ACAT1 Antibody

What is ACAT1 and what are its primary cellular functions?

ACAT1, known as Acetyl-CoA Acetyltransferase 1, is a mitochondrially localized enzyme that catalyzes the reversible formation of acetoacetyl-CoA from two acetyl-CoA molecules . It plays a major role in ketone body metabolism and influences lipid accumulation within cells . The protein mediates the regulation of cellular cholesterol levels, which is vital for maintaining membrane integrity and cellular function . ACAT1 has several synonyms in the literature, including T2, MAT, THIL, and ACAT . The enzyme has a calculated molecular weight of 45 kDa, though it is often observed at approximately 42 kDa in experimental conditions . In human cells, ACAT1 is predominantly localized in the mitochondria, where it participates in metabolic pathways essential for energy production and lipid homeostasis .

What types of ACAT1 antibodies are available for research applications?

Multiple types of ACAT1 antibodies are available for research, varying in the epitope recognized, host species, clonality, and conjugation status. Polyclonal antibodies are common, typically generated in rabbits, with some produced in goats . These antibodies target different regions of the ACAT1 protein, including:

• N-terminal region (AA 1-145)

• Internal regions

• C-terminal regions (AA 296-329)

• Specific sequences such as AA 76-106, AA 111-427, or AA 257-269

Monoclonal antibodies are also available, such as the [9H10AB4] clone, which offers high specificity for particular epitopes . Most ACAT1 antibodies are unconjugated, allowing researchers flexibility in detection methods . Both monoclonal and polyclonal options provide different advantages depending on experimental requirements for specificity versus broad epitope recognition.

What experimental applications are ACAT1 antibodies validated for?

ACAT1 antibodies have been validated for multiple experimental techniques, with applications varying by specific antibody product. Common validated applications include:

Validation status differs between antibodies, with some being extensively tested across multiple applications and species, while others have more limited validation data available . Researchers should review the specific validation data for their antibody of interest before designing experiments.

How do ACAT1 antibodies contribute to cancer research, particularly in clear cell renal cell carcinoma (ccRCC)?

ACAT1 antibodies have revealed significant insights into the role of ACAT1 in cancer biology, particularly in clear cell renal cell carcinoma (ccRCC). Immunohistochemical analysis using ACAT1 antibodies on tissue microarrays has demonstrated that ACAT1 expression levels correlate with clinical outcomes in ccRCC patients . Methodologically, researchers have employed a systematic approach for quantifying ACAT1 expression in tissue samples:

• Paraffin sections are hydrated, embedded, and incubated with 3% H₂O₂

• Antigen retrieval is performed using citrate buffer

• Tissues are blocked with 5% BSA before incubation with ACAT1 antibody

• A scoring system evaluates both staining intensity (0-3 points) and positive rate (0-4 points)

• Total scores are calculated by multiplying intensity and positive rate scores

Research utilizing ACAT1 antibodies has revealed that overexpression of ACAT1 significantly inhibits proliferation and migration of ccRCC cells . This was demonstrated through multiple experimental approaches including MTT assays, cloning formation assays, Ki-67 immunofluorescence staining, and Transwell migration assays . These findings suggest ACAT1 may function as a tumor suppressor in ccRCC, with potential implications for diagnostic and therapeutic strategies.

What considerations should researchers make when interpreting subcellular localization patterns of ACAT1?

When interpreting subcellular localization patterns of ACAT1 using immunofluorescence or immunohistochemistry, researchers should consider several methodological factors:

• ACAT1 exhibits distinctive subcellular localization patterns that vary by cell type. In neuronal tissues, particularly in Purkinje cells of the human cerebellum, ACAT1 shows a distinctive subcellular distribution pattern .

• While ACAT1 is primarily described as mitochondrial, the specific distribution pattern within cells may have functional significance not yet fully understood .

• When analyzing localization patterns, researchers should employ co-localization studies with established mitochondrial markers to confirm the expected mitochondrial distribution.

• Fixation methods can significantly affect the observed subcellular distribution pattern. Overfixation may mask epitopes in certain cellular compartments, while inadequate fixation may lead to extraction of the protein during processing.

• The specific epitope targeted by the antibody may influence the observed localization pattern, as some epitopes might be masked in particular subcellular contexts.

