ACAA1 Antibody

What is ACAA1 and why is it an important research target?

ACAA1 (acetyl-CoA acyltransferase 1) is an enzyme involved in lipid β-oxidation that provides substrates to the tricarboxylic acid (TCA) cycle, representing a critical step in cellular metabolism . The protein has a calculated molecular weight of 44 kDa, though it is typically observed at approximately 41 kDa in experimental contexts . ACAA1 is expressed in multiple tissues, with notable expression patterns in heart, liver, spleen, lung, kidney, and muscle tissues . Liver tissue demonstrates the highest expression levels, making it particularly relevant for metabolic research . The gene's involvement in fatty acid metabolism pathways makes it a valuable target for investigations into metabolic disorders, lipid metabolism, and related pathologies.

Which applications can ACAA1 antibodies be reliably used for?

ACAA1 antibodies have been validated for multiple experimental applications:

For optimal results, researchers should titrate the antibody for each specific experimental system, as reactivity may vary based on tissue type, fixation method, and detection system .

What species reactivity can be expected with commonly available ACAA1 antibodies?

ACAA1 antibodies show variable cross-reactivity depending on the specific product. The most commonly observed reactivity patterns include:

• Human, mouse, and rat samples are generally well-detected by many commercial antibodies

• Some antibodies demonstrate broader reactivity profiles, including guinea pig, horse, rabbit, zebrafish, cow, dog, and monkey samples, particularly those targeting conserved epitopes

When planning experiments with non-standard model organisms, researchers should carefully review the antibody specifications or conduct preliminary validation studies to confirm reactivity.

What are the optimal antigen retrieval methods for ACAA1 immunohistochemistry?

For effective immunohistochemical detection of ACAA1, the following antigen retrieval protocols have shown reliable results:

• Primary recommendation: TE buffer at pH 9.0

• Alternative approach: Citrate buffer at pH 6.0

When working with formalin-fixed paraffin-embedded (FFPE) tissues, adequate antigen retrieval is critical as ACAA1 epitopes may be masked during fixation processes. Heat-induced epitope retrieval (HIER) using the recommended buffers typically produces optimal staining results. Researchers should optimize retrieval time and temperature based on tissue type and section thickness. Generally, 15-20 minutes of heating at 95-100°C provides balanced retrieval while preserving tissue morphology.

How should researchers optimize Western blot protocols for ACAA1 detection?

For successful detection of ACAA1 by Western blot:

• Sample preparation: Use RIPA or NP-40 buffer supplemented with protease inhibitors

• Protein loading: 20-40 μg of total protein per lane is typically sufficient for detection

• Separation: 10-12% SDS-PAGE gels offer optimal resolution around the 41 kDa range where ACAA1 is observed

• Transfer: Semi-dry or wet transfer systems are suitable; PVDF membranes may provide better signal-to-noise ratios than nitrocellulose

• Blocking: 5% non-fat milk or BSA in TBST for 1 hour at room temperature

• Primary antibody: Dilute according to manufacturer recommendations (typically 1:500-1:2000) and incubate overnight at 4°C

• Detection: HRP-conjugated secondary antibodies with appropriate chemiluminescent substrates

When troubleshooting, consider that ACAA1 is predominantly expressed in liver tissues, so using liver extracts as positive controls is advisable .

What storage conditions maximize ACAA1 antibody stability and shelf life?

ACAA1 antibodies should be stored according to manufacturer recommendations to preserve functionality. Typical storage conditions include:

• Temperature: -20°C for long-term storage

• Buffer: PBS with 0.02% sodium azide and 50% glycerol at pH 7.3

• Aliquoting: For 20 μL size products containing 0.1% BSA, aliquoting may be unnecessary for -20°C storage

Antibodies maintained under these conditions remain stable for approximately one year after shipment . Researchers should avoid repeated freeze-thaw cycles, which can lead to antibody degradation and reduced binding efficiency. Working solutions should be prepared fresh and maintained at 4°C for short-term use only.

How can ACAA1 expression patterns be effectively analyzed across different tissues and developmental stages?

Analysis of ACAA1 expression across tissues and developmental stages requires careful experimental design:

• Tissue selection: Based on current research, liver tissue demonstrates the highest ACAA1 expression, followed by other metabolically active tissues such as heart, spleen, lung, kidney, and muscle

• Developmental considerations: ACAA1 gene expression in longissimus dorsi muscle has been shown to decrease with age (p < 0.01) , suggesting dynamic regulation during development

• Quantification methodology: For relative quantification of mRNA expression, the 2^-ΔΔCt method using GAPDH as a reference gene has proven effective

• Protein expression analysis: Combine Western blot quantification with immunohistochemical localization to correlate expression levels with specific cell types within tissues

When designing temporal expression studies, researchers should include multiple time points spanning the developmental period of interest, as exemplified by studies analyzing newborn, 6-month-old, and 12-month-old subjects to capture age-related expression changes .

