CHMP1B Human

What is CHMP1B and what is its role in the ESCRT-III complex?

CHMP1B is a member of the Charged Multivesicular Body Protein (CHMP) family that constitutes a core component of the Endosomal Sorting Complex Required for Transport III (ESCRT-III). Unlike in yeast, the human ESCRT-III consists of 12 CHMP proteins, including CHMP1A, CHMP1B, CHMP2A, CHMP2B, CHMP3 (VPS24), CHMP4A, CHMP4B, CHMP4C, CHMP5, CHMP6, CHMP7, and IST1 (CHMP8) .

CHMP1B contributes to fundamental cellular processes including membrane remodeling, multivesicular body (MVB) assembly, and cellular protein catabolic processes. The protein functions within a network of ESCRT-III components to facilitate membrane deformation and scission during processes such as cytokinesis, viral budding, and autophagy .

Methodologically, researchers investigating CHMP1B's function typically employ techniques including:

• Fluorescence microscopy with tagged CHMP1B to observe localization

• Co-immunoprecipitation to identify interaction partners

• GUV (Giant Unilamellar Vesicle) and NT (Nanotube) experiments to study membrane remodeling capabilities

• Lipid-binding assays to characterize membrane interaction properties

How does differential expression of CHMP1B compare between normal and tumor tissues?

CHMP1B shows altered expression patterns in tumor tissues compared to normal counterparts. In liver hepatocellular carcinoma (LIHC), research has demonstrated significant changes in CHMP1B expression. Analysis of 424 samples from the TCGA-LIHC dataset (comprising 50 normal tissue and 374 HC tissue samples) revealed that CHMP1B, along with other CHMP family members, was significantly overexpressed in tumor tissue compared to normal tissue (P<0.05) .

This finding was further validated through paired sample analysis of 50 normal tissue samples and their matched 50 HC tissue counterparts, which confirmed the elevated expression of CHMP1B in tumor tissue (P<0.05) . Interestingly, unlike some other CHMP family members (CHMP1A, CHMP2B, CHMP3, CHMP4B, CHMP5, and CHMP7), CHMP1B expression did not show significant correlation with clinicopathological staging (P>0.05) .

Immunohistochemical validation from the Human Protein Atlas database has corroborated these findings at the protein level, demonstrating increased CHMP1B expression in tumor tissue consistent with differential gene expression analysis .

What methodological approaches are recommended for analyzing CHMP1B mutations in cancer?

When analyzing CHMP1B mutations in cancer contexts, researchers should implement a multi-faceted methodological approach:

• Comprehensive Mutation Screening:

  • Utilize next-generation sequencing data from databases like TCGA (The Cancer Genome Atlas)

  • Analyze both TCGA PanCancer Atlas and TCGA Firehose Legacy datasets for comprehensive coverage

  • Focus on identifying amplifications, which represent the highest frequency mutation type among CHMP family members

• Copy Number Variation (CNV) Analysis:

  • Perform both heterozygous and homozygous CNV analysis

  • Present findings using pie charts to visualize distribution of CNV patterns

  • Compare CNV findings with expression data to identify correlations

• Survival Impact Assessment:

  • Stratify patient cohorts based on mutation status

  • Conduct Kaplan-Meier survival analysis comparing mutated vs. non-mutated groups

  • Employ log-rank tests to determine statistical significance of survival differences

• Methylation Analysis:

  • Examine promoter methylation levels using R software

  • Compare methylation patterns between normal and tumor tissues

  • Correlate methylation status with expression levels to identify potential regulatory mechanisms

While CHMP1B-specific mutation data was not extensively detailed in the provided research, the study methodology demonstrated that CHMP4C had the highest mutation frequency (10%) followed by CHMP7 (7%) among the CHMP family members in LIHC samples .

How can researchers effectively measure CHMP1B interaction with membrane structures?

