Serine-linked PARP1 auto-modification controls PARP inhibitor response

Poly(ADP-ribose) polymerase 1 (PARP1) and PARP2 are recruited and activated by DNA damage, resulting in ADP-ribosylation at numerous sites, both within PARP1 itself and in other proteins. Several PARP1 and PARP2 inhibitors are currently employed in the clinic or undergoing trials for treatment of various cancers. These drugs act primarily by trapping PARP1 on damaged chromatin, which can lead to cell death, especially in cells with DNA repair defects. Although PARP1 trapping is thought to be caused primarily by the catalytic inhibition of PARP-dependent modification, implying that ADP-ribosylation (ADPr) can counteract trapping, it is not known which exact sites are important for this process. Following recent findings that PARP1- or PARP2-mediated modification is predominantly serine-linked, we demonstrate here that serine ADPr plays a vital role in cellular responses to PARP1/PARP2 inhibitors. Specifically, we identify three serine residues within PARP1 (499, 507, and 519) as key sites whose efficient HPF1-dependent modification counters PARP1 trapping and contributes to inhibitor tolerance. Our data implicate genes that encode serine-specific ADPr regulators, HPF1 and ARH3, as potential PARP1/PARP2 inhibitor therapy biomarkers.


Statistics
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Software and code
Policy information about availability of computer code Data collection Flow cytometry data were collected using CytExpert Acquisition and Analysis Software Version 2.3 (Beckman Coulter). Data collection for fluorescence polarisation/anisotropy assays was performed using SoftMax Pro version 5.01 and PHERAstar software version 4.00 R3.

Data analysis
Flow Cytometry data were analysed using FlowJo v10 (BD Biosciences). Live-cell imaging data were analysed using Matlab (MathWorks). Image analysis for the colony formation assay was done using ImageJ. Data visualization and statistical analysis was done using GraphPad PRISM 7, Microsoft Excel 2016 (including Solver). Images were assembled in Adobe Illustrator 25.1.
For manuscripts utilizing custom algorithms or software that are central to the research but not yet described in published literature, software must be made available to editors and reviewers. We strongly encourage code deposition in a community repository (e.g. GitHub). See the Nature Research guidelines for submitting code & software for further information.

Data
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Life sciences Behavioural & social sciences Ecological, evolutionary & environmental sciences
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Life sciences study design
All studies must disclose on these points even when the disclosure is negative.

Sample size
No statistical method was used to determine sample size as no inference from small sample to larger populations was done. Two or three independent repeats were performed for each experiment to confirm reproducibility according to the best practice in the field.
Data exclusions No data were excluded.

Replication
All experiments were repeated at least two to three times independently with similar results. All observations were found to be reproducible.
Randomization Randomisation was not required due to the mechanistic character of the study with objective readouts and lack of animal-based experiments.

Blinding
No blinding was performed as the bias from prior knowledge of samples in case of biochemical, blotting, survival, and imagining experiments described in the study is considered limited. All samples including controls were analysed in exactly the same manner.

Validation
All commercial antibodies were validated by manufacturers for the use at least in immunoblotting and immunoprecipitation. The commercial anti-HPF1 anti-body was validated by the Human Priotein Atlas project in multiple tissues and cell lines (data at https:// www.proteinatlas.org/ENSG00000056050-HPF1) and additionally by us using immunoblotting with 293T WT and HPF1 KO cells (Suskiewicz et al., Nature, 2020). The anti-ARH3 antibody was validated by the manufacturer using both immunoblotting and immunocytochemistry (images at https://www.atlasantibodies.com/products/antibodies/primary-antibodies/triple-a-polyclonals/ adprhl2-antibody-hpa027104/) and addtionally by us using immunoblotting in 293T and U2OS WT and ARH3 KO cell lines (see Palazzo et al., eLife, 2018). The custom-made anti-HPF1 antibody was validated by us with immunoblotting using purified human HPF1 and 293T and U2OS WT and HPF1 KO cells (Gibbs-Seymour et al., Mol Cell, 2016 andPalazzo et al., eLife, 2018), as well as testis, ovary, brain, heart, kidney and liver tissue from WT and HPF1 KO mice (unpublished). Anti γ-H2AX antibody was validated by the manufacturer for the use in immunocytochemistry and immunoblotting (see data at https://www.abcam.com/gamma-h2axphospho-s139-antibody-ab2893.html) and additionally by us for the use in flow cytometry by comparing untreated cells and cells treated with genotoxic drugs. Anti pan-ADPr binding reagent (MABE1016) was extensively validated with dot blot, immunoblotting, and immunofluorescence by the Krauss group as described in

Authentication
Cells were not authenticated in our lab. 293T and U2OS cell lines were authenticated with morphology, karyotyping, and PCR based approaches by ATCC.

Mycoplasma contamination
The cell lines were tested for mycoplasma contamination and confirmed as mycoplasma negative.
Commonly misidentified lines (See ICLAC register) No commonly misidentified lines were used.

Flow Cytometry
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The axis scales are clearly visible. Include numbers along axes only for bottom left plot of group (a 'group' is an analysis of identical markers).
All plots are contour plots with outliers or pseudocolor plots.
A numerical value for number of cells or percentage (with statistics) is provided.

Methodology
Sample preparation