1
|
Oliveira Pereira EA, Warriner TR, Simmons DBD, Jobst KJ, Simpson AJ, Simpson MJ. Metabolomic-Based Comparison of Daphnia magna and Japanese Medaka Responses After Exposure to Acetaminophen, Diclofenac, and Ibuprofen. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY 2024; 43:1339-1351. [PMID: 38661510 DOI: 10.1002/etc.5876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Revised: 01/31/2024] [Accepted: 03/22/2024] [Indexed: 04/26/2024]
Abstract
Pharmaceuticals are found in aquatic environments due to their widespread use and environmental persistence. To date, a range of impairments to aquatic organisms has been reported with exposure to pharmaceuticals; however, further comparisons of their impacts across different species on the molecular level are needed. In the present study, the crustacean Daphnia magna and the freshwater fish Japanese medaka, common model organisms in aquatic toxicity, were exposed for 48 h to the common analgesics acetaminophen (ACT), diclofenac (DCF), and ibuprofen (IBU) at sublethal concentrations. A targeted metabolomic-based approach, using liquid chromatography-tandem mass spectrometry to quantify polar metabolites from individual daphnids and fish was used. Multivariate analyses and metabolite changes identified differences in the metabolite profile for D. magna and medaka, with more metabolic perturbations for D. magna. Pathway analyses uncovered disruptions to pathways associated with protein synthesis and amino acid metabolism with D. magna exposure to all three analgesics. In contrast, medaka exposure resulted in disrupted pathways with DCF only and not ACT and IBU. Overall, the observed perturbations in the biochemistry of both organisms were different and consistent with assessments using other endpoints reporting that D. magna is more sensitive to pollutants than medaka in short-term studies. Our findings demonstrate that molecular-level responses to analgesic exposure can reflect observations of other endpoints, such as immobilization and mortality. Thus, environmental metabolomics can be a valuable tool for selecting sentinel species for the biomonitoring of freshwater ecosystems while also uncovering mechanistic information. Environ Toxicol Chem 2024;43:1339-1351. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
Collapse
Affiliation(s)
- Erico A Oliveira Pereira
- Environmental Nuclear Magnetic Resonance Centre and Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada
| | | | | | - Karl J Jobst
- Department of Chemistry, Memorial University of Newfoundland, St. John's, Newfoundland and Labrador, Canada
| | - André J Simpson
- Environmental Nuclear Magnetic Resonance Centre and Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada
- Department of Chemistry, University of Toronto, Toronto, Ontario, Canada
| | - Myrna J Simpson
- Environmental Nuclear Magnetic Resonance Centre and Department of Physical and Environmental Sciences, University of Toronto Scarborough, Toronto, Ontario, Canada
- Department of Chemistry, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
2
|
Chang C, Roh YS, Du M, Kuo YC, Zhang Y, Hardy M, Gahler R, Solnier J. Differences in Metabolite Profiles of Dihydroberberine and Micellar Berberine in Caco-2 Cells and Humans-A Pilot Study. Int J Mol Sci 2024; 25:5625. [PMID: 38891813 PMCID: PMC11171481 DOI: 10.3390/ijms25115625] [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: 04/15/2024] [Revised: 05/17/2024] [Accepted: 05/20/2024] [Indexed: 06/21/2024] Open
Abstract
We investigated the pharmacokinetic pathway of berberine and its metabolites in vitro, in Caco-2 cells, and in human participants following the administration of dihydroberberine (DHB) and micellar berberine (LipoMicel®, LMB) formulations. A pilot trial involving nine healthy volunteers was conducted over a 24 h period; blood samples were collected and subjected to Ultra High-Performance Liquid Chromatography-High Resolution Mass Spectrometry (UHPLC-HRMS) analyses to quantify the concentrations of berberine and its metabolites. Pharmacokinetic correlations indicated that berberrubine and thalifendine follow distinct metabolic pathways. Additionally, jatrorrhizine sulfate appeared to undergo metabolism differently compared to the other sulfated metabolites. Moreover, berberrubine glucuronide likely has a unique metabolic pathway distinct from other glucuronides. The human trial revealed significantly higher blood concentrations of berberine metabolites in participants of the DHB treatment group compared to the LMB treatment group-except for berberrubine glucuronide, which was only detected in the LMB treatment group. Similarly, results from in vitro investigations showed significant differences in berberine metabolite profiles between DHB and LMB. Dihydroberberine, dihydroxy-berberrubine/thalifendine and jatrorrhizine sulfate were detected in LMB-treated cells, but not in DHB-treated cells; thalifendine and jatrorrhizine-glucuronide were detected in DHB-treated cells only. While DHB treatment provided higher blood concentrations of berberine and most berberine metabolites, both in vitro (Caco-2 cells) and in vivo human studies showed that treatment with LMB resulted in a higher proportion of unmetabolized berberine compared to DHB. These findings suggest potential clinical implications that merit further investigation in future large-scale trials.
Collapse
Affiliation(s)
- Chuck Chang
- ISURA, Clinical Research, Burnaby, BC V3N 4S9, Canada; (C.C.); (Y.S.R.); (M.D.); (Y.C.K.); (Y.Z.)
| | - Yoon Seok Roh
- ISURA, Clinical Research, Burnaby, BC V3N 4S9, Canada; (C.C.); (Y.S.R.); (M.D.); (Y.C.K.); (Y.Z.)
| | - Min Du
- ISURA, Clinical Research, Burnaby, BC V3N 4S9, Canada; (C.C.); (Y.S.R.); (M.D.); (Y.C.K.); (Y.Z.)
| | - Yun Chai Kuo
- ISURA, Clinical Research, Burnaby, BC V3N 4S9, Canada; (C.C.); (Y.S.R.); (M.D.); (Y.C.K.); (Y.Z.)
