A novel USP30 inhibitor recapitulates genetic loss of USP30 and sets the trigger for PINK1-PARKIN amplification of mitochondrial ubiquitylation

Rusilowicz‐Jones, Emma V; Jardine, Jane; Pinto-Fernández, Adán; Guenther, Franziska; Giurrandino, Mariacarmela; Barone, Francesco G.; McCarron, Katy R; Burke, Christopher; Murad, Alejandro D.; Amador, Martínez; Marcassa, Elena; Gersch, Malte; Buckmelter, Alex J.; Kayser-Bricker, Katherine J.; Lamoliatte, Frederic; Gajbhiye, Akshada; Davis, Simon; Scott, Hannah C.; Murphy, Emma J.; England, Katherine S.; Mortiboys, Heather; Komander, David; Trost, Matthias; Kessler, Benedikt M.; Ioannidis, Stephanos; Ahlijanian, Michael K.; Urbé, Sylvie; Clague, Michael J.

doi:10.1101/2020.04.16.044206

Cited by 6 publications

(26 citation statements)

References 66 publications

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“…However in USP30 -/cells the signal is already maximally elevated and is impervious to the inhibitor (Figure 2A,B,D,E). The same pattern holds for a second biomarker, SYNJ2BP, identified by global ubiquitomic analysis of the response to FT385, a cyanopyrrolidine class of USP30 inhibitor (Figure 2A,C,D) [16]. Mitochondrial depolarisation leads to the accumulation of the kinase PINK1 which phosphorylates ubiquitin (pUb) and Parkin at Ser65 [23,24].…”

Section: Resultsmentioning

confidence: 66%

“…Applying CMPD-39 to SHSY5Y neuroblastoma cells shows strong competition for Ub-PA in the sub µM range of concentrations (Figure 1C). A robust proxy read-out for target engagement is the enhancement of TOM20 ubiquitylation following mitochondrial depolarisation [6,16]. This second assay indicates a maximal effect with 200 nM CMPD-39 applied to RPE1-YFP-Parkin cells cells (Figure 1D).…”

Section: Resultsmentioning

confidence: 96%

“…In the case of FT385 the specificity of the drug across a panel of DUBs was high at concentrations up to 200nM but it becomes less specific at higher concentrations. In the optimal concentration range it is recommended to define target engagement for each cell line under study using a competition assay with reactive ubiquitin probes [16,19]. Phu et al used higher concentrations of a related compound in a large scale proteomic analysis.…”

Section: Introductionmentioning

confidence: 99%

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Benchmarking a highly selective USP30 inhibitor for enhancement of mitophagy and pexophagy

Rusilowicz‐Jones

Barone

Lopes

et al. 2021

Preprint

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The deubiquitylase USP30 is an actionable target considered for treatment of conditions associated with defects in the PINK1/Parkin pathway leading to mitophagy. These include Parkinson's disease and pulmonary fibrosis. We provide a detailed cell biological characterisation of a benzenesulphonamide molecule, compound 39, that has previously been reported to inhibit USP30 in an in vitro enzymatic assay. The current compound offers increased selectivity over previously described inhibitors. It enhances mitophagy and generates a signature response for USP30 inhibition following mitochondrial depolarisation. This includes enhancement of TOM20 and SYNJ2BP ubiquitylation and phosphoubiquitin accumulation, alongside increased mitophagy. In dopaminergic neurons, generated from Parkinson's disease patients carrying loss of function Parkin mutations, compound 39 could significantly restore mitophagy to a level approaching control values. USP30 is located on both mitochondria and peroxisomes and has also been linked to the PINK1 independent pexophagy pathway. Using a fluorescence reporter of pexophagy expressed in U20S cells, we observe increased pexophagy upon application of compound 39 that recapitulates the previously described effect for USP30 depletion. This provides the first pharmacological intervention with a synthetic molecule to enhance peroxisome turnover.

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Section: Resultsmentioning

confidence: 66%

Section: Resultsmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

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Benchmarking a highly selective USP30 inhibitor for enhancement of mitophagy and pexophagy

Rusilowicz‐Jones

Barone

Lopes

et al. 2021

Preprint

Self Cite

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“…We also detected genes NUP88 [ 62 ], ROBO4 [ 63 ], DLGAP2 [ 64 ], AHR [ 65 ], PPP1R3E [ 66 ], RFX3 [ 67 ] and NOS2 [ 68 ] that were shown to possess biological link with AD. Additional identified genes USP30 [ 69 ], GRIN2A [ 70 ], SLC25A28 [ 71 ], HLA-DRB5 [ 72 ], ZMAT2 [ 73 ], SLC4A10 [ 74 ], MTFMT [ 75 ] and SETD6 [ 76 ] were shown to be related with neurological diseases by previous studies.…”

