SPBC530.08 Antibody

What is SPBC530.08 and what is its functional role in S. pombe?

SPBC530.08 is a transcription factor in the fission yeast Schizosaccharomyces pombe that has recently been characterized as Ntu2, one component of a heterodimeric transcription factor complex called "Nattou." According to recent research, SPBC530.08/Ntu2 forms a transcription factor heterodimer with SPBC16G5.16 (Ntu1) . This interaction was previously detected in a proteome-wide Y2H screen and has been confirmed through reciprocal experiments under high stringency conditions . As a binuclear zinc cluster transcription factor, it participates in gene regulation through specific DNA binding and protein-protein interactions within the S. pombe regulatory network.

What protein family does SPBC530.08 belong to and what are its structural characteristics?

SPBC530.08 (Ntu2) belongs to the binuclear zinc cluster family of transcription factors . This protein family is characterized by DNA-binding domains containing two zinc atoms coordinated by six cysteine residues. These transcription factors typically recognize specific DNA motifs and can form homo- or heterodimers to regulate gene expression. Comprehensive studies have shown that S. pombe contains several binuclear zinc cluster TFs including Toe1, Toe3, SPAC3H8.08c, and SPBC16G5.17, which show similar DNA-binding motifs but have limited overlap in their binding sites . SPBC530.08/Ntu2's function appears to be dependent on its heterodimeric interaction with SPBC16G5.16/Ntu1 in the Nattou complex.

How does SPBC530.08 (Ntu2) interact with other proteins in the transcriptional network?

SPBC530.08/Ntu2 primarily interacts with SPBC16G5.16/Ntu1 to form the Nattou complex, a transcription factor heterodimer . This interaction has been observed:

• Under both low (150 mM NaCl) and high (500 mM NaCl) stringency conditions, indicating a stable interaction

• Reciprocally in immunoprecipitation experiments, confirming mutual binding

• Previously in proteome-wide Y2H screens, providing independent validation

The formation of this heterodimer likely modifies the DNA binding specificity and regulatory functions of both proteins. As part of the larger transcriptional regulatory network, the Nattou complex may interact with other transcription factors and co-factors to coordinate gene expression programs, although the complete interaction network is still being characterized.

What are the recommended protocols for using SPBC530.08 antibodies in Western blotting?

When using SPBC530.08 antibodies (such as CSB-PA528874XA01SXV) for Western blotting, researchers should follow these methodological guidelines:

Sample Preparation:

• Harvest S. pombe cells in mid-log phase (OD600 0.5-0.8)

• Lyse cells with glass beads in buffer containing protease inhibitors

• Clarify lysates by centrifugation (14,000 × g for 15 minutes at 4°C)

• Quantify protein using Bradford or BCA assays

SDS-PAGE and Transfer:

• Load 20-50 μg total protein per lane

• Separate proteins on 10-12% polyacrylamide gels

• Transfer to PVDF membranes (0.45 μm) at 100V for 1 hour or 30V overnight

Antibody Incubation:

• Block membranes with 5% non-fat milk in TBST for 1 hour

• Incubate with anti-SPBC530.08 antibody at 1:1000 dilution in blocking buffer overnight at 4°C

• Wash 3× with TBST (10 minutes each)

• Incubate with appropriate secondary antibody (e.g., goat anti-rabbit IgG-HRP at 1:5000) for 1 hour

• Wash 4× with TBST (10 minutes each)

Detection and Controls:

• Develop using enhanced chemiluminescence (ECL) reagents

• Include wild-type and SPBC530.08 deletion strains as positive and negative controls

• Use anti-tubulin or anti-actin antibodies as loading controls

This protocol has been validated in multiple studies of S. pombe transcription factors and provides reliable detection of SPBC530.08 protein .

How should researchers optimize immunoprecipitation experiments for studying SPBC530.08 interactions?

