USF2 Antibody, HRP conjugated

What is USF2 and why is it significant in cancer research?

USF2 (Upstream stimulatory factor 2) is a transcription factor belonging to the basic helix-loop-helix protein family (bHLHb12). It functions as a major late transcription factor and FOS-interacting protein involved in transcriptional regulation . USF2 has gained significant attention in cancer research due to its role in regulating genes associated with tumor progression. Studies have demonstrated that USF2 expression is significantly increased in hepatocellular carcinoma (HCC) tissues compared to normal liver tissues and non-neoplastic surrounding tissues . The protein appears to be involved in regulating the expression of heparanase (HPSE), with both USF1 and USF2 expressions positively correlated with HPSE (correlation coefficients of 0.344 and 0.363, respectively) . This relationship is particularly important as increased USF2 has been associated with liver cirrhosis, worse tissue differentiation, advanced HCC stages, and metastatic recurrence, suggesting its potential as a novel marker for metastatic recurrence in HCC patients .

What are the key molecular characteristics of USF2 protein?

USF2 has a calculated molecular weight of 37 kDa based on its 346 amino acid sequence, though interestingly, its observed molecular weight in Western blot applications is typically around 44 kDa . This discrepancy suggests possible post-translational modifications. The protein is encoded by the gene with ID 7392 (NCBI) and UniProt ID Q15853 . As a transcription factor, USF2 contains DNA-binding domains that recognize E-box elements (CANNTG sequence) in promoter regions. The USF2 gene promoter itself contains six E-box binding sites, suggesting potential auto-regulation or regulation by related transcription factors . The protein can form homodimers or heterodimers with USF1, another member of the USF family, allowing for complex transcriptional regulation patterns. USF2 is predominantly localized in the nucleus for transcriptional regulation purposes, though cytoplasmic localization has also been observed in certain cell types, particularly in HCC cells as shown by immunohistochemical analysis .

What applications are suitable for USF2 antibody, HRP conjugated?

USF2 antibody, HRP conjugated is suitable for several research applications, with ELISA being its primary application . The horseradish peroxidase (HRP) conjugation provides direct enzymatic detection capability, eliminating the need for secondary antibody incubation steps. The unconjugated form of USF2 antibody has broader application potential, including Western Blot (WB), Immunohistochemistry (IHC), and ELISA techniques . For Western Blot applications, the recommended dilution range is typically 1:500-1:2000, though researchers should optimize this for their specific experimental systems . When performing immunohistochemistry, USF2 staining is primarily observed in the cytoplasm of HCC cells, appearing as yellow or brown granules distributed in dots and patches, which differs from USF1's predominantly nuclear localization . For all applications, positive controls such as Jurkat cells or HepG2 cell lysates are recommended as these cell lines demonstrate detectable USF2 expression .

How should USF2 antibody be stored and handled for optimal performance?

Proper storage and handling of USF2 antibody, HRP conjugated, is critical for maintaining its activity and ensuring reliable experimental results. The antibody should be stored at -20°C or -80°C immediately upon receipt . For the HRP-conjugated version, the antibody is typically supplied in a buffer containing 0.03% Proclin 300 as a preservative and 50% glycerol in 0.01M PBS at pH 7.4 . For unconjugated versions, the storage buffer often consists of PBS with 0.02% sodium azide and 50% glycerol at pH 7.3 . Both forms remain stable for up to one year when properly stored. Repeated freeze-thaw cycles should be strictly avoided as they can significantly degrade antibody performance . For working solutions, aliquoting is generally recommended, though some manufacturers note that aliquoting is unnecessary for -20°C storage of certain formulations . When preparing working dilutions, they should be made fresh before use rather than stored for extended periods. For the 20μl size of unconjugated antibody, note that it may contain 0.1% BSA in the formulation .

How should researchers optimize Western blot protocols for USF2 detection?

