Recombinant Mouse Transmembrane and coiled-coil domains protein 1 (Tmcc1)

What is the basic structure of mouse TMCC1 and how does it compare to human TMCC1?

Mouse TMCC1, like its human counterpart, belongs to the transmembrane and coiled-coil domain family, which consists of at least three conserved proteins (TMCC1-3). The protein contains two adjacent transmembrane domains near the C-terminus and characteristic coiled-coil domains. The transmembrane domains are responsible for targeting TMCC1 to the endoplasmic reticulum . The structure is highly conserved across species, with the N-terminal fragment (amino acids 1-200) being unique among TMCC family members in humans, which allows for specific antibody generation against this region .

The protein adopts a specific topology where both the N-terminal region and C-terminal tail reside in the cytoplasm, with the transmembrane domains spanning the ER membrane. This topology has been confirmed through multiple experimental approaches including protease protection assays and selective membrane permeabilization studies .

What are the known functions of TMCC1 in cellular physiology?

TMCC1 functions primarily as an ER organizational protein. Research indicates that TMCC1 plays a significant role in maintaining the structure of the rough ER, as evidenced by ER deformation observed in cells expressing high levels of either full-length TMCC1 or just the transmembrane domains .

The protein associates with ribosomal proteins through its cytosolic region, suggesting involvement in protein synthesis regulation at the rough ER . Additionally, TMCC1's ability to dimerize or oligomerize with other TMCC family members through its large coiled-coil domain suggests a potential scaffolding function in organizing protein complexes at the ER membrane .

Recent research has also identified a circular RNA derived from the Tmcc1 gene (circTmcc1) that regulates astrocyte function, particularly glutamate metabolism, with implications for cognitive function in conditions like hepatic encephalopathy .

How does TMCC1 localize to the endoplasmic reticulum?

TMCC1 localizes specifically to the rough ER through its C-terminal transmembrane domains (amino acids 571-653). Experimental evidence shows that this region is both necessary and sufficient for proper ER targeting . When GFP-tagged full-length TMCC1 is expressed at low levels in cells, it displays a distribution pattern identical to established ER markers like calnexin .

Interestingly, each of the two transmembrane domains (TMCC1 571-615 and TMCC1 615-653) independently possesses ER-targeting properties, as demonstrated by their colocalization with calnexin when expressed separately . This suggests a redundant mechanism ensuring proper ER localization.

Biochemical fractionation studies further confirm TMCC1's rough ER localization, as it displays the same distribution pattern as established rough ER markers CLIMP-63 and ribosomal protein RPL4 in sucrose gradient fractionation, distinguishing it from general ER proteins like BAP31 .

What are the most effective methods for detecting endogenous TMCC1 in mouse tissues?

For detecting endogenous TMCC1 in mouse tissues, immunoblotting and immunofluorescence microscopy using specific antibodies represent the most reliable approaches. Based on the literature, polyclonal antibodies against the N-terminal fragment (amino acids 1-200) of TMCC1 have been successfully generated and shown to specifically recognize endogenous TMCC1 in western blotting experiments .

For immunofluorescence detection, fixation with paraformaldehyde followed by permeabilization with Triton X-100 provides optimal results. When studying TMCC1's topology, researchers have effectively used differential permeabilization techniques comparing digitonin (which selectively permeabilizes the plasma membrane) with Triton X-100 (which permeabilizes all cellular membranes) .

For validating antibody specificity, siRNA-mediated knockdown serves as an excellent control. In previous studies, anti-TMCC1 antibodies showed greater than 80% reduction in signal intensity in cells transfected with TMCC1 siRNAs, confirming specificity .

How can researchers effectively express and purify recombinant mouse TMCC1 for experimental studies?

For expression and purification of recombinant mouse TMCC1, researchers should consider the following methodological approach:

• Expression system selection: Mammalian expression systems such as HEK293T cells are recommended for full-length TMCC1 to ensure proper folding and post-translational modifications. For specific domains like the N-terminal fragment (1-200), bacterial expression systems may be sufficient .

• Tag selection: N-terminal tags (GFP, FLAG) are preferable since the C-terminus contains transmembrane domains critical for localization. Previous studies have successfully used both GFP and FLAG tags at the N-terminus without disrupting TMCC1 function .

