IFN g Human, His

What is human IFN-γ and what is the significance of a His-tag in research applications?

Human interferon gamma (IFN-γ) is a pleiotropic cytokine that plays essential roles in both innate and adaptive immune responses. It is the only type II interferon found in humans and binds to the heterodimeric IFN-γ receptor (IFNGR) consisting of IFNGR1 and IFNGR2 chains . This interaction activates the JAK-STAT signaling pathway, leading to various immunomodulatory effects.

The addition of a histidine tag (His-tag) to recombinant human IFN-γ serves several research purposes:

• Facilitates protein purification through metal affinity chromatography

• Enables detection using anti-His antibodies

• Provides a consistent attachment point for immobilization in binding assays

• Allows for controlled orientation in structural studies

The His-tag generally does not interfere with the biological activity of IFN-γ when positioned appropriately, though validation of functionality is always recommended when using His-tagged proteins in critical experiments.

What are the primary cellular sources of IFN-γ in humans?

While T lymphocytes and natural killer (NK) cells are traditionally considered the principal sources of IFN-γ, research has demonstrated that human macrophages also produce significant amounts of this cytokine . This finding has important implications for understanding innate immune responses.

Specifically, studies have shown that:

• T lymphocytes secrete IFN-γ following antigen recognition and appropriate co-stimulation

• NK cells produce IFN-γ rapidly upon activation by cytokines or target cell recognition

• Macrophages secrete IFN-γ when stimulated with IL-12 and IL-18, as demonstrated through both immunohistochemistry and ELISPOT analysis

• Dendritic cells have also been shown to produce IFN-γ under certain conditions

This expanded understanding of cellular IFN-γ sources provides a more complete picture of the cytokine network in immune responses.

How does the JAK-STAT signaling pathway mediate IFN-γ biological effects?

IFN-γ initiates signaling by binding to the IFNGR1 component of its heterodimeric receptor, which then recruits IFNGR2 to form an active signaling complex . This binding event triggers a cascade of molecular events:

• Receptor dimerization brings associated JAK1 and JAK2 kinases into proximity

• JAK kinases phosphorylate tyrosine residues on the receptor chains

• These phosphorylated sites serve as docking points for STAT1 molecules

• Recruited STAT1 proteins are phosphorylated by JAKs

• Phosphorylated STAT1 molecules dimerize to form gamma-activated factor (GAF)

• GAF translocates to the nucleus and binds gamma-activated sequences (GAS) in promoters

• This binding activates transcription of IFN-γ-responsive genes

This pathway mediates numerous biological effects, including upregulation of MHC class I and II molecules, activation of macrophages, and regulation of T cell differentiation toward the Th1 phenotype .

What are the standard methods for measuring IFN-γ levels in biological samples?

Two primary approaches exist for quantifying IFN-γ in research settings, each with distinct advantages:

Immunological detection methods:

• Enzyme-linked immunosorbent assay (ELISA) - Based on IFN-γ's unique antigenic structure, offering high specificity for human or murine IFN-γ depending on the antibodies used

• ELISPOT - Enables detection of IFN-γ secretion at the single-cell level, particularly useful for quantifying the frequency of IFN-γ-producing cells

• Flow cytometry with intracellular staining - Allows simultaneous phenotyping of IFN-γ-producing cells

• Multiplex bead assays - Permits simultaneous measurement of IFN-γ alongside other cytokines

Functional activity assays:

• MHC class II induction assay - Based on IFN-γ's ability to upregulate MHC class II (HLA-DR) expression on responsive cells, offering higher sensitivity than immunological methods

• Viral protection assays - Measures the ability of IFN-γ to protect cells from viral cytopathic effects

• Growth inhibition assays - Quantifies IFN-γ-mediated inhibition of susceptible cell lines

The choice between these methods depends on the specific research question, required sensitivity, and available resources .

How can researchers effectively design experiments to study IFN-γ production by human macrophages?

