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Holbrook-Smith D, Trouillon J, Sauer U. Metabolomics and Microbial Metabolism: Toward a Systematic Understanding. Annu Rev Biophys 2024; 53:41-64. [PMID: 38109374 DOI: 10.1146/annurev-biophys-030722-021957] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
Over the past decades, our understanding of microbial metabolism has increased dramatically. Metabolomics, a family of techniques that are used to measure the quantities of small molecules in biological samples, has been central to these efforts. Advances in analytical chemistry have made it possible to measure the relative and absolute concentrations of more and more compounds with increasing levels of certainty. In this review, we highlight how metabolomics has contributed to understanding microbial metabolism and in what ways it can still be deployed to expand our systematic understanding of metabolism. To that end, we explain how metabolomics was used to (a) characterize network topologies of metabolism and its regulation networks, (b) elucidate the control of metabolic function, and (c) understand the molecular basis of higher-order phenomena. We also discuss areas of inquiry where technological advances should continue to increase the impact of metabolomics, as well as areas where our understanding is bottlenecked by other factors such as the availability of statistical and modeling frameworks that can extract biological meaning from metabolomics data.
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Affiliation(s)
| | - Julian Trouillon
- Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland;
| | - Uwe Sauer
- Institute of Molecular Systems Biology, ETH Zürich, Zürich, Switzerland;
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2
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Dixon RA, Dickinson AJ. A century of studying plant secondary metabolism-From "what?" to "where, how, and why?". PLANT PHYSIOLOGY 2024; 195:48-66. [PMID: 38163637 PMCID: PMC11060662 DOI: 10.1093/plphys/kiad596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 08/15/2023] [Indexed: 01/03/2024]
Abstract
Over the past century, early advances in understanding the identity of the chemicals that collectively form a living plant have led scientists to deeper investigations exploring where these molecules localize, how they are made, and why they are synthesized in the first place. Many small molecules are specific to the plant kingdom and have been termed plant secondary metabolites, despite the fact that they can play primary and essential roles in plant structure, development, and response to the environment. The past 100 yr have witnessed elucidation of the structure, function, localization, and biosynthesis of selected plant secondary metabolites. Nevertheless, many mysteries remain about the vast diversity of chemicals produced by plants and their roles in plant biology. From early work characterizing unpurified plant extracts, to modern integration of 'omics technology to discover genes in metabolite biosynthesis and perception, research in plant (bio)chemistry has produced knowledge with substantial benefits for society, including human medicine and agricultural biotechnology. Here, we review the history of this work and offer suggestions for future areas of exploration. We also highlight some of the recently developed technologies that are leading to ongoing research advances.
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Affiliation(s)
- Richard A Dixon
- BioDiscovery Institute and Department of Biological Sciences, University of North Texas, Denton, TX 76203, USA
| | - Alexandra Jazz Dickinson
- Department of Cell and Developmental Biology, University of California at San Diego, La Jolla, CA 92093, USA
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3
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Li S, Looby N, Chandran V, Kulasingam V. Challenges in the Metabolomics-Based Biomarker Validation Pipeline. Metabolites 2024; 14:200. [PMID: 38668328 PMCID: PMC11051909 DOI: 10.3390/metabo14040200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 03/27/2024] [Accepted: 03/31/2024] [Indexed: 04/28/2024] Open
Abstract
As end-products of the intersection between the genome and environmental influences, metabolites represent a promising approach to the discovery of novel biomarkers for diseases. However, many potential biomarker candidates identified by metabolomics studies fail to progress beyond analytical validation for routine implementation in clinics. Awareness of the challenges present can facilitate the development and advancement of innovative strategies that allow improved and more efficient applications of metabolite-based markers in clinical settings. This minireview provides a comprehensive summary of the pre-analytical factors, required analytical validation studies, and kit development challenges that must be resolved before the successful translation of novel metabolite biomarkers originating from research. We discuss the necessity for strict protocols for sample collection, storage, and the regulatory requirements to be fulfilled for a bioanalytical method to be considered as analytically validated. We focus especially on the blood as a biological matrix and liquid chromatography coupled with tandem mass spectrometry as the analytical platform for biomarker validation. Furthermore, we examine the challenges of developing a commercially viable metabolomics kit for distribution. To bridge the gap between the research lab and clinical implementation and utility of relevant metabolites, the understanding of the translational challenges for a biomarker panel is crucial for more efficient development of metabolomics-based precision medicine.
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Affiliation(s)
- Shenghan Li
- Division of Rheumatology, Psoriatic Arthritis Program, Schroeder Arthritis Program, University Health Network, Toronto, ON M5T 0S8, Canada; (S.L.); (N.L.)
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A1, Canada
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
| | - Nikita Looby
- Division of Rheumatology, Psoriatic Arthritis Program, Schroeder Arthritis Program, University Health Network, Toronto, ON M5T 0S8, Canada; (S.L.); (N.L.)
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
- Division of Orthopaedic Surgery, Osteoarthritis Research Program, Schroeder Arthritis Institute, University Health Network, Toronto, ON M5T 0S8, Canada
| | - Vinod Chandran
- Division of Rheumatology, Psoriatic Arthritis Program, Schroeder Arthritis Program, University Health Network, Toronto, ON M5T 0S8, Canada; (S.L.); (N.L.)
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A1, Canada
- Krembil Research Institute, University Health Network, Toronto, ON M5T 0S8, Canada
- Division of Rheumatology, Department of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Vathany Kulasingam
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5S 1A1, Canada
- Division of Clinical Biochemistry, Laboratory Medicine Program, University Health Network, Toronto, ON M5G 2C4, Canada
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4
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Bacher S, Schmitz ML. Open questions in the NF-κB field. BIOCHIMICA ET BIOPHYSICA ACTA. MOLECULAR CELL RESEARCH 2024; 1871:119469. [PMID: 37951506 DOI: 10.1016/j.bbamcr.2023.119469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 03/23/2023] [Accepted: 03/23/2023] [Indexed: 11/14/2023]
Abstract
A variety of stress signals leads to activation of the inducible transcription factor NF-κB, one of the master regulators of the innate immune response. Despite a wealth of information available on the NF-κB core components and its control by different activation pathways and negative feedback loops, several levels of complexity hamper our understanding of the system. This has also contributed to the limited success of NF-κB inhibitors in the clinic and explains some of their unexpected effects. Here we consider the molecular and cellular events generating this complexity at all levels and point to a number of unresolved questions in the field. We also discuss potential future experimental and computational strategies to provide a deeper understanding of NF-κB and its coregulatory signaling networks.
