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Poretsky E, Andorf CM, Sen TZ. PhosBoost: Improved phosphorylation prediction recall using gradient boosting and protein language models. PLANT DIRECT 2023; 7:e554. [PMID: 38124705 PMCID: PMC10732782 DOI: 10.1002/pld3.554] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 11/20/2023] [Accepted: 11/26/2023] [Indexed: 12/23/2023]
Abstract
Protein phosphorylation is a dynamic and reversible post-translational modification that regulates a variety of essential biological processes. The regulatory role of phosphorylation in cellular signaling pathways, protein-protein interactions, and enzymatic activities has motivated extensive research efforts to understand its functional implications. Experimental protein phosphorylation data in plants remains limited to a few species, necessitating a scalable and accurate prediction method. Here, we present PhosBoost, a machine-learning approach that leverages protein language models and gradient-boosting trees to predict protein phosphorylation from experimentally derived data. Trained on data obtained from a comprehensive plant phosphorylation database, qPTMplants, we compared the performance of PhosBoost to existing protein phosphorylation prediction methods, PhosphoLingo and DeepPhos. For serine and threonine prediction, PhosBoost achieved higher recall than PhosphoLingo and DeepPhos (.78, .56, and .14, respectively) while maintaining a competitive area under the precision-recall curve (.54, .56, and .42, respectively). PhosphoLingo and DeepPhos failed to predict any tyrosine phosphorylation sites, while PhosBoost achieved a recall score of .6. Despite the precision-recall tradeoff, PhosBoost offers improved performance when recall is prioritized while consistently providing more confident probability scores. A sequence-based pairwise alignment step improved prediction results for all classifiers by effectively increasing the number of inferred positive phosphosites. We provide evidence to show that PhosBoost models are transferable across species and scalable for genome-wide protein phosphorylation predictions. PhosBoost is freely and publicly available on GitHub.
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Affiliation(s)
- Elly Poretsky
- Agricultural Research Service, Crop Improvement and Genetics Research UnitU.S. Department of AgricultureAlbanyCAUnited States
| | - Carson M. Andorf
- Agricultural Research Service, Corn Insects and Crop Genetics ResearchU.S. Department of AgricultureAmesIAUnited States
- Department of Computer ScienceIowa State UniversityAmesIAUnited States
| | - Taner Z. Sen
- Agricultural Research Service, Crop Improvement and Genetics Research UnitU.S. Department of AgricultureAlbanyCAUnited States
- Department of BioengineeringUniversity of CaliforniaBerkeleyCAUnited States
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2
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Weigle AT, Feng J, Shukla D. Thirty years of molecular dynamics simulations on posttranslational modifications of proteins. Phys Chem Chem Phys 2022; 24:26371-26397. [PMID: 36285789 PMCID: PMC9704509 DOI: 10.1039/d2cp02883b] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/06/2023]
Abstract
Posttranslational modifications (PTMs) are an integral component to how cells respond to perturbation. While experimental advances have enabled improved PTM identification capabilities, the same throughput for characterizing how structural changes caused by PTMs equate to altered physiological function has not been maintained. In this Perspective, we cover the history of computational modeling and molecular dynamics simulations which have characterized the structural implications of PTMs. We distinguish results from different molecular dynamics studies based upon the timescales simulated and analysis approaches used for PTM characterization. Lastly, we offer insights into how opportunities for modern research efforts on in silico PTM characterization may proceed given current state-of-the-art computing capabilities and methodological advancements.
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Affiliation(s)
- Austin T Weigle
- Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Jiangyan Feng
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
| | - Diwakar Shukla
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA
- Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, USA.
