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Monyela S, Kayoka PN, Ngezimana W, Nemadodzi LE. Evaluating the Metabolomic Profile and Anti-Pathogenic Properties of Cannabis Species. Metabolites 2024; 14:253. [PMID: 38786730 PMCID: PMC11122914 DOI: 10.3390/metabo14050253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2024] [Revised: 04/17/2024] [Accepted: 04/22/2024] [Indexed: 05/25/2024] Open
Abstract
The Cannabis species is one of the potent ancient medicinal plants acclaimed for its medicinal properties and recreational purposes. The plant parts are used and exploited all over the world for several agricultural and industrial applications. For many years Cannabis spp. has proven to present a highly diverse metabolomic profile with a pool of bioactive metabolites used for numerous pharmacological purposes ranging from anti-inflammatory to antimicrobial. Cannabis sativa has since been an extensive subject of investigation, monopolizing the research. Hence, there are fewer studies with a comprehensive understanding of the composition of bioactive metabolites grown in different environmental conditions, especially C. indica and a few other Cannabis strains. These pharmacological properties are mostly attributed to a few phytocannabinoids and some phytochemicals such as terpenoids or essential oils which have been tested for antimicrobial properties. Many other discovered compounds are yet to be tested for antimicrobial properties. These phytochemicals have a series of useful properties including anti-insecticidal, anti-acaricidal, anti-nematicidal, anti-bacterial, anti-fungal, and anti-viral properties. Research studies have reported excellent antibacterial activity against Gram-positive and Gram-negative multidrug-resistant bacteria as well as methicillin-resistant Staphylococcus aureus (MRSA). Although there has been an extensive investigation on the antimicrobial properties of Cannabis, the antimicrobial properties of Cannabis on phytopathogens and aquatic animal pathogens, mostly those affecting fish, remain under-researched. Therefore, the current review intends to investigate the existing body of research on metabolomic profile and anti-microbial properties whilst trying to expand the scope of the properties of the Cannabis plant to benefit the health of other animal species and plant crops, particularly in agriculture.
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Affiliation(s)
- Shadrack Monyela
- Department of Agriculture and Animal Health, University of South Africa, Science Campus, Florida, Johannesburg 1710, South Africa
| | - Prudence Ngalula Kayoka
- Department of Agriculture and Animal Health, University of South Africa, Science Campus, Florida, Johannesburg 1710, South Africa
| | - Wonder Ngezimana
- Department of Horticulture, Faculty of Plant and Animal Sciences and Technology, Marondera University of Agricultural Sciences and Technology, Marondera P.O. Box 35, Zimbabwe
| | - Lufuno Ethel Nemadodzi
- Department of Agriculture and Animal Health, University of South Africa, Science Campus, Florida, Johannesburg 1710, South Africa
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Razavi SA, Khorsand B, Salehipour P, Hedayati M. Metabolite signature of human malignant thyroid tissue: A systematic review and meta-analysis. Cancer Med 2024; 13:e7184. [PMID: 38646957 PMCID: PMC11033922 DOI: 10.1002/cam4.7184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 02/13/2024] [Accepted: 03/26/2024] [Indexed: 04/25/2024] Open
Abstract
BACKGROUND Thyroid cancer (TC) is the predominant malignancy within the endocrine system. However, the standard method for TC diagnosis lacks the capability to identify the pathological condition of all thyroid lesions. The metabolomics approach has the potential to manage this problem by identifying differential metabolites. AIMS This study conducted a systematic review and meta-analysis of the NMR-based metabolomics studies in order to identify significant altered metabolites associated with TC. METHODS A systematic search of published literature in any language in three databases including Embase, PubMed, and Scopus was conducted. Out of 353 primary articles, 12 studies met the criteria for inclusion in the systematic review. Among these, five reports belonging to three articles were eligible for meta-analysis. The correlation coefficient of the orthogonal partial least squares discriminant analysis, a popular model in the multivariate statistical analysis of metabolomic data, was chosen for meta-analysis. The altered metabolites were chosen based on the fact that they had been found in at least three studies. RESULTS In total, 49 compounds were identified, 40 of which were metabolites. The increased metabolites in thyroid lesions compared normal samples included lactate, taurine, alanine, glutamic acid, glutamine, leucine, lysine, phenylalanine, serine, tyrosine, valine, choline, glycine, and isoleucine. Lipids were the decreased compounds in thyroid lesions. Lactate and alanine were increased in malignant versus benign thyroid lesions, while, myo-inositol, scyllo-inositol, citrate, choline, and phosphocholine were found to be decreased. The meta-analysis yielded significant results for three metabolites of lactate, alanine, and citrate in malignant versus benign specimens. DISCUSSION In this study, we provided a concise summary of 12 included metabolomic studies, making it easier for future researchers to compare their results with the prior findings. CONCLUSION It appears that the field of TC metabolomics will experience notable advancement, leading to the discovery of trustworthy diagnostic and prognostic biomarkers.
