Recombinant Bovine Coiled-coil domain-containing protein 167 (CCDC167)

What is the basic structure of Bovine CCDC167?

Bovine Coiled-coil domain-containing protein 167 (CCDC167) is a 97-amino acid protein characterized by its coiled-coil structural motifs. The full amino acid sequence is MTKKKRENLGVALEIDGLEKKLSQCRRDLEVVNSRLCGVELSSEARRSLEKEKSSLMNKASNYEKELKLLRQENRKNMLLSVAIFLLLTVIYAYWAL . As its name suggests, the protein contains coiled-coil domains, which are structural motifs where multiple alpha-helices are coiled together like strands of a rope. This structural arrangement plays an important role in protein-protein interactions and may contribute to the protein's functional properties in cellular processes. The protein is encoded by the CCDC167 gene, with UniProt ID A1A4P9 .

How is Recombinant Bovine CCDC167 typically produced for research?

Recombinant Bovine CCDC167 is typically produced using bacterial expression systems, with E. coli being the predominant host . The full-length protein (amino acids 1-97) is expressed with an N-terminal His-tag to facilitate purification. The expression process involves cloning the CCDC167 coding sequence into an appropriate bacterial expression vector, transforming the construct into competent E. coli cells, inducing protein expression, and subsequently purifying the protein using affinity chromatography that targets the His-tag. The purified protein is typically obtained at greater than 90% purity as determined by SDS-PAGE analysis . This recombinant production method allows researchers to obtain sufficient quantities of the protein for structural, functional, and interaction studies.

What are the optimal storage and handling conditions for maintaining CCDC167 stability?

Recombinant CCDC167 requires specific storage and handling conditions to maintain stability and biological activity. The protein is typically supplied as a lyophilized powder in a Tris/PBS-based buffer containing 6% trehalose at pH 8.0 . For long-term storage, the protein should be kept at -20°C to -80°C. When preparing working stocks, it is recommended to:

• Briefly centrifuge the vial before opening to bring contents to the bottom

• Reconstitute the protein in deionized sterile water to a concentration of 0.1-1.0 mg/mL

• Add glycerol to a final concentration of 5-50% (50% is often recommended)

• Aliquot the solution to avoid repeated freeze-thaw cycles

Working aliquots can be stored at 4°C for up to one week, but repeated freezing and thawing should be strictly avoided as it can compromise protein integrity . These careful storage protocols are essential for preserving the structural and functional characteristics of the protein for experimental applications.

What experimental approaches are recommended for studying CCDC167 function?

For investigating CCDC167 function, several complementary experimental approaches are recommended based on current research methodologies:

• Gene Expression Analysis: Quantitative PCR (qPCR) can be used to measure CCDC167 mRNA levels across different tissues or cell lines, as demonstrated in breast cancer research where MCF-7 cells showed the highest expression compared to other breast cancer cell lines .

• Gene Knockdown/Overexpression Studies: Transfection with CCDC167-targeted shRNA plasmids for knockdown or CCDC167-overexpressing vectors can help elucidate the protein's role in cellular processes. These approaches have successfully demonstrated CCDC167's influence on cell proliferation in breast cancer models .

• Proliferation Assays: Both short-term (MTT assay) and long-term (colony formation assay) proliferation assays can reveal the functional impact of CCDC167 expression modulation .

• Bioinformatic Analyses: Co-expression analyses using databases like METABRIC and TCGA, followed by Gene Ontology enrichment analysis through platforms like MetaCore, can identify functional networks and pathways associated with CCDC167 .

These methods provide complementary insights into CCDC167's biological roles and can be adapted based on specific research questions.

How can researchers effectively perform CCDC167 knockdown experiments?

Based on published methodologies, researchers can effectively perform CCDC167 knockdown experiments following these steps:

• shRNA Design and Selection: Design short hairpin RNAs (shRNAs) specifically targeting the CCDC167 transcript. Multiple shRNA sequences may be tested to identify those with optimal knockdown efficiency.

• Vector Selection: Choose appropriate expression vectors (such as those available from RNAi Core facilities) that contain suitable promoters and selection markers.

• Transfection: Transfect target cells (such as MCF-7 for breast cancer studies) with the CCDC167-shRNA plasmids using established transfection protocols. Include vector controls in parallel experiments.