What approaches can be used to study ACAA1 genetic variants and their functional implications?

ACAA1 genetic variants can be studied through several methodological approaches:

• SNP identification: Four SNPs have been detected in the ACAA1 gene, including exon 7 g.48810 A>G (rs343060194), intron 9 g.51546 T>C (rs319197012), exon 15 g.55035 T>C (rs333279910), and exon 15 g.55088 C>T (rs322138947)

• Sequence analysis: Comparing exonic mutation sites with reference sequences (e.g., NCBI amino acid reference sequence XP_003132151.1) to determine if mutations are synonymous or non-synonymous

• Linkage disequilibrium (LD) analysis: Strong LD has been observed between g.55035 T>C (rs333279910) and g.55088 C>T (rs322138947) , which can be quantified using squared allele-frequency correlations (r²) and normalized coefficient (D′)

• Statistical analysis: Hardy-Weinberg equilibrium testing (χ² test, p-value), genetic index calculation (gene heterozygosity (He), gene homozygosity (Ho), polymorphism information content (PIC)), and effective number of alleles (Ae) analysis

• Haplotype analysis: Using platforms like SHEsis (http://analysis.bio-x.cn) for LD analysis and haplotype analysis of SNPs

These approaches enable researchers to connect genetic variation with phenotypic traits and potentially exploit the ACAA1 gene for marker-assisted selection in agricultural applications or identify disease associations in biomedical research.

What are the considerations for multiplexing ACAA1 with other markers in immunofluorescence studies?

When designing multiplexed immunofluorescence experiments including ACAA1:

• Antibody compatibility: Select primary antibodies raised in different host species to enable simultaneous detection with species-specific secondary antibodies

• Expression localization: ACAA1 is primarily localized to peroxisomes, so consider co-staining with peroxisomal markers (e.g., PEX14, catalase) for subcellular context

• Spectral separation: Choose fluorophores with minimal spectral overlap to reduce bleed-through during imaging

• Sequential staining: For cases where primary antibodies are from the same host species, consider sequential staining protocols with intermediate blocking steps

• Validated cell systems: U-251 cells have been validated for ACAA1 immunofluorescence detection and can serve as positive controls

• Dilution optimization: When multiplexing, antibody dilutions may need to be adjusted from single-staining protocols; typically, use 1:250-1:1000 dilution for ACAA1 antibodies in IF/ICC applications

Proper controls, including single-stained samples and secondary-only controls, are essential for accurate interpretation of multiplexed experiments.

What are common challenges in ACAA1 antibody applications and how can they be addressed?

Researchers frequently encounter these challenges when working with ACAA1 antibodies:

• Weak signal in Western blot:

  • Increase protein loading (40-60 μg)

  • Extend primary antibody incubation time to overnight at 4°C

  • Use enhanced chemiluminescent substrates

  • Confirm sample source is appropriate (liver samples show highest expression)

• Background in immunohistochemistry:

  • Optimize blocking (try 5-10% normal serum from secondary antibody host species)

  • Increase washing steps (5-6 washes of 5 minutes each)

  • Reduce primary antibody concentration (try 1:50-1:200 range)

  • Test alternative antigen retrieval methods (TE buffer pH 9.0 vs. citrate buffer pH 6.0)

• Non-specific bands in Western blot:

  • Increase blocking time and concentration

  • Include 0.1-0.3% Tween-20 in wash buffers

  • Consider membrane stripping and reprobing with different ACAA1 antibodies targeting different epitopes

• Inconsistent results across species:

  • Verify antibody species reactivity claims

  • Select antibodies targeting highly conserved epitopes for cross-species detection

  • Consider species-specific positive controls

How should researchers interpret and validate ACAA1 expression data across different experimental systems?

Proper interpretation and validation of ACAA1 expression data requires:

• Multiple detection methods: Corroborate findings using complementary techniques (e.g., Western blot, qPCR, immunohistochemistry)

• Appropriate controls:

  • Positive tissue controls (liver tissue shows highest expression)

  • Negative controls (tissues with minimal ACAA1 expression)

  • Technical controls (secondary antibody only, isotype controls)

• Quantification approaches:

  • For protein: Densitometry normalized to loading controls (β-actin, GAPDH)

  • For mRNA: 2^-ΔΔCt method with appropriate housekeeping genes (GAPDH has been validated)

• Statistical analysis:

  • For tissue comparison: One-way ANOVA to compare differences among tissues

  • For developmental studies: ANOVA to assess differences across age groups

• Biological replication: Minimum of three biological replicates to account for individual variation

• Technical replication: Multiple technical replicates to ensure methodological reproducibility

When comparing across experimental systems, researchers should consider tissue-specific expression patterns and developmental regulation documented in the literature .