To effectively measure CHMP1B interactions with membrane structures, researchers should consider implementing the following methodological approaches:

• GUV (Giant Unilamellar Vesicle) Experiments:

  • Prepare lipid-covered silica beads hydrated in trehalose solution (1M)

  • Generate freestanding GUVs through gentle manual stirring

  • Add fluorescently labeled CHMP1B protein at specified concentrations

  • Observe membrane interactions using fluorescence microscopy

  • Quantify protein recruitment to membrane surfaces

• Membrane Nanotube (NT) Experiments:

  • Produce glass micropipettes using a P-1000 micropipette puller

  • Create lipid nanotubes through direct physical contact between micropipettes and GUVs

  • Control micropipette position using a micropositioning system (e.g., MP-285)

  • Add fluorescently labeled CHMP1B before tube pulling

  • Image using spinning disc microscopy with high-resolution objectives (100× 1.49–numerical aperture)

• Quantification of Relative Abundance Between Curved and Flat Membranes:

  • Compare CHMP1B recruitment to different membrane geometries

  • Measure fluorescence intensity across flat vesicle surfaces versus curved nanotubes

  • Calculate enrichment ratios to determine curvature preference

• Membrane Structural Feature Analysis:

  • Document CHMP1B-induced membrane deformations

  • Quantify structural changes using image analysis software

  • Correlate protein concentration with membrane remodeling events

This multi-technique approach enables comprehensive characterization of how CHMP1B interacts with and potentially remodels membrane structures in various experimental conditions.

What are the molecular mechanisms underlying CHMP1B's role in cancer progression?

The molecular mechanisms through which CHMP1B influences cancer progression appear to involve multiple cellular pathways, though its specific contributions differ from some other CHMP family members:

These findings suggest CHMP1B operates through complex mechanisms in cancer, with potential context-dependent roles in different malignancies. Further research employing CHMP1B knockdown/overexpression models would help elucidate its specific contributions to oncogenic processes.

How does CHMP1B expression correlate with immune cell infiltration in tumor microenvironments?

Analysis of CHMP family proteins, including CHMP1B, reveals significant correlations with immune cell infiltration in tumor microenvironments:

• Correlation with Multiple Immune Cell Types:
  CHMP1B expression shows positive correlation with infiltration of various immune cells in tumor tissue, including:

  • B cells

  • CD4+ T cells

  • CD8+ T cells

  • Neutrophils

  • Macrophages

  • Dendritic cells (P<0.05 for all correlations)

• Tumor Purity Considerations:
  Importantly, CHMP1B expression showed insignificant correlation with tumor purity (P>0.05), suggesting the observed immune cell correlations are not simply artifacts of tumor composition variation .

• Immunosubtype Analysis:
  The distribution of CHMP expression varies across cancer immunosubtypes classified based on:

  • Macrophage or lymphocyte characteristics

  • Th1:Th2 cell ratios

  • Tumor heterogeneity

  • Aneuploidy

  • Neoantigen load

  • Cell proliferation rates

  • Immunoregulatory gene expression

• Methodological Approach:
  Researchers investigating these correlations utilized:

  • RNA-Seq expression profiling data

  • Computational deconvolution of immune cell populations

  • Statistical correlation analyses (Spearman correlation)

  • Visualization of relationships through heatmaps and scatter plots

These findings suggest that CHMP1B may influence, or be influenced by, immune cell recruitment and function within the tumor microenvironment, potentially contributing to cancer immunobiology through mechanisms that remain to be fully elucidated.

What are the current challenges in establishing structure-function relationships in CHMP1B research?

Establishing structure-function relationships for CHMP1B presents several methodological and conceptual challenges:

• Polymerization Dynamics Characterization:

  • Accurately measuring CHMP1B polymerization rates on membranes requires specialized techniques

  • Determining maximum surface coverage parameters demands quantitative image analysis

  • Correlating polymerization kinetics with functional outcomes remains technically challenging

• Curvature Sensitivity Analysis:

  • Distinguishing CHMP1B's intrinsic preference for curved versus flat membranes requires controlled experimental systems

  • Quantifying relative abundances between different membrane geometries necessitates careful normalization

  • Separating direct curvature sensing from cooperative assembly effects presents analytical difficulties

• Structural Heterogeneity:

  • CHMP proteins, including CHMP1B, can adopt multiple structural conformations

  • Capturing transitional states during membrane remodeling requires time-resolved techniques

  • Relating observed structures to functional outcomes remains challenging

• Interaction Network Complexity:

  • CHMP1B functions within a complex network of 12 human CHMP proteins

  • Delineating specific contributions of CHMP1B versus other family members requires sophisticated genetic approaches

  • Understanding compensatory mechanisms when CHMP1B is altered necessitates comprehensive analysis

• Technological Limitations:

  • Achieving sufficient temporal and spatial resolution to observe CHMP1B-mediated membrane events requires advanced microscopy

  • Current methods like spinning disc microscopy with EVOLVE EM-CCD cameras provide valuable data but may miss transient events

  • Correlating in vitro observations with in vivo function requires complementary methodological approaches

Addressing these challenges requires integrative approaches combining structural biology, advanced microscopy, biochemical assays, and computational modeling to fully elucidate CHMP1B's structure-function relationships.

