Recombinant Rat DDB1- and CUL4-associated factor 17 (Dcaf17)

What is DCAF17 and what cellular functions does it regulate?

DCAF17 functions as a substrate co-receptor for the ubiquitin ligase complex Cul4-DDB1, which plays critical roles in many cellular processes . This nucleolar protein is expressed in various tissues including the brain, liver, skin, and seminiferous tubules in males . When DCAF17 is mutated or deleted, it leads to disruption of the nucleolus, resulting in dysregulated ribosome biogenesis, abnormal cell cycle regulation, impaired cellular responses to stress, and defective RNA processing . These disruptions have significant consequences for developing and mature cells, particularly in reproductive tissues where DCAF17 has been shown to be essential for normal spermatogenesis .

Where is DCAF17 primarily expressed in mammalian tissues?

Expression profiling of Dcaf17 using quantitative RT-PCR reveals highest expression in the testis, with detectable levels also present in brain, liver, and skin tissues . This expression pattern aligns with the observed phenotypes when the gene is disrupted. Analysis of Dcaf17 transcripts during post-natal development of testis shows a gradual increase in mRNA levels with age, suggesting developmental regulation of expression . The specific expression pattern in seminiferous tubules correlates with its critical role in spermatogenesis, while expression in other tissues explains the diverse manifestations observed in systemic disorders associated with DCAF17 mutations .

What is the molecular structure and cellular localization of DCAF17?

The DCAF17 gene is located on chromosome 2q31.1 and encodes a nucleolar protein with two identified isoforms: alpha (453 amino acid residues; NP_001158293.1) and beta (520 amino acids residues; NP_079276.2) . As a member of the DCAF family, it likely contains WD40 repeats typical of this family, which facilitate protein-protein interactions, particularly with the DDB1-CUL4 ubiquitin ligase complex. DCAF17 is primarily localized to the nucleolus, positioning it to influence critical cellular processes including ribosome biogenesis, cell cycle regulation, cellular aging, signal recognition, small-RNA processing, and mRNA transport . This localization is consistent with the diverse cellular dysfunctions observed when DCAF17 is mutated.

How can researchers generate effective DCAF17 knockout models?

Generation of DCAF17 knockout models requires precise gene targeting approaches. Based on published research, an effective protocol includes:

• Design of targeting vectors to specifically disrupt the Dcaf17 gene

• Introduction of the targeting construct into embryonic stem cells

• Selection of cells with successful integration

• Generation of chimeric mice through blastocyst injection

• Breeding to obtain heterozygous and then homozygous knockouts

• Confirmation of gene deletion through PCR and expression analysis

Phenotypic analysis should focus on reproductive parameters, particularly in males, where Dcaf17 knockout mice show infertility due to abnormal sperm development . Histological examination of testicular tissue is essential to characterize specific defects in spermatogenesis. Female fertility should also be assessed, although existing research indicates Dcaf17 disruption does not affect female fertility . When designing knockout strategies, researchers should consider potential compensatory mechanisms and evaluate expression of related DCAF family members.

What techniques are most effective for analyzing sperm abnormalities in DCAF17-deficient models?

Analysis of DCAF17-related sperm abnormalities requires a multi-parameter approach:

The comprehensive characterization of abnormalities in Dcaf17-/- models has revealed specific defects including asymmetric acrosome capping, impaired nuclear compaction, and abnormal round spermatid to elongated spermatid transition . These findings highlight DCAF17's essential role in late spermiogenesis stages.

What genetic testing approaches are used to identify DCAF17 mutations in clinical samples?

Several complementary approaches are employed for DCAF17 mutation detection:

• Whole Exome Sequencing (WES): Enables comprehensive detection of mutations across all protein-coding regions, typically performed at high depth (200×) with target coverage exceeding 99% .

• Targeted Sequencing: More focused approach using primers specific to DCAF17 exons. Example primers used in clinical research include:

  • Forward: 3′-CAGAATCTCCGAATTTGAAGGAG-5′

  • Reverse: 3′-TCTTTAAATCTGAAATGTACATGGG-5′

• Mutation-Specific PCR: Useful for detecting known mutations in familial cases or population screening.

• Segregation Analysis: Testing family members to confirm inheritance patterns, particularly valuable in consanguineous families with suspected recessive disorders .