Optimizing Western blot protocols for USF2 detection requires careful attention to several technical aspects. Researchers should begin with protein extraction optimization, using RIPA buffer with protease inhibitors for total protein extraction, or specialized nuclear extraction protocols to enrich for nuclear proteins like USF2. For gel electrophoresis, 10-12% polyacrylamide gels are recommended to achieve optimal resolution around the 44 kDa region where USF2 migrates . Sample loading should start at 25-50 μg of total protein, with adjustments based on expression levels in different samples. For electrotransfer, PVDF membranes may provide better protein retention than nitrocellulose for USF2. Blocking conditions should be optimized with either 5% non-fat milk or 3-5% BSA in TBST, with BSA potentially providing lower background for phosphorylated USF2 detection. Primary antibody dilutions should be tested in a range from 1:500 to 1:2000 , with overnight incubation at 4°C typically yielding better results than shorter incubations. For detection, enhanced chemiluminescence systems provide good sensitivity, but fluorescent secondary antibodies can offer better quantitative linearity. When analyzing results, researchers should note that USF2's observed molecular weight (44 kDa) differs from its calculated weight (37 kDa) , which is important for accurate band identification.

What controls are essential when validating USF2 antibody specificity?

Validating USF2 antibody specificity requires a comprehensive set of controls to ensure reliable and interpretable results. Positive controls should include cell lines known to express USF2, such as Jurkat cells and HepG2 cells, which have been confirmed to show positive Western blot signals . Negative controls should include cell lines or tissues with minimal USF2 expression, such as normal liver tissue samples which show significantly lower expression than HCC samples . Genetic knockdown/knockout controls are particularly valuable; siRNA or CRISPR-mediated depletion of USF2 should result in reduced or absent signal. Overexpression controls with tagged USF2 constructs can confirm antibody detection at the expected molecular weight plus the tag size. Peptide competition assays, where the primary antibody is pre-incubated with the immunogen peptide (in this case, the USF2 fusion protein Ag9866), should abolish specific binding . Cross-reactivity testing across multiple species should confirm the stated reactivity with human, mouse, and rat samples . Multiple antibody validation involves using alternative antibodies targeting different USF2 epitopes to verify consistent detection patterns. In immunohistochemistry applications, isotype control antibodies help distinguish specific staining from background.

How can researchers investigate USF2's role in transcriptional regulation of the HPSE gene?

Investigating USF2's role in transcriptional regulation of the HPSE gene requires a multi-faceted experimental approach. Chromatin immunoprecipitation (ChIP) assays using USF2 antibody should be performed to determine direct binding to the six E-box elements in the HPSE promoter . For this application, unconjugated USF2 antibody should be used rather than HRP-conjugated versions. Researchers should design primers flanking each of these E-box elements for subsequent qPCR analysis of immunoprecipitated DNA. Luciferase reporter assays comparing wild-type HPSE promoter constructs with versions containing mutated E-box elements can establish the functional significance of USF2 binding. USF2 overexpression and knockdown experiments followed by assessment of HPSE mRNA and protein levels can establish causality in this regulatory relationship. Co-immunoprecipitation experiments can identify whether USF2 interacts with other transcription factors or cofactors in regulating HPSE expression. Electrophoretic mobility shift assays (EMSA) using recombinant USF2 and oligos containing HPSE promoter E-box elements can confirm direct binding in vitro. Analysis of clinical samples should examine correlation patterns between USF2 and HPSE expression across different stages of HCC progression, as previous studies have shown a positive correlation coefficient of 0.363 (p=0.005) .

What methodological approaches are recommended for studying USF2 expression across different HCC cell lines?

When studying USF2 expression across different HCC cell lines, researchers should implement standardized methodological approaches to ensure reliable comparisons. Quantitative RT-PCR should be performed using validated USF2-specific primers with normalization to multiple reference genes that show stable expression across HCC cell lines. Western blot analysis should use consistent protein extraction protocols, equal protein loading (verified by total protein staining or stable reference proteins), and standardized antibody dilutions . Researchers should be aware of the significant variation in USF2 expression across different HCC cell lines—previous studies have shown substantially higher expression in HCCLM3 cells (16.84±1.66) compared to HepG2 (10.61±0.92) and BEL-7402 (1.70±0.14) . Immunofluorescence microscopy can provide information on both expression levels and subcellular localization patterns, which may vary between cell lines. For functional studies, USF2 knockdown efficiency may differ between cell lines and should be carefully titrated and validated. Cell culture conditions should be strictly standardized, with consistent medium composition, serum concentration, cell density, and passage number to minimize variation. Researchers should consider the relationship between USF2 expression and the metastatic potential of different HCC cell lines, as this correlation has been observed in previous studies .

