UMPS Antibody, FITC conjugated, consists of:
Antibody Backbone: A rabbit-derived polyclonal IgG antibody raised against recombinant human UMPS (amino acids 314–444) .
FITC Conjugation: Covalent attachment of FITC to primary amines (e.g., lysine residues) via isothiocyanate chemistry, forming stable thiourea linkages .
This antibody is validated for diverse techniques, with optimized dilutions and tested reactivity:
UMPS Antibody, FITC conjugated, has been instrumental in studying pyrimidine metabolism and its role in disease:
Cancer Metabolism: UMPS upregulation is linked to gemcitabine resistance in pancreatic cancer and pyrimidine synthesis in hypoxic tumors .
Lung Cancer Prognosis: UMPS expression correlates with thymidylate synthase levels, influencing chemotherapy responses .
Hereditary Disorders: Defects in UMPS cause orotic aciduria, a metabolic disorder .
Pancreatic Cancer: UMPS-mediated pyrimidine release inhibits gemcitabine efficacy .
Lung Cancer: UMPS/thymidylate synthase co-expression predicts adjuvant chemotherapy outcomes .
Hypoxic Tumors: UMPS coordinates glutamine carbon/nitrogen metabolism under low oxygen .
For custom conjugation (e.g., bulk production):
UMPS, also known as OPRT (Orotate Phosphoribosyltransferase) and ODC (Orotidine 5'-phosphate decarboxylase), plays a crucial role in pyrimidine synthesis by converting orotic acid to uridine 5′ monophosphate . This bifunctional enzyme comprises two enzymatic activities: orotate phosphoribosyltransferase and orotidine 5'-phosphate decarboxylase. UMPS exists in four isoforms with molecular weights of approximately 53 kDa, 43 kDa, 33 kDa, and 23 kDa . Dysregulation of this pathway has been implicated in various diseases, including cancer and metabolic disorders, making it an important target for research in fields ranging from biochemistry to drug development .
FITC conjugation refers to the chemical attachment of the fluorescent dye Fluorescein Isothiocyanate to an antibody molecule. This process typically involves crosslinking the antibody with the FITC fluorophore using established protocols that target primary amine groups on the antibody . The conjugation allows researchers to visualize the antibody-antigen interaction through fluorescence detection methods. The FITC molecule has excitation and emission maxima around 495 nm and 525 nm, respectively, producing a green fluorescence that can be detected using appropriate filters in various imaging and analytical instruments .
FITC-conjugated antibodies are versatile tools in biomedical research with several key applications:
Flow Cytometry: Most commonly used for identifying and quantifying specific cell populations based on marker expression
Immunofluorescence: For visualization of protein localization in fixed cells or tissue sections
Monitoring Extracellular pH: FITC conjugates can be used to track pH changes in cellular microenvironments
Protein-Protein Interaction Studies: When combined with other techniques like FRET (Fluorescence Resonance Energy Transfer)
Cell Sorting: For isolation of specific cell populations using FACS (Fluorescence-Activated Cell Sorting)
FITC-conjugated antibodies are particularly useful in multicolor flow cytometry experiments, where they can be combined with other fluorophores that have distinct spectral properties .
For optimal preservation of FITC-conjugated UMPS antibodies:
When preparing to use the antibody, thaw it slowly on ice and protect from light throughout the experimental procedure.
When designing flow cytometry experiments with FITC-conjugated UMPS antibodies:
Antibody Titration: Always perform titration experiments to determine the optimal concentration. Start with the manufacturer's recommended dilution (typically around 1:500 to 1:2000 for polyclonal antibodies) , then test serial dilutions to find the concentration that gives the highest signal-to-noise ratio.
Cell Preparation:
Staining Protocol:
Maintain cells at 4°C during staining to prevent internalization of surface antigens
Stain in buffers containing EDTA to prevent cell clumping
Use appropriate washing steps to remove unbound antibody
Include a viability dye to exclude dead cells from analysis
Controls:
Instrument Settings:
Use appropriate excitation (488 nm laser) and emission filters (530/30 nm bandpass)
Set voltage based on unstained and positive control samples
Consider compensation when using multiple fluorophores
Background fluorescence is a common challenge when working with FITC-conjugated antibodies. To minimize it:
Optimize Blocking Conditions:
Use 10% serum from the same species as the secondary antibody
Include 0.1-0.3% Triton X-100 for intracellular staining
Consider using commercial blocking solutions specifically designed for immunofluorescence
Antibody Concentration:
Use the lowest effective concentration determined by titration experiments
Over-concentration often leads to increased non-specific binding
Fixation Considerations:
Some fixatives (particularly aldehyde-based ones) can increase autofluorescence
Consider using methanol fixation which typically produces less autofluorescence
If using formaldehyde/paraformaldehyde, treat with sodium borohydride to quench autofluorescence
Washing Steps:
Include additional and more stringent washing steps
Consider using PBS with 0.05-0.1% Tween-20 for more effective removal of unbound antibody
Anti-FITC Antibody Quenching:
Optical Considerations:
Use high-quality filters with narrow bandpass to minimize spectral overlap
Adjust PMT voltage to optimize signal-to-noise ratio
The conjugation of FITC to antibodies can potentially affect their binding properties through several mechanisms:
A robust experimental design requires appropriate controls for accurate interpretation of results:
Additionally, when monitoring potential release of FITC conjugates from cellular compartments, anti-fluorescein antibody can be used to quench extracellular fluorescence, ensuring observed signals are genuinely intracellular .
