IRF9 Antibody, Biotin conjugated

What is IRF9 and why is it important in immunological research?

IRF9 (Interferon Regulatory Factor 9) is a critical component of the interferon signaling pathway, functioning as part of the ISGF3 (Interferon-Stimulated Gene Factor 3) complex. This complex forms when IRF9 associates with STAT1 and STAT2 following type I interferon stimulation. Research has demonstrated that IRF9 plays essential roles in autoimmune conditions, including Systemic Lupus Erythematosus (SLE), where it contributes to IgG autoantibody production and B cell responses . The molecule participates in both basal (homeostatic) and interferon-induced gene expression, making it critical for understanding immune system regulation. Methodologically, IRF9 detection using specific antibodies enables researchers to track interferon pathway activation in various experimental systems, providing insights into both normal immune function and pathological states.

How do biotin-conjugated antibodies differ from unconjugated or fluorophore-conjugated IRF9 antibodies?

Biotin-conjugated IRF9 antibodies offer distinct methodological advantages compared to unconjugated or directly fluorophore-labeled alternatives. The biotin-streptavidin system provides signal amplification capabilities that can enhance sensitivity in detection methods like flow cytometry, immunoprecipitation, and ChIP experiments. Unlike fluorophore-conjugated antibodies that have a fixed detection channel, biotin-conjugated antibodies allow flexible detection through various streptavidin-conjugated secondary reagents (fluorophores, enzymes, or quantum dots). This flexibility permits multi-parameter experimental designs where channel selection can be adjusted based on other markers in your panel .

The choice between conjugation types should be guided by your specific research application:

• Biotin conjugation: Optimal for signal amplification in low-expression targets and proximity labeling experiments

• Direct fluorophore conjugation (e.g., FITC or AF647): Best for straightforward detection without secondary steps

• Unconjugated: Provides maximum flexibility for secondary detection methods

What are the key differences between monoclonal and polyclonal IRF9 antibodies?

The choice between monoclonal and polyclonal IRF9 antibodies significantly impacts experimental outcomes and data interpretation. Monoclonal antibodies recognize a single epitope with high specificity but potentially lower sensitivity. For example, the highly validated monoclonal anti-IRF9 antibody 6FI-H5 delivers exceptional signal-to-noise ratios in ChIP applications , making it valuable for precise genomic mapping of IRF9 binding sites.

Polyclonal antibodies recognize multiple epitopes, offering broader detection capabilities but potentially increased background. This table summarizes key considerations:

For studying IRF9's role in protein complexes like ISGF3, polyclonal antibodies may detect IRF9 regardless of its binding partners, while monoclonal antibodies might be epitope-blocked when IRF9 forms complexes with STAT1/2 .

What are the optimal staining protocols for intracellular IRF9 detection using biotin-conjugated antibodies?

For optimal intracellular IRF9 detection using biotin-conjugated antibodies in flow cytometry, a methodical approach is essential. First, proper cell fixation and permeabilization are critical as IRF9 primarily localizes to the cytoplasm in resting cells and translocates to the nucleus upon interferon stimulation.

Detailed Protocol:

• Cell Preparation:

  • Harvest cells (5×10⁵ to 1×10⁶ per sample)

  • Wash twice with cold PBS containing 2% FBS

  • Fix cells with 4% paraformaldehyde for 15 minutes at room temperature

• Permeabilization:

  • Use a methanol-based permeabilization for nuclear factor detection:

    • Resuspend cell pellet in ice-cold 90% methanol

    • Incubate for 30 minutes on ice

  • Alternatively, for cytoplasmic detection, use 0.1% Triton X-100 or a commercial permeabilization buffer

• Blocking and Staining:

  • Block with 5% normal serum from the same species as the secondary reagent

  • Incubate with biotin-conjugated anti-IRF9 antibody (optimal concentration typically 1-5 μg/ml) for 45-60 minutes at room temperature

  • Wash three times with PBS containing 2% FBS

  • Incubate with streptavidin-fluorophore conjugate (adjust based on your cytometer configuration)

  • Wash three times before analysis

• Controls:

  • Include an isotype-matched biotin-conjugated control antibody

  • For positive controls, treat cells with type I interferons (1000 U/ml IFN-α for 30-90 minutes) to induce ISGF3 complex formation

This protocol allows for detection of both basal and interferon-stimulated IRF9 levels, enabling quantification of interferon pathway activation in various cell types.

How can biotin-conjugated IRF9 antibodies be incorporated into multi-parameter flow cytometry panels?

