SPAC3C7.04 Antibody

What is SPAC3C7.04 and why is it significant in fission yeast research?

SPAC3C7.04 is an uncharacterized transcriptional regulatory protein in Schizosaccharomyces pombe (fission yeast) that contains a fungal Zn(2)-Cys(6) binuclear cluster domain . This 783-amino acid protein is localized in both the nucleus and cytoplasm , functioning primarily in the regulation of transcription. Its significance stems from its role in gene-specific transcription from RNA polymerase II promoter and its potential involvement in cell cycle regulation .

Researchers interested in transcriptional networks in fission yeast find SPAC3C7.04 particularly intriguing because it has been identified as a potentially significant transcription factor with periodic activities during the cell cycle . Analysis of regulatory networks in S. pombe has shown that SPAC3C7.04 demonstrates significant activity (P-value 2.84E-15) with its fungal Zn(2)-Cys(6) binuclear cluster domain, suggesting it may play a key role in coordinating phase-specific gene expression .

What experimental evidence exists regarding the function of SPAC3C7.04?

While SPAC3C7.04 remains relatively uncharacterized, several studies have begun to elucidate its functions:

• Cell Cycle Roles: Genetic interaction screens have revealed potential cell cycle functions for SPAC3C7.04, alongside other transcription factors like SPBC56F2.05 and SPCC320.03 .

• Telomere Association: Research has shown that SPAC3C7.04 mutants have elongated telomeres, suggesting a potential role in telomere maintenance .

• Transcriptional Regulation: Gene ontology analysis classifies it with specific RNA polymerase II transcription factor activity , placing it in important regulatory networks.

• Periodic Expression: Global gene regulatory network analyses identified SPAC3C7.04 as having phase-specific expression patterns during the cell cycle, clustering with genes involved in M phase regulation .

The protein's localization to both nuclear and cytoplasmic compartments suggests it may shuttle between these locations, possibly in response to specific cellular signals or cell cycle stages .

What are the optimal validation methods for SPAC3C7.04 antibodies in fission yeast research?

Comprehensive validation of SPAC3C7.04 antibodies should employ multiple complementary approaches:

• Western Blotting Validation:

  • Use wild-type S. pombe extracts alongside SPAC3C7.04 deletion strains

  • Expected molecular weight is approximately 87 kDa (calculated from 783 amino acids)

  • Test antibody specificity across varying protein concentrations (5-50 μg of total protein)

  • Include positive controls with tagged versions of SPAC3C7.04 (e.g., GFP-SPAC3C7.04)

• Immunocytochemistry Validation:

  • Compare staining patterns between wild-type and knockout strains

  • Co-localization with nuclear markers is expected given its known nuclear localization

  • Assess puncta co-localization with markers for transcription factories

  • Calculate ratio between co-localizing and non-co-localizing signals as demonstrated in similar validation protocols

• Immunoprecipitation:

  • Validate ability to pull down SPAC3C7.04 and associated proteins

  • Confirm identity of precipitated protein via mass spectrometry

  • Use chromatin immunoprecipitation to confirm DNA-binding sites

• Cross-Reactivity Analysis:

  • Test against other fungal Zn(2)-Cys(6) domain-containing proteins in S. pombe

  • Evaluate potential cross-reactivity with SPBC19G7.04, which has been shown to function in similar regulatory networks

The most rigorous validation integrates all these approaches, with particular emphasis on genetic controls (deletion strains) to definitively establish specificity .

What is the optimal protocol for chromatin immunoprecipitation (ChIP) using SPAC3C7.04 antibodies?

For effective ChIP using SPAC3C7.04 antibodies, we recommend the following optimized protocol:

Fixation and Crosslinking:

• Grow S. pombe cells to mid-log phase (OD600 = 0.5-0.8)

• Crosslink with 1% formaldehyde for 15 minutes at room temperature

• Quench with 125 mM glycine for 5 minutes

• Wash cells 3× with cold PBS

Chromatin Preparation:

• Lyse cells using glass beads in lysis buffer (50 mM HEPES-KOH pH 7.5, 140 mM NaCl, 1 mM EDTA, 1% Triton X-100, 0.1% sodium deoxycholate, protease inhibitors)

• Sonicate to generate DNA fragments of 200-500 bp

• Clear lysate by centrifugation at 14,000×g for 10 minutes

Immunoprecipitation:

• Pre-clear chromatin with Protein A/G beads for 1 hour at 4°C

• Incubate 100 μg of chromatin with 5-10 μg SPAC3C7.04 antibody overnight at 4°C

• Add Protein A/G beads and incubate for 2 hours at 4°C

• Wash progressively with:

  • Low salt wash buffer (0.1% SDS, 1% Triton X-100, 2 mM EDTA, 20 mM Tris-HCl pH 8.0, 150 mM NaCl)

  • High salt wash buffer (same as low salt but with 500 mM NaCl)

  • LiCl wash buffer (0.25 M LiCl, 1% NP-40, 1% sodium deoxycholate, 1 mM EDTA, 10 mM Tris-HCl pH 8.0)

  • TE buffer (10 mM Tris-HCl pH 8.0, 1 mM EDTA)

Elution and Reversal of Crosslinks:

• Elute with elution buffer (1% SDS, 0.1 M NaHCO3)

• Reverse crosslinks at 65°C overnight

• Treat with RNase A and Proteinase K

• Purify DNA using phenol-chloroform extraction or commercial kits

This protocol has been adapted from chromatin immunoprecipitation studies in S. pombe that successfully isolated chromatin-bound proteins . For SPAC3C7.04 specifically, focus on enrichment of regions containing fungal Zn(2)-Cys(6) binding motifs.

How can SPAC3C7.04 antibodies be employed to study its potential role in cell cycle regulation?

To investigate SPAC3C7.04's role in cell cycle regulation using antibodies:

Experimental Design Strategy:

• Cell Cycle Synchronization and ChIP-seq Analysis:

  • Synchronize S. pombe cells using nitrogen starvation and release

  • Collect samples at 20-minute intervals throughout the cell cycle

  • Perform ChIP-seq with SPAC3C7.04 antibodies at each timepoint

  • Identify dynamic binding patterns and correlate with cell cycle phases

  • Compare to known periodic transcription factors like Fkh2, which shows late G2 activity

• Co-Immunoprecipitation at Different Cell Cycle Stages:

  • Synchronize cells and collect at G1, S, G2, and M phases

  • Immunoprecipitate SPAC3C7.04 at each phase

  • Identify phase-specific interaction partners by mass spectrometry

  • Create interaction networks showing temporal dynamics

• Phosphorylation State Analysis:

  • Use phospho-specific antibodies or general SPAC3C7.04 antibodies followed by phospho-enrichment

  • Map phosphorylation sites that change during cell cycle progression

  • Connect to known CDK or cell cycle kinase consensus motifs

The genetic interaction data shows potential connections to cell cycle regulation , and global gene regulatory network analysis places SPAC3C7.04 in context with known cell cycle regulators like SPBC19G7.04 and Fkh2 . Utilizing antibodies to map its dynamic binding patterns, interaction partners, and post-translational modifications will reveal its regulatory mechanisms.

What approaches can be used to study the relationship between SPAC3C7.04 and other transcription factors in regulatory networks?

To elucidate SPAC3C7.04's position in transcriptional regulatory networks:

Multi-dimensional Experimental Approach:

• Sequential ChIP (Re-ChIP) Analysis:

  • Primary ChIP with SPAC3C7.04 antibody

  • Secondary ChIP with antibodies against potential co-regulators:

    • Fkh2 (showed coordinated activity with SPBC19G7.04)

    • SPBC19G7.04 (HMG-box transcription factor active in early M phase)

    • Other fungal Zn(2)-Cys(6) domain transcription factors

  • Identify genomic loci where multiple factors co-bind

• Proximity-Dependent Biotin Identification (BioID):

  • Create SPAC3C7.04-BirA fusion proteins

  • Identify proteins in close proximity to SPAC3C7.04 in living cells

  • Compare the proximity interactome with known transcription factors and co-regulators

• Integrative Network Analysis:

  • Combine ChIP-seq data with RNA-seq from SPAC3C7.04 deletion/overexpression strains

  • Construct directed regulatory networks showing target genes

  • Perform motif analysis to identify binding sequence preferences

  • Correlate with datasets from existing transcription factor studies

• Synthetic Genetic Array Analysis:

  • Expand on existing genetic interaction data

  • Create double mutants with other transcription factors and analyze phenotypes

  • Identify functional redundancy or synergistic relationships

Network analysis from previous studies has already placed SPAC3C7.04 in context with several cell cycle-regulated transcription factors . The P-value of 2.84E-15 for its fungal Zn(2)-Cys(6) binuclear cluster domain indicates a highly significant role in transcriptional regulation that warrants deep investigation of its network connections.