Known pathogenic variants in DCAF17 include:

• Splice site mutations (c.321+1G>A, c.1422+5G>T, c.1091+2T>C, c.1091+1G>A, c.1091+6T>G)

• Frameshift mutations (c.1238delA, c.270delA, c.270dupA, c.289dupA, c.127-3_127-1delTAGinsAA, c.995delT, c.436delC, c.459-7_499del, c.50delC)

• Start loss mutations (c.1G>A)

These variants can be assessed for pathogenicity using bioinformatic prediction tools, conservation analysis, and functional studies.

How do mutations in DCAF17 cause Woodhouse-Sakati syndrome?

Woodhouse-Sakati syndrome (WSS, MIM 241080) is a rare autosomal recessive neuroendocrine disorder characterized by hypogonadism, alopecia, diabetes mellitus, intellectual disability, and extrapyramidal syndrome . The pathophysiology involves:

• Molecular disruption: DCAF17 mutations lead to either truncated proteins that cannot interact with the DDB1-CUL4 ubiquitin ligase complex or nonsense-mediated mRNA decay . For example, the c.1111delA mutation results in a termination codon (p.Ile371Term) creating an incomplete protein missing essential functional domains .

• Nucleolar dysfunction: As DCAF17 localizes to the nucleolus, mutations disrupt this cellular compartment's function, affecting:

  • Ribosome biogenesis

  • Cell cycle regulation

  • Cellular aging processes

  • RNA processing and transport

• Tissue-specific effects: DCAF17 expression in the brain, liver, skin, and gonads explains the diverse clinical manifestations of WSS . Neurological features may result from disrupted protein homeostasis in neurons, while endocrine manifestations reflect dysfunction in hormone-producing tissues.

• MRI findings: Neuroimaging in WSS patients shows characteristic features including partially empty sella and a small pituitary gland, without abnormal iron deposition .

The diverse phenotypic manifestations of WSS highlight the importance of DCAF17 in multiple organ systems and developmental processes.

What is the relationship between DCAF17 and male infertility?

DCAF17 plays a critical role in male fertility through several mechanisms:

• Expression pattern: Dcaf17 shows highest expression in the testis, with levels increasing during postnatal development, corresponding to the maturation of spermatogenic function .

• Knockout phenotype: Male Dcaf17-/- mice are infertile while females maintain normal fertility, demonstrating its sex-specific requirement in reproduction .

• Sperm abnormalities: Dcaf17 deletion results in:

  • Significantly reduced sperm count

  • Abnormal sperm morphology

  • Severely impaired motility

• Histological findings: Examination of Dcaf17-/- testes reveals:

  • Impaired spermatogenesis

  • Vacuolation in seminiferous tubules

  • Presence of sloughed cells in tubular lumina

• Specific developmental defects:

  • Asymmetric acrosome capping

  • Impaired nuclear compaction

  • Defective round-to-elongated spermatid transition

These findings establish DCAF17 as an essential factor for normal spermiogenesis, particularly during the critical morphological transformation of round spermatids into elongated spermatozoa. The identification of DCAF17's role in spermatogenesis provides valuable insights into potential genetic causes of idiopathic male infertility, which accounts for approximately 50% of all male infertility cases .

How can researchers use DCAF17 as a model for studying nucleolar protein dysfunction?

DCAF17 offers a valuable model for investigating nucleolar protein dysfunction for several reasons:

• Defined genetic basis: Well-characterized mutations in a single gene (DCAF17) provide a clear genetic entry point for studying nucleolar dysfunction .

• Multi-system effects: The diverse phenotypes in WSS demonstrate how nucleolar dysfunction affects multiple organ systems, providing insight into tissue-specific consequences of nucleolar disruption .

• Cellular processes affected: DCAF17 dysfunction impacts:

  • Ribosome biogenesis

  • Cell cycle regulation

  • Cellular aging processes

  • RNA processing and transport

  • Apoptotic pathways

• Clear reproductive phenotype: The defined impact on spermatogenesis offers a well-characterized developmental process for studying nucleolar function in cellular differentiation .

• Available animal models: Dcaf17 knockout mice reproduce key aspects of human pathology, enabling detailed mechanistic studies .

Research approaches should integrate:

• Proteomics to identify DCAF17 interaction partners

• RNA-seq to characterize transcriptional consequences of nucleolar disruption

• Super-resolution microscopy to visualize nucleolar structure in affected cells

• Tissue-specific conditional knockouts to dissect organ-specific requirements

This research may reveal broader principles of nucleolar function relevant to other conditions involving nucleolar disruption, including neurodegenerative diseases and cancer.

How does DCAF17 interact with the Cullin-RING E3 ubiquitin ligase complex?