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Affiliation(s)
- Susanne Bacher
- Institute of Biochemistry, Justus Liebig University Giessen (Germany), Member of the German Center for Lung Research (DZL), Germany
| | - M Lienhard Schmitz
- Institute of Biochemistry, Justus Liebig University Giessen (Germany), Member of the German Center for Lung Research (DZL), Germany.
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5
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Tozetto R, Santos Rocha B, Assis de Andrade E, Stolz Cruz L, da Rosa RL, Machinski I, Lemos de Oliveira É, Borges Monteiro JR, Koga AY, Cavalcante Lipinski L, Meurer EC, Kitagawa RR, Beltrame FL. Study of the Antioxidant, Antimicrobial, and Wound Healing Properties of Raw Hydrolyzed Extract from Nile Tilapia Skin (Oreochromis niloticus). Chem Biodivers 2023; 20:e202300863. [PMID: 37747297 DOI: 10.1002/cbdv.202300863] [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: 06/13/2023] [Revised: 09/19/2023] [Accepted: 09/24/2023] [Indexed: 09/26/2023]
Abstract
Oreochromis niloticus (Nile tilapia) skin is a by-product of Brazilian fish farming, rich in collagen. The present study aims to evaluate the wound healing, antioxidant, and antimicrobial potential of the raw hydrolyzed extract of Nile tilapia skin, as well as the identification of the main compounds. The in vitro activity was performed using antioxidant, antimicrobial and scratch wound healing assays. An in vivo experiment was performed to evaluate the wound healing potential. On days 1, 7, 14 and 21, the lesions were photographed to assess wound retraction and on the 7th , 14th and 21st days the skins were removed for histological evaluation and the blood of the animals was collected for glutamic oxaloacetic transaminase and glutamic pyruvic transaminase determination. The chemical study was carried out through liquid chromatography-tandem mass spectrometry and de novo sequencing of peptides. The in vitro assays showed a reduction of the gap area in 24 h, dose-dependent antimicrobial activity for both bacteria, and antioxidant activity. The chemical analysis highlighted the presence of active biopeptides. The histological evaluation showed that the raw hydrolyzed extract of Nile tilapia skin has a healing potential, and does not present toxicological effects; therefore, is promising for the treatment of wounds.
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Affiliation(s)
- Rodrigo Tozetto
- Department of Pharmaceutical Sciences, State University of Ponta Grossa, General, Carlos Cavalcanti Avenue, 4748, 84900-030, Paraná, Brazil
| | - Beatriz Santos Rocha
- Department of Chemistry, Federal University of Paraná, Dr. João Maxímiano Street, 426, 86900-000, Paraná, Brazil
| | - Evelyn Assis de Andrade
- Pharmaceutical Science Post-graduation Program, State University of Ponta Grossa, General Carlos Cavalcanti Avenue, 4748, 84900-030, Paraná, Brazil
| | - Luiza Stolz Cruz
- Department of Pharmaceutical Sciences, State University of Centro-Oeste, Élio Antonio Dalla Vecchia Street, 838, 85040-167, Paraná, Brazil
| | - Rosana Letícia da Rosa
- Pharmaceutical Science Post-graduation Program, State University of Ponta Grossa, General Carlos Cavalcanti Avenue, 4748, 84900-030, Paraná, Brazil
| | - Isadora Machinski
- Pharmaceutical Science Post-graduation Program, State University of Ponta Grossa, General Carlos Cavalcanti Avenue, 4748, 84900-030, Paraná, Brazil
| | - Évelin Lemos de Oliveira
- Chemistry Post-graduation Program, State University of Maringá, Colombo Avenue, 5790, 87020-900, Paraná, Brazil
| | - Jessica Raquel Borges Monteiro
- Department of Pharmaceutical Sciences, Federal University of Espírito Santo, Fernando Ferrari Avenue, 514, 29075-910, Espírito Santo, Brazil
| | - Adriana Yuriko Koga
- Department of Medicine, State University of Ponta Grossa, General Carlos Cavalcanti Avenue, 4748, 84900-030, Paraná, Brazil
| | - Leandro Cavalcante Lipinski
- Department of Medicine, State University of Ponta Grossa, General Carlos Cavalcanti Avenue, 4748, 84900-030, Paraná, Brazil
| | - Eduardo César Meurer
- Department of Chemistry, Federal University of Paraná, Dr. João Maxímiano Street, 426, 86900-000, Paraná, Brazil
| | - Rodrigo Rezende Kitagawa
- Department of Pharmaceutical Sciences, Federal University of Espírito Santo, Fernando Ferrari Avenue, 514, 29075-910, Espírito Santo, Brazil
| | - Flávio Luís Beltrame
- Department of Pharmaceutical Sciences, State University of Ponta Grossa, General, Carlos Cavalcanti Avenue, 4748, 84900-030, Paraná, Brazil
- Pharmaceutical Science Post-graduation Program, State University of Ponta Grossa, General Carlos Cavalcanti Avenue, 4748, 84900-030, Paraná, Brazil
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Minen RI, Thirumalaikumar VP, Skirycz A. Proteinogenic dipeptides, an emerging class of small-molecule regulators. CURRENT OPINION IN PLANT BIOLOGY 2023; 75:102395. [PMID: 37311365 DOI: 10.1016/j.pbi.2023.102395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 05/07/2023] [Accepted: 05/10/2023] [Indexed: 06/15/2023]
Abstract
Proteinogenic dipeptides, with few known exceptions, are products of protein degradation. Dipeptide levels respond to the changes in the environment, often in a dipeptide-specific manner. What drives this specificity is currently unknown; what likely contributes is the activity of the different peptidases that cleave off the terminal dipeptide from the longer peptides. Dipeptidases that degrade dipeptides to amino acids, and the turnover rates of the "substrate" proteins/peptides. Plants can both uptake dipeptides from the soil, but dipeptides are also found in root exudates. Dipeptide transporters, members of the proton-coupled peptide transporters NTR1/PTR family, contribute to nitrogen reallocation between the sink and source tissues. Besides their role in nitrogen distribution, it becomes increasingly clear that dipeptides may also serve regulatory, dipeptide-specific functions. Dipeptides are found in protein complexes affecting the activity of their protein partners. Moreover, dipeptide supplementation leads to cellular phenotypes reflected in changes in plant growth and stress tolerance. Herein we will review the current understanding of dipeptides' metabolism, transport, and functions and discuss significant challenges and future directions for the comprehensive characterization of this fascinating but underrated group of small-molecule compounds.
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Affiliation(s)
| | | | - Aleksandra Skirycz
- Boyce Thompson Institute, 14853, Ithaca, NY, USA; Cornell University, 14853, Ithaca, NY, USA.