| | - Yiming Zhang
- ISURA, Clinical Research, Burnaby, BC V3N 4S9, Canada; (C.C.); (Y.S.R.); (M.D.); (Y.C.K.); (Y.Z.)
| | - Mary Hardy
- Academy of Integrative and Holistic Medicine, San Diego, CA 92037, USA;
| | | | - Julia Solnier
- ISURA, Clinical Research, Burnaby, BC V3N 4S9, Canada; (C.C.); (Y.S.R.); (M.D.); (Y.C.K.); (Y.Z.)
| |
Collapse
|
3
|
Zhang Y, Lin X, Gao Z, Wang T, Dong K, Zhang J. An omics data analysis method based on feature linear relationship and graph convolutional network. J Biomed Inform 2023; 145:104479. [PMID: 37634557 DOI: 10.1016/j.jbi.2023.104479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 07/26/2023] [Accepted: 08/23/2023] [Indexed: 08/29/2023]
Abstract
Biological networks are known to be highly modular, and the dysfunction of network modules may cause diseases. Defining the key modules from the omics data and establishing the classification model is helpful in promoting the research of disease diagnosis and prognosis. However, for applying modules in downstream analysis such as disease states discrimination, most methods only utilize the node information, and ignore the node interactions or topological information, which may lead to false positives and limit the model performance. In this study, we propose an omics data analysis method based on feature linear relationship and graph convolutional network (LCNet). In LCNet, we adopt a way of applying the difference of feature linear relationships during disease development to characterize physiological and pathological changes and construct the differential linear relation network, which is simple and interpretable from the perspective of feature linear relationship. A greedy strategy is developed for searching the highly interactive modules with a strong discrimination ability. To fully utilize the information of the detected modules, the personalized sub-graphs for each sample based on the modules are defined, and the graph convolutional network (GCN) classifiers are trained to predict the sample labels. The experimental results on public datasets show the superiority of LCNet in classification performance. For Breast Cancer metabolic data, the identified metabolites by LCNet involve important pathways. Thus, LCNet can identify the module biomarkers by feature linear relationship and a greedy strategy, and label samples by personalized sub-graphs and GCN. It provides a new manner of utilizing node (molecule) information and topological information in the defined modules for better disease classification.
Collapse
Affiliation(s)
- Yanhui Zhang
- School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, Liaoning, China
| | - Xiaohui Lin
- School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, Liaoning, China.
| | - Zhenbo Gao
- School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, Liaoning, China
| | - Tianxiang Wang
- School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, Liaoning, China
| | - Kunjie Dong
- School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, Liaoning, China
| | - Jianjun Zhang
- Cancer Hospital of Dalian University of Technology (Liaoning Cancer Hospital & Institute), Liaoning, China
| |
Collapse
|
4
|
Melograna F, Li Z, Galazzo G, van Best N, Mommers M, Penders J, Stella F, Van Steen K. Edge and modular significance assessment in individual-specific networks. Sci Rep 2023; 13:7868. [PMID: 37188794 PMCID: PMC10185658 DOI: 10.1038/s41598-023-34759-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Accepted: 05/07/2023] [Indexed: 05/17/2023] Open
Abstract
Individual-specific networks, defined as networks of nodes and connecting edges that are specific to an individual, are promising tools for precision medicine. When such networks are biological, interpretation of functional modules at an individual level becomes possible. An under-investigated problem is relevance or "significance" assessment of each individual-specific network. This paper proposes novel edge and module significance assessment procedures for weighted and unweighted individual-specific networks. Specifically, we propose a modular Cook's distance using a method that involves iterative modeling of one edge versus all the others within a module. Two procedures assessing changes between using all individuals and using all individuals but leaving one individual out (LOO) are proposed as well (LOO-ISN, MultiLOO-ISN), relying on empirically derived edges. We compare our proposals to competitors, including adaptions of OPTICS, kNN, and Spoutlier methods, by an extensive simulation study, templated on real-life scenarios for gene co-expression and microbial interaction networks. Results show the advantages of performing modular versus edge-wise significance assessments for individual-specific networks. Furthermore, modular Cook's distance is among the top performers across all considered simulation settings. Finally, the identification of outlying individuals regarding their individual-specific networks, is meaningful for precision medicine purposes, as confirmed by network analysis of microbiome abundance profiles.
Collapse
Affiliation(s)
- Federico Melograna
- BIO3 - Laboratory for Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, Belgium.
| | - Zuqi Li
- BIO3 - Laboratory for Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Gianluca Galazzo
- School of Nutrition and Translational Research in Metabolism (NUTRIM), Department of Medical Microbiology Infectious Diseases and Infection Prevention, Maastricht University Medical Center+, Maastricht, The Netherlands
| | - Niels van Best
- Institute of Medical Microbiology, RWTH University Hospital Aachen, RWTH University, Aachen, Germany
- Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands
| | - Monique Mommers
- Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands
| | - John Penders
- School of Nutrition and Translational Research in Metabolism (NUTRIM), Department of Medical Microbiology Infectious Diseases and Infection Prevention, Maastricht University Medical Center+, Maastricht, The Netherlands
- Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, The Netherlands
| | - Fabio Stella
- Department of Informatics, Systems and Communication, University of Milano-Bicocca, 20126, Milan, Italy
| | - Kristel Van Steen
- BIO3 - Laboratory for Systems Medicine, Department of Human Genetics, KU Leuven, Leuven, Belgium
- BIO3 - Laboratory for Systems Genetics, GIGA-R Medical Genomics, University of Liège, Liège, Belgium
| |
Collapse
|
5
|
Rath E, Palma Medina LM, Jahagirdar S, Mosevoll KA, Damås JK, Madsen MB, Svensson M, Hyldegaard O, Martins Dos Santos VAP, Saccenti E, Norrby-Teglund A, Skrede S, Bruun T. Systemic immune activation profiles in streptococcal necrotizing soft tissue infections: A prospective multicenter study. Clin Immunol 2023; 249:109276. [PMID: 36871764 DOI: 10.1016/j.clim.2023.109276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 02/05/2023] [Accepted: 02/28/2023] [Indexed: 03/07/2023]
Abstract
OBJECTIVE Early stages with streptococcal necrotizing soft tissue infections (NSTIs) are often difficult to discern from cellulitis. Increased insight into inflammatory responses in streptococcal disease may guide correct interventions and discovery of novel diagnostic targets. METHODS Plasma levels of 37 mediators, leucocytes and CRP from 102 patients with β-hemolytic streptococcal NSTI derived from a prospective Scandinavian multicentre study were compared to those of 23 cases of streptococcal cellulitis. Hierarchical cluster analyses were also performed. RESULTS Differences in mediator levels between NSTI and cellulitis cases were revealed, in particular for IL-1β, TNFα and CXCL8 (AUC >0.90). Across streptococcal NSTI etiologies, eight biomarkers separated cases with septic shock from those without, and four mediators predicted a severe outcome. CONCLUSION Several inflammatory mediators and wider profiles were identified as potential biomarkers of NSTI. Associations of biomarker levels to type of infection and outcomes may be utilized to improve patient care and outcomes.
