ELOB Human

What is the molecular structure and function of ELOB in humans?

ELOB is a 118 amino acid protein that functions as a regulatory subunit initially identified in RNA polymerase II elongation processes. It forms part of the Elongin (SIII) complex alongside ELOA (transcriptionally active component) and ELOC (another regulatory subunit) . This complex plays a critical role in regulating the elongation process of RNA polymerase II by preventing transient pausing of the polymerase at various sites within the transcriptional unit. Beyond transcriptional regulation, ELOB serves as a pivotal element in the ELOB/c-Cullin2/5-SOCS-box E3 ubiquitin-protein ligase complex, which catalyzes the ubiquitination and subsequent degradation of various target proteins .

How does ELOB interact with other components in ubiquitin-protein ligase complexes?

ELOB functions as an integral component of several ubiquitin-proteasome systems (UPSs), most notably in Cullin-RING ligases (CRLs) such as CRL2 and CRL5. In the CRL2 complex specifically, ELOB interacts with RBX1, Cullin-2, and connexin ELOC, forming a structural scaffold that facilitates the binding of substrate recognition proteins . One well-studied example involves the Von Hippel-Lindau (VHL) protein, which acts as a recognition protein interacting with the CRL2 complex. To study these interactions experimentally, coimmunoprecipitation assays can be performed using ELOB antibodies (such as ab151743 from Abcam) followed by immunoblotting for suspected interaction partners .

What is the expression pattern of ELOB across different human tissues?

ELOB demonstrates widespread expression across human tissues, suggesting its fundamental importance in cellular processes. According to data from the Human Protein Atlas, ELOB is expressed in neural tissues (including hippocampal formation, amygdala, basal ganglia, midbrain, spinal cord, cerebral cortex, cerebellum, hypothalamus), endocrine organs (thyroid, parathyroid, adrenal, and pituitary glands), digestive system (esophagus, stomach, intestines, liver, gallbladder, pancreas), reproductive organs, cardiovascular tissues, and the immune system . For researchers examining tissue-specific ELOB expression, immunohistochemistry staining protocols using anti-ELOB antibodies (such as sc-133090 from Santa Cruz) are recommended, with subsequent evaluation using the H-score semi-quantitative method (ranging from 0-300) .

How can researchers accurately quantify ELOB expression in patient-derived samples?

Researchers can employ multiple complementary techniques to quantify ELOB expression:

• RNA-seq analysis: Utilizing transcriptomic data from databases such as TCGA (The Cancer Genome Atlas) or GEO (Gene Expression Omnibus) for large-scale comparative studies. Differential expression analysis can be performed using the limma package in R, with filtering criteria of P < 0.05 and |log2 fold change| > 0.58 .

• Western blot quantification: For protein-level validation, researchers should use validated antibodies against ELOB and appropriate loading controls. Cell lysates should be generated and analyzed via standardized immunoblotting protocols .

• Immunohistochemistry: For tissue-specific expression patterns, IHC staining using tissue arrays with 5-micron thickness sections. After dehydration and peroxidase blocking, apply ELOB antibody and incubate for 30 minutes, followed by detection using appropriate systems such as DakoCytomation EnVision + System-HRP .

• Single-cell RNA sequencing: For cellular heterogeneity analysis, scRNA-seq data can be analyzed using the "Seurat" package and t-distributed Stochastic Neighbor Embedding (tSNE) method for non-linear dimensionality reduction and visualization .

How does ELOB contribute to protein degradation pathways?

