SERTAD1 Human

What is SERTAD1 and what are its alternative nomenclatures in the scientific literature?

SERTAD1 (SERTA domain-containing protein 1) is alternatively known as transcriptional regulator interacting with PHD-bromodomain 1 (Trip-Br1) or p34 (SEI-1). It belongs to the Sertad family of proteins and functions as a multifunctional regulator involved in cell cycle progression, transcriptional regulation, and cell survival pathways . The protein is encoded by a gene located in chromosomal region 19q13.1-13.2, a region frequently amplified in various malignancies . This protein contains multiple functional domains that facilitate its diverse cellular functions and protein-protein interactions, making it a critical player in both normal physiology and pathological states.

What are the key functional domains of SERTAD1 and their biological significance?

SERTAD1 possesses several distinct functional domains that contribute to its diverse cellular activities:

• N-terminal Cyclin A binding sequence (amino acids 1-30): Though homologous to cyclin A binding regions, experimental confirmation of this interaction remains incomplete .

• SERTA domain (amino acids 43-82): A novel heptad hydrophobic repeat conserved from insects to humans. While its precise biological function remains under investigation, it mediates key protein interactions .

• CDK4 binding domain (amino acids 30-160): Facilitates direct interaction with CDK4, allowing SERTAD1 to modulate cell cycle progression .

• C-terminal transactivation domains:

  • PHD-bromodomain-interacting domain (amino acids 161-178): Enables interactions with bromodomain and/or PHD zinc finger-containing general transcriptional co-activators like p300/CBP .

  • Acidic region (amino acids 167-220): Possesses intrinsic transactivation activity critical for gene regulation .

These structural elements enable SERTAD1 to function as a transcriptional co-activator despite lacking intrinsic DNA-binding capacity, as it can form complexes with transcription factors such as E2F1 and SMAD1 to regulate target gene expression .

How is SERTAD1 subcellular localization regulated, and how does this affect its function?

SERTAD1 exhibits dual subcellular localization, being present in both the nucleus and cytoplasm of cells. This distribution pattern has been confirmed through immunostaining of both immortalized cardiomyocytes (NkL-TAg cells) and primary embryonic cardiomyocyte cultures . Interestingly, BMP stimulation does not appear to significantly alter this subcellular distribution pattern . The nuclear localization of SERTAD1 aligns with its role as a transcriptional co-activator, while its cytoplasmic presence suggests additional non-nuclear functions.

In the nucleus, SERTAD1 interacts with activated (phosphorylated) SMAD1 and other transcription factors to enhance the expression of target genes . Western blot analysis of fractionated cells has confirmed the presence of SERTAD1 in both cytoplasmic and nuclear fractions, though studies suggest the signal may be stronger in the cytoplasm of certain cell types such as embryonic cardiomyocytes . This dual localization likely enables SERTAD1 to participate in distinct cellular processes depending on its subcellular compartmentalization.

What is the role of SERTAD1 in ischemic stroke and neurological injury?

SERTAD1 plays a significant pathological role in ischemic stroke by promoting neurological injury through the CDK4/p-Rb pathway. Research has demonstrated that SERTAD1 expression becomes upregulated in mouse models of middle cerebral artery occlusion and reperfusion, as well as in HT22 cells subjected to oxygen-glucose deprivation/reoxygenation (OGD/R) . This upregulation contributes to neuronal damage through multiple mechanisms.

Experimental evidence shows that SERTAD1 knockdown significantly ameliorates ischemia-induced brain infarct volume, neurological deficits, and neuronal apoptosis in vivo . Similarly, in vitro studies reveal that SERTAD1 knockdown improves cell viability and reduces apoptotic cell death in HT22 cells after OGD/R . Mechanistically, SERTAD1 directly binds to CDK4, activating the CDK4/p-Rb pathway and subsequently increasing the expression of downstream targets including p-Rb, B-Myb, and Bim .

