mug146 Antibody

What is MYH14 antibody and what cellular functions does it target?

MYH14 antibody targets Myosin-14 (also known as Myosin heavy chain 14, Non-muscle myosin heavy chain IIc, NMHC II-C, KIAA2034, or FP17425), which is a cellular myosin that plays crucial roles in cytokinesis, cell shape maintenance, and specialized functions such as secretion and capping . This protein is particularly important in understanding basic cellular mechanics and motility. The antibody serves as a valuable tool for detecting and studying these protein functions across various experimental contexts.

What applications is the MYH14 antibody validated for?

The rabbit polyclonal MYH14 antibody (such as ab230418) has been validated for Western Blot (WB) and Immunohistochemistry on paraffin-embedded sections (IHC-P) specifically with human samples . When selecting this antibody for your research, ensure that your experimental design aligns with these validated applications. For applications outside these parameters, preliminary validation experiments are highly recommended to confirm antibody performance in your specific experimental system.

What is the appropriate dilution range for MYH14 antibody in different applications?

Based on experimental validation, the recommended dilutions for MYH14 antibody are:

• For Western Blot: 1/1000 dilution has been shown to be effective for detecting MYH14 in human cell lines such as A431 (human epidermoid carcinoma)

• For IHC-P: 1/100 dilution has demonstrated appropriate staining in human small intestine tissue samples

These dilutions should be optimized for your specific experimental conditions, tissue types, and detection systems.

How should I design proper controls when using MYH14 antibody?

When using MYH14 antibody, implement the following control strategy:

• Positive control: Include samples known to express MYH14, such as A431 cells for Western blot or human small intestine tissue for IHC-P

• Negative control: Use either:

  • Samples known not to express MYH14

  • Primary antibody omission (incubate with antibody diluent only)

  • Isotype control (use a non-targeting antibody of the same isotype)

• Loading control: For Western blots, include detection of housekeeping proteins (β-actin, GAPDH, etc.)

• Blocking peptide: If available, pre-incubate the antibody with the immunogen peptide to confirm specificity

This comprehensive control scheme helps validate antibody specificity and differentiate true signal from background or non-specific binding.

How can I validate the specificity of MYH14 antibody for my experimental system?

To rigorously validate MYH14 antibody specificity for your experimental system, implement this multi-step approach:

• Genetic validation: Use CRISPR/Cas9 to knock out MYH14 or siRNA to knock down expression, then confirm signal loss

• Orthogonal detection: Compare results with a second MYH14 antibody targeting a different epitope

• Mass spectrometry validation: Perform immunoprecipitation followed by mass spectrometry to confirm the identity of the pulled-down protein

• Recombinant expression: Express tagged recombinant MYH14 and confirm antibody detection

• Cross-reactivity testing: Test antibody against closely related myosin family members to assess potential cross-reactivity

For structural studies, antibody binding should be validated using techniques such as surface plasmon resonance (SPR) to determine binding kinetics (kon and koff) and affinity (KD) values .

What methods can I use to quantify MYH14 antibody binding affinity and how should I interpret the results?

Quantifying MYH14 antibody binding affinity requires several complementary techniques:

• Surface Plasmon Resonance (SPR): Measures real-time binding kinetics without labels

  • kon (association rate): Typically 1×10⁴ to 1×10⁶ M⁻¹s⁻¹ for high-quality antibodies

  • koff (dissociation rate): Typically 1×10⁻² to 1×10⁻⁵ s⁻¹

  • KD (equilibrium dissociation constant): KD = koff/kon (lower values indicate higher affinity)

• Bio-Layer Interferometry (BLI): Alternative label-free kinetic measurement

• Enzyme-Linked Immunosorbent Assay (ELISA): Provides EC50 values for comparative affinity assessment

• Flow Cytometry: Measures binding to cell-surface targets with median fluorescence intensity (MFI)

Interpretation guidance:

• KD values <10⁻⁹ M generally indicate high affinity

• Compare kinetic parameters (especially koff) rather than just equilibrium constants

• Validate findings across multiple methods to ensure robustness

How can I optimize MYH14 antibody for use in multi-color immunofluorescence studies?

