NFKBIL1 Antibody, Biotin conjugated

What is NFKBIL1 and what role does it play in cellular signaling?

NFKBIL1 (Nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor-like 1), also known as IkappaBL, functions as a critical regulator in innate immune response pathways. It acts as a negative regulator of Toll-like receptor and interferon-regulatory factor signaling cascades, contributing significantly to the negative regulation of transcriptional activation of NF-kappa-B target genes in response to endogenous proinflammatory stimuli . Recent research has identified NFKBIL1 as a key locus associated with quantitative antibody responses to multiple pathogens, including those from herpes, retro-, and polyoma-virus families. The protein plays a central role in modulating hematopoietic pathways and likely impacts cell survival, antibody production, and inflammation resolution . Understanding this protein's function is essential when designing experiments that aim to investigate immune regulation mechanisms.

How is the biotin conjugation achieved in NFKBIL1 antibodies, and what are the structural consequences?

Biotin conjugation to NFKBIL1 antibodies typically involves chemical coupling strategies that target specific reactive groups on the antibody molecule. Most commonly, this involves either amine coupling (targeting lysine residues), thiol coupling (targeting reduced cysteine residues), or carbohydrate coupling (targeting glycosylation sites). Research has demonstrated that conjugation methods significantly impact antibody performance characteristics, with carbohydrate and amine-coupled antibody-drug conjugates (ADCs) generally showing the least destabilizing effects compared to thiol-coupled conjugates . The biotin load (number of biotin molecules per antibody) correlates with structural stability loss, particularly in thiol-conjugated antibodies, though this relationship varies between different IgG scaffolds. When working with biotin-conjugated NFKBIL1 antibodies, researchers should consider the specific conjugation chemistry employed in their selected product and its potential impact on thermal stability and target recognition properties .

What are the appropriate storage and handling conditions for maintaining NFKBIL1 antibody integrity?

To preserve the functional integrity of NFKBIL1 Antibody, Biotin conjugated preparations, store the antibody at either -20°C or -80°C upon receipt . It is crucial to avoid repeated freeze-thaw cycles as these can significantly compromise antibody stability and functionality. The antibody is typically supplied in a buffer containing preservatives (such as 0.03% Proclin 300) and stabilizers (50% Glycerol, 0.01M PBS, pH 7.4) . When handling the antibody for experimental procedures, maintain cold chain conditions whenever possible, and consider aliquoting the stock solution into single-use volumes to minimize freeze-thaw cycles. Monitor the solution for any visible precipitation or cloudiness before use, as these may indicate structural degradation. Research data suggests that conjugated antibodies generally show decreased thermostability compared to their unconjugated counterparts, making proper storage particularly important for maintaining experimental consistency .

How should researchers optimize ELISA protocols when using biotin-conjugated NFKBIL1 antibodies?

When optimizing ELISA protocols with biotin-conjugated NFKBIL1 antibodies, several methodological considerations are essential. First, determine the optimal antibody concentration through titration experiments, typically starting with a range of 0.1-10 μg/mL and assessing signal-to-noise ratios for each concentration. Second, consider the blocking buffer composition—BSA-based blockers may be preferable over milk-based ones as the latter can contain endogenous biotin that interferes with detection. Third, optimize the streptavidin-HRP concentration and incubation time to maximize sensitivity while minimizing background. For enhanced detection, implement a signal amplification strategy such as using avidin-biotin complex (ABC) systems, which leverage the multivalent binding between avidin and biotin. Additionally, include adequate controls, including a biotinylated isotype control antibody (Rabbit IgG-Biotin) to determine non-specific binding levels . When developing sandwich ELISA formats, consider that antibody pairs recognizing distinct epitopes yield optimal sensitivity, as demonstrated in parallel research with other biotin-conjugated antibodies .

What experimental approaches can be used to assess the effect of NFKBIL1 variants on immune response regulation?

