The NSUN2 Antibody, FITC conjugated is a polyclonal rabbit antibody designed to detect the nucleolar RNA methyltransferase NSUN2, which catalyzes 5-methylcytosine (m5C) modifications in RNAs. This antibody is covalently linked to fluorescein isothiocyanate (FITC), enabling fluorescence-based detection in applications like immunofluorescence (IF) or flow cytometry. Its primary use is in studying NSUN2’s role in RNA metabolism, cancer progression, and cellular stress responses.
NSUN2 is implicated in tumorigenesis, with overexpression linked to poor prognosis in gastric cancer (GC), thyroid cancer, and others . The FITC-conjugated antibody aids in visualizing NSUN2’s subcellular localization (nucleus, cytoplasm) and interactions with partners like SUMO-2/3, which stabilize NSUN2 and promote its nuclear transport .
Gastric Cancer: NSUN2 interacts with SUMO-2/3, enhancing its stability and nuclear localization. Knockdown reduces m5C methylation on target mRNAs (e.g., PIK3R1, PCYT1A), impairing cell proliferation and invasion .
Thyroid Cancer: NSUN2 drives multidrug resistance (MDR) by methylating SRSF6 mRNA, promoting alternative splicing of UAP1 to stabilize ABC transporters. FITC-based NSUN2 detection could localize these effects in drug-resistant cells .
RNA Methylation and Export: NSUN2-mediated m5C modification facilitates mRNA export by recruiting ALYREF, a reader protein. FITC-conjugated antibodies enable tracking of NSUN2’s role in this process .
Glucose Sensing: NSUN2 binds glucose via its N-terminal region, linking metabolic stress to tumorigenesis. Fluorescent imaging could elucidate NSUN2’s spatial dynamics under varying glucose conditions .
| SKU | Size | Price | Quantity |
|---|---|---|---|
| A56053-50ug | 50 µg | $225.00 | 1 vial |
| A56053-100ug | 100 µg | $330.00 | 1 vial |
The antibody targets a 78-amino acid fragment (432–509) of human NSUN2, ensuring specificity for this region. This contrasts with other antibodies (e.g., CAB3443) that target residues 617–708 .
NSUN2 is an RNA methyltransferase that induces 5-methylcytosine (m5C) modification in mRNA, an important chemical posttranscriptional modification. It has been proven to play critical roles in the progression of various cancers, including osteosarcoma and anaplastic thyroid cancer. NSUN2 operates as a "writer" of m5C on target mRNAs, affecting their stability and expression levels. Higher expression of NSUN2 has been correlated with poorer prognosis in cancer patients, making it a potential prognostic marker and therapeutic target .
For optimal results with NSUN2-FITC antibody in immunofluorescence:
Fix cells with 4% paraformaldehyde for 15 minutes at room temperature
Permeabilize with 0.2% Triton X-100 in PBS for 10 minutes
Follow permeabilization with thorough washing (3× PBS, 5 minutes each)
Block with 5% normal serum (matching secondary antibody host) for 1 hour
Incubate with NSUN2-FITC antibody (1:100-1:500 dilution, optimized for your specific antibody) overnight at 4°C
This protocol preserves both cellular morphology and NSUN2 protein epitopes while allowing sufficient antibody penetration for accurate detection of nuclear NSUN2, which is critical when studying its methyltransferase activity in cancer cells .
A multi-step validation approach is recommended:
Positive and negative controls: Use tissues/cells known to express (positive) or not express (negative) NSUN2
Knockdown verification: Compare staining between NSUN2 knockdown/knockout cells and wild-type cells
Western blot correlation: Confirm antibody detects a band of expected size (~86 kDa) in western blot
Competitive binding assay: Pre-incubate antibody with recombinant NSUN2 protein before staining
Cross-validation: Compare results with another validated NSUN2 antibody with a different epitope
In published research, NSUN2 knockdown in osteosarcoma cells showed significantly decreased expression levels, confirming antibody specificity for studying NSUN2-related pathways in cancer progression .
