Recombinant Mouse GATS-like protein 2 (Gatsl2)

What is Gatsl2 and what is its primary function in cellular pathways?

Gatsl2, also known as CASTOR2, functions as a negative regulator of the TORC1 signaling pathway through interaction with the GATOR complex. It forms homodimers or heterodimers with CASTOR1 and directly binds and inhibits the GATOR subcomplex GATOR2, which in turn inhibits mTORC1 activation. Unlike CASTOR1, Gatsl2 does not directly bind arginine, but the binding of arginine to CASTOR1 disrupts the interaction of CASTOR2-containing heterodimers with GATOR2, allowing activation of mTORC1 and the TORC1 signaling pathway .

In which tissues is mouse Gatsl2 predominantly expressed?

Based on expression data, mouse Gatsl2 is expressed in multiple tissues, primarily in the artery, blood, notochord, and yolk syncytial layer. This expression pattern suggests its functional importance in these specific tissues, potentially related to nutrient sensing and cellular growth regulation. The cross-species expression comparison data indicates that Gatsl2 expression patterns are conserved to some degree across different vertebrate species, highlighting its evolutionary significance in cellular metabolism regulation .

What are the optimal expression systems for producing recombinant mouse Gatsl2?

The expression protocol should include optimization of induction conditions (temperature, time, and inducer concentration), followed by chromatographic purification steps such as affinity chromatography using the protein's His-tag, followed by size exclusion chromatography to ensure homogeneity of the final preparation.

How can researchers effectively design studies to investigate Gatsl2-GATOR2 interactions?

To effectively investigate Gatsl2-GATOR2 interactions, researchers should employ a multi-tiered approach combining in vitro and cellular techniques:

• In vitro interaction studies:

  • Pull-down assays using purified recombinant Gatsl2 and GATOR2 components

  • Surface plasmon resonance to determine binding kinetics

  • Isothermal titration calorimetry to assess thermodynamic parameters of binding

• Cellular interaction studies:

  • Co-immunoprecipitation of endogenous or tagged proteins

  • Proximity ligation assays to visualize interactions in situ

  • FRET-based approaches to monitor dynamic interactions

• Functional validation studies:

  • CRISPR/Cas9-mediated knockout or knockdown experiments

  • Rescue experiments with wild-type and mutant Gatsl2

  • Downstream mTORC1 activity measurements (S6K phosphorylation, 4E-BP1 phosphorylation)

When designing these studies, it's critical to include appropriate controls, such as using CASTOR1 as a positive control for GATOR2 interaction, and to verify the specificity of any antibodies used for detection, similar to validation approaches for the Anti-GATSL2 antibody .

What methods are recommended for studying Gatsl2 homodimers versus Gatsl2-CASTOR1 heterodimers?

For distinguishing and studying Gatsl2 homodimers versus Gatsl2-CASTOR1 heterodimers, researchers should consider the following methodological approaches:

• Differential tagging strategy:

  • Express Gatsl2 and CASTOR1 with different epitope tags (e.g., FLAG-Gatsl2 and HA-CASTOR1)

  • Perform sequential immunoprecipitation to isolate heterodimers specifically

  • Alternatively, use size exclusion chromatography coupled with multi-angle light scattering to determine complex stoichiometry

• Crosslinking mass spectrometry:

  • Apply chemical crosslinking of purified complexes

  • Analyze by mass spectrometry to identify specific interaction interfaces

  • Compare crosslinks observed in homodimers versus heterodimers

• Functional response analysis:

  • Compare arginine sensitivity of homodimers versus heterodimers

  • Measure GATOR2 binding affinity for each complex type

  • Assess downstream mTORC1 activity in cells expressing engineered versions that preferentially form either homo- or heterodimers

A critical aspect of these studies is careful preparation of protein samples with defined dimer composition, which typically requires expression and purification of individual components followed by controlled in vitro reconstitution .