To optimize immunoprecipitation (IP) experiments for SPBC530.08, researchers should implement this systematic approach:

Pre-IP Considerations:

• Tag selection: FLAG or HA tags have been successfully used for S. pombe TF studies

• Expression level: Use endogenous promoter to maintain physiological levels

• Controls: Include untagged strains and IgG controls

Optimized IP Protocol:

• Cell Preparation:

  • Harvest 50-100 ml of culture at OD600 0.6-0.8

  • Wash cells in ice-cold PBS with protease inhibitors

• Lysis Conditions:

  • Use mild detergent buffer (0.5% NP-40 or 1% Triton X-100)

  • Test both low (150 mM) and high (500 mM) NaCl concentrations

  • Include protease and phosphatase inhibitor cocktails

• IP Procedure:

  • Pre-clear lysates with Protein A/G beads (1 hour at 4°C)

  • Incubate with antibody (2-5 μg) overnight at 4°C

  • Add Protein A/G beads for 2 hours

  • Wash 4× with decreasing salt concentrations

• Analysis Methods:

  • Direct Western blotting for known interactors

  • Mass spectrometry for unbiased interactome profiling

  • Compare results to other anti-FLAG IPs as controls

Recent research successfully employed this approach to confirm the interaction between SPBC530.08/Ntu2 and SPBC16G5.16/Ntu1, even under high stringency conditions . Multiple biological replicates (at least triplicate) are essential for reliable results.

What techniques are most effective for analyzing SPBC530.08 DNA binding sites genome-wide?

For comprehensive analysis of SPBC530.08 DNA binding sites, researchers should implement this ChIP-seq workflow:

ChIP Protocol Optimization:

• Crosslinking and Sonication:

  • 1% formaldehyde for 15 minutes at room temperature

  • Sonication to generate 200-300 bp fragments

  • Verify fragment size by gel electrophoresis

• Immunoprecipitation:

  • Use validated anti-SPBC530.08 antibody or epitope tag antibody

  • Include input controls and mock IP (IgG) controls

  • Perform in biological triplicates

• Library Preparation and Sequencing:

  • Generate paired-end libraries for improved mapping

  • Sequence to minimum depth of 20 million reads per sample

  • Include spike-in controls for normalization

Data Analysis Pipeline:

• Quality Control and Alignment:

  • Filter low-quality reads (Q < 30)

  • Align to S. pombe genome using Bowtie2

  • Remove duplicates and multimapping reads

• Peak Calling:

  • Use MACS2 with parameters optimized for TFs

  • Apply stringent thresholds (≥1.75-fold enrichment over input)

  • Require peaks to be present in at least two replicates

• Motif Analysis:

  • Perform de novo motif discovery using MEME or HOMER

  • Conduct k-mer enrichment analysis for unbiased motif identification

  • Compare with motifs of related TFs

Recent studies employed this approach to identify binding sites for 77 S. pombe TFs, demonstrating its effectiveness for characterizing transcription factor binding patterns genome-wide .

How can researchers validate the specificity of their SPBC530.08 antibody?

A comprehensive validation strategy for SPBC530.08 antibodies should include:

Genetic Validation:

• Strain Comparison:

  • Wild-type S. pombe (positive control)

  • SPBC530.08 deletion strain (negative control)

  • Tagged SPBC530.08 strain (positive control with known expression)

• Expression System Tests:

  • Heterologous expression in E. coli or mammalian cells

  • Titrated expression levels to assess sensitivity

Biochemical Validation:

• Western Blot Analysis:

  • Verify single band at expected molecular weight (~59 kDa for SPBC530.08)

  • Test multiple antibody concentrations

  • Compare different antibody lots for consistency

• Peptide Competition:

  • Pre-incubate antibody with immunizing peptide

  • Should eliminate specific signal

• Immunoprecipitation-Mass Spectrometry:

  • Confirm SPBC530.08 as a major component in IP eluates

  • Detect known partners (e.g., SPBC16G5.16/Ntu1)

Functional Validation:

• ChIP-qPCR:

  • Target known binding regions

  • Compare signal between wild-type and deletion strains

• Immunofluorescence Microscopy:

  • Verify nuclear localization consistent with TF function

  • Compare staining patterns between control and experimental samples

These validation steps are essential before using the antibody for critical experiments, as antibody specificity can significantly impact experimental outcomes and reproducibility .

How does the binding specificity of SPBC530.08 compare to other binuclear zinc cluster transcription factors?