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3
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van Gelder CAGH, Altelaar M. Neuroproteomics of the Synapse: Subcellular Quantification of Protein Networks and Signaling Dynamics. Mol Cell Proteomics 2021; 20:100087. [PMID: 33933679 PMCID: PMC8167277 DOI: 10.1016/j.mcpro.2021.100087] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 04/21/2021] [Accepted: 04/26/2021] [Indexed: 01/21/2023] Open
Abstract
One of the most fascinating features of the brain is its ability to adapt to its surroundings. Synaptic plasticity, the dynamic mechanism of functional and structural alterations in synaptic strength, is essential for brain functioning and underlies a variety of processes such as learning and memory. Although the molecular mechanisms underlying such rapid plasticity are not fully understood, a consensus exists on the important role of proteins. The study of these neuronal proteins using neuroproteomics has increased rapidly in the last decades, and advancements in MS-based proteomics have broadened our understanding of neuroplasticity exponentially. In this review, we discuss the trends in MS-based neuroproteomics for the study of synaptic protein-protein interactions and protein signaling dynamics, with a focus on sample types, different labeling and enrichment approaches, and data analysis and interpretation. We highlight studies from the last 5 years, with a focus on synapse structure, composition, functioning, or signaling and finally discuss some recent developments that could further advance the field of neuroproteomics.
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Affiliation(s)
- Charlotte A G H van Gelder
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands
| | - Maarten Altelaar
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Utrecht, The Netherlands; Netherlands Proteomics Center, Utrecht, The Netherlands.
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4
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Phosphoproteomics of Acute Cell Stressors Targeting Exercise Signaling Networks Reveal Drug Interactions Regulating Protein Secretion. Cell Rep 2020; 29:1524-1538.e6. [PMID: 31693893 DOI: 10.1016/j.celrep.2019.10.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 09/09/2019] [Accepted: 09/30/2019] [Indexed: 01/25/2023] Open
Abstract
Exercise engages signaling networks to control the release of circulating factors beneficial to health. However, the nature of these networks remains undefined. Using high-throughput phosphoproteomics, we quantify 20,249 phosphorylation sites in skeletal muscle-like myotube cells and monitor their responses to a panel of cell stressors targeting aspects of exercise signaling in vivo. Integrating these in-depth phosphoproteomes with the phosphoproteome of acute aerobic exercise in human skeletal muscle suggests that co-administration of β-adrenergic and calcium agonists would activate complementary signaling relevant to this exercise context. The phosphoproteome of cells treated with this combination reveals a surprising divergence in signaling from the individual treatments. Remarkably, only the combination treatment promotes multisite phosphorylation of SERBP1, a regulator of Serpine1 mRNA stability, a pro-fibrotic secreted protein. Secretome analysis reveals that the combined treatments decrease secretion of SERPINE1 and other deleterious factors. This study provides a framework for dissecting phosphorylation-based signaling relevant to acute exercise.
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5
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Nelson ME, Parker BL, Burchfield JG, Hoffman NJ, Needham EJ, Cooke KC, Naim T, Sylow L, Ling NXY, Francis D, Norris DM, Chaudhuri R, Oakhill JS, Richter EA, Lynch GS, Stöckli J, James DE. Phosphoproteomics reveals conserved exercise-stimulated signaling and AMPK regulation of store-operated calcium entry. EMBO J 2019; 38:e102578. [PMID: 31381180 PMCID: PMC6912027 DOI: 10.15252/embj.2019102578] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 06/27/2019] [Accepted: 07/01/2019] [Indexed: 12/20/2022] Open
Abstract
Exercise stimulates cellular and physiological adaptations that are associated with widespread health benefits. To uncover conserved protein phosphorylation events underlying this adaptive response, we performed mass spectrometry-based phosphoproteomic analyses of skeletal muscle from two widely used rodent models: treadmill running in mice and in situ muscle contraction in rats. We overlaid these phosphoproteomic signatures with cycling in humans to identify common cross-species phosphosite responses, as well as unique model-specific regulation. We identified > 22,000 phosphosites, revealing orthologous protein phosphorylation and overlapping signaling pathways regulated by exercise. This included two conserved phosphosites on stromal interaction molecule 1 (STIM1), which we validate as AMPK substrates. Furthermore, we demonstrate that AMPK-mediated phosphorylation of STIM1 negatively regulates store-operated calcium entry, and this is beneficial for exercise in Drosophila. This integrated cross-species resource of exercise-regulated signaling in human, mouse, and rat skeletal muscle has uncovered conserved networks and unraveled crosstalk between AMPK and intracellular calcium flux.
