Recombinant Human UPF0766 protein C6orf228 (C6orf228)

What is UPF0766 protein C6orf228 and what is its current nomenclature?

UPF0766 protein C6orf228 is now officially designated as SMIM13 (small integral membrane protein 13). This protein-coding gene (Gene ID: 221710) is located on chromosome 6p24.2. The term "UPF" stands for "uncharacterized protein family," indicating its function was not fully elucidated when initially identified. As research progressed, it was reclassified as SMIM13 based on its structural characteristics as a small integral membrane protein .

What experimental systems are available for studying SMIM13?

Recombinant expression systems are available for SMIM13 research. The protein can be produced as a full-length human recombinant protein (amino acids 1-91) with an N-terminal His-tag in E. coli expression systems. Typical applications include:

The recombinant protein is typically provided in lyophilized form with >90% purity as determined by SDS-PAGE .

How should experimental design accommodate the membrane-bound nature of SMIM13?

When designing experiments for SMIM13, researchers must consider its membrane-bound characteristics. Standard methodological approaches include:

• Detergent selection: Use mild non-ionic detergents (e.g., DDM, LMNG) that maintain membrane protein structure while enabling solubilization.

• Buffer optimization: Include 50mM Tris/PBS buffer (pH 8.0) with 6% trehalose for stability during reconstitution and storage .

• Reconstitution procedures: After initial solubilization in detergent, reconstitute at 0.1-1.0 mg/mL in deionized sterile water with 5-50% glycerol (final concentration) to prevent aggregation during freeze-thaw cycles .

• Storage conditions: Store at -20°C/-80°C with aliquoting to prevent multiple freeze-thaw cycles that could compromise structural integrity .

• Expression system considerations: While E. coli-expressed protein is readily available, eukaryotic expression systems may provide more appropriate post-translational modifications for functional studies.

What are the experimental challenges in determining SMIM13 function?

Determining the function of previously uncharacterized membrane proteins like SMIM13 presents several methodological challenges:

• Limited baseline information: As a protein initially classified as "uncharacterized" (UPF), there are few established functional assays specific to SMIM13.

• Membrane protein solubility issues: Standard structural determination methods may be complicated by the hydrophobic regions necessary for membrane integration.

• Potential redundancy with other SMIM family members: Functional redundancy may mask phenotypes in knockout/knockdown experiments.

• Context-dependent function: SMIM13 may have tissue-specific functions that require appropriate cellular models.

To address these challenges, researchers typically employ a multi-faceted approach including:

• Comparative genomics to identify conserved domains

• Interaction proteomics to identify binding partners

• RNA-seq analysis following SMIM13 perturbation

• Targeted CRISPR-Cas9 modification in relevant cell types

How should researchers interpret potential connections between SMIM13 and disease states?

Current genomics databases suggest potential associations between SMIM13 and cortical surface area and thickness of Heschl's gyrus . When investigating potential disease associations, researchers should:

• Distinguish correlation from causation through mechanistic studies

• Consider SMIM13 variants reported in ClinVar databases

• Analyze tissue-specific expression patterns

• Implement appropriate controls when studying SMIM13 in disease models

• Validate findings across multiple experimental systems

What are the optimal storage and handling conditions for recombinant SMIM13?

Recombinant SMIM13 requires specific handling protocols to maintain functionality:

Researchers should avoid repeated freeze-thaw cycles as they significantly reduce protein activity. For working stocks, storage at 4°C for up to one week is acceptable .

What experimental controls are essential when studying SMIM13 function?

When designing experiments to characterize SMIM13 function, several controls are essential:

• Empty vector controls: For overexpression studies, include cells transfected with empty vector to control for transfection effects.

• Scrambled/non-targeting controls: For knockdown/knockout studies, include appropriate negative controls (scrambled siRNA or non-targeting gRNA).

• Related protein controls: Include other SMIM family members to assess specificity of observed phenotypes.

