KEGG: ath:AT2G39820
STRING: 3702.AT2G39820.1
EIF6, also known as eukaryotic translation initiation factor 6, is a protein that primarily functions as an anti-association factor interacting with the 60S ribosomal subunit. It prevents the premature joining of 60S and 40S ribosomal subunits in the cytoplasm, thus regulating translation initiation . Beyond translation control, EIF6 affects the maturation of 60S ribosomal subunits and has been implicated in ribosomal biogenesis pathways . The protein is predominantly located in the cytoplasm of mammalian cells, though it can also be detected in the nucleus, suggesting compartmentalized functions that vary by cellular location .
Human EIF6 is a canonical protein consisting of 245 amino acid residues with a molecular weight of approximately 26.6 kDa . Up to two different isoforms have been reported for this protein . EIF6 belongs to the EIF-6 protein family and has several synonyms in the literature, including EIF3A, ITGB4BP, b(2)gcn, p27(BBP), p27BBP, and CAB . The protein shows remarkable evolutionary conservation, with human EIF6 sharing 99.3% amino acid sequence identity with both mouse and rat EIF6, indicating its essential biological function across species .
EIF6 displays tissue-specific expression patterns with significant implications for pathology. It is expressed at very high levels in colon carcinoma compared to normal colon and ileum, with the lowest expression observed in kidney and muscle tissues . Originally, EIF6 was first identified in the proliferating compartment of the colonic epithelium and stem cells, and is highly expressed in epithelial and embryonic tissues . This differential expression pattern suggests EIF6 may play important roles in cellular proliferation and differentiation processes. Notably, dysregulated EIF6 expression has been documented in several cancer types, including head and neck carcinoma, colorectal cancer, non-small cell lung cancer, and ovarian serous adenocarcinoma .
When selecting an EIF6 antibody, researchers should consider several critical factors. First, the specific epitope recognition is important - antibodies targeting different regions (e.g., AA 1-245, AA 66-210, or C-terminal regions) may yield different results depending on protein conformation and interactions . Second, evaluate the host species and clonality - polyclonal rabbit antibodies are common for EIF6 detection, but the choice between polyclonal and monoclonal affects specificity and application versatility . Third, examine cross-reactivity profiles - high-quality EIF6 antibodies should demonstrate minimal cross-reactivity with other proteins . Finally, match the antibody's validated applications (WB, IHC, IF, ELISA) with your experimental needs, as not all antibodies perform equally across different techniques .
Antibody validation requires a multi-faceted approach to ensure specificity for EIF6. Begin with positive and negative control tissues - colon carcinoma samples provide excellent positive controls due to high EIF6 expression, while kidney or muscle tissues serve as low-expression controls . Include knockout/knockdown controls where EIF6 expression is eliminated or reduced through genetic approaches. Peptide competition assays, where the antibody is pre-incubated with purified EIF6 protein or immunizing peptide before application to samples, can confirm binding specificity. Multiple antibody verification involves using two or more antibodies targeting different EIF6 epitopes to confirm consistent detection patterns. Finally, molecular weight verification on Western blots should show a primary band at approximately 26.6 kDa, corresponding to the known molecular weight of EIF6 .
Western Blot (WB) is consistently reported as the most reliable and widely used application for EIF6 antibody detection across multiple antibody products . Immunohistochemistry (IHC), particularly on paraffin-embedded sections (IHC-p), represents another well-validated application that allows visualization of EIF6 in tissue context, enabling assessment of expression levels and subcellular localization patterns . Immunofluorescence (IF) and immunocytochemistry (ICC) applications provide high-resolution analysis of EIF6 subcellular distribution, which is particularly valuable given its dual localization in cytoplasm and nucleus . ELISA applications are also supported by several antibodies, offering quantitative measurement options . For novel or challenging applications, researchers should prioritize antibodies with published citation records demonstrating successful use in their application of interest.
For optimal EIF6 detection via Western blotting, several protocol modifications are recommended. Use RIPA or NP-40 based lysis buffers supplemented with protease inhibitors to effectively extract both nuclear and cytoplasmic pools of EIF6. Given EIF6's molecular weight (26.6 kDa), optimize gel separation using 12-15% polyacrylamide gels for better resolution in this molecular weight range. Transfer conditions should be adjusted for smaller proteins (e.g., lower voltage for longer time or semi-dry transfer systems). For blocking, 5% non-fat dry milk in TBST is generally effective, but BSA-based blocking may yield cleaner results with some antibodies. Primary antibody dilutions typically range from 1:500 to 1:2000, but should be empirically determined. Longer primary antibody incubation (overnight at 4°C) often improves specific signal detection. Enhanced chemiluminescence (ECL) detection systems with medium exposure times (2-5 minutes) generally provide optimal signal-to-noise ratio for EIF6 visualization.
