msmo1 Antibody

What is MSMO1 and why are antibodies against it important for research?

MSMO1 (Methylsterol Monooxygenase 1, also known as DESP4, ERG25, or SC4MOL) is a protein localized to the endoplasmic reticulum membrane that functions primarily in cholesterol biosynthesis. It contains putative metal binding motifs similar to those in membrane desaturases-hydroxylases . MSMO1 antibodies are important for detecting endogenous levels of this protein in various experimental settings, facilitating studies on cholesterol metabolism and related disease mechanisms .

The protein was initially isolated based on its similarity to the yeast ERG25 protein. Researchers studying lipid metabolism, sterol synthesis, and related diseases rely on high-quality MSMO1 antibodies for accurate detection and quantification of this protein .

What applications are MSMO1 antibodies validated for?

MSMO1 antibodies have been validated for multiple experimental applications:

When designing experiments, researchers should perform antibody titration tests to determine optimal dilutions for their specific experimental conditions and sample types .

What are the optimal storage conditions for MSMO1 antibodies?

For maximum longevity and performance, MSMO1 antibodies should be:

• Stored at -20°C in a non-frost-free freezer

• Aliquoted to avoid repeated freeze/thaw cycles which can degrade antibody performance

• Maintained in proper buffer conditions (typically PBS pH 7.3-7.4, containing 0.05% NaN3 and 40-50% Glycerol)

How should researchers choose between different MSMO1 antibody formats?

The most common MSMO1 antibodies are rabbit polyclonal antibodies . When selecting an antibody:

• Consider the specific epitope targeted: Some antibodies target N-terminal regions , while others target internal residues

• Evaluate reported reactivity: Available antibodies show varying reactivity profiles across species (human, mouse, rat, etc.)

• Match purification method to application: Antigen affinity-purified antibodies provide higher specificity for applications like IHC and WB

For co-localization studies or experiments requiring detection of multiple targets, consider antibodies raised in different host species to avoid cross-reactivity in secondary antibody detection .

How does MSMO1 function in cancer progression and what methods best detect its expression changes?

MSMO1 exhibits dual roles in different cancers, necessitating careful experimental design when studying its function:

In pancreatic cancer (PC), MSMO1 acts as a tumor suppressor:

• MSMO1 expression is negatively associated with T stage, lymph node metastasis, and vascular permeation

• MSMO1 silencing promotes cell invasion and migration via activating EMT and PI3K-AKT-mTOR pathway

• Positive MSMO1 expression indicates better prognosis and is an independent favorable prognostic factor

In cervical squamous cell carcinoma (CESC), MSMO1 is upregulated:

• MSMO1 is highly expressed in tumor specimens compared to normal tissues

• Higher MSMO1 expression correlates with advanced pathological stages

• MSMO1 expression has significant negative correlation with infiltration levels of CD4+ T cells, macrophages, neutrophils, and dendritic cells

For optimal detection of MSMO1 expression changes, researchers should employ multiple complementary techniques:

• IHC for protein localization in tissue sections (1:25-1:100 dilution)

• Western blot for quantitative protein level assessment

• qRT-PCR for mRNA expression analysis

What experimental controls should be included when using MSMO1 antibodies?

To ensure reliable results, researchers should include these critical controls:

• Positive controls: Use tissues or cell lines known to express MSMO1 (examples from literature include tonsil cancer tissue and cervical cancer tissue)

• Negative controls:

  • Primary antibody omission control

  • Isotype control (using non-specific rabbit IgG at equivalent concentration)

  • Tissue negative control (tissues known not to express MSMO1)

• Blocking peptide controls: When available, pre-incubation of the antibody with the immunizing peptide should eliminate specific staining

• siRNA validation: For cell line studies, comparison with MSMO1 knockdown cells provides strong validation of antibody specificity

Additionally, researchers should verify that the staining pattern matches the expected subcellular localization (endoplasmic reticulum membrane for MSMO1) .

