SPAC13F5.05 Antibody

What is SPAC13F5.05 and why are antibodies against it important for research?

SPAC13F5.05 is a gene found in the fission yeast Schizosaccharomyces pombe that plays a role in cellular functions related to iron homeostasis regulation. Antibodies against this protein are essential research tools that enable detection, quantification, and functional analysis of the protein in various experimental contexts. These antibodies allow researchers to study protein expression patterns, subcellular localization, protein-protein interactions, and post-translational modifications, particularly in the context of iron-dependent transcriptional regulation pathways similar to those involving factors like Php4 .

What types of experiments can be performed using SPAC13F5.05 antibodies?

SPAC13F5.05 antibodies can be utilized in numerous experimental applications including:

• Western blotting to detect and quantify protein expression levels

• Immunoprecipitation to study protein-protein interactions

• Chromatin immunoprecipitation (ChIP) to analyze protein-DNA interactions

• Immunofluorescence to determine subcellular localization

• Flow cytometry to analyze protein expression in cell populations

• ELISA to quantify protein levels in various samples

These techniques are commonly employed in studies examining iron-responsive transcriptional regulation mechanisms similar to those described for Php4 in S. pombe, which controls the expression of genes encoding iron-dependent enzymes under iron-deficient conditions .

How should SPAC13F5.05 antibodies be validated before experimental use?

Before using SPAC13F5.05 antibodies in experiments, comprehensive validation is essential to ensure specificity and reliability:

• Specificity testing through Western blot analysis comparing wild-type and knockout/knockdown strains

• Cross-reactivity assessment against related proteins or in different species

• Epitope mapping to confirm binding to the intended protein region

• Multiple technique validation (using the antibody in different applications)

• Positive and negative controls in each experimental setup

For optimal validation, researchers should follow protocols similar to those used for other yeast antibodies, such as using protein lysates from strains with and without the target protein to confirm specificity, similar to the validation approaches used for antibodies against other yeast transcription factors .

How can SPAC13F5.05 antibodies be optimized for chromatin immunoprecipitation studies?

Optimizing SPAC13F5.05 antibodies for chromatin immunoprecipitation requires multiple considerations:

• Crosslinking optimization: Test different formaldehyde concentrations (0.5-3%) and incubation times (5-30 minutes) to preserve protein-DNA interactions without overfixing.

• Sonication parameters: Establish optimal sonication conditions (amplitude, pulse duration, number of cycles) to generate DNA fragments of 200-500 bp while preserving epitope integrity.

• Antibody selection: Choose high-affinity antibodies against native epitopes that remain accessible after crosslinking. Monoclonal antibodies often provide higher specificity, while polyclonals may offer better signal.

• Pre-clearing strategy: Implement rigorous pre-clearing steps using protein A/G beads to reduce background.

• Washing stringency: Develop appropriate washing protocols that remove non-specific interactions while preserving specific binding.

• Elution methods: Test different elution buffers to maximize recovery while maintaining antibody integrity.

These optimizations are particularly important when studying transcription factors like SPAC13F5.05 that may have context-dependent DNA binding patterns similar to other yeast transcriptional regulators involved in iron homeostasis .

What approaches can overcome epitope masking issues when SPAC13F5.05 forms protein complexes?

When SPAC13F5.05 forms protein complexes, epitope masking can significantly impair antibody recognition. Several strategies can address this challenge:

• Multiple antibody approach: Develop and use antibodies targeting different epitopes across the protein to increase detection probability.

• Native versus denaturing conditions: Compare antibody performance under native versus denaturing conditions to identify optimal detection parameters.

• Crosslinking optimization: Adjust crosslinking protocols to preserve complexes while maintaining epitope accessibility.

• Sequential immunoprecipitation: Implement tandem IP strategies to first capture interacting partners, then isolate SPAC13F5.05 under conditions that expose the epitope.

• Epitope tagging strategies: Consider introducing small epitope tags that remain accessible in complexes, using techniques like CRISPR-based genome editing.

This approach is particularly relevant when studying proteins that may function in multi-subunit complexes, similar to how Php4 functions as part of the CCAAT-binding factor in regulating gene expression during iron deprivation in S. pombe .

How can SPAC13F5.05 antibodies be utilized to study post-translational modifications that occur during iron stress response?