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Affiliation(s)
- S. Adeleh Razavi
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine SciencesShahid Beheshti University of Medical SciencesTehranIran
| | - Babak Khorsand
- Department of NeurologyUniversity of CaliforniaIrvineCaliforniaUSA
- Department of Computer Engineering, Faculty of EngineeringFerdowsi University of MashhadMashhadIran
| | - Pouya Salehipour
- Department of Medical Genetics, School of MedicineTehran University of Medical SciencesTehranIran
| | - Mehdi Hedayati
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine SciencesShahid Beheshti University of Medical SciencesTehranIran
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García-Perdomo HA, Dávila-Raigoza AM, Korkes F. Metabolomics for the diagnosis of bladder cancer: A systematic review. Asian J Urol 2024; 11:221-241. [PMID: 38680576 PMCID: PMC11053311 DOI: 10.1016/j.ajur.2022.11.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 11/29/2022] [Indexed: 05/01/2024] Open
Abstract
Objective Metabolomics has been extensively utilized in bladder cancer (BCa) research, employing mass spectrometry and nuclear magnetic resonance spectroscopy to compare various variables (tissues, serum, blood, and urine). This study aimed to identify potential biomarkers for early BCa diagnosis. Methods A search strategy was designed to identify clinical trials, descriptive and analytical observational studies from databases such as Medline, Embase, Cochrane Central Register of Controlled Trials, and Latin American and Caribbean Literature in Health Sciences. Inclusion criteria comprised studies involving BCa tissue, serum, blood, or urine profiling using widely adopted metabolomics techniques like mass spectrometry and nuclear magnetic resonance. Primary outcomes included description of metabolites and metabolomics profiling in BCa patients and the association of metabolites and metabolomics profiling with BCa diagnosis compared to control patients. The risk of bias was assessed using the Quality Assessment of Studies of Diagnostic Accuracy. Results The search strategy yielded 2832 studies, of which 30 case-control studies were included. Urine was predominantly used as the primary sample for metabolite identification. Risk of bias was often unclear inpatient selection, blinding of the index test, and reference standard assessment, but no applicability concerns were observed. Metabolites and metabolomics profiles associated with BCa diagnosis were identified in glucose, amino acids, nucleotides, lipids, and aldehydes metabolism. Conclusion The identified metabolites in urine included citric acid, valine, tryptophan, taurine, aspartic acid, uridine, ribose, phosphocholine, and carnitine. Tissue samples exhibited elevated levels of lactic acid, amino acids, and lipids. Consistent findings across tissue, urine, and serum samples revealed downregulation of citric acid and upregulation of lactic acid, valine, tryptophan, taurine, glutamine, aspartic acid, uridine, ribose, and phosphocholine.
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Affiliation(s)
- Herney Andrés García-Perdomo
- Division of Urology/Urooncology, Department of Surgery, School of Medicine, Universidad del Valle, Cali, Colombia
- UROGIV Research Group, School of Medicine, Universidad del Valle, Cali, Colombia
| | | | - Fernando Korkes
- Urologic Oncology, Division of Urology, ABC Medical School, Sao Paulo, Brazil
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Lekka P, Fragopoulou E, Terpou A, Dasenaki M. Exploring Human Metabolome after Wine Intake-A Review. Molecules 2023; 28:7616. [PMID: 38005338 PMCID: PMC10673339 DOI: 10.3390/molecules28227616] [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: 10/02/2023] [Revised: 10/21/2023] [Accepted: 10/24/2023] [Indexed: 11/26/2023] Open
Abstract
Wine has a rich history dating back to 2200 BC, originally recognized for its medicinal properties. Today, with the aid of advanced technologies like metabolomics and sophisticated analytical techniques, we have gained remarkable insights into the molecular-level changes induced by wine consumption in the human organism. This review embarks on a comprehensive exploration of the alterations in human metabolome associated with wine consumption. A great number of 51 studies from the last 25 years were reviewed; these studies systematically investigated shifts in metabolic profiles within blood, urine, and feces samples, encompassing both short-term and long-term studies of the consumption of wine and wine derivatives. Significant metabolic alterations were observed in a wide variety of metabolites belonging to different compound classes, such as phenolic compounds, lipids, organic acids, and amino acids, among others. Within these classes, both endogenous metabolites as well as diet-related metabolites that exhibited up-regulation or down-regulation following wine consumption were included. The up-regulation of short-chain fatty acids and the down-regulation of sphingomyelins after wine intake, as well as the up-regulation of gut microbial fermentation metabolites like vanillic and syringic acid are some of the most important findings reported in the reviewed literature. Our results confirm the intact passage of certain wine compounds, such as tartaric acid and other wine acids, to the human organism. In an era where the health effects of wine consumption are of growing interest, this review offers a holistic perspective on the metabolic underpinnings of this centuries-old tradition.
