Recombinant Human Vacuolar protein sorting-associated protein 13B (VPS13B), partial, refers to a recombinant form of the VPS13B protein that is not full-length. The VPS13B protein is a giant protein associated with the Golgi apparatus, playing a crucial role in post-Golgi apparatus sorting and trafficking . It is involved in various cellular processes, including protein modification, organization, and distribution . The full-length VPS13B protein is composed of approximately 4,022 amino acids and is located on chromosome 8 at position 8q22.2 .
VPS13B is localized at the interface between proximal and distal Golgi subcompartments, suggesting a role in maintaining Golgi structure and facilitating lipid transport between these compartments . It interacts with RAB6, a GTPase involved in Golgi trafficking, indicating its involvement in vesicular transport processes . The protein's localization and interactions are critical for Golgi complex reformation and maintenance .
Mutations in the VPS13B gene have been linked to several diseases, including Cohen syndrome and autism . Cohen syndrome is characterized by intellectual disability, microcephaly, and other systemic abnormalities, and mutations in VPS13B can lead to a nonfunctional protein, disrupting normal cellular processes . Additionally, there is evidence suggesting a link between VPS13B mutations and osteoporosis, as increased copy number variants of VPS13B have been associated with lower bone mineral density .
Recent studies have highlighted the importance of VPS13B in Golgi function and its potential role in neurodevelopmental disorders. For instance, Vps13b knockout mice exhibit neuroanatomical defects and male sterility due to impaired acrosomal membrane formation, which is a Golgi-derived structure essential for fertilization . The protein's interaction with other Golgi proteins, such as FAM177A1, further underscores its significance in cellular processes .
While VPS13B is involved in Golgi-related processes, other members of the VPS13 family, such as VPS13C, have distinct roles. VPS13C is associated with lipid droplets in brown adipocytes, where it inhibits lipolysis and regulates lipid droplet dynamics . This highlights the diverse functional roles within the VPS13 protein family.
Wikipedia: VPS13B - Wikipedia
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PMC: Vacuolar protein sorting 13C is a novel lipid droplet protein that inhibits lipolysis in brown adipocytes
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VPS13B (also known as COH1) is a 4022-amino-acid transmembrane protein located on chromosome 8 (8q22.2). It functions as a Golgi-associated peripheral membrane protein involved in Golgi integrity, homeostasis, and membrane transport . The protein contains ten transmembrane domains, a potential vacuolar targeting motif, an endoplasmic reticulum retention signal on the C-terminus, and two peroxisomal matrix protein targeting signal 2 (PTS2) consensus sequences on both N- and C-termini . VPS13B belongs to the VPS13 protein family, which is highly conserved in eukaryotic cells and plays critical roles in intracellular protein transport and vesicle-mediated sorting . The protein is widely expressed in brain, blood, small intestine, muscles, placenta, heart, retina, kidney, and lung tissues .
Methodological approach:
Clone the VPS13B gene into a mammalian expression vector (e.g., pcDNA3.1_VPS13B)
Verify the sequence integrity through Sanger sequencing
Transfect standard cell cultures (e.g., HeLa cells) using appropriate transfection reagents
Optimize transfection conditions (DNA concentration, cell density, incubation time)
Confirm expression through western blotting or immunofluorescence microscopy
The expression of complete VPS13B is challenging due to its large size (4022 amino acids). Therefore, working with partial constructs containing specific functional domains may be more practical for certain experiments. When using partial constructs, ensure they contain the domains of interest, such as transmembrane regions or Golgi-targeting sequences .
Methodological approach:
Immunofluorescence microscopy:
Western blotting:
Prepare cell lysates in appropriate lysis buffer
Separate proteins on SDS-PAGE (note: use low percentage gels for full-length VPS13B)
Transfer to PVDF membrane
Probe with anti-VPS13B antibody
Visualize using chemiluminescence or fluorescent detection systems
Quantification methods:
Methodological approach:
Generate VPS13B constructs containing the missense variants of interest using site-directed mutagenesis
Express wild-type and mutant VPS13B proteins in appropriate cell lines
Assess subcellular localization through immunofluorescence microscopy:
Define two regions of interest (ROIs) for each cell:
a. Total cell ROI (outlines the cell border and measures total VPS13B immunofluorescence)
b. Golgi ROI (outlines the GM130-positive Golgi structure and measures Golgi-associated VPS13B immunofluorescence)
Calculate the percentage of Golgi-associated VPS13B fluorescence compared to total VPS13B cell fluorescence
Compare Golgi enrichment between wild-type and mutant proteins
Include appropriate controls:
Perform statistical analysis to determine significance of differences in localization patterns
This approach has been validated for characterizing VPS13B missense variants and can provide functional evidence for pathogenicity classification according to ACMG guidelines .
