The provided sources focus on:
SPA17 (sperm autoantigenic protein 17), a cancer-testis antigen with prognostic and immunotherapeutic implications .
No direct mention of "SPAC17A2.14 Antibody" was found.
Typographical Error: The name "SPAC17A2.14" may be a misspelling of a known antibody (e.g., SPA17-specific antibodies studied in cancer research) .
Novel Compound: If "SPAC17A2.14" refers to a newly developed antibody, it may not yet be documented in publicly available databases.
Without additional context, the following assumptions must be made:
Target Antigen: If SPAC17A2.14 targets SPA17, it could be part of ongoing studies on cancer immunotherapy biomarkers.
Function: Antibodies targeting SPA17 might inhibit tumor growth or enhance immune responses, as implied by SPA17’s role in immune checkpoint therapy .
To address the query fully, further details are required:
Clarify the antibody’s target antigen.
Provide specific study references or manufacturers.
Confirm if "SPAC17A2.14" is part of a proprietary or unpublished dataset.
Until more information is available, a comprehensive analysis of this compound remains impossible.
KEGG: spo:SPAC17A2.14
STRING: 4896.SPAC17A2.14.1
The SPAC17A2.14 antibody is a polyclonal antibody raised in rabbits against the SPAC17A2.14 protein from Schizosaccharomyces pombe (fission yeast, strain 972/24843). This antibody targets a putative metal ion transporter from the CorA family of magnesium ion transporters . The protein is also referred to by alternative names including "C17A12.14" and "SPAC17G6.01" in some databases. It specifically recognizes epitopes of this transmembrane protein involved in magnesium ion transport across cellular membranes.
The SPAC17A2.14 antibody has been validated for:
ELISA (Enzyme-Linked Immunosorbent Assay) for quantitative detection
When using this antibody for research applications, it's important to confirm proper identification of the antigen. Unlike antibodies against common mammalian targets like CD3 or cytokeratin, which have extensive validation data across multiple applications , specialized yeast protein antibodies may require additional optimization steps for each application.
Optimizing Western blot protocols for SPAC17A2.14 antibody requires:
Sample preparation considerations:
Use specialized yeast lysis buffers containing protease inhibitors
Include detergents appropriate for membrane proteins (e.g., 1% Triton X-100)
Consider glass bead disruption methods for efficient yeast cell wall breakage
Blotting parameters:
Transfer using standard PVDF membranes (0.45 μm pore size)
Block with 5% non-fat milk or BSA in TBST
Initial antibody dilution: 1:500-1:1000 (optimize as needed)
Secondary antibody: Anti-rabbit IgG HRP conjugate at 1:5000 dilution
Detection optimization:
Extended exposure times may be required (2-15 minutes)
Consider enhanced chemiluminescence detection systems
Validate with appropriate positive controls from S. pombe lysates
Unlike widely-used antibodies that have standardized protocols , specialized yeast antibodies require empirical optimization for each laboratory setting.
Validating antibody specificity using genetic approaches is critical for less commonly used research antibodies. For SPAC17A2.14:
Generate validation controls:
Use CRISPR-Cas9 or homologous recombination to create SPAC17A2.14 knockout strains
Alternatively, use temperature-sensitive mutants if the gene is essential
Create epitope-tagged versions (HA, FLAG, etc.) for parallel validation
Perform comparative analyses:
| Sample Type | Expected Western Blot Result | ELISA Signal | Notes |
|---|---|---|---|
| Wild-type S. pombe | Band at ~45 kDa | High signal | Positive control |
| ΔSPAC17A2.14 strain | No specific band | Background only | Negative control |
| Tagged SPAC17A2.14 | Size-shifted band | High signal | Confirmatory control |
Cross-reactivity assessment:
Test against closely related CorA family transporters
Evaluate potential cross-reactivity with S. cerevisiae homologs
This validation approach mirrors knockout validation techniques used for commercial antibodies like those against cytokeratin 14, which employ KRT14 knockout cell lines .
Non-specific binding is a common challenge with polyclonal antibodies against lesser-studied proteins. For SPAC17A2.14 antibody:
Pre-clearing strategy:
Pre-clear lysates with protein A/G beads (30-60 minutes at 4°C)
Add non-immune rabbit IgG during pre-clearing
Filter lysates through 0.45 μm filters before immunoprecipitation
Blocking optimization:
Test alternative blocking agents (BSA, fish gelatin, commercial blockers)
Include 0.1-0.5% detergents (NP-40 or Triton X-100) in wash buffers
Consider adding competing peptides that don't contain the target epitope
Elution considerations:
Use acid elution (0.1M glycine, pH 2.5) rather than denaturing conditions
Neutralize immediately with Tris buffer (pH 8.0)
Validate specificity with mass spectrometry analysis of eluates
This approach builds on established immunoprecipitation methodologies used for well-characterized antibodies in research settings .
