PSMG3 Human

What is human PSMG3 and what is its primary function in cellular biology?

Human PSMG3 (Proteasome Assembly Chaperone 3), also known as C7orf48 or PAC3, is a chaperone protein that plays a critical role in proteasome biogenesis. Its primary function is to promote the assembly of the 20S proteasome, a barrel-shaped proteolytic complex essential for regulated intracellular protein degradation . PSMG3 likely cooperates with PSMG1-PSMG2 heterodimers to orchestrate the correct assembly of proteasomes .

The 20S proteasome core particle (CP) is a 700-kDa complex composed of four stacked rings (two α-rings and two β-rings), each containing seven distinct subunits . As an assembly chaperone, PSMG3 helps ensure the ordered incorporation of these subunits into functional proteasomes, which are critical for degrading misfolded or aggregation-prone proteins associated with neurodegenerative and other diseases .

Methodologically, studying PSMG3 function typically involves recombinant protein expression systems, co-immunoprecipitation studies with other proteasome assembly factors, and functional assays examining proteasome assembly efficiency in the presence or absence of PSMG3.

What is the molecular composition of human PSMG3 protein?

Human PSMG3 is a 122-amino acid protein encoded by the PSMG3 gene located on chromosome 7 . The protein has a molecular weight of approximately 13 kDa and is identified in UniProt with the accession number Q9BT73 .

While the search results don't provide detailed information about specific domains within PSMG3, it appears to contain regions that facilitate interactions with proteasome subunits and possibly other assembly chaperones. For experimental work, PSMG3 can be expressed as a recombinant protein with fusion tags such as GST to facilitate purification and functional studies .

To investigate PSMG3's molecular structure, researchers typically employ techniques including:

• Recombinant protein expression in E. coli or other systems

• Protein purification via affinity chromatography

• Structural analysis through X-ray crystallography or cryo-electron microscopy

• Sequence alignment with homologs to identify conserved functional regions

What is the relationship between PSMG3 and the lncRNA PSMG3-AS1?

PSMG3-AS1 is a long non-coding RNA (lncRNA) that is antisense to the PSMG3 gene. While PSMG3 protein functions in proteasome assembly, PSMG3-AS1 appears to have distinct regulatory roles, particularly in cancer progression .

Studies have revealed that PSMG3-AS1 is frequently upregulated in various cancer types, including gastric cancer and breast cancer . In gastric cancer, elevated PSMG3-AS1 expression is associated with tumor mutational burden (TMB) and microsatellite instability (MSI) . In breast cancer, PSMG3-AS1 functions as a competitive endogenous RNA (ceRNA) by sponging miR-143-3p, thereby regulating the expression of collagen type 1 alpha 1 (COL1A1) .

Methodologically, to investigate the potential regulatory relationship between PSMG3 and PSMG3-AS1, researchers should:

• Examine co-expression patterns in various tissues and cell types

• Perform knockdown studies of PSMG3-AS1 to assess effects on PSMG3 expression

• Analyze potential shared regulatory elements in their promoter regions

• Investigate whether PSMG3-AS1 directly interacts with PSMG3 mRNA

What experimental approaches are most effective for studying PSMG3's role in proteasome assembly?

To effectively study PSMG3's role in proteasome assembly, researchers should employ multiple complementary approaches:

• Cryo-electron microscopy (cryo-EM): This technique has proven instrumental in visualizing assembly intermediates of the proteasome. Recent studies have used cryo-EM reconstructions to capture subcomplexes that contain assembly chaperones, including PSMG3, bound to proteasome intermediates . This approach provides structural insights into how chaperones guide the assembly process.

• Recombinant protein expression and purification: Expression of recombinant PSMG3 with tags such as GST allows for in vitro studies of its interactions with proteasome subunits . Purified proteins can be used in reconstitution experiments to analyze assembly processes step by step.

• Cell-based assays: Using cell lines with inducible knockdown or knockout of PSMG3 helps assess its role in proteasome assembly in a cellular context. Techniques like CRISPR-Cas9 gene editing permit precise manipulation of PSMG3 expression .

• Co-immunoprecipitation and proximity labeling: These techniques can identify protein-protein interactions involving PSMG3 during proteasome assembly, revealing its binding partners and the timing of these interactions.

