Breast cancer immunopeptidomes contain numerous shared tumor antigens.

Hormone receptor-positive breast cancer (HR+) is immunologically cold and has not benefited from advances in immunotherapy. In contrast, subsets of triple-negative breast cancer (TNBC) display high leukocytic infiltration and respond to checkpoint blockade. CD8+ T cells, the main effectors of anticancer responses, recognize MHC I-associated peptides (MAPs). Our work aimed to characterize the repertoire of MAPs presented by HR+ and TNBC tumors. Using mass spectrometry, we identified 57,094 unique MAPs in 26 primary breast cancer samples. MAP source genes highly overlapped between both subtypes. We identified 25 tumor-specific antigens (TSAs) mainly deriving from aberrantly expressed regions. TSAs were most frequently identified in TNBC samples and were more shared among The Cancer Genome Atlas (TCGA) database TNBC than HR+ samples. In the TNBC cohort, the predicted number of TSAs positively correlated with leukocytic infiltration and overall survival, supporting their immunogenicity in vivo. We detected 49 tumor-associated antigens (TAAs), some of which derived from cancer-associated fibroblasts. Functional expansion of specific T cell assays confirmed the in vitro immunogenicity of several TSAs and TAAs. Our study identified attractive targets for cancer immunotherapy in both breast cancer subtypes. The higher prevalence of TSAs in TNBC tumors provides a rationale for their responsiveness to checkpoint blockade.

SUMO Proteomics Analyses Identify Protein Inhibitor of Activated STAT-Mediated Regulatory Networks Involved in Cell Cycle and Cell Proliferation.

Protein inhibitor of activated STAT (PIAS) proteins are E3 SUMO ligases playing important roles in protein stability and signaling transduction pathways. PIAS proteins are overexpressed in the triple-negative breast cancer cell line MDA-MB-231, and PIAS knockout (KO) results in a reduction in cell proliferation and cell arrest in the S phase. However, the molecular mechanisms underlying PIAS functions in cell proliferation and cell cycle remain largely unknown. Here, we used quantitative SUMO proteomics to explore the regulatory role of PIAS SUMO E3 ligases upon CRISPR/Cas9 KO of individual PIAS. A total of 1422 sites were identified, and around 10% of SUMO sites were regulated following KO of one or more PIAS genes. We identified protein substrates that were either specific to individual PIAS ligase or regulated by several PIAS ligases. Ki-67 and TOP2A, which are involved in cell proliferation and epithelial-to-mesenchymal transition, are SUMOylated at several lysine residues by all PIAS ligases, suggesting a level of redundancy between these proteins. Confocal microscopy and biochemical experiments revealed that SUMOylation regulated TOP2A protein stability, while this modification is involved in the recruitment of Ki-67 nucleolar proteins containing the SUMO interacting motif. These results provide novel insights into both the redundant and specific regulatory mechanisms of cell proliferation and cell cycle mediated by PIAS SUMO E3 ligases.

Induced pluripotent stem cells display a distinct set of MHC I-associated peptides shared by human cancers.

Previous reports showed that mouse vaccination with pluripotent stem cells (PSCs) induces durable anti-tumor immune responses via T cell recognition of some elusive oncofetal epitopes. We characterize the MHC I-associated peptide (MAP) repertoire of human induced PSCs (iPSCs) using proteogenomics. Our analyses reveal a set of 46 pluripotency-associated MAPs (paMAPs) absent from the transcriptome of normal tissues and adult stem cells but expressed in PSCs and multiple adult cancers. These paMAPs derive from coding and allegedly non-coding (48%) transcripts involved in pluripotency maintenance, and their expression in The Cancer Genome Atlas samples correlates with source gene hypomethylation and genomic aberrations common across cancer types. We find that several of these paMAPs were immunogenic. However, paMAP expression in tumors coincides with activation of pathways instrumental in immune evasion (WNT, TGF-ß, and CDK4/6). We propose that currently available inhibitors of these pathways could synergize with immune targeting of paMAPs for the treatment of poorly differentiated cancers.

Head-to-tail cyclization of side chain-protected linear peptides to recapitulate genetically-encoded cyclized peptides.

