SPAC1786.02 Antibody

What is SPAC1786.02 and why is it studied in fission yeast research?

SPAC1786.02 encodes a probable lysophospholipase in Schizosaccharomyces pombe. This protein is of interest in yeast biology research due to its potential role in lipid metabolism pathways. Lysophospholipases typically catalyze the hydrolysis of the ester bond at the sn-1 position of lysophospholipids, contributing to membrane lipid homeostasis. Studying this protein helps researchers understand fundamental cellular processes in eukaryotic organisms, as S. pombe is an important model organism with conserved pathways relevant to human cell biology. The antibody against SPAC1786.02 enables detection, localization, and functional studies of this protein in various experimental contexts .

What applications are suitable for SPAC1786.02 Antibody?

Based on standard antibody applications, SPAC1786.02 Antibody can likely be used in multiple experimental techniques:

• Western blotting for protein detection and semi-quantitative analysis

• Immunoprecipitation for protein-protein interaction studies

• Immunofluorescence for subcellular localization

• Flow cytometry for cell population analysis

• ELISA for quantitative protein measurement

• ChIP assays if the protein has DNA-binding properties

For optimal results, validation should be performed for each application, similar to how other antibodies like Human B7-2/CD86 Antibody are validated for specific applications including Western blot, flow cytometry, and functional assays .

What are the recommended storage conditions for SPAC1786.02 Antibody?

While specific storage information for SPAC1786.02 Antibody isn't directly provided in the search results, standard antibody storage protocols should be followed. Based on similar research-grade antibodies, the following guidelines are recommended:

• Store at -20°C to -70°C for long-term storage (12 months from date of receipt)

• For short-term storage (up to 1 month), store at 2-8°C under sterile conditions after reconstitution

• For medium-term storage (up to 6 months), store at -20°C to -70°C under sterile conditions after reconstitution

• Avoid repeated freeze-thaw cycles by aliquoting the antibody upon first thaw

How should specificity of the SPAC1786.02 Antibody be validated?

Validation of antibody specificity is critical for experimental reliability. For SPAC1786.02 Antibody, consider these validation methods:

• Western blot analysis comparing wild-type S. pombe with SPAC1786.02 knockout strains

• Immunostaining comparing signal between wild-type and knockout cells

• Peptide competition assays

• Cross-reactivity testing with closely related proteins

For example, the specificity of antibodies like Human B7-2/CD86 is validated by comparing signal between parental and knockout cell lines in both Western blot and flow cytometry. B7-2/CD86 antibody detects specific bands at approximately 74 kDa in parental Ramos cell lines but shows no detection in B7-2/CD86 knockout Ramos cell lines .

How can SPAC1786.02 Antibody be used in co-immunoprecipitation studies to identify interaction partners?

For co-immunoprecipitation (co-IP) studies with SPAC1786.02 Antibody:

• Lysate Preparation: Prepare S. pombe cell lysates under non-denaturing conditions to preserve protein-protein interactions. Use buffer systems containing mild detergents (0.1-0.5% NP-40 or Triton X-100) with protease inhibitors.

• Pre-clearing: Pre-clear lysates with protein A/G beads to reduce non-specific binding.

• Immunoprecipitation: Incubate pre-cleared lysates with SPAC1786.02 Antibody (typically 2-5 μg per mg of total protein) overnight at 4°C with gentle rotation. Add protein A/G beads and incubate for an additional 2-4 hours.

• Controls: Include negative controls (isotype-matched control antibody) and positive controls (input lysate).

• Analysis: After washing and elution, analyze precipitated complexes by mass spectrometry or Western blotting with antibodies against suspected interaction partners.

• Validation: Confirm interactions by reverse co-IP and/or functional assays.

This approach can identify novel interaction partners of the SPAC1786.02 protein and provide insights into its functional roles in cellular pathways .

What strategies can be employed to optimize immunofluorescence protocols with SPAC1786.02 Antibody in fission yeast?

Optimizing immunofluorescence with SPAC1786.02 Antibody in S. pombe requires addressing the unique challenges of yeast cell wall and fixation:

• Cell Wall Digestion: Treat cells with zymolyase or lyticase to create spheroplasts and improve antibody accessibility.

• Fixation Optimization:

  • Test multiple fixatives: 4% paraformaldehyde, methanol, or combined formaldehyde-methanol

  • Optimize fixation time (10-30 minutes) and temperature (room temperature vs. 4°C)

  • For membrane-associated proteins like lysophospholipases, avoid strong detergents that may disrupt membrane structures

• Antibody Concentration Titration: Test dilutions ranging from 1:100 to 1:1000 to determine optimal signal-to-noise ratio.

• Blocking and Permeabilization:

  • Use 3-5% BSA or normal serum for blocking

  • Test different permeabilization agents (0.1-0.5% Triton X-100, 0.05% SDS, or 0.1% saponin)

  • Extend blocking time (1-2 hours) to reduce background

• Signal Amplification: Consider using fluorophore-conjugated secondary antibodies with higher sensitivity or tyramide signal amplification if the target protein is expressed at low levels.

• Counterstaining: Use DAPI for nuclear staining and rhodamine-phalloidin for cell boundary visualization.

• Controls: Include negative controls (antibody omission, isotype control) and positive controls (GFP-tagged SPAC1786.02 if available) .

How can computational approaches be integrated with SPAC1786.02 Antibody data to enhance functional characterization?

Integration of computational approaches with antibody-generated data can significantly enhance functional characterization of SPAC1786.02:

• Sequence Analysis Pipelines: Utilize tools like ASAP-SML (Antibody Sequence Analysis Pipeline using Statistical testing and Machine Learning) to identify key sequence features that might influence antibody binding and specificity .

• Structural Prediction and Modeling:

  • Generate 3D models of SPAC1786.02 using homology modeling

  • Predict antibody epitopes using computational tools

  • Dock antibody-antigen complexes to understand binding mechanisms

• Network Analysis:

  • Integrate co-IP data with existing protein interaction networks

  • Identify functional modules and pathways where SPAC1786.02 may play a role

  • Predict additional interaction partners based on network topology

• Phylogenetic Analysis:

  • Compare SPAC1786.02 with lysophospholipases across species

  • Identify conserved domains that may be relevant for antibody cross-reactivity

  • Predict functional conservation based on evolutionary relationships

• Machine Learning Applications:

  • Use immunofluorescence images in machine learning pipelines for automated localization analysis

  • Develop predictive models for protein function based on multiple experimental datasets

What are the considerations for using SPAC1786.02 Antibody in quantitative proteomic analyses?

When integrating SPAC1786.02 Antibody into quantitative proteomic workflows:

• Antibody-Based Enrichment:

  • Optimize immunoprecipitation conditions for maximum recovery and specificity

  • Consider crosslinking the antibody to beads to prevent antibody contamination in downstream analyses

  • Validate enrichment efficiency through Western blotting before mass spectrometry

• Sample Preparation:

  • Use appropriate lysis buffers compatible with both immunoprecipitation and proteomic analysis

  • Consider filter-aided sample preparation (FASP) or single-pot solid-phase-enhanced sample preparation (SP3) methods

  • Include spike-in standards for normalization

• Quantitative Approaches:

  • Label-free quantification: Compare spectral counts or ion intensities

  • Isotope labeling: SILAC for cell culture or TMT/iTRAQ for multiplexed analysis

  • Targeted proteomics: Develop SRM/MRM assays for specific peptides from SPAC1786.02

• Data Analysis and Interpretation:

  • Apply appropriate statistical methods for differential analysis

  • Validate findings with orthogonal techniques like Western blotting

  • Use pathway enrichment analysis to contextualize results

• Challenges and Solutions:

  • Low abundance: Use fractionation techniques to reduce sample complexity

  • Post-translational modifications: Consider enrichment strategies for phosphorylation, ubiquitination, etc.

  • Membrane association: Use specialized extraction protocols for membrane proteins

How can knockout and knockdown models be used to validate SPAC1786.02 Antibody specificity?

