell signaling . GLUL is expressed during early fetal stages and plays a crucial role in maintaining body pH by removing ammonia from circulation . Additionally, it is important for acid-base homeostasis and ammonia detoxification .

The enzyme is also known by several synonyms including GLNS, GS, Glutamate decarboxylase, and Glutamate-ammonia ligase . GLUL activity is linked to the tricarboxylic acid (TCA) cycle via reversed glutaminolysis, highlighting its central role in cellular metabolism .

How is recombinant GLUL Human, His Active produced and what are its physical characteristics?

Recombinant GLUL Human is typically produced in Escherichia coli expression systems . The protein is a single, non-glycosylated polypeptide chain containing 393 amino acids (1-373 a.a.) with a molecular mass of approximately 44.2 kDa . For research applications, GLUL is commonly fused to a 20 amino acid His-Tag at the N-terminus to facilitate purification using proprietary chromatographic techniques .

The purified protein appears as a sterile filtered colorless solution . Standard formulations include GLUL Human solution containing 20mM Tris-HCl pH-8, 5mM DTT, 0.2M NaCl & 20% glycerol . The purity of the recombinant protein is generally greater than 90.0% as determined by SDS-PAGE analysis .

What methodologies are recommended for measuring GLUL enzymatic activity?

GLUL activity can be measured through several methodological approaches:

The specific activity of recombinant GLUL Human, His Active is typically > 2,800 pmol/min/ug, defined as the amount of enzyme that converts 1.0 pmole of L-glutamate to L-glutamine per minute at pH 7.5 at 37°C . This is commonly measured in a coupled system with pyruvate kinase (PK) and lactate dehydrogenase (LDH), allowing spectrophotometric monitoring of the reaction through the oxidation of NADH to NAD+.

For metabolic flux analysis, researchers can employ isotope tracing with 13C5 glutamine, 13C5 glutamate, or 13C6 glucose followed by mass spectrometry analysis to quantify the production of labeled metabolites . This approach enables tracking of carbon flow through both glycolysis and TCA pathways, providing insights into how GLUL activity influences broader metabolic networks.

When studying GLUL in the context of cellular metabolism, it's important to consider its relationship with other pathways, such as the malate-aspartate shuttle, which can be assessed through specific labeling patterns in malate and aspartate .

How does GLUL expression vary across different human tissues and cell types?

GLUL shows distinct expression patterns across different tissues and cell types:

In neural tissues, GLUL is highly expressed in glial cell types, particularly astrocytes, while showing minimal expression in post-mitotic neurons . Single-nucleus transcriptomic datasets from human prefrontal cortex demonstrate that GLUL expression is substantially higher in glial cell types compared to neuronal clusters, including both excitatory and inhibitory neurons .

During human brain development, GLUL is widely expressed in neuro- and glial-progenitor cell lineages but not in post-mitotic neurons . Analysis of EGFR+ cells (enriched for glial- and neuronal-lineage progenitors) from human cerebral cortex samples revealed that GLUL expression is constant across progenitor cell type clusters early in development . As cortical development progresses, GLUL expression becomes increasingly restricted to the astrocytic lineage .

In cancer, expression levels vary significantly across different cell lines. Studies have shown differential expression between basal-type and luminal-type breast cancer cells, with luminal cells typically showing higher GLUL expression . This expression pattern correlates with their relative independence from exogenous glutamine .

How does GLUL regulation via the N-terminal degron mechanism impact experimental design?

The N-terminal degron-mediated regulation of GLUL represents a critical post-translational control mechanism that significantly impacts experimental approaches:

GLUL levels are regulated through an autoregulatory negative feedback mechanism where elevated glutamine levels trigger ubiquitin-mediated proteasomal degradation of the enzyme . This process involves acetylation of an N-terminal degron by p300/CREB binding protein, followed by recognition and ubiquitination by CRL4CRBN, ultimately leading to proteasomal degradation .

When designing experiments, researchers must consider that modifications to the N-terminus (including His-tags) may potentially interfere with degron function. This is particularly important when studying the physiological regulation of GLUL. The concentration of glutamine in culture media directly affects GLUL stability, so standardizing glutamine concentrations across experiments is crucial for reproducibility.

The dynamic nature of this regulation necessitates temporal considerations in experimental design. Short-term glutamine flux experiments may yield different results compared to steady-state conditions due to the time required for degron-mediated degradation to affect GLUL protein levels.

Disease-relevant mutations, such as start-loss variants, can disrupt the N-terminal degron, leading to a stable, feedback-insensitive GLUL protein . This has profound implications for interpreting data from systems where GLUL regulation might be perturbed and requires careful control experiments.

What is the relationship between GLUL expression and cancer drug resistance?

