UBE2I Human His

What is UBE2I and what is its functional role in the ubiquitin pathway?

UBE2I, also known as UBC9, is a small ubiquitin-like modifier (SUMO) E2 enzyme that plays a critical role in the SUMOylation pathway. Unlike typical E2 enzymes that function in ubiquitination, UBE2I specifically facilitates the conjugation of SUMO to target proteins. UBE2I shares the conserved core ubiquitin conjugating (UBC) domain of approximately 150 amino acid residues found in all E2 proteins, which is critical for its enzymatic function .

Methodologically, UBE2I function can be studied through:

• In vitro SUMOylation assays using purified components (similar to ubiquitylation assays described in )

• Assessment of thioester bond formation between UBE2I and SUMO

• Structure-function analysis comparing UBE2I with other E2 enzymes

How can I produce and purify recombinant UBE2I with a histidine tag for in vitro studies?

Production of His-tagged UBE2I for biochemical studies requires a systematic approach:

• Cloning strategy:

  • Amplify the UBE2I open reading frame by PCR

  • Insert into a pET28 vector with 6xHis-tag and thrombin/TEV cleavage site upstream of the cDNA insert using the Infusion system

  • Verify the construct by sequencing

• Expression protocol:

  • Transform the construct into E. coli BL21(DE3) or Rosetta2(DE3) cells

  • Grow cultures at 37°C until OD600 reaches 0.6-0.8

  • Induce protein expression with IPTG (0.5-1mM)

  • Continue growth at lower temperature (16-20°C) overnight

• Purification procedure:

  • Harvest and lyse cells in appropriate buffer

  • Purify using Ni-NTA resin following manufacturer's instructions

  • Dialyze against 20mM Tris-Cl pH 8.0, 150mM NaCl, 10% glycerol, 2mM DTT

  • For crystallography, remove the His-tag by thrombin digestion (1 unit/mg protein, 2h at 21-23°C)

  • Further purify by gel filtration on a Superdex 200 column

  • Concentrate to 20-40mg/ml for structural studies

This approach has been successfully used for other E2 enzymes and can be applied to UBE2I .

How is UBE2I expression altered in human cancers and what are its prognostic implications?

UBE2I expression shows significant alterations in human cancers, particularly in hepatocellular carcinoma (HCC):

• Expression profile:

  • Bioinformatics analysis using HCCDB, TIMER, and Kaplan-Meier plotter databases shows UBE2I is highly expressed in HCC

  • Expression levels vary with alcohol ingestion and hepatitis status

  • High expression correlates with poor prognosis in HCC

• Methodological approach for expression analysis:

  • Database mining using GEPIA (http://gepia2.cancer-pku.cn/#index) and Kaplan-Meier plotter (https://kmplot.com/analysis/)[2]

  • Stratified analysis by gender, race, and clinical parameters

  • Construction of gene-gene interaction networks using geneMANIA plugin of Cytoscape

  • Co-expression analysis using Cbioportal (https://www.cbioportal.org/)[2]

• Functional significance:

  • Silencing UBE2I expression decreases cell migration, invasion and proliferation in HCC cells

  • UBE2I expression is associated with immune infiltrates in tumors

These findings suggest UBE2I could serve as both a prognostic marker and potential therapeutic target in HCC.

What experimental approaches can be used to study UBE2I loading with SUMO?

Studying UBE2I loading with SUMO requires careful experimental design similar to the E2 loading assays described for ubiquitin E2s:

• Basic loading assay protocol:

  • Prepare reaction mixture containing E1 enzyme (1μg), UBE2I (1μg), and His-tagged SUMO (5μg)

  • Use buffer containing 10mM HEPES pH7.5, 100mM NaCl, 40μM ATP, and 2mM MgCl2

  • Incubate for 10 minutes at 30°C

  • Stop reaction with non-reducing SDS-PAGE sample buffer

  • Analyze by 4-20% gradient SDS-PAGE and Western blotting using anti-His antibodies

• Detection methods:

  • Western blotting to visualize thioester-linked UBE2I~SUMO intermediate

  • Mass spectrometry for detailed characterization

  • Fluorescence-based assays for real-time kinetics

• Control experiments:

  • Catalytic cysteine mutant of UBE2I (negative control)

  • Omission of ATP (negative control)

  • Comparison with other E2 enzymes for specificity

This methodology parallels the ubiquitin E2 loading assays described in search result , adapted for SUMO-specific components.

How can I design effective UBE2I knockdown experiments to study its function in cellular models?

