TCOF1 Antibody

What is TCOF1 and why is it significant in research?

TCOF1 (Treacle ribosome biogenesis factor 1) is a nucleolar protein that regulates ribosomal DNA (rDNA) transcription in the nucleolus. It plays critical roles in ribosome biogenesis by connecting RNA polymerase I with enzymes responsible for ribosomal processing and modification . TCOF1 is particularly significant in research due to its involvement in Treacher Collins–Franceschetti syndrome (TCS) and its emerging roles in cancer biology, including hepatocellular carcinoma (HCC) and triple-negative breast cancer . Recent studies have demonstrated that TCOF1 coordinates oncogenic activation and rRNA production to promote tumorigenesis, making it a potential therapeutic target in cancer research .

How should I select the appropriate TCOF1 antibody for my research application?

The selection of a TCOF1 antibody should be guided by your specific research application and the cellular localization of your target. Consider these methodological factors:

• Application compatibility: Verify the antibody has been validated for your specific application (WB, IHC, ICC/IF, IP, ELISA)

• Species reactivity: Confirm reactivity with your experimental model (human, mouse, etc.)

• Epitope recognition: Choose antibodies targeting specific domains based on your research question (N-terminal, C-terminal, or central repeat domain)

• Clonality considerations: Polyclonal antibodies offer broader epitope recognition but may have greater batch-to-batch variation compared to monoclonals

• Validation data: Review images from validation studies to confirm expected localization patterns (TCOF1 typically shows nucleolar localization)

For nucleolar localization studies, antibodies validated for immunofluorescence showing distinct nucleolar staining patterns are most suitable, as TCOF1 characteristically localizes to the nucleolar fibrillar center .

What are the expected molecular weights for TCOF1 detection in Western blotting?

TCOF1 typically exhibits variability in observed molecular weights due to multiple isoforms and post-translational modifications. Researchers should be aware of the following expectations:

The discrepancy between calculated and observed molecular weights is typically attributed to post-translational modifications and the high proportion of disordered regions (~73% of TCOF1 consists of intrinsically disordered regions) . When troubleshooting, confirm specificity through positive controls with known TCOF1 expression (such as U-2 OS or MCF-7 cell lines) .

How should I design experiments to investigate TCOF1's role in cancer progression?

When investigating TCOF1's role in cancer progression, a comprehensive experimental design should include:

• Expression analysis:

  • Analyze TCOF1 expression across cancer stages using RNA-seq data (e.g., from TCGA datasets)

  • Validate at protein level using IHC on patient tissue microarrays with appropriate controls

• Functional studies:

  • Employ CRISPR/Cas9 or RNAi-based knockdown approaches

  • Generate stable TCOF1-overexpression cell lines using lentiviruses

  • Assess phenotypic effects using proliferation assays (CCK8), colony formation assays, and migration/invasion assays

• Mechanistic investigations:

  • Examine rRNA production changes using qRT-PCR for pre-rRNA transcripts

  • Analyze downstream oncogenic pathways (KRAS-activated genes, EMT markers) using RNA-seq/qPCR

  • Investigate immune infiltration correlations using bioinformatics approaches or immune cell co-culture systems

• In vivo validation:

  • Establish xenograft models with TCOF1-manipulated cells

  • Monitor tumor growth, volume, and weight over time

  • Examine histopathological features of resulting tumors

What controls are essential when using TCOF1 antibodies in immunohistochemistry and immunofluorescence?

Proper controls are critical for accurate interpretation of TCOF1 immunostaining. The following controls should be incorporated:

• Positive tissue controls:

  • For IHC: Testis tissue shows strong nuclear and nucleolar staining in cells of seminiferous ducts

  • For ICC/IF: U-2 OS (human osteosarcoma) or MCF-7 (breast cancer) cell lines demonstrate reliable nucleolar staining

• Negative tissue controls:

  • Liver tissue typically shows very low TCOF1 positivity, serving as a useful low-expression control

  • Primary cell types with minimal nucleolar activity

• Technical controls:

  • Antibody omission control (all reagents except primary antibody)

  • Isotype control (irrelevant antibody of same isotype and concentration)

  • Peptide competition/blocking experiments using the immunizing peptide

• Validation controls:

  • TCOF1 knockdown/knockout cells to confirm antibody specificity

  • Multiple antibodies targeting different epitopes to confirm consistent staining patterns

  • Correlation with RNA expression data when available

• Subcellular localization control:

  • Co-staining with established nucleolar markers (e.g., UBF, fibrillarin) to confirm appropriate nucleolar localization

Documenting these controls systematically enhances the reliability and reproducibility of TCOF1 immunodetection experiments.

How can TCOF1 antibodies be used to investigate the relationship between TCOF1 and immune infiltration in cancer?

