Recombinant Human Talanin (ZNF365)

What is Talanin and what is its relationship to ZNF365?

Talanin is a protein encoded by the ZNF365D transcript, which is one of several isoforms produced through alternative splicing of the ZNF365 gene located on chromosome 10q21-q22. ZNF365 gene produces several transcripts coding for four protein isoforms, with Talanin being one of them. The protein is referred to as Talanin when discussing the specific isoform associated with uric acid nephrolithiasis (UAN) .

What are the known functions of Talanin (ZNF365) in human biology?

Talanin (ZNF365) has been primarily associated with uric acid nephrolithiasis, a condition characterized by kidney stones formed from uric acid. Evolutionary studies suggest that Talanin emerged during primate evolution in parallel with the disappearance of uricase, which in most mammals degrades uric acid to allantoin. This evolutionary timing suggests Talanin may play a role in uric acid metabolism or in mitigating the effects of hyperuricemia in humans . Different isoforms of ZNF365 have different expression patterns and functions, with some evidence suggesting roles in various cellular processes including potential tumor suppressor activity .

What are the key molecular characteristics of Human Talanin (ZNF365)?

Human Talanin (ZNF365) has the following molecular characteristics:

The protein belongs to the zinc finger protein family, which typically functions in DNA binding and transcriptional regulation .

What are the optimal methods for expressing recombinant Human Talanin (ZNF365) in bacterial systems?

For bacterial expression of recombinant Human Talanin (ZNF365), E. coli is typically the preferred host system due to its rapid growth, well-established genetic manipulation techniques, and cost-effectiveness. The expression strategy should include:

• Codon optimization for E. coli expression, as human proteins often contain codons rarely used in E. coli

• Addition of suitable tags (e.g., His-tag) for purification purposes

• Selection of appropriate expression vectors with strong, inducible promoters (e.g., T7)

• Growth at lower temperatures (16-25°C) after induction to enhance proper folding

• Consideration of fusion partners to improve solubility (e.g., MBP, SUMO, GST)

Since ZNF365 contains zinc finger domains, the expression media should be supplemented with zinc salts (typically ZnCl₂ or ZnSO₄ at 50-100 μM) to ensure proper folding of these domains .

What detection methods are most reliable for quantifying Human Talanin (ZNF365) in experimental samples?

Several methods can be employed for quantifying Human Talanin (ZNF365), with their selection depending on the specific research requirements:

For ELISA-based quantification, commercial kits are available with a detection range of 0.156-10 ng/ml, suitable for various biological samples including serum, plasma, tissue homogenates, and cell culture supernatants .

How should researchers design experiments to study the role of Talanin in uric acid metabolism?

When designing experiments to investigate Talanin's role in uric acid metabolism, researchers should consider a multi-faceted approach:

• Cellular models:

  • Establish cell lines with Talanin overexpression, knockdown, or knockout

  • Compare uric acid handling in cells with different Talanin expression levels

  • Assess the impact of Talanin mutations associated with UAN

• Biochemical assays:

  • Measure uric acid uptake, secretion, and intracellular levels

  • Examine potential interactions between Talanin and uric acid transporters

  • Investigate potential enzymatic activities related to purine metabolism

• Molecular interactions:

  • Perform co-immunoprecipitation to identify Talanin's binding partners

  • Use chromatin immunoprecipitation if Talanin is suspected to regulate genes involved in uric acid metabolism

  • Consider yeast two-hybrid or proximity labeling approaches to discover novel interactions

• Evolutionary context:

  • Include comparative studies with primates that retain functional uricase

  • Consider the timing of Talanin emergence versus uricase loss during primate evolution

• Clinical correlations:

  • Analyze Talanin expression or mutations in patients with hyperuricemia or UAN

  • Assess potential correlations between Talanin variants and uric acid levels in the general population

This comprehensive approach allows for triangulation of Talanin's functional roles from multiple experimental angles.

What are the mechanisms underlying Talanin (ZNF365) epigenetic regulation and its impact on disease progression?

Research suggests that ZNF365 expression can be regulated through epigenetic mechanisms, particularly DNA methylation. Studies have shown that downregulation of ZNF365 by methylation may predict poor prognosis in certain conditions . To investigate these mechanisms:

• Methylation analysis:

  • Perform bisulfite sequencing of the ZNF365 promoter region

  • Use methylation-specific PCR to quantify the degree of promoter methylation

  • Employ genome-wide methylation arrays to identify CpG islands affected

• Functional consequences:

  • Correlate methylation status with ZNF365 expression levels

  • Use demethylating agents (e.g., 5-azacytidine) to restore expression

  • Assess the impact of restored expression on cellular phenotypes

• Clinical implications:

  • Apply Kaplan-Meier survival analysis to correlate ZNF365 methylation with patient outcomes

  • Use Cox's proportional hazards regression models for multivariate analysis

  • Calculate hazard ratios (HRs) with 95% confidence intervals to quantify risk

• Therapeutic potential:

  • Evaluate whether epigenetic drugs can effectively restore Talanin expression

  • Investigate downstream pathways that could be targeted in cases of Talanin dysfunction

Understanding these epigenetic mechanisms could potentially lead to novel biomarkers and therapeutic approaches for diseases associated with Talanin dysregulation.