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7
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Liu T, Gao C. Decode protein-metabolite regulatory network: one MIDAS at a time. Signal Transduct Target Ther 2023; 8:318. [PMID: 37607931 PMCID: PMC10444752 DOI: 10.1038/s41392-023-01566-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 06/07/2023] [Accepted: 07/12/2023] [Indexed: 08/24/2023] Open
Affiliation(s)
- Tian Liu
- Department of Pharmacology and Systems Physiology, University of Cincinnati, Cincinnati, OH, USA
| | - Chen Gao
- Department of Pharmacology and Systems Physiology, University of Cincinnati, Cincinnati, OH, USA.
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8
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Wang C, Yuan C, Wang Y, Chen R, Shi Y, Zhang T, Xue F, Patti GJ, Wei L, Hou Q. MPI-VGAE: protein-metabolite enzymatic reaction link learning by variational graph autoencoders. Brief Bioinform 2023; 24:bbad189. [PMID: 37225420 PMCID: PMC10359079 DOI: 10.1093/bib/bbad189] [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: 02/20/2023] [Revised: 04/10/2023] [Accepted: 04/27/2023] [Indexed: 05/26/2023] Open
Abstract
Enzymatic reactions are crucial to explore the mechanistic function of metabolites and proteins in cellular processes and to understand the etiology of diseases. The increasing number of interconnected metabolic reactions allows the development of in silico deep learning-based methods to discover new enzymatic reaction links between metabolites and proteins to further expand the landscape of existing metabolite-protein interactome. Computational approaches to predict the enzymatic reaction link by metabolite-protein interaction (MPI) prediction are still very limited. In this study, we developed a Variational Graph Autoencoders (VGAE)-based framework to predict MPI in genome-scale heterogeneous enzymatic reaction networks across ten organisms. By incorporating molecular features of metabolites and proteins as well as neighboring information in the MPI networks, our MPI-VGAE predictor achieved the best predictive performance compared to other machine learning methods. Moreover, when applying the MPI-VGAE framework to reconstruct hundreds of metabolic pathways, functional enzymatic reaction networks and a metabolite-metabolite interaction network, our method showed the most robust performance among all scenarios. To the best of our knowledge, this is the first MPI predictor by VGAE for enzymatic reaction link prediction. Furthermore, we implemented the MPI-VGAE framework to reconstruct the disease-specific MPI network based on the disrupted metabolites and proteins in Alzheimer's disease and colorectal cancer, respectively. A substantial number of novel enzymatic reaction links were identified. We further validated and explored the interactions of these enzymatic reactions using molecular docking. These results highlight the potential of the MPI-VGAE framework for the discovery of novel disease-related enzymatic reactions and facilitate the study of the disrupted metabolisms in diseases.
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Affiliation(s)
- Cheng Wang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, 250000, China
| | - Chuang Yuan
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, 250000, China
| | - Yahui Wang
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, 63130, USA
- Center for Metabolomics and Isotope Tracing, Washington University in St. Louis, St. Louis, MO, 63130, USA
| | - Ranran Chen
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, 250000, China
| | - Yuying Shi
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, 250000, China
| | - Tao Zhang
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, 250000, China
| | - Fuzhong Xue
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, 250000, China
| | - Gary J Patti
- Department of Chemistry, Washington University in St. Louis, St. Louis, MO, 63130, USA
- Department of Medicine, Washington University in St. Louis, St. Louis, MO, 63130, USA
- Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO, 63130, USA
- Center for Metabolomics and Isotope Tracing, Washington University in St. Louis, St. Louis, MO, 63130, USA
| | - Leyi Wei
- School of Software, Shandong University, Jinan, 250100, China
| | - Qingzhen Hou
- Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, 250012, China
- National Institute of Health Data Science of China, Shandong University, Jinan, 250000, China
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9
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Soleymani Babadi F, Razaghi-Moghadam Z, Zare-Mirakabad F, Nikoloski Z. Prediction of metabolite-protein interactions based on integration of machine learning and constraint-based modeling. BIOINFORMATICS ADVANCES 2023; 3:vbad098. [PMID: 37521309 PMCID: PMC10374491 DOI: 10.1093/bioadv/vbad098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 06/28/2023] [Accepted: 07/15/2023] [Indexed: 08/01/2023]
Abstract
Motivation Metabolite-protein interactions play an important role in regulating protein functions and metabolism. Yet, predictions of metabolite-protein interactions using genome-scale metabolic networks are lacking. Here, we fill this gap by presenting a computational framework, termed SARTRE, that employs features corresponding to shadow prices determined in the context of flux variability analysis to predict metabolite-protein interactions using supervised machine learning. Results By using gold standards for metabolite-protein interactomes and well-curated genome-scale metabolic models of Escherichia coli and Saccharomyces cerevisiae, we found that the implementation of SARTRE with random forest classifiers accurately predicts metabolite-protein interactions, supported by an average area under the receiver operating curve of 0.86 and 0.85, respectively. Ranking of features based on their importance for classification demonstrated the key role of shadow prices in predicting metabolite-protein interactions. The quality of predictions is further supported by the excellent agreement of the organism-specific classifiers on unseen interactions shared between the two model organisms. Further, predictions from SARTRE are highly competitive against those obtained from a recent deep-learning approach relying on a variety of protein and metabolite features. Together, these findings show that features extracted from constraint-based analyses of metabolic networks pave the way for understanding the functional roles of the interactions between proteins and small molecules. Availability and implementation https://github.com/fayazsoleymani/SARTRE.
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Affiliation(s)
- Fayaz Soleymani Babadi
- Departement of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran
| | - Zahra Razaghi-Moghadam
- Systems Biology and Mathematical Biology, Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany
| | - Fatemeh Zare-Mirakabad
- Departement of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran
| | - Zoran Nikoloski
- Corresponding author. Bioinformatics Department, Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476 Potsdam, Germany. E-mail:
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10
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Pandey AK, Loscalzo J. Network medicine: an approach to complex kidney disease phenotypes. Nat Rev Nephrol 2023:10.1038/s41581-023-00705-0. [PMID: 37041415 DOI: 10.1038/s41581-023-00705-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/13/2023] [Indexed: 04/13/2023]
Abstract
Scientific reductionism has been the basis of disease classification and understanding for more than a century. However, the reductionist approach of characterizing diseases from a limited set of clinical observations and laboratory evaluations has proven insufficient in the face of an exponential growth in data generated from transcriptomics, proteomics, metabolomics and deep phenotyping. A new systematic method is necessary to organize these datasets and build new definitions of what constitutes a disease that incorporates both biological and environmental factors to more precisely describe the ever-growing complexity of phenotypes and their underlying molecular determinants. Network medicine provides such a conceptual framework to bridge these vast quantities of data while providing an individualized understanding of disease. The modern application of network medicine principles is yielding new insights into the pathobiology of chronic kidney diseases and renovascular disorders by expanding the understanding of pathogenic mediators, novel biomarkers and new options for renal therapeutics. These efforts affirm network medicine as a robust paradigm for elucidating new advances in the diagnosis and treatment of kidney disorders.
