KEGG: spo:SPAPB15E9.06
SPAPB15E9.06 is a putative uncharacterized transmembrane protein in Schizosaccharomyces pombe with 89 amino acids. The complete amino acid sequence is: MKLNVCFRICNFLFQFSLEFFSISSLHSISSLHSISLSLSLFFLVAILYNIYIYLFRSKKKPKRILFAIPPLCPLCSPCFFFGTSSMLL . The protein contains hydrophobic regions characteristic of transmembrane domains, particularly in the N-terminal region. The protein appears to be conserved within the Schizosaccharomyces genus, suggesting functional importance, but its exact function remains uncharacterized.
For experimental work, recombinant versions can be produced with various tags, such as His-tags, to facilitate purification and detection . The protein should be stored in Tris-based buffer with 50% glycerol at -20°C for short-term storage or -80°C for extended storage to maintain stability .
S. pombe offers several advantages as a model organism for transmembrane protein research:
It resembles human cells in terms of mitochondrial inheritance, transport mechanisms, and metabolism
The organism has conserved regulatory processes and genetic features shared with metazoans
S. pombe possesses a relatively small genome with lower redundancy compared to higher eukaryotes
As a unicellular eukaryote, it combines experimental simplicity with relevant eukaryotic cellular organization
It offers tractable genetics with well-established transformation protocols
The petite-negative phenotype makes it particularly suitable for mitochondrial membrane protein studies
Furthermore, S. pombe has significantly contributed to biomedical research on fundamental cellular processes, with powerful experimental techniques and comprehensive database resources available .
When designing experiments to study SPAPB15E9.06, follow this systematic approach:
This approach ensures logical progression while maintaining flexibility to accommodate the challenges inherent in studying uncharacterized proteins.
Several proteomics approaches can elucidate the function of uncharacterized transmembrane proteins like SPAPB15E9.06:
Comparative Proteome Analysis: This powerful approach can identify targets for protein production and secretion in S. pombe . For SPAPB15E9.06:
Compare proteome profiles between wild-type and SPAPB15E9.06 knockout/overexpression strains
Analyze changes in abundance of functionally related proteins
Look for co-regulated proteins that may function in the same pathway
Dynamic SILAC (Stable Isotope Labeling with Amino acids in Cell culture): This technique can determine protein half-lives and turnover rates :
Typical experimental setup involves culturing cells in media containing heavy isotope-labeled amino acids
Samples are collected at different time points to measure incorporation of labeled amino acids
Data analysis determines half-lives ranging from <1 to >20 days
Results can reveal whether SPAPB15E9.06 is short-lived (suggesting regulatory role) or long-lived (suggesting structural function)
Immunoprecipitation-Mass Spectrometry: This approach can identify protein interaction partners :
Create strains with tagged SPAPB15E9.06 (e.g., GFP, FLAG, or His tag)
Perform immunoprecipitation under native conditions
Analyze co-precipitated proteins by LC-MS/MS
Validate interactions with reciprocal co-IP or proximity labeling
These methods provide complementary information that collectively can reveal functional insights into this uncharacterized protein.
Several genetic strategies can help decipher the function of SPAPB15E9.06:
Synthetic Lethality Screening: This powerful approach can identify genetic interactions:
Create a strain with SPAPB15E9.06 deletion (if viable) or under regulated expression
Cross with arrays of deletion or temperature-sensitive mutants
Identify combinations that result in synthetic lethality or growth defects
Example methodology from search result :
Use plasmid shuffling with 5-FOA selection
Perform whole-genome sequencing on synthetic lethal strains
Validate candidates with complementation tests
Transcription Factor Regulatory Network Analysis: Based on the comprehensive S. pombe TF atlas :
Identify transcription factors that bind near SPAPB15E9.06 locus
Examine expression changes in TF mutant strains
Map the regulatory network controlling SPAPB15E9.06 expression
Flocculation Phenotype Analysis: As demonstrated in search result :
Test SPAPB15E9.06 deletion/overexpression for flocculation phenotypes
Perform microarray expression profiling and ChIP-chip analysis
Identify target genes and transcription factors in the regulatory network
These genetic approaches can provide valuable insights into the biological pathways and processes involving SPAPB15E9.06.
