TRIM33 Monoclonal Antibody

What are the optimal applications for TRIM33 antibodies in laboratory research?

TRIM33 antibodies have been validated for multiple experimental applications with specific recommended parameters:

When working with TRIM33 antibodies, it's essential to optimize conditions for your specific experimental system. For immunohistochemistry applications, antigen retrieval is recommended with TE buffer pH 9.0, with citrate buffer pH 6.0 as an alternative . For Western blot applications, the observed molecular weight typically ranges from 140-150 kDa, which differs slightly from the calculated molecular weight of 122 kDa, likely due to post-translational modifications .

How should I store and handle TRIM33 antibodies to maintain optimal activity?

For maximum antibody stability and performance:

• Store antibodies at -20°C in their recommended buffer (typically PBS with 0.02% sodium azide and 50% glycerol at pH 7.3)

• Antibodies remain stable for one year after shipment when properly stored

• Aliquoting is generally unnecessary for -20°C storage

• Small volume preparations (20μl) may contain 0.1% BSA as a stabilizer

When working with TRIM33 antibodies, avoid repeated freeze-thaw cycles and maintain cold chain management during experimental procedures to prevent degradation and maintain consistent performance across experiments.

What controls should I include when using TRIM33 antibodies for knockdown/knockout studies?

When designing TRIM33 knockdown experiments, proper controls are essential for result validation:

• Verification of knockdown efficiency: Always quantify TRIM33 knockdown at both mRNA and protein levels. Research shows that effective TRIM33 siRNA typically achieves more than 60% knockdown of mRNA levels as measured by real-time PCR .

• Appropriate controls: Include both non-transfected controls and scramble siRNA (siSCR) controls in all experiments to distinguish between specific TRIM33 knockdown effects and non-specific transfection effects .

• Functional readouts: When studying TRIM33 in inflammatory responses, measure relevant cytokines such as IL-1β and IL18 by ELISA to confirm functional consequences of TRIM33 depletion .

• Multiple cell lines: Validate findings across different cell types when possible, as TRIM33 functions may vary between cellular contexts (e.g., BGC-823 and SGC-7901 gastric cancer cell lines show similar but not identical responses to TRIM33 knockdown) .

How can I validate the specificity of TRIM33 antibodies in my experimental system?

To ensure antibody specificity and reliable results:

• Genetic controls: Include TRIM33 knockdown or knockout samples as negative controls. The absence or significant reduction of signal in these samples confirms antibody specificity .

• Multiple antibody validation: When possible, use antibodies from different sources or that recognize different epitopes to confirm findings.

• Expected molecular weight verification: For TRIM33, confirm detection at 140-150 kDa in Western blot applications, which corresponds to the observed molecular weight rather than the calculated 122 kDa .

• Cross-reactivity testing: If working across species, confirm reactivity with your species of interest. Available TRIM33 antibodies show reactivity with human samples, and some are validated for mouse and rat samples as well .

How can TRIM33 antibodies be utilized to study TGF-β signaling pathway modulation?

TRIM33 plays a crucial role in regulating the TGF-β signaling pathway, making this interaction a valuable research target:

• Pathway component analysis: Use TRIM33 antibodies in combination with antibodies against Smad proteins to analyze changes in the TGF-β signaling pathway. Research shows that TRIM33 knockdown results in upregulation of p-Smad2 (Ser465/467), Smad2, Smad3, and Smad4 .

• EMT marker examination: TRIM33 modulation affects epithelial-mesenchymal transition (EMT) markers. When TRIM33 is downregulated, vimentin and N-Cadherin are upregulated while E-Cadherin is downregulated, suggesting activation of EMT programs .

• Quantitative analysis: Perform quantitative Western blot analysis to measure changes in protein expression levels. For example, TRIM33 knockdown has been shown to decrease E-cadherin expression (1.48 ± 0.09 vs 1.93 ± 0.19 in control cells) while increasing vimentin (1.52 ± 0.07 vs 0.76 ± 0.05) and N-cadherin (1.42 ± 0.10 vs 0.65 ± 0.06) .

• SMAD4 ubiquitination: Use TRIM33 antibodies in ubiquitination assays to study how TRIM33 promotes SMAD4 ubiquitination, nuclear exclusion, and degradation via the ubiquitin proteasome pathway .

