ACSS1 Antibody

What is ACSS1 and what cellular compartment does it primarily function in?

ACSS1 (acetyl-CoA synthetase short-chain family member 1) is an enzyme that catalyzes the conversion of free acetate into acetyl coenzyme A (acetyl-CoA). Unlike its family members ACSS2 and ACSS3, ACSS1 is primarily localized to the mitochondria as confirmed through cellular fractionation experiments in multiple cell lines including Maver and Jeko-1 . This mitochondrial localization is critical for its function in energy metabolism, particularly under nutrient-deprived conditions when cells increasingly rely on acetate as a carbon source. The enzyme has a calculated molecular weight of 75 kDa based on its 689 amino acid sequence, though the observed molecular weight in experimental settings typically ranges between 70-75 kDa when detected via Western blot . ACSS1 represents one of three known mammalian enzymes capable of acetate-to-acetyl-CoA conversion, with each family member demonstrating distinct subcellular localization patterns that correlate with their specialized metabolic functions .

How does ACSS1 expression vary across different tissue types and disease states?

ACSS1 demonstrates variable expression patterns across different tissues and is significantly altered in several disease states. In normal tissues, ACSS1 protein is readily detectable in kidney and liver tissues, as evidenced by positive Western blot results from mouse kidney samples . In pathological conditions, particularly in hematological malignancies, ACSS1 shows marked upregulation. Immunohistochemical (IHC) staining of tumor tissue microarrays has revealed significant ACSS1 overexpression in mantle cell lymphoma (MCL) patient samples, with 92.59% (25/27) showing positive staining . Similarly, in diffuse large B-cell lymphoma (DLBCL), 79.54% (35/44) of patient samples showed ACSS1 positivity . Chronic lymphocytic leukemia (CLL) samples also demonstrated ACSS1 overexpression, with 53.84% (7/13) testing positive . Interestingly, ACSS1 expression appears to correlate with resistance to Ibrutinib (IBR) treatment in MCL and DLBCL cell lines, with IBR-resistant lines showing significantly higher ACSS1 expression compared to sensitive lines (18-fold increase in Jeko-1 and 24-fold increase in Maver compared to IBR-sensitive RL cells) .

What experimental methods are commonly used to detect ACSS1 in research settings?

Several experimental approaches can be employed to detect and quantify ACSS1 in research settings. Western blot (WB) represents the most widely used method, with recommended antibody dilutions ranging from 1:500 to 1:3000 . This technique has been successfully applied to various sample types including cell lines (Caco-2, Jurkat, RAW 264.7) and tissue samples (mouse kidney) . Immunohistochemistry (IHC) is another valuable approach, especially for examining ACSS1 expression in tissue sections, with recommended antibody dilutions of 1:100 to 1:400 . For IHC applications, antigen retrieval with TE buffer (pH 9.0) or alternatively citrate buffer (pH 6.0) is suggested for optimal results . Immunoprecipitation (IP) can be performed using 0.5-4.0 μg of antibody for 1.0-3.0 mg of total protein lysate . Immunofluorescence (IF) is also applicable for subcellular localization studies. When validating ACSS1 knockdown or knockout models, antibody specificity is particularly important, as evidenced by multiple published studies utilizing these techniques .

What metabolic alterations result from ACSS1-K635 acetylation site modification in mouse models?

The ACSS1-K635 acetylation site plays a crucial role in regulating ACSS1 function, as demonstrated by the K635Q knock-in mouse model that mimics constitutive acetylation at this position. K635Q/K635Q ACSS1 mice exhibit significant phenotypic and metabolic alterations including:

• Reduced body size despite normal food consumption and absorption (no differences in fecal lipids)

• Elevated metabolic rate accompanied by increased blood acetate levels

• Decreased liver and serum ATP and lactate concentrations

• Severe metabolic vulnerability during fasting, manifesting as hypothermia and liver abnormalities after 48-hour fast