Incorporating biotin-conjugated IRF9 antibodies into multi-parameter flow cytometry panels requires strategic planning to maximize information while avoiding technical conflicts. The flexibility of biotin detection allows researchers to select streptavidin conjugates that complement existing panel design.

Methodological Approach:

• Panel Design Considerations:

  • Select a streptavidin conjugate in a detection channel not occupied by other markers

  • Consider signal strength: place streptavidin conjugates in appropriate channels based on IRF9 expression level

  • Account for spectral overlap with careful compensation controls

• Staining Sequence:

  • For surface/intracellular combinations:

    • Complete all surface staining before fixation and permeabilization

    • Perform IRF9 staining after permeabilization

    • Add streptavidin conjugate last to prevent non-specific binding

• Example Panel for Dendritic Cell IRF9 Analysis:

• Titration and Validation:

  • Titrate both primary biotin-conjugated antibody and streptavidin conjugate

  • Validate with positive controls (IFN-treated cells) and negative controls (IRF9-deficient cells if available)

This approach enables simultaneous assessment of IRF9 expression alongside cellular phenotype, activation status, and other signaling molecules to create a comprehensive view of interferon responses in complex cell populations .

How does IRF9 interact with STAT1 and STAT2 to form the ISGF3 complex?

The formation of the ISGF3 complex represents a fascinating instance of conditional protein assembly that recent research has clarified. Contrary to previous assumptions, ISGF3 formation appears to be DNA-dependent rather than occurring freely in the cytoplasm.

Recent ChIP-sequencing studies using the novel anti-IRF9 monoclonal antibody 6FI-H5 revealed that IRF9-STAT1-STAT2 co-localization primarily occurs on DNA at interferon-stimulated response elements (ISREs) . Co-immunoprecipitation experiments demonstrated that in resting cells, IRF9 forms stable complexes with STAT2, but not with STAT1. Similarly, STAT1-STAT2 heterodimers exist independently in resting cells. Notably, despite IFN-I treatment, complexes containing both STAT1 and IRF9 were not detected in solution .

DNA-mediated precipitation studies provided the critical insight: oligonucleotides representing ISREs from ISG15 or Oas1a genes precipitated only STAT2-IRF9 complexes from resting cell extracts, while the complete ISGF3 complex was only precipitated after IFN-I stimulation . This suggests that either:

• ISRE DNA binding stabilizes the complete ISGF3 complex, which is otherwise too transient to detect

• DNA binding is actually required for ISGF3 formation

These findings fundamentally shift our understanding of how this key interferon signaling complex assembles and functions, suggesting a model where partial complexes exist in the cellular milieu, but complete assembly requires appropriate DNA binding sites.

What proximity labeling approaches can be used to study IRF9 protein interactions?

Proximity labeling has emerged as a powerful approach for studying dynamic protein interactions in the interferon signaling pathway. The BioID technology, employing a modified biotin ligase (BirA*) fused to proteins of interest, provides critical insights into protein proximity within approximately 10nm distances in living cells.

Methodological Implementation:

• System Design:

  • Construction of doxycycline-inducible IRF9-BirA* fusion proteins

  • Expression titration to match endogenous IRF9 levels (avoiding overexpression artifacts)

  • Control constructs with N-terminally tagged BirA* alone

• Proximity Labeling Protocol:

  • Culture cells in biotin-supplemented media (50μM biotin)

  • Induce expression at endogenous-equivalent levels

  • Allow biotinylation to occur (12-24 hours)

  • Optional: Treat with interferon to assess dynamic changes in interaction partners

  • Lyse cells under stringent conditions

  • Capture biotinylated proteins with streptavidin affinity purification

• Analysis Approaches:

  • Parallel Reaction Monitoring (PRM) for targeted, quantitative assessment of specific interactors

  • Mass spectrometry for unbiased interactome discovery

  • Western blotting validation of key interactions

Research Findings:
When implemented in RAW 264.7 macrophages, IRF9-BirA* proximity labeling revealed constitutive association between IRF9 and STAT2 in resting cells, even before interferon stimulation. Importantly, STAT1 was not enriched in these experiments, confirming the absence of preformed ISGF3 complexes . Complementary STAT2-BirA* experiments demonstrated proximity between STAT2 and both IRF9 and STAT1, validating the model of separate STAT2-IRF9 and STAT1-STAT2 complexes existing prior to interferon stimulation .

