ATP6V0A1 Antibody

What is ATP6V0A1 and what cellular functions does it regulate?

ATP6V0A1 (ATPase, H+ transporting, lysosomal V0 subunit a1) is a critical component of vacuolar ATPase (V-ATPase), a multisubunit enzyme responsible for mediating acidification of eukaryotic intracellular organelles. It serves as part of the membrane-embedded V0 domain that facilitates proton translocation across cellular membranes. This protein is essential for maintaining pH balance in acidic compartments within cells and plays vital roles in multiple cellular processes including protein degradation, membrane trafficking, and ion homeostasis . Recent research has identified ATP6V0A1 as a novel immunosuppressive factor in colorectal cancer, where it promotes RABGEF1-dependent cholesterol absorption and subsequently initiates paracrine TGF-β1/SMAD3 signaling to deactivate memory CD8+ T cells . This mechanism represents a previously uncharacterized pathway by which tumor cells can evade immune responses.

Which experimental applications are validated for ATP6V0A1 antibodies?

ATP6V0A1 antibodies have been validated for multiple research applications with specific recommended dilutions:

Both antibodies have been rigorously tested and validated in peer-reviewed publications across multiple techniques, with demonstrated reactivity in human, mouse, and rat samples . For optimal results, it is recommended to titrate the antibody concentration in each specific experimental system to account for variations in tissue type, sample preparation, and detection methods.

What tissue-specific considerations exist when using ATP6V0A1 antibodies?

ATP6V0A1 antibodies have demonstrated reliable detection in specific tissues with important methodological considerations. Positive Western blot detection has been confirmed in mouse and rat brain tissues, suggesting particularly high expression or favorable detection conditions in neural tissues . For immunohistochemistry applications in brain tissues, antigen retrieval becomes a critical step. The recommended protocol utilizes TE buffer at pH 9.0, though citrate buffer at pH 6.0 serves as an acceptable alternative . This difference in buffer systems highlights the importance of optimizing antigen retrieval conditions when working with different tissue types. Researchers studying ATP6V0A1 in colorectal cancer contexts should note that while the protein is detectable in these tissues, optimization may be required due to potentially varying expression levels based on the tumor's lipid metabolism status and immune activity profile .

How can I address observed discrepancies between calculated and observed molecular weights for ATP6V0A1?

The calculated molecular weight of ATP6V0A1 (96 kDa based on 837 amino acids) differs from its observed molecular weight of approximately 116 kDa on SDS-PAGE . This 20 kDa discrepancy likely results from post-translational modifications, particularly glycosylation patterns that are common in membrane proteins. When troubleshooting western blots showing unexpected band patterns:

• Verify antibody specificity through knockout/knockdown validation controls if available (publications have confirmed KD/KO applications) .

• Consider enzymatic deglycosylation treatments (PNGase F or Endo H) prior to SDS-PAGE to determine if glycosylation accounts for the size difference.

• Explore tissue-specific variations, as expression patterns may differ between brain tissues (where validation is robust) and other sample types.

• If investigating ATP6V0A1 in cancer contexts, note that malignant transformation may alter post-translational modification patterns, potentially resulting in subtle changes to the observed molecular weight .

This molecular weight consideration becomes particularly important when analyzing ATP6V0A1 in different disease contexts, where altered glycosylation might correlate with pathological states.

What methodological approaches can optimize ATP6V0A1 detection in immunoprecipitation experiments?

Immunoprecipitation (IP) of ATP6V0A1 requires careful optimization due to its membrane-embedded nature and association with other V-ATPase subunits. Based on validated protocols:

• Lysis buffer composition is critical - use buffer containing 1% NP-40 or Triton X-100, 150 mM NaCl, 50 mM Tris-HCl (pH 7.4), and protease inhibitors.

• For brain tissue samples (where IP has been confirmed successful):

  • Use 0.5-4.0 μg of ATP6V0A1 antibody per 1.0-3.0 mg of total protein lysate

  • Pre-clear lysate with protein A/G beads (1 hour at 4°C) before antibody addition

  • Extend incubation time to overnight at 4°C with gentle rotation to enhance capture of membrane-associated complexes

• When investigating ATP6V0A1 interactions with potential binding partners (like RABGEF1 in colorectal cancer cells), consider:

  • Crosslinking prior to lysis to stabilize transient interactions

  • Sequential IP approaches to capture multi-protein complexes

  • Modified wash conditions that maintain specific interactions while removing background

• For co-immunoprecipitation validations, reciprocal IP with antibodies against known V-ATPase complex components provides important confirmation of specificity.

These optimized IP approaches are particularly valuable when investigating novel interaction partners of ATP6V0A1, such as those involved in the recently identified cholesterol absorption pathway in colorectal cancer .

How should experimental design address ATP6V0A1's dual role in normal physiology and cancer pathology?

