TMED9 Antibody

What is TMED9 and what cellular functions does it regulate?

TMED9 (transmembrane emp24 protein transport domain containing 9) is a 235 amino acid protein with an observed molecular weight of 24-27 kDa that plays critical roles in protein transport and secretory pathways. It primarily functions in regulating protein transport between the endoplasmic reticulum and Golgi apparatus . Research demonstrates that TMED9 influences cellular processes including antigen presentation and processing capabilities through its association with MHC molecules . Additionally, TMED9 has been implicated in modulating polarization and activation of immune cells, suggesting its broader involvement in immune system regulation .

What sample types have been validated for TMED9 antibody reactivity?

TMED9 antibodies have been extensively tested across multiple species and tissue types. According to validation data, commercially available TMED9 antibodies (such as 21620-1-AP) demonstrate confirmed reactivity with human, mouse, rat, and pig samples . Specifically, positive Western Blot detection has been validated in HepG2 cells, L02 cells, pig liver tissue, mouse lung tissue, mouse pancreas tissue, mouse brain tissue, mouse liver tissue, and rat liver tissue . For immunohistochemistry applications, human liver tissue has shown positive detection, while immunofluorescence has been confirmed in HepG2 and HEK-293 cells . This cross-species reactivity makes TMED9 antibodies particularly valuable for comparative studies across animal models.

What mechanisms underlie TMED9's role in tumor metastasis and invasion?

TMED9 demonstrates a significant positive correlation with the epithelial-mesenchymal transition (EMT) pathway, a crucial process in cancer cell invasion and metastasis . Gene set enrichment analysis across multiple glioma datasets has confirmed this correlation, which is further supported by pathway enrichment analysis of proteomics data . At the molecular level, TMED9 positively correlates with EMT-related genes, including VIM, MMP2, and MMP14, at both transcriptomic and proteomic levels . Experimental validation in glioma cell lines (U-87MG and U251) revealed that TMED9 knockdown significantly reduced expression of these EMT markers and inhibited cell migration and invasion capabilities . This mechanistic link suggests TMED9 may promote tumor progression through EMT pathway modulation.

How does TMED9 influence the tumor immune microenvironment?

TMED9 exhibits significant correlations with various immune regulators, particularly MHC molecules, suggesting enhanced antigen presentation and processing capabilities in TMED9-high tumors . Immune subtype analysis revealed that across pan-cancer datasets, TMED9 high-expression correlates predominantly with C1 (Wound Healing) and C2 (IFN-γ Dominant) immune subtypes . TMED9 demonstrates significant positive correlations with various immune cell infiltrates, most notably macrophages, across multiple cancer types including LGG (Lower Grade Glioma), SARC (Sarcoma), THYM (Thymoma), and UVM (Uveal Melanoma) . In gliomas specifically, TMED9 expression correlates with altered cancer immune cycle activities, affecting processes from antigen release to T-cell recognition . Higher TMED9 expression is associated with increased TIDE scores, suggesting diminished efficacy of immune checkpoint blockade therapy .

What are the optimal protocols for TMED9 detection across different experimental techniques?

Based on validated research protocols, the recommended dilutions for TMED9 antibody applications are as follows:

For optimal results, it is recommended to titrate the antibody concentration for each specific experimental system . When performing IHC, antigen retrieval is a critical step, with suggested protocols using either TE buffer (pH 9.0) or alternatively citrate buffer (pH 6.0) . For Western blot applications, the expected molecular weight range is 24-27 kDa .

What controls should be included when validating TMED9 antibody specificity?

A robust validation strategy for TMED9 antibodies should include multiple controls. Positive controls should incorporate samples with confirmed TMED9 expression, such as HepG2 cells, liver tissues (human, mouse, or rat), or other validated cell lines . Negative controls should include TMED9 knockdown or knockout samples, which have been used in several published studies . For competitive binding assays, the immunogen (TMED9 fusion protein Ag13813) can be used . When conducting knockdown validation experiments, researchers have successfully employed siRNA-mediated approaches in cell lines such as U-87MG and U251, confirming knockdown efficiency through both RT-PCR and western blot analyses . To rule out non-specific binding, secondary antibody-only controls should also be included in immunostaining applications.

How can TMED9 antibodies be utilized for co-localization studies?

TMED9 functions primarily in protein transport between the endoplasmic reticulum and Golgi apparatus, making co-localization studies particularly valuable. For effective co-localization experiments, immunofluorescence applications using TMED9 antibodies (recommended dilution 1:50-1:500) can be combined with markers for subcellular compartments . Recommended co-staining markers include calnexin or PDI (for endoplasmic reticulum), GM130 or TGN46 (for Golgi apparatus), and RAB proteins (for vesicular transport). When performing multi-color immunofluorescence, it's critical to select secondary antibodies with non-overlapping emission spectra and to include appropriate controls for antibody cross-reactivity. Confocal microscopy is the preferred imaging method, and quantitative co-localization analysis should employ established metrics such as Pearson's correlation coefficient or Manders' overlap coefficient.

What molecular interactions mediate TMED9's effects on cellular signaling pathways?

