metrnl Antibody

What is METRNL protein and why is it significant for research?

METRNL (Meteorin-like protein/IL-41) is a secreted protein with diverse physiological roles in immune regulation, metabolism, and tissue repair. It functions as a cytokine/myokine that modulates inflammatory responses across multiple tissues. Research significance stems from its involvement in:

• Immune system modulation, particularly affecting Type 2 immune responses

• Regulation of glucose metabolism via AMPK pathways

• Anti-inflammatory properties in conditions like atopic dermatitis and arthritis

• Adipose tissue thermogenesis and energy expenditure

• Potential therapeutic applications in metabolic and inflammatory disorders

METRNL's 34.4 kDa molecular structure is typically detected at 30-35 kDa on Western blots, though post-translational modifications may result in bands between 34-43 kDa .

Which experimental techniques are most effective for detecting METRNL expression?

Multiple validated techniques can detect METRNL expression with specific methodological considerations:

Western Blotting:

• Recommended dilutions: 1:500-1:5000

• Sample preparation: Use reducing conditions with appropriate buffer groups (e.g., Immunoblot Buffer Group 8)

• Expected molecular weight: ~30 kDa under reducing conditions

• Validation method: Include recombinant METRNL protein as positive control

Immunohistochemistry:

• Recommended dilutions: 1:20-1:200

• Detection pattern: Strong signals in keratinocytes and infiltrating immune cells in inflammatory conditions

• Counterstaining: Can be combined with CD11b/CD11c for co-localization studies

ELISA:

• Recommended dilutions: 1:2000-1:10000

• Pair with monoclonal detection antibody for sandwich ELISA development

• Validate specificity through antigen-antibody neutralization experiments

Multiplex Immunofluorescence:

• Effectively distinguishes METRNL-expressing cell types (macrophages/CD163+, eosinophils/Siglec-F+, keratinocytes)

• Enable co-localization studies with cellular markers for detailed expression patterns

How should researchers validate METRNL antibody specificity?

Thorough validation requires multiple complementary approaches:

• Antigen competition assay: Pre-incubate antibody with recombinant METRNL protein before application to verify signal reduction

• Western blot validation:

  • Compare bands from recombinant protein with endogenous samples

  • Confirm molecular weight (~30-35 kDa depending on post-translational modifications)

  • Test antibody in METRNL knockout/knockdown models to confirm signal absence

• Cross-reactivity assessment:

  • Test against related proteins (e.g., Meteorin)

  • Verify species specificity with orthologous proteins (many antibodies show cross-reactivity between human, mouse, and rat METRNL)

• Immunoprecipitation validation:

  • Perform mass spectrometry on immunoprecipitated proteins to confirm identity

  • Use two different antibodies targeting different epitopes for confirmation

• Biological validation:

  • Correlate antibody signal with mRNA expression data

  • Verify increased staining in tissues known to express METRNL (e.g., skeletal muscle after exercise)

How can single-cell analysis be optimized for studying METRNL expression patterns in heterogeneous tissues?

Single-cell analysis of METRNL requires methodological refinement for accurate expression profiling:

• Tissue dissociation optimization:

  • Use gentle enzymatic dissociation to preserve cell surface proteins

  • Implement immediate RNA stabilization to prevent artificial expression changes

  • Validate dissociation protocols with known METRNL-expressing cells (e.g., macrophages, keratinocytes)

• scRNA-seq considerations:

  • Implement sufficient sequencing depth (>50,000 reads/cell) to detect METRNL's variable expression

  • Apply computational correction for dropout events using established algorithms

  • Validate expression patterns with immunofluorescence on tissue sections

• Cell cluster interpretation:

  • METRNL exhibits broad expression across multiple cell types including:

    • Spinous keratinocytes

    • Fibroblasts

    • Macrophage/Monocyte/DC populations

    • Mast cells with KIT receptor expression

  • Analyze expression dynamics across disease progression and treatment conditions

• Functional validation:

  • Correlate METRNL expression with pathway activities (e.g., WNT signaling)

  • Profile co-expression with cell type-specific markers to identify functional subpopulations

  • Track temporal expression changes following stimulation

Single-cell RNA-seq analysis has revealed distinct patterns of METRNL expression in myeloid lineages (monocytes, macrophages, dendritic cells) with dynamic changes following tissue injury that parallel whole-tissue expression patterns .

What are the methodological considerations for studying METRNL signaling pathways in different cellular contexts?