Section: Resultsmentioning

confidence: 99%

Novel Variance-Component TWAS method for studying complex human diseases with applications to Alzheimer’s dementia

et al. 2021

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Transcriptome-wide association studies (TWAS) have been widely used to integrate transcriptomic and genetic data to study complex human diseases. Within a test dataset lacking transcriptomic data, traditional two-stage TWAS methods first impute gene expression by creating a weighted sum that aggregates SNPs with their corresponding cis-eQTL effects on reference transcriptome. Traditional TWAS methods then employ a linear regression model to assess the association between imputed gene expression and test phenotype, thereby assuming the effect of a cis-eQTL SNP on test phenotype is a linear function of the eQTL’s estimated effect on reference transcriptome. To increase TWAS robustness to this assumption, we propose a novel Variance-Component TWAS procedure (VC-TWAS) that assumes the effects of cis-eQTL SNPs on phenotype are random (with variance proportional to corresponding reference cis-eQTL effects) rather than fixed. VC-TWAS is applicable to both continuous and dichotomous phenotypes, as well as individual-level and summary-level GWAS data. Using simulated data, we show VC-TWAS is more powerful than traditional TWAS methods based on a two-stage Burden test, especially when eQTL genetic effects on test phenotype are no longer a linear function of their eQTL genetic effects on reference transcriptome. We further applied VC-TWAS to both individual-level (N = ~3.4K) and summary-level (N = ~54K) GWAS data to study Alzheimer’s dementia (AD). With the individual-level data, we detected 13 significant risk genes including 6 known GWAS risk genes such as TOMM40 that were missed by traditional TWAS methods. With the summary-level data, we detected 57 significant risk genes considering only cis-SNPs and 71 significant genes considering both cis- and trans- SNPs; these findings also validated our findings with the individual-level GWAS data. Our VC-TWAS method is implemented in the TIGAR tool for public use.

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“…We also detected genes NUP88 [60], ROBO4 [61], DLGAP2 [62], AHR [63], PPP1R3E [64], RFX3 [65] and NOS2 [66] that were shown to possess biological link with AD. Additional identified genes USP30 [67], GRIN2A [68], SLC25A28 [69], HLA-DRB5 [70], ZMAT2 [71], SLC4A10 [72], MTFMT [73] and SETD6 [74] were shown to be related with neurological diseases by previous studies.…”

Section: Resultsmentioning

confidence: 99%

Novel Variance-Component TWAS method for studying complex human diseases with applications to Alzheimer’s dementia

Tang

Buchman

Jager

et al. 2020

Preprint

View full text Add to dashboard Cite

Transcriptome-wide association studies (TWAS) have been widely used to integrate transcriptomic and genetic data to study complex human diseases. Within a test dataset lacking transcriptomic data, existing TWAS methods impute gene expression by creating a weighted sum that aggregates SNPs with their corresponding cis-eQTL effects on transcriptome estimated from reference datasets. Existing TWAS methods then apply a linear regression model to assess the association between imputed gene expression and test phenotype, thereby assuming the effect of a cis-eQTL SNP on test phenotype is a linear function of the eQTL's estimated effect on reference transcriptome. Thus, existing TWAS methods make a strong assumption that cis-eQTL effect sizes on reference transcriptome are reflective of their corresponding SNP effect sizes on test phenotype. To increase TWAS robustness to this assumption, we propose a Variance-Component TWAS procedure (VC-TWAS) that assumes the effects of cis-eQTL SNPs on phenotype are random (with variance proportional to corresponding cis-eQTL effects in reference dataset) rather than fixed. By doing so, we show VC-TWAS is more powerful than traditional TWAS when cis-eQTL SNP effects on test phenotype truly differ from their eQTL effects within reference dataset. We further applied VC-TWAS using cis-eQTL effect sizes estimated by a nonparametric Bayesian method to study Alzheimer's dementia (AD) related phenotypes and detected 13 genes significantly associated with AD, including 6 known GWAS risk loci. All significant loci are proximal to the major known risk loci APOE for AD. Further, we add this VC-TWAS function into our previously developed tool TIGAR for public use.

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A novel USP30 inhibitor recapitulates genetic loss of USP30 and sets the trigger for PINK1-PARKIN amplification of mitochondrial ubiquitylation

Cited by 6 publications

References 66 publications

Benchmarking a highly selective USP30 inhibitor for enhancement of mitophagy and pexophagy

Benchmarking a highly selective USP30 inhibitor for enhancement of mitophagy and pexophagy

Novel Variance-Component TWAS method for studying complex human diseases with applications to Alzheimer’s dementia

Novel Variance-Component TWAS method for studying complex human diseases with applications to Alzheimer’s dementia

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