FITC-conjugated antibodies can be effectively incorporated into multi-color flow cytometry panels with careful planning:
Spectral Considerations:
FITC has excitation/emission maxima around 495/525 nm
Avoid fluorophores with significant spectral overlap such as PE (phycoerythrin) without proper compensation
Compatible fluorophores include:
APC (allophycocyanin) - minimal overlap
PE-Cy5 or PerCP - minimal overlap
Pacific Blue - excited by different laser
Panel Design Principles:
Place FITC on abundant targets or those requiring less sensitivity (FITC is relatively bright but not the brightest fluorophore)
Consider using brighter fluorophores (PE, APC) for low-abundance targets
Account for antigen density when assigning fluorophores
Compensation Requirements:
Prepare single-color controls for each fluorophore
Use compensation beads for consistent signal intensity
Modern flow cytometers allow for automated compensation but manual verification is recommended
Data Analysis Approach:
Use appropriate gating strategies based on isotype controls
Consider fluorescence minus one (FMO) controls for setting accurate gates
Analyze compensation matrices carefully to ensure proper correction of spectral overlap
FITC-Specific Limitations:
FITC is pH-sensitive (fluorescence decreases at lower pH)
Relatively rapid photobleaching compared to some other fluorophores
Consider using alternatives like Alexa Fluor 488 for experiments requiring higher photostability
When encountering signal issues with FITC-conjugated UMPS antibodies, follow this systematic approach:
Antibody-Related Factors:
Check storage conditions – improper storage can lead to fluorophore degradation
Verify antibody hasn't been exposed to prolonged light
Test a new lot or aliquot of antibody
Increase antibody concentration (but be cautious of increasing background)
Sample Preparation Issues:
Ensure proper fixation and permeabilization for intracellular targets
Verify antigen retrieval steps if working with tissue sections
Check for excessive wash steps that might remove antibody
Assess if target protein is expressed at detectable levels
Instrumentation Considerations:
Verify laser alignment and proper functioning
Check filter sets are appropriate for FITC (excitation ~495 nm, emission ~525 nm)
Adjust PMT voltage/gain settings to optimize detection
Ensure instrument has been properly calibrated
Protocol Modifications:
Extend incubation time with primary antibody (e.g., overnight at 4°C)
Reduce washing stringency
Try alternative fixation methods
Consider signal amplification methods
Experimental Controls to Implement:
Test antibody on positive control samples
Perform parallel staining with unconjugated primary followed by FITC-conjugated secondary
Test antibody in a different application (e.g., if not working in IF, try flow cytometry)
FITC-Specific Considerations:
Check pH of buffers (FITC fluorescence is optimal at pH 8-9)
Avoid using procedures or buffers that might quench fluorescence
Consider photobleaching – minimize exposure to light during all steps
FITC-conjugated UMPS antibodies provide valuable tools for investigating alterations in pyrimidine metabolism in cancer research:
Expression Pattern Analysis:
Flow cytometry can quantify UMPS expression levels across different cancer cell populations
Correlation of UMPS expression with clinical parameters or treatment responses
Identification of cancer subtypes based on UMPS expression profiles
Subcellular Localization Studies:
Immunofluorescence microscopy to determine if UMPS localization changes in cancer cells
Co-localization studies with organelle markers to track potential translocation events
Live-cell imaging to monitor dynamic changes in UMPS localization during cell cycle or in response to treatments
Therapeutic Response Monitoring:
Assessment of UMPS expression changes following treatment with anticancer agents
Correlation between UMPS levels and sensitivity to pyrimidine analogs (e.g., 5-fluorouracil)
Identification of patient subgroups likely to respond to pyrimidine metabolism-targeting therapies
Combination with Other Techniques:
FACS sorting of UMPS-high vs. UMPS-low populations followed by functional assays
Integration with metabolomic analyses to correlate UMPS expression with metabolite levels
Dual staining with proliferation markers to assess relationship between UMPS and cell cycle
Experimental Design Considerations:
Include multiple cancer cell lines representing different tissue origins and mutation profiles
Pair with normal cell counterparts as controls
Validate findings from FITC-conjugated antibody experiments with orthogonal methods (e.g., qPCR, Western blot)
Developing robust flow cytometry assays for intracellular proteins like UMPS requires careful methodological considerations:
Cell Preparation Protocol:
Fixation: Use 4% paraformaldehyde (10-15 minutes) or 70-90% methanol (30 minutes at -20°C)
Permeabilization: Apply 0.1-0.3% Triton X-100 or saponin-based buffers
Blocking: Incubate with 5-10% serum from the same species as the secondary antibody
Staining Optimization:
Titrate antibody concentration using a minimum of 5 dilutions
Test different incubation times and temperatures (e.g., 1 hour at room temperature vs. overnight at 4°C)
For dual surface/intracellular staining, perform surface staining before fixation/permeabilization
Signal Validation Approach:
Perform parallel experiments with unconjugated primary antibody plus FITC-secondary antibody
Compare staining patterns between conjugated and unconjugated systems
Use siRNA knockdown or CRISPR knockout cells as specificity controls
Data Analysis Considerations:
Use median fluorescence intensity (MFI) rather than mean for more robust measurement
Calculate staining index: (MFI positive - MFI negative) / (2 × SD of negative)
Consider multiparametric analysis to correlate UMPS expression with cell cycle phase or other markers
Protocol Documentation:
| Parameter | Recommended Documentation |
|---|---|
| Fixation | Agent, concentration, time, temperature |
| Permeabilization | Agent, concentration, time, temperature |
| Blocking | Solution composition, incubation conditions |
| Antibody | Clone, concentration, incubation conditions |
| Washing | Buffer composition, number of washes, volumes |
| Instrument | Cytometer model, laser configuration, filter sets |
| Analysis | Software, gating strategy, compensation matrix |
Distinguishing specific from non-specific binding is critical for accurate data interpretation:
Control-Based Approaches:
Isotype controls: Match the isotype, concentration, and fluorophore of the test antibody
Blocking peptide competition: Pre-incubate antibody with excess target peptide
Genetic controls: Use knockout/knockdown cells lacking the target protein
Fluorescence minus one (FMO) controls: Include all fluorophores except the one being controlled
Signal Pattern Analysis:
Specific binding typically shows distinct subcellular localization patterns
Non-specific binding often appears as diffuse staining or high background
Compare staining pattern with published literature on UMPS localization
Antibody Validation Techniques:
Optimizing Experimental Conditions:
Add 0.1-0.5% BSA to staining buffers to reduce non-specific binding
Include mild detergents (0.05% Tween-20) in wash buffers
Extend washing steps to remove weakly bound antibodies
Advanced Analytical Methods:
Competitive binding assays with unlabeled antibody
Dilution linearity analysis: signal should decrease proportionally with antibody dilution
Correlation with orthogonal measurements of protein expression
Addressing Conjugation-Specific Issues:
Recent advances have expanded the utility of FITC-conjugated antibodies:
Antibody-Conjugated Nanoparticles:
Multi-Modal Imaging Systems:
FITC-antibodies combined with MRI contrast agents or radiotracers
Allows correlation between microscopic and macroscopic imaging modalities
Facilitates translation between in vitro and in vivo research
Advanced Flow Cytometry Integration:
Mass cytometry (CyTOF) using antibodies labeled with both fluorophores and metal isotopes
Spectral flow cytometry allowing separation of highly overlapping fluorophores
Imaging flow cytometry combining the quantitative power of flow cytometry with spatial information
Single-Cell Analysis Platforms:
FITC-antibody staining paired with single-cell RNA sequencing
Integration with spatial transcriptomics to correlate protein localization with gene expression
Combination with metabolomics for comprehensive single-cell phenotyping
Click Chemistry Applications:
AI and machine learning are transforming analysis of immunofluorescence and flow cytometry data:
Automated Image Analysis:
Deep learning algorithms for automated segmentation of cellular compartments
Convolutional neural networks (CNNs) for classification of staining patterns
Generative adversarial networks (GANs) for noise reduction and image enhancement
Flow Cytometry Data Analysis:
Unsupervised clustering algorithms (e.g., FlowSOM, PhenoGraph) for identifying cell populations
Dimension reduction techniques (e.g., t-SNE, UMAP) for visualizing high-dimensional data
Anomaly detection for identifying rare cell populations
Cross-Platform Data Integration:
Machine learning models to correlate FITC-antibody signals with genomic or proteomic data
Natural language processing to extract relevant information from literature for experimental design
Transfer learning to apply knowledge gained from one experimental system to another
Quality Control Applications:
Automated detection of batch effects in large-scale experiments
Algorithms to identify optimal compensation matrices
Predictive models for antibody performance based on sequence and structure
Experimental Design Optimization:
Bayesian optimization for antibody titration experiments
Reinforcement learning for developing optimal staining protocols
Predictive models for antibody-antigen interactions based on physicochemical properties
Practical Implementation Considerations:
Requirement for standardized data formats and metadata annotation
Need for sufficient training data from well-validated experiments
Importance of explainable AI models for scientific interpretation
Through these advanced analytical approaches, researchers can extract more information from experiments using FITC-conjugated UMPS antibodies, leading to deeper insights into pyrimidine metabolism and related biological processes.