What techniques are recommended for studying TRIM33's role in chromatin binding and epigenetic regulation?

TRIM33's function in chromatin regulation can be studied using several advanced techniques:

• ChIP-Seq analysis: Chromatin immunoprecipitation followed by sequencing has revealed over 4000 TRIM33 binding sites in the genome, enriched near genes involved in stem cell maintenance and mesoderm development .

• Technical considerations for ChIP-Seq:

  • Use high-quality antibodies validated for immunoprecipitation

  • Process samples using appropriate algorithms (e.g., MACS v2.1.0 with p-value cutoff of 1e-7)

  • Remove known false ChIP-Seq peaks using blacklists

  • Extend alignments in silico to match genomic fragment length (typically 200 bp)

  • Create genomic signal maps stored in bigWig files for visualization

• Co-occupancy analysis: Nearly half of TRIM33 binding sites overlap with Ctcf insulator protein binding sites, suggesting functional interactions. Consider performing sequential ChIP or co-immunoprecipitation experiments to explore these relationships .

• Integration with other epigenetic marks: Combine TRIM33 ChIP-Seq with analysis of histone modifications such as H3K27Ac to gain insights into TRIM33's role in active chromatin regulation .

How can TRIM33 antibodies be applied to investigate cancer progression mechanisms?

TRIM33 has significant implications for cancer research, particularly in gastric cancer:

What methodologies are effective for investigating TRIM33's function in immune response regulation?

TRIM33 plays a role in cytosolic RNA sensing and immune responses:

• RNA stimulation models: Using cytosolic high molecular weight (HMW) poly I:C, bacterial RNA, or viral RNA (such as reoviral RNA) to stimulate cells can help investigate TRIM33's role in RNA sensing pathways .

• Cytokine measurement: Quantify IL-1β and IL-18 secretion by ELISA following RNA stimulation in control versus TRIM33-depleted cells. Research shows reduced cytokine production in TRIM33 knockdown cells in response to cytosolic RNA stimulation .

• Ubiquitination analysis: TRIM33 can bind DHX33 directly and induce its ubiquitination via lysine 218 upon dsRNA stimulation. Analyze this process using ubiquitination assays combined with mutational studies of key residues .

• Primary cell models: Validate findings in primary cell systems such as human primary monocyte-derived macrophages (hPMDM) to ensure physiological relevance of results .

Why might I observe discrepancies between calculated and observed molecular weights for TRIM33?

The calculated molecular weight of TRIM33 is 122 kDa, but the observed molecular weight in Western blot applications is typically 140-150 kDa . This discrepancy could result from:

• Post-translational modifications: Ubiquitination, phosphorylation, or other modifications can increase apparent molecular weight.

• Protein isoforms: Alternative splicing may generate different protein variants.

• Highly charged domains: Some protein domains can bind disproportionate amounts of SDS, altering migration patterns.

To address this issue:

• Include positive control lysates such as COLO 320 cells, MCF-7 cells, or PC-3 cells that are known to express TRIM33

• Consider using gradient gels to improve resolution of higher molecular weight proteins

• Validate identity using mass spectrometry if critical for your research

How can I optimize ChIP protocols for studying TRIM33 chromatin binding?

For effective ChIP studies of TRIM33:

• Library preparation: After immunoprecipitation, prepare Illumina sequencing libraries through end-polishing, dA-addition, and adaptor ligation followed by PCR amplification .

• Sequencing parameters: Use appropriate sequencing depth (e.g., 75 nt reads, single end on platforms such as Illumina's NextSeq 500) .

• Data analysis workflow:

  • Align reads to the reference genome (e.g., mm10 for mouse) using BWA algorithm

  • Remove duplicate reads and filter for uniquely mapped reads (mapping quality ≥25)

  • Extend alignments to match fragment length (typically 200 bp)

  • Assign to bins along the genome (e.g., 32-nt bins)

  • Store histograms in bigWig files

  • Determine peak locations using algorithms like MACS with appropriate cutoffs

• Control datasets: Include input DNA controls and consider including datasets for interacting factors such as Ctcf to identify regions of co-occupancy .