Recombinant Schizosaccharomyces pombe Uncharacterized transcriptional regulatory protein C1773.16c (SPBC1773.16c)

What is known about the function of SPBC1773.16c in Schizosaccharomyces pombe?

SPBC1773.16c is currently classified as an uncharacterized transcriptional regulatory protein in Schizosaccharomyces pombe (fission yeast). While the specific function remains to be fully elucidated, its classification suggests involvement in transcriptional regulation processes. The protein has been assigned UniProt accession number O94573 and is derived from S. pombe strain 972 / ATCC 24843 . As an uncharacterized protein, determining its precise role requires applying standard approaches for functional characterization including gene deletion/complementation studies, localization analyses, and interaction studies with known transcriptional complexes in S. pombe.

How can I optimize storage conditions for recombinant SPBC1773.16c protein to maintain activity?

For optimal storage of recombinant SPBC1773.16c protein, multiple factors must be considered to preserve structural integrity and activity. The liquid form has a shelf life of approximately 6 months when stored at -20°C/-80°C, while the lyophilized form can be maintained for up to 12 months at the same temperature range . To reconstitute the protein, centrifuge the vial briefly before opening, then dissolve in deionized sterile water to a concentration of 0.1-1.0 mg/mL. Addition of glycerol (5-50% final concentration) is recommended for long-term storage, with 50% being the standard recommendation . Working aliquots should be stored at 4°C for no longer than one week, and repeated freeze-thaw cycles should be strictly avoided as they can compromise protein integrity and activity .

What expression systems are most effective for producing recombinant SPBC1773.16c?

Based on the available data, E. coli has been successfully employed as an expression system for producing recombinant SPBC1773.16c protein with purity levels exceeding 85% as verified by SDS-PAGE analysis . When designing expression systems for this protein, researchers should consider:

• Codon optimization for the host organism

• Selection of appropriate fusion tags to facilitate purification

• Expression conditions that minimize inclusion body formation

• Purification strategies that maintain protein folding and activity

While E. coli represents a cost-effective and efficient expression system, researchers investigating protein-protein interactions or post-translational modifications might consider eukaryotic expression systems such as yeast (Pichia pastoris) or insect cells (baculovirus expression system) to better approximate native conditions.

What strategies can be employed to elucidate the transcriptional regulatory function of SPBC1773.16c?

To determine the transcriptional regulatory function of SPBC1773.16c, multiple complementary approaches should be employed:

• Chromatin Immunoprecipitation (ChIP) analysis: Using antibodies against tagged versions of SPBC1773.16c to identify DNA binding sites, followed by sequencing (ChIP-seq) to map genome-wide binding profiles.

• Transcriptome analysis: RNA-seq comparing wild-type and SPBC1773.16c deletion mutants can reveal genes whose expression is affected by this protein. Differential gene expression analysis using methods similar to those described in BPF degradation studies would be appropriate, defining differentially expressed genes as having P values <0.05 and |log2(fold change)| >1 .

• Protein-protein interaction studies: Yeast two-hybrid screens, co-immunoprecipitation, or proximity labeling approaches to identify protein binding partners within transcriptional complexes.

• Functional genomic screens: Synthetic genetic array (SGA) analysis in S. pombe to identify genetic interactions that could reveal pathways involving SPBC1773.16c.

• DNA binding assays: Electrophoretic mobility shift assays (EMSA) or DNA footprinting to characterize potential DNA binding properties and sequence specificity.

A systematic application of these methods would provide complementary lines of evidence regarding the specific transcriptional regulatory function of this protein.

How can I design experiments to study SPBC1773.16c involvement in DNA damage response pathways?

S. pombe is a powerful model organism for studying DNA damage repair mechanisms . To investigate whether SPBC1773.16c plays a role in these pathways:

• Sensitivity assays: Compare the sensitivity of wild-type and SPBC1773.16c deletion strains to DNA damaging agents (UV, ionizing radiation, methyl methanesulfonate, hydroxyurea).

• Genetic interaction studies: Create double mutants with known DNA repair factors (e.g., rad51, rad50, mre11) to identify potential synthetic lethality or epistatic relationships.

• Localization studies: Use fluorescently tagged SPBC1773.16c to monitor its subcellular localization before and after DNA damage induction.

• Mitotic recombination assays: Employ established S. pombe recombination assays to determine if SPBC1773.16c affects mitotic recombination rates. These could include:

  • Non-tandem repeat assays that measure deletion, inversion, and duplication rates

  • Assays that utilize the ade6 locus to monitor recombination frequencies

• Recruitment kinetics: Study the temporal dynamics of SPBC1773.16c localization to sites of DNA damage using laser microirradiation coupled with live-cell imaging.