Designing effective UBE2I knockdown studies requires systematic optimization:

• siRNA approach (as used in HCC studies) :

  • Design multiple siRNA sequences targeting different UBE2I regions

  • Include scrambled siRNA controls

  • Optimize transfection conditions for each cell line

  • Confirm knockdown efficiency by Western blot and qRT-PCR

• Experimental design considerations:

  • Determine optimal timepoint for analysis (24-72h post-transfection)

  • Include appropriate functional assays:

    • Migration assays (wound healing, transwell)

    • Invasion assays (Matrigel-coated transwell)

    • Proliferation assays (MTT, colony formation)

  • Analyze pathway effects through Western blot of key markers

• Results analysis:

  • Quantify migration, invasion, and proliferation using image analysis software

  • Perform statistical analysis (unpaired t-test for comparisons between groups)

  • Use GraphPad or similar software for data visualization

This approach has successfully demonstrated that UBE2I silencing leads to decreased cell migration, invasion and proliferation in HCC cells .

How do the structural features of UBE2I determine its substrate specificity compared to other E2 enzymes?

Understanding UBE2I's structural determinants of specificity requires comprehensive structure-function analysis:

• Key structural features to analyze:

  • Surface charge distribution (net positive or neutral charge is associated with chain building activity in E2s)

  • Presence of an "acidic trough" near the catalytic cysteine

  • Basic region surrounding the acidic trough

  • Similarity to known HECT binding signatures in other E2s like UBE2L3

• Methodological approaches:

  • High-resolution X-ray crystallography (as performed for 15 E2 catalytic domains)

  • Surface charge analysis of UBC domains

  • Homology modeling if experimental structures are unavailable

  • Site-directed mutagenesis of key residues followed by functional assays

• Comparative structural analysis:

  • Superimpose UBE2I structure with other E2 structures

  • Analyze structural differences around the active site

  • Compare electrostatic surface potentials

  • Identify regions that correlate with differential activity

This approach parallels the systematic structure-function analysis described for other E2 enzymes , adapted specifically for UBE2I's role in SUMOylation.

What molecular mechanisms underlie UBE2I's influence on cancer cell migration and invasion?

The mechanisms by which UBE2I promotes cancer cell migration and invasion can be elucidated through comprehensive pathway analysis:

• RNA-sequencing approach:

  • Compare transcriptomes of control and UBE2I-silenced cancer cells

  • Identify differentially expressed genes (DEGs) using DESeq2 method

  • Apply stringent criteria: |log2FoldChange| > 0, adjusted P ≤ 0.05

  • In HCC studies, silencing UBE2I identified:

    • 166 DEGs in HCCM cells (74 upregulated, 92 downregulated)

    • 1883 DEGs in Huh7 cells (845 upregulated, 1038 downregulated)

    • 27 common DEGs between both cell lines

• Pathway analysis:

  • Conduct enrichment analysis of GO terms, KEGG pathways, Reactome pathways

  • Analyze disease ontology (DO) terms and DisGeNET data

  • Construct interaction networks using CluGO plugin in Cytoscape

• Validation experiments:

  • Confirm expression changes of key genes by qRT-PCR

  • Validate protein-level changes by Western blot

  • Perform rescue experiments to establish causality

This systematic approach has revealed potential pathways through which UBE2I influences cancer progression in HCC models .

How can I analyze UBE2I-mediated SUMOylation products using mass spectrometry?

Mass spectrometry (MS) provides powerful tools for characterizing UBE2I-mediated SUMOylation products:

• Sample preparation strategy:

  • Perform in vitro SUMOylation reactions with purified components

  • Use His-tagged SUMO for affinity purification

  • Alternatively, immunoprecipitate SUMOylated proteins from cells

  • Process samples following protocols similar to those used for ubiquitylation studies

• MS analysis approach:

  • Digest samples with trypsin or other suitable proteases

  • For SUMO remnant identification, use specific antibodies to enrich modified peptides

  • Perform LC-MS/MS analysis using high-resolution instruments

  • Apply database searching to identify modified proteins and sites

• Data interpretation:

  • Identify SUMOylation sites based on characteristic mass shifts

  • Quantify relative SUMOylation levels

  • Compare modification patterns between experimental conditions

  • Integrate with protein-protein interaction data

This methodology adapts approaches used for characterizing ubiquitylation products of E2-HECT E3 pairs to the analysis of UBE2I-mediated SUMOylation.

What is the relationship between UBE2I expression and autophagy pathways in cancer progression?

UBE2I's relationship with autophagy pathways in cancer can be systematically investigated:

• Experimental approach:

  • Manipulate UBE2I expression through knockdown or overexpression

  • Analyze autophagy markers by Western blot

  • Monitor autophagic flux using LC3-I to LC3-II conversion assays

  • Use autophagy inhibitors/inducers to confirm pathway involvement

• Mechanistic investigation:

  • Examine key autophagy regulators (Beclin-1, ATG proteins) after UBE2I manipulation

  • Investigate mTOR pathway components and their activation status

  • Analyze RNA-seq data for autophagy-related gene expression changes

  • Use reporter assays to monitor autophagy activity

• Functional relevance:

  • Determine whether autophagy modulation mediates UBE2I's effects on:

    • Cell migration and invasion

    • Proliferation and survival

    • Response to therapeutic agents

  • Perform rescue experiments by co-modulating UBE2I and autophagy

Western blot analysis in HCC studies has established a connection between downregulated UBE2I expression and autophagy pathways, suggesting this may be a mechanism by which UBE2I influences cancer progression .

