Recombinant Human UPF0197 transmembrane protein C11orf10 (C11orf10)

What is C11orf10 and what are its alternative names?

C11orf10, also known as TMEM258 (transmembrane protein 258) or HSPC005, is a protein encoded by a gene located on chromosome 11 in humans. It is classified as an UPF0197 transmembrane protein and has been identified as an important protein in various metabolic pathways . The protein has been conserved across species, with homologs identified in model organisms such as Xenopus laevis and Danio rerio .

What is the genomic organization of the C11orf10 gene?

The C11orf10 gene is located immediately upstream of the FEN1 gene in reverse orientation. Importantly, in the human genome, the mRNAs of C11orf10 and FEN1 overlap by 14 bp in their 5′ ends. This makes the FEN1/C11orf10 locus a notable example of two overlapping, divergent transcription units in the human genome . This unique genomic arrangement may have implications for the coordinated regulation of these two genes.

What is the subcellular localization of the C11orf10 protein?

Immunostaining studies have revealed that the C11orf10 protein is predominantly located in the cytoplasm. This contrasts with FEN-1, which is primarily found in the nucleus. This differential localization suggests that despite their genomic proximity and overlapping transcription units, these two proteins do not form a physical complex in the cell .

What expression systems are commonly used for producing recombinant C11orf10 protein?

Recombinant Human UPF0197 transmembrane protein C11orf10 can be produced using various expression systems. According to available product information, the protein can be expressed in E. coli, yeast, baculovirus, or mammalian cell systems . The choice of expression system depends on specific research requirements, such as post-translational modifications needed, protein folding considerations, and intended downstream applications.

What purification methods are recommended for C11orf10 recombinant protein?

Standard purification protocols for recombinant C11orf10 typically aim to achieve greater than or equal to 85% purity as determined by SDS-PAGE . While specific purification strategies depend on the expression system used, common approaches include:

• Affinity chromatography (using tags such as His, GST, or FLAG)

• Ion exchange chromatography

• Size exclusion chromatography

• Combination of these methods in sequence

Researchers should optimize purification parameters based on the specific construct and experimental needs.

What evidence links C11orf10 to glucose metabolism?

This evidence suggests C11orf10 plays a potentially important role in glucose homeostasis .

How is C11orf10 related to fatty acid metabolism?

C11orf10 has been demonstrated to play an important role in fatty acid metabolism. It is located in close proximity to FADS1 (fatty acid desaturase 1), and both genes have been implicated in polyunsaturated fatty acid (PUFA) metabolism. Genome-wide meta-analyses have identified significant associations between variants in this genomic region and various PUFAs, including linoleic acid (LA), gamma-linolenic acid (GLA), and arachidonic acid (AA) .

The strongest associations were observed on chromosome 11 in the region containing FADS1/2, FEN1, C11orf9, and C11orf10 . This suggests a potential functional relationship between these genes in regulating fatty acid metabolism. Furthermore, C11orf10 and FADS1 have been significantly associated with metabolic syndrome, highlighting their importance in metabolic health .

What are the recommended methods for studying the interaction between C11orf10 and FADS1?

Given the genomic proximity and functional relationships between C11orf10 and FADS1, several methodological approaches are recommended for investigating their interactions:

• Chromatin Conformation Capture (3C/4C/Hi-C): These techniques can help elucidate potential physical interactions between the genomic regions containing C11orf10 and FADS1, which might reveal shared regulatory elements.

• RNA-seq with differential expression analysis: Comparing expression patterns of C11orf10 and FADS1 across different tissues and under various conditions can reveal coordinated regulation.

• Co-immunoprecipitation (Co-IP): Although immunostaining suggests C11orf10 and FEN-1 don't form a physical complex , Co-IP could be used to investigate potential protein-protein interactions between C11orf10 and FADS1 or other proteins in related pathways.

• CRISPR-Cas9 gene editing: Creating knockouts or mutations in either gene and observing effects on the expression and function of the other gene can provide insights into their functional relationship.

• Promoter analysis and reporter assays: These can help identify shared transcription factors or regulatory elements that might coordinate the expression of these genes.

What experimental design is recommended for investigating C11orf10's role in glucose metabolism?

To investigate C11orf10's role in glucose metabolism, a multi-faceted experimental design is recommended:

• CRISPR-Cas9 mediated knockout or knockdown: Generate C11orf10-deficient cell lines or animal models to assess the impact on glucose uptake, insulin sensitivity, and related metabolic pathways.

• Glucose tolerance tests (GTT) and insulin tolerance tests (ITT): Perform these tests in C11orf10-modified animal models to assess whole-body glucose homeostasis.