How do experimental approaches for studying CHMP1B differ between cancer research and basic cell biology investigations?

The experimental approaches for studying CHMP1B differ significantly between cancer research and basic cell biology investigations, reflecting their distinct objectives:

Basic Cell Biology Approaches:

• Membrane Interaction Studies:

  • Giant Unilamellar Vesicle (GUV) preparation and analysis

  • Nanotube (NT) formation using micropipette techniques

  • Quantification of protein recruitment to membranes of different curvatures

• High-Resolution Imaging:

  • Spinning disc microscopy with high-numerical-aperture objectives

  • Fluorescently labeled protein tracking

  • Microposition-controlled membrane manipulation

• Evolutionary Conservation Analysis:

  • Comparison of CHMP1B structure and function across species

  • Particular focus on archaea to eukaryote evolutionary conservation

  • Identification of fundamental mechanistic principles

• Reconstitution Experiments:

  • In vitro reconstitution of ESCRT-III assemblies

  • Analysis of polymerization dynamics

  • Quantification of membrane remodeling capabilities

The methodological differences highlight the complementary nature of cancer and basic biology research: cancer studies focus on clinical relevance and large-scale analysis, while basic cell biology investigations emphasize mechanistic understanding and fundamental processes. Integration of both approaches provides the most comprehensive understanding of CHMP1B function.

What emerging technologies are advancing our understanding of CHMP1B function in membrane remodeling?

Several cutting-edge technologies are revolutionizing our understanding of CHMP1B's role in membrane remodeling:

• Advanced Fluorescence Microscopy Techniques:

  • Spinning disc microscopy with EVOLVE EM-CCD cameras enables high-resolution visualization of CHMP1B dynamics

  • Single-molecule localization microscopy (SMLM) provides nanoscale resolution of CHMP1B assemblies

  • Total internal reflection fluorescence (TIRF) microscopy allows precise visualization of membrane-proximal events

• Micromanipulation Systems:

  • Micropositioning systems (e.g., MP-285) enable precise control of membrane geometry

  • Micropipette manipulation techniques facilitate creation of membrane nanotubes with controlled curvature

  • These approaches allow systematic investigation of CHMP1B's curvature sensitivity and remodeling capacity

• Synthetic Membrane Systems:

  • Giant Unilamellar Vesicles (GUVs) prepared using trehalose solutions provide controlled membrane environments

  • Lipid-covered silica beads serve as platforms for initiating membrane structure formation

  • These systems allow isolation of specific parameters influencing CHMP1B function

• Quantitative Image Analysis:

  • Advanced algorithms enable measurement of relative protein abundance between curved and flat membranes

  • Automated detection and characterization of CHMP1B-induced membrane structural features

  • Mathematical modeling of polymerization dynamics and maximum surface coverage

• Multi-technique Integration:

  • Combining structural biology (cryo-EM, X-ray crystallography) with functional assays

  • Correlating in vitro observations with cellular phenotypes

  • Development of structure-based models to predict functional outcomes

These technological advances are enabling researchers to address fundamental questions about CHMP1B's membrane remodeling mechanisms, including:

• How does CHMP1B recognize and preferentially bind to specific membrane curvatures?

• What are the kinetics and structural transitions during CHMP1B-mediated membrane deformation?

• How do CHMP1B assemblies generate mechanical forces sufficient for membrane scission?

Future integration of these approaches with computational modeling and in vivo validation will likely reveal novel insights into CHMP1B's fundamental roles in membrane biology.

How can CHMP1B research inform therapeutic approaches for hepatocellular carcinoma?

CHMP1B research offers several potential avenues for developing novel therapeutic approaches for hepatocellular carcinoma (LIHC):

• Biomarker Development:
  The differential expression of CHMP1B between normal and tumor tissues suggests its potential as a diagnostic or prognostic biomarker for LIHC. While CHMP1B alone did not show significant correlation with clinicopathological staging, a combined panel including multiple CHMP family members might provide enhanced diagnostic value .

