Gene Name: C13orf44 (alias SMIM2)
Protein Name: Small Integral Membrane Protein 2
Uniprot ID: Q9BVW6
Function: Putative transmembrane protein with unknown specific biological role; part of the SMIM family, which includes proteins with potential roles in membrane organization or signaling .
The recombinant form of C13orf44 is produced using various expression systems, with specifications tailored for research applications.
C13orf44 recombinant protein is utilized in studies exploring transmembrane protein localization and function.
While not directly studied in the provided sources, the broader context of transmembrane proteins (e.g., MCHR1, PKD2) highlights their role in ciliary targeting. For example, short peptide sequences from transmembrane proteins can direct constructs to primary cilia in human neurons and other cell types . Although C13orf44’s specific role in ciliary targeting is unconfirmed, its recombinant form may serve as a model for studying such mechanisms.
Thermo Fisher Scientific offers truncated SMIM2 fragments (aa 1–26, 51–85) as controls for antibody validation or binding assays .
Functional Elucidation: The protein’s exact biological role remains undefined, necessitating further studies on its interactions or subcellular localization.
Ciliary Targeting: Research on transmembrane proteins like MCHR1 and PKD2 suggests potential avenues for investigating C13orf44’s involvement in ciliary pathways.
C13orf44, now commonly referred to as SMIM2 (Small Integral Membrane Protein 2), is a putative transmembrane protein predicted to function as an integral component of cellular membranes. The protein has been identified across multiple species with conserved domains suggesting evolutionary importance . Structurally, C13orf44/SMIM2 belongs to a class of small membrane proteins that typically contain one or more transmembrane domains with relatively small extracellular and intracellular portions.
When expressed recombinantly, the protein is typically tagged (often with a 6xHis tag at the C-terminus) to facilitate purification and detection in experimental systems. The human variant is expressed in mammalian cell systems to ensure proper post-translational modifications and folding essential for maintaining native protein conformation and function .
Mammalian expression systems are strongly preferred for C13orf44/SMIM2 production due to the protein's transmembrane nature and potential requirements for proper post-translational modifications. Based on current research protocols, the following expression systems have demonstrated successful production:
Expression System | Advantages | Considerations | Recommended for |
---|---|---|---|
HEK293 cells | Native folding, human PTMs | Moderate yield, higher cost | Functional studies, interaction analysis |
CHO cells | Scalable, consistent glycosylation | Regulatory approval pathway | Larger-scale production |
Expi293F cells | High yield, suspension culture | Requires specialized media | High-throughput screening |
For optimal results, the protein should be expressed with appropriate tagging strategies (typically C-terminal His tags) that minimize interference with membrane insertion while facilitating downstream purification. Expression verification should be performed via Western blotting with tag-specific or protein-specific antibodies prior to functional characterization .
Purification of membrane proteins like C13orf44/SMIM2 requires specialized approaches to maintain protein stability and functionality. The recommended purification protocol follows a multi-step approach:
Cell lysis using mild detergents (e.g., 1% DDM, 0.5% CHAPS) that effectively solubilize membranes while preserving protein structure
Affinity chromatography utilizing the His-tag, with binding buffers containing reduced detergent concentrations
Size exclusion chromatography to remove aggregates and obtain homogeneous protein preparations
Quality control assessment via SDS-PAGE and Western blotting to confirm purity (≥95% as assessed by SDS-PAGE)
For experimental applications requiring higher purity, additional ion-exchange chromatography may be incorporated between steps 2 and 3. The purified protein should be stored in stabilizing buffer conditions that maintain its native conformation, typically with appropriate detergent concentrations above their critical micelle concentration.
Functional characterization of membrane proteins like C13orf44/SMIM2 requires thoughtful experimental design that controls for various factors affecting protein behavior. Based on established experimental design principles, researchers should implement the following strategies:
Systematic variable manipulation: When investigating C13orf44/SMIM2 function, independently manipulate key variables (expression level, cellular localization, interacting partners) while controlling for confounding factors .
