Recombinant Mouse High affinity copper uptake protein 1 (Slc31a1)

What is mouse Slc31a1 and how does it function in copper homeostasis?

Mouse Slc31a1 encodes the High affinity copper uptake protein 1, also known as Copper transporter 1 (CTR1), which plays a critical role in maintaining intracellular copper concentration. This protein belongs to the CTR family that mediates copper translocation across cellular membranes into the cytoplasm in eukaryotes . Functionally, Slc31a1 serves as a limiting factor for cellular copper acquisition, as evidenced by excess copper accumulation in cells over-expressing the protein .

The importance of Slc31a1 in copper homeostasis can be observed in knockout mouse models. Slc31a1 heterozygous knockout mice show normal growth and reproduction compared to wild-type mice, but exhibit approximately 50% reduction in copper levels in the brain and spleen, demonstrating that both Slc31a1 alleles are necessary for optimal copper uptake in these organs . Additionally, intestine-specific Slc31a1 deficiency studies have confirmed its crucial role in copper absorption .

What expression patterns does Slc31a1 exhibit across different mouse tissues?

Based on the human data, which likely parallels mouse expression patterns, Slc31a1 is expressed in all organs and tissues, with particularly high levels in the liver and kidney . This widespread expression reflects the essential nature of copper as a cofactor for numerous enzymes across various physiological systems.

When studying Slc31a1 expression, researchers should consider both mRNA and protein levels, as these may not always correlate. For instance, the search results indicate that in some cancer cell lines, mRNA and protein expression levels of SLC31A1 showed divergent patterns . This highlights the importance of validating expression at both levels using techniques such as RT-qPCR and Western blotting.

What are the optimal methods for detecting Slc31a1 expression in mouse tissues and cells?

For accurate detection of Slc31a1 expression, researchers should employ multiple complementary techniques:

• RT-qPCR Analysis: For mRNA expression quantification, the following primers have been used successfully :

  • Slc31a1-F: 5'-GGGGATGAGCTATATGGACTCC-3'

  • Slc31a1-R: 5'-TCACCAAACCGGAAAACAGTAG-3'

  • GAPDH-F: 5'-ACCCACTCCTCCACCTTTGAC-3' (reference gene)

  • GAPDH-R: 5'-CTGTTGCTGTAGCCAAATTCG-3' (reference gene)

  The 2-ΔΔCT method is commonly used for quantification, with appropriate reference genes like GAPDH .

• Western Blot Analysis: For protein level detection, commercial antibodies targeting conserved epitopes of Slc31a1 are available. When interpreting Western blot results, consider that post-translational modifications may affect band patterns.

• Immunohistochemistry/Immunofluorescence: These techniques allow visualization of Slc31a1 localization within tissues and cells, providing insights into subcellular distribution patterns.

• Single-Cell RNA Sequencing: For high-resolution analysis of expression heterogeneity across cell populations, as indicated in the search results for human SLC31A1 .

When comparing expression across different experimental conditions, always include appropriate positive and negative controls, and consider factors such as copper availability that might influence Slc31a1 expression.

What are the key considerations when designing recombinant Slc31a1 expression systems?

When producing recombinant mouse Slc31a1, researchers should consider:

• Expression System Selection:

  • Mammalian systems: HEK293 cells are particularly suitable since SLC31A1 naturally localizes to the plasma membrane in these cells .

  • Yeast systems: May provide proper folding environment, as yeast CTR1 shows similar membrane localization to mammalian SLC31A1 .

  • Bacterial systems: Challenging for membrane proteins but can be optimized with fusion partners to enhance solubility.

• Construct Design Elements:

  • Affinity tags for purification (His, FLAG, etc.)

  • Signal sequences for proper membrane targeting

  • Fluorescent protein fusions for localization studies

  • Inducible promoters to control expression levels

• Purification Considerations:

  • Membrane protein extraction requires appropriate detergents

  • Maintaining protein stability throughout purification

  • Reconstitution into liposomes or nanodiscs for functional studies

• Functional Validation:

  • Copper uptake assays using radioactive 64Cu or fluorescent sensors

  • Binding studies using techniques like surface plasmon resonance

  • Complementation assays in Slc31a1-deficient cells

For membrane proteins like Slc31a1, maintaining native structure and function during recombinant expression and purification presents significant challenges that must be carefully addressed.

How can researchers establish and validate Slc31a1 knockout or knockdown mouse models?

Based on the knockout studies mentioned in the search results , several approaches can be employed:

• Genome Editing Strategies:

  • Global knockout: May affect multiple systems due to widespread expression

  • Conditional knockout: Using Cre-loxP systems for tissue-specific deletion

  • Inducible knockout: Temporal control to avoid developmental effects

• Knockdown Approaches:

  • siRNA or shRNA for transient suppression

  • Antisense oligonucleotides for in vivo applications

  • CRISPR interference (CRISPRi) for targeted repression

• Validation Requirements:

  • Genotyping to confirm genetic modifications

  • Expression analysis at mRNA and protein levels

  • Functional assessment of copper transport capacity

  • Measurement of tissue copper levels (especially in brain and spleen)

• Control Considerations:

  • Littermate controls to minimize genetic background effects

  • Heterozygous models as intermediates (showing ~50% reduction in copper levels in certain tissues)

  • Rescue experiments to confirm specificity of observed phenotypes

The search results indicate that Slc31a1 heterozygous knockout mice maintain normal growth and reproduction despite reduced copper levels in specific tissues , which provides important baseline information for phenotypic analysis.

How does Slc31a1 contribute to cancer biology and what are the implications for cancer models?

The search results reveal significant connections between SLC31A1 and cancer biology that can inform mouse cancer model studies:

These findings suggest that Slc31a1 may play context-dependent roles in cancer biology and could serve as a potential therapeutic target in appropriate mouse cancer models.

What interactions occur between Slc31a1 and other copper homeostasis proteins?

Understanding Slc31a1's interactome is crucial for comprehending copper homeostasis networks:

• Known Interaction Partners:
  The search results mention several genes correlated with SLC31A1 expression:

  • CHGB, CYB561, DBH, EML5, PHOX2B, and TBX20 show expression correlation with SLC31A1 across cancer types

• Functional Associations:

  • Enrichment analysis indicates SLC31A1-related genes are primarily associated with the mitochondrial matrix and coated vesicles

  • These associations suggest potential roles in mitochondrial copper delivery and vesicular trafficking

• Mechanistic Insights:

  • SLC31A1 affects intracellular Cu2+ levels by acting as a copper importer

  • Higher threshold levels of mitochondrial membrane potential (ΔΨm) are required for trace element entrance into the mitochondrial matrix

  • Interactions with calcium transport systems, including the Na+/Ca2+ exchanger (NCX) and mitochondrial calcium uniporter (MCU)

When studying these interactions in mouse models, researchers should consider both direct protein-protein interactions and functional relationships that may not involve physical binding.

How can researchers investigate the role of Slc31a1 in neurological disorders?

The search results indicate that copper levels in the brain of Slc31a1 knockout mice are approximately 50% lower than in control mice , highlighting the importance of this transporter in neurological function:

• Experimental Approaches:

  • Neuronal-specific conditional knockout models to avoid systemic effects

  • Behavioral testing to assess cognitive and motor functions

  • Electrophysiological studies to evaluate neuronal activity

  • Histological and biochemical analyses of copper-dependent processes in the brain

• Relevant Disease Models:

  • Neurodegenerative disorders where copper dysregulation is implicated

  • Models of conditions with altered energy metabolism, given the links between SLC31A1 and mitochondrial function

  • Developmental disorders, considering the likely importance of copper during neurodevelopment

• Mechanistic Investigations:

  • Copper delivery to copper-dependent enzymes in neurons

  • Effects on synaptic function and plasticity

  • Mitochondrial function and energy metabolism

  • Oxidative stress responses and antioxidant systems

• Therapeutic Implications:

  • Targeted copper delivery strategies bypassing Slc31a1

  • Modulation of Slc31a1 expression or function

  • Combinatorial approaches addressing downstream effects of altered copper homeostasis

How should researchers interpret conflicting data regarding Slc31a1 expression and function?

The search results reveal instances where mRNA and protein expression levels of SLC31A1 show discordant patterns , highlighting important considerations for data interpretation:

• Expression Level Discrepancies:

  • Always assess both mRNA and protein levels when possible

  • Consider post-transcriptional regulation mechanisms

  • Evaluate half-life differences between mRNA and protein

  • Use multiple detection methods to cross-validate findings

• Functional Assessment Challenges:

  • Copper transport capacity may not directly correlate with expression levels

  • Consider compensatory mechanisms in knockout/knockdown models

  • Evaluate downstream copper-dependent processes as functional readouts

  • Account for cellular copper status when interpreting transport activity

• Experimental Design Considerations:

  • Include appropriate positive and negative controls

  • Standardize experimental conditions, particularly copper availability

  • Account for cell/tissue type-specific differences in regulation

  • Consider temporal dynamics of copper transport

• Statistical Analysis:

  • Perform sufficient biological and technical replicates

  • Apply appropriate statistical tests for the data distribution

  • Consider effect sizes alongside statistical significance

  • Control for multiple comparisons in large-scale datasets

What bioinformatic approaches are valuable for analyzing Slc31a1 in multi-omics datasets?