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Affiliation(s)
- Marin E Nelson
- Charles Perkins CentreSchool of Life and Environmental SciencesSydney Medical SchoolThe University of SydneySydneyNSWAustralia
| | - Benjamin L Parker
- Charles Perkins CentreSchool of Life and Environmental SciencesSydney Medical SchoolThe University of SydneySydneyNSWAustralia
- Present address:
Department of PhysiologyThe University of MelbourneMelbourneVic.Australia
| | - James G Burchfield
- Charles Perkins CentreSchool of Life and Environmental SciencesSydney Medical SchoolThe University of SydneySydneyNSWAustralia
| | - Nolan J Hoffman
- Charles Perkins CentreSchool of Life and Environmental SciencesSydney Medical SchoolThe University of SydneySydneyNSWAustralia
- Present address:
Exercise and Nutrition Research ProgramMary MacKillop Institute for Health ResearchAustralian Catholic UniversityMelbourneVic.Australia
| | - Elise J Needham
- Charles Perkins CentreSchool of Life and Environmental SciencesSydney Medical SchoolThe University of SydneySydneyNSWAustralia
| | - Kristen C Cooke
- Charles Perkins CentreSchool of Life and Environmental SciencesSydney Medical SchoolThe University of SydneySydneyNSWAustralia
| | - Timur Naim
- Centre for Muscle ResearchDepartment of PhysiologySchool of Biomedical SciencesThe University of MelbourneMelbourneVicAustralia
| | - Lykke Sylow
- Department of Nutrition, Exercise and SportsFaculty of ScienceThe University of CopenhagenCopenhagenDenmark
| | - Naomi XY Ling
- Metabolic Signalling LaboratorySt. Vincent's Institute of Medical ResearchMelbourneVic.Australia
| | - Deanne Francis
- Charles Perkins CentreSchool of Life and Environmental SciencesSydney Medical SchoolThe University of SydneySydneyNSWAustralia
| | - Dougall M Norris
- Charles Perkins CentreSchool of Life and Environmental SciencesSydney Medical SchoolThe University of SydneySydneyNSWAustralia
| | - Rima Chaudhuri
- Charles Perkins CentreSchool of Life and Environmental SciencesSydney Medical SchoolThe University of SydneySydneyNSWAustralia
| | - Jonathan S Oakhill
- Metabolic Signalling LaboratorySt. Vincent's Institute of Medical ResearchMelbourneVic.Australia
- Exercise and Nutrition Research ProgramMary MacKillop Institute for Health ResearchAustralian Catholic UniversityMelbourneVic.Australia
| | - Erik A Richter
- Department of Nutrition, Exercise and SportsFaculty of ScienceThe University of CopenhagenCopenhagenDenmark
| | - Gordon S Lynch
- Centre for Muscle ResearchDepartment of PhysiologySchool of Biomedical SciencesThe University of MelbourneMelbourneVicAustralia
| | - Jacqueline Stöckli
- Charles Perkins CentreSchool of Life and Environmental SciencesSydney Medical SchoolThe University of SydneySydneyNSWAustralia
| | - David E James
- Charles Perkins CentreSchool of Life and Environmental SciencesSydney Medical SchoolThe University of SydneySydneyNSWAustralia
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6
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Noor Z, Ranganathan S. Bioinformatics approaches for improving seminal plasma proteome analysis. Theriogenology 2019; 137:43-49. [PMID: 31186128 DOI: 10.1016/j.theriogenology.2019.05.036] [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: 10/26/2022]
Abstract
Reproduction efficiency of male animals is one of the key factors influencing the sustainability of livestock. Mass spectrometry (MS) based proteomics has become an important tool for studying seminal plasma proteomes. In this review, we summarize bioinformatics analysis strategies for current proteomics approaches, for identifying novel biomarkers of reproductive robustness.
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Affiliation(s)
- Zainab Noor
- Department of Molecular Sciences, Macquarie University, Sydney, Australia
| | - Shoba Ranganathan
- Department of Molecular Sciences, Macquarie University, Sydney, Australia.