How should researchers organize and analyze data from Gatsl2 binding studies?

For effective organization and analysis of Gatsl2 binding studies, researchers should implement a structured approach to data collection and interpretation:

Data tables should clearly indicate the independent variable (e.g., protein concentration, arginine concentration) in the left column, with dependent variables (measured parameters) in subsequent columns, following standard scientific data table guidelines . Each experiment should include multiple trials (at least three) to enable statistical analysis, with derived quantities such as means and standard deviations in the rightmost columns .

For complex binding models, such as cooperative binding or multi-site interactions, researchers should employ specialized binding equation models and present the fitted parameters with confidence intervals. Graphical representation should complement tabular data, showing binding curves, Scatchard plots, or thermograms as appropriate for the experimental technique3 .

What are the key parameters to assess when validating recombinant Gatsl2 quality for experimental use?

When validating recombinant Gatsl2 quality for experimental use, researchers should assess multiple parameters to ensure experimental reliability:

• Purity assessment:

  • SDS-PAGE analysis: Should demonstrate >95% purity

  • Mass spectrometry confirmation of intact protein mass

  • Endotoxin levels: Should be <1 EU/μg for cell-based assays

• Structural integrity:

  • Circular dichroism to confirm secondary structure elements

  • Thermal shift assays to assess protein stability

  • Size exclusion chromatography to verify oligomeric state

• Functional validation:

  • GATOR2 binding activity compared to reference standards

  • Heterodimer formation with CASTOR1

  • Response to arginine in CASTOR1-containing heterodimers

• Batch consistency:

  • Lot-to-lot comparison of activity

  • Stability during storage (freeze-thaw cycles, temperature sensitivity)

Researchers should maintain detailed records of these parameters in standardized data tables that include specification ranges for each parameter. Additionally, validation should include positive controls such as commercial reference standards or previously validated in-house preparations to ensure consistency across experiments .

How can researchers effectively analyze and interpret data showing Gatsl2's impact on mTORC1 pathway activity?

To effectively analyze Gatsl2's impact on mTORC1 pathway activity, researchers should implement a comprehensive data collection and analysis framework:

• Direct mTORC1 activity markers:

  • Phosphorylation levels of S6K (Thr389)

  • Phosphorylation of 4E-BP1 (multiple sites)

  • Ribosomal protein S6 phosphorylation

• Data normalization approaches:

  • Normalize phospho-protein signals to total protein levels

  • Compare to internal control conditions (serum starvation, rapamycin treatment)

  • Account for Gatsl2 expression levels in overexpression studies

• Time-course analysis:

  • Measure acute versus sustained responses to arginine

  • Determine kinetics of mTORC1 reactivation following arginine stimulation

  • Compare wildtype versus Gatsl2-modified conditions at multiple timepoints

• Pathway context analysis:

  • Examine upstream regulator status (GATOR1/2 components)

  • Assess parallel amino acid sensing inputs (Sestrin, SLC38A9)

  • Evaluate downstream functional outputs (protein synthesis rate, autophagy markers)

Data should be organized in tables with clear independent variables (e.g., time points, Gatsl2 variant, arginine concentration) and dependent variables (measured pathway activities). Statistical analysis should include appropriate tests for time-course data, such as repeated measures ANOVA, and dose-response relationships should be fitted to appropriate models to determine EC50 values and efficacy parameters .

How can researchers effectively use Gatsl2 knockout/knockdown approaches to study its physiological role?