• Purification strategy: For membrane proteins like TMCC1, a two-step purification process is recommended:

  • Membrane fraction isolation

  • Detergent solubilization (mild non-ionic detergents like DDM or CHAPS)

  • Affinity chromatography based on the chosen tag

• Quality control: Verify purified protein by SDS-PAGE, western blotting, and mass spectrometry. Functional validation can include testing the ability of the recombinant protein to associate with binding partners identified in previous studies .

What approaches are recommended for studying TMCC1 topology in the endoplasmic reticulum?

Understanding TMCC1's topology in the ER membrane requires multiple complementary approaches:

• Differential permeabilization immunofluorescence: Fix cells with paraformaldehyde followed by selective permeabilization with either digitonin (plasma membrane only) or Triton X-100 (all membranes). This technique revealed that both N-terminal GFP-tagged and C-terminal GFP-tagged TMCC1 were detectable in digitonin-permeabilized cells, indicating cytoplasmic orientation of both termini .

• Protease protection assays: Permeabilize cells with digitonin followed by trypsin treatment. TMCC1 degradation by trypsin confirms cytoplasmic orientation. This method effectively demonstrated that TMCC1's N-terminus resides in the cytoplasm, as it was digested by trypsin under conditions where lysosomal proteins remained protected .

• Glycosylation mapping: Though not explicitly mentioned in the provided references, introducing N-glycosylation sites at various positions can help map protein topology since glycosylation occurs only on ER luminal domains.

• Fluorescence protease protection assay: This real-time imaging technique can provide dynamic information about membrane protein topology in living cells.

Based on these approaches, researchers established that both the N-terminal region and C-terminal tail of TMCC1 reside in the cytoplasm, with the transmembrane domains spanning the ER membrane .

What methods are most effective for identifying TMCC1 protein-protein interactions?

Several complementary approaches have proven effective for studying TMCC1 protein-protein interactions:

• Co-immunoprecipitation (Co-IP): This remains the gold standard for detecting physiologically relevant protein interactions. Previous studies successfully demonstrated TMCC1-TMCC1 interactions and TMCC1 interactions with other TMCC family members using Co-IP approaches in HEK293T cells transfected with tagged constructs .

• Pull-down assays: Using purified recombinant domains of TMCC1 to identify direct binding partners. The coiled-coil domains are particularly important for protein interactions, as demonstrated by pull-down experiments showing that only fragments containing the large coiled-coil domain (amino acids 460-575) interacted with full-length TMCC1 .

• Proximity-based labeling: Though not explicitly mentioned in the provided references, BioID or APEX2 fusions with TMCC1 would allow identification of proximal proteins in the native cellular environment.

• Crosslinking mass spectrometry: For capturing transient interactions and mapping interaction interfaces at amino acid resolution.

Based on these approaches, researchers have established that TMCC1 can form homo-oligomers and hetero-oligomers with other TMCC family members through its large coiled-coil domain adjacent to the C-terminus .

How does TMCC1 interact with other TMCC family members and what are the functional implications?

TMCC1 can dimerize or oligomerize not only with itself but also with other TMCC family members (TMCC2 and TMCC3). Co-immunoprecipitation experiments demonstrated that both GFP-TMCC2 and GFP-TMCC3 could be pulled down with endogenous TMCC1 . These interactions are mediated through the large coiled-coil domain adjacent to the C-terminus, which is highly conserved among TMCC family members .

The functional implications of these interactions include:

• ER structural organization: The ability to form higher-order complexes likely contributes to organizing ER membrane domains. High expression levels of TMCC1 cause ER deformation, suggesting a structural role .

• Regulation of protein complexes: TMCC proteins may serve as scaffolds, bringing together different protein complexes at the ER membrane.

• Functional redundancy: The ability of TMCC family members to interact with each other suggests potential redundancy in function, which may explain why genetic studies have found it challenging to attribute specific phenotypes to TMCC1 mutations alone .

• Specialized cell-type functions: Different expression patterns of TMCC family members in different tissues may allow for tissue-specific regulation of ER functions.

What role does TMCC1 play in ribosomal association and protein synthesis at the rough ER?

TMCC1 associates with ribosomal proteins through its cytosolic region, suggesting involvement in protein synthesis regulation at the rough ER . This association is supported by several lines of evidence:

• Subcellular fractionation: TMCC1 shows the same distribution pattern as the ribosomal protein RPL4 in sucrose gradient fractionation experiments .