Researchers face several challenges when studying uncharacterized transmembrane proteins like SPAPB15E9.06:
Biochemical Environment Requirements:
Transmembrane proteins reside in lipid bilayers, restricting their activity to specialized biochemical environments
They represent only 20-30% of human genes but account for over half of known drug targets
The lipid membrane constitutes only 6-12% of cytosolic volume, with plasma membrane representing only 2-5% of this total
Lack of Reference Phenotypes:
Expression and Purification Difficulties:
Maintaining proper folding during recombinant expression
Need for detergents or lipid environments for solubilization
Challenges in crystallization for structural studies
Technical Approaches to Overcome These Challenges:
Protein turnover studies can reveal critical functional insights for SPAPB15E9.06:
Methodology for Dynamic SILAC:
Expected Insights from Turnover Studies:
Determine if SPAPB15E9.06 is short-lived (regulatory) or long-lived (structural)
Compare half-life in different cellular compartments
Examine turnover rates under different stress conditions
Interpretation Framework based on Known Patterns:
Membrane proteins typically show shorter half-lives (SPAPB15E9.06 would likely follow this pattern)
Mitochondrial proteins generally have longer half-lives
Receptors and signaling molecules show shorter half-lives than structural proteins
Protein half-lives correlate with function and dynamics of protein complexes
Comparative Turnover Data Analysis:
From study , protein half-lives in rat primary hippocampal cultures showed:
Protein Category | Typical Half-Life Range | Notes |
---|---|---|
Membrane proteins | Relatively shorter | Including those of plasma membrane, ER, Golgi |
Mitochondrial proteins | Significantly longer | Possibly due to unique quality control mechanisms |
Receptors (e.g., glutamate) | Shorter than population average | Enabling faster regulation |
Signaling molecules | Short-lived | Allowing fine-tuned regulation |
Energy metabolism proteins | Long-lived (12-15 days) | Reflecting steady function |
This comparative framework provides context for interpreting SPAPB15E9.06 turnover data.
Understanding the transcriptional regulation of SPAPB15E9.06 requires several complementary approaches:
Chromatin Immunoprecipitation Sequencing (ChIP-seq):
Transcription Factor Library Screening:
A comprehensive approach used in recent S. pombe research :
Systematically test a library of 89 endogenously tagged S. pombe transcription factors
Map protein and chromatin interactions
Identify transcription factors that regulate SPAPB15E9.06
Discover DNA binding motifs and regulatory networks
Expression Profiling Under Different Conditions:
Analyze SPAPB15E9.06 expression during different growth phases
Test expression under various stress conditions
Examine expression in different genetic backgrounds
Regulatory Network Mapping:
Identify potential autoregulation mechanisms
Map inhibitory feed-forward loops involving SPAPB15E9.06
Discover cross-regulation with other genes
This multi-faceted approach can establish a comprehensive understanding of when and how SPAPB15E9.06 is expressed, providing clues to its function.
Several complementary methods can be employed to identify SPAPB15E9.06 interaction partners:
Affinity Purification Coupled with Mass Spectrometry:
Express SPAPB15E9.06 with a tag (His, FLAG, or GFP)
Perform gentle lysis to maintain native interactions
Purify using affinity chromatography
Identify co-purified proteins via mass spectrometry
Validate interactions through reciprocal pull-downs
Proximity Labeling Approaches:
Create fusion proteins with BioID or APEX2
These enzymes biotinylate proteins in close proximity
Purify biotinylated proteins using streptavidin
Identify labeled proteins by mass spectrometry
This method is particularly valuable for transient interactions
Split-Reporter Systems:
Yeast two-hybrid (Y2H) screening with modified membrane protein protocols
Split-GFP or split-luciferase assays for in vivo validation
Bimolecular fluorescence complementation (BiFC) for subcellular localization
Co-localization Studies:
Use fluorescently tagged SPAPB15E9.06
Perform co-localization studies with known organelle markers
Employ super-resolution microscopy for detailed localization
For transmembrane proteins like SPAPB15E9.06, special considerations include using appropriate detergents for solubilization and considering membrane-specific interaction environments.
Undergraduate students can meaningfully contribute to research on uncharacterized proteins through several approaches:
This structured approach enables meaningful undergraduate participation while building essential research skills.