Validation of antibody specificity using genetic models is crucial for reliable research. For SPAC1786.02 Antibody:

• CRISPR-Cas9 Knockout Generation:

  • Design guide RNAs targeting the SPAC1786.02 gene

  • Introduce CRISPR-Cas9 components into S. pombe using appropriate transformation protocols

  • Screen transformants for successful knockout using PCR and sequencing

  • Verify protein absence using the SPAC1786.02 Antibody

• RNA Interference Approach:

  • Design shRNA or siRNA constructs targeting SPAC1786.02 mRNA

  • Transform constructs into S. pombe cells

  • Validate knockdown efficiency at mRNA level using qRT-PCR

  • Compare protein levels between knockdown and control cells using the antibody

• Specificity Assessment:

  • Perform Western blot analysis comparing wild-type and knockout/knockdown samples

  • If the antibody is specific, bands should be present in wild-type samples and absent/reduced in knockout/knockdown samples

  • Quantify signal reduction in knockdown models to correlate with mRNA reduction levels

• Cross-Reactivity Testing:

  • Overexpress SPAC1786.02 and related proteins in a heterologous system

  • Test antibody reactivity against each protein to assess potential cross-reactivity

Similar approaches have been demonstrated with other antibodies, such as B7-2/CD86 antibody, where specificity was confirmed by comparing parental and knockout cell lines in both Western blot and flow cytometry analyses .

What are the recommended protocols for using SPAC1786.02 Antibody in Western blotting applications?

For optimal Western blotting results with SPAC1786.02 Antibody:

• Sample Preparation:

  • Harvest S. pombe cells in mid-log phase

  • Lyse cells using glass beads in appropriate buffer (e.g., 50 mM Tris-HCl pH 7.5, 150 mM NaCl, 1% NP-40, protease inhibitors)

  • Clear lysates by centrifugation (13,000 × g, 10 min, 4°C)

  • Determine protein concentration using Bradford or BCA assay

• Gel Electrophoresis:

  • Load 20-50 μg total protein per lane

  • Use 10-12% SDS-PAGE gels (based on the predicted molecular weight of SPAC1786.02)

  • Include molecular weight markers and positive/negative controls

• Transfer and Blocking:

  • Transfer proteins to PVDF membrane (recommended over nitrocellulose for better protein retention)

  • Block with 5% non-fat dry milk or BSA in TBST for 1 hour at room temperature

• Antibody Incubation:

  • Dilute SPAC1786.02 Antibody 1:500 to 1:2000 in blocking buffer

  • Incubate overnight at 4°C with gentle rocking

  • Wash membrane 4× with TBST, 5 minutes each

  • Incubate with appropriate HRP-conjugated secondary antibody (typically 1:5000) for 1 hour

  • Wash 4× with TBST, 5 minutes each

• Detection and Analysis:

  • Develop using ECL substrate and expose to film or digital imager

  • For quantitative analysis, use digital imaging and analysis software

• Troubleshooting Common Issues:

  • High background: Increase blocking time or washing steps

  • No signal: Increase antibody concentration or protein loading

  • Multiple bands: Optimize lysis conditions or check for degradation/isoforms

How can SPAC1786.02 Antibody be used in conjunction with recombinant protein standards for quantitative analysis?

Integrating recombinant protein standards with antibody detection enables precise quantitation:

• Recombinant Protein Selection:

  • Use purified recombinant SPAC1786.02 protein as a standard

  • Consider using recombinant proteins from different expression systems (E. coli, yeast, baculovirus) to match post-translational modifications

• Standard Curve Generation:

  • Prepare serial dilutions of recombinant SPAC1786.02 (e.g., 0.1-100 ng)

  • Process standards alongside samples in Western blot or ELISA

  • Plot band intensity or absorbance against known protein amounts

• Quantitative Western Blot Protocol:

  • Load recombinant protein standards and samples on the same gel

  • Process as described in section 3.2

  • Use digital imaging and densitometry software for quantification

  • Ensure signal is within linear range of detection

• ELISA-Based Quantitation:

  • Coat plates with capture antibody (anti-SPAC1786.02 or anti-tag)

  • Add recombinant standards and samples

  • Detect with SPAC1786.02 Antibody followed by HRP-conjugated secondary antibody

  • Measure absorbance and calculate concentration based on standard curve

• Considerations for Accuracy:

  • Account for extraction efficiency differences between samples

  • Include internal loading controls for normalization

  • Validate linearity of detection across the concentration range of interest

What are common challenges when using SPAC1786.02 Antibody and how can they be addressed?

When working with SPAC1786.02 Antibody, researchers may encounter several technical challenges:

• High Background Signal:

  • Cause: Insufficient blocking, antibody concentration too high, or non-specific binding

  • Solution: Optimize blocking (try different blockers like BSA, casein, or commercial blockers), titrate antibody, increase wash stringency, or pre-adsorb antibody with cell lysate from knockout strain

• Weak or No Signal:

  • Cause: Low protein expression, inefficient extraction, epitope masking, or antibody degradation

  • Solution: Increase protein loading, optimize lysis method (try different detergents), try alternative fixation methods, or use fresh antibody aliquot

• Multiple Unexpected Bands:

  • Cause: Protein degradation, cross-reactivity, or post-translational modifications

  • Solution: Add protease inhibitors, perform peptide competition assay, or use phosphatase inhibitors if phosphorylation is suspected

• Inconsistent Results Between Experiments:

  • Cause: Variations in cell growth, protein extraction, or antibody performance

  • Solution: Standardize growth conditions, use internal controls, create standard operating procedures, or prepare larger antibody aliquots to reduce freeze-thaw cycles

How should researchers interpret differences between predicted and observed molecular weights for SPAC1786.02?

Discrepancies between predicted and observed molecular weights are common in protein research and require careful interpretation:

• Post-Translational Modifications:

  • Phosphorylation typically adds ~0.5-1 kDa per phosphate group

  • Glycosylation can add 2-50 kDa depending on glycan complexity

  • Ubiquitination adds ~8.5 kDa per ubiquitin moiety

  • Use phosphatase or glycosidase treatments to confirm modifications

• Protein Structure Influences:

  • Highly charged or hydrophobic regions can affect SDS binding and mobility

  • Proline-rich regions often run higher than predicted

  • Confirm with mass spectrometry to determine actual mass

• Technical Considerations:

  • Variation between gel systems and molecular weight markers

  • Use different percentage gels to improve resolution

  • Consider native vs. denaturing conditions

• Verification Approaches:

  • Express tagged versions of the protein to confirm identity

  • Perform immunoprecipitation followed by mass spectrometry

  • Compare with knockout/knockdown samples

For example, the Human Skp2 antibody detects specific bands at approximately 45 and 48 kDa despite a predicted molecular weight of approximately 45 kDa, likely due to post-translational modifications .

How can researchers differentiate between specific and non-specific binding in complex samples?

Distinguishing specific from non-specific binding is crucial for accurate data interpretation:

• Experimental Controls:

  • Knockout/knockdown validation: Compare signal between wild-type and genetic models lacking SPAC1786.02

  • Peptide competition: Pre-incubate antibody with immunizing peptide to block specific binding

  • Isotype control: Use matched isotype antibody to identify non-specific binding

  • Secondary-only control: Omit primary antibody to detect secondary antibody background

• Technical Approaches:

  • Titrate antibody concentration to find optimal signal-to-noise ratio

  • Increase stringency of washing steps (higher salt or detergent concentration)

  • Use alternative blocking agents (milk vs. BSA vs. commercial blockers)

  • Compare signal across multiple detection methods (IF, WB, ELISA)

• Advanced Validation Methods:

  • Perform IP-MS to identify all proteins bound by the antibody

  • Use multiple antibodies targeting different epitopes of SPAC1786.02

  • Express tagged versions of the protein for orthogonal detection

• Data Analysis:

  • Quantify signal-to-background ratios across different conditions

  • Apply statistical methods to distinguish specific signal from background

  • Consider signal distribution patterns in imaging data

How can SPAC1786.02 Antibody be integrated into high-throughput screening approaches?

