ATP6V1F Antibody

What is ATP6V1F and why is it important in scientific research?

ATP6V1F encodes a constituent of vacuolar ATPase (V-ATPase), a critical enzyme complex that mediates organelle acidification in eukaryotic cells. This acidification is essential for numerous intracellular processes including receptor-mediated endocytosis, protein sorting, zymogen activation, and synaptic vesicle proton gradient generation . The importance of ATP6V1F in research has grown significantly as its overexpression has been linked to poor prognosis in multiple cancer types, particularly hepatocellular carcinoma (HCC) . Understanding the role of ATP6V1F provides insights into fundamental cellular processes and potential therapeutic targets for various diseases.

What detection methods are validated for ATP6V1F antibodies?

Commercial polyclonal antibodies against ATP6V1F have been validated for multiple detection methods including:

• Immunohistochemistry (IHC)

• Immunocytochemistry/Immunofluorescence (ICC-IF)

• Western Blotting (WB)

For optimal results in Western blotting, researchers typically use primary antibody dilutions between 1:1000 (for detecting ATP6V1F) and 1:5000 (for control proteins like GAPDH), followed by appropriate HRP-labeled secondary antibodies . When performing these techniques, proper sample preparation is essential - for Western blotting, cell lysates should be prepared with protease inhibitors and phosphatase inhibitors in RIPA lysis buffer, centrifuged at 12,000 rpm for 20 minutes, and the proteins separated using 12% sodium dodecyl sulfate-polyacrylamide gels .

How do I optimize immunostaining protocols for ATP6V1F detection?

Optimization of immunostaining protocols for ATP6V1F detection requires careful consideration of several variables:

• Fixation method: For most applications, 4% paraformaldehyde works well, but specific tissues may require alternative fixatives

• Antigen retrieval: Heat-induced epitope retrieval in citrate buffer (pH 6.0) is commonly employed

• Blocking solution: 5% serum (matching the species of the secondary antibody) in PBS with 0.1% Triton X-100

• Antibody dilution: Begin with manufacturer's recommended dilution (typically 1:200-1:1000) and adjust as needed

• Incubation conditions: Overnight at 4°C for primary antibody, 1-2 hours at room temperature for secondary antibody

• Controls: Include positive controls (tissues known to express ATP6V1F) and negative controls (omitting primary antibody)

Each parameter should be systematically optimized for your specific sample type and experimental conditions to maximize signal-to-noise ratio.

How can ATP6V1F antibodies be employed to investigate cancer progression mechanisms?

ATP6V1F antibodies serve as valuable tools for investigating cancer progression through multiple experimental approaches:

• Expression profiling: Quantify ATP6V1F levels across tumor stages using IHC and Western blotting to correlate with clinical outcomes. Recent studies have shown that ATP6V1F is significantly overexpressed in multiple cancer types including bladder urothelial carcinoma, breast invasive carcinoma, cholangiocarcinoma, and hepatocellular carcinoma .

• Functional assays: Following ATP6V1F knockdown or overexpression, use the antibody to confirm altered protein levels before assessing effects on:

  • Cell migration (wound healing assays)

  • Invasion capacity (Transwell invasion assays)

  • Apoptosis resistance (flow cytometry with Annexin V/PI staining)

  • Proliferation rates (EdU incorporation assays)

• Mechanistic studies: Combine ATP6V1F antibodies with antibodies against other pathway components to elucidate:

  • Signaling cascades affected by ATP6V1F expression

  • Protein-protein interactions via co-immunoprecipitation

  • Subcellular localization changes during malignant transformation

Research has demonstrated that ATP6V1F promotes development of HCC by enhancing migration and invasion while inhibiting apoptosis of cancer cells , making these functional assays particularly relevant.

What are the critical considerations for using ATP6V1F antibodies in tumor microenvironment (TME) studies?