This approach also identified previously unknown IRF9 interactions with chromatin modifiers, suggesting broader roles in transcriptional regulation beyond canonical interferon signaling.

How do IRF9-containing complexes differ between resting and interferon-stimulated cells?

The composition and function of IRF9-containing protein complexes undergo significant remodeling during interferon stimulation, as revealed by biochemical and proximity labeling studies. Understanding these dynamic changes provides insight into both homeostatic and activated states of the interferon pathway.

In Resting Cells:

• IRF9 primarily exists in complex with STAT2, as demonstrated by co-immunoprecipitation and BioID proximity labeling

• These STAT2-IRF9 complexes can bind to ISRE DNA elements even without interferon stimulation

• A smaller population of STAT1-STAT2 heterodimers exists independently

• Complete ISGF3 complexes (STAT1-STAT2-IRF9) are not detectable in solution

• IRF9 associates with chromatin modifiers, suggesting transcriptional regulatory functions even in the basal state

After Interferon Stimulation:

• STAT1 and STAT2 become phosphorylated

• Complete ISGF3 complexes form on DNA at ISRE elements, as demonstrated by ChIP-sequencing of all three components

• The interaction between STAT2 and IRF9 increases, as shown by increased recovery in proximity labeling experiments

• DNA-binding studies show that only after interferon stimulation can all three components (STAT1, STAT2, and IRF9) be pulled down together using ISRE oligonucleotides

This dynamic remodeling likely explains the two distinct phases of interferon responses: a basal, homeostatic regulation through STAT2-IRF9 complexes and an amplified, activated state through complete ISGF3 assembly on target genes.

What is the role of IRF9 in autoantibody production and autoimmune diseases?

IRF9 plays a critical role in autoantibody production and autoimmune pathogenesis, particularly in Systemic Lupus Erythematosus (SLE). Studies using pristane-induced lupus models have provided definitive evidence for IRF9's involvement in isotype switching and autoantibody development.

In pristane-induced mouse models of SLE, IRF9 deficiency (Irf9-/-) resulted in significant alterations in the autoantibody profile:

• Reduced IgG Autoantibodies: Irf9-/- mice showed a marked decrease in the production of high-titer, high-affinity, isotype-switched IgG autoantibodies directed against nucleic acid-associated antigens, which are hallmarks of SLE

• Increased IgM Autoantibodies: Interestingly, levels of IgM autoantibodies were significantly elevated in pristane-treated Irf9-/- mice, suggesting that IRF9 plays a specific role in promoting isotype switching from IgM to IgG in response to self-antigens

• Impaired TLR7 Responses: B cells from Irf9-/- mice exhibited severely impaired responses to TLR7 ligands, demonstrating IRF9's crucial role in linking type I interferon signaling to TLR7-mediated B cell activation

These findings establish IRF9 as a critical link between type I interferon signaling and TLR-mediated autoimmunity. Mechanistically, type I interferons upregulate TLR7 expression in B cells through an IRF9-dependent pathway, creating a feed-forward loop that amplifies autoimmune responses . Without IRF9, B cells cannot effectively respond to nucleic acid-containing immune complexes through TLR7, thereby interrupting a key pathway in autoimmunity.

The research demonstrates that IFN-I signaling operates upstream of TLR activation in autoreactive B cells, positioning IRF9 as a potential therapeutic target for interrupting autoantibody production in SLE and related autoimmune conditions.

How does IRF9 deficiency affect B cell responses to TLR ligands?

IRF9 deficiency profoundly impacts B cell responses to Toll-like receptor ligands, particularly TLR7, revealing a critical role for this transcription factor in linking interferon signaling to innate immune activation in B cells.

Experimental Findings:

• TLR7 Expression: B cells from Irf9-/- mice exhibited greatly reduced upregulation of TLR7 in response to IFN-α stimulation . This indicates that IRF9 is essential for interferon-mediated enhancement of TLR7 expression.

• TLR7 Functionality: Irf9-/- B cells were functionally incapable of being activated through TLR7 stimulation . This comprehensive defect suggests that IRF9 regulates not only TLR7 expression but potentially additional components of the TLR7 signaling pathway.

• TLR9 Responses: In contrast to STAT1-deficient B cells (which showed impairment in both TLR7 and TLR9 responses), IRF9-deficient B cells maintained some TLR9 functionality . This differential effect indicates that IRF9 and STAT1 play distinct roles in regulating various TLR pathways.