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7
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Antfolk D, Antila C, Kemppainen K, Landor SKJ, Sahlgren C. Decoding the PTM-switchboard of Notch. BIOCHIMICA ET BIOPHYSICA ACTA-MOLECULAR CELL RESEARCH 2019; 1866:118507. [PMID: 31301363 PMCID: PMC7116576 DOI: 10.1016/j.bbamcr.2019.07.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Revised: 07/03/2019] [Accepted: 07/06/2019] [Indexed: 01/08/2023]
Abstract
The developmentally indispensable Notch pathway exhibits a high grade of pleiotropism in its biological output. Emerging evidence supports the notion of post-translational modifications (PTMs) as a modus operandi controlling dynamic fine-tuning of Notch activity. Although, the intricacy of Notch post-translational regulation, as well as how these modifications lead to multiples of divergent Notch phenotypes is still largely unknown, numerous studies show a correlation between the site of modification and the output. These include glycosylation of the extracellular domain of Notch modulating ligand binding, and phosphorylation of the PEST domain controlling half-life of the intracellular domain of Notch. Furthermore, several reports show that multiple PTMs can act in concert, or compete for the same sites to drive opposite outputs. However, further investigation of the complex PTM crosstalk is required for a complete understanding of the PTM-mediated Notch switchboard. In this review, we aim to provide a consistent and up-to-date summary of the currently known PTMs acting on the Notch signaling pathway, their functions in different contexts, as well as explore their implications in physiology and disease. Furthermore, we give an overview of the present state of PTM research methodology, and allude to a future with PTM-targeted Notch therapeutics.
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Affiliation(s)
- Daniel Antfolk
- Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku, Finland
| | - Christian Antila
- Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku, Finland
| | - Kati Kemppainen
- Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku, Finland
| | - Sebastian K-J Landor
- Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku, Finland.
| | - Cecilia Sahlgren
- Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku, Finland; Department of Biomedical Engineering, Institute for Complex Molecular Systems, Eindhoven University of Technology, Eindhoven, the Netherlands.
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8
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Xu L, Dong Z, Fang L, Luo Y, Wei Z, Guo H, Zhang G, Gu YQ, Coleman-Derr D, Xia Q, Wang Y. OrthoVenn2: a web server for whole-genome comparison and annotation of orthologous clusters across multiple species. Nucleic Acids Res 2019; 47:W52-W58. [PMID: 31053848 PMCID: PMC6602458 DOI: 10.1093/nar/gkz333] [Citation(s) in RCA: 551] [Impact Index Per Article: 110.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 04/16/2019] [Accepted: 04/25/2019] [Indexed: 12/28/2022] Open
Abstract
OrthoVenn is a powerful web platform for the comparison and analysis of whole-genome orthologous clusters. Here we present an updated version, OrthoVenn2, which provides new features that facilitate the comparative analysis of orthologous clusters among up to 12 species. Additionally, this update offers improvements to data visualization and interpretation, including an occurrence pattern table for interrogating the overlap of each orthologous group for the queried species. Within the occurrence table, the functional annotations and summaries of the disjunctions and intersections of clusters between the chosen species can be displayed through an interactive Venn diagram. To facilitate a broader range of comparisons, a larger number of species, including vertebrates, metazoa, protists, fungi, plants and bacteria, have been added in OrthoVenn2. Finally, a stand-alone version is available to perform large dataset comparisons and to visualize results locally without limitation of species number. In summary, OrthoVenn2 is an efficient and user-friendly web server freely accessible at https://orthovenn2.bioinfotoolkits.net.