Conversely, SERTAD1 overexpression exacerbates OGD/R-induced cell viability inhibition and apoptotic cell death while increasing p-Rb, B-Myb, and Bim expression . The causal relationship between SERTAD1 and the CDK4/p-Rb pathway was further confirmed when the CDK4 inhibitor ON123300 was shown to counteract the deleterious effects of SERTAD1 overexpression in OGD/R conditions . These findings collectively establish SERTAD1 as a key mediator of ischemic/hypoxic neurological injury.

How does SERTAD1 contribute to cancer development and progression?

SERTAD1 functions as an oncoprotein in numerous malignancies, contributing to cancer development and progression through multiple mechanisms. It significantly influences oncogenesis and programmed cell death under nutrient starvation conditions . At the molecular level, SERTAD1 promotes cell growth by interacting with E2F1/DP-1 and modulating the CDK4/p16INK4a cell cycle regulatory pathway .

Enhanced SERTAD1 expression has been linked to tumor induction, increased ubiquitination, and genomic instability . It plays a particularly important role in modulating programmed cell death, with aberrant expression and persistent activation of SERTAD1 implicated in drug resistance against hypoxia-induced cell death . For instance, in breast cancer cell lines, SERTAD1 inhibition accelerates hypoxia-induced cell apoptosis . Similarly, in prostate cancer, SERTAD1 promotes cell proliferation and contributes to disease progression .

SERTAD1 overexpression has been documented in numerous cancer types, including:

• Breast cancer

• Prostate cancer

• Head and neck cancer

• Colon cancer

• Lung cancer

• Brain tumors

• Renal cancer

• Leukemia and lymphoma

The chromosomal region containing SERTAD1 (19q13.1-13.2) shows gain in more than 30% of ovarian carcinomas and numerous other tumor types including pancreatic and lung cancers, further supporting its oncogenic role .

What experimental techniques are effective for detecting SERTAD1-protein interactions?

Several complementary experimental approaches have proven effective for detecting and validating SERTAD1 protein interactions:

• Yeast Two-Hybrid Screening: This technique has successfully identified novel interaction partners of SERTAD1. For example, using Smad1 as bait, researchers have discovered SERTAD1 as a novel interaction partner of SMAD1 .

• In vitro GST Pull-Down Assays: This biochemical approach has confirmed direct protein-protein interactions involving SERTAD1. The procedure typically involves producing 35S-labeled SERTAD1 and GST-tagged potential binding partners (such as GST-SMAD1), followed by pull-down and detection via autoradiography .

• Mammalian Cell GST Pull-Down Analysis: To verify SERTAD1 interactions in a more physiologically relevant context, co-expression of GST-SERTAD1 and HA-tagged potential partners (e.g., HA-Smad1) in HEK293 cells, followed by GST pull-down and Western blotting, has proven effective . This approach can be enhanced by including activators of relevant signaling pathways, such as constitutively active ALK6 to activate BMP signaling when studying SERTAD1-SMAD1 interactions .

• Co-Immunoprecipitation: Although not explicitly detailed in the provided references, co-immunoprecipitation represents another commonly used technique for confirming protein-protein interactions in mammalian cells under endogenous conditions.

• STRING Bioinformatics Platform: For computational prediction and analysis of SERTAD1 protein interactions, the STRING online tool has been utilized to identify interaction networks. This approach integrates information from genomic context predictions, high-throughput experiments, co-expression data, automated text mining, and previous knowledge from databases .

These methodologies provide complementary approaches for discovering and validating SERTAD1 interaction partners under various experimental conditions.

What are effective methods to modulate SERTAD1 expression in experimental models?

Researchers have successfully employed several methodologies to experimentally modulate SERTAD1 expression levels:

• Genetic Knockdown Approaches:

  • RNA interference (RNAi) techniques have been effectively used to downregulate SERTAD1 expression in both in vitro and in vivo models. This approach has revealed that SERTAD1 knockdown significantly ameliorates ischemia-induced brain infarct volume, neurological deficits, and neuronal apoptosis in mouse models .

  • In cellular models such as HT22 cells subjected to oxygen-glucose deprivation/reoxygenation (OGD/R), SERTAD1 knockdown significantly improved cell viability and reduced apoptotic cell death .

