1
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Zhang X, Theotokis PI, Li N, Wright CF, Samocha KE, Whiffin N, Ware JS. Genetic constraint at single amino acid resolution in protein domains improves missense variant prioritisation and gene discovery. Genome Med 2024; 16:88. [PMID: 38992748 PMCID: PMC11238507 DOI: 10.1186/s13073-024-01358-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 06/26/2024] [Indexed: 07/13/2024] Open
Abstract
BACKGROUND One of the major hurdles in clinical genetics is interpreting the clinical consequences associated with germline missense variants in humans. Recent significant advances have leveraged natural variation observed in large-scale human populations to uncover genes or genomic regions that show a depletion of natural variation, indicative of selection pressure. We refer to this as "genetic constraint". Although existing genetic constraint metrics have been demonstrated to be successful in prioritising genes or genomic regions associated with diseases, their spatial resolution is limited in distinguishing pathogenic variants from benign variants within genes. METHODS We aim to identify missense variants that are significantly depleted in the general human population. Given the size of currently available human populations with exome or genome sequencing data, it is not possible to directly detect depletion of individual missense variants, since the average expected number of observations of a variant at most positions is less than one. We instead focus on protein domains, grouping homologous variants with similar functional impacts to examine the depletion of natural variations within these comparable sets. To accomplish this, we develop the Homologous Missense Constraint (HMC) score. We utilise the Genome Aggregation Database (gnomAD) 125 K exome sequencing data and evaluate genetic constraint at quasi amino-acid resolution by combining signals across protein homologues. RESULTS We identify one million possible missense variants under strong negative selection within protein domains. Though our approach annotates only protein domains, it nonetheless allows us to assess 22% of the exome confidently. It precisely distinguishes pathogenic variants from benign variants for both early-onset and adult-onset disorders. It outperforms existing constraint metrics and pathogenicity meta-predictors in prioritising de novo mutations from probands with developmental disorders (DD). It is also methodologically independent of these, adding power to predict variant pathogenicity when used in combination. We demonstrate utility for gene discovery by identifying seven genes newly significantly associated with DD that could act through an altered-function mechanism. CONCLUSIONS Grouping variants of comparable functional impacts is effective in evaluating their genetic constraint. HMC is a novel and accurate predictor of missense consequence for improved variant interpretation.
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Affiliation(s)
- Xiaolei Zhang
- National Heart & Lung Institute, Imperial College London, London, UK.
- MRC Laboratory of Medical Sciences, Imperial College London, London, UK.
- Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, UK.
- Present address: European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, UK.
| | - Pantazis I Theotokis
- National Heart & Lung Institute, Imperial College London, London, UK
- MRC Laboratory of Medical Sciences, Imperial College London, London, UK
- Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, UK
| | - Nicholas Li
- National Heart & Lung Institute, Imperial College London, London, UK
- MRC Laboratory of Medical Sciences, Imperial College London, London, UK
- Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, UK
| | - Caroline F Wright
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter, UK
| | - Kaitlin E Samocha
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nicola Whiffin
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Centre for Human Genetics, University of Oxford, Oxford, UK.
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
| | - James S Ware
- National Heart & Lung Institute, Imperial College London, London, UK.
- MRC Laboratory of Medical Sciences, Imperial College London, London, UK.
- Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, UK.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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2
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Cruz-Mireles N, Osés-Ruiz M, Derbyshire P, Jégousse C, Ryder LS, Bautista MJA, Eseola A, Sklenar J, Tang B, Yan X, Ma W, Findlay KC, Were V, MacLean D, Talbot NJ, Menke FLH. The phosphorylation landscape of infection-related development by the rice blast fungus. Cell 2024; 187:2557-2573.e18. [PMID: 38729111 DOI: 10.1016/j.cell.2024.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 02/02/2024] [Accepted: 04/10/2024] [Indexed: 05/12/2024]
Abstract
Many of the world's most devastating crop diseases are caused by fungal pathogens that elaborate specialized infection structures to invade plant tissue. Here, we present a quantitative mass-spectrometry-based phosphoproteomic analysis of infection-related development by the rice blast fungus Magnaporthe oryzae, which threatens global food security. We mapped 8,005 phosphosites on 2,062 fungal proteins following germination on a hydrophobic surface, revealing major re-wiring of phosphorylation-based signaling cascades during appressorium development. Comparing phosphosite conservation across 41 fungal species reveals phosphorylation signatures specifically associated with biotrophic and hemibiotrophic fungal infection. We then used parallel reaction monitoring (PRM) to identify phosphoproteins regulated by the fungal Pmk1 MAPK that controls plant infection by M. oryzae. We define 32 substrates of Pmk1 and show that Pmk1-dependent phosphorylation of regulator Vts1 is required for rice blast disease. Defining the phosphorylation landscape of infection therefore identifies potential therapeutic interventions for the control of plant diseases.
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Affiliation(s)
- Neftaly Cruz-Mireles
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK
| | - Miriam Osés-Ruiz
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK
| | - Paul Derbyshire
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK
| | - Clara Jégousse
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK
| | - Lauren S Ryder
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK
| | - Mark Jave A Bautista
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK
| | - Alice Eseola
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK
| | - Jan Sklenar
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK
| | - Bozeng Tang
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK
| | - Xia Yan
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK
| | - Weibin Ma
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK
| | - Kim C Findlay
- Department of Cell and Developmental Biology, The John Innes Centre, Norwich Research Park, Norwich NR4 7UH, UK
| | - Vincent Were
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK
| | - Dan MacLean
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK
| | - Nicholas J Talbot
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK.
| | - Frank L H Menke
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich NR4 7UH, UK.
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3
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Zhang G, Zhang C, Cai M, Luo C, Zhu F, Liang Z. FuncPhos-STR: An integrated deep neural network for functional phosphosite prediction based on AlphaFold protein structure and dynamics. Int J Biol Macromol 2024; 266:131180. [PMID: 38552697 DOI: 10.1016/j.ijbiomac.2024.131180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 03/19/2024] [Accepted: 03/26/2024] [Indexed: 04/01/2024]
Abstract
Phosphorylation modifications play important regulatory roles in most biological processes. However, the functional assignment for the vast majority of the identified phosphosites remains a major challenge. Here, we provide a deep learning framework named FuncPhos-STR as an online resource, for functional prediction and structural visualization of human proteome-level phosphosites. Based on our reported FuncPhos-SEQ framework, which was built by integrating phosphosite sequence evolution and protein-protein interaction (PPI) information, FuncPhos-STR was developed by further integrating the structural and dynamics information on AlphaFold protein structures. The characterized structural topology and dynamics features underlying functional phosphosites emphasized their molecular mechanism for regulating protein functions. By integrating the structural and dynamics, sequence evolutionary, and PPI network features from protein different dimensions, FuncPhos-STR has advantage over other reported models, with the best AUC value of 0.855. Using FuncPhos-STR, the phosphosites inside the pocket regions are accessible to higher functional scores, theoretically supporting their potential regulatory mechanism. Overall, FuncPhos-STR would accelerate the functional identification of huge unexplored phosphosites, and facilitate the elucidation of their allosteric regulation mechanisms. The web server of FuncPhos-STR is freely available at http://funcptm.jysw.suda.edu.cn/str.
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Affiliation(s)
- Guangyu Zhang
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China
| | - Cai Zhang
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China
| | - Mingyue Cai
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Cheng Luo
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Fei Zhu
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
| | - Zhongjie Liang
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China; Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Soochow University, Suzhou 215123, China.
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4
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Sexton JA, Potchernikov T, Bibeau JP, Casanova-Sepúlveda G, Cao W, Lou HJ, Boggon TJ, De La Cruz EM, Turk BE. Distinct functional constraints driving conservation of the cofilin N-terminal regulatory tail. Nat Commun 2024; 15:1426. [PMID: 38365893 PMCID: PMC10873347 DOI: 10.1038/s41467-024-45878-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 02/06/2024] [Indexed: 02/18/2024] Open
Abstract
Cofilin family proteins have essential roles in remodeling the cytoskeleton through filamentous actin depolymerization and severing. The short, unstructured N-terminal region of cofilin is critical for actin binding and harbors the major site of inhibitory phosphorylation. Atypically for a disordered sequence, the N-terminal region is highly conserved, but specific aspects driving this conservation are unclear. Here, we screen a library of 16,000 human cofilin N-terminal sequence variants for their capacity to support growth in S. cerevisiae in the presence or absence of the upstream regulator LIM kinase. Results from the screen and biochemical analysis of individual variants reveal distinct sequence requirements for actin binding and regulation by LIM kinase. LIM kinase recognition only partly explains sequence constraints on phosphoregulation, which are instead driven to a large extent by the capacity for phosphorylation to inactivate cofilin. We find loose sequence requirements for actin binding and phosphoinhibition, but collectively they restrict the N-terminus to sequences found in natural cofilins. Our results illustrate how a phosphorylation site can balance potentially competing sequence requirements for function and regulation.
