Recombinant Macaca fascicularis E3 ubiquitin-protein ligase RNF133 (RNF133)

What is RNF133 and what is its primary function in mammalian reproduction?

RNF133 (RING finger protein 133) is a testis-specific E3 ubiquitin-protein ligase that plays a critical role in male fertility. Based on knockout studies, it appears to be essential for proper sperm morphology and motility. The protein contains a transmembrane domain and a RING finger domain, with the transmembrane region anchoring it to the endoplasmic reticulum (ER) . Its primary function involves protein quality control within the ER during spermatogenesis, where it participates in the ubiquitination of proteins that require degradation via the ubiquitin-proteasome pathway . Expression analysis indicates that RNF133 is particularly active during the transition from round to elongating spermatids, suggesting its critical role during this specific stage of sperm development .

How is RNF133 expression regulated during spermatogenesis?

RNF133 expression follows a specific temporal pattern during spermatogenesis. Research using postnatal mouse testes shows that RNF133 expression begins around day 25, which corresponds to the transition period when round spermatids develop into elongating spermatids . This highly regulated expression pattern suggests that transcriptional control mechanisms specific to spermiogenesis govern RNF133 production. The restricted expression window indicates that RNF133 functions are particularly important during this critical transition phase of sperm development . When designing experiments using recombinant Macaca fascicularis RNF133, researchers should consider this temporal expression pattern to better simulate physiological conditions.

What protein domains characterize RNF133, and how do they relate to its function?

RNF133 contains two key structural elements: a transmembrane domain and a RING finger domain. In silico prediction analyses indicate that the transmembrane region anchors the protein to the endoplasmic reticulum, while the RING finger domain is positioned in the cytoplasm . The RING finger domain is characteristic of many E3 ubiquitin ligases and is essential for their catalytic activity in transferring ubiquitin from an E2 enzyme to target substrates. Immunostaining of recombinantly expressed human RNF133 confirms its localization to the ER . This domain organization is consistent with RNF133's proposed function in ER-associated degradation (ERAD), where it would participate in recognizing and facilitating the degradation of misfolded or unnecessary proteins during spermatid development.

How does RNF133 interact with UBE2J1 in the ubiquitination pathway during spermatogenesis?

RNF133 has been identified as an interaction partner of UBE2J1, an ER-associated E2 ubiquitin-conjugating enzyme known to be essential for spermiogenesis . This interaction represents a functional E2-E3 pair in the ubiquitin-proteasome pathway specifically operating during spermatogenesis. The interaction likely occurs through the RING finger domain of RNF133, which is typical for E3 ligases. When designing experiments to study this interaction using recombinant Macaca fascicularis RNF133, researchers should consider co-expression systems with UBE2J1 and implement techniques such as co-immunoprecipitation or proximity ligation assays to verify the interaction. The UBE2J1-RNF133 complex presumably targets specific proteins for degradation during sperm development, particularly at the elongating spermatid stage, although these target proteins remain largely unidentified .

What are the phenotypic consequences of RNF133 dysfunction in reproductive biology?

Knockout studies of RNF133 in mice demonstrate severe reproductive defects. Males lacking RNF133 show significant subfertility, producing much smaller litter sizes (2.3 ± 1.6 pups per litter) compared to heterozygous controls (8.6 ± 0.7 pups per litter) . The pregnancy success rate drops dramatically from 100% in heterozygous males to only 10% in knockout males . This subfertility stems from multiple sperm abnormalities, including:

• Reduced sperm motility (21.7 ± 3.5% motile sperm in knockout vs. 41.1 ± 6.4% in heterozygous controls)

• Decreased progressive motility (14.5 ± 2.7% in knockout vs. 38.4 ± 6.2% in heterozygous controls)

• Impaired velocity parameters, including average path velocity (VAP), curvilinear velocity (VCL), and straight-line velocity (VSL)

• Significantly reduced hyperactivation capacity (1.3 ± 0.4% in knockout vs. 5.2 ± 1.7% in controls after 120 minutes of capacitation)

• Retention of cytoplasmic droplets in mature spermatozoa

• Abnormal morphology of sperm

These findings suggest that RNF133 plays a critical role in the final stages of sperm maturation and in the acquisition of proper motility parameters essential for successful fertilization.