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Affiliation(s)
- Ling Xu
- Biological Science Research Center, Southwest University, Chongqing 400715, China
| | - Zhaobin Dong
- Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA 94710, USA
- USDA-ARS, Plant Gene Expression Center, Albany, CA 94706, USA
| | - Lu Fang
- Biological Science Research Center, Southwest University, Chongqing 400715, China
| | - Yongjiang Luo
- Biological Science Research Center, Southwest University, Chongqing 400715, China
| | - Zhaoyuan Wei
- Biological Science Research Center, Southwest University, Chongqing 400715, China
| | - Hailong Guo
- Biological Science Research Center, Southwest University, Chongqing 400715, China
| | - Guoqing Zhang
- Biological Science Research Center, Southwest University, Chongqing 400715, China
| | - Yong Q Gu
- USDA-ARS, Western Regional Research Center, Crop Improvement and Genetics Research Unit, Albany, CA 94706, USA
| | - Devin Coleman-Derr
- Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA 94710, USA
- USDA-ARS, Plant Gene Expression Center, Albany, CA 94706, USA
| | - Qingyou Xia
- Biological Science Research Center, Southwest University, Chongqing 400715, China
| | - Yi Wang
- Biological Science Research Center, Southwest University, Chongqing 400715, China
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9
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Balik-Meisner MR, Mav D, Phadke DP, Everett LJ, Shah RR, Tal T, Shepard PJ, Merrick BA, Paules RS. Development of a Zebrafish S1500+ Sentinel Gene Set for High-Throughput Transcriptomics. Zebrafish 2019; 16:331-347. [PMID: 31188086 PMCID: PMC6685209 DOI: 10.1089/zeb.2018.1720] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Sentinel gene sets have been developed with the purpose of maximizing the information from targeted transcriptomic platforms. We recently described the development of an S1500+ sentinel gene set, which was built for the human transcriptome, utilizing a data- and knowledge-driven hybrid approach to select a small subset of genes that optimally capture transcriptional diversity, correlation with other genes based on large-scale expression profiling, and known pathway annotation within the human genome. While this detailed bioinformatics approach for gene selection can in principle be applied to other species, the reliability of the resulting gene set depends on availability of a large body of transcriptomics data. For the model organism zebrafish, we aimed to create a similar sentinel gene set (Zf S1500+ gene set); however, there is insufficient standardized expression data in the public domain to train the gene correlation model. Therefore, our strategy was to use human-zebrafish ortholog mapping of the human S1500+ genes and nominations from experts in the zebrafish scientific community. In this study, we present the bioinformatics curation and refinement process to produce the final Zf S1500+ gene set, explore whole transcriptome extrapolation using this gene set, and assess pathway-level inference. This gene set will add value to targeted high-throughput transcriptomics in zebrafish for toxicogenomic screening and other research domains.
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Affiliation(s)
| | - Deepak Mav
- 1Sciome, LLC, Research Triangle Park, North Carolina
| | | | | | - Ruchir R Shah
- 1Sciome, LLC, Research Triangle Park, North Carolina
| | - Tamara Tal
- 2National Health and Environmental Effects Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
| | | | - B Alex Merrick
- 4Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina
| | - Richard S Paules
- 4Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, North Carolina
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10
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Abstract
Advancements in MS-based phospho-proteomics techniques have helped uncover hundred thousands of protein phosphorylation sites in human and various model organisms. The majority of these sites are uncharacterized. The sheer number of uncharacterized sites necessitates systematic approaches to prioritize sites for more in-depth annotation. Analyzing the phosphorylation and sequence conservation of uncharacterized sites across species can help reveal a subset of the functionally important phosphorylation events. Here, we outline the workflow and provide an overview of publicly available computational resources for conservation analysis of novel phosphorylation sites.
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11
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Nichio BTL, Marchaukoski JN, Raittz RT. New Tools in Orthology Analysis: A Brief Review of Promising Perspectives. Front Genet 2017; 8:165. [PMID: 29163633 PMCID: PMC5674930 DOI: 10.3389/fgene.2017.00165] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2017] [Accepted: 10/16/2017] [Indexed: 11/23/2022] Open
Abstract
Nowadays defying homology relationships among sequences is essential for biological research. Within homology the analysis of orthologs sequences is of great importance for computational biology, annotation of genomes and for phylogenetic inference. Since 2007, with the increase in the number of new sequences being deposited in large biological databases, researchers have begun to analyse computerized methodologies and tools aimed at selecting the most promising ones in the prediction of orthologous groups. Literature in this field of research describes the problems that the majority of available tools show, such as those encountered in accuracy, time required for analysis (especially in light of the increasing volume of data being submitted, which require faster techniques) and the automatization of the process without requiring manual intervention. Conducting our search through BMC, Google Scholar, NCBI PubMed, and Expasy, we examined more than 600 articles pursuing the most recent techniques and tools developed to solve most the problems still existing in orthology detection. We listed the main computational tools created and developed between 2011 and 2017, taking into consideration the differences in the type of orthology analysis, outlining the main features of each tool and pointing to the problems that each one tries to address. We also observed that several tools still use as their main algorithm the BLAST "all-against-all" methodology, which entails some limitations, such as limited number of queries, computational cost, and high processing time to complete the analysis. However, new promising tools are being developed, like OrthoVenn (which uses the Venn diagram to show the relationship of ortholog groups generated by its algorithm); or proteinOrtho (which improves the accuracy of ortholog groups); or ReMark (tackling the integration of the pipeline to turn the entry process automatic); or OrthAgogue (using algorithms developed to minimize processing time); and proteinOrtho (developed for dealing with large amounts of biological data). We made a comparison among the main features of four tool and tested them using four for prokaryotic genomas. We hope that our review can be useful for researchers and will help them in selecting the most appropriate tool for their work in the field of orthology.