• Liver pathology consistent with nonalcoholic fatty liver disease (NAFLD), including enlargement, discoloration, lipid droplet accumulation, and microsteatosis

RNA sequencing analysis of these mice revealed dysregulation of multiple metabolic networks, particularly those involved in fatty acid metabolism and cellular senescence . At the molecular level, fasted K635Q/K635Q ACSS1 mouse livers showed increased expression of fatty acid synthase (FASN) and stearoyl-CoA desaturase 1 (SCD1), both established NAFLD markers . Mechanistically, this appears to involve enhanced binding of carbohydrate response element-binding protein to the enhancer regions of Fasn and Scd1 genes . Lipidomic analysis further confirmed NAFLD-like alterations with elevated levels of ceramide, lysophosphatidylethanolamine, and lysophosphatidylcholine .

How does ACSS1 contribute to cancer metabolism in hematological malignancies?

ACSS1 plays a significant role in cancer metabolism, particularly in hematological malignancies where it shows notable overexpression. In mantle cell lymphoma (MCL), diffuse large B cell lymphoma (DLBCL), and chronic lymphocytic leukemia (CLL), ACSS1 expression is markedly elevated compared to normal tissues . Functional studies using ACSS1 knockdown (KD) cell lines have revealed several critical metabolic contributions:

• Mitochondrial function: ACSS1 KD results in reduced oxygen consumption, indicating impaired mitochondrial respiration

• Acetate metabolism: 13C-acetate stable isotope tracing experiments demonstrate that ACSS1 KD attenuates the flux of mitochondrial acetate to acetyl-CoA, acetylcarnitine, and TCA cycle intermediates

• De novo pyrimidine synthesis: ACSS1 depletion disrupts the production of glutamine and aspartate (TCA cycle-derived precursors for pyrimidine synthesis), resulting in decreased labeling of glutamate, aspartate, dihydroorotate, and orotate pools

• Oncometabolite regulation: ACSS1 regulates the oncometabolite 2-hydroxyglutarate, which is known to influence epigenetic programming in cancer cells

Notably, ACSS1 expression correlates with resistance to Ibrutinib (IBR) in MCL and DLBCL cell lines, with IBR-resistant lines showing significantly higher ACSS1 expression . This suggests that ACSS1-mediated metabolic adaptations may contribute to treatment resistance, highlighting its potential as a therapeutic target in refractory disease.

What are the key distinctions between ACSS1, ACSS2, and ACSS3 in terms of expression patterns and functions?

The ACSS enzyme family consists of three members with distinct subcellular localizations and expression patterns that dictate their specialized functions:

Analysis of cancer cell line encyclopedia data revealed that ACSS1 is highly expressed in hematological cancer cell lines including MCL, DLBCL, and anaplastic large cell lymphoma (ALCL) . In contrast, ACSS2 shows higher expression in solid tumor cell lines . Within MCL cell lines, ACSS1 expression is significantly higher than both ACSS2 and ACSS3 . The differential expression and subcellular localization of these enzymes suggest non-redundant roles in acetate metabolism, with ACSS1 primarily supporting mitochondrial energetics and ACSS2 contributing to cytosolic acetyl-CoA pools for lipid synthesis and histone modification .

What are the optimal conditions for using ACSS1 antibodies in Western blot applications?

For optimal Western blot detection of ACSS1, researchers should consider the following conditions and parameters:

• Antibody selection: Use validated antibodies like 17138-1-AP that have been tested with multiple sample types including cell lines and tissues

• Dilution ratio: The recommended dilution range is 1:500-1:3000, though optimal concentration should be determined empirically for each experimental system

• Expected molecular weight: ACSS1 typically appears at 70-75 kDa on Western blots, consistent with its calculated molecular weight of 75 kDa (689 amino acids)

• Validated sample types: Successful detection has been reported in:

  • Human cell lines: Caco-2, Jurkat

  • Mouse tissues: Kidney

  • Mouse cell lines: RAW 264.7

• Controls: Include appropriate positive controls such as mouse kidney tissue lysate, where ACSS1 is consistently detected

• Loading controls: Standard housekeeping proteins like GAPDH or β-actin should be used to normalize ACSS1 expression

When comparing ACSS1 expression across different tissues or experimental conditions, it is advisable to run samples in triplicate and quantify band intensity using image analysis software. For studying ACSS1 in subcellular compartments, cellular fractionation followed by Western blot analysis can confirm its mitochondrial localization, as demonstrated in MCL cell lines Maver and Jeko-1 .

How should researchers optimize immunohistochemistry protocols for ACSS1 detection in tissue samples?

Successful detection of ACSS1 in tissue samples via immunohistochemistry requires careful optimization of several parameters:

• Antigen retrieval: TE buffer (pH 9.0) is recommended as the primary method, though citrate buffer (pH 6.0) can serve as an alternative

• Antibody dilution: The recommended range is 1:100-1:400, with optimal concentration determined empirically for each tissue type

• Tissue preparation: Formalin-fixed, paraffin-embedded (FFPE) sections are suitable, as demonstrated in various human cancer tissues

• Positive control tissues: Human liver cancer tissue has been validated as a positive control for ACSS1 IHC

• Signal interpretation: In MCL and DLBCL samples, ACSS1 staining has been categorized as:

  • Strong: 25.93% of MCL samples; 13.63% of DLBCL samples

  • Moderate: 33.33% of MCL samples; 31.82% of DLBCL samples

  • Weak: 33.33% of MCL samples; 34.09% of DLBCL samples

• Background minimization: Proper blocking with appropriate serum (matching the species of the secondary antibody) helps reduce non-specific staining

For tissue microarray (TMA) analysis, researchers have successfully used ACSS1 antibodies to evaluate expression across multiple patient samples simultaneously, as demonstrated with MCL (N=27), DLBCL (N=44), and CLL (N=13) samples . When examining cellular localization, higher magnification imaging can confirm the mitochondrial pattern of ACSS1 expression, which appears as punctate cytoplasmic staining consistent with mitochondrial distribution.

What strategies can be employed to validate ACSS1 knockdown or knockout models?

Validation of ACSS1 knockdown (KD) or knockout (KO) models is critical for ensuring experimental rigor in functional studies. Based on published methodologies, researchers should implement the following validation strategies:

• Genotyping: For genetic models like the ACSS1-K635Q knock-in mouse, PCR-based genotyping using specific primers is essential. The wild-type and knock-in alleles yield distinct PCR product sizes (169 bp and 217 bp, respectively)

• mRNA expression: Quantitative PCR (qPCR) should confirm equivalent levels of ACSS1 mRNA expression between wild-type and mutant genotypes, or verify successful knockdown in KD models

• Protein expression: Western blot analysis using validated ACSS1 antibodies (e.g., 17138-1-AP) confirms altered protein expression in multiple tissues:

  • Heart and kidney tissues (Fig. 1E in referenced studies)

  • Liver tissue (Fig. 1F)

• Functional validation: For metabolic phenotyping, researchers should assess:

  • Oxygen consumption rate (OCR) using mitochondrial stress tests, which show reduced respiration in ACSS1 KD lines

  • 13C-acetate stable isotope tracing to confirm altered metabolic flux through ACSS1-dependent pathways

  • Changes in TCA cycle intermediates and related metabolites

• Phenotypic characterization: In mouse models, comprehensive assessment should include:

  • Body size measurements over time

  • Metabolic parameters (blood acetate, ATP levels)

  • Tissue-specific changes, particularly in liver morphology and lipid content

These multi-level validation approaches ensure that observed phenotypes can be confidently attributed to specific alterations in ACSS1 expression or function.

What are common technical challenges in detecting ACSS1 and how can they be overcome?