• Proteasome activity assays: Measuring proteasome activity using fluorogenic peptide substrates in cells with normal or depleted PSMG3 levels can provide functional insights into its role in generating catalytically active proteasomes.

• Live-cell imaging: Tracking fluorescently tagged PSMG3 and proteasome subunits can reveal the dynamics of proteasome assembly in real time.

How can researchers effectively investigate PSMG3-AS1's function as a miRNA sponge in cancer?

Based on recent studies, PSMG3-AS1 functions as a miRNA sponge in cancer progression. To investigate this function effectively, researchers should employ these methodological approaches:

• Expression correlation analysis: First establish the expression pattern of PSMG3-AS1 in cancer tissues versus normal tissues using RT-qPCR. In breast cancer, PSMG3-AS1 was found to be upregulated in cancer tissues compared to adjacent normal tissues .

• Knockdown experiments: Use siRNA or shRNA to reduce PSMG3-AS1 expression in cancer cell lines. In studies of breast cancer cell lines (MDA-MB-231 and MCF-7), PSMG3-AS1 knockdown reduced proliferation and migration capacity .

• miRNA binding site prediction and validation: Employ bioinformatics tools to predict potential miRNA binding sites on PSMG3-AS1, then validate these interactions using luciferase reporter assays. Research has identified miR-143-3p as a target of PSMG3-AS1 in breast cancer .

• Rescue experiments: After PSMG3-AS1 knockdown, transfect cells with inhibitors of the putative target miRNA (e.g., miR-143-3p inhibitor) to determine if this reverses the phenotypic effects of PSMG3-AS1 depletion .

• Downstream target analysis: Identify and validate potential downstream targets of the miRNA being sponged. For example, COL1A1 was identified as a downstream target of miR-143-3p in the PSMG3-AS1/miR-143-3p axis in breast cancer .

• Functional assays: Assess the effects of PSMG3-AS1 manipulation on cancer cell behaviors using assays such as:

  • Cell proliferation (Cell Counting Kit-8, colony formation assays)

  • Cell migration (Transwell assays, wound-healing assays)

  • Cell invasion assays

  • Apoptosis assays

What bioinformatic approaches should be employed to analyze PSMG3 and PSMG3-AS1 in large genomic datasets?

For comprehensive bioinformatic analysis of PSMG3 and PSMG3-AS1 in large genomic datasets, researchers should consider these methodological approaches:

• Expression analysis across cancer types: Analyze RNA-sequencing data from cancer databases (TCGA, GEO) to compare expression patterns. Studies have shown that PSMG3-AS1 is highly expressed in over 20 different types of cancer .

• Correlation with clinical parameters: Examine associations between PSMG3/PSMG3-AS1 expression and clinical features like tumor stage, grade, and patient survival. For PSMG3-AS1, survival analysis and ROC curves have confirmed its association with prognosis in gastric cancer patients .

• Sequence alignment of vertebrate orthologs: Perform comparative sequence analysis to identify evolutionarily conserved regions that might be functionally important .

• SNP analysis: Compile and analyze single nucleotide polymorphisms in PSMG3 that might affect function or be associated with disease .

• Structural prediction: Use computational tools to predict 3D structures and identify functional domains .

• Protein-protein interaction network analysis: Construct interaction networks to understand the functional context of PSMG3 within the proteasome assembly machinery.

• Integration of multi-omics data: Combine transcriptomic, proteomic, and functional genomic data to gain comprehensive insights.

• miRNA-target prediction: Employ algorithms to predict potential miRNA binding sites on PSMG3-AS1 and validate through experimental approaches.

How should experimental controls be designed when studying PSMG3's role in proteasome assembly?

When designing experiments to study PSMG3's role in proteasome assembly, appropriate controls are essential for reliable data interpretation:

• Genetic manipulation controls:

  • When using CRISPR-Cas9 for PSMG3 knockout, include both wild-type cells and cells treated with non-targeting gRNAs .

  • For knockdown experiments, use scrambled siRNA or shRNA sequences that don't target any known transcripts.

  • Consider rescue experiments by reintroducing wild-type PSMG3 to confirm phenotype specificity.

• Protein-protein interaction controls:

  • For co-immunoprecipitation experiments, include IgG controls and lysates from cells not expressing the bait protein.