How does RNF133 contribute to endoplasmic reticulum quality control during spermiogenesis?

RNF133 appears to function as part of the endoplasmic reticulum quality control (ERQC) system during spermiogenesis. Its structural features—a transmembrane domain localizing it to the ER and a RING finger domain facing the cytoplasm—position it ideally for recognizing and ubiquitinating misfolded or unnecessary proteins in the ER . During spermiogenesis, extensive cellular remodeling occurs, requiring efficient protein turnover mechanisms. RNF133 likely works in conjunction with UBE2J1 to target specific proteins for degradation through the ubiquitin-proteasome system .

Histological analysis of RNF133 knockout mouse testes revealed that approximately 80.6% of sperm nuclei at stage IX were surrounded by excess cytoplasm, compared to only 20.5% in control testes . This suggests that RNF133 is essential for the proper elimination of cytoplasm during spermiogenesis, a critical step in sperm maturation. The mechanism may involve ubiquitination of structural proteins or regulators of cytoplasmic reduction, marking them for degradation at the appropriate developmental stage.

What are the optimal conditions for expressing and purifying recombinant Macaca fascicularis RNF133?

When expressing recombinant Macaca fascicularis RNF133, researchers should consider its native membrane-associated nature. The following methodological approach is recommended:

• Expression System Selection: Mammalian expression systems (e.g., HEK293 or CHO cells) are preferable for maintaining proper protein folding and post-translational modifications of RNF133, especially given its transmembrane domain. Insect cell systems (Sf9, Hi5) represent an alternative that balances yield with proper folding.

• Construct Design:

  • Include the full-length sequence with its transmembrane domain for functional studies

  • For structural studies of the RING finger domain alone, design constructs excluding the transmembrane region

  • Consider adding a cleavable tag (His6 or FLAG) at the N-terminus, avoiding C-terminal tags that might interfere with the RING finger domain function

• Solubilization Strategy: Given RNF133's membrane localization, use mild detergents such as n-dodecyl-β-D-maltoside (DDM) or digitonin for extraction. Alternatively, consider nanodisc or styrene-maleic acid lipid particle (SMALP) approaches to maintain the native lipid environment.

• Purification Protocol:

  • Initial capture using affinity chromatography (based on the chosen tag)

  • Intermediate purification using ion exchange chromatography

  • Final polishing step using size exclusion chromatography

  • Maintain detergent concentration above critical micelle concentration throughout purification

• Quality Control Measures:

  • SDS-PAGE and western blotting to confirm size and purity

  • Mass spectrometry to verify protein identity

  • Circular dichroism to assess proper folding

  • Functional ubiquitination assays to confirm activity

This methodological approach should yield recombinant RNF133 suitable for downstream functional and structural studies.

How can researchers effectively design knockout and knockdown models to study RNF133 function?

Based on previous successful studies with mouse models , the following methodological approaches for generating RNF133 knockout or knockdown models are recommended:

• CRISPR/Cas9 Knockout Approach:

  • Design multiple guide RNAs targeting critical exons encoding the RING finger domain

  • Focus particularly on disrupting the zinc-coordinating residues essential for E3 ligase activity

  • Include at least 3-4 guide RNAs to account for variable efficiency

  • Verify knockouts through genomic sequencing, RT-PCR, and western blotting

  • Design genotyping primers that can distinguish between wild-type and knockout alleles

• RNAi Knockdown Approach (for partial or inducible depletion):

  • Design multiple siRNA or shRNA constructs targeting conserved regions of RNF133 mRNA

  • Test knockdown efficiency in relevant cell lines expressing RNF133

  • For in vivo studies, consider viral delivery methods that can target testicular tissue

  • Validate knockdown efficiency using quantitative RT-PCR and western blotting

• Functional Validation Methods:

  • Sperm parameter analysis using computer-assisted sperm analysis (CASA)

