The INO4 antibody specifically recognizes the Ino4 protein, a basic helix-loop-helix (bHLH) transcription factor that forms a heterodimer with Ino2p. This complex binds to inositol/choline-responsive elements (ICREs) in promoters of genes involved in lipid metabolism, including INO1, FAS1, and FAS2 .
Epitope Tags: Studies often employ HA-tagged Ino4 constructs (e.g., INO4-HA) for detection. The antibody targets epitopes within the N-terminal region of Ino4p .
Functional Assays: Used in chromatin immunoprecipitation (ChIP), Western blotting, and immunofluorescence to localize Ino4p and quantify its expression under varying conditions (e.g., inositol/choline supplementation) .
Transcriptional Regulation: Validates Ino4p’s role in activating phospholipid biosynthetic genes and its autoregulatory mechanism .
Stress Response Studies: Detects Ino4p levels during genotoxic stress (e.g., methyl methanesulfonate (MMS) exposure) to study its interaction with Opi1, a repressor of inositol metabolism .
Protein-Protein Interactions: Identifies Ino4p’s binding partners, such as Ino2p, using co-immunoprecipitation (Co-IP) .
Promoter Analysis: The INO4 promoter contains two critical regions:
| Promoter Region | Function | Impact on Expression | Source |
|---|---|---|---|
| −58 to −46 | Transcription initiation site | Absolute requirement | |
| −114 to −86 | Enhancer region | 5–10 fold increase |
Lipid Biosynthesis: ino4Δ strains show 50% reduction in FAS1 and FAS2 expression and impaired fatty acid synthesis .
ERAD Pathway: ino4Δ stabilizes Hrd1 and Doa10 substrates, indicating a role in endoplasmic reticulum-associated degradation (ERAD) .
Stress Sensitivity: Constitutive Ino2-Ino4 activity in opi1Δ mutants causes hypersensitivity to MMS, reversed by INO4 deletion .
Low Abundance: The INO4 transcript and protein are weakly expressed, necessitating high-sensitivity probes or antibodies for detection .
Cross-Reactivity: Specificity is critical due to structural similarities between bHLH transcription factors. Validations include using ino4Δ strains as negative controls .
Structural Insights: Cryo-EM studies reveal Ino2p/Ino4p dimerization and DNA-binding interfaces, aiding antibody epitope mapping .
Transcriptome-Lipidome Integration: INO4 deletion perturbs lipid profiles, linking transcriptional regulation to membrane composition .
KEGG: sce:YOL108C
STRING: 4932.YOL108C
INO4 functions as a transcription factor that forms a heterodimeric complex with INO2 to regulate phospholipid biosynthesis in yeast. The INO2-INO4 complex binds to inositol-choline-responsive elements through basic helix-loop-helix domains to control the expression of phospholipid biosynthetic genes . INO4 is required for the derepression of inositol/choline-regulated genes such as INO1, CHO1, CHO2, and OPI3, playing a crucial role in lipid homeostasis . Recent research has also revealed that INO4 deletion broadly impairs protein degradation mediated by endoplasmic reticulum-associated degradation (ERAD) ubiquitin ligases Hrd1 and Doa10, suggesting a broader role in maintaining proteostasis .
Validating INO4 antibodies requires multiple approaches to ensure specificity. Begin with Western blot analysis comparing wild-type yeast lysates to those from ino4Δ knockout strains, expecting a specific band at approximately the predicted molecular weight in wild-type samples and absence in knockout samples . Follow with immunoprecipitation experiments coupled with mass spectrometry to confirm the identity of pulled-down proteins. Additional validation should include immunofluorescence microscopy comparing wild-type and knockout strains to verify nuclear localization patterns consistent with transcription factor function. Cross-reactivity testing against similar helix-loop-helix transcription factors, particularly INO2, is essential given their structural similarity and functional relationship.
For optimal INO4 detection, culture yeast under conditions that influence INO4 expression and activity. Since INO4 expression appears constitutive but its activity may be regulated by inositol availability, prepare samples from cells grown in both inositol-replete and inositol-depleted conditions . For protein extraction, use a buffer containing 50 mM Tris-HCl (pH 7.5), 150 mM NaCl, 1% Triton X-100, 0.1% SDS, protease inhibitor cocktail, and phosphatase inhibitors. Include a nuclear extraction step since INO4 functions as a transcription factor. For Western blotting, transfer to PVDF membranes rather than nitrocellulose to enhance protein retention, and block with 5% BSA rather than milk to prevent nonspecific interactions.