• Mechanistic Implications: These findings suggest that IRF9 functions as a critical molecular link between the type I interferon pathway and nucleic acid-sensing TLRs, particularly TLR7. Without IRF9, B cells cannot effectively respond to RNA-containing immune complexes, a key trigger in autoimmune conditions like SLE.

This research has important implications for understanding autoimmunity, as it positions IRF9 at the intersection of interferon signaling and B cell activation by nucleic acid-containing autoantigens. The selective effect on TLR7 versus TLR9 pathways may explain differential autoantibody profiles observed in various autoimmune conditions and suggests that targeting IRF9 might provide a more selective approach to modulating nucleic acid-driven autoimmunity.

What are the best validation methods for confirming IRF9 antibody specificity?

Thorough validation of IRF9 antibody specificity is essential for generating reliable research data. A comprehensive validation strategy employs multiple complementary approaches to confirm both binding specificity and functionality in relevant applications.

Recommended Validation Protocol:

• Genetic Controls:

  • Test antibody in Irf9-/- cells or tissues

  • Use siRNA/shRNA knockdown in relevant cell types

  • Compare signal with overexpression systems

• Application-Specific Validation:

  • For ChIP applications: Perform ChIP-qPCR at known IRF9 binding sites (e.g., ISG15 or Oas1a promoters) and compare with IRF9-deficient controls

  • For flow cytometry: Compare staining in IFN-stimulated vs. unstimulated cells, with corresponding shifts in nuclear translocation

  • For Western blotting: Confirm single band at expected molecular weight (~48 kDa) that increases after IFN treatment

• Cross-Application Validation:

  • Antibodies that perform well in multiple applications (e.g., the 6FI-H5 clone for both ChIP and Western blotting) have higher confidence of specificity

  • Confirm interactions with known partners (STAT2) via co-IP

• Peptide Competition:

  • Pre-incubate antibody with purified IRF9 protein or immunizing peptide

  • Observe abolishment of specific signal

Performance Metrics Table:
For a properly validated IRF9 antibody, the following performance characteristics should be established:

Implementing this multi-faceted validation approach ensures that experimental observations truly reflect IRF9 biology rather than non-specific antibody interactions.

How can researchers troubleshoot weak or non-specific signals when using biotin-conjugated IRF9 antibodies?

When troubleshooting weak or non-specific signals with biotin-conjugated IRF9 antibodies, a systematic approach addressing each component of the detection system is essential. The biotin-streptavidin system introduces specific considerations beyond those of conventional antibody applications.

Methodological Troubleshooting Approach:

• Addressing Low Signal Strength:

  • Increase primary antibody concentration (perform titration series)

  • Extend primary antibody incubation time (4°C overnight instead of 1-2 hours at RT)

  • Optimize fixation and permeabilization for nuclear factor access

  • Enhance epitope retrieval (for tissue sections)

  • Increase biotin-streptavidin amplification by using higher sensitivity detection systems

  • Verify IRF9 expression levels (may be low in non-stimulated cells)

• Reducing Background and Non-Specific Binding:

  • Block endogenous biotin with avidin/biotin blocking kit (essential for tissues with high endogenous biotin)

  • Increase blocking stringency (5-10% serum plus 1% BSA)

  • Add 0.1-0.3% Triton X-100 to reduce hydrophobic interactions

  • Reduce streptavidin conjugate concentration (often the source of background)

  • Include additional wash steps with PBS-T (0.05% Tween-20)

• Application-Specific Optimizations:

  • For flow cytometry: Exclude dead cells with viability dye; single cells with doublet discrimination

  • For ChIP: Increase sonication efficiency for better chromatin fragmentation; modify wash stringency

  • For Western blotting: Optimize transfer conditions; use milk instead of BSA for blocking

• Positive Control Strategies:

  • Include IFN-treated samples (30-90 min with 1000 U/ml IFN-α) to upregulate IRF9

  • Use cell lines with known high IRF9 expression (e.g., plasmacytoid dendritic cells)

  • Consider transfected overexpression controls for very low abundance targets

Decision Matrix for Signal Issues:

By systematically addressing each variable in this process, researchers can optimize detection of IRF9 while minimizing artifacts that could confound interpretation of experimental results.

How can ChIP-Seq be optimized for IRF9 binding site identification?

Chromatin immunoprecipitation followed by sequencing (ChIP-Seq) for IRF9 requires careful optimization to generate high-quality genomic binding profiles. The first successful ChIP-Seq study examining all three ISGF3 components simultaneously provides valuable methodological insights for researchers pursuing similar experiments.