  • Fertility assessment through breeding tests or in vitro fertilization

  • Histological examination of testicular tissue, focusing on spermiogenesis stages

  • Ultrastructural analysis using electron microscopy to detect cytoplasmic droplet retention

  • Co-immunoprecipitation studies to assess interaction with UBE2J1 and other partners

• Control Considerations:

  • Include heterozygous animals as controls, as they show normal fertility

  • Consider generating conditional knockouts to bypass potential developmental issues

  • For paralog analysis, design studies that can also target RNF148 independently and in combination with RNF133

This comprehensive approach will enable researchers to effectively study RNF133 function in various model systems.

What are the key methodological considerations for investigating RNF133-substrate interactions?

To identify and characterize the substrates of RNF133 E3 ligase activity, researchers should consider the following methodological approaches:

• Substrate Identification Methods:

  • Proximity-dependent biotin identification (BioID) with RNF133 as the bait protein

  • Immunoprecipitation coupled with mass spectrometry under conditions that preserve transient enzyme-substrate interactions

  • Global ubiquitinome analysis comparing wild-type and RNF133-deficient samples

  • Yeast two-hybrid screening using the RING finger domain as bait

  • Protein arrays probed with recombinant RNF133

• Validation of Putative Substrates:

  • In vitro ubiquitination assays using purified components (E1, UBE2J1, RNF133, and candidate substrate)

  • Cellular ubiquitination assays in systems with and without RNF133

  • Monitoring substrate protein levels and turnover rates in RNF133-deficient vs. wild-type cells

  • Co-localization studies using fluorescence microscopy

  • Mutagenesis of predicted ubiquitination sites on candidate substrates

• Functional Significance Assessment:

  • Rescue experiments in RNF133 knockout models by manipulating levels of identified substrates

  • Analysis of how substrate dysregulation contributes to the observed fertility phenotypes

  • Temporal correlation of substrate ubiquitination with specific stages of spermiogenesis

  • Structural studies of RNF133-substrate complexes

• Technical Considerations:

  • Use cell lines that recapitulate the spermatogenic environment when possible

  • Consider the membrane-associated nature of RNF133 in experimental design

  • Account for potential redundancy with paralogous proteins like RNF148

  • Include appropriate controls for non-specific binding in interaction studies

This systematic approach will help identify the physiological substrates of RNF133 and understand how their regulation contributes to proper spermiogenesis and male fertility.

How should researchers interpret conflicting data between RNF133 knockout phenotypes and in vitro ubiquitination assays?

When confronted with discrepancies between in vivo knockout phenotypes and in vitro ubiquitination assays involving RNF133, researchers should apply the following analytical framework:

• Context Dependency Analysis:

  • Evaluate whether the in vitro system adequately replicates the specialized ER environment of spermatids

  • Consider if key cofactors or adaptors present in vivo might be missing in the in vitro system

  • Assess whether post-translational modifications of RNF133 essential for its function in vivo are preserved in recombinant proteins

• Substrate Specificity Considerations:

  • The substrates used in in vitro assays might not represent physiological targets

  • Model substrates often used in ubiquitination assays may not interact with RNF133 as endogenous substrates would

  • Consider developing assays with proteins known to be important in spermiogenesis

• Technical Validation Approaches:

  • Repeat experiments using multiple expression and purification methods for recombinant RNF133

  • Compare activity of full-length RNF133 versus isolated RING domain constructs

  • Validate antibody specificity and knockout efficiency using multiple methods

• Reconciliation Strategies:

  • Use rescue experiments with structure-function mutants to identify critical domains

  • Employ proximity labeling techniques in vivo to identify physiological substrates

  • Develop cell-based assays that better recapitulate the spermatogenic environment

When interpreting discordant results, consider that RNF133 may have non-canonical functions beyond its E3 ligase activity, or that its activity might be highly context-dependent, requiring specific cellular conditions found only during spermiogenesis.

What statistical methods are most appropriate for analyzing sperm parameter differences in RNF133 functional studies?

