Recombinant Schizosaccharomyces pombe Uncharacterized protein C16E8.18 (SPAC16E8.18)

What is the molecular structure of SPAC16E8.18 protein?

SPAC16E8.18 is a 107-amino acid protein from Schizosaccharomyces pombe with Uniprot accession number O13746. The complete amino acid sequence is: MEVTSFILNATFKEFACFGNNYLIIILPGIMLERNVFRHTNYSTNSIESHYQFFGGFYESFELLVVIVYYFSHVGSFSLAEIYRITWDKRIVLYGTTTTLVYCSEGSD . As an uncharacterized protein, its three-dimensional structure has not been fully determined through crystallography or cryo-electron microscopy methods. Computational structure prediction methods would be required to generate hypothetical models of its tertiary structure based on amino acid sequence homology with proteins of known structure.

For researchers interested in structural studies, recombinant expression systems are available that provide the protein in quantities suitable for structural biology techniques. The recombinant form is typically supplied in a Tris-based buffer with 50% glycerol, optimized for protein stability .

Where is SPAC16E8.18 located within the cell?

The subcellular localization of SPAC16E8.18 has not been definitively characterized in the available literature. Determining the subcellular localization would typically involve:

• GFP-fusion experiments where the SPAC16E8.18 gene is tagged with green fluorescent protein

• Immunofluorescence studies using antibodies specific to the protein

• Subcellular fractionation followed by Western blotting

Computational prediction tools suggest potential membrane association based on the hydrophobic regions in its amino acid sequence, but experimental validation is required for confirmation.

What is currently known about the gene expression pattern of SPAC16E8.18?

Transcriptomic analysis indicates that SPAC16E8.18 exhibits interesting expression patterns during S. pombe meiosis. Of particular note is the observation of read-through transcripts that connect SPAC16E8.02 and SPAC16E8.03, with SPAC16E8.18 potentially being involved in similar transcriptional events . The read-through transcripts appear to be highly induced during the late stages of meiosis, while individual transcripts show lower expression levels .

Analysis of RNA-Seq data reveals that SPAC16E8.18 may be subject to alternative splicing events, which could generate protein isoforms with potentially distinct functions. As with many S. pombe genes, intron retention appears to be the dominant type of alternative splicing event affecting this locus, followed by "intron in exon" patterns .

What are the optimal conditions for recombinant expression of SPAC16E8.18?

For recombinant expression of SPAC16E8.18, researchers should consider the following methodological approach:

Expression System Selection:

• Prokaryotic systems (E. coli BL21(DE3)) for high yield but potential folding issues

• Eukaryotic systems (S. cerevisiae or insect cells) for better post-translational modifications

• Native S. pombe expression for authentic modifications and folding

Expression Protocol:

• Clone the full SPAC16E8.18 coding sequence (covering positions 1-107) into an appropriate expression vector with a purification tag (His, GST, or MBP)

• Transform into the chosen expression system

• Induce protein expression under optimized conditions (temperature, induction time, media composition)

• Harvest cells and lyse using appropriate buffer systems

• Purify using affinity chromatography, followed by size exclusion chromatography

• Store in Tris-based buffer with 50% glycerol at -20°C for short-term or -80°C for long-term storage

The commercially available recombinant protein is typically supplied at a concentration of 50 μg, though larger quantities can be produced for specific research applications .

What methods are most effective for studying SPAC16E8.18 function in vivo?

To investigate the function of SPAC16E8.18 in vivo, several complementary approaches can be employed:

Gene Deletion/Disruption:

• Generate a SPAC16E8.18 knockout strain using homologous recombination

• Perform phenotypic analysis under various growth conditions

• Examine effects on cell cycle, meiosis, and stress responses

Conditional Expression:

• Place SPAC16E8.18 under an inducible promoter (nmt1) for controlled expression

• Observe phenotypic consequences of overexpression or repression

Protein Tagging:

• Create C- or N-terminal tagged versions for localization and interaction studies

• Use fluorescent protein fusions for live-cell imaging

• Employ epitope tags for co-immunoprecipitation experiments

Transcriptomic Analysis:

• Perform RNA-Seq on wild-type and SPAC16E8.18 mutant strains

• Analyze differential gene expression patterns

• Identify potential regulatory networks involving SPAC16E8.18

For researchers studying the potential relationship between SPAC16E8.18 and the reported read-through transcripts with SPAC16E8.02, specialized RT-PCR approaches targeting the junction regions would be particularly valuable to validate the existence of these transcript forms in various physiological conditions .