Every experiment using INO4 antibodies should include multiple controls to ensure reliable results. Essential negative controls include: samples from ino4Δ knockout strains, secondary antibody-only controls, and isotype controls using non-specific IgG of the same class as the INO4 antibody . Positive controls should include samples with verified INO4 overexpression, such as strains containing INO4 under a galactose-inducible promoter . For experiments examining INO4 regulation, include samples from opi1Δ strains, which would be expected to show altered INO4 activity due to the constitutive activation of INO2-INO4 regulated genes . Additionally, include technical replicates to assess experimental variability and biological replicates to account for strain-to-strain variation.
INO4 antibodies can be powerful tools for investigating the dynamics of INO2-INO4 complex formation under various cellular conditions. Implement co-immunoprecipitation assays using INO4 antibodies followed by Western blotting for INO2 to track their association in response to changing inositol or lipid levels . For temporal dynamics, combine this approach with time-course experiments after inositol deprivation or repletion. Chromatin immunoprecipitation (ChIP) using INO4 antibodies can map genome-wide binding sites and reveal how INO2-INO4 occupancy changes in response to metabolic shifts. Advanced techniques like proximity ligation assays (PLA) using both INO2 and INO4 antibodies can visualize the subcellular locations where these proteins interact. Sequential ChIP (ChIP-reChIP) with INO2 and INO4 antibodies can definitively identify genomic loci bound by the heterodimer versus each factor independently.
Post-translational modifications (PTMs) can significantly impact INO4 antibody recognition, potentially leading to false negative results if the epitope is modified. Generate a panel of phospho-specific INO4 antibodies that recognize known or predicted phosphorylation sites to comprehensively study INO4 regulation. Before immunoprecipitation experiments, treat samples with phosphatases to determine whether phosphorylation affects antibody binding. Use 2D gel electrophoresis followed by Western blotting with INO4 antibodies to separate differently modified forms of the protein. For mass spectrometry analysis, perform immunoprecipitation with INO4 antibodies under native conditions to preserve protein-protein interactions and potential PTMs. Consider developing antibodies against specific modified forms of INO4 if particular PTMs are found to be functionally significant in regulating its activity or interactions.
To investigate INO4 binding to target promoters during genotoxic stress, implement a combination of genomic and biochemical approaches. Perform chromatin immunoprecipitation sequencing (ChIP-seq) using INO4 antibodies on cells treated with genotoxic agents such as methyl methanesulfonate (MMS) . Compare binding profiles between wild-type and opi1Δ strains to understand how Opi1-mediated regulation affects INO4 recruitment to chromatin during stress response. For specific target genes, use ChIP-qPCR to quantitatively measure INO4 occupancy at promoters of genes involved in phospholipid biosynthesis and DNA damage response. Combine with nascent transcript analysis using PRO-seq (precision nuclear run-on sequencing) to correlate INO4 binding with transcriptional output. Advanced methods like CUT&RUN or CUT&Tag using INO4 antibodies provide higher resolution mapping of binding sites with lower background than traditional ChIP approaches.
INO4 antibodies can be instrumental in exploring the emerging role of INO4 in proteostasis. Design co-immunoprecipitation experiments with INO4 antibodies followed by mass spectrometry to identify novel interaction partners involved in protein degradation pathways . Perform ChIP-seq after proteasome inhibition or ER stress induction to determine whether INO4 directly regulates genes involved in protein quality control. Use immunofluorescence with INO4 antibodies to track its localization during proteotoxic stress, potentially revealing stress-induced relocalization. Combine with fluorescence recovery after photobleaching (FRAP) to measure the dynamics of INO4 association with chromatin under normal versus stress conditions. Develop proximity labeling approaches using INO4 antibodies conjugated to enzymes like BioID or APEX2 to capture transient interactions occurring during stress response.
For successful immunodetection of INO4 in yeast cells, proper fixation and permeabilization are critical. For immunofluorescence microscopy, fix cells with 3.7% formaldehyde for 30 minutes at room temperature, followed by treatment with zymolyase (100 μg/ml) for 30 minutes at 30°C to digest the cell wall. Permeabilize with 0.1% Triton X-100 for 10 minutes at room temperature. This combination preserves nuclear structure while allowing antibody access to the nuclear transcription factor. For electron microscopy applications, use high-pressure freezing followed by freeze substitution in acetone containing 0.1% uranyl acetate and 0.25% glutaraldehyde for optimal ultrastructural preservation while maintaining antigenicity. For flow cytometry applications, fix cells in 70% ethanol at -20°C overnight, followed by RNase treatment and gentle permeabilization with 0.1% Triton X-100 to maintain cell integrity while allowing antibody penetration.