  • Use truncation or point mutants of PSMG3 to map specific interaction domains.

• Functional assay controls:

  • When measuring proteasome activity, include specific proteasome inhibitors (e.g., MG132) as negative controls.

  • Compare effects of PSMG3 depletion with depletion of other known assembly chaperones.

• Structural biology controls:

  • For cryo-EM studies of assembly intermediates, analyze samples at different time points during assembly.

  • Include purified mature proteasome as a reference structure .

• Cell viability controls:

  • Since proteasome dysfunction can affect cell viability, monitor cell death markers to distinguish specific effects from general cytotoxicity.

• Specificity controls:

  • Examine effects on other cellular complexes to ensure observed phenotypes are specific to proteasome assembly.

What are the key methodological considerations when investigating PSMG3-AS1 in different cancer contexts?

When investigating PSMG3-AS1 in various cancer contexts, researchers should consider these methodological factors:

• Tissue specificity:

  • PSMG3-AS1 functions may vary across cancer types. Studies have examined its role in both gastric cancer and breast cancer, finding distinct molecular mechanisms .

  • Always compare cancer tissues with matched adjacent normal tissues from the same patients.

• Expression analysis techniques:

  • Use multiple methods (RT-qPCR, RNA-seq, in situ hybridization) to validate expression patterns.

  • Consider subcellular localization analysis to inform function (nuclear vs. cytoplasmic).

• Cell line selection:

  • Choose multiple cell lines representing different subtypes of the cancer being studied.

  • Studies of PSMG3-AS1 in breast cancer used both MDA-MB-231 and MCF-7 cell lines to ensure findings weren't cell line-specific .

• Knockdown efficiency validation:

  • Confirm knockdown at both RNA level (RT-qPCR) and downstream functional levels.

  • Consider dose-response relationships in knockdown experiments.

• Molecular mechanism validation:

  • For miRNA sponge function, validate direct binding using luciferase assays and RIP (RNA immunoprecipitation).

  • Confirm effects on downstream targets at both mRNA and protein levels .

• Clinical correlation approaches:

  • Correlate expression with multiple clinical parameters (stage, grade, survival).

  • Use appropriate statistical methods for survival analysis (Kaplan-Meier, Cox regression).

  • In gastric cancer, PSMG3-AS1 expression was found to correlate with tumor mutational burden (TMB) and microsatellite instability (MSI) .

• Heterogeneity considerations:

  • Account for tumor heterogeneity through single-cell approaches or microdissection where appropriate.

How should researchers interpret contradictory results regarding PSMG3 function or expression?

When encountering contradictory results in PSMG3 research, consider these methodological approaches to interpretation:

• Experimental context differences:

  • Different cell types or tissue contexts may result in varying PSMG3 functions.

  • Proteasome assembly requirements might differ between cell types or under different cellular stresses.

• Technical approach variations:

  • Different knockdown/knockout strategies might achieve different efficiency levels.

  • Antibody specificity issues in Western blotting or immunoprecipitation can lead to discrepant results.

  • Different expression analysis platforms (microarray vs. RNA-seq) might yield varying results.

• Temporal considerations:

  • Transient vs. stable knockdown might reveal different aspects of PSMG3 function.

  • Acute vs. chronic loss of PSMG3 might trigger different compensatory mechanisms.

• Redundancy in proteasome assembly:

  • Other assembly chaperones might compensate for PSMG3 loss in some contexts but not others.

  • The proteasome assembly pathway involves multiple chaperones working together, which might mask individual contributions .

• Isoform-specific functions:

  • If PSMG3 has multiple isoforms, different studies might be examining different isoforms.

• Statistical and biological validation:

  • Evaluate the statistical methods used in conflicting studies.

  • Consider both statistical significance and biological significance.

  • Examine sample sizes and statistical power in comparative studies.

• Replication with modified controls:

  • Design experiments that specifically address the contradictions.

  • Include additional controls that might reveal context-dependent effects.

How does PSMG3 coordinate with other chaperones in the stepwise assembly of the 20S proteasome?

