Phospho-IRF3 (S386) Recombinant Monoclonal Antibody

What is IRF3 and why is phosphorylation at S386 biologically significant?

IRF3 (Interferon Regulatory Factor 3) serves as a key transcriptional regulator of type I interferon (IFN)-dependent immune responses, playing a critical role in the innate immune response against DNA and RNA viruses. In its inactive state, IRF3 resides in the cytoplasm of uninfected cells. Upon viral infection, double-stranded RNA (dsRNA) recognition, or toll-like receptor (TLR) signaling, IRF3 becomes phosphorylated by IKBKE and TBK1 kinases at several serine residues, with S386 being particularly critical for activation. This phosphorylation induces a conformational change that enables IRF3 dimerization, nuclear translocation, and association with CREB binding protein (CREBBP) to form dsRNA-activated factor 1 (DRAF1). This complex activates transcription of type I IFN and interferon-stimulated genes (ISGs), forming the basis of the antiviral response.

Phosphorylation at S386 specifically serves as a molecular switch that transforms IRF3 from an inactive cytoplasmic protein to an active transcription factor. Understanding this phosphorylation event is crucial for studying innate immune responses, viral infection mechanisms, and potential therapeutic targets for immune-related disorders.

What are the key applications for Phospho-IRF3 (S386) antibodies in basic research?

Phospho-IRF3 (S386) antibodies are versatile tools that enable researchers to track IRF3 activation across various experimental contexts. Basic research applications include:

• Western blotting (WB) to quantify IRF3 phosphorylation levels in cell or tissue lysates following viral challenge or other immune stimuli

• Immunocytochemistry (ICC) and immunofluorescence (IF) to visualize the subcellular localization of phosphorylated IRF3, particularly its nuclear translocation following activation

• Dot blotting to rapidly screen for IRF3 phosphorylation across multiple samples

• Monitoring innate immune activation in response to pathogen-associated molecular patterns (PAMPs)

• Validating successful stimulation of pattern recognition receptor (PRR) pathways in experimental systems

When designing basic experiments, researchers should include appropriate positive controls (e.g., cells treated with poly(I:C) or infected with Sendai virus) and negative controls (unstimulated cells or phosphatase-treated samples) to validate antibody specificity and experimental protocols.

How do different sample preparation methods affect Phospho-IRF3 (S386) detection?

Sample preparation significantly impacts the detection of phosphorylated IRF3. Phosphorylation marks are labile and can be rapidly lost due to endogenous phosphatase activity. For optimal results:

• Include phosphatase inhibitors (e.g., sodium fluoride, sodium orthovanadate, β-glycerophosphate) in all lysis and sample handling buffers

• Maintain cold temperature throughout sample processing to minimize phosphatase activity

• Process samples quickly to prevent degradation of phosphorylation marks

• For western blotting applications, handle samples gently to prevent protein degradation while ensuring complete lysis

Different extraction protocols yield varying results based on experimental needs:

For immunofluorescence applications, fixation method is crucial - paraformaldehyde (4%) typically preserves phospho-epitopes better than methanol-based fixatives.

What are the optimal stimulation conditions to induce IRF3 phosphorylation at S386 in different cell types?

IRF3 phosphorylation dynamics vary considerably across cell types and stimulation conditions. Optimizing these parameters is essential for generating reproducible data:

For studies examining IRF3 phosphorylation in the context of viral infection, timing is particularly critical as phosphorylation often follows a biphasic pattern - an early peak (2-6 hours post-infection) followed by a potential second wave depending on viral replication kinetics. When designing time-course experiments, include multiple timepoints (0.5, 1, 2, 4, 8, 12, 24 hours) to capture the complete phosphorylation profile.

Additionally, cell density can significantly impact IRF3 phosphorylation efficiency. For adherent cells, 70-80% confluence typically yields optimal results, while excessive confluence may dampen the response.

How can I determine the specificity of a Phospho-IRF3 (S386) antibody in my experimental system?

Validating antibody specificity is crucial for generating reliable data. Implement these approaches to confirm specificity:

• Phosphatase treatment control: Treat a portion of your positive control sample with lambda phosphatase before immunoblotting. The phospho-specific signal should disappear while total IRF3 remains detectable.

