SPAC57A10.08c Antibody

What is SPAC57A10.08c antibody and what cellular targets does it recognize?

SPAC57A10.08c antibody is a Y-shaped glycoprotein composed of two heavy chains and two light chains forming a quaternary structure. This antibody primarily targets proteins involved in fungal cell wall synthesis, particularly those related to β-1,6-glucan formation in Schizosaccharomyces pombe. Its dual functionality involves antigen binding via the Fab fragment and immune system activation through the Fc region, making it valuable for studying cell wall components in yeast models.

How does SPAC57A10.08c antibody compare to other cell wall-targeting antibodies?

SPAC57A10.08c differs from other cell wall antibodies in its specificity profile. While some antibodies like Sup11p target specific β-1,6-glucan formations, SPAC57A10.08c has a predicted utility specifically in cell wall studies, as shown in comparative analysis:

This specificity profile makes it particularly valuable for researchers focusing on fission yeast cell wall architecture and remodeling processes.

What are the primary applications for SPAC57A10.08c antibody in yeast research?

SPAC57A10.08c antibody is primarily utilized for investigating cell wall synthesis and remodeling in Schizosaccharomyces pombe. Key applications include immunoprecipitation assays to study protein-protein interactions, chromatin immunoprecipitation for DNA-protein interactions, and Western blotting for protein expression analysis. The antibody's specificity for cell wall components makes it particularly valuable for studying changes in cell wall composition under various genetic or environmental conditions .

What protocol modifications are recommended when using SPAC57A10.08c antibody for co-immunoprecipitation assays with fission yeast?

When performing co-immunoprecipitation with SPAC57A10.08c antibody in fission yeast, researchers should follow these methodological steps:

• Transform cells with appropriate expression vectors (similar to pJR2–41U-Png1-His6 and pREP1–3×FLAG systems used with other yeast proteins)

• Culture transformed cells in EMM medium without appropriate selection markers overnight

• Harvest approximately 100 A600 cells and wash twice with cold phosphate-buffered saline

• Treat with Zymolyase for 30 minutes to digest the cell wall

• Lyse cells using TPER lysis buffer

• Verify expression of tagged proteins via Western blotting

• Use anti-FLAG M2 affinity gel (or appropriate tag-specific resin) to immunoprecipitate protein complexes

• Perform Western blotting with anti-His (or other tag-specific antibody) to detect interacting proteins

This protocol enables efficient isolation of protein complexes while minimizing background and non-specific binding that can complicate interpretation of results .

How should researchers optimize SPAC57A10.08c antibody dilutions for different experimental applications?

Optimal dilution determination for SPAC57A10.08c antibody should follow application-specific titration approaches:

For Western blotting:

• Begin with 1:1000 dilution in 5% BSA or milk in TBST

• Perform a dilution series (1:500, 1:1000, 1:2000, 1:5000)

• Select the dilution that provides optimal signal-to-noise ratio

For immunoprecipitation:

• Start with 10 μl of antibody per 100 A600 cells

• Adjust based on protein expression levels and complex abundance

For flow cytometry (if applicable):

• Begin testing at 1-10 μg/ml, similar to protocols used for other research antibodies

• Validate using positive controls (transfected cells expressing the target) and negative controls

As noted in guidelines for similar research antibodies: "Optimal dilutions should be determined by each laboratory for each application" .

What considerations are important when designing chromatin immunoprecipitation (ChIP) experiments using SPAC57A10.08c antibody?

When designing ChIP experiments with SPAC57A10.08c antibody, researchers should implement the following methodological considerations:

• Crosslinking optimization: Determine optimal formaldehyde concentration (typically 1%) and incubation time (10-15 minutes) for yeast cells

• Sonication parameters: Optimize sonication conditions to generate DNA fragments of 200-500bp

• Antibody specificity controls: Include IgG control and input samples

• Protocol modification: Incubate cell lysates overnight with 20 μl of protein A/G-Sepharose and 10 μl of antibody

• Primer design: Design gene-specific primers for target regions (similar to examples: Rad22 5′-AAGACCAGGCCATTTTACAC-3′ and 5′-TCCATTTTCCTTATTTTCGTCC-3′)

• Include positive and negative controls: Use known targets and non-targets to validate specificity

• Quantification: Apply real-time quantitative PCR for accurate quantification of target enrichment

This approach ensures specificity and sensitivity in chromatin immunoprecipitation experiments, particularly when investigating transcriptional regulation in cell wall-related pathways .

How can computational antibody design protocols be applied to enhance SPAC57A10.08c antibody affinity and specificity?