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Affiliation(s)
| | | | - Roberto Tadeu Raittz
- Department of Bioinformatics, Professional and Technical Education Sector, Federal University of Paraná, Curitiba, Brazil
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12
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Hoffman NJ. Omics and Exercise: Global Approaches for Mapping Exercise Biological Networks. Cold Spring Harb Perspect Med 2017; 7:cshperspect.a029884. [PMID: 28348175 DOI: 10.1101/cshperspect.a029884] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
The application of global "-omics" technologies to exercise has introduced new opportunities to map the complexity and interconnectedness of biological networks underlying the tissue-specific responses and systemic health benefits of exercise. This review will introduce major research tracks and recent advancements in this emerging field, as well as critical gaps in understanding the orchestration of molecular exercise dynamics that will benefit from unbiased omics investigations. Furthermore, significant research hurdles that need to be overcome to effectively fill these gaps related to data collection, computation, interpretation, and integration across omics applications will be discussed. Collectively, a cross-disciplinary physiological and omics-based systems approach will lead to discovery of a wealth of novel exercise-regulated targets for future mechanistic validation. This frontier in exercise biology will aid the development of personalized therapeutic strategies to improve athletic performance and human health through precision exercise medicine.
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Affiliation(s)
- Nolan J Hoffman
- Centre for Exercise and Nutrition, Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria 3000, Australia
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13
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Ünal EB, Uhlitz F, Blüthgen N. A compendium of ERK targets. FEBS Lett 2017; 591:2607-2615. [PMID: 28675784 DOI: 10.1002/1873-3468.12740] [Citation(s) in RCA: 104] [Impact Index Per Article: 14.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2017] [Revised: 06/28/2017] [Accepted: 06/29/2017] [Indexed: 12/20/2022]
Abstract
The RAF-MEK-ERK cascade is one of the most studied signaling pathways as it controls many vital cellular programs. There has been an immense amount of effort to determine ERK target proteins involved in regulating these programs. Classical biochemical and genetic approaches have elicited hundreds of direct ERK substrates, and with the advent of phospho-proteomic technologies, numerous studies have expanded the number of ERK target proteins. Here, we compile a comprehensive ERK target phospho-site archive, in which we gathered information from various research studies, and we provide this archive as an online database to form a searchable compendium of ERK targets.
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Affiliation(s)
- Evrim B Ünal
- Integrative Research Institute Life Sciences & Institute for Theoretical Biology, Humboldt Universität zu Berlin, Germany.,Institute of Pathology, Charité - Universitätsmedizin Berlin, Germany
| | - Florian Uhlitz
- Integrative Research Institute Life Sciences & Institute for Theoretical Biology, Humboldt Universität zu Berlin, Germany.,Institute of Pathology, Charité - Universitätsmedizin Berlin, Germany
| | - Nils Blüthgen
- Integrative Research Institute Life Sciences & Institute for Theoretical Biology, Humboldt Universität zu Berlin, Germany.,Institute of Pathology, Charité - Universitätsmedizin Berlin, Germany.,Berlin Institute of Health, Germany
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14
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Audagnotto M, Dal Peraro M. Protein post-translational modifications: In silico prediction tools and molecular modeling. Comput Struct Biotechnol J 2017; 15:307-319. [PMID: 28458782 PMCID: PMC5397102 DOI: 10.1016/j.csbj.2017.03.004] [Citation(s) in RCA: 109] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2016] [Revised: 03/17/2017] [Accepted: 03/21/2017] [Indexed: 02/09/2023] Open
Abstract
Post-translational modifications (PTMs) occur in almost all proteins and play an important role in numerous biological processes by significantly affecting proteins' structure and dynamics. Several computational approaches have been developed to study PTMs (e.g., phosphorylation, sumoylation or palmitoylation) showing the importance of these techniques in predicting modified sites that can be further investigated with experimental approaches. In this review, we summarize some of the available online platforms and their contribution in the study of PTMs. Moreover, we discuss the emerging capabilities of molecular modeling and simulation that are able to complement these bioinformatics methods, providing deeper molecular insights into the biological function of post-translational modified proteins.
