Recombinant Schizosaccharomyces pombe Putative uncharacterized transmembrane protein C1235.17 (SPCC1235.17)

What is SPCC1235.17 and what are its basic structural characteristics?

SPCC1235.17 is a putative uncharacterized transmembrane protein in Schizosaccharomyces pombe. It is a relatively small protein with a full length of 150 amino acids and contains transmembrane domains . As a recombinant protein, it is typically produced with a His-tag to facilitate purification and subsequent studies. Like many membrane proteins in S. pombe, SPCC1235.17 likely plays a role in cellular processes that involve the membrane architecture, though its specific function remains to be elucidated.

The protein can be produced recombinantly in expression systems such as E. coli, as evidenced by available products:

How should I design experiments to investigate the expression pattern of SPCC1235.17 during different growth phases and conditions?

To investigate SPCC1235.17 expression patterns:

• Temporal expression analysis: Use Northern blotting with gene-specific PCR-generated fragments as probes, as described in published S. pombe studies. RNA should be prepared with phenol:chloroform and resolved on a 1.2% agarose gel containing 6.7% formaldehyde in MOPS buffer .

• RNA-seq approach: For more comprehensive analysis, implement RNA-seq as described in the MultiRNAflow package methodology. This allows temporal expression analysis across different conditions:

  • Extract total RNA using standard hot-phenol procedure

  • Add ERCC RNA Spike-In for normalization

  • Deplete rRNAs using the RiboMinus Eukaryote System

  • Prepare strand-specific total RNA-Seq libraries

  • Perform paired-end sequencing (2 × 50 nt)

• Analysis of expression data: Use the R package MultiRNAflow for integrated analysis of temporal transcriptomic data, which provides functions for:

  • Data normalization with DATAnormalization()

  • Factorial analysis with PCAanalysis() and HCPCanalysis()

  • Temporal clustering with MFUZZanalysis()

  • Gene expression profile visualization with DATAplotExpressionGenes()

This multiparametric approach will provide insights into when and under what conditions SPCC1235.17 is expressed, potentially revealing clues about its biological function.

How can I create stable integration of tagged SPCC1235.17 for localization studies?

For stable integration of tagged SPCC1235.17, use the following methodological approach:

• Vector selection: Use stable integration vectors (SIVs) that produce non-repetitive, stable genomic loci as described by recent S. pombe research:

  • These vectors integrate predominantly as single copy

  • They prevent false-positive integration events

  • They avoid the instability issues seen with vectors that create repetitive genomic regions

• C-terminal tagging strategy:

  • Create fusion constructs by transforming a pFA6a integration cassette

  • Use gene-specific primers for insertion at the 3' end of SPCC1235.17

  • Select appropriate fluorophores (e.g., mMaple3, GFP) based on experimental needs

• N-terminal tagging strategy (if SPCC1235.17 is non-essential):

  • Assemble a construct containing:

    • 500 bp 5' flank of SPCC1235.17

    • Fluorophore (mMaple3/GFP) with a GGGGSGGGGSG C-terminal linker

    • SPCC1235.17 coding sequence

    • 500 bp 3' flank

  • Transform into a ura4+ deletion strain of SPCC1235.17

• Verification of localization:

  • Use fluorescence microscopy for live cell imaging

  • For higher resolution, employ super-resolution microscopy as used in recent S. pombe studies

  • Use immunogold electron microscopy for precise subcellular localization

This approach ensures stable expression of tagged SPCC1235.17 while maintaining its native regulation and function.

What methods should I use to identify potential binding partners of SPCC1235.17?

To identify binding partners of SPCC1235.17, employ multiple complementary approaches:

• Immunoprecipitation coupled with mass spectrometry (IP-MS):

  • Use the tagged version of SPCC1235.17 (His-tagged or fluorophore-tagged)

  • Perform cell lysis under conditions that preserve membrane protein interactions

  • Immunoprecipitate with antibodies against the tag

  • Analyze co-precipitated proteins by mass spectrometry

• Yeast two-hybrid (Y2H) screening:

  • Generate bait constructs with SPCC1235.17 fragments that exclude transmembrane domains

  • Screen against an S. pombe cDNA library

  • Validate potential interactions through reciprocal Y2H assays

• Proximity-based labeling:

  • Create a fusion protein with SPCC1235.17 and a proximity-dependent labeling enzyme (BioID or APEX2)

  • Express in S. pombe to biotinylate nearby proteins

  • Purify biotinylated proteins and identify by mass spectrometry

• Genetic interaction screening:

  • Cross SPCC1235.17 mutants with a collection of S. pombe deletion mutants

  • Analyze genetic interactions through growth phenotypes

  • Identify synthetic lethal or suppressor interactions that suggest functional relationships

Document all identified interactions in a format similar to this table:

How can I determine if SPCC1235.17 is involved in cell wall integrity or membrane function?