Optimized ChIP-Seq Protocol for IRF9:

• Antibody Selection:

  • The monoclonal antibody 6FI-H5 has demonstrated excellent signal-to-noise ratios for IRF9 ChIP applications

  • For biotin-conjugated antibodies, implement a two-step ChIP using streptavidin beads for capture

• Experimental Design:

  • Include both resting and interferon-stimulated conditions (typically 1000 U/ml IFN-α/β for 30-90 minutes)

  • Add STAT1 and STAT2 ChIP in parallel for comprehensive ISGF3 complex mapping

  • Include input controls and IgG negative controls

  • Consider including Irf9-/- cells as biological negative controls

• Chromatin Preparation:

  • Crosslink with 1% formaldehyde for 10 minutes at room temperature

  • For nuclear factors, optimize sonication to generate 150-300 bp fragments

  • Verify fragmentation efficiency by agarose gel electrophoresis

  • Pre-clear chromatin with protein A/G beads before immunoprecipitation

• Quality Control Metrics:

  • Perform ChIP-qPCR at known IRF9 binding sites (ISG15, Oas1a promoters) before sequencing

  • Target enrichment >10-fold over IgG control indicates successful ChIP

  • Aim for >10 million uniquely mapped reads for sufficient coverage

  • Expected proportion of peaks near promoters: 30-50% for transcription factors

Analytical Considerations:
Peak calling for IRF9 should account for its unique binding characteristics. Since IRF9 can bind DNA in both resting conditions (as STAT2-IRF9) and after stimulation (as ISGF3), differential binding analysis between these conditions provides valuable insights into the dynamic regulation of interferon responses . Target gene identification should incorporate RNA-seq data to correlate binding events with transcriptional outcomes.

This optimized approach has revealed that in mouse bone marrow-derived macrophages, IRF9 binding occurs at ISRE motifs in both basal and interferon-stimulated conditions, with STAT1 recruitment occurring primarily after stimulation .

What approaches can be used to study the dynamic formation of ISGF3 complexes?

Studying the dynamic assembly of the ISGF3 complex requires methods that can capture transient interactions and distinguish different molecular states. Recent research indicates that ISGF3 formation may be DNA-dependent, necessitating techniques that examine protein-protein interactions in the context of chromatin binding.

Complementary Methodological Approaches:

• DNA-Mediated Precipitation:

  • Synthesize biotinylated oligonucleotides containing ISRE sequences (e.g., from ISG15 or Oas1a promoters)

  • Incubate with nuclear extracts from resting and IFN-stimulated cells

  • Capture DNA-protein complexes with streptavidin beads

  • Analyze bound proteins by Western blotting for STAT1, STAT2, and IRF9

  • This approach has demonstrated that complete ISGF3 complexes form only after IFN stimulation and only in the presence of DNA

• Sequential ChIP (ChIP-reChIP):

  • Perform first ChIP with anti-IRF9 antibody

  • Elute captured complexes

  • Perform second ChIP with anti-STAT1 or anti-STAT2 antibodies

  • This identifies genomic regions where multiple components co-localize

  • Can distinguish between IRF9-only, STAT2-IRF9, and complete ISGF3 binding sites

• Live-Cell Imaging:

  • Express fluorescently tagged IRF9, STAT1, and STAT2 (ensuring expression at physiological levels)

  • Use Förster Resonance Energy Transfer (FRET) to detect protein proximity

  • Implement Fluorescence Recovery After Photobleaching (FRAP) to assess mobility and binding dynamics

  • Apply fluorescence correlation spectroscopy to determine complex stoichiometry

• Proximity Ligation Assay (PLA):

  • Use antibodies against IRF9, STAT1, and STAT2

  • Apply secondary antibodies with attached DNA probes

  • When proteins are in close proximity (<40nm), DNA probes can be ligated and amplified

  • Provides spatial resolution of complex formation within cells

  • Quantifiable by microscopy or flow cytometry

Research Findings:
These methodologies have challenged the traditional model of ISGF3 complex formation. Rather than forming in solution following IFN stimulation, research now suggests that STAT2-IRF9 and STAT1-STAT2 exist as separate complexes, with complete ISGF3 assembly occurring on DNA . This model explains why co-immunoprecipitation and BioID approaches fail to detect interactions between STAT1 and IRF9 despite their co-localization on chromatin in ChIP-seq experiments.

These insights have significant implications for understanding interferon signaling dynamics and developing strategies to modulate these pathways in disease contexts.