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Affiliation(s)
- Joel A Sexton
- Department of Pharmacology, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Tony Potchernikov
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jeffrey P Bibeau
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | | | - Wenxiang Cao
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Hua Jane Lou
- Department of Pharmacology, Yale School of Medicine, New Haven, CT, 06520, USA
| | - Titus J Boggon
- Department of Pharmacology, Yale School of Medicine, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Enrique M De La Cruz
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Benjamin E Turk
- Department of Pharmacology, Yale School of Medicine, New Haven, CT, 06520, USA.
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5
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Ilyas M, Rahman A, Khan NH, Haroon M, Hussain H, Rehman L, Alam M, Rauf A, Waggas DS, Bawazeer S. Analysis of Germin-like protein genes family in Vitis vinifera (VvGLPs) using various in silico approaches. BRAZ J BIOL 2024; 84:e256732. [DOI: 10.1590/1519-6984.256732] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 12/28/2021] [Indexed: 12/26/2022] Open
Abstract
Abstract Germin-like proteins (GLPs) play an important role against various stresses. Vitis vinifera L. genome contains 7 GLPs; many of them are functionally unexplored. However, the computational analysis may provide important new insight into their function. Currently, physicochemical properties, subcellular localization, domain architectures, 3D structures, N-glycosylation & phosphorylation sites, and phylogeney of the VvGLPs were investigated using the latest computational tools. Their functions were predicted using the Search tool for the retrieval of interacting genes/proteins (STRING) and Blast2Go servers. Most of the VvGLPs were extracellular (43%) in nature but also showed periplasmic (29%), plasma membrane (14%), and mitochondrial- or chloroplast-specific (14%) expression. The functional analysis predicted unique enzymatic activities for these proteins including terpene synthase, isoprenoid synthase, lipoxygenase, phosphate permease, receptor kinase, and hydrolases generally mediated by Mn+ cation. VvGLPs showed similarity in the overall structure, shape, and position of the cupin domain. Functionally, VvGLPs control and regulate the production of secondary metabolites to cope with various stresses. Phylogenetically VvGLP1, -3, -4, -5, and VvGLP7 showed greater similarity due to duplication while VvGLP2 and VvGLP6 revealed a distant relationship. Promoter analysis revealed the presence of diverse cis-regulatory elements among which CAAT box, MYB, MYC, unnamed-4 were common to all of them. The analysis will help to utilize VvGLPs and their promoters in future food programs by developing resistant cultivars against various biotic (Erysiphe necator and in Powdery Mildew etc.) and abiotic (Salt, drought, heat, dehydration, etc.) stresses.
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Affiliation(s)
| | | | | | | | | | | | - M. Alam
- University of Swabi, Pakistan
| | - A. Rauf
- University of Swabi, Pakistan
| | - D. S. Waggas
- Fakeeh College of Medical Sciences, Saudi Arabia
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6
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Xi S, Ban X, Kong H, Li C, Gu Z, Li Z. Conserved residues at the family and subfamily levels determine enzyme activity and substrate binding in glycoside hydrolase family 13. Int J Biol Macromol 2023; 253:126980. [PMID: 37729992 DOI: 10.1016/j.ijbiomac.2023.126980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 08/24/2023] [Accepted: 09/16/2023] [Indexed: 09/22/2023]
Abstract
Site-directed mutagenesis is a valuable strategy for modifying enzymes, but the lack of understanding of conserved residues regulating glycosidase function hinders enzyme design. We analyzed 1662 enzyme sequences to identify conserved amino acids in maltohexaose-forming amylase at both family and subfamily levels. Several conserved residues at the family level (G37, P45, R52, Y57, D101, V103, H106, G230, R232, D234, E264, H330, D331, and G360) were found, mutations of which resulted in reduced enzyme activity or inactivation. At the subfamily level, several conserved residues (L65, E67, F68, D111, E114, R126, R147, F154, W156, F161, G163, D165, W218H, V342, W345, and F346) were identified, which primarily facilitate substrate binding in the enzyme's active site, as shown by molecular dynamics and kinetic assays. Our findings provide critical insights into conserved residues essential for catalysis and can inform targeted enzyme design in protein engineering.
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Affiliation(s)
- Shixia Xi
- School of Food Science and Technology, Jiangnan University, Wuxi 214122, People's Republic of China
| | - Xiaofeng Ban
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, People's Republic of China; School of Food Science and Technology, Jiangnan University, Wuxi 214122, People's Republic of China; Collaborative Innovation Center of Food Safety and Quality Control, Jiangnan University, Wuxi 214122, People's Republic of China
| | - Haocun Kong
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, People's Republic of China; School of Food Science and Technology, Jiangnan University, Wuxi 214122, People's Republic of China
| | - Caiming Li
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, People's Republic of China; School of Food Science and Technology, Jiangnan University, Wuxi 214122, People's Republic of China; Collaborative Innovation Center of Food Safety and Quality Control, Jiangnan University, Wuxi 214122, People's Republic of China
| | - Zhengbiao Gu
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, People's Republic of China; School of Food Science and Technology, Jiangnan University, Wuxi 214122, People's Republic of China; Collaborative Innovation Center of Food Safety and Quality Control, Jiangnan University, Wuxi 214122, People's Republic of China
| | - Zhaofeng Li
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, People's Republic of China; School of Food Science and Technology, Jiangnan University, Wuxi 214122, People's Republic of China; Collaborative Innovation Center of Food Safety and Quality Control, Jiangnan University, Wuxi 214122, People's Republic of China.
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7
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Skinnider MA, Akinlaja MO, Foster LJ. Mapping protein states and interactions across the tree of life with co-fractionation mass spectrometry. Nat Commun 2023; 14:8365. [PMID: 38102123 PMCID: PMC10724252 DOI: 10.1038/s41467-023-44139-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Accepted: 12/01/2023] [Indexed: 12/17/2023] Open
Abstract
We present CFdb, a harmonized resource of interaction proteomics data from 411 co-fractionation mass spectrometry (CF-MS) datasets spanning 21,703 fractions. Meta-analysis of this resource charts protein abundance, phosphorylation, and interactions throughout the tree of life, including a reference map of the human interactome. We show how large-scale CF-MS data can enhance analyses of individual CF-MS datasets, and exemplify this strategy by mapping the honey bee interactome.
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Affiliation(s)
- Michael A Skinnider
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
- Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
- Ludwig Institute for Cancer Research, Princeton University, Princeton, NJ, USA
| | - Mopelola O Akinlaja
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
- Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, Canada
| | - Leonard J Foster
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada.
- Department of Biochemistry and Molecular Biology, University of British Columbia, Vancouver, BC, Canada.
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8
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Hu H, He B, He M, Tao H, Li B. A glycosylation-related signature predicts survival in pancreatic cancer. Aging (Albany NY) 2023; 15:13710-13737. [PMID: 38048216 PMCID: PMC10756102 DOI: 10.18632/aging.205258] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 10/19/2023] [Indexed: 12/06/2023]
Abstract
BACKGROUND Tumor initiation and progression are closely associated with glycosylation. However, glycosylated molecules have not been the subject of extensive studies as prognostic markers for pancreatic cancer. The objectives of this study were to identify glycosylation-related genes in pancreatic cancer and use them to construct reliable prognostic models. MATERIALS AND METHODS The Cancer Genome Atlas and Gene Expression Omnibus databases were used to assess the differential expression of glycosylation-related genes; four clusters were identified based on consistent clustering analysis. Kaplan-Meier analyses identified three glycosylation-related genes associated with overall survival. LASSO analysis was then performed on The Cancer Genome Atlas and International Cancer Genome Consortium databases to identify glycosylation-related signatures. We identified 12 GRGs differently expressed in pancreatic cancer and selected three genes (SEL1L, TUBA1C, and SDC1) to build a prognostic model. Thereafter, patients were divided into high and low-risk groups. Eventually, we performed Quantitative real-time PCR (qRT-PCR) to validate the signature. RESULTS Clinical outcomes were significantly poorer in the high-risk group than in the low-risk group. There were also significant correlations between the high-risk group and several risk factors, including no-smoking history, drinking history, radiotherapy history, and lower tumor grade. Furthermore, the high-risk group had a higher proportion of immune cells. Eventually, three glycosylation-related genes were validated in human PC cell lines. CONCLUSION This study identified the glycosylation-related signature for pancreatic cancer. It is an effective predictor of survival and can guide treatment decisions.
