tmem147 Antibody

What is TMEM147 and what are its key structural characteristics?

TMEM147 (also known as NIFIE14 or NEDFLPH) is a highly conserved protein consisting of 224 amino acids. It is characterized by seven transmembrane domains, making it a highly hydrophobic protein that is largely embedded within the membrane . The protein has a molecular weight of approximately 22-25 kDa in its native form, while tagged versions (such as V5-tagged TMEM147) appear at approximately 25 kDa on Western blots . The protein is widely expressed across different tissue types according to gene expression databases, suggesting it may play fundamental roles in cellular function .

What are the known biological functions of TMEM147?

TMEM147 has been identified as a component of the Nicalin-NOMO complex, as demonstrated by co-immunoprecipitation studies . Recent research indicates that TMEM147 plays roles in cell signaling, membrane trafficking, and potentially immune regulation . Its involvement in these processes makes it a promising target for research investigating various diseases, including cancer, neurodegenerative disorders, and metabolic conditions . In particular, TMEM147 has been associated with:

• B lymphocyte function

• Antigen response

• IL6 signaling pathway

• Cell cycle regulation

• KRAS signaling pathway

• MYC targets

What sample types has TMEM147 been detected in?

TMEM147 protein expression has been successfully detected in:

• Human hepatocellular carcinoma (HCC) tissues and adjacent normal liver tissues

• Various human cancer cell lines, including HCC cell lines

• MCF7 breast cancer cells (often used as a positive control)

• Mouse tissue samples

What are the primary research applications for TMEM147 antibodies?

TMEM147 antibodies have been validated for several key research applications:

• Western Blotting (WB): Most commonly used to detect TMEM147 protein expression levels in tissue or cell lysates. Recommended dilutions typically range from 1:500 to 1:2000 .

• Immunoprecipitation (IP): TMEM147 antibodies have been successfully used to precipitate the protein along with its binding partners, enabling the study of protein-protein interactions .

• ELISA: For quantitative measurement of TMEM147 levels in various sample types .

• Immunohistochemistry (IHC): For examination of TMEM147 expression patterns in tissue sections, particularly valuable for cancer research .

• Protein Complex Analysis: For investigating TMEM147's association with the Nicalin-NOMO complex and other potential binding partners .

How should TMEM147 antibodies be validated for research use?

Validation of TMEM147 antibodies should include multiple approaches:

• Western blot analysis: Confirm the antibody detects a band of the expected molecular weight (~22-25 kDa). Comparison with a tagged version of TMEM147 (e.g., V5-tagged) can provide additional confirmation .

• RNA interference (RNAi): Verify antibody specificity by demonstrating reduced signal in cells expressing TMEM147-specific short hairpin RNAs. The confirmed TMEM147-specific target sequence CTGCTTCGCTCTTGCCTACTT has been successfully used for this purpose .

• Positive control samples: Use known positive samples like MCF7 cells that express detectable levels of TMEM147 .

• Cross-reactivity testing: Ensure the antibody performs as expected across relevant species (e.g., human and mouse samples if conducting comparative studies) .

• Immunoprecipitation followed by mass spectrometry: For definitive identification, perform IP followed by LC-MS/MS analysis to confirm the identity of the immunoprecipitated protein .

What are the optimal experimental conditions for detecting TMEM147 in Western blotting?

For optimal Western blot detection of TMEM147:

• Sample preparation: As TMEM147 is a transmembrane protein, use lysis buffers containing appropriate detergents to efficiently extract membrane proteins.

• Antibody selection: Polyclonal antibodies against TMEM147, such as rabbit polyclonal antibodies targeting epitopes within amino acids 1-100 of human TMEM147, have shown good specificity .

• Antibody dilution: The recommended dilution range for Western blotting is typically 1:500 to 1:2000 . Optimization may be required for specific antibodies and sample types.

• Positive controls: Include MCF7 cell lysate as a positive control .

• Expected results: Native TMEM147 appears at ~22 kDa, while tagged versions may appear at ~25 kDa depending on the tag used .

• Verification of specificity: Run parallel samples with TMEM147 knockdown to confirm antibody specificity .

How can I design experiments to investigate TMEM147's role in cancer progression?