When investigating NSUN2's m5C methyltransferase activity:
| Control Type | Implementation | Purpose |
|---|---|---|
| Positive control | Known NSUN2 target (e.g., FABP5 mRNA) | Validate assay functionality |
| Negative control | Non-target RNA or IgG pulldown | Assess non-specific binding |
| Enzymatic activity control | Catalytically inactive NSUN2 mutant (C271A and C321A) | Distinguish enzymatic vs. binding effects |
| Knockdown/knockout | shRNA or CRISPR targeting NSUN2 | Confirm specificity of observed effects |
| Pharmacological | NSUN2 inhibitor (e.g., cycloleucine) | Validate biochemical inhibition approach |
Studies have employed RNA immunoprecipitation (RIP) and methylated RIP to screen and validate NSUN2 targets, identifying FABP5 as a direct target in osteosarcoma cells. This methodological approach ensures reliable assessment of NSUN2's methyltransferase activity .
For successful dual immunofluorescence with NSUN2-FITC antibody:
Spectral considerations: Pair FITC (excitation ~490nm, emission ~525nm) with fluorophores having minimal spectral overlap (e.g., Cy5, Texas Red)
Sequential staining protocol:
First round: Apply NSUN2-FITC antibody (1:200 dilution) and incubate overnight at 4°C
Wash thoroughly (4× PBS, 5 minutes each)
Second round: Apply non-conjugated primary antibody followed by appropriate secondary antibody
Signal balancing: Adjust acquisition settings to balance the typically strong nuclear NSUN2 signal with other targets
Cross-reactivity prevention:
Block with 5% serum matching the host species of the second primary antibody
Include 0.1% Tween-20 in washing buffer to reduce non-specific binding
This approach has successfully demonstrated co-localization of NSUN2 with reader proteins like YBX1 in nuclei, providing valuable insights into m5C-dependent RNA processing mechanisms .
To investigate NSUN2-RNA interactions:
RNA Immunoprecipitation (RIP):
Cross-link protein-RNA complexes with 1% formaldehyde
Lyse cells and sonicate to fragment RNA
Immunoprecipitate with NSUN2-FITC antibody or separate NSUN2 antibody with magnetic beads
Reverse cross-links and isolate RNA
Perform RT-qPCR for suspected target RNAs (e.g., FABP5)
Methylated RNA Immunoprecipitation (MeRIP):
Extract total RNA from cells
Fragment RNA and denature
Immunoprecipitate with m5C-specific antibody
Analyze enrichment by RNA sequencing or RT-qPCR
Fluorescence in situ hybridization combined with immunofluorescence (FISH-IF):
Perform standard fixation and permeabilization
Hybridize with fluorescently labeled RNA probes for target RNA
Counter-stain with NSUN2-FITC antibody
Analyze co-localization using confocal microscopy
These techniques have successfully identified FABP5 as a direct target of NSUN2 in osteosarcoma cells, demonstrating that NSUN2 binds to and stabilizes FABP5 mRNA through m5C modification .
For correlating NSUN2 expression with drug resistance:
Tissue microarray analysis:
Prepare tissue sections from drug-sensitive and resistant tumors
Perform immunofluorescence with NSUN2-FITC antibody
Quantify nuclear NSUN2 intensity using image analysis software
Correlate with patient treatment response data
Single-cell RNA analysis with drug sensitivity correlation:
Process tumor samples for single-cell RNA sequencing
Cluster cells based on transcriptional profiles
Correlate NSUN2 expression with known drug resistance markers
Apply computational analysis to predict drug sensitivity
Paired pre/post-treatment sample comparison:
Collect matched samples before and after treatment failure
Assess NSUN2 expression changes using immunofluorescence
Quantify changes in expression levels and cellular localization
Research has demonstrated that NSUN2 expression positively correlates with IC50 values of multiple anticancer agents, including both chemotherapy drugs and tyrosine kinase inhibitors, suggesting a role in multidrug resistance in cancer cells .