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Affiliation(s)
- Arvind K Pandey
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Joseph Loscalzo
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA.
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11
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Exploring the Potential of Black Soldier Fly Larval Proteins as Bioactive Peptide Sources through in Silico Gastrointestinal Proteolysis: A Cheminformatic Investigation. Catalysts 2023. [DOI: 10.3390/catal13030605] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2023] Open
Abstract
Despite their potential as a protein source for human consumption, the health benefits of black soldier fly larvae (BSFL) proteins following human gastrointestinal (GI) digestion are poorly understood. This computational study explored the potential of BSFL proteins to release health-promoting peptides after human GI digestion. Twenty-six proteins were virtually proteolyzed with GI proteases. The resultant peptides were screened for high GI absorption and non-toxicity. Shortlisted peptides were searched against the BIOPEP-UWM and Scopus databases to identify their bioactivities. The potential of the peptides as inhibitors of myeloperoxidase (MPO), NADPH oxidase (NOX), and xanthine oxidase (XO), as well as a disruptor of Keap1–Nrf2 protein–protein interaction, were predicted using molecular docking and dynamics simulation. Our results revealed that about 95% of the 5218 fragments generated from the proteolysis of BSFL proteins came from muscle proteins. Dipeptides comprised the largest group (about 25%) of fragments arising from each muscular protein. Screening of 1994 di- and tripeptides using SwissADME and STopTox tools revealed 65 unique sequences with high GI absorption and non-toxicity. A search of the databases identified 16 antioxidant peptides, 14 anti-angiotensin-converting enzyme peptides, and 17 anti-dipeptidyl peptidase IV peptides among these sequences. Results from molecular docking and dynamic simulation suggest that the dipeptide DF has the potential to inhibit Keap1–Nrf2 interaction and interact with MPO within a short time frame, whereas the dipeptide TF shows promise as an XO inhibitor. BSFL peptides were likely weak NOX inhibitors. Our in silico results suggest that upon GI digestion, BSFL proteins may yield high-GI-absorbed and non-toxic peptides with potential health benefits. This study is the first to investigate the bioactivity of peptides liberated from BSFL proteins following human GI digestion. Our findings provide a basis for further investigations into the potential use of BSFL proteins as a functional food ingredient with significant health benefits.
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12
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Wang C, Yuan C, Wang Y, Chen R, Shi Y, Patti GJ, Hou Q. Genome-scale enzymatic reaction prediction by variational graph autoencoders. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.08.531729. [PMID: 36945484 PMCID: PMC10028866 DOI: 10.1101/2023.03.08.531729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/14/2023]
Abstract
Background Enzymatic reaction networks are crucial to explore the mechanistic function of metabolites and proteins in biological systems and understanding the etiology of diseases and potential target for drug discovery. The increasing number of metabolic reactions allows the development of deep learning-based methods to discover new enzymatic reactions, which will expand the landscape of existing enzymatic reaction networks to investigate the disrupted metabolisms in diseases. Results In this study, we propose the MPI-VGAE framework to predict metabolite-protein interactions (MPI) in a genome-scale heterogeneous enzymatic reaction network across ten organisms with thousands of enzymatic reactions. We improved the Variational Graph Autoencoders (VGAE) model to incorporate both molecular features of metabolites and proteins as well as neighboring features to achieve the best predictive performance of MPI. The MPI-VGAE framework showed robust performance in the reconstruction of hundreds of metabolic pathways and five functional enzymatic reaction networks. The MPI-VGAE framework was also applied to a homogenous metabolic reaction network and achieved as high performance as other state-of-art methods. Furthermore, the MPI-VGAE framework could be implemented to reconstruct the disease-specific MPI network based on hundreds of disrupted metabolites and proteins in Alzheimer's disease and colorectal cancer, respectively. A substantial number of new potential enzymatic reactions were predicted and validated by molecular docking. These results highlight the potential of the MPI-VGAE framework for the discovery of novel disease-related enzymatic reactions and drug targets in real-world applications. Data availability and implementation The MPI-VGAE framework and datasets are publicly accessible on GitHub https://github.com/mmetalab/mpi-vgae . Author Biographies Cheng Wang received his Ph.D. in Chemistry from The Ohio State Univesity, USA. He is currently a Assistant Professor in School of Public Health at Shandong University, China. His research interests include bioinformatics, machine learning-based approach with applications to biomedical networks. Chuang Yuan is a research assistant at Shandong University. He obtained the MS degree in Biology at the University of Science and Technology of China. His research interests include biochemistry & molecular biology, cell biology, biomedicine, bioinformatics, and computational biology. Yahui Wang is a PhD student in Department of Chemistry at Washington University in St. Louis. Her research interests include biochemistry, mass spectrometry-based metabolomics, and cancer metabolism. Ranran Chen is a master graduate student in School of Public Health at University of Shandong, China. Yuying Shi is a master graduate student in School of Public Health at University of Shandong, China. Gary J. Patti is the Michael and Tana Powell Professor at Washington University in St. Louis, where he holds appointments in the Department of Chemisrty and the Department of Medicine. He is also the Senior Director of the Center for Metabolomics and Isotope Tracing at Washington University. His research interests include metabolomics, bioinformatics, high-throughput mass spectrometry, environmental health, cancer, and aging. Leyi Wei received his Ph.D. in Computer Science from Xiamen University, China. He is currently a Professor in School of Software at Shandong University, China. His research interests include machine learning and its applications to bioinformatics. Qingzhen Hou received his Ph.D. in the Centre for Integrative Bioinformatics VU (IBIVU) from Vrije Universiteit Amsterdam, the Netherlands. Since 2020, He has serveved as the head of Bioinformatics Center in National Institute of Health Data Science of China and Assistant Professor in School of Public Health, Shandong University, China. His areas of research are bioinformatics and computational biophysics. Key points Genome-scale heterogeneous networks of metabolite-protein interaction (MPI) based on thousands of enzymatic reactions across ten organisms were constructed semi-automatically.An enzymatic reaction prediction method called Metabolite-Protein Interaction Variational Graph Autoencoders (MPI-VGAE) was developed and optimized to achieve higher performance compared with existing machine learning methods by using both molecular features of metabolites and proteins.MPI-VGAE is broadly useful for applications involving the reconstruction of metabolic pathways, functional enzymatic reaction networks, and homogenous networks (e.g., metabolic reaction networks).By implementing MPI-VGAE to Alzheimer's disease and colorectal cancer, we obtained several novel disease-related protein-metabolite reactions with biological meanings. Moreover, we further investigated the reasonable binding details of protein-metabolite interactions using molecular docking approaches which provided useful information for disease mechanism and drug design.