Methodological solutions:
Size limitations:
The full-length VPS13B cDNA (approximately 12 kb) is challenging to manipulate
Solution: Work with partial constructs containing specific functional domains
Validate that partial constructs retain relevant biological activities
Expression efficiency:
Large proteins often express poorly in heterologous systems
Solutions:
a. Optimize codon usage for the host system
b. Use strong promoters (e.g., CMV for mammalian cells)
c. Consider inducible expression systems to minimize toxicity
d. Test different cell lines for optimal expression
Protein stability:
Large proteins may be subject to increased degradation
Solutions:
a. Include proteasome inhibitors during protein extraction
b. Optimize extraction buffers with appropriate protease inhibitors
c. Perform experiments at shorter time points after transfection
Functional analysis:
Develop specific assays to measure VPS13B activity:
a. Golgi morphology analysis
b. Vesicle trafficking assays
c. Protein-protein interaction studies (co-immunoprecipitation, proximity labeling)
Methodological approach:
Express wild-type or mutant VPS13B in cell culture systems
Analyze Golgi morphology:
Immunostain for Golgi markers (GM130, TGN46)
Quantify Golgi area, fragmentation, and distribution
Use high-resolution microscopy techniques (confocal, super-resolution)
Assess Golgi function:
Protein glycosylation assays
Vesicle trafficking analyses
Golgi stress response measurements
Quantitative analysis:
Measure the area covered by the Golgi complex
Assess Golgi fragmentation index
Evaluate cisternal stacking through electron microscopy
Recovery experiments:
Rescue experiments by co-expressing wild-type VPS13B in cells with mutant variants
Assess whether Golgi abnormalities can be reversed
These approaches allow for comprehensive characterization of how VPS13B mutations impact Golgi structure and function, providing insights into pathogenic mechanisms .
Methodological comparison:
| Model System | Advantages | Limitations | Best Applications |
|---|---|---|---|
| HeLa cells | Easy transfection, well-characterized Golgi | Not neuronal | Localization studies, basic functional assays |
| Neuronal cell lines (SH-SY5Y, Neuro2A) | Relevant for neurological disorders | Lower transfection efficiency | Neuron-specific VPS13B functions |
| Primary neurons | Physiologically relevant | Difficult transfection, limited lifespan | Validation of findings from cell lines |
| Patient-derived fibroblasts | Contain natural mutations | Variable expression levels | Disease-relevant phenotyping |
| iPSC-derived models | Can generate relevant cell types | Complex differentiation protocols | Disease modeling, drug screening |
| Knockout/knockin mouse models | In vivo relevance | Time-consuming and expensive | Systemic effects of VPS13B mutations |
For initial characterization of recombinant VPS13B variants, HeLa cells provide an accessible and well-characterized system, particularly for subcellular localization studies . For more disease-relevant contexts, neuronal models or patient-derived cells may be more appropriate, depending on the specific research questions.