Collapse
Affiliation(s)
- Eivind Rath
- Department of Medicine, Haukeland University Hospital, Bergen, Norway.
| | - Laura M Palma Medina
- Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Huddinge, Sweden
| | - Sanjeevan Jahagirdar
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, the Netherlands
| | - Knut A Mosevoll
- Department of Medicine, Haukeland University Hospital, Bergen, Norway; Department of Clinical Science, University of Bergen, Norway
| | - Jan K Damås
- Department of Infectious Diseases, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway; Centre of Molecular Inflammation Research, Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Martin B Madsen
- Department of Intensive Care, Copenhagen University Hospital, Rigshospitalet, Denmark
| | - Mattias Svensson
- Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Huddinge, Sweden
| | - Ole Hyldegaard
- Department of Anaesthesia- and Surgery, Head and Orthopaedic centre, Hyperbaric Unit, Copenhagen University Hospital, Rigshospitalet, Denmark; Department of Clinical Medicine, University of Copenhagen, Denmark
| | - Vitor A P Martins Dos Santos
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, the Netherlands; LifeGlimmer GmbH, Berlin, Germany
| | - Edoardo Saccenti
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, the Netherlands
| | - Anna Norrby-Teglund
- Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Huddinge, Sweden
| | - Steinar Skrede
- Department of Medicine, Haukeland University Hospital, Bergen, Norway; Department of Clinical Science, University of Bergen, Norway
| | - Trond Bruun
- Department of Medicine, Haukeland University Hospital, Bergen, Norway; Department of Clinical Science, University of Bergen, Norway
| |
Collapse
|
6
|
Zhang D, Lü J, Ren Z, Zhang X, Wu H, Sa R, Wang X, Wang Y, Lin Z, Zhang B. Potential cardiotoxicity induced by Euodiae Fructus: In vivo and in vitro experiments and untargeted metabolomics research. Front Pharmacol 2022; 13:1028046. [PMID: 36353487 PMCID: PMC9637925 DOI: 10.3389/fphar.2022.1028046] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Accepted: 10/05/2022] [Indexed: 09/16/2023] Open
Abstract
Background: Euodiae Fructus, a well-known herbal medicine, is widely used in Asia and has also gained in popularity in Western countries over the last decades. It has known side effects, which have been observed in clinical settings, but few studies have reported on its cardiotoxicity. Methods: In the present study, experiments using techniques of untargeted metabolomics clarify the hazardous effects of Euodiae Fructus on cardiac function and metabolism in rats in situations of overdosage and unsuitable syndrome differentiation. In vitro assays are conducted to observe the toxic effects of evodiamine and rutaecarpine, two main chemical constituents of Euodiae Fructus, in H9c2 and neonatal rat cardiomyocytes (NRCMs), with their signaling mechanisms analyzed accordingly. Results: The cardiac cytotoxicity of evodiamine and rutaecarpine in in vivo experiments is associated with remarkable alterations in lactate dehydrogenase, creatine kinase, and mitochondrial membrane potential; also with increased intensity of calcium fluorescence, decreased protein expression of the cGMP-PKG pathway in H9c2 cells, and frequency of spontaneous beat in NRCMs. Additionally, the results in rats with Yin deficiency receiving a high-dosage of Euodiae Fructus suggest obvious cardiac physiological dysfunction, abnormal electrocardiogram, pathological injuries, and decreased expression of PKG protein. At the level of endogenous metabolites, the cardiac side effects of overdose and irrational usage of Euodiae Fructus relate to 34 differential metabolites and 10 metabolic pathways involving among others, the purine metabolism, the glycerophospholipid metabolism, the glycerolipid metabolism, and the sphingolipid metabolism. Conclusion: These findings shed new light on the cardiotoxicity induced by Euodiae Fructus, which might be associated with overdose and unsuitable syndrome differentiation, that comes from modulating the cGMP-PKG pathway and disturbing the metabolic pathways of purine, lipid, and amino acid. Continuing research is needed to ensure pharmacovigilance for the safe administration of Chinese herbs in the future.