ATP6V0A1's involvement in both normal cellular physiology and cancer pathology necessitates careful experimental design. Recent findings demonstrate that tumor cell-intrinsic ATP6V0A1 suppresses anti-tumor immune responses, particularly in colorectal cancer contexts with high lipid metabolism . When designing experiments to investigate this dual functionality:

• Include appropriate control systems:

  • Compare ATP6V0A1 expression and function in normal colonic epithelium versus colorectal cancer samples

  • Utilize both immunocompetent and immunodeficient mouse models when assessing tumor growth (as demonstrated with MC38 and CT26 tumor models)

• Consider lipid metabolism context:

  • Stratify analyses based on lipid metabolism scores, as ATP6V0A1's correlation with immune activity appears highly dependent on this parameter

  • The inverse correlation between ATP6V0A1 and immune activity was observed only in CRC samples with high lipid metabolism

• Implement parallel in vitro and in vivo approaches:

  • ATP6V0A1 knockdown showed minimal effects on cell growth in vitro

  • The same modification dramatically inhibited tumor growth in immunocompetent but not immunodeficient mice

• Evaluate downstream pathways methodically:

  • Assess RABGEF1-dependent cholesterol absorption

  • Measure paracrine TGF-β1/SMAD3 signaling

  • Quantify memory CD8+ T cell activation status

These methodological considerations ensure robust experimental design that can distinguish between ATP6V0A1's normal physiological functions and its pathological roles in cancer contexts.

How can I optimize antibody selection when studying ATP6V0A1 in disease models?

When investigating ATP6V0A1 in disease contexts, antibody selection requires careful consideration of several factors:

• Epitope location considerations:

  • The ATP6V0A1 fusion protein immunogen Ag4191 used in the Proteintech antibody generation targets specific regions that may be differentially accessible in disease states

  • Structural alterations in disease models might affect epitope accessibility

• Cross-reactivity validation:

  • Confirm species reactivity is appropriate for your model system (both major commercial antibodies show reactivity with human, mouse, and rat samples)

  • Validate antibody performance in your specific disease model, as pathological changes can affect antibody performance

• Application-specific optimization:

  • For investigations of ATP6V0A1 in colorectal cancer immune evasion mechanisms, antibodies that successfully detect the protein in both western blot and immunohistochemistry applications are preferable

  • In complex tissue environments, higher antibody concentrations within the recommended range may be necessary

• Control strategies:

  • Include appropriate positive controls (brain tissue has confirmed high expression)

  • Implement knockdown/knockout validation controls when possible

  • Consider comparison between antibodies from different vendors or targeting different epitopes for critical experiments

These optimization approaches ensure reliable detection of ATP6V0A1 across diverse experimental contexts, particularly important when investigating novel functions like its role in cancer immunosuppression.

What are the methodological considerations for investigating ATP6V0A1's role in cholesterol metabolism and immune suppression?

Recent research has uncovered ATP6V0A1's critical involvement in colorectal cancer immune evasion through cholesterol metabolism . When designing experiments to further investigate this pathway:

• Cholesterol absorption assessment techniques:

  • Utilize fluorescently labeled cholesterol analogs to quantify uptake rates

  • Measure intracellular cholesterol accumulation through filipin staining

  • Assess membrane cholesterol through methyl-β-cyclodextrin extraction and quantification

• RABGEF1-ATP6V0A1 interaction analysis:

  • Implement proximity ligation assays to visualize protein interactions in situ

  • Utilize FRET-based approaches to assess dynamic interactions

  • Confirm interactions through co-immunoprecipitation with appropriate controls

• T cell functional assessment:

  • Design co-culture systems with ATP6V0A1-manipulated cancer cells and isolated memory CD8+ T cells

  • Quantify T cell activation through multiple parameters (cytokine production, cytotoxicity, activation markers)

  • Implement flow cytometry to assess memory CD8+ T cell functional status

• In vivo verification approaches:

  • Compare tumor growth kinetics in immunocompetent versus immunodeficient mouse models

  • Analyze tumor-infiltrating lymphocyte populations through flow cytometry and spatial transcriptomics

  • Assess responses to immune checkpoint inhibition in ATP6V0A1-high versus ATP6V0A1-low tumors

These methodological considerations enable comprehensive investigation of ATP6V0A1's newly identified role in establishing an immunosuppressive tumor microenvironment through cholesterol metabolism manipulation.

How do I interpret apparent discrepancies between ATP6V0A1 functions in different cellular contexts?