Selection of appropriate dependent variables: Measure multiple outcomes (protein localization, downstream signaling effects, interaction profiles) to comprehensively characterize function.
Control for extraneous variables: Account for factors like cell type-specific effects, tag interference, and expression level variation that might confound results .
Experimental validation: Employ multiple complementary techniques to validate findings:
Technique | Application | Data Output | Limitations |
---|---|---|---|
Immunofluorescence | Localization | Subcellular distribution | Antibody specificity |
Co-immunoprecipitation | Protein interactions | Binding partners | Weak/transient interactions may be missed |
CRISPR-Cas9 knockout | Loss-of-function | Phenotypic changes | Compensatory mechanisms |
Mass spectrometry | Interactome analysis | Comprehensive binding partners | Complex data interpretation |
Hypothesis formulation: Develop clear null and alternate hypotheses about C13orf44/SMIM2 function based on bioinformatic predictions and preliminary data .
When designing these experiments, researchers should incorporate proper negative controls (e.g., empty vector transfections, non-specific antibodies) and positive controls (known membrane proteins with similar characteristics) to ensure result validity.
Resolving contradictory findings in C13orf44/SMIM2 research requires systematic analysis of methodological differences and careful experimental design. When faced with contradictory data, researchers should:
Compare experimental conditions: Systematically analyze differences in expression systems, tags, purification methods, and functional assays that may explain divergent results.
Control for protein conformation: Verify that the recombinant protein maintains proper folding and membrane insertion across different experimental systems using conformation-sensitive techniques like limited proteolysis or circular dichroism.
Implement meta-analytical approaches: Synthesize findings across multiple studies, weighting results based on methodological rigor and sample size.
Design reconciliation experiments: Develop experiments specifically aimed at testing competing hypotheses under standardized conditions that bridge methodological differences between contradictory studies.
Consider context-dependent functions: Investigate whether C13orf44/SMIM2 exhibits different functions in different cellular contexts, which may explain apparently contradictory findings.
A structured approach using factorial experimental design allows systematic evaluation of how different variables interact to influence C13orf44/SMIM2 function, potentially explaining contradictory findings in the literature .
Validating the biological activity of recombinant C13orf44/SMIM2 requires multi-faceted approaches that assess both structural integrity and functional activity:
Structural validation:
Circular dichroism spectroscopy to confirm secondary structure content
Limited proteolysis to verify proper folding
Size exclusion chromatography to assess oligomeric state
Functional validation:
Membrane integration assays to confirm proper insertion into lipid bilayers
Protein-protein interaction studies via pull-down assays or surface plasmon resonance
Cell-based assays measuring downstream signaling events
Comparative analysis:
Functional comparison between recombinant protein and endogenously expressed C13orf44/SMIM2
Cross-species activity comparison to identify conserved functions
Validation experiments should include appropriate positive controls (e.g., well-characterized membrane proteins) and negative controls (e.g., denatured protein samples), with activity assessed across multiple independent protein preparations to ensure reproducibility. Researchers should verify activity using ELISA and cell culture validation as standard quality control measures .
Immunological techniques provide powerful tools for C13orf44/SMIM2 research, particularly when optimized for membrane protein analysis:
Antibody selection considerations:
Epitope location relative to transmembrane domains
Cross-reactivity with related proteins
Performance in various applications (WB, IP, IF, FACS)
Optimized immunoprecipitation protocol:
Membrane solubilization using mild detergents (0.5-1% NP-40, CHAPS, or digitonin)
Pre-clearing lysates to reduce non-specific binding
Extended incubation periods (overnight at 4°C) to capture low-abundance interactions
Flow cytometry applications:
Detection of surface-exposed epitopes using non-permeabilizing conditions
Quantification of expression levels across cell populations
Sorting of cells based on expression for downstream analysis
ELISA-based quantification:
Sandwich ELISA using capture and detection antibodies targeting different epitopes
Competitive ELISA for measuring binding interactions
Time-resolved ELISA for enhanced sensitivity
When working with recombinant tagged versions, researchers can leverage the affinity tag (e.g., His-tag) for detection and purification, complementing antibody-based approaches. Validation of antibody specificity should be performed using knockout or knockdown controls to ensure signal specificity .