ELOB functions as a critical component of E3 ubiquitin ligase complexes, particularly within the CRL2 (Cullin2-RBX1-ELOB E3 ligase) complex. This complex facilitates the ubiquitination and subsequent proteasomal degradation of target proteins. The mechanistic process involves:

• ELOB forms a complex with ELOC and Cullin-2/RBX1

• This complex recruits substrate recognition proteins (like VHL)

• Together, they coordinate the transfer of ubiquitin to target substrates

• Polyubiquitinated substrates are then recognized by the 26S proteasome and degraded

To experimentally investigate this process, researchers should employ in vivo ubiquitination assays. For example, to assess endogenous p14/ARF ubiquitination (a known ELOB target), transfect cells with siRNA targeting ELOB, treat with proteasome inhibitor MG-132 for 2 hours, lyse cells in 1% SDS-containing buffer, boil lysates for 10 minutes, dilute in SDS-free buffer, perform immunoprecipitation with anti-p14/ARF antibody, and analyze by immunoblotting with anti-ubiquitin antibody .

What is the relationship between ELOB and transcriptional regulation?

ELOB was initially characterized for its role in transcriptional regulation as part of the Elongin (SIII) complex. This complex enhances RNA polymerase II activity by suppressing transient pausing during transcriptional elongation. The precise molecular mechanisms involve:

• Association of the Elongin complex (ELOA, ELOB, ELOC) with RNA polymerase II

• ELOA directly interacts with polymerase to stimulate elongation rates

• ELOB and ELOC serve as regulatory subunits stabilizing the complex and potentially mediating additional protein interactions

This dual functionality - in both transcriptional regulation and protein degradation pathways - positions ELOB as a multifunctional adaptor protein at the intersection of gene expression and protein turnover. Researchers studying this function should use chromatin immunoprecipitation (ChIP) assays to identify genomic regions where ELOB-containing complexes associate with transcriptional machinery .

What evidence links ELOB expression to breast cancer progression and prognosis?

Multiple lines of evidence connect ELOB expression to breast cancer:

• Expression analysis: Bioinformatic analysis of TCGA and FUSCC (Fudan University Shanghai Cancer Center) databases demonstrates significant ELOB overexpression in breast cancer tissues compared to normal tissues .

• Prognostic correlation: Higher ELOB expression correlates with unfavorable prognosis in breast cancer patients, as validated through Kaplan-Meier survival analysis .

• Pathway enrichment: GSEA and KEGG pathway analyses reveal that elevated ELOB expression associates with multiple cancer-promoting pathways, including cell cycle regulation, DNA replication, proteasome function, and PI3K-Akt signaling .

• Functional validation: Both in vivo and in vitro experiments confirm that downregulation of ELOB significantly suppresses breast cancer cell proliferation .

• Tissue microarray validation: Analysis of breast cancer tissue microarrays and western blot analysis of patient samples demonstrates elevated ELOB expression in tumor tissues compared to adjacent normal tissues .

For researchers investigating ELOB in cancer contexts, a combination of public database mining (TCGA, cBioPortal), tissue microarray analysis, and functional validation through genetic manipulation (siRNA knockdown, overexpression constructs) is recommended .

What methodological approaches can be used to study ELOB's role in tumor progression?

Researchers should employ a multi-tiered approach:

• Genetic manipulation:

  • siRNA knockdown using sequences targeting ELOB (e.g., 5′-UGAACAAGCCGUGCAGUGA-3′, 5′-AGCGGCUGUACAAGGAUGA-3′)

  • Overexpression constructs with tags (e.g., FLAG-tagged ELOB)

  • CRISPR-Cas9 genome editing for stable cell lines

• Protein-protein interaction studies:

  • Coimmunoprecipitation using pre-chilled NP-40 lysis buffer (50 mM Tris–HCl pH 7.5, 150 mM NaCl, 0.5% NP-40)

  • Primary antibody incubation (ELOB ab151743 from Abcam) overnight at 4°C

  • Protein A/G magnetic bead incubation for 2 hours

  • Immunoprecipitate washing and immunoblot analysis

• Protein stability assessment:

  • Cycloheximide (CHX) chase assays with 50 μg/mL CHX treatment

  • Optional inclusion of 1.0 μM/L MLN4924 (neddylation inhibitor) or DMSO control

  • Time-course protein level analysis by western blot

• Localization studies:

  • Immunofluorescence with paraformaldehyde fixation

  • Cell permeabilization with 0.5% Triton X-100

  • Primary antibody incubation (e.g., anti-FLAG F1804 or anti-HA H6908 from Sigma)

  • Confocal microscopy imaging using appropriate systems (e.g., LSM880 with Fast Airyscan, Zeiss)

• In vivo validation:

  • Xenograft models with ELOB-manipulated cell lines

  • Tissue analysis via immunohistochemistry and western blotting

How does ELOB specifically regulate p14/ARF degradation in cancer cells?

