Recombinant Schizosaccharomyces pombe Uncharacterized acyltransferase C428.14 (SPBC428.14)

What is known about the evolutionary conservation of SPBC428.14?

SPBC428.14 is classified as a class "Ib" protein based on phylogenetic analysis, indicating it has homologs in both S. cerevisiae and metazoa but not in prokaryotes . Its S. cerevisiae homolog has been identified as YBR042c, providing a comparative model for functional studies . This evolutionary conservation across different eukaryotic species suggests potential functional importance despite being non-essential for vegetative growth in S. pombe. When designing experiments to elucidate its function, researchers should consider comparative analyses with its orthologous proteins, particularly the S. cerevisiae YBR042c, to identify conserved domains and potential functions.

What phenotypic data is available from SPBC428.14 gene deletion studies?

Deletion studies have shown that SPBC428.14 is non-essential for vegetative growth in S. pombe, as haploid cells with this gene deleted remain viable under standard laboratory conditions . The table below summarizes deletion data from a systematic study:

The viability of the deletion mutant indicates that SPBC428.14 doesn't serve a critical function under standard growth conditions, but it may still play important roles under specific stress conditions or developmental processes that weren't assessed in the initial characterization . When working with deletion mutants, researchers should examine phenotypes under various stress conditions (oxidative, temperature, nutritional) and throughout different stages of the yeast life cycle.

What is the basic structure and properties of recombinant SPBC428.14 protein?

Recombinant SPBC428.14 is available as a full-length protein containing 350 amino acids with a His-tag, produced in E. coli expression systems . The recombinant protein is designated as "Recombinant Full Length Schizosaccharomyces Pombe Uncharacterized Acyltransferase C428.14 (SPBC428.14) Protein, His-Tagged" . When designing experiments with the recombinant protein, researchers should consider buffer optimization for storage and stability, as uncharacterized proteins may have unknown requirements for maintaining native structure. Analytical techniques such as circular dichroism spectroscopy and differential scanning fluorimetry are recommended to assess protein folding and stability under various conditions.

What experimental systems are available to study SPBC428.14 in vivo?

Several experimental approaches can be used to study SPBC428.14 in vivo. Based on protocols mentioned in the literature for similar studies, researchers can:

• Generate epitope-tagged strains following established protocols similar to those described for other S. pombe proteins .

• Perform chromatin immunoprecipitation (ChIP) to identify potential DNA-binding properties or chromatin association patterns .

• Utilize viable deletion strains to conduct phenotypic screens under various conditions .

• Create GFP fusion constructs to monitor subcellular localization using protocols similar to those described for PCR-mediated gene modification .

When designing these experiments, ensure proper controls are included and consider that protein tagging may affect native function or localization.

What basic biochemical characterization should be done for SPBC428.14?

As an uncharacterized acyltransferase, initial biochemical characterization should include:

• Analysis of acyltransferase activity using common acyl-donor substrates (acetyl-CoA, malonyl-CoA, palmitoyl-CoA).

• pH and temperature optima determination.

• Metal ion dependence/cofactor requirements.

• Substrate specificity analysis.

• Enzyme kinetics (Km, Vmax, kcat).

Researchers should design systematic assays to detect acyl transfer to various acceptor substrates, starting with common acceptors for acyltransferases and extending to S. pombe-specific metabolites or proteins. Testing specific inhibitors of known acyltransferase families can also provide insights into the catalytic mechanism.

How can I identify potential protein interaction partners of SPBC428.14?

To identify protein interactions for SPBC428.14, implement a multi-faceted approach:

• Affinity purification coupled with mass spectrometry (AP-MS): Generate strains expressing epitope-tagged SPBC428.14 (similar to methods described for Med4-FLAG and Ell1 purification) . Perform immunoprecipitation followed by MudPIT mass spectrometry to identify co-purifying proteins.

• Yeast two-hybrid screening: Use SPBC428.14 as bait to screen S. pombe cDNA libraries.

• BioID or TurboID proximity labeling: Fuse SPBC428.14 with a biotin ligase to identify proximal proteins in vivo.