Investigating IFN-γ production by human macrophages requires careful experimental design to avoid potential pitfalls and ensure reliable results:

Cell preparation considerations:

• Use multiple purification steps to eliminate lymphoid cell contamination, as even minimal NK or T cell presence can confound results

• Confirm macrophage purity using specific markers such as CD68 alongside morphological assessment

• Consider using adherence-based methods followed by CD14 positive selection

Stimulation protocols:

• The combination of IL-12 and IL-18 has been shown to effectively stimulate IFN-γ production in macrophages

• Include appropriate timing controls, as the kinetics of IFN-γ production differ between macrophages and lymphoid cells

• Consider priming with macrophage colony-stimulating factor (M-CSF) to differentiate monocytes into macrophages prior to stimulation

Detection at single-cell level:

• Utilize techniques that can detect IFN-γ production at the single-cell level, such as immunohistochemistry and ELISPOT assays

• These methods can identify rare IFN-γ-producing cells (as few as 1 in 1000) and definitively attribute production to macrophages based on morphology and surface markers

This approach definitively established that human macrophages contribute to IFN-γ responses, providing an important link between innate and acquired immunity .

What are the known epitopes on human IFN-γ and their relevance to autoantibody research?

Research on autoantibodies against IFN-γ (AIGAs) has identified three distinct non-overlapping binding sites (epitopes) on the IFN-γ molecule with different functional implications :

Site I:

• Location: Includes regions critical for receptor binding

• Function: Antibodies targeting this site prevent IFN-γ from binding to IFNGR1

• Consequence: Complete neutralization of IFN-γ signaling

Site II:

• Location: Helical C and E regions of IFN-γ

• Function: Antibodies to this site can bind IFN-γ even when it's receptor-bound

• Mechanism: Prevents IFNGR1-IFNGR2 heterodimerization, blocking downstream signaling

• Notable: High-affinity antibodies (Kd < 10⁻¹⁰ M) to this site cannot recognize denatured IFN-γ on Western blots, indicating conformational epitope recognition

Site III:

• Location: Region potentially near H19/S20 residues

• Function: Similar to Site II antibodies in blocking receptor heterodimerization

• Added feature: Can mediate antibody-dependent cellular cytotoxicity through forming antibody-IFN-γ complexes on cell surfaces

Understanding these epitopes is crucial for:

• Designing therapeutic antibodies with specific blocking properties

• Characterizing patient autoantibodies to predict disease severity

• Developing strategies to overcome autoantibody-mediated immunodeficiency

This research provides insights into the structural basis of IFN-γ function and how autoantibodies can disrupt normal signaling through multiple mechanisms .

How do genetic polymorphisms in the IFNG gene affect functional outcomes in disease models?

Genetic variations in the IFNG gene can significantly impact IFN-γ production and function, with notable implications for disease susceptibility and progression:

The +874T/A polymorphism (rs2430561):

• Location: First intron of the IFNG gene

• Functional significance: The T allele correlates with higher IFN-γ production compared to the A allele

• Disease associations: Has been studied in relation to cardiovascular events in rheumatoid arthritis patients

Research findings on this polymorphism include:

• In a study of 1,635 rheumatoid arthritis patients, the presence of the minor allele A was not significantly associated with increased risk of cardiovascular events after adjustment for relevant factors

• Despite this, IFN-γ levels were higher in patients who had experienced cardiovascular events compared to those who had not

• This suggests that while the polymorphism itself may not be directly causative, the resulting cytokine levels may contribute to disease pathophysiology

This exemplifies how genetic variants must be evaluated not only for direct clinical associations but also for their impact on functional parameters like cytokine production levels, which may have more complex relationships with disease outcomes .

What computational approaches exist for predicting IFN-γ inducing peptides?

Recent advancements in computational biology have enabled the prediction of peptides capable of inducing IFN-γ production, which has significant implications for vaccine development and immunotherapy design:

IFNepitope2 prediction system:

• Built on extensively validated datasets containing 25,492 human and 7,983 mouse IFN-γ inducing peptides

• Employs a hybrid approach combining machine learning with sequence similarity methods (BLAST)

• Performance metrics: Achieved AUROC of 0.90 for human and 0.85 for mouse host predictions

Technical details:

• Machine learning approaches: Extra trees algorithm outperformed other techniques

• Feature selection: Dipeptide composition provided better performance than one-hot encoding or binary profiles

• Implementation: Available as web server, standalone application, and Python package for integration with other workflows

This computational tool allows researchers to:

• Screen candidate peptides prior to experimental validation

• Design novel peptides with enhanced IFN-γ inducing capacity

• Optimize epitope selection for vaccines targeting specific pathogens

• Understand sequence patterns that contribute to IFN-γ induction

These predictive approaches significantly reduce the time and resources required for identifying effective immunomodulatory peptides, accelerating research in infectious disease and cancer immunotherapy fields .

