TCF7L1 Antibody, Biotin conjugated

What is TCF7L1 and what are its primary functions in cellular biology?

TCF7L1 (Transcription Factor 7-Like 1) is a member of the TCF/LEF family of transcription factors that functions primarily as a transcriptional repressor within the Wnt signaling pathway. It contains a high-mobility group (HMG) box DNA-binding domain that recognizes specific target sequences. TCF7L1 plays critical roles in embryonic stem cell (ESC) biology, where it serves as a dominant downstream effector influencing the balance between pluripotency and differentiation. In ESCs, TCF7L1 represses genes important for maintaining pluripotency and self-renewal, as well as those involved in lineage commitment. This repression is partially mediated through interactions with corepressors such as transducin-like enhancer of split 2 (TLE2) and C-terminal Binding Protein (CtBP) . TCF7L1 has also been implicated in cancer progression, particularly in colorectal cancer where it promotes cell migration and invasion .

What structural elements of TCF7L1 are most commonly targeted by antibodies?

Most commercially available TCF7L1 antibodies target either the N-terminal or C-terminal regions of the protein, with some specifically recognizing internal domains. The N-terminal region antibodies (such as ABIN6972849) target sequences important for protein-protein interactions, while C-terminal antibodies (such as ABIN3044552) recognize the region containing amino acids 561-588 (sequence: SFPATLHAHQALPVLQAQPLSLVTKSAH) . The HMG-box DNA binding domain, which spans approximately amino acids 330-410, is another important structural element sometimes targeted. When selecting an antibody for research applications, the specific epitope recognized can significantly impact experimental outcomes, particularly if certain protein-protein interactions might mask the epitope in native conditions .

How does TCF7L1 expression and function differ between stem cells and differentiated tissues?

TCF7L1 expression is tightly regulated during development, with high expression in pluripotent stem cells that decreases during differentiation. In human embryonic stem cells (hESCs), which represent the "primed" state of pluripotency resembling postimplantation epiblast cells, TCF7L1 helps retain pluripotency while simultaneously preparing genes for differentiation . In mouse embryonic stem cells (mESCs), TCF7L1 promotes the transition from naïve to primed pluripotency . Its expression and activity are regulated by various mechanisms, including post-translational modifications and protein-protein interactions. In differentiated tissues, TCF7L1 generally shows lower expression but maintains tissue-specific functions, particularly in contexts where Wnt signaling modulation is important. Western blot analysis has detected TCF7L1 expression in human pancreas and lung tissues, as well as in the nuclei of embryonic stem cells .

What are the critical factors to consider when selecting a TCF7L1 antibody for specific applications?

When selecting a TCF7L1 antibody, researchers should evaluate several parameters based on their experimental needs:

The antibody should be validated for the specific application and experimental system. For ChIP or CUT&RUN experiments that study TCF7L1-DNA interactions, antibodies validated for these applications (such as ABIN6972849) should be prioritized . For protein-protein interaction studies, antibodies targeting regions not involved in these interactions are preferable to avoid epitope masking .

How can researchers validate the specificity of TCF7L1 antibodies in their experimental system?

Comprehensive validation of TCF7L1 antibodies should include multiple approaches:

• Western blot analysis with positive and negative controls:

  • Positive controls: Cell lines known to express TCF7L1 (e.g., embryonic stem cells)

  • Negative controls: TCF7L1 knockout cells or siRNA-mediated knockdown

  • Expected band size: Approximately 70 kDa under reducing conditions

• Immunofluorescence with specificity controls:

  • Observe nuclear localization pattern consistent with transcription factor function

  • Include secondary-only controls to assess background

  • Compare with TCF7L1 knockdown samples to confirm signal reduction

• ChIP-seq validation:

  • Enrichment at known TCF7L1 binding sites

  • Motif analysis showing enrichment of TCF/LEF binding motifs

  • Comparison with published TCF7L1 ChIP-seq datasets

• Functional validation:

  • Mutational analysis: Use TCF7L1 with mutations in the targeted epitope or DNA-binding domain (such as L387P and P411L that interfere with DNA binding capacity)

  • Comparison of wild-type and mutant TCF7L1 effects in reporter assays (e.g., TOPflash assay)

What critical controls should be included when using biotin-conjugated TCF7L1 antibodies?

