insight - Proteomics - # Proteasome Interactome and Substrate Identification

Quantitative Mapping of Proteasome Interactomes and Substrates for In Vitro and In Vivo Studies

Q: How could ProteasomeID be adapted to study the dynamics of proteasome interactions and substrates during specific cellular processes, such as the cell cycle or differentiation

ProteasomeID can be adapted to study the dynamics of proteasome interactions and substrates during specific cellular processes by implementing time-course experiments. For instance, to investigate proteasome dynamics during the cell cycle, cells can be synchronized at different stages (G1, S, G2, M) and then subjected to ProteasomeID analysis at various time points. By comparing the proteasome interactome and substrate landscape at different stages of the cell cycle, researchers can elucidate how proteasome interactions and substrate profiles change throughout cell division. This approach can provide insights into the regulation of proteasome activity during the cell cycle and identify cell cycle-specific proteasome substrates. Similarly, to study proteasome dynamics during differentiation, stem cells can be induced to differentiate into specific cell types, and ProteasomeID can be performed at different time points during the differentiation process. By comparing the proteasome interactome and substrate profiles in stem cells versus differentiated cells, researchers can uncover how proteasome interactions and substrate specificity are altered during cellular differentiation. This can shed light on the role of the proteasome in regulating key differentiation processes and maintaining cellular homeostasis.

Q: What are the potential limitations of the ProteasomeID approach, and how could it be further improved to enhance its sensitivity and coverage

One potential limitation of the ProteasomeID approach is the reliance on biotin labeling, which may not capture all transient or weak interactions of the proteasome. To enhance sensitivity and coverage, several improvements can be considered: Optimizing Biotin Ligase Fusion: Further optimization of the fusion strategy, such as exploring different fusion sites or using alternative biotin ligases with higher efficiency, could improve the labeling of proteasome interactions. Time-course Experiments: Implementing time-course experiments with shorter biotin labeling periods can capture more transient interactions and dynamic changes in proteasome substrates. Cross-linking: Incorporating cross-linking agents before biotin labeling can stabilize transient interactions, allowing for the detection of weaker interactions that may be missed under normal conditions. Combining with Other Proximity Labeling Techniques: Integrating ProteasomeID with other proximity labeling techniques, such as APEX or BioID, can provide complementary information and enhance the coverage of proteasome interactors and substrates. Validation Strategies: Employing orthogonal validation methods, such as co-immunoprecipitation or proximity ligation assays, can confirm the identified proteasome interactors and substrates, ensuring the reliability of the ProteasomeID results.

Q: Given the ability of ProteasomeID to identify novel proteasome interactors and substrates, what are the potential implications for understanding proteasome function in health and disease

The ability of ProteasomeID to identify novel proteasome interactors and substrates has significant implications for understanding proteasome function in health and disease: Uncovering Novel Regulatory Pathways: By identifying previously unknown proteasome interactors, ProteasomeID can reveal novel regulatory pathways and protein networks that modulate proteasome activity and substrate specificity. Insights into Disease Mechanisms: The discovery of novel proteasome substrates through ProteasomeID can provide insights into the molecular mechanisms underlying various diseases, including neurodegenerative disorders, cancer, and autoimmune conditions. Understanding how these substrates are targeted for degradation by the proteasome can offer new therapeutic targets for disease intervention. Personalized Medicine: The identification of disease-specific proteasome interactors and substrates using ProteasomeID can contribute to the development of personalized medicine approaches by targeting specific proteasome pathways implicated in individual patients' conditions. Drug Development: Proteasome inhibitors are widely used in cancer therapy, and ProteasomeID can aid in the discovery of novel proteasome substrates that may serve as targets for developing more selective and effective proteasome inhibitors with reduced side effects. Functional Studies: Studying the newly identified proteasome interactors and substrates can provide valuable insights into their roles in cellular processes, signaling pathways, and disease pathogenesis, advancing our understanding of proteasome function in diverse biological contexts.

Core Concepts

Proximity labeling coupled to mass spectrometry can be used to comprehensively map proteasome interactions and substrates in cultured cells and mouse models.

Abstract

The authors developed a proximity labeling strategy called ProteasomeID to quantitatively map proteasome interacting proteins and substrates both in vitro and in vivo.

Key highlights:

ProteasomeID involves fusing the proteasome subunit PSMA4 with a promiscuous biotin ligase, which gets incorporated into fully assembled proteasomes without affecting their activity.
In cultured HEK293T cells, ProteasomeID was able to identify known proteasome interacting proteins as well as novel candidates.
Combining ProteasomeID with proteasome inhibition enabled the identification of both known and novel proteasome substrates, including low-abundance transcription factors.
The authors generated a mouse model expressing the PSMA4-miniTurbo fusion protein, allowing them to apply ProteasomeID in various mouse organs and identify both known and novel proteasome interacting proteins in vivo.
ProteasomeID could also be used to detect the degradation of known targets of proteolysis-targeting chimeric molecules (PROTACs) in cells.