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13
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Schlossarek D, Zhang Y, Sokolowska EM, Fernie AR, Luzarowski M, Skirycz A. Don't let go: co-fractionation mass spectrometry for untargeted mapping of protein-metabolite interactomes. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2023; 113:904-914. [PMID: 36575913 DOI: 10.1111/tpj.16084] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 12/20/2022] [Accepted: 12/23/2022] [Indexed: 06/17/2023]
Abstract
The chemical complexity of metabolomes goes hand in hand with their functional diversity. Small molecules have many essential roles, many of which are executed by binding and modulating the function of a protein partner. The complex and dynamic protein-metabolite interaction (PMI) network underlies most if not all biological processes, but remains under-characterized. Herein, we highlight how co-fractionation mass spectrometry (CF-MS), a well-established approach to map protein assemblies, can be used for proteome and metabolome identification of the PMIs. We will review recent CF-MS studies, discuss the main advantages and limitations, summarize the available CF-MS guidelines, and outline future challenges and opportunities.
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Affiliation(s)
- Dennis Schlossarek
- Depeartment One, Max-Planck-Institute of Molecular Plant Physiology, 14476, Potsdam, Germany
| | - Youjun Zhang
- Depeartment One, Max-Planck-Institute of Molecular Plant Physiology, 14476, Potsdam, Germany
| | - Ewelina M Sokolowska
- Depeartment One, Max-Planck-Institute of Molecular Plant Physiology, 14476, Potsdam, Germany
| | - Alisdair R Fernie
- Depeartment One, Max-Planck-Institute of Molecular Plant Physiology, 14476, Potsdam, Germany
| | - Marcin Luzarowski
- Center for Molecular Biology Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Aleksandra Skirycz
- Depeartment One, Max-Planck-Institute of Molecular Plant Physiology, 14476, Potsdam, Germany
- Boyce Thompson Institute, Ithaca, NY, 14850, USA
- School of Integrative Plant Science, Cornell University, Ithaca, NY, 14850, USA
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14
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Kurbatov I, Dolgalev G, Arzumanian V, Kiseleva O, Poverennaya E. The Knowns and Unknowns in Protein-Metabolite Interactions. Int J Mol Sci 2023; 24:ijms24044155. [PMID: 36835565 PMCID: PMC9964805 DOI: 10.3390/ijms24044155] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Revised: 02/11/2023] [Accepted: 02/15/2023] [Indexed: 02/22/2023] Open
Abstract
Increasing attention has been focused on the study of protein-metabolite interactions (PMI), which play a key role in regulating protein functions and directing an orchestra of cellular processes. The investigation of PMIs is complicated by the fact that many such interactions are extremely short-lived, which requires very high resolution in order to detect them. As in the case of protein-protein interactions, protein-metabolite interactions are still not clearly defined. Existing assays for detecting protein-metabolite interactions have an additional limitation in the form of a limited capacity to identify interacting metabolites. Thus, although recent advances in mass spectrometry allow the routine identification and quantification of thousands of proteins and metabolites today, they still need to be improved to provide a complete inventory of biological molecules, as well as all interactions between them. Multiomic studies aimed at deciphering the implementation of genetic information often end with the analysis of changes in metabolic pathways, as they constitute one of the most informative phenotypic layers. In this approach, the quantity and quality of knowledge about PMIs become vital to establishing the full scope of crosstalk between the proteome and the metabolome in a biological object of interest. In this review, we analyze the current state of investigation into the detection and annotation of protein-metabolite interactions, describe the recent progress in developing associated research methods, and attempt to deconstruct the very term "interaction" to advance the field of interactomics further.
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15
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Muralidhara P, Ewald JC. Protein-Metabolite Interactions Shape Cellular Metabolism and Physiology. Methods Mol Biol 2023; 2554:1-10. [PMID: 36178616 DOI: 10.1007/978-1-0716-2624-5_1] [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] [Indexed: 06/16/2023]
Abstract
Protein-metabolite interactions regulate many important cellular processes but still remain understudied. Recent technological advancements are gradually uncovering the complexity of the protein-metabolite interactome. Here, we highlight some classic and recent examples of how protein metabolite interactions regulate metabolism, both locally and globally, and how this contributes to cellular physiology. We also discuss the importance of these interactions in diseases such as cancer.
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Affiliation(s)
| | - Jennifer C Ewald
- Interfaculty Institute of Cell Biology, University of Tübingen, Tübingen, Germany
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16
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Luzarowski M, Sokolowska EM, Schlossarek D, Skirycz A. PROMIS: Co-fractionation Mass Spectrometry for Analysis of Protein-Metabolite Interactions. Methods Mol Biol 2023; 2554:141-153. [PMID: 36178625 DOI: 10.1007/978-1-0716-2624-5_10] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
The roles of small molecules in every aspect of life have been gaining increased recognition. Many are known to exert their effect by binding proteins-but a comprehensive overview of protein-metabolite interactions (PMIs) is missing. Recently we devised a non-targeted method for detecting PMIs using size-exclusion chromatography followed by proteomic and metabolomic analysis: PROMIS. Under test this method was able to identify known PMIs such as enzyme-cofactor complexes as well as novel ones.
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Affiliation(s)
- Marcin Luzarowski
- Zentrum für Molekulare Biologie der Universität Heidelberg, Potsdam, Germany
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17
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Figueroa NE, Hernandez-Sanchez IE, Maruri-Lopez I, Chodasiewicz M. Affinity Purification Protocol Starting with a Small Molecule as Bait. Methods Mol Biol 2023; 2554:11-19. [PMID: 36178617 DOI: 10.1007/978-1-0716-2624-5_2] [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] [Indexed: 06/16/2023]
Abstract
Protein-metabolite interactions (PMIs) are fundamental for several biological processes. Even though PMI studies have increased in recent years, our knowledge is still limited. The screening of PMIs using small molecules as bait will broaden our ability to uncover novel PMIs, setting the basis for establishing their biological relevance. Here, we describe a protocol that allows the identification of multiple protein partners for one ligand. This protocol describes a straightforward methodology that can be adapted to a wide variety of organisms.