Given its transmembrane nature, SPCC1235.17 might play a role in cell wall integrity or membrane function. To investigate this:

• Phenotypic analysis of mutants:

  • Test sensitivity to cell wall stressors (Calcofluor White, Congo Red)

  • Examine resistance to cell membrane disruptors (SDS, detergents)

  • Analyze growth under osmotic stress conditions (sorbitol, NaCl)

• Cell wall composition analysis:

  • Stain with Aniline blue to visualize β-1,3-glucan distribution

  • Examine β-1,6-glucan using specific antibodies

  • Investigate if SPCC1235.17 depletion affects glucan partitioning in the septum and lateral cell wall, similar to methods used for other S. pombe transmembrane proteins

• Genetic interaction analysis:

  • Test for genetic interactions with known cell wall synthesis genes

  • Look for interactions with β-1,6-glucanase family members

  • Document interactions similar to this described approach:

  "sup11+ interacts genetically with β-1,6-glucanase family members"

• Transcriptomic analysis:

  • Perform RNA-seq on SPCC1235.17 mutants vs. wild-type

  • Look for differential expression of cell wall-related genes

  • Analyze if "oligosaccharide catabolic processes, cell wall proteins, and the septum separation pathway" are affected at the transcriptional level

What approaches can detect and analyze microhomology-mediated tandem duplications (MTDs) that might affect SPCC1235.17 expression or function?

Microhomology-mediated tandem duplications (MTDs) may affect SPCC1235.17 expression or function. To investigate this:

• Computational detection of potential MTDs:

  • Identify all microhomology pairs (MHPs) in SPCC1235.17 and flanking regions

  • Generate "signatures" for sequences that would be created by each possible MTD

  • Match these signatures against sequencing reads to detect subclonal MTDs

• High-coverage sequencing for MTD detection:

  • Perform high-coverage (10,000×) whole-genome sequencing

  • Apply computational pipeline to detect subclonal MTDs

  • Follow this methodology:

  "This method first identifies all MHPs in a DNA segment or genome and generates 'signatures' for sequences that would be created by each possible MTD. It then identifies sequencing reads that match these signatures, and thus provides experimental support for the existence of a particular MTD within the population"

• Experimental validation of MTDs:

  • Design PCR primers flanking potential MTD sites

  • Perform statistical analysis to distinguish true MTDs from technical artifacts

  • Test whether MTDs are specific to genomic DNA by comparing with chemically synthesized DNA

• Analysis of factors affecting MTD frequency:

  • Investigate the role of DNA repair genes

  • Test strains with mutations in DNA replication, repair, recombination or chromatin organization genes

  • Screen for mutants that affect the rate of MTD formation/reversion

  • Pay particular attention to homologous recombination genes (Rad50, Rad52, Ctp1)

How should I design experiments to resolve contradictory data about SPCC1235.17 subcellular localization?

When facing contradictory data about SPCC1235.17 subcellular localization:

• Multi-method localization approach:

  • Implement fluorescence microscopy with different tagging strategies (N- and C-terminal)

  • Use immunofluorescence with methanol fixation for preserved membrane structures

  • Employ immunogold electron microscopy for high-resolution localization

  • Perform cellular fractionation via sucrose density gradient centrifugation

• Control experiments to validate tag functionality:

  • Ensure tagged proteins complement knockout phenotypes

  • Test multiple fluorophores to rule out tag-specific artifacts

  • Implement proteinase K protection assays to determine membrane topology

• Co-localization studies:

  • Use established organelle markers in co-localization experiments

  • Employ super-resolution microscopy to determine precise spatial organization

  • Create a nanoscale map of protein localization relative to the plasma membrane:

  "Similar to other membrane-tethered actin structures, we find proteins localize in specific layers relative to the membrane. The most membrane-proximal layer (0–80 nm) is composed of membrane-binding scaffolds..."

• Dynamic localization analysis:

  • Track protein localization through the cell cycle

  • Monitor changes during specific stress conditions

  • Analyze temporal changes during septum formation and cell division

This multi-faceted approach helps resolve contradictions by distinguishing between technical artifacts and biologically meaningful localization patterns.

What are the best practices for analyzing RNA-seq data to study transcriptional changes related to SPCC1235.17 function?