• Overexpression Systems:

  • Plasmid-based overexpression of SERTAD1 has been successfully implemented in cell culture models. For example, SERTAD1 overexpression in HT22 cells exacerbated OGD/R-induced inhibition of cell viability and increased apoptotic cell death .

  • In cardiomyocyte studies, overexpression of SERTAD1 enhanced the activity of BMP reporters in a dose-dependent manner and increased the expression of BMP/SMAD regulatory targets .

• Pharmacological Modulation:

  • While not directly targeting SERTAD1 expression, CDK4 inhibitors such as ON123300 have been used to counteract the effects of SERTAD1 overexpression. This approach restored the effects of SERTAD1 overexpression on OGD/R-induced apoptotic cell death in HT22 cells .

These experimental approaches provide complementary strategies for investigating SERTAD1 function in various biological contexts and disease models.

What is the role of SERTAD1 in cardiac development and BMP signaling?

SERTAD1 plays a significant role in cardiac development through its function as a transcriptional co-activator in the BMP signaling pathway. Expression analyses have confirmed the presence of SERTAD1 in developing mouse hearts using multiple techniques including RT-PCR, Western blotting, and in situ hybridization . Unlike its homologs Sertad3 and Cdca4, both SERTAD1 and Sertad2 are expressed in embryonic hearts during the critical developmental window of E9.5-E11.5 .

Protein expression studies revealed that SERTAD1 is present in embryonic hearts throughout early to mid-development (E10.5 to E15.5), with expression levels declining at E15.5 compared to earlier stages . This temporal pattern suggests stage-specific functions during cardiogenesis. Mechanistically, SERTAD1 functions as a novel transcriptional co-activator of SMAD1, a key mediator of BMP signaling, which is essential for proper cardiac development .

Functional studies have demonstrated that SERTAD1 overexpression in immortalized cardiomyocytes enhances the activity of BMP-responsive reporters in a dose-dependent manner . Furthermore, it increases the expression of several established BMP/SMAD regulatory targets upon BMP stimulation, including NKX2.5, ID2, and TBX20, which are critical factors in heart development . The SERTAD1-SMAD1 interaction is enhanced through active BMP signaling, indicating a positive feedback mechanism in this developmental pathway .

How does SERTAD1 integrate with the CDK4/p-Rb signaling pathway?

SERTAD1 serves as a critical regulator of the CDK4/p-Rb signaling pathway, primarily through its direct binding to CDK4. This interaction represents one of the key mechanisms by which SERTAD1 influences cell cycle progression, cell survival, and pathological processes. SERTAD1 contains a specific CDK4 binding domain (amino acids 30-160) that facilitates this direct interaction .

Functionally, SERTAD1 acts as a growth factor sensor and facilitates the formation and activation of cyclin D/CDK4 complexes . It also antagonizes the activity of the CDK inhibitor p16INK4a, thereby promoting cell proliferation . This molecular mechanism explains how SERTAD1 contributes to cell cycle regulation in both normal and pathological contexts.

In pathological settings such as ischemic/hypoxic neurological injury, SERTAD1 activates the CDK4/p-Rb pathway, leading to increased expression of downstream targets including p-Rb, B-Myb, and Bim, which contribute to neuronal apoptosis . Experimental evidence supporting this mechanism includes:

• SERTAD1 knockdown significantly inhibits ischemic/hypoxic-induced expression of p-Rb, B-Myb, and Bim both in vivo and in vitro .

• Conversely, SERTAD1 overexpression significantly increases p-Rb, B-Myb, and Bim expression in HT22 cells subjected to OGD/R .

• The CDK4 inhibitor ON123300 restores the deleterious effects of SERTAD1 overexpression on OGD/R-induced apoptotic cell death and p-Rb, B-Myb, and Bim expression in HT22 cells .

These findings establish a causal relationship between SERTAD1, CDK4/p-Rb pathway activation, and resultant cellular outcomes in pathological conditions.

How can researchers interpret conflicting data about SERTAD1 function in different cellular contexts?

