VPS16 Antibody

What is the primary function of VPS16 in cellular biology?

VPS16 plays a critical role in vesicle-mediated protein trafficking to lysosomal compartments, including endocytic membrane transport and autophagic pathways. It functions as a core component of the putative HOPS (homotypic fusion and protein sorting) and CORVET (class C core vacuole/endosome tethering) endosomal tethering complexes. These complexes are involved in the Rab5-to-Rab7 endosome conversion process, likely implicating MON1A/B proteins. VPS16 binds SNAREs and SNARE complexes to mediate tethering and docking events during membrane fusion .

The HOPS complex containing VPS16 is recruited to Rab7 on late endosomal membranes, where it regulates late endocytic, phagocytic, and autophagic traffic toward lysosomes. Meanwhile, the CORVET complex functions as a Rab5 effector to mediate early endosome fusion in specific endosome subpopulations .

Which applications are most reliable for VPS16 antibody-based detection?

Based on available commercial antibodies, VPS16 can be reliably detected using multiple applications:

• Western Blotting (WB): Provides quantitative analysis of VPS16 protein expression levels

• Immunohistochemistry-Paraffin (IHC-P): Enables visualization of VPS16 distribution in tissue sections

• Immunofluorescence (IF): Allows subcellular localization studies of VPS16

• ELISA: Offers quantitative measurement of VPS16 in solution

When selecting a VPS16 antibody, researchers should consider the specific epitope recognition. For example, some antibodies target amino acids 350-400 , while others target the C-terminal region (AA 754-839) . This distinction can be crucial depending on whether you need to detect specific isoforms or distinguish between protein complexes.

What species reactivity should be considered when selecting a VPS16 antibody?

Current commercially available VPS16 antibodies predominantly show reactivity with human and mouse samples . When planning cross-species studies, it's important to verify the antibody's reactivity profile. Some antibodies, like the goat polyclonal antibody described in search result , have been validated for both human and mouse samples. For other species, it may be necessary to perform preliminary validation studies based on sequence homology predictions.

Researchers should consider the degree of conservation in the epitope region across species. For example, if studying VPS16 in non-human primates or other mammals not explicitly listed in reactivity profiles, sequence alignment of the epitope region can help predict potential cross-reactivity.

How can VPS16 expression be effectively quantified in hepatocellular carcinoma research?

Recent research has established VPS16 as a potential biomarker for liver hepatocellular carcinoma (LIHC). For accurate quantification of VPS16 expression in LIHC research, a multi-platform approach is recommended:

• mRNA expression analysis: Using TCGA database analysis as demonstrated in recent research, VPS16 mRNA levels can be compared between tumor samples and normal tissues. This approach revealed significantly higher VPS16 expression in 374 LIHC tumor samples compared to 50 normal samples .

• Protein expression validation: Immunohistochemistry (IHC) staining provides visual confirmation of protein-level changes. The Human Protein Atlas (HPA) database has been successfully used to analyze VPS16 protein expression in LIHC cases. The staining index (SI) calculation method is as follows:

  SI = (intensity score) × (positive cell percentage score)

  Where:

  • Intensity is scored as 0, 1+, 2+, or 3+

  • Positive cell percentage is scored as 0 (0%), 1 (1-25%), 2 (25-50%), 3 (50-75%), or 4 (75-100%)

  • SI ≤ 3 indicates low expression, SI ≥ 4 indicates high expression

The table below illustrates the IHC scoring approach used in recent VPS16 research:

This quantification approach demonstrated that VPS16 protein expression was significantly higher in LIHC tissues compared to normal hepatocyte tissues (p < 0.01) .

What controls should be implemented when investigating VPS16's role in autophagy pathways?

When investigating VPS16's role in autophagy using antibody-based techniques, proper controls are essential:

• Positive and negative tissue controls: Include tissues known to express high levels of VPS16 (thyroid gland, spleen) and those with lower expression as controls .