These approaches would provide comprehensive insights into whether SPBC1773.16c functions in DNA damage response pathways, a role consistent with many transcriptional regulators in S. pombe.

What computational approaches can predict structural domains and potential functions of SPBC1773.16c?

For comprehensive structural and functional prediction of SPBC1773.16c, implement the following bioinformatic pipeline:

• Sequence homology analysis: Use BLAST, HHpred, and HMMER to identify distant homologs that might have characterized functions.

• Domain prediction: Apply InterProScan, SMART, and Pfam to identify conserved domains that might suggest functional roles.

• Secondary structure prediction: Employ PSIPRED, JPred, and SOPMA to predict secondary structural elements.

• Tertiary structure prediction: Utilize AlphaFold2, RoseTTAFold, or I-TASSER to generate three-dimensional structural models.

• Binding site prediction: Apply CASTp, COACH, and FTSite to identify potential ligand binding pockets or DNA-binding interfaces.

• Post-translational modification prediction: Use NetPhos, SUMOplot, and UbPred to identify potential regulatory modification sites.

• Phylogenetic analysis: Construct phylogenetic trees with related proteins across species to understand evolutionary relationships and functional conservation.

• Protein-protein interaction prediction: Implement STRING, PRISM, and Interactome3D to predict potential interaction partners.

The integration of these various computational predictions can provide valuable hypotheses about protein function that can guide experimental design, particularly for proteins like SPBC1773.16c where experimental characterization is limited.

How can I design a comprehensive mass spectrometry approach to identify post-translational modifications of SPBC1773.16c?

To systematically characterize post-translational modifications (PTMs) of SPBC1773.16c:

• Sample preparation:

  • Express tagged versions of SPBC1773.16c in S. pombe under various conditions (normal growth, stress, cell cycle phases)

  • Purify using tandem affinity purification to ensure high purity

  • Prepare parallel samples with specific enrichment strategies for phosphorylation, acetylation, ubiquitination, etc.

• Enzymatic digestion strategy:

  • Perform parallel digestions with different proteases (trypsin, chymotrypsin, Glu-C) to maximize sequence coverage

  • Consider limited proteolysis to identify domain boundaries

• MS analysis approaches:

  • Employ high-resolution LC-MS/MS using both collision-induced dissociation (CID) and electron transfer dissociation (ETD) fragmentation

  • Use neutral loss scanning for phosphorylation site mapping

  • Implement targeted approaches (parallel reaction monitoring) for suspected modification sites

• Data analysis pipeline:

  • Search against S. pombe database with variable modifications

  • Apply false discovery rate control (typically <1%)

  • Validate PTM site assignments using site-determining ions

  • Quantify modification stoichiometry using label-free or isotope labeling approaches

• Validation experiments:

  • Generate site-specific antibodies against identified PTMs

  • Create point mutations at modified residues to assess functional significance

  • Monitor temporal dynamics of modifications across conditions

This comprehensive approach will provide a detailed map of the post-translational modification landscape of SPBC1773.16c and potential regulatory mechanisms.

How can SPBC1773.16c be utilized to study transcriptional regulatory networks in S. pombe?

To leverage SPBC1773.16c in studies of transcriptional regulatory networks:

• Network mapping:

  • Perform ChIP-seq to identify direct genomic targets

  • Couple with RNA-seq to distinguish between activated and repressed targets

  • Construct regulatory networks by integrating with existing transcription factor binding data

• Perturbation studies:

  • Design conditional depletion systems (e.g., auxin-inducible degron) to study temporal effects of SPBC1773.16c loss

  • Create partial function alleles through targeted mutagenesis to identify separation-of-function phenotypes

• Co-regulatory analysis:

  • Perform sequential ChIP (re-ChIP) to identify co-occupancy with other transcription factors

  • Use proteomics approaches to define the composition of SPBC1773.16c-containing complexes under different conditions

• Dynamic regulatory studies:

  • Implement live-cell imaging with fluorescently tagged SPBC1773.16c to monitor recruitment dynamics

  • Use rapidly inducible promoters to observe immediate transcriptional consequences of SPBC1773.16c activation

• Synthetic biology applications:

  • Engineer chimeric proteins containing SPBC1773.16c domains fused to heterologous DNA-binding domains to test modular functionality

  • Develop synthetic transcriptional circuits incorporating SPBC1773.16c to test network properties

These approaches would position SPBC1773.16c as a tool for understanding fundamental principles of transcriptional regulation in S. pombe.

What are the best approaches to investigate potential roles of SPBC1773.16c in non-transcriptional processes?