Researchers should document and quantify the distinctive subcellular patterns observed, as these may provide insights into previously unrecognized functions of ACAT1 in different cell types or disease states .

How can researchers optimize ACAT1 antibody dilutions for Western blot applications?

Optimizing ACAT1 antibody dilutions for Western blot requires a systematic approach to achieve specific signal detection while minimizing background:

• Initial dilution assessment: Begin with the manufacturer's recommended dilution range, typically 1:500-1:1000 for ACAT1 antibodies . Conduct a preliminary experiment testing 3-4 different dilutions within this range.

• Sample source considerations: Different sample types require different optimization approaches:

  • For cell lines with known ACAT1 expression (e.g., HepG2, PC-3, DU145, A-549), use these as positive controls

  • For tissue samples, human liver mitochondria serve as strong positive controls

  • Include negative controls where possible (ACAT1-knockdown cells or non-relevant tissue)

• Loading control selection: GAPDH is commonly used as a loading control for ACAT1 Western blots, but mitochondrial markers may be more appropriate given ACAT1's mitochondrial localization .

• Molecular weight verification: Confirm that the detected band appears at the expected molecular weight - calculated at 45 kDa but often observed at approximately 42 kDa .

• Signal-to-noise optimization: If background is high at the recommended dilution, conduct a titration series increasing the antibody dilution (e.g., 1:1000, 1:2000, 1:5000) while extending exposure time as needed.

• Blocking optimization: If non-specific binding persists, modify your blocking solution (test BSA vs. non-fat dry milk) and consider including low concentrations (0.1-0.3%) of Tween-20 in wash buffers.

This methodical approach ensures optimal signal specificity while conserving valuable antibody resources.

What cross-reactivity considerations exist when using ACAT1 antibodies across different species?

When selecting ACAT1 antibodies for cross-species applications, researchers should carefully evaluate reactivity profiles and sequence homology:

When using antibodies across species, researchers should:

• Perform sequence alignments of the target epitope region across species of interest to predict potential cross-reactivity.

• Validate antibody performance in each species experimentally, even when cross-reactivity is claimed by manufacturers.

• Include appropriate positive control samples from each species (e.g., mouse heart, rat heart, rat liver, and rat kidney tissues have been validated for certain ACAT1 antibodies) .

• Consider epitope-specific differences in cross-reactivity - antibodies targeting highly conserved domains (like catalytic regions) typically show better cross-reactivity.

• Adjust antibody concentrations when moving between species, as optimal dilutions may differ even with cross-reactive antibodies.

This systematic approach ensures reliable results when studying ACAT1 across different experimental animal models.

What sample preparation protocols enhance ACAT1 detection in immunohistochemistry?

Effective sample preparation is critical for successful ACAT1 detection in immunohistochemistry applications. The following protocol has been validated for optimal ACAT1 immunodetection:

• Fixation and embedding:

  • Process tissues through standard paraffin embedding

  • Section tissues at 4-6 μm thickness

  • Mount sections on positively charged slides

• Deparaffinization and rehydration:

  • Incubate sections at 60°C for 1 hour

  • Deparaffinize in xylene (two changes, 5 minutes each)

  • Rehydrate through graded ethanol series to distilled water

• Antigen retrieval (critical step):

  • Immerse slides in citrate buffer (pH 6.0)

  • Heat using a pressure cooker or microwave method

  • Allow sections to cool to room temperature gradually

• Endogenous peroxidase blocking:

  • Incubate with 3% H₂O₂ for 15 minutes

  • Wash thoroughly in PBS or TBS

• Protein blocking:

  • Block with 5% BSA for optimal results

  • Incubate at room temperature for 30-60 minutes

• Primary antibody incubation:

  • Apply ACAT1 antibody at optimized dilution

  • Incubate in a humidified chamber at 4°C overnight

  • Include negative controls (omitting primary antibody)

• Detection system:

  • Use biotinylated secondary antibody followed by HRP substrate solution

  • Develop with DAB chromogen

  • Counterstain with hematoxylin

This protocol has successfully demonstrated ACAT1 localization in various tissues, including distinctive patterns in neuronal cell bodies like Purkinje cells .

What methodological approaches help resolve discrepancies between calculated and observed molecular weights of ACAT1?