Recent comprehensive studies reveal important insights about SPBC530.08/Ntu2 DNA binding specificity compared to other binuclear zinc cluster TFs:

Motif Characteristics:

• Binuclear zinc cluster TFs typically recognize CGG triplets with varying spacing

• SPBC530.08/Ntu2 likely shares this general preference, though its specific motif is still being characterized

• Related S. pombe factors (Toe1, Toe3, SPAC3H8.08c, and SPBC16G5.17) show similar motifs but distinct binding patterns

Binding Site Selection:

• Despite similar motifs, binding site overlap between related TFs is limited

• Only a small percentage (0.3-17.5%) of available genomic motifs are actually bound

• Most TFs bind between 1.2-4.5% of their predicted motifs

Heterodimer Influence:

• As part of the Nattou complex with SPBC16G5.16/Ntu1, binding specificity may differ from either factor alone

• Heterodimer formation can alter DNA sequence recognition and binding affinity

Chromatin Context:

• Binding occurs preferentially in regions with low nucleosome occupancy

• Local chromatin environment may be as important as sequence motifs in determining binding

This suggests that while sequence specificity is important, additional factors including protein partners, chromatin accessibility, and broader genomic context significantly influence the actual binding patterns of SPBC530.08/Ntu2 in vivo .

What approaches should be used to study the regulatory network controlled by the Nattou complex?

To elucidate the regulatory network controlled by the Nattou complex (SPBC530.08/Ntu2 and SPBC16G5.16/Ntu1), a multi-faceted approach is required:

Genomic Approaches:

• Comparative ChIP-seq:

  • Perform ChIP-seq for both Ntu1 and Ntu2 individually

  • Compare binding sites to identify unique and shared targets

  • Conduct ChIP-seq under various conditions to detect condition-specific binding

• Transcriptome Analysis:

  • RNA-seq of wild-type, Δntu1, Δntu2, and double deletion strains

  • Time-course analysis following conditional depletion

  • NET-seq to measure nascent transcription directly affected by the complex

• Chromatin Structure Analysis:

  • ATAC-seq to correlate binding with chromatin accessibility

  • MNase-seq to determine effects on nucleosome positioning

  • Hi-C to identify potential effects on genome organization

Biochemical Approaches:

• Protein Complex Analysis:

  • MS-based identification of all complex components

  • Size exclusion chromatography to determine complex composition

  • In vitro reconstitution to define minimal functional units

• DNA-Binding Studies:

  • EMSA with recombinant proteins to define sequence requirements

  • DNA footprinting to map precise binding sites

  • SELEX to derive comprehensive binding preferences

Functional Approaches:

• Genetic Interaction Mapping:

  • Synthetic genetic array analysis with Δntu1 and Δntu2

  • Chemical-genetic profiling to identify condition-specific functions

  • Suppressor screens to identify downstream effectors

• Reporter Assays:

  • Test activity of putative target promoters

  • Mutational analysis of binding sites

  • Single-cell analysis to examine expression noise

Integration of these datasets within computational frameworks can generate testable models of the Nattou complex regulatory network .

How might post-translational modifications regulate SPBC530.08 function?

Post-translational modifications (PTMs) likely play critical roles in regulating SPBC530.08/Ntu2 function through multiple mechanisms:

Phosphorylation:

• Potential sites: Serine, threonine, and tyrosine residues, particularly in non-DNA-binding regions

• Functional effects: May alter protein-protein interactions, DNA binding affinity, or nuclear localization

• Regulatory significance: Likely responsive to cellular signaling pathways

Experimental approach for study:

• Identification of Modification Sites:

  • Immunoprecipitate SPBC530.08 followed by mass spectrometry

  • Compare PTM profiles under different growth conditions

  • Integrate with S. pombe phosphoproteome datasets

• Functional Characterization:

  • Create phospho-mimetic (S/T→D/E) and phospho-dead (S/T→A) mutants

  • Assess effects on DNA binding using ChIP-qPCR

  • Test protein-protein interactions with modified versions

  • Examine transcriptional activity of target genes

• Signaling Pathway Integration:

  • Identify kinases and phosphatases acting on SPBC530.08

  • Map condition-specific modification patterns

  • Determine how modifications coordinate with cell cycle or stress responses

• Crosstalk with Other Modifications:

  • Assess potential for ubiquitination, SUMOylation, or acetylation

  • Evaluate interdependence of different modifications

  • Map modification sites relative to functional domains

This comprehensive approach can reveal how cellular signaling networks regulate SPBC530.08/Ntu2 activity in response to different environmental conditions or developmental stages.

What are the challenges in developing highly specific antibodies against SPBC530.08?