Collapse
Affiliation(s)
- Dan Zhang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Jintao Lü
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Zhixin Ren
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Xiaomeng Zhang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
- Centre for Pharmacovigilance and Rational Use of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Huanzhang Wu
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Rina Sa
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
- Gansu Provincial Hospital, Lanzhou, China
| | - Xiaofang Wang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
| | - Yu Wang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
- Centre for Pharmacovigilance and Rational Use of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Zhijian Lin
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
- Centre for Pharmacovigilance and Rational Use of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| | - Bing Zhang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, China
- Centre for Pharmacovigilance and Rational Use of Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
| |
Collapse
|
7
|
Dekker PM, Azad MB, Boeren S, Mandhane PJ, Moraes TJ, Simons E, Subbarao P, Turvey SE, Saccenti E, Hettinga KA. The human milk proteome and allergy of mother and child: Exploring associations with protein abundances and protein network connectivity. Front Immunol 2022; 13:977470. [PMID: 36311719 PMCID: PMC9613325 DOI: 10.3389/fimmu.2022.977470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 09/23/2022] [Indexed: 11/13/2022] Open
Abstract
Background The human milk proteome comprises a vast number of proteins with immunomodulatory functions, but it is not clear how this relates to allergy of the mother or allergy development in the breastfed infant. This study aimed to explore the relation between the human milk proteome and allergy of both mother and child. Methods Proteins were analyzed in milk samples from a subset of 300 mother-child dyads from the Canadian CHILD Cohort Study, selected based on maternal and child allergy phenotypes. For this selection, the definition of "allergy" included food allergy, eczema, allergic rhinitis, and asthma. Proteins were analyzed with non-targeted shotgun proteomics using filter-aided sample preparation (FASP) and nanoLC-Orbitrap-MS/MS. Protein abundances, based on label-free quantification, were compared using multiple statistical approaches, including univariate, multivariate, and network analyses. Results Using univariate analysis, we observed a trend that milk for infants who develop an allergy by 3 years of age contains higher abundances of immunoglobulin chains, irrespective of the allergy status of the mother. This observation suggests a difference in the milk's immunological potential, which might be related to the development of the infant's immune system. Furthermore, network analysis showed overall increased connectivity of proteins in the milk of allergic mothers and milk for infants who ultimately develop an allergy. This difference in connectivity was especially noted for proteins involved in the protein translation machinery and may be due to the physiological status of the mother, which is reflected in the interconnectedness of proteins in her milk. In addition, it was shown that network analysis complements the other methods for data analysis by revealing complex associations between the milk proteome and mother-child allergy status. Conclusion Together, these findings give new insights into how the human milk proteome, through differences in the abundance of individual proteins and protein-protein associations, relates to the allergy status of mother and child. In addition, these results inspire new research directions into the complex interplay of the mother-milk-infant triad and allergy.
Collapse
Affiliation(s)
- Pieter M. Dekker
- Food Quality and Design Group, Wageningen University and Research, Wageningen, Netherlands
- Laboratory of Biochemistry, Wageningen University and Research, Wageningen, Netherlands
| | - Meghan B. Azad
- Department of Pediatrics and Child Health, University of Manitoba, Winnipeg, MB, Canada
- Manitoba Interdisciplinary Lactation Centre (MILC), Children’s Hospital Research Institute of Manitoba, Winnipeg, MB, Canada
| | - Sjef Boeren
- Laboratory of Biochemistry, Wageningen University and Research, Wageningen, Netherlands
| | | | - Theo J. Moraes
- Division of Respiratory Medicine, Department of Pediatrics, Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Elinor Simons
- Department of Pediatrics and Child Health, University of Manitoba, Winnipeg, MB, Canada
- Manitoba Interdisciplinary Lactation Centre (MILC), Children’s Hospital Research Institute of Manitoba, Winnipeg, MB, Canada
| | - Padmaja Subbarao
- Division of Respiratory Medicine, Department of Pediatrics, Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
- Department of Physiology, University of Toronto, Toronto, ON, Canada
| | - Stuart E. Turvey
- Department of Pediatrics, University of British Columbia, Vancouver, BC, Canada
| | - Edoardo Saccenti
- Laboratory of Systems and Synthetic Biology, Wageningen University and Research, Wageningen, Netherlands
| | - Kasper A. Hettinga
- Food Quality and Design Group, Wageningen University and Research, Wageningen, Netherlands
| |
Collapse
|
8
|
Zhang Y, Lin X, Gao Z, Bai S. A Novel Method for Feature Selection Based on Molecular Interactive Effect Network. J Pharm Biomed Anal 2022; 218:114873. [DOI: 10.1016/j.jpba.2022.114873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 06/01/2022] [Accepted: 06/01/2022] [Indexed: 10/18/2022]
|
9
|
Li C, Gao Z, Su B, Xu G, Lin X. Data analysis methods for defining biomarkers from omics data. Anal Bioanal Chem 2021; 414:235-250. [PMID: 34951658 DOI: 10.1007/s00216-021-03813-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 11/26/2021] [Accepted: 11/29/2021] [Indexed: 02/01/2023]
Abstract
Omics mainly includes genomics, epigenomics, transcriptomics, proteomics and metabolomics. The rapid development of omics technology has opened up new ways to study disease diagnosis and prognosis and to define prospective information of complex diseases. Since omics data are usually large and complex, the method used to analyze the data and to define important information is crucial in omics study. In this review, we focus on advances in biomarker discovery methods based on omics data in the last decade, and categorize them as individual feature analysis, combinatorial feature analysis and network analysis. We also discuss the challenges and perspectives in this field.
Collapse
Affiliation(s)
- Chao Li
- School of Computer Science and Technology, Dalian University of Technology, Dalian, 116024, Liaoning, China
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, Liaoning, China
| | - Zhenbo Gao
- School of Computer Science and Technology, Dalian University of Technology, Dalian, 116024, Liaoning, China
| | - Benzhe Su
- School of Computer Science and Technology, Dalian University of Technology, Dalian, 116024, Liaoning, China
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, Liaoning, China
| | - Xiaohui Lin
- School of Computer Science and Technology, Dalian University of Technology, Dalian, 116024, Liaoning, China.