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Affiliation(s)
- Nicolás E Figueroa
- Center for Desert Agriculture, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Itzell E Hernandez-Sanchez
- Center for Desert Agriculture, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Israel Maruri-Lopez
- Center for Desert Agriculture, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
| | - Monika Chodasiewicz
- Center for Desert Agriculture, Biological and Environmental Science and Engineering Division, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia.
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18
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Alseekh S, Zhu F, Vallarino JG, Sokolowska EM, Yoshida T, Bergmann S, Wendenburg R, Bolze A, Skirycz A, Avin-Wittenberg T, Fernie AR. Autophagy modulates the metabolism and growth of tomato fruit during development. HORTICULTURE RESEARCH 2022; 9:uhac129. [PMID: 35928403 PMCID: PMC9343920 DOI: 10.1093/hr/uhac129] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 05/29/2022] [Indexed: 06/15/2023]
Abstract
Although autophagy is a conserved mechanism operating across eukaryotes, its effects on crops and especially their metabolism has received relatively little attention. Indeed, whilst a few recent studies have used systems biology tools to look at the consequences of lack of autophagy in maize these focused on leaf tissues rather than the kernels. Here we utilized RNA interference (RNAi) to generate tomato plants that were deficient in the autophagy-regulating protease ATG4. Plants displayed an early senescence phenotype yet relatively mild changes in the foliar metabolome and were characterized by a reduced fruit yield phenotype. Metabolite profiling indicated that metabolites of ATG4-RNAi tomato leaves just exhibited minor alterations while that of fruit displayed bigger difference compared to the WT. In detail, many primary metabolites exhibited decreases in the ATG4-RNAi lines, such as proline, tryptophan and phenylalanine, while the representative secondary metabolites (quinic acid and 3-trans-caffeoylquinic acid) were present at substantially higher levels in ATG4-RNAi green fruits than in WT. Moreover, transcriptome analysis indicated that the most prominent differences were in the significant upregulation of organelle degradation genes involved in the proteasome or chloroplast vesiculation pathways, which was further confirmed by the reduced levels of chloroplastic proteins in the proteomics data. Furthermore, integration analysis of the metabolome, transcriptome and proteome data indicated that ATG4 significantly affected the lipid metabolism, chlorophyll binding proteins and chloroplast biosynthesis. These data collectively lead us to propose a more sophisticated model to explain the cellular co-ordination of the process of autophagy.
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Affiliation(s)
| | | | - José G Vallarino
- Max-Planck-Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | | | - Takuya Yoshida
- Max-Planck-Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Susan Bergmann
- Max-Planck-Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Regina Wendenburg
- Max-Planck-Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Antje Bolze
- Max-Planck-Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
| | - Aleksandra Skirycz
- Max-Planck-Institute of Molecular Plant Physiology, 14476 Potsdam-Golm, Germany
- Boyce Thompson Institute, 14850, Ithaca, US
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19
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Skirycz A, Fernie AR. Past accomplishments and future challenges of the multi-omics characterization of leaf growth. PLANT PHYSIOLOGY 2022; 189:473-489. [PMID: 35325227 PMCID: PMC9157134 DOI: 10.1093/plphys/kiac136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Accepted: 01/25/2022] [Indexed: 06/14/2023]
Abstract
The advent of omics technologies has revolutionized biology and advanced our understanding of all biological processes, including major developmental transitions in plants and animals. Here, we review the vast knowledge accumulated concerning leaf growth in terms of transcriptional regulation before turning our attention to the historically less well-characterized alterations at the protein and metabolite level. We will then discuss how the advent of biochemical methods coupled with metabolomics and proteomics can provide insight into the protein-protein and protein-metabolite interactome of the growing leaves. We finally highlight the substantial challenges in detection, spatial resolution, integration, and functional validation of the omics results, focusing on metabolomics as a prerequisite for a comprehensive understanding of small-molecule regulation of plant growth.
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Affiliation(s)
- Aleksandra Skirycz
- Max-Planck-Institute of Molecular Plant Physiology, Potsdam-Golm 14476, Germany
- Boyce Thompson Institute, Ithaca, New York 14853, USA
- Cornell University, Ithaca, New York 14853, USA
| | - Alisdair R Fernie
- Max-Planck-Institute of Molecular Plant Physiology, Potsdam-Golm 14476, Germany
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20
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Chodasiewicz M, Kerber O, Gorka M, Moreno JC, Maruri-Lopez I, Minen RI, Sampathkumar A, Nelson ADL, Skirycz A. 2',3'-cAMP treatment mimics the stress molecular response in Arabidopsis thaliana. PLANT PHYSIOLOGY 2022; 188:1966-1978. [PMID: 35043968 PMCID: PMC8968299 DOI: 10.1093/plphys/kiac013] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Accepted: 12/01/2021] [Indexed: 05/12/2023]
Abstract
The role of the RNA degradation product 2',3'-cyclic adenosine monophosphate (2',3'-cAMP) is poorly understood. Recent studies have identified 2',3'-cAMP in plant material and determined its role in stress signaling. The level of 2',3'-cAMP increases upon wounding, in the dark, and under heat, and 2',3'-cAMP binding to an RNA-binding protein, Rbp47b, promotes stress granule (SG) assembly. To gain further mechanistic insights into the function of 2',3'-cAMP, we used a multi-omics approach by combining transcriptomics, metabolomics, and proteomics to dissect the response of Arabidopsis (Arabidopsis thaliana) to 2',3'-cAMP treatment. We demonstrated that 2',3'-cAMP is metabolized into adenosine, suggesting that the well-known cyclic nucleotide-adenosine pathway of human cells might also exist in plants. Transcriptomics analysis revealed only minor overlap between 2',3'-cAMP- and adenosine-treated plants, suggesting that these molecules act through independent mechanisms. Treatment with 2',3'-cAMP changed the levels of hundreds of transcripts, proteins, and metabolites, many previously associated with plant stress responses, including protein and RNA degradation products, glucosinolates, chaperones, and SG components. Finally, we demonstrated that 2',3'-cAMP treatment influences the movement of processing bodies, confirming the role of 2',3'-cAMP in the formation and motility of membraneless organelles.