• siRNA/shRNA knockdown controls: Include samples where VPS16 has been knocked down to validate antibody specificity and observe the functional impact on autophagy.

• Autophagy flux assessment: Since VPS16 is required for fusion of autophagosomes with lysosomes, autophagy flux should be monitored alongside VPS16 detection. This can be done by:

  • Measuring LC3-II levels with and without lysosomal inhibitors

  • Monitoring p62/SQSTM1 degradation

  • Assessing colocalization of autophagosomal and lysosomal markers

• VPS complex component controls: Examine other HOPS complex components (VPS11, VPS18, VPS33A, VPS39, VPS41) since VPS16 functions as part of this complex. Research has shown that VPS16 is required for recruitment of VPS33A to the HOPS complex .

• STX17 and UVRAG assessment: Since VPS16's function in autophagosome-lysosome fusion involves STX17 but not UVRAG, these proteins should be monitored as mechanistic controls .

How should discordance between mRNA and protein expression of VPS16 be interpreted?

When faced with discrepancies between VPS16 mRNA and protein expression levels, consider the following interpretive framework:

• Post-transcriptional regulation: VPS16 may be subject to microRNA regulation or RNA-binding protein influences that affect translation efficiency without changing mRNA levels.

• Protein stability factors: VPS16 protein stability might vary between tissue types or disease states due to differences in proteasomal degradation or autophagy-mediated turnover.

• Detection methodology limitations: Consider technical factors such as:

  • Antibody epitope accessibility in different sample preparations

  • mRNA splice variants that may not be detected by all primer sets

  • Protein extraction efficiency differences between protocols

• Biological context: The HPA, GTEx, and FANTOM5 datasets show that VPS16 is differentially expressed across tissues, with high expression in thyroid gland and spleen . Context-specific regulation may explain apparent discrepancies.

• Validation approach: To resolve discrepancies, implement:

  • Multiple antibodies targeting different epitopes of VPS16

  • Alternative detection methods (e.g., mass spectrometry)

  • In vitro translation assays to evaluate translational efficiency

What are the optimal experimental conditions for studying VPS16 interactions with other HOPS complex components?

To effectively study VPS16 interactions with other HOPS complex components:

• Co-immunoprecipitation (Co-IP) conditions:

  • Use mild lysis buffers (e.g., 1% NP-40 or 0.5% CHAPS) to preserve protein-protein interactions

  • Include protease inhibitors and phosphatase inhibitors to prevent degradation

  • Perform IP at 4°C to maintain complex integrity

  • Consider crosslinking approaches for transient or weak interactions

• Antibody selection strategies:

  • Use antibodies targeting different regions of VPS16 (N-terminal vs. C-terminal)

  • Verify that the epitope doesn't overlap with known interaction domains

  • Consider tagged protein approaches if antibody interference is suspected

• Complex component verification:

  • Reciprocal Co-IPs with different complex members (VPS11, VPS18, VPS33A, VPS39, VPS41)

  • Size exclusion chromatography to isolate intact complexes

  • Mass spectrometry to identify all associated proteins

• Functional validation techniques:

  • Mutational analysis of key residues in VPS16 interaction domains

  • Domain mapping using truncation constructs

  • Competitive binding assays with synthesized peptides

Research has established that VPS16 is required for recruitment of VPS33A to the HOPS complex , making this interaction a positive control for optimizing experimental conditions.

How does VPS16 expression correlate with clinical outcomes in liver cancer?

Recent bioinformatics analysis has revealed significant correlations between VPS16 expression and clinical outcomes in liver hepatocellular carcinoma (LIHC):

These findings collectively suggest that VPS16 may serve as a prognostic biomarker for LIHC, with higher expression levels indicating poorer outcomes. For researchers investigating VPS16 in LIHC, stratifying patient samples by expression level is recommended for more nuanced analysis of clinical correlations.

What molecular mechanisms connect VPS16 overexpression to hepatocellular carcinoma progression?

