MEF2C regulates gene expression in muscle, neuronal, and cardiovascular systems. Phosphorylation at S387 modulates its activity, influencing critical cellular processes:
Post-translational modifications, including phosphorylation and sumoylation, fine-tune MEF2C’s nuclear localization and DNA-binding capacity .
Dot Blot: Validated at 0.5 µg/mL for detecting phosphorylated MEF2C .
Immunohistochemistry (IHC): Effective at 1:100–1:300 dilution in human tissues .
Immunofluorescence (IF): Used to study subcellular localization in neuronal and muscle cells .
Blocking: Requires non-phospho-specific peptide pre-adsorption to confirm specificity .
Cross-Reactivity: Predicted for pig due to sequence homology .
Studies utilizing this antibody have revealed:
Kinase Interactions: Phosphorylation at S387 by CDK5 enhances MEF2C’s transcriptional activity in neuronal cells .
Neurotoxicity: Caspase-7 cleaves hyperphosphorylated MEF2C under neurotoxic conditions, promoting apoptosis .
Cardiac Development: MEF2C phosphorylation is critical for heart valve formation in zebrafish models .
B-Cell Function: Phosphorylated MEF2C supports antibody class switching to IgG1 in germinal centers .
The antibody has been cited in peer-reviewed studies, including:
MEF2C (Myocyte-specific enhancer factor 2C) is a transcription activator that binds specifically to the MEF2 element present in regulatory regions of many muscle-specific genes. Beyond muscle development, MEF2C controls cardiac morphogenesis, vascular development, and is crucial for neuronal development. It also plays essential roles in B-lymphopoiesis, being required for B-cell survival and proliferation in response to BCR stimulation . The phosphorylation at S387 is particularly significant as it is one of the key sites phosphorylated by p38 MAPK, alongside threonines 293 and 300, within the MEF2C transactivation domain. This phosphorylation event regulates the transactivation activity of MEF2C and plays an important role in the regulation of c-Jun expression in monocytic cells .
The primary validated application for this antibody is dot blotting, with a recommended working concentration of 0.5μg per ml . In dot blot analysis, the antibody demonstrates specific recognition of phosphorylated MEF2C at S387, as shown in validation studies where 50ng of phospho-peptide or non-phospho-peptide were adsorbed on nitrocellulose membrane . While not explicitly validated for other applications, researchers may explore its utility in Western blotting, immunoprecipitation, or immunofluorescence with appropriate optimization and validation protocols.
For optimal antibody performance, short-term storage (up to 2 weeks) should be at 2-8°C, while long-term storage requires -20°C in small aliquots to prevent freeze-thaw cycles . The antibody is supplied in PBS with 0.09% (W/V) sodium azide, which helps preserve its activity . When working with the antibody, always use clean pipettes to avoid contamination and make small working aliquots from the stock solution to minimize freeze-thaw cycles, which can degrade antibody performance. The manufacturer indicates a shelf life of 12 months from the date of shipment when stored properly .
To validate specificity of the phospho-signal, implement multiple complementary approaches:
Phosphatase treatment: Treat a portion of your sample with lambda phosphatase to verify signal reduction if it's truly phospho-specific.
Peptide competition: Preincubate the antibody with the phosphopeptide used for immunization, which should block specific signal, whereas preincubation with non-phosphorylated peptide should not affect signal detection .
Kinase inhibition/activation: Treat cells with p38 MAPK inhibitors to reduce phospho-signal, while treatment with p38 MAPK activators should enhance it, as p38 is the primary kinase for S387 .
Mutagenesis studies: Express wild-type MEF2C alongside S387A mutant (which cannot be phosphorylated at this site) to confirm the antibody only detects the wild-type protein following appropriate stimulation.
Two-dimensional immunoblot: As demonstrated in research studies, 2D immunoblots can reveal phosphorylation-dependent mobility shifts in MEF2C .
A robust experimental design for studying MEF2C phosphorylation should include several controls:
| Control Type | Description | Purpose |
|---|---|---|
| Positive Control | Cells treated with p38 MAPK activators | Confirm antibody can detect increased phosphorylation |
| Negative Control | Cells treated with p38 MAPK inhibitors or phosphatase | Verify reduction of phospho-specific signal |
| Loading Control | Total MEF2C detection | Normalize phospho-MEF2C signal to total protein |
| Specificity Control | Phosphopeptide competition | Confirm signal is specific to phosphorylated epitope |
| Technical Control | Non-phosphorylated peptide competition | Should not affect specific signal detection |
| Biological Control | S387A mutant MEF2C expression | Verify antibody does not detect non-phosphorylatable variant |
Always normalize phospho-MEF2C signal to total MEF2C levels to account for variations in protein expression across samples .
When working with phospho-specific antibodies like anti-Phospho-MEF2C(S387), researchers may encounter several common issues:
High background: Optimize blocking conditions (test BSA vs. non-fat dry milk), increase washing steps, and adjust antibody concentration from the recommended 1:500 dilution .
Loss of phosphorylation during sample preparation: Always prepare samples with phosphatase inhibitors and maintain cold temperature throughout processing to preserve phosphorylation status.
