Recombinant Human Integral membrane protein 2C (ITM2C)

What is the molecular structure and basic characterization of ITM2C?

ITM2C is a type II integral transmembrane protein with the N-terminus located intracellularly and the C-terminus in either extracellular or luminal organelle domains. The protein consists of 269 amino acids with a calculated molecular weight of approximately 30,482 Da and a theoretical isoelectric point (pI) of 8.83. A notable structural feature includes a conserved N-glycosylation site at amino acid position 171 (Asn), which is preserved across all three members of the ITM2 family in both mice and humans . The protein shares 41% and 49% sequence identity with mouse ITM2A and ITM2B, respectively . ITM2C is identified in genomic databases under several external IDs including HGNC: 6175, NCBI Gene: 81618, Ensembl: ENSG00000135916, OMIM: 609554, and UniProtKB/Swiss-Prot: Q9NQX7 .

What are the primary cellular localizations and tissue expression patterns of ITM2C?

ITM2C is localized in several cellular compartments, including the Golgi apparatus, lysosomes, and the perinuclear region of the cytoplasm . Regarding tissue expression, ITM2C demonstrates a distinct pattern with highest expression in the adult brain, though it is detectable at lower levels in other tissues . This contrasts with other ITM2 family members, which show different tissue distributions. Northern blot and RT-PCR analyses have confirmed that ITM2C is particularly abundant in both adult and postimplantation embryonic brain tissues . This expression pattern suggests specialized neurological functions that may differ from its family counterparts.

What distinguishes ITM2C from other members of the ITM2 family?

The ITM2 family consists of three members (ITM2A, ITM2B, and ITM2C), which share structural similarities but exhibit distinct functional and expression characteristics. While ITM2C shares moderate sequence homology with ITM2A (41%) and ITM2B (49%), it demonstrates unique tissue expression patterns . Unlike its family counterparts, ITM2C is predominantly expressed in brain tissues. Additionally, while ITM2A has been identified as a potential tumor suppressor in certain cancers like breast cancer , the tumor-related functions of ITM2C are still being elucidated, with emerging evidence suggesting a role in colorectal cancer biomarkers . The conserved N-glycosylation site across all family members suggests shared post-translational modification mechanisms despite their functional divergence.

What are the challenges and optimal approaches for recombinant ITM2C expression?

Expressing recombinant membrane proteins like ITM2C presents significant challenges due to the hydrophobic nature of their transmembrane segments, which can lead to protein aggregation and misfolding . When using E. coli as an expression host, researchers should consider these key methodological approaches:

• Moderated expression levels: Excessive expression often saturates the membrane protein biogenesis pathway, leading to cell death or inclusion body formation. The Lemo21(DE3) strain is recommended as it allows tunable T7 expression .

• Expression system selection: The choice between prokaryotic and eukaryotic expression systems should be guided by the research objectives. E. coli systems offer simplicity and high yield but may compromise proper folding and post-translational modifications. Mammalian cell lines provide better folding environments but with lower yields.

• Fusion tag optimization: Testing different solubility-enhancing tags such as MBP, SUMO, or TrxA can improve folding and solubility.

• Detergent screening: A systematic evaluation of detergents for solubilization is critical, as different membrane proteins require specific detergent environments.

How should researchers optimize ITM2C purification protocols?

Purification of ITM2C requires careful consideration of its membrane protein characteristics. The following methodological approach is recommended:

• Initial solubilization: Select mild detergents like DDM or CHAPS that maintain protein stability while effectively extracting ITM2C from membranes.

• Affinity chromatography: Utilize His-tag or other affinity tags for initial capture, with optimized imidazole gradients to reduce non-specific binding.

• Size exclusion chromatography: This critical step separates monomeric ITM2C from aggregates and confirms proper folding through evaluation of elution profiles.

• Stability assessment: Monitor protein stability through thermal shift assays or limited proteolysis to optimize buffer conditions for long-term storage.

• Functional validation: Verify the purified protein's functionality through binding assays with known partners such as amyloid-beta peptides.

The purification protocol should be iteratively refined based on yield, purity, and retained biological activity measurements.

What approaches are effective for detecting endogenous ITM2C expression?