How should researchers address discrepancies between ELISA measurements and functional assays of IFN-γ?

When ELISA and functional assay results for IFN-γ diverge, systematic troubleshooting is required:

Common causes of discrepancies:

Methodological solutions:

• Always include appropriate positive and negative controls in both assay types

• Consider running parallel assays with recombinant IFN-γ standards spiked into test matrix

• Validate antibody specificity against known interfering factors

• When possible, use multiple detection methods to triangulate true values

• Document and report discrepancies rather than selecting only "agreeable" data points

Understanding the biological basis of measurement discrepancies often leads to valuable insights about IFN-γ regulation and function in the experimental system being studied .

What are the optimal storage conditions for maintaining the activity of His-tagged human IFN-γ?

Proper storage of His-tagged human IFN-γ is critical for maintaining its biological activity across experiments:

Short-term storage (1-4 weeks):

• Temperature: -20°C to -80°C depending on buffer composition

• Buffer recommendations: PBS with 0.1% carrier protein (BSA or HSA)

• Avoid: Repeated freeze-thaw cycles (aliquot upon receipt)

• Additives to consider: 10-25% glycerol as cryoprotectant

Long-term storage (months to years):

• Temperature: -80°C preferred

• Format: Lyophilized powder shows superior stability compared to solutions

• Reconstitution: Use sterile water or appropriate buffer immediately before use

• Documentation: Maintain detailed records of storage time and conditions

Activity preservation guidelines:

• Perform activity testing after extended storage periods

• Consider reference standards stored in parallel for relative activity assessment

• Protect from light during handling as aromatic amino acids can photooxidize

• Avoid metal contamination that can promote oxidation (use low-binding tubes)

Following these guidelines helps ensure experimental reproducibility when working with His-tagged human IFN-γ across different studies and time points.

How do somatic hypermutations affect autoantibodies to IFN-γ and their neutralizing capacity?

Research on autoantibodies against IFN-γ (AIGAs) has revealed fascinating insights into how somatic hypermutation (SHM) influences their binding and neutralizing properties:

Key findings from molecular studies:

• AIGA-producing B cells appear to exist in the naive state with inherent reactivity to IFN-γ

• Isolated AIGAs show extensive somatic hypermutation, with some containing 15-27 amino acid substitutions in the heavy chain and 12-21 in the light chain

• When these mutations were reverted to create unmutated common ancestor (UCA) variants, binding to IFN-γ was reduced but not eliminated

• The UCA antibodies still demonstrated nanomolar affinity (10⁻⁸ to 10⁻¹⁰ M) for IFN-γ

Functional consequences of SHM:

• Mutated antibodies showed higher affinity primarily due to decreased dissociation rates

• The correlation between binding affinity and neutralizing capacity suggests SHM enhances pathogenicity

• Different epitope recognition patterns emerged through the SHM process

These findings suggest that:

• Pre-existing naive B cells with reactivity to IFN-γ undergo affinity maturation through SHM

• This process enhances their ability to bind and neutralize IFN-γ

• The epitope specificity and neutralizing mechanism may be influenced by specific mutation patterns

This research provides important insights for understanding autoimmunity against cytokines and potential approaches for therapeutic intervention in conditions associated with neutralizing autoantibodies to IFN-γ .

What are the emerging applications of IFN-γ in cancer immunotherapy research?

IFN-γ's pleiotropic immunomodulatory effects make it a focus of cutting-edge cancer immunotherapy research:

Direct anti-tumor mechanisms:

• Upregulation of MHC class I and II on tumor cells, enhancing antigen presentation

• Direct antiproliferative and proapoptotic effects on certain malignant cells

• Inhibition of angiogenesis through multiple pathways

Immunotherapeutic synergies:

• IFN-γ-inducing peptides can enhance responses to immune checkpoint inhibitors

• Prediction tools like IFNepitope2 facilitate identification of optimal peptide sequences for inducing IFN-γ production

• Engineered T cells designed to produce sustained IFN-γ in the tumor microenvironment show enhanced efficacy

Biomarker applications:

• IFN-γ signature gene expression profiles correlate with immunotherapy response

• Sequential measurement of IFN-γ-producing cells can monitor therapeutic efficacy

• ELISPOT and intracellular cytokine staining methods provide cellular resolution of IFN-γ responses

These applications leverage the fundamental immunological properties of IFN-γ while addressing the challenges of delivery, stability, and potential systemic toxicity through innovative approaches.