Interpreting contradictory findings regarding SERTAD1 function across different cellular contexts requires systematic consideration of several factors:

• Tissue-Specific Effects: SERTAD1 may exert opposing effects in different tissue types due to the presence of tissue-specific cofactors or signaling networks. For example, while SERTAD1 promotes cell survival in cancer cells, it contributes to neuronal death in models of ischemia . Researchers should carefully document the cellular context of their experiments and avoid generalization across tissue types.

• Interaction Partner Availability: SERTAD1 functions through interactions with multiple proteins, including CDK4, SMAD1, E2F1, and p16INK4a . The relative abundance of these interaction partners likely differs between cell types, potentially explaining context-dependent functions. Methodologically, researchers should consider profiling the expression of known SERTAD1 interaction partners in their experimental system.

• Post-Translational Modifications: Research indicates that post-translational modifications can significantly modulate SERTAD1 function. Abnormal SERTAD1 expression promoted by post-translational modifications can lead to enhanced programmed cell death . Investigators should employ techniques like phospho-specific antibodies or mass spectrometry to characterize the post-translational modification status of SERTAD1 in their system.

• Activation State of Relevant Signaling Pathways: SERTAD1-SMAD1 interaction, for instance, is enhanced through active BMP signaling . Therefore, the activation state of relevant signaling cascades may determine SERTAD1 function. Experimental designs should include assessment of pathway activation states alongside SERTAD1 functional studies.

• Methodological Approach to Data Integration: When facing conflicting data, meta-analysis approaches similar to those used in SERTAD1 cancer studies can be valuable . These include examining heterogeneity between studies (using I² index and Cochran's Q test) and employing random-effects models when appropriate to account for study population and design differences .

By systematically addressing these factors, researchers can better reconcile seemingly contradictory findings and develop a more nuanced understanding of SERTAD1 biology.

What are the current methodological approaches for studying SERTAD1 as a potential therapeutic target?

Investigating SERTAD1 as a therapeutic target requires a multi-faceted approach incorporating several methodological strategies:

• Pharmacological Inhibition Studies: CDK4 inhibitors such as ON123300 have demonstrated efficacy in counteracting SERTAD1-mediated pathological effects in neurological injury models . This suggests that targeting SERTAD1's downstream effectors represents a viable therapeutic strategy. Researchers should systematically evaluate existing CDK4 inhibitors against SERTAD1-mediated pathologies and develop more specific inhibitors that disrupt SERTAD1-CDK4 interaction.

• Gene Network Analysis: Tools like STRING and GeneMANIA have been employed to map protein-protein interactions and identify common pathways associated with SERTAD1 . These computational approaches help identify additional therapeutic targets within SERTAD1-associated networks. When designing studies, researchers should integrate network analysis with experimental validation of key nodes.

• miRNA Regulation: Investigating miRNAs that regulate SERTAD1 expression represents an emerging therapeutic strategy. Studies have begun exploring the association between SERTAD1 and various miRNAs . Experimental approaches should include miRNA expression profiling in tissues of interest and functional validation of miRNA-SERTAD1 regulatory relationships.

• Xenograft Models: Based on gene networking studies, xenograft paradigms have been proposed for further elucidation of SERTAD1's role in cancer . This approach allows evaluation of potential anti-SERTAD1 therapies in vivo. Researchers should develop appropriate animal models that recapitulate SERTAD1-dependent pathologies for therapeutic testing.

• Survival Analysis in Patient Cohorts: Cancer patient survival analysis based on SERTAD1 expression levels provides critical baseline data for therapeutic development . Meta-analyses integrating thousands of gene expression profiles and clinical outcomes have revealed significant associations between SERTAD1 expression and patient survival in various cancers . These analyses should inform patient stratification strategies in future clinical trials targeting SERTAD1.

By integrating these methodological approaches, researchers can systematically evaluate SERTAD1 as a therapeutic target and develop effective intervention strategies for SERTAD1-dependent pathologies.

What statistical approaches are recommended for analyzing SERTAD1 expression data across clinical samples?

When analyzing SERTAD1 expression data in clinical contexts, researchers should implement robust statistical methodologies that account for data heterogeneity and potential confounding factors:

• Meta-Analysis Techniques: For integrating data across multiple studies, the DerSimonian and Laird (DL) random-effects model and Mantel-Haenszel Fixed effect model are recommended to account for heterogeneity of study populations and designs . These approaches have been successfully applied to SERTAD1 expression data in cancer studies.

• Heterogeneity Assessment: The I² index and Cochran's Q test should be employed to quantify heterogeneity between studies, with significant heterogeneity assumed for I² > 50% or a Q-test p-value < 0.05 . This assessment helps determine whether fixed or random effects models are more appropriate.

• Survival Analysis Methods: When correlating SERTAD1 expression with patient outcomes, Kaplan-Meier survival curves with log-rank tests and Cox proportional hazards regression models should be used. The latter allows adjustment for covariates that might influence outcomes independently of SERTAD1 expression .

• Expression Data Normalization: Prior to statistical analysis, appropriate normalization methods should be applied to minimize technical variability while preserving biological differences. Methods such as quantile normalization or normalization against housekeeping genes should be considered depending on the platform used.

• Subgroup Analysis: When analyzing SERTAD1 across different cancer types or clinical subgroups, stratified analyses should be performed to identify potential tissue-specific or context-dependent effects. This approach has revealed differential prognostic implications of SERTAD1 across cancer types .

• Multiple Testing Correction: When performing numerous statistical tests, appropriate multiple testing corrections (e.g., Benjamini-Hochberg false discovery rate) should be applied to minimize false positive findings while maintaining statistical power.

These statistical approaches provide a robust framework for analyzing SERTAD1 expression data across clinical samples, enabling reliable identification of associations with disease features and patient outcomes.

How should researchers design experiments to distinguish direct versus indirect effects of SERTAD1?

Designing experiments that clearly differentiate between direct and indirect effects of SERTAD1 requires careful methodological planning:

• Domain Mutation Studies: Creating mutations in specific functional domains of SERTAD1 (such as the CDK4 binding domain or PHD-bromodomain-interacting domain) can help determine which molecular interactions mediate particular cellular effects . For example, mutation of the CDK4 binding domain would specifically disrupt SERTAD1-CDK4 interaction while preserving other functions.

• Temporal Analysis of Signaling Events: Time-course experiments measuring the activation of downstream effectors following SERTAD1 modulation can help establish causal relationships and distinguish immediate (likely direct) from delayed (potentially indirect) effects. This approach should include measurement of p-Rb, B-Myb, and Bim expression at multiple time points after SERTAD1 manipulation .

• Combinatorial Knockdown/Inhibition Studies: Simultaneously manipulating SERTAD1 and its putative effectors (e.g., CDK4, SMAD1) can reveal dependency relationships. If inhibiting an effector prevents SERTAD1-mediated outcomes, this suggests the effect requires that particular pathway. The study demonstrating that CDK4 inhibitor ON123300 blocks the effects of SERTAD1 overexpression exemplifies this approach .

• Proteomic Interaction Mapping: Comprehensive mapping of SERTAD1 protein-protein interactions under various conditions using techniques like proximity labeling (BioID, APEX) or immunoprecipitation followed by mass spectrometry can identify direct binding partners versus components of larger complexes.

• Transcriptomic Analysis with Motif Examination: For transcriptional effects, combining RNA-seq after SERTAD1 modulation with promoter motif analysis can distinguish genes directly regulated by SERTAD1-containing complexes (which should contain binding motifs for SERTAD1's transcription factor partners) from secondary effects.

• Reconstitution Experiments in Cell-Free Systems: For biochemical pathways, reconstitution of purified components in cell-free systems can definitively establish direct biochemical relationships, though this approach may be technically challenging for complex transcriptional mechanisms.

These methodological approaches, particularly when used in combination, can provide strong evidence distinguishing direct from indirect effects of SERTAD1 on cellular processes and disease pathogenesis.

What are promising unexplored areas for future SERTAD1 research?

Several promising research directions remain underexplored in the SERTAD1 field:

• SERTAD1 in Immune Regulation: While SERTAD1's roles in cancer and neurological injury have been investigated, its potential functions in immune cell regulation and inflammatory responses remain largely unexplored. Given its involvement in cell cycle regulation and transcriptional control, SERTAD1 may influence immune cell proliferation and differentiation.

• Structural Biology of SERTAD1 Complexes: High-resolution structural studies of SERTAD1 in complex with its binding partners (CDK4, SMAD1, E2F1) would provide critical insights into the molecular mechanisms of these interactions and facilitate structure-based drug design targeting specific SERTAD1 functions.

• SERTAD1 in Metabolic Regulation: The observation that SERTAD1 functions in cellular responses to nutrient starvation suggests potential roles in metabolic regulation. Investigating SERTAD1's involvement in cellular metabolism and metabolic diseases represents an important unexplored area.

• Isoform-Specific Functions: Studies should examine whether alternative splicing generates SERTAD1 isoforms with distinct functions in different tissues or developmental stages, which might explain some context-dependent effects.

• Epigenetic Regulation by SERTAD1: Given SERTAD1's interaction with bromodomain-containing proteins , it may influence chromatin structure and epigenetic regulation. Genome-wide studies of chromatin modifications in response to SERTAD1 modulation could reveal novel functions.

• SERTAD1 in Stem Cell Biology: The involvement of SERTAD1 in both development and cancer suggests potential roles in stem cell maintenance or differentiation, which remain largely unexplored.

• Therapeutic Targeting Strategies: Development of specific inhibitors of SERTAD1 protein-protein interactions, particularly those disrupting SERTAD1-CDK4 binding, represents a promising therapeutic approach that requires further investigation.

These research directions offer significant potential for advancing our understanding of SERTAD1 biology and developing novel therapeutic approaches targeting SERTAD1-dependent pathologies.

How should researchers integrate multi-omics approaches in studying SERTAD1 function?

Integrating multi-omics approaches provides a comprehensive understanding of SERTAD1 function across multiple levels of biological organization. Researchers should consider the following methodological framework:

• Genomic Analysis:

  • Identify genetic variations in SERTAD1 and correlate with disease phenotypes using genome-wide association studies (GWAS)

  • Analyze copy number variations in the chromosomal region 19q13.1-13.2 containing SERTAD1, which shows gain in over 30% of ovarian carcinomas and numerous other tumor types

  • Employ CRISPR-Cas9 genomic editing to create precise mutations in SERTAD1 and assess phenotypic consequences

• Transcriptomic Integration:

  • Perform RNA-seq after SERTAD1
    modulation to identify directly and indirectly regulated genes

  • Conduct comparative analysis of transcriptomes across different cell types to identify context-specific SERTAD1-regulated genes

  • Integrate with transcription factor binding site analysis to identify direct transcriptional targets

• Proteomic Approaches:

  • Conduct immunoprecipitation-mass spectrometry to comprehensively map SERTAD1 protein-protein interactions under various conditions

  • Employ phosphoproteomics to identify signaling cascades affected by SERTAD1 manipulation

  • Use protein array technologies to assess how SERTAD1 modulation affects global signaling pathway activation

• Metabolomic Analysis:

  • Profile cellular metabolites after SERTAD1 modulation to identify metabolic pathways affected

  • Integrate with transcriptomic data to identify SERTAD1-regulated metabolic genes

• Single-Cell Analysis:

  • Apply single-cell RNA-seq and proteomics to investigate cell-to-cell variability in SERTAD1 expression and function

  • This approach is particularly valuable for understanding heterogeneous responses in cancer and developmental contexts

• Network Analysis Integration:

  • Develop computational frameworks that integrate data across omics platforms

  • Apply tools like STRING and GeneMANIA, which have already shown utility in SERTAD1 research

  • Construct comprehensive regulatory networks incorporating transcriptional, protein interaction, and metabolic data

• Temporal and Spatial Dimensions:

  • Design experiments that capture both temporal dynamics and spatial organization

  • In developmental contexts, this approach is crucial for understanding SERTAD1's role in processes like cardiogenesis

This integrated multi-omics approach will provide a systems-level understanding of SERTAD1 function, revealing emergent properties that may not be apparent from individual omics approaches alone.