• Validation of Knockdown Efficiency: Use qPCR to confirm reduction in CCDC167 mRNA expression. In published studies, significant reductions in CCDC167 mRNA were observed upon transfection with shCCDC167 plasmids .

• Functional Assays: Following confirmed knockdown, assess phenotypic changes using relevant assays. For example, in cancer studies, researchers should examine cell proliferation (MTT assay), long-term growth (colony formation assay), and expression of cell cycle-related and apoptosis-related genes .

This methodological approach provides a comprehensive framework for investigating the functional consequences of CCDC167 depletion in cellular models.

What analytical techniques are most informative for characterizing CCDC167 interactions?

To characterize CCDC167 protein interactions comprehensively, researchers should consider a multi-tiered analytical approach:

• Co-immunoprecipitation (Co-IP): This technique can identify direct protein-protein interactions with CCDC167, particularly focusing on predicted interaction partners from bioinformatic analyses.

• Proximity Ligation Assays: These assays can visualize and quantify protein interactions in situ, providing spatial information about where CCDC167 interactions occur within cells.

• Co-expression Network Analysis: Computational approaches using large datasets (as demonstrated with METABRIC and TCGA databases) can identify genes consistently co-expressed with CCDC167, suggesting functional relationships .

• Pathway Mapping: Integration of interaction data with pathway analysis tools can contextualize CCDC167's role within cellular signaling networks. Research has shown CCDC167 is involved in cell cycle-related signaling pathways .

• Structural Studies: Given CCDC167's coiled-coil domains, techniques like X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy could provide insights into the structural basis of its interactions.

These complementary approaches can collectively build a comprehensive understanding of CCDC167's interactome and functional networks.

What evidence connects CCDC167 to cancer progression?

Multiple lines of evidence connect CCDC167 to cancer progression, particularly in breast cancer:

• Expression Correlation: Bioinformatic analyses have revealed that CCDC167 is significantly upregulated in breast ductal carcinoma compared to normal breast tissue. This pattern was observed in both the METABRIC dataset and other data sources for invasive ductal carcinoma .

• Prognostic Value: High expression levels of CCDC167 predict poor prognoses in breast cancer patients, suggesting its potential role as a prognostic biomarker .

• Correlation with Cancer Grade: CCDC167 expression shows a direct correlation with histological differentiation of breast cancer, with expression levels progressively increasing from nuclear grade I to grade III tumors. This suggests CCDC167 may be involved in mechanisms driving tumor dedifferentiation and aggressiveness .

• Functional Evidence: Experimental knockdown of CCDC167 in breast cancer cell lines attenuated aggressive cancer growth and proliferation, demonstrating a functional role in maintaining the cancer phenotype .

• Response to Chemotherapeutics: CCDC167 expression is decreased following treatment with established breast cancer chemotherapeutic agents (fluorouracil, carboplatin, paclitaxel, and doxorubicin), suggesting it may be linked to mechanisms of drug response .

These findings collectively indicate that CCDC167 plays a significant role in breast cancer progression and could represent a potential therapeutic target.

How does CCDC167 influence cellular proliferation and what are the underlying mechanisms?

CCDC167 exerts significant effects on cellular proliferation through multiple interconnected mechanisms:

• Cell Cycle Regulation: Co-expression analyses from METABRIC and TCGA databases revealed that CCDC167 is strongly associated with cell cycle-related signaling pathways. Pathway mapping indicates this is a key mechanism underlying its proliferative effects .

• Direct Proliferative Effects: Experimental evidence demonstrates that:

  • CCDC167 knockdown reduces both short-term proliferation (as measured by MTT assay) and long-term colony formation in MCF-7 breast cancer cells

  • Conversely, CCDC167 overexpression enhances cell proliferation and colony formation capacity

• Gene Expression Modulation: CCDC167 knockdown significantly alters the expression of:

  • Cell cycle-related genes

  • Apoptosis-related genes

This suggests that CCDC167 may influence proliferation by modulating cell cycle progression and cell survival pathways, though the exact transcriptional or signaling mechanisms remain under investigation.

The consistency between computational predictions (co-expression with cell cycle genes) and experimental observations (effects on proliferation) strengthens the evidence for CCDC167's mechanistic role in controlling cellular proliferation.

What is the relationship between CCDC167 and estrogen receptor signaling in breast cancer?