For robust RNA-seq analysis of SPCC1235.17-related transcriptional changes:

• Experimental design:

  • Include biological replicates (minimum 3 per condition)

  • Use spike-in controls for normalization (e.g., ERCC RNA Spike-In)

  • Consider time-course experiments to capture dynamic responses

  • Include both wild-type and SPCC1235.17 mutant samples

• Data processing pipeline:

  • Align reads to the S. pombe genome (ASM294v2.28) using TopHat or Bowtie2

  • Filter for properly aligned pairs

  • Normalize data accounting for spike-in controls

  • Use DESeq2 for differential expression analysis with manual normalization to spike-in counts

• Advanced analysis approaches:

  • Implement temporal differential expression analysis using MultiRNAflow:

    • Normalization with DATAnormalization()

    • Exploratory analysis with PCAanalysis() and HCPCanalysis()

    • Temporal clustering with MFUZZanalysis()

    • Gene expression visualization with DATAplotExpressionGenes()

• Functional interpretation:

  • Perform Gene Ontology enrichment analysis using gprofiler2

  • Generate outputs compatible with additional tools:

    • DAVID, Webgestalt, GSEA, gProfiler, Panther, ShinyGO, Enrichr, and GOrilla

  • Focus on pathways potentially related to SPCC1235.17 function

This methodology allows for comprehensive characterization of transcriptional changes associated with SPCC1235.17 function or dysfunction.

What are the optimal conditions for expression and purification of recombinant SPCC1235.17?

For optimal expression and purification of recombinant SPCC1235.17:

• Expression system selection:

  • E. coli is the documented successful host for recombinant SPCC1235.17 expression

  • Consider testing multiple expression strains optimized for membrane proteins

  • For native-like conditions, evaluate S. pombe expression using nmt1 promoter-based vectors:

    • Strong expression: full strength nmt1 promoter

    • Moderate expression: nmt41 promoter

    • Weak expression: nmt81 promoter

• Optimization of expression conditions:

  • If using E. coli:

    • Test induction temperatures (16°C, 25°C, 30°C)

    • Optimize inducer concentration and induction time

    • Consider additives that stabilize membrane proteins (glycerol, specific detergents)

  • If using S. pombe with nmt1 promoter system:

    • Control expression by thiamine concentration in the media

    • Grow in Edinburgh minimal medium (EMM) lacking thiamine to induce expression

• Purification strategy:

  • Use His-tag affinity purification as the initial capture step

  • Implement size exclusion chromatography for further purification

  • Consider detergent screening for optimal solubilization:

    • Test mild detergents (DDM, LMNG) for function preservation

    • Use stronger detergents (SDS, Triton X-100) if only structural studies are planned

• Quality control:

  • Verify protein purity by SDS-PAGE

  • Confirm identity by mass spectrometry

  • Assess protein folding by circular dichroism

  • Evaluate oligomeric state by size exclusion chromatography

This comprehensive approach optimizes the production of functional recombinant SPCC1235.17 for subsequent structural and functional studies.

How can I design experiments to determine if SPCC1235.17 undergoes post-translational modifications?

To investigate post-translational modifications (PTMs) of SPCC1235.17:

• Mass spectrometry-based PTM mapping:

  • Purify recombinant SPCC1235.17 or immunoprecipitate from S. pombe

  • Perform tryptic digestion for peptide generation

  • Implement LC-MS/MS analysis with PTM-specific detection methods

  • Look for common modifications: phosphorylation, glycosylation, acetylation, ubiquitination

• Glycosylation analysis (particularly relevant for transmembrane proteins):

  • Test for N-linked glycosylation with EndoH treatment

    • "EndoH treatment" is a documented method for S. pombe glycoproteins

  • Investigate O-mannosylation, a common modification in S. pombe

    • Note that "sup11+ is a multicopy-suppressor of a conditionally lethal O-mannosylation mutant"

  • Use PAS-Silver staining to detect glycoproteins

• Phosphorylation studies:

  • Use phospho-specific antibodies for Western blotting

  • Implement Phos-tag SDS-PAGE for mobility shift detection

  • Consider kinase inhibitor treatments to identify responsible kinases

• Site-directed mutagenesis:

  • Identify potential modification sites through bioinformatic prediction

  • Generate mutants (S/T/Y to A for phosphorylation; N/S/T to A for glycosylation)

  • Test functional consequences of preventing specific modifications

This methodical approach will provide comprehensive insights into the post-translational modification landscape of SPCC1235.17 and its functional significance.