• Drug Sensitivity Analysis:
  Research has demonstrated correlations between CHMP family expression and drug sensitivity/resistance profiles. The methodological approach employing:

  • The Cancer Therapeutics Response Portal (CTRP)

  • The Genomics of Drug Sensitivity in Cancer (GDSC) database

  • Analysis of area under the dose-response curve values

  • Spearman correlation analysis between gene expression and drug sensitivity

  This approach revealed that high expression of certain CHMP family members confers resistance to various drugs . Similar analysis focused specifically on CHMP1B could identify:

  • Drugs less effective in CHMP1B-overexpressing tumors (suggesting contraindications)

  • Compounds showing enhanced efficacy against CHMP1B-high tumors (potential therapeutic opportunities)

• Targeting ESCRT-Dependent Pathways:
  CHMP1B's role in the ESCRT-III complex suggests potential therapeutic approaches:

  • Disrupting aberrant ESCRT-III function in cancer cells

  • Modulating CHMP1B's involvement in EGFR degradation pathways

  • Developing compounds that restore normal ESCRT function in tumors with dysregulated CHMP expression

• Immunotherapy Considerations:
  The significant correlation between CHMP1B expression and immune cell infiltration suggests immunological relevance:

  • Potential influence on immunotherapy response

  • Possible role in modulating tumor microenvironment

  • Opportunity for combination approaches targeting both CHMP1B-related pathways and immune checkpoints

These approaches require further validation through mechanistic studies and preclinical models, but the established methodologies provide a framework for developing CHMP1B-informed therapeutic strategies for hepatocellular carcinoma.

What methodological approaches are most effective for studying CHMP1B's evolutionary conservation?

To effectively study CHMP1B's evolutionary conservation, researchers should implement the following methodological approaches:

• Comparative Genomic Analysis:

  • Identify CHMP1B homologs across diverse species including archaea, which represent ancient evolutionary lineages

  • Employ phylogenetic analysis to construct evolutionary trees reflecting CHMP1B's history

  • Calculate sequence conservation scores to identify highly preserved functional domains

• Structural Comparison Studies:

  • Determine protein structures from diverse organisms using X-ray crystallography or cryo-electron microscopy

  • Perform structural alignments to identify conserved three-dimensional features

  • Map conservation onto structural models to visualize evolutionary constraints

• Functional Conservation Assays:

  • Test functional complementation by expressing CHMP1B homologs from different species in model organisms

  • Assess polymerization behavior of CHMP1B proteins from diverse evolutionary origins

  • Compare membrane binding and remodeling capabilities using standardized assays:

    • GUV (Giant Unilamellar Vesicle) experiments

    • Membrane nanotube formation assays

    • Quantification of protein recruitment to curved versus flat membranes

• Systems-Level Evolutionary Analysis:

  • Compare ESCRT-III complex composition across species

  • Analyze conservation of interaction networks

  • Identify co-evolution patterns between CHMP1B and its binding partners

• Asgard Archaea as Evolutionary Reference Points:

  • Utilize Asgard archaea as particularly valuable models for evolutionary studies

  • Compare Asgard ESCRT-IIIB relative abundance between curved and flat membranes

  • Analyze conserved principles of ESCRT-III membrane remodeling from archaea to humans

These approaches have revealed that fundamental principles of ESCRT-III function, including CHMP1B's role, are remarkably conserved from archaea to humans despite billions of years of evolutionary divergence, suggesting essential and irreplaceable cellular functions .

What statistical methods are most appropriate for analyzing CHMP1B expression data in cancer studies?

Based on established research protocols, the following statistical methods are most appropriate for analyzing CHMP1B expression data in cancer studies:

These statistical methods, when properly applied with appropriate controls and validation approaches, provide robust analysis of CHMP1B's expression patterns and functional significance in cancer contexts.

How should researchers interpret conflicting data regarding CHMP1B's role in different cancer types?

When confronted with conflicting data regarding CHMP1B's role across different cancer types, researchers should implement the following interpretive framework:

This structured approach enables researchers to distinguish genuine biological complexity from technical artifacts, potentially revealing that CHMP1B exhibits true functional diversity across cancer contexts rather than simply contradictory data.

What are the optimal protocols for fluorescent labeling of CHMP1B for live-cell imaging studies?