How do post-translational modifications affect UBE2I function and activity?

Post-translational modifications (PTMs) of UBE2I constitute an important regulatory layer:

• Key PTMs affecting UBE2I:

  • Phosphorylation at specific residues

  • Acetylation

  • Self-SUMOylation

  • Ubiquitination affecting stability

• Methodological approach to study PTMs:

  • Mass spectrometry to identify modification sites

  • Site-directed mutagenesis to create non-modifiable mutants

  • Phospho-specific or acetylation-specific antibodies

  • In vitro enzymatic assays comparing modified vs unmodified UBE2I

• Functional assessment:

  • Compare activity of wild-type vs. mutant UBE2I in SUMOylation assays

  • Analyze subcellular localization using confocal microscopy

  • Examine interactions with E3 ligases and substrates

  • Assess stability and turnover rates

This approach parallels methods used to study regulatory mechanisms of other E2 enzymes in the ubiquitin system .

What bioinformatics tools and databases are most valuable for comprehensive UBE2I research?

A comprehensive bioinformatics approach to UBE2I research utilizes multiple resources:

• Expression and clinical correlation databases:

  • HCCDB: Database specific for hepatocellular carcinoma data

  • TIMER: Tool for immune infiltrate analysis across cancers

  • Kaplan-Meier plotter (https://kmplot.com/analysis/): Survival analysis tool

  • GEPIA (http://gepia2.cancer-pku.cn/#index): Gene expression profiling and analysis

  • Cbioportal (https://www.cbioportal.org/): For identifying co-expressed genes

• Network analysis tools:

  • GeneMANIA plugin in Cytoscape: For visualizing gene-gene interaction networks

  • CluGO plugin in Cytoscape: For constructing functional interaction networks

  • STRING database: For protein-protein interaction mapping

• Pathway and enrichment analysis:

  • GO terms enrichment

  • KEGG pathways analysis

  • Reactome pathways analysis

  • Disease ontology (DO) terms and DisGeNET analysis

• Structural analysis tools:

  • PDB database for 3D structural information

  • SwissModel for homology modeling

  • PyMOL or UCSF Chimera for structural visualization and analysis

This integrated approach has been successfully applied in UBE2I research in HCC and structure-function studies of E2 enzymes .

How can I design experiments to identify novel UBE2I substrates in specific cancer contexts?

Identifying novel UBE2I substrates requires a multi-faceted experimental approach:

• Proteomics-based identification:

  • SUMO-remnant immunoaffinity profiling

  • Stable isotope labeling (SILAC) comparing control vs. UBE2I-manipulated cells

  • Purification of SUMOylated proteins using His-tagged SUMO pulldown

  • Mass spectrometry analysis to identify modified proteins

• Bioinformatics prediction:

  • Use SUMOylation site prediction algorithms

  • Analyze gene expression data for co-regulation with UBE2I

  • Integrate with protein-protein interaction networks

• Validation strategy:

  • In vitro SUMOylation assays with candidate substrates

  • Site-directed mutagenesis of predicted SUMOylation sites

  • Cell-based validation using co-immunoprecipitation

  • Functional studies to determine consequences of substrate SUMOylation

• Cancer-specific considerations:

  • Compare substrate profiles across different cancer types

  • Correlate substrate SUMOylation with cancer progression markers

  • Analyze clinical relevance of identified substrates

This methodology builds on approaches used for E2-substrate identification in the ubiquitin system , adapted for UBE2I-specific SUMOylation research.

What are the key considerations for interpreting RNA-sequencing data after UBE2I manipulation?

Proper interpretation of RNA-sequencing data after UBE2I manipulation requires careful analysis:

• Experimental design considerations:

  • Include sufficient biological replicates

  • Use appropriate controls (scrambled siRNA)

  • Consider time-dependent effects after UBE2I manipulation

  • Account for cell type-specific responses (e.g., differences between HCCM and Huh7 cells)

• Data analysis pipeline:

  • Quality control and preprocessing of sequencing reads

  • Alignment to reference genome

  • Quantification of gene expression

  • Identification of differentially expressed genes (DEGs):

    • Apply stringent criteria: |log2FoldChange| > 0, adjusted P ≤ 0.05

    • Compare DEGs across different cell lines

• Pathway analysis approach:

  • GO term enrichment

  • KEGG and Reactome pathway analysis

  • Disease ontology terms and DisGeNET analysis

  • Construction of interaction networks using appropriate tools

• Validation and integration:

  • Confirm key findings by qRT-PCR

  • Validate protein-level changes by Western blot

  • Integrate with functional data

  • Connect transcriptional changes to phenotypic effects

This approach has been successfully applied in UBE2I research in HCC, revealing complex transcriptional networks influenced by UBE2I expression .