GLUL expression levels have been implicated in cancer drug resistance through complex metabolic reprogramming mechanisms:

Research has identified reduced GLUL transcription to be associated with resistance to chemotherapeutic agents in acute lymphoblastic leukemia . Follow-up investigations using siRNA or lentiviral CRISPR-Cas9 mediated knockout (KO), as well as doxycycline-inducible shRNA-mediated knockdown (KD), revealed that GLUL ablation can confer drug resistance in specific cancer cell types .

The mechanism of resistance appears to be linked to metabolic adaptation. GLUL knockout in A549 non-small cell lung cancer (NSCLC) cells resulted in increased drug resistance, while the same genetic modification in H1299 NSCLC cells did not confer resistance . This cell-line specific effect suggests that genetic context significantly influences the metabolic consequences of GLUL modulation.

Metabolic studies revealed that resistant GLUL KO cells displayed increased 13C-labeling of malate and aspartate, whereas the non-resistant GLUL KO cells showed decreased labeling . This enhanced malate-aspartate shuttle activity supports cellular NADH production and is associated with increased metabolic fitness, which may enable cancer cells to escape drug pressure .

Importantly, rescuing GLUL expression in A549 KO cells increased drug sensitivity, confirming the causal relationship between GLUL levels and drug response . This suggests that the level of GLUL expression can fine-tune metabolic fitness, potentially offering therapeutic opportunities for combination therapies targeting metabolic vulnerabilities.

How do start-loss variants in GLUL affect protein function and contribute to neurodevelopmental disorders?

Start-loss variants in GLUL have profound effects on protein stability and function, contributing to severe neurodevelopmental phenotypes:

Recent research identified nine individuals with severe developmental delay, seizures, and white matter abnormalities who carried de novo variants in GLUL . Seven out of nine had start-loss variants, and two had disrupted 5′ UTR splicing resulting in splice exclusion of the initiation codon .

These variants lead to translation initiation from methionine 18, downstream of the N-terminal degron motif . This produces a truncated protein that is stable and enzymatically competent but critically insensitive to negative feedback regulation by glutamine . As a result, the enzyme remains active regardless of cellular glutamine levels, disrupting the tight regulation of glutamine metabolism.

Glutamine synthetase is pivotal for the generation of neurotransmitters glutamate and gamma-aminobutyric acid and serves as the primary mechanism of ammonia detoxification in the brain . Dysregulation of this enzyme during neurodevelopment appears to have severe consequences for brain formation and function.

Analysis of human single-cell transcriptomes demonstrated that GLUL is widely expressed in neuro- and glial-progenitor cells and mature astrocytes but not in post-mitotic neurons . This expression pattern provides context for understanding how dysregulated glutamine metabolism might affect specific cell populations during neurodevelopment.

What metabolomic approaches are most informative when studying the impact of GLUL modulation?

Comprehensive metabolomic approaches provide crucial insights into the complex consequences of GLUL modulation:

Targeted relative-quantitative profiling of approximately 80 different metabolites can reveal specific metabolic signatures associated with GLUL deficiency . This approach has demonstrated that glutamine accumulates when GLUL is knocked down, regardless of the drug resistance phenotype .

Stable isotope tracing using 13C5 glutamine, 13C5 glutamate, and 13C6 glucose enables tracking of carbon flux through both glycolysis and TCA pathways . This methodology has revealed increased labeling of malate and aspartate in resistant GLUL KO cells, indicating enhanced activity of the malate-aspartate shuttle .

Pathway-specific inhibition experiments provide functional validation of metabolic alterations. For example, inhibition of the malate-aspartate shuttle with aminooxyacetic acid significantly impacts cell viability, with an IC50 of 11.5 μM in resistant GLUL KO A549 cells compared to 28 μM in control A549 cells . This links resistance to the activity of this metabolic shuttle and provides potential therapeutic targets.

Nutritional dependency profiling through culture in media with varying concentrations of glucose and glutamine can identify shifts in metabolic preferences. GLUL KO A549 cells show increased dependency on exogenous glucose for proliferation compared to control cells , highlighting a metabolic vulnerability that could be therapeutically exploited.

Integration of metabolomic data with transcriptomic changes, such as increased expression of the glutamine transporter SLC1A5 and glutamate synthesizing enzyme GLS in GLUL KO cells , provides a more comprehensive understanding of the adaptive responses to GLUL modulation.

What are the optimal storage conditions for maintaining GLUL activity?

Maintaining GLUL activity requires specific storage conditions and handling protocols:

For short-term storage (2-4 weeks), GLUL can be stored at 4°C in its appropriate buffer formulation . For longer periods, it is recommended to store the enzyme frozen at -20°C .

To enhance stability during long-term storage, adding a carrier protein such as 0.1% HSA (Human Serum Albumin) or BSA (Bovine Serum Albumin) is recommended . This helps prevent protein adsorption to container surfaces and provides a protective environment for the enzyme.

