MUC17 Recombinant Monoclonal Antibody

What is MUC17 and why is it significant in research?

MUC17 (also known as MUC3) is a transmembrane mucin encoded by the MUC17 gene located at chromosome 7q22.1 between MUC12 and SERPINE1 genes. It spans a 39-kb DNA fragment with 13 exons, producing a 14.2-kb mRNA . This large glycoprotein (approximately 494 kDa, 4493 amino acids) contains a signal peptide, a large tandemly repeated central domain, two epidermal growth factor (EGF)-like domains, a SEA domain, a transmembrane domain, and an 80-amino acid cytoplasmic tail .

MUC17 is significant in research due to its:

• Role in maintaining homeostasis on mucosal surfaces

• Function in protecting intestinal epithelial cells against bacterial invasion

• Potential as a tumor-associated antigen in gastric/gastroesophageal junction cancers

• Protective role during inflammation, particularly against enteropathogenic E. coli

• Potential tumor suppressor function in colorectal cancer

• Therapeutic target potential for pancreatic cancer

What are the structural and functional differences between recombinant MUC17 antibodies and traditional antibodies?

Recombinant MUC17 antibodies offer several advantages over traditional antibodies:

Structural differences:

• Recombinant antibodies are produced using defined DNA sequences expressed in controlled expression systems (often CHO cells)

• They have consistent amino acid sequences with batch-to-batch uniformity

• Available in various formats including full IgG, ready-for-conjugation, and matched antibody pairs

Functional differences:

• Increased sensitivity in detection applications

• Confirmed specificity with reduced cross-reactivity

• High repeatability in experimental results

• Excellent batch-to-batch consistency, eliminating variability seen in traditional polyclonal antibodies

• Sustainable supply without animal dependency

• Ability to be used in matched pair formats for complex assays

How should I optimize immunohistochemistry protocols when using anti-MUC17 recombinant antibodies?

Optimizing immunohistochemistry (IHC) protocols with anti-MUC17 recombinant antibodies requires systematic approach:

Tissue preparation:

• Use paraffin-embedded tissues with standard fixation protocols

• For human small intestine tissue, which shows high MUC17 expression, dilution ratios of 1/20 have been successful

• For other recommended human tissues, dilutions of 1:500-1:1000 have been reported

Antigen retrieval:

• Heat-induced epitope retrieval in citrate buffer (pH 6.0) is recommended

• Alternative buffers may be tested if staining is suboptimal

Antibody incubation:

• Start with manufacturer's recommended dilution (often 1:50-200 for IHC)

• Perform titration experiments (1:20, 1:50, 1:100, 1:200, 1:500) to determine optimal signal-to-noise ratio

• Incubate at 4°C overnight or 1-2 hours at room temperature

Detection systems:

• Use high-sensitivity detection systems compatible with rabbit or human IgG depending on the host species

• Include appropriate positive control tissues (small intestine) and negative controls

• If background is high, implement additional blocking steps

Validation:

• Compare staining patterns with expected cellular localization (membrane/cytoplasmic in intestinal epithelium)

• Verify specificity through siRNA knockdown controls when possible

What are the optimal parameters for using MUC17 antibodies in multiplex assays?

When using MUC17 antibodies in multiplex assays, several parameters need careful optimization:

For cytometric bead arrays:

• Use validated matched antibody pairs (e.g., MP00499-1 targeting MUC17)

• Working range for cytometric bead array: 0.156-20 ng/mL

• Capture antibody: Use recombinant antibody at 1 mg/mL concentration

• Detection antibody: Use compatible detector antibody (e.g., 83528-3-PBS)

For other multiplex platforms:

• When using in FRET/TR-FRET/HTRF, optimize donor-acceptor pair distances

• For AlphaLISA®, Simoa®, or Meso Scale Discovery® platforms, follow platform-specific optimization protocols

• Always include standard curve using recombinant MUC17 protein standard (e.g., Eg0413)

Cross-reactivity considerations:

• Test for cross-reactivity with other mucins (especially MUC3) due to structural similarities

• Include isotype controls and technical replicates

• Titrate antibody concentrations to minimize non-specific binding

Signal optimization:

• Conjugate antibodies with appropriate fluorophores/enzymes that have minimal spectral overlap

• Validate each antibody individually before combining in multiplex format

• Account for potential steric hindrance when multiple antibodies target the same protein

How can I address inconsistent MUC17 detection in patient samples?