Studying post-translational modifications (PTMs) of SPAC13F5.05 during iron stress response requires specialized antibody-based approaches:

• Modification-specific antibodies: Develop or obtain antibodies that specifically recognize phosphorylated, ubiquitinated, or otherwise modified forms of SPAC13F5.05.

• Sequential immunoprecipitation protocol:

  • First IP: Capture total SPAC13F5.05 using general antibodies

  • Elution under mild conditions

  • Second IP: Use modification-specific antibodies

  • Analyze by Western blot or mass spectrometry

• Time-course analysis: Monitor PTM patterns at different time points following iron depletion or repletion to track dynamic modifications.

• Mutation-based validation: Compare PTM patterns between wild-type and mutant versions of SPAC13F5.05 where potential modification sites are altered.

• Mass spectrometry validation: Confirm antibody-detected modifications through mass spectrometry analysis of immunoprecipitated samples.

These approaches can reveal regulatory mechanisms similar to those observed for other iron-responsive transcription factors in S. pombe, where protein activity is modulated by PTMs in response to changing iron conditions .

What are the optimal buffer conditions for SPAC13F5.05 antibody-based immunoprecipitation?

Optimal buffer conditions for SPAC13F5.05 immunoprecipitation must balance protein solubility, complex integrity, and antibody binding efficiency:

• Lysis buffer composition:

  • Base buffer: 50 mM Tris-HCl (pH 7.4-8.0) or 20 mM HEPES (pH 7.4)

  • Salt concentration: 100-150 mM NaCl (standard); 50-75 mM for preserving weak interactions; 200-300 mM for reducing nonspecific binding

  • Detergents: 0.1-1% NP-40 or Triton X-100 (mild); 0.1% SDS (stronger, more denaturing)

  • Protease inhibitors: Complete cocktail including PMSF, aprotinin, leupeptin, pepstatin A

  • Phosphatase inhibitors: Sodium fluoride, sodium orthovanadate, β-glycerophosphate

  • Chelating agents: 1-2 mM EDTA or EGTA (caution: may affect metal-dependent interactions)

• Binding conditions:

  • Temperature: 4°C is standard; room temperature may increase binding but risks degradation

  • Duration: 2-4 hours or overnight, depending on antibody affinity

  • Rotation speed: Gentle to avoid foam formation but sufficient for mixing

• Washing stringency gradient:

  • First wash: Low stringency (lysis buffer)

  • Middle washes: Increasing salt concentration (150-300 mM NaCl)

  • Final wash: Buffer without detergent

These conditions should be systematically optimized for each antibody and experimental goal, particularly when studying iron-responsive proteins that may undergo conformational changes under different iron concentrations .

What are the recommended primary and secondary antibody dilutions for Western blotting detection of SPAC13F5.05?

Optimal antibody dilutions for Western blotting detection of SPAC13F5.05 depend on antibody quality, detection method, and protein abundance:

Primary Antibody Recommendations:

• Initial testing range: 1:500 to 1:2000

• High-affinity antibodies: 1:1000 to 1:5000

• For low abundance proteins: 1:250 to 1:1000

• Incubation: Overnight at 4°C or 2 hours at room temperature

Secondary Antibody Recommendations:

• HRP-conjugated antibodies: 1:2000 to 1:10,000 (typical starting point: 1:5000)

• Fluorescent-labeled antibodies: 1:5000 to 1:15,000

• Incubation: 1 hour at room temperature

Optimization Strategy:

• Start with manufacturer's recommended dilutions if available

• Perform a dilution series for both primary and secondary antibodies

• Evaluate signal-to-noise ratio at each dilution

• Select the highest dilution that provides adequate signal with minimal background

When using anti-mouse secondary antibodies for detection in yeast systems, pre-adsorbed secondaries like Goat Anti-Mouse IgG, Human ads-HRP (similar to SouthernBiotech Cat. No. 1030-05) are recommended to minimize cross-reactivity with endogenous proteins .

How can researchers quantitatively assess SPAC13F5.05 protein-protein interactions using antibody-based approaches?