When studying ATP6V1F in the context of tumor microenvironment, researchers should consider:

• Multiplex immunofluorescence optimization:

  • Sequential staining protocols to avoid cross-reactivity

  • Appropriate fluorophore selection to minimize spectral overlap

  • Automated quantification of co-localization with immune cell markers

• Correlation with immune infiltrates:

  • ATP6V1F expression has been shown to significantly correlate with immune cell infiltration patterns

  • Paired analysis with immune checkpoint markers (CTLA4, TIGIT, PDCD1, SIGLEC15, CD274, HAVCR2, LAG3, and PDCD1LG2)

• Experimental design considerations:

  • Use of patient-derived xenografts or orthotopic models

  • Single-cell analysis to distinguish ATP6V1F expression in tumor cells versus stromal components

  • Integration with spatial transcriptomics to map ATP6V1F expression in relation to immune niches

Recent findings suggest that ATP6V1F expression levels may influence response to immune checkpoint inhibitors, making these considerations especially important for immunotherapy-related research .

How do tissue-specific processing variants of V-ATPase components affect antibody selection and experimental design?

The V-ATPase complex shows significant tissue-specific variations that researchers must consider when selecting antibodies and designing experiments:

• Tissue-specific protein isoforms:

  • Related V-ATPase components like Ac45 (ATP6AP1) display distinct forms across tissues: 40-kDa form in brain, 62-kDa intact protein in liver, and 50-kDa form in B-cells

  • These tissue-specific processing variants may affect antibody epitope accessibility

• Experimental design implications:

  • Antibody selection: Choose antibodies targeting epitopes present in all relevant isoforms

  • Control selection: Include tissue-matched controls to account for processing differences

  • Size verification: Always confirm expected molecular weight based on tissue source

  • Extraction protocols: Optimize lysis buffers for different tissues to ensure complete extraction of membrane-associated V-ATPase components

• Validation strategy:

  • Cross-validate findings using multiple antibodies targeting different epitopes

  • Complement protein detection with mRNA analysis to confirm expression patterns

  • Consider immunoprecipitation followed by mass spectrometry to identify tissue-specific interactors

This tissue-specific processing has functional implications, as evidenced by research showing that mutations in related V-ATPase components manifest different phenotypes across tissues .

How can researchers troubleshoot non-specific binding of ATP6V1F antibodies?

Non-specific binding is a common challenge when working with antibodies. For ATP6V1F antibodies specifically:

• Common sources of non-specificity:

  • Cross-reactivity with other V-ATPase subunits (ATP6V1A-G family)

  • Insufficient blocking

  • Secondary antibody cross-reactions

• Optimization solutions:

  • Blocking optimization: Test different blocking agents (BSA, normal serum, commercial blockers)

  • Antibody dilution series: Perform a titration to identify optimal concentration

  • Secondary antibody controls: Include controls omitting primary antibody

  • Pre-adsorption: Pre-incubate antibody with recombinant ATP6V1F protein to confirm specificity

  • Alternative antibody clones: Test antibodies targeting different epitopes of ATP6V1F

• Validation approaches:

  • Genetic validation using CRISPR knockout or knockdown models

  • Peptide competition assays

  • Parallel analysis with RNA expression data

  • Comparison of multiple antibodies targeting different regions of ATP6V1F

These approaches will help ensure the specificity of observed signals and minimize false positive results.

What are the recommended protocols for quantifying ATP6V1F expression in tissue microarrays versus cell lines?

Quantification protocols differ substantially between tissue microarrays (TMAs) and cell lines:

For Tissue Microarrays:

• Staining optimization:

  • Standardize antigen retrieval conditions

  • Optimize antibody concentration with titration series

  • Process all TMAs in a single batch to minimize technical variability

• Scoring methods:

  • H-score (combines intensity and percentage of positive cells)

  • Automated image analysis using software like QuPath or Aperio

  • Machine learning-based classification for heterogeneous samples

• Analysis considerations:

  • Account for tumor heterogeneity with multiple cores per case

  • Include on-slide positive and negative controls

  • Normalize scores against reference tissues

  • Employ at least two independent pathologists for scoring

For Cell Lines:

• Western blot quantification:

