Recombinant Mouse Acetyl-CoA acetyltransferase, cytosolic (Acat2)

What are the fundamental properties of recombinant mouse ACAT2?

Recombinant mouse Acetyl-CoA acetyltransferase 2 (ACAT2) is a cytosolic enzyme involved in the biosynthetic pathway of cholesterol. The recombinant form typically has the following characteristics:

• Alternative names: ACTL, Acetoacetyl Coenzyme A Thiolase, Acetyl-CoA transferase-like protein, Cytosolic acetoacetyl-CoA thiolase

• Molecular mass: Approximately 45.0 kDa (predicted) with accurate molecular mass of 45 kDa

• Subcellular location: Cytoplasm

• Isoelectric point: 7.1

• Typical expression system: Prokaryotic expression in E. coli with N-terminal His Tag

• Protein residues: Met1~Gly397

The recombinant protein is generally supplied as a freeze-dried powder with >97% purity and can be reconstituted for various experimental applications .

What are the optimal storage and stability conditions for recombinant mouse ACAT2?

To maintain the integrity and activity of recombinant mouse ACAT2, the following storage conditions are recommended:

• Short-term storage: 2-8°C for up to one month

• Long-term storage: Aliquot and store at -80°C for up to 12 months

• Avoid repeated freeze/thaw cycles as this can lead to protein degradation

The thermal stability of recombinant ACAT2 is characterized by its loss rate, which can be determined through accelerated thermal degradation testing. When incubated at 37°C for 48 hours, properly manufactured recombinant ACAT2 should show no obvious degradation or precipitation, with a loss rate of less than 5% within its expiration date under appropriate storage conditions .

How should recombinant mouse ACAT2 be reconstituted for experimental use?

For optimal reconstitution:

• Use 10mM PBS (pH 7.4) to achieve a concentration of 0.1-1.0 mg/mL

• Do not vortex the solution during reconstitution as this may denature the protein

• The buffer formulation typically contains PBS, pH 7.4, with 0.01% SKL and 5% Trehalose as stabilizers

What are the primary research applications for recombinant mouse ACAT2?

Recombinant mouse ACAT2 has several key applications in research settings:

• Positive Control: Serves as a standard in experiments measuring endogenous ACAT2 levels

• Immunogen: Used for antibody production against ACAT2

• SDS-PAGE and Western Blotting: Functions as a reference protein for molecular weight determination and analytical purposes

• Enzyme Activity Studies: Used to investigate cholesterol metabolism pathways

• Biomarker Research: Employed in studies exploring ACAT2's potential as a disease biomarker

• Inhibitor Screening: Utilized in drug discovery efforts aimed at identifying selective ACAT2 antagonists

How can ACAT2 activity be reliably measured in experimental settings?

Several methodologies can be employed to measure ACAT2 activity:

• NBD22-steryl ester fluorescence assay: This fluorescence-based assay monitors the formation of sterol esters catalyzed by ACAT2 .

• Cholesterol oxidase assay: Used to measure free cholesterol levels, which indirectly reflects ACAT2 activity by quantifying the unconverted substrate .

• ELISA-based quantification: Commercial ELISA kits are available for mouse ACAT2 with:

  • Detection range: 0.16-10 ng/mL

  • Sensitivity: 0.057 ng/mL

  • Assay principle: Sandwich enzyme immunoassay using antibodies specific to mouse ACAT2

Table 1: Standard Curve Data for Mouse ACAT2 ELISA

What experimental considerations should be addressed when using recombinant ACAT2 in functional studies?

When designing experiments using recombinant ACAT2:

• Endotoxin Levels: Verify endotoxin levels (<1.0EU per 1μg as determined by the LAL method) to prevent unwanted immune responses in cell culture or in vivo experiments .

• Buffer Compatibility: Ensure compatibility between the reconstitution buffer and your experimental system, as some buffer components may interfere with certain assays .

• Positive and Negative Controls: Include appropriate controls to validate your experimental setup and ensure specificity of observed effects .

• Recovery Validation: When measuring ACAT2 in biological samples, validate recovery rates by spiking known amounts of recombinant ACAT2 into your matrix .

• Cross-Reactivity: Be aware of potential cross-reactivity with other thiolase family members, particularly when using antibodies against ACAT2 .

How should experimental design be approached when studying ACAT2 function in disease models?

When investigating ACAT2's role in disease pathogenesis, experimental design is critical. Based on model selection principles:

What are the current approaches for developing selective ACAT2 inhibitors for research applications?