• IRF3 knockout/knockdown controls: Compare phospho-IRF3 detection in wild-type versus IRF3-deficient cells following stimulation. No signal should be detected in knockout/knockdown samples.

• Peptide competition assay: Pre-incubate the antibody with excess phosphorylated peptide (containing the S386 epitope) before immunodetection. This should abolish specific binding.

• Phosphomimetic and phospho-dead mutants: Express IRF3 constructs with S386D (phosphomimetic) or S386A (phospho-dead) mutations and verify appropriate detection or lack thereof.

• Cross-validation with multiple antibodies: Compare results using antibodies from different manufacturers or those recognizing distinct phosphorylated epitopes on IRF3.

For immunofluorescence applications, include appropriate secondary antibody-only controls to rule out non-specific binding and perform parallel staining with total IRF3 antibodies to confirm localization patterns.

What are the key considerations when designing Western blot protocols for Phospho-IRF3 (S386) detection?

Western blotting for phospho-IRF3 requires careful optimization to achieve sensitive and specific detection:

• Sample preparation considerations:

  • Use fresh samples whenever possible

  • Include phosphatase inhibitors in lysis buffers

  • Avoid multiple freeze-thaw cycles

• Gel selection and running conditions:

  • Use 8-10% polyacrylamide gels for optimal resolution

  • IRF3 migrates at approximately 47-50 kDa, but phosphorylated forms may appear at 55-60 kDa due to mobility shift

  • Some researchers observe higher molecular weight bands (up to 120 kDa) that may represent dimerized or post-translationally modified forms

• Transfer parameters:

  • Semi-dry transfer: 15V for 30-45 minutes

  • Wet transfer: 100V for 60-90 minutes or 30V overnight at 4°C

  • PVDF membranes are generally preferred over nitrocellulose for phospho-epitope retention

• Blocking and antibody incubation:

  • BSA-based blocking solutions (3-5% in TBST) generally perform better than milk-based blockers, which contain phosphatases

  • Optimal primary antibody dilutions range from 1:1000 to 1:2000 for most commercially available phospho-IRF3 (S386) antibodies

  • Overnight incubation at 4°C often yields cleaner results than shorter incubations at room temperature

• Detection considerations:

  • Enhanced chemiluminescence (ECL) detection works well for most applications

  • For quantitative analysis, consider fluorescent secondary antibodies and imaging systems

  • Always probe for loading controls (β-actin, GAPDH) and total IRF3 on separate blots or after stripping

How can I quantitatively assess IRF3 phosphorylation kinetics in response to different stimuli?

For advanced phosphorylation kinetics studies, several quantitative approaches can be employed:

• ELISA-based quantification: Commercial phospho-IRF3 (S386) ELISA kits allow for sensitive and high-throughput quantification of phosphorylation levels. These sandwich-based assays can detect phospho-IRF3 in cell and tissue lysates with high specificity.

• HTRF (Homogeneous Time-Resolved Fluorescence) assay: This technique uses two labeled antibodies - one specific to the phosphorylated motif and another that recognizes total protein independent of phosphorylation state. When both antibodies bind their respective epitopes, a FRET signal is generated proportional to the concentration of phosphorylated protein.

  The HTRF assay workflow typically involves:

  • Culturing cells in 96-well plates

  • Stimulating with appropriate agonists in a time-course manner

  • Cell lysis directly in the plate

  • Transfer of lysates to 384-well detection plates

  • Addition of detection antibodies and signal measurement

  This approach offers higher throughput than Western blotting and eliminates the need for gel electrophoresis, transfer, and washing steps.

• Phospho-flow cytometry: For single-cell resolution of IRF3 phosphorylation, phospho-flow cytometry can be employed using permeabilized cells and fluorochrome-conjugated phospho-IRF3 antibodies.

For all quantitative approaches, standard curves using recombinant phosphorylated proteins or cell lysates with known stimulation conditions should be included to enable accurate quantification.

What strategies can address common issues with phospho-epitope detection in immunofluorescence experiments?