Investigating protein-protein interactions involving C13orf44/SMIM2 requires specialized approaches that account for its membrane-embedded nature:
Proximity-based interaction methods:
BioID or TurboID proximity labeling to identify proteins in close proximity to C13orf44/SMIM2 in living cells
FRET/BRET analysis for real-time interaction monitoring
Split-protein complementation assays to verify direct interactions
Affinity-based methods:
Crosslinking mass spectrometry (XL-MS) with membrane-compatible crosslinkers
Co-immunoprecipitation with specialized membrane protein extraction buffers
Pull-down assays using purified recombinant protein as bait
Experimental design considerations:
Control for tag-mediated artifacts by comparing N- and C-terminally tagged constructs
Include appropriate negative controls (e.g., unrelated membrane proteins)
Validate interactions through reciprocal pull-downs
Data analysis and validation:
Implement statistical thresholding for mass spectrometry data
Validate key interactions through orthogonal methods
Assess biological relevance through functional studies
A systematic approach combining multiple complementary techniques provides the most robust characterization of C13orf44/SMIM2's interaction network. This multi-method strategy helps overcome the limitations of individual techniques, particularly for membrane proteins where interactions may be affected by the local lipid environment .
Structural characterization of membrane proteins like C13orf44/SMIM2 presents unique challenges that require specialized approaches:
These techniques should be applied in combination, as each provides complementary information about different aspects of C13orf44/SMIM2 structure and function. Researchers should consider the limitations of each method, particularly regarding sample preparation requirements and resolution limitations for membrane proteins.
Several cutting-edge technologies show promise for advancing C13orf44/SMIM2 research beyond current methodological limitations:
AlphaFold2 and structure prediction:
Application of AI-based structure prediction to generate working structural models
Integration with experimental data for hybrid structural determination
Structure-based functional hypothesis generation
Single-cell multi-omics:
Correlation of C13orf44/SMIM2 expression with transcriptomic and proteomic profiles
Identification of cell type-specific functions and regulatory networks
Characterization of expression heterogeneity in complex tissues
CRISPR-based functional genomics:
High-throughput screening using CRISPR activation/inhibition
Base editing for introducing specific mutations to test structure-function hypotheses
CRISPRi for temporal control of expression to study dynamic processes
Advanced imaging techniques:
Super-resolution microscopy for nanoscale localization studies
Live-cell single-molecule tracking to analyze dynamics
Correlative light and electron microscopy for structural contextualization
These emerging approaches, when combined with established methodologies, offer new avenues for understanding C13orf44/SMIM2 function in greater detail and may help resolve outstanding questions in the field .
Developing robust hypotheses about C13orf44/SMIM2 function requires integration of multiple evidence sources through a systematic approach:
Data integration framework:
Compile evidence from structural predictions, expression patterns, and evolutionary conservation
Apply weight-of-evidence methodology to evaluate hypothesis strength
Identify key knowledge gaps requiring experimental investigation
Computational prediction approaches:
Leverage machine learning algorithms trained on known membrane protein functions
Apply network analysis to identify potential functional pathways
Use domain-based functional prediction tools
Experimental validation pipeline:
Design experiments with clear discrimination between competing hypotheses
Implement hierarchical testing from in vitro to cellular to in vivo systems
Establish quantitative metrics for hypothesis evaluation
Evidence synthesis matrix:
Evidence Type | Strength | Limitations | Integration Approach |
---|---|---|---|
Sequence homology | Medium | Limited to conserved functions | Weighted with experimental data |
Expression correlation | Medium | Association not causation | Network analysis |
Knockdown phenotypes | High | Potential off-target effects | Validation across models |
Interaction partners | High | May include non-functional interactions | Functional enrichment analysis |
This systematic approach to hypothesis development ensures that research directions are grounded in existing evidence while identifying the most promising avenues for new discovery .