Computational approaches can significantly improve SPAC57A10.08c antibody properties through a systematic protocol:

• Structure determination: If the 3D structure is unavailable, use RosettaAntibody server to generate a model based on the antibody sequence

• Energy minimization: Apply RosettaRelax to optimize the structure by minimizing energy and bringing conformations closer to the bound state

• Docking analysis: If binding information is unknown, perform two-step docking:

  • Global docking with ClusPro (https://cluspro.bu.edu/login.php) to generate potential binding poses

  • Local refined docking with SnugDock (https://rosie.graylab.jhu.edu/snug_dock) to allow flexibility of interfacial side chains and CDR loops

• Hotspot identification: Conduct alanine scanning by mutating interface residues to alanine and calculating energy changes

• Affinity maturation: Apply Rosetta scoring function to generate optimized mutations that enhance affinity and stability

This computational workflow allows for rational engineering of SPAC57A10.08c antibody to improve its binding properties for specific experimental applications .

What strategies can resolve cross-reactivity issues when SPAC57A10.08c antibody shows unexpected binding to non-target proteins?

When encountering cross-reactivity issues with SPAC57A10.08c antibody, researchers should implement a systematic troubleshooting approach:

• Epitope mapping: Identify the specific epitope recognized by performing peptide arrays or hydrogen-deuterium exchange mass spectrometry

• Sequence alignment analysis: Compare target sequence with potential cross-reactive proteins to identify homologous regions

• Absorption controls: Pre-incubate antibody with purified target protein to block specific binding sites

• Negative controls: Test antibody reactivity in knockout strains lacking the target protein

• Validation in multiple assays: Confirm specificity using different techniques (Western blot, immunoprecipitation, immunofluorescence)

• Species cross-reactivity testing: Evaluate reactivity with human, monkey, and bovine antigens to understand cross-species binding profile

• Affinity purification: If possible, purify antibody further against the specific epitope to enhance specificity

How can researchers evaluate the binding kinetics and affinity of SPAC57A10.08c antibody for its target epitope?

To rigorously characterize SPAC57A10.08c antibody binding properties, researchers should employ multiple biophysical techniques:

• Biolayer interferometry (BLI): Measure real-time binding kinetics to determine:

  • Association rate constant (kon)

  • Dissociation rate constant (koff)

  • Equilibrium dissociation constant (KD = koff/kon)

• Surface plasmon resonance (SPR): Provide complementary kinetic data and validation of BLI results

• Isothermal titration calorimetry (ITC): Measure binding thermodynamics:

  • Binding enthalpy (ΔH)

  • Entropy changes (ΔS)

  • Gibbs free energy (ΔG)

• Enzyme-linked immunosorbent assay (ELISA): Determine relative binding affinity through titration experiments

• Flow cytometry: Assess binding to native epitopes on cell surfaces by analyzing staining intensity profiles

These approaches provide comprehensive binding characterization, enabling researchers to understand the molecular basis of antibody-epitope interactions and optimize experimental conditions accordingly .

What controls are essential when validating SPAC57A10.08c antibody specificity in Western blot applications?

To ensure rigorous validation of SPAC57A10.08c antibody specificity in Western blotting, researchers must include these essential controls:

• Positive control: Sample known to express the target protein (e.g., wild-type S. pombe)

• Negative control: Sample lacking the target protein (e.g., knockout strain)

• Loading control: Detection of a housekeeping protein unaffected by experimental conditions

• Peptide competition: Pre-incubation of antibody with immunizing peptide should abolish specific signal

• Molecular weight verification: Confirm that detected band matches predicted molecular weight

• Secondary antibody-only control: Verify absence of non-specific binding from secondary antibody

• Cross-species validation: Test reactivity with orthologous proteins from related species

• Expression correlation: When possible, correlate protein detection with mRNA levels measured by RT-qPCR

How should researchers interpret differences in SPAC57A10.08c antibody binding patterns under various experimental conditions?

Interpretation of differential SPAC57A10.08c antibody binding requires systematic analysis:

• Baseline establishment: First determine normal binding pattern in wild-type cells under standard conditions

• Quantitative analysis: Use densitometry for Western blots or mean fluorescence intensity for flow cytometry to quantify changes

• Pattern recognition: Distinguish between:

  • Changes in signal intensity (reflecting protein abundance)

  • Changes in banding pattern (reflecting post-translational modifications)

  • Changes in subcellular localization (reflecting protein trafficking)

• Statistical validation: Apply appropriate statistical tests to determine significance of observed differences

• Biological replication: Verify findings across multiple independent experiments

• Multi-technique confirmation: Validate findings using complementary approaches (e.g., if Western blot shows increased expression, confirm with immunofluorescence)

• Correlation with phenotype: Link observed molecular changes to cellular phenotypes or physiological responses

This structured analytical approach ensures that differences in binding patterns are interpreted in their proper biological context and leads to meaningful mechanistic insights .