Optimization of INO4 antibody concentration is essential for different experimental applications to balance sensitivity and specificity. The table below provides starting points for various techniques:
| Application | Recommended Dilution Range | Optimization Approach |
|---|---|---|
| Western Blot | 1:500 - 1:2000 | Perform titration series with 2-fold dilutions, comparing signal-to-noise ratio |
| Immunoprecipitation | 2-5 μg per 500 μg protein lysate | Test multiple concentrations against fixed lysate amount |
| ChIP | 5-10 μg per reaction | Compare enrichment of known targets versus non-targets |
| Immunofluorescence | 1:100 - 1:500 | Test on wild-type and ino4Δ strains to confirm specificity |
| Flow Cytometry | 1:50 - 1:200 | Compare median fluorescence intensity between positive and negative controls |
Validation should include both positive controls (wild-type cells under conditions with known INO4 expression) and negative controls (ino4Δ strains) . When transitioning between applications, re-optimization is necessary as the optimal concentration for Western blotting may not be suitable for immunofluorescence due to differences in epitope accessibility and detection methods.
When encountering problems with INO4 antibody detection, implement a systematic troubleshooting approach. For weak or absent signals, first verify INO4 expression under your experimental conditions, as INO4 regulation is affected by inositol and choline levels . Low signal may result from insufficient protein extraction from the nucleus; ensure your lysis buffer contains appropriate detergents and consider sonication to improve nuclear protein release. High background can be addressed by adjusting blocking conditions (try 5% BSA instead of milk) and increasing washing stringency with higher salt concentrations (up to 500 mM NaCl) in wash buffers. For inconsistent results between experiments, standardize cell growth conditions, particularly inositol concentration, as this significantly affects the INO2-INO4 regulatory system . Multiple bands in Western blots may indicate degradation (add fresh protease inhibitors) or post-translational modifications (consider phosphatase treatment to determine if phosphorylation contributes to band shifts).
Epitope mapping can significantly enhance INO4 antibody applications by precisely identifying the antibody binding region, enabling more targeted experimental design and interpretation. Begin with computational prediction of potential antigenic regions within the INO4 protein sequence, focusing on hydrophilic and surface-exposed regions while avoiding the DNA-binding domain to prevent interference with function. Create a peptide array containing overlapping 15-20 amino acid peptides spanning the entire INO4 sequence, and probe with the antibody to identify reactive peptides. Alternatively, generate a series of truncated INO4 constructs and analyze antibody reactivity by Western blotting to narrow down the binding region. Once the epitope is identified, assess its conservation across species if cross-reactivity is desired. Knowledge of the epitope location allows researchers to predict whether the antibody might interfere with protein-protein interactions (particularly with INO2) or DNA binding, and whether post-translational modifications near the epitope might affect recognition.
INO4 plays a multifaceted role in cellular stress responses beyond its canonical function in phospholipid biosynthesis regulation. Recent research has revealed that loss of INO4 sensitizes yeast to proteotoxic stress, suggesting a broader requirement for lipid homeostasis in maintaining proteostasis . Under genotoxic stress conditions, INO4 activity appears to be modulated by the transcriptional repressor Opi1, as deletion of the transcriptional activator Ino2-Ino4 rescues the methyl methanesulfonate (MMS) sensitivity of opi1 cells . This indicates that constitutive activation of Ino2-Ino4 is detrimental during DNA damage response. The connection between lipid metabolism and stress response may be mediated through membrane composition changes that affect organelle function, particularly the endoplasmic reticulum and mitochondria. INO4 antibodies can be used to track changes in INO4 localization, abundance, and post-translational modifications during various stress conditions, providing insights into how cells integrate metabolic regulation with stress response pathways.
INO4 has significant implications for protein degradation pathways, particularly in endoplasmic reticulum-associated degradation (ERAD). Studies have demonstrated that INO4 deletion stabilizes diverse ERAD substrates, including integral membrane Hrd1 substrate (HA-Pdr5*), soluble luminal Hrd1 substrate (CPY*-HA), integral membrane Doa10 substrate (Deg1-Vma12), and soluble cytosolic Doa10 substrate (Deg1-GFP) . This broad impairment of protein degradation suggests INO4 plays a fundamental role in maintaining cellular proteostasis. The mechanism likely involves INO4's function in regulating lipid biosynthesis, as proper membrane composition is essential for the function of membrane-bound protein degradation machinery. INO4 antibodies can be used to investigate potential direct interactions between INO4 and components of degradation pathways through co-immunoprecipitation experiments. ChIP-seq with INO4 antibodies can also identify whether INO4 directly regulates genes encoding components of protein degradation machinery, potentially expanding our understanding of INO4's role beyond lipid metabolism to protein quality control systems.