For optimal multi-color immunofluorescence using MYH14 antibody:

• Epitope blocking and antibody order:

  • Test sequential vs. simultaneous incubation protocols

  • For sequential staining, apply antibodies in order of decreasing affinity

• Spectral optimization:

  • Choose fluorophores with minimal spectral overlap

  • Perform single-color controls to establish proper compensation

  • Consider spectral unmixing for closely overlapping fluorophores

• Signal amplification options:

  • Tyramide signal amplification (TSA) for weak signals

  • Use secondary antibodies from different host species to avoid cross-reactivity

• Fixation optimization:

  • Compare paraformaldehyde, methanol, and acetone fixation effects on epitope preservation

  • Optimize fixation duration and temperature specifically for MYH14 epitope

• Validation controls:

  • Include fluorescence-minus-one (FMO) controls

  • Test antibody combinations on known positive/negative tissues

What are the considerations when using MYH14 antibody in conjunction with computational antibody design approaches?

When integrating MYH14 antibody research with computational approaches:

• Scoring function selection:

  • Log-likelihood scores from generative models correlate well with experimental binding affinities

  • Structure-based models generally outperform sequence-based models in predicting binding characteristics

• Model selection for affinity prediction:

  • Consider both structure-based approaches (diffusion-based, graph-based) and sequence-based (LLM-style) models

  • DiffAbXL and similar scaled diffusion models have demonstrated superior performance in correlating computational predictions with experimental affinity measurements

• Structural considerations:

  • When modeling antibody-antigen interactions, include:

    • CDR loop flexibility

    • Framework region stabilization effects

    • Potential post-translational modifications

• Validation metrics:

  • Correlate computational predictions with experimental measurements using:

    • Pearson correlation coefficient (linear relationship)

    • Spearman correlation coefficient (monotonic relationship)

    • Kendall's tau (rank ordering)

Note: Correlation values are approximate ranges based on benchmarking studies

How should I troubleshoot inconsistent results when using MYH14 antibody across different experimental systems?

When facing inconsistent results with MYH14 antibody:

• Epitope accessibility analysis:

  • The MYH14 antibody targets an epitope within amino acids 650-700

  • Protein conformation changes, fixation methods, or protein-protein interactions may affect epitope exposure

  • Test alternative sample preparation methods that preserve epitope structure

• Sample-specific optimization:

  • Adjust antibody concentration for each tissue/cell type

  • Modify incubation time and temperature based on target abundance

  • Test different antigen retrieval methods for IHC-P applications

• Cross-reactivity investigation:

  • Test in MYH14-knockout systems to confirm specificity

  • Perform Western blot analysis to identify potential cross-reactive proteins

  • Compare with alternative MYH14 antibodies targeting different epitopes

• Batch-to-batch variability assessment:

  • Document lot numbers and compare performance metrics between lots

  • Maintain internal reference standards for normalized comparisons

  • Consider creating a large single-batch stock for long-term projects

• Data normalization strategies:

  • Implement ratiometric analysis against invariant controls

  • Use statistical approaches to identify and correct for batch effects

  • Consider implementing machine learning-based normalization for complex datasets

How can I design experiments to study MYH14's role in cytokinesis using specific antibodies?

To investigate MYH14's role in cytokinesis:

• Temporal expression analysis:

  • Synchronize cells at different cell cycle stages

  • Perform time-course Western blot analysis with MYH14 antibody

  • Quantify expression relative to cell cycle markers

• Localization during cytokinesis:

  • Design co-immunofluorescence experiments with MYH14 antibody (1/100 dilution) and markers for:

    • Contractile ring (anillin, septin)

    • Microtubules (α-tubulin)

    • Chromosomes (DAPI)

  • Capture high-resolution z-stack images at different cytokinesis stages

• Functional perturbation:

  • Combine MYH14 antibody detection with:

    • siRNA knockdown of MYH14

    • Expression of dominant-negative MYH14 mutants

    • Small molecule inhibitors of myosin activity

  • Quantify cytokinesis defects (timing, success rate, morphology)

• Interaction partner identification:

  • Perform immunoprecipitation with MYH14 antibody

  • Analyze binding partners by mass spectrometry

  • Validate key interactions with co-immunoprecipitation and proximity ligation assays

What are the best practices for quantifying MYH14 expression in tissue microarrays using immunohistochemistry?

For quantifying MYH14 expression in tissue microarrays:

• Staining protocol standardization:

  • Use automated staining platforms to minimize technical variability

  • Include positive and negative control tissues on each microarray

  • Use MYH14 antibody at validated dilution (1/100 for IHC-P)

• Image acquisition parameters:

  • Capture images with consistent exposure settings

  • Use color calibration standards

  • Acquire multiple fields per tissue core (minimum 3-5)

• Quantification approaches:

  • H-score method: Multiply staining intensity (0-3) by percentage of positive cells (0-100)

  • Automated digital analysis: Use validated image analysis algorithms to quantify:

    • DAB staining intensity (optical density)

    • Membrane vs. cytoplasmic localization

    • Percentage of positive cells

• Statistical considerations:

  • Calculate intra- and inter-observer variability

  • Establish scoring cutoffs based on clinical correlations

  • Use appropriate statistical tests based on score distribution

• Validation approaches:

  • Correlate IHC results with mRNA expression data

  • Compare results between different MYH14 antibodies

  • Validate findings in independent cohorts

How can I effectively use MYH14 antibody in studying protein-protein interactions in secretory pathways?