Multiple freeze-thaw cycles should be avoided as they can compromise enzyme activity . Aliquoting the enzyme before freezing is advisable to minimize the number of freeze-thaw cycles.

The typical formulation for GLUL Human includes 20mM Tris-HCl pH-8, 5mM DTT, 0.2M NaCl & 20% glycerol . The inclusion of DTT helps maintain reducing conditions for thiol groups in the enzyme, which is important for preserving catalytic activity.

What experimental approaches are recommended for studying GLUL in neurodevelopmental contexts?

Investigating GLUL in neurodevelopmental contexts requires specialized experimental approaches:

Cell type-specific analysis is essential given GLUL's differential expression across neural populations. Single-cell approaches can resolve this heterogeneity, as GLUL is expressed in glial- and neuronal-progenitor lineages but not in post-mitotic neurons . Cell sorting strategies to isolate specific neural populations, such as EGFR+ progenitors, can provide focused analysis of GLUL function in relevant cell types.

Developmental timeline considerations are crucial, as GLUL expression patterns change throughout neurodevelopment. Analysis across multiple developmental timepoints and brain regions can capture these dynamic changes . As cortical development progresses, GLUL expression becomes increasingly restricted to the astrocytic lineage, so temporal resolution in experimental design is important .

Genetic manipulation strategies should include precise modeling of human disease variants. Generation of start-loss variants that mimic those found in patients with neurodevelopmental disorders can provide direct insights into pathogenic mechanisms . Comparison of complete knockout versus degron-deficient models can distinguish between loss-of-function and dysregulation phenotypes.

Functional readouts relevant to neurodevelopment include assessment of neural migration and cortical layering, evaluation of myelination and white matter development, and analysis of neuronal marker expression . The examination of markers such as Pax6, Tbr2 (for neuronal lineage), and Olig2 (for glial lineage) can help determine if GLUL modulation affects progenitor cell abundance and neuronal differentiation .

In vivo approaches such as in utero electroporation allow for targeted manipulation of GLUL in developing brain regions and assessment of consequences for neuronal migration and positioning . This technique has been used to investigate the effects of stabilized GLUL on neurodevelopmental processes.

What are emerging areas for GLUL research in cancer metabolism?

The role of GLUL in cancer metabolism presents several promising research directions:

Combination therapy approaches targeting metabolic fitness during induction treatment could potentially suppress the selection of resistant clones . The finding that GLUL ablation can confer drug resistance through enhanced malate-aspartate shuttle activity suggests that inhibitors of this shuttle might sensitize resistant cells to conventional chemotherapy.

Personalized metabolic profiling of tumors could identify patients likely to develop resistance through GLUL-related mechanisms. Different cancer cell lines (e.g., A549 vs. H1299 NSCLC cells) exhibit distinct metabolic adaptations to GLUL loss , suggesting that genetic and metabolic context significantly influences therapeutic responses.

Exploration of the relationship between GLUL expression and tumor microenvironment could reveal how metabolic adaptations interact with environmental factors. GLUL's role in ammonia detoxification may be particularly relevant in hypoxic or nutrient-deprived tumor regions.

Investigation of GLUL as a biomarker for treatment response or resistance could provide clinically useful prognostic information. Elevated GLUL expression has been reported as an early marker of hepatocellular carcinoma and as an unfavorable prognostic marker in patients with glioblastoma multiforme and ovarian cancer .

Development of small molecule modulators of GLUL activity or its regulatory mechanisms could offer new therapeutic strategies. The N-terminal degron-mediated regulation of GLUL represents a potential drug target for modulating enzyme levels in specific contexts.

How might single-cell analyses further our understanding of GLUL in development and disease?

Single-cell analyses offer powerful approaches for advancing GLUL research:

Cell lineage trajectory analysis using single-cell RNA-seq data can map GLUL expression changes during transitions from progenitor to differentiated states . This approach has revealed that as cortical development progresses, GLUL expression becomes increasingly restricted to the astrocytic lineage.

Spatial transcriptomics can provide crucial insights by mapping GLUL expression in the anatomical context of developing tissues . This approach can reveal spatial relationships between GLUL-expressing cells and specific developmental niches or structural features.

Integration of single-cell multi-omics (transcriptomics, proteomics, metabolomics) could provide comprehensive understanding of how GLUL regulation affects cellular state at multiple levels. This integrated approach is particularly relevant given the post-translational regulation of GLUL through the N-terminal degron mechanism.

Comparative analysis of normal versus pathological development using single-cell approaches could identify specific cell populations and developmental timepoints where GLUL dysregulation has the most significant impact. This is particularly relevant for understanding neurodevelopmental disorders associated with GLUL variants.

Single-cell perturbation analyses could map the consequences of GLUL modulation across diverse cell types. Since GLUL is widely expressed in progenitor populations but shows cell-type specific expression in mature tissues, understanding this heterogeneity of response could reveal cell type-specific vulnerabilities.