How can researchers resolve contradictory data regarding Talanin's evolutionary emergence and its functional importance?

The evolutionary history of Talanin presents several interesting contradictions that researchers should address methodically:

• Sequence analysis approach:

  • Perform comprehensive phylogenetic analysis across primate species

  • Compare genomic regions corresponding to ZNF365D across mammals

  • Analyze selection pressures using dN/dS ratios to identify functional constraints

• Transcriptomic evidence:

  • Conduct RNA-seq in tissues from various primate species

  • Search for potential cryptic expression in species thought to lack functional Talanin

  • Examine alternative splicing patterns across evolutionary lineages

• Biochemical function:

  • Compare the biochemical activities of human Talanin with homologous proteins in other species

  • Investigate whether other proteins might perform Talanin's function in species lacking this specific isoform

  • Consider the relationship between uricase loss and Talanin emergence

• Addressing contradictions:

  • When faced with contradictory data, implement cross-validation using multiple methods

  • Consider technical limitations that might influence results (e.g., antibody specificity)

  • Develop clear criteria for determining true orthology versus convergent evolution

The apparent timing of Talanin emergence coinciding with uricase loss during primate evolution suggests an intriguing functional relationship that warrants further investigation using these approaches.

What are the implications of ZNF365 alternative splicing for therapeutic targeting in associated disorders?

ZNF365 produces several isoforms through alternative splicing, with different expression patterns and functions. This complexity has significant implications for therapeutic development:

• Isoform-specific targeting:

  • Design antisense oligonucleotides to modulate specific splicing events

  • Develop isoform-selective antibodies for potential therapeutic applications

  • Consider small molecules that might affect specific protein-protein interactions

• Expression profiling:

  • Conduct comprehensive tissue-specific isoform expression analysis

  • Determine which isoforms are predominantly expressed in disease-relevant tissues

  • Assess whether isoform ratios change during disease progression

• Functional redundancy:

  • Investigate potential compensatory mechanisms between isoforms

  • Determine whether selective targeting of Talanin would affect other ZNF365 isoforms

  • Assess potential off-target effects of isoform-specific interventions

• Therapeutic development strategy:

  • For UAN, focus on the ZNF365D (Talanin) isoform specifically

  • For other conditions, carefully assess which isoform(s) are mechanistically relevant

  • Consider combinatorial approaches if multiple isoforms contribute to pathology

This isoform-aware approach is critical for developing precisely targeted therapeutics while minimizing off-target effects.

What optimization strategies should be employed when using anti-ZNF365 antibodies for Western blot analysis?

When optimizing Western blot analysis for ZNF365 detection, researchers should consider the following strategies:

• Antibody selection:

  • Use validated monoclonal antibodies like OTI4C6 that have demonstrated specificity for human ZNF365

  • Consider whether the antibody recognizes all isoforms or is specific to certain ones

  • Verify antibody specificity using positive and negative controls

• Sample preparation:

  • Include protease inhibitors to prevent protein degradation

  • Optimize lysis buffers depending on the cellular localization (nuclear vs. cytoplasmic)

  • Consider sample concentration methods if ZNF365 is expressed at low levels

• Protocol optimization:

  • Test multiple blocking agents (e.g., BSA, milk) to reduce background

  • Optimize primary antibody concentration (typically start with 1:1000 dilution)

  • Extend incubation times (overnight at 4°C) for better sensitivity

  • Include appropriate positive controls (e.g., recombinant ZNF365)

• Isoform considerations:

  • Be aware that different isoforms will appear at different molecular weights

  • Use gradient gels (4-15%) to better resolve multiple isoforms

  • Consider running longer SDS-PAGE to separate closely sized isoforms

• Signal detection:

  • Use enhanced chemiluminescence (ECL) for standard detection

  • Consider fluorescent secondary antibodies for multiplex detection of different isoforms

  • Use signal enhancement systems for low-abundance detection

These optimization strategies will help ensure specific and sensitive detection of ZNF365 in Western blot applications.

How should researchers approach experimental design when investigating Talanin (ZNF365) function in cellular models?

A systematic approach to investigating Talanin function in cellular models should include:

• Model selection:

  • Choose cell lines that naturally express Talanin or are relevant to suspected functions

  • Consider primary cells from tissues where Talanin is naturally expressed

  • For UAN studies, renal epithelial cells would be appropriate

• Gene modulation strategies:

  • Overexpression: Use expression vectors with CMV or other strong promoters

  • Knockdown: Employ siRNA, shRNA, or CRISPR interference (CRISPRi)

  • Knockout: Apply CRISPR-Cas9 genome editing

  • Mutation analysis: Introduce specific mutations associated with UAN

• Experimental controls:

  • Include empty vector controls for overexpression studies

  • Use non-targeting siRNA/shRNA for knockdown experiments

  • Rescue experiments to confirm specificity of observed phenotypes

  • Isoform-specific controls to distinguish Talanin effects from other ZNF365 isoforms

• Functional assays:

  • Proliferation: Cell counting, MTT/XTT assays, BrdU incorporation

  • Migration/Invasion: Wound healing, transwell assays

  • Metabolism: Uric acid uptake/secretion, metabolomics

  • Stress response: Oxidative stress, DNA damage

• Data analysis:

  • Employ appropriate statistical methods (t-tests, ANOVA, etc.)