How can researchers distinguish between specific and non-specific binding when using ACAA1 antibodies?

To distinguish between specific and non-specific binding:

• Expected molecular weight: ACAA1 has a calculated molecular weight of 44 kDa but is typically observed at 41 kDa in Western blot applications

• Blocking peptide competition: Pre-incubating the antibody with the immunizing peptide should eliminate specific binding

• Knockdown/knockout validation: Using ACAA1 siRNA knockdown or CRISPR/Cas9 knockout samples provides definitive validation of antibody specificity

• Multiple antibodies approach: Testing multiple antibodies targeting different ACAA1 epitopes should yield consistent results for specific binding

• Tissue expression pattern: Specific binding should reflect known expression patterns, with highest detection in liver tissue

• Subcellular localization: ACAA1 is primarily localized to peroxisomes, so immunofluorescence patterns should be consistent with peroxisomal distribution

• Isotype control antibodies: Using matched isotype control antibodies at equivalent concentrations can help identify non-specific binding

Proper validation using these approaches ensures reliable interpretation of experimental results and supports reproducible research findings.

What role does ACAA1 play in metabolic disorders and how can antibody-based techniques contribute to this research?

ACAA1's role in lipid β-oxidation and TCA cycle substrate provision positions it as a key player in metabolic disorders. Antibody-based techniques can contribute to this research through:

• Expression profiling: Quantifying ACAA1 protein levels across patient cohorts with metabolic disorders versus controls

• Tissue distribution analysis: Mapping changes in ACAA1 expression across tissues in disease models using immunohistochemistry

• Post-translational modification detection: Developing and applying modification-specific antibodies to detect regulatory changes in ACAA1 under pathological conditions

• Protein-protein interaction studies: Using co-immunoprecipitation with ACAA1 antibodies to identify novel interaction partners in health and disease

• Therapeutic response monitoring: Measuring ACAA1 expression changes following pharmacological interventions targeting metabolic pathways

When designing such studies, researchers should consider tissue-specific expression patterns, with particular attention to liver tissue where ACAA1 is most abundantly expressed .

How can ACAA1 genetic variants be effectively studied in relation to phenotypic outcomes?

The study of ACAA1 genetic variants in relation to phenotypes requires:

• Comprehensive SNP identification: Beyond the four documented SNPs (rs343060194, rs319197012, rs333279910, rs322138947) , expanded sequencing efforts may reveal additional variants

• Functional characterization:

  • Synonymous mutations (as observed in exonic sites g.48810 A>G, g.55035 T>C, g.55088 C>T) may still affect mRNA stability or translation efficiency

  • Intronic mutations (e.g., g.51546 T>C) may influence splicing patterns

• Association analysis:

  • Genotype-phenotype correlations require appropriate statistical methodologies

  • Haplotype analysis may provide stronger associations than individual SNPs

  • Strong linkage disequilibrium between variants (e.g., between g.55035 T>C and g.55088 C>T with r² > 0.8) should be considered in association studies

• Population stratification:

  • Consider genetic background differences when interpreting associations

  • Calculate population genetic parameters (He, Ho, PIC) to characterize study populations

• Functional validation:

  • Expression quantitative trait loci (eQTL) analysis to link variants to expression levels

  • In vitro enzymatic activity assays to assess functional consequences

  • Animal models with specific genetic variants to evaluate phenotypic impacts

These approaches can elucidate the molecular mechanisms underlying ACAA1 variant associations with metabolic traits or disease susceptibility.

What considerations are important when studying ACAA1 in the context of peroxisomal disorders?

When investigating ACAA1 in peroxisomal disorders:

• Subcellular localization verification:

  • Co-localization studies with established peroxisomal markers

  • Subcellular fractionation followed by Western blotting

  • Electron microscopy with immunogold labeling for high-resolution localization

• Functional assays:

  • Measurement of thiolase activity in patient samples

  • Analysis of very long-chain fatty acid (VLCFA) accumulation

  • Assessment of peroxisomal β-oxidation pathway functionality

• Interaction studies:

  • Investigation of ACAA1 interactions with other peroxisomal proteins

  • Analysis of import machinery functionality in disease states

  • Evaluation of peroxisomal targeting sequence recognition

• Tissue-specific effects:

  • Comprehensive analysis across multiple tissues, with emphasis on liver where ACAA1 is highly expressed

  • Developmental considerations given the age-dependent expression patterns observed in some tissues

• Therapeutic monitoring:

  • Using ACAA1 antibodies to evaluate protein expression changes following experimental therapies

  • Correlation of ACAA1 levels with clinical biomarkers of peroxisomal function

These approaches provide a comprehensive framework for investigating ACAA1's role in peroxisomal disorders and potential therapeutic interventions.