• Co-immunoprecipitation validation: Validate specific interactions with candidate partners identified through genomic and proteomic screens.

When analyzing interaction data, prioritize proteins with functions related to acyltransferase activity or proteins that show consistent interaction across multiple experimental approaches. Data interpretation should consider both stable and transient interactions, as enzymatic interactions may be short-lived.

What approaches should be used to determine the enzymatic activity of SPBC428.14 as a putative acyltransferase?

To determine the enzymatic activity of this putative acyltransferase:

• In vitro reconstitution assays:

  • Express and purify recombinant SPBC428.14

  • Screen a panel of acyl-CoA donors (acetyl-CoA, malonyl-CoA, propionyl-CoA)

  • Test various acceptor substrates (proteins, lipids, small molecules)

  • Detect acyl transfer using radioisotope-labeled acyl-CoA or LC-MS/MS

• Targeted metabolomics:

  • Compare metabolite profiles between wild-type and SPBC428.14Δ strains

  • Focus on compounds that might be modified by acyltransferases

  • Employ high-resolution mass spectrometry to detect mass shifts indicative of acylation

• Proteome-wide acylation analysis:

  • Perform western blots with pan-acylation antibodies

  • Use chemical proteomics approaches with acyl-biotin exchange or click chemistry

  • Compare acylation patterns between wild-type and deletion strains

• Structural analysis:

  • Perform homology modeling using related acyltransferases

  • Identify potential catalytic residues

  • Generate and test point mutations of predicted catalytic residues

Data interpretation should include control experiments with known acyltransferase inhibitors and substrate competition assays to validate specificity.

How can I integrate SPBC428.14 into existing transcriptional regulatory networks in S. pombe?

To integrate SPBC428.14 into transcriptional regulatory networks:

• Genome-wide transcriptome analysis:

  • Perform RNA-seq comparing wild-type and SPBC428.14Δ strains

  • Identify differentially expressed genes and enriched pathways

  • Compare with existing transcriptome datasets, particularly those involving chromatin regulation

• ChIP-seq analysis:

  • Generate a tagged SPBC428.14 strain

  • Perform ChIP-seq to identify genomic binding sites

  • Compare binding patterns with known transcription factors and chromatin regulators like Ell1, Eaf1, and Ebp1

• Genetic interaction mapping:

  • Perform synthetic genetic array (SGA) analysis

  • Cross SPBC428.14Δ with deletion libraries

  • Score genetic interactions to identify functional relationships

• Epigenetic profiling:

  • Examine histone modification patterns in SPBC428.14Δ strains

  • Focus on modifications related to transcriptional regulation

When interpreting these data, look for patterns similar to those observed with transcriptional elongation factors. For example, the study by Gopalan (2018) showed that Ell1, Eaf1, and Ebp1 co-localize at genes with high Pol II and Cdk9 occupancy . Determine if SPBC428.14 shows similar patterns of localization or affects similar sets of genes.

What considerations should be made when designing experiments to study potential roles of SPBC428.14 in stress response?

Given that many non-essential genes become critical under stress conditions, design the following experimental approaches:

• Systematic stress sensitivity assays:

  • Test SPBC428.14Δ strains under various stressors (oxidative, genotoxic, thermal, osmotic)

  • Include mycophenolic acid (MPA) treatment, which was informative for ell1Δ strains

  • Quantify growth rates, lag phases, and maximum densities

• Stress-induced relocalization:

  • Monitor localization of fluorescently-tagged SPBC428.14 before and after stress

  • Use time-lapse microscopy to track dynamic responses

• Stress-dependent interaction profiling:

  • Perform immunoprecipitation under both standard and stress conditions

  • Identify stress-specific protein interaction partners

• Conditional phenotype analysis:

  • Test genetic interactions that manifest only under stress conditions

  • Cross-reference with data showing that "ell1Δ interacts genetically with some genes only in the presence of MPA"

When interpreting results, consider that acyltransferases often function in post-translational modification systems that regulate rapid stress responses. Look for condition-specific phenotypes that might reveal the protein's functional context.

What computational approaches can predict potential functions of SPBC428.14?