PSMG3 functions within a sophisticated network of assembly chaperones that orchestrate 20S proteasome biogenesis:

• Assembly pathway coordination:

  • Recent cryo-EM studies have visualized seven recombinant human subcomplexes that show all five chaperones and three active site propeptides across the assembly pathway .

  • PSMG3 likely cooperates with PSMG1-PSMG2 heterodimers to ensure correct incorporation of specific proteasome subunits .

• Structural adaptation during assembly:

  • Proteasome subcomplexes and assembly factors structurally adapt upon progressive subunit incorporation .

  • These adaptations serve to stabilize intermediates and facilitate the formation of subsequent intermediates.

• Order determination:

  • PSMG3, along with other chaperones, helps determine the order of successive subunit additions .

  • This ordered assembly is crucial for forming the correctly structured 20S proteasome barrel.

• Active site coordination:

  • Assembly factors like PSMG3 ultimately rearrange to coordinate proteolytic activation with gated access to active sites .

  • This ensures that proteolytic activity is only enabled once assembly is complete.

• Quality control mechanisms:

  • PSMG3 likely participates in quality control checkpoints during assembly, preventing progression when subunits are incorrectly incorporated.

Methodologically, understanding these mechanisms requires combining structural approaches (cryo-EM) with biochemical assays and genetic manipulation to track the assembly process and identify the specific contributions of each chaperone.

What molecular mechanisms underlie PSMG3-AS1's function as a miRNA sponge in cancer progression?

The molecular mechanisms through which PSMG3-AS1 functions as a miRNA sponge in cancer involve several coordinated processes:

• Competitive binding to miRNAs:

  • In breast cancer, PSMG3-AS1 competitively binds to miR-143-3p, preventing this miRNA from targeting its normal mRNA targets .

  • This competitive binding relies on sequence complementarity between PSMG3-AS1 and the miRNA.

• Regulation of downstream targets:

  • By sequestering miR-143-3p, PSMG3-AS1 indirectly upregulates COL1A1 (collagen type 1 alpha 1) in breast cancer .

  • In gastric cancer, disruption of PSMG3-AS1 appears to impact the CAV1/miR-451a signaling pathway .

• Effect on cellular phenotypes:

  • Knockdown of PSMG3-AS1 in breast cancer cell lines (MDA-MB-231 and MCF-7) reduced their proliferative and invasive capabilities .

  • Similarly, in gastric cancer cells (AGS and MKN-45), PSMG3-AS1 knockdown reduced proliferation and invasion .

• Feedback regulation:

  • PSMG3-AS1 knockdown increased miR-143-3p expression in breast cancer cells, suggesting a reciprocal regulatory relationship .

• Association with clinical features:

  • PSMG3-AS1 expression correlates with tumor mutational burden (TMB) and microsatellite instability (MSI) in gastric cancer .

  • Its expression is associated with patient prognosis, as confirmed by survival analysis .

Methodologically, these mechanisms are investigated through a combination of expression analyses, knockdown experiments, luciferase reporter assays for direct binding confirmation, and functional assays to assess biological impacts.

What is known about the structural properties of PSMG3 and how do they relate to its function?

While detailed structural information about PSMG3 is limited in the provided search results, we can infer several important aspects:

• Protein size and composition:

  • Human PSMG3 is a 122-amino acid protein with a molecular weight of approximately 13 kDa .

  • It can be expressed as a recombinant protein with fusion tags like GST, suggesting it has stable folding properties .

• Functional domains:

  • Based on its role in proteasome assembly, PSMG3 likely contains domains that interact with specific proteasome subunits.

  • It may also have regions that facilitate interactions with other assembly chaperones like PSMG1 and PSMG2 .

• Structural insights from proteasome assembly:

  • Recent cryo-EM studies of proteasome assembly intermediates have visualized chaperone-bound states, which would include PSMG3 in specific contexts .

  • These structures reveal how chaperones structurally adapt during progressive subunit incorporation .

• Structure-function relationships:

  • PSMG3's structure likely facilitates its role in stabilizing assembly intermediates.

  • Its structural features probably enable specific recognition of proteasome subunits to ensure correct assembly order.