  • Normalize ATP6V1F signal to housekeeping proteins (GAPDH)

  • Use gradient loading to ensure linearity of signal

  • Employ digital imaging systems for densitometry

• Flow cytometry approach:

  • Optimize permeabilization protocols for intracellular staining

  • Use median fluorescence intensity for quantification

  • Include isotype controls and unstained cells

• Quantitative immunofluorescence:

  • Z-stack imaging to capture total cellular expression

  • Subcellular compartment analysis using organelle markers

  • Automated image analysis for high-throughput screening

Recent publications analyzing ATP6V1F in hepatocellular carcinoma utilized both approaches, with TMAs for patient sample analysis and Western blotting for cell line validation .

How does ATP6V1F expression correlate with cancer progression and prognosis?

ATP6V1F expression has emerged as a significant biomarker for cancer progression and prognosis, with substantial evidence supporting its clinical relevance:

These correlations highlight the importance of ATP6V1F as both a biomarker and potential therapeutic target, particularly in hepatocellular carcinoma research.

What methodologies can assess the functional relationship between ATP6V1F and immune cell infiltration?

Investigating the relationship between ATP6V1F and immune cell infiltration requires sophisticated methodological approaches:

• Computational analysis methods:

  • TIMER database analysis to evaluate correlations between ATP6V1F expression and immune cell infiltration

  • ESTIMATE algorithm to assess stromal and immune scores in relation to ATP6V1F levels

  • TIDE (Tumor Immune Dysfunction and Exclusion) algorithm to predict patient response to immune checkpoint inhibitors based on ATP6V1F expression

  • Spearman correlation analysis to identify associations between ATP6V1F and immune checkpoint genes

• Experimental validation approaches:

  • Multiplex immunohistochemistry/immunofluorescence:

    • Co-staining of ATP6V1F with immune cell markers (CD4, CD8, CD68, etc.)

    • Spatial relationship analysis between ATP6V1F-expressing cells and tumor-infiltrating lymphocytes

  • Single-cell RNA sequencing:

    • Cell type-specific ATP6V1F expression profiling

    • Trajectory analysis to identify developmental relationships

  • Functional assays:

    • Co-culture systems with ATP6V1F-overexpressing tumor cells and immune cells

    • Conditioned media experiments to assess secreted factors

    • Immune cell migration and activation assays in response to ATP6V1F modulation

• In vivo modeling:

  • Syngeneic mouse models with ATP6V1F knockdown/overexpression

  • Analysis of tumor microenvironment composition using flow cytometry

  • Response to immune checkpoint inhibitors in ATP6V1F-high versus ATP6V1F-low tumors

Recent findings indicate that ATP6V1F overexpression associates with infiltration of specific immune cell populations and impacts expression of several immune checkpoints, suggesting potential implications for immunotherapy response prediction .

How can researchers distinguish between ATP6V1F and other V-ATPase components in experimental designs?

Distinguishing ATP6V1F from other V-ATPase components requires careful experimental design:

• Antibody specificity verification:

  • Western blot analysis to confirm correct molecular weight (ATP6V1F: ~13 kDa)

  • Testing in knockout/knockdown models to verify specificity

  • Peptide competition assays to confirm epitope specificity

  • Cross-reactivity assessment against other V-ATPase subunits (ATP6V1A-G)

• Expression analysis approaches:

  • qRT-PCR primer design:

    • Target unique regions of ATP6V1F mRNA

    • Validate primers against other V-ATPase component sequences

    • Include melt curve analysis to confirm amplification specificity

  • RNA interference strategies:

    • Design siRNAs/shRNAs with minimal off-target effects

    • Validate knockdown specificity by measuring other V-ATPase components

    • Use rescue experiments with ATP6V1F constructs resistant to RNAi

• Functional discrimination:

  • Subcellular localization studies:

    • Each V-ATPase component may have unique distribution patterns

    • Use high-resolution microscopy to map precise localization

  • Protein-protein interaction mapping:

    • Immunoprecipitation followed by mass spectrometry

    • Proximity labeling techniques (BioID, APEX) to identify unique interactors

    • Yeast two-hybrid screening with ATP6V1F as bait

• Evolutionary conservation analysis:

  • ATP6V1F is highly conserved down to fruitfly, tetraodon and frog

  • Comparative analysis with other V-ATPase components can reveal unique functional domains

  • Homology modeling based on crystal structures helps identify component-specific regions

These approaches collectively enable researchers to specifically target and study ATP6V1F while minimizing confounding effects from other V-ATPase components.