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Affiliation(s)
| | - Olga Kerber
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam, Germany
| | - Michal Gorka
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam, Germany
| | - Juan C Moreno
- Center for Desert Agriculture, Biological and Environmental Science and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam, Germany
| | - Israel Maruri-Lopez
- Center for Desert Agriculture, Biological and Environmental Science and Engineering Division (BESE), King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia
| | - Romina I Minen
- Boyce Thompson Institute, Cornell University, Ithaca, New York 14853, USA
| | - Arun Sampathkumar
- Max Planck Institute of Molecular Plant Physiology, 14476 Potsdam, Germany
| | - Andrew D L Nelson
- Boyce Thompson Institute, Cornell University, Ithaca, New York 14853, USA
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21
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Rajczewski AT, Jagtap PD, Griffin TJ. An overview of technologies for MS-based proteomics-centric multi-omics. Expert Rev Proteomics 2022; 19:165-181. [PMID: 35466851 PMCID: PMC9613604 DOI: 10.1080/14789450.2022.2070476] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
INTRODUCTION Mass spectrometry-based proteomics reveals dynamic molecular signatures underlying phenotypes reflecting normal and perturbed conditions in living systems. Although valuable on its own, the proteome has only one level of moleclar information, with the genome, epigenome, transcriptome, and metabolome, all providing complementary information. Multi-omic analysis integrating information from one or more of these other domains with proteomic information provides a more complete picture of molecular contributors to dynamic biological systems. AREAS COVERED Here, we discuss the improvements to mass spectrometry-based technologies, focused on peptide-based, bottom-up approaches that have enabled deep, quantitative characterization of complex proteomes. These advances are facilitating the integration of proteomics data with other 'omic information, providing a more complete picture of living systems. We also describe the current state of bioinformatics software and approaches for integrating proteomics and other 'omics data, critical for enabling new discoveries driven by multi-omics. EXPERT COMMENTARY Multi-omics, centered on the integration of proteomics information with other 'omic information, has tremendous promise for biological and biomedical studies. Continued advances in approaches for generating deep, reliable proteomic data and bioinformatics tools aimed at integrating data across 'omic domains will ensure the discoveries offered by these multi-omic studies continue to increase.
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Affiliation(s)
- Andrew T. Rajczewski
- Department of Biochemistry, Molecular and Cell Biology Building, University of Minnesota, 420 Washington Ave SE 7-129, Minneapolis, MN, 55455, USA
| | - Pratik D. Jagtap
- Department of Biochemistry, Molecular and Cell Biology Building, University of Minnesota, 420 Washington Ave SE 7-129, Minneapolis, MN, 55455, USA,Coauthor, Research Department of Biochemistry, Molecular and Cell Biology Building, University of Minnesota, 420 Washington Ave SE 7-129, Minneapolis, MN, 55455, USA
| | - Timothy J. Griffin
- Department of Biochemistry, Molecular and Cell Biology Building, University of Minnesota, 420 Washington Ave SE 7-129, Minneapolis, MN, 55455, USA,Department of Biochemistry, Molecular and Cell Biology Building, University of Minnesota, 420 Washington Ave SE 7-129, Minneapolis, MN, 55455, USA
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22
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Calderan-Rodrigues MJ, Luzarowski M, Monte-Bello CC, Minen RI, Zühlke BM, Nikoloski Z, Skirycz A, Caldana C. Proteogenic Dipeptides Are Characterized by Diel Fluctuations and Target of Rapamycin Complex-Signaling Dependency in the Model Plant Arabidopsis thaliana. FRONTIERS IN PLANT SCIENCE 2021; 12:758933. [PMID: 35003157 PMCID: PMC8727597 DOI: 10.3389/fpls.2021.758933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Accepted: 11/11/2021] [Indexed: 06/14/2023]
Abstract
As autotrophic organisms, plants capture light energy to convert carbon dioxide into ATP, nicotinamide adenine dinucleotide phosphate (NADPH), and sugars, which are essential for the biosynthesis of building blocks, storage, and growth. At night, metabolism and growth can be sustained by mobilizing carbon (C) reserves. In response to changing environmental conditions, such as light-dark cycles, the small-molecule regulation of enzymatic activities is critical for reprogramming cellular metabolism. We have recently demonstrated that proteogenic dipeptides, protein degradation products, act as metabolic switches at the interface of proteostasis and central metabolism in both plants and yeast. Dipeptides accumulate in response to the environmental changes and act via direct binding and regulation of critical enzymatic activities, enabling C flux distribution. Here, we provide evidence pointing to the involvement of dipeptides in the metabolic rewiring characteristics for the day-night cycle in plants. Specifically, we measured the abundance of 13 amino acids and 179 dipeptides over short- (SD) and long-day (LD) diel cycles, each with different light intensities. Of the measured dipeptides, 38 and eight were characterized by day-night oscillation in SD and LD, respectively, reaching maximum accumulation at the end of the day and then gradually falling in the night. Not only the number of dipeptides, but also the amplitude of the oscillation was higher in SD compared with LD conditions. Notably, rhythmic dipeptides were enriched in the glucogenic amino acids that can be converted into glucose. Considering the known role of Target of Rapamycin (TOR) signaling in regulating both autophagy and metabolism, we subsequently investigated whether diurnal fluctuations of dipeptides levels are dependent on the TOR Complex (TORC). The Raptor1b mutant (raptor1b), known for the substantial reduction of TOR kinase activity, was characterized by the augmented accumulation of dipeptides, which is especially pronounced under LD conditions. We were particularly intrigued by the group of 16 dipeptides, which, based on their oscillation under SD conditions and accumulation in raptor1b, can be associated with limited C availability or photoperiod. By mining existing protein-metabolite interaction data, we delineated putative protein interactors for a representative dipeptide Pro-Gln. The obtained list included enzymes of C and amino acid metabolism, which are also linked to the TORC-mediated metabolic network. Based on the obtained results, we speculate that the diurnal accumulation of dipeptides contributes to its metabolic adaptation in response to changes in C availability. We hypothesize that dipeptides would act as alternative respiratory substrates and by directly modulating the activity of the focal enzymes.
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Affiliation(s)
| | - Marcin Luzarowski
- Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany
| | | | | | - Boris M. Zühlke
- Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany
- Institute for Biochemistry and Biology, University of Potsdam, Potsdam, Germany
| | - Zoran Nikoloski
- Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany
- Institute for Biochemistry and Biology, University of Potsdam, Potsdam, Germany
| | - Aleksandra Skirycz
- Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany
- Boyce Thompson Institute, Ithaca, NY, United States
| | - Camila Caldana
- Max Planck Institute of Molecular Plant Physiology, Potsdam, Germany
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23
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Schlossarek D, Luzarowski M, Sokołowska E, Górka M, Willmitzer L, Skirycz A. PROMISed: A novel web-based tool to facilitate analysis and visualization of the molecular interaction networks from co-fractionation mass spectrometry (CF-MS) experiments. Comput Struct Biotechnol J 2021; 19:5117-5125. [PMID: 34589187 PMCID: PMC8453180 DOI: 10.1016/j.csbj.2021.08.042] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Revised: 08/27/2021] [Accepted: 08/27/2021] [Indexed: 11/24/2022] Open
Abstract
Co-fractionation mass spectrometry (CF-MS)-based approaches enable cell-wide identification of protein-protein and protein-metabolite complexes present in the cellular lysate. CF-MS combines biochemical separation of molecular complexes with an untargeted mass-spectrometry-based proteomics and/or metabolomics analysis of the obtained fractions, and is used to delineate putative interactors. CF-MS data are a treasure trove for biological discovery. To facilitate analysis and visualization of original or publically available CF-MS datasets, we designed PROMISed, a user-friendly tool available online via https://myshiny.mpimp-golm.mpg.de/PDP1/ or as a repository via https://github.com/DennisSchlossarek/PROMISed. Specifically, starting with raw fractionation profiles, PROMISed (i) contains activities for data pre-processing and normalization, (ii) deconvolutes complex fractionation profiles into single, distinct peaks, (iii) identifies co-eluting protein-protein or protein-metabolite pairs using user-defined correlation methods, and (iv) performs co-fractionation network analysis. Given multiple CF-MS datasets, for instance representing different environmental condition, PROMISed allows to select for proteins and metabolites that differ in their elution profile, which may indicate change in the interaction status. But it also enables the identification of protein-protein and protein-metabolite pairs that co-elute together across multiple datasets. PROMISed enables users to (i) easily adjust parameters at each step of the analysis, (ii) download partial and final results, and (iii) select among different data-visualization options. PROMISed renders CF-MS data accessible to a broad scientific audience, allowing users with no computational or statistical background to look for novel protein-protein and protein-metabolite complexes for further experimental validation.
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Affiliation(s)
- Dennis Schlossarek
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, D-14476 Potsdam-Golm, Germany
| | - Marcin Luzarowski
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, D-14476 Potsdam-Golm, Germany
| | - Ewelina Sokołowska
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, D-14476 Potsdam-Golm, Germany
| | - Michał Górka
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, D-14476 Potsdam-Golm, Germany
| | - Lothar Willmitzer
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, D-14476 Potsdam-Golm, Germany
| | - Aleksandra Skirycz
- Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, D-14476 Potsdam-Golm, Germany.,Boyce Thompson Institute, 533 Tower Rd., Ithaca, NY 14853, United States
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24
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Moreno JC, Rojas BE, Vicente R, Gorka M, Matz T, Chodasiewicz M, Peralta‐Ariza JS, Zhang Y, Alseekh S, Childs D, Luzarowski M, Nikoloski Z, Zarivach R, Walther D, Hartman MD, Figueroa CM, Iglesias AA, Fernie AR, Skirycz A. Tyr-Asp inhibition of glyceraldehyde 3-phosphate dehydrogenase affects plant redox metabolism. EMBO J 2021; 40:e106800. [PMID: 34156108 PMCID: PMC8327957 DOI: 10.15252/embj.2020106800] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Accepted: 05/13/2021] [Indexed: 12/28/2022] Open
Abstract
How organisms integrate metabolism with the external environment is a central question in biology. Here, we describe a novel regulatory small molecule, a proteogenic dipeptide Tyr-Asp, which improves plant tolerance to oxidative stress by directly interfering with glucose metabolism. Specifically, Tyr-Asp inhibits the activity of a key glycolytic enzyme, glyceraldehyde 3-phosphate dehydrogenase (GAPC), and redirects glucose toward pentose phosphate pathway (PPP) and NADPH production. In line with the metabolic data, Tyr-Asp supplementation improved the growth performance of both Arabidopsis and tobacco seedlings subjected to oxidative stress conditions. Moreover, inhibition of Arabidopsis phosphoenolpyruvate carboxykinase (PEPCK) activity by a group of branched-chain amino acid-containing dipeptides, but not by Tyr-Asp, points to a multisite regulation of glycolytic/gluconeogenic pathway by dipeptides. In summary, our results open the intriguing possibility that proteogenic dipeptides act as evolutionarily conserved small-molecule regulators at the nexus of stress, protein degradation, and metabolism.
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Affiliation(s)
- Juan C Moreno
- Max Planck Institute of Molecular Plant PhysiologyPotsdamGermany
- Center for Desert Agriculture, Biological and Environmental Science and Engineering Division (BESE)King Abdullah University of Science and Technology (KAUST)ThuwalSaudi Arabia
| | - Bruno E Rojas
- Instituto de Agrobiotecnología del LitoralUNLCONICET, FBCBSanta FeArgentina
| | - Rubén Vicente
- Max Planck Institute of Molecular Plant PhysiologyPotsdamGermany
| | - Michal Gorka
- Max Planck Institute of Molecular Plant PhysiologyPotsdamGermany
| | - Timon Matz
- Max Planck Institute of Molecular Plant PhysiologyPotsdamGermany
- BioinformaticsInstitute of Biochemistry and BiologyUniversity of PotsdamPotsdamGermany
| | | | | | - Youjun Zhang
- Max Planck Institute of Molecular Plant PhysiologyPotsdamGermany
- Center of Plant Systems Biology and Biotechnology (CPSBB)PlovdivBulgaria
| | - Saleh Alseekh
- Max Planck Institute of Molecular Plant PhysiologyPotsdamGermany
- Center of Plant Systems Biology and Biotechnology (CPSBB)PlovdivBulgaria
| | - Dorothee Childs
- European Molecular Biology Laboratory (EMBL) HeidelbergHeidelbergGermany
| | | | - Zoran Nikoloski
- Max Planck Institute of Molecular Plant PhysiologyPotsdamGermany
- BioinformaticsInstitute of Biochemistry and BiologyUniversity of PotsdamPotsdamGermany
- Center of Plant Systems Biology and Biotechnology (CPSBB)PlovdivBulgaria
| | - Raz Zarivach
- Faculty of Natural SciencesThe Ben Gurion University of the NegevBeer ShevaIsrael
| | - Dirk Walther
- Max Planck Institute of Molecular Plant PhysiologyPotsdamGermany
| | - Matías D Hartman
- Instituto de Agrobiotecnología del LitoralUNLCONICET, FBCBSanta FeArgentina
| | - Carlos M Figueroa
- Instituto de Agrobiotecnología del LitoralUNLCONICET, FBCBSanta FeArgentina
| | - Alberto A Iglesias
- Instituto de Agrobiotecnología del LitoralUNLCONICET, FBCBSanta FeArgentina
| | - Alisdair R Fernie
- Max Planck Institute of Molecular Plant PhysiologyPotsdamGermany
- Center of Plant Systems Biology and Biotechnology (CPSBB)PlovdivBulgaria
| | - Aleksandra Skirycz
- Max Planck Institute of Molecular Plant PhysiologyPotsdamGermany
- Boyce Thompson InstituteIthacaUSA
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