When encountering variable NSUN2-FITC antibody staining:
| Problem | Potential Cause | Solution |
|---|---|---|
| Weak signal | Insufficient antibody concentration | Increase antibody concentration or incubation time |
| Epitope masking during fixation | Try different fixation methods (e.g., methanol vs. PFA) | |
| Low NSUN2 expression | Increase exposure time or use signal amplification systems | |
| High background | Excessive antibody concentration | Titrate antibody to optimal concentration |
| Inadequate blocking | Increase blocking time or use different blocking reagent | |
| Non-specific binding | Add 0.1-0.3% Triton X-100 to antibody dilution buffer | |
| Punctate nuclear staining | Normal NSUN2 distribution | This may reflect actual nuclear bodies where NSUN2 functions |
| Antibody aggregation | Centrifuge antibody before use or filter through 0.22 μm filter |
For nuclear staining of NSUN2, ensure proper nuclear permeabilization, as NSUN2 is predominantly localized in the nucleus where it performs its methyltransferase activity on target RNAs .
When experimental results contradict expected NSUN2-related phenotypes:
Verify NSUN2 enzymatic activity:
Perform m5C dot blot assays to confirm methyltransferase activity
Use a catalytically inactive NSUN2 mutant as control
Check if total mRNA m5C levels decrease with NSUN2 knockdown
Examine compensatory mechanisms:
Assess expression of other m5C methyltransferases (e.g., NSUN5, NSUN6)
Evaluate potential redundancy in RNA methylation pathways
Validate downstream targets:
Confirm expression changes in known NSUN2 targets (e.g., FABP5)
Perform RIP-seq to identify cell type-specific RNA targets
Context-dependent function analysis:
Investigate tissue/cell type-specific factors affecting NSUN2 function
Examine potential post-translational modifications altering NSUN2 activity
Research has shown that NSUN2 function can vary significantly between cancer types, with specific downstream targets like FABP5 in osteosarcoma and SRSF6 in anaplastic thyroid cancer, highlighting the importance of context-specific analysis .
To investigate NSUN2's role in mRNA stability:
RNA stability assay with NSUN2 modulation:
Treat cells with actinomycin D (5 μg/ml) to inhibit transcription
Harvest RNA at sequential timepoints (0, 1, 2, 4 hours)
Perform RT-qPCR to measure decay rate of target mRNAs
Compare stability between NSUN2 wildtype, knockdown, and overexpression conditions
m5C reader protein analysis:
Use NSUN2-FITC for co-immunoprecipitation with potential reader proteins (e.g., YBX1)
Perform western blot to detect protein-protein interactions
Conduct RIP with YBX1 antibody to identify shared RNA targets
Site-specific m5C analysis:
Employ bisulfite sequencing to map m5C sites in target mRNAs
Correlate methylation sites with NSUN2 binding regions
Create site-directed mutants to evaluate functional importance
Studies have demonstrated that NSUN2 stabilizes FABP5 mRNA through m5C modification, with YBX1 acting as a critical m5C reader that maintains mRNA stability. Knockdown of either NSUN2 or YBX1 decreased the stability and expression of FABP5 mRNA in osteosarcoma cells .
To investigate NSUN2's impact on alternative splicing:
Splicing reporter assays:
Design minigene constructs containing alternative exons
Transfect into cells with NSUN2 overexpression or knockdown
Analyze splicing patterns through RT-PCR
RNA-seq for global splicing analysis:
Perform RNA-seq on NSUN2 modulated cells
Use computational tools (rMATS, VAST-TOOLS) to identify differential splicing events
Validate key events with RT-PCR
CLIP-seq for splicing factor binding:
Conduct CLIP-seq for splicing factors (e.g., SRSF6) in NSUN2 wildtype vs. knockout cells
Map binding sites relative to alternatively spliced regions
Correlate with m5C modification sites
Nuclear-cytoplasmic fractionation:
Separate nuclear and cytoplasmic fractions
Perform western blot with NSUN2-FITC antibody
Analyze distribution of splicing factors in relation to NSUN2 expression
Research has revealed that NSUN2 functions as a "writer" and ALYREF as a "reader" of m5C on SRSF6 mRNA, inducing alternative splicing reprogramming and redirecting the splice form of the UAP1 gene from AGX1 to AGX2 in anaplastic thyroid cancer .