Genetically-encoded cyclic peptide libraries allow rapid in vivo screens for inhibitors of any target protein of interest. In particular, the Split Intein Circular Ligation of Protein and Peptides (SICLOPPS) system exploits spontaneous protein splicing of inteins to produce intracellular cyclic peptides. A previous SICLOPPS screen against Aurora B kinase, which plays a critical role during chromosome segregation, identified several candidate inhibitors that we sought to recapitulate by chemical synthesis. We describe the syntheses of cyclic peptide hits and analogs via solution-phase macrocyclization of side chain-protected linear peptides obtained from standard solid-phase peptide synthesis. Cyclic peptide targets, including cyclo-[CTWAR], were designed to match both the variable portions and conserved cysteine residue of their genetically-encoded counterparts. Synthetic products were characterized by tandem high-resolution mass spectrometry to analyze a combination of exact mass, isotopic pattern, and collisional dissociation-induced fragmentation pattern. The latter analyses facilitated the distinction between targets and oligomeric side products, and served to confirm peptidic sequences in a manner that can be readily extended to analyses of complex biological samples. This alternative chemical synthesis approach for cyclic peptides allows cost-effective validation and facile chemical elaboration of hit candidates from SICLOPPS screens.

Immunopeptidomic analyses of colorectal cancers with and without microsatellite instability.

Colorectal cancer is the second leading cause of cancer death worldwide, and the incidence of this disease is expected to increase as global socioeconomic changes occur. Immune checkpoint inhibition therapy is effective in treating a minority of colorectal cancer tumors; however, microsatellite stable tumors do not respond well to this treatment. Emerging cancer immunotherapeutic strategies aim to activate a cytotoxic T cell response against tumor-specific antigens, presented exclusively at the cell surface of cancer cells. These antigens are rare and are most effectively identified with a mass spectrometry-based approach, which allows the direct sampling and sequencing of these peptides. Although the few tumor-specific antigens identified to date are derived from coding regions of the genome, recent findings indicate that a large proportion of tumor-specific antigens originate from allegedly noncoding regions. Here, we employed a novel proteogenomic approach to identify tumor antigens in a collection of colorectal cancer-derived cell lines and biopsy samples consisting of matched tumor and normal adjacent tissue. The generation of personalized cancer databases paired with mass spectrometry analyses permitted the identification of more than 30,000 unique MHC I-associated peptides. We identified 19 tumor-specific antigens in both microsatellite stable and unstable tumors, over two-thirds of which were derived from noncoding regions. Many of these peptides were derived from source genes known to be involved in colorectal cancer progression, suggesting that antigens from these genes could have therapeutic potential in a wide range of tumors. These findings could benefit the development of T cell-based vaccines, in which T cells are primed against these antigens to target and eradicate tumors. Such a vaccine could be used in tandem with existing immune checkpoint inhibition therapies, to bridge the gap in treatment efficacy across subtypes of colorectal cancer with varying prognoses. Data are available via ProteomeXchange with identifier PXD028309.

MhcVizPipe: A Quality Control Software for Rapid Assessment of Small- to Large-Scale Immunopeptidome Datasets.

MS-based immunopeptidomics is maturing into an automatized and high-throughput technology, producing small- to large-scale datasets of clinically relevant major histocompatibility complex (MHC) class I-associated and class II-associated peptides. Consequently, the development of quality control (QC) and quality assurance systems capable of detecting sample and/or measurement issues is important for instrument operators and scientists in charge of downstream data interpretation. Here, we created MhcVizPipe (MVP), a semiautomated QC software tool that enables rapid and simultaneous assessment of multiple MHC class I and II immunopeptidomic datasets generated by MS, including datasets generated from large sample cohorts. In essence, MVP provides a rapid and consolidated view of sample quality, composition, and MHC specificity to greatly accelerate the "pass-fail" QC decision-making process toward data interpretation. MVP parallelizes the use of well-established immunopeptidomic algorithms (NetMHCpan, NetMHCIIpan, and GibbsCluster) and rapidly generates organized and easy-to-understand reports in HTML format. The reports are fully portable and can be viewed on any computer with a modern web browser. MVP is intuitive to use and will find utility in any specialized immunopeptidomic laboratory and proteomics core facility that provides immunopeptidomic services to the community.

CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.