• Colocalization studies: TMCC1 colocalizes with Sec61α, a component of the translocon complex that associates tightly with membrane-bound ribosomes .

• Functional domains: The cytosolic domains of TMCC1 likely mediate interactions with ribosomal proteins, though the specific binding interfaces remain to be fully characterized.

The potential functional implications of TMCC1-ribosome associations include:

• Spatial organization: TMCC1 may help organize ribosomes at specific ER domains, potentially influencing which mRNAs are translated.

• Translation efficiency: By interacting with ribosomal proteins, TMCC1 might influence the efficiency of protein synthesis for specific subsets of proteins.

• ER stress responses: TMCC1 could potentially play a role in regulating translation during ER stress conditions, though this hypothesis requires further investigation.

What is the relationship between circTmcc1 and hepatic encephalopathy?

Circular RNA Tmcc1 (circTmcc1) has been identified as a significant player in hepatic encephalopathy-induced cognitive dysfunction. Research in a bile duct ligation (BDL) mouse model of hepatic encephalopathy revealed specific expression changes of circTmcc1 in the brain cortex .

Hepatic encephalopathy causes hyperammonemia, which alters astrocytic glutamate metabolism in the brain, contributing to cognitive decline. circTmcc1 appears to regulate the expression of genes associated with intracellular metabolism and astrocyte function in this condition .

Specifically, circTmcc1 binds with the NF-κB p65-CREB transcriptional complex and regulates the expression of the astrocyte transporter EAAT2, which is critical for glutamate clearance . Through this mechanism, circTmcc1 influences glutamate metabolism in astrocytes and subsequently modulates spatial memory by mediating neuronal synaptic plasticity .

This research suggests that circTmcc1 may be a promising candidate for targeted interventions to prevent and treat the neuropathophysiological complications of hepatic encephalopathy .

How does circTmcc1 modulate astrocyte function in hyperammonemic conditions?

In hyperammonemic conditions, circTmcc1 plays a crucial role in modulating astrocyte function through several mechanisms:

• Regulation of EAAT2 expression: circTmcc1 binds to the NF-κB p65-CREB transcriptional complex to regulate the expression of the astrocytic glutamate transporter EAAT2 . This transporter is essential for maintaining appropriate glutamate levels in the brain.

• Modulation of inflammatory responses: circTmcc1 contributes to the secretion of proinflammatory mediators in astrocytes under hyperammonemic conditions . This inflammatory response is a key component of hepatic encephalopathy pathophysiology.

• Regulation of glutamate metabolism: circTmcc1 influences the glutamate-glutamine cycle in astrocytes, which becomes altered during hyperammonemic conditions . In the CNS, astrocytes are the only cell type that removes excess ammonia, and this process affects glutamate handling.

These functions were investigated using in vitro models where cells were treated with 20 mM ammonium chloride (NH₄Cl) for 24 hours to induce hyperammonemic conditions similar to those observed in hepatic encephalopathy .

What experimental approaches are recommended for studying circTmcc1 function in neural tissues?

Based on the research methodologies described, the following experimental approaches are recommended for studying circTmcc1 function in neural tissues:

• RNA sequencing and bioinformatic analysis:

  • Use tools like FastQc for quality control of RNA-seq reads

  • STAR aligner for genome alignment

  • Cuffnorm for calculating FPKM values

  • Salmon quantifier and edgeR for differential expression analysis

  • Exclude genes with average FPKM values less than 1

• Transcription factor prediction and analysis:

  • BART (http://bartweb.org/) and ChEA3 (http://maayanlab.cloud/chea3/) for identifying transcription factors involved in circTmcc1-mediated regulation

  • RPISeq (http://pridb.gdcb.iastate.edu/RPISeq/) for predicting RNA-protein interactions

• In vitro modeling of hyperammonemia:

  • Culture of appropriate cell lines (such as astrocytic cell lines) in DMEM with appropriate supplements

  • Treatment with 20 mM NH₄Cl for 24 hours to induce hyperammonemic conditions

• Functional assays:

  • Evaluation of glutamate uptake and metabolism

  • Assessment of inflammatory mediator production

  • Analysis of effects on synaptic plasticity in co-culture systems with neurons

• In vivo modeling:

  • Bile duct ligation (BDL) mouse model of hepatic encephalopathy

  • Behavioral testing to assess cognitive function and spatial memory

These approaches provide a comprehensive framework for investigating the complex roles of circTmcc1 in neural tissues under both normal and pathological conditions.