• Metabolomic profiling: Compare the metabolite profiles between wild-type and C11orf10-deficient models to identify affected metabolic pathways.

• Isotope tracer studies: Use labeled glucose to track its metabolic fate in the presence and absence of C11orf10.

• RNA-seq and proteomics: Identify genes and proteins with altered expression in response to C11orf10 manipulation, focusing on those involved in glucose metabolism.

• Functional validation in relevant cell types: Confirm findings in cell types important for glucose metabolism (e.g., hepatocytes, adipocytes, and pancreatic β-cells).

How can researchers interpret the heterogeneity in GWAS findings related to C11orf10?

When interpreting heterogeneity in GWAS findings related to C11orf10, researchers should consider several factors:

• Population differences: Significant heterogeneity has been observed in the effects of SNPs in the FADS1/C11orf10 region across different populations. For example, SNP rs174547 exhibited significant heterogeneity in effects on linoleic acid (LA), dihomo-gamma-linolenic acid (DGLA), and arachidonic acid (AA) when comparing across different cohorts .

• Phenotypic measurement differences: Even after implementing log-transformation and z-score normalization of PUFA levels, heterogeneity in associations remained, suggesting that differences in measurement techniques or definitions could contribute to heterogeneity .

• Gene-environment interactions: Variations in diet, lifestyle, and other environmental factors across study populations can modify genetic effects.

• Linkage disequilibrium patterns: Different linkage disequilibrium structures across populations can result in different association patterns.

• Methodological considerations: When analyzing heterogeneity, researchers should use appropriate statistical methods, such as the Q-test or I² statistic, and consider random-effects meta-analysis when significant heterogeneity is present.

What are the current challenges in studying the regulatory mechanisms of C11orf10 expression?

Studying the regulatory mechanisms of C11orf10 expression presents several challenges:

• Overlapping transcription units: The overlapping nature of C11orf10 and FEN1 transcription units (14 bp overlap in their 5′ ends) complicates the study of promoter activity and transcriptional regulation specific to C11orf10.

• Tissue-specific expression patterns: Understanding how C11orf10 expression varies across different tissues and cell types requires comprehensive expression profiling.

• Epigenetic regulation: The role of DNA methylation, histone modifications, and chromatin structure in regulating C11orf10 expression remains poorly understood.

• Post-transcriptional regulation: The mechanisms controlling C11orf10 mRNA stability, processing, and translation efficiency need further investigation.

• Feedback loops: Potential feedback mechanisms between C11orf10 and metabolic pathways (e.g., glucose and fatty acid metabolism) add complexity to regulatory studies.

• Genetic variants: The functional consequences of genetic variants in and around the C11orf10 gene on its expression and function require careful validation.

What are the key unresolved questions about C11orf10 function?

Despite progress in understanding C11orf10, several key questions remain unresolved:

• Molecular function: The precise molecular function of C11orf10 protein remains largely unknown. As a transmembrane protein, it may function as a transporter, receptor, or structural component, but definitive evidence is lacking.

• Signaling pathways: The signaling pathways involving C11orf10 and how it interacts with other proteins to influence glucose and fatty acid metabolism are not fully elucidated.

• Regulation: The factors controlling C11orf10 expression under different physiological and pathological conditions are not well characterized.

• Tissue-specific roles: While associations with metabolic traits suggest importance in metabolic tissues, the specific roles of C11orf10 in different tissues remain to be determined.

• Pathological implications: The potential involvement of C11orf10 dysfunction in metabolic diseases beyond its statistical associations needs further investigation.

What novel methodologies might advance our understanding of C11orf10?

Several emerging methodologies could significantly advance our understanding of C11orf10:

• Single-cell genomics and transcriptomics: These approaches can reveal cell type-specific expression patterns and regulatory mechanisms of C11orf10.

• Spatial transcriptomics: This technique can map C11orf10 expression within tissues with spatial resolution, providing insights into its function in tissue microenvironments.

• CRISPR-based screens: Genome-wide CRISPR screens can identify genes that interact functionally with C11orf10.

• Protein structure determination: Cryo-electron microscopy or X-ray crystallography of C11orf10 can provide insights into its molecular function.

• Metabolic flux analysis: Advanced metabolic tracing techniques can reveal how C11orf10 affects specific metabolic pathways.

• Integrative multi-omics approaches: Combining genomics, transcriptomics, proteomics, and metabolomics data can provide a comprehensive view of C11orf10's role in cellular physiology.

• Organoid models: These can be used to study C11orf10 function in more physiologically relevant contexts than traditional cell culture.