Quantitative assessment of SPAC13F5.05 protein-protein interactions can be achieved through several antibody-based techniques:

• Co-immunoprecipitation with quantitative Western blotting:

  • Perform IP with anti-SPAC13F5.05 antibodies

  • Analyze co-precipitated proteins by Western blot

  • Include calibration curves using recombinant proteins

  • Quantify band intensities using digital imaging software

  • Calculate molar ratios of interacting proteins

• Proximity Ligation Assay (PLA):

  • Use primary antibodies against SPAC13F5.05 and potential interacting partners

  • Apply species-specific PLA probes

  • Quantify interaction signals per cell

  • Perform statistical analysis across multiple fields

• FRET-based immunoassays:

  • Label anti-SPAC13F5.05 antibodies with donor fluorophores

  • Label antibodies against interaction partners with acceptor fluorophores

  • Measure energy transfer efficiency

  • Calculate interaction distances and binding affinities

• Biolayer Interferometry:

  • Immobilize anti-SPAC13F5.05 antibodies on biosensor tips

  • Capture SPAC13F5.05 from cell lysates

  • Measure association/dissociation kinetics with potential partners

  • Calculate KD values (as demonstrated for SpA5-Abs-9 interactions with KD = 1.959 × 10^-9 M)

• Mass Spectrometry-based quantification:

  • Perform IP with SPAC13F5.05 antibodies

  • Analyze samples using quantitative MS approaches (SILAC, TMT, label-free)

  • Validate specific interactions through reciprocal IPs

These methods can provide valuable insights into how SPAC13F5.05 may function within protein complexes, particularly in different iron availability conditions similar to how Php4 regulates gene expression during iron deprivation .

How can researchers address non-specific binding issues with SPAC13F5.05 antibodies?

Non-specific binding is a common challenge with antibodies in yeast systems. For SPAC13F5.05 antibodies, consider these troubleshooting approaches:

• Pre-clearing optimization:

  • Incubate lysates with protein A/G beads before adding antibodies

  • Use species-matched IgG-UNLB for pre-clearing (similar to Mouse IgG-UNLB or Rabbit IgG-UNLB)

  • Extend pre-clearing time to 1-2 hours at 4°C

• Blocking strategy enhancement:

  • Test different blocking agents (BSA, milk, fish gelatin, commercial blockers)

  • Increase blocking time to 1-2 hours

  • Add 0.1-0.5% Tween-20 to blocking buffer

• Antibody specificity validation:

  • Test antibody on knockout/knockdown strains

  • Perform peptide competition assays

  • Use multiple antibodies targeting different epitopes

• Buffer optimization:

  • Increase salt concentration (150-300 mM NaCl)

  • Add mild detergents (0.1-0.5% NP-40 or Triton X-100)

  • Test addition of 0.1-1% BSA to antibody dilution buffer

• Detection system modification:

  • Use human-adsorbed secondary antibodies to reduce cross-reactivity

  • Switch to directly conjugated primary antibodies

  • Consider biotin-streptavidin amplification systems

• Validation controls:

  • Include isotype controls

  • Perform "no primary antibody" controls

  • Use protein A/G beads alone as IP controls

These approaches can significantly reduce non-specific binding issues that might complicate the interpretation of results, especially when studying less abundant yeast proteins .

What statistical approaches are recommended for analyzing antibody-based SPAC13F5.05 data across different experimental conditions?

Robust statistical analysis is essential for interpreting antibody-based SPAC13F5.05 data:

• Normalization strategies:

  • Normalize to loading controls (e.g., actin, tubulin, total protein)

  • Consider global normalization methods for large-scale datasets

  • Use spike-in controls for absolute quantification

• Statistical tests based on experimental design:

  • Two conditions: Student's t-test (parametric) or Mann-Whitney U test (non-parametric)

  • Multiple conditions: ANOVA with appropriate post-hoc tests (Tukey, Bonferroni, Dunnett)

  • Time-course experiments: Repeated measures ANOVA or mixed-effects models

  • Dose-response: Regression analysis with appropriate model fitting

• Sample size determination:

  • Power analysis based on preliminary data

  • Minimum n=3 biological replicates per condition

  • Consider technical replicates for high-variation assays

• Data visualization:

  • Box plots or violin plots for distribution data

  • Heat maps for correlation analysis

  • Scatter plots with error bars for comparative analysis

• Advanced analytical approaches:

  • Machine learning models for pattern recognition in complex datasets

  • Bayesian statistics for experiments with limited sample sizes

  • LOESS or LOWESS regression for non-linear relationships

• Multiple testing correction:

  • Bonferroni correction (conservative)

  • Benjamini-Hochberg procedure (FDR control)

  • Q-value calculation for large-scale experiments

These statistical approaches are particularly important when analyzing data from experiments comparing SPAC13F5.05 protein levels, interactions, or activities across different iron availability conditions, similar to studies examining iron-responsive transcription factors in yeast .