• Methodological approaches for structural studies:

  • X-ray crystallography of purified PSMG3, alone or in complex with binding partners

  • Cryo-EM studies of PSMG3 bound to proteasome assembly intermediates

  • NMR spectroscopy for dynamic structural information

  • Computational structure prediction and molecular dynamics simulations

  • Hydrogen-deuterium exchange mass spectrometry to map interaction surfaces

What emerging technologies could advance our understanding of PSMG3's role in proteasome assembly?

Several cutting-edge technologies hold promise for deepening our understanding of PSMG3's role in proteasome assembly:

• Advanced cryo-electron microscopy techniques:

  • Time-resolved cryo-EM could capture different stages of PSMG3-mediated assembly.

  • Cryo-electron tomography could visualize proteasome assembly in situ within cells.

  • These approaches have already proven valuable in visualizing chaperone-bound proteasome assembly intermediates .

• Integrative structural biology approaches:

  • Combining cryo-EM with crosslinking mass spectrometry to map protein-protein interactions.

  • Hydrogen-deuterium exchange mass spectrometry to identify conformational changes during assembly.

• CRISPR-based technologies:

  • CRISPR interference (CRISPRi) or activation (CRISPRa) for temporal control of PSMG3 expression.

  • Base editing or prime editing for introducing specific mutations to study structure-function relationships .

• Proximity labeling methods:

  • BioID or APEX2 fusion proteins to identify transient interaction partners of PSMG3 during assembly.

  • This would help map the dynamic interactome of PSMG3 throughout the assembly process.

• Live-cell imaging advances:

  • Super-resolution microscopy to visualize proteasome assembly in living cells.

  • Fluorescence correlation spectroscopy to analyze binding kinetics of PSMG3 with proteasome subunits.

• Protein engineering approaches:

  • Designer proteins to modulate or redirect PSMG3 function.

  • Split fluorescent proteins to visualize PSMG3 interactions in real-time.

• Single-molecule techniques:

  • Single-molecule FRET to study conformational changes during PSMG3-mediated assembly.

  • Optical tweezers to measure forces involved in proteasome assembly.

What are the most promising therapeutic applications of PSMG3-AS1 research in cancer?

Research on PSMG3-AS1 in cancer contexts suggests several promising therapeutic applications:

• RNA-based therapeutics:

  • Antisense oligonucleotides (ASOs) targeting PSMG3-AS1 could reduce its expression in cancers where it's upregulated.

  • Small interfering RNAs (siRNAs) have demonstrated efficacy in reducing PSMG3-AS1 levels and inhibiting cancer cell proliferation and invasion in experimental models .

• miRNA-based approaches:

  • miRNA mimics could be used to increase levels of miRNAs that are sponged by PSMG3-AS1 (such as miR-143-3p in breast cancer) .

  • This would counteract the oncogenic effects of PSMG3-AS1 upregulation.

• Biomarker applications:

  • PSMG3-AS1 expression could serve as a prognostic biomarker, as demonstrated in gastric cancer where its expression correlates with patient outcomes .

  • It could potentially be used to stratify patients for specific treatments based on expression levels.

• Combination therapies:

  • PSMG3-AS1 targeting could be combined with conventional chemotherapy or targeted therapies to enhance efficacy.

  • The association with tumor mutational burden (TMB) and microsatellite instability (MSI) in gastric cancer suggests potential synergy with immunotherapy approaches .

• Targeting downstream pathways:

  • Inhibitors of pathways regulated by PSMG3-AS1, such as the CAV1/miR-451a pathway in gastric cancer or COL1A1 in breast cancer, could be developed .

• Delivery technologies:

  • Nanoparticle-based delivery systems could be optimized for PSMG3-AS1-targeting therapeutics to enhance tissue specificity.

What key questions remain unanswered about PSMG3 and PSMG3-AS1 functions?

Despite recent advances, several critical questions about PSMG3 and PSMG3-AS1 remain unanswered:

• PSMG3 structure and interactions:

  • What is the detailed atomic structure of PSMG3?

  • Which specific proteasome subunits does PSMG3 directly interact with?

  • How does PSMG3 cooperate mechanistically with PSMG1-PSMG2 heterodimers?

• Regulatory mechanisms:

  • How is PSMG3 expression regulated during normal development and in disease states?

  • Are there post-translational modifications that regulate PSMG3 function?

  • Is PSMG3 function altered in neurodegenerative diseases where proteasome dysfunction is implicated?