How can I validate alternative splicing events in SPAC16E8.18?

Alternative splicing of SPAC16E8.18 can be validated using several complementary techniques:

RT-PCR Analysis:

• Design primers flanking predicted splice junctions

• Perform RT-PCR using RNA extracted from cells at different meiotic stages

• Analyze PCR products by gel electrophoresis to identify different splice variants

• Sequence the PCR products to confirm splice junction identities

Long-Read Sequencing:

• Use Oxford Nanopore or PacBio sequencing technologies for full-length transcript analysis

• Generate cDNA libraries from different meiotic stages

• Map reads to the reference genome to identify novel splice junctions

• Quantify the abundance of different isoforms

Minigene Assays:

• Create reporter constructs containing the SPAC16E8.18 gene with its introns

• Introduce mutations at predicted splice sites

• Express in S. pombe and analyze resulting transcript patterns

Based on the patterns observed in S. pombe transcriptome studies, researchers should pay particular attention to intron retention events, as these represent the dominant form of alternative splicing in this organism . The validation should be performed across different meiotic stages, as temporal regulation of alternative splicing has been documented for numerous S. pombe genes.

What computational approaches can predict SPAC16E8.18 function?

To predict the potential function of this uncharacterized protein, several bioinformatic approaches can be employed sequentially:

Sequence Homology Analysis:

• Perform BLAST searches against protein databases to identify homologs

• Compare with proteins of known function across different species

• Identify conserved domains using tools like Pfam, SMART, or InterPro

Structural Prediction:

• Generate 3D protein structure predictions using AlphaFold2 or similar tools

• Compare predicted structures with proteins of known function using tools like DALI

• Identify potential binding pockets or catalytic sites

Gene Context Analysis:

• Examine neighboring genes in the S. pombe genome

• Identify potential operons or functionally related gene clusters

• Compare with syntenic regions in related species

Co-expression Network Analysis:

• Analyze RNA-Seq datasets to identify genes co-expressed with SPAC16E8.18

• Construct gene co-expression networks

• Apply guilt-by-association approaches to predict function based on network neighbors

Table 1: Computational Tools for Functional Prediction of Uncharacterized Proteins

The relationship between SPAC16E8.18 and the reported read-through transcripts involving SPAC16E8.02 should be carefully considered when performing co-expression analyses, as this phenomenon might suggest functional relationships between these physically adjacent genes .

How can I investigate potential protein-protein interactions involving SPAC16E8.18?

To identify and characterize protein-protein interactions involving SPAC16E8.18, several complementary experimental approaches should be considered:

Co-immunoprecipitation (Co-IP):

• Express tagged SPAC16E8.18 in S. pombe

• Perform immunoprecipitation using tag-specific antibodies

• Identify co-precipitated proteins using mass spectrometry

• Validate interactions using reciprocal Co-IP

Yeast Two-Hybrid (Y2H) Screening:

• Clone SPAC16E8.18 into bait vectors

• Screen against S. pombe cDNA library

• Validate positive interactions through secondary screens

• Consider performing directed Y2H with suspected interactors

Proximity-Based Labeling:

• Create fusion proteins with BioID or APEX2 labeling enzymes

• Express in S. pombe and induce proximity labeling

• Purify biotinylated proteins and identify by mass spectrometry

• Map the proximal protein network

Crosslinking Mass Spectrometry (XL-MS):

• Apply chemical crosslinkers to S. pombe cells expressing SPAC16E8.18

• Perform protein extraction and digestion

• Enrich for crosslinked peptides

• Identify interaction partners and specific contact sites

Given the possible involvement of SPAC16E8.18 in read-through transcription events with neighboring genes, special attention should be paid to potential interactions with transcription and RNA processing machinery components . Additionally, temporal regulation during meiosis suggests that interaction studies should be performed at different meiotic stages to capture dynamic interaction patterns.

What approaches can determine if SPAC16E8.18 is essential for S. pombe survival?

