SPAC23A1.09 Antibody

What is SPAC23A1.09 and why is it significant in research?

SPAC23A1.09 encodes the fission yeast (Schizosaccharomyces pombe) ortholog of Y14, also known as RNA-binding protein 8, which functions as a core component of the exon junction complex (EJC) . This protein plays critical roles in RNA metabolism, particularly in splicing regulation and mRNA surveillance pathways. It's significant because studying this ortholog provides insights into evolutionarily conserved RNA processing mechanisms applicable to higher eukaryotes.

The protein contains RNA recognition motifs (RRMs) that enable specific binding to RNA substrates, participating in the post-transcriptional regulation network essential for proper gene expression . Research indicates it associates with other RNA-binding proteins in multi-protein complexes that coordinate RNA processing events.

What are the recommended protocols for validating SPAC23A1.09 antibody specificity?

A multi-step validation approach is essential to confirm antibody specificity:

• Genetic controls: Compare antibody reactivity between wild-type and SPAC23A1.09 deletion strains (SPAC23A1.09Δ) . The complete absence of signal in deletion strains confirms specificity.

• Epitope-tagged controls: Generate strains expressing SPAC23A1.09 with C-terminal epitope tags (e.g., MYC, FLAG, or FTP) and verify co-detection with both anti-tag and anti-SPAC23A1.09 antibodies.

• Western blot analysis: Perform immunoblotting with appropriate controls to determine:

  • Expected molecular weight detection

  • Absence of non-specific bands

  • Signal intensity correlation with expression levels

• Cross-reactivity assessment: Test antibody against closely related proteins, particularly other RNA-binding proteins with similar domains .

This systematic approach should be documented with representative blots showing control samples alongside experimental samples to demonstrate specificity conclusively.

How should co-immunoprecipitation (Co-IP) experiments be designed to study SPAC23A1.09 protein interactions?

For robust Co-IP experiments with SPAC23A1.09 antibodies, follow this optimized protocol based on published methods :

Sample preparation:

• Harvest 50-100 mL of exponentially growing S. pombe culture (OD₆₀₀ = 0.5-0.8)

• Wash cells twice with cold PBS

• Lyse cells in immunoprecipitation buffer (50 mM HEPES pH 7.5, 150 mM NaCl, 1 mM EDTA, 1% Triton X-100, 0.1% NP-40) supplemented with protease inhibitors and phosphatase inhibitors

• Sonicate briefly (3 × 10 s pulses) to shear chromatin

• Clear lysate by centrifugation at 14,000 × g for 15 minutes at 4°C

Immunoprecipitation:

• Pre-clear lysate with protein A/G beads for 1 hour at 4°C

• Incubate pre-cleared lysate with SPAC23A1.09 antibody (5-10 μg) overnight at 4°C with gentle rotation

• Add protein A/G beads and incubate for 2-3 hours at 4°C

• Wash beads 5 times with IP buffer

• Elute proteins with SDS sample buffer and analyze by immunoblotting

Critical controls:

• Input sample (5-10% of total lysate)

• IgG control antibody immunoprecipitation

• Immunoprecipitation from SPAC23A1.09Δ strain

This protocol has successfully demonstrated interaction between SPAC23A1.09 (Y14) and other EJC components like pFal1 .

What approaches can resolve challenges in detecting low-abundance SPAC23A1.09 interactions?

When studying low-abundance interactions, several methodologies can enhance detection sensitivity:

• Cross-linking assisted immunoprecipitation:

  • Treat cells with 1% formaldehyde for 10 minutes at room temperature before lysis

  • Quench with 125 mM glycine for 5 minutes

  • This stabilizes transient interactions that might be lost during conventional Co-IP

• Tandem affinity purification:

  • Generate strains expressing SPAC23A1.09 with dual tags (e.g., TAP-tag or FLAG-HA)

  • Perform sequential purification steps to reduce background

  • This approach successfully identified interactions between Red5-FTP and SPAC23A1.09

• Proximity-dependent labeling:

  • Fuse SPAC23A1.09 to a promiscuous biotin ligase (BioID)

  • Identify proximal proteins through streptavidin purification and mass spectrometry

  • Particularly useful for detecting weak or transient interactions

• RNA-dependent considerations:

  • Perform parallel experiments with and without RNase treatment

  • This distinguishes direct protein-protein interactions from RNA-mediated associations

These approaches have successfully resolved complex interaction networks involving SPAC23A1.09 in the context of splicing and RNA processing machinery .

How can researchers assess the role of SPAC23A1.09 in splicing regulation through antibody-based techniques?