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Affiliation(s)
- Martina Audagnotto
- Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Matteo Dal Peraro
- Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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15
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Abstract
Protein post-translational modifications (PTMs) are crucial for signal transduction in cells. In order to understand key cell signaling events, identification of functionally important PTMs, which are more likely to be evolutionarily conserved, is necessary. In recent times, high-throughput mass spectrometry (MS) has made quantitative datasets in diverse species readily available, which has led to a growing need for tools to facilitate cross-species comparison of PTM data. Cross-species comparison of PTM sites is difficult since they often lie in structurally disordered protein domains. Current tools that address this can only map known PTMs between species based on previously annotated orthologous phosphosites and do not enable cross-species mapping of newly identified modification sites. Here, we describe an automated web-based tool, PhosphOrtholog, that accurately maps annotated and novel orthologous PTM sites from high-throughput MS-based experimental data obtained from different species without relying on existing PTM databases. Identification of conserved PTMs across species from large-scale experimental data increases our knowledgebase of evolutionarily conserved and functional PTM sites that influence most biological processes. In this Chapter, we illustrate with examples how to use PhosphOrtholog to map novel PTM sites from cross-species MS-based phosphoproteomics data.
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Affiliation(s)
- Rima Chaudhuri
- Charles Perkins Centre, School of Life and Environmental Sciences, University of Sydney, Camperdown, NSW, 2006, Australia.
| | - Jean Yee Hwa Yang
- School of Mathematics and Statistics, University of Sydney, Camperdown, NSW, 2006, Australia
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16
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Crowgey EL, Matlock A, Fort-Bober J, Van Eky JE, Van Eyk JE. Mapping Biological Networks from Quantitative Data-Independent Acquisition Mass Spectrometry: Data to Knowledge Pipelines. Methods Mol Biol 2017; 1558:395-413. [PMID: 28150249 PMCID: PMC6844627 DOI: 10.1007/978-1-4939-6783-4_19] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Data-independent acquisition mass spectrometry (DIA-MS) strategies and applications provide unique advantages for qualitative and quantitative proteome probing of a biological sample allowing constant sensitivity and reproducibility across large sample sets. These advantages in LC-MS/MS are being realized in fundamental research laboratories and for clinical research applications. However, the ability to translate high-throughput raw LC-MS/MS proteomic data into biological knowledge is a complex and difficult task requiring the use of many algorithms and tools for which there is no widely accepted standard and best practices are slowly being implemented. Today a single tool or approach inherently fails to capture the full interpretation that proteomics uniquely supplies, including the dynamics of quickly reversible chemically modified states of proteins, irreversible amino acid modifications, signaling truncation events, and, finally, determining the presence of protein from allele-specific transcripts. This chapter highlights key steps and publicly available algorithms required to translate DIA-MS data into knowledge.