When working with biotin-conjugated TCF7L1 antibodies, several essential controls should be incorporated:

• Background biotinylation control:

  • Include wild-type cells without biotin-conjugated antibody to assess endogenous biotinylated proteins

  • This is particularly important as research has shown "considerable background biotinylation in wildtype mESCs, even in the absence of biotin"

• Blocking controls:

  • Use free biotin or streptavidin pre-incubation to demonstrate specificity of the biotin-streptavidin interaction

  • Include non-biotinylated primary antibody competition to confirm epitope specificity

• Specificity controls:

  • TCF7L1 knockdown or knockout samples to verify signal reduction

  • Pre-absorption of the antibody with the immunizing peptide

  • Isotype control antibodies conjugated to biotin

• Technical controls:

  • Secondary reagent-only controls (streptavidin without primary antibody)

  • Cross-reactivity assessment with related TCF family members (TCF7, TCF7L2, LEF1)

  • Known TCF7L1-interacting proteins (e.g., TLE3/4, β-catenin) should co-localize or co-precipitate as a positive control

How can BioID approaches be optimized for studying TCF7L1 interactome?

BioID (proximity-based biotin labeling) has been effectively used to study TCF7L1 protein interactions. Optimization strategies include:

• Expression system selection:

  • Endogenous BioID: Knockin BirA* fusion to the endogenous TCF7L1 locus provides physiologically relevant expression levels

  • Inducible BioID: Doxycycline-inducible BirA*-TCF7L1 systems allow temporal control but may cause artifacts from overexpression (3-fold higher than endogenous levels)

• Fusion protein design:

  • N-terminal BirA* fusion preserves TCF7L1 function better than C-terminal fusion

  • Inclusion of flexible linkers between BirA* and TCF7L1 improves folding

  • Consider a BirA*-P2A-TCF7L1 system to express independent proteins for controls

• Experimental conditions:

  • Biotin concentration: 50 μM biotin is typically used for labeling

  • Treatment duration: 24 hours of biotin exposure optimizes labeling

  • Special conditions: GSK-3 inhibition with CHIR99021 (5 μM) can be used to study Wnt pathway activation effects

• Controls and validation:

  • Use BirA* alone or BirA*-GFP as controls for non-specific biotinylation

  • Include wild-type cells without BirA* to identify endogenous biotinylated proteins

  • Validate key interactions by co-immunoprecipitation and proximity ligation assay (PLA)

Research has shown that "despite reduced BirA*-TCF7L1 levels, the number of hits identified with both BioID approaches increased after GSK-3 inhibition," indicating that interaction dynamics rather than bait abundance may be the critical factor in certain contexts .

What are the known protein interaction partners of TCF7L1 and how do they vary across cell types?

TCF7L1 interacts with numerous proteins in a context-dependent manner:

The interaction landscape varies significantly between pluripotent stem cells and differentiated/cancer cells. In mESCs, BioID studies have identified chromatin modifiers and transcriptional regulators as primary interaction partners . In colorectal cancer, TCF7L1 interactions affect migration and invasion through repression of specific targets like GAS1 . Wnt pathway activation through GSK-3 inhibition significantly alters the TCF7L1 interactome, often increasing interactions with chromatin remodeling factors while decreasing association with repressive complexes .

How does TCF7L1 interaction with β-catenin differ from other TCF/LEF family members?

TCF7L1 interaction with β-catenin has distinct features compared to other TCF/LEF family members:

• Binding affinity and dynamics:

  • TCF7L1 primarily functions as a transcriptional repressor even in the presence of β-catenin

  • Unlike other TCF/LEF members that become strong activators when bound to β-catenin

  • β-catenin binding to TCF7L1 can lead to TCF7L1 degradation, a mechanism not as pronounced with other family members

• Structural considerations:

  • All TCF/LEF family members share an N-terminal β-catenin binding domain

  • TCF7L1 has unique repression domains that remain partially active even when bound to β-catenin

  • Post-translational modifications differentially affect β-catenin interaction across family members

• Functional consequences:

  • TCF7L1-β-catenin interaction often results in derepression rather than strong activation

  • In stem cells, this interaction mediates the transition between pluripotency states

  • In cancer cells like CRC, the interaction contributes to migration and invasion phenotypes

Research suggests that "β-catenin-dependent TCF7L1 degradation and subsequent derepression of target genes" is a key mechanism, while other TCF/LEF members primarily mediate direct transcriptional activation when bound to β-catenin .

What are the optimal conditions for TCF7L1 ChIP-seq experiments?