To assess the effect of NFKBIL1 variants on immune regulation, researchers should implement multi-faceted experimental designs. First, conduct genotyping studies to identify variants like the insertion-deletion polymorphism rs28362491, which has been associated with altered NFKBIL1 expression . For functional characterization, employ expression quantitative trait locus (eQTL) analysis in relevant immune cell types, including B cells, NK cells, neutrophils, and monocytes, correlating variant genotypes with NFKBIL1 mRNA expression levels. Include both naive and stimulated cell conditions (e.g., LPS or IFNγ treatment) to capture context-dependent effects . Complement these studies with immunophenotyping flow cytometry to assess cell population distributions. To evaluate the impact on antibody responses, measure antibody titers against various pathogens in individuals with different NFKBIL1 variants, as demonstrated in UK Biobank studies that revealed associations between NFKBIL1 variants and antibody responses to herpes, retro-, and polyoma-virus families . Additionally, implement cellular assays measuring NF-κB activation levels using reporter systems or phospho-protein detection methods to directly assess the regulatory impact of NFKBIL1 variants on this key signaling pathway.

How can researchers accurately quantify NFKBIL1 protein expression in different cell types?

For accurate quantification of NFKBIL1 protein expression across different cell types, researchers should employ a comprehensive methodological approach combining multiple techniques. Start with western blotting using biotin-conjugated NFKBIL1 antibodies for semi-quantitative analysis, including appropriate loading controls and standard curves with recombinant NFKBIL1 protein for relative quantification. For more precise quantification, develop a sandwich ELISA system utilizing a capture antibody against one NFKBIL1 epitope and the biotin-conjugated NFKBIL1 antibody as a detection reagent . To address cell-type-specific expression patterns, implement flow cytometry protocols for intracellular NFKBIL1 staining, optimizing permeabilization conditions to maintain cellular integrity while ensuring antibody access. Complement protein-level analyses with mRNA quantification via RT-qPCR, designing primers that distinguish between potential splice variants. For spatial contextualization, perform immunohistochemistry on tissue sections using the biotin-conjugated antibody in conjunction with streptavidin-HRP detection systems, as validated for other biotin-conjugated antibodies in formalin-fixed, paraffin-embedded samples . Finally, validate expression data through multiple antibodies targeting different NFKBIL1 epitopes to ensure specificity and consistency in quantification results.

What strategies can address non-specific binding issues when using biotin-conjugated NFKBIL1 antibodies?

To address non-specific binding with biotin-conjugated NFKBIL1 antibodies, implement a multi-faceted optimization strategy. First, examine your blocking protocol—increase blocking duration (2-4 hours at room temperature or overnight at 4°C) and evaluate alternative blocking agents such as fish gelatin, casein, or commercial blocking buffers specifically formulated for biotin-streptavidin systems. Second, add 0.1-0.5% detergent (Tween-20 or Triton X-100) to washing and antibody diluent buffers to reduce hydrophobic interactions. Third, consider adding carrier proteins like 1-5% BSA or 1-5% normal serum (matching the species of your secondary reagent) to antibody dilution buffers to compete for non-specific binding sites. For immunohistochemistry applications, implement an avidin-biotin blocking step to neutralize endogenous biotin, particularly in biotin-rich tissues like liver, kidney, and brain . Additionally, titrate the biotin-conjugated antibody concentration to determine the optimal signal-to-noise ratio, as excess antibody often contributes to background. If non-specific binding persists, perform pre-adsorption of the antibody with tissues or cell lysates from species with expected cross-reactivity. Finally, include appropriate negative controls in each experiment, such as isotype controls and secondary-only controls, to accurately distinguish specific from non-specific signals.

How does the biotin load affect antibody performance, and how can researchers account for variability?

The biotin load (number of biotin molecules per antibody) significantly influences antibody performance characteristics. Research demonstrates a strong correlation between increased biotin load and decreased thermal stability, particularly in thiol-conjugated antibodies . While high biotin loads can enhance detection sensitivity through increased avidin binding sites, excessive conjugation can compromise structural integrity and alter binding properties. Higher biotin loads have been shown to negatively impact Fc receptor binding, potentially affecting immune complex formation and antibody effector functions . To account for batch-to-batch variability in biotin load, researchers should implement several strategies: (1) characterize each antibody lot using differential scanning calorimetry (DSC) to assess thermal stability shifts; (2) perform titration experiments with each new lot to establish optimal working concentrations; (3) maintain consistent suppliers when possible to minimize manufacturing variations; (4) include internal standards in experimental designs to normalize results across different antibody lots; and (5) when feasible, determine the actual biotin-to-antibody ratio using spectrophotometric methods or specialized assay kits designed for this purpose. For critical experiments, consider preparing larger batches of working dilutions to maintain consistency throughout a study sequence.