To investigate TMEM147's role in cancer progression, consider the following experimental approaches:

• Expression analysis across cancer types:

  • Compare TMEM147 expression in multiple cancer types using publicly available datasets like TCGA

  • Analyze expression differences between tumor and adjacent normal tissues

  • Examine expression patterns in paired samples from the same patients

• Clinical correlation studies:

  • Correlate TMEM147 expression with clinical parameters such as:

    • T stage

    • Pathological stage

    • Histological grade

    • Alpha-fetoprotein levels (for HCC)

    • Vascular invasion status

• Survival analysis:

  • Perform Kaplan-Meier survival analysis comparing high vs. low TMEM147 expression groups

  • Conduct Cox regression analysis to assess TMEM147 as an independent prognostic factor alongside other clinical variables

• Functional studies:

  • RNA interference experiments to knockdown TMEM147 expression

  • Assess effects on cell proliferation, migration, invasion, and apoptosis

  • Analyze changes in proposed downstream pathways (e.g., IL6 signaling, cell cycle, KRAS signaling)

• Mechanism investigations:

  • Perform gene enrichment analysis to identify associated pathways

  • Investigate interactions with Nicalin-NOMO complex and other binding partners

  • Examine effects on immune cell infiltration and function

How does TMEM147 expression correlate with cancer progression and immune infiltration?

TMEM147 has shown significant correlations with cancer progression and immune cell infiltration:

What methodologies are most effective for studying TMEM147's role in immune regulation?

For investigating TMEM147's role in immune regulation, researchers should consider these methodological approaches:

• Transcriptomic analysis:

  • RNA sequencing to identify differentially expressed genes between high and low TMEM147 expression groups

  • Gene Set Enrichment Analysis (GSEA) to identify enriched biological processes and pathways

  • Single-sample Gene Set Enrichment Analysis (ssGSEA) to evaluate the relative infiltration levels of immune cell types in tumor samples

• Correlation analysis:

  • Spearman correlation analysis to assess relationships between TMEM147 expression and immune cell infiltration scores

  • Wilcoxon rank-sum test to compare immune cell infiltration between high and low TMEM147 expression groups

• Immune profiling experiments:

  • Immunohistochemical staining of tumor tissues to visualize and quantify immune cell infiltration

  • Flow cytometry to analyze immune cell populations in response to TMEM147 manipulation

  • Cytokine profiling to assess inflammatory responses

• Functional validation:

  • TMEM147 knockdown or overexpression studies in cancer cell lines

  • Co-culture experiments with immune cells to assess direct effects on immune function

  • In vivo models to evaluate immune response in the tumor microenvironment

• Pathway analysis:

  • Focus on previously identified pathways associated with TMEM147, including:

    • B lymphocyte function

    • Antigen response mechanisms

    • IL6 signaling pathway

    • Cell cycle regulation

    • KRAS signaling pathway

    • MYC targets

How can I incorporate TMEM147 into multi-omics analyses for cancer research?

For comprehensive multi-omics analyses involving TMEM147:

• Integrated genomic and transcriptomic analysis:

  • Combine TMEM147 expression data with mutation profiles, copy number variations, and methylation status

  • Analyze how genetic alterations affect TMEM147 expression and function

  • Identify potential regulatory mechanisms controlling TMEM147 expression

• Proteomics integration:

  • Use immunoprecipitation followed by mass spectrometry to identify TMEM147 interaction partners

  • Perform differential proteomics to assess changes in protein expression and post-translational modifications in response to TMEM147 manipulation

  • Analyze TMEM147's position within protein-protein interaction networks

• Pathway-based analyses:

  • Conduct Gene Ontology (GO) term enrichment analysis

  • Perform Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis

  • Use Gene Set Enrichment Analysis (GSEA) with defined gene sets related to cancer hallmarks and immune function

• Clinical data integration:

  • Develop prognostic models incorporating TMEM147 expression alongside other molecular and clinical features

  • Create and validate nomograms for predicting patient outcomes

  • Stratify patients based on TMEM147 expression and associated molecular features

• Single-cell analyses:

  • Apply single-cell RNA sequencing to understand cell-type-specific expression patterns of TMEM147

  • Examine how TMEM147 expression varies across different cell populations within the tumor microenvironment

  • Assess cellular heterogeneity in relation to TMEM147 expression and function

What are the key considerations when interpreting TMEM147 expression data across different cancer types?