| |
Collapse
|
10
|
Di Cesare F, Luchinat C, Tenori L, Saccenti E. Age and sex dependent changes of free circulating blood metabolite and lipid abundances, correlations and ratios. J Gerontol A Biol Sci Med Sci 2021; 77:918-926. [PMID: 34748631 PMCID: PMC9071469 DOI: 10.1093/gerona/glab335] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Indexed: 11/24/2022] Open
Abstract
In this study, we investigated how the concentrations, pairwise correlations and ratios of 202 free circulating blood metabolites and lipids vary with age in a panel of n = 1 882 participants with an age range from 48 to 94 years. We report a statistically significant sex-dependent association with age of a panel of metabolites and lipids involving, in women, linoleic acid, α-linoleic acid, and carnitine, and, in men, monoacylglycerols and lysophosphatidylcholines. Evaluating the association of correlations among metabolites and/or lipids with age, we found that phosphatidylcholines correlations tend to have a positive trend associated with age in women, and monoacylglycerols and lysophosphatidylcholines correlations tend to have a negative trend associated with age in men. The association of ratio between molecular features with age reveals that decanoyl-l-carnitine/lysophosphatidylcholine ratio in women “decrease” with age, while l-carnitine/phosphatidylcholine and l-acetylcarnitine/phosphatidylcholine ratios in men “increase” with age. These results suggest an age-dependent remodeling of lipid metabolism that induces changes in cell membrane bilayer composition and cell cycle mechanisms. Furthermore, we conclude that lipidome is directly involved in this age-dependent differentiation. Our results demonstrate that, using a comprehensive approach focused on the changes of concentrations and relationships of blood metabolites and lipids, as expressed by their correlations and ratios, it is possible to obtain relevant information about metabolic dynamics associated with age.
Collapse
Affiliation(s)
- Francesca Di Cesare
- Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi, Sesto Fiorentino, Firenze, Italy
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi, Sesto Fiorentino, Firenze, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Via della Lastruccia, Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi, Sesto Fiorentino, Firenze, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Via della Lastruccia, Sesto Fiorentino, Italy
| | - Edoardo Saccenti
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Stippeneng, Wageningen, the Netherlands
| |
Collapse
|
11
|
Licari C, Tenori L, Giusti B, Sticchi E, Kura A, De Cario R, Inzitari D, Piccardi B, Nesi M, Sarti C, Arba F, Palumbo V, Nencini P, Marcucci R, Gori AM, Luchinat C, Saccenti E. Analysis of Metabolite and Lipid Association Networks Reveals Molecular Mechanisms Associated with 3-Month Mortality and Poor Functional Outcomes in Patients with Acute Ischemic Stroke after Thrombolytic Treatment with Recombinant Tissue Plasminogen Activator. J Proteome Res 2021; 20:4758-4770. [PMID: 34473513 PMCID: PMC8491161 DOI: 10.1021/acs.jproteome.1c00406] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
![]()
Here, we present
an integrated multivariate, univariate, network
reconstruction and differential analysis of metabolite–metabolite
and metabolite–lipid association networks built from an array
of 18 serum metabolites and 110 lipids identified and quantified through
nuclear magnetic resonance spectroscopy in a cohort of 248 patients,
of which 22 died and 82 developed a poor functional outcome within
3 months from acute ischemic stroke (AIS) treated with intravenous
recombinant tissue plasminogen activator. We explored differences
in metabolite and lipid connectivity of patients who did not develop
a poor outcome and who survived the ischemic stroke from the related
opposite conditions. We report statistically significant differences
in the connectivity patterns of both low- and high-molecular-weight
metabolites, implying underlying variations in the metabolic pathway
involving leucine, glycine, glutamine, tyrosine, phenylalanine, citric,
lactic, and acetic acids, ketone bodies, and different lipids, thus
characterizing patients’ outcomes. Our results evidence the
promising and powerful role of the metabolite–metabolite and
metabolite–lipid association networks in investigating molecular
mechanisms underlying AIS patient’s outcome.
Collapse
Affiliation(s)
- Cristina Licari
- Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, Sesto Fiorentino, Florence 50019, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, Sesto Fiorentino, Florence 50019, Italy.,Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (C.I.R.M.M.P.), Via Luigi Sacconi 6, Sesto Fiorentino, Florence 50019, Italy.,Department of Chemistry, University of Florence, Via della Lastruccia, 3, Sesto Fiorentino, Florence 50019, Italy
| | - Betti Giusti
- Department of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, Florence 50134, Italy.,Atherothrombotic Diseases Center, Careggi Hospital, Florence, Largo Brambilla 3, Florence 50134, Italy.,Excellence Centre for Research, Transfer and High Education for the Development of DE NOVO Therapies (DENOTHE), University of Florence, Viale Pieraccini 6, Firenze 50139, Italy
| | - Elena Sticchi
- Department of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, Florence 50134, Italy
| | - Ada Kura
- Department of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, Florence 50134, Italy.,Atherothrombotic Diseases Center, Careggi Hospital, Florence, Largo Brambilla 3, Florence 50134, Italy
| | - Rosina De Cario
- Department of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, Florence 50134, Italy
| | - Domenico Inzitari
- Stroke Unit, Careggi University Hospital, Florence 50134, Italy.,Institute of Neuroscience, Italian National Research Council (CNR), Via Madonna del Piano, 10, Sesto Fiorentino, Florence 50019, Italy
| | | | - Mascia Nesi
- Stroke Unit, Careggi University Hospital, Florence 50134, Italy
| | - Cristina Sarti