DCAF17 functions as a substrate receptor in the Cullin-RING E3 ubiquitin ligase complex through several key interactions:

• Molecular architecture: As a DCAF family protein, DCAF17 likely contains WD40 repeats that mediate its binding to DDB1 (DNA damage-binding protein 1) within the CUL4-DDB1 E3 ligase complex .

• Functional role: DCAF17 is responsible for substrate recognition and recruitment, determining which proteins are targeted for ubiquitination by the ligase complex .

• Substrate specificity: While the specific substrates recognized by DCAF17 have not been fully characterized, its high expression in testis and the phenotype of knockout mice suggest it targets proteins involved in spermatogenesis .

• Mutation consequences: The c.1111delA nonsense mutation identified in WSS patients likely produces a truncated protein missing domains required for interaction with the DDB1-CUL4 complex, disrupting its ability to recruit substrates for ubiquitination .

• Nucleolar context: DCAF17's nucleolar localization suggests it may target nucleolar proteins for degradation, potentially explaining how its dysfunction disrupts nucleolar processes .

Further research using techniques such as proximity-based labeling, co-immunoprecipitation, and structural studies is needed to fully characterize DCAF17's interaction partners and the specific substrates it targets for degradation. Understanding these interactions will provide critical insights into the molecular mechanisms underlying both male infertility and WSS.

What are the current challenges in studying DCAF17 function?

Researchers investigating DCAF17 face several significant challenges:

• Functional redundancy: Other DCAF family proteins may compensate for DCAF17 loss in some tissues, complicating phenotypic interpretation and requiring careful analysis of related family members.

• Substrate identification: Identifying the specific proteins targeted by DCAF17 for ubiquitination remains challenging, limiting our understanding of the molecular pathways disrupted in DCAF17 deficiency.

• Tissue-specific functions: DCAF17's varying expression across tissues suggests context-dependent functions that may require specialized tissue-specific experimental systems .

• Nucleolar localization: The nucleolar compartment presents technical challenges for protein interaction studies and live-cell imaging of DCAF17 function.

• Isoform complexity: The existence of multiple DCAF17 isoforms (alpha and beta) complicates functional studies, as each may have distinct roles .

• Limited clinical samples: The rarity of WSS limits availability of patient samples for studying human DCAF17 mutations .

• Complex phenotypes: The diverse manifestations of DCAF17 dysfunction require multidisciplinary approaches spanning reproductive biology, neurology, and endocrinology.

Addressing these challenges requires:

• Development of conditional and tissue-specific knockout models

• Advanced proteomics approaches for substrate identification

• Single-cell analysis techniques to capture cellular heterogeneity

• Integrative multi-omics approaches combining genomics, transcriptomics, and proteomics

Research advances in these areas will enhance our understanding of DCAF17's diverse biological roles.

How does DCAF17 expression change during development and in response to cellular stress?

DCAF17 expression exhibits dynamic regulation during development and may be modulated by cellular stress:

• Developmental regulation in testis: Analysis of Dcaf17 transcripts shows a gradual increase in expression during post-natal testicular development, correlating with the maturation of spermatogenic function . This pattern suggests developmental control of DCAF17 expression, potentially through stage-specific transcription factors.

• Tissue-specific expression patterns: The varying expression across tissues (highest in testis, with expression also in brain, liver, and skin) indicates tissue-specific regulatory mechanisms .

• Potential stress responsiveness: As a nucleolar protein involved in the ubiquitin-proteasome system, DCAF17 may be regulated in response to cellular stresses that affect protein homeostasis . The nucleolus serves as a stress sensor in many cell types, suggesting DCAF17 might participate in stress-responsive pathways.

• Hormonal regulation: Given its role in reproductive tissues, DCAF17 expression may be influenced by hormonal signals, particularly those governing sexual development and function.

• Cell cycle dependency: As a component of the ubiquitin ligase machinery, DCAF17 expression or activity might fluctuate through the cell cycle to regulate timely protein degradation.

Further research using techniques such as:

• Single-cell RNA sequencing of developing tissues

• Reporter assays to identify DCAF17 promoter regulatory elements

• Analysis of DCAF17 levels under various stress conditions

• ChIP-seq to identify transcription factors regulating DCAF17

These approaches would enhance our understanding of the complex regulation of this important nucleolar protein and potentially identify intervention points for DCAF17-related pathologies.

What bioinformatic approaches are recommended for analyzing DCAF17 structure and interactions?

