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. 2023 Oct 18;623(7988):842–852. doi: 10.1038/s41586-023-06626-z

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© The Author(s) 2023, corrected publication 2024

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 2 — a, The (phospho)proteomics experimental design. Quiescent primary fibroblasts were cultured in duplicate for 14 days under the indicated conditions, for adaptation to increased or decreased temperature/osmotic strength. Quantitative proteomics (tandem mass tag (TMT)-MS/MS) was then performed to analyse the proteome and phosphoproteome differences between samples. b, The number of proteins of which the abundance changed significantly in a particular direction, and the overlap between conditions. Green, proteins of which the abundance significantly increased with increasing osmolarity (directly correlated with external osmolarity); orange, proteins of which the abundance significantly decreased with increasing osmolarity (inversely correlated with external osmolarity); red, proteins of which the abundance increased with increasing temperature (directly correlated with temperature); blue, proteins of which the abundance decreased with increasing temperature (inversely correlated with temperature). Statistical analysis was performed using Fisher’s exact tests comparing the overlap between different sets of proteins, given the total number of proteins detected. c, The percentage of proteins reported as phase separating in the PhaSepDB high-throughput database v.1. Statistical analysis was performed using a one-proportion z-test. d, The proportion of phosphosites predicted to map to IDRs, comparing subsets of phosphosites that change significantly in a particular direction against the overall percentage of IDR phosphorylation (76.8%). Phosphopeptides that increase with temperature and decrease with osmolarity have a significantly lower proportion of IDR phosphorylation, whereas phosphopeptides that increase with temperature and decrease with osmolarity have significantly higher proportion of IDR phosphorylation (proportion z-test, Benjamini–Hochberg-adjusted P < 1 × 10⁻¹⁵ for both temperature and osmolarity). Predicted disorder information was available for 12,495 out of 14,530 detected phosphopeptides. e, Representative example of an IDR phosphosite, at which the phosphorylation level changed in a manner consistent with Ψ_π homeostasis. n = 2. OXSR1 kinase is a key effector of osmotic balance, activated by Ser339 phosphorylation. The effect of hyperosmotic challenge on OXSR1 phosphorylation is fully consistent with recent results⁵⁰.