The emerging literature reveals context-dependent functions of ATP6V0A1 that may appear contradictory without proper interpretation. When analyzing apparently discrepant results:

• Consider cellular context specificity:

  • ATP6V0A1's primary role in normal physiology involves acidification of intracellular organelles

  • In colorectal cancer, it adopts additional functions in cholesterol metabolism and immune suppression

  • These divergent functions likely reflect repurposing of normal cellular machinery in the tumor context

• Evaluate interaction partners systematically:

  • ATP6V0A1 interacts with numerous proteins as part of the V-ATPase complex

  • Cancer-specific interactions (like with RABGEF1) may redirect its functionality

  • Map interaction networks in different contexts to explain divergent functions

• Assess regulatory mechanism differences:

  • Lipid metabolism status significantly impacts ATP6V0A1's relationship with immune activity

  • Cell-type specific regulatory mechanisms may explain functional divergence

• Consider evolutionary context:

  • ATP6V0A1 belongs to a family of proteins with roles in various V-ATPase complexes

  • Related proteins (ATP6V1A, ATP6V1C1, ATP6V1B2) have been implicated in neurological disorders

  • Functional divergence may reflect evolutionary adaptation of this protein family

This interpretive framework helps reconcile seemingly contradictory observations about ATP6V0A1 functions across different experimental systems and disease contexts.

What methodological approaches enable investigation of ATP6V0A1 as a therapeutic target in cancer?

The identification of ATP6V0A1 as a driver of immune suppression in colorectal cancer presents opportunities for therapeutic targeting . Researchers investigating this potential should consider:

• Target validation methodologies:

  • Implement conditional knockout systems in established tumor models

  • Utilize domain-specific mutations to identify critical functional regions

  • Develop selective inhibitors through structure-guided design approaches

• Therapeutic assessment parameters:

  • Monitor changes in tumor immune microenvironment following ATP6V0A1 inhibition

  • Assess combination potential with existing immunotherapies

  • Evaluate effects on tumor growth versus normal tissue homeostasis

• Biomarker development approaches:

  • Correlate ATP6V0A1 expression with response to immunotherapy in patient cohorts

  • Develop assays to measure ATP6V0A1-dependent cholesterol metabolism activity

  • Identify patient stratification parameters based on lipid metabolism status

• Delivery system considerations:

  • Explore tumor-targeted siRNA/shRNA delivery systems

  • Investigate small molecule inhibitors with favorable pharmacokinetic properties

  • Consider antibody-drug conjugates targeting cells with high ATP6V0A1 expression

These methodological approaches provide a framework for translating the basic science discovery of ATP6V0A1's role in cancer immune evasion into potential therapeutic strategies.

How can researchers effectively study interactions between ATP6V0A1 and other V-ATPase subunits?

ATP6V0A1 functions as part of the multi-subunit V-ATPase complex, necessitating specialized approaches to study subunit interactions:

• Structural biology approaches:

  • Cryo-EM analysis of V-ATPase complexes with and without ATP6V0A1

  • Crosslinking mass spectrometry to map intersubunit contact points

  • Hydrogen-deuterium exchange mass spectrometry to identify dynamic interaction surfaces

• Functional reconstitution strategies:

  • Develop in vitro reconstitution systems with purified components

  • Utilize liposome-based proton pumping assays to assess functional consequences of subunit interactions

  • Implement targeted mutations at predicted interaction interfaces

• Live-cell imaging methodologies:

  • Apply bimolecular fluorescence complementation to visualize protein-protein interactions

  • Utilize FRET-based sensors to monitor dynamic assembly/disassembly

  • Implement single-molecule tracking to assess complex formation kinetics

• Computational prediction validation:

  • Generate interaction models based on related ATPase structures

  • Validate through targeted mutagenesis of predicted interface residues

  • Correlate functional consequences with structural alterations

These approaches enable detailed characterization of how ATP6V0A1 interfaces with other V-ATPase subunits in different cellular contexts, potentially revealing how these interactions are modified in disease states.

What considerations are important when studying ATP6V0A1 in relation to other V-ATPase family members implicated in disease?

Recent research has implicated several V-ATPase components in human disease, including ATP6V1A in encephalopathy and ATP6V1C1/ATP6V1B2 in multisystem phenotypic disorders . When investigating potential connections:

• Functional redundancy assessment:

  • Determine whether ATP6V0A1 functions can be compensated by other family members

  • Implement simultaneous knockdown/knockout experiments to identify synthetic interactions

  • Assess tissue-specific expression patterns that might explain differential disease manifestations

• Mutation impact comparison:

  • Compare effects of disease-associated variants across family members

  • Assess whether mutations cluster in analogous functional domains

  • Evaluate differential effects on proton pumping versus potential moonlighting functions

• Pathway integration analysis:

  • Investigate whether ATP6V0A1's role in cholesterol metabolism is shared by other family members

  • Determine if immunosuppressive functions extend to mutations in ATP6V1A, ATP6V1C1, or ATP6V1B2

  • Map shared versus distinct interactomes across family members

• Model system coordination:

  • Develop comparable cellular and animal models for different V-ATPase component disorders

  • Implement consistent phenotyping approaches across models

  • Utilize rescue experiments to assess functional overlap

These considerations facilitate comparison across the emerging spectrum of V-ATPase-associated disorders, potentially revealing common mechanisms and therapeutic opportunities applicable across multiple conditions.