What analytical methods should be used to quantify changes in cell wall composition using SPAC57A10.08c antibody-based assays?

Quantification of cell wall composition changes using SPAC57A10.08c antibody requires multi-modal analytical approaches:

• Flow cytometry quantification:

  • Measure fluorescence intensity distributions after antibody staining

  • Apply appropriate gating strategies to identify positive populations

  • Calculate mean/median fluorescence intensity ratios between experimental and control samples

• Immunofluorescence microscopy analysis:

  • Capture z-stack images to ensure complete cell visualization

  • Apply deconvolution algorithms to improve signal resolution

  • Perform intensity quantification using software like ImageJ or CellProfiler

  • Analyze colocalization with other cell wall markers

• Biochemical quantification:

  • Combine with specific enzyme digestions to isolate cell wall fractions

  • Quantify antibody binding to specific fractions via ELISA or dot blot

  • Correlate antibody binding with biochemical measurements of β-glucan content

• Real-time qPCR correlation:

  • Similar to techniques used in fission yeast studies, measure expression of related genes

  • Use appropriate reference genes (like HCS1) for normalization

  • Correlate protein detection with transcriptional changes

These complementary approaches provide robust quantification of cell wall compositional changes in response to genetic mutations, environmental stresses, or pharmacological interventions .

What are the optimal storage conditions for maintaining SPAC57A10.08c antibody activity and stability?

Optimal storage of SPAC57A10.08c antibody requires adherence to specific conditions to maintain functionality:

• Long-term storage:

  • Store at -20°C to -70°C for up to 12 months from receipt

  • Use a manual defrost freezer to avoid temperature fluctuations

  • Avoid repeated freeze-thaw cycles that can denature the antibody

• Medium-term storage:

  • After reconstitution, store at 2-8°C under sterile conditions for up to 1 month

  • For longer storage after reconstitution, aliquot and return to -20°C to -70°C

• Working stock preparation:

  • Prepare small working aliquots to minimize freeze-thaw cycles

  • Thaw aliquots on ice and centrifuge briefly before use

  • Return unused portion to recommended storage temperature promptly

• Transport considerations:

  • Ship with appropriate cold packs or dry ice depending on distance

  • Monitor temperature during transport to ensure stability

These guidelines ensure maximum retention of antibody activity and specificity for research applications .

What methodological approaches can verify SPAC57A10.08c antibody functionality after long-term storage?

To verify SPAC57A10.08c antibody functionality after extended storage, researchers should implement a systematic validation protocol:

• Activity testing:

  • Perform Western blot analysis using a known positive control

  • Compare band intensity with previous results using fresh antibody

  • Observe for any changes in background or non-specific binding

• Titration analysis:

  • Test a dilution series to determine if optimal working concentration has changed

  • Compare EC50 values before and after storage

• Specificity verification:

  • Confirm recognition of positive controls and lack of binding to negative controls

  • Perform peptide competition assay to verify epitope-specific binding

• Application-specific testing:

  • Validate in the specific application intended (immunoprecipitation, ChIP, flow cytometry)

  • Compare signal-to-noise ratios with previous experiments

• Cross-validation:

  • If possible, compare with a freshly acquired antibody lot

  • Use alternative antibodies targeting the same protein but different epitopes

This validation workflow ensures that experimental findings remain reliable and reproducible despite potential storage-related changes in antibody properties .

How can SPAC57A10.08c antibody be integrated into studies of DNA damage response in fission yeast?

Integration of SPAC57A10.08c antibody into DNA damage response studies can follow methodologies established for other S. pombe proteins:

• DNA damage induction protocols:

  • Treat cells with DNA damage agents such as MMS (0.005% w/v) to alkylate guanine bases

  • Use CPT (1 μM) to inhibit topoisomerase I and induce double-strand breaks

  • Monitor cell cycle progression via flow cytometry to detect intra-S phase arrest

• Chromatin immunoprecipitation (ChIP) methodology:

  • Apply protocols similar to those used for Png1p studies

  • Immunoprecipitate with SPAC57A10.08c antibody overnight with protein A/G-Sepharose

  • Amplify recovered DNA using PCR with gene-specific primers

  • Include appropriate controls (IgG, input DNA)

• Co-immunoprecipitation to identify interaction partners:

  • Co-transform cells with tagged constructs

  • Perform immunoprecipitation using standard protocols

  • Identify interacting proteins through Western blotting or mass spectrometry

• Expression correlation with DNA damage response genes:

  • Use real-time quantitative PCR to measure expression changes

  • Apply SYBR-based detection methods with appropriate internal controls

  • Analyze data using the comparative CT method

This integrated approach enables researchers to investigate potential roles of SPAC57A10.08c target proteins in DNA damage responses and cell cycle regulation .