• Antibody validation: For immunodetection, include SMIM13-null samples and competing peptide controls.

• Subcellular fractionation controls: When assessing membrane localization, include markers for different cellular compartments (plasma membrane, ER, Golgi).

These controls help distinguish specific SMIM13-related effects from experimental artifacts and ensure reliable, reproducible results .

How can researchers effectively characterize SMIM13 interactions with other proteins?

Characterizing protein-protein interactions for membrane proteins like SMIM13 requires specialized approaches:

• Proximity labeling techniques: BioID or APEX2 fusion proteins can identify proximal interacting partners in living cells while maintaining membrane localization.

• Split-reporter assays: Techniques like split-luciferase complementation allow detection of protein interactions in native membrane environments.

• Co-immunoprecipitation adaptations: Use membrane-compatible detergents (digitonin, CHAPS) that preserve protein-protein interactions while solubilizing membrane components.

• Surface plasmon resonance: For in vitro validation, using the recombinant protein immobilized on sensor chips can quantify binding kinetics.

• Crosslinking mass spectrometry: Chemical crosslinking followed by mass spectrometry can capture transient or weak interactions.

When analyzing potential interaction networks, researchers should consider both direct and indirect interactions, and validate key findings through multiple complementary techniques.

How should researchers interpret SMIM13 expression data across different tissues?

When analyzing SMIM13 expression across tissues, consider:

• Normalization methods: Different RNA-seq or microarray platforms require appropriate normalization strategies.

• Tissue-specific expression patterns: Evaluate whether SMIM13 shows preferential expression in specific tissues or cell types.

• Splice variants: Assess whether alternative splicing produces tissue-specific isoforms with potentially distinct functions.

• Co-expression patterns: Identify genes with similar expression patterns that might function in common pathways.

• Single-cell resolution: Where available, single-cell RNA-seq data can reveal cell type-specific expression patterns not apparent in bulk tissue analysis.

Expression data should always be validated using orthogonal techniques such as qRT-PCR or protein-level detection where possible.

What approaches should be used to analyze SMIM13 conservation across species?

Evolutionary analysis provides important functional insights:

• Sequence alignment: Compare SMIM13 protein sequences across species to identify conserved domains or motifs.

• Synteny analysis: Examine conservation of genomic context surrounding SMIM13 to identify potential co-evolved gene clusters.

• Rate of evolution: Calculate Ka/Ks ratios to determine if SMIM13 is under positive, negative, or neutral selection pressure.

• Domain architecture: Analyze conservation of predicted structural features like transmembrane domains.

• Comparative expression: Compare expression patterns across species to identify conserved regulatory mechanisms.

Strong conservation of specific regions suggests functional importance and can guide targeted mutagenesis experiments.

What emerging technologies could advance understanding of SMIM13 function?

Several cutting-edge approaches show promise for elucidating SMIM13 function:

• Cryo-electron microscopy: For membrane proteins like SMIM13, advances in cryo-EM may enable structural determination without crystallization.

• AlphaFold2 and structural prediction: AI-based structural prediction can provide structural models to guide experimental design.

• Spatial transcriptomics: These techniques can reveal tissue-specific expression patterns at subcellular resolution.

• Organoid models: Complex 3D culture systems may reveal functions not apparent in standard 2D cultures.

• Single-cell multi-omics: Integrated analysis of transcriptome, proteome, and epigenome at single-cell resolution can identify cell type-specific functions.

How might researchers explore potential roles of SMIM13 in developmental processes?

To investigate developmental roles of SMIM13, researchers could:

• Create developmental time-course expression profiles in model organisms

• Generate conditional knockout models with temporal control of gene deletion

• Employ lineage tracing in SMIM13-expressing cells

• Analyze potential roles in stem cell differentiation models

• Investigate interaction with known developmental signaling pathways (Wnt, Notch, BMP)

These approaches would help determine if SMIM13 functions in specific developmental windows or processes.