Abstract

Ubiquitin is essential for eukaryotic life and varies in only 3 amino acid positions between yeast and humans. However, recent deep sequencing studies indicate that ubiquitin is highly tolerant to single mutations. We hypothesized that this tolerance would be reduced by chemically induced physiologic perturbations. To test this hypothesis, a class of first year UCSF graduate students employed deep mutational scanning to determine the fitness landscape of all possible single residue mutations in the presence of five different small molecule perturbations. These perturbations uncover 'shared sensitized positions' localized to areas around the hydrophobic patch and the C-terminus. In addition, we identified perturbation specific effects such as a sensitization of His68 in HU and a tolerance to mutation at Lys63 in DTT. Our data show how chemical stresses can reduce buffering effects in the ubiquitin proteasome system. Finally, this study demonstrates the potential of lab-based interdisciplinary graduate curriculum.

Article and author information

Author details

  1. David Mavor

    Biophysics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Kyle Barlow

    Bioinformatics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Samuel Thompson

    Biophysics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Benjamin A Barad

    Biophysics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Alain R Bonny

    Biophysics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Clinton L Cario

    Bioinformatics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Garrett Gaskins

    Biophysics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Zairan Liu

    Biophysics Graduate Group, University of California, San Francisco, San Fransisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Laura Deming

    Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Seth D Axen

    Bioinformatics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. Elena Caceres

    Bioinformatics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Weilin Chen

    Bioinformatics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  13. Adolfo Cuesta

    Chemistry and Chemical Biology Graduate Program, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. Rachel Gate

    Bioinformatics Graduate Group, University of California, San Francisco, San Fransisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  15. Evan M Green

    Biophysics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  16. Kaitlin R Hulce

    Chemistry and Chemical Biology Graduate Program, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  17. Weiyue Ji

    Biophysics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  18. Lillian R Kenner

    Biophysics Graduate Group, University of California, San Francisco, San Fransisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  19. Bruk Mensa

    Chemistry and Chemical Biology Graduate Program, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  20. Leanna S Morinishi

    Bioinformatics Graduate Group, University of California, San Francisco, San Fransisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  21. Steven M Moss

    Chemistry and Chemical Biology Graduate Program, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  22. Marco Mravic

    Biophysics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  23. Ryan K Muir

    Chemistry and Chemical Biology Graduate Program, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  24. Stefan Niekamp

    Biophysics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  25. Chimno I Nnadi

    Chemistry and Chemical Biology Graduate Program, University of California, San Francisco, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  26. Eugene Palovcak

    Biophysics Graduate Group, University of California, San Francisco, San Fransisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  27. Erin M Poss

    Chemistry and Chemical Biology Graduate Program, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  28. Tyler D Ross

    Biophysics Graduate Group, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  29. Eugenia C Salcedo

    Chemistry and Chemical Biology Graduate Program, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  30. Stephanie See

    Chemistry and Chemical Biology Graduate Program, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  31. Meena Subramaniam

    Bioinformatics Graduate Group, University of California, San Francisco, San Fransisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  32. Allison W Wong

    Chemistry and Chemical Biology Graduate Program, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  33. Jennifer Li

    UCSF Science and Health Education Partnership, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  34. Kurt S Thorn

    UCSF Science and Health Education Partnership, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  35. Shane Thomas Ó Conchúir

    Department of Bioengineering and Therapeutic Science, California Institute for Quantitative Biology, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  36. Benjamin P Roscoe

    Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, United States
    Competing interests
    The authors declare that no competing interests exist.
  37. Eric D Chow

    Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  38. Joseph L DeRisi

    Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  39. Tanja Kortemme

    Department of Bioengineering and Therapeutic Science, California Institute for Quantitative Biology, University of California, San Francisco, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  40. Daniel NA Bolon

    Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, United States
    Competing interests
    The authors declare that no competing interests exist.
  41. James S Fraser

    Department of Bioengineering and Therapeutic Science, California Institute for Quantitative Biology, University of California, San Francisco, San Francisco, United States
    For correspondence
    jfraser@fraserlab.com
    Competing interests
    The authors declare that no competing interests exist.