Inconsistent MUC17 detection in patient samples can stem from multiple factors that require systematic troubleshooting:

Biological variability factors:

• MUC17 expression varies by tissue type and pathological state

• In colorectal cancer, MUC17 shows punctate staining in 44% of cases and complete lack/diffuse low levels in 56% of cases

• Inflammatory conditions may upregulate MUC17 expression (e.g., TNFα stimulation)

Technical considerations:

• Fixation variability: Standardize fixation time and conditions; over-fixation can mask epitopes

• Antibody selection: Different antibody clones may recognize different epitopes affected by glycosylation

• Epitope accessibility: MUC17's extensive glycosylation can mask epitopes; consider neuraminidase treatment

• Sample storage: Degradation may occur; analyze freshly prepared or properly stored samples

• Protocol consistency: Use automated staining platforms when possible

Validation approaches:

• Use multiple antibodies targeting different MUC17 epitopes

• Include patient-matched normal tissue controls

• Employ mRNA detection methods (RT-qPCR, RNA-seq) as orthogonal validation

• Consider glycoprotein-specific staining methods to confirm mucin presence

Data interpretation guidelines:

• Document staining patterns (membrane, cytoplasmic, punctate)

• Score intensity and percentage of positive cells

• Correlate with clinical parameters to identify meaningful patterns

• Consider TNFα or inflammatory status as potential confounding factors

What are the critical quality control parameters for validating MUC17 antibody specificity in research applications?

Critical quality control parameters for validating MUC17 antibody specificity include:

Positive controls:

• Cell lines with confirmed MUC17 expression (intestinal epithelial cell lines)

• Human small intestine tissue sections

• Recombinant MUC17 protein

Negative controls:

• MUC17 knockdown cell lines (siRNA or CRISPR)

• Tissues known not to express MUC17

• Pre-adsorption with immunizing peptide

Cross-reactivity assessment:

• Test against other mucin family members, particularly MUC3

• Perform western blot to confirm molecular weight specificity (expected ~494 kDa)

• Verify glycosylated vs. unglycosylated protein detection

Orthogonal validation:

• Correlate with RNA-seq data

• Compare results from multiple antibody clones

• Validate with mass spectrometry when feasible

Batch testing:

• Perform lot-to-lot comparison with standardized samples

• Document batch information and maintain reference standards

• Test sensitivity across batches using dilution series

Application-specific validation:

• For IHC: Assess staining pattern, background, and reproducibility

• For Western blot: Verify band size and specificity

• For ELISA/multiplex: Test linearity, recovery, and precision

How can MUC17 antibodies be utilized to investigate the role of glycosylation patterns in mucin function?

MUC17 antibodies can be powerful tools for investigating glycosylation patterns through several advanced approaches:

Epitope-specific antibody selection:

• Choose antibodies recognizing protein backbone versus glycosylation-dependent epitopes

• Utilize antibodies targeting specific glycan structures present on MUC17

• Compare detection before and after glycosidase treatment to map glycosylation sites

Methodological approaches:

• Sequential deglycosylation: Treat samples with specific glycosidases (neuraminidase, O-glycosidase, PNGase F) before antibody application

• Lectin co-labeling: Combine MUC17 antibodies with various lectins to identify specific glycan structures

• Proximity ligation assays: Detect spatial relationships between MUC17 protein backbone and specific glycan modifications

• Mass spectrometry integration: Use antibodies for immunoprecipitation followed by glycoproteomic analysis

Functional correlation studies:

• Compare glycosylation patterns between normal and disease states (inflammatory conditions, cancer)

• Assess how glycosylation influences bacterial interaction with MUC17-expressing cells

• Evaluate the impact of glycosylation on MUC17 shedding and turnover rates

Technical considerations:

• Preserve native glycosylation through gentle sample preparation

• Use multiple fixation methods to retain different glycan epitopes

• Consider the impact of sample source (cell lines vs. tissue) on glycosylation complexity

What are the molecular mechanisms through which MUC17 contributes to bacterial defense and how can antibodies help elucidate these pathways?

MUC17's role in bacterial defense involves complex molecular mechanisms that can be investigated using antibodies:

Barrier function mechanisms:

• Physical barrier: MUC17's large extracellular domain creates steric hindrance

• Shedding mechanism: Similar to MUC1, MUC17 may act as a sheddable decoy for bacterial binding

• Glycan-mediated binding: Specific bacteria may be trapped by glycan structures on MUC17

Signal transduction investigation:

• The cytoplasmic domain of MUC17 contains potential phosphorylation sites that may mediate signal transduction

• Phospho-specific antibodies can help identify activated signaling pathways

• Antibodies against the cytoplasmic domain can be used to co-immunoprecipitate binding partners

Antibody-based experimental approaches:

• Antibody blocking experiments: Use antibodies targeting different MUC17 domains to block specific functions during bacterial challenge

• Live cell imaging: Fluorescently labeled antibodies can track MUC17 redistribution during bacterial interaction

• Domain-specific knockout models: Compare bacterial susceptibility in cells expressing truncated MUC17 variants

• Proximity labeling: Use antibody-enzyme conjugates to identify proteins interacting with MUC17 during bacterial exposure

Research observations and directions:

• TNFα stimulation increases MUC17 expression, suggesting a role in inflammatory response

• MUC17 suppression in intestinal cell lines increases susceptibility to bacterial invasion

• Investigating whether modifications of MUC17's extracellular domain alter its protective properties against different bacterial species

• Determining if MUC17's protective role extends beyond enteropathogenic E. coli to other pathogens

How do MUC17 expression levels correlate with cancer progression, and what experimental design would best capture this relationship?