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Affiliation(s)
- Pelagia Lekka
- Food Chemistry Laboratory, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zographou, 15771 Athens, Greece;
| | - Elizabeth Fragopoulou
- School of Health Science and Education, Department of Nutrition and Dietetics, Harokopio University, 17671 Athens, Greece;
| | - Antonia Terpou
- Department of Agricultural Development, Agrofood and Management of Natural Resources, School of Agricultural Development, Nutrition & Sustainability, National and Kapodistrian University of Athens, 34400 Psachna, Greece;
| | - Marilena Dasenaki
- Food Chemistry Laboratory, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zographou, 15771 Athens, Greece;
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Oliveira N, Sousa A, Amaral AP, Graça G, Verde I. Searching for Metabolic Markers of Stroke in Human Plasma via NMR Analysis. Int J Mol Sci 2023; 24:16173. [PMID: 38003362 PMCID: PMC10671802 DOI: 10.3390/ijms242216173] [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: 09/30/2023] [Revised: 10/31/2023] [Accepted: 11/08/2023] [Indexed: 11/26/2023] Open
Abstract
More than 12 million people around the world suffer a stroke every year, one every 3 s. Stroke has a variety of causes and is often the result of a complex interaction of risk factors related to age, genetics, gender, lifestyle, and some cardiovascular and metabolic diseases. Despite this evidence, it is not possible to prevent the onset of stroke. The use of innovative methods for metabolite analysis has been explored in the last years to detect new stroke biomarkers. We use NMR spectroscopy to identify small molecule variations between different stages of stroke risk. The Framingham Stroke Risk Score was used in people over 63 years of age living in long-term care facilities (LTCF) to calculate the probability of suffering a stroke. Using this parameter, three study groups were formed: low stroke risk (LSR, control), moderate stroke risk (MSR) and high stroke risk (HSR). Univariate statistical analysis showed seven metabolites with increasing plasma levels across different stroke risk groups, from LSR to HSR: isoleucine, asparagine, formate, creatinine, dimethylsulfone and two unidentified molecules, which we termed "unknown-1" and "unknown-3". These metabolic markers can be used for early detection and to detect increasing stages of stroke risk more efficiently.
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Affiliation(s)
- Nádia Oliveira
- Health Sciences Research Centre (CICS-UBI), University of Beira Interior (UBI), Av. Infante D. Henrique, 6200-506 Covilha, Portugal; (N.O.); (A.S.); (A.P.A.)
| | - Adriana Sousa
- Health Sciences Research Centre (CICS-UBI), University of Beira Interior (UBI), Av. Infante D. Henrique, 6200-506 Covilha, Portugal; (N.O.); (A.S.); (A.P.A.)
| | - Ana Paula Amaral
- Health Sciences Research Centre (CICS-UBI), University of Beira Interior (UBI), Av. Infante D. Henrique, 6200-506 Covilha, Portugal; (N.O.); (A.S.); (A.P.A.)
| | - Gonçalo Graça
- Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, UK
| | - Ignacio Verde
- Health Sciences Research Centre (CICS-UBI), University of Beira Interior (UBI), Av. Infante D. Henrique, 6200-506 Covilha, Portugal; (N.O.); (A.S.); (A.P.A.)