MHC-I associated peptides (MAPs) play a central role in the elimination of virus-infected and neoplastic cells by CD8 T cells. However, accurately predicting the MAP repertoire remains difficult, because only a fraction of the transcriptome generates MAPs. In this study, we investigated whether codon arrangement (usage and placement) regulates MAP biogenesis. We developed an artificial neural network called Codon Arrangement MAP Predictor (CAMAP), predicting MAP presentation solely from mRNA sequences flanking the MAP-coding codons (MCCs), while excluding the MCC per se. CAMAP predictions were significantly more accurate when using original codon sequences than shuffled codon sequences which reflect amino acid usage. Furthermore, predictions were independent of mRNA expression and MAP binding affinity to MHC-I molecules and applied to several cell types and species. Combining MAP ligand scores, transcript expression level and CAMAP scores was particularly useful to increase MAP prediction accuracy. Using an in vitro assay, we showed that varying the synonymous codons in the regions flanking the MCCs (without changing the amino acid sequence) resulted in significant modulation of MAP presentation at the cell surface. Taken together, our results demonstrate the role of codon arrangement in the regulation of MAP presentation and support integration of both translational and post-translational events in predictive algorithms to ameliorate modeling of the immunopeptidome.

Most non-canonical proteins uniquely populate the proteome or immunopeptidome.

Combining RNA sequencing, ribosome profiling, and mass spectrometry, we elucidate the contribution of non-canonical translation to the proteome and major histocompatibility complex (MHC) class I immunopeptidome. Remarkably, of 14,498 proteins identified in three human B cell lymphomas, 2,503 are non-canonical proteins. Of these, 28% are novel isoforms and 72% are cryptic proteins encoded by ostensibly non-coding regions (60%) or frameshifted canonical genes (12%). Cryptic proteins are translated as efficiently as canonical proteins, have more predicted disordered residues and lower stability, and critically generate MHC-I peptides 5-fold more efficiently per translation event. Translating 5' "untranslated" regions hinders downstream translation of genes involved in transcription, translation, and antiviral responses. Novel protein isoforms show strong enrichment for signaling pathways deregulated in cancer. Only a small fraction of cryptic proteins detected in the proteome contribute to the MHC-I immunopeptidome, demonstrating the high preferential access of cryptic defective ribosomal products to the class I pathway.

Extending the Comprehensiveness of Immunopeptidome Analyses Using Isobaric Peptide Labeling.

Defining the repertoire of peptides presented by the major histocompatibility complex class I (MHC I) is a key step toward the identification of relevant antigens for cancer immunotherapy. However, the identification of cancer-specific antigens is a significant analytical challenge in view of their low abundance and low mutational load found in most primary cancer specimens. Here, we describe the application of isobaric peptide labeling with tandem mass tag (TMT) to improve the detection of the MHC I peptides. Isobaric peptide labeling was found to promote the formation of multiply charged ions and to enhance the formation of b-type fragment ions, thus resulting in a 50% improvement of MHC I peptide identification. The gain in sensitivity obtained using TMT labeling enabled the detection of low-abundance MHC I peptides including tumor-specific antigens (TSAs) and minor histocompatibility antigens (MiHAs). We further demonstrate the application of this approach to quantify MiHAs presented by B-cell lymphocytes and determined their expression levels by LC-MS/MS using both synchronous precursor selection (SPS) and high-field asymmetric waveform ion mobility spectrometry (FAIMS).

Proteogenomics Uncovers a Vast Repertoire of Shared Tumor-Specific Antigens in Ovarian Cancer.

High-grade serous ovarian cancer (HGSC), the principal cause of death from gynecologic malignancies in the world, has not significantly benefited from advances in cancer immunotherapy. Although HGSC infiltration by lymphocytes correlates with superior survival, the nature of antigens that can elicit anti-HGSC immune responses is unknown. The goal of this study was to establish the global landscape of HGSC tumor-specific antigens (TSA) using a mass spectrometry pipeline that interrogated all reading frames of all genomic regions. In 23 HGSC tumors, we identified 103 TSAs. Classic TSA discovery approaches focusing only on mutated exonic sequences would have uncovered only three of these TSAs. Other mutated TSAs resulted from out-of-frame exonic translation (n = 2) or from noncoding sequences (n = 7). One group of TSAs (n = 91) derived from aberrantly expressed unmutated genomic sequences, which were not expressed in normal tissues. These aberrantly expressed TSAs (aeTSA) originated primarily from nonexonic sequences, in particular intronic (29%) and intergenic (22%) sequences. Their expression was regulated at the transcriptional level by variations in gene copy number and DNA methylation. Although mutated TSAs were unique to individual tumors, aeTSAs were shared by a large proportion of HGSCs. Taking into account the frequency of aeTSA expression and HLA allele frequencies, we calculated that, in Caucasians, the median number of aeTSAs per tumor would be five. We conclude that, in view of their number and the fact that they are shared by many tumors, aeTSAs may be the most attractive targets for HGSC immunotherapy.