What factors contribute to diminished signal in NFKBIL1 detection assays, and how can these be mitigated?

Diminished signal in NFKBIL1 detection assays can stem from multiple factors requiring systematic troubleshooting. First, antibody degradation represents a primary concern—check for repeated freeze-thaw cycles, improper storage temperatures, or extended storage beyond recommended shelf-life. The conjugated antibody preparation contains specific buffer components (50% Glycerol, 0.01M PBS, pH 7.4) crucial for maintaining stability . Second, examine protein denaturation conditions in sample preparation; excessive heat, extreme pH, or harsh detergents can disrupt NFKBIL1 epitopes. Third, insufficient antigen retrieval in immunohistochemistry applications may limit epitope accessibility. Optimize retrieval methods by testing different buffer systems (citrate, EDTA, or Tris) and varying retrieval durations. Fourth, streptavidin reagent quality impacts detection sensitivity—ensure proper storage and freshness of detection reagents. Fifth, endogenous biotin in samples can compete with biotinylated antibodies; implement avidin-biotin blocking steps particularly in biotin-rich tissues. For sandwich ELISA formats, test different antibody pairs targeting distinct epitopes to improve detection efficiency, as shown in studies with other antibody systems . Finally, implement signal amplification strategies such as tyramide signal amplification or enhanced chemiluminescence detection systems for low-abundance targets. Systematic evaluation of each variable through controlled experiments will help identify and address specific causes of diminished signal.

How can researchers utilize NFKBIL1 antibodies to investigate the interplay between NF-κB signaling and inflammatory responses?

To investigate the interplay between NFKBIL1, NF-κB signaling, and inflammatory responses, researchers should implement a multi-modal experimental approach. First, design co-immunoprecipitation studies using biotin-conjugated NFKBIL1 antibodies to identify protein interaction partners within the NF-κB pathway, capturing complexes with streptavidin beads followed by mass spectrometry analysis. Second, establish cell models with NFKBIL1 knockdown or overexpression using siRNA/shRNA or expression vectors, respectively, then quantify changes in NF-κB activation using reporter assays (luciferase-based NF-κB reporters) and nuclear translocation assays (immunofluorescence or cellular fractionation followed by western blotting) . Third, perform chromatin immunoprecipitation (ChIP) experiments to determine if NFKBIL1 associates with specific genomic regions, particularly at NF-κB binding sites. Fourth, conduct transcriptome analysis (RNA-seq) comparing wild-type and NFKBIL1-modulated cells following inflammatory stimuli (LPS, TNF-α, IL-1β) to identify differentially regulated inflammatory gene networks. Fifth, develop ex vivo systems using primary cells from individuals with different NFKBIL1 variants to assess functional differences in inflammatory responses, as suggested by UK Biobank studies showing associations between NFKBIL1 variants and infection risk or allergic disease protection . Finally, utilize phospho-flow cytometry to simultaneously measure activation states of multiple signaling nodes within the NF-κB pathway, providing high-resolution analysis of how NFKBIL1 modulates signaling dynamics in response to inflammatory triggers.

What methodological approaches can determine the epitope specificity of NFKBIL1 antibodies and their impact on protein function?

Determining the epitope specificity of NFKBIL1 antibodies requires a systematic methodological approach combining computational and experimental techniques. Begin with computational epitope prediction using the antibody's immunogen sequence (amino acids 185-312 of human NFKBIL1) to identify potential linear and conformational epitopes. Follow with experimental epitope mapping through: (1) peptide array analysis using overlapping synthetic peptides spanning the immunogen region to identify linear epitopes; (2) alanine scanning mutagenesis, where sequential amino acids are substituted with alanine to identify critical binding residues; (3) hydrogen-deuterium exchange mass spectrometry (HDX-MS) to identify regions protected from exchange upon antibody binding; and (4) X-ray crystallography or cryo-EM of antibody-antigen complexes for high-resolution epitope characterization. To assess functional impact, design competition assays between the antibody and known NFKBIL1 interaction partners to determine if antibody binding disrupts protein-protein interactions. Implement functional blockade experiments by pre-incubating cells with the antibody before stimulation with inflammatory triggers, then measuring NF-κB activation through reporter assays or biochemical readouts . For comparative analysis, characterize multiple antibodies against different NFKBIL1 epitopes and correlate their binding sites with their ability to modulate protein function, similar to approaches used with other antibodies that successfully blocked NF-κB activation .