Temporal dynamics: Phosphorylation events can be transient. Consider time-course experiments to capture the optimal window for S387 phosphorylation, particularly following BCR stimulation or p38 MAPK pathway activation .
Context-dependent phosphorylation: The phosphorylation of S387 depends on cell type and stimulus. For example, BCR stimulation in B cells results in detectable phosphorylation of MEF2C that can be visualized by 2D immunoblot showing multiple phosphorylated forms .
Cross-reactivity: Verify specificity through peptide competition assays and consider using additional detection methods to confirm phosphorylation status.
The p38 MAPK pathway is the primary regulator of MEF2C S387 phosphorylation. When activated, p38 directly phosphorylates MEF2C at three key residues in the transactivation domain: serine 387 and threonines 293 and 300 . This p38-mediated phosphorylation enhances the transcriptional activity of MEF2C. The pathway can be activated by various stimuli including stress, inflammatory cytokines, and specific receptor signaling events such as B-cell receptor (BCR) activation .
In B cells, BCR stimulation leads to phosphorylation of MEF2C, which can be visualized by 2D immunoblot showing the appearance of additional spots representing phosphorylated forms of MEF2C . This phosphorylation is functionally significant, as a phosphorylation-mutant form of MEF2C (P-mut) inhibits BCR-dependent activation of MEF2-dependent reporters, suggesting that phosphorylation is required for proper MEF2C function in the context of BCR signaling .
MEF2C plays a critical role in B-cell biology, with its phosphorylation serving as a key regulatory mechanism:
B-cell proliferation and survival: MEF2C is required for B-cell survival and proliferation in response to BCR stimulation, with p38 directly phosphorylating MEF2C to drive these processes .
Humoral immune response: Mef2c knockout mice exhibit reduced immune responses, specifically with reduced peak IgG1 titers on immunization with T-dependent antigens, demonstrating an approximately 80% reduction in germinal center B cells .
BCR signaling transduction: MEF2C acts as a direct transcriptional effector downstream of BCR signaling via the p38 MAPK cascade. Stimulation of the BCR results in phosphorylation of MEF2C, which is required for its function in this pathway .
Transcriptional regulation: Gene expression profiling of Mef2c-null B cells showed a decrease in many cell cycle genes, suggesting that MEF2C phosphorylation regulates proliferation in response to BCR stimulation via transcriptional control of cell cycle regulators .
MEF2C is regulated by multiple phosphorylation events at different sites, creating a complex regulatory network:
S387, T293, and T300 phosphorylation by p38 MAPK: These sites in the transactivation domain collectively regulate MEF2C's transcriptional activity .
S222 phosphorylation by MARK kinases: This site has been identified as a marker of chemotherapy resistance in acute myeloid leukemia (AML) and is phosphorylated by MARK kinases. MARK-induced phosphorylation potentiates MEF2C's transcriptional activity .
S59 phosphorylation: This site is constitutively phosphorylated in vivo, probably by casein kinase II, and enhances DNA binding activity of MEF2C .
Regulation by BMK1/ERK5: MEF2C is also a substrate for BMK1/ERK5, which regulates MEF2C via somewhat different phosphorylation patterns compared to p38 MAPK .
The interplay between these different phosphorylation events likely allows for fine-tuned regulation of MEF2C activity in response to various stimuli and cellular contexts.
MEF2C phosphorylation has been implicated in several disease processes, particularly in cancer:
Chemotherapy resistance in AML: MEF2C S222 phosphorylation has been identified as a specific marker of primary chemoresistance in acute myeloid leukemia patient specimens .
Leukemogenesis: While MEF2C phosphorylation appears dispensable for normal hematopoiesis in mice (as established using genome editing), it is required for MLL-AF9 induced leukemogenesis .
Leukemia stem cell maintenance: MEF2C phosphorylation has been shown to be required for leukemia stem cell maintenance, suggesting it plays a role in sustaining the disease .
Potential therapeutic target: Chemical inhibition of MARK-induced MEF2C phosphorylation has been shown to overcome chemotherapy resistance and exhibit selective toxicity against MEF2C-activated human AML cells, suggesting that targeting MEF2C phosphorylation pathways could be a promising therapeutic strategy .
Researchers investigating these disease connections should consider using patient-derived samples with appropriate controls to correlate phosphorylation status with clinical outcomes.
To investigate how S387 phosphorylation affects MEF2C's molecular interactions, researchers can employ several sophisticated approaches:
Phospho-mimetic and phospho-deficient mutants: Generate S387E/D (phospho-mimetic) and S387A (phospho-deficient) MEF2C mutants to study differential protein interactions. These can be expressed in relevant cell types to examine functional consequences .
Co-immunoprecipitation studies: Compare protein interaction partners of wild-type versus phospho-mutant MEF2C to identify phosphorylation-dependent interactions.
Proximity labeling approaches: Use BioID or APEX2 fused to wild-type or mutant MEF2C to identify proteins that interact with MEF2C in a phosphorylation-dependent manner in living cells.