Researchers investigating endogenous ITM2C expression should consider the following methods, depending on their specific research objectives:

• Quantitative RT-PCR: This method has successfully identified ITM2C transcripts in various tissues, with highest expression detected in brain tissues . For effective qRT-PCR analysis, researchers should design primers spanning exon junctions to avoid genomic DNA amplification.

• Northern blot analysis: This technique has demonstrated a single ~2.1 kb ITM2C transcript with varying levels across tissues . Proper RNA integrity verification and loading controls are essential.

• Immunohistochemistry: When performing IHC, researchers should validate antibody specificity given the sequence similarities between ITM2 family members.

• Western blotting: This method can detect the ~30 kDa ITM2C protein, with attention to potential glycosylation-induced size shifts.

• RNA-Seq analysis: For comprehensive expression profiling, RNA-Seq offers advantages in detecting splice variants and providing absolute quantification, as demonstrated in colorectal cancer studies .

What is the emerging role of ITM2C in cancer biomarker research?

Recent studies have identified ITM2C as part of a three-gene signature (alongside CA2 and CA7) with significant potential for early colorectal cancer (CRC) detection . The methodological significance of this finding is considerable:

This emerging evidence positions ITM2C as a promising component in cancer biomarker panels, particularly for colorectal cancer, with potential applications in early diagnosis and prognostication.

How does ITM2C contribute to neurological function and pathology?

ITM2C's predominant expression in brain tissues suggests specialized neurological functions . Its involvement in neurological processes includes:

• Amyloid-beta regulation: ITM2C functions as a negative regulator of amyloid-beta peptide production by inhibiting APP processing, suggesting a neuroprotective role against amyloid-related pathologies .

• Neurodevelopmental regulation: ITM2C is involved in the negative regulation of neuron projection development and neuron differentiation, indicating its importance in brain development and neural circuit formation .

• Potential roles in neurodegenerative diseases: Given its association with amyloid-beta binding and processing, ITM2C may have implications for conditions like Alzheimer's disease and Cerebral Amyloid Angiopathy .

Researchers investigating ITM2C in neurological contexts should consider both its developmental roles and potential contributions to pathological processes in their experimental designs.

What experimental models are most appropriate for studying ITM2C function in disease contexts?

When investigating ITM2C's role in disease pathology, researchers should consider these methodological approaches:

• Cell line selection:

  • Neuronal cell lines (SH-SY5Y, primary neurons) for studying amyloid-beta processing

  • Colorectal cancer cell lines (HCT116, SW480) for investigating cancer biomarker potential

  • Stable overexpression and knockdown models to evaluate functional consequences

• Animal models:

  • Transgenic mice with ITM2C overexpression or knockout to assess neurodevelopmental and amyloid processing effects

  • Patient-derived xenograft models for cancer studies

  • Conditional expression systems to study temporal aspects of ITM2C function

• Disease-specific assays:

  • Amyloid-beta production and aggregation assays for neurodegenerative disease studies

  • Migration, invasion, and proliferation assays for cancer studies

  • Transcriptome and proteome profiling to identify pathway alterations

The selection of experimental models should be guided by the specific disease context and research questions being addressed.

How can structural biology approaches illuminate ITM2C function?

Understanding the structural basis of ITM2C function requires sophisticated methodological approaches:

• Cryo-electron microscopy (Cryo-EM): Particularly valuable for membrane proteins like ITM2C, Cryo-EM can reveal structural details without the need for crystallization. Sample preparation should utilize nanodiscs or amphipols to maintain native-like membrane environments.

• X-ray crystallography: Though challenging for membrane proteins, this approach can provide atomic-resolution structures. Researchers should focus on:

  • Screening multiple detergents for crystal formation

  • Incorporating fusion partners like T4 lysozyme to increase soluble domains

  • Testing lipidic cubic phase crystallization methods

• NMR spectroscopy: Solution and solid-state NMR can provide dynamic information about ITM2C's interaction with binding partners like amyloid-beta peptides.

• Molecular dynamics simulations: These computational approaches can model ITM2C's behavior in membranes and predict conformational changes associated with its function.

• Cross-linking mass spectrometry: This method can identify interaction surfaces between ITM2C and its binding partners, providing insights into functional mechanisms.

What bioinformatic strategies can enhance ITM2C functional analysis?