Investigating SPAC23A1.09's splicing regulatory function requires integrating antibody-based techniques with splicing analysis:

Chromatin immunoprecipitation followed by sequencing (ChIP-seq):

• Cross-link cells with 1% formaldehyde

• Sonicate chromatin to 200-500 bp fragments

• Immunoprecipitate with SPAC23A1.09 antibody

• Sequence pulled-down DNA

• Analyze data to identify genomic binding sites, particularly near splice junctions

Individual-nucleotide resolution crosslinking and immunoprecipitation (iCLIP):

• UV-crosslink cells (254 nm, 150 mJ/cm²)

• Immunoprecipitate SPAC23A1.09-RNA complexes

• Partially digest RNA and attach adapters

• Sequence and map binding sites at nucleotide resolution

Functional splicing assays:

• Generate SPAC23A1.09 depletion or knockout cells

• Perform RNA-seq to identify mis-spliced transcripts

• Compare with known splicing patterns

• Validate specific targets by RT-PCR across exon-exon junctions

Research has demonstrated that SPAC23A1.09 and related EJC components affect splicing of introns with suboptimal splicing signals, particularly in meiotic transcripts . For example, studies using similar approaches on related splicing factors showed that phosphorylation of splicing factors by Dsk1 (SR protein kinase) affects splicing of nonconsensus introns .

What are the experimental considerations when using SPAC23A1.09 antibodies for flow cytometry applications?

When adapting SPAC23A1.09 antibodies for flow cytometry, consider these critical parameters:

Cell preparation:

• Fix cells with 4% paraformaldehyde for 15 minutes

• Permeabilize with 0.1% Triton X-100 for intracellular staining

• Block with 3% BSA in PBS for 30 minutes

Antibody optimization:

• Titrate antibody concentrations (typically 1-10 μg/mL)

• Include appropriate isotype controls

• Perform parallel validation with known positive and negative controls (e.g., wild-type vs. SPAC23A1.09Δ)

Fluorophore selection:

• PE conjugation provides high sensitivity for low-abundance proteins (similar to conjugates used in other antibody applications)

• Consider spectral overlap when designing multi-parameter panels

Gating strategy:

• Use forward/side scatter to identify intact cells

• Apply dead cell exclusion dye (e.g., DAPI or 7-AAD)

• Gate on specific cell cycle phases if protein expression varies with cell cycle

While flow cytometry is less commonly used for yeast studies than mammalian systems, it can provide quantitative data about protein expression levels across populations and correlate with cell cycle phases or other cellular parameters.

What strategies can overcome non-specific binding issues with SPAC23A1.09 antibodies?

Non-specific binding is a common challenge with antibodies against RNA-binding proteins. These methodological refinements can enhance specificity:

Buffer optimization:

• Increase salt concentration (150-500 mM NaCl) to reduce electrostatic interactions

• Add competing agents like 0.1-0.5% BSA to reduce non-specific binding

• Include 0.1-0.5% NP-40 or Triton X-100 to reduce hydrophobic interactions

• Test different detergents (CHAPS, Brij-35) that may preserve specific interactions while reducing non-specific binding

Pre-adsorption protocol:

• Incubate antibody with lysate from SPAC23A1.09Δ strain for 2 hours at 4°C

• Remove complexes by centrifugation

• Use pre-adsorbed antibody in experiments

Cross-reactivity analysis:

RNase treatment:

• Include parallel samples with RNase A/T1 treatment to distinguish RNA-dependent interactions

• This is particularly important when investigating RNA-binding proteins within complexes

These approaches have been successfully employed in studies of RBP complexes in fission yeast, including those involving SPAC23A1.09 and related proteins .

How should researchers interpret conflicting results between antibody-based and genetic approaches to SPAC23A1.09 function?

When antibody-based experiments yield results that differ from genetic approaches (deletion, mutation, or tagging), consider these methodological explanations and resolution strategies:

Potential causes of discrepancies:

• Antibody epitope interference with protein function:

  • The antibody may bind to functionally critical domains

  • Solution: Map the epitope and use alternative antibodies targeting different regions

• Genetic compensation mechanisms:

  • Deletion strains may activate compensatory pathways absent in antibody inhibition

  • Solution: Use acute depletion systems (e.g., auxin-inducible degron) for comparison

• Partial functionality of modified proteins:

  • Tagged versions may retain partial function

  • Solution: Position tags at different locations and validate functionality of each construct

• Complex-specific epitope masking:

  • Antibody epitopes may be occluded in certain protein complexes

  • Solution: Use multiple antibodies targeting different epitopes

Resolution approach:

• Compare phenotypes between genetic deletion, antibody inhibition, and epitope tagging

• Perform rescue experiments with wild-type and mutant proteins

• Integrate results with orthogonal approaches (e.g., mass spectrometry, functional assays)

• Consider performing time-resolved experiments to detect transient effects

For example, research on RNA-binding proteins like SPAC23A1.09 showed that genetic approaches identified it as essential for proper meiotic gene expression , while antibody-based approaches helped elucidate its physical interactions with other EJC components. When findings differ, correlating results with functional outcomes can resolve discrepancies.

How can SPAC23A1.09 antibodies be employed to investigate its role in nonsense-mediated decay (NMD)?