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Affiliation(s)
- Huidong Hu
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
| | - Bingsheng He
- Department of Oncology, The Affiliated Hospital of Southwest Medical University, Luzhou 646000, China
| | - Mingang He
- Department of Gastrointestinal Surgery, Shandong Tumor Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China
| | - Hengmin Tao
- Department of Head and Neck Radiotherapy, Shandong Provincial ENT Hospital, Shandong University, Jinan 250117, China
| | - Baosheng Li
- Department of Radiation Oncology, Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan 250117, China
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9
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Liang Z, Liu T, Li Q, Zhang G, Zhang B, Du X, Liu J, Chen Z, Ding H, Hu G, Lin H, Zhu F, Luo C. Deciphering the functional landscape of phosphosites with deep neural network. Cell Rep 2023; 42:113048. [PMID: 37659078 DOI: 10.1016/j.celrep.2023.113048] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/11/2023] [Accepted: 08/11/2023] [Indexed: 09/04/2023] Open
Abstract
Current biochemical approaches have only identified the most well-characterized kinases for a tiny fraction of the phosphoproteome, and the functional assignments of phosphosites are almost negligible. Herein, we analyze the substrate preference catalyzed by a specific kinase and present a novel integrated deep neural network model named FuncPhos-SEQ for functional assignment of human proteome-level phosphosites. FuncPhos-SEQ incorporates phosphosite motif information from a protein sequence using multiple convolutional neural network (CNN) channels and network features from protein-protein interactions (PPIs) using network embedding and deep neural network (DNN) channels. These concatenated features are jointly fed into a heterogeneous feature network to prioritize functional phosphosites. Combined with a series of in vitro and cellular biochemical assays, we confirm that NADK-S48/50 phosphorylation could activate its enzymatic activity. In addition, ERK1/2 are discovered as the primary kinases responsible for NADK-S48/50 phosphorylation. Moreover, FuncPhos-SEQ is developed as an online server.
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Affiliation(s)
- Zhongjie Liang
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China; Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Soochow University, Suzhou 215123, China
| | - Tonghai Liu
- Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Zhongshan 528437, China; State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Qi Li
- Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Zhongshan 528437, China; State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Guangyu Zhang
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China
| | - Bei Zhang
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Xikun Du
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Jingqiu Liu
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Zhifeng Chen
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Hong Ding
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China; Jiangsu Province Engineering Research Center of Precision Diagnostics and Therapeutics Development, Soochow University, Suzhou 215123, China
| | - Hao Lin
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China
| | - Fei Zhu
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China.
| | - Cheng Luo
- Zhongshan Institute for Drug Discovery, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Zhongshan 528437, China; State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, 555 Zuchongzhi Road, Shanghai 201203, China; School of Pharmaceutical Science and Technology, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China; School of Life Science and Technology, Shanghai Tech University, 100 Haike Road, Shanghai 201210, China; School of Pharmacy, Fujian Medical University, Fuzhou 350122, China.
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10
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Liang X, Yadav SP, Batz ZA, Nellissery J, Swaroop A. Protein kinase CK2 modulates the activity of Maf-family bZIP transcription factor NRL in rod photoreceptors of mammalian retina. Hum Mol Genet 2023; 32:948-958. [PMID: 36226585 PMCID: PMC9991000 DOI: 10.1093/hmg/ddac256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 09/21/2022] [Accepted: 10/07/2022] [Indexed: 11/14/2022] Open
Abstract
Maf-family basic motif leucine zipper protein NRL specifies rod photoreceptor cell fate during retinal development and, in concert with homeodomain protein CRX and other regulatory factors, controls the expression of most rod-expressed genes including the visual pigment gene Rhodopsin (Rho). Transcriptional regulatory activity of NRL is modulated by post-translational modifications, especially phosphorylation, and mutations at specific phosphosites can lead to retinal degeneration. During our studies to elucidate NRL-mediated transcriptional regulation, we identified protein kinase CK2 in NRL-enriched complexes bound to Rho promoter-enhancer regions and in NRL-enriched high molecular mass fractions from the bovine retina. The presence of CK2 in NRL complexes was confirmed by co-immunoprecipitation from developing and adult mouse retinal extracts. In vitro kinase assay and bioinformatic analysis indicated phosphorylation of NRL at Ser117 residue by CK2. Co-transfection of Csnk2a1 cDNA encoding murine CK2 with human NRL and CRX reduced the bovine Rho promoter-driven luciferase expression in HEK293 cells and mutagenesis of NRL-Ser117 residue to Ala restored the reporter gene activity. In concordance, overexpression of CK2 in the mouse retina in vivo by electroporation resulted in reduction of Rho promoter-driven DsRed reporter expression as well as the transcript level of many phototransduction genes. Thus, our studies demonstrate that CK2 can phosphorylate Ser117 of NRL. Modulation of NRL activity by CK2 suggests intricate interdependence of transcriptional and signaling pathways in maintaining rod homeostasis.
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Affiliation(s)
- Xulong Liang
- Neurobiology-Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, 6 Center Drive, MSC0610, Bethesda, MD 20892, USA
| | - Sharda P Yadav
- Neurobiology-Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, 6 Center Drive, MSC0610, Bethesda, MD 20892, USA
| | - Zachary A Batz
- Neurobiology-Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, 6 Center Drive, MSC0610, Bethesda, MD 20892, USA
| | - Jacob Nellissery
- Neurobiology-Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, 6 Center Drive, MSC0610, Bethesda, MD 20892, USA
| | - Anand Swaroop
- Neurobiology-Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, 6 Center Drive, MSC0610, Bethesda, MD 20892, USA
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11
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Xiao D, Chen C, Yang P. Computational systems approach towards phosphoproteomics and their downstream regulation. Proteomics 2023; 23:e2200068. [PMID: 35580145 DOI: 10.1002/pmic.202200068] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 04/26/2022] [Accepted: 05/03/2022] [Indexed: 11/07/2022]
Abstract
Protein phosphorylation plays an essential role in modulating cell signalling and its downstream transcriptional and translational regulations. Until recently, protein phosphorylation has been studied mostly using low-throughput biochemical assays. The advancement of mass spectrometry (MS)-based phosphoproteomics transformed the field by enabling measurement of proteome-wide phosphorylation events, where tens of thousands of phosphosites are routinely identified and quantified in an experiment. This has brought a significant challenge in analysing large-scale phosphoproteomic data, making computational methods and systems approaches integral parts of phosphoproteomics. Previous works have primarily focused on reviewing the experimental techniques in MS-based phosphoproteomics, yet a systematic survey of the computational landscape in this field is still missing. Here, we review computational methods and tools, and systems approaches that have been developed for phosphoproteomics data analysis. We categorise them into four aspects including data processing, functional analysis, phosphoproteome annotation and their integration with other omics, and in each aspect, we discuss the key methods and example studies. Lastly, we highlight some of the potential research directions on which future work would make a significant contribution to this fast-growing field. We hope this review provides a useful snapshot of the field of computational systems phosphoproteomics and stimulates new research that drives future development.
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Affiliation(s)
- Di Xiao
- Computational Systems Biology Group, Children's Medical Research Institute, The University of Sydney, Westmead, New South Wales, Australia.,Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Carissa Chen
- Computational Systems Biology Group, Children's Medical Research Institute, The University of Sydney, Westmead, New South Wales, Australia.,Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - Pengyi Yang
- Computational Systems Biology Group, Children's Medical Research Institute, The University of Sydney, Westmead, New South Wales, Australia.,Charles Perkins Centre, The University of Sydney, Sydney, New South Wales, Australia.,School of Mathematics and Statistics, The University of Sydney, Sydney, New South Wales, Australia
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12
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Pasquier C, Robichon A. Evolutionary Divergence of Phosphorylation to Regulate Interactive Protein Networks in Lower and Higher Species. Int J Mol Sci 2022; 23:ijms232214429. [PMID: 36430905 PMCID: PMC9697241 DOI: 10.3390/ijms232214429] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 11/15/2022] [Accepted: 11/17/2022] [Indexed: 11/22/2022] Open
Abstract
The phosphorylation of proteins affects their functions in extensively documented circumstances. However, the role of phosphorylation in many interactive networks of proteins remains very elusive due to the experimental limits of exploring the transient interaction in a large complex of assembled proteins induced by stimulation. Previous studies have suggested that phosphorylation is a recent evolutionary process that differently regulates ortholog proteins in numerous lineages of living organisms to create new functions. Despite the fact that numerous phospho-proteins have been compared between species, little is known about the organization of the full phospho-proteome, the role of phosphorylation to orchestrate large interactive networks of proteins, and the intertwined phospho-landscape in these networks. In this report, we aimed to investigate the acquired role of phosphate addition in the phenomenon of protein networking in different orders of living organisms. Our data highlighted the acquired status of phosphorylation in organizing large, connected assemblages in Homo sapiens. The protein networking guided by phosphorylation turned out to be prominent in humans, chaotic in yeast, and weak in flies. Furthermore, the molecular functions of GO annotation enrichment regulated by phosphorylation were found to be drastically different between flies, yeast, and humans, suggesting an evolutionary drift specific to each species.