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Ghini V, Meoni G, Vignoli A, Di Cesare F, Tenori L, Turano P, Luchinat C. Fingerprinting and profiling in metabolomics of biosamples. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2023; 138-139:105-135. [PMID: 38065666 DOI: 10.1016/j.pnmrs.2023.10.002] [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: 06/27/2023] [Revised: 10/13/2023] [Accepted: 10/15/2023] [Indexed: 12/18/2023]
Abstract
This review focuses on metabolomics from an NMR point of view. It attempts to cover the broad scope of metabolomics and describes the NMR experiments that are most suitable for each sample type. It is addressed not only to NMR specialists, but to all researchers who wish to approach metabolomics with a clear idea of what they wish to achieve but not necessarily with a deep knowledge of NMR. For this reason, some technical parts may seem a bit naïve to the experts. The review starts by describing standard metabolomics procedures, which imply the use of a dedicated 600 MHz instrument and of four properly standardized 1D experiments. Standardization is a must if one wants to directly compare NMR results obtained in different labs. A brief mention is also made of standardized pre-analytical procedures, which are even more essential. Attention is paid to the distinction between fingerprinting and profiling, and the advantages and disadvantages of fingerprinting are clarified. This aspect is often not fully appreciated. Then profiling, and the associated problems of signal assignment and quantitation, are discussed. We also describe less conventional approaches, such as the use of different magnetic fields, the use of signal enhancement techniques to increase sensitivity, and the potential of field-shuttling NMR. A few examples of biomedical applications are also given, again with the focus on NMR techniques that are most suitable to achieve each particular goal, including a description of the most common heteronuclear experiments. Finally, the growing applications of metabolomics to foodstuffs are described.
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Affiliation(s)
- Veronica Ghini
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Gaia Meoni
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Alessia Vignoli
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Italy
| | - Francesca Di Cesare
- Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino, Italy; Department of Chemistry "Ugo Schiff", 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; Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy
| | - Paola Turano
- 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 Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy.
| | - Claudio Luchinat
- Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), Sesto Fiorentino, Italy; Giotto Biotech S.r.l., Sesto Fiorentino, Italy.
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Mulder FAA, Tenori L, Licari C, Luchinat C. Practical considerations for rapid and quantitative NMR-based metabolomics. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2023; 352:107462. [PMID: 37141802 DOI: 10.1016/j.jmr.2023.107462] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 03/23/2023] [Accepted: 04/21/2023] [Indexed: 05/06/2023]
Abstract
NMR is a key technology for metabolomics because of its robustness and reproducibility. Herein we discuss practical considerations that extend the utility of NMR spectroscopy. First, the long T1 spin relaxation times of small molecules limits high-throughput data acquisition because most experimental time is lost while waiting for signal recovery. In principle, the addition of a small amount of commercially-available paramagnetic gadolinium chelate allows cost-effective and efficient high-throughput mixture analysis with correct concentration determination. However, idle time caused by slow temperature regulation during sample exchanges, poses a next constraint. We show how, with proper care, NMR sample scanning times can be reduced additionally by a factor of two. Lastly, we describe how equidistant bucketing is a simple and fast procedure for metabolomic fingerprinting. The combination of these advancements help to make NMR metabolomics more versatile than it is today.
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Affiliation(s)
| | - Leonardo Tenori
- Magnetic Resonance Center (CERM) and Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Florence, Italy; Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (CIRMMP), Sesto Fiorentino, Florence, Italy
| | - Cristina Licari
- Magnetic Resonance Center (CERM) and Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Florence, Italy; Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (CIRMMP), Sesto Fiorentino, Florence, Italy
| | - Claudio Luchinat
- Magnetic Resonance Center (CERM) and Department of Chemistry "Ugo Schiff", University of Florence, Sesto Fiorentino, Florence, Italy; Consorzio Interuniversitario Risonanze Magnetiche di Metallo Proteine (CIRMMP), Sesto Fiorentino, Florence, Italy; GiottoBiotech s.r.l., Sesto Fiorentino, Florence, Italy.