Based on the analytical approaches described in the search results , several bioinformatic strategies can be applied:

• Expression Analysis Tools:

  • Databases like TIMER2.0, GEPIA, UALCAN, and cBioPortal were used for SLC31A1 analysis

  • These platforms enable comprehensive assessment across multiple cancer types and normal tissues

• Correlation Analyses:

  • Gene expression correlation with clinical outcomes (survival analysis)

  • Association with immune cell infiltration patterns

  • Correlation with other genes to identify functional networks

• Methylation Analysis:

  • Assessment of promoter methylation status and its impact on expression

  • Correlation between methylation and clinical features

  • Identification of differentially methylated regions

• Mutation and Genetic Alteration Analysis:

  • Identification of mutation hotspots and frequencies

  • Evaluation of copy number variations

  • Assessment of structural variants and their functional consequences

• Functional Enrichment Analysis:

  • GO/KEGG pathway analysis of Slc31a1-associated genes

  • Identification of enriched biological processes and cellular components

  • The search results identified enrichment in mitochondrial matrix and coated vesicles

• Single-Cell Analysis Approaches:

  • Databases like CancerSEA for single-cell level functional state analysis

  • Correlation with biological processes like angiogenesis, differentiation, and quiescence

These approaches can provide comprehensive insights into the multifaceted roles of Slc31a1 across different biological contexts.

How might Slc31a1 be involved in cuproptosis and related cell death mechanisms?

The search results specifically mention SLC31A1 as a "cuproptosis-associated" gene , suggesting emerging connections to this copper-dependent cell death mechanism:

• Cuproptosis Mechanism:

  • A recently described form of cell death triggered by copper overload

  • Involves mitochondrial dysfunction and protein lipoylation disruption

  • SLC31A1 as a copper importer would be a key regulator of cellular copper availability

• Research Approaches:

  • Modulation of Slc31a1 expression to alter sensitivity to cuproptosis inducers

  • Assessment of mitochondrial function in Slc31a1-manipulated models

  • Evaluation of protein lipoylation status in relation to Slc31a1 activity

  • Investigation of the threshold effects of copper transport on cell viability

• Cancer Relevance:

  • The search results indicate associations between SLC31A1 and cancer outcomes

  • Potential therapeutic exploitation of cuproptosis by modulating Slc31a1 function

  • Differential sensitivity of cancer cells versus normal cells to copper-dependent death

• Interaction with Other Death Pathways:

  • Cross-talk with apoptosis, as suggested by negative correlation with apoptosis in UVM

  • Connections to DNA damage responses, also negatively correlated in UVM

  • Potential synergies with other cell death mechanisms for therapeutic applications

What is the significance of Slc31a1 in the context of tumor immunology and immunotherapy?

The search results reveal extensive associations between SLC31A1 and immune cell infiltration in various cancers :

• Immune Cell Correlations:

  • Positive correlation with CD8+ T cells in multiple cancer types

  • Varied associations with dendritic cells across different cancers

  • Cancer-specific correlations with regulatory T cells (Tregs)

  • Relationships with numerous other immune cell populations

• Research Questions to Address:

  • Does Slc31a1 directly influence immune cell recruitment or function?

  • Are these correlations causal or consequential?

  • How does Slc31a1-mediated copper transport affect immune cell metabolism and activity?

  • Could Slc31a1 modulation enhance immunotherapy responses?

• Experimental Approaches:

  • Immune profiling of tumors with altered Slc31a1 expression

  • Co-culture systems examining cancer-immune cell interactions

  • Assessment of immune checkpoint molecule expression

  • Combination of copper modulators with immunotherapeutics

• Therapeutic Implications:

  • Potential for Slc31a1 targeting to reshape the tumor immune microenvironment

  • Biomarker value for predicting immunotherapy response

  • Development of combination approaches targeting both copper homeostasis and immune checkpoints

This represents a promising frontier for Slc31a1 research with significant translational potential.