How can researchers integrate antibody-based SPAC13F5.05 data with transcriptomic and proteomic datasets?

Integrating antibody-based data with -omics datasets provides a comprehensive understanding of SPAC13F5.05 function:

• Correlation analysis approaches:

  • Calculate Pearson or Spearman correlations between protein levels and mRNA expression

  • Implement time-lagged correlation analysis for dynamic responses

  • Use partial correlation analysis to control for confounding variables

• Multi-omics integration platforms:

  • Pathway enrichment analysis incorporating both datasets

  • Network analysis to identify regulatory connections

  • Clustering approaches (hierarchical, k-means, self-organizing maps)

• Validation strategies:

  • Confirm key findings using orthogonal methods

  • Perform causal testing through genetic perturbation

  • Develop predictive models and test with new experiments

• Visualization methods:

  • Integrated heat maps showing protein and transcript changes

  • Pathway maps with multi-level data overlay

  • Interactive network visualizations with multi-omics annotation

• Temporal integration approaches:

  • Time-course alignment of transcriptomic and proteomic data

  • Identification of lead-lag relationships

  • Dynamic Bayesian network modeling

This integration is particularly valuable for understanding iron-responsive transcription factors like those in yeast, where coordination between protein activity and transcriptional output is tightly regulated, as observed in studies of iron-responsive gene regulation in S. pombe where changes in protein levels and activities directly affect downstream gene expression patterns .

How can machine learning approaches improve SPAC13F5.05 antibody-based experimental design?

Machine learning (ML) can significantly enhance antibody-based experimental design for SPAC13F5.05 research:

• Active learning for optimized experimental planning:

  • Start with a small labeled dataset of antibody binding results

  • Train initial ML models to predict binding outcomes

  • Identify most informative next experiments to maximize information gain

  • Iteratively expand the labeled dataset based on model-guided selection

  • This approach can reduce the number of required experiments by up to 35% compared to random sampling

• Epitope prediction and antibody design:

  • Apply ML algorithms to predict optimal epitopes on SPAC13F5.05

  • Identify regions likely to remain accessible in different conformational states

  • Design antibodies targeting these regions with higher probability of success

  • Similar to computational approaches used to predict SpA5 epitopes that bind to antibodies

• Cross-reactivity prediction:

  • Train ML models on existing antibody cross-reactivity data

  • Predict potential cross-reactivity issues with new antibodies

  • Design experiments to specifically test these predictions

• Experimental condition optimization:

  • Apply Bayesian optimization to identify optimal buffer compositions

  • Design multifactorial experiments to test interactions between variables

  • Develop predictive models for antibody performance under different conditions

These ML approaches can substantially improve experimental efficiency and success rates in antibody-based research, as demonstrated in library-on-library antibody-antigen binding prediction studies where active learning strategies significantly outperformed random sampling approaches .

What are the considerations for developing antibodies against modified forms of SPAC13F5.05 during iron stress response?

Developing antibodies against modified SPAC13F5.05 during iron stress requires specific considerations:

• Modification identification strategy:

  • Perform mass spectrometry analysis of SPAC13F5.05 under iron-replete and iron-depleted conditions

  • Identify specific sites of phosphorylation, ubiquitination, SUMOylation, or other PTMs

  • Determine modification dynamics during iron stress response

  • Compare with known regulatory modifications in related transcription factors

• Antigen design parameters:

  • Synthesize peptides containing the exact modified residue with surrounding sequence (typically 12-20 amino acids)

  • Ensure modification stability during conjugation to carrier proteins

  • Consider multiple peptide designs with the modification at different positions

  • Include both modified and unmodified peptides for comparative screening

• Screening and validation protocol:

  • Implement rigorous counter-screening against unmodified peptides

  • Validate specificity using cell lysates from wild-type and mutant strains

  • Test antibody performance under different iron conditions

  • Confirm recognition of native modified protein by immunoprecipitation followed by mass spectrometry

• Application-specific optimization:

  • Adjust fixation protocols for immunofluorescence to preserve modifications

  • Optimize extraction buffers to maintain modification integrity

  • Include appropriate phosphatase or deubiquitinase inhibitors

  • Consider rapid sample processing to prevent modification loss

These considerations are particularly important when studying iron-responsive transcription factors that may undergo regulatory post-translational modifications in response to changing iron availability, similar to the regulatory mechanisms observed for other yeast transcription factors involved in iron homeostasis .

How might single-cell sequencing approaches complement SPAC13F5.05 antibody-based studies?

Single-cell sequencing approaches can powerfully complement antibody-based studies of SPAC13F5.05:

• Single-cell resolution of protein expression heterogeneity:

  • Combine index sorting with antibody-based cell isolation

  • Correlate SPAC13F5.05 protein levels with transcriptomic profiles

  • Identify cell subpopulations with distinct SPAC13F5.05 activity states

  • Similar to approaches used to identify antigen-binding IgG1+ clonotypes from immunized volunteers

• Spatial transcriptomics integration:

  • Perform immunofluorescence to localize SPAC13F5.05 protein

  • Combine with spatial transcriptomics to correlate localization with gene expression

  • Map spatial regulation of SPAC13F5.05 target genes within colonies or tissues

• Temporal dynamics analysis:

  • Implement scRNA-seq at multiple time points following iron depletion

  • Track transcriptional changes in relation to SPAC13F5.05 activity

  • Develop pseudotime trajectories to map cellular responses to iron stress

• Multi-omic single-cell profiling:

  • Combine antibody-based protein detection with transcriptome sequencing

  • Implement CITE-seq or related approaches to correlate protein and mRNA levels

  • Develop computational methods to integrate these multi-modal datasets

• Clonal evolution studies:

  • Track how SPAC13F5.05 function varies across yeast populations

  • Identify adaptive responses to prolonged iron limitation

  • Correlate genetic variation with protein function across clones

These integrative approaches can provide unprecedented insights into the heterogeneity and dynamics of SPAC13F5.05 function across cellular populations, similar to how single-cell approaches have revealed insights into antibody diversity and function in other systems .

What emerging techniques might enhance the specificity and sensitivity of SPAC13F5.05 antibody-based detection?

Several emerging techniques show promise for enhancing SPAC13F5.05 antibody detection:

• Proximity proteomics approaches:

  • APEX2 or BioID fusion to SPAC13F5.05 for proximity labeling

  • TurboID variants for rapid biotin labeling of neighboring proteins

  • Split-BioID for detecting specific protein-protein interactions

  • These approaches can map the proximal proteome of SPAC13F5.05 under different iron conditions

• Super-resolution microscopy enhancements:

  • DNA-PAINT for ultra-high resolution imaging with standard antibodies

  • Expansion microscopy to physically enlarge samples for improved resolution

  • Correlative light and electron microscopy for ultrastructural context

  • These techniques can reveal precise subcellular localization patterns

• Microfluidic antibody characterization:

  • Droplet-based single-cell antibody screening

  • Microfluidic affinity measurement platforms

  • Automated epitope mapping systems

  • These approaches enable rapid antibody characterization and optimization

• Nanobody and alternative binding scaffold development:

  • SPAC13F5.05-specific nanobodies for improved tissue penetration

  • DARPins, Affibodies, or Monobodies as alternatives to traditional antibodies

  • Aptamer-based detection systems for non-protein detection modalities

  • These smaller binding reagents can access epitopes unavailable to conventional antibodies

• Computational antibody engineering:

  • Structure-based antibody design targeting specific SPAC13F5.05 epitopes

  • ML-guided affinity maturation

  • Molecular dynamics simulations to predict binding characteristics

  • These approaches can generate antibodies with enhanced properties for specific applications

These emerging techniques represent the cutting edge of antibody technology and can significantly enhance the study of proteins like SPAC13F5.05, similar to how advanced techniques have improved the characterization of antibodies against bacterial virulence factors like SpA5 .