Robust experimental design with EIF6 antibodies requires appropriate controls. Positive tissue controls should include colon carcinoma samples where EIF6 is highly expressed, while negative controls might include kidney or muscle tissues with lower expression levels . Loading controls must be carefully selected - traditional housekeeping proteins like GAPDH or β-actin for cytoplasmic fractions, and histone H3 or lamin for nuclear fractions, reflect EIF6's dual localization. Isotype controls (non-specific IgG from the same host species as the EIF6 antibody) help distinguish specific from non-specific binding. When applicable, include EIF6 knockdown/knockout samples as definitive negative controls. For immunostaining techniques, secondary-only controls (omitting primary antibody) identify potential non-specific secondary antibody binding. Finally, treatment controls exploring conditions known to alter EIF6 expression or localization (such as cell cycle perturbations) provide functional validation.
Distinguishing between nuclear and cytoplasmic EIF6 populations requires specialized techniques. Subcellular fractionation followed by Western blotting represents the most quantitative approach - protocols using sequential detergent extraction can effectively separate cytoplasmic and nuclear fractions, allowing comparative analysis of EIF6 distribution . Immunofluorescence microscopy provides complementary visual evidence of EIF6 localization - counterstaining with DAPI for nuclei alongside EIF6 antibody staining enables clear differentiation between compartments. Nuclear/cytoplasmic ratios can be quantified using image analysis software measuring signal intensity across defined cellular regions. Co-immunostaining with compartment-specific markers (such as lamin for nuclear envelope or α-tubulin for cytoplasm) provides additional confirmation. For more precise analysis, confocal microscopy with Z-stack imaging can eliminate signal overlap artifacts and generate three-dimensional localization data.
Several factors can contribute to false positives or negatives when working with EIF6 antibodies. Cross-reactivity with related translation factors can cause false positives, particularly with polyclonal antibodies - some EIF6 antibodies may recognize structural similarities in other EIF family members . Fixation artifacts in immunohistochemistry may create false negatives if fixation conditions denature or mask the EIF6 epitope. Incomplete extraction during sample preparation can lead to false negatives, especially when EIF6 is tightly associated with the 60S ribosomal subunit. Background issues are common in colon tissue analysis due to endogenous biotin or peroxidase activity, requiring appropriate blocking steps. Over-developed Western blots may detect minor cross-reactive bands that can be misinterpreted as EIF6 isoforms. Finally, phosphorylation states of EIF6 may affect antibody recognition, potentially causing inconsistent detection across samples with varying activation states.
Normalizing EIF6 expression across diverse tissue types presents challenges due to its variable baseline expression. Reference gene selection is critical - use multiple reference genes validated for stability across your specific tissue panel, as traditional housekeeping genes may vary considerably between tissue types. Tissue-specific normalization factors may be necessary - calculate correction factors based on established EIF6 expression patterns (e.g., accounting for known higher expression in proliferative tissues). Absolute quantification techniques like digital PCR or ELISA with recombinant protein standards can provide reference-independent measurements. Use tissue microarrays with multiple samples from the same tissue type to establish baseline variation before comparing across tissues. For clinical samples, consider normalization to matched normal adjacent tissue from the same patient to account for individual variation. Finally, computational normalization using algorithms designed for cross-tissue comparisons (such as quantile normalization) may be applied to large datasets.
EIF6 antibodies offer several sophisticated approaches to investigate its role in cancer progression. Tissue microarray analysis with EIF6 antibodies can assess expression patterns across cancer stages, providing correlations between EIF6 levels and disease progression . Multiplex immunofluorescence combining EIF6 antibodies with cancer stem cell markers or proliferation markers (Ki-67) can reveal associations with aggressive tumor phenotypes. Chromatin immunoprecipitation (ChIP) using anti-EIF6 antibodies can explore potential non-canonical roles in transcriptional regulation suggested by its nuclear localization. Proximity ligation assays (PLA) with EIF6 antibodies paired with antibodies against pathway components (Notch-1, β-catenin) can visualize and quantify physical interactions implicated in cancer signaling . Patient-derived xenograft (PDX) models stained for EIF6 can track expression during tumor evolution and therapy response. Finally, correlation of EIF6 expression with patient outcome data provides translational relevance for its potential as a prognostic biomarker.