Investigating the inverse correlation between TCOF1 expression and antitumor immune cell infiltration requires a strategic approach combining immunodetection and functional analyses:

• Multiplexed immunostaining approach:

  • Perform multiplex IF/IHC with TCOF1 antibody alongside immune cell markers (CD8+ T cells, NK cells, dendritic cells)

  • Quantify spatial relationships between TCOF1-high tumor regions and immune-dense regions

  • Analyze using digital pathology platforms with multi-channel capabilities

• Flow cytometry applications:

  • Dissociate tumors and perform intracellular staining for TCOF1 alongside surface immune markers

  • Quantify correlations between TCOF1 expression levels and immune cell percentages

  • Sort TCOF1-high versus TCOF1-low tumor cells for downstream analyses

• Mechanistic investigations:

  • Analyze secretome differences between TCOF1-high and TCOF1-low cancer cells

  • Examine changes in chemokine/cytokine production using targeted arrays

  • Assess impact on immune cell migration using transwell chemotaxis assays

• In vivo models:

  • Develop syngeneic mouse models with TCOF1-manipulated cancer cells

  • Analyze immune infiltration patterns using flow cytometry and immunohistochemistry

  • Test immunotherapy responsiveness in TCOF1-high versus TCOF1-low tumors

This multi-modal approach can elucidate whether the inverse correlation between TCOF1 expression and immune infiltration is causal or correlative, potentially identifying new immunotherapy strategies.

What approaches can resolve discrepancies in TCOF1 antibody detection between different experimental systems?

When encountering inconsistent TCOF1 antibody results across experimental systems, implement this systematic resolution strategy:

• Epitope accessibility analysis:

  • Different fixation protocols may mask epitopes - compare methanol vs. PFA fixation

  • Test various antigen retrieval methods (heat-mediated with citrate buffer pH 6 is recommended)

  • Consider native vs. denatured conditions affecting epitope conformation

• Isoform-specific detection:

  • TCOF1 has multiple isoforms (97 kDa, 144 kDa, 152 kDa calculated)

  • Map antibody epitopes to specific domains to determine isoform recognition patterns

  • Use RT-PCR to verify isoform expression in your experimental system

• Post-translational modification interference:

  • TCOF1 undergoes monoubiquitination by BCR(KBTBD8) complex

  • Phosphorylation states may alter antibody binding

  • Compare detection after phosphatase or deubiquitinase treatment

• Cross-validation approach:

  • Employ multiple antibodies targeting different TCOF1 epitopes

  • Compare polyclonal vs. monoclonal antibody detection patterns

  • Supplement with genetic approaches (tagged TCOF1 constructs)

• Sample preparation optimization:

  • For Western blotting: Test different lysis buffers and protein extraction methods

  • For IHC/IF: Compare whole tissue, tissue microarrays, and cultured cells

  • Consider subcellular fractionation to enrich nucleolar proteins

This systematic troubleshooting workflow helps identify the source of variability and establish reliable detection protocols for your specific experimental system.

How can I optimize nucleolar extraction protocols for enhanced TCOF1 detection?

Optimizing nucleolar extraction for TCOF1 detection requires attention to preserving nucleolar integrity while maximizing protein recovery:

• Stepwise fractionation procedure:

  • Begin with NE-PER nuclear and cytoplasmic extraction kit (Thermo Fisher Scientific) for initial fractionation

  • Further isolate nucleoli using sucrose density gradient ultracentrifugation

  • Maintain samples at 4°C throughout processing to prevent protein degradation

• Buffer optimization for nucleolar proteins:

  • Use high-salt extraction buffer (>300 mM NaCl) to efficiently release nucleolar proteins

  • Include phosphatase inhibitors to preserve phosphorylation states

  • Add 0.1% SDS or 1% Triton X-100 to disrupt nucleolar protein complexes while maintaining antibody epitopes

• Validation of fraction purity:

  • Confirm nucleolar enrichment using established markers (fibrillarin, nucleolin)

  • Verify depletion of non-nucleolar proteins (cytoplasmic: GAPDH, α-tubulin; nucleoplasmic: HDAC1)

  • Quantify enrichment factor by comparing TCOF1 signal in total lysate versus nucleolar fraction

• Western blot detection considerations:

  • Use 8-10% SDS-PAGE gels for optimal resolution of high-molecular-weight TCOF1 (observed at 220 kDa)

  • Load 10-15 μg of nucleolar protein per lane

  • Extend transfer time for complete transfer of large proteins

This optimized protocol significantly enhances the signal-to-noise ratio for TCOF1 detection compared to whole-cell lysates, enabling more precise quantification of nucleolar TCOF1 levels.

What are the best practices for evaluating TCOF1 knockdown efficiency in functional studies?

Comprehensive evaluation of TCOF1 knockdown efficiency requires multi-level analysis:

• mRNA level assessment:

  • Design qRT-PCR primers spanning different exon junctions to detect all relevant isoforms

  • Include primers targeting the region of knockdown to directly measure targeted reduction

  • Normalize to multiple reference genes (GAPDH, ACTB, and a tissue-specific reference gene)

• Protein level validation:

  • Western blot analysis using antibodies targeting epitopes outside the knockdown region

  • Quantify band intensity relative to loading controls (GAPDH or α-tubulin)

  • Consider subcellular fractionation to specifically assess nucleolar depletion

• Functional readouts:

  • Measure pre-rRNA synthesis using pulse-labeling with 5-fluorouridine

  • Assess nucleolar morphology changes using immunofluorescence

  • Quantify downstream KRAS-activated and EMT genes as functional validation

• Rescue experiments:

  • Generate knockdown-resistant TCOF1 constructs (with silent mutations in the target region)

  • Confirm phenotype reversal upon expression of knockdown-resistant construct

  • Include domain mutants to map functional regions

• Temporal considerations:

  • Establish time course of knockdown to determine optimal analysis timepoint

  • Monitor for potential compensatory mechanisms in prolonged knockdown

A knockdown efficiency of >70% at both mRNA and protein levels is generally considered sufficient for functional studies, with <50% potentially leading to incomplete phenotypes or inconsistent results.

How can I resolve non-specific binding issues with TCOF1 antibodies in Western blotting?

Non-specific binding with TCOF1 antibodies can be systematically addressed using this optimized protocol:

• Blocking optimization:

  • Test different blocking agents (5% BSA frequently performs better than milk for phosphorylated proteins)

  • Extend blocking time to 2 hours at room temperature

  • Add 0.1% Tween-20 to washing buffers to reduce hydrophobic interactions

• Antibody dilution optimization:

  • Titrate primary antibody concentration (recommended ranges: 1:500-1:2000 for WB)

  • Extend primary antibody incubation to overnight at 4°C

  • Include 0.1-0.5% BSA in antibody dilution buffer to reduce non-specific binding

• Sample preparation refinements:

  • Include additional protease inhibitors in lysis buffer

  • Centrifuge lysates at 16,000 × g for 10 min at 4°C to remove debris

  • Consider nuclear/cytoplasmic fractionation to enrich for TCOF1

• Validation approaches:

  • Include TCOF1 knockdown/knockout samples as negative controls

  • Perform peptide competition assays with the immunizing peptide

  • Compare multiple antibodies targeting different TCOF1 epitopes

• Technical optimizations:

  • Reduce SDS concentration in transfer buffer for large proteins

  • Use PVDF membrane instead of nitrocellulose for better protein retention

  • Apply longer blocking times (2+ hours) to reduce background

When interpreting results, focus on the band at the expected molecular weight (152-220 kDa range), as TCOF1 frequently appears larger than its calculated weight due to post-translational modifications .

What advanced techniques can be used to study TCOF1's role in phase separation and nucleolar organization?

To investigate TCOF1's role in phase separation and nucleolar organization, implement these advanced methodological approaches:

• Live-cell imaging techniques:

  • Generate fluorescently-tagged TCOF1 constructs (preferably with small tags like mNeonGreen)

  • Perform FRAP (Fluorescence Recovery After Photobleaching) to measure protein mobility within nucleoli

  • Use optogenetic tools to manipulate TCOF1 phase separation in real-time

• Phase separation assays:

  • Purify recombinant TCOF1 (full-length or specific domains)

  • Assess in vitro phase separation properties under varying conditions (salt, pH, protein concentration)

  • Monitor phase separation using turbidity measurements and microscopy

  • Test interaction with known nucleolar phase-separated proteins

• Structural disorder analysis:

  • Apply IUPred2 and ANCHOR2 computational prediction tools to map disordered regions

  • Correlate disordered regions with phase separation properties

  • Design mutants with altered disorder propensity to test functional impacts

• Advanced microscopy applications:

  • Implement super-resolution microscopy (HIS-SIM) to visualize TCOF1's subnucleolar distribution

  • Use expansion microscopy to physically enlarge nucleolar structures

  • Apply correlative light and electron microscopy to link protein localization with ultrastructural features

• Protein-protein interaction landscape:

  • Perform BioID or APEX proximity labeling with TCOF1 as bait

  • Identify phase separation partners using mass spectrometry

  • Validate interactions using co-IP and in vitro reconstitution experiments

The intrinsically disordered nature of approximately 73% of TCOF1 protein facilitates extensive interactions with other proteins through phase separation . This property is crucial for executing various physiological processes within cells and may be disrupted in pathological conditions like Treacher Collins syndrome and cancer.