Phosphorylation is a critical post-translational modification involved in the regulation of almost all cellular processes. However, fewer than 5% of thousands of recently discovered phosphosites have been functionally annotated. In this study, we devised a chemical genetic approach to study the functional relevance of phosphosites in Saccharomyces cerevisiae. We generated 474 yeast strains with mutations in specific phosphosites that were screened for fitness in 102 conditions, along with a gene deletion library. Of these phosphosites, 42% exhibited growth phenotypes, suggesting that these are more likely functional. We inferred their function based on the similarity of their growth profiles with that of gene deletions and validated a subset by thermal proteome profiling and lipidomics. A high fraction exhibited phenotypes not seen in the corresponding gene deletion, suggestive of a gain-of-function effect. For phosphosites conserved in humans, the severity of the yeast phenotypes is indicative of their human functional relevance. This high-throughput approach allows for functionally characterizing individual phosphosites at scale.
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The mass spectrometry proteomics data were deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD017929. Yeast mutant strain growth measurements are provided in the Supplementary Data.
Functional enrichment in the phosphorylation network was performed using SAFE (https://www.bioconductor.org/packages/release/bioc/html/safe.html). Image processing and S score calculations were performed using EMAP (https://www.bioconductor.org/packages/release/bioc/html/safe.html). GO enrichment analysis to assign annotations to yeast phosphosites was performed using the ClusterProfiler package (https://bioconductor.org/packages/release/bioc/html/clusterProfiler.html).
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We thank N. Krogan and J. Woolford Jr. for generously providing strains; M. Knop for generously providing plasmids; M. Gierlach and N. Nepke from the EMBL lab kitchen for their help making media and pouring screening plates; N. Gabrielli for providing nitrogen stress media; R. Gathungu and P. Phapale from the EMBL Metabolomics Core Facility; and K. Roy and J. Villen for critical reading of the manuscript. This study was funded by EMBL core funding and a Starting Grant Award from the European Research Council (ERC-2014-STG 638884 PhosFunc PB). L.M.S, S.C.V. and S.T.C. were supported by a European Research Council Advanced Investigator Grant under the European Union’s Horizon 2020 Research and Innovation Programme (AdG-742804-SystGeneEdit). S.C.V. was supported by an Advanced Postdoc Mobility Fellowship from the Swiss National Science Foundation (grant no. P300PA_177909). V.G.P. is supported by grants from the Swiss National Science Foundation, NCCR RNA & Disease, the Novartis Foundation and Olga Mayenfisch Stiftung. M.O.-O. was supported by a Boehringer Ingelheim Fonds PhD fellowship. K.-M.N. was supported by the DFG fund (SPP 1738) and Fondazione Cariplo (2018-0525 DEPRECAD).
The authors declare no competing interests.
Peer review information Nature Biotechnology thanks Stephen Tenzer and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Supplementary Figs. 1–10
List of phosphorylation sites selected for mutation
Conditions used for growth measurments
Growth measurements for mutants in each condition reported as S scores and q values
Growth measurements for replicates
Spot assay growth measurements
Characterization of phospho-mutants, including degree of conservation, number of replicates and correlation with corresponding gene deletion
Predicted functional annotation for mutated phosphosite positions
Sequencing quality control information
Thermal proteome profile dataset
Lipidomics dataset on negative mode
Lipidomics dataset on positive mode
Lipidomics ID confirmations
GO enrichment for thermal proteome profile results
Lipid changes in VMA2 and ELO2 mutants
Annotations for human phosphosites at orthologous positions to the yeast phospho-mutants
Sample mapping for thermal proteome profiling dataset
List of plasmids used
List of generated humanized yeast strains
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Viéitez, C., Busby, B.P., Ochoa, D. et al. High-throughput functional characterization of protein phosphorylation sites in yeast. Nat Biotechnol (2021). https://doi.org/10.1038/s41587-021-01051-x