Immunofluorescence detection of phospho-IRF3 presents several technical challenges that can be addressed through methodological refinements:

• Low signal intensity issues:

  • Implement tyramide signal amplification (TSA) to enhance detection sensitivity

  • Use high-affinity monoclonal antibodies specifically validated for immunofluorescence

  • Optimize fixation protocols to preserve phospho-epitopes (try 4% paraformaldehyde for 10-15 minutes)

  • Consider antigen retrieval methods (citrate buffer, pH 6.0, heated to 95°C for 10-20 minutes)

• High background problems:

  • Increase blocking stringency (5% BSA + 5% normal serum from secondary antibody species)

  • Include 0.1-0.3% Triton X-100 in antibody dilution buffers to reduce non-specific binding

  • Extend washing steps (5 x 5 minutes with gentle agitation)

  • Dilute primary antibodies further (1:100 to 1:200 range is optimal for many phospho-IRF3 antibodies)

• Nuclear translocation assessment:

  • Co-stain with nuclear markers (DAPI, Hoechst) and total IRF3 antibodies

  • Use confocal microscopy for better resolution of subcellular localization

  • Implement quantitative image analysis to measure nuclear:cytoplasmic intensity ratios

• Confirming specificity in situ:

  • Include unstimulated controls alongside stimulated samples

  • Pre-treat a subset of stimulated samples with phosphatase

  • Establish IRF3-knockout cell lines as definitive negative controls

How can phospho-IRF3 detection be integrated into multi-parameter analysis of innate immune signaling pathways?

Advanced research often requires examining IRF3 phosphorylation in the broader context of innate immune signaling networks. Several approaches facilitate multi-parameter analysis:

• Multiplex Western blotting: Using fluorescent secondary antibodies with distinct emission spectra allows simultaneous detection of phospho-IRF3 alongside other phosphorylated signaling proteins (e.g., phospho-TBK1, phospho-STING, phospho-NF-κB) from the same sample.

• Sequential immunoprecipitation: To analyze protein complexes involving phospho-IRF3:

  • First immunoprecipitate with phospho-IRF3 (S386) antibodies

  • Elute bound complexes

  • Analyze by mass spectrometry or Western blotting for interacting partners

• ChIP-seq following IRF3 activation: To identify IRF3-regulated genes in specific contexts:

  • Stimulate cells to induce IRF3 phosphorylation

  • Perform chromatin immunoprecipitation using phospho-IRF3 antibodies

  • Sequence precipitated DNA to identify binding sites genome-wide

  • Integrate with RNA-seq data to correlate binding with transcriptional output

• Proximity ligation assay (PLA): This technique enables visualization of protein-protein interactions involving phospho-IRF3 in situ:

  • Uses antibodies against phospho-IRF3 and potential interaction partners

  • When proteins are in close proximity (<40 nm), secondary antibodies linked to oligonucleotides can interact

  • Rolling circle amplification and fluorescent probe hybridization create a detectable signal

  • Particularly useful for confirming interactions with STING, TBK1, or CREBBP in different subcellular compartments

• Single-cell analysis: Combining phospho-flow cytometry with single-cell RNA-seq or CyTOF allows correlation of IRF3 phosphorylation status with transcriptional responses at single-cell resolution, revealing population heterogeneity in innate immune responses.

How can I address inconsistent phospho-IRF3 (S386) detection in my experiments?

Inconsistency in phospho-IRF3 detection often stems from several methodological factors that can be systematically addressed:

• Antibody storage and handling issues:

  • Store antibodies according to manufacturer recommendations (typically -20°C)

  • Avoid repeated freeze-thaw cycles by preparing small aliquots

  • Check for precipitates before use and centrifuge if necessary

  • Verify antibody expiration dates and lot-to-lot consistency

• Cell culture variability:

  • Maintain consistent passage numbers across experiments (ideally <15 passages)

  • Standardize cell density at time of stimulation (70-80% confluence recommended)

  • Ensure cells are mycoplasma-negative, as contamination can alter signaling responses

  • Use consistent serum lots and media preparations

• Stimulation protocol variables:

  • Prepare fresh stock solutions of stimulants regularly

  • Standardize the timing between media changes and stimulation

  • Control temperature and CO₂ conditions precisely during stimulation

• Sample processing inconsistencies:

  • Develop a standardized lysate preparation protocol with precise timing

  • Ensure rapid sample processing to minimize phosphatase activity

  • Maintain consistent protein concentrations across samples (20-40 μg/lane for Western blot)

  • Include phosphorylation stability controls (samples deliberately left at room temperature to demonstrate phosphate loss)

• Technical validation approaches:

  • Run inter-assay control samples across multiple experiments

  • Include graduated positive controls (cells stimulated with increasing concentrations of inducers)

  • Consider developing stable cell lines expressing phosphomimetic IRF3 as consistent positive controls

What are the key differences between various detection methods for phospho-IRF3 (S386) and when should each be used?

Selecting the appropriate detection method depends on experimental objectives, available resources, and required sensitivity:

Method selection should consider biological question complexity, required quantitative rigor, sample number, and available instrumentation. For initial phospho-IRF3 characterization, Western blotting remains the gold standard, while high-throughput analyses benefit from ELISA or HTRF approaches. Subcellular dynamics questions are best addressed with imaging techniques.

How can I validate phospho-IRF3 (S386) antibody specificity in the context of complex signaling networks?

Comprehensive validation of phospho-IRF3 antibodies requires multi-faceted approaches, particularly when studying complex signaling networks:

• Genetic validation strategies:

  • Compare wild-type cells with CRISPR/Cas9-generated IRF3 knockout lines

  • Utilize cells expressing IRF3 with phospho-site mutations (S386A, S396A, S398A, S402A)

  • Re-express IRF3 in knockout cells to rescue phosphorylation signal

  • Test antibody reactivity in TBK1/IKKε double-knockout cells (upstream kinases)

• Pharmacological validation approaches:

  • Treat cells with specific TBK1/IKKε inhibitors (e.g., BX795, MRT67307) to block phosphorylation

  • Use pathway-specific inhibitors (e.g., cGAS inhibitors for DNA sensing, RIG-I inhibitors for RNA sensing)

  • Apply broad-spectrum kinase inhibitors as negative controls

  • Test phosphatase inhibitor concentration gradients to optimize preservation

• Cross-platform validation:

  • Compare phospho-IRF3 detection across multiple methods (Western blot, ELISA, immunofluorescence)

  • Correlate phospho-IRF3 levels with functional readouts (IFN-β promoter activity, ISG expression)

  • Validate with mass spectrometry-based phosphoproteomics

  • Confirm with complementary antibodies recognizing different phospho-epitopes

• Pathway integration controls:

  • Monitor parallel activation of complementary pathways (NF-κB, MAPK)

  • Track activation of upstream components (STING, MAVS, TBK1)

  • Correlate with downstream outputs (STAT1 phosphorylation, ISG expression)

  • Compare timing of IRF3 phosphorylation with canonical pathway activation markers

By implementing these comprehensive validation strategies, researchers can confidently interpret phospho-IRF3 data within the context of innate immune signaling networks and generate more robust and reproducible findings.

How can phospho-IRF3 (S386) detection be applied to study emerging viral infections and host-pathogen interactions?

Phospho-IRF3 (S386) detection provides valuable insights into host-pathogen interactions during viral infections:

• Viral evasion mechanism studies:

  • Compare IRF3 phosphorylation kinetics between viruses with known immune evasion strategies

  • Identify viral proteins that interfere with IRF3 phosphorylation through biochemical approaches

  • Create reporter cell lines expressing fluorescent protein-tagged IRF3 to visualize phosphorylation dynamics during infection

  • Use phospho-IRF3 detection to screen viral mutant libraries for immune evasion phenotypes

• Emerging virus research applications:

  • Develop standardized phospho-IRF3 assays as biomarkers for active viral sensing

  • Compare IRF3 activation profiles across virus families to identify pattern recognition receptor preferences

  • Correlate phospho-IRF3 levels with disease severity in clinical samples

  • Identify virus-specific signatures in IRF3-dependent gene expression

• Therapeutic development approaches:

  • Screen for compounds that enhance IRF3 phosphorylation as potential broad-spectrum antivirals

  • Identify molecules that can restore IRF3 signaling in the presence of viral antagonists

  • Develop cell-based phospho-IRF3 reporter systems for high-throughput drug screening

  • Monitor IRF3 activation as a biomarker for immunomodulatory therapy efficacy

The COVID-19 pandemic has highlighted the importance of IRF3 in coronavirus infections, with SARS-CoV-2 targeting multiple components of the IRF3 pathway. Phospho-IRF3 detection has been instrumental in elucidating how viral proteins like NSP3, NSP13, and ORF6 interfere with the interferon response.

What are the cutting-edge approaches for studying IRF3 phosphorylation dynamics in primary human immune cells?

Advanced technologies enable sophisticated analysis of IRF3 phosphorylation in primary human samples:

• Ex vivo stimulation systems:

  • Whole blood stimulation assays with virus-mimetic ligands, followed by phospho-flow cytometry

  • Precision-cut lung slices maintaining tissue architecture for studying IRF3 activation in situ

  • Patient-derived immune cell stimulation to identify aberrant IRF3 responses in disease states

• Single-cell multi-omics integration:

  • CITE-seq with phospho-antibodies to correlate surface phenotype, transcriptome, and IRF3 phosphorylation

  • Spatial transcriptomics combined with phospho-IRF3 immunofluorescence to map activation in tissue context

  • Time-of-flight mass cytometry (CyTOF) with metal-tagged phospho-IRF3 antibodies for deep immune phenotyping

• Live-cell imaging innovations:

  • FRET-based biosensors for real-time monitoring of IRF3 phosphorylation

  • Optogenetic control of IRF3 activation pathways to dissect spatiotemporal dynamics

  • Light-sheet microscopy of IRF3 nuclear translocation in 3D cell culture models

• Humanized model systems:

  • IRF3 phosphorylation analysis in humanized mouse models

  • Human organ-on-chip platforms for studying tissue-specific IRF3 responses

  • iPSC-derived immune cells with engineered IRF3 variants to study human-specific regulation

These approaches provide unprecedented resolution of IRF3 activation dynamics in physiologically relevant human immune cell populations, bridging the gap between reductionist in vitro systems and complex in vivo biology.

How can computational approaches be integrated with phospho-IRF3 (S386) detection to advance systems-level understanding of innate immunity?

Computational biology approaches synergize with experimental phospho-IRF3 data to generate systems-level insights:

• Mathematical modeling of IRF3 activation:

  • Ordinary differential equation (ODE) models incorporating phosphorylation kinetics

  • Stochastic modeling of cell-to-cell variability in IRF3 activation

  • Agent-based models of IRF3-dependent intercellular communication

  • Parameter estimation using phosphorylation time-course data across multiple stimulation conditions

• Network analysis approaches:

  • Reconstruction of IRF3-centered innate immune networks from phosphoproteomics data

  • Identification of network motifs controlling IRF3 phosphorylation dynamics

  • Perturbation analysis to identify critical nodes regulating phospho-IRF3 levels

  • Integration of transcriptomic data to link phosphorylation events to gene expression changes

• Machine learning applications:

  • Pattern recognition in phospho-IRF3 responses to classify pathogen signatures

  • Deep learning models predicting IRF3 activation based on pathogen molecular features

  • Automated image analysis of phospho-IRF3 immunofluorescence for high-content screening

  • Multi-parametric data integration to identify novel regulators of IRF3 phosphorylation

• Structural biology integration:

  • Molecular dynamics simulations of IRF3 conformational changes upon S386 phosphorylation

  • In silico prediction of compounds targeting IRF3 activation or inhibition

  • Structure-based design of improved phospho-specific antibodies

  • Modeling of IRF3-protein interactions dependent on phosphorylation status

By combining quantitative phospho-IRF3 data with computational approaches, researchers can gain unprecedented insights into the systems-level organization of innate immune responses and develop more effective strategies for therapeutic modulation of these pathways.