Researchers frequently observe discrepancies between the calculated molecular weight of ACAT1 (45 kDa) and its apparent molecular weight on Western blots (often observed at 42 kDa) . Several methodological approaches can help investigate and resolve these differences:

• SDS-PAGE optimization:

  • Use gradient gels (4-15% or 4-20%) to improve resolution around the 40-50 kDa range

  • Include molecular weight markers that bracket the expected range closely

  • Employ extended run times to improve separation of similar-sized proteins

• Sample preparation considerations:

  • Test different lysis buffers to ensure complete protein extraction

  • Include protease inhibitors to prevent degradation

  • Compare reducing and non-reducing conditions

• Post-translational modification analysis:

  • Treat lysates with phosphatases to identify phosphorylation contributions

  • Use deglycosylation enzymes (PNGase F, Endo H) to identify glycosylation effects

  • Consider other modifications (acetylation, methylation) that may alter mobility

• Isoform identification:

  • Design primers for RT-PCR to detect potential splice variants

  • Use antibodies targeting different epitopes to determine if different-sized bands represent isoforms

  • Perform mass spectrometry analysis on the immunoprecipitated protein

• Confirming specificity:

  • Use ACAT1 knockout or knockdown samples as negative controls

  • Perform peptide competition assays to verify antibody specificity

  • Employ immunoprecipitation followed by mass spectrometry to confirm protein identity

These approaches provide a systematic framework for investigating molecular weight discrepancies, ensuring accurate interpretation of ACAT1 experimental results.

How can ACAT1 antibodies be utilized to investigate the enzyme's role in metabolic disorders?

ACAT1 antibodies enable multifaceted investigation of this enzyme's role in metabolic disorders through several methodological approaches:

• Tissue expression profiling:

  • Perform immunohistochemistry on tissues relevant to metabolic disorders (liver, adipose, pancreas)

  • Quantify ACAT1 expression patterns using standardized scoring systems (intensity × positive rate)

  • Compare expression across healthy and diseased states using tissue microarrays

• Subcellular distribution analysis:

  • Use immunofluorescence with confocal microscopy to map ACAT1 localization

  • Perform co-localization studies with mitochondrial markers and lipid droplet stains

  • Investigate redistribution of ACAT1 under metabolic stress conditions

• Protein-protein interaction studies:

  • Conduct co-immunoprecipitation with ACAT1 antibodies to identify binding partners

  • Verify interactions through reciprocal immunoprecipitation

  • Perform proximity ligation assays to confirm interactions in intact cells

• Response to metabolic interventions:

  • Utilize Western blotting to measure ACAT1 expression changes during:

    • High-fat diet interventions

    • Fasting-feeding cycles

    • Pharmacological treatments targeting lipid metabolism

  • Correlate ACAT1 levels with metabolic parameters and lipid profiles

• Functional correlation studies:

  • Combine ACAT1 immunodetection with functional assays (cellular cholesterol measurements, lipid droplet quantification)

  • Assess ACAT1 expression in relation to enzyme activity measurements

  • Correlate expression patterns with disease severity markers

These approaches leverage ACAT1 antibodies to build comprehensive understanding of how this enzyme contributes to metabolic dysregulation and identify potential intervention points for metabolic disorders.

What techniques can researchers employ to study ACAT1 in cell-specific contexts using immunofluorescence?

Researchers can employ advanced immunofluorescence techniques to study ACAT1 in cell-specific contexts through the following methodological approaches:

• Multiplex immunofluorescence:

  • Combine ACAT1 antibodies with cell-type-specific markers (e.g., NeuN for neurons, GFAP for astrocytes)

  • Use antibodies raised in different host species to allow simultaneous detection

  • Employ sequential labeling protocols with tyramide signal amplification for same-species antibodies

  • Analysis example: This approach has revealed distinctive ACAT1 patterns in Purkinje cells compared to other cerebellar neurons

• High-resolution microscopy techniques:

  • Implement super-resolution microscopy (STED, STORM, SIM) to resolve ACAT1 localization beyond diffraction limit

  • Employ deconvolution algorithms to enhance spatial resolution in conventional confocal microscopy

  • Use Airyscan or similar technologies for improved signal-to-noise ratio with preserved sample integrity

• Live-cell imaging approaches:

  • Combine immunofluorescence with genetically encoded reporters in live specimens