While the complete interactome of TMED9 continues to be elucidated, research has identified several significant molecular interactions that mediate its cellular effects. TMED9 positively correlates with EMT-related genes including VIM, MMP2, and MMP14 at both transcriptomic and proteomic levels . These interactions likely contribute to TMED9's observed effects on cell migration and invasion. In the immune context, TMED9 shows positive correlations with various immune regulators, particularly MHC molecules, suggesting potential interactions that influence antigen presentation and processing . The mechanistic pathways through which TMED9 exerts its effects appear to involve modulation of secretory pathways, potentially through ER-Golgi transport regulation . This may affect processes such as cytokine release, antigen presentation, and MHC-I/II trafficking, subsequently influencing immune cell responses including macrophage polarization (M1/M2 balance) and T-cell activation . Further proteomic and interactome analyses are needed to fully characterize these molecular networks.

How can single-cell analysis approaches enhance our understanding of TMED9 expression heterogeneity in tumors?

Single-cell analysis technologies offer powerful approaches to investigate TMED9 expression heterogeneity within tumor microenvironments. While the provided search results don't specifically address single-cell studies of TMED9, this represents an important frontier for research. Single-cell RNA sequencing (scRNA-seq) could reveal cell type-specific expression patterns of TMED9 within heterogeneous tumor tissues, potentially identifying specific cellular subpopulations with elevated expression. Single-cell protein analysis methods such as mass cytometry (CyTOF) or CODEX could map TMED9 protein levels at single-cell resolution when combined with validated antibodies. These approaches would be particularly valuable for characterizing the relationship between TMED9 expression and immune cell infiltrates, which has been identified in bulk sequencing analyses . Spatial transcriptomics or multiplexed immunofluorescence could further reveal the spatial distribution of TMED9-expressing cells relative to specific tumor regions (e.g., invasive front, hypoxic areas) or immune cell clusters, providing insights into its functional significance within the tumor architecture.

What are the most common technical challenges when using TMED9 antibodies and how can they be addressed?

Researchers may encounter several technical challenges when working with TMED9 antibodies:

• Background signal in immunostaining: This can be minimized by optimizing blocking conditions (typically 5-10% normal serum from the same species as the secondary antibody), using lower antibody concentrations (start with 1:500 dilution for IHC/IF), and implementing more stringent washing steps (increasing wash duration or number of washes) .

• Inconsistent Western blot results: For optimal detection, use freshly prepared samples, ensure complete protein denaturation, optimize transfer conditions for proteins in the 24-27 kDa range, and consider longer blocking times (1-2 hours) with 5% non-fat dry milk or BSA .

• Variability in immunoprecipitation efficiency: For IP applications, use 0.5-4.0 μg antibody per 1.0-3.0 mg of total protein lysate, pre-clear lysates, and optimize incubation conditions (typically overnight at 4°C with gentle rotation) .

• Cross-reactivity concerns: Validate antibody specificity using TMED9 knockdown controls, which have been successfully employed in published studies . When possible, compare results using different antibody clones targeting distinct epitopes.

How can researchers effectively quantify TMED9 expression in tissue samples?

Quantification of TMED9 expression in tissue samples can be approached through several methodologies:

For IHC quantification, researchers should implement standardized scoring systems such as H-score (combining intensity and percentage of positive cells) or Allred scoring. Digital image analysis using software such as ImageJ with appropriate plugins can provide more objective quantification. When working with tissue microarrays (TMA), ensure sufficient tumor representation in each core (minimum 1.0 mm diameter recommended) .

For quantitative analysis of Western blots, use appropriate housekeeping controls (β-actin, GAPDH) for normalization, and employ densitometry software for band intensity quantification. Standard curves using recombinant TMED9 protein can provide absolute quantification if needed.

For mRNA quantification, RT-qPCR remains the gold standard, requiring carefully validated primers and appropriate reference genes for normalization. In situ hybridization techniques can provide spatial information about TMED9 expression when antibody-based detection is problematic.

Multi-omic approaches combining protein and mRNA quantification are recommended for comprehensive analysis, as these have proven valuable in characterizing TMED9's role in cancer contexts .

What considerations are important when designing TMED9 knockdown or knockout experiments?

When designing TMED9 knockdown or knockout experiments, several critical factors should be considered:

For siRNA-mediated knockdown, published research has successfully employed multiple siRNA constructs targeting different regions of TMED9 mRNA . Testing multiple siRNAs is recommended to confirm that observed phenotypes are not due to off-target effects. In glioma cell lines (U-87MG and U251), researchers achieved significant knockdown using four distinct siRNAs, with siRNA1 and siRNA3 demonstrating higher efficiency .

For CRISPR-Cas9 knockout strategies, guide RNA design should consider TMED9's genomic structure to avoid off-target effects. Verification of knockout should employ both genomic (sequencing) and protein-level (Western blot) validation.

Phenotypic analyses should focus on processes linked to TMED9 function, including cell migration and invasion assays, which have demonstrated significant impairment following TMED9 knockdown in glioma cells . Expression analysis of downstream genes, particularly EMT markers (VIM, MMP2, MMP14), should be included to characterize molecular consequences .

For rescue experiments, expression constructs should use codon-optimized TMED9 sequences resistant to the knockdown approach, ensuring specific attribution of phenotypic effects to TMED9 restoration.