To determine whether SPAC16E8.18 is essential for S. pombe viability, researchers should employ a systematic approach:

Gene Deletion Analysis:

• Generate a heterozygous diploid strain with one SPAC16E8.18 allele deleted

• Induce sporulation and perform tetrad dissection

• Analyze spore viability patterns and genotype surviving colonies

• If no haploid deletions survive, the gene is likely essential

Conditional Expression Systems:

• Replace the native promoter with a regulatable promoter (e.g., nmt1)

• Repress expression and monitor cell viability

• Observe phenotypic consequences during repression

• Document terminal phenotypes before cell death

Auxin-Inducible Degron (AID) System:

• Tag SPAC16E8.18 with an AID tag

• Express TIR1 in the same cells

• Add auxin to induce rapid protein degradation

• Monitor cellular consequences of acute protein depletion

Complementation Assays:

• In cases where deletion is lethal, test whether heterologous expression of homologs can rescue viability

• Identify critical domains through domain complementation experiments

• Engineer point mutations to identify essential residues

It's worth noting that neighboring genes SPAC16E8.02 and SPAC16E8.03 have been identified as essential for spore germination , which may suggest functional relationships if read-through transcription proves physiologically relevant.

How does SPAC16E8.18 expression change during the cell cycle and meiosis?

Analysis of SPAC16E8.18 expression throughout the cell cycle and meiosis reveals interesting regulatory patterns:

Cell Cycle Regulation:

• Synchronize S. pombe cells using standard methods (cdc25-22 block-release, lactose gradient, or elutriation)

• Collect samples at defined time points throughout the cell cycle

• Perform RT-qPCR or RNA-Seq to quantify SPAC16E8.18 mRNA levels

• Correlate expression with cell cycle phases using established markers

Meiotic Expression Profile:
Based on transcriptomic data, SPAC16E8.18 shows distinctive expression patterns during meiosis. Of particular interest is the appearance of read-through transcripts connecting SPAC16E8.18 with neighboring genes, particularly during late meiotic stages . These read-through transcripts may represent important regulatory mechanisms specific to meiotic progression.

The transcriptomic data suggests that the read-through transcript combining SPAC16E8.02 and SPAC16E8.03 (with potential involvement of SPAC16E8.18) is highly induced in late meiosis, while the individual transcripts show lower expression levels . This observation suggests a potential role in meiotic progression or spore formation, which aligns with the finding that both SPAC16E8.02 and SPAC16E8.03 are essential for spore germination .

What transcription factors regulate SPAC16E8.18 expression?

To identify transcription factors that regulate SPAC16E8.18 expression, researchers should employ a multi-faceted approach:

Promoter Analysis:

• Identify the promoter region of SPAC16E8.18 (typically 500-1000 bp upstream)

• Perform in silico analysis to identify transcription factor binding motifs

• Compare with known S. pombe transcription factor binding sites

• Prioritize factors known to be active during relevant cell states

Chromatin Immunoprecipitation (ChIP):

• Perform ChIP-seq with antibodies against suspected transcription factors

• Target factors active during meiosis or specific conditions where SPAC16E8.18 is regulated

• Analyze enrichment at the SPAC16E8.18 promoter region

• Validate binding using directed ChIP-qPCR

Reporter Assays:

• Clone the SPAC16E8.18 promoter upstream of a reporter gene

• Introduce mutations in predicted binding sites

• Measure reporter activity under different conditions

• Test the effects of transcription factor overexpression or deletion

Genetic Screens:

• Use a reporter system driven by the SPAC16E8.18 promoter

• Perform mutagenesis or deletion library screening

• Identify mutants with altered reporter expression

• Characterize the responsible regulatory factors

The expression patterns during meiosis and the formation of read-through transcripts suggest that SPAC16E8.18 may be subject to regulation by meiosis-specific transcription factors. Attention should be paid to factors like Mei4, which coordinates middle meiotic gene expression in S. pombe .

How do post-translational modifications affect SPAC16E8.18 function?

Post-translational modifications (PTMs) often play crucial roles in regulating protein function. For SPAC16E8.18, researchers should:

Identify Potential Modification Sites:

• Use computational tools to predict common PTM sites (phosphorylation, ubiquitination, etc.)

• Compare predicted sites with known modification motifs

• Look for conservation of these sites in homologs from related species

Mass Spectrometry Analysis:

• Purify SPAC16E8.18 from cells under different conditions

• Perform proteolytic digestion and LC-MS/MS analysis

• Search for modified peptides using PTM-specific parameters

• Quantify modification stoichiometry under different conditions

Site-Directed Mutagenesis:

• Generate mutant versions with modified residues replaced by non-modifiable amino acids

• Express mutants in S. pombe and assess protein function

• Compare phenotypes to wild-type protein expression

• Determine if modifications are essential for function

Modification-Specific Antibodies:

• Generate or obtain antibodies specific to predicted PTMs

• Use these for Western blotting to detect modifications

• Perform immunofluorescence to determine if modifications affect localization

• Analyze modification patterns during cell cycle or meiosis

While specific PTM information for SPAC16E8.18 is not directly provided in the search results, the meiosis-specific expression patterns suggest potential regulation by cell cycle-dependent kinases or other meiosis-specific modifying enzymes.

