TXNL4A Antibody

What is TXNL4A and what biological processes is it involved in?

TXNL4A (Thioredoxin-like protein 4A) is a member of the U5 small ribonucleoprotein particle (snRNP) that plays a crucial role in pre-mRNA splicing. It contains a thioredoxin-like fold and interacts with multiple proteins, including the polyglutamine tract-binding protein 1 (PQBP1). The protein is implicated in RNA processing pathways and has been associated with Burn-McKeown syndrome, a rare disorder characterized by craniofacial dysmorphisms, cardiac defects, and hearing loss . Recent research has identified TXNL4A as a potential prognostic marker in hepatocellular carcinoma and other cancers .

What is the molecular weight and structure of the TXNL4A protein?

TXNL4A has a calculated molecular weight of approximately 16.8 kDa (16,786 Da). It belongs to the DIM1 protein family and has a thioredoxin-like fold structural motif. This structure facilitates its interaction with other proteins involved in RNA splicing complexes. The protein is encoded by the TXNL4A gene, which produces multiple transcript variants through alternative splicing .

What criteria should be considered when selecting a TXNL4A antibody for research?

When selecting a TXNL4A antibody for research applications, consider these critical factors:

• Species reactivity: Ensure the antibody reacts with your species of interest (e.g., human, mouse).

• Clonality: Determine whether a polyclonal or monoclonal antibody is more suitable for your application.

• Validated applications: Verify that the antibody has been validated for your intended application (WB, IHC, ICC, etc.).

• Immunogen information: Check the immunogen used to generate the antibody to ensure it will recognize your target region.

• Validation data: Review western blot images and other validation data to confirm specificity.

• Storage requirements: Confirm you can meet the proper storage conditions (-20°C long-term, 4°C short-term) .

Always review published literature to identify antibodies that have been successfully used in experiments similar to yours.

How can I validate the specificity of a TXNL4A antibody for my experiments?

To validate the specificity of a TXNL4A antibody:

• Positive and negative controls: Use tissues or cell lines known to express or not express TXNL4A.

• Knockdown/knockout validation: Compare antibody reactivity in wild-type versus TXNL4A knockdown/knockout samples.

• Multiple antibody comparison: Use multiple antibodies targeting different epitopes of TXNL4A.

• Peptide competition assay: Pre-incubate the antibody with the immunizing peptide to block specific binding.

• Western blot analysis: Confirm single band detection at the expected molecular weight (16.8 kDa).

• Cross-reactivity testing: Test antibody against related proteins to ensure specificity .

Document all validation steps thoroughly to support the reliability of your experimental findings.

What are the optimal conditions for using TXNL4A antibodies in Western blotting?

For optimal Western blot results with TXNL4A antibodies:

• Sample preparation:

  • Use RIPA or NP-40 buffer with protease inhibitors

  • Load 20-40 μg of total protein per lane

• Electrophoresis conditions:

  • 12-15% SDS-PAGE gel (optimal for low molecular weight proteins)

  • Include positive control (e.g., HepG2 cell lysate for hepatocellular samples)

• Transfer conditions:

  • PVDF membrane (0.22 μm pore size)

  • 100V for 60-90 minutes at 4°C

• Antibody dilution:

  • Primary antibody: 1:500-1:2000 dilution in 5% BSA/TBST

  • Incubate overnight at 4°C

• Detection method:

  • HRP-conjugated secondary antibody (1:5000)

  • ECL substrate for visualization

Expected result: Single band at approximately 16.8 kDa with minimal background.

How can TXNL4A antibodies be used to study its role in RNA splicing mechanisms?

To investigate TXNL4A's role in RNA splicing:

• Co-immunoprecipitation (Co-IP):

  • Use TXNL4A antibody to pull down splicing complexes

  • Identify interacting partners through mass spectrometry

  • Analyze splicing complex formation under different conditions

• RNA-Immunoprecipitation (RIP):

  • Cross-link protein-RNA complexes

  • Immunoprecipitate with TXNL4A antibody

  • Identify bound RNAs through sequencing

• Immunofluorescence microscopy:

  • Visualize co-localization with other splicing factors

  • Track dynamic changes during cell cycle or stress responses

• Splicing reporter assays:

  • After TXNL4A knockdown/overexpression

  • Assess changes in splicing patterns using minigene constructs

These approaches enable comprehensive analysis of TXNL4A's functional interactions within the splicing machinery.

What are common troubleshooting strategies for weak or non-specific TXNL4A antibody signals?

When encountering weak or non-specific signals:

For optimal results, always use freshly prepared buffers and follow the manufacturer's recommended storage conditions (-20°C long-term, 4°C for up to one month) .

How should TXNL4A antibodies be stored and handled to maintain reactivity?

To maintain optimal TXNL4A antibody reactivity:

• Long-term storage:

  • Store at -20°C in small aliquots to avoid repeated freeze-thaw cycles

  • Original formulation typically contains 50% glycerol as cryoprotectant

• Short-term storage:

  • Store at 4°C for up to one month for frequent use

  • Avoid exposure to light for fluorescently-labeled antibodies

• Handling precautions:

  • Allow antibody to equilibrate to room temperature before opening

  • Centrifuge briefly before opening to collect solution at the bottom

  • Use sterile technique when removing aliquots

  • Return to proper storage temperature immediately after use

• Avoid degradation factors:

  • Minimize freeze-thaw cycles (≤5 recommended)

  • Avoid exposure to heat or extreme pH conditions

  • Protect from microbial contamination

Proper storage and handling significantly extend antibody shelf-life and maintain consistent experimental results.