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Bennett S, Brocherie F, Phelan MM, Tiollier E, Guibert E, Morales‐Artacho AJ, Lalire P, Morton JP, Louis JB, Owens DJ. Acute heat stress amplifies exercise-induced metabolomic perturbations and reveals variation in circulating amino acids in endurance-trained males. Exp Physiol 2023; 108:838-851. [PMID: 36691850 PMCID: PMC10988456 DOI: 10.1113/ep090911] [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: 10/15/2022] [Accepted: 01/03/2023] [Indexed: 01/25/2023]
Abstract
NEW FINDINGS What is the central question of this study? Whole-body substrate utilisation is altered during exercise in hot environments, characterised by increased glycolytic metabolism: does heat stress alter the serum metabolome in response to high intensity exercise? What are the main finding and its importance? Alongside increases in glycolytic metabolite abundance, circulating amino acid concentrations are reduced following exercise under heat stress. Prior research has overlooked the impact of heat stress on protein metabolism during exercise, raising important practical implications for protein intake recommendations in the heat. ABSTRACT Using untargeted metabolomics, we aimed to characterise the systemic impact of environmental heat stress during exercise. Twenty-three trained male triathletes (V ̇ O 2 peak ${\dot V_{{{\rm{O}}_2}{\rm{peak}}}}$ = 64.8 ± 9.2 ml kg min-1 ) completed a 30-min exercise test in hot (35°C) and temperate (21°C) conditions. Venous blood samples were collected immediately pre- and post-exercise, and the serum fraction was assessed via untargeted 1 H-NMR metabolomics. Data were analysed via uni- and multivariate analyses to identify differences between conditions. Mean power output was higher in temperate (231 ± 36 W) versus hot (223 ± 31 W) conditions (P < 0.001). Mean heart rate (temperate, 162 ± 10 beats min-1 , hot, 167 ± 9 beats min-1 , P < 0.001), peak core temperature (Trec ), core temperature change (ΔTrec ) (P < 0.001) and peak rating of perceived exertion (P = 0.005) were higher in hot versus temperate conditions. Change in metabolite abundance following exercise revealed distinct clustering following multivariate analysis. Six metabolites increased (2-hydroxyvaleric acid, acetate, alanine, glucarate, glucose, lactate) in hot relative to temperate (P < 0.05) conditions. Leucine and lysine decreased in both conditions but to a greater extent in temperate conditions (P < 0.05). Citrate (P = 0.04) was greater in temperate conditions whilst creatinine decreased in hot conditions only (P > 0.05). Environmental heat stress increased glycolytic metabolite abundance and led to distinct alterations in the circulating amino acid availability, including increased alanine, glutamine, leucine and isoleucine. The data highlight the need for additional exercise nutrition and metabolism research, specifically focusing on protein requirements for exercise under heat stress.
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Affiliation(s)
- Samuel Bennett
- Research Institute of Sport and Exercise Science (RISES)Liverpool John Moores UniversityLiverpoolUK
- Laboratory SportExpertise and Performance (EA 7370)French Institute of SportParisFrance
| | - Franck Brocherie
- Laboratory SportExpertise and Performance (EA 7370)French Institute of SportParisFrance
| | - Marie M. Phelan
- NMR Metabolomics Shared Research FacilityTechnology DirectorateUniversity of LiverpoolLiverpoolUK
| | - Eve Tiollier
- Laboratory SportExpertise and Performance (EA 7370)French Institute of SportParisFrance
| | - Elodie Guibert
- Laboratory SportExpertise and Performance (EA 7370)French Institute of SportParisFrance
| | | | - Paul Lalire
- French Triathlon Federation (FFTri)Saint Denis La PlaineFrance
| | - James P. Morton
- Research Institute of Sport and Exercise Science (RISES)Liverpool John Moores UniversityLiverpoolUK
| | - Julien B. Louis
- Research Institute of Sport and Exercise Science (RISES)Liverpool John Moores UniversityLiverpoolUK
| | - Daniel J. Owens
- Research Institute of Sport and Exercise Science (RISES)Liverpool John Moores UniversityLiverpoolUK
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Porto VA, da Rocha Júnior ER, Ursulino JS, Porto RS, da Silva M, de Jesus LWO, Oliveira JMD, Crispim AC, Santos JCC, Aquino TMD. NMR-based metabolomics applied to ecotoxicology with zebrafish (Danio rerio) as a prominent model for metabolic profiling and biomarker discovery: Overviewing the most recent approaches. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 868:161737. [PMID: 36693575 DOI: 10.1016/j.scitotenv.2023.161737] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 12/28/2022] [Accepted: 01/17/2023] [Indexed: 06/17/2023]
Abstract
Metabolomics is an innovative approach used in the medical, toxicological, and biological sciences. As an interdisciplinary topic, metabolomics and its relation with the environment and toxicological research are extensive. The use of substances, such as drugs and pesticides, contributes to the continuous releasing of xenobiotics into the environment, harming organisms and their habitats. In this context, fish are important bioindicators of the environmental condition and have often been used as model species. Among them, zebrafish (Danio rerio) presents itself as a versatile and straightforward option due to its unique attributes for research. Zebrafish proves to be a valuable model for toxicity assays and also for metabolomics profiling by analytical tools. Thus, NMR-based metabolomics associated with statistical analysis can reasonably assist researchers in critical factