Potential Function: A potential NADPH-dependent oxidoreductase potentially involved in regulating neuronal survival, differentiation, and axonal outgrowth.
KEGG: rno:306766
UniGene: Rn.162182
The Rat UPF0498 protein KIAA1191 homolog is a member of the uncharacterized protein family 0498, with structural similarities to the human KIAA1191 protein. While its precise function remains under investigation, it likely participates in cellular nitrogen metabolism pathways similar to other proteins in this family . Structurally, the protein belongs to the aminotransferase family with a pyridoxal-phosphate-dependent domain architecture . Researchers should approach functional studies with multiple methodologies including co-immunoprecipitation and subcellular localization techniques to establish binding partners and cellular distribution patterns.
For laboratory-scale production of Rat UPF0498 protein KIAA1191 homolog, Escherichia coli expression systems typically yield sufficient protein with ≥80% purity . The truncated construct (Aa2-141) represents a functional fragment that maintains core enzymatic activity while improving expression efficiency. When establishing your expression protocol, consider the following methodology:
Clone the coding sequence into a vector containing an N-terminal His-tag for purification
Transform into BL21(DE3) E. coli strain for protein expression
Induce expression at OD600 of 0.6-0.8 with 0.5mM IPTG
Harvest after 4-6 hours of induction at 30°C rather than 37°C to improve protein folding
Verify expression using SDS-PAGE analysis before scaling up production
For applications requiring higher purity or mammalian post-translational modifications, consider using HEK293 or CHO cell expression systems, though these will require significant protocol optimization.
Verification of recombinant Rat UPF0498 protein KIAA1191 homolog requires a multi-method approach:
SDS-PAGE analysis under reducing conditions should reveal a single band at the expected molecular weight (approximately 16 kDa for the Aa2-141 fragment with His-tag)
Western blotting using anti-His antibodies confirms the presence of the tagged protein
Mass spectrometry analysis provides definitive identification through peptide mass fingerprinting
Size-exclusion chromatography assesses aggregation state and homogeneity
For functional verification, design activity assays based on predicted aminotransferase activity
Purity assessment should target ≥80% for most research applications, with higher standards (≥95%) required for structural studies or therapeutic research contexts .
For maintaining stability and activity of Recombinant Rat UPF0498 protein KIAA1191 homolog, implement the following evidence-based storage protocol:
Store purified protein at -80°C in small single-use aliquots to avoid freeze-thaw cycles
Use a stabilizing buffer containing 50mM Tris-HCl (pH 7.5), 150mM NaCl, 10% glycerol, and 1mM DTT
For short-term storage (1-2 weeks), 4°C storage is acceptable if the buffer contains protease inhibitors
Avoid repeated freeze-thaw cycles as this significantly reduces enzymatic activity
Monitor protein stability through periodic activity assays and SDS-PAGE analysis
The addition of stabilizers such as glycerol or trehalose (5-10%) can significantly extend shelf-life by preventing freeze-induced denaturation, particularly important for the Aa2-141 fragment which may have reduced inherent stability compared to the full-length protein.
When reconstituting lyophilized Rat UPF0498 protein KIAA1191 homolog, follow this methodological approach:
Allow the lyophilized protein to equilibrate to room temperature before opening the container to prevent moisture condensation
Reconstitute using sterile deionized water or an appropriate buffer (typically PBS or Tris buffer at pH 7.4-8.0)
Add buffer slowly while gently rotating the vial rather than vortexing to prevent protein denaturation
Allow 15-30 minutes at room temperature for complete dissolution
Centrifuge briefly (10,000 × g for 1 minute) to collect all material and remove potential insoluble aggregates
Verify protein concentration using Bradford or BCA assay considering the amino acid composition of this specific fragment
For experiments requiring high protein activity, supplement the reconstitution buffer with 1mM pyridoxal phosphate, a common cofactor for aminotransferase family proteins .
Designing rigorous experiments to determine the function of this poorly characterized protein requires a systematic approach following established experimental design principles :
Begin with bioinformatic analysis to identify conserved domains and potential orthologs with known functions
Design experiments with multiple independent and dependent variables:
Control for extraneous variables by:
Implement a step-wise investigation methodology:
First, determine subcellular localization using immunofluorescence or fractionation
Identify binding partners through pull-down assays and mass spectrometry
Assess potential enzymatic activities based on aminotransferase family functions
Validate findings through gene knockout/knockdown followed by phenotypic analysis
This multilayered approach controls for confounding variables while systematically building evidence for protein function through hypothesis testing .
When developing activity assays for Rat UPF0498 protein KIAA1191 homolog, consider these methodology-focused guidelines:
Based on aminotransferase family characteristics, design assays that measure:
Implement multiple detection methods:
Spectrophotometric coupled enzyme assays for real-time monitoring
HPLC analysis for precise quantification of reaction products
Mass spectrometry for definitive identification of novel substrates or products
Establish assay conditions through systematic optimization:
pH range evaluation (typically 7.0-8.5 for aminotransferases)
Temperature dependence (25-37°C)
Metal ion requirements or inhibition
Substrate specificity testing with multiple potential amino acid substrates
Validate assay reliability through:
Determining linear range, detection limits, and reproducibility
Testing with known inhibitors of aminotransferases (e.g., aminooxyacetic acid)
Comparing with related enzymes like ALT as positive controls
This comprehensive assay development approach enables accurate characterization of enzymatic parameters (Km, Vmax, kcat) essential for understanding physiological function.
When faced with contradictory experimental results in protein characterization studies, implement this systematic resolution framework:
Identify potential sources of experimental variation:
Protein batch-to-batch inconsistencies (verify with quality control testing)
Post-translational modification differences between expression systems
Assay-specific artifacts (validate using orthogonal methods)
Sample contamination (confirm with mass spectrometry analysis)
Apply statistical approaches to quantify variation:
Resolve contradictions methodologically:
Design experiments that directly test competing hypotheses
Systematically modify one variable at a time to identify critical factors
Consider protein conformation changes under different experimental conditions
Document all experimental conditions meticulously, including:
To predict substrate specificity of Rat UPF0498 protein KIAA1191 homolog, employ this computational analysis workflow:
Sequence-based approaches:
Perform multiple sequence alignment with characterized aminotransferase family members
Identify conserved active site residues through homology modeling
Use BLAST and HHpred to identify distant homologs with known substrates
Structure-based predictions:
Generate homology models using AlphaFold or RoseTTAFold
Perform molecular docking with potential substrates
Calculate binding energies for candidate molecules
Analyze active site architecture for substrate constraints
Machine learning integration:
Train prediction algorithms on known aminotransferase-substrate pairs
Implement fingerprint-based similarity searching for substrate prediction
Validate computational predictions with focused biochemical assays
Data integration methodology:
Create a consensus prediction by weighting results from multiple approaches
Prioritize candidates for experimental validation
Design targeted assays for top-predicted substrates
This computational-experimental feedback loop accelerates functional characterization while minimizing resource-intensive broad-spectrum substrate screening approaches.
Developing cell-based systems for physiological studies requires careful consideration of cellular contexts and detection methods:
Cell line selection strategy:
Primary rat hepatocytes provide physiologically relevant context for liver-expressed proteins
Established rat cell lines (e.g., H4IIE, PC12) offer experimental consistency
Consider tissue-specific expression patterns when selecting model systems
Genetic manipulation approach:
CRISPR/Cas9 knockout to eliminate endogenous expression
RNAi for dose-dependent knockdown studies
Overexpression systems with inducible promoters for temporal control
Tagged constructs (GFP, FLAG) for localization and interaction studies
Phenotypic analysis methodology:
Measure cellular metabolism parameters (glucose uptake, ATP production)
Assess growth rates and cell cycle progression
Examine stress responses and adaptive pathways
Monitor transcriptional changes using RNA-seq
Pathway integration analysis:
Perform phosphoproteomics to identify signaling pathways affected
Use metabolomics to detect changes in aminotransferase-related metabolites
Implement interactome mapping to position the protein within cellular networks
This systematic approach enables correlation of molecular function with cellular phenotypes, providing physiological context for biochemical findings.
To comprehensively map protein-protein interactions, implement this multi-method strategy:
In vitro interaction analysis:
Cell-based interaction methods:
Co-immunoprecipitation using antibodies against the tagged protein
Proximity labeling approaches (BioID, APEX) to capture contextual interactions
Fluorescence resonance energy transfer (FRET) for direct interaction visualization
Mammalian two-hybrid assays for validation of specific interactions
Bioinformatic prediction integration:
Use existing interactome databases to identify potential binding partners
Apply structural docking simulations to predict interaction interfaces
Analyze co-expression patterns across tissues and conditions
Functional validation methodology:
Mutagenesis of predicted interaction interfaces
Competition assays with peptide mimetics
Phenotypic rescue experiments in knockout systems This comprehensive approach provides both high-confidence direct interactions and broader network context, essential for understanding multifunctional proteins like KIAA1191 homolog.