To effectively use Gatsl2 knockout/knockdown approaches for studying its physiological role, researchers should implement a comprehensive experimental design that addresses multiple levels of biological organization:

• Gene editing strategy selection:

  • CRISPR/Cas9 for complete gene knockout: Design guide RNAs targeting early exons of Gatsl2 with minimal off-target effects

  • RNAi for temporary knockdown: Test multiple siRNA/shRNA sequences for maximum knockdown efficiency and specificity

  • Conditional knockout systems (Cre-loxP) for tissue-specific or inducible deletion

• Validation of knockout/knockdown efficiency:

  • mRNA quantification using RT-qPCR with primers spanning multiple exons

  • Protein level assessment using validated antibodies such as Anti-GATSL2 antibody

  • Functional validation by examining known downstream effects on mTORC1 signaling

• Phenotypic analysis framework:

  • Cellular level: Growth rates, metabolic profiles, and response to nutrient stress

  • Tissue level: Histological analysis of tissues known to express Gatsl2 (artery, blood, notochord)

  • Whole organism: Development, growth patterns, and response to dietary interventions

• Mechanistic dissection:

  • Epistasis experiments with other pathway components (CASTOR1, GATOR complex)

  • Rescue experiments with wildtype and mutant Gatsl2 variants

  • Nutrient response profiling beyond arginine (other amino acids, energy status)

When analyzing data from these experiments, researchers should use appropriate statistical methods for comparing knockout/knockdown conditions to controls, including Student's t-test for simple comparisons and ANOVA for multi-factorial experiments. Results should be presented in clearly organized tables showing the relationship between genotype/treatment and measured parameters across multiple experimental replicates .

What are the most effective approaches for investigating Gatsl2's interaction with the GATOR complex at the structural level?

For investigating Gatsl2's interaction with the GATOR complex at the structural level, researchers should consider a multi-technique approach that provides complementary structural information:

Data from these studies should be organized in tables that clearly relate structural features to functional outcomes. For instance, mutation studies should be presented with structural context, binding parameters, and functional impact systematically arranged to highlight structure-function relationships .

What methodologies are recommended for studying the temporal dynamics of Gatsl2 in response to nutrient fluctuations?

To study the temporal dynamics of Gatsl2 in response to nutrient fluctuations, researchers should implement time-resolved experimental approaches coupled with appropriate data analysis:

• Live-cell imaging techniques:

  • Fluorescent protein-tagged Gatsl2 to monitor localization changes

  • FRET-based biosensors to detect Gatsl2-GATOR2 interaction dynamics

  • Optogenetic tools to precisely control Gatsl2 activity in specific cellular compartments

• Biochemical temporal profiling:

  • Time-course sampling following nutrient addition/depletion

  • Quantitative immunoprecipitation to measure complex formation kinetics

  • Phosphoproteomics to monitor downstream signaling events

• Mathematical modeling approaches:

  • Ordinary differential equation models of the Gatsl2-mTORC1 regulatory network

  • Parameter estimation from time-course data

  • Sensitivity analysis to identify key control points in the temporal response

• Experimental design considerations:

  • High temporal resolution during acute phase (seconds to minutes)

  • Extended monitoring for adaptive responses (hours to days)

  • Simultaneous tracking of multiple pathway components

Data from temporal studies should be organized in time-course tables with clear time points as the independent variable and measured parameters as dependent variables. Statistical analysis should employ methods appropriate for time-series data, such as repeated measures ANOVA or mixed-effects models. Visualization should include time-course plots with error bands representing variation across replicates3 .

How does mouse Gatsl2 compare to its human ortholog in terms of structure and function?

Mouse Gatsl2 (CASTOR2) and its human ortholog share significant structural and functional similarities, though with some notable species-specific differences:

What techniques should researchers use to investigate the evolutionary conservation of Gatsl2 function across species?

To investigate the evolutionary conservation of Gatsl2 function across species, researchers should employ a comprehensive comparative biology approach:

• Sequence-based evolutionary analysis:

  • Phylogenetic tree construction using Gatsl2 sequences from diverse species

  • Calculation of selection pressure (dN/dS ratios) across different domains

  • Identification of highly conserved motifs and residues

• Structural conservation analysis:

  • Homology modeling of Gatsl2 from different species

  • Structural alignment to identify conserved binding interfaces

  • Molecular dynamics simulations to compare dynamic behaviors

• Functional conservation testing:

  • Cross-species complementation assays (e.g., can zebrafish Gatsl2 rescue mouse Gatsl2 knockout?)