Researchers may encounter several technical challenges when detecting ACSS1 in experimental systems. Here are common issues and their solutions:

• Low signal intensity in Western blots:

  • Increase antibody concentration (within the recommended 1:500-1:3000 range)

  • Extend primary antibody incubation time (overnight at 4°C)

  • Use enhanced chemiluminescence (ECL) substrates with higher sensitivity

  • Increase protein loading (30-50 μg of total protein recommended)

• High background in immunohistochemistry:

  • Optimize antibody dilution (test range from 1:100-1:400)

  • Improve blocking (5% normal serum from secondary antibody species)

  • Extend washing steps (3x 5 minutes with PBS-T)

  • Ensure proper antigen retrieval with recommended TE buffer (pH 9.0)

• Cross-reactivity with other ACSS family members:

  • Verify antibody specificity using ACSS1 knockout/knockdown controls

  • Consider using antibodies raised against unique epitopes of ACSS1

  • Confirm results with multiple antibody clones if possible

• Variable expression in tissue samples:

  • Use tissue microarrays (TMAs) to standardize staining conditions across samples

  • Implement digital pathology scoring to reduce subjective interpretation

  • Include positive controls (e.g., human liver cancer tissue) in each staining batch

• Immunoprecipitation inefficiency:

  • Optimize antibody amount (0.5-4.0 μg for 1.0-3.0 mg of total protein lysate)

  • Consider crosslinking antibody to beads to reduce heavy chain interference

  • Use mouse kidney tissue as a positive control for IP optimization

By systematically addressing these technical challenges, researchers can achieve more consistent and reliable detection of ACSS1 across different experimental applications.

How can researchers differentiate between the effects of ACSS1 and other acetyl-CoA producing enzymes in metabolic studies?

Distinguishing ACSS1-specific effects from those of other acetyl-CoA producing enzymes requires strategic experimental approaches:

• Subcellular fractionation: Separate mitochondrial and cytosolic fractions to isolate ACSS1 activity (mitochondrial) from ACSS2 (cytosolic/nuclear) . This approach has successfully demonstrated predominant mitochondrial localization of ACSS1 in MCL cell lines like Maver and Jeko-1 .

• Selective inhibition or knockdown:

  • Use siRNA or shRNA specifically targeting ACSS1 while monitoring ACSS2 and ACSS3 expression to ensure specificity

  • Compare metabolic effects of ACSS1 knockdown with those of other family members

  • Rescue experiments with wild-type ACSS1 can confirm specificity of observed phenotypes

• 13C-labeled substrate tracing:

  • 13C-acetate is particularly useful for tracking ACSS1-dependent metabolism

  • Analyze isotope incorporation into TCA cycle intermediates, which are predominantly influenced by mitochondrial ACSS1 activity

  • Compare patterns with other labeled substrates (e.g., glucose, glutamine) that enter metabolism through different pathways

• Oxygen consumption measurement:

  • Mitochondrial stress tests show reduced oxygen consumption specifically in ACSS1 knockdown cells

  • This parameter primarily reflects mitochondrial acetyl-CoA production rather than cytosolic pathways

• Conditional knockout models:

  • Tissue-specific or inducible ACSS1 knockout systems provide temporal and spatial control

  • The ACSS1-K635Q knock-in mouse model offers insights into post-translational regulation specifically affecting ACSS1 function

By combining these approaches, researchers can attribute metabolic phenotypes to specific enzymes in the acetyl-CoA production pathway with greater confidence.

What controls should be included when studying ACSS1 in disease models such as NAFLD or cancer?