The relationship between CCDC167 and estrogen receptor (ER) signaling represents a significant area of investigation in breast cancer research:

• Contextual Relevance: Up to 80% of breast cancers are classified as ER-positive, indicating a crucial role for estrogen in breast cancer development . Understanding how CCDC167 interfaces with ER signaling is therefore clinically relevant.

• Prognostic Significance: High CCDC167 expression levels predict poor prognoses specifically in ER-positive breast cancer patients, suggesting a potential functional interaction between CCDC167 and estrogen-dependent pathways .

• Experimental Model Selection: Research on CCDC167 has utilized MCF-7 cells, which are an established ER-positive breast cancer cell line model, suggesting recognition of a potential relationship between CCDC167 and estrogen signaling .

• Therapeutic Implications: Given that ER-positive breast cancers are treated with endocrine therapies, understanding CCDC167's role in these cancers could have implications for developing complementary therapeutic strategies that might enhance responses to endocrine treatments.

While direct molecular interactions between CCDC167 and estrogen receptor signaling components require further investigation, the current evidence suggests important functional relationships that may have clinical relevance for ER-positive breast cancer treatment.

How can co-expression analysis provide insights into CCDC167 function?

Co-expression analysis represents a powerful approach for elucidating CCDC167 function, particularly when direct experimental data is limited:

• Methodological Approach: Researchers have successfully employed co-expression analyses using multiple independent datasets, including METABRIC and TCGA databases, to identify genes consistently co-expressed with CCDC167 in breast cancer .

• Functional Prediction: Gene Ontology (GO) enrichment analysis of co-expressed genes, performed through platforms like MetaCore, revealed that CCDC167 co-expressed genes are significantly enriched in cell cycle-related signaling pathways . This computational prediction was subsequently validated by experimental observations showing CCDC167's role in proliferation.

• Advantage of Integration: By merging results from multiple datasets (METABRIC and TCGA), researchers identified common co-expressed genes with higher confidence, minimizing database-specific biases .

• Network Perspective: Co-expression analysis provides insights beyond individual gene effects, highlighting that non-differentially expressed genes like CCDC167 can contribute to disease dysfunction through clusters of co-expressed genes and interaction networks .

• Implementation Strategy:

  • Identify co-expressed genes using correlation analyses across multiple datasets

  • Import common co-expressed genes into pathway analysis platforms

  • Perform GO enrichment analysis to predict biological functions

  • Validate predictions with targeted experimental approaches

This integrated computational and experimental approach has successfully revealed CCDC167's functional associations and provided testable hypotheses about its biological roles.

What are the challenges in studying CCDC167 protein-protein interactions and how can they be addressed?

Investigating CCDC167 protein-protein interactions presents several challenges that require specific methodological considerations:

• Small Protein Size: At only 97 amino acids , CCDC167 is relatively small, which may complicate traditional interaction studies. Researchers can address this by:

  • Using smaller affinity tags to minimize interference with interaction surfaces

  • Employing chemical crosslinking to stabilize transient interactions

  • Utilizing proximity-based approaches like BioID or APEX2 to capture the interaction neighborhood

• Coiled-Coil Domain Complexity: The coiled-coil structural motifs in CCDC167 can participate in multiple protein interactions with varying specificities. Researchers should:

  • Perform structure-based predictions to identify potential interaction interfaces

  • Consider competitive binding assays to determine interaction hierarchies

  • Employ mutational analyses targeting specific coiled-coil regions

• Subcellular Localization Considerations: Different interaction partners may exist in different cellular compartments. Approaches to address this include:

  • Compartment-specific protein interaction studies

  • Immunofluorescence co-localization with candidate interactors

  • Fractionation-based interaction studies

• Validation Strategies: To ensure biological relevance of identified interactions:

  • Confirm interactions using multiple orthogonal techniques

  • Demonstrate co-expression of interaction partners in relevant tissues

  • Establish functional consequences of disrupting specific interactions

By employing these strategies, researchers can overcome the technical challenges inherent in studying CCDC167 interactions and develop a more comprehensive understanding of its protein interaction network.

How can cross-species comparisons enhance our understanding of CCDC167 function?