Based on previous research methodologies , the following statistical approaches are recommended for analyzing sperm parameters in RNF133 studies:

• For Single Parameter Comparisons:

  • Student's t-test (for normally distributed data) or Mann-Whitney U test (for non-parametric data) when comparing two groups (e.g., knockout vs. wild-type)

  • One-way ANOVA followed by appropriate post-hoc tests (e.g., Tukey's HSD) when comparing more than two groups (e.g., wild-type vs. heterozygous vs. knockout)

  • Consider paired tests when examining samples from the same animals under different conditions

• For Multifactorial Experimental Designs:

  • Two-way ANOVA when examining the interaction between genotype and another factor (e.g., time points during capacitation)

  • Mixed-effects models when dealing with repeated measures or hierarchical data structures

  • MANOVA when examining multiple related sperm parameters simultaneously

• For Fertility and Breeding Data:

  • Poisson regression for litter size analysis

  • Chi-square or Fisher's exact test for pregnancy rate comparisons

  • Survival analysis (e.g., Kaplan-Meier) for time-to-pregnancy data

• Sample Size and Power Considerations:

  • Based on previous RNF133 studies , significant differences were detected with sample sizes of n=5 per group for fertility studies

  • For sperm motility parameters, appropriate sample sizes typically range from 3-6 animals per group

  • Power analyses should aim for at least 80% power to detect differences similar to those reported (e.g., reduction in motility from ~40% to ~20%)

• Data Presentation:

  • Present data as mean ± SEM for normally distributed data

  • Include individual data points alongside means and error bars

  • For sperm motility parameters, consider using box plots or violin plots to better represent distributions

Example table format for presenting sperm motility data:

This structured statistical approach ensures robust analysis and interpretation of the complex phenotypic data associated with RNF133 studies.

How can researchers differentiate between direct and indirect effects of RNF133 in ubiquitination pathways during spermatogenesis?

Distinguishing direct from indirect effects of RNF133 in ubiquitination pathways requires a methodical approach:

• Direct Target Identification Strategy:

  • Perform in vitro ubiquitination assays with recombinant components (E1, UBE2J1, RNF133, and putative substrates)

  • Use catalytically inactive RNF133 mutants (targeting zinc-coordinating residues in the RING domain) as negative controls

  • Implement crosslinking approaches to capture transient enzyme-substrate interactions

  • Use TUBE (Tandem Ubiquitin Binding Entities) technology to enrich for ubiquitinated proteins in wild-type versus RNF133 knockout samples

• Temporal Resolution Analysis:

  • Conduct time-course experiments to establish the sequence of molecular events

  • Direct effects should be observable immediately after RNF133 induction or depletion

  • Indirect effects typically show delayed kinetics

  • Use rapid inducible systems or degradation tags for temporal control of RNF133 levels

• Pathway Perturbation Analysis:

  • Selectively inhibit different components of ubiquitination pathways

  • Use specific E1 or E2 inhibitors to block ubiquitination cascades at different levels

  • Analyze how these perturbations affect RNF133-dependent phenotypes

  • Implement proteasome inhibitors to determine if effects are dependent on protein degradation

• Data Integration Framework:

  • Combine ubiquitinome, proteome, and transcriptome data to build regulatory networks

  • Identify proteins whose abundance or ubiquitination state changes rapidly after RNF133 manipulation (likely direct targets)

  • Distinguish these from secondary changes in protein levels or modifications

  • Use computational modeling to predict the cascade of effects from direct RNF133 targets

• Validation Through Domain Mutants:

  • Generate RNF133 variants with mutations in different functional domains

  • Analyze which phenotypes are rescued by which mutants

  • Substrate-binding mutations that preserve catalytic activity can help distinguish direct from indirect targets

This comprehensive approach allows researchers to build a hierarchy of RNF133-dependent effects and distinguish primary ubiquitination events from their downstream consequences during spermatogenesis.

How might understanding RNF133 function contribute to male contraceptive development?