When investigating ACSS1 in disease models, comprehensive controls are essential to ensure experimental validity and interpretability:

• Genetic model controls:

  • For the ACSS1-K635Q knock-in mouse model, include wild-type (+/+), heterozygous (+/K635Q), and homozygous (K635Q/K635Q) animals to assess dose-dependent effects

  • Confirm equivalent ACSS1 expression levels across genotypes using qPCR and Western blot to rule out expression-level artifacts

• Physiological condition controls:

  • In NAFLD studies, compare fed versus fasted states (e.g., 48-hour fast revealed severe phenotypes in K635Q/K635Q mice)

  • For cancer studies, compare normoxic versus hypoxic conditions, as ACSS1 may be particularly important under oxygen limitation

• Cell line controls:

  • In lymphoma studies, include both Ibrutinib-sensitive (e.g., RL, OCI-LY1) and Ibrutinib-resistant (e.g., Jeko-1, Maver, OCI-LY8) cell lines to correlate ACSS1 expression with drug response

  • Use multiple cell lines representing the same cancer type to account for genetic heterogeneity

• Technical controls for antibody-based detection:

  • Positive tissue controls: Mouse kidney for Western blot; human liver cancer tissue for IHC

  • Negative controls: Secondary antibody only; isotype controls; ACSS1 knockdown samples

• Metabolic pathway controls:

  • Compare acetate metabolism with glucose and glutamine utilization to determine pathway-specific effects

  • In 13C-acetate tracing experiments, analyze multiple downstream metabolites including acetyl-CoA, acetylcarnitine, TCA cycle intermediates, and pyrimidine precursors

• Patient sample controls:

  • For tissue microarray studies, include normal adjacent tissue when available

  • Stratify cancer samples by relevant clinical parameters (stage, treatment history, etc.)

Inclusion of these comprehensive controls enables more confident interpretation of ACSS1's role in disease pathophysiology and potential as a therapeutic target.

How does ACSS1 acetylation at K635 contribute to nonalcoholic fatty liver disease pathogenesis?

Recent research using ACSS1-K635Q knock-in mice has revealed a critical role for ACSS1 acetylation in nonalcoholic fatty liver disease (NAFLD) pathogenesis. The K635Q substitution mimics constitutive acetylation at this site and produces several NAFLD-associated phenotypes:

• Metabolic dysregulation: K635Q/K635Q mice exhibit higher metabolic rates with elevated blood acetate levels but decreased liver/serum ATP and lactate concentrations, indicating fundamental bioenergetic alterations .

• Fasting vulnerability: Following a 48-hour fast, K635Q/K635Q mice develop severe hypothermia and striking liver pathology including:

  • Macroscopic changes: Liver enlargement and discoloration

  • Microscopic alterations: Significant lipid droplet accumulation and microsteatosis

• Molecular mechanisms: RNA sequencing analysis identified dysregulation of:

  • Fatty acid metabolism networks

  • Cellular senescence pathways

  • Hepatic steatosis-associated gene signatures

• Lipogenic enzyme dysregulation: Fasted K635Q/K635Q mouse livers showed marked upregulation of:

  • Fatty acid synthase (FASN)

  • Stearoyl-CoA desaturase 1 (SCD1)
    Both enzymes are established NAFLD markers and promote lipid accumulation

• Transcriptional regulation: Enhanced binding of carbohydrate response element-binding protein to the enhancer regions of Fasn and Scd1 genes in K635Q/K635Q mice, suggesting a direct mechanism for increased lipogenic enzyme expression

• Lipidomic alterations: Comprehensive liver lipidomics revealed elevated levels of:

  • Ceramide species

  • Lysophosphatidylethanolamine

  • Lysophosphatidylcholine
    All of these lipid species are established NAFLD biomarkers

These findings suggest that ACSS1-K635 acetylation serves as a critical regulatory switch that, when dysregulated, promotes a metabolic environment conducive to NAFLD development through altered mitochondrial acetyl-CoA metabolism and subsequent lipogenic programming.

What is the relationship between ACSS1 expression and treatment resistance in hematological malignancies?

Recent investigations have uncovered a significant correlation between ACSS1 expression and treatment resistance in hematological malignancies, particularly regarding Ibrutinib (IBR) therapy:

• Expression pattern analysis: Across multiple B-cell lymphoma cell lines, ACSS1 expression levels strongly correlate with IBR sensitivity:

  • IBR-resistant MCL cell lines (Jeko-1, Maver) exhibit 18-fold and 24-fold higher ACSS1 expression, respectively, compared to IBR-sensitive RL cells

  • In DLBCL, IBR-resistant OCI-LY8 cells show significantly higher ACSS1 expression than IBR-sensitive OCI-LY1 cells

  • Immunoblotting confirms this pattern across five MCL cell lines (Jeko-1, Maver, Mino, Granta, and RL) and four DLBCL cell lines (OCI-LY1, OCI-LY4, OCI-LY8, and Toledo)

• Patient sample validation: Immunohistochemical analysis of patient-derived samples demonstrates ACSS1 overexpression in:

  • 92.59% of MCL patient samples (N=27)

  • 79.54% of DLBCL patient samples (N=44)

  • 53.84% of CLL patient samples (N=13)

• Metabolic adaptations: ACSS1 knockdown experiments reveal several metabolic effects that may contribute to treatment resistance:

  • Reduced mitochondrial respiration (oxygen consumption)

  • Decreased acetate-to-acetyl-CoA flux

  • Impaired TCA cycle intermediate production

  • Disrupted de novo pyrimidine synthesis

• Oncometabolite regulation: ACSS1 regulates the production of 2-hydroxyglutarate, an oncometabolite known to influence epigenetic programming and potentially contributing to therapy resistance mechanisms

These findings suggest that high ACSS1 expression may enable metabolic adaptations that confer resistance to targeted therapies like IBR. The correlation between ACSS1 levels and treatment resistance across multiple lymphoma types indicates that ACSS1 could serve as both a biomarker for predicting treatment response and a potential therapeutic target for overcoming resistance in refractory disease.

How might ACSS1 be leveraged as a therapeutic target in metabolic diseases and cancer?

Based on emerging understanding of ACSS1 biology, several strategies for therapeutic targeting can be envisioned:

• Direct enzyme inhibition:

  • Development of small molecule inhibitors specifically targeting ACSS1's catalytic domain

  • Design of compounds that selectively inhibit ACSS1 while sparing ACSS2 and ACSS3 to minimize off-target effects

  • Creation of mitochondria-targeted inhibitors to enhance specificity for ACSS1 over cytosolic ACSS2

• Post-translational modification targeting:

  • Modulation of the acetylation status of ACSS1-K635, given its critical regulatory role demonstrated in knock-in mouse models

  • Development of compounds that prevent or reverse acetylation at K635 to restore normal ACSS1 function in NAFLD

• Combinatorial approaches for cancer therapy:

  • ACSS1 inhibition combined with Ibrutinib in resistant lymphomas, targeting the metabolic adaptation mechanisms associated with high ACSS1 expression

  • Dual targeting of ACSS1 and de novo pyrimidine synthesis pathways, given ACSS1's role in supporting nucleotide biosynthesis

  • Combination with inhibitors of oncometabolite (2-hydroxyglutarate) production or signaling

• Metabolic vulnerability exploitation:

  • Therapeutic fasting protocols that might selectively stress ACSS1-dependent cancer cells

  • Acetate availability modulation to target cancers with high ACSS1 expression

• Biomarker-guided precision medicine:

  • ACSS1 IHC scoring as a predictive biomarker for treatment selection in lymphomas

  • Stratification of patients based on ACSS1 expression levels (strong, moderate, weak) as demonstrated in MCL and DLBCL studies

• Diagnostic applications:

  • Development of ACSS1 activity-based probes for functional imaging

  • Monitoring ACSS1 expression or acetylation status to track NAFLD progression

As research continues to elucidate ACSS1's complex roles in normal physiology and disease states, these therapeutic strategies will likely be refined to maximize efficacy while minimizing potential side effects on normal cellular metabolism.