Methodological approach:
Domain identification and construct design:
Analyze VPS13B sequence using bioinformatics tools to identify stable domains
Design expression constructs with appropriate boundaries to enhance solubility
Include affinity tags (e.g., His, GST, MBP) to facilitate purification
Expression optimization:
Test multiple expression systems:
a. Bacterial systems (E. coli): Fast but may not provide proper folding
b. Insect cells (Sf9, High Five): Better for complex eukaryotic proteins
c. Mammalian cells (HEK293, CHO): Best for post-translational modifications
Optimize temperature, induction conditions, and expression time
Solubility enhancement:
Consider fusion partners that enhance solubility (MBP, SUMO, thioredoxin)
Test different lysis buffers with varying salt concentrations, pH, and detergents
For membrane-associated domains, include appropriate detergents (DDM, CHAPS)
Purification strategy:
Multi-step purification combining:
a. Affinity chromatography (based on chosen tag)
b. Ion exchange chromatography
c. Size exclusion chromatography
Assess protein purity by SDS-PAGE and protein quality by dynamic light scattering
Structural validation:
Circular dichroism to confirm secondary structure
Limited proteolysis to identify stable domains
Thermal shift assays to assess stability
Initial characterization by negative-stain electron microscopy
Methodological approach:
Quantitative analysis of subcellular localization:
Define clear metrics for Golgi enrichment
Calculate the percentage of Golgi-associated VPS13B fluorescence compared to total VPS13B cell fluorescence
Use appropriate statistical tests (t-test, ANOVA) to compare variants
Data normalization and controls:
Include positive controls (known pathogenic variants) and negative controls (benign variants)
Normalize data relative to wild-type VPS13B to account for experiment-to-experiment variation
Assess multiple parameters to create a comprehensive functional profile
Integration with pathogenicity prediction:
Combine functional data with in silico prediction tools
Apply ACMG classification guidelines to interpret variants
Correlate functional deficits with clinical phenotypes when possible
Presentation of results:
Methodological considerations:
Expression level variations:
Problem: Different expression levels can affect localization patterns
Solution: Analyze cells with comparable expression levels; normalize data appropriately
Cell-to-cell variability:
Problem: Heterogeneous response in cell populations
Solution: Analyze sufficient cell numbers (>30 cells per condition); present distribution of results
Partial loss of function:
Problem: Subtle functional defects may be missed
Solution: Use quantitative methods with appropriate statistical power; compare to variants with known effects
Overexpression artifacts:
Problem: Overexpression can lead to mislocalization unrelated to variant effects
Solution: Include wild-type controls at similar expression levels; consider inducible systems
Context dependence:
Problem: Effects may vary in different cell types
Solution: Validate key findings in multiple cell types, including disease-relevant cells when possible
Interpretation guidelines:
Methodological applications:
Structure-function analyses:
Express recombinant VPS13B constructs containing patient-specific mutations
Assess effects on protein localization, stability, and function
Compare cellular phenotypes with clinical presentations
Disease modeling:
Introduce VPS13B mutations in cellular models using CRISPR/Cas9
Analyze effects on Golgi structure, protein trafficking, and cellular homeostasis
Develop phenotypic assays relevant to Cohen Syndrome
Protein interaction studies:
Identify VPS13B binding partners using techniques such as:
a. Co-immunoprecipitation with recombinant VPS13B
b. Proximity labeling (BioID, APEX)
c. Yeast two-hybrid screening with VPS13B domains
Determine how disease-causing mutations affect these interactions
Therapeutic development:
Use recombinant VPS13B systems to screen for compounds that:
a. Stabilize mutant VPS13B proteins
b. Enhance their correct localization
c. Bypass the functional defects caused by mutations
Biomarker identification:
Assess downstream effects of VPS13B dysfunction
Identify potential biomarkers for disease progression and treatment response
Methodological innovations:
Live-cell imaging approaches:
Express VPS13B fused to fluorescent proteins (e.g., GFP, mCherry)
Track protein dynamics and localization in real-time
Utilize FRAP (Fluorescence Recovery After Photobleaching) to assess protein mobility
Proximity labeling techniques:
Fuse VPS13B to promiscuous biotin ligases (BioID, TurboID) or peroxidases (APEX)
Identify proximal proteins through biotinylation followed by streptavidin pulldown and mass spectrometry
Map the spatial organization of VPS13B in specific cellular compartments
Structural biology approaches:
Cryo-electron microscopy of VPS13B protein domains
X-ray crystallography of stable VPS13B fragments
Molecular dynamics simulations to understand conformational changes
Protein-lipid interaction assays:
Liposome binding assays to assess interaction with membrane lipids
Identify lipid binding domains within VPS13B
Determine how mutations affect lipid interactions
Systems biology integration:
Transcriptomics and proteomics to identify pathways affected by VPS13B dysfunction
Network analysis to place VPS13B in cellular signaling contexts
Multi-omics approaches to understand global effects of VPS13B mutations