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Affiliation(s)
- Claude Pasquier
- I3S, Université Côte d’Azur, Campus SophiaTech, CNRS, 06903 Nice, France
- Correspondence:
| | - Alain Robichon
- INRAE, ISA, Université Côte d’Azur, Campus SophiaTech, CNRS, 06903 Nice, France
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13
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Garza-Domínguez R, Torres-Quiroz F. Evolutionary Signals in Coronaviral Structural Proteins Suggest Possible Complex Mechanisms of Post-Translational Regulation in SARS-CoV-2 Virus. Viruses 2022; 14:v14112469. [PMID: 36366566 PMCID: PMC9696223 DOI: 10.3390/v14112469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/18/2022] [Accepted: 10/31/2022] [Indexed: 11/11/2022] Open
Abstract
Post-translational regulation of proteins has emerged as a central topic of research in the field of functional proteomics. Post-translational modifications (PTMs) dynamically control the activities of proteins and are involved in a wide range of biological processes. Crosstalk between different types of PTMs represents a key mechanism of regulation and signaling. Due to the current pandemic of the novel and dangerous SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) virus, here we present an in silico analysis of different types of PTMs in structural proteins of coronaviruses. A dataset of PTM sites was studied at three levels: conservation analysis, mutational analysis and crosstalk analysis. We identified two sets of PTMs which could have important functional roles in the regulation of the structural proteins of coronaviruses. Additionally, we found seven interesting signals of potential crosstalk events. These results reveal a higher level of complexity in the mechanisms of post-translational regulation of coronaviral proteins and provide new insights into the adaptation process of the SARS-CoV-2 virus.
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14
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Aguoru NA, Kirk RS, Walker AJ. Molecular insights into the heat shock proteins of the human parasitic blood fluke Schistosoma mansoni. Parasit Vectors 2022; 15:365. [PMID: 36229862 PMCID: PMC9559072 DOI: 10.1186/s13071-022-05500-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 09/16/2022] [Indexed: 11/22/2022] Open
Abstract
Background Heat shock proteins (HSPs) are evolutionarily conserved proteins, produced by cells in response to hostile environmental conditions, that are vital to organism homeostasis. Here, we undertook the first detailed molecular bioinformatic analysis of these important proteins and mapped their tissue expression in the human parasitic blood fluke, Schistosoma mansoni, one of the causative agents of the neglected tropical disease human schistosomiasis. Methods Using bioinformatic tools we classified and phylogenetically analysed HSP family members in schistosomes, and performed transcriptomic, phosphoproteomic, and interactomic analysis of the S. mansoni HSPs. In addition, S. mansoni HSP protein expression was mapped in intact parasites using immunofluorescence. Results Fifty-five HSPs were identified in S. mansoni across five HSP families; high conservation of HSP sequences were apparent across S. mansoni, Schistosoma haematobium and Schistosoma japonicum, with S. haematobium HSPs showing greater similarity to S. mansoni than those of S. japonicum. For S. mansoni, differential HSP gene expression was evident across the various parasite life stages, supporting varying roles for the HSPs in the different stages, and suggesting that they might confer some degree of protection during life stage transitions. Protein expression patterns of HSPs were visualised in intact S. mansoni cercariae, 3 h and 24 h somules, and adult male and female worms, revealing HSPs in the tegument, cephalic ganglia, tubercles, testes, ovaries as well as other important organs. Analysis of putative HSP protein-protein associations highlighted proteins that are involved in transcription, modification, stability, and ubiquitination; functional enrichment analysis revealed functions for HSP networks in S. mansoni including protein export for HSP 40/70, and FOXO/mTOR signalling for HSP90 networks. Finally, a total of 76 phosphorylation sites were discovered within 17 of the 55 HSPs, with 30 phosphorylation sites being conserved with those of human HSPs, highlighting their likely core functional significance. Conclusions This analysis highlights the fascinating biology of S. mansoni HSPs and their likely importance to schistosome function, offering a valuable and novel framework for future physiological investigations into the roles of HSPs in schistosomes, particularly in the context of survival in the host and with the aim of developing novel anti-schistosome therapeutics. Supplementary Information The online version contains supplementary material available at 10.1186/s13071-022-05500-7.
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Affiliation(s)
- Nancy A Aguoru
- Molecular Parasitology Laboratory, School of Life Sciences, Pharmacy and Chemistry, Kingston University, Penrhyn Road, Kingston upon Thames, KT1 2EE, Surrey, UK
| | - Ruth S Kirk
- Molecular Parasitology Laboratory, School of Life Sciences, Pharmacy and Chemistry, Kingston University, Penrhyn Road, Kingston upon Thames, KT1 2EE, Surrey, UK
| | - Anthony J Walker
- Molecular Parasitology Laboratory, School of Life Sciences, Pharmacy and Chemistry, Kingston University, Penrhyn Road, Kingston upon Thames, KT1 2EE, Surrey, UK.
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15
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Zhu F, Yang S, Meng F, Zheng Y, Ku X, Luo C, Hu G, Liang Z. Leveraging Protein Dynamics to Identify Functional Phosphorylation Sites using Deep Learning Models. J Chem Inf Model 2022; 62:3331-3345. [PMID: 35816597 DOI: 10.1021/acs.jcim.2c00484] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Accurate prediction of post-translational modifications (PTMs) is of great significance in understanding cellular processes, by modulating protein structure and dynamics. Nowadays, with the rapid growth of protein data at different "omics" levels, machine learning models largely enriched the prediction of PTMs. However, most machine learning models only rely on protein sequence and little structural information. The lack of the systematic dynamics analysis underlying PTMs largely limits the PTM functional predictions. In this research, we present two dynamics-centric deep learning models, namely, cDL-PAU and cDL-FuncPhos, by incorporating sequence, structure, and dynamics-based features to elucidate the molecular basis and underlying functional landscape of PTMs. cDL-PAU achieved satisfactory area under the curve (AUC) scores of 0.804-0.888 for predicting phosphorylation, acetylation, and ubiquitination (PAU) sites, while cDL-FuncPhos achieved an AUC value of 0.771 for predicting functional phosphorylation (FuncPhos) sites, displaying reliable improvements. Through a feature selection, the dynamics-based coupling and commute ability show large contributions in discovering PAU sites and FuncPhos sites, suggesting the allosteric propensity for important PTMs. The application of cDL-FuncPhos in three oncoproteins not only corroborates its strong performance in FuncPhos prioritization but also gains insight into the physical basis for the functions. The source code and data set of cDL-PAU and cDL-FuncPhos are available at https://github.com/ComputeSuda/PTM_ML.
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Affiliation(s)
- Fei Zhu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China.,School of Computer Science and Technology, Soochow University, Suzhou 215006, China
| | - Sijie Yang
- School of Computer Science and Technology, Soochow University, Suzhou 215006, China
| | - Fanwang Meng
- Department of Chemistry and Chemical Biology, McMaster University, Hamilton L8S 4L8, Ontario, Canada
| | - Yuxiang Zheng
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Xin Ku
- Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Cheng Luo
- State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Guang Hu
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China
| | - Zhongjie Liang
- Center for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215123, China.,Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China.,State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
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16
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Ramasamy P, Vandermarliere E, Vranken WF, Martens L. Panoramic Perspective on Human Phosphosites. J Proteome Res 2022; 21:1894-1915. [PMID: 35793420 DOI: 10.1021/acs.jproteome.2c00164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Protein phosphorylation is the most common reversible post-translational modification of proteins and is key in the regulation of many cellular processes. Due to this importance, phosphorylation is extensively studied, resulting in the availability of a large amount of mass spectrometry-based phospho-proteomics data. Here, we leverage the information in these large-scale phospho-proteomics data sets, as contained in Scop3P, to analyze and characterize proteome-wide protein phosphorylation sites (P-sites). First, we set out to differentiate correctly observed P-sites from false-positive sites using five complementary site properties. We then describe the context of these P-sites in terms of the protein structure, solvent accessibility, structural transitions and disorder, and biophysical properties. We also investigate the relative prevalence of disease-linked mutations on and around P-sites. Moreover, we assess the structural dynamics of P-sites in their phosphorylated and unphosphorylated states. As a result, we show how large-scale reprocessing of available proteomics experiments can enable a more reliable view on proteome-wide P-sites. Furthermore, adding the structural context of proteins around P-sites helps uncover possible conformational switches upon phosphorylation. Moreover, by placing sites in different biophysical contexts, we show the differential preference in protein dynamics at phosphorylated sites when compared to the nonphosphorylated counterparts.