For studying NSUN2's role in cancer metabolism:
Metabolic pathway analysis:
Use NSUN2-FITC antibody to isolate NSUN2-expressing cells via FACS
Perform metabolomics analysis on sorted populations
Compare metabolic profiles between NSUN2-high and NSUN2-low cells
Fatty acid metabolism assessment:
Stain cells with NSUN2-FITC antibody and BODIPY 493/503 for neutral lipids
Quantify lipid content using flow cytometry or fluorescence microscopy
Compare lipid levels in NSUN2 wildtype vs. knockdown/knockout conditions
Metabolic inhibitor studies:
Treat cells with metabolic inhibitors (e.g., Etomoxir for fatty acid oxidation)
Analyze NSUN2 expression and localization changes
Assess impact on m5C target mRNAs involved in metabolism
Research has demonstrated that NSUN2 promotes fatty acid metabolism in osteosarcoma cells by up-regulating FABP5 expression through m5C modification. NSUN2 knockdown led to accumulation of neutral lipids, while NSUN2 overexpression resulted in reduced neutral lipid content, highlighting a direct link between NSUN2 activity and lipid metabolism in cancer cells .
To investigate NSUN2 as a therapeutic target:
NSUN2 inhibitor screening:
Develop high-throughput screening assays using NSUN2-FITC for binding displacement
Test small molecule compounds for inhibition of NSUN2 methyltransferase activity
Validate promising candidates with m5C dot blot assays
Combination therapy assessment:
Treat drug-resistant cells with NSUN2 inhibitors alongside chemotherapy or targeted therapies
Monitor drug sensitivity using cell viability assays
Analyze expression of ABC transporters and drug efflux activity
In vivo efficacy studies:
Establish xenograft models with NSUN2-high, drug-resistant tumors
Administer NSUN2 inhibitors alone or in combination with standard therapies
Assess tumor growth, m5C levels, and expression of NSUN2 target genes
Biomarker development:
Use NSUN2-FITC antibody to establish NSUN2 expression thresholds that predict drug response
Correlate NSUN2 levels with resistance to specific therapeutic agents
Develop companion diagnostic approaches for patient stratification
Research has shown that NSUN2 expression correlates with multidrug resistance in anaplastic thyroid cancer, and NSUN2 inhibitors can reduce NSUN2 enzymatic activity and diminish downstream target expression, presenting a promising therapeutic approach to overcome MDR in cancer .
For accurate quantification of NSUN2 using FITC-conjugated antibodies:
Standardized acquisition parameters:
Establish fixed exposure settings for consistent signal detection
Include calibration standards in each experiment
Account for FITC photobleaching in time-course experiments
Quantification methods:
Mean fluorescence intensity (MFI) for flow cytometry applications
Integrated density measurements for microscopy images
Nuclear:cytoplasmic ratio analysis for localization studies
Normalization strategies:
Use housekeeping proteins as internal controls
Employ ratiometric analysis with stable reference fluorophores
Include biological reference samples across experimental batches
Statistical approaches:
Apply appropriate statistical tests based on data distribution
Utilize correlation analyses for relating NSUN2 levels to phenotypic outcomes
Consider multivariate analyses when examining multiple parameters
Researchers have successfully used these approaches to demonstrate that higher NSUN2 expression predicts poorer prognosis in cancer patients and correlates with resistance to multiple anticancer agents, including both chemotherapy drugs and tyrosine kinase inhibitors .
For investigating NSUN2's role in drug resistance:
| Experimental Approach | Methodology | Key Measurements |
|---|---|---|
| Gene expression modulation | NSUN2 knockout, knockdown, and overexpression | IC50 values for chemotherapy agents and TKIs |
| ABC transporter analysis | Western blot, cell surface staining | Protein levels, glycosylation status, half-life |
| N-linked glycosylation assessment | Lectin binding assays, PNGase F treatment | Glycan profile changes, protein stability |
| m5C target identification | RNA-seq, m5C-RIP, RIP-seq | Differential RNA methylation patterns |
| Pathway analysis | GO analysis, GSEA | Correlation with drug response pathways |