The molecular mechanisms linking VPS16 overexpression to hepatocellular carcinoma progression involve multiple pathways and cellular processes:

• Signaling pathway alterations: GSEA analysis has identified five key pathways enriched in VPS16 high-expression groups:

  • Complement and coagulation cascades

  • Drug metabolism (cytochrome P450)

  • Fatty acid metabolism

  • Primary bile acid biosynthesis

  • Retinol metabolism

• Cell cycle regulation: GO and KEGG enrichment analysis revealed that upregulated genes in the VPS16 high-expression group concentrate in:

  • Mitotic cell cycle pathways

  • DNA replication pathways
    This suggests VPS16 may promote cancer by affecting cell cycle progression and mitosis .

• Metabolic reprogramming: VPS16 overexpression appears to cause abnormal:

  • Fatty acid metabolism

  • Bile acid synthesis

  • Retinol metabolism
    These metabolic alterations may contribute to the cancer phenotype .

• Protein interaction network: GeneMANIA analysis identified five genes strongly correlated with VPS16:

  • VIPAS39

  • VPS33A

  • VPS18

  • VPS11

  • VPS41
    Of these, VPS11 and VPS18 are core components of VPS-C, which has been identified as a promising target for cancer therapy .

• Autophagy dysregulation: Given VPS16's role in autophagosome-lysosome fusion , its overexpression may disrupt normal autophagy, potentially contributing to tumor cell survival under stress conditions.

Which methodological approaches are optimal for investigating VPS16 as a therapeutic target?

To investigate VPS16 as a therapeutic target for LIHC or other cancers, researchers should consider these methodological approaches:

• Drug sensitivity screening: Analyze differential drug sensitivity between VPS16 high-expression and low-expression groups. Recent research identified 63 sensitive drugs for VPS16-overexpressing cells .

• Molecular docking analysis: Perform computational docking studies to identify compounds with strong binding potential to VPS16. Research has identified 19 drugs with strong molecular binding energy (< -7 kcal/mol) to VPS16, including:

  • Vinorelbine

  • Cyclopamine

  • HG-6-64-1

  • Midostaurin

  • OSU-03012

  • Parthenolide

  • GSK-650394

  • BMS-509744

  • Dasatinib

• Target validation approaches:

  • CRISPR/Cas9 knockout or knockdown studies to confirm VPS16 dependency

  • Rescue experiments to verify specificity

  • Patient-derived xenograft (PDX) models stratified by VPS16 expression

• Functional assays:

  • Cell proliferation and viability assays

  • Migration and invasion assays

  • Autophagy flux assessment

  • Endosomal trafficking visualization

• Combination therapy assessment: Test candidate compounds in combination with standard-of-care treatments for synergistic effects.

• Biomarker development: Develop IHC or other detection methods to identify patients most likely to benefit from VPS16-targeted therapies based on expression levels.

How can conflicting data on VPS16 expression across different cancer types be reconciled?

When facing conflicting data on VPS16 expression across cancer types, researchers should employ these reconciliation strategies:

• Standardized analysis methods: Ensure consistent methodology when comparing across cancer types:

  • Use the same normalization method for expression data

  • Apply identical cutoff criteria for "high" versus "low" expression

  • Utilize matched normal-tumor pair analysis when possible

• Context-specific interpretation: Consider that VPS16 may play different roles in different cellular contexts:

  • Pancancer analysis shows VPS16 is highly expressed in numerous tumor types (UCEC, STAD, READ, PRAD, PCPG, LUSC, LUAD, LIHC, etc.) but downregulated in KICH

  • Tissue-specific regulatory mechanisms may explain these differences

• Multi-omics integration: Combine multiple data types to build a more complete picture:

  • Integrate transcriptomics, proteomics, and functional data

  • Consider genomic alterations (mutations, copy number) alongside expression data

  • Analyze epigenetic regulation patterns

• Subcellular localization assessment: Determine if differences in expression are accompanied by changes in subcellular localization, which could indicate different functional roles.