Developing highly specific antibodies against SPBC530.08 presents several technical challenges that researchers should address:

Structural Challenges:

• Homology with Related Proteins:

  • SPBC530.08 belongs to a family of binuclear zinc cluster TFs with conserved DNA-binding domains

  • Antibodies must target unique epitopes to avoid cross-reactivity

  • Sequence alignment analysis is crucial for optimal epitope selection

• Conformational Epitopes:

  • Native protein structure may present epitopes differently than linear peptides

  • Polyclonal antibodies like CSB-PA528874XA01SXV may recognize multiple epitopes

  • Antibodies raised against recombinant proteins may not recognize native conformations

Methodological Considerations:

• Immunogen Design:

  • Selection between full-length protein, domains, or peptide conjugates

  • Expression system affects post-translational modifications

  • Proper folding of recombinant antigens is essential

• Validation Requirements:

  • Need for genetic controls (deletion strains)

  • Cross-reactivity testing against related TFs

  • Application-specific validation (Western blot vs. ChIP)

Empirical Solutions:

• Characterization Protocol:

  Validation Step	Method	Acceptance Criteria
  Specificity	Western blot	Single band at predicted MW; absent in deletion strain
  Sensitivity	Titration series	Detection at physiological concentrations
  Application versatility	Test in multiple assays	Consistent performance in WB, IP, ChIP
  Lot-to-lot consistency	Compare batches	<15% variation in signal intensity

• Alternative Approaches:

  • Epitope tagging (FLAG, HA) when antibodies are inadequate

  • Using multiple antibodies targeting different epitopes

  • Developing nanobodies for improved specificity

This systematic approach to antibody development and validation is critical for obtaining reliable results in SPBC530.08 research .

How should researchers interpret ChIP-seq data for SPBC530.08 binding patterns?

Proper interpretation of SPBC530.08/Ntu2 ChIP-seq data requires careful analysis at multiple levels:

Peak Characterization:

• Distribution Analysis:

  • Map binding sites relative to genomic features (promoters, enhancers, etc.)

  • Determine average distance from transcription start sites

  • Compare to other binuclear zinc cluster TFs to identify common patterns

• Binding Strength Assessment:

  • Analyze peak heights (fold enrichment over input)

  • Compare signal intensity across different conditions

  • Distinguish high-confidence from borderline binding events

Motif Analysis:

• De Novo Motif Discovery:

  • Identify enriched sequence patterns within binding regions

  • Compare to known binuclear zinc cluster TF motifs

  • Assess effect of heterodimer formation on motif preferences

• Motif Utilization:

  • Calculate percentage of available genomic motifs bound (typically 1.2-4.5%)

  • Identify features distinguishing bound vs. unbound motifs

  • Consider local chromatin accessibility and co-factor availability

Network Integration:

• Target Gene Assignment:

  • Define rules for associating peaks with genes (e.g., nearest TSS, within 1kb)

  • Integrate with expression data to identify functional targets

  • Perform Gene Ontology analysis on target genes

• Co-binding Analysis:

  • Identify overlap with SPBC16G5.16/Ntu1 binding sites

  • Compare with other TFs to detect cooperative or competitive binding

  • Build network models incorporating multiple regulatory factors

Visualization Strategies:

• Generate genome browser tracks showing binding profiles

• Create heat maps clustering binding sites by pattern similarity

• Produce average profile plots centered on features of interest

This multi-layered analytical approach transforms raw ChIP-seq data into meaningful biological insights about SPBC530.08/Ntu2 function .

What are common pitfalls in interpreting protein-protein interaction data for SPBC530.08?

When interpreting protein-protein interaction data for SPBC530.08/Ntu2, researchers should be aware of these common pitfalls and their solutions:

Technical Artifacts:

• Problem: Non-specific binding in immunoprecipitation experiments
  Solution: Include multiple controls (IgG, untagged strains) and perform reciprocal IPs

• Problem: Artifactual interactions from cell lysis
  Solution: Validate with orthogonal methods (Y2H, proximity labeling) and consider crosslinking approaches

• Problem: Sensitivity to buffer conditions
  Solution: Test interactions under multiple stringencies (e.g., 150mM vs. 500mM NaCl)

Biological Complexity:

• Problem: Context-dependent interactions missed in single-condition experiments
  Solution: Test multiple growth conditions and stress responses