Implement the following computational strategies to predict SPBC428.14 functions:

• Structural prediction and analysis:

  • Use AlphaFold2 or RoseTTAFold to generate structural models

  • Identify potential catalytic sites and substrate-binding pockets

  • Compare with known acyltransferase structures

• Network-based function prediction:

  • Construct protein-protein interaction networks incorporating known genetic interaction data

  • Apply graph theory algorithms to predict functional clusters

  • Use guilt-by-association approaches to infer function

• Evolutionary analysis:

  • Perform detailed phylogenetic analysis across species

  • Identify conserved domains and sequence motifs

  • Look for co-evolution patterns with other proteins

• Text mining and literature-based discovery:

  • Extract functional information about homologs from scientific literature

  • Identify recurring associations with biological processes or pathways

When integrating computational predictions with experimental data, establish confidence scores for predictions and prioritize validation experiments for high-confidence predictions.

How should I design gene deletion confirmation experiments for SPBC428.14?

To confirm successful deletion of SPBC428.14:

• PCR verification strategy:

  • Design primers flanking the expected deletion junction

  • Include primers within the deleted region as negative controls

  • Use primers specific to the selection marker

• Confirmation protocol:

  • Perform colony PCR using established methods

  • Verify by genomic DNA extraction and PCR

  • Sequence across junction points to confirm precise replacement

• Phenotypic verification:

  • Test selection marker resistance

  • Compare growth rates with wild-type strain

  • Verify any known phenotypes associated with deletion

Consider that the average efficiency of correct deletion in previous studies was 51%, based on analysis of 650 geneticin-resistant clones . Include appropriate controls and expect variable efficiency depending on the genomic region.

What controls should be included when studying potential roles of SPBC428.14 in transcriptional regulation?

Given the possible connection to transcriptional processes (based on other proteins in S. pombe), include these controls:

• Positive controls:

  • Include known transcriptional regulators (e.g., Ell1, Eaf1, Ebp1)

  • Use genes with well-characterized transcriptional responses

• Negative controls:

  • Include unrelated proteins with similar size/structure

  • Use genomic regions known to be transcriptionally inactive

• Specificity controls:

  • Perform rescue experiments with wild-type SPBC428.14

  • Create point mutants affecting predicted catalytic residues

  • Use heterologous complementation with orthologs

• Technical controls:

  • Normalize for cell number, growth phase, and extraction efficiency

  • Include spike-in standards for RNA-seq or ChIP-seq experiments

  • Control for antibody specificity in immunoprecipitation experiments

When analyzing results, compare the effects of SPBC428.14 deletion with those observed for known transcriptional regulators in S. pombe, looking for both similarities and differences in global expression patterns.

How can I resolve conflicts in functional data for SPBC428.14?

When confronting contradictory results:

• Systematic validation approach:

  • Replicate experiments using multiple methodologies

  • Vary experimental conditions to identify context-dependent effects

  • Use orthogonal techniques to validate findings

• Strain background considerations:

  • Verify genetic background of all strains

  • Test effects in multiple strain backgrounds

  • Check for suppressor mutations that might mask phenotypes

• Technical variable assessment:

  • Evaluate protein expression levels in tagged strains

  • Assess tag interference with protein function

  • Control for growth conditions and media composition

• Temporal and developmental analysis:

  • Examine effects across different cell cycle stages

  • Test under various developmental conditions

  • Consider acute vs. chronic loss-of-function effects

Document all experimental conditions thoroughly to facilitate troubleshooting and replication. Consider that apparent contradictions may reflect biological reality, such as context-dependent functions or redundancy mechanisms.

How should ChIP-seq data for SPBC428.14 be analyzed in the context of transcriptional regulation?