• Temporal dynamics consideration: Evaluate whether expression differences represent different stages in disease progression rather than fundamental biological differences.

• Technical validation: Confirm findings using orthogonal techniques:

  • Validate RNA-seq findings with qRT-PCR

  • Confirm protein expression using multiple antibodies targeting different epitopes

  • Use multiple patient cohorts to verify expression patterns

What are the critical validation steps for a new VPS16 antibody before application in research?

Before implementing a new VPS16 antibody in research, thorough validation is essential:

• Specificity verification:

  • Western blot analysis with positive and negative control samples

  • siRNA/shRNA knockdown controls to confirm band specificity

  • Pre-adsorption tests with immunizing peptide

  • Testing in VPS16 knockout models (if available)

• Epitope characterization:

  • Confirm the exact epitope region (e.g., amino acids 350-400 or 754-839 )

  • Assess potential cross-reactivity with related proteins (other VPS family members)

  • Verify epitope conservation if using across species

• Application-specific validation:

  • For WB: Optimize protein extraction, loading amounts, blocking conditions, and antibody dilutions

  • For IHC-P: Test multiple fixation protocols, antigen retrieval methods, and detection systems

  • For IF: Evaluate different fixation/permeabilization methods and colocalization with known markers

• Reproducibility assessment:

  • Test multiple antibody lots if available

  • Compare results across different experimental conditions

  • Validate in multiple cell lines or tissue types

• Comparative analysis:

  • Benchmark against previously validated antibodies if available

  • Compare results with orthogonal detection methods (mass spectrometry)

How should VPS16 antibodies be optimized for detection of protein complexes versus free protein?

Detecting VPS16 within protein complexes versus its free form requires specific methodological considerations:

• Sample preparation optimization:

  • For complex detection: Use gentle lysis buffers (0.5-1% NP-40 or digitonin) that preserve protein-protein interactions

  • For free protein: More stringent conditions (SDS-containing buffers) may be appropriate

  • Consider native vs. denaturing conditions based on detection goals

• Gel filtration/size exclusion approaches:

  • Fractionate lysates prior to immunoblotting to separate complexes from free protein

  • Analyze fractions corresponding to expected molecular weights of HOPS (~500-700 kDa) and CORVET complexes versus monomeric VPS16 (~95 kDa)

• Epitope accessibility considerations:

  • Select antibodies whose epitopes remain accessible in the complex

  • VPS16 functions in HOPS and CORVET complexes, interacting with VPS33A and other components

  • Epitope mapping can help identify regions that remain exposed in complexes

• Cross-linking strategies:

  • Implement mild cross-linking to stabilize transient interactions

  • Optimize cross-linker concentration and reaction time to preserve physiologically relevant complexes

• Co-immunoprecipitation approaches:

  • Use antibodies against other complex components (VPS11, VPS18, VPS33A) to pull down intact complexes

  • Detect VPS16 within these complexes using a separate VPS16 antibody

• Proximity ligation assays (PLA):

  • Employ PLA to detect VPS16 in close proximity to other complex components in situ

  • This approach can visualize complexes within their native cellular context

What troubleshooting approaches are recommended when VPS16 antibodies show inconsistent results?

When experiencing inconsistent results with VPS16 antibodies, implement these troubleshooting strategies:

• Sample preparation variables:

  • Evaluate different lysis buffer compositions (detergent types and concentrations)

  • Compare fresh vs. frozen samples

  • Assess the impact of different protease inhibitor cocktails

  • Consider phosphatase inhibitors if post-translational modifications affect epitope recognition

• Technical optimization:

  • For WB: Test gradient gels vs. fixed percentage gels

  • For IHC: Compare different antigen retrieval methods (heat vs. enzymatic)

  • For IF: Evaluate different fixation protocols (paraformaldehyde vs. methanol)

• Antibody-specific factors:

  • Test different antibody lots

  • Optimize antibody concentration through titration experiments

  • Consider storage conditions and freeze-thaw cycles

  • Evaluate different blocking agents (BSA vs. milk protein)

• Sample-specific considerations:

  • VPS16 expression varies by tissue type, with high expression in thyroid gland and spleen

  • Consider tissue-specific optimization

  • Evaluate potential interfering substances in specific sample types

• Positive control implementation:

  • Include samples with known VPS16 overexpression (e.g., LIHC samples)

  • Use recombinant VPS16 protein as a positive control where appropriate

  • Consider transfection of tagged VPS16 as a definitive positive control

• Documentation and standardization:

  • Maintain detailed records of protocols and conditions

  • Standardize key variables across experiments

  • Consider developing standard operating procedures for your specific research context

What emerging methods show promise for studying VPS16 trafficking dynamics in live cells?

Several cutting-edge approaches are showing promise for real-time analysis of VPS16 trafficking dynamics:

• Live-cell imaging with fluorescent protein fusions:

  • CRISPR knock-in of fluorescent tags at endogenous VPS16 loci

  • Careful validation to ensure fusion proteins maintain native localization and function

  • Multi-color imaging with markers for endosomes, autophagosomes, and lysosomes

• Advanced microscopy techniques:

  • Super-resolution microscopy (STED, PALM, STORM) to visualize VPS16-containing complexes below the diffraction limit

  • Lattice light-sheet microscopy for extended imaging with reduced phototoxicity

  • FCS (Fluorescence Correlation Spectroscopy) to measure diffusion characteristics of VPS16-containing complexes

• Optogenetic approaches:

  • Light-inducible dimerization systems to manipulate VPS16 localization

  • Spatiotemporal control of VPS16 activity to dissect trafficking dynamics

  • Combination with live imaging for direct visualization of consequences

• Split-fluorescent protein systems:

  • Visualize VPS16 interactions with other HOPS/CORVET components in real-time

  • Detect formation of functional complexes at specific cellular locations

  • Quantify interaction dynamics under different conditions

• CRISPR-based tracking:

  • CRISPR-based RNA-guided DNA visualization for tracking genomic loci

  • Correlate gene expression dynamics with protein trafficking events

  • Integrated analysis of transcription and trafficking regulation

These approaches, combined with traditional antibody-based methods, will provide unprecedented insights into VPS16's dynamic roles in cellular trafficking pathways.

How might VPS16 antibodies be utilized in developing targeted cancer therapies?

VPS16 antibodies could contribute to cancer therapeutic development in several innovative ways:

• Companion diagnostic development:

  • IHC-based stratification of patients for clinical trials

  • Identification of cancers most likely to respond to VPS16-targeting therapies

  • Monitoring treatment response via changes in expression or localization

• Drug screening platforms:

  • High-content screening assays using VPS16 antibodies to identify compounds that modulate its expression or localization

  • Phenotypic screens to identify drugs that synergize with VPS16 inhibition

  • Patient-derived organoid screening with VPS16 as a readout

• Antibody-drug conjugates (ADCs):

  • While VPS16 is primarily intracellular, internalized antibody fragments could be developed

  • Targeting of overexpressed VPS16 in cancer cells

  • Delivery of cytotoxic payloads specifically to cancer cells

• Mechanistic validation:

  • Confirmation of drug mechanism of action via changes in VPS16 complex formation

  • Analysis of compensatory pathways activated upon VPS16 targeting

  • Investigation of resistance mechanisms through changes in VPS16 expression or localization

• Combination therapy rationale:

  • Identification of signaling pathways affected by VPS16 modulation

  • Rational design of combination approaches targeting complementary pathways

  • VPS16 expression as a marker for autophagy dependence could guide combination with autophagy inhibitors

Research has already identified several drugs with potential activity against VPS16-overexpressing cells, including vinorelbine, cyclopamine, and dasatinib , providing a foundation for further therapeutic development.