Advanced bioinformatic approaches can significantly enhance ITM2C research:

• Machine learning for biomarker discovery: As demonstrated in colorectal cancer research, algorithms such as Random Forest and Support Vector Machine can be applied to identify ITM2C-containing gene signatures with diagnostic potential . Critical methodological considerations include:

  Algorithm	TCGA-CRC Accuracy (%)	GSE50760 Accuracy (%)
  Adaboost	99.94	94.16
  Random Forest	100	94.44
  Gaussian Naive Bayes	99.93	93.21
  SVM	100	93.40
  Linear Regression	100	92.12

• Network analysis: Protein-protein interaction networks centered on ITM2C can reveal functional associations and pathway connections.

• Phylogenetic analysis: Evolutionary conservation patterns across species can highlight functionally important domains and residues.

• Structural prediction: Tools like AlphaFold2 can generate structural predictions that inform experimental design, particularly for protein engineering approaches.

• Transcriptome integration: Correlating ITM2C expression with genome-wide expression patterns can identify co-regulated genes and functional pathways.

How should researchers interpret contradictory data about ITM2C function?

When faced with seemingly contradictory results regarding ITM2C function, researchers should apply these methodological approaches:

• Context-dependent analysis: Recognize that ITM2C may have different functions in different tissues or cellular contexts. Systematically document the experimental conditions, cell types, and disease models used in conflicting studies.

• Technical validation: Evaluate whether differences arise from technical variables:

  • Antibody specificity issues (confirm with multiple antibodies or orthogonal techniques)

  • Expression level artifacts (physiological vs. overexpression)

  • Tagged vs. untagged protein behaviors

• Isoform consideration: Determine if contradictions stem from different ITM2C isoforms or post-translational modifications.

• Integrated meta-analysis: Apply statistical approaches to integrate multiple datasets, weighting evidence based on methodological rigor.

• Mechanistic reconciliation: Develop testable hypotheses that could explain apparently contradictory observations, particularly considering ITM2C's multiple cellular localizations and potential for context-dependent functions.

How can single-cell technologies advance our understanding of ITM2C function?

Single-cell approaches offer unprecedented opportunities to explore ITM2C biology:

• Single-cell RNA sequencing: This technique can reveal cell-type-specific expression patterns of ITM2C in heterogeneous tissues like brain or tumors, providing insights into its role in specific cellular subpopulations.

• Spatial transcriptomics: Methods like Visium or MERFISH can map ITM2C expression within tissue architectures, revealing spatial relationships that may inform function.

• Single-cell proteomics: Emerging technologies for single-cell protein analysis can detect ITM2C protein levels and post-translational modifications at the individual cell level.

• Live-cell imaging: Advanced microscopy combined with fluorescent tagging can track ITM2C dynamics in real-time within living cells.

• CyTOF and spectral flow cytometry: These methods can correlate ITM2C expression with numerous other cellular markers to identify functional relationships.

What is the potential therapeutic relevance of ITM2C in disease contexts?

Emerging evidence suggests several potential therapeutic applications related to ITM2C:

• Neurodegenerative disease applications: Given ITM2C's role in amyloid-beta regulation , therapeutic strategies could include:

  • Modulating ITM2C expression or activity to influence amyloid processing

  • Developing mimetic peptides based on ITM2C's functional domains

  • Targeting ITM2C-mediated signaling pathways

• Cancer biomarker applications: The diagnostic potential of ITM2C in colorectal cancer suggests applications such as:

  • Development of minimally invasive screening tests

  • Monitoring treatment response using ITM2C expression

  • Stratifying patients for personalized treatment approaches

• Drug delivery applications: ITM2C's specific expression pattern could be leveraged for targeted delivery of therapeutics to brain tissues.

How might gene editing approaches contribute to ITM2C research?

CRISPR-Cas9 and related technologies offer powerful tools for investigating ITM2C:

• Knockout models: Generation of ITM2C-null cell lines and animal models to assess loss-of-function phenotypes, with careful consideration of potential compensation by other ITM2 family members.

• Knock-in strategies: Introduction of tagged versions or specific mutations at the endogenous locus to study protein localization and variant effects.

• CRISPRi/CRISPRa approaches: Reversible modulation of ITM2C expression to study dosage effects without complete ablation.

• Base and prime editing: Precise introduction of disease-associated variants to create cellular models of pathological conditions.

• CRISPR screens: Genome-wide or targeted screens to identify genetic interactors or synthetic lethal partners of ITM2C.