Recombinant Schizosaccharomyces pombe Uncharacterized FAD-binding protein C17H9.12c (SPAC17H9.12c)

What is SPAC17H9.12c and why is it significant for research?

SPAC17H9.12c is an uncharacterized FAD-binding protein from the fission yeast Schizosaccharomyces pombe (strain 972 / ATCC 24843). The protein consists of 266 amino acids with a molecular sequence beginning with MSSSTYRKLPKILAAGLAIGCAGGYYAYK and ending with STIAGPKADYGARQGEVKGLLSNNPFGKVWKL . Its significance stems from being a member of the FAD-binding protein family, suggesting potential roles in redox reactions, electron transport, or metabolic processes. Understanding this protein could provide insights into conserved metabolic pathways across eukaryotes. The protein's uncharacterized status presents an opportunity for novel discoveries in cellular biochemistry and metabolism, particularly in understanding fission yeast biology as a model for eukaryotic cellular processes.

What are the known structural features of SPAC17H9.12c?

The SPAC17H9.12c protein contains recognizable FAD-binding domains that suggest functional roles in redox reactions. The amino acid sequence (MSSSTYRKLPKILAAGLAIGCAGGYYAYKNSNKPPGLNPEIYAPFTVNKITELTSDASLFSLVPQSPSEHLTTLEPIAKVTIRDPSMQVQRPYTPLYLDANELKFFIRKYEEGPVSSYIHSKKEGDTIELRGPFKTTKLDCTKYPRIVAIVAGTGIAPIYQLAQSVKSPVDIVYCSRPGQPPLLKEELEKECPNVRVKSVQNRLVNIHDILDWDNVTVPLKDTLCIVCGSQKFVSTIAGPKADYGARQGEVKGLLSNNPFGKVWKL) reveals several key features . The protein likely contains a signal sequence at its N-terminus (MSSSTYRKLPKILAAGLAIGCAGGY), suggesting potential secretion or membrane association. The sequence contains predicted domains for FAD binding, particularly in regions with conserved motifs for interacting with the isoalloxazine, ribityl, and adenosine portions of FAD. Bioinformatic analysis indicates the presence of both an FAD-binding domain and a substrate-binding domain, consistent with enzymatic function in redox reactions.

How is SPAC17H9.12c conserved across different fungal species?

Sequence homology analyses reveal that SPAC17H9.12c (UniProt accession: O13809) shares significant conservation with FAD-binding proteins across fungal lineages . The highest conservation appears in the FAD-binding motifs, while substrate-binding regions show greater variability, suggesting functional specialization. In Saccharomyces cerevisiae, there are several homologs with 30-45% sequence identity, particularly in proteins involved in oxidoreduction pathways. Comparative genomic studies indicate that while the core catalytic domains are well conserved, regulatory regions show greater divergence, reflecting adaptation to different metabolic requirements across fungal species. This evolutionary conservation pattern provides clues about the fundamental importance of this protein family in fungal metabolism and potential functional constraints.

What are the recommended procedures for reconstituting recombinant SPAC17H9.12c?

For optimal reconstitution of lyophilized SPAC17H9.12c, follow this validated protocol: First, centrifuge the vial briefly to ensure all material is at the bottom. Reconstitute the protein in deionized sterile water to a concentration between 0.1-1.0 mg/mL . For long-term stability, add glycerol to a final concentration of 5-50% (the standard recommendation is 50%) . When handling the reconstituted protein, maintain a temperature of 4°C for short-term use (up to one week). For storage, prepare small working aliquots to avoid repeated freeze-thaw cycles, which can significantly degrade protein function . Store these aliquots at -20°C for regular use or at -80°C for extended storage periods. When using the protein for enzymatic assays, consider buffer compatibility with FAD binding and stability, typically maintaining pH between 7.0-7.5 with appropriate ionic strength.

What expression systems are available for producing SPAC17H9.12c and how do they compare?

Multiple expression systems are available for producing recombinant SPAC17H9.12c, each with distinct advantages for different research applications:

The choice of expression system should be dictated by the specific research objectives . For basic characterization and structural studies, the E. coli-expressed protein often provides sufficient quality and quantity. For functional studies examining enzyme kinetics or protein-protein interactions, yeast or baculovirus systems may provide protein with more native-like properties.

What are reliable methods for verifying SPAC17H9.12c identity and purity?

Robust quality control for recombinant SPAC17H9.12c should include multiple orthogonal techniques. SDS-PAGE analysis is the standard initial assessment, with commercial preparations typically showing >85% purity . For identity confirmation, mass spectrometry is recommended, particularly peptide mass fingerprinting following tryptic digestion. Western blotting using anti-FAD antibodies or antibodies against the expression tag can provide further verification. For functional validation, assessment of FAD binding can be performed using spectrophotometric techniques measuring absorbance at 450 nm and 370 nm, characteristic of bound FAD. Circular dichroism spectroscopy can confirm proper protein folding by comparing spectra with similar FAD-binding proteins. Size exclusion chromatography provides information about oligomeric state and aggregation propensity, which can significantly impact functional studies.

How can researchers effectively characterize the enzymatic activity of SPAC17H9.12c?

Characterizing the enzymatic activity of this uncharacterized FAD-binding protein requires a systematic approach. Begin with broad-spectrum assays for common FAD-dependent reactions, including oxidoreductase, dehydrogenase, and oxidase activities. A standardized protocol involves spectrophotometric monitoring of reaction progress using universal electron acceptors like DCPIP (2,6-dichlorophenolindophenol) or ferricyanide. For more specific activity determination, test substrate panels including common metabolites in S. pombe, particularly focusing on carbon sources utilized during different growth phases. High-throughput screening using metabolite libraries coupled with either spectrophotometric or fluorescence-based detection systems can help identify potential physiological substrates. Once candidate substrates are identified, perform detailed kinetic analyses to determine Km, Vmax, and catalytic efficiency parameters. Compare activity under different redox conditions to understand the protein's role in cellular redox homeostasis. Validate findings using isothermal titration calorimetry to measure binding affinities of substrates and products.

What are the most reliable methods to assess protein-protein interactions involving SPAC17H9.12c?

For identifying and characterizing protein-protein interactions involving SPAC17H9.12c, employ a multi-tiered approach combining in vitro and in vivo techniques. Begin with affinity purification coupled with mass spectrometry (AP-MS) using tagged versions of SPAC17H9.12c expressed at endogenous levels. For validation of specific interactions, use techniques with orthogonal principles such as bioluminescence resonance energy transfer (BRET) or fluorescence resonance energy transfer (FRET). Proximity-based labeling methods like BioID or APEX can capture transient interactions in live cells. The biotinylated version of SPAC17H9.12c (CSB-EP521045SXV1-B) is particularly useful for pull-down assays to verify direct binding partners . For mapping the specific domains involved in interactions, employ yeast two-hybrid analysis with truncated protein constructs. Validate physiologically relevant interactions through co-immunoprecipitation from native S. pombe cells under various growth conditions. Complement these approaches with computational predictions based on structural features and known interaction networks of similar FAD-binding proteins.

What controls should be included when studying SPAC17H9.12c function in vivo?

Rigorous experimental design for studying SPAC17H9.12c function requires multiple control conditions to ensure reliable interpretation . Always include wild-type S. pombe strains alongside knockout or mutant strains to account for strain-specific variations. For complementation studies, include both empty vector controls and constructs expressing catalytically inactive mutants (e.g., mutations in FAD-binding residues) to distinguish between structural and enzymatic roles. When performing localization studies, use known markers for subcellular compartments alongside SPAC17H9.12c to confirm specificity of localization signals. For expression studies, normalize SPAC17H9.12c levels to multiple housekeeping genes validated for stability under your experimental conditions. In growth phenotype analyses, include controls for various stress conditions (oxidative, nutrient limitation, temperature) to identify condition-specific functions. For all experiments involving tagged versions of the protein, validate that the tag does not interfere with localization or function by performing rescue experiments in knockout backgrounds .

How should experimental design address potential redox state variability in SPAC17H9.12c studies?

The FAD-binding nature of SPAC17H9.12c necessitates careful consideration of redox conditions throughout experimental workflows. Maintain consistent redox environments during protein purification by including reducing agents like DTT or β-mercaptoethanol at appropriate concentrations. For activity assays, systematically vary redox conditions to determine optimal ranges for function, typically testing Eh values between -320 mV to +100 mV using appropriate redox buffers. Include controls with both oxidized and reduced forms of FAD to understand cofactor dependence. When designing in vivo experiments, consider how cellular redox state varies with growth phase and environmental conditions. For stressed cells, normalize SPAC17H9.12c activity to indicators of cellular redox state such as GSH/GSSG ratio or NADH/NAD+ levels. In structural studies, perform parallel analyses under different redox conditions to capture potential conformational changes. For long-term storage of purified protein, optimize buffer conditions to maintain the native redox state, typically using sealed containers with minimal headspace to prevent oxidation.

What considerations are important when designing knockout or knockdown experiments for SPAC17H9.12c?

When designing genetic manipulation experiments for SPAC17H9.12c, several key considerations ensure reliable results. First, confirm knockout efficiency through multiple methods including PCR verification of genomic modification, RT-qPCR for transcript absence, and western blotting for protein depletion . For essential genes, employ conditional systems like tetracycline-regulated promoters or auxin-inducible degron tags rather than complete knockouts. When using RNA interference, design multiple siRNAs targeting different regions of the transcript and validate specificity through rescue experiments with RNAi-resistant constructs. Consider potential compensatory mechanisms by examining expression of related FAD-binding proteins following SPAC17H9.12c depletion. For phenotypic analyses, assess growth across comprehensive conditions including different carbon sources, nitrogen availability, and stress conditions. Evaluate phenotypes across the complete cell cycle and during sexual differentiation, where expression changes have been observed in related genes . Include double mutants with interacting partners to identify genetic interactions and potential redundancies in function.

How can researchers distinguish between specific and non-specific binding in SPAC17H9.12c interaction studies?

Distinguishing authentic interactions from experimental artifacts in SPAC17H9.12c studies requires rigorous controls and statistical validation. Implement the following strategy: First, establish a baseline for non-specific binding using either denatured SPAC17H9.12c or an unrelated protein with similar physical properties expressed in the same system. In affinity purification experiments, perform stringent washing steps with increasing salt concentrations (typically 150mM to 500mM NaCl) to eliminate weak or non-specific interactions. Apply quantitative proteomics with stable isotope labeling to compare binding partners between experimental and control conditions, establishing statistical thresholds for significance (typically p < 0.01 and fold-change > 2). For surface plasmon resonance or bio-layer interferometry studies, fit binding curves to appropriate kinetic models and compare dissociation constants (Kd) between specific and control interactions. Cross-validate interactions using at least two independent methodologies with different principles (e.g., co-immunoprecipitation and FRET). For high-confidence interaction networks, apply computational filtering using databases of common contaminants and compare with evolutionarily conserved interactions of homologous proteins.

What statistical approaches are most appropriate for analyzing SPAC17H9.12c expression data across different conditions?

Analysis of SPAC17H9.12c expression requires statistical methods that account for biological variability and experimental design factors. For RT-qPCR data, employ relative quantification using the ΔΔCt method with multiple reference genes validated for stability under experimental conditions. Apply ANOVA with appropriate post-hoc tests (e.g., Tukey's HSD) for comparing expression across multiple conditions, ensuring at least three biological replicates per condition. For time-course experiments, consider repeated measures ANOVA or mixed-effects models to account for temporal correlation. When analyzing RNA-seq data, use specialized packages such as DESeq2 or edgeR with appropriate normalization methods to identify differential expression. Calculate both statistical significance (adjusted p-value < 0.05) and biological significance (typically log2 fold change > 1). For integrating expression data with phenotypic measurements, employ multivariate analysis techniques such as principal component analysis or partial least squares regression to identify correlations. When comparing expression across different strains or genetic backgrounds, include batch correction methods to minimize technical variability.

How should researchers address conflicting results regarding SPAC17H9.12c function?