Optimizing TCF7L1 ChIP-seq requires careful attention to several parameters:

• Antibody selection:

  • Use ChIP-validated antibodies specifically (ABIN6972849 or similar antibodies validated for ChIP/ChIP-seq)

  • N-terminal targeting antibodies often perform better as the C-terminus may be involved in chromatin interactions

• Crosslinking conditions:

  • 1% formaldehyde for 10 minutes at room temperature is standard

  • Dual crosslinking with both formaldehyde and disuccinimidyl glutarate can improve capture of protein-protein interactions in TCF7L1 complexes

• Sonication parameters:

  • Optimize to achieve DNA fragments of 200-500 bp

  • Verify fragmentation by agarose gel electrophoresis before immunoprecipitation

• IP conditions:

  • Pre-clear chromatin with protein A/G beads and non-immune IgG

  • Use 3-5 μg of TCF7L1 antibody per IP reaction

  • Include negative controls (IgG) and positive controls (antibodies against histone marks)

• Bioinformatic analysis:

  • Use peak callers optimized for transcription factors (e.g., MACS2)

  • Perform motif enrichment analysis for TCF/LEF binding motifs

  • Compare with published datasets for validation

Research has demonstrated that ChIP-seq can identify direct TCF7L1 targets such as DKK4, EPHB3, LGR5, and GAS1 in colorectal cancer cells . Integration with RNA-seq data is recommended to correlate binding with gene expression changes.

How can CUT&RUN be adapted for TCF7L1 studies compared to traditional ChIP-seq?

CUT&RUN (Cleavage Under Targets and Release Using Nuclease) offers several advantages over traditional ChIP-seq for TCF7L1 studies:

• Protocol adaptations:

  • Use antibodies specifically validated for CUT&RUN (such as ABIN6972849)

  • Optimized cell permeabilization: 0.1% digitonin works well for most cell types

  • Protein A-MNase concentration: 700 ng/mL is recommended for TCF7L1

  • Calcium activation time: 30 minutes at 0°C produces optimal cleavage

• Advantages for TCF7L1 studies:

  • Lower background: CUT&RUN has significantly reduced background compared to ChIP-seq

  • Fewer cells required: Effective with 100,000-500,000 cells versus millions for ChIP-seq

  • Higher resolution: Clearer identification of TCF7L1 binding motifs

  • No crosslinking: Better for capturing native TCF7L1 complexes

• Data analysis considerations:

  • Use specialized pipelines for CUT&RUN data

  • Different normalization compared to ChIP-seq due to sparse cutting pattern

  • Spike-in controls recommended for quantitative comparisons

• Combined approaches:

  • Perform both CUT&RUN and ChIP-seq on key samples for validation

  • Compare binding profiles to identify potential method-specific biases

  • Integrate with transcriptomic and other epigenomic data for comprehensive analysis

CUT&RUN can provide higher resolution maps of TCF7L1 binding sites with better signal-to-noise ratio, particularly valuable when studying closely spaced binding events or in systems with limited cell numbers.

What bioinformatic approaches are most effective for analyzing TCF7L1 chromatin binding patterns?

Several specialized bioinformatic approaches enhance TCF7L1 chromatin binding analysis:

• Peak calling optimization:

  • MACS2 with parameters optimized for transcription factors (--nomodel --extsize 200)

  • IDR (Irreproducible Discovery Rate) analysis for replicate consistency

  • Signal-to-noise ratio optimization through input normalization

• Motif analysis:

  • De novo motif discovery using MEME, Homer, or similar tools

  • Known motif enrichment analysis for TCF/LEF binding sites (CTTTG[A/T][A/T])

  • Motif co-occurrence analysis to identify cooperative transcription factors

• Integrative analysis:

  • Integration of RNA-seq to correlate binding with expression changes

  • Combination with histone modification data (H3K27ac, H3K4me3, H3K27me3)

  • Overlap with open chromatin regions (ATAC-seq, DNase-seq)

• Differential binding analysis:

  • Use specialized tools like DiffBind or MAnorm for condition comparisons

  • Implement sophisticated normalization strategies for quantitative comparisons

  • Consider batch effect correction for multi-condition or time-series data

• Network-based approaches:

  • Gene regulatory network reconstruction incorporating TCF7L1 binding data

  • Pathway enrichment analysis of bound regions

  • Integration with protein-protein interaction data from BioID studies

Research on colorectal cancer has successfully employed "RNA-sequencing (RNA-seq) to identify genes whose expression are regulated by TCF7L1" combined with "ChIP-sequencing to localize TCF7L1 binding across the CRC genome," demonstrating the power of integrated approaches .