Cross-species comparisons provide valuable insights into CCDC167 function through evolutionary and comparative biology approaches:

• Conservation Assessment: CCDC167 orthologs have been identified across diverse species including:

  • Mammals: Human, rat, mouse, chinchilla, bonobo, dog, pig, naked mole-rat

  • Primates: Green monkey

  • Rodents: Thirteen-lined ground squirrel

• Functional Inference: High conservation across species suggests essential biological functions. Researchers can:

  • Align amino acid sequences to identify invariant residues likely critical for function

  • Compare expression patterns across species to identify conserved regulatory mechanisms

  • Examine phenotypes in model organisms with CCDC167 mutations or knockouts

• Model System Selection: The Rat Genome Database contains extensive information on rat Ccdc167 , suggesting rats could serve as valuable model organisms for studying CCDC167 function. Researchers should consider:

  • Whether rat models recapitulate human CCDC167 expression patterns

  • If disease models in rats show similar CCDC167 dysregulation as human conditions

  • The translational relevance of findings between rodent models and human studies

• Evolutionary Analysis Approaches:

  • Phylogenetic analyses to determine evolutionary relationships between CCDC167 orthologs

  • Selective pressure analyses to identify regions under positive or negative selection

  • Synteny analyses to examine genomic context conservation

These comparative approaches can reveal fundamental aspects of CCDC167 biology conserved through evolution and help distinguish between essential functions and species-specific adaptations.

What are promising research areas for therapeutic targeting of CCDC167?

Several promising research directions could advance CCDC167 as a therapeutic target:

• Small Molecule Inhibitor Development: Given CCDC167's role in cancer progression, researchers could:

  • Perform virtual screening against CCDC167 structure to identify candidate inhibitors

  • Design molecules targeting coiled-coil interaction interfaces

  • Repurpose existing drugs that modulate CCDC167 expression or function

• Combination Therapy Approaches: Evidence suggests that established breast cancer chemotherapeutics (fluorouracil, carboplatin, paclitaxel, and doxorubicin) decrease CCDC167 expression . Future research could:

  • Investigate whether CCDC167 inhibition sensitizes cancer cells to these treatments

  • Develop rational combination therapies targeting CCDC167 and related pathways

  • Identify biomarkers predicting response to CCDC167-targeted therapies

• RNA Interference Therapeutics: Building on successful shRNA experiments , researchers could:

  • Develop siRNA or antisense oligonucleotides targeting CCDC167 for therapeutic applications

  • Optimize delivery systems for CCDC167-targeting RNA therapeutics

  • Evaluate efficacy in preclinical models, particularly for breast cancer

• Diagnostic/Prognostic Applications: Given the correlation between CCDC167 expression and cancer grade :

  • Validate CCDC167 as a prognostic biomarker in larger clinical cohorts

  • Develop standardized assays for measuring CCDC167 expression in clinical samples

  • Investigate whether CCDC167 expression patterns can guide treatment selection

These research directions could translate the fundamental understanding of CCDC167 biology into clinically relevant applications, particularly for breast cancer patients.

What methodological advances would enhance CCDC167 research?

Several methodological advances could significantly enhance CCDC167 research:

• Structural Biology Approaches:

  • Cryo-electron microscopy to determine the structure of CCDC167 protein complexes

  • NMR studies to characterize dynamic interactions of the coiled-coil domains

  • Hydrogen-deuterium exchange mass spectrometry to map interaction surfaces

• Advanced Genetic Models:

  • CRISPR-engineered cell lines with endogenous tagging of CCDC167 for localization studies

  • Conditional knockout animal models to study tissue-specific functions

  • Patient-derived organoids with CCDC167 modifications to study disease relevance

• Systems Biology Integration:

  • Multi-omics approaches integrating transcriptomics, proteomics, and metabolomics data

  • Network modeling to position CCDC167 within broader cellular signaling networks

  • Machine learning algorithms to predict patient outcomes based on CCDC167 expression patterns

• Translational Research Tools:

  • Development of high-quality, validated antibodies against different epitopes of CCDC167

  • Establishment of standardized assays for measuring CCDC167 in clinical samples

  • Creation of reporter systems for monitoring CCDC167 expression in real-time

These methodological advances would address current technical limitations in CCDC167 research and facilitate more comprehensive understanding of its biological functions and disease relevance.

CCDC167 Expression in Cancer Models

Effects of CCDC167 Manipulation on Cancer Phenotypes