  • Comparative biochemical assays of GATOR2 binding across orthologs

  • Assessment of arginine responsiveness in heterodimers from different species

• Systems-level conservation:

  • Comparison of expression patterns across equivalent tissues in different species

  • Network analysis of Gatsl2-interacting partners across species

  • Phenotypic comparison of Gatsl2 deficiency across model organisms

Data should be organized in comparative tables that align homologous features across species, with statistical measures of conservation (percent identity, similarity scores) included. Visualization methods should include multiple sequence alignments, structural superpositions, and comparative pathway diagrams to highlight both conserved and divergent aspects .

What are the most common technical challenges in studying Gatsl2-CASTOR1 heterodimers and how can they be overcome?

Researchers face several technical challenges when studying Gatsl2-CASTOR1 heterodimers, each requiring specific troubleshooting approaches:

• Heterodimer versus homodimer discrimination:

  • Challenge: Difficulty separating heterodimers from homodimers of either protein

  • Solution: Use dual-affinity tag purification strategy (e.g., His-tag on Gatsl2, GST-tag on CASTOR1) with sequential purification steps

  • Validation: Size exclusion chromatography coupled with multi-angle light scattering to confirm stoichiometry

• Protein stability issues:

  • Challenge: Heterodimers may exhibit different stability than homodimers

  • Solution: Screen buffer conditions (pH, salt concentration, additives) using thermal shift assays

  • Optimization: Add stabilizing agents like glycerol or specific amino acids identified during screening

• Expression level imbalance:

  • Challenge: Unequal expression leading to excess of one component

  • Solution: Use bicistronic expression constructs with optimized translation efficiency for each component

  • Alternative: Dual inducible promoters with titrated induction levels

• Artifactual interactions in overexpression systems:

  • Challenge: Non-physiological interactions due to high concentration

  • Solution: Validate interactions at near-endogenous expression levels

  • Control: Include competition assays with unlabeled components to test specificity

• Functional assessment complications:

  • Challenge: Determining specific contribution of heterodimers versus homodimers

  • Solution: Design mutants that preferentially form heterodimers but maintain functional interfaces

  • Approach: Use proximity-based labeling techniques (BioID, APEX) in cellular contexts

For each troubleshooting approach, researchers should maintain detailed records of optimization experiments in data tables that systematically vary the relevant parameters and record the outcome measures (yield, purity, activity) .

How can researchers address inconsistent results in Gatsl2 nutrient sensing studies?

When addressing inconsistent results in Gatsl2 nutrient sensing studies, researchers should implement a systematic troubleshooting framework:

• Experimental condition standardization:

  • Cell culture variation: Standardize passage number, confluence, and serum starvation protocols

  • Nutrient preparation: Use freshly prepared, sterile-filtered amino acid solutions at precisely defined concentrations

  • Timing precision: Implement rigorous timing protocols with automated or timer-controlled sampling

• Technical variable control:

  • Antibody validation: Verify specificity of all antibodies using knockdown/knockout controls

  • Sample processing: Standardize lysis conditions and phosphatase inhibitor use

  • Detection methods: Calibrate detection systems using standard curves

• Biological variable assessment:

  • Cell line authentication: Regularly verify cell line identity

  • Gatsl2 expression levels: Quantify endogenous versus overexpressed protein levels

  • Pathway component status: Check for mutations or expression variations in other pathway components

• Systematic meta-analysis:

  • Create a structured data table comparing experimental conditions across studies

  • Identify patterns in results that correlate with specific variables

  • Design controlled experiments that specifically test identified variables

When inconsistencies persist despite these controls, researchers should consider biological explanations such as cell type-specific regulatory mechanisms or context-dependent functions of Gatsl2. The inconsistent results themselves may reveal important biological insights about conditional regulation of the mTORC1 pathway .