To study MYH14's role in secretory pathways:

• Co-localization analysis:

  • Perform dual immunofluorescence with MYH14 antibody and markers for:

    • Golgi apparatus (GM130)

    • Secretory vesicles (Rab11, Rab27)

    • Cell membrane (WGA, Na+/K+ ATPase)

  • Analyze co-localization using Pearson's or Manders' coefficients

• Proximity-based interaction studies:

  • Proximity Ligation Assay (PLA): Detect interactions within 40nm using MYH14 antibody and antibodies against suspected interaction partners

  • FRET/FLIM: Combine fluorescently-tagged MYH14 with potential interaction partners

• Dynamic tracking of secretory events:

  • Use MYH14 antibody to immunoprecipitate protein complexes at different stages of secretion

  • Combine with live-cell imaging of fluorescently tagged secretory cargo

  • Analyze MYH14 recruitment during specific secretory events

• Functional secretion assays:

  • Measure secretion efficiency after MYH14 knockdown/knockout

  • Rescue experiments with wild-type vs. mutant MYH14

  • Correlate MYH14 expression patterns with secretory capacity

What are the considerations for using MYH14 antibody in conjunction with high-throughput screening approaches?

For high-throughput screening with MYH14 antibody:

• Assay miniaturization:

  • Optimize MYH14 antibody concentration for microplate formats

  • Validate signal-to-background ratio in 96, 384, and 1536-well formats

  • Determine minimum cell numbers required for reliable detection

• Automation compatibility:

  • Test antibody stability under automated handling conditions

  • Validate consistent performance after repeated freeze-thaw cycles

  • Develop robust plate washing protocols to minimize background

• Multiplexed detection strategies:

  • Combine MYH14 detection with additional markers using:

    • Spectrally distinct fluorophores

    • Sequential detection with compatible antibody stripping methods

    • Mass cytometry approaches for highly multiplexed analysis

• Data analysis pipeline:

  • Implement automated image analysis for phenotypic screens

  • Develop normalization methods to correct for plate position effects

  • Use machine learning approaches to identify complex phenotypes

• Validation strategy:

  • Include known modulators of MYH14 as positive controls

  • Implement orthogonal secondary screens

  • Validate hits with dose-response curves and complementary techniques

How can MYH14 antibody be utilized in studying the role of non-muscle myosin in mechanotransduction?

For mechanotransduction studies with MYH14 antibody:

• Force-dependent conformational changes:

  • Compare MYH14 antibody epitope accessibility under different mechanical conditions

  • Use stretch chambers or micropattern substrates with varying stiffness

  • Perform immunofluorescence to detect potential force-induced conformational changes

• Stress fiber association analysis:

  • Co-stain for MYH14 (1/100 dilution) and F-actin (phalloidin)

  • Quantify co-localization under varying mechanical stimuli

  • Correlate with activation of mechanosensitive signaling pathways

• Cell migration and mechanosensing:

  • Track MYH14 localization during durotaxis (migration toward stiffer substrates)

  • Measure traction forces in cells with normal vs. altered MYH14 expression

  • Correlate MYH14 distribution with focal adhesion dynamics

• Molecular tension sensors:

  • Develop FRET-based tension sensors incorporating MYH14

  • Use MYH14 antibody to validate sensor localization and expression

  • Measure tension across MYH14 during different cellular processes

What strategies can be employed to combine MYH14 antibody with advanced imaging techniques?