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Affiliation(s)
| | - Andrea Matlock
- Advanced Clinical BioSystems Research Institute, Cedars Sinai Medical Center, Heart Institute, 127 S. San Vicente Blvd, Los Angeles, CA 90048
| | | | - Jennifer E Van Eky
- Cedar Sinai, Advanced Clinical BioSystems Research Institute, Cedars Sinai Medical Center, Heart Institute, 127 S. San Vicente Blvd, Los Angeles, CA 90048
| | - Jennifer E Van Eyk
- Advanced Clinical BioSystems Research Institute, Cedars Sinai Medical Center, Heart Institute, Los Angeles, CA, 90048, USA
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Affiliation(s)
- Nicholas M. Riley
- Genome Center of Wisconsin, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Joshua J. Coon
- Genome Center of Wisconsin, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
- Department of Biomolecular Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
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18
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McDowell G, Philpott A. New Insights Into the Role of Ubiquitylation of Proteins. INTERNATIONAL REVIEW OF CELL AND MOLECULAR BIOLOGY 2016; 325:35-88. [DOI: 10.1016/bs.ircmb.2016.02.002] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Hoffman NJ, Parker BL, Chaudhuri R, Fisher-Wellman KH, Kleinert M, Humphrey SJ, Yang P, Holliday M, Trefely S, Fazakerley DJ, Stöckli J, Burchfield JG, Jensen TE, Jothi R, Kiens B, Wojtaszewski JFP, Richter EA, James DE. Global Phosphoproteomic Analysis of Human Skeletal Muscle Reveals a Network of Exercise-Regulated Kinases and AMPK Substrates. Cell Metab 2015; 22:922-35. [PMID: 26437602 PMCID: PMC4635038 DOI: 10.1016/j.cmet.2015.09.001] [Citation(s) in RCA: 283] [Impact Index Per Article: 31.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2015] [Revised: 06/29/2015] [Accepted: 09/01/2015] [Indexed: 12/19/2022]
Abstract
Exercise is essential in regulating energy metabolism and whole-body insulin sensitivity. To explore the exercise signaling network, we undertook a global analysis of protein phosphorylation in human skeletal muscle biopsies from untrained healthy males before and after a single high-intensity exercise bout, revealing 1,004 unique exercise-regulated phosphosites on 562 proteins. These included substrates of known exercise-regulated kinases (AMPK, PKA, CaMK, MAPK, mTOR), yet the majority of kinases and substrate phosphosites have not previously been implicated in exercise signaling. Given the importance of AMPK in exercise-regulated metabolism, we performed a targeted in vitro AMPK screen and employed machine learning to predict exercise-regulated AMPK substrates. We validated eight predicted AMPK substrates, including AKAP1, using targeted phosphoproteomics. Functional characterization revealed an undescribed role for AMPK-dependent phosphorylation of AKAP1 in mitochondrial respiration. These data expose the unexplored complexity of acute exercise signaling and provide insights into the role of AMPK in mitochondrial biochemistry.
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Affiliation(s)
- Nolan J Hoffman
- Charles Perkins Centre, School of Molecular Bioscience, The University of Sydney, Sydney, NSW 2006, Australia
| | - Benjamin L Parker
- Charles Perkins Centre, School of Molecular Bioscience, The University of Sydney, Sydney, NSW 2006, Australia
| | - Rima Chaudhuri
- Charles Perkins Centre, School of Molecular Bioscience, The University of Sydney, Sydney, NSW 2006, Australia
| | | | - Maximilian Kleinert
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia; University of Copenhagen, August Krogh Centre, Department of Nutrition, Exercise and Sports, Copenhagen 2100, Denmark
| | - Sean J Humphrey
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia
| | - Pengyi Yang
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia; Systems Biology Section, Epigenetics & Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Mira Holliday
- Charles Perkins Centre, School of Molecular Bioscience, The University of Sydney, Sydney, NSW 2006, Australia
| | - Sophie Trefely
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia
| | - Daniel J Fazakerley
- Charles Perkins Centre, School of Molecular Bioscience, The University of Sydney, Sydney, NSW 2006, Australia
| | - Jacqueline Stöckli
- Charles Perkins Centre, School of Molecular Bioscience, The University of Sydney, Sydney, NSW 2006, Australia
| | - James G Burchfield
- Charles Perkins Centre, School of Molecular Bioscience, The University of Sydney, Sydney, NSW 2006, Australia
| | - Thomas E Jensen
- University of Copenhagen, August Krogh Centre, Department of Nutrition, Exercise and Sports, Copenhagen 2100, Denmark
| | - Raja Jothi
- Systems Biology Section, Epigenetics & Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Bente Kiens
- University of Copenhagen, August Krogh Centre, Department of Nutrition, Exercise and Sports, Copenhagen 2100, Denmark
| | - Jørgen F P Wojtaszewski
- University of Copenhagen, August Krogh Centre, Department of Nutrition, Exercise and Sports, Copenhagen 2100, Denmark
| | - Erik A Richter
- University of Copenhagen, August Krogh Centre, Department of Nutrition, Exercise and Sports, Copenhagen 2100, Denmark
| | - David E James
- Charles Perkins Centre, School of Molecular Bioscience, The University of Sydney, Sydney, NSW 2006, Australia; School of Medicine, The University of Sydney, Sydney, NSW 2006, Australia.
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