METRNL activates distinct signaling pathways in different cellular contexts, requiring tailored experimental approaches:

• Skeletal muscle cells (metabolic signaling):

  • Monitor AMPK pathway activation: phosphorylation of AMPKα2, ACC, TBC1D1

  • Track HDAC5 phosphorylation and cytoplasmic translocation

  • Assess GLUT4 transcription and membrane translocation

  • Measure 14-3-3 protein interactions with phosphorylated HDAC5

  • Evaluate glucose uptake with 2-NBDG or radiolabeled glucose

• Immune cells (anti-inflammatory signaling):

  • Assess Type 2 immune cascade activation (IL-4/IL-13)

  • Measure M2 macrophage polarization markers

  • Evaluate dendritic cell maturation markers (CD80, CD86, MHC-II)

  • Analyze T-cell proliferation in co-culture systems

  • Monitor WNT/β-catenin pathway activation

• Adipose tissue (thermogenic signaling):

  • Track thermogenic gene expression (UCP-1, DIO2, PGC-1α, ERRα)

  • Measure β-oxidation gene expression (Acsl1, Acox1, Cpt1)

  • Assess catecholamine production

  • Evaluate whole-body fat content changes

• Skin cells (anti-inflammatory signaling):

  • Monitor KIT receptor binding and signaling

  • Assess WNT pathway activation through β-catenin levels

  • Measure Th2-related chemokine/cytokine expression

  • Track Arginase-1 expressing macrophage populations

How should researchers address contradictory findings regarding METRNL's role in different disease contexts?

Resolving contradictory findings requires systematic methodological approaches:

• Context-dependent expression analysis:

  • METRNL is upregulated in inflammatory conditions (atopic dermatitis, rheumatoid arthritis)

  • Yet downregulated in others (Graves' disease, osteoarthritis)

  • Temporal analysis throughout disease progression is essential

  • Comparative analysis across different affected tissues within the same disease model

• Dual pro/anti-inflammatory roles reconciliation:

  • Categorize experimental models by:

    • Acute vs. chronic inflammation

    • Tissue-specific responses

    • Underlying pathophysiology (autoimmune vs. metabolic)

  • Document inflammatory markers alongside METRNL levels

  • Assess local vs. systemic METRNL concentrations

• Functional validation approaches:

  • Gain/loss of function studies with recombinant protein administration

  • Blocking antibodies to inhibit endogenous METRNL function

  • Temporal control of METRNL expression using inducible systems

  • Cell type-specific conditional knockout models

• Standardized quantification methods:

  • Implement absolute quantification standards for METRNL protein levels

  • Report fold changes relative to appropriate controls

  • Validate findings across multiple antibody clones

  • Correlate protein levels with gene expression data

What are the critical parameters for optimizing METRNL protein detection in different tissue samples?

Optimizing METRNL detection requires tissue-specific methodology adjustments:

• Skin tissue:

  • Fixation: 4% paraformaldehyde for 24h optimal for epitope preservation

  • Antigen retrieval: Citrate buffer (pH 6.0) heat-mediated retrieval

  • Blocking: Use 5% normal serum from antibody host species

  • Primary antibody dilution: 1:20-1:200 range with overnight incubation

  • Detection system: HRP-polymer systems offer better signal-to-noise than avidin-biotin

• Skeletal muscle:

  • Sample timing: Collect 1-4h post-exercise for peak expression

  • Cryosectioning recommended over paraffin embedding

  • Co-staining with fiber-type markers for localization

  • Cell fractionation required for subcellular localization studies

• Adipose tissue:

  • Lipid removal essential for consistent staining

  • Longer primary antibody incubation (48h at 4°C)

  • Higher antibody concentration may be required

  • Validate with both WAT and BAT tissues for comparison

• Immune cells:

  • Flow cytometry: Fixation/permeabilization optimization critical

  • Fresh vs. frozen samples yield significantly different results

  • CD11b/CD163 co-staining identifies METRNL-expressing macrophages

  • Careful gating strategy implementation for rare cell populations

How can researchers effectively investigate temporal changes in METRNL expression during disease progression or treatment?

Effective temporal profiling requires comprehensive experimental design:

• Sampling strategy:

  • Establish clear baseline measurements before intervention

  • Multiple timepoints (early: 1-4h, intermediate: 24-72h, late: 7-14d)

  • Parallel tissue and serum collection for local vs. systemic correlation

  • Consider circadian variations in expression

• Quantification approaches:

  • Western blot with densitometry for relative protein changes

  • ELISA for absolute quantification in serum/plasma

  • qPCR for mRNA expression dynamics

  • Tissue section quantification with digital image analysis

• Intervention-specific considerations:

  • Exercise models: Sample at rest, immediate post-exercise, 1h, 4h, 24h

  • Inflammatory models: Pre-inflammation, peak inflammation, resolution phase

  • Treatment response: Pre-treatment, early response, stable response periods

  • Disease progression: Stratify samples by clinical disease severity

• Control implementation:

  • Age/sex-matched non-intervention controls at each timepoint

  • Vehicle-only controls for treatment studies

  • Multiple housekeeping proteins for normalization

  • Technical replicates to account for assay variability

Studies have shown that METRNL expression peaks approximately 1h post-exercise in humans, with corresponding increases in circulating levels detected by 24h . In disease models like atopic dermatitis, METRNL levels progressively increase with repeated inflammatory stimulation .