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Affiliation(s)
- Pathmanaban Ramasamy
- VIB-UGent Center for Medical Biotechnology, VIB, 9000 Ghent, Belgium.,Department of Biomolecular Medicine, Faculty of Health Sciences and Medicine, Ghent University, 9000 Ghent, Belgium.,Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, 1050 Brussels, Belgium.,Structural Biology Brussels, Vrije Universiteit Brussel, 1050 Brussels, Belgium.,Centre for Structural Biology, VIB, 1050 Brussels, Belgium
| | | | - Wim F Vranken
- Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, 1050 Brussels, Belgium.,Structural Biology Brussels, Vrije Universiteit Brussel, 1050 Brussels, Belgium.,Centre for Structural Biology, VIB, 1050 Brussels, Belgium
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, VIB, 9000 Ghent, Belgium.,Department of Biomolecular Medicine, Faculty of Health Sciences and Medicine, Ghent University, 9000 Ghent, Belgium
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17
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Trafficking regulator of GLUT4-1 (TRARG1) is a GSK3 substrate. Biochem J 2022; 479:1237-1256. [PMID: 35594055 PMCID: PMC9284383 DOI: 10.1042/bcj20220153] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 05/12/2022] [Accepted: 05/20/2022] [Indexed: 12/19/2022]
Abstract
Trafficking regulator of GLUT4-1, TRARG1, positively regulates insulin-stimulated GLUT4 trafficking and insulin sensitivity. However, the mechanism(s) by which this occurs remain(s) unclear. Using biochemical and mass spectrometry analyses we found that TRARG1 is dephosphorylated in response to insulin in a PI3K/Akt-dependent manner and is a novel substrate for GSK3. Priming phosphorylation of murine TRARG1 at serine 84 allows for GSK3-directed phosphorylation at serines 72, 76 and 80. A similar pattern of phosphorylation was observed in human TRARG1, suggesting that our findings are translatable to human TRARG1. Pharmacological inhibition of GSK3 increased cell surface GLUT4 in cells stimulated with a submaximal insulin dose, and this was impaired following Trarg1 knockdown, suggesting that TRARG1 acts as a GSK3-mediated regulator in GLUT4 trafficking. These data place TRARG1 within the insulin signaling network and provide insights into how GSK3 regulates GLUT4 trafficking in adipocytes.
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18
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Wolff DW, Deng Z, Bianchi-Smiraglia A, Foley CE, Han Z, Wang X, Shen S, Rosenberg MM, Moparthy S, Yun DH, Chen J, Baker BK, Roll MV, Magiera AJ, Li J, Hurley E, Feltri ML, Cox AO, Lee J, Furdui CM, Liu L, Bshara W, LaConte LE, Kandel ES, Pasquale EB, Qu J, Hedstrom L, Nikiforov MA. Phosphorylation of guanosine monophosphate reductase triggers a GTP-dependent switch from pro- to anti-oncogenic function of EPHA4. Cell Chem Biol 2022; 29:970-984.e6. [PMID: 35148834 PMCID: PMC9620470 DOI: 10.1016/j.chembiol.2022.01.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Revised: 11/19/2021] [Accepted: 01/11/2022] [Indexed: 12/11/2022]
Abstract
Signal transduction pathways post-translationally regulating nucleotide metabolism remain largely unknown. Guanosine monophosphate reductase (GMPR) is a nucleotide metabolism enzyme that decreases GTP pools by converting GMP to IMP. We observed that phosphorylation of GMPR at Tyr267 is critical for its activity and found that this phosphorylation by ephrin receptor tyrosine kinase EPHA4 decreases GTP pools in cell protrusions and levels of GTP-bound RAC1. EPHs possess oncogenic and tumor-suppressor activities, although the mechanisms underlying switches between these two modes are poorly understood. We demonstrated that GMPR plays a key role in EPHA4-mediated RAC1 suppression. This supersedes GMPR-independent activation of RAC1 by EPHA4, resulting in a negative overall effect on melanoma cell invasion and tumorigenicity. Accordingly, EPHA4 levels increase during melanoma progression and inversely correlate with GMPR levels in individual melanoma tumors. Therefore, phosphorylation of GMPR at Tyr267 is a metabolic signal transduction switch controlling GTP biosynthesis and transformed phenotypes.
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Affiliation(s)
- David W. Wolff
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA,Department of Cancer Biology, Wake Forest School of Medicine, Winston Salem, NC 27157, USA
| | - Zhiyong Deng
- Department of Cancer Biology, Wake Forest School of Medicine, Winston Salem, NC 27157, USA
| | - Anna Bianchi-Smiraglia
- Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, USA
| | - Colleen E. Foley
- Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, USA
| | - Zhannan Han
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA,Department of Cancer Biology, Wake Forest School of Medicine, Winston Salem, NC 27157, USA
| | - Xingyou Wang
- Department of Chemistry, Brandeis University, Waltham, MA 02453, USA
| | - Shichen Shen
- Department of Pharmaceutical Sciences, University at Buffalo, Buffalo, NY 14214, USA
| | | | - Sudha Moparthy
- Department of Cancer Biology, Wake Forest School of Medicine, Winston Salem, NC 27157, USA
| | - Dong Hyun Yun
- Department of Cancer Biology, Wake Forest School of Medicine, Winston Salem, NC 27157, USA
| | - Jialin Chen
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA,Department of Cancer Biology, Wake Forest School of Medicine, Winston Salem, NC 27157, USA
| | - Brian K. Baker
- Department of Cancer Biology, Wake Forest School of Medicine, Winston Salem, NC 27157, USA
| | - Matthew V. Roll
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA,Department of Cancer Biology, Wake Forest School of Medicine, Winston Salem, NC 27157, USA
| | - Andrew J. Magiera
- Department of Cancer Biology, Wake Forest School of Medicine, Winston Salem, NC 27157, USA
| | - Jun Li
- Department of Pharmaceutical Sciences, University at Buffalo, Buffalo, NY 14214, USA
| | - Edward Hurley
- Department of Biochemistry and Neurology, Hunter James Kelly Research Institute, University at Buffalo, Buffalo NY, USA
| | - Maria Laura Feltri
- Department of Biochemistry and Neurology, Hunter James Kelly Research Institute, University at Buffalo, Buffalo NY, USA
| | - Anderson O. Cox
- Department of Internal Medicine, Section of Molecular Medicine, Wake Forest School of Medicine, Winston-Salem NC, USA
| | - Jingyun Lee
- Department of Internal Medicine, Section of Molecular Medicine, Wake Forest School of Medicine, Winston-Salem NC, USA
| | - Cristina M. Furdui
- Department of Internal Medicine, Section of Molecular Medicine, Wake Forest School of Medicine, Winston-Salem NC, USA
| | - Liang Liu
- Department of Cancer Biology, Wake Forest School of Medicine, Winston Salem, NC 27157, USA
| | - Wiam Bshara
- Department of Pathology, Roswell Park Comprehensive Cancer Center, Buffalo NY 14203, USA
| | - Leslie E.W. LaConte
- Fralin Biomedical Research Institute at Virginia Tech Carilion School of Medicine, Roanoke, VA 24016, USA
| | - Eugene S. Kandel
- Department of Cell Stress Biology, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, USA
| | - Elena B. Pasquale
- Sanford Burnham Prebys Medical Discovery Institute, La Jolla, CA 92037, USA
| | - Jun Qu
- Department of Chemistry, Brandeis University, Waltham, MA 02453, USA
| | - Lizbeth Hedstrom
- Department of Chemistry, Brandeis University, Waltham, MA 02453, USA,Department of Biology, Brandeis University, Waltham, MA 02453, USA
| | - Mikhail A. Nikiforov
- Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC 27708, USA,Department of Cancer Biology, Wake Forest School of Medicine, Winston Salem, NC 27157, USA,Department of Pathology, Duke University School of Medicine, Durham, NC 27710, USA,Corresponding author and lead contact: Mikhail A. Nikiforov,
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19
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Kalyuzhnyy A, Eyers PA, Eyers CE, Bowler-Barnett E, Martin MJ, Sun Z, Deutsch EW, Jones AR. Profiling the Human Phosphoproteome to Estimate the True Extent of Protein Phosphorylation. J Proteome Res 2022; 21:1510-1524. [PMID: 35532924 PMCID: PMC9171898 DOI: 10.1021/acs.jproteome.2c00131] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Public phosphorylation databases such as PhosphoSitePlus (PSP) and PeptideAtlas (PA) compile results from published papers or openly available mass spectrometry (MS) data. However, there is no database-level control for false discovery of sites, likely leading to the overestimation of true phosphosites. By profiling the human phosphoproteome, we estimate the false discovery rate (FDR) of phosphosites and predict a more realistic count of true identifications. We rank sites into phosphorylation likelihood sets and analyze them in terms of conservation across 100 species, sequence properties, and functional annotations. We demonstrate significant differences between the sets and develop a method for independent phosphosite FDR estimation. Remarkably, we report estimated FDRs of 84, 98, and 82% within sets of phosphoserine (pSer), phosphothreonine (pThr), and phosphotyrosine (pTyr) sites, respectively, that are supported by only a single piece of identification evidence─the majority of sites in PSP. We estimate that around 62 000 Ser, 8000 Thr, and 12 000 Tyr phosphosites in the human proteome are likely to be true, which is lower than most published estimates. Furthermore, our analysis estimates that 86 000 Ser, 50 000 Thr, and 26 000 Tyr phosphosites are likely false-positive identifications, highlighting the significant potential of false-positive data to be present in phosphorylation databases.