Systems biology approaches can powerfully integrate INO4 antibody-derived data with other omics datasets to build comprehensive regulatory networks. Start by generating multiple data types using INO4 antibodies, including ChIP-seq to map genome-wide binding sites, co-immunoprecipitation coupled with mass spectrometry to identify protein interaction partners, and immunofluorescence to determine subcellular localization under various conditions. Integrate these antibody-derived datasets with transcriptomic data (RNA-seq) from wild-type and ino4Δ strains to correlate binding events with gene expression changes . Further incorporate lipidomics data to connect transcriptional changes with alterations in membrane composition. Use mathematical modeling to predict how perturbations in INO4 function cascade through these interconnected networks. Network analysis tools can identify regulatory motifs and feedback loops in the INO4 signaling network. This integrated approach can reveal emergent properties not apparent from individual experiments, such as how INO4-mediated transcriptional changes in lipid biosynthesis genes ultimately affect protein degradation pathways and stress responses.
INO4 antibodies can provide valuable comparative insights across different yeast species, illuminating evolutionary conservation and divergence of lipid regulatory mechanisms. Perform Western blot analysis using INO4 antibodies on protein extracts from diverse yeast species including Saccharomyces cerevisiae, Candida albicans, Schizosaccharomyces pombe, and Pichia pastoris to assess cross-reactivity and determine whether epitopes are conserved. Conduct ChIP-seq experiments across species where the antibody shows cross-reactivity to compare binding site preferences and identify core conserved targets versus species-specific regulatory connections. Use co-immunoprecipitation coupled with mass spectrometry to compare INO4 interaction partners across species, potentially revealing conserved and divergent regulatory complexes. Perform complementation studies where INO4 from different species is expressed in S. cerevisiae ino4Δ strains, then use the antibody to confirm expression and test functional conservation through phenotypic rescue. This comparative approach can reveal fundamental principles of lipid regulation that have been preserved through evolution and identify species-specific adaptations that might relate to different ecological niches or metabolic strategies.
CRISPR-mediated tagging offers transformative possibilities for INO4 antibody applications by enabling endogenous protein tagging with minimal disruption to native function. Generate yeast strains with CRISPR-Cas9 to introduce small epitope tags (FLAG, HA, or V5) at either the N- or C-terminus of endogenous INO4, carefully avoiding disruption of functional domains. These tagged strains allow the use of highly specific commercial tag antibodies with validated performance characteristics, circumventing limitations of INO4-specific antibodies. For chromatin studies, create CRISPR knock-ins of INO4 fused to HaloTag or SNAP-tag to enable super-resolution microscopy and single-molecule tracking of INO4 dynamics. Implement auxin-inducible degron (AID) tagging of INO4 to achieve rapid, conditional protein depletion, allowing temporal examination of INO4 function. CRISPR-mediated homology-directed repair can also introduce specific mutations in potential post-translational modification sites, followed by antibody detection to determine how these modifications affect INO4 function. The precision of CRISPR editing enables creation of allelic series of INO4 variants to dissect domain-specific functions when combined with antibody-based detection methods.
Single-cell approaches using INO4 antibodies can uncover previously masked cellular heterogeneity in INO4 expression and function within seemingly homogeneous yeast populations. Implement imaging mass cytometry using INO4 antibodies conjugated to rare earth metals to simultaneously measure INO4 levels alongside dozens of other proteins at single-cell resolution. Apply single-cell CUT&Tag with INO4 antibodies to map chromatin binding patterns in individual cells, potentially revealing distinct subpopulations with different INO4 regulatory states. For live-cell applications, develop INO4 intrabodies (intracellular antibodies) that can track INO4 dynamics in real-time without fixation. Combine with microfluidic approaches to correlate INO4 levels or localization with single-cell phenotypes such as growth rate, stress resistance, or cell cycle position. Computational analysis of resulting high-dimensional datasets can identify previously unrecognized cell states and transitions. This single-cell perspective can reveal how cellular heterogeneity in INO4 function might contribute to population-level phenotypes, such as variable resistance to proteotoxic or genotoxic stress.
Computational approaches can significantly enhance INO4 antibody design and selection through in silico predictions and modeling. Employ epitope prediction algorithms that integrate protein structure, surface accessibility, and sequence conservation to identify optimal antigenic regions of INO4 for antibody generation. Use molecular dynamics simulations to predict how post-translational modifications might alter epitope conformation and accessibility. Implement machine learning approaches trained on antibody-antigen interaction datasets to predict binding affinity and specificity of candidate antibodies before experimental validation. For applications requiring high specificity, conduct in silico cross-reactivity analysis against the entire yeast proteome to identify potential off-target binding. Virtual screening of phage display libraries can accelerate the identification of high-affinity INO4-binding antibody fragments. These computational approaches can be particularly valuable when developing antibodies against specific modified forms of INO4 or for distinguishing between INO4 and the structurally similar INO2 protein, reducing the time and resources required for experimental antibody development and validation.