Incorporating SPAC1786.02 Antibody into high-throughput workflows enables large-scale studies:

• Automated Western Blotting Systems:

  • Adapt SPAC1786.02 Antibody protocols for Simple Western™ or similar capillary-based systems

  • Optimize antibody concentration and incubation times for automated platforms

  • Validate correlation between traditional and automated detection methods

• High-Content Imaging:

  • Develop immunofluorescence protocols compatible with automated microscopy

  • Optimize cell plating, fixation, and staining in microplate format

  • Design image analysis algorithms to quantify SPAC1786.02 levels, localization, and co-localization

• Reverse Phase Protein Arrays (RPPA):

  • Validate SPAC1786.02 Antibody for RPPA applications

  • Create lysate dilution series to ensure linear detection range

  • Include appropriate controls for normalization and quality control

• Bead-Based Multiplex Assays:

  • Conjugate SPAC1786.02 Antibody to microspheres for multiplexed detection

  • Combine with antibodies against related proteins or pathway components

  • Validate specificity and sensitivity in multiplex format

• Considerations for Scale-Up:

  • Antibody lot consistency and stability over time

  • Standardization of sample preparation across plates/batches

  • Robust statistical methods for large-scale data analysis

What emerging technologies can enhance the utility of SPAC1786.02 Antibody in research?

Several cutting-edge technologies can expand applications for SPAC1786.02 Antibody:

• Proximity Labeling Techniques:

  • APEX2 or BioID fusion proteins combined with antibody detection

  • Identify proteins in close proximity to SPAC1786.02 in living cells

  • Map spatial proteomics of SPAC1786.02 microenvironment

• Super-Resolution Microscopy:

  • Optimize SPAC1786.02 Antibody protocols for STORM, PALM, or STED microscopy

  • Achieve nanoscale resolution of protein localization

  • Combine with other markers for co-localization studies

• Live-Cell Imaging Approaches:

  • Develop cell-permeable nanobodies derived from SPAC1786.02 Antibody

  • Create fluorescent biosensors to monitor protein dynamics

  • Implement optogenetic tools to manipulate protein function

• Single-Cell Analysis:

  • Adapt SPAC1786.02 Antibody for CyTOF or CITE-seq applications

  • Correlate protein expression with transcriptome at single-cell level

  • Identify cell-to-cell variability in protein expression or localization

• Microfluidic Applications:

  • Develop on-chip immunoassays for SPAC1786.02 detection

  • Create droplet-based single-cell protein analysis systems

  • Implement continuous monitoring of protein dynamics

How can machine learning approaches enhance antibody-based studies of SPAC1786.02?

Machine learning integration can revolutionize antibody-based research on SPAC1786.02:

• Image Analysis Enhancement:

  • Train deep learning models to recognize SPAC1786.02 localization patterns

  • Automate segmentation and quantification in immunofluorescence images

  • Identify subtle phenotypes associated with SPAC1786.02 perturbation

• Sequence-Based Predictions:

  • Apply ASAP-SML or similar pipelines to identify key features in antibody-antigen interactions

  • Predict epitopes and binding affinity based on sequence features

  • Design improved antibodies with enhanced specificity and sensitivity

• Experimental Design Optimization:

  • Develop predictive models for optimal experimental conditions

  • Use active learning to guide iterative protocol refinement

  • Generate decision trees for troubleshooting common issues

• Data Integration Frameworks:

  • Combine antibody-based data with omics datasets (transcriptomics, proteomics)

  • Build integrative models of SPAC1786.02 function in cellular pathways

  • Identify hidden relationships between experimental variables

• Antibody Specificity Assessment:

  • Train algorithms to distinguish specific from non-specific binding patterns

  • Predict potential cross-reactivity based on protein sequence similarity

  • Quantify confidence scores for antibody-based detections