What are the latest methodologies for studying ATP6V1F in relation to immunotherapy responsiveness?

Emerging methodologies for investigating ATP6V1F's role in immunotherapy response include:

• Predictive biomarker development:

  • Integrated multi-omics approaches:

    • Combining ATP6V1F protein expression with genomic alterations and transcriptomic signatures

    • Machine learning algorithms to identify ATP6V1F-associated response patterns

    • Developing ATP6V1F-based scoring systems for patient stratification

  • Liquid biopsy techniques:

    • Detecting ATP6V1F in circulating tumor cells or exosomes

    • Correlating ATP6V1F levels with response to immune checkpoint inhibitors

    • Longitudinal monitoring during treatment

• Mechanistic investigation tools:

  • CRISPR-based screens:

    • Genome-wide CRISPR screens in ATP6V1F-high versus ATP6V1F-low backgrounds

    • CRISPRa/CRISPRi modulation of ATP6V1F to identify synthetic lethal interactions

  • Organoid and patient-derived xenograft models:

    • Testing immunotherapy efficacy in ATP6V1F-modulated organoids

    • Humanized mouse models with patient-derived tumors

• Functional immunology approaches:

  • Immune cell phenotyping:

    • Mass cytometry (CyTOF) to characterize immune populations in relation to ATP6V1F

    • Assessment of T-cell exhaustion markers in ATP6V1F-high tumors

  • Spatial analysis technologies:

    • Multiplexed ion beam imaging (MIBI) for high-parameter spatial analysis

    • Digital spatial profiling to map ATP6V1F expression relative to immune contexture

Recent studies have employed the TIDE algorithm to demonstrate that patient response to immune checkpoint inhibitor treatment varies based on ATP6V1F expression levels, suggesting its potential utility in immunotherapy patient selection .

How can researchers integrate ATP6V1F antibody-based detection with transcriptomic and proteomic approaches?

Integrating ATP6V1F antibody-based detection with multi-omics approaches requires sophisticated experimental design:

• Integrated single-cell analysis:

  • CITE-seq (Cellular Indexing of Transcriptomes and Epitopes by Sequencing):

    • Simultaneous measurement of ATP6V1F protein (using antibodies) and transcriptome

    • Correlation of protein levels with mRNA expression at single-cell resolution

  • Single-cell proteogenomics:

    • Linking ATP6V1F protein levels to genomic/transcriptomic features

    • Identifying regulatory mechanisms controlling ATP6V1F expression

• Spatial multi-omics approaches:

  • Spatial transcriptomics with antibody validation:

    • Visium or similar platforms to map ATP6V1F mRNA expression

    • Validation with immunohistochemistry on serial sections

    • Co-registration of protein and transcript maps

  • DSP (Digital Spatial Profiling):

    • Simultaneous quantification of ATP6V1F protein and pathway-related proteins

    • Spatial mapping of ATP6V1F in relation to tissue architecture

• Proteomics integration:

  • Immunoprecipitation-mass spectrometry:

    • Using ATP6V1F antibodies to pull down protein complexes

    • Identifying post-translational modifications and binding partners

    • Quantitative analysis of complex stoichiometry

  • Parallel reaction monitoring (PRM):

    • Targeted proteomics approach for absolute quantification

    • Correlation with antibody-based quantification methods

• Functional validation approaches:

  • Phospho-proteomics following ATP6V1F modulation:

    • Mapping signaling pathway alterations

    • Identifying therapeutic vulnerabilities

  • Metabolomic profiling:

    • Assessing impact of ATP6V1F on cellular metabolism

    • Correlating with organelle acidification functions

Such integrated approaches have been applied in recent hepatocellular carcinoma studies, revealing that ATP6V1F correlates with multiple tumor-associated signaling pathways and immune checkpoint expression .