What strategies can overcome challenges in detecting SPAC3C7.04 in immunoprecipitation experiments?

When facing difficulties detecting SPAC3C7.04 in immunoprecipitation experiments:

Methodological Solutions:

• Optimize Extraction Conditions:

  • Test different lysis buffers with varying salt concentrations (150-500 mM NaCl)

  • Include specialized detergents for nuclear proteins (0.1-0.5% NP-40 or 0.1% SDS)

  • Incorporate sonication steps to disrupt nuclear membranes

  • Add specialized nuclear extraction reagents like benzonase nuclease

• Cross-linking Optimization:

  • Test dual cross-linking with DSP (dithiobis[succinimidyl propionate]) before formaldehyde

  • Optimize formaldehyde concentration (0.5-2%) and cross-linking times (10-30 minutes)

  • Use protein-protein cross-linkers for transient interactions

• Antibody Enhancement Strategies:

  • Pre-clear lysates thoroughly to reduce non-specific binding

  • Utilize antibody concentrations between 2-10 μg per 1 mg of protein lysate

  • Consider using a cocktail of antibodies targeting different epitopes

  • Employ epitope-tagged SPAC3C7.04 (HA, FLAG, etc.) as a parallel approach

• Detection Enhancement:

  • Use highly sensitive western blot detection systems (ECL Prime or Femto)

  • Consider mass spectrometry-based detection for low abundance proteins

  • Implement signal amplification methods like biotin-streptavidin systems

Since SPAC3C7.04 is involved in transcriptional regulation and has both nuclear and cytoplasmic localization , extraction conditions are particularly critical. The dual localization may also indicate different functional pools with varying extraction requirements.

How can background signals be reduced when using SPAC3C7.04 antibodies in immunofluorescence microscopy?

To reduce background signals in immunofluorescence microscopy:

Optimization Protocol:

• Fixation and Permeabilization Refinement:

  • Compare different fixatives: 4% paraformaldehyde, methanol, or methanol-acetone

  • Test permeabilization agents: 0.1-0.5% Triton X-100, 0.05-0.2% Saponin, or 0.01-0.1% SDS

  • Optimize fixation times (10-30 minutes) and permeabilization times (5-15 minutes)

• Blocking Protocol Enhancement:

  • Extend blocking time to 1-2 hours at room temperature

  • Test different blocking agents:

    • 5% normal serum from the species of secondary antibody origin

    • 3-5% BSA with 0.1-0.3% Tween-20

    • Commercial blocking reagents with protein-free formulations

  • Include 0.05-0.2% Tween-20 in all antibody dilution and wash buffers

• Antibody Dilution Optimization:

  • Test serial dilutions from 1:100 to 1:2000

  • Extend primary antibody incubation to overnight at 4°C

  • Perform extensive washing (5× 5 minutes) after antibody incubations

  • Pre-absorb antibodies with cell extracts from SPAC3C7.04 deletion strains

• Controls and Signal Verification:

  • Include SPAC3C7.04 deletion strains as negative controls

  • Use peptide competition assays to confirm specificity

  • Compare staining patterns with GFP-tagged SPAC3C7.04 in live cells

  • Quantify signal-to-noise ratios using image analysis software

• Mounting Media Optimization:

  • Test anti-fade agents with different refractive indices

  • Include DAPI or other nuclear counterstains to verify nuclear localization

  • Consider using clearing agents for better signal penetration

For transcription factors like SPAC3C7.04 with dual localization patterns , distinguishing specific signal from background is particularly challenging. Quantitative co-localization analysis with nuclear markers can help verify true signals from artifacts.

How should researchers interpret ChIP-seq data for SPAC3C7.04 in the context of cell cycle regulation?

When interpreting ChIP-seq data for SPAC3C7.04 in cell cycle contexts:

Analytical Framework:

• Phase-Specific Binding Pattern Analysis:

  • Map SPAC3C7.04 binding sites to gene promoters and regulatory regions

  • Group target genes by cell cycle phase expression patterns

  • Compare binding profiles across synchronized timepoints

  • Create heat maps showing temporal binding dynamics

  • Look specifically for co-regulation with the Fkh2 transcription factor, which has been shown to have coordinated late G2 phase activity

• Motif Analysis and Integration:

  • Identify enriched DNA motifs in binding regions using MEME or similar tools

  • Compare identified motifs with known binuclear Zn cluster consensus sequences

  • Look for composite motifs suggesting co-factor binding

  • Integrate with published S. pombe regulatory motif databases

• Target Gene Function Analysis:

  • Perform Gene Ontology enrichment on target genes

  • Focus on cell cycle-related processes, especially M phase functions

  • Create functional interaction networks of target genes

  • Compare with targets of SPBC19G7.04, which shows early M phase activity

• Comparative Analysis with Known Cell Cycle Regulators:

  • Overlay binding data with other cell cycle transcription factors

  • Identify regions of co-binding or mutually exclusive binding

  • Calculate statistical significance of binding site overlaps

  • Create integrated regulatory maps showing temporal coordination

• Integration with Expression Data:

  • Correlate binding strength with target gene expression levels

  • Determine if SPAC3C7.04 functions primarily as an activator or repressor

  • Identify any discordant binding-expression relationships

Previous studies have placed SPAC3C7.04 in the context of cell cycle regulation , making it essential to interpret ChIP-seq data with specific attention to phase-specific binding patterns and coordination with known cell cycle regulators.

What bioinformatic approaches best identify the complete regulon of SPAC3C7.04 in fission yeast?

To comprehensively define the SPAC3C7.04 regulon:

Integrated Bioinformatic Strategy:

• Multi-omic Data Integration:

  • Combine ChIP-seq data with RNA-seq from knockout/overexpression experiments

  • Integrate proteomics data to confirm translation of target gene mRNAs

  • Include metabolomic data for downstream functional effects

  • Use machine learning to weight different data types in predicting direct vs. indirect targets

• Network Inference Algorithms:

  • Apply ARACNE, GENIE3, or similar algorithms to infer regulatory relationships

  • Build Bayesian networks incorporating prior knowledge from existing S. pombe datasets

  • Use time-lagged correlation analysis for cell cycle synchronized datasets

  • Employ module detection algorithms to identify co-regulated gene clusters

• Comparative Genomics Approach:

  • Compare SPAC3C7.04 binding sites across different fission yeast species

  • Identify evolutionarily conserved targets as core regulon components

  • Use orthology mapping to relate targets to known regulons in other fungi

  • Apply phylogenetic footprinting to identify conserved regulatory motifs

• Synthetic Genetic Analysis Integration:

  • Incorporate genetic interaction data to identify functional relationships

  • Prioritize genes showing both binding and genetic interactions

  • Use genetic interaction strength to weight regulon membership confidence

• Data Visualization and Analysis:

  • Create interactive network visualizations with Cytoscape

  • Implement hierarchical clustering of targets based on expression patterns

  • Develop phase-specific regulon maps for cell cycle-regulated targets

  • Calculate statistical significance of regulon enrichment for specific functions

The comprehensive systems-level analysis previously applied to S. pombe cell cycle regulation provides an excellent methodological template. Similar approaches can be used to fully characterize the SPAC3C7.04 regulon, with particular attention to its fungal Zn(2)-Cys(6) binuclear cluster domain binding preferences.

How can SPAC3C7.04 antibodies be adapted for proximity labeling techniques to study its interaction network?

To adapt SPAC3C7.04 antibodies for proximity labeling studies:

Methodological Implementations:

• Antibody-Directed BioID Approaches:

  • Conjugate SPAC3C7.04 antibodies to modified BirA* enzyme

  • Optimize biotin concentration (50-500 μM) and labeling times (15-360 minutes)

  • Extract biotinylated proteins using streptavidin pulldown

  • Identify proximal proteins via mass spectrometry

  • Compare interaction networks across cell cycle stages

• APEX2-Based Proximity Labeling:

  • Conjugate antibodies to APEX2 peroxidase

  • Optimize H₂O₂ concentration (0.5-5 mM) and labeling time (30 seconds-5 minutes)

  • Identify rapidly labeled proximal proteins

  • Create spatiotemporal maps of SPAC3C7.04 interactions

• Split-BioID or Split-APEX Approaches:

  • Generate constructs with SPAC3C7.04 fused to one half of split BioID

  • Create libraries of potential interactors fused to complementary half

  • Identify specific interactions through reconstituted enzymatic activity

  • Validate interactions using co-immunoprecipitation with SPAC3C7.04 antibodies

• In situ Proximity Ligation Assay (PLA):

  • Use SPAC3C7.04 antibodies with antibodies against suspected interaction partners

  • Visualize and quantify interactions as fluorescent puncta

  • Map interaction dynamics throughout the cell cycle

  • Compare interaction patterns in different cellular compartments

• Calibration and Controls:

  • Use GFP-tagged SPAC3C7.04 as positive control

  • Include SPAC3C7.04 deletion strains as negative controls

  • Perform parallel experiments with non-specific IgG antibodies

  • Calculate enrichment ratios relative to controls

Given SPAC3C7.04's role in transcriptional networks and its dual localization , proximity labeling can reveal both nuclear transcriptional complexes and potential cytoplasmic regulatory interactions or transport factors.