How can researchers effectively use NFKBIL1 antibodies to study the genetic basis of infection susceptibility and allergic disease?

To investigate the genetic basis of infection susceptibility and allergic disease in relation to NFKBIL1, researchers should implement an integrated approach combining genetic epidemiology with functional immunology. First, utilize large-scale genetic datasets like the UK Biobank to identify associations between NFKBIL1 variants (particularly the insertion-deletion variant rs28362491) and clinical phenotypes related to infection and allergy . Design case-control studies comparing individuals with extreme phenotypes (high infection susceptibility versus resistance, or allergic versus non-allergic) and genotype for NFKBIL1 variants. Second, perform quantitative antibody profiling using multiplex serology against diverse pathogens in individuals with different NFKBIL1 genotypes to identify pathogen-specific associations . Third, establish genotype-specific expression profiles (eQTL analysis) in relevant cell types, including both resting and stimulated conditions, to determine how NFKBIL1 variants affect gene expression dynamics . Fourth, develop ex vivo functional assays using cells from genotyped donors to assess infection susceptibility (pathogen challenge assays), inflammatory responses (cytokine production), and allergic reactivity (basophil activation tests). Fifth, create humanized mouse models carrying different NFKBIL1 variants to study in vivo consequences on infection and allergy. Finally, use biotin-conjugated NFKBIL1 antibodies for immunophenotyping studies to determine if NFKBIL1 variants are associated with differences in immune cell subset distributions or activation states. This comprehensive approach will provide mechanistic insights into how NFKBIL1 genetic variation influences the balance between infection resistance and allergic disease susceptibility.

How should researchers interpret NFKBIL1 expression data across different experimental platforms?

When interpreting NFKBIL1 expression data across different experimental platforms, researchers must implement a structured analytical framework that accounts for platform-specific variables. First, establish normalized reference ranges for each experimental method (western blot, qPCR, ELISA, flow cytometry) using standardized control samples. For western blotting using biotin-conjugated antibodies, always normalize band intensities to housekeeping proteins and include recombinant NFKBIL1 standards for semi-quantitative analysis . For qPCR data, apply appropriate normalization with validated reference genes, preferably using the geometric mean of multiple reference genes to improve accuracy. When comparing protein versus mRNA expression, recognize that discrepancies may reflect post-transcriptional regulation rather than experimental error. For immunohistochemistry or immunofluorescence using biotinylated antibodies, implement digital image analysis with standardized acquisition parameters and quantification algorithms . When integrating data from population studies, such as the UK Biobank analyses of NFKBIL1 variants, account for covariates including age, sex, and genetic background through appropriate statistical models . Additionally, when conducting expression quantitative trait locus (eQTL) analyses, incorporate the first 25 principal components of gene-expression data to account for confounding variation, as implemented in studies examining NFKBIL1 expression in immune cell subsets . Finally, when meta-analyzing across studies, apply random-effects models to account for between-study heterogeneity in NFKBIL1 detection methodologies.

What statistical approaches are most appropriate for analyzing NFKBIL1 genetic variant associations with immune phenotypes?

For analyzing associations between NFKBIL1 genetic variants and immune phenotypes, researchers should implement rigorous statistical frameworks tailored to the specific study design. For genome-wide association studies (GWAS) of antibody responses, as conducted with UK Biobank data, employ linear mixed models incorporating a genetic relatedness matrix as a random effect covariate to account for population substructure . When analyzing multiple related immune phenotypes, implement multivariate GWAS approaches using software like SNPTEST, including age, sex, and principal components as covariates . For meta-analysis across cohorts, utilize methods like Metasoft that can handle heterogeneity between studies. When correlating NFKBIL1 genotypes with gene expression (eQTL analysis), apply linear regression models that include the first 25 principal components of gene expression data to account for confounding variation, with significance assessed using F-tests . For case-control studies examining infection or allergy risk associated with NFKBIL1 variants, implement logistic regression with adjustment for relevant demographic and clinical covariates. Consider applying Bayesian approaches when prioritizing potential causal variants through fine mapping. To account for multiple testing when examining numerous immune phenotypes, implement appropriate correction methods such as Bonferroni, Benjamini-Hochberg FDR, or permutation-based approaches. For complex traits showing non-normal distributions, consider non-parametric methods or appropriate data transformations prior to analysis. Finally, calculate and report effect sizes with confidence intervals rather than relying solely on p-values to facilitate biological interpretation of statistical associations.