For immunofluorescence studies of SPAC17A2.14:
Cell preparation:
Fix with 4% paraformaldehyde (10-15 minutes)
Permeabilize with enzyme cocktails optimized for yeast cell walls
Consider spheroplast preparation for improved antibody accessibility
Staining protocol optimization:
Extended primary antibody incubation (overnight at 4°C)
Higher primary antibody concentration (1:50-1:200)
Use high-sensitivity detection systems (tyramide signal amplification)
Controls and co-localization:
Include DAPI nuclear staining
Use markers for cellular compartments (ER, Golgi, plasma membrane)
Compare with GFP-tagged SPAC17A2.14 expression patterns
Microscopy considerations:
Use confocal microscopy with appropriate filter sets
Acquire Z-stacks to capture full cellular distribution
Apply deconvolution algorithms to improve signal-to-noise ratio
Unlike antibodies against structural proteins like cytokeratin 14 , membrane transporters may require specialized immunofluorescence approaches.
For quantitative assessment of SPAC17A2.14 expression:
Experimental design:
Test multiple growth media (minimal, rich, defined)
Examine various metal ion stress conditions (Mg²⁺ depletion/excess)
Sample at different growth phases (log, early stationary, late stationary)
Quantification methods:
| Method | Advantages | Limitations | Controls Needed |
|---|---|---|---|
| Western blot + densitometry | Semi-quantitative, visual verification | Limited dynamic range | Loading control (e.g., GAPDH) |
| ELISA | Higher throughput, better quantitation | No size verification | Standard curve with recombinant protein |
| Flow cytometry | Single-cell resolution | Requires cell permeabilization | Isotype control antibody |
Data normalization:
Normalize to total protein content (BCA/Bradford assay)
Use housekeeping gene products as internal controls
Consider spike-in standards for absolute quantification
This approach is similar to expression analysis methods used for other cellular proteins, though with specific considerations for membrane transporters .
For co-immunoprecipitation with SPAC17A2.14 antibody:
Sample preparation:
Use mild lysis conditions to preserve protein-protein interactions
Include stabilizing agents (10% glycerol, divalent cations)
Avoid harsh detergents (use digitonin or CHAPS instead of SDS)
Experimental controls:
Input control (pre-IP lysate)
IgG control (non-immune rabbit IgG)
Bead-only control (no antibody)
Reciprocal IP with antibodies against suspected interactors
Validation of interactions:
Direct western blot for known/suspected partners
Mass spectrometry for unbiased discovery
Confirmation with alternative methods (Y2H, FRET, PLA)
Specific challenges for membrane transporters:
Consider crosslinking before lysis (1-2% formaldehyde, 10 minutes)
Test detergent panel for optimal solubilization
Evaluate buffer ionic strength effects on interaction stability
This methodology adapts standard co-IP procedures used for other proteins while addressing specific challenges of membrane protein complexes .
When facing weak or inconsistent signals:
Sample-related factors:
Increase protein loading (50-100 μg total protein)
Verify protein extraction efficiency from yeast cells
Check for proteolytic degradation (add additional protease inhibitors)
Antibody-related factors:
Test new antibody dilutions (1:100-1:1000 range)
Extend primary antibody incubation (overnight at 4°C)
Try alternative detection systems (enhanced chemiluminescence)
Protocol modifications:
Extend blocking time (2-3 hours)
Add 0.1% SDS to antibody dilution buffer
Increase washing stringency (higher salt concentration)
Storage and handling:
Avoid repeated freeze-thaw cycles of antibody
Prepare fresh working dilutions for each experiment
Add antibody stabilizers (1% BSA, 0.02% sodium azide)
Unlike heavily studied antibodies against proteins like CD3 or Snail1 , specialized antibodies may require more extensive troubleshooting.