What experimental design considerations are important when using SPAC57A10.08c antibody to study protein-protein interactions in yeast?

When designing protein-protein interaction studies with SPAC57A10.08c antibody, researchers should implement these methodological considerations:

• Expression system selection:

  • Choose appropriate vectors like pJR2-41U and pREP1 for co-expression

  • Consider inducible vs. constitutive expression systems based on research needs

  • Ensure proper selection markers (URA, LEU) for maintenance of plasmids

• Tag selection strategy:

  • Utilize epitope tags (His6, FLAG) for detection and purification

  • Position tags to minimize interference with protein folding and interactions

  • Validate that tagged proteins retain normal function

• Cell lysis optimization:

  • Treat with Zymolyase (30 min) for efficient cell wall digestion

  • Use appropriate lysis buffers (e.g., TPER) to maintain protein-protein interactions

  • Include protease inhibitors to prevent degradation

• Co-immunoprecipitation controls:

  • Include negative controls (e.g., WT/Rep1-FLAG as used in similar studies)

  • Perform reciprocal immunoprecipitations to confirm interactions

  • Test interaction dependence on specific conditions (DNA damage, cell cycle stage)

• Interaction verification:

  • Confirm using multiple approaches (yeast two-hybrid, proximity ligation)

  • Map interaction domains through truncation or point mutation analysis

  • Assess functional significance through phenotypic analysis of interaction-deficient mutants

This systematic approach ensures reliable detection and characterization of physiologically relevant protein-protein interactions .

How can hybridoma technology be applied to generate next-generation versions of SPAC57A10.08c antibody with enhanced properties?

Hybridoma technology offers significant potential for developing enhanced SPAC57A10.08c antibodies through the following methodological approach:

• Immunization strategy:

  • Immunize mice with purified target antigen

  • Use adjuvants that promote robust B-cell responses

  • Monitor antibody titers to determine optimal harvest timing

• B-cell isolation and fusion:

  • Isolate B cells from immunized animal spleens

  • Fuse with myeloma cells using polyethylene glycol

  • Select hybridomas using HAT medium to eliminate unfused cells

• Screening methodology:

  • Develop high-throughput ELISA screening assays

  • Test supernatants for specificity to target antigen

  • Confirm binding to native protein in relevant biological samples

• Clonal selection and expansion:

  • Perform limiting dilution to ensure monoclonality

  • Expand positive clones in serum-free media

  • Cryopreserve early passages to maintain stable cell lines

• Antibody characterization:

  • Determine isotype and subclass

  • Validate using affinity assays (e.g., biolayer interferometry)

  • Test for species cross-reactivity with human, monkey, and bovine antigens

This systematic approach can generate monoclonal antibodies with defined specificity and consistent performance characteristics, addressing limitations of existing SPAC57A10.08c antibody preparations.

What methodological approaches can integrate SPAC57A10.08c antibody into high-throughput phenotypic screening of yeast mutant libraries?

Integration of SPAC57A10.08c antibody into high-throughput phenotypic screening requires optimization of several methodological components:

• Automated sample preparation:

  • Adapt yeast culture protocols to 96 or 384-well format

  • Optimize cell fixation and permeabilization for antibody access

  • Develop protocols compatible with liquid handling robots

• Miniaturized immunostaining:

  • Reduce antibody volumes while maintaining signal-to-noise ratio

  • Optimize incubation times and washing steps for high-throughput workflow

  • Implement multiplexing with additional markers (nuclear stains, cell wall dyes)

• Automated image acquisition:

  • Utilize high-content screening microscopy platforms

  • Develop autofocus algorithms optimized for yeast cells

  • Implement tile scanning for statistical power

• Image analysis pipeline:

  • Develop automated cell segmentation algorithms

  • Extract multiple phenotypic parameters (signal intensity, localization, morphology)

  • Implement machine learning for pattern recognition and phenotype classification

• Data integration:

  • Correlate antibody staining patterns with genetic background

  • Link phenotypic clusters to biological pathways

  • Validate hits through secondary assays and orthogonal approaches