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Affiliation(s)
- Anton Kalyuzhnyy
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7BE, U.K.,Computational Biology Facility, Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7BE, U.K
| | - Patrick A Eyers
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7BE, U.K
| | - Claire E Eyers
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7BE, U.K.,Centre for Proteome Research, Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7BE, U.K
| | - Emily Bowler-Barnett
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge CB10 1SD, U.K
| | - Maria J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge CB10 1SD, U.K
| | - Zhi Sun
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Eric W Deutsch
- Institute for Systems Biology, Seattle, Washington 98109, United States
| | - Andrew R Jones
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7BE, U.K.,Computational Biology Facility, Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L69 7BE, U.K
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20
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Abstract
Three-dimensional protein structural data at the molecular level are pivotal for successful precision medicine. Such data are crucial not only for discovering drugs that act to block the active site of the target mutant protein but also for clarifying to the patient and the clinician how the mutations harbored by the patient work. The relative paucity of structural data reflects their cost, challenges in their interpretation, and lack of clinical guidelines for their utilization. Rapid technological advancements in experimental high-resolution structural determination increasingly generate structures. Computationally, modeling algorithms, including molecular dynamics simulations, are becoming more powerful, as are compute-intensive hardware, particularly graphics processing units, overlapping with the inception of the exascale era. Accessible, freely available, and detailed structural and dynamical data can be merged with big data to powerfully transform personalized pharmacology. Here we review protein and emerging genome high-resolution data, along with means, applications, and examples underscoring their usefulness in precision medicine. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Ruth Nussinov
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA; .,Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Hyunbum Jang
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA;
| | - Guy Nir
- Department of Biochemistry and Molecular Biology, Department of Neuroscience, Cell Biology and Anatomy, and Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, Texas, USA
| | - Chung-Jung Tsai
- Computational Structural Biology Section, Frederick National Laboratory for Cancer Research in the Laboratory of Cancer Immunometabolism, National Cancer Institute, Frederick, Maryland, USA;
| | - Feixiong Cheng
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA.,Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, Ohio, USA.,Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA
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21
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Glycosylation-Related Genes Predict the Prognosis and Immune Fraction of Ovarian Cancer Patients Based on Weighted Gene Coexpression Network Analysis (WGCNA) and Machine Learning. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2022; 2022:3665617. [PMID: 35281472 PMCID: PMC8916863 DOI: 10.1155/2022/3665617] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 02/10/2022] [Accepted: 02/21/2022] [Indexed: 12/24/2022]
Abstract
Background Ovarian cancer (OC) is a malignancy exhibiting high mortality in female tumors. Glycosylation is a posttranslational modification of proteins but research has failed to demonstrate a systematic link between glycosylation-related signatures and tumor environment of OC. Purpose This study is aimed at developing a novel model with glycosylation-related messenger RNAs (GRmRNAs) to predict the prognosis and immune function in OC patients. Methods The transcriptional profiles and clinical phenotypes of OC patients were collected from the Gene Expression Omnibus and The Cancer Genome Atlas databases. A weighted gene coexpression network analysis and machine learning were performed to find the optimal survival-related GRmRNAs. Least absolute shrinkage and selection operator regression (LASSO) and Cox regression were carried out to calculate the coefficients of each GRmRNA and compute the risk score of each patient as well as develop a prognostic model. A nomogram model was constructed, and several algorithms were used to investigate the relationship between risk subtypes and immune-infiltrating levels. Results A total of four signatures (ALG8, DCTN4, DCTN6, and UBB) were determined to calculate the risk scores, classifying patients into the high-and low-risk groups. High-risk patients exhibited significantly poorer survival outcomes, and the established nomogram model had a promising prediction for OC patients' prognosis. Tumor purity and tumor mutation burden were negatively correlated with risk scores. In addition, risk scores held statistical associations with pathway signatures such as Wnt, Hippo, and reactive oxygen species, and nonsynonymous mutation counts. Conclusion The currently established risk scores based on GRmRNAs can accurately predict the prognosis, the immune microenvironment, and the immunotherapeutic efficacy of OC patients.
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22
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High-throughput functional characterization of protein phosphorylation sites in yeast. Nat Biotechnol 2022; 40:382-390. [PMID: 34663920 PMCID: PMC7612524 DOI: 10.1038/s41587-021-01051-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 08/09/2021] [Indexed: 12/11/2022]
Abstract
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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23
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Xiao D, Kim HJ, Pang I, Yang P. Functional analysis of the stable phosphoproteome reveals cancer vulnerabilities. Bioinformatics 2022; 38:1956-1963. [PMID: 35015814 PMCID: PMC9113330 DOI: 10.1093/bioinformatics/btac015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 12/21/2021] [Accepted: 01/06/2022] [Indexed: 11/29/2022] Open
Abstract
Motivation The advance of mass spectrometry-based technologies enabled the profiling of the phosphoproteomes of a multitude of cell and tissue types. However, current research primarily focused on investigating the phosphorylation dynamics in specific cell types and experimental conditions, whereas the phosphorylation events that are common across cell/tissue types and stable regardless of experimental conditions are, so far, mostly ignored. Results Here, we developed a statistical framework to identify the stable phosphoproteome across 53 human phosphoproteomics datasets, covering 40 cell/tissue types and 194 conditions/treatments. We demonstrate that the stably phosphorylated sites (SPSs) identified from our statistical framework are evolutionarily conserved, functionally important and enriched in a range of core signaling and gene pathways. Particularly, we show that SPSs are highly enriched in the RNA splicing pathway, an essential cellular process in mammalian cells, and frequently disrupted by cancer mutations, suggesting a link between the dysregulation of RNA splicing and cancer development through mutations on SPSs. Availability and implementation The source code for data analysis in this study is available from Github repository https://github.com/PYangLab/SPSs under the open-source license of GPL-3. The data used in this study are publicly available (see Section 2.8). Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Di Xiao
- Computational Systems Biology Group
| | - Hani Jieun Kim
- Computational Systems Biology Group.,Charles Perkins Centre, School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia
| | - Ignatius Pang
- Bioinformatics Group, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia
| | - Pengyi Yang
- Computational Systems Biology Group.,Charles Perkins Centre, School of Mathematics and Statistics, The University of Sydney, Sydney, NSW, Australia
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24
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English N, Torres M. Enhancing the Discovery of Functional Post-Translational Modification Sites with Machine Learning Models - Development, Validation, and Interpretation. Methods Mol Biol 2022; 2499:221-260. [PMID: 35696084 DOI: 10.1007/978-1-0716-2317-6_12] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Protein posttranslational modifications (PTMs) are a rapidly expanding feature class of significant importance in cell biology. Due to a high burden of experimental proof, the number of functionals PTMs in the eukaryotic proteome is currently underestimated. Furthermore, not all PTMs are functionally equivalent. Computational approaches that can confidently recommend PTMs of probable function can improve the heuristics of PTM investigation and alleviate these problems. To address this need, we developed SAPH-ire: a multifeature heuristic neural network model that takes community wisdom into account by recommending experimental PTMs similar to those which have previously been established as having regulatory impact. Here, we describe the principle behind the SAPH-ire model, how it is developed, how we evaluate its performance, and important caveats to consider when building and interpreting such models. Finally, we discus current limitations of functional PTM prediction models and highlight potential mechanisms for their improvement.