While the currently available SPAC17A2.14 antibody is polyclonal , it's useful to understand comparative performance characteristics:
| Feature | Polyclonal SPAC17A2.14 | Hypothetical Monoclonal Alternative |
|---|---|---|
| Epitope recognition | Multiple epitopes | Single epitope |
| Batch-to-batch variation | Moderate to high | Minimal |
| Sensitivity | Higher sensitivity due to multiple epitope binding | Potentially lower but more consistent |
| Background | Potentially higher | Generally lower |
| Applications | Broader application range | More specific for certain applications |
| Production scalability | Limited by animal immunization | Unlimited through hybridoma culture |
For robust assay development:
Positive controls:
Wild-type S. pombe extracts
Recombinant SPAC17A2.14 protein (if available)
Cells with overexpressed SPAC17A2.14
Negative controls:
SPAC17A2.14 knockout strains
Pre-immune serum
Primary antibody omission
Competing peptide blocking
Specificity controls:
Related protein family members
Cross-species testing (if relevant)
Tag-only controls for fusion proteins
Quantitative controls:
Standard curves with known protein amounts
Dilution series to establish linear detection range
Spike-in controls for sample matrix effects
This control strategy aligns with best practices established for antibody validation in research applications, similar to approaches used for other research antibodies .
Integrating proteomics with SPAC17A2.14 antibody research:
Immunoprecipitation-mass spectrometry (IP-MS):
Use the antibody to enrich SPAC17A2.14 and associated proteins
Apply label-free quantitation to determine relative abundance
Perform SILAC labeling for comparative studies across conditions
Proximity labeling approaches:
Express SPAC17A2.14 fused to BioID or APEX2
Identify proximal proteins through streptavidin pulldown
Validate key interactions using SPAC17A2.14 antibody
Antibody-based proteomic profiling:
Perform reverse-phase protein arrays using the antibody
Develop multiplex assays with other transporter antibodies
Create quantitative assays for post-translational modifications
Data integration:
Correlate antibody-based detection with transcriptomic data
Map interaction networks through multiple methods
Validate findings from high-throughput methods with targeted approaches
This integration of techniques represents an advanced research approach similar to those employed for other proteins in complex research scenarios .
For metal ion homeostasis studies:
Expression correlation studies:
Monitor SPAC17A2.14 protein levels under various metal stresses
Compare expression across magnesium-limiting and excess conditions
Correlate with cellular metal content measured by ICP-MS
Subcellular localization changes:
Track redistribution under different ionic conditions
Co-localize with other transporters and metal sensors
Examine expression in metal-sensitive yeast mutants
Functional correlation:
Correlate protein levels with transport activity measurements
Examine post-translational modifications under stress conditions
Investigate protein stability and turnover using cycloheximide chase
Comparative studies:
| Condition | Expected SPAC17A2.14 Expression | Cellular Localization | Functional Impact |
|---|---|---|---|
| Mg²⁺ depletion | Upregulation | Enhanced plasma membrane | Increased transport activity |
| Mg²⁺ excess | Potential downregulation | Partial internalization | Reduced transport activity |
| Other metal stress | Context-dependent | Possible redistribution | Compensatory regulation |
This research direction adapts approaches used in studying other transport proteins and their regulation in cellular systems.
For investigating post-translational modifications (PTMs):
PTM detection strategies:
Phosphorylation-specific detection using phospho-antibodies after IP
Mobility shift assays (Phos-tag gels) with SPAC17A2.14 antibody
Lambda phosphatase treatment to confirm phosphorylation
Mass spectrometry analysis of immunoprecipitated protein
Functional correlation:
Site-directed mutagenesis of potential PTM sites
Correlation of modification status with transport activity
Temporal analysis during stress responses
Manipulation of relevant kinases/phosphatases
Regulation mechanisms:
Examine PTM changes during cell cycle progression
Assess impact of osmotic/oxidative stress on modification status
Investigate crosstalk between different modification types
This methodological approach is similar to studies of post-translational regulation of other transport proteins and signaling molecules .
For cross-species comparative studies:
Homology assessment:
Alignment of SPAC17A2.14 with homologs from other yeasts
Epitope conservation analysis across species
Western blot testing against multiple species extracts
Functional conservation studies:
Compare expression patterns in response to metal stress
Assess subcellular localization across species
Evaluate heterologous complementation in knockout strains
Evolutionary insights:
Correlate antibody reactivity with evolutionary distance
Examine conservation of regulatory mechanisms
Investigate species-specific interaction partners
Technical considerations:
Optimize extraction conditions for each species
Adjust antibody concentrations for cross-reactivity differences
Include appropriate controls for each species
This approach leverages techniques from evolutionary proteomics while addressing specific challenges of transport protein research across species .