When interpreting TMEM147 expression data across cancer types, researchers should consider:

• Tissue specificity:

  • TMEM147 expression patterns may vary significantly between tissue types

  • Baseline expression in normal tissues should be considered when interpreting cancer-specific changes

  • Different thresholds for "high" versus "low" expression may be appropriate for different cancer types

• Cancer subtype variation:

  • TMEM147 expression has been shown to vary significantly across molecular subtypes within the same cancer type

  • Subtype-specific analyses may reveal different functional roles or prognostic significance

  • Consider analyzing:

    • Molecular subtypes (e.g., basal, classical, iCluster)

    • Immune subtypes

    • Histological subtypes

• Technical considerations:

  • Different detection methods (RNA-seq, microarray, qPCR, Western blot, IHC) may yield different results

  • Standardization and normalization methods affect expression measurements

  • Batch effects and platform differences should be accounted for in meta-analyses

• Biological context:

  • TMEM147 functions may differ depending on the cellular context and microenvironment

  • Consider the expression of known interacting partners (e.g., Nicalin, NOMO)

  • Evaluate TMEM147 in relation to pathway activation status

• Prognostic versus predictive value:

  • Distinguish between TMEM147's value as a prognostic marker (associated with outcome regardless of treatment) versus a predictive marker (predicts response to specific therapies)

  • The effect of TMEM147 on prognosis has been shown to vary among different clinical subtypes, particularly in liver hepatocellular carcinoma (LIHC)

What are common challenges when working with TMEM147 antibodies and how can they be addressed?

Researchers often encounter these challenges when working with TMEM147 antibodies:

• Low detection sensitivity:

  • Solution: Optimize protein extraction methods for membrane proteins, using detergents appropriate for transmembrane proteins

  • Solution: Try signal enhancement systems or more sensitive detection methods

  • Solution: Enrich for membrane fractions in sample preparation

• Non-specific binding:

  • Solution: Validate antibody specificity using TMEM147 knockdown controls (e.g., with the validated siRNA target sequence CTGCTTCGCTCTTGCCTACTT)

  • Solution: Optimize blocking conditions and antibody dilutions

  • Solution: Use monoclonal antibodies if polyclonal antibodies show high background

• Variability in protein detection:

  • Solution: Use consistent positive controls (e.g., MCF7 cells)

  • Solution: Include tagged TMEM147 constructs as additional controls

  • Solution: Standardize protein loading and normalize to appropriate housekeeping proteins

• Cross-reactivity issues:

  • Solution: Choose species-specific antibodies if working with models from different species

  • Solution: Verify species reactivity before beginning experiments

  • Solution: Consider using synthetic peptide competition assays to confirm specificity

• Inconsistent immunoprecipitation results:

  • Solution: Optimize lysis conditions to maintain protein complexes

  • Solution: Consider using crosslinking methods to stabilize protein-protein interactions

  • Solution: Confirm successful IP with Western blotting before proceeding to downstream analyses

How can I distinguish between genuine and artifactual TMEM147 signals in my experiments?

To distinguish between genuine and artifactual TMEM147 signals:

• Multiple detection methods:

  • Confirm findings using different antibodies targeting distinct epitopes of TMEM147

  • Validate protein expression using complementary techniques (e.g., mass spectrometry, RNA expression)

  • Compare results from multiple experimental approaches (Western blot, IHC, IF)

• Appropriate controls:

  • Positive controls: Include samples known to express TMEM147 (e.g., MCF7 cells)

  • Negative controls: Include samples with TMEM147 knockdown or from tissues known not to express the protein

  • Antibody controls: Include secondary antibody-only controls to assess non-specific binding

• Expression manipulation:

  • Compare signal in wild-type cells versus those overexpressing tagged TMEM147 constructs

  • Use RNA interference to reduce TMEM147 expression and confirm corresponding reduction in antibody signal

  • Consider CRISPR-based knockout models for definitive validation

• Size verification:

  • Confirm the detected band is at the expected molecular weight (~22 kDa for native TMEM147, ~25 kDa for tagged versions)

  • Be aware of potential post-translational modifications that might alter apparent molecular weight

  • Use protein ladders with appropriate range for small proteins

• Reproducibility assessment:

  • Ensure results are reproducible across multiple experiments

  • Test consistency across different lots of the same antibody

  • Verify findings in different cell lines or tissue types where TMEM147 is expected to be expressed