- NEUROFARBA Department, Neuroscience Section, University of Florence, Largo Brambilla 3, Florence 50134, Italy
| | - Francesco Arba
- Department of Neurology, Careggi University Hospital, Largo Brambilla 3, Florence 50134, Italy
| | - Vanessa Palumbo
- Stroke Unit, Careggi University Hospital, Florence 50134, Italy
| | | | - Rossella Marcucci
- Department of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, Florence 50134, Italy.,Atherothrombotic Diseases Center, Careggi Hospital, Florence, Largo Brambilla 3, Florence 50134, Italy.,Excellence Centre for Research, Transfer and High Education for the Development of DE NOVO Therapies (DENOTHE), University of Florence, Viale Pieraccini 6, Firenze 50139, Italy
| | - Anna Maria Gori
- Department of Experimental and Clinical Medicine, University of Florence, Largo Brambilla 3, Florence 50134, Italy.,Atherothrombotic Diseases Center, Careggi Hospital, Florence, Largo Brambilla 3, Florence 50134, Italy.,Excellence Centre for Research, Transfer and High Education for the Development of DE NOVO Therapies (DENOTHE), University of Florence, Viale Pieraccini 6, Firenze 50139, Italy
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, Via Luigi Sacconi 6, Sesto Fiorentino, Florence 50019, Italy.,Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (C.I.R.M.M.P.), Via Luigi Sacconi 6, Sesto Fiorentino, Florence 50019, Italy.,Department of Chemistry, University of Florence, Via della Lastruccia, 3, Sesto Fiorentino, Florence 50019, Italy
| | - Edoardo Saccenti
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Stippeneng 4, Wageningen 6708 WE, the Netherlands
| |
Collapse
|
12
|
Ahn E, Lee J, Han J, Lee SM, Kwon KS, Hwang GS. Glutathione is an aging-related metabolic signature in the mouse kidney. Aging (Albany NY) 2021; 13:21009-21028. [PMID: 34492635 PMCID: PMC8457589 DOI: 10.18632/aging.203509] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 08/24/2021] [Indexed: 11/25/2022]
Abstract
The ability to maintain systemic metabolic homeostasis through various mechanisms represents a crucial strength of kidneys in the study of metabolic syndrome or aging. Moreover, age-associated kidney failure has been widely accepted. However, efforts to demonstrate aging-dependent renal metabolic rewiring have been limited. In the present study, we investigated aging-related renal metabolic determinants by integrating metabolomic and transcriptomic data sets from kidneys of young (3 months, n = 7 and 3 for respectively) and old (24 months, n = 8 and 3 for respectively) naive C57BL/6 male mice. Metabolite profiling analysis was conducted, followed by data processing via network and pathway analyses, to identify differential metabolites. In the aged group, the levels of glutathione and oxidized glutathione were significantly increased, but the levels of gamma-glutamyl amino acids, amino acids combined with the gamma-glutamyl moiety from glutathione by membrane transpeptidases, and circulating glutathione levels were decreased. In transcriptomic analysis, differential expression of metabolic enzymes is consistent with the hypothesis of aging-dependent rewiring in renal glutathione metabolism; pathway and network analyses further revealed the increased expression of immune-related genes in the aged group. Collectively, our integrative analysis results revealed that defective renal glutathione metabolism is a signature of renal aging. Therefore, we hypothesize that restraining renal glutathione metabolism might alleviate or delay age-associated renal metabolic deterioration, and aberrant activation of the renal immune system.
Collapse
Affiliation(s)
- Eunyong Ahn
- Integrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seodaemun-Gu, Seoul 03759, Korea
| | - Jueun Lee
- Integrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seodaemun-Gu, Seoul 03759, Korea
| | - Jisu Han
- Integrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seodaemun-Gu, Seoul 03759, Korea
| | - Seung-Min Lee
- Aging Research Center, Korea Research Institute of Bioscience and Biotechnology, Yuseong-Gu, Daejeon 34141, Korea
| | - Ki-Sun Kwon
- Aging Research Center, Korea Research Institute of Bioscience and Biotechnology, Yuseong-Gu, Daejeon 34141, Korea
- Aventi Inc., Yuseong-Gu, Daejeon 34141, Korea
| | - Geum-Sook Hwang
- Integrated Metabolomics Research Group, Western Seoul Center, Korea Basic Science Institute, Seodaemun-Gu, Seoul 03759, Korea
- Department of Chemistry and Nano Science, Ewha Womans University, Seodaemun-Gu, Seoul 03760, Korea
| |
Collapse
|
13
|
Di Cesare F, Tenori L, Meoni G, Gori AM, Marcucci R, Giusti B, Molino-Lova R, Macchi C, Pancani S, Luchinat C, Saccenti E. Lipid and metabolite correlation networks specific to clinical and biochemical covariate show differences associated with sexual dimorphism in a cohort of nonagenarians. GeroScience 2021; 44:1109-1128. [PMID: 34324142 PMCID: PMC9135919 DOI: 10.1007/s11357-021-00404-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Accepted: 06/13/2021] [Indexed: 12/26/2022] Open
Abstract
This study defines and estimates the metabolite-lipidic component association networks constructed from an array of 20 metabolites and 114 lipids identified and quantified via NMR spectroscopy in the serum of a cohort of 355 Italian nonagenarians and ultra-nonagenarian. Metabolite-lipid association networks were built for men and women and related to an array of 101 clinical and biochemical parameters, including the presence of diseases, bio-humoral parameters, familiarity diseases, drugs treatments, and risk factors. Different connectivity patterns were observed in lipids, branched chains amino acids, alanine, and ketone bodies, suggesting their association with the sex-related and sex-clinical condition-related intrinsic metabolic changes. Furthermore, our results demonstrate, using a holistic system biology approach, that the characterization of metabolic structures and their dynamic inter-connections is a promising tool to shed light on the dimorphic pathophysiological mechanisms of aging at the molecular level.