What controls should be included when studying TMCC1 localization and function?

When designing experiments to study TMCC1 localization and function, researchers should include several essential controls:

• Antibody specificity controls:

  • Pre-immune serum comparisons - critical for validating polyclonal antibodies

  • siRNA-mediated knockdown - signal reduction confirms antibody specificity

  • Peptide competition assays - pre-incubation with immunizing peptide should abolish specific signals

• Localization controls:

  • Co-staining with established ER markers (calnexin, Sec61α) to confirm ER localization

  • Comparison with markers for other organelles (mitochondria, Golgi) to confirm specificity

  • Expression level controls - overexpression may alter localization patterns and cause ER deformation

• Functional controls:

  • Domain deletion/mutation constructs - particularly important when studying the role of transmembrane domains or coiled-coil regions

  • Other TMCC family members - to distinguish TMCC1-specific effects from general TMCC family functions

  • Cell type comparisons - to identify cell-type-specific functions

• Technical controls:

  • For differential permeabilization experiments: positive controls like cathepsin D (protected by lysosomal membrane) and negative controls (cytoplasmic proteins)

  • For protein-protein interaction studies: non-interacting protein fragments like TMCC1(571-653) that do not contain interaction domains

How can researchers effectively study the oligomerization of TMCC1 proteins?

To effectively study TMCC1 oligomerization, researchers should consider multiple complementary approaches:

• Co-immunoprecipitation with differently tagged constructs:

  • Express combinations of GFP-tagged and FLAG-tagged TMCC1 constructs

  • Immunoprecipitate with anti-FLAG and detect GFP-TMCC1 by western blotting

  • Include domain deletion constructs to map interaction regions (the large coiled-coil domain is critical)

• Size exclusion chromatography:

  • Analyze the molecular weight of native TMCC1 complexes

  • Compare with predicted monomeric weight to determine oligomeric state

• Crosslinking approaches:

  • Chemical crosslinking followed by SDS-PAGE to capture transient interactions

  • In-cell crosslinking to preserve native oligomeric states

• Fluorescence techniques:

  • Förster resonance energy transfer (FRET) between differently labeled TMCC1 molecules

  • Fluorescence recovery after photobleaching (FRAP) to assess dynamics of oligomerization

• Analytical ultracentrifugation:

  • Determine stoichiometry and binding affinities of purified TMCC1

Previous research has demonstrated that TMCC1 can form homo-oligomers and hetero-oligomers with TMCC2 and TMCC3, with the large coiled-coil domain (amino acids 460-575) being essential for these interactions .

What considerations are important when designing experiments involving circTmcc1?

When designing experiments involving circTmcc1, researchers should consider several important factors:

• RNA detection and quantification:

  • Design divergent primers that span the back-splice junction to specifically amplify circular RNA

  • Include RNase R treatment to enrich for circular RNAs by degrading linear RNAs

  • Use appropriate normalization controls that are not affected by the experimental conditions

• Expression manipulation:

  • Design siRNAs or shRNAs that specifically target the back-splice junction of circTmcc1

  • Consider using CRISPR-based approaches to delete splice sites required for circTmcc1 formation

  • For overexpression, use minigene constructs containing the necessary exons and flanking introns

• Functional analysis:

  • When studying transcriptional regulation, use tools like BART and ChEA3 to identify involved transcription factors

  • For RNA-protein interactions, use tools like RPISeq and validate predictions experimentally

  • Include appropriate cell models - for hepatic encephalopathy studies, use ammonium chloride treatment (20 mM NH₄Cl for 24h) to mimic hyperammonemic conditions

• Data analysis considerations:

  • For RNA-seq, exclude genes with average FPKM values less than 1

  • Select differentially expressed genes with log2 fold change more than 0.5 or less than -0.5

  • Use multiple bioinformatic approaches and integrate results for more robust findings

• Validation in relevant models:

  • Consider both in vitro cell models and in vivo animal models (such as bile duct ligation models for hepatic encephalopathy)

  • Include behavioral testing when studying cognitive effects

How should researchers interpret conflicting data regarding TMCC1 localization?

When faced with conflicting data regarding TMCC1 localization, researchers should consider several factors:

• Expression level effects: High expression levels of TMCC1 can cause ER deformation and clustering of ER markers like calnexin . Therefore, comparing low versus high expression studies may naturally yield different results.