ELOB regulates p14/ARF through a precise molecular mechanism:

• As a core component of the Cullin2-RBX1-ELOB E3 ligase (CRL2) complex, ELOB facilitates the recognition and ubiquitination of p14/ARF

• This ubiquitination marks p14/ARF for proteasomal degradation

• When ELOB is downregulated, p14/ARF degradation is impaired, leading to p14/ARF accumulation

• The anticancer effects of ELOB depletion can be rescued by simultaneous knockdown of p14/ARF, confirming the mechanistic relationship

To experimentally validate this relationship, researchers should:

• Perform coimmunoprecipitation to demonstrate physical interaction between components of the CRL2 complex and p14/ARF

• Conduct in vivo ubiquitination assays after MG-132 treatment

• Assess p14/ARF protein levels following ELOB manipulation using western blot

• Perform rescue experiments with simultaneous manipulation of both ELOB and p14/ARF

What signaling pathways intersect with ELOB-mediated protein degradation?

ELOB-containing E3 ligase complexes intersect with multiple cancer-related signaling pathways:

• Cell cycle regulation: GSEA analysis indicates that high ELOB expression correlates with cell cycle pathway activation

• DNA replication: ELOB expression levels associate with DNA replication pathways, suggesting a role in regulating proteins involved in genome replication

• PI3K-Akt signaling: Pathway enrichment analysis demonstrates a connection between ELOB expression and PI3K-Akt pathway activity, a key cancer-promoting signaling axis

• Proteasome pathway: Naturally, ELOB's role in ubiquitination connects to the proteasomal degradation system

To comprehensively map these pathway interactions, researchers should:

• Use RNA-seq following ELOB manipulation to identify global transcriptional changes

• Conduct phospho-proteomic analysis to detect altered signaling node activity

• Perform pathway analysis using tools like GSEA, GO enrichment, and KEGG pathway analysis with the R package "clusterProfiler"

• Validate key interactions through targeted inhibition of identified pathway components

What are the methodological challenges in generating stable ELOB knockdown models?

When creating stable ELOB knockdown models, researchers should consider:

• Essential gene concerns: ELOB's fundamental role in cellular processes may make complete knockout lethal or severely growth-inhibiting, requiring inducible systems or partial knockdown approaches

• Off-target effects: Carefully design siRNA sequences to avoid off-target effects; validate with multiple independent sequences and rescue experiments

• Functional redundancy: Consider potential compensation by related proteins (e.g., other elongin family members)

• Experimental validation: Confirm knockdown efficiency at both RNA and protein levels using qRT-PCR and western blotting

• Phenotypic assessment: Thoroughly characterize models using proliferation assays, cell cycle analysis, and apoptosis measurements to distinguish between specific and non-specific effects

For optimal results, researchers should employ lentiviral delivery of shRNA or CRISPR-Cas9 systems for stable integration, with tetracycline-inducible promoters to control the degree and timing of ELOB depletion .

How can researchers effectively study ELOB interactions in complex cellular environments?