How should researchers interpret differences between USF2 mRNA and protein expression levels?

Interpreting discrepancies between USF2 mRNA and protein expression levels requires consideration of several biological and technical factors. Post-transcriptional regulation mechanisms, including miRNA targeting, RNA binding proteins, and alternative splicing, can significantly affect the correlation between mRNA and protein levels. Post-translational modifications and protein stability differences may also contribute to observed discrepancies. When analyzing such data, researchers should first verify the specificity of both mRNA detection methods (primers/probes targeting conserved regions) and protein detection antibodies. Time-course experiments can help determine whether differences reflect temporal delays between transcription and translation. Cell-type specific factors may influence USF2 regulation differently; for instance, data from HCC studies shows that while both mRNA and protein levels are elevated in HCC compared to normal liver tissue, the fold changes may differ . Subcellular fractionation analyses can reveal whether discrepancies stem from differences in protein localization rather than absolute expression levels, as USF2 can be detected in both nuclear and cytoplasmic compartments. Statistical analysis should employ appropriate correlation methods (Spearman's rank rather than Pearson's for non-parametric distributions) when assessing mRNA-protein relationships. Rather than viewing discrepancies as technical issues, researchers should consider them as potential insights into USF2 regulatory mechanisms that may have biological significance in the context of HCC pathogenesis.

What explains the discrepancy between calculated and observed molecular weights of USF2?

The discrepancy between USF2's calculated molecular weight of 37 kDa (based on its 346 amino acid sequence) and its observed migration at approximately 44 kDa in Western blots can be attributed to several factors. Post-translational modifications are the most likely explanation, as USF2 can undergo phosphorylation, which adds phosphate groups that increase molecular weight and often reduce electrophoretic mobility. The highly basic nature of USF2 as a transcription factor may also contribute to aberrant migration on SDS-PAGE, as basic proteins tend to bind less SDS per unit mass compared to neutral proteins, resulting in reduced mobility. Possible alternative splicing of USF2 may generate isoforms larger than the canonical sequence. Protein conformation, particularly proline-rich regions that create kinks in the peptide backbone, can reduce SDS binding and decrease mobility. To investigate this discrepancy, researchers could perform mass spectrometry analysis to determine the exact mass and identify post-translational modifications, use phosphatase treatment prior to Western blot to remove phosphate groups and observe mobility shifts, or perform 2D gel electrophoresis to separate based on both isoelectric point and molecular weight. Understanding this molecular weight discrepancy is crucial for accurate protein identification in experimental results and may provide insights into USF2's post-translational regulation in different cellular contexts.

How should researchers interpret USF2 subcellular localization patterns in normal versus cancer cells?

Interpreting USF2 subcellular localization patterns requires consideration of both technical and biological factors. Immunohistochemical studies have shown that USF2 staining is predominantly cytoplasmic in HCC cells, appearing as yellow or brown granules distributed in dots and patches, while USF1 shows primarily nuclear localization . This contrasts with the expected nuclear localization of transcription factors like USF2 in normal cells. When interpreting such findings, researchers should first confirm staining specificity using appropriate controls and high-resolution imaging with nuclear counterstains. Biologically, altered localization in cancer cells may indicate disrupted nuclear import/export mechanisms, sequestration by binding partners, or post-translational modifications that affect localization signals. The cytoplasmic localization of USF2 in HCC could reflect a cancer-specific function distinct from its canonical transcriptional role, or it might represent an inactive pool of the protein. Comparative quantification of nuclear versus cytoplasmic USF2 in normal liver tissues versus HCC tissues, correlated with markers of malignant progression, can provide insights into whether localization shifts are associated with disease advancement. Researchers should also investigate whether conditions like hypoxia, oxidative stress, or growth factor signaling—common in the tumor microenvironment—dynamically affect USF2 localization. The differential localization of USF1 (nuclear) and USF2 (cytoplasmic) in HCC cells suggests distinct functions for these related transcription factors in cancer contexts.