How can TXNL4A antibodies be utilized to investigate its role in hepatocellular carcinoma pathogenesis?

Advanced research techniques for investigating TXNL4A in HCC include:

• Tissue microarray (TMA) immunohistochemistry:

  • Compare TXNL4A expression across tumor stages and grades

  • Correlate expression with patient survival data

  • Analyze co-expression with other cancer biomarkers

• Single-cell RNA sequencing integration:

  • Combine scRNA-seq data with TXNL4A protein expression

  • Identify cell populations with altered TXNL4A expression

  • Analyze correlation with CD8+ T cell infiltration profiles

• ChIP-sequencing approaches:

  • Investigate transcriptional regulation of TXNL4A

  • Identify potential therapeutic targets affecting TXNL4A expression

• Multiplexed imaging:

  • Simultaneously visualize TXNL4A with immune markers

  • Analyze spatial relationships within the tumor microenvironment

• Functional studies:

  • CRISPR-Cas9 modulation of TXNL4A in HCC cell lines

  • Analysis of resulting transcriptome and splicing alterations

Recent studies have shown TXNL4A is highly expressed in HCC and correlates with clinical features, making it a promising target for further investigation.

What methods can be used to study TXNL4A's interaction with the immune microenvironment in cancer?

To study TXNL4A's immunological interactions:

• Multiplex immunofluorescence imaging:

  • Co-stain for TXNL4A, immune cell markers (CD8, CD4, etc.)

  • Quantify spatial relationships between TXNL4A+ cells and immune infiltrates

  • Analyze tumor-immune boundaries and interaction zones

• Mass cytometry (CyTOF):

  • Profile TXNL4A expression alongside immune markers

  • Create high-dimensional maps of immune populations

• Single-cell analysis:

  • Integrate scRNA-seq with TXNL4A protein data

  • Correlate TXNL4A expression with immune cell states

  • Identify cell clusters with significant associations

• Functional immune assays:

  • Co-culture TXNL4A-modulated cancer cells with immune cells

  • Assess changes in immune cytotoxicity and activation

  • Measure cytokine production and immune signaling

• In vivo models:

  • Generate TXNL4A knockout/overexpression tumor models

  • Analyze immune infiltration and response to immunotherapy

Research has demonstrated correlation between TXNL4A expression and CD8+ T cell infiltration in HCC, suggesting important immunomodulatory functions.

How should contradictory findings about TXNL4A expression in different cancer types be interpreted?

When encountering contradictory findings regarding TXNL4A expression:

• Consider tissue-specific context:

  • TXNL4A may have divergent roles across different tissues

  • Analyze tissue-specific splicing requirements and partners

• Examine methodological differences:

  • Compare antibody clones and epitopes used across studies

  • Assess detection methods (WB vs. IHC vs. RNA-seq)

  • Evaluate normalization strategies and reference genes

• Account for tumor heterogeneity:

  • Subtype-specific expression patterns may exist

  • Single-cell analysis may reveal population-specific expressions

  • Consider microenvironmental influences on expression

• Statistical considerations:

  • Evaluate sample sizes and statistical power

  • Review patient cohort characteristics and selection criteria

  • Assess the robustness of findings through meta-analysis

• Functional validation:

  • Confirm expression findings with multiple orthogonal techniques

  • Validate functional consequences through gain/loss-of-function studies

Current evidence shows TXNL4A is highly expressed in most tumors including HCC, BLCA, BRCA, CHOL, COAD, ESCA, KICH, LUAD, LUSC, PRAD, and UCEC, but expression patterns and prognostic significance may vary.

What bioinformatic approaches can be used to integrate TXNL4A antibody-based proteomic data with transcriptomic data?

For integrating TXNL4A proteomic and transcriptomic data:

• Multi-omics correlation analysis:

  • Calculate protein-mRNA correlation coefficients

  • Identify discordant expression patterns suggesting post-transcriptional regulation

  • Apply linear and non-linear modeling approaches

• Pathway enrichment integration:

  • Perform GSEA on both protein and transcript datasets

  • Identify convergent and divergent pathway activations

  • Apply weighted gene co-expression network analysis (WGCNA)

• Splicing-aware integration:

  • Analyze alternative splicing events in RNA-seq data

  • Connect protein isoform detection with transcript isoform abundance

  • Integrate spliceosome complex protein interactions

• Machine learning approaches:

  • Train predictive models using combined proteomic-transcriptomic features

  • Identify feature importance in cancer classification

  • Apply transfer learning across tumor types

• Visualization techniques:

  • Generate integrated heatmaps and correlation plots

  • Develop dimensionality reduction visualizations (t-SNE, UMAP)

  • Create interactive multi-omics dashboards

These approaches can reveal functional consequences of TXNL4A alterations across biological levels and identify potential therapeutic vulnerabilities.