For optimal fluorescent labeling of CHMP1B in live-cell imaging studies, researchers should consider the following protocol elements:

• Selection of Fluorescent Tags:

  • Choose bright, photostable fluorophores compatible with live-cell imaging

  • Consider size constraints: smaller tags (e.g., mNeonGreen, HaloTag) minimize functional interference

  • For dual-color imaging, select spectrally distinct fluorophores with minimal bleed-through

• Genetic Fusion Strategies:

  • Terminal fusion considerations:

    • C-terminal tagging may interfere with membrane binding

    • N-terminal tagging might disrupt interactions with other ESCRT components

    • Test both orientations to determine optimal configuration for functional preservation

  • Internal tagging options:

    • Identify permissive insertion sites based on structural data

    • Validate that internal tags maintain normal CHMP1B function

• Expression System Selection:

  • Endogenous tagging:

    • CRISPR-Cas9 knock-in approach for physiological expression levels

    • Homology-directed repair with fluorescent tag template

  • Exogenous expression:

    • Use weak promoters to avoid overexpression artifacts

    • Consider inducible systems for temporal control

• Microscopy Configuration:

  • Employ spinning disc microscopy for optimal balance of speed and resolution

  • Utilize high-numerical-aperture objectives (e.g., 100× 1.49–NA oil immersion)

  • Select appropriate cameras (e.g., EVOLVE EM-CCD) for sensitive detection

• Image Acquisition Parameters:

  • Minimize laser power and exposure time to reduce phototoxicity

  • Optimize frame rates based on CHMP1B dynamics (typically seconds to minutes)

  • Implement multi-position acquisition for statistical power

• Validation Controls:

  • Confirm tagged CHMP1B localization matches immunofluorescence of endogenous protein

  • Verify function through rescue experiments in CHMP1B-depleted cells

  • Include labeled non-functional CHMP1B mutants as negative controls

This comprehensive approach ensures generation of reliable, physiologically relevant data while minimizing artifacts associated with fluorescent protein tagging and imaging conditions.

What are the recommended experimental designs for investigating CHMP1B's role in immune cell interactions with cancer cells?

Based on current research methodologies, the following experimental designs are recommended for investigating CHMP1B's role in immune cell interactions with cancer cells:

• Co-culture Systems with Expression Modulation:

  • Experimental setup:

    • Establish cancer cell lines with CHMP1B knockdown, overexpression, and controls

    • Co-culture with relevant immune cell populations (B cells, T cells, macrophages, etc.)

    • Analyze immune cell recruitment, activation, and effector functions

  • Readouts:

    • Flow cytometry for immune cell phenotyping

    • Cytokine profiling of culture supernatants

    • Live-cell imaging of dynamic interactions

• Patient-Derived Models with Immune Components:

  • Experimental approach:

    • Develop patient-derived xenografts in humanized mouse models

    • Modulate CHMP1B expression in tumor compartment

    • Analyze immune infiltration patterns and functional status

  • Analysis methods:

    • Immunohistochemistry for spatial relationships

    • Single-cell RNA sequencing for detailed immune phenotyping

    • Correlation with immunosubtype classifications (C1-C6)

• 3D Organoid Co-culture Systems:

  • Setup parameters:

    • Generate tumor organoids with controlled CHMP1B expression

    • Incorporate relevant immune populations

    • Evaluate bidirectional signaling and functional consequences

  • Analytical approaches:

    • Live confocal imaging to track cellular interactions

    • Cytokine and chemokine profiling

    • Transcriptomic analysis of both tumor and immune compartments

• Mechanistic Dissection Using Pathway Inhibition:

  • Experimental design:

    • Identify CHMP1B-dependent secretory pathways using inhibitors

    • Block specific immune recognition receptors

    • Employ genetic approaches to disrupt potential interaction mechanisms

  • Functional assays:

    • Immune cell activation markers

    • Cytotoxicity assays

    • Antigen presentation efficiency

• Correlation Studies in Patient Samples:

  • Sample requirements:

    • Matched tumor and normal tissue

    • Fresh samples for immune cell isolation

    • Comprehensive clinical annotation

  • Analytical approach:

    • Multiplex immunofluorescence for spatial relationships

    • Correlation of CHMP1B expression with immune cell infiltration

    • Integration with clinical outcomes data

These experimental designs build upon established correlative evidence showing relationships between CHMP1B expression and immune cell infiltration in tumors, advancing toward mechanistic understanding of how CHMP1B influences the cancer-immune cell interface .