SNAI2 Human

What is SNAI2 and what is its primary function in human cells?

SNAI2 (Snail Family Transcriptional Repressor 2) is a transcription factor that functions primarily as a transcriptional repressor in human cells. It serves as an inducer of epithelial to mesenchymal transition (EMT), which mediates cell migration during development and tumor invasion . SNAI2 binds to specific DNA sequences in promoter regions of target genes and represses their expression .

In epithelial cells, SNAI2 expression is enriched in progenitor cells and plays a critical role in maintaining the undifferentiated state . The levels of SNAI2 expression are important for cell fate decisions, with different expression levels triggering different cellular responses: high levels can induce EMT and dedifferentiation, moderate (physiological) levels promote progenitor function, and low levels permit differentiation .

How is SNAI2 expression regulated in normal human tissues?

In normal human tissues, SNAI2 expression follows a specific pattern related to cell differentiation status. In the epidermis, SNAI2 expression is enriched in the basal layer where progenitor cells reside and is extinguished upon differentiation . This suggests a tight regulatory control linked to differentiation pathways.

SNAI2 expression is also regulated in response to DNA damage , indicating its involvement in stress response pathways. The regulation of SNAI2 appears to involve p53-dependent mechanisms, as studies in mouse embryonic fibroblasts (MEFs) have shown interactions between SNAI2 and the p53 pathway in response to DNA damage .

Transcriptional regulation of SNAI2 involves a complex network of factors that maintain its expression in stem/progenitor cells while ensuring its downregulation during differentiation processes . This precise control allows SNAI2 to function in maintaining the undifferentiated state while permitting differentiation when appropriate.

What cellular processes does SNAI2 control in human epidermal cells?

In human epidermal cells, SNAI2 functions as a master regulator of multiple key cellular processes:

• Differentiation: SNAI2 controls the differentiation status of epidermal progenitor cells. Loss of SNAI2 results in premature differentiation, whereas increased SNAI2 expression inhibits differentiation .

• Cell adhesion: SNAI2 depletion in cultured epidermal cells results in increased cell adhesion, suggesting its role in modulating cell-cell interactions .

• Gene expression: SNAI2 binds to and represses the expression of differentiation genes, with increased binding leading to further transcriptional silencing .

• Progenitor cell maintenance: SNAI2 is essential for maintaining the undifferentiated state of epidermal progenitor cells in the basal layer of the epidermis .

• Cell motility: High levels of SNAI2 promote increased cell motility, which is important for processes like wound healing .

The impact of SNAI2 on these processes is dose-dependent, with different levels of SNAI2 expression leading to different cellular outcomes .

What are the DNA binding characteristics of SNAI2?

SNAI2 functions as a transcriptional repressor that binds to specific DNA sequences in the promoter regions of target genes. The search results indicate that SNAI2 binds to specific SNAI2 DNA-binding sites that have been characterized in previous studies . These binding sites have been identified in the promoter regions of various genes including Atm, Cdkn1b/p27, Bid , and several differentiation-associated genes in epidermal cells .

Chromatin immunoprecipitation combined with deep sequencing (ChIP-Seq) has revealed that SNAI2 binding across the genome is dictated by the levels of SNAI2 expression, with overexpression of SNAI2 increasing binding to target sites . In differentiated cells, SNAI2 binding to targets is reduced, but this binding can be restored by overexpression of SNAI2, which blocks the expression of differentiation genes .

SNAI2 may directly regulate up to 43.9% of the induced genes in SNAI2-depleted cells, with the remaining genes potentially being regulated indirectly through SNAI2's regulation of other transcription factors like KLF4 and GRHL3 .

How does SNAI2 interact with the p53 pathway?

SNAI2 interacts with the p53 pathway in the context of DNA damage response. Snai2-deficient cells are radiosensitive to DNA damage, suggesting a critical function of SNAI2 in response to DNA damage that is important for its role in normal development and cancer .

The presence of SNAI2 DNA-binding sites in the promoter regions of these p53 target genes suggests that SNAI2 could be directly involved in controlling their transcription . This selective regulation of p53 target genes by SNAI2 indicates a complex interplay between SNAI2 and the p53 pathway in response to DNA damage, with implications for both normal development and cancer management .

How does SNAI2 regulate the epidermal differentiation program at the molecular level?

At the molecular level, SNAI2 regulates the epidermal differentiation program through direct binding to and repression of differentiation genes. When SNAI2 is depleted using shRNAs, there is faster induction and more robust expression of differentiation proteins like K10 during epidermal tissue regeneration . Moreover, SNAI2 depletion results in premature expression of differentiation proteins such as TGM1, increased cell adhesion, and upregulation of differentiation gene expression similar to cells undergoing calcium-induced differentiation .

Genome-wide analyses have identified genes regulated by SNAI2 in epidermal cells. Genes downregulated by SNAI2 overexpression and upregulated during differentiation were enriched for GO terms related to cornified envelope, cell-cell junction, and keratinocyte differentiation . This suggests that high levels of SNAI2 promote dedifferentiation and increased cell motility.

By overlapping gene signatures from SNAI2-depleted and SNAI2-overexpressing cells, researchers identified 248 genes that are likely direct targets of SNAI2, with 144 genes being downregulated in SNAI2-overexpressing cells and upregulated in SNAI2-depleted cells, enriched for epidermal differentiation GO terms .

SNAI2 may also indirectly regulate differentiation by controlling other transcription factors critical for epidermal differentiation, such as KLF4 and GRHL3 .

What is the role of SNAI2 in DNA damage response pathways?

SNAI2 plays a significant role in DNA damage response pathways. Snai2-deficient cells have been found to be radiosensitive to DNA damage, indicating that SNAI2 function in response to DNA damage is critical for its role in normal development and cancer .

Studies using functional genomics approaches have provided insights into the Snai2-dependent transcriptional response to DNA damage. In mouse embryonic fibroblasts (MEFs), which undergo p53-dependent growth arrest in response to DNA damage, researchers combined gene expression profiling and computational molecular network analysis to dissect the Snai2-dependent response .

• Downregulated genes in Snai2-deficient cells compared to control: Atm, Cdkn1b/p27, and Bid. These proteins were confirmed to be downregulated in Snai2-deficient cells in response to DNA damage by quantitative RT-PCR and using specific antibodies .

• P53 target genes modulated by Snai2, which belong to categories such as metastasis (Cxcl1), cell cycle/DNA/oxidative damage (Hspb1, Mt1, Fos), survival (Tgm2), and cell development (Foxg1) .

The presence of Snai2 DNA-binding sites in the promoter regions of these genes suggests that Snai2 might be directly involved in controlling their transcription-repression .

How does SNAI2 control the expression of differentiation genes?

SNAI2 controls the expression of differentiation genes through direct binding to their promoter regions and repressing their transcription. This control is dependent on the levels of SNAI2 expression, with increased binding leading to further transcriptional silencing .

Chromatin immunoprecipitation combined with deep sequencing (ChIP-Seq) studies have revealed that SNAI2 binding across the genome is dictated by SNAI2 expression levels . In progenitor cells, SNAI2 binds to and represses differentiation genes. When SNAI2 is depleted using shRNAs, there is a dramatic loss of SNAI2 binding on the genomic level as well as on single genes, leading to derepression of differentiation genes .

SNAI2 may directly regulate up to 43.9% (215/490) of the induced genes in SNAI2-depleted cells. The remaining 56.1% may be regulated indirectly by SNAI2 through its direct regulation of other transcription factors like KLF4 and GRHL3, which are necessary for the transcriptional activation of the epidermal differentiation program .

What experimental approaches are used to study SNAI2 binding to genomic targets?

Several experimental approaches are used to study SNAI2 binding to genomic targets, with chromatin immunoprecipitation combined with deep sequencing (ChIP-Seq) being the primary method highlighted in the search results . This approach allows researchers to identify genome-wide binding sites of SNAI2 and understand how binding patterns change under different conditions.

In the studies described, ChIP-Seq was performed using a SNAI2 antibody on:

• Progenitor cells overexpressing LACZ (control) or SNAI2

• Differentiated cells overexpressing LACZ or SNAI2

• Control shRNA and SNAI2-depleted (SNAI2i) progenitor cells to determine antibody specificity

The experimental design allowed researchers to observe that depletion of SNAI2 by shRNAs resulted in a dramatic loss of SNAI2 binding on the genomic level as well as on single genes. They also observed that in differentiated cells, normal SNAI2 binding was reduced, but overexpression of SNAI2, even in differentiated cells, restored the binding and blocked the expression of differentiation genes .

To validate potential SNAI2 binding sites, researchers examine promoter regions for the presence of known SNAI2 DNA-binding motifs . Additional validation is achieved through quantitative RT-PCR to measure changes in gene expression and Western blotting with specific antibodies to confirm protein-level changes .

How is SNAI2 implicated in maintaining stemness in epithelial progenitor cells?

SNAI2 is critically implicated in maintaining stemness in epithelial progenitor cells through several mechanisms:

• Expression pattern: SNAI2 expression is enriched in the basal layer of the interfollicular epidermis where progenitor cells reside and is extinguished upon differentiation .

• Differentiation control: Loss of SNAI2 results in premature differentiation, whereas gain of SNAI2 expression inhibits differentiation . This indicates that SNAI2 is necessary for maintaining cells in an undifferentiated state.

• Transcriptional repression: SNAI2 controls the differentiation status of epidermal progenitor cells by binding to and repressing the expression of differentiation genes . This repression is level-dependent, with increased binding leading to further transcriptional silencing.

• Basal layer maintenance: In SNAI2-depleted (SNAI2i) tissue, the basal layer is much smaller with at most 1 cell layer, whereas control tissue has several layers of undifferentiated basal layer cells .

• Promotion of progenitor function: Moderate (physiological) levels of SNAI2 promote epidermal progenitor function, while low levels lead to epidermal differentiation .

SNAI2 has also been shown to promote the generation of mammary epithelial stem cells from differentiated luminal cells when overexpressed , further supporting its role in maintaining and potentially inducing stemness.

What is the role of SNAI2 in neuroblastoma progression?

SNAI2 has significant implications for neuroblastoma progression. One study specifically investigates how the transcriptional repressor SNAI2 impairs neuroblastoma differentiation and inhibits response to retinoic acid therapy .

Neuroblastoma is a tumor mentioned in the search results in connection with SNAI2, and the title of one of the papers suggests that SNAI2 plays a role in inhibiting differentiation in neuroblastoma cells . This is consistent with SNAI2's known role as a repressor of differentiation in other cell types, such as epidermal progenitor cells .

The search results mention that the study involved animals, cell lines, tumor cell movement, and neural crest and neural stem cells, suggesting that the research examined SNAI2's role in neuroblastoma through multiple experimental approaches .

Additionally, the study appears to have investigated SNAI2's impact on the response to retinoic acid therapy, which is a treatment approach for neuroblastoma . This suggests that SNAI2 might be involved in therapy resistance mechanisms in neuroblastoma.

While the search results don't provide detailed findings from this study, the title strongly suggests that SNAI2 has a negative impact on neuroblastoma differentiation and treatment response, which would be consistent with its role as a maintainer of the undifferentiated state in other cell types .

How does SNAI2 expression affect response to retinoic acid therapy?

According to the search results, SNAI2 expression can inhibit response to retinoic acid therapy . The title of one of the papers specifically mentions that "The transcriptional repressor SNAI2 impairs neuroblastoma differentiation and inhibits response to retinoic acid therapy" .

Retinoic acid is a vitamin A derivative that induces differentiation in various cell types and is used as a therapeutic agent in neuroblastoma and other cancers. The ability of SNAI2 to inhibit response to retinoic acid therapy is consistent with its known role as a repressor of differentiation .

While the search results don't provide detailed mechanisms of how SNAI2 inhibits retinoic acid response, we can infer potential mechanisms based on SNAI2's known functions:

• SNAI2 is a transcriptional repressor that binds to and represses differentiation genes , which may include genes that are normally activated by retinoic acid signaling.

• SNAI2 maintains cells in an undifferentiated state , potentially counteracting the differentiation-inducing effects of retinoic acid.

• SNAI2 may regulate other transcription factors involved in differentiation , potentially interfering with the transcriptional networks activated by retinoic acid.

This negative impact on retinoic acid response suggests that SNAI2 may be a potential therapeutic target in neuroblastoma, particularly in cases where retinoic acid therapy is part of the treatment regimen .

What transcriptional networks are regulated by SNAI2 in cancer?

Based on the search results, SNAI2 regulates various transcriptional networks in cancer, particularly in the context of DNA damage response and cell differentiation:

• DNA Damage Response Network: In response to DNA damage, SNAI2 regulates a subset of p53 target genes involved in:

  • Metastasis (e.g., Cxcl1)

  • Cell cycle/DNA/oxidative damage (e.g., Hspb1, Mt1, Fos)

  • Survival (e.g., Tgm2)

  • Cell development (e.g., Foxg1)

• DNA Damage Repair Pathway: SNAI2 appears to regulate key components of DNA damage sensing and repair, including Atm, which is a critical kinase in the DNA damage response pathway .

• Cell Cycle Regulation: SNAI2 regulates Cdkn1b/p27, which is involved in cell cycle control .

• Apoptosis Pathway: SNAI2 regulates Bid, which is a pro-apoptotic protein involved in the intrinsic apoptosis pathway .

• Differentiation Networks: SNAI2 represses differentiation gene networks, which may contribute to cancer progression by maintaining cells in a less differentiated, more stem-like state .

The Ingenuity program analysis of microarray data from Snai2-deficient cells identified molecular networks in which proteins like Atm, Cdkn1b/p27, and Bid showed altered expression in response to DNA damage . The presence of SNAI2 DNA-binding sites in the promoter regions of these genes suggests that SNAI2 might directly regulate their transcription , forming a SNAI2-dependent transcriptional network with implications for cancer management.

What experimental models are used to study SNAI2 function in cancer?

Based on the search results, several experimental models are used to study SNAI2 function in cancer:

• Cell Lines:

  • Neuroblastoma cell lines are mentioned in relation to studying SNAI2's role in neuroblastoma differentiation and response to retinoic acid therapy .

  • Mouse Embryonic Fibroblasts (MEFs) are used to study SNAI2's role in DNA damage response, with experiments comparing wild-type MEFs, p53-/- MEFs, and Snai2-deficient MEFs .

• Animal Models:

  • Mice are mentioned in the tags of one study , suggesting the use of mouse models.

  • Studies involving adrenal glands and kidneys fixed in paraformaldehyde, followed by histological analysis of tumors in the liver, suggest the use of mouse models of cancer .

• Genetic Manipulation Approaches:

  • SNAI2 depletion using shRNAs to study loss-of-function effects .

  • Overexpression of SNAI2 to study gain-of-function effects .

  • CRISPR-Cas9 technology is mentioned in the tags of one study , suggesting its use for genetic manipulation of SNAI2.

  • Double knockdown experiments (e.g., simultaneous knockdown of SNAI2 and KLF4 or SNAI2 and GRHL3) to study functional interactions .

• DNA Damage Models:

  • Treatment with doxorubicin to induce DNA damage in MEFs .

  • Exposure to γ-irradiation (5 and 8 Gy) to induce well-characterized arrest in both G1 and G2 phases .

• Molecular and Genomic Approaches:

  • Gene expression profiling using microarrays to identify SNAI2-regulated genes .

  • Chromatin immunoprecipitation combined with deep sequencing (ChIP-Seq) to identify SNAI2 binding sites .

  • Computational molecular network analysis using tools like the Ingenuity Pathways Analysis program .

These diverse experimental models and approaches allow researchers to gain comprehensive insights into SNAI2's functions in cancer at multiple levels.

How do SNAI2 levels correlate with patient outcomes in different cancers?

While the search results do not provide direct information about correlations between SNAI2 levels and patient outcomes in different cancers, we can infer potential implications based on SNAI2's functional roles:

• Therapy Response: SNAI2 impairs neuroblastoma differentiation and inhibits response to retinoic acid therapy , suggesting that high SNAI2 levels might correlate with poor response to differentiation-inducing therapies like retinoic acid in neuroblastoma patients.

• DNA Damage Response: SNAI2 plays a role in the DNA damage response , which could potentially impact the efficacy of DNA-damaging cancer therapies such as radiation and certain chemotherapies. Snai2-deficient cells are radiosensitive to DNA damage , suggesting that low SNAI2 levels might correlate with better response to radiotherapy.

• Differentiation Status: SNAI2 maintains cells in an undifferentiated state , and poorly differentiated tumors are generally associated with worse prognosis. This suggests that high SNAI2 levels might correlate with poorly differentiated tumors and potentially worse outcomes.

• Epithelial to Mesenchymal Transition (EMT): SNAI2 is an inducer of EMT , which is associated with increased invasiveness, metastatic potential, and therapy resistance in many cancers. This suggests that high SNAI2 levels might correlate with increased metastasis and worse outcomes.

While these inferences are reasonable based on the known functions of SNAI2, the search results do not provide direct evidence for correlations between SNAI2 levels and patient outcomes in specific cancer types.

What are the recommended methods for studying SNAI2 binding to DNA?

Based on the search results, the primary recommended method for studying SNAI2 binding to DNA is Chromatin Immunoprecipitation combined with deep sequencing (ChIP-Seq) . Here's a detailed overview of the methodology and considerations:

• ChIP-Seq Protocol:

  • Use a specific SNAI2 antibody for immunoprecipitation of SNAI2-bound chromatin .

  • Include appropriate controls such as:

    • Cells overexpressing LACZ as a control for SNAI2 overexpression

    • Cells with SNAI2 knockdown (SNAI2i) to determine antibody specificity

  • Compare binding patterns across different conditions (e.g., progenitor vs. differentiated cells, control vs. SNAI2-overexpressing cells) .

• Validation of Binding Sites:

  • Analyze promoter regions for the presence of known SNAI2 DNA-binding motifs .

  • Perform quantitative RT-PCR (qRT-PCR) to validate changes in expression of potential target genes .

  • Use specific antibodies to confirm protein-level changes of potential targets by Western blotting .

• Functional Validation:

  • Manipulate SNAI2 levels through overexpression or knockdown .

  • Assess the functional impact of SNAI2 binding on target gene expression and cellular phenotypes .

• Data Analysis:

  • Process ChIP-Seq data to identify SNAI2 binding peaks across the genome.

  • Correlate binding data with gene expression data to identify direct targets of SNAI2.

  • Use tools like the Ingenuity Pathways Analysis program to identify molecular networks regulated by SNAI2 .

These methods have been successfully used to identify SNAI2 binding sites in the context of both epidermal differentiation and DNA damage response .

How can researchers effectively modulate SNAI2 expression in experimental systems?

Based on the search results, researchers have employed several approaches to effectively modulate SNAI2 expression in experimental systems:

• RNA Interference (RNAi):

  • Short hairpin RNAs (shRNAs) targeting SNAI2 have been used for stable knockdown of SNAI2 expression .

  • Small interfering RNAs (siRNAs) are mentioned in one study , suggesting their use for transient knockdown of SNAI2.

• CRISPR-Cas9 Gene Editing:

  • Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technology is mentioned in one study , indicating its use for genetic manipulation of SNAI2, potentially for knockout or precise editing of the SNAI2 gene.

• Overexpression Systems:

  • Viral vectors have been used to overexpress SNAI2 in cells, such as the LZRS-SNAI2 system mentioned in the context of differentiated cells .

  • Control vectors expressing LACZ have been used as appropriate controls for overexpression studies .

• Validation of Modulation:

  • Knockdown efficiency has been validated through immunostaining, showing the absence of SNAI2 staining in the basal layer of SNAI2i epidermis .

  • Western blotting with SNAI2-specific antibodies can be used to confirm protein-level changes .

  • Quantitative RT-PCR can be used to measure changes in SNAI2 mRNA levels .

• Combinatorial Approaches:

  • Simultaneous knockdown of SNAI2 and other transcription factors (e.g., KLF4 or GRHL3) has been performed to study functional interactions .

These approaches allow researchers to effectively modulate SNAI2 expression in a variety of experimental systems, enabling detailed studies of SNAI2's functions in different cellular contexts.

What cell and animal models are most appropriate for SNAI2 functional studies?

Based on the search results, several cell and animal models have been used effectively for SNAI2 functional studies:

• Cell Models:

  • Primary Mouse Embryonic Fibroblasts (MEFs): These have been used extensively to study SNAI2's role in DNA damage response. MEFs represent an ideal cell system in which the activities of p53 can be studied, as they undergo cell cycle checkpoint activation by arresting in G1 when treated with DNA-damaging agents .

  • Human Epidermal Progenitor Cells: These have been used to study SNAI2's role in maintaining the undifferentiated state and in epidermal differentiation . The ability to regenerate the entire human epidermis in vitro makes this a valuable model system .

  • Neuroblastoma Cell Lines: These have been used to study SNAI2's role in neuroblastoma differentiation and response to retinoic acid therapy .

• Animal Models:

  • Mice: Several studies have used mouse models, including:

    • Snai2-deficient mice to study the effects of SNAI2 loss on various tissues and processes .

    • Mouse models allowing the examination of adrenal glands, kidneys, and liver tumors in the context of SNAI2 function .

• Tissue Models:

  • Epidermal Tissue Regeneration Models: These have been used to study the role of SNAI2 in epidermal differentiation and progenitor cell function .

These models have proven valuable for elucidating SNAI2's diverse functions in differentiation, DNA damage response, and cancer progression. The selection of an appropriate model depends on the specific aspect of SNAI2 function being investigated.

How should researchers analyze SNAI2-dependent transcriptional networks?

Based on the search results, researchers have employed several approaches to analyze SNAI2-dependent transcriptional networks effectively:

• Gene Expression Profiling:

  • Microarray analysis comparing gene expression in control versus SNAI2-depleted or SNAI2-overexpressing cells .

  • For DNA damage studies, compare expression profiles of cells before and after treatment with DNA-damaging agents .

  • Include appropriate controls such as wild-type versus Snai2-deficient cells, and untreated versus DNA-damaged cells .

• Identification of Direct Targets:

  • Chromatin Immunoprecipitation combined with deep sequencing (ChIP-Seq) to identify direct binding targets of SNAI2 .

  • Analyze promoter regions of differentially expressed genes for the presence of known SNAI2 DNA-binding motifs .

  • Correlate binding data with gene expression data to distinguish direct from indirect targets .

• Network Analysis:

  • Use computational tools like the Ingenuity Pathways Analysis program to identify molecular networks regulated by SNAI2 .

  • This approach relates each gene entry with a database of known physical transcriptional or protein interactions .

  • Identify proteins whose expression is altered in SNAI2-deficient cells in response to specific stimuli .

• Functional Categorization:

  • Categorize SNAI2-regulated genes based on biological or pathological functions, such as metastasis, cell cycle/DNA damage, survival, and cell development .

  • Use Gene Ontology (GO) term enrichment analysis to identify biological processes enriched in SNAI2-regulated gene sets .

• Overlapping Gene Signatures:

  • Overlap gene signatures from different conditions (e.g., SNAI2-depleted and SNAI2-overexpressed) to identify the most susceptible genes to SNAI2 levels as well as potential direct targets .

These approaches together provide a comprehensive understanding of SNAI2-dependent transcriptional networks in different cellular contexts.

What are the current technical challenges in studying SNAI2 function?

Several technical challenges can be inferred in studying SNAI2 function based on the search results:

• Antibody Specificity and Quality:

  • The search results mention using ChIP-Seq on control shRNA and SNAI2i progenitor cells to determine the specificity of the SNAI2 antibody , suggesting that antibody specificity is a concern.

  • Reliable antibodies are crucial for techniques like ChIP-Seq, Western blotting, and immunostaining that are used to study SNAI2.

• Distinguishing Direct from Indirect Targets:

  • SNAI2 may directly regulate up to 43.9% of the induced genes in SNAI2i cells, with the remaining potentially being regulated indirectly through other transcription factors .

  • Distinguishing direct from indirect regulation requires integrating multiple data types and can be technically challenging.

• Level-Dependent Effects:

  • SNAI2's effects are level-dependent, with different levels triggering different cellular responses . This complexity makes it challenging to interpret results from experiments where SNAI2 levels may vary.

• Cell Type and Context Specificity:

  • SNAI2 functions differently in different cell types and contexts (e.g., progenitor vs. differentiated cells, normal vs. cancer cells, untreated vs. DNA-damaged cells) .

  • This context specificity necessitates careful selection of experimental systems and complicates the generalization of findings.

• Integration of Multiple Data Types:

  • The comprehensive study of SNAI2 function requires integrating data from multiple approaches (e.g., gene expression, ChIP-Seq, functional assays).

  • The search results describe the use of tools like the Ingenuity Pathways Analysis program to integrate different data types , but this integration remains technically challenging.

These technical challenges highlight the complexity of studying SNAI2 function and the need for careful experimental design and data interpretation in this field.