• Problem: Transient interactions may be overlooked
  Solution: Use crosslinking approaches and rapid isolation techniques

• Problem: Post-translational modifications affecting interactions
  Solution: Analyze phosphorylation states and other modifications by mass spectrometry

Data Analysis Challenges:

• Problem: Distinguishing direct from indirect interactions
  Solution: Combine IP-MS with Y2H or in vitro binding assays

• Problem: Determining interaction stoichiometry
  Solution: Use quantitative MS approaches and size exclusion chromatography

• Problem: Network complexity obscuring key interactions
  Solution: Apply computational filtering (using moderated t-statistics) to prioritize significant interactions

For SPBC530.08/Ntu2, the heterodimeric interaction with SPBC16G5.16/Ntu1 demonstrates how applying appropriate controls and validation (reciprocal IP, high stringency testing) can identify biologically significant interactions with high confidence .

How should discrepancies between antibody-based detection methods be reconciled?

When facing discrepancies between different antibody-based detection methods for SPBC530.08, researchers should follow this systematic reconciliation approach:

Methodological Factors:

• Epitope Accessibility:

  • Some epitopes may be masked in native protein complexes

  • Western blot (denatured proteins) vs. IP (native conformation) may yield different results

  • Solution: Use multiple antibodies targeting different epitopes

• Antibody Performance in Different Applications:

  • Antibodies may work in one application but not others

  • Example: Some anti-Shb antibodies were effective in either Western blotting OR immunoprecipitation, but not both

  • Solution: Validate each antibody specifically for its intended application

Technical Validation Approach:

• Cross-Validation Protocol:

  Method	Control	Expected Outcome
  Western Blot	Recombinant protein ladder	Single band at predicted MW
  IP-Western	IP followed by blotting	Enrichment of target protein
  IP-MS	Mass spec of eluate	Target protein among top hits
  ChIP-qPCR	Known binding sites	Enrichment over background

• Troubleshooting Strategy:

  • For weak signals: Optimize antibody concentration, incubation conditions

  • For multiple bands: Test specificity with competing peptides

  • For IP failure: Try different lysis conditions, detergents

Integration and Interpretation:

• Use orthogonal detection methods (MS, activity assays) when antibody results conflict

• Consider biological variables (modifications, isoforms) that might explain discrepancies

• Maintain detailed records of antibody performance under different conditions

• Share validation data with suppliers and the research community

This systematic approach can help researchers navigate discrepancies between different antibody-based methods, as demonstrated in comprehensive antibody validation studies .

What statistical approaches should be used when analyzing SPBC530.08 binding site enrichment?

When analyzing SPBC530.08/Ntu2 binding site enrichment, researchers should implement robust statistical approaches:

Enrichment Analysis:

• Peak Calling Statistics:

  • Use MACS2 or similar tools that model background distribution

  • Apply false discovery rate (FDR) control (<0.05) or fold-enrichment thresholds (>1.75)

  • Consider local background correction for accurate enrichment estimation

• Replicate Analysis:

  • Require peaks to be present in multiple replicates (≥2 recommended)

  • Calculate irreproducible discovery rate (IDR) between replicates

  • Use DESeq2 or edgeR for differential binding analysis between conditions

Motif Statistics:

• Motif Discovery:

  • Apply MEME/STREME with appropriate background models

  • Calculate E-values for motif significance

  • Use TOMTOM to compare with known motifs

• Motif Enrichment:

  • Conduct k-mer enrichment analysis comparing TF-specific peaks against control sequences

  • Calculate hypergeometric p-values for motif occurrence

  • Apply multiple testing correction (Benjamini-Hochberg)

Advanced Statistical Methods:

• Comparative Analysis:

  • Use moderated t-statistics to identify TF-specific interactions by comparing across multiple IP experiments

  • Apply clustering methods to identify factors with similar binding patterns

  • Implement multiple testing corrections appropriate for genomic scale

• Integrated Analysis:

  • Correlate binding with expression using regression models

  • Apply Gene Set Enrichment Analysis (GSEA) for pathway analysis

  • Use machine learning approaches to identify predictive features of binding sites

This statistical framework enables robust identification of genuine SPBC530.08/Ntu2 binding events and their biological significance, while controlling for false discoveries in genome-wide analyses .