How can NFKBIL1 antibodies contribute to understanding the genetic basis of variable immune responses to pathogens?

NFKBIL1 antibodies can significantly advance our understanding of genetically determined immune response variability through several methodological approaches. First, establish immunophenotyping protocols using biotin-conjugated NFKBIL1 antibodies to quantify protein expression levels in immune cell populations from individuals with different NFKBIL1 genotypes, particularly focusing on the insertion-deletion variant rs28362491 identified in UK Biobank studies . These expression profiles can be correlated with antibody titers against multiple pathogens, including herpes, retro-, and polyoma-virus families, to establish genotype-phenotype relationships. Second, develop ex vivo stimulation assays using pathogen-associated molecular patterns (PAMPs) to compare NF-κB activation kinetics between cells from individuals with different NFKBIL1 variants, using the antibodies to track NFKBIL1 protein dynamics during stimulation. Third, implement chromatin immunoprecipitation sequencing (ChIP-seq) experiments to identify genomic regions differentially bound by NF-κB transcription factors in relation to NFKBIL1 variant status. Fourth, design multiplexed single-cell analyses combining NFKBIL1 detection with measurements of cytokine production and activation markers to identify cell-specific consequences of genetic variation. Fifth, utilize biotin-conjugated NFKBIL1 antibodies in proximity ligation assays to investigate how genetic variants affect protein-protein interaction networks within the immune signaling cascade. These approaches will help elucidate the molecular mechanisms by which NFKBIL1 genetic variation contributes to the observed associations with infection risk and allergic disease protection , potentially identifying novel targets for immunomodulatory interventions.

What are the methodological considerations for using NFKBIL1 antibodies in multiplex immunoassays and high-throughput screening?

Implementing NFKBIL1 antibodies in multiplex immunoassays and high-throughput screening requires careful methodological optimization. First, validate antibody specificity in the multiplex context by confirming minimal cross-reactivity with other targets in the panel through spike-in experiments with recombinant proteins. Second, determine optimal working concentrations specifically for multiplex formats, which often differ from single-target assays due to altered reaction kinetics and potential competition effects. Third, select complementary detection systems—when using biotin-conjugated NFKBIL1 antibodies, employ fluorophore-conjugated streptavidin variants (e.g., streptavidin-PE, streptavidin-APC) with spectral properties compatible with other detection channels in the multiplex panel . Fourth, implement bead-based multiplexing platforms (e.g., Luminex) by conjugating capture antibodies against NFKBIL1 to spectrally distinct microspheres, followed by detection with biotin-conjugated antibodies recognizing different epitopes. Fifth, for microarray applications, optimize spotting buffer composition and surface chemistry to maintain antibody functionality after immobilization. Sixth, develop appropriate quality control metrics including internal calibrators and controls for each assay in the multiplex panel. Seventh, implement statistical approaches specifically designed for multiplex data, accounting for batch effects and cross-assay normalization. Finally, when scaling to high-throughput screening, consider automated liquid handling systems and standardized plate layouts with edge wells reserved for controls to minimize positional effects. These methodological considerations will maximize data quality and reproducibility when incorporating NFKBIL1 antibodies into complex multiplex assay systems.

How might NFKBIL1 antibodies be integrated into studies examining the relationship between inflammation and autoimmune pathologies?