While SPBC1773.16c is annotated as a transcriptional regulatory protein, many regulatory proteins have multiple functions. To investigate potential non-transcriptional roles:

• Subcellular localization studies:

  • Perform immunofluorescence or live-cell imaging across different cell cycle stages and stress conditions

  • Use subcellular fractionation coupled with western blotting to detect presence in different cellular compartments

• Proteome-wide interaction studies:

  • Implement BioID or APEX proximity labeling to identify proteins in close proximity to SPBC1773.16c

  • Perform immunoprecipitation coupled with mass spectrometry under non-crosslinked conditions to identify stable interactors

• Metabolomic analysis:

  • Compare metabolomic profiles between wild-type and SPBC1773.16c mutant strains

  • Look for specific metabolic pathways affected by SPBC1773.16c deletion

• Cytoskeletal and cellular morphology:

  • Analyze cell shape, size, and cytoskeletal organization in SPBC1773.16c mutants

  • Monitor cellular processes like endocytosis, vesicle trafficking, and organelle dynamics

• Cell cycle progression:

  • Perform synchronization experiments to determine if SPBC1773.16c affects specific cell cycle transitions

  • Use flow cytometry and live-cell imaging to quantify cell cycle timing

By systematically investigating these non-transcriptional processes, researchers can uncover potential moonlighting functions of SPBC1773.16c beyond its annotated role in transcriptional regulation.

What strategies can overcome challenges in detecting protein-protein interactions involving SPBC1773.16c?

Detecting protein-protein interactions for transcriptional regulators like SPBC1773.16c can be challenging due to potentially transient interactions, low abundance, or specific interaction conditions. To address these challenges:

• Crosslinking strategies:

  • Implement formaldehyde crosslinking for capturing transient interactions

  • Use photoactivatable crosslinkers for higher specificity

  • Consider protein-interaction reporter systems like FRET or BiFC for live-cell detection

• Expression optimization:

  • Use endogenous expression levels with minimal tags to maintain physiological interactions

  • For weak interactions, consider controlled overexpression using inducible promoters

  • Test multiple tag positions (N-terminal, C-terminal, internal) to minimize interference

• Interaction stabilization:

  • Add phosphatase inhibitors to preserve phosphorylation-dependent interactions

  • Test multiple buffer conditions to optimize interaction stability

  • Consider addition of DNA or chromatin in buffers for transcription factors that may require DNA binding for certain interactions

• Advanced detection methods:

  • Use highly sensitive mass spectrometry approaches like SWATH-MS for detecting low-abundance interactors

  • Implement methods like single-molecule pull-down (SiMPull) for detecting low-affinity interactions

  • Consider hydrogen-deuterium exchange mass spectrometry (HDX-MS) to map interaction interfaces

• Functional validation:

  • Confirm biological relevance of detected interactions through genetic interaction studies

  • Test co-localization under multiple conditions

  • Perform domain mapping to identify specific interaction regions

These methodological optimizations can significantly improve detection of protein-protein interactions involving SPBC1773.16c, providing insight into its functional complexes.

How can researchers troubleshoot expression and purification issues with recombinant SPBC1773.16c?

When encountering challenges with expression and purification of recombinant SPBC1773.16c, consider this systematic troubleshooting approach:

For optimal reconstitution of purified SPBC1773.16c, follow the recommended protocol: briefly centrifuge the vial before opening, reconstitute in deionized sterile water to 0.1-1.0 mg/mL, and add glycerol to a final concentration of 5-50% for long-term storage at -20°C/-80°C . Working aliquots should be stored at 4°C for a maximum of one week, and repeated freeze-thaw cycles should be avoided .

How does SPBC1773.16c compare to homologous proteins in other yeast species?

Understanding the evolutionary context of SPBC1773.16c requires comprehensive comparative analysis:

• Homology assessment:

  • Identify orthologs in related species (Schizosaccharomyces japonicus, S. octosporus, S. cryophilus)

  • Look for functional homologs in distantly related yeasts (Saccharomyces cerevisiae, Candida albicans)

  • Search for conservation in filamentous fungi and higher eukaryotes

• Domain architecture comparison:

  • Map conserved domains and motifs across homologs

  • Identify species-specific insertions or deletions that might reflect functional specialization

  • Compare DNA-binding domains for conservation of specific recognition elements

• Functional complementation experiments:

  • Test whether homologs from other species can rescue S. pombe SPBC1773.16c deletion phenotypes

  • Create chimeric proteins with domains from different species to identify functionally critical regions

• Co-evolution analysis:

  • Look for co-evolving proteins that might function in the same pathway

  • Identify conservation of regulatory sites (promoters, enhancers) for homologous genes

• Comparative expression analysis:

  • Compare expression patterns of homologs across species

  • Identify conserved regulation in response to environmental conditions or developmental stages

This evolutionary perspective can provide insight into conserved functional roles and species-specific adaptations of SPBC1773.16c and related proteins.