What are the gold standard approaches for validating ATP6V1F antibody specificity?

Validating ATP6V1F antibody specificity requires a multi-faceted approach:

• Genetic validation:

  • CRISPR/Cas9 knockout: Complete elimination of target protein should abolish antibody signal

  • siRNA/shRNA knockdown: Reduction in antibody signal proportional to knockdown efficiency

  • Overexpression validation: Increased signal in cells transfected with ATP6V1F expression constructs

  • Rescue experiments: Reintroduction of ATP6V1F in knockout cells should restore antibody signal

• Biochemical validation:

  • Western blot analysis:

    • Confirmation of single band at expected molecular weight (~13 kDa for ATP6V1F)

    • Absence of non-specific bands in various tissue types

  • Peptide competition assays:

    • Pre-incubation of antibody with immunizing peptide should eliminate specific signal

    • Titration series to determine blocking efficiency

  • Orthogonal antibody comparison:

    • Testing multiple antibodies targeting different epitopes

    • Concordance in staining patterns across techniques

• Advanced validation techniques:

  • Mass spectrometry verification:

    • Immunoprecipitation followed by MS identification

    • Confirmation of peptide sequences unique to ATP6V1F

  • Epitope mapping:

    • Determining precise binding region using peptide arrays

    • Assessing potential cross-reactivity with homologous proteins

• Application-specific validation:

  • IHC validation:

    • Testing in known positive and negative tissues

    • Correlation with mRNA expression (RNA-scope or in situ hybridization)

  • IF validation:

    • Co-localization with organelle markers consistent with expected distribution

    • Z-stack analysis to confirm subcellular localization

These rigorous validation approaches ensure reliable and reproducible results when using ATP6V1F antibodies for research applications.

How should researchers interpret contradictory results between ATP6V1F protein and mRNA expression data?

Discrepancies between ATP6V1F protein and mRNA levels are not uncommon and require careful consideration:

• Common causes of protein-mRNA discordance:

  • Post-transcriptional regulation:

    • microRNA-mediated repression

    • RNA-binding protein effects on translation efficiency

    • mRNA stability differences

  • Post-translational mechanisms:

    • Protein half-life variations

    • Ubiquitin-proteasome degradation

    • Processing of immature proteins

  • Technical factors:

    • Antibody specificity limitations

    • RNA isolation efficiency differences

    • Normalization method variations

• Systematic troubleshooting approach:

  • Verification with multiple methods:

    • Alternative antibody clones for protein detection

    • Different primer sets for mRNA quantification

    • Orthogonal techniques (e.g., mass spectrometry, RNA-seq)

  • Time-course experiments:

    • Investigating temporal relationships between mRNA and protein

    • Pulse-chase studies to determine protein stability

  • Subcellular fractionation:

    • Determining if protein distribution rather than total levels explains discrepancy

    • Checking for membrane-bound versus soluble fractions

• Biological interpretation strategies:

  • Tissue-specific processing consideration:

    • Similar to related V-ATPase components, ATP6V1F may undergo differential processing

    • Checking for tissue-specific isoforms or post-translational modifications

  • Disease context analysis:

    • Comparing normal versus pathological conditions

    • Evaluating cellular stress responses affecting translation

• Advanced reconciliation methods:

  • Ribosome profiling:

    • Directly measuring translation efficiency

    • Identifying regulatory elements affecting protein synthesis

  • Integrated multi-omics analysis:

    • Statistical modeling of relationships between transcriptome and proteome

    • Identification of factors explaining discordance

Research on related V-ATPase components has revealed significant tissue-specific processing variants , suggesting ATP6V1F may similarly display complex regulatory patterns requiring integrated analytical approaches.