Investigating EIF6's relationship with signaling pathways requires integrative approaches. Co-immunoprecipitation (Co-IP) using EIF6 antibodies followed by blotting for Notch-1 or β-catenin components can demonstrate physical interactions within these pathways . Pathway perturbation experiments manipulating Notch-1 (using γ-secretase inhibitors) or Wnt (using GSK3β inhibitors) while monitoring EIF6 levels and localization can establish causality. Reporter assays measuring pathway activity (using TOPFlash for Wnt/β-catenin or CBF1-luciferase for Notch) in conditions of EIF6 overexpression or knockdown can quantify functional impact. Chromatin immunoprecipitation sequencing (ChIP-seq) with antibodies against transcription factors downstream of these pathways can identify binding at the EIF6 promoter, confirming direct regulation. RNA-sequencing comparing transcriptomes in EIF6-modulated versus control cells can reveal broader pathway effects. Finally, phospho-specific antibodies against EIF6 can determine if its activity is modulated by kinases within these signaling cascades.
Distinguishing between canonical and non-canonical EIF6 functions requires sophisticated experimental approaches. Polysome profiling combined with EIF6 immunodetection can visualize its association with specific ribosomal fractions, confirming its canonical role in ribosome assembly . Subcellular fractionation with subsequent immunoprecipitation can isolate distinct EIF6-containing complexes from different cellular compartments, potentially revealing non-canonical interaction partners. Mass spectrometry following EIF6 pull-down can comprehensively identify associated proteins beyond the expected ribosomal components. Mutational analysis expressing EIF6 variants with disrupted ribosome-binding capacity can separate translation-dependent from translation-independent functions. Transcriptomics comparing EIF6 knockout/knockdown effects on global mRNA levels versus translation efficiency (through ribosome profiling) can distinguish direct translational impacts from secondary effects. Temporal analyses tracking EIF6 localization and activity through cell cycle phases may reveal context-dependent functional switching between canonical and non-canonical roles.
Emerging research positions EIF6 as a promising cancer biomarker with significant diagnostic and prognostic potential. Multiple studies have confirmed EIF6 overexpression across diverse cancer types, including head and neck carcinoma, colorectal cancer, non-small cell lung cancer, and ovarian serous adenocarcinoma . In head and neck metastatic carcinoma, nucleolar overexpression of EIF6 has been specifically detected, suggesting a potential signature for metastatic disease . This differential expression makes EIF6 immunohistochemistry a valuable addition to diagnostic panels, particularly for distinguishing aggressive phenotypes. The mechanistic links between EIF6 and oncogenic pathways provide biological rationale for its role as a progression marker - oncogenic Ras activates Notch-1 and promotes transcription of EIF6 via RBP-J dependent mechanisms, while EIF6 overexpression results in aberrant activation of the Wnt/β-catenin signaling pathway . These pathway connections position EIF6 as not merely a correlative marker but a functional indicator of activated oncogenic signaling.
EIF6 antibodies can facilitate therapeutic development through multiple research applications. Target validation studies using EIF6 antibodies in tissue microarrays can identify cancer types with consistently high expression, prioritizing indication selection for EIF6-directed therapies. Mechanistic studies employing EIF6 antibodies can uncover druggable nodes in EIF6-associated pathways, potentially revealing indirect targeting strategies through Notch-1 or Wnt/β-catenin modulation . Pharmacodynamic biomarker development using EIF6 antibodies can track target engagement and pathway modulation during preclinical testing of pathway inhibitors. Antibody-drug conjugates (ADCs) targeting surface-accessible EIF6 in certain contexts could deliver cytotoxic payloads specifically to cancer cells. Companion diagnostic development using validated EIF6 antibodies could help stratify patients for clinical trials targeting EIF6-dependent cancers. Intrabody approaches, where antibody fragments are expressed intracellularly, could directly inhibit EIF6 function in specific cellular compartments as a novel therapeutic modality.
Next-generation technological approaches promise to advance EIF6 research substantially. Single-cell proteomics technologies could reveal cell-to-cell variability in EIF6 expression and localization within heterogeneous tumor microenvironments. Phospho-specific and modification-specific EIF6 antibodies would enable tracking of activity states rather than mere expression levels. Super-resolution microscopy (STORM, PALM) coupled with EIF6 immunolabeling could visualize nanoscale associations with ribosomes and regulatory complexes. Proximity labeling approaches (BioID, APEX) using EIF6 fusions could map the complete protein interaction landscape across cellular compartments. Live-cell imaging with EIF6 antibody fragments or nanobodies could track dynamic changes in localization in response to stimuli or drug treatments. CRISPR-based screening platforms combined with EIF6 detection could identify genetic modifiers of its expression and function. Finally, computational modeling integrating EIF6 expression data with multi-omics datasets could predict patient-specific responses to therapies targeting EIF6-dependent pathways.