MAPDP: A Cloud-Based Computational Platform for Immunopeptidomics Analyses.

The immunopeptidome corresponds to the repertoire of peptides presented at the cell surface by the major histocompatibility complex (MHC) molecules. Cytotoxic T cells scan this repertoire to identify nonself antigens that can arise from tumors or infected cells. The identification of actionable antigenic targets is key to the development of therapeutic cancer vaccines, T-cell therapy, and other T-cell receptor-based biologics. The growing clinical interest for immunopeptidomics has accelerated the development of high throughput proteogenomic platforms that provide a system-level analysis of MHC-associated peptides. Improvement in sensitivity and throughput of mass spectrometers now allows the detection of a few thousands of peptides from less than 100 million cells. To manage the amount of data generated by these instruments, we have developed the MHC-associated peptide discovery platform (MAPDP), a novel open-source cloud-based computational platform for immunopeptidomic analyses. It provides convenient access from a web portal to immunopeptidomes stored in the database, filtering tools, various visualizations, annotations (e.g., IEDB, dbSNP, gnomAD), peptide-binding affinity prediction (mhcflurry, NetMHC), HLA genotyping, and the generation of personalized proteome databases. MAPDP functionalities are demonstrated here by the discovery of MHC peptides featuring new genetic variants identified in two previously published ovarian carcinoma data sets.

Noncoding regions are the main source of targetable tumor-specific antigens.

Tumor-specific antigens (TSAs) represent ideal targets for cancer immunotherapy, but few have been identified thus far. We therefore developed a proteogenomic approach to enable the high-throughput discovery of TSAs coded by potentially all genomic regions. In two murine cancer cell lines and seven human primary tumors, we identified a total of 40 TSAs, about 90% of which derived from allegedly noncoding regions and would have been missed by standard exome-based approaches. Moreover, most of these TSAs derived from nonmutated yet aberrantly expressed transcripts (such as endogenous retroelements) that could be shared by multiple tumor types. Last, we demonstrated that, in mice, the strength of antitumor responses after TSA vaccination was influenced by two parameters that can be estimated in humans and could serve for TSA prioritization in clinical studies: TSA expression and the frequency of TSA-responsive T cells in the preimmune repertoire. In conclusion, the strategy reported herein could considerably facilitate the identification and prioritization of actionable human TSAs.

Comparison of the MHC I Immunopeptidome Repertoire of B-Cell Lymphoblasts Using Two Isolation Methods.

Significant technological advances in both affinity chromatography and mass spectrometry have facilitated the identification of peptides associated with the major histocompatibility complex class I (MHC I) molecules, and enabled a greater understanding of the dynamic nature of the immunopeptidome of normal and neoplastic cells. While the isolation of MHC I-associated peptides (MIPs) typically used mild acid elution (MAE) or immunoprecipitation (IP), limited information currently exists regarding their respective analytical merits. Here, a comparison of these approaches for the isolation of two different B-cell lymphoblast cell models is presented, and it is reported on the recovery, reproducibility, scalability, and complementarity of identification from each method. Both approaches yielded reproducible datasets for peptide extracts obtained from 2 to 100 million cells, with 2016 to 5093 MIPs, respectively. The IP typically provides up to 6.4-fold increase in MIPs compared to the MAE. The comprehensiveness of these immunopeptidome analyses is extended using personalized genomic database of B-cell lymphoblasts, and it is discovered that 0.4% of their respective MIP repertoire harbored nonsynonymous single nucleotide variations (also known as minor histocompatibility antigens, MiHAs).

The SysteMHC Atlas project.