How conserved is SPAC16E8.18 across fungal species?

Understanding the evolutionary conservation of SPAC16E8.18 provides insights into its functional importance. A systematic approach involves:

Sequence Conservation Analysis:

• Perform BLAST searches against fungal genome databases

• Identify orthologs in related yeast species (S. cerevisiae, S. japonicus, etc.)

• Extend search to more distant fungal lineages

• Conduct multiple sequence alignment to identify conserved residues

Phylogenetic Analysis:

• Construct phylogenetic trees using aligned sequences

• Determine evolutionary relationships among homologs

• Identify potential gene duplication or loss events

• Correlate evolutionary patterns with known species phylogeny

Synteny Analysis:

• Examine genomic context of SPAC16E8.18 orthologs

• Determine if neighboring gene relationships are conserved

• Identify potential operon-like structures across species

• Correlate synteny conservation with functional relationships

Domain Architecture Comparison:

• Identify functional domains in SPAC16E8.18 and its homologs

• Compare domain organization across species

• Identify lineage-specific domain gain or loss events

• Correlate domain architecture with predicted function

The transcriptomic data suggests that novel protein isoforms are often species-specific, potentially representing evolutionary innovation . This observation suggests that alternative splicing and transcriptional read-through might contribute to species-specific adaptations, making comparative analysis particularly valuable.

What insights can be gained from comparing SPAC16E8.18 with its homologs in other organisms?

Comparative analysis of SPAC16E8.18 with its homologs provides valuable functional insights:

Functional Inference:

• Identify homologs with known functions in other organisms

• Transfer functional annotations when sequence similarity is high

• Consider partial or divergent functions when similarity is moderate

• Use structural comparisons to strengthen functional predictions

Critical Residue Identification:

• Identify strictly conserved amino acids across homologs

• Map these onto predicted structural models

• Prioritize these residues for mutational analysis

• Correlate conservation patterns with predicted functional sites

Experimental Cross-Validation:

• Test if homologs from other species can complement S. pombe mutants

• Determine if SPAC16E8.18 can complement corresponding mutants in other species

• Compare phenotypes of deletion mutants across species

• Identify shared and species-specific functions

Table 2: Comparative Analysis of SPAC16E8.18 with Selected Fungal Homologs

Note: The exact values would need to be determined through actual sequence analysis, as the search results do not provide this specific information.

The transcriptomic analysis suggests that many novel isoforms in S. pombe do not encode protein isoforms found in closely related species, which could represent "background noise" from aberrant splicing or potentially new gene functions evolving through species-specific alternative splicing .

How do expression patterns of SPAC16E8.18 orthologs differ across species?

Comparing expression patterns of SPAC16E8.18 orthologs across species can provide evolutionary insights:

Comparative Transcriptomics:

• Collect RNA-Seq data from multiple fungal species under comparable conditions

• Align orthologous genes and quantify expression levels

• Compare expression patterns during cell cycle, meiosis, and stress responses

• Identify conserved and divergent regulatory patterns

Promoter Comparison:

• Extract promoter regions of SPAC16E8.18 orthologs

• Identify conserved transcription factor binding sites

• Compare with species-specific regulatory elements

• Correlate promoter conservation with expression similarity

Alternative Splicing Comparison:

• Analyze alternative splicing patterns of orthologs across species

• Determine if similar isoforms are produced

• Identify species-specific splicing events

• Correlate splicing conservation with functional significance

Condition-Specific Expression:

• Compare expression under various stress conditions across species

• Identify shared and species-specific responses

• Determine if expression regulation has diverged while sequence remains conserved

• Link expression divergence to ecological niches of different species

The search results indicate that alternative splicing patterns in S. pombe show interesting dynamics during meiosis, with some genes switching between annotated and alternative isoforms during this process . Comparing these patterns with those in related species could reveal evolutionary conservation of these regulatory mechanisms.

How might SPAC16E8.18 be involved in read-through transcription with neighboring genes?