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Affiliation(s)
- Nolan English
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Matthew Torres
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA.
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25
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Hollenstein DM, Gérecová G, Romanov N, Ferrari J, Veis J, Janschitz M, Beyer R, Schüller C, Ogris E, Hartl M, Ammerer G, Reiter W. A phosphatase-centric mechanism drives stress signaling response. EMBO Rep 2021; 22:e52476. [PMID: 34558777 PMCID: PMC8567219 DOI: 10.15252/embr.202152476] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Revised: 08/27/2021] [Accepted: 09/03/2021] [Indexed: 12/14/2022] Open
Abstract
Changing environmental cues lead to the adjustment of cellular physiology by phosphorylation signaling networks that typically center around kinases as active effectors and phosphatases as antagonistic elements. Here, we report a signaling mechanism that reverses this principle. Using the hyperosmotic stress response in Saccharomyces cerevisiae as a model system, we find that a phosphatase-driven mechanism causes induction of phosphorylation. The key activating step that triggers this phospho-proteomic response is the Endosulfine-mediated inhibition of protein phosphatase 2A-Cdc55 (PP2ACdc55 ), while we do not observe concurrent kinase activation. In fact, many of the stress-induced phosphorylation sites appear to be direct substrates of the phosphatase, rendering PP2ACdc55 the main downstream effector of a signaling response that operates in parallel and independent of the well-established kinase-centric stress signaling pathways. This response affects multiple cellular processes and is required for stress survival. Our results demonstrate how a phosphatase can assume the role of active downstream effectors during signaling and allow re-evaluating the impact of phosphatases on shaping the phosphorylome.
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Affiliation(s)
- David Maria Hollenstein
- Department of Biochemistry and Cell BiologyMax Perutz LabsVienna BioCenter (VBC)University of ViennaViennaAustria
| | - Gabriela Gérecová
- Department of Biochemistry and Cell BiologyMax Perutz LabsVienna BioCenter (VBC)University of ViennaViennaAustria
| | | | - Jessica Ferrari
- Department of Biochemistry and Cell BiologyMax Perutz LabsVienna BioCenter (VBC)University of ViennaViennaAustria
| | - Jiri Veis
- Department of Biochemistry and Cell BiologyMax Perutz LabsVienna BioCenter (VBC)University of ViennaViennaAustria
- Center for Medical BiochemistryMax Perutz Labs, Vienna BioCenterMedical University of ViennaViennaAustria
| | - Marion Janschitz
- Department of Biochemistry and Cell BiologyMax Perutz LabsVienna BioCenter (VBC)University of ViennaViennaAustria
| | - Reinhard Beyer
- Department of Applied Genetics and Cell Biology (DAGZ)University of Natural Resources and Life Sciences (BOKU)ViennaAustria
- Research Platform Bioactive Microbial Metabolites (BiMM)Tulln a.d. DonauAustria
| | - Christoph Schüller
- Department of Applied Genetics and Cell Biology (DAGZ)University of Natural Resources and Life Sciences (BOKU)ViennaAustria
- Research Platform Bioactive Microbial Metabolites (BiMM)Tulln a.d. DonauAustria
| | - Egon Ogris
- Center for Medical BiochemistryMax Perutz Labs, Vienna BioCenterMedical University of ViennaViennaAustria
| | - Markus Hartl
- Department of Biochemistry and Cell BiologyMax Perutz LabsVienna BioCenter (VBC)University of ViennaViennaAustria
- Mass Spectrometry FacilityMax Perutz Labs, Vienna BioCenterUniversity of ViennaViennaAustria
| | - Gustav Ammerer
- Department of Biochemistry and Cell BiologyMax Perutz LabsVienna BioCenter (VBC)University of ViennaViennaAustria
| | - Wolfgang Reiter
- Department of Biochemistry and Cell BiologyMax Perutz LabsVienna BioCenter (VBC)University of ViennaViennaAustria
- Mass Spectrometry FacilityMax Perutz Labs, Vienna BioCenterUniversity of ViennaViennaAustria
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26
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Decoding post translational modification crosstalk with proteomics. Mol Cell Proteomics 2021; 20:100129. [PMID: 34339852 PMCID: PMC8430371 DOI: 10.1016/j.mcpro.2021.100129] [Citation(s) in RCA: 91] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 07/06/2021] [Accepted: 07/27/2021] [Indexed: 12/12/2022] Open
Abstract
Post-translational modification (PTM) of proteins allows cells to regulate protein functions, transduce signals and respond to perturbations. PTMs expand protein functionality and diversity, which leads to increased proteome complexity. PTM crosstalk describes the combinatorial action of multiple PTMs on the same or on different proteins for higher order regulation. Here we review how recent advances in proteomic technologies, mass spectrometry instrumentation, and bioinformatics spurred the proteome-wide identification of PTM crosstalk through measurements of PTM sites. We provide an overview of the basic modes of PTM crosstalk, the proteomic methods to elucidate PTM crosstalk, and approaches that can inform about the functional consequences of PTM crosstalk. Description of basic modules and different modes of PTM crosstalk. Overview of current proteomic methods to identify and infer PTM crosstalk. Discussion of large-scale approaches to characterize functional PTM crosstalk. Future directions and potential proteomic methods for elucidating PTM crosstalk.
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27
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Kamacioglu A, Tuncbag N, Ozlu N. Structural analysis of mammalian protein phosphorylation at a proteome level. Structure 2021; 29:1219-1229.e3. [PMID: 34192515 DOI: 10.1016/j.str.2021.06.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 04/07/2021] [Accepted: 06/04/2021] [Indexed: 10/21/2022]
Abstract
Phosphorylation is an essential post-translational modification for almost all cellular processes. Several global phosphoproteomics analyses have revealed phosphorylation profiles under different conditions. Beyond identification of phospho-sites, protein structures add another layer of information about their functionality. In this study, we systematically characterize phospho-sites based on their 3D locations in the protein and establish a location map for phospho-sites. More than 250,000 phospho-sites have been analyzed, of which 8,686 sites match at least one structure and are stratified based on their respective 3D positions. Core phospho-sites possess two distinct groups based on their dynamicity. Dynamic core phosphorylations are significantly more functional compared with static ones. The dynamic core and the interface phospho-sites are the most functional among all 3D phosphorylation groups. Our analysis provides global characterization and stratification of phospho-sites from a structural perspective that can be utilized for predicting functional relevance and filtering out false positives in phosphoproteomic studies.
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Affiliation(s)
- Altug Kamacioglu
- Department of Molecular Biology and Genetics, Koc University, Istanbul, Turkey
| | - Nurcan Tuncbag
- Chemical and Biological Engineering, College of Engineering, Koc University, 34450 Istanbul, Turkey; School of Medicine, Koc University, 34450 Istanbul, Turkey; Koc University Research Center for Translational Medicine (KUTTAM), 34450 Istanbul, Turkey.
| | - Nurhan Ozlu
- Department of Molecular Biology and Genetics, Koc University, Istanbul, Turkey; School of Medicine, Koc University, 34450 Istanbul, Turkey; Koc University Research Center for Translational Medicine (KUTTAM), 34450 Istanbul, Turkey.
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28
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Šoštarić N, van Noort V. Molecular dynamics shows complex interplay and long-range effects of post-translational modifications in yeast protein interactions. PLoS Comput Biol 2021; 17:e1008988. [PMID: 33979327 PMCID: PMC8143416 DOI: 10.1371/journal.pcbi.1008988] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 05/24/2021] [Accepted: 04/21/2021] [Indexed: 12/13/2022] Open
Abstract
Post-translational modifications (PTMs) play a vital, yet often overlooked role in the living cells through modulation of protein properties, such as localization and affinity towards their interactors, thereby enabling quick adaptation to changing environmental conditions. We have previously benchmarked a computational framework for the prediction of PTMs’ effects on the stability of protein-protein interactions, which has molecular dynamics simulations followed by free energy calculations at its core. In the present work, we apply this framework to publicly available data on Saccharomyces cerevisiae protein structures and PTM sites, identified in both normal and stress conditions. We predict proteome-wide effects of acetylations and phosphorylations on protein-protein interactions and find that acetylations more frequently have locally stabilizing roles in protein interactions, while the opposite is true for phosphorylations. However, the overall impact of PTMs on protein-protein interactions is more complex than a simple sum of local changes caused by the introduction of PTMs and adds to our understanding of PTM cross-talk. We further use the obtained data to calculate the conformational changes brought about by PTMs. Finally, conservation of the analyzed PTM residues in orthologues shows that some predictions for yeast proteins will be mirrored to other organisms, including human. This work, therefore, contributes to our overall understanding of the modulation of the cellular protein interaction networks in yeast and beyond. Proteins are a diverse set of biological molecules responsible for numerous functions within cells, such as obtaining energy from food or transport of small molecules, and many processes rely on interactions of specific proteins. Moreover, a single protein may acquire different roles depending on cellular requirements and as a response to changes in the environment. A commonly used way to quickly change protein’s function or activity is by introducing small chemical modifications on specific locations within the protein. These modifications can cause the protein to interact in a more or less stable way with other proteins. We have previously developed a computational pipeline for predicting the effect of modifications on interactions of proteins, and in this work we apply it to all yeast proteins with known structures. We find differences in effects on the binding for different types of modifications. Importantly, we demonstrate that the modifications far from the interaction interface also significantly contribute to binding due to their impact on protein’s shape, which is often neglected by other methods. This work contributes to our understanding of the modulation of protein interactions in yeast due to modifications, while our widely applicable method will allow similar investigations in other organisms.