Copyright

© 2016, Mavor et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 4,433
    views
  • 667
    downloads
  • 75
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. David Mavor
  2. Kyle Barlow
  3. Samuel Thompson
  4. Benjamin A Barad
  5. Alain R Bonny
  6. Clinton L Cario
  7. Garrett Gaskins
  8. Zairan Liu
  9. Laura Deming
  10. Seth D Axen
  11. Elena Caceres
  12. Weilin Chen
  13. Adolfo Cuesta
  14. Rachel Gate
  15. Evan M Green
  16. Kaitlin R Hulce
  17. Weiyue Ji
  18. Lillian R Kenner
  19. Bruk Mensa
  20. Leanna S Morinishi
  21. Steven M Moss
  22. Marco Mravic
  23. Ryan K Muir
  24. Stefan Niekamp
  25. Chimno I Nnadi
  26. Eugene Palovcak
  27. Erin M Poss
  28. Tyler D Ross
  29. Eugenia C Salcedo
  30. Stephanie See
  31. Meena Subramaniam
  32. Allison W Wong
  33. Jennifer Li
  34. Kurt S Thorn
  35. Shane Thomas Ó Conchúir
  36. Benjamin P Roscoe
  37. Eric D Chow
  38. Joseph L DeRisi
  39. Tanja Kortemme
  40. Daniel NA Bolon
  41. James S Fraser
(2016)
Determination of ubiquitin fitness landscapes under different chemical stresses in a classroom setting
eLife 5:e15802.
https://doi.org/10.7554/eLife.15802

Share this article

https://doi.org/10.7554/eLife.15802

Further reading

    1. Computational and Systems Biology
    2. Genetics and Genomics
    Jia-Ying Su, Yun-Lin Wang ... Chien-Ling Lin
    Research Article

    Untranslated regions (UTRs) contain crucial regulatory elements for RNA stability, translation and localization, so their integrity is indispensable for gene expression. Approximately 3.7% of genetic variants associated with diseases occur in UTRs, yet a comprehensive understanding of UTR variant functions remains limited due to inefficient experimental and computational assessment methods. To systematically evaluate the effects of UTR variants on RNA stability, we established a massively parallel reporter assay on 6555 UTR variants reported in human disease databases. We examined the RNA degradation patterns mediated by the UTR library in two cell lines, and then applied LASSO regression to model the influential regulators of RNA stability. We found that UA dinucleotides and UA-rich motifs are the most prominent destabilizing element. Gain of UA dinucleotide outlined mutant UTRs with reduced stability. Studies on endogenous transcripts indicate that high UA-dinucleotide ratios in UTRs promote RNA degradation. Conversely, elevated GC content and protein binding on UA dinucleotides protect high-UA RNA from degradation. Further analysis reveals polarized roles of UA-dinucleotide-binding proteins in RNA protection and degradation. Furthermore, the UA-dinucleotide ratio of both UTRs is a common characteristic of genes in innate immune response pathways, implying a coordinated stability regulation through UTRs at the transcriptomic level. We also demonstrate that stability-altering UTRs are associated with changes in biobank-based health indices, underscoring the importance of precise UTR regulation for wellness. Our study highlights the importance of RNA stability regulation through UTR primary sequences, paving the way for further exploration of their implications in gene networks and precision medicine.

    1. Computational and Systems Biology
    2. Medicine
    Hong Yang, Cheng Zhang ... Adil Mardinoglu
    Research Article

    Excessive consumption of sucrose, in the form of sugar-sweetened beverages, has been implicated in the pathogenesis of metabolic dysfunction‐associated fatty liver disease (MAFLD) and other related metabolic syndromes. The c-Jun N-terminal kinase (JNK) pathway plays a crucial role in response to dietary stressors, and it was demonstrated that the inhibition of the JNK pathway could potentially be used in the treatment of MAFLD. However, the intricate mechanisms underlying these interventions remain incompletely understood given their multifaceted effects across multiple tissues. In this study, we challenged rats with sucrose-sweetened water and investigated the potential effects of JNK inhibition by employing network analysis based on the transcriptome profiling obtained from hepatic and extrahepatic tissues, including visceral white adipose tissue, skeletal muscle, and brain. Our data demonstrate that JNK inhibition by JNK-IN-5A effectively reduces the circulating triglyceride accumulation and inflammation in rats subjected to sucrose consumption. Coexpression analysis and genome-scale metabolic modeling reveal that sucrose overconsumption primarily induces transcriptional dysfunction related to fatty acid and oxidative metabolism in the liver and adipose tissues, which are largely rectified after JNK inhibition at a clinically relevant dose. Skeletal muscle exhibited minimal transcriptional changes to sucrose overconsumption but underwent substantial metabolic adaptation following the JNK inhibition. Overall, our data provides novel insights into the molecular basis by which JNK inhibition exerts its metabolic effect in the metabolically active tissues. Furthermore, our findings underpin the critical role of extrahepatic metabolism in the development of diet-induced steatosis, offering valuable guidance for future studies focused on JNK-targeting for effective treatment of MAFLD.