What can be learned from integrating SPBC1773.16c studies with other transcriptional regulatory factors in S. pombe?

To position SPBC1773.16c within the broader transcriptional regulatory network of S. pombe:

• Network integration approaches:

  • Compare ChIP-seq profiles with other transcription factors to identify collaborative or antagonistic relationships

  • Construct transcription factor co-binding networks to identify regulatory modules

  • Analyze the combinatorial logic of transcription factor binding sites at co-regulated genes

• Genetic interaction mapping:

  • Perform systematic genetic interaction screens between SPBC1773.16c and other transcriptional regulators

  • Look for suppressor or enhancer relationships that suggest pathway connections

  • Create conditional alleles to test temporal aspects of genetic interactions

• Dynamic regulatory studies:

  • Monitor binding dynamics of multiple factors at shared target sites

  • Implement nascent transcription assays to determine the functional consequences of factor recruitment

  • Study factor replacement or sequential binding during cellular transitions

• Comparative genomics integration:

  • Analyze conservation of regulatory networks across yeast species

  • Identify species-specific rewiring events that might reflect adaptive changes

• Multi-omics data integration:

  • Combine transcriptomics, proteomics, and metabolomics data to construct comprehensive regulatory models

  • Use machine learning approaches to predict regulatory relationships from integrated datasets

These integrative approaches position SPBC1773.16c studies within a systems biology framework, providing deeper insight into transcriptional regulation in S. pombe.

What emerging technologies could advance our understanding of SPBC1773.16c function?

Several cutting-edge technologies have the potential to significantly advance research on SPBC1773.16c:

• CRISPR-based technologies:

  • CRISPRi/CRISPRa for conditional regulation of SPBC1773.16c expression

  • Base editing for generating point mutations without double-strand breaks

  • Prime editing for precise genomic modifications

  • CRISPR screening for identifying genetic interactions

• Single-cell approaches:

  • Single-cell RNA-seq to detect cell-to-cell variability in transcriptional responses

  • Single-cell proteomics to measure protein levels and modifications

  • Single-cell chromatin accessibility assays to link chromatin state to transcriptional output

• Spatial technologies:

  • Super-resolution microscopy for studying subnuclear localization

  • Spatial transcriptomics to map spatial organization of transcription

  • Proximity labeling methods (TurboID, APEX) for mapping local protein environments

• In situ structural biology:

  • Cryo-electron tomography for visualizing macromolecular complexes in their native context

  • Integrative structural biology combining multiple data types (crystallography, cryo-EM, crosslinking MS)

  • Live-cell NMR for studying protein dynamics in vivo

• Synthetic biology approaches:

  • Minimal synthetic transcription circuits incorporating SPBC1773.16c

  • Optogenetic control of SPBC1773.16c activity

  • Cell-free expression systems for studying reconstituted regulatory complexes

Implementing these technologies could provide unprecedented insight into the molecular mechanisms and biological functions of SPBC1773.16c.

How might understanding SPBC1773.16c contribute to broader knowledge of transcriptional regulation?

Research on SPBC1773.16c has the potential to advance several key areas in transcriptional regulation research:

• Regulatory principles in unicellular eukaryotes:

  • Elucidate fundamental mechanisms of transcriptional control in a simple eukaryotic system

  • Discover principles that may be conserved across eukaryotic evolution

  • Identify specializations unique to fission yeast biology

• Stress response regulation:

  • Characterize how transcriptional networks reorganize under various stress conditions

  • Identify regulatory principles governing adaptation and survival

  • Uncover stress-specific regulatory mechanisms

• Cell cycle-dependent transcription:

  • Understand how transcriptional programs are coordinated with cell cycle progression

  • Characterize mechanisms for ensuring proper timing of gene expression

  • Identify control points for cell cycle-dependent transcriptional regulation

• Chromatin-transcription factor interplay:

  • Elucidate how transcription factors like SPBC1773.16c interact with the chromatin landscape

  • Understand mechanisms for accessing DNA in the context of nucleosomes

  • Characterize cooperative interactions between transcription factors and chromatin remodelers

• Regulatory network evolution:

  • Provide insights into how transcriptional networks evolve across species

  • Identify conserved core regulatory modules and species-specific adaptations

  • Understand principles governing network rewiring during evolution

By positioning SPBC1773.16c research within these broader contexts, findings can contribute to fundamental understanding of eukaryotic gene regulation beyond the specific protein itself.