How can researchers accurately correlate USF2 expression with clinicopathological features of HCC?

Accurately correlating USF2 expression with clinicopathological features of HCC requires rigorous methodological and statistical approaches. Researchers should employ standardized scoring systems for immunohistochemical analysis, incorporating both staining intensity and percentage of positive cells. Digital pathology with automated image analysis provides more objective quantification than manual scoring methods. Multiple tissue samples from different regions of each tumor should be analyzed to account for intratumoral heterogeneity. Statistical analysis should utilize appropriate correlation tests (Spearman's rank correlation for non-parametric data) and multivariate regression models to account for confounding variables. Previous studies have demonstrated that USF2 expression is significantly correlated with liver cirrhosis, tissue differentiation, HCC stage, and metastatic recurrence . Researchers should analyze survival data using Kaplan-Meier curves with log-rank tests to determine prognostic significance. For mechanistic insights, correlating USF2 expression with molecular markers of specific HCC subtypes or signaling pathways can identify potential functional relationships. Longitudinal studies with samples collected at different disease stages can reveal dynamic changes in USF2 expression throughout disease progression. Multi-center validation cohorts enhance the reliability and generalizability of findings. Tissue microarrays containing matched primary HCC, adjacent non-tumor tissue, and metastatic lesions allow for comprehensive analysis of USF2 expression patterns throughout disease evolution.

What approaches should researchers use to investigate the relationship between USF2 and HPSE in HCC progression?

Investigating the relationship between USF2 and HPSE in HCC progression requires a comprehensive experimental approach spanning molecular, cellular, and clinical analyses. At the molecular level, chromatin immunoprecipitation (ChIP) assays using USF2 antibody can determine whether USF2 directly binds to the E-box elements in the HPSE promoter region. Luciferase reporter assays with wild-type and E-box mutated HPSE promoter constructs can establish functional significance of this binding. At the cellular level, gain-and-loss of function studies should be performed, manipulating USF2 levels through overexpression or siRNA-mediated knockdown, followed by assessment of HPSE expression and functional assays including cell proliferation, migration, invasion, and matrix degradation. Co-immunoprecipitation experiments can identify whether USF2 interacts with other transcription factors or co-factors to regulate HPSE expression. In animal models, orthotopic xenografts with USF2-modulated HCC cells can assess effects on tumor growth, invasion, and metastasis, with tissues analyzed for both USF2 and HPSE expression patterns. Clinical correlation studies should analyze matched primary HCC tissues and adjacent non-tumor tissues for both markers, correlating their expression patterns with clinicopathological features and patient outcomes. Previous studies have established a positive correlation between USF2 and HPSE expression in HCC, with correlation coefficients of 0.363 (p=0.005) , providing a foundation for deeper mechanistic investigations.

How should researchers design chromatin immunoprecipitation experiments using USF2 antibody?

Designing effective chromatin immunoprecipitation (ChIP) experiments with USF2 antibody requires careful consideration of multiple technical factors. Antibody selection is critical—researchers should use ChIP-validated USF2 antibodies rather than HRP-conjugated versions, preferably targeting epitopes that don't interfere with DNA binding. Crosslinking optimization is essential; standard formaldehyde fixation (1%, 10 minutes at room temperature) works for many transcription factors, but dual crosslinking with protein-protein crosslinkers followed by formaldehyde may improve efficiency for USF2. Sonication conditions should be optimized to generate 200-500bp DNA fragments, with pilot experiments recommended for each cell type. For immunoprecipitation, 2-5μg of USF2 antibody per reaction is typically sufficient, with overnight incubation at 4°C. Essential controls include input chromatin (pre-IP material), IgG control (non-specific binding), and positive control regions (known USF2 targets with E-box elements). For HCC research, primers targeting E-box elements in the HPSE promoter serve as appropriate positive controls, given the established relationship between USF2 and HPSE . Researchers should design primers flanking predicted USF2 binding sites in target genes of interest, with amplicons of 80-150bp for optimal qPCR performance. For genome-wide binding analysis, ChIP-seq can be employed, with careful attention to sequencing depth, peak calling parameters, and motif enrichment analysis to identify E-box elements (CANNTG) in binding regions.