For integrating MYH14 antibody with advanced imaging:

• Super-resolution microscopy optimization:

  • STORM/PALM: Use directly conjugated MYH14 antibody with appropriate fluorophores (Alexa647, Cy5)

  • STED: Select fluorophores with appropriate photostability (ATTO647N, Abberior STAR RED)

  • SIM: Optimize sample preparation to minimize out-of-focus signal

• Live-cell imaging approaches:

  • Use Fab fragments of MYH14 antibody for reduced interference with protein function

  • Combine with genetically encoded fluorescent protein fusions

  • Validate that antibody binding doesn't alter normal MYH14 dynamics

• Correlative light and electron microscopy (CLEM):

  • Use MYH14 antibody with gold-conjugated secondary antibodies

  • Perform pre-embedding immunogold labeling for transmission EM

  • Optimize fixation to preserve both antigenicity and ultrastructure

• Expansion microscopy compatibility:

  • Test primary and secondary antibody retention after hydrogel expansion

  • Optimize antibody concentration for expanded samples

  • Validate spatial distribution of MYH14 before and after expansion

How can computational approaches enhance the interpretation of MYH14 antibody-based experimental data?

To enhance MYH14 antibody data interpretation:

• Quantitative image analysis:

  • Implement automated segmentation of subcellular compartments

  • Apply machine learning algorithms for pattern recognition

  • Develop spatial statistics to quantify distribution patterns

• Integration with -omics data:

  • Correlate MYH14 protein expression (antibody-based) with transcriptomic data

  • Integrate with phosphoproteomics to identify regulatory mechanisms

  • Perform network analysis to identify functional modules

• Predictive modeling:

  • Use generative models to predict antibody binding affinity

  • Apply diffusion-based or graph-based models that incorporate structural information

  • Correlate computational predictions with experimental measurements using appropriate statistical methods

• Digital pathology applications:

  • Develop machine learning algorithms to quantify MYH14 expression in tissue samples

  • Correlate expression patterns with clinical outcomes

  • Implement multi-parameter analysis combining MYH14 with other markers

What are the considerations for using MYH14 antibody in studying post-translational modifications?

For studying MYH14 post-translational modifications:

• Phosphorylation analysis:

  • Use phospho-specific antibodies in conjunction with total MYH14 antibody

  • Perform Western blot before and after phosphatase treatment

  • Use mobility shift assays to detect heavily phosphorylated forms

• Immunoprecipitation strategies:

  • Use MYH14 antibody for immunoprecipitation followed by:

    • Western blot with modification-specific antibodies

    • Mass spectrometry to identify modified residues

    • Edman sequencing for N-terminal modifications

• Site-specific mutant analysis:

  • Compare antibody reactivity between wild-type and PTM site mutants

  • Correlate PTM status with subcellular localization

  • Assess functional consequences of preventing specific modifications

• Temporal dynamics:

  • Design time-course experiments after stimulation

  • Use MYH14 antibody in combination with PTM-specific antibodies

  • Correlate modification status with cellular events (e.g., cytokinesis progression)

What quality control measures should I implement when using MYH14 antibody across different experimental batches?

To ensure reproducibility with MYH14 antibody:

• Antibody validation for each lot:

  • Perform Western blot on standard positive control (A431 cells)

  • Compare band intensity and specificity between lots

  • Document lot-specific optimal working dilutions

• Reference standard development:

  • Create a laboratory reference standard (LRS) - a large batch of positive control lysate/tissue

  • Include LRS on each experimental run for normalization

  • Quantify deviation from established LRS values

• Storage and handling standardization:

  • Establish consistent aliquoting procedures to minimize freeze-thaw cycles

  • Document storage conditions and age of antibody for each experiment

  • Test antibody stability at defined intervals (3, 6, 12 months)

• Comprehensive method documentation:

  • Create detailed standard operating procedures (SOPs)

  • Record all relevant experimental parameters:

    • Antibody dilution, incubation time and temperature

    • Buffer compositions and pH

    • Detection system specifications

How should I approach contradictory results between different MYH14 antibody-based detection methods?

When facing contradictory results:

• Systematic comparison:

  • Create a comparison matrix of all methods (Western blot, IHC, IF, etc.)

  • Test identical samples across all platforms

  • Document specific protocol differences that might explain discrepancies

• Epitope accessibility analysis:

  • Consider how sample preparation affects the MYH14 epitope (aa 650-700)

  • Test alternative fixation and permeabilization methods

  • Assess native vs. denatured protein detection differences

• Cross-validation with orthogonal approaches:

  • Compare antibody-based results with:

    • mRNA expression (qPCR, RNA-seq)

    • Mass spectrometry-based protein quantification

    • Functional assays measuring MYH14 activity

• Statistical analysis of method agreement:

  • Calculate Bland-Altman plots to assess systematic bias between methods

  • Determine intraclass correlation coefficients

  • Implement statistical corrections for method-specific variations

• Resolution strategies:

  • For critical results, use multiple detection methods and antibodies

  • Weight evidence based on method validation robustness

  • Consider reporting all methods with transparent discussion of discrepancies