Bioinformatics offers powerful tools for predicting functions of uncharacterized proteins like SPAPB15E9.06:
Sequence-Based Analysis:
Transmembrane domain prediction using TMHMM, Phobius, or TOPCONS
Signal peptide detection with SignalP
Domain identification using InterPro or Pfam
Sequence conservation analysis across species
Motif identification for potential post-translational modifications
Structural Prediction and Analysis:
Secondary structure prediction with PSIPRED
3D structure modeling using AlphaFold2 or RoseTTAFold
Molecular dynamics simulations in membrane environments
Binding site prediction for potential ligands
Functional Inference from Networks:
Co-expression network analysis across conditions
Protein-protein interaction network integration
Phylogenetic profiling to identify functionally related proteins
Gene neighborhood analysis in related organisms
Integrated Deorphanization Strategy:
Based on search result , an effective approach includes:
Integration of experimental and bioinformatics approaches
Focused functional characterization within particular protein classes
Systematic screening with bioinformatics guidance
Landscape reference comparison across genomes
This multi-layered bioinformatics approach can generate testable hypotheses about SPAPB15E9.06 function before extensive experimental work.
As a putative transmembrane protein, SPAPB15E9.06 likely plays a role in membrane organization that could be explored through:
Membrane Domain Localization Studies:
Determine if SPAPB15E9.06 localizes to specific membrane microdomains
Analyze co-localization with lipid raft markers
Examine distribution during cell division or stress responses
Membrane Protein Turnover Analysis:
Based on search result , membrane proteins typically show distinct turnover patterns:
Membrane Location | Typical Turnover Rate | Potential Significance |
---|---|---|
Plasma membrane | Relatively short-lived | Adaptability to external signals |
ER membrane | Short to medium half-life | Quality control mechanisms |
Golgi apparatus | Short half-life | Dynamic sorting function |
Mitochondrial membrane | Longer half-life | Structural stability requirement |
Determining where SPAPB15E9.06 fits in this spectrum could provide functional insights.
Membrane Stress Response Investigation:
Test whether SPAPB15E9.06 expression changes under membrane stress
Examine phenotypes of deletion/overexpression strains under conditions like:
Osmotic stress
Lipid composition alterations
Membrane-disrupting agents
Potential Role in Specialized Membrane Functions:
Investigate involvement in membrane fusion/fission events
Examine potential roles in vesicular trafficking
Test for functions in cell wall synthesis or remodeling
These approaches can collectively reveal the membrane-related functions of this uncharacterized protein.
Understanding the evolutionary context of SPAPB15E9.06 requires systematic comparative genomics:
Ortholog Identification and Analysis:
Identify orthologs across fungal species using reciprocal BLAST
Compare conservation patterns in other Schizosaccharomyces species
Examine presence/absence patterns across evolutionary distances
Analyze selection pressure through Ka/Ks ratios
Synteny Analysis:
Examine conservation of genomic context around SPAPB15E9.06
Identify co-evolved gene clusters
Map chromosomal rearrangements affecting this locus
Structural Conservation Analysis:
Compare predicted transmembrane topologies across species
Identify conserved residues that may be functionally important
Analyze conservation of potential protein-protein interaction interfaces
Expression Pattern Evolution:
Compare regulation mechanisms across species
Identify conserved transcription factor binding sites
Analyze expression correlation patterns with known genes
This evolutionary perspective can provide crucial context for functional hypotheses and identify functionally important regions of the protein.
CRISPR-Cas9 offers powerful tools for studying SPAPB15E9.06, with specific considerations for S. pombe:
Knockout Strategy Optimization:
Design specific gRNAs targeting SPAPB15E9.06
Include controls to verify editing efficiency
Create complete gene deletion versus domain-specific mutations
Validate knockouts through sequencing and protein detection
Tagging Strategies for Functional Analysis:
C-terminal versus N-terminal tags based on predicted protein topology
Fluorescent protein fusions for localization studies
Affinity tags for interaction studies
Base editing for introducing specific mutations
Conditional Systems for Essential Gene Analysis:
If SPAPB15E9.06 proves essential, implement:
Auxin-inducible degron system
Transcriptional repression strategies
Temperature-sensitive mutants
Multiplexed Editing for Pathway Analysis:
Simultaneous editing of SPAPB15E9.06 and potential interacting partners
Creation of double/triple mutants to test genetic interactions
Systematic editing of predicted functional domains
Genome-Wide Screens:
CRISPR interference (CRISPRi) for transcriptional repression
CRISPR activation (CRISPRa) for overexpression
Pooled screens to identify genetic interactions