Integrating NFKBIL1 antibodies into studies of inflammation and autoimmunity requires sophisticated experimental designs that bridge molecular mechanisms with clinical phenotypes. First, establish immunohistochemistry protocols using biotin-conjugated NFKBIL1 antibodies to characterize protein expression patterns in tissue biopsies from autoimmune disease patients compared to healthy controls . Focus particularly on tissues with active inflammatory lesions versus uninvolved regions to identify disease-specific expression patterns. Second, implement flow cytometry panels incorporating NFKBIL1 detection to identify immune cell subsets with altered expression in autoimmune conditions, correlating these patterns with clinical disease activity scores. Third, design longitudinal studies measuring NFKBIL1 expression dynamics during disease flares and remission, potentially identifying biomarkers for disease activity or treatment response. Fourth, develop ex vivo functional assays using cells from autoimmune patients to assess how NFKBIL1 modulates inflammatory responses to relevant stimuli, using blocking experiments with anti-NFKBIL1 antibodies to determine functional consequences. Fifth, perform genotyping for the NFKBIL1 insertion-deletion variant rs28362491 in autoimmune disease cohorts, correlating genotypes with disease susceptibility, severity, and treatment response . Sixth, establish in vitro models of autoimmune pathology incorporating NFKBIL1 genetic variants to investigate differential responses to therapeutic interventions. These integrated approaches will help elucidate how NFKBIL1's role in regulating NF-κB signaling and inflammation contributes to autoimmune disease pathogenesis, potentially identifying novel targets for therapeutic intervention.

How might emerging technologies enhance the utility of NFKBIL1 antibodies in immunological research?

Emerging technologies offer transformative potential for expanding NFKBIL1 antibody applications in immunological research. First, spatial transcriptomics combined with in situ protein detection using biotin-conjugated NFKBIL1 antibodies will enable simultaneous visualization of NFKBIL1 protein expression and the surrounding transcriptional landscape within tissue microenvironments. Second, the integration of NFKBIL1 antibodies into high-parameter cytometry platforms, including spectral cytometry and mass cytometry (CyTOF), will allow simultaneous detection of NFKBIL1 alongside 40+ other markers, providing unprecedented cellular phenotyping resolution. Third, microfluidic single-cell western blotting systems can be adapted for NFKBIL1 detection, enabling protein quantification at the single-cell level while preserving information about cellular heterogeneity. Fourth, proximity extension assays (PEA) incorporating NFKBIL1 antibodies will facilitate ultrasensitive protein quantification in minimal sample volumes through antibody-oligonucleotide conjugates and qPCR amplification. Fifth, CRISPR-based genomic screening platforms combined with NFKBIL1 antibody detection will enable systematic identification of genes modulating NFKBIL1 expression and function. Sixth, organ-on-a-chip systems incorporating real-time immunosensing with NFKBIL1 antibodies will allow dynamic monitoring of protein expression under physiologically relevant conditions. Finally, integrating machine learning algorithms with high-content imaging using fluorescently labeled NFKBIL1 antibodies will enhance pattern recognition of subcellular localization changes in response to stimuli. These technological advancements will significantly expand our ability to investigate NFKBIL1's role in immune regulation at unprecedented resolution and scale.

What potential exists for developing novel functional assays to measure NFKBIL1-mediated NF-κB pathway inhibition?

Developing novel functional assays for NFKBIL1-mediated NF-κB pathway inhibition requires innovative methodological approaches that capture the dynamic and context-dependent nature of this signaling system. First, design bioluminescence resonance energy transfer (BRET) or fluorescence resonance energy transfer (FRET) biosensor systems to directly measure NFKBIL1 interaction with key NF-κB pathway components in living cells, enabling real-time monitoring of molecular interactions. Second, adapt CRISPR activation (CRISPRa) and CRISPR interference (CRISPRi) systems to achieve titratable modulation of NFKBIL1 expression, allowing dose-response analyses of NF-κB inhibition. Third, develop luciferase reporter systems under the control of specific NF-κB-responsive promoters that can distinguish between different NF-κB dimer configurations, potentially revealing selective effects of NFKBIL1 on specific transcriptional outputs. Fourth, implement live-cell imaging approaches using fluorescently tagged NF-κB components combined with optogenetic control of NFKBIL1 expression to dissect temporal aspects of pathway regulation. Fifth, design multiplexed ELISA systems utilizing biotin-conjugated NFKBIL1 antibodies that simultaneously measure multiple phosphorylated components of the NF-κB pathway, providing a systems-level view of signaling dynamics. Sixth, develop in vitro reconstitution assays with purified components to determine the direct biochemical mechanisms of NFKBIL1-mediated inhibition. Seventh, adapt biotin-conjugated NFKBIL1 antibodies for proximity ligation assays to map the spatial organization of NFKBIL1-containing protein complexes within different subcellular compartments. These innovative functional assays will significantly advance our mechanistic understanding of how NFKBIL1 regulates NF-κB signaling in various physiological and pathological contexts.