Overall, ProteasomeID provides a powerful tool to comprehensively profile the proteasome interactome and substrate landscape in physiological and disease contexts.

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Stats

Proteasome subunits are enriched by ProteasomeID with log2 fold changes typically >4 compared to control.
Proteasome activators and ubiquitin are enriched upon proteasome inhibition by MG132.
Bromodomain-containing proteins are enriched upon treatment with the PROTAC molecule KB02-JQ1.

Quotes

"ProteasomeID can be used to obtain snapshots of the proteasome-proximal proteome, and to identify proteasome substrates."
"Combining ProteasomeID with proteasome inhibition enabled the identification of both known and novel proteasome substrates, including low-abundance transcription factors."
"ProteasomeID could also be used to detect the degradation of known targets of proteolysis-targeting chimeric molecules (PROTACs) in cells."

Key Insights Distilled From

ProteasomeID: quantitative mapping of proteasome interactomes and substrates for in vitro and in vivo studies

by Bartolome,A.... at www.biorxiv.org 08-09-2022

https://www.biorxiv.org/content/10.1101/2022.08.09.503299v3

Deeper Inquiries

How could ProteasomeID be adapted to study the dynamics of proteasome interactions and substrates during specific cellular processes, such as the cell cycle or differentiation

ProteasomeID can be adapted to study the dynamics of proteasome interactions and substrates during specific cellular processes by implementing time-course experiments. For instance, to investigate proteasome dynamics during the cell cycle, cells can be synchronized at different stages (G1, S, G2, M) and then subjected to ProteasomeID analysis at various time points. By comparing the proteasome interactome and substrate landscape at different stages of the cell cycle, researchers can elucidate how proteasome interactions and substrate profiles change throughout cell division. This approach can provide insights into the regulation of proteasome activity during the cell cycle and identify cell cycle-specific proteasome substrates.
Similarly, to study proteasome dynamics during differentiation, stem cells can be induced to differentiate into specific cell types, and ProteasomeID can be performed at different time points during the differentiation process. By comparing the proteasome interactome and substrate profiles in stem cells versus differentiated cells, researchers can uncover how proteasome interactions and substrate specificity are altered during cellular differentiation. This can shed light on the role of the proteasome in regulating key differentiation processes and maintaining cellular homeostasis.

What are the potential limitations of the ProteasomeID approach, and how could it be further improved to enhance its sensitivity and coverage

One potential limitation of the ProteasomeID approach is the reliance on biotin labeling, which may not capture all transient or weak interactions of the proteasome. To enhance sensitivity and coverage, several improvements can be considered:

Optimizing Biotin Ligase Fusion: Further optimization of the fusion strategy, such as exploring different fusion sites or using alternative biotin ligases with higher efficiency, could improve the labeling of proteasome interactions.

Time-course Experiments: Implementing time-course experiments with shorter biotin labeling periods can capture more transient interactions and dynamic changes in proteasome substrates.

Cross-linking: Incorporating cross-linking agents before biotin labeling can stabilize transient interactions, allowing for the detection of weaker interactions that may be missed under normal conditions.

Combining with Other Proximity Labeling Techniques: Integrating ProteasomeID with other proximity labeling techniques, such as APEX or BioID, can provide complementary information and enhance the coverage of proteasome interactors and substrates.

Validation Strategies: Employing orthogonal validation methods, such as co-immunoprecipitation or proximity ligation assays, can confirm the identified proteasome interactors and substrates, ensuring the reliability of the ProteasomeID results.

Given the ability of ProteasomeID to identify novel proteasome interactors and substrates, what are the potential implications for understanding proteasome function in health and disease

The ability of ProteasomeID to identify novel proteasome interactors and substrates has significant implications for understanding proteasome function in health and disease:

Uncovering Novel Regulatory Pathways: By identifying previously unknown proteasome interactors, ProteasomeID can reveal novel regulatory pathways and protein networks that modulate proteasome activity and substrate specificity.

Insights into Disease Mechanisms: The discovery of novel proteasome substrates through ProteasomeID can provide insights into the molecular mechanisms underlying various diseases, including neurodegenerative disorders, cancer, and autoimmune conditions. Understanding how these substrates are targeted for degradation by the proteasome can offer new therapeutic targets for disease intervention.

Personalized Medicine: The identification of disease-specific proteasome interactors and substrates using ProteasomeID can contribute to the development of personalized medicine approaches by targeting specific proteasome pathways implicated in individual patients' conditions.

Drug Development: Proteasome inhibitors are widely used in cancer therapy, and ProteasomeID can aid in the discovery of novel proteasome substrates that may serve as targets for developing more selective and effective proteasome inhibitors with reduced side effects.

Functional Studies: Studying the newly identified proteasome interactors and substrates can provide valuable insights into their roles in cellular processes, signaling pathways, and disease pathogenesis, advancing our understanding of proteasome function in diverse biological contexts.