• Cell type differences: Different cell types may show variation in TMCC1 localization patterns due to differences in ER structure and composition. Compare results across multiple cell types and prioritize findings in physiologically relevant cells.

• Detection method variations: Different antibodies or tagging strategies may yield different results:

  • N-terminal versus C-terminal tags may affect localization

  • Different fixation and permeabilization protocols may reveal different aspects of localization

  • The specificity of antibodies should be thoroughly validated

• Dynamic localization possibilities: TMCC1 localization may change under different cellular conditions or states:

  • Cell cycle stage

  • ER stress conditions

  • Differentiation state

• Resolution of microscopy techniques: Higher resolution techniques like super-resolution microscopy may reveal subdomains of localization not visible with standard confocal microscopy.

To resolve conflicts, combine multiple complementary approaches including:

• Biochemical fractionation

• Immunofluorescence with differential permeabilization

• Protease protection assays

• Electron microscopy for ultrastructural localization

What are common challenges in studying TMCC1 protein-protein interactions and how can they be addressed?

Studying TMCC1 protein-protein interactions presents several challenges that can be addressed with specific strategies:

• Membrane protein solubilization issues:

  • Challenge: Transmembrane domains can aggregate during solubilization

  • Solution: Optimize detergent type and concentration; consider using digitonin or CHAPS for milder extraction

• Distinguishing direct from indirect interactions:

  • Challenge: Co-IP may pull down entire complexes rather than direct binding partners

  • Solution: Use purified recombinant proteins for in vitro binding assays; consider crosslinking mass spectrometry to map interaction interfaces

• Capturing transient interactions:

  • Challenge: Some interactions may be dynamic or weak

  • Solution: Use crosslinking approaches; consider proximity labeling methods (BioID, APEX2)

• Overexpression artifacts:

  • Challenge: Overexpressed proteins may form non-physiological interactions

  • Solution: Validate interactions at endogenous expression levels; use CRISPR knock-in tags

• Domain-specific interactions:

  • Challenge: Determining which domains mediate specific interactions

  • Solution: Use domain mapping with truncation constructs as demonstrated for the coiled-coil domain of TMCC1

• Functional relevance verification:

  • Challenge: Determining if interactions have functional consequences

  • Solution: Design mutations that specifically disrupt interactions without affecting other properties; assess functional outcomes

Previous research successfully demonstrated TMCC1 interactions using co-IP approaches with tagged constructs and careful domain mapping, establishing the large coiled-coil domain (amino acids 460-575) as critical for both homo-oligomerization and hetero-oligomerization with other TMCC family members .

How should researchers approach data analysis when studying circTmcc1 expression in disease models?

When analyzing data related to circTmcc1 expression in disease models, researchers should consider the following approaches:

• RNA-seq data analysis pipeline:

  • Use multiple analysis methods to ensure robust results:

    • STAR aligner with Cuffnorm for FPKM calculation

    • Salmon quantifier with edgeR for differential expression analysis

  • Apply appropriate filtering criteria:

    • Exclude genes with average FPKM values less than 1

    • Select genes with log2 fold change more than 0.5 or less than -0.5

• Biological replication and statistical analysis:

  • Ensure adequate biological replicates (minimum n=3)

  • Apply appropriate statistical tests (e.g., Student's t-test) with multiple testing correction

  • Report both p-values and effect sizes

• Validation of circular RNA specificity:

  • Confirm back-splicing events using divergent primers

  • Verify resistance to RNase R treatment compared to linear RNAs

  • Use Northern blotting to confirm the expected size of circular RNA

• Integration of multiple data types:

  • Combine transcriptomic data with protein expression data

  • Correlate circTmcc1 levels with functional outcomes (e.g., glutamate metabolism, cognitive performance)

  • Use bioinformatic tools to predict RNA-protein interactions (e.g., RPISeq) and transcription factor binding (e.g., BART, ChEA3)

• Consideration of heterogeneity in disease models:

  • Compare results across different models of the same disease

  • Account for disease progression and severity

  • Consider cell-type-specific effects within complex tissues

By following these approaches, researchers can generate more reliable and biologically meaningful interpretations of circTmcc1 expression data in disease models, particularly in the context of hepatic encephalopathy and related neurological disorders .