  • Establish correlative light and electron microscopy (CLEM) workflows to connect fluorescence patterns with ultrastructural features

  • Implement proximity ligation assays to visualize ACAT1 interactions with binding partners

• Quantitative analysis workflows:

  • Develop automated image analysis pipelines for unbiased quantification

  • Implement machine learning approaches for pattern recognition in complex tissues

  • Establish standardized protocols for comparing ACAT1 distribution across experimental conditions

• Functional correlation:

  • Combine immunofluorescence with functional readouts such as Ki-67 staining to correlate ACAT1 expression with proliferation

  • Implement metabolic labeling techniques to connect ACAT1 localization with active lipid metabolism

These approaches enable researchers to move beyond simple protein detection to understand the functional significance of ACAT1 in specific cellular contexts and disease states.

How might ACAT1 antibodies contribute to developing therapeutic strategies for ACAT1-related disorders?

ACAT1 antibodies can significantly advance therapeutic development for ACAT1-related disorders through several research pathways:

• Target validation and mechanism elucidation:

  • Use immunohistochemistry with ACAT1 antibodies to establish expression patterns in disease tissues

  • Correlate ACAT1 expression with disease progression through tissue microarray analysis

  • Map changes in ACAT1 expression in response to experimental therapeutics

• Drug screening and development:

  • Develop cell-based assays using ACAT1 antibodies to screen compounds that modulate ACAT1 expression

  • Employ Western blotting to validate hits from high-throughput screens

  • Use immunofluorescence to assess subcellular redistribution of ACAT1 in response to therapeutic candidates

• Biomarker development:

  • Establish standardized immunohistochemical scoring systems for ACAT1 (similar to the 0-12 point system used in ccRCC)

  • Correlate expression scores with clinical outcomes to establish prognostic value

  • Develop companion diagnostic approaches to identify patients likely to respond to ACAT1-targeted therapies

• Therapeutic efficacy monitoring:

  • Monitor changes in ACAT1 expression patterns during clinical trials

  • Correlate expression changes with clinical response parameters

  • Identify resistance mechanisms through analysis of non-responding samples

• Delivery system development and validation:

  • Use immunofluorescence to track distribution of ACAT1-targeted delivery systems

  • Verify target engagement in specific cell populations

  • Assess on-target versus off-target effects of therapeutic approaches

These approaches leverage ACAT1 antibodies not only as research tools but as essential components in translating basic science findings into clinical applications, particularly in cancer contexts where ACAT1 has demonstrated anti-proliferative and anti-migratory effects .

What methodological considerations are important when developing ACAT1 antibody-based diagnostic tests?

Developing ACAT1 antibody-based diagnostic tests requires attention to several critical methodological considerations to ensure reliability, reproducibility, and clinical utility:

• Antibody selection and validation:

  • Evaluate multiple antibodies targeting different ACAT1 epitopes

  • Perform extensive cross-reactivity testing to ensure specificity

  • Validate antibodies using positive and negative control samples (e.g., ACAT1 knockout models)

  • Demonstrate reproducibility across different sample types and preparation methods

• Sample preparation standardization:

  • Establish standardized protocols for tissue fixation, processing, and antigen retrieval

  • Determine optimal sectioning thickness for consistent results

  • Develop standardized cell preparation protocols for circulating tumor cell analysis

  • Validate preservation methods for long-term sample storage

• Staining protocol optimization:

  • Develop automated staining protocols to reduce inter-operator variability

  • Establish quality control procedures using reference materials

  • Implement internal controls within each test run

  • Determine optimal primary antibody concentrations and incubation conditions

• Scoring system development:

  • Establish standardized scoring systems combining intensity and percentage positivity

  • Validate scoring systems through multi-observer studies to assess reproducibility

  • Correlate scores with disease parameters to establish clinical relevance

  • Consider automated image analysis to reduce subjective interpretation

• Clinical validation:

  • Determine sensitivity and specificity in well-characterized patient cohorts

  • Establish reference ranges for normal versus pathological ACAT1 expression

  • Assess prognostic value through correlation with clinical outcomes

  • Compare performance against established diagnostic methods

The development of such tests could be particularly valuable in cancer contexts, where ACAT1 expression has shown prognostic significance, as demonstrated in clear cell renal cell carcinoma studies .