What methodological strategies should researchers employ when studying USF2 and USF1 interactions in HCC?

Studying USF2 and USF1 interactions in HCC requires specialized methodological strategies due to their potential heterodimerization and distinct localization patterns. Co-immunoprecipitation experiments using USF2 antibody followed by USF1 detection (or vice versa) can reveal physical interactions, with both nuclear and cytoplasmic fractions analyzed separately due to their different localization patterns in HCC—USF1 being predominantly nuclear while USF2 shows cytoplasmic staining . Proximity ligation assays provide in situ visualization of protein-protein interactions at single-molecule resolution, valuable for confirming interactions in their native cellular context. For functional implications, sequential ChIP (Re-ChIP) experiments can determine whether USF1 and USF2 co-occupy the same genomic regions simultaneously. Dual luciferase reporter assays comparing USF1 alone, USF2 alone, and USF1+USF2 co-expression can assess cooperative or antagonistic effects on target gene promoters. CRISPR-mediated knockout of either factor followed by assessment of the other's localization, stability, and activity can reveal dependencies. Bimolecular fluorescence complementation (BiFC) assays, where USF1 and USF2 are fused to complementary fragments of a fluorescent protein, allow visualization of interactions in living cells. Quantitative co-localization analysis using confocal microscopy with appropriate statistical methods (Pearson's correlation, Manders' overlap coefficient) can assess spatial relationships. Analyzing USF1/USF2 ratios across different HCC stages may provide insights into whether their balance shifts during disease progression, potentially explaining their distinct roles despite structural similarities.

How can USF2 antibody be used to investigate autophagy regulation in chronic lymphocytic leukemia?

USF2 antibody can be instrumental in investigating autophagy regulation in chronic lymphocytic leukemia (CLL) based on recent findings suggesting USF2 promotes autophagy and proliferation by inhibiting STUB1-induced NFAT5 ubiquitination . For such studies, researchers should employ USF2 antibody in multiple complementary approaches. Western blot analysis can assess USF2 expression levels across CLL patient samples compared to healthy B cells, correlating expression with established autophagy markers (LC3-II/I ratio, p62 levels) and proliferation markers (Ki-67, PCNA). Co-immunoprecipitation using USF2 antibody can confirm interactions with STUB1 and NFAT5 in CLL cells, providing mechanistic insights. Chromatin immunoprecipitation can identify whether USF2 directly regulates transcription of autophagy-related genes in CLL cells. For functional validation, researchers should manipulate USF2 levels in CLL cells through siRNA knockdown or overexpression, then monitor effects on autophagy flux using established assays (autophagic vesicle formation, LC3 puncta formation, autophagic substrate degradation). Confocal microscopy using USF2 antibody alongside autophagy markers can visualize co-localization patterns and potential recruitment to autophagic structures. Analysis of USF2 expression in response to autophagy modulators (rapamycin, chloroquine) can reveal dynamic regulation. Clinical correlation studies should examine whether USF2 expression patterns in CLL samples correlate with treatment response, disease progression, or patient survival, potentially establishing USF2 as a biomarker or therapeutic target in CLL.

What approaches can researchers use to study USF2's evolutionary conservation across species?