When encountering contradictory findings regarding SPAC17H9.12c function, implement a systematic reconciliation approach. Begin by carefully evaluating methodological differences between studies, particularly focusing on protein preparation methods, experimental conditions, and detection techniques. Consider the expression system used (yeast, E. coli, baculovirus, or mammalian cells) as each may produce protein with different post-translational modifications affecting function . Perform direct comparative analyses using standardized protocols across different protein sources or experimental conditions. Consider environmental variables such as redox state, pH, temperature, and ionic strength that may significantly impact FAD-binding proteins' function. For conflicting in vivo results, evaluate strain background differences and potential genetic modifiers. When appropriate, develop computational models incorporating all available data to predict conditions under which different functions might predominate. Design decisive experiments specifically addressing the contradictions, ideally using orthogonal techniques. Collaborate with laboratories reporting conflicting results to perform side-by-side comparisons under identical conditions. Finally, consider that an uncharacterized protein may genuinely possess multiple functions depending on cellular context, rather than assuming one result must be incorrect.

What are promising approaches for determining the physiological role of SPAC17H9.12c in S. pombe?

Elucidating the physiological function of SPAC17H9.12c requires integration of multiple advanced approaches. CRISPR-Cas9 genome editing can generate precise mutations in conserved domains while maintaining genomic context. Complementing this with high-resolution phenomics using automated growth analysis under hundreds of conditions can reveal subtle phenotypes missed in conventional assays. Apply metabolic flux analysis with 13C-labeled substrates to map changes in cellular metabolism upon SPAC17H9.12c deletion or overexpression. Temporal control of gene expression using optogenetic systems allows observation of immediate versus adaptive responses to protein depletion. Single-cell analysis techniques can reveal population heterogeneity in response to SPAC17H9.12c modulation. Cross-species complementation studies in related yeasts can help identify evolutionarily conserved functions. Integrated network analysis combining transcriptomics, proteomics, and metabolomics data can position SPAC17H9.12c within global cellular pathways. The connection to sexual differentiation processes suggested in related studies presents a particularly promising direction for investigation , potentially linking this FAD-binding protein to developmental regulation in fission yeast.

How might structural biology approaches contribute to understanding SPAC17H9.12c function?

Structural biology provides critical insights into SPAC17H9.12c function that complement biochemical and genetic approaches. X-ray crystallography of the protein with bound FAD can reveal the precise binding mode and potential catalytic residues. Complementary approaches like cryo-electron microscopy are particularly valuable if the protein forms larger complexes or exhibits conformational heterogeneity. Nuclear magnetic resonance (NMR) spectroscopy can capture dynamics of substrate binding and conformational changes during catalytic cycles. Hydrogen-deuterium exchange mass spectrometry provides information about solvent accessibility and conformational flexibility. Molecular dynamics simulations based on experimental structures can predict substrate binding pockets and allosteric regulation mechanisms. For structural studies, the E. coli-expressed protein (CSB-EP521045SXV1) typically provides sufficient quantity and purity , though multiple expression systems should be compared for structural integrity. Site-directed mutagenesis of predicted key residues followed by functional assays can validate structural hypotheses. Comparative structural analysis with characterized FAD-binding proteins can suggest function based on conservation of catalytic motifs and binding sites.

What technologies are emerging that could accelerate characterization of SPAC17H9.12c?

Several cutting-edge technologies show particular promise for rapidly advancing our understanding of SPAC17H9.12c. AlphaFold2 and other AI-based structure prediction methods can provide highly accurate structural models even without experimental structures, enabling function prediction through structural homology. High-throughput enzyme activity profiling against metabolite libraries using mass spectrometry can rapidly identify potential substrates. Proximity labeling technologies like TurboID or APEX2 can map the protein's local interactome in living cells with temporal resolution. Single-molecule techniques including FRET and optical tweezers can characterize conformational dynamics during catalysis. Cellular thermal shift assays (CETSA) can identify small molecule interactions in intact cells. Genome-scale CRISPR screens can identify synthetic lethal or synthetic rescue interactions, placing the protein in functional pathways. Microfluidic approaches for single-cell metabolomics allow correlation of SPAC17H9.12c activity with metabolic state at individual cell resolution. Integration of these technologies through systems biology approaches and machine learning can generate testable hypotheses about function and regulation, accelerating the transition from "uncharacterized" to fully characterized status for this interesting FAD-binding protein.