To study ELOB interactions in complex cellular contexts:

• Proximity labeling approaches:

  • BioID or TurboID fusion proteins to identify proteins in close proximity to ELOB

  • APEX2-based proximity labeling for temporal resolution of interaction networks

• Mass spectrometry-based interactomics:

  • Immunoprecipitation of tagged ELOB followed by mass spectrometry

  • SILAC or TMT labeling for quantitative comparison across conditions

• Fluorescence-based interaction studies:

  • FRET (Förster Resonance Energy Transfer) or BiFC (Bimolecular Fluorescence Complementation) to visualize interactions in living cells

  • High-content imaging for spatiotemporal dynamics

• Genetic interaction mapping:

  • CRISPR screening approaches to identify synthetic lethal interactions

  • Combinatorial genetic manipulation to map functional interactions

• Single-cell analysis:

  • Use techniques like scRNA-seq with the "Seurat" software package and tSNE for dimensionality reduction

  • Cell cluster identification and annotation using "singleR"

What strategies can be employed to therapeutically target ELOB in cancer?

Based on ELOB's role in cancer progression, several therapeutic approaches warrant investigation:

• Direct ELOB inhibition:

  • Small molecule inhibitors disrupting ELOB interactions with other complex components

  • Peptide-based inhibitors mimicking key interaction interfaces

• CRL2 complex disruption:

  • Targeting the ELOB-ELOC interface

  • Disrupting ELOB-Cullin2 interactions

  • Neddylation inhibitors like MLN4924 that impair CRL activation

• Substrate-specific approaches:

  • Blocking recognition of specific substrates like p14/ARF

  • Developing proteolysis-targeting chimeras (PROTACs) to redirect ELOB-containing complexes

• Combinatorial approaches:

  • Pairing ELOB targeting with inhibitors of intersecting pathways like PI3K-Akt

  • Synthetic lethality-based combinations

• Gene therapy approaches:

  • siRNA delivery systems specifically targeting ELOB

  • CRISPR-based approaches for precise genetic manipulation

To identify potential therapeutic compounds, researchers can utilize the Connectivity Map (CMap) analysis platform (https://clue.io), which can discover small molecules and inform clinical trials by identifying compounds with expression signatures inverse to ELOB-driven signatures .

How does ELOB compare between human and mouse models in research applications?

Understanding cross-species conservation is crucial for translational research:

• Evolutionary conservation: The mouse Elob gene (MGI:1914923) shares significant homology with human ELOB, suggesting conserved fundamental functions .

• Expression patterns: Both human and mouse ELOB show widespread tissue distribution, though some tissue-specific differences may exist .

• Functional conservation: The core role in ubiquitin ligase complexes appears conserved, though substrate specificity may vary between species.

• Model considerations: When using mouse models:

  • Validate key findings in human cell lines or tissues

  • Consider potential differences in protein interaction networks

  • Assess pathway conservation through comparative genomics

  • Evaluate phenotypic differences following genetic manipulation

• Translational limitations: Researchers should be aware that certain cancer-promoting mechanisms, particularly those involving p14/ARF, may have species-specific aspects requiring careful validation across models .

What bioinformatic pipelines are recommended for analyzing ELOB expression across cancer datasets?

For comprehensive ELOB expression analysis across cancer datasets:

• Data acquisition:

  • Extract RNA-seq data with clinical information from TCGA (https://tcga-data.nci.nih.gov/tcga/)

  • Access additional datasets through cBioPortal (https://www.cbioportal.org/)

  • Include specialized datasets like FUSCC for validation

• Differential expression analysis:

  • Use the limma package in R

  • Apply filtering criteria of P < 0.05 and |log2 fold change (FC)| > 0.58

  • Compare tumor vs. normal tissues, as well as across cancer subtypes

• Survival analysis:

  • Employ Kaplan-Meier method with log-rank test

  • Utilize online tools like Kaplan-Meier plotter (https://kmplot.com/analysis/)

  • Stratify patients by ELOB expression levels (high vs. low)

• Methylation analysis:

  • Use the Methsurv database (https://biit.cs.ut.ee/methsurv/) to analyze DNA methylation patterns

  • Correlate methylation status with expression and clinical outcomes

• Pathway and network analysis:

  • Perform GO enrichment and KEGG pathway analyses using the "clusterProfiler" R package

  • Apply GSEA to assess ELOB expression impact on pathway activity

  • Construct protein-protein interaction networks using publicly available databases

How can researchers integrate multi-omics data to better understand ELOB function?