Mass spectrometry (MS)-based immunopeptidomics investigates the repertoire of peptides presented at the cell surface by major histocompatibility complex (MHC) molecules. The broad clinical relevance of MHC-associated peptides, e.g. in precision medicine, provides a strong rationale for the large-scale generation of immunopeptidomic datasets and recent developments in MS-based peptide analysis technologies now support the generation of the required data. Importantly, the availability of diverse immunopeptidomic datasets has resulted in an increasing need to standardize, store and exchange this type of data to enable better collaborations among researchers, to advance the field more efficiently and to establish quality measures required for the meaningful comparison of datasets. Here we present the SysteMHC Atlas (https://systemhcatlas.org), a public database that aims at collecting, organizing, sharing, visualizing and exploring immunopeptidomic data generated by MS. The Atlas includes raw mass spectrometer output files collected from several laboratories around the globe, a catalog of context-specific datasets of MHC class I and class II peptides, standardized MHC allele-specific peptide spectral libraries consisting of consensus spectra calculated from repeat measurements of the same peptide sequence, and links to other proteomics and immunology databases. The SysteMHC Atlas project was created and will be further expanded using a uniform and open computational pipeline that controls the quality of peptide identifications and peptide annotations. Thus, the SysteMHC Atlas disseminates quality controlled immunopeptidomic information to the public domain and serves as a community resource toward the generation of a high-quality comprehensive map of the human immunopeptidome and the support of consistent measurement of immunopeptidomic sample cohorts.

CLMSVault: A Software Suite for Protein Cross-Linking Mass-Spectrometry Data Analysis and Visualization.

Protein cross-linking mass spectrometry (CL-MS) enables the sensitive detection of protein interactions and the inference of protein complex topology. The detection of chemical cross-links between protein residues can identify intra- and interprotein contact sites or provide physical constraints for molecular modeling of protein structure. Recent innovations in cross-linker design, sample preparation, mass spectrometry, and software tools have significantly improved CL-MS approaches. Although a number of algorithms now exist for the identification of cross-linked peptides from mass spectral data, a dearth of user-friendly analysis tools represent a practical bottleneck to the broad adoption of the approach. To facilitate the analysis of CL-MS data, we developed CLMSVault, a software suite designed to leverage existing CL-MS algorithms and provide intuitive and flexible tools for cross-platform data interpretation. CLMSVault stores and combines complementary information obtained from different cross-linkers and search algorithms. CLMSVault provides filtering, comparison, and visualization tools to support CL-MS analyses and includes a workflow for label-free quantification of cross-linked peptides. An embedded 3D viewer enables the visualization of quantitative data and the mapping of cross-linked sites onto PDB structural models. We demonstrate the application of CLMSVault for the analysis of a noncovalent Cdc34-ubiquitin protein complex cross-linked under different conditions. CLMSVault is open-source software (available at https://gitlab.com/courcelm/clmsvault.git ), and a live demo is available at http://democlmsvault.tyerslab.com/ .

MHC class I-associated peptides derive from selective regions of the human genome.

MHC class I-associated peptides (MAPs) define the immune self for CD8+ T lymphocytes and are key targets of cancer immunosurveillance. Here, the goals of our work were to determine whether the entire set of protein-coding genes could generate MAPs and whether specific features influence the ability of discrete genes to generate MAPs. Using proteogenomics, we have identified 25,270 MAPs isolated from the B lymphocytes of 18 individuals who collectively expressed 27 high-frequency HLA-A,B allotypes. The entire MAP repertoire presented by these 27 allotypes covered only 10% of the exomic sequences expressed in B lymphocytes. Indeed, 41% of expressed protein-coding genes generated no MAPs, while 59% of genes generated up to 64 MAPs, often derived from adjacent regions and presented by different allotypes. We next identified several features of transcripts and proteins associated with efficient MAP production. From these data, we built a logistic regression model that predicts with good accuracy whether a gene generates MAPs. Our results show preferential selection of MAPs from a limited repertoire of proteins with distinctive features. The notion that the MHC class I immunopeptidome presents only a small fraction of the protein-coding genome for monitoring by the immune system has profound implications in autoimmunity and cancer immunology.

Gpr161 anchoring of PKA consolidates GPCR and cAMP signaling.

Scaffolding proteins organize the information flow from activated G protein-coupled receptors (GPCRs) to intracellular effector cascades both spatially and temporally. By this means, signaling scaffolds, such as A-kinase anchoring proteins (AKAPs), compartmentalize kinase activity and ensure substrate selectivity. Using a phosphoproteomics approach we identified a physical and functional connection between protein kinase A (PKA) and Gpr161 (an orphan GPCR) signaling. We show that Gpr161 functions as a selective high-affinity AKAP for type I PKA regulatory subunits (RI). Using cell-based reporters to map protein-protein interactions, we discovered that RI binds directly and selectively to a hydrophobic protein-protein interaction interface in the cytoplasmic carboxyl-terminal tail of Gpr161. Furthermore, our data demonstrate that a binary complex between Gpr161 and RI promotes the compartmentalization of Gpr161 to the plasma membrane. Moreover, we show that Gpr161, functioning as an AKAP, recruits PKA RI to primary cilia in zebrafish embryos. We also show that Gpr161 is a target of PKA phosphorylation, and that mutation of the PKA phosphorylation site affects ciliary receptor localization. Thus, we propose that Gpr161 is itself an AKAP and that the cAMP-sensing Gpr161:PKA complex acts as cilium-compartmentalized signalosome, a concept that now needs to be considered in the analyzing, interpreting, and pharmaceutical targeting of PKA-associated functions.