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Affiliation(s)
| | - Vera van Noort
- KU Leuven, Centre of Microbial and Plant Genetics, Leuven, Belgium
- Leiden University, Institute of Biology Leiden, Leiden, The Netherlands
- * E-mail:
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29
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Floyd BM, Drew K, Marcotte EM. Systematic Identification of Protein Phosphorylation-Mediated Interactions. J Proteome Res 2021; 20:1359-1370. [PMID: 33476154 DOI: 10.1021/acs.jproteome.0c00750] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Protein phosphorylation is a key regulatory mechanism involved in nearly every eukaryotic cellular process. Increasingly sensitive mass spectrometry approaches have identified hundreds of thousands of phosphorylation sites, but the functions of a vast majority of these sites remain unknown, with fewer than 5% of sites currently assigned a function. To increase our understanding of functional protein phosphorylation we developed an approach (phospho-DIFFRAC) for identifying the phosphorylation-dependence of protein assemblies in a systematic manner. A combination of nonspecific protein phosphatase treatment, size-exclusion chromatography, and mass spectrometry allowed us to identify changes in protein interactions after the removal of phosphate modifications. With this approach we were able to identify 316 proteins involved in phosphorylation-sensitive interactions. We recovered known phosphorylation-dependent interactors such as the FACT complex and spliceosome, as well as identified novel interactions such as the tripeptidyl peptidase TPP2 and the supraspliceosome component ZRANB2. More generally, we find phosphorylation-dependent interactors to be strongly enriched for RNA-binding proteins, providing new insight into the role of phosphorylation in RNA binding. By searching directly for phosphorylated amino acid residues in mass spectrometry data, we identified the likely regulatory phosphosites on ZRANB2 and FACT complex subunit SSRP1. This study provides both a method and resource for obtaining a better understanding of the role of phosphorylation in native macromolecular assemblies. All mass spectrometry data are available through PRIDE (accession #PXD021422).
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Affiliation(s)
- Brendan M Floyd
- Department of Molecular Biosciences Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Kevin Drew
- Department of Molecular Biosciences Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas 78712, United States
| | - Edward M Marcotte
- Department of Molecular Biosciences Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, Texas 78712, United States
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30
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Controlling the Controllers: Regulation of Histone Methylation by Phosphosignalling. Trends Biochem Sci 2020; 45:1035-1048. [DOI: 10.1016/j.tibs.2020.08.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Revised: 07/23/2020] [Accepted: 08/07/2020] [Indexed: 01/05/2023]
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31
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Bonne Køhler J, Jers C, Senissar M, Shi L, Derouiche A, Mijakovic I. Importance of protein Ser/Thr/Tyr phosphorylation for bacterial pathogenesis. FEBS Lett 2020; 594:2339-2369. [PMID: 32337704 DOI: 10.1002/1873-3468.13797] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Revised: 04/16/2020] [Accepted: 04/20/2020] [Indexed: 12/13/2022]
Abstract
Protein phosphorylation regulates a large variety of biological processes in all living cells. In pathogenic bacteria, the study of serine, threonine, and tyrosine (Ser/Thr/Tyr) phosphorylation has shed light on the course of infectious diseases, from adherence to host cells to pathogen virulence, replication, and persistence. Mass spectrometry (MS)-based phosphoproteomics has provided global maps of Ser/Thr/Tyr phosphosites in bacterial pathogens. Despite recent developments, a quantitative and dynamic view of phosphorylation events that occur during bacterial pathogenesis is currently lacking. Temporal, spatial, and subpopulation resolution of phosphorylation data is required to identify key regulatory nodes underlying bacterial pathogenesis. Herein, we discuss how technological improvements in sample handling, MS instrumentation, data processing, and machine learning should improve bacterial phosphoproteomic datasets and the information extracted from them. Such information is expected to significantly extend the current knowledge of Ser/Thr/Tyr phosphorylation in pathogenic bacteria and should ultimately contribute to the design of novel strategies to combat bacterial infections.
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Affiliation(s)
- Julie Bonne Køhler
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark
| | - Carsten Jers
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark
| | - Mériem Senissar
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark
| | - Lei Shi
- Systems and Synthetic Biology Division, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Abderahmane Derouiche
- Systems and Synthetic Biology Division, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Ivan Mijakovic
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark.,Systems and Synthetic Biology Division, Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden
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32
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Invergo BM, Petursson B, Akhtar N, Bradley D, Giudice G, Hijazi M, Cutillas P, Petsalaki E, Beltrao P. Prediction of Signed Protein Kinase Regulatory Circuits. Cell Syst 2020; 10:384-396.e9. [DOI: 10.1016/j.cels.2020.04.005] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2019] [Revised: 01/24/2020] [Accepted: 04/20/2020] [Indexed: 01/18/2023]
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33
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Ochoa D, Jarnuczak AF, Viéitez C, Gehre M, Soucheray M, Mateus A, Kleefeldt AA, Hill A, Garcia-Alonso L, Stein F, Krogan NJ, Savitski MM, Swaney DL, Vizcaíno JA, Noh KM, Beltrao P. The functional landscape of the human phosphoproteome. Nat Biotechnol 2020; 38:365-373. [PMID: 31819260 PMCID: PMC7100915 DOI: 10.1038/s41587-019-0344-3] [Citation(s) in RCA: 221] [Impact Index Per Article: 55.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 11/05/2019] [Indexed: 12/18/2022]
Abstract
Protein phosphorylation is a key post-translational modification regulating protein function in almost all cellular processes. Although tens of thousands of phosphorylation sites have been identified in human cells, approaches to determine the functional importance of each phosphosite are lacking. Here, we manually curated 112 datasets of phospho-enriched proteins, generated from 104 different human cell types or tissues. We re-analyzed the 6,801 proteomics experiments that passed our quality control criteria, creating a reference phosphoproteome containing 119,809 human phosphosites. To prioritize functional sites, we used machine learning to identify 59 features indicative of proteomic, structural, regulatory or evolutionary relevance and integrate them into a single functional score. Our approach identifies regulatory phosphosites across different molecular mechanisms, processes and diseases, and reveals genetic susceptibilities at a genomic scale. Several regulatory phosphosites were experimentally validated, including identifying a role in neuronal differentiation for phosphosites in SMARCC2, a member of the SWI/SNF chromatin-remodeling complex.
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Affiliation(s)
- David Ochoa
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
| | - Andrew F Jarnuczak
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Cristina Viéitez
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Maja Gehre
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Margaret Soucheray
- Gladstone Institute of Data Science and Biotechnology, J. David Gladstone Institutes, San Francisco, CA, USA
- Department of Cellular and Molecular Pharmacology and the Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA, USA
| | - André Mateus
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Askar A Kleefeldt
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Anthony Hill
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Luz Garcia-Alonso
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Frank Stein
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Nevan J Krogan
- Gladstone Institute of Data Science and Biotechnology, J. David Gladstone Institutes, San Francisco, CA, USA
- Department of Cellular and Molecular Pharmacology and the Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA, USA
| | - Mikhail M Savitski
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Danielle L Swaney
- Gladstone Institute of Data Science and Biotechnology, J. David Gladstone Institutes, San Francisco, CA, USA
- Department of Cellular and Molecular Pharmacology and the Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA, USA
| | - Juan A Vizcaíno
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Kyung-Min Noh
- Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany
| | - Pedro Beltrao
- European Molecular Biology Laboratory (EMBL), European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK.
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