Recombinant Human Transcription factor HIVEP3 (HIVEP3), partial

What is the molecular structure of HIVEP3 and how does it function as a transcription factor?

HIVEP3 (Human Immunodeficiency Virus Type I Enhancer-Binding Protein 3) belongs to the HIVEP family of transcription factors. The protein contains multiple zinc finger and acid-rich (ZAS) domains along with serine-threonine rich regions that facilitate its function as a transcription factor . HIVEP3 regulates gene expression by binding to the kappa-B motif in target genes, thereby modulating nuclear factor kappaB-mediated transcription . Additionally, HIVEP3 binds to the recombination signal sequence (RSS) that flanks the V, D, and J regions of immunoglobulin and T-cell receptor genes, suggesting a role in immune system development . The functional architecture of HIVEP3 enables it to interact with multiple signaling pathways, including those involved in cell growth, differentiation, and immune response regulation.

How does HIVEP3 interact with NF-κB signaling pathways?

HIVEP3 exhibits complex interactions with NF-κB signaling through multiple mechanisms:

• As a competitive transcription factor: HIVEP3 can bind to kappa-B motifs in target genes, potentially competing with NF-κB transcription factors for binding sites .

• Through transcriptional repression: Once bound to DNA, HIVEP3 can repress transcription of certain NF-κB target genes in the nucleus .

• Via non-transcriptional processes: HIVEP3 inhibits nuclear translocation of RELA (p65) by associating with TRAF2, an adapter molecule in tumor necrosis factor signaling . This interaction blocks the formation of the IKK complex, thereby preventing NF-κB activation.

• Through TRAF protein interactions: HIVEP3 interactions with TRAF proteins inhibit both NF-κB-mediated and c-Jun N-terminal kinase (JNK)-mediated responses, including apoptosis and pro-inflammatory cytokine gene expression .

Notably, HIVEP3 strongly inhibits TNF-α-induced NF-κB activation, suggesting a potential role in modulating inflammatory responses .

What are optimal methods for expressing and purifying recombinant HIVEP3 for research applications?

When working with recombinant HIVEP3 protein, researchers should consider the following methodological approaches:

• Expression system selection: E. coli has been successfully used as an expression system for recombinant HIVEP3 protein production . This prokaryotic system offers advantages of high yield and cost-effectiveness.

• Purification strategy: Immobilized metal affinity chromatography (IMAC) is an effective purification method for His-tagged HIVEP3 recombinant proteins . The addition of a His6-ABP tag at the N-terminus facilitates purification while minimally affecting protein function.

• Buffer optimization: Recombinant HIVEP3 demonstrates stability in PBS with 1M urea at pH 7.4 . This buffer composition helps maintain protein solubility and prevent aggregation.

• Quality control: Protein purity should be assessed using SDS-PAGE and Western blotting, with >80% purity as an acceptable threshold for most research applications .

• Storage considerations: Store purified recombinant HIVEP3 at -20°C and avoid freeze-thaw cycles to maintain protein integrity .

For applications requiring higher purity or alternative tagging strategies, researchers may need to optimize these protocols based on their specific experimental requirements.

What are the validated experimental applications for recombinant HIVEP3 protein?

Recombinant HIVEP3 protein has been validated for several experimental applications:

• Antibody competition assays: Recombinant HIVEP3 protein can be used to confirm antibody specificity by competitive binding . This application is particularly useful for validating newly developed antibodies against HIVEP3.

• Protein-protein interaction studies: The protein can be employed in pull-down assays to identify novel binding partners or confirm suspected interactions, particularly with components of the NF-κB pathway .

• DNA binding assays: Given HIVEP3's role as a transcription factor, recombinant protein can be used in electrophoretic mobility shift assays (EMSA) to study its binding to kappa-B motifs and recombination signal sequences .

• Structural studies: Purified recombinant HIVEP3 fragments can facilitate crystallography or NMR studies to elucidate the three-dimensional structure of functional domains.

When designing experiments with recombinant HIVEP3, researchers should note that the commercially available protein (34 kDa) represents a partial sequence of the full-length protein, which contains the following amino acid sequence: SYSFDDHITDSEALSRSSHVFTSHPRMLKRQPAIELPLGGEYSSEEPGPSSKDTASKPSDEVEPKESELTKKTKKGLKTKGVIYECNICGARYKKRDNYEAHKKYYCSELQIAKPISAGTHTSPEAEKSQIEHEPWSQMMHYKLGTTL .

How is HIVEP3 involved in cancer progression and what methodologies are used to study this relationship?

HIVEP3 has been implicated in multiple cancer types, with particularly strong evidence in prostate cancer and acute myeloid leukemia:

• Prostate cancer association:

  • Expression analysis using quantitative RT-PCR has revealed significantly higher HIVEP3 mRNA expression in prostate cancer tissues compared to adjacent benign tissues (p=0.006) .

  • Immunohistochemical staining shows elevated HIVEP3 protein levels in prostate cancer tissues, particularly in cases with PSA failure (p=0.042) .

  • Correlation studies demonstrate that HIVEP3 expression positively correlates with SOX9 expression (Spearman correlation coefficient rs=0.51, p<0.001) .

• Acute myeloid leukemia involvement:

  • Transcriptomic analysis of TCGA datasets shows augmented HIVEP3 expression in AML patients (p<0.001) .

  • HIVEP3 expression correlates with AML subtypes, patient age, cytogenetic risk, and disease-related molecules .

  • Gene co-expression analysis reveals that HIVEP3-associated gene clusters are enriched in pathways related to AML leukemogenesis, including ribosome function, metabolism, and calcium signaling .

Methodologically, researchers investigating HIVEP3 in cancer typically employ:

• qRT-PCR for mRNA expression analysis

• Immunohistochemistry for protein localization and expression levels

• Survival analyses using Kaplan-Meier curves to correlate expression with patient outcomes

• LASSO regression algorithms to create prognostic signatures combining HIVEP3 with other molecules

• In vitro knockdown experiments using siRNA to evaluate functional consequences of HIVEP3 suppression

What is the mechanism of HIVEP3 involvement in ferroptosis and how can researchers experimentally investigate this connection?

Recent research has established a connection between HIVEP3 and ferroptosis pathways in acute myeloid leukemia:

• Expression correlation: HIVEP3 expression changes have been observed in leukemia cell lines treated with ferroptosis-inducing compounds, suggesting a functional relationship between HIVEP3 and ferroptosis mechanisms .

• Integrated modeling: LASSO regression modeling has identified an integrated prognostic signature combining HIVEP3 with ferroptosis regulators AIFM2 and LPCAT3, which effectively predicts outcomes for AML patients .

• Signaling pathway interactions: Co-expression analyses indicate that HIVEP3 interacts with multiple tumorigenesis signaling pathways, including those involved in ferroptosis regulation .

Researchers interested in investigating the HIVEP3-ferroptosis connection can employ several experimental approaches:

• Gene expression analysis: Monitor HIVEP3 expression changes in response to ferroptosis inducers (e.g., erastin, RSL3) using qRT-PCR .

• Cell viability assays: Compare ferroptotic cell death in cell lines with normal versus altered HIVEP3 expression levels.

• Lipid peroxidation assessment: Measure lipid peroxidation (a hallmark of ferroptosis) in relation to HIVEP3 expression using C11-BODIPY or TBARS assays.

• Redox state analysis: Evaluate GSH/GSSG ratios and iron metabolism in the context of HIVEP3 manipulation.

• Protein interaction studies: Investigate physical interactions between HIVEP3 and known ferroptosis regulators using co-immunoprecipitation or proximity ligation assays.

These methodological approaches can help elucidate the mechanistic basis of HIVEP3's involvement in ferroptosis, potentially revealing new therapeutic targets for AML treatment.

How does HIVEP3 cooperate with SOX9 in prostate cancer progression and what experimental designs best characterize this interaction?

The cooperation between HIVEP3 and SOX9 in prostate cancer represents a significant area of research with important clinical implications:

• Co-expression pattern: Immunohistochemical studies have demonstrated a significantly positive correlation between HIVEP3 and SOX9 protein expression in prostate cancer tissues (Spearman correlation coefficient rs=0.51, p<0.001) .

• Clinical significance: Tumors exhibiting high expression of both HIVEP3 and SOX9 (HIVEP3-high/SOX9-high) more frequently experience PSA failure (p=0.024) . Patients with combined overexpression of both proteins show worse biochemical recurrence-free survival (p<0.001) .

• Independent prognostic value: Multivariate analysis confirms that HIVEP3/SOX9 co-expression serves as an independent predictor of unfavorable biochemical recurrence-free survival in prostate cancer patients .

Researchers investigating this interaction should consider the following experimental approaches:

• Co-immunoprecipitation studies to determine whether HIVEP3 and SOX9 physically interact or form part of the same transcriptional complex.

• ChIP-seq analysis to identify genomic regions where both transcription factors bind, potentially revealing co-regulated target genes.

• Sequential ChIP (re-ChIP) to determine whether HIVEP3 and SOX9 simultaneously occupy the same genomic regions.

• Luciferase reporter assays with promoters of candidate target genes to assess the functional consequences of HIVEP3 and SOX9 co-expression on transcriptional activation or repression.

• RNA-seq analysis of cells with various combinations of HIVEP3 and SOX9 expression (single and double knockdown/overexpression) to elucidate the gene expression programs regulated by their cooperative action.

• In vivo studies using xenograft models with manipulated HIVEP3 and SOX9 expression to validate the significance of their cooperation in tumor progression.

These approaches can help elucidate the molecular mechanisms underlying the clinical observations and potentially identify intervention points for targeted therapy development.

What are the current knowledge gaps and future research directions for HIVEP3 in neurodevelopmental disorders?

HIVEP3 has been associated with neurodevelopmental disorders, particularly autism spectrum disorder, but significant knowledge gaps remain:

• Current evidence: HIVEP3 is listed in the SFARI Gene database with a score of 2, indicating strong evidence for its involvement in autism spectrum disorders . Additionally, HIVEP3 has been linked to Meckel Syndrome, Type 1 .

• Knowledge gaps:

  • The neuronal expression pattern of HIVEP3 across brain regions and developmental stages is incompletely characterized.

  • The molecular mechanisms by which HIVEP3 variants contribute to neurodevelopmental phenotypes remain largely unknown.

  • The specific target genes regulated by HIVEP3 in neural cells and their relevance to brain development have not been comprehensively identified.

  • The potential interaction of HIVEP3 with environmental factors in neurodevelopmental disorder etiology is unexplored.

• Future research directions:

  • Conditional knockout models: Generate and characterize neuron-specific or brain region-specific HIVEP3 knockout models to evaluate behavioral, electrophysiological, and structural consequences.

  • Single-cell transcriptomics: Apply single-cell RNA-seq to map HIVEP3 expression in various neural cell types throughout development and in neurodevelopmental disorder models.

  • Induced pluripotent stem cells (iPSCs): Derive neural cells from iPSCs harboring HIVEP3 variants to assess developmental trajectories, electrophysiological properties, and transcriptional profiles.

  • CRISPR-based screening: Employ CRISPR activation or interference screens to identify genetic modifiers of HIVEP3 function in neural cells.

  • Structural biology approaches: Determine how disease-associated variants affect HIVEP3 protein structure and interaction with DNA or protein partners.

  • Systems biology integration: Develop computational models integrating HIVEP3 into known neurodevelopmental gene networks to predict functional consequences of perturbations.

These research directions could significantly advance our understanding of HIVEP3's role in brain development and neurodevelopmental disorders, potentially revealing new diagnostic or therapeutic approaches.