What technical challenges should researchers anticipate when working with METRNL knockout/knockdown models?

METRNL genetic manipulation presents specific technical challenges requiring methodological adaptation:

• Model generation considerations:

  • Complete knockout may affect B-cell immune system development

  • Consider tissue-specific conditional knockouts to avoid developmental effects

  • Inducible systems provide temporal control of expression

  • Verify knockdown efficiency at both mRNA and protein levels

• Phenotypic characterization approach:

  • Baseline immunophenotyping essential (lower serum IgG levels, particularly IgG2b and IgG3)

  • Assess chemokine production capacity (CCL3, CCL4)

  • Measure glucose tolerance and insulin sensitivity

  • Evaluate inflammatory responses in challenge models

• Compensatory mechanism assessment:

  • Monitor related family members (Meteorin) for compensatory upregulation

  • Assess alternate pathway activation (insulin signaling vs. AMPK pathway)

  • Evaluate changes in receptor expression profiles

  • Consider microbiome analysis for metabolic phenotypes

• Experimental controls:

  • Include heterozygous models alongside homozygous knockouts

  • Use both global and tissue-specific knockouts for comparison

  • Implement rescue experiments with recombinant protein administration

  • Age/sex-matched wild-type controls from same breeding colony

METRNL knockout models have shown specific phenotypes including defects in B-cell immune function, impaired chemokine secretion, reduced interferon levels, and altered MHC-II expression in peritoneal macrophages . When studying glucose metabolism, validation in AMPK β1β2 muscle-specific null mice provides critical mechanistic insights .

How should researchers design experiments to investigate METRNL's role in autoimmune diseases?

Systematic experimental design for autoimmune disease research requires:

• Disease model selection:

  • Type 1 diabetes: Non-obese diabetic (NOD) mice model

  • Rheumatoid arthritis: Collagen-induced arthritis model

  • Graves' disease: TSH receptor immunization model

  • Multiple sclerosis: Experimental autoimmune encephalomyelitis model

• Intervention timing and delivery:

  • Preventive administration (before disease onset)

  • Therapeutic administration (after disease establishment)

  • Delivery routes: Intravenous, intraperitoneal, or local administration

  • Dosage optimization through dose-response experiments

• Outcome measurements:

  • Clinical scores and disease progression metrics

  • Immune cell profiling (flow cytometry for T-cell, B-cell, macrophage subsets)

  • Cytokine/chemokine profiling (IL-4, IL-10, IL-2, IL-17, IFN-γ)

  • Tissue-specific pathology assessment

• Translational validation:

  • Correlate with human patient sample analysis

  • Compare tissue and circulation levels in matched cohorts

  • Stratify analysis by disease severity and treatment response

  • Perform ex vivo validation with patient-derived cells

Research has demonstrated that METRNL administration can delay onset of type 1 diabetes in NOD mice by reducing islet lymphocyte infiltration and modulating immune cell responses . In rheumatoid arthritis, METRNL levels are elevated in synovial fluid compared to osteoarthritis, positively correlating with disease activity indices .

What methodological approaches are most effective for investigating METRNL's metabolic functions?

Comprehensive metabolic function analysis requires multi-level experimental approaches:

• In vitro metabolic assessments:

  • Glucose uptake assays in skeletal muscle cells (L6 myotubes, C2C12)

  • GLUT4 translocation assays using membrane fractionation

  • AMPK pathway activation measurements

  • ChIP assays for HDAC5 binding to GLUT4 promoter

• Ex vivo tissue analysis:

  • Isolated skeletal muscle (EDL) glucose uptake measurements

  • Adipose tissue explant thermogenic response

  • Pancreatic islet function assessment

  • Primary cell culture from relevant tissues

• In vivo metabolic phenotyping:

  • Glucose tolerance tests following recombinant METRNL administration

  • Insulin tolerance tests

  • Metabolic cage studies for energy expenditure

  • Body composition analysis (MRI for fat mass quantification)

• Mechanistic validation approaches:

  • Compound C (AMPK inhibitor) administration

  • Genetic models (AMPK β1β2 muscle-specific null mice)

  • RNA interference for pathway components

  • Pharmacological targeting of downstream effectors

Research has established that METRNL improves glucose tolerance both in skeletal muscle cells and in mice through the AMPKα2 pathway . Specifically, METRNL increases glucose uptake by promoting GLUT4 transcription through HDAC5 phosphorylation and cytoplasmic sequestration, as well as enhancing GLUT4 translocation via TBC1D1 phosphorylation .

How can researchers effectively investigate METRNL's role in inflammatory skin conditions?