Collapse
Affiliation(s)
- Francesca Di Cesare
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | | | - Anna Maria Gori
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.,Atherothrombotic Unit, Careggi University Hospital, Florence, Italy
| | - Rossella Marcucci
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.,Atherothrombotic Unit, Careggi University Hospital, Florence, Italy
| | - Betti Giusti
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.,Atherothrombotic Unit, Careggi University Hospital, Florence, Italy
| | | | - Claudio Macchi
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.,IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | | | - Claudio Luchinat
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy.,Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy.,Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy
| | - Edoardo Saccenti
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Wageningen, the Netherlands.
| |
Collapse
|
14
|
Palma Medina LM, Rath E, Jahagirdar S, Bruun T, Madsen MB, Strålin K, Unge C, Hansen MB, Arnell P, Nekludov M, Hyldegaard O, Lourda M, dos Santos VAM, Saccenti E, Skrede S, Svensson M, Norrby-Teglund A. Discriminatory plasma biomarkers predict specific clinical phenotypes of necrotizing soft-tissue infections. J Clin Invest 2021; 131:149523. [PMID: 34263738 PMCID: PMC8279592 DOI: 10.1172/jci149523] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 05/25/2021] [Indexed: 12/29/2022] Open
Abstract
BACKGROUNDNecrotizing soft-tissue infections (NSTIs) are rapidly progressing infections frequently complicated by septic shock and associated with high mortality. Early diagnosis is critical for patient outcome, but challenging due to vague initial symptoms. Here, we identified predictive biomarkers for NSTI clinical phenotypes and outcomes using a prospective multicenter NSTI patient cohort.METHODSLuminex multiplex assays were used to assess 36 soluble factors in plasma from NSTI patients with positive microbiological cultures (n = 251 and n = 60 in the discovery and validation cohorts, respectively). Control groups for comparative analyses included surgical controls (n = 20), non-NSTI controls (i.e., suspected NSTI with no necrosis detected upon exploratory surgery, n = 20), and sepsis patients (n = 24).RESULTSThrombomodulin was identified as a unique biomarker for detection of NSTI (AUC, 0.95). A distinct profile discriminating mono- (type II) versus polymicrobial (type I) NSTI types was identified based on differential expression of IL-2, IL-10, IL-22, CXCL10, Fas-ligand, and MMP9 (AUC >0.7). While each NSTI type displayed a distinct array of biomarkers predicting septic shock, granulocyte CSF (G-CSF), S100A8, and IL-6 were shared by both types (AUC >0.78). Finally, differential connectivity analysis revealed distinctive networks associated with specific clinical phenotypes.CONCLUSIONSThis study identifies predictive biomarkers for NSTI clinical phenotypes of potential value for diagnostic, prognostic, and therapeutic approaches in NSTIs.TRIAL REGISTRATIONClinicalTrials.gov NCT01790698.FUNDINGCenter for Innovative Medicine (CIMED); Region Stockholm; Swedish Research Council; European Union; Vinnova; Innovation Fund Denmark; Research Council of Norway; Netherlands Organisation for Health Research and Development; DLR Federal Ministry of Education and Research; and Swedish Children's Cancer Foundation.
Collapse
Affiliation(s)
- Laura M. Palma Medina
- Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institute, Stockholm, Sweden
| | - Eivind Rath
- Department of Medicine, Division for Infectious Diseases, Haukeland University Hospital, Bergen, Norway
| | - Sanjeevan Jahagirdar
- Laboratory of Systems and Synthetic Biology, Wageningen University and Research, Wageningen, Netherlands
| | - Trond Bruun
- Department of Medicine, Division for Infectious Diseases, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Martin B. Madsen
- Department of Intensive Care, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Kristoffer Strålin
- Department of Medicine Huddinge, Karolinska Institute, Stockholm, Sweden
- Department of Infectious Diseases and
| | - Christian Unge
- Department of Medicine Huddinge, Karolinska Institute, Stockholm, Sweden
- Functional Area of Emergency Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Marco Bo Hansen
- Department of Anaesthesia, Centre of Head and Orthopaedics, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Per Arnell
- Department of Anaesthesia and Intensive Care, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Michael Nekludov
- Department of Anaesthesia, Surgical Services and Intensive Care, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden
| | - Ole Hyldegaard
- Department of Intensive Care, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Magda Lourda
- Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institute, Stockholm, Sweden
- Childhood Cancer Research Unit, Department of Women’s and Children’s Health, Karolinska Institutet, Stockholm, Sweden
| | - Vitor A.P. Martins dos Santos
- Laboratory of Systems and Synthetic Biology, Wageningen University and Research, Wageningen, Netherlands
- LifeGlimmer GmbH, Berlin, Germany
| | - Edoardo Saccenti
- Laboratory of Systems and Synthetic Biology, Wageningen University and Research, Wageningen, Netherlands
| | - Steinar Skrede
- Department of Medicine, Division for Infectious Diseases, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Mattias Svensson
- Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institute, Stockholm, Sweden
| | - Anna Norrby-Teglund
- Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institute, Stockholm, Sweden
| |
Collapse
|
15
|
Hageman J, Engel J. Special Issue: Development and Application of Statistical Methods for Analyzing Metabolomics Data. Metabolites 2021; 11:metabo11070451. [PMID: 34357345 PMCID: PMC8307789 DOI: 10.3390/metabo11070451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 07/12/2021] [Indexed: 11/16/2022] Open
|
16
|
Pazhamala LT, Kudapa H, Weckwerth W, Millar AH, Varshney RK. Systems biology for crop improvement. THE PLANT GENOME 2021; 14:e20098. [PMID: 33949787 DOI: 10.1002/tpg2.20098] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2020] [Accepted: 03/09/2021] [Indexed: 05/19/2023]
Abstract
In recent years, generation of large-scale data from genome, transcriptome, proteome, metabolome, epigenome, and others, has become routine in several plant species. Most of these datasets in different crop species, however, were studied independently and as a result, full insight could not be gained on the molecular basis of complex traits and biological networks. A systems biology approach involving integration of multiple omics data, modeling, and prediction of the cellular functions is required to understand the flow of biological information that underlies complex traits. In this context, systems biology with multiomics data integration is crucial and allows a holistic understanding of the dynamic system with the different levels of biological organization interacting with external environment for a phenotypic expression. Here, we present recent progress made in the area of various omics studies-integrative and systems biology approaches with a special focus on application to crop improvement. We have also discussed the challenges and opportunities in multiomics data integration, modeling, and understanding of the biology of complex traits underpinning yield and stress tolerance in major cereals and legumes.