The search results indicate that read-through transcription involving genes in the SPAC16E8 region has been observed, suggesting potential functional implications:

Characterization of Read-Through Transcripts:

• Design RT-PCR assays targeting junction regions between adjacent genes

• Perform Northern blot analysis to visualize full-length transcripts

• Use 5' and 3' RACE to precisely map transcript boundaries

• Employ long-read sequencing to capture complete transcript structures

Functional Significance Analysis:

• Generate mutants that specifically disrupt read-through transcription

• Assess phenotypic consequences of preventing read-through

• Determine if read-through transcripts produce fusion proteins

• Investigate whether read-through is regulated under specific conditions

Mechanistic Investigation:

• Examine chromatin structure in the intergenic regions

• Identify transcription factors that promote or prevent read-through

• Investigate the role of transcription termination factors

• Assess whether RNA processing machinery recognizes read-through transcripts

Evolutionary Perspective:

• Determine if read-through transcription is conserved in related species

• Assess whether intergenic regions show signs of selection

• Investigate if read-through could lead to gene fusion events over evolutionary time

• Compare with known cases of gene fusion in other organisms

The search results specifically mention read-through transcripts for SPAC16E8.02-SPAC16E8.03, noting that the transcript "lacked the last, noncoding exon of SPAC16E8.02, which theoretically leads to an in-frame fusion of the two ORFs" . This suggests a potential mechanism for generating novel protein functions. The transcript was "highly induced at the late stage of meiosis but individual transcripts were low" , indicating specific regulation during meiotic progression.

What methodological approaches are most effective for studying alternative splicing of SPAC16E8.18?

Analysis of alternative splicing requires specialized approaches:

Isoform-Specific RT-PCR:

• Design primers that specifically amplify different splice variants

• Optimize PCR conditions for specificity and sensitivity

• Use quantitative RT-PCR to measure relative isoform abundance

• Validate results with Sanger sequencing of PCR products

Next-Generation Sequencing Approaches:

• Perform RNA-Seq with sufficient depth to capture low-abundance isoforms

• Use long-read sequencing (PacBio, Nanopore) to identify full-length transcripts

• Implement specialized bioinformatic pipelines for isoform detection and quantification

• Validate computational predictions with targeted experiments

Minigene Splicing Assays:

• Clone genomic fragments containing SPAC16E8.18 exons and introns

• Introduce mutations at splice sites or potential regulatory elements

• Express in S. pombe and analyze resulting splice patterns

• Identify cis-regulatory elements controlling alternative splicing

Splicing Factor Manipulation:

• Overexpress or deplete known splicing factors

• Examine effects on SPAC16E8.18 splicing patterns

• Perform RNA immunoprecipitation to identify direct interactions

• Create a map of splicing factor binding sites within the gene

According to the search results, S. pombe exhibits various types of alternative splicing, with intron retention being the dominant type . For SPAC16E8.18, researchers should pay particular attention to this pattern while also investigating other forms of alternative splicing. The search results also indicate that some novel isoforms show distinct temporal patterns compared to annotated isoforms , suggesting that temporal regulation of splicing during meiosis could be particularly important for SPAC16E8.18 function.

How can structured visual analysis methods be applied to SPAC16E8.18 expression data?

Structured visual analysis methods can enhance interpretation of complex expression data:

Application of Structured Visual Analysis:

• Implement systematic approaches to graph interpretation

• Establish clear criteria for analyzing expression patterns

• Use standardized visual representations of data

• Apply consistent interpretation methods across experiments

Time-Series Visualization Techniques:

• Create heatmaps showing expression across meiotic time points

• Generate line plots tracking isoform abundance over time

• Implement ribbon plots to visualize changing proportions of isoforms

• Use statistical methods to identify significant expression changes

Comparative Visualization Approaches:

• Develop parallel plots comparing expression in different genetic backgrounds

• Create scatter plots to identify co-regulated genes

• Implement network visualizations showing gene regulatory relationships

• Use dimensionality reduction techniques to identify expression patterns

Integration with Other Data Types:

• Combine expression data with chromatin state information

• Correlate expression patterns with protein-protein interaction networks

• Integrate with phenotypic data from mutant strains

• Develop multi-layered visualizations that incorporate diverse data types

According to search result , structured visual analysis is "the primary method used to interpret single-case experimental design (SCED) data in applied behavior analysis" and technological advancements have been developed to address inconsistent interpretations of data . These principles can be applied to expression data for SPAC16E8.18, particularly when analyzing complex patterns of alternative splicing and read-through transcription events.

The search results indicate that some novel isoforms showed "distinct temporal patterns compared to the corresponding annotated isoforms" , suggesting that careful visual analysis of temporal expression data is crucial for understanding the regulation of SPAC16E8.18 and its potential role during meiosis.