SPAC23A1.09 (Y14) is implicated in nonsense-mediated decay (NMD) through its function in the EJC. These antibody-based approaches can elucidate its specific contributions:

RNA immunoprecipitation (RIP) protocol:

• Cross-link cells with 1% formaldehyde for 10 minutes

• Lyse cells and sonicate to shear chromatin

• Immunoprecipitate with SPAC23A1.09 antibody

• Isolate bound RNA and analyze by RT-qPCR or sequencing

• Identify transcripts associated with SPAC23A1.09

Pulse-chase RNA decay assay:

• Inhibit transcription with 1,10-phenanthroline or thiolutin

• Collect samples at time points (0, 15, 30, 60 min)

• Extract RNA and analyze specific transcript levels by RT-qPCR

• Compare decay rates in wild-type versus SPAC23A1.09-depleted cells

Polysome profiling with immunoblotting:

• Prepare cell lysates in polysome buffer (10 mM Tris-HCl pH 7.5, 100 mM NaCl, 30 mM MgCl₂, 100 μg/mL cycloheximide)

• Separate polysomes on 10-50% sucrose gradients

• Collect fractions and analyze by immunoblotting with SPAC23A1.09 antibody

• Determine association with translating ribosomes

Studies of SPAC23A1.09's orthologs in other organisms have shown that Y14 participates in marking transcripts for NMD . In fission yeast, analyzing the interaction between SPAC23A1.09 and other proteins involved in RNA surveillance could reveal conserved and divergent aspects of NMD mechanisms.

What are the technical considerations for using SPAC23A1.09 antibodies in analyzing post-translational modifications?

Post-translational modifications (PTMs) of SPAC23A1.09 likely regulate its function in RNA processing. These specialized approaches can characterize PTMs:

Phosphorylation analysis:

• Immunoprecipitate SPAC23A1.09 under phosphorylation-preserving conditions (phosphatase inhibitors)

• Treat parallel samples with λ-phosphatase

• Analyze migration patterns by Phos-tag or standard SDS-PAGE

• Detect with SPAC23A1.09 antibody

Studies on related SR proteins (Srp1, Srp2) showed that phosphorylation by Dsk1 affects their function in splicing regulation , suggesting SPAC23A1.09 may be similarly regulated.

PTM-specific detection:

• Use antibodies against common PTMs (phospho-serine/threonine, ubiquitin) after SPAC23A1.09 immunoprecipitation

• Alternatively, perform tandem immunoprecipitation with SPAC23A1.09 antibody followed by PTM-specific antibody

Mass spectrometry identification:

• Large-scale immunoprecipitation with SPAC23A1.09 antibody

• Separate by SDS-PAGE and excise bands

• Perform in-gel digestion and LC-MS/MS analysis

• Search for PTMs in the resulting peptides

The SCF ubiquitin ligase has been implicated in regulating RNA metabolism proteins in fission yeast , suggesting SPAC23A1.09 may be subject to ubiquitination as a regulatory mechanism.

How can machine learning approaches be integrated with SPAC23A1.09 antibody data to predict protein-RNA interactions?

Combining antibody-derived experimental data with computational approaches offers new insights into SPAC23A1.09 function:

Integrated prediction workflow:

• Generate RIP-seq or CLIP-seq data using SPAC23A1.09 antibodies

• Extract sequence and structural features from bound RNA regions

• Train machine learning models (Random Forest, CNN, etc.) on these features

• Validate predictions with targeted mutagenesis and binding assays

This approach mirrors methods used successfully for designing antibodies targeting SARS-CoV-2 receptor binding domains , which integrated machine learning with experimental validation.

Key features for model training:

• RNA sequence motifs

• Secondary structure elements

• Conservation across species

• Proximity to splice sites or other regulatory elements

Performance metrics:

By integrating experimental data from antibody-based studies with machine learning, researchers can develop predictive models for SPAC23A1.09 binding preferences and regulatory functions.

What considerations should researchers take when designing novel antibody-based approaches to study SPAC23A1.09 in dynamic cellular processes?

Investigating SPAC23A1.09's role in dynamic processes requires specialized antibody applications:

Live-cell antibody fragment imaging:

• Generate and validate single-chain variable fragments (scFvs) from SPAC23A1.09 antibodies

• Fuse to fluorescent proteins

• Express in fission yeast cells

• Perform time-lapse microscopy to track SPAC23A1.09 localization during cellular processes

Proximity labeling with antibody-guided approach:

• Conjugate SPAC23A1.09 antibody to a promiscuous biotin ligase (TurboID)

• Introduce into permeabilized cells

• Add biotin for short pulses (10 minutes)

• Identify biotinylated proteins by streptavidin pulldown and mass spectrometry

• Map dynamic interaction networks under different conditions

Cell cycle analysis:

• Synchronize cells by centrifugal elutriation or chemical block-release

• Collect samples at defined cell cycle stages

• Perform immunoprecipitation with SPAC23A1.09 antibody

• Identify stage-specific protein interactions or RNA targets

These approaches can reveal how SPAC23A1.09's interactions and functions change during processes like cell division, stress response, or meiotic differentiation.