What methodologies are recommended for studying MSMO1's role in signaling pathways?

Based on published research, these methodologies have proven effective for studying MSMO1's role in signaling:

• RNA interference approaches:

  • siRNA transfection (e.g., sequence: Sense: GAAGCCCUUUAUUUUCUUAUTT, Anti-sense: AUAAGAAAUAAAGGGCUUCTT)

  • Verification of knockdown efficiency by Western blot and qRT-PCR

  • Observation of phenotypic changes in morphology, migration, and invasion

• Western blot analysis for signaling pathway components:

  • Detection of EMT markers: E-cadherin, β-catenin, Vimentin

  • PI3K-AKT-mTOR pathway proteins: AKT, PI3K, mTOR

  • Phosphorylated forms: p-AKT (Ser473), p-PI3K (Tyr458), p-mTOR (Ser2448)

  • GAPDH as loading control

• In vivo models:

  • Cell-line-derived tumor xenograft models (e.g., PANC-02 cells in C57B6 mice)

  • Subcutaneous tumor measurement (V=1/2ab²)

  • Post-tumor extraction analysis: protein extraction, H&E staining, IHC

How can researchers evaluate MSMO1 antibody specificity for their experimental systems?

Comprehensive validation of MSMO1 antibody specificity should include:

• Western blot validation:

  • Verify single band at expected molecular weight (~29 kDa for human MSMO1)

  • Compare with lysates from cells with MSMO1 knockdown/knockout

  • Test across relevant tissue/cell types to confirm consistent detection

• Orthogonal method validation:

  • Correlate antibody-based protein detection with mRNA levels by qRT-PCR

  • Use multiple antibodies targeting different epitopes of MSMO1

  • Compare results with PrEST antigen control where available

• Cross-reactivity testing:

  • Test against closely related family members

  • Evaluate species cross-reactivity if working across multiple model organisms

  • Perform peptide competition assays with immunizing peptide

• Subcellular localization confirmation:

  • Verify endoplasmic reticulum membrane localization pattern

  • Use co-localization with established ER markers

What is known about MSMO1's interaction with the immune system and how can this be studied?

MSMO1 exhibits significant correlations with immune cell infiltration in cancer:

• In CESC, MSMO1 expression shows negative correlation with infiltration levels of CD4+ T cells, macrophages, neutrophils, and dendritic cells

• GSEA analysis identified MSMO1 involvement in pathways related to immune function including systemic lupus erythematosus, cytokine receptor interaction, and chemokine signaling pathways

To study these interactions, researchers can employ:

• Bioinformatic approaches:

  • TIMER and TISIDB databases to analyze correlations between MSMO1 and immune cell markers

  • GSEA to identify enriched immune-related pathways

  • Analysis of co-expressed genes using databases like cBioPortal

• Experimental validation methods:

  • Flow cytometry to quantify immune cell populations in MSMO1-manipulated models

  • Multiplex cytokine assays to measure secreted immune mediators

  • Co-culture experiments with immune cells and MSMO1-modified cancer cells

  • Immunohistochemistry with dual staining for MSMO1 and immune cell markers

• In vivo immune profiling:

  • Analysis of tumor-infiltrating lymphocytes in MSMO1-manipulated xenograft models

  • Assessment of immunomodulatory effects using syngeneic mouse models

  • Evaluation of response to immunotherapies in relation to MSMO1 expression

What are common troubleshooting strategies for MSMO1 antibody detection in IHC?