Phosphoproteome dynamics reveal novel ERK1/2 MAP kinase substrates with broad spectrum of functions.

The ERK1/2 MAP kinase pathway is an evolutionarily conserved signaling module that controls many fundamental physiological processes. Deregulated activity of ERK1/2 MAP kinases is associated with developmental syndromes and several human diseases. Despite the importance of this pathway, a comprehensive picture of the natural substrate repertoire and biochemical mechanisms regulated by ERK1/2 is still lacking. In this study, we used large-scale quantitative phosphoproteomics and bioinformatics analyses to identify novel candidate ERK1/2 substrates based on their phosphorylation signature and kinetic profiles in epithelial cells. We identified a total of 7936 phosphorylation sites within 1861 proteins, of which 155 classify as candidate ERK1/2 substrates, including 128 new targets. Candidate ERK1/2 substrates are involved in diverse cellular processes including transcriptional regulation, chromatin remodeling, RNA splicing, cytoskeleton dynamics, cellular junctions and cell signaling. Detailed characterization of one newly identified substrate, the transcriptional regulator JunB, revealed that ERK1/2 phosphorylate JunB on a serine adjacent to the DNA-binding domain, resulting in increased DNA-binding affinity and transcriptional activity. Our study expands the spectrum of cellular functions controlled by ERK1/2 kinases.

Occurrence and detection of phosphopeptide isomers in large-scale phosphoproteomics experiments.

The past decade has been marked by the emergence of selective affinity media and sensitive mass spectrometry instrumentation that facilitated large-scale phosphoproteome analyses and expanded the repertoire of protein phosphorylation. Despite these remarkable advances, the precise location of the phosphorylation site still represents a sizable challenge in view of the labile nature of the phosphoester bond and the presence of neighboring phosphorylatable residues within the same peptide. This difficulty is exacerbated by the combinatorial distribution of phosphorylated residues giving rise to different phosphopeptide isomers. These peptides have similar physicochemical properties, and their separation by LC is often problematic. Few studies have described the frequency and distribution of phosphoisomers in large-scale phosphoproteomics experiments, and no convenient informatics tools currently exist to facilitate their detection. To address this analytical challenge, we developed two algorithms to detect separated and co-eluting phosphopeptide isomers and target their subsequent identification using an inclusion list in LC-MS/MS experiments. Using these algorithms, we determined that the proportion of isomers present in phosphoproteomics studies from mouse, rat, and fly cell extracts represents 3-6% of all identified phosphopeptides. While conventional analysis can identify chromatographically separated phosphopeptides, targeted LC-MS/MS analyses using inclusion lists provided complementary identification and expanded the number of phosphopeptide isomers by at least 52%. Interestingly, these analyses revealed that the occurrence of phosphopeptides isomers can also correlate with the presence of extended phosphorylatable amino acids that can act as a "phosphorylation switch" to bind complementary domains such as those present in SR proteins and ribonucleoprotein complexes.

Phosphorylation network rewiring by gene duplication.

Elucidating how complex regulatory networks have assembled during evolution requires a detailed understanding of the evolutionary dynamics that follow gene duplication events, including changes in post-translational modifications. We compared the phosphorylation profiles of paralogous proteins in the budding yeast Saccharomyces cerevisiae to that of a species that diverged from the budding yeast before the duplication of those genes. We found that 100 million years of post-duplication divergence are sufficient for the majority of phosphorylation sites to be lost or gained in one paralog or the other, with a strong bias toward losses. However, some losses may be partly compensated for by the evolution of other phosphosites, as paralogous proteins tend to preserve similar numbers of phosphosites over time. We also found that up to 50% of kinase-substrate relationships may have been rewired during this period. Our results suggest that after gene duplication, proteins tend to subfunctionalize at the level of post-translational regulation and that even when phosphosites are preserved, there is a turnover of the kinases that phosphorylate them.