What approaches can determine whether post-translational modifications regulate SPAC3C7.04 activity?

To investigate post-translational regulation of SPAC3C7.04:

Comprehensive PTM Analysis Strategy:

• Phosphorylation Analysis:

  • Immunoprecipitate SPAC3C7.04 using validated antibodies

  • Perform phospho-specific western blots or Phos-tag SDS-PAGE

  • Analyze phosphorylation sites using mass spectrometry

  • Compare phosphorylation patterns across cell cycle stages

  • Focus on S2, S6, S685, S697, S699, and T701 sites previously identified in related proteins

• Ubiquitination and SUMOylation Analysis:

  • Co-immunoprecipitate with ubiquitin or SUMO antibodies

  • Perform denaturing IP to preserve modified forms

  • Analyze stability following treatment with proteasome inhibitors

  • Investigate potential regulation by E3 ligases like Ubr1 (shown to regulate other transcription factors)

• Acetylation and Methylation:

  • Immunoprecipitate with SPAC3C7.04 antibodies

  • Probe western blots with pan-acetyl-lysine or methyl-lysine antibodies

  • Perform mass spectrometry to map specific modification sites

  • Compare with known acetylation patterns on zinc finger domains

• Functional Impact Assessment:

  • Generate phosphomimetic and phospho-deficient mutants

  • Perform ChIP-seq to compare binding profiles of modified vs. unmodified forms

  • Correlate modifications with transcriptional output of target genes

  • Investigate temporal dynamics of modifications during cell cycle progression

• Enzyme Identification:

  • Use proximity labeling to identify candidate modifying enzymes

  • Perform genetic interaction screens with known kinases, phosphatases, and other PTM enzymes

  • Validate with targeted enzyme inhibition or deletion

The identification of phosphorylation sites on similar regulatory proteins suggests that SPAC3C7.04 likely undergoes similar regulation. Given its role in cell cycle regulation , post-translational modifications probably control its activity in a phase-specific manner.

How do monoclonal versus polyclonal antibodies against SPAC3C7.04 compare in research applications?

When comparing monoclonal and polyclonal SPAC3C7.04 antibodies:

Comparative Analysis Table:

Application-Specific Recommendations:

For transcription factors like SPAC3C7.04 with specific DNA-binding domains , monoclonal antibodies targeting the DNA-binding region are ideal for ChIP applications, while polyclonal antibodies may be better for detecting the protein in multiple experimental contexts. The recombinant monoclonal approach, similar to that used for other transcription factors , offers advantages in specificity and reproducibility for long-term studies.

What considerations should guide the choice between using antibodies versus epitope tagging approaches for studying SPAC3C7.04?

When deciding between antibody-based detection and epitope tagging for SPAC3C7.04 research:

Decision Framework:

• Experimental Objectives Assessment:

  Research Goal	Antibody Approach	Epitope Tagging Approach
  Endogenous expression analysis	Preferred - maintains native regulation	Limited - tag may affect expression
  Protein-protein interactions	Variable success depending on epitope accessibility	Highly effective with established tag purification
  Chromatin binding (ChIP)	May interfere with DNA binding if targeting Zn cluster domain	May alter DNA binding if tag is near DNA-binding domain
  Subcellular localization	Requires fixation, potential artifacts	Live cell imaging possible with fluorescent tags
  Post-translational modifications	Can detect natural modifications	Tag may interfere with some modifications
  Conditional depletion	Not applicable	Enables degron tagging for targeted degradation

• Technical Considerations:

  • Antibody-based approach advantages:

    • Detects endogenous protein without genetic manipulation

    • Preserves all natural splice variants and modifications

    • No concerns about tag-induced artifacts

  • Epitope tagging advantages:

    • Consistent detection regardless of conformation

    • Standardized purification protocols with high reproducibility

    • Enables live-cell imaging with fluorescent tags

• Experimental Validation Strategy:

  • Confirm tag doesn't disrupt SPAC3C7.04 function through complementation assays

  • Verify localization patterns match between antibody and tag detection

  • Compare ChIP-seq profiles from antibody and tag approaches

  • Check if tag affects known genetic interactions

• Biological Considerations:

  • SPAC3C7.04's dual nuclear/cytoplasmic localization may be affected by tagging

  • Its transcription factor function could be compromised by N-terminal tags near the DNA-binding domain

  • C-terminal tagging may be preferable given the N-terminal location of the Zn(2)-Cys(6) domain

• Combined Strategy Recommendation:

  • Use both approaches in parallel for cross-validation

  • Employ antibodies for initial characterization of endogenous function

  • Use tagging for specific applications requiring high sensitivity or live-cell analysis

For SPAC3C7.04, with its critical role in transcriptional networks and potentially dynamic cell cycle regulation , the combination of both approaches provides the most comprehensive and reliable results.

How might SPAC3C7.04 antibodies contribute to understanding transcription factor dynamics in non-coding RNA regulation?

SPAC3C7.04 antibodies can illuminate transcription factor involvement in non-coding RNA regulation through:

Innovative Research Approaches:

• Comprehensive Genomic Binding Analysis:

  • Perform ChIP-seq to map SPAC3C7.04 binding across the entire genome, including non-coding regions

  • Analyze binding to promoters of known non-coding RNA genes

  • Identify enrichment at enhancers or silencers that regulate ncRNA transcription

  • Compare binding profiles in wild-type versus stress conditions

• Non-coding RNA-Protein Interaction Studies:

  • Use RNA immunoprecipitation (RIP) with SPAC3C7.04 antibodies

  • Identify direct RNA-protein interactions

  • Implement CLIP-seq (cross-linking immunoprecipitation) to map RNA binding sites at nucleotide resolution

  • Compare RNA interactions between nuclear and cytoplasmic fractions

• Functional Impact Assessment:

  • Correlate SPAC3C7.04 binding with expression of proximal non-coding RNAs

  • Analyze SPAC3C7.04 knockout effects on ncRNA transcriptome using RNA-seq

  • Investigate whether SPAC3C7.04 regulates antisense transcripts of its target genes

  • Examine effects on cell cycle-regulated long non-coding RNAs

• Mechanistic Studies:

  • Investigate co-localization with RNA polymerase II and III at ncRNA loci

  • Identify SPAC3C7.04 interactions with chromatin remodeling complexes that regulate ncRNA expression

  • Examine involvement in phase separation at transcriptional condensates

  • Test for pioneer factor activity in opening chromatin at ncRNA loci

The dual nuclear/cytoplasmic localization of SPAC3C7.04 suggests potential roles in both transcriptional and post-transcriptional regulation of RNAs. Given its function as a transcription factor with cell cycle connections , it may specifically regulate ncRNAs involved in cell cycle progression.

What approaches can determine if SPAC3C7.04 functions within phase-separated transcriptional condensates?

To investigate SPAC3C7.04's potential involvement in phase-separated transcriptional condensates:

Multidisciplinary Experimental Strategy:

• Microscopy-Based Condensate Analysis:

  • Perform immunofluorescence with SPAC3C7.04 antibodies and known condensate markers

  • Quantify co-localization with transcriptional condensate components

  • Analyze condensate dynamics during cell cycle progression

  • Use super-resolution microscopy to characterize condensate structure

  • Implement optogenetic tools to trigger condensate formation/dissolution

• Biochemical Phase Separation Assays:

  • Express and purify SPAC3C7.04 protein domains

  • Test for in vitro phase separation properties

  • Examine effects of DNA/RNA on phase separation behavior

  • Investigate impact of post-translational modifications on condensate formation

  • Analyze domain requirements for phase separation

• Molecular Dynamics Studies:

  • Identify intrinsically disordered regions (IDRs) in SPAC3C7.04 sequence

  • Examine prion-like domains or low complexity sequences

  • Predict phase separation propensity using algorithms like PLAAC or catGRANULE

  • Model interactions with known condensate scaffolds

• Functional Impact Assessment:

  • Create domain mutants that disrupt phase separation properties

  • Perform ChIP-seq to compare genomic binding of wild-type vs. mutant proteins

  • Analyze transcriptional output of target genes

  • Examine effects on target gene clustering in nuclear space

  • Investigate impact on transcriptional bursting

• Dynamics and Regulation:

  • Study how cell cycle signals affect SPAC3C7.04 condensate association

  • Examine the role of known phosphorylation sites in condensate dynamics

  • Investigate how environmental stress affects condensate formation