  • Consider multiple hypothesis testing corrections

  • Ensure adequate biological replicates (minimum n=3)

  • Validate key findings using alternative approaches3

This comprehensive approach allows for robust analysis of Talanin function while controlling for potential confounding factors.

What statistical approaches are most appropriate for analyzing Talanin (ZNF365) expression data in clinical samples?

When analyzing Talanin expression data in clinical samples, researchers should employ rigorous statistical methods:

• Descriptive statistics:

  • Calculate means, medians, standard deviations, and interquartile ranges

  • Present expression data using appropriate visualizations (box plots, scatter plots)

  • Consider normalization methods appropriate for the detection technique used

• Comparative analyses:

  • Use parametric tests (t-test, ANOVA) for normally distributed data

  • Apply non-parametric alternatives (Mann-Whitney U, Kruskal-Wallis) when appropriate

  • Correct for multiple testing using methods like Bonferroni or Benjamini-Hochberg

• Correlation with clinical outcomes:

  • Employ Kaplan-Meier survival analysis to assess prognostic significance

  • Use log-rank tests to determine statistical differences between survival curves

  • Apply Cox proportional hazards regression for multivariable analysis

• Multivariate approaches:

  • Include relevant clinical covariates (age, sex, disease stage, etc.)

  • Calculate adjusted hazard ratios (HRs) with 95% confidence intervals

  • Consider propensity score matching to reduce bias in observational studies

• Sample size considerations:

  • Conduct power analysis to determine adequate sample sizes

  • Report confidence intervals alongside p-values

  • Consider meta-analysis approaches when individual studies have limited power

For clinical studies specifically examining the relationship between Talanin and disease outcomes, Cox's proportional hazards regression model has proven valuable, allowing for adjustment of confounding factors while quantifying risk through hazard ratios .

What emerging technologies might advance our understanding of Talanin (ZNF365) biology?

Several cutting-edge technologies hold promise for elucidating Talanin biology:

• Single-cell technologies:

  • Single-cell RNA-seq to identify cell populations expressing specific ZNF365 isoforms

  • Single-cell ATAC-seq to examine chromatin accessibility at the ZNF365 locus

  • Spatial transcriptomics to map ZNF365 expression within tissue architecture

• Genome editing advancements:

  • Base editing for precise introduction of disease-associated mutations

  • Prime editing for scarless genomic modifications

  • CRISPR screens to identify genetic interactions with ZNF365

• Structural biology approaches:

  • Cryo-EM to determine Talanin's three-dimensional structure

  • Hydrogen-deuterium exchange mass spectrometry to analyze protein dynamics

  • AlphaFold2 or similar AI-based structure prediction tools

• Proteomics innovations:

  • Proximity labeling methods (BioID, APEX) to identify Talanin interactors

  • Protein correlation profiling to map Talanin to subcellular compartments

  • Targeted proteomics using parallel reaction monitoring for isoform quantification

• Physiological models:

  • Organoids that recapitulate kidney function for UAN studies

  • Humanized mouse models expressing human Talanin

  • Patient-derived iPSCs differentiated into relevant cell types

These emerging technologies could provide unprecedented insights into Talanin function and regulation, potentially revealing new therapeutic targets.

How might integrative multi-omics approaches clarify the role of Talanin (ZNF365) in disease pathogenesis?

Integrative multi-omics approaches offer powerful strategies to comprehensively understand Talanin's role in disease:

• Multi-layer data integration:

  • Combine genomics (SNPs, CNVs), transcriptomics (expression, splicing), proteomics (abundance, PTMs), and metabolomics

  • Integrate epigenomic data (methylation, histone modifications) with expression data

  • Correlate Talanin genetic variants with its expression (eQTL analysis)

• Network biology approaches:

  • Construct protein-protein interaction networks centered on Talanin

  • Perform gene co-expression analysis to identify functional modules

  • Apply causal network inference to distinguish drivers from passengers

• Machine learning applications:

  • Develop predictive models of disease risk based on Talanin status

  • Use dimensionality reduction techniques to visualize complex multi-omics data

  • Implement deep learning to identify subtle patterns across data types

• Temporal dynamics:

  • Study longitudinal changes in Talanin expression during disease progression

  • Assess acute vs. chronic effects of Talanin modulation

  • Investigate potential feedback mechanisms in Talanin regulatory networks

• Analytical frameworks:

  • Apply Bayesian network analysis to infer causal relationships

  • Use structural equation modeling to test hypothesized pathways

  • Implement multi-block data integration methods like DIABLO or MOFA

These integrative approaches could reveal how Talanin fits into broader molecular networks and help identify critical nodes for therapeutic intervention.