Understanding MUC17's correlation with cancer progression requires carefully designed experimental approaches:

Observed expression patterns:

• Colorectal cancer: Loss of punctate MUC17 staining pattern associated with aggressive behavior and shortened patient survival

• Gastric/gastroesophageal junction cancer: MUC17 overexpression observed on cell membranes

• Pancreatic cancer: MUC17 identified as a potential therapeutic target

Optimal experimental design:

• Comprehensive tissue analysis:

  • Use tissue microarrays spanning different cancer types and stages

  • Include matched normal-adjacent tissue, preneoplastic lesions, and tumor samples

  • Quantify both expression intensity and localization pattern

• Multi-modal analysis protocol:

  • IHC with recombinant MUC17 antibodies at standardized dilutions (1:50-1:200)

  • Transcript analysis (RT-qPCR, RNA-seq) for correlation with protein levels

  • Analysis of MUC17 glycosylation changes during progression

• Functional correlation studies:

  • siRNA knockdown in cell lines to assess proliferation, migration, invasion

  • Clonogenic assays before and after MUC17 modulation

  • Analysis of cell cycle distribution using flow cytometry

• Statistical analysis approach:

  • Correlate MUC17 expression with clinicopathological parameters

  • Survival analysis stratified by MUC17 expression patterns

  • Multivariate analysis to control for confounding factors

Interpretive framework:

• Consider tissue-specific roles (tumor suppressor in colorectal cancer vs. potential oncogenic role in gastric cancer)

• Evaluate expression in context of inflammatory markers

• Analyze subcellular localization changes during progression

• Document glycosylation pattern alterations alongside expression levels

What are the optimal storage conditions and handling protocols for maintaining MUC17 recombinant antibody activity?

Proper storage and handling of MUC17 recombinant antibodies are crucial for maintaining their activity:

Storage temperature requirements:

• Store unconjugated antibodies at -20°C for general long-term storage

• For unconjugated antibodies in PBS only format, store at -80°C

• Avoid repeated freeze-thaw cycles that can lead to antibody degradation

• Working aliquots can be stored at 4°C for frequent use (up to 1 month)

Buffer composition considerations:

• Many MUC17 recombinant antibodies are supplied in:

  • PBS only (BSA and azide free) at 1 mg/mL concentration

  • PBS, pH 7.4, containing 0.02% NaN3, 50% glycerol

• For conjugation-ready formats, maintain in buffer without BSA or azide

Reconstitution protocol:

• For lyophilized antibodies, reconstitute with sterile distilled water to 1 mg/mL

• Gently mix to solubilize the protein completely; do not vortex

• Allow complete dissolution before aliquoting

Stability parameters:

• Thermal stability testing shows <5% loss rate when stored properly

• Accelerated thermal degradation test (37°C for 48h) can be used to assess stability

• Document lot number and receipt date for traceability

Handling best practices:

• Minimize exposure to light, especially for fluorophore-conjugated antibodies

• Use sterile technique when opening and sampling from antibody vials

• Centrifuge briefly before opening to collect solution at the bottom of the tube

• Use low protein-binding tubes for dilutions and storage

How should researchers design experiments to compare the performance of different MUC17 antibody clones in specialized applications?

Designing comparative experiments for MUC17 antibody clones requires systematic planning:

Standardized sample preparation:

• Use identical sample processing for all antibody evaluations

• Include positive controls (small intestine tissue, MUC17-expressing cell lines)

• Prepare negative controls (MUC17-knockout or low-expressing samples)

Antibody performance parameters to assess:

• Sensitivity: Determine limit of detection using dilution series

• Specificity: Evaluate cross-reactivity with other mucins

• Signal-to-noise ratio: Compare background staining levels

• Reproducibility: Assess intra- and inter-assay variability

• Epitope accessibility: Compare performance in native vs. denatured conditions

Application-specific comparison designs:

Data recording and analysis:

• Document all antibody details (clone, lot, concentration, source)

• Use quantitative image analysis for IHC/ICC comparisons

• Calculate performance metrics for each clone across applications

• Create decision matrix to determine optimal clone for each application

Experimental controls:

• Include isotype controls matched to each antibody

• Use pre-adsorption controls when available

• Incorporate orthogonal validation (e.g., transcript analysis)

• Evaluate performance across multiple tissue/cell types

By implementing this structured approach, researchers can objectively compare antibody performance and select the optimal clone for their specific research questions.