The testis-specific expression pattern and critical role of RNF133 in male fertility make it a promising target for contraceptive development. Research-based approaches for exploring this potential include:

• Target Validation Strategy:

  • Confirm conservation of RNF133 function across primate species, including humans

  • Verify testis-specific expression in human tissues to minimize off-target effects

  • Develop inducible knockout models to confirm reversibility of fertility effects

  • Assess long-term physiological consequences of RNF133 inhibition

• Inhibitor Development Approaches:

  • Design small molecules targeting the RING finger domain to inhibit E3 ligase activity

  • Develop PROTACs (Proteolysis Targeting Chimeras) that could selectively degrade RNF133

  • Screen for compounds that disrupt the RNF133-UBE2J1 interaction

  • Consider peptide-based inhibitors that mimic substrate binding interfaces

• Delivery System Considerations:

  • Explore blood-testis barrier-permeable drug formulations

  • Investigate local delivery methods to target testicular tissue

  • Consider long-acting reversible contraceptive approaches

• Efficacy and Safety Assessment Framework:

  • Based on knockout studies , targeting RNF133 could reduce male fertility by approximately 90%

  • Monitor sperm parameters (motility, morphology) as biomarkers of efficacy

  • Assess reversibility timelines after treatment cessation

  • Conduct comprehensive toxicology studies with emphasis on reproductive and endocrine systems

RNF133 represents a particularly promising contraceptive target because its deletion specifically affects sperm function without altering hormone levels or sexual behavior , potentially offering a non-hormonal approach to male contraception with fewer systemic side effects.

What implications does RNF133 research have for understanding and treating male infertility?

Research on RNF133 offers several pathways for advancing our understanding and treatment of male infertility:

• Diagnostic Applications:

  • Develop screening assays for RNF133 mutations or expression abnormalities in infertile men

  • Incorporate RNF133 assessment into genetic panels for male infertility, particularly for cases involving sperm motility defects or abnormal morphology

  • Create diagnostic algorithms that include RNF133 pathway dysfunction assessment

• Phenotypic Correlations:

  • The RNF133 knockout phenotype includes reduced sperm motility, abnormal morphology, and retained cytoplasmic droplets

  • These characteristics align with several forms of human male infertility

  • Patients with unexplained asthenozoospermia (reduced sperm motility) or teratozoospermia (abnormal morphology) may have RNF133 pathway dysfunctions

• Therapeutic Strategies:

  • For cases with reduced RNF133 function, explore gene therapy approaches to restore expression

  • Develop methods to bypass RNF133-dependent defects in assisted reproduction techniques

  • Target downstream effectors in the RNF133 pathway that might be more amenable to therapeutic intervention

• Personalized Medicine Approaches:

  • Classify infertile patients based on RNF133 pathway functionality

  • Tailor assisted reproduction protocols based on specific molecular defects

  • Consider RNF133 status in predicting success rates of different fertility treatments

By elucidating the molecular mechanisms of RNF133 in spermiogenesis, researchers can develop more targeted and effective approaches to diagnosing and treating specific forms of male infertility, moving beyond empirical treatments toward precision reproductive medicine.

What are the most significant unanswered questions in RNF133 research?

Despite progress in understanding RNF133 function, several critical questions remain unanswered:

• Substrate Identification: The physiological targets of RNF133 ubiquitination during spermiogenesis remain largely unknown. Identifying these substrates is crucial for understanding the molecular mechanisms underlying the RNF133 knockout phenotype .

• Regulatory Mechanisms: How is RNF133 expression and activity regulated during spermatogenesis? The factors controlling its stage-specific expression pattern and potential post-translational modifications affecting its activity require investigation.

• Species Conservation: While mouse studies have established the importance of RNF133 , the degree of functional conservation across species, particularly in primates and humans, needs confirmation.

• Pathway Integration: How does the RNF133-UBE2J1 ubiquitination pathway integrate with other quality control mechanisms during spermiogenesis? The interplay between this pathway and other cellular processes during sperm development remains to be elucidated.

• Functional Redundancy: Although RNF148 is structurally similar to RNF133, knockout studies suggest limited functional redundancy . The evolutionary reasons for maintaining these paralogous genes and their potentially distinct functions require further investigation.