Collapse
Affiliation(s)
- Lekha T Pazhamala
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Hyderabad, 502 324, India
| | - Himabindu Kudapa
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Hyderabad, 502 324, India
| | - Wolfram Weckwerth
- Department of Ecogenomics and Systems Biology, University of Vienna, Vienna, Austria
- Vienna Metabolomics Center, University of Vienna, Vienna, Austria
| | - A Harvey Millar
- ARC Centre of Excellence in Plant Energy Biology and School of Molecular Sciences, The University of Western Australia, Perth, WA, Australia
| | - Rajeev K Varshney
- Center of Excellence in Genomics & Systems Biology, International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Patancheru, Hyderabad, 502 324, India
- State Agricultural Biotechnology Centre, Crop Research Innovation Centre, Food Futures Institute, Murdoch University, Murdoch, WA, Australia
| |
Collapse
|
17
|
Balder Y, Vignoli A, Tenori L, Luchinat C, Saccenti E. Exploration of Blood Lipoprotein and Lipid Fraction Profiles in Healthy Subjects through Integrated Univariate, Multivariate, and Network Analysis Reveals Association of Lipase Activity and Cholesterol Esterification with Sex and Age. Metabolites 2021; 11:metabo11050326. [PMID: 34070169 PMCID: PMC8158518 DOI: 10.3390/metabo11050326] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 05/14/2021] [Accepted: 05/14/2021] [Indexed: 02/08/2023] Open
Abstract
In this study, we investigated blood lipoprotein and lipid fraction profiles, quantified using nuclear magnetic resonance, in a cohort of 844 healthy blood donors, integrating standard univariate and multivariate analysis with predictive modeling and network analysis. We observed a strong association of lipoprotein and lipid main fraction profiles with sex and age. Our results suggest an age-dependent remodulation of lipase lipoprotein activity in men and a change in the mechanisms controlling the ratio between esterified and non-esterified cholesterol in both men and women.
Collapse
Affiliation(s)
- Yasmijn Balder
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Stippeneng 4, 6708 WE Wageningen, The Netherlands;
| | - Alessia Vignoli
- Magnetic Resonance Center (CERM) and Department of Chemistry “Ugo Schiff”, University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.); (C.L.)
- Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM) and Department of Chemistry “Ugo Schiff”, University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.); (C.L.)
- Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM) and Department of Chemistry “Ugo Schiff”, University of Florence, Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy; (A.V.); (L.T.); (C.L.)
- Consorzio Interuniversitario Risonanze Magnetiche MetalloProteine (CIRMMP), Via Luigi Sacconi 6, 50019 Sesto Fiorentino, Italy
| | - Edoardo Saccenti
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Stippeneng 4, 6708 WE Wageningen, The Netherlands;
- Correspondence:
| |
Collapse
|
18
|
Desmet S, Brouckaert M, Boerjan W, Morreel K. Seeing the forest for the trees: Retrieving plant secondary biochemical pathways from metabolome networks. Comput Struct Biotechnol J 2020; 19:72-85. [PMID: 33384856 PMCID: PMC7753198 DOI: 10.1016/j.csbj.2020.11.050] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 11/26/2020] [Accepted: 11/28/2020] [Indexed: 02/06/2023] Open
Abstract
Over the last decade, a giant leap forward has been made in resolving the main bottleneck in metabolomics, i.e., the structural characterization of the many unknowns. This has led to the next challenge in this research field: retrieving biochemical pathway information from the various types of networks that can be constructed from metabolome data. Searching putative biochemical pathways, referred to as biotransformation paths, is complicated because several flaws occur during the construction of metabolome networks. Multiple network analysis tools have been developed to deal with these flaws, while in silico retrosynthesis is appearing as an alternative approach. In this review, the different types of metabolome networks, their flaws, and the various tools to trace these biotransformation paths are discussed.
Collapse
Affiliation(s)
- Sandrien Desmet
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Marlies Brouckaert
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Wout Boerjan
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| | - Kris Morreel
- Ghent University, Department of Plant Biotechnology and Bioinformatics, Ghent, Belgium
- VIB Center for Plant Systems Biology, Ghent, Belgium
| |
Collapse
|
19
|
Jahagirdar S, Saccenti E. Evaluation of Single Sample Network Inference Methods for Metabolomics-Based Systems Medicine. J Proteome Res 2020; 20:932-949. [PMID: 33267585 PMCID: PMC7786380 DOI: 10.1021/acs.jproteome.0c00696] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
![]()
Networks
and network analyses are fundamental tools of systems
biology. Networks are built by inferring pair-wise relationships among
biological entities from a large number of samples such that subject-specific
information is lost. The possibility of constructing these sample
(individual)-specific networks from single molecular profiles might
offer new insights in systems and personalized medicine and as a consequence
is attracting more and more research interest. In this study, we evaluated
and compared LIONESS (Linear Interpolation to Obtain Network Estimates
for Single Samples) and ssPCC (single sample network based on Pearson
correlation) in the metabolomics context of metabolite–metabolite
association networks. We illustrated and explored the characteristics
of these two methods on (i) simulated data, (ii) data generated from
a dynamic metabolic model to simulate real-life observed metabolite
concentration profiles, and (iii) 22 metabolomic data sets and (iv)
we applied single sample network inference to a study case pertaining
to the investigation of necrotizing soft tissue infections to show
how these methods can be applied in metabolomics. We also proposed
some adaptations of the methods that can be used for data exploration.
Overall, despite some limitations, we found single sample networks
to be a promising tool for the analysis of metabolomics data.
Collapse
Affiliation(s)
- Sanjeevan Jahagirdar
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Stippeneng 4, 6708 WE Wageningen, The Netherlands
| | - Edoardo Saccenti
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, Stippeneng 4, 6708 WE Wageningen, The Netherlands
| |
Collapse
|