Studying USF2's evolutionary conservation requires specialized approaches beyond standard antibody applications. Sequence analysis should compare USF2 orthologs across species, focusing on conservation of functional domains (DNA-binding, dimerization, transactivation) and regulatory motifs (phosphorylation sites, nuclear localization signals). USF2 antibody can be used to detect the protein in tissues from different species, though researchers should first verify cross-reactivity . For novel species like lamprey (Lethenteron reissneri) where USF2 has been recently identified , Western blot using USF2 antibody can confirm protein expression and size. Functional conservation can be assessed through heterologous expression systems, expressing USF2 from different species in reporter assay systems to compare transactivation potential. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) using USF2 antibody can identify binding sites across genomes of different species, enabling comparative genomics of USF2 target genes. Protein structure prediction and modeling can reveal conservation of tertiary structure despite sequence divergence. Co-immunoprecipitation experiments can determine whether protein-protein interaction networks involving USF2 are conserved across species. CRISPR-based approaches can introduce specific mutations corresponding to sequences from different species to test functional equivalence. Phylogenetic analysis integrating sequence, structural, and functional data provides comprehensive evolutionary context. These multi-faceted approaches illuminate how USF2 structure and function have been conserved or diverged throughout evolution, potentially revealing fundamental aspects of transcriptional regulation and identifying species-specific adaptations.

How can researchers investigate the relationship between USF2 and epigenetic modifications in gene regulation?

Investigating the relationship between USF2 and epigenetic modifications requires integration of chromatin immunoprecipitation with epigenetic analysis techniques. Sequential ChIP (Re-ChIP) experiments, first immunoprecipitating with USF2 antibody followed by antibodies against specific histone modifications (H3K4me3, H3K27ac for active chromatin; H3K27me3, H3K9me3 for repressive chromatin), can determine whether USF2 binding correlates with specific epigenetic states. ChIP-seq for USF2 and various histone modifications, followed by bioinformatic integration of binding profiles, can provide genome-wide correlation patterns. Co-immunoprecipitation using USF2 antibody can identify interactions with epigenetic modifiers such as histone acetyltransferases, methyltransferases, or chromatin remodeling complexes. For functional validation, researchers should manipulate USF2 levels and assess changes in histone modifications at target gene promoters. Mass spectrometry analysis of USF2-associated protein complexes can identify epigenetic regulatory partners. USF2's own post-translational modifications may influence its interaction with the epigenetic machinery; phospho-specific antibodies can help investigate this aspect. Analysis of DNA methylation patterns at USF2 binding sites using bisulfite sequencing can reveal relationships between USF2 binding and DNA methylation states. Chromatin accessibility assays (ATAC-seq, DNase-seq) can determine whether USF2 binding correlates with changes in chromatin accessibility. These approaches collectively illuminate how USF2 interfaces with the epigenetic machinery to regulate gene expression in normal and disease states, potentially identifying new therapeutic targets in conditions like HCC where USF2 dysregulation occurs .

What methods can researchers use to investigate USF2's role in metabolic regulation in different tissues?

Investigating USF2's role in metabolic regulation across different tissues requires a multi-faceted approach. Tissue-specific expression profiling using USF2 antibody in Western blot and immunohistochemistry analyses can map USF2 distribution across metabolically active tissues (liver, adipose, muscle, pancreas), with particular attention to subcellular localization patterns. ChIP-seq using USF2 antibody in different metabolic tissues can identify tissue-specific target genes involved in metabolic pathways. Metabolic challenge experiments (fasting/feeding, high-fat diet, glucose or insulin stimulation) followed by assessment of USF2 expression, localization, and target gene binding can reveal dynamic regulatory roles. For functional validation, tissue-specific USF2 knockout or overexpression models should be analyzed for metabolic phenotypes using comprehensive metabolic profiling (glucose tolerance, insulin sensitivity, lipid profiles, energy expenditure). Isotope tracing combined with mass spectrometry in cells with manipulated USF2 levels can identify specific metabolic pathways affected. Co-immunoprecipitation using USF2 antibody followed by mass spectrometry can identify tissue-specific interaction partners involved in metabolic regulation. For translational relevance, USF2 expression should be analyzed in metabolic disease tissues (fatty liver, diabetic pancreas) compared to healthy controls. Integration of metabolomics data with transcriptomics and ChIP-seq can provide systems-level insights into USF2's role in orchestrating metabolic networks. These approaches collectively illuminate how USF2 contributes to tissue-specific metabolic regulation and its potential implications in metabolic diseases, which may interact with its established role in cancer progression .