To comprehensively analyze DCAF17 structure and interactions, researchers should employ several complementary bioinformatic approaches:

• Protein structure prediction:

  • AlphaFold or RoseTTAFold for predicting DCAF17 tertiary structure

  • SWISS-MODEL for homology modeling based on related DCAF family members

  • PyMOL or UCSF Chimera for visualizing structural features and analyzing mutation impacts

• Domain and motif analysis:

  • InterPro and Pfam for identifying functional domains, particularly WD40 repeats

  • ELM (Eukaryotic Linear Motif) resource for short functional motifs

  • SMART for detection of signaling domains

• Protein-protein interaction prediction:

  • STRING database to identify known and predicted interaction partners

  • PrePPI for structure-based prediction of protein interactions

  • BioGRID for curated interaction data

• Mutation effect prediction:

  • SIFT, PolyPhen-2, and MutationTaster for predicting functional effects of variants

  • FoldX for calculating mutation effects on protein stability

  • ConSurf for evolutionary conservation analysis to identify functionally important residues

• Network analysis:

  • Cytoscape for visualizing and analyzing DCAF17 in protein interaction networks

  • Reactome and KEGG for pathway analysis

  • Gene Ontology enrichment tools for functional annotation of interacting proteins

Integration of these approaches can provide comprehensive insights into DCAF17 structure-function relationships, particularly how mutations disrupt its interactions with the ubiquitin ligase complex and substrate proteins.

How should researchers interpret conflicting results in DCAF17 functional studies?

When encountering conflicting results in DCAF17 research, a systematic approach to data interpretation is essential:

• Experimental system differences:

  • Species variations (human vs. mouse) may account for functional differences

  • Cell type-specific functions may explain tissue-dependent results

  • In vitro vs. in vivo contexts might yield different outcomes due to missing physiological factors

• Isoform-specific effects:

  • Discrepancies may arise if studies examined different DCAF17 isoforms (alpha vs. beta)

  • Isoform-specific antibodies or detection methods should be employed when possible

• Methodological considerations:

  • Different knockout strategies might result in varying phenotypes (complete vs. conditional)

  • Technical variations in protein interaction studies can yield different results

  • Quantitative differences in DCAF17 expression may produce qualitatively different outcomes

• Developmental timing:

  • The gradual increase in DCAF17 expression during development suggests time-dependent functions

  • Ages of experimental animals or developmental stages of cells should be carefully matched

• Genetic background effects:

  • Strain differences in mouse models may modify phenotypes

  • Genetic modifiers may be present in some experimental systems

To resolve conflicts, researchers should:

• Directly compare methodologies between studies

• Reproduce key findings using standardized protocols

• Use multiple complementary approaches to test the same hypothesis

• Consider conditional systems to control for developmental effects

• Collaborate across laboratories to standardize approaches

This structured approach can help reconcile apparently contradictory findings and build a more coherent understanding of DCAF17 function.

What are the best approaches for integrating DCAF17 data into broader biological pathways?

Effective integration of DCAF17 research into broader biological contexts requires several strategic approaches:

• Pathway enrichment analysis:

  • Analyze DCAF17 interactors using tools like DAVID, PANTHER, or g:Profiler

  • Identify overrepresented pathways and biological processes

  • Connect DCAF17 to established ubiquitin-proteasome system pathways

• Multi-omics data integration:

  • Combine transcriptomic, proteomic, and phenotypic data from DCAF17 studies

  • Use tools like GeneWeaver or NetworkAnalyst for cross-platform integration

  • Identify convergent evidence across multiple data types

• Comparative analysis across DCAF family members:

  • Leverage functional information from better-characterized DCAF proteins

  • Identify shared and distinct pathways across the family

  • Place DCAF17 within the evolutionary context of substrate receptor proteins

• Disease network analysis:

  • Connect DCAF17 to other genes involved in male infertility

  • Map relationships between DCAF17 and genes implicated in Woodhouse-Sakati syndrome-like disorders

  • Use tools like DisGeNET or DISEASES to establish disease associations

• Systems biology modeling:

  • Develop mathematical models of DCAF17's role in ubiquitin-mediated protein degradation

  • Integrate temporal dynamics of spermatogenesis with DCAF17 function

  • Simulate the effects of DCAF17 mutations on cellular processes

• Visualization strategies:

  • Use Cytoscape for network visualization with custom DCAF17-centric layouts

  • Develop tissue-specific network visualizations reflecting DCAF17's varying roles

  • Create dynamic representations showing developmental changes in DCAF17 networks

These approaches enable researchers to contextualize DCAF17 findings within broader biological frameworks, generating hypotheses about its roles in development, disease, and cellular homeostasis that extend beyond the immediate experimental observations.