The development of selective ACAT2 inhibitors has employed several computational and biological approaches:

• Computational Methods:

  • Pharmacophore modeling: Identifies essential features required for ACAT2 inhibition

  • Molecular docking: Predicts binding modes of potential inhibitors to ACAT2

  • Molecular dynamics simulations: Evaluates stability and interactions of ACAT2-inhibitor complexes

• Virtual Screening:

  • Libraries of compounds are virtually screened against ACAT2 using the above computational methods

  • Promising candidates are selected for experimental validation

• Biological Validation:

  • NBD22-steryl ester fluorescence assay: Measures direct inhibition of ACAT2 enzymatic activity

  • Cholesterol oxidase assay: Assesses impact on cholesterol metabolism

Selective inhibition of ACAT2 has been shown to significantly mitigate hypercholesterolemia and atherosclerosis in mouse models, highlighting the importance of developing specific inhibitors that don't affect related enzymes .

How can contradictory findings about ACAT2 function be reconciled in research?

Contradictory findings about ACAT2 function may arise due to several factors:

Research has demonstrated that "different models can be selected depending on the experiment undertaken," suggesting that experimental design implicitly makes confidence a selection criterion .

What is the current understanding of ACAT2's role as a biomarker in disease progression?

Research indicates that ACAT2 may serve as a novel predictive biomarker and therapeutic target in certain diseases:

What are the best practices for analyzing ACAT2 expression data in complex disease models?

For rigorous analysis of ACAT2 expression in disease models:

• Database Selection:

  • TCGA (The Cancer Genome Atlas) provides comprehensive genomic data for analyzing ACAT2 expression across multiple cancer types

  • TIMER2.0 database can be used to compare ACAT2 expression between normal and tumor tissues

  • GEPIA database helps analyze correlations between ACAT2 expression and pathological stage

• Statistical Methods:

  • Use Wilcoxon test for comparing ACAT2 expression between tumor and normal samples

  • Apply ANOVA for comparing expression across multiple groups

  • Employ Spearman's correlation coefficient to analyze relationships between ACAT2 and associated genes

• Visualization Techniques:

  • Heat maps for visualizing correlations between ACAT2 expression and functional status of various tumors

  • Kaplan-Meier curves for depicting survival differences based on ACAT2 expression levels

  • ROC curves for assessing the predictive performance of ACAT2 as a biomarker

How can researchers effectively design experiments to study the functional interactions between ACAT2 and other metabolic enzymes?

To investigate functional interactions between ACAT2 and other metabolic enzymes:

• Interaction Network Analysis:

  • Use STRING tool (https://cn.string-db.org/) to identify proteins that interact with ACAT2

  • Input ACAT2 as the query protein and select the appropriate organism (e.g., Mus musculus for mouse studies)

• Co-expression Analysis:

  • Calculate Pearson's or Spearman's correlation coefficients between ACAT2 and potential interacting proteins

  • Identify genes with significant correlations that may function in the same pathways

• Pathway Analysis:

  • Perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses

  • Determine biological processes, cellular components, and molecular functions associated with ACAT2 and its interacting partners

• Experimental Validation:

  • Co-immunoprecipitation (IP) experiments to confirm physical interactions

  • Enzymatic assays to assess functional relationships

  • siRNA knockdown or CRISPR-Cas9 gene editing to evaluate the impact of ACAT2 on the activity of other metabolic enzymes

What are the emerging techniques for studying ACAT2 in complex biological systems?

Several cutting-edge approaches are being developed for investigating ACAT2 function:

• Computational Drug Discovery:

  • Integration of hypogen pharmacophore modeling, molecular docking, and molecular dynamics simulations

  • Virtual screening of compound libraries to identify novel ACAT2 inhibitors with improved efficacy and safety profiles

• Advanced Imaging Techniques:

  • Fluorescence-based assays using NBD22-steryl ester to visualize ACAT2 activity in living cells

  • Live cell imaging to track cholesterol metabolism in real-time

• Systems Biology Approaches:

  • Integration of multi-omics data to build comprehensive models of ACAT2's role in lipid metabolism

  • Development of mathematical models to predict the effects of ACAT2 modulation on cellular and organismal physiology

• Model Selection Optimization:

  • Implementation of Bayesian approaches for model selection in systems biology

  • Development of experimental design frameworks that account for model inaccuracies and structural uncertainties

How might discrepancies in experimental outcomes be addressed when working with ACAT2?

When faced with discrepancies in experimental outcomes involving ACAT2:

• Experimental Design Evaluation:

  • Consider how experimental design choices might influence model selection

  • Recognize that confidence in a model doesn't necessarily correlate with its predictive ability across all conditions

• Multi-model Analysis:

  • Instead of relying on a single model, consider multiple models that explain different aspects of ACAT2 function

  • Use model ensembles to capture the range of possible interpretations of experimental data

• Robustness Testing:

  • Perform experiments under diverse conditions to test the generalizability of findings

  • Conduct systematic variations of key experimental parameters to determine boundary conditions for observed effects

• Statistical Framework:

  • Employ Bayesian approaches that can incorporate prior knowledge about ACAT2

  • Use time-dependent analyses to capture dynamic aspects of ACAT2 function