For integrative multi-omics analysis of ELOB:

• Data layer integration:

  • Combine genomic (mutations, CNVs), transcriptomic (expression), proteomic, and epigenomic (methylation) data

  • Use tools like MultiOmics Factor Analysis (MOFA) for dimensionality reduction across data types

• Single-cell multi-omics:

  • Analyze scRNA-seq data using "Seurat" package and tSNE for visualization

  • Integrate with spatial transcriptomics for tissue context

  • Potentially include single-cell proteomics for protein-level validation

• Network construction and analysis:

  • Build integrative networks incorporating expression, protein-protein interactions, and pathway information

  • Identify key nodes and regulatory relationships

  • Use weighted gene co-expression network analysis (WGCNA) to identify modules associated with ELOB expression

• Causal inference approaches:

  • Apply computational causal inference to identify potential regulatory relationships

  • Use methods like Mendelian randomization to establish causal relationships where genetic variants are available

• Visualization and interpretation:

  • Employ circos plots, heatmaps, and network visualizations

  • Develop interactive dashboards for data exploration

  • Use dimensionality reduction techniques to identify patterns across multi-omics datasets

This comprehensive approach enables researchers to place ELOB in broader cellular contexts and identify novel functional relationships that may not be apparent from single-omics analyses.

What unresolved questions remain about ELOB's role in normal development and disease?

Several critical questions remain unexplored:

• Developmental roles: How does ELOB function during embryonic development and tissue differentiation? Mouse models suggest broad expression across tissue types, but detailed developmental functions remain unclear .

• Tissue-specific functions: Does ELOB have tissue-specific roles beyond its core function in ubiquitination? The widespread expression pattern suggests potential specialized functions in different cellular contexts .

• Non-canonical functions: Beyond its established roles in transcriptional regulation and protein degradation, does ELOB participate in other cellular processes?

• Regulatory mechanisms: How is ELOB itself regulated at transcriptional, post-transcriptional, and post-translational levels?

• Cancer type specificity: Why does ELOB overexpression appear particularly impactful in breast cancer, and does this extend to other cancer types?

• Therapeutic resistance: Does ELOB contribute to therapeutic resistance mechanisms in cancer treatment?

• Non-oncogenic roles in disease: Does ELOB dysregulation contribute to non-cancer pathologies?

To address these questions, researchers should employ conditional knockout models, tissue-specific approaches, and comprehensive multi-omics analyses across development and disease contexts.

What emerging technologies could advance our understanding of ELOB biology?

Cutting-edge technologies poised to enhance ELOB research include:

• Spatial transcriptomics and proteomics:

  • Mapping ELOB expression and its targets with spatial resolution in tissues

  • Correlating with pathological features in disease states

• CRISPR-based functional genomics:

  • Base editing for precise genetic manipulation

  • CRISPRi/CRISPRa for reversible modulation of ELOB expression

  • CRISPR screens to identify synthetic lethal interactions

• Structural biology approaches:

  • Cryo-EM to resolve structures of ELOB-containing complexes

  • Hydrogen-deuterium exchange mass spectrometry for dynamic structural information

  • AlphaFold and other AI-based structure prediction for interaction modeling

• Single-molecule techniques:

  • Live-cell imaging of ELOB dynamics

  • Single-molecule pulldown to analyze complex stoichiometry

  • Super-resolution microscopy for subcellular localization

• Organoid and patient-derived models:

  • 3D organoid systems to study ELOB in more physiologically relevant contexts

  • Patient-derived xenografts to validate findings in heterogeneous tumor environments

These technologies will provide unprecedented insights into ELOB biology and potentially reveal novel therapeutic opportunities across multiple disease contexts.