For optimal ChIP-seq analysis:

• Data processing pipeline:

  • Align reads to the S. pombe genome assembly

  • Identify enriched regions using MACS2 or similar peak-calling software

  • Normalize using appropriate input controls

• Integration with transcriptional data:

  • Compare binding sites with transcription start sites, gene bodies, and termination sites

  • Correlate binding intensity with RNA Pol II occupancy and transcript levels

  • Examine co-localization with known transcriptional regulators like Ell1, Eaf1, and Ebp1

• Motif analysis:

  • Identify enriched sequence motifs within binding regions

  • Compare with known transcription factor binding sites

  • Validate motifs using reporter assays

• Comparative analysis:

  • Compare binding patterns under different conditions

  • Analyze binding site overlap with histone modifications

  • Examine evolutionary conservation of binding sites

When interpreting results, consider that previous studies have shown transcriptional regulators like Ell1, Eaf1, and Ebp1 are co-recruited to genes and show correlation with Pol II and Cdk9 occupancy . Look for similar patterns or distinct differences that might suggest a novel regulatory role.

What statistical approaches are appropriate for analyzing genetic interaction data involving SPBC428.14?

For robust analysis of genetic interaction data:

• Quantitative scoring methods:

  • Calculate genetic interaction scores (ε) as deviation from multiplicative model

  • Apply appropriate normalization for growth rate differences

  • Use replicate measures to establish confidence intervals

• Network analysis:

  • Construct genetic interaction networks using established algorithms

  • Identify significant interaction clusters

  • Compare with existing genetic interaction maps

• Pathway enrichment:

  • Perform Gene Ontology enrichment analysis on interacting genes

  • Identify overrepresented biological processes or molecular functions

  • Compare with interactions observed for genes of known function

• Conditional dependency analysis:

  • Analyze interaction patterns across different conditions

  • Identify condition-specific interactions

  • Reference data showing that "ell1Δ interacts genetically with some genes only in the presence of MPA"

When interpreting genetic interaction data, consider both negative and positive interactions, as they provide complementary information about functional relationships. Negative genetic interactions often indicate parallel pathways, while positive interactions suggest functioning in the same pathway.

What are the recommended expression systems for recombinant SPBC428.14 production?

For optimal recombinant protein production:

• E. coli expression:

  • Use BL21(DE3) or Rosetta strains for high-level expression

  • Optimize codon usage for heterologous expression

  • Test various fusion tags (His, GST, MBP) for solubility enhancement

  • Express as a His-tagged protein as previously described

• Yeast expression systems:

  • Consider S. pombe expression for native post-translational modifications

  • Use strong inducible promoters (nmt1) with varying strength

  • Include proper targeting sequences if required

• Insect cell expression:

  • Use baculovirus expression for complex eukaryotic proteins

  • Test multiple cell lines (Sf9, High Five)

  • Optimize infection parameters for yield and activity

• Cell-free protein synthesis:

  • Test wheat germ or insect cell extracts

  • Optimize conditions for folding and activity

When selecting an expression system, consider that the full-length SPBC428.14 protein (350 amino acids) has been successfully expressed in E. coli with a His-tag , but alternative systems may be needed if studying potential post-translational modifications or if activity requires eukaryotic co-factors.

What specialized techniques can be used to study potential chromatin associations of SPBC428.14?

To investigate chromatin associations:

• Advanced ChIP protocols:

  • Implement ChIP-exo or ChIP-nexus for high-resolution binding site mapping

  • Use CUT&RUN or CUT&Tag for improved signal-to-noise ratio

  • Perform sequential ChIP to identify co-occupancy with other factors

• Chromosome conformation capture:

  • Apply Hi-C or Micro-C to examine 3D genome organization

  • Use Capture-C to focus on specific genomic regions

  • Integrate with ChIP data to correlate binding with structural changes

• Live-cell imaging:

  • Implement FRAP (Fluorescence Recovery After Photobleaching) to measure binding dynamics

  • Use single-particle tracking to monitor real-time interactions

  • Apply optogenetic tools to manipulate protein localization

• Biochemical fractionation:

  • Perform sequential extraction of chromatin-associated proteins

  • Use salt stability assays to determine binding strength

  • Couple with mass spectrometry for comprehensive identification

When designing these experiments, consider that transcriptional regulators in S. pombe such as Ell1, Eaf1, and Ebp1 have been shown to co-localize at specific genomic regions , and SPBC428.14 might follow similar patterns if involved in transcriptional processes.