Investigating METRNL in skin inflammation requires specialized methodological approaches:

• Model selection and characterization:

  • MC903 (vitamin D3 analogue)-induced atopic dermatitis model

  • Imiquimod-induced psoriasis model

  • Contact hypersensitivity models

  • Human skin explant cultures

• Treatment design and administration:

  • Recombinant murine METRNL protein (rmMETRNL) administration schedules

  • Topical vs. systemic delivery comparison

  • Preventive vs. therapeutic intervention timing

  • METRNL-blocking antibody controls

• Comprehensive outcome measures:

  • Clinical scoring (erythema, scaling, infiltration)

  • Histopathological analysis

  • Immune cell profiling by flow cytometry

  • Single-cell RNA sequencing for detailed cellular responses

  • WNT/β-catenin pathway activation assessment

• Mechanistic investigations:

  • KIT receptor binding and signaling pathway analysis

  • Th2-related molecule expression profiling

  • Arginase-1hi macrophage quantification and characterization

  • In vitro keratinocyte and immune cell co-culture systems

Studies have demonstrated that METRNL expression is significantly elevated in lesional skin and serum from atopic dermatitis patients . Administration of rmMETRNL ameliorates allergic skin inflammation by enhancing β-catenin activation and limiting Th2-related inflammatory responses that attract macrophages, dendritic cells, and activated mast cells .

What are common sources of variability in METRNL antibody performance and how can they be addressed?

Addressing variability requires systematic troubleshooting:

• Antibody-related factors:

  • Lot-to-lot variation: Validate each new lot against previous standards

  • Polyclonal vs. monoclonal considerations: Polyclonals offer higher sensitivity but greater variability

  • Storage conditions: Aliquot antibodies to avoid freeze-thaw cycles

  • Concentration verification: Periodically check protein concentration

• Protocol optimization:

  • Blocking buffer composition: Optimize serum type and concentration

  • Incubation conditions: Temperature and duration significantly affect binding

  • Washing stringency: Balance between signal retention and background reduction

  • Detection system sensitivity: Choose based on expected expression level

• Sample preparation considerations:

  • Fixation methods affect epitope accessibility

  • Protein extraction buffers impact protein conformation

  • Fresh vs. frozen tissue comparison

  • Tissue section thickness standardization

• Quality control implementation:

  • Include positive control samples with known METRNL expression

  • Implement negative controls (isotype, secondary-only, blocking peptide)

  • Use recombinant METRNL protein standards

  • Document antibody validation data comprehensively

How can researchers reconcile differences between mRNA and protein expression data for METRNL?

Addressing mRNA-protein discrepancies requires systematic investigation:

• Technical validation approaches:

  • Verify primer specificity for qPCR (METRNL has homology with related genes)

  • Confirm antibody specificity with knockout/knockdown controls

  • Use multiple primer pairs and antibody clones targeting different epitopes

  • Implement absolute quantification methods for both mRNA and protein

• Biological considerations:

  • Post-transcriptional regulation: microRNA targeting of METRNL transcripts

  • Post-translational modifications affecting antibody recognition

  • Protein secretion/transport from production site

  • Protein stability and turnover rates

• Temporal dynamics analysis:

  • Time-course sampling to capture lag between transcription and translation

  • Consider circadian rhythms affecting expression

  • Stress/stimulus response timing

  • Disease stage progression

• Spatial expression reconciliation:

  • Cell type-specific expression patterns

  • In situ hybridization combined with immunohistochemistry

  • Subcellular localization studies

  • Secreted vs. cell-associated protein fractions

Studies have shown temporal discrepancies between METRNL mRNA upregulation and protein accumulation following exercise, with mRNA peaking at 1h post-exercise while circulating protein levels reach maximum at 24h .

What special considerations apply when detecting METRNL in different biological fluids?

Biological fluid analysis requires specialized methodology:

• Serum/plasma considerations:

  • Sample collection timing: Standardize fasting/fed state

  • Anticoagulant effects: EDTA vs. heparin vs. citrate

  • Processing time: Minimize proteolytic degradation

  • Storage conditions: -80°C with protease inhibitors

  • Expected concentration range: Detectable but low (requires sensitive ELISA)

• Synovial fluid analysis:

  • Dilution requirements due to high METRNL concentrations in inflammatory arthritis

  • Hyaluronic acid interference mitigation

  • Cellular contamination minimization

  • Comparative analysis with matched serum samples

• Other biological fluids:

  • Cerebrospinal fluid: Low protein content requires concentration

  • Bronchoalveolar lavage fluid: Standardize collection volume

  • Urine: Normalization to creatinine levels

  • Cell culture supernatants: Serum-free conditions for detection

• Validation approaches:

  • Spike-in recovery experiments to assess matrix effects

  • Serial dilution linearity testing

  • Comparison of multiple detection methods

  • Reference ranges establishment for each fluid type