• PSMG3-AS1 mechanisms beyond miRNA sponging:

  • Does PSMG3-AS1 have functions beyond acting as a miRNA sponge?

  • Does it regulate PSMG3 expression or function?

  • Are there protein interactions of PSMG3-AS1 that contribute to its function?

• Tissue specificity:

  • Why is PSMG3-AS1 upregulated in specific cancer types?

  • Are there tissue-specific functions of PSMG3 in proteasome assembly?

• Therapeutic potential:

  • Would targeting PSMG3-AS1 be effective in clinical settings?

  • Could modulating PSMG3 function affect proteasome assembly enough to have therapeutic benefits in diseases with proteasome dysfunction?

• Evolutionary conservation:

  • How conserved are PSMG3 functions across species?

  • Did PSMG3-AS1 evolve alongside PSMG3 or independently?

• Relationship between PSMG3 and PSMG3-AS1:

  • Is there any functional relationship between PSMG3 protein and PSMG3-AS1 lncRNA?

  • Do they share regulatory elements or cross-regulate each other's expression?

Addressing these questions will require integrated approaches combining structural biology, functional genomics, and detailed mechanistic studies in relevant model systems.

What are the most significant recent advances in PSMG3 and PSMG3-AS1 research?

Recent significant advances in PSMG3 and PSMG3-AS1 research have expanded our understanding of these molecules in both normal cellular processes and disease states:

For PSMG3, the visualization of proteasome assembly intermediates through cryo-EM has been transformative, enabling researchers to see the roles of assembly chaperones, including PSMG3, in orchestrating the stepwise assembly of the 26S proteasome . These structural studies have revealed how chaperones determine the order of subunit addition and how they structurally adapt during progressive assembly.

For PSMG3-AS1, the identification of its role as an oncogenic lncRNA in multiple cancer types represents a major advance. Studies have demonstrated its upregulation in gastric cancer and breast cancer, and elucidated molecular mechanisms involving miRNA sponging . The PSMG3-AS1/miR-143-3p/COL1A1 regulatory axis in breast cancer and the impact on the CAV1/miR-451a pathway in gastric cancer provide mechanistic insights into how this lncRNA contributes to cancer progression.

Together, these advances highlight the diverse functions of genes and transcripts from the PSMG3 locus, from fundamental cellular processes like proteasome assembly to regulatory roles in cancer development. Future research will likely continue to uncover how these functions are integrated and how they might be targeted for therapeutic benefit.

How might future collaborative approaches accelerate PSMG3 and PSMG3-AS1 research?

Advancing our understanding of PSMG3 and PSMG3-AS1 will benefit from collaborative approaches that integrate diverse expertise and methodologies:

• Structural biology and biochemistry collaborations:

  • Partnerships between cryo-EM experts and biochemists can further elucidate the structural details of PSMG3 in proteasome assembly.

  • These collaborations could reveal the precise molecular interactions that govern PSMG3's chaperone function.

• Cancer biology and RNA biology integration:

  • Joint efforts between cancer researchers and RNA biologists can further unravel PSMG3-AS1's roles in different cancer types.

  • Such collaborations could identify shared and distinct mechanisms across cancer contexts.

• Translational research partnerships:

  • Collaborations between basic scientists and clinicians could accelerate the development of PSMG3-AS1-based biomarkers or therapeutics.

  • Patient-derived samples could be used to validate findings from cell and animal models.

• Computational and experimental biology synergy:

  • Computational predictions of PSMG3 structure and function could guide experimental design.

  • Machine learning approaches could identify patterns in large datasets that suggest new functional roles.

• Multi-omics approaches:

  • Integrating genomics, transcriptomics, proteomics, and metabolomics data could provide comprehensive views of PSMG3 and PSMG3-AS1 functions.

  • Single-cell multi-omics could reveal cell-type-specific roles.

• Shared resources and databases:

  • Development of specialized reagents, cell lines, and animal models for studying PSMG3 and PSMG3-AS1.

  • Centralized databases of research findings to facilitate meta-analyses and systematic reviews.

• Interdisciplinary training initiatives:

  • Training programs that bridge disciplines relevant to PSMG3 and PSMG3-AS1 research.

  • Workshops focused on specialized techniques for studying these molecules.