Chromatin immunoprecipitation (ChIP-seq): Compare genome-wide binding patterns of wild-type and mutant MEF2C to identify phosphorylation-dependent changes in DNA binding and chromatin interactions.
Protein dimerization analysis: Investigate how phosphorylation affects MEF2C dimerization with other MEF2 family members, as research has shown that MEF2A (another MEF2 family member regulated by p38) can dimerize with MEF2D .
Structural studies: Use X-ray crystallography or cryo-EM to determine how phosphorylation affects MEF2C structure and protein-protein interactions.
To investigate the cell-type specific functions of MEF2C S387 phosphorylation:
CRISPR/Cas9 genome editing: Generate knock-in cell lines or animal models with S387A or S387E mutations to study the effects of blocking or mimicking phosphorylation under endogenous expression conditions.
Cell-type specific conditional expression: Use inducible systems to express wild-type or phospho-mutant MEF2C in specific cell types or at specific developmental stages.
Functional readouts based on cell type:
B cells: Measure proliferation, antibody production, and germinal center formation in response to BCR stimulation .
Neuronal cells: Assess synapse formation, synaptic transmission, and memory-related functions .
Cardiac cells: Evaluate cardiac morphogenesis and myogenesis .
Leukemia cells: Test chemotherapy sensitivity and resistance, cell survival, and leukemic potential .
Transcriptomic analysis: Perform RNA-seq on cells expressing wild-type versus S387A MEF2C to identify phosphorylation-dependent target genes in different cellular contexts.
Signaling pathway integration: Use specific pathway inhibitors to determine how S387 phosphorylation interacts with other signaling pathways in different cell types.
For comprehensive analysis of MEF2C phosphorylation patterns, researchers should consider these mass spectrometry (MS) approaches:
Phospho-enrichment strategies:
Immobilized metal affinity chromatography (IMAC)
Titanium dioxide (TiO₂) enrichment
Phospho-specific antibody immunoprecipitation prior to MS
MS acquisition methods:
Parallel reaction monitoring (PRM) for targeted quantification of specific phosphorylation sites
Data-dependent acquisition (DDA) for discovery of novel phosphorylation sites
Data-independent acquisition (DIA) for comprehensive phosphopeptide quantification
Fragmentation techniques:
Higher-energy collisional dissociation (HCD) combined with electron transfer dissociation (ETD) to improve phosphosite localization
Quantitative approaches:
SILAC or TMT labeling for relative quantification of phosphorylation across conditions
Label-free quantification for comparing phosphorylation stoichiometry
Software for phosphosite analysis:
MaxQuant with PTM scoring algorithms
Skyline for targeted phosphopeptide quantification
PTM-specific localization algorithms (e.g., PhosphoRS, Ascore)
When analyzing results, researchers should confirm phosphorylation sites through manual validation of spectra and consider the biological context of identified phosphorylation events.
To characterize the temporal dynamics of MEF2C S387 phosphorylation:
Time-course experiments: Collect samples at multiple time points after stimulation (e.g., BCR activation, p38 MAPK pathway stimulation) to capture the kinetics of phosphorylation and dephosphorylation.
Pulse-chase approaches: Use kinase inhibitors to block new phosphorylation events after initial stimulation to determine the stability of the phosphorylation mark.
Live-cell imaging approaches:
Generate phospho-specific biosensors that change conformation or FRET signal upon S387 phosphorylation
Combine with optogenetic control of p38 MAPK activity to precisely control and monitor phosphorylation events
Single-cell analysis: Use flow cytometry with phospho-specific antibodies to examine cell-to-cell variability in signaling dynamics.
Mathematical modeling: Develop kinetic models of the phosphorylation/dephosphorylation cycle based on experimental data to predict system behavior under different conditions.
Integrated multi-omics: Combine phosphoproteomics with transcriptomics at different time points to link phosphorylation events to downstream transcriptional responses.
For analyzing MEF2C phosphorylation in complex biological samples such as patient specimens or tissue samples:
Single-cell phospho-proteomics: Apply single-cell technologies to understand cellular heterogeneity in phosphorylation patterns within complex tissues.
Spatial phospho-proteomics: Combine imaging mass spectrometry or spatial transcriptomics with phospho-specific antibodies to map the spatial distribution of MEF2C phosphorylation within tissues.
Integrated analysis platforms:
Combine phosphoproteomics with genomics and transcriptomics to link genetic alterations to changes in MEF2C phosphorylation
Correlate phosphorylation data with clinical outcomes in patient samples
Targeted proteomics using multiple reaction monitoring (MRM): Develop sensitive assays for specific phosphopeptides to enable reliable quantification in complex samples.
Patient-derived models: Establish patient-derived xenografts or organoids to study MEF2C phosphorylation in a more physiologically relevant context while maintaining the ability to perform controlled experiments.
Computational approaches: Apply machine learning algorithms to identify patterns in phosphorylation data and predict functional outcomes or therapeutic responses.
Multi-parameter flow cytometry: Combine phospho-specific antibodies with markers for cell type, cell cycle, and other phosphorylation events to obtain a comprehensive view of signaling networks in heterogeneous samples.