When optimizing MSMO1 immunohistochemistry:

• Signal optimization:

  • Test multiple antibody dilutions (starting with 1:25-1:100)

  • Evaluate different antigen retrieval methods (heat-induced vs. enzymatic)

  • Extend primary antibody incubation (overnight at 4°C may improve signal)

  • Compare detection systems (ABC vs. polymer-based)

• Background reduction:

  • Include additional blocking steps (protein block, avidin/biotin block if needed)

  • Optimize washing steps (increase number or duration)

  • Reduce secondary antibody concentration

  • Use tissues with validated MSMO1 expression (tonsil or cervical cancer)

• Fixation considerations:

  • Standardize fixation time to minimize variability

  • Test MSMO1 antibody on both frozen and FFPE sections if possible

  • Consider testing alternative fixatives beyond formalin

How can researchers integrate MSMO1 expression data with other molecular profiles?

For comprehensive molecular characterization:

• Multi-omics approaches:

  • Correlate MSMO1 protein levels (by IHC/WB) with mRNA expression (RNA-seq/qPCR)

  • Investigate relationship with methylation status (methylation showed increased levels in CESC tumor tissues)

  • Examine miRNA regulation (hsa-miR-23a-3p, hsa-miR-23b-3p, hsa-miR-130b-3p have been linked to MSMO1)

• Co-expression analysis:

  • Identify co-expressed genes (e.g., IDI1 shows strong correlation with MSMO1, Spearman: 0.58)

  • Use STRING database to analyze protein-protein interactions

  • Apply GSEA to identify enriched pathways

• Clinical correlation methods:

  • Calculate ROC values for diagnostic potential (T stage AUC = 0.720 in CESC)

  • Perform Cox regression analysis for prognostic significance

  • Stratify patients by MSMO1 expression for survival analysis

What considerations apply when developing assays for MSMO1 in different sample types?

Sample-specific considerations for MSMO1 detection:

• Cell lines:

  • Western blot and immunofluorescence are preferred methods

  • Verify expression in relevant cell lines (Capan-2, Panc-1, SW1990 for pancreatic studies)

  • Consider induction/repression conditions that might affect MSMO1 levels

• Tissue samples:

  • IHC is the gold standard for spatial localization in tissues

  • Employ tissue microarrays for high-throughput screening

  • Consider heterogeneity in different regions of the same tumor

  • Use specialized fixation protocols for ER membrane proteins

• Blood/serum samples:

  • Limited evidence for circulating MSMO1 detection

  • ELISA may be applicable for secreted forms

  • Consider proximity ligation assays for improved sensitivity

What emerging technologies might enhance MSMO1 antibody applications?

Several cutting-edge approaches show promise for MSMO1 research:

• Single-cell applications:

  • Single-cell proteomics with MSMO1 antibodies to detect cell-specific expression patterns

  • Mass cytometry (CyTOF) incorporation of metal-conjugated MSMO1 antibodies

  • Spatial transcriptomics combined with IHC for correlating MSMO1 protein and mRNA in situ

• Advanced imaging:

  • Super-resolution microscopy for precise subcellular localization

  • Multiplexed ion beam imaging (MIBI) for simultaneous detection of multiple proteins

  • Live-cell imaging with fluorescently tagged antibody fragments

• Therapeutic applications:

  • Development of function-blocking antibodies targeting MSMO1

  • Antibody-drug conjugates for targeting MSMO1-overexpressing cells

  • CAR-T approaches against MSMO1 in relevant cancer types

How might MSMO1 antibodies contribute to understanding broader cholesterol metabolism dysregulation in disease?

MSMO1 antibodies can facilitate investigation of cholesterol metabolism in various pathological contexts:

• Cancer metabolism studies:

  • Correlation of MSMO1 with other cholesterol biosynthesis enzymes

  • Investigation of metabolic adaptations in different cancer types

  • Relationship between MSMO1, lipid rafts, and oncogenic signaling

• Neurodegenerative disease research:

  • MSMO1's potential role in brain cholesterol homeostasis

  • Relationship to amyloid and tau pathology

  • Correlation with apolipoprotein E variants

• Metabolic disorder investigations:

  • MSMO1 expression changes in obesity and diabetes

  • Relationship to insulin resistance mechanisms

  • Potential as therapeutic target for metabolic interventions