How can RIME (Rapid Immunoprecipitation of Endogenous Proteins) be applied to study TCF7L1 complexes on chromatin?

RIME offers a powerful approach for studying TCF7L1-associated protein complexes directly on chromatin:

• Protocol adaptations for TCF7L1:

  • Use TCF7L1 antibodies validated for ChIP applications

  • Optimize crosslinking: 1% formaldehyde for 10 minutes

  • Include RNase treatment to eliminate RNA-dependent interactions

  • Extended digestion times may be necessary for complete complex solubilization

• Advantages over conventional approaches:

  • Captures native chromatin-associated complexes

  • Identifies context-specific interaction partners

  • Can be performed with limited cell numbers

  • Distinguishes chromatin-bound from soluble TCF7L1 complexes

• Data analysis considerations:

  • Compare RIME results with solution-based interactome studies (IP-MS, BioID)

  • Integrate with ChIP-seq data to correlate protein complexes with binding sites

  • Implement comprehensive bioinformatic filtering to minimize false positives

Research in human embryonic stem cells has successfully employed RIME to "characterize the protein complex associated with TCF7L1 when bound to chromatin," providing "novel insights into how TCF7L1 and pluripotency itself might be regulated" . This approach identified both "known and new partners of TCF7L1 on chromatin" in their native cellular context .

How can engineered TCF7L1 variants be used to dissect specific protein functions?

Engineered TCF7L1 variants provide powerful tools for functional studies:

• DNA-binding mutants:

  • L387P and P411L mutations in the HMG box DNA binding domain disrupt DNA binding

  • These mutants can separate DNA-binding dependent from independent functions

  • Research confirmed that "DNA-binding capacity was required for full activity" in repression assays

• β-catenin interaction mutants:

  • Mutations in the N-terminal β-catenin binding domain

  • Allow the study of β-catenin-independent functions

  • Help understand repression versus activation modes

• Domain deletion variants:

  • Systematic deletion of functional domains (repression domains, context-dependent regulatory domains)

  • Pinpoint regions required for specific protein-protein interactions

  • Identify minimal functional units

• Fusion proteins for specialized applications:

  • BirA*-TCF7L1 fusions for proximity labeling

  • Fluorescent protein fusions for live imaging

  • Degron-tagged versions for rapid protein depletion

• Orthogonal approaches:

  • CRISPR-mediated genomic engineering of endogenous TCF7L1

  • Site-specific modification of key residues

  • Knock-in of tagged versions at the endogenous locus

Studies comparing wild-type TCF7L1 with DNA-binding mutants in luciferase assays using the Wnt-responsive TOPflash reporter confirmed the DNA-binding dependency of TCF7L1's transcriptional repressor function in multiple colorectal cancer cell lines .

What are the latest methodological advances for studying TCF7L1 in single-cell resolution?

Several cutting-edge approaches enable TCF7L1 studies at single-cell resolution:

• Single-cell genomics applications:

  • scRNA-seq to correlate TCF7L1 expression with transcriptional states

  • scATAC-seq to examine chromatin accessibility at TCF7L1 binding sites

  • CUT&Tag-seq at single-cell level for TCF7L1 binding profiles

• Single-cell proteomics approaches:

  • Mass cytometry (CyTOF) with TCF7L1 antibodies for protein quantification

  • Single-cell Western blotting for TCF7L1 protein level analysis

  • Imaging mass cytometry for spatial context of TCF7L1 expression

• Spatial techniques:

  • Multiplexed immunofluorescence for TCF7L1 and interacting partners

  • In situ proximity ligation assay (PLA) for visualizing TCF7L1 interactions

  • CODEX imaging for highly multiplexed protein detection

• Live-cell approaches:

  • CRISPR knock-in of fluorescent tags to endogenous TCF7L1

  • Optogenetic control of TCF7L1 activity in selected cells

  • Live-cell monitoring of TCF7L1-regulated reporter expression

• Computational integration:

  • Trajectory analysis to map TCF7L1 dynamics during cellular transitions

  • Regulatory network inference at single-cell level

  • Integration of multi-omic single-cell data for comprehensive understanding

These emerging technologies will enable researchers to dissect the heterogeneity in TCF7L1 function across individual cells within complex tissues and during dynamic processes such as development and disease progression.

How can researchers address non-specific binding issues with TCF7L1 antibodies?

Strategies to overcome non-specific binding include:

• Antibody optimization:

  • Titrate antibody concentration to find optimal signal-to-noise ratio

  • Test multiple antibodies targeting different epitopes

  • Pre-adsorb antibodies with cell lysates from TCF7L1 knockout cells

• Blocking improvements:

  • Extended blocking (2-3 hours) with 5% BSA or 5% milk

  • Addition of 0.1-0.5% Triton X-100 to reduce hydrophobic interactions

  • Use of commercial blocking reagents specifically designed for transcription factors

• Stringent washing:

  • Increased wash buffer stringency (higher salt, 0.1% SDS addition)

  • Extended and additional washing steps

  • Temperature optimization for wash steps (4°C vs. room temperature)

• Sample preparation modifications:

  • Nuclear extraction protocols to enrich for TCF7L1

  • Protein extraction buffers optimized for nuclear proteins

  • Pre-clearing samples with protein A/G beads before antibody addition

• Validation controls:

  • Include TCF7L1 knockdown or knockout samples as negative controls

  • Use competing peptides to demonstrate specificity

  • Perform knockout-validated antibody testing

Research has noted that some antibodies may show "cross reactivity with other proteins," so validation controls are essential . For biotin-conjugated antibodies, accounting for "background biotinylation in wildtype cells" is particularly important .

What strategies can address the challenge of detecting TCF7L1 due to its low abundance?

Several approaches can enhance detection of low-abundance TCF7L1:

• Sample enrichment:

  • Nuclear fractionation to concentrate TCF7L1

  • Immunoprecipitation before Western blotting

  • Use of phosphatase inhibitors to preserve all forms of the protein

• Signal amplification:

  • Enhanced chemiluminescence (ECL) substrates for Western blots

  • Tyramide signal amplification for immunohistochemistry

  • Use of biotin-streptavidin systems for increased sensitivity

• Detection optimization:

  • Extended primary antibody incubation (overnight at 4°C)

  • Higher antibody concentrations (validated to avoid non-specific binding)

  • Use of more sensitive detection systems (e.g., digital Western blots)

• Interference reduction:

  • Remove cross-reacting proteins through pre-adsorption

  • Use monoclonal antibodies for higher specificity

  • Implement background reduction techniques

• Empirically validated protocols:

  • Documented antibody concentration: 0.2 μg/mL for Western blotting of human tissue lysates

  • Immunofluorescence concentration: 10 μg/mL with 3-hour room temperature incubation

  • PVDF membrane usage for Western blotting under reducing conditions

Research has demonstrated successful detection of TCF7L1 in human pancreas and lung tissue lysates as a band of approximately 70 kDa using these optimized conditions .

How can researchers reconcile contradictory data from different TCF7L1 antibodies?

When facing contradictory results from different antibodies, implement this systematic reconciliation approach:

• Epitope mapping analysis:

  • Determine exactly which epitopes are recognized by each antibody

  • Consider whether post-translational modifications might affect epitope accessibility

  • Evaluate whether protein interactions could mask specific epitopes

• Validation in controlled systems:

  • Test all antibodies on known positive and negative controls

  • Use TCF7L1 overexpression and knockout/knockdown systems

  • Compare with tagged TCF7L1 detected by anti-tag antibodies

• Cross-application validation:

  • Test each antibody in multiple applications (WB, IP, IF, ChIP)

  • Determine application-specific performance differences

  • Consider potential differences in native versus denatured detection

• Context-dependent considerations:

  • Evaluate cell-type or condition-specific differences in TCF7L1 isoforms

  • Consider the impact of Wnt signaling activation on TCF7L1 levels and interactions

  • Assess whether contradictions might reflect biologically relevant differences

• Orthogonal approaches:

  • Validate key findings with non-antibody methods (CRISPR tagging, etc.)

  • Use RNA-level analysis to corroborate protein expression patterns

  • Implement functional assays to support antibody-based observations

Research has shown that "treatment with CHIR caused a reduction in total TCF7L1 protein," but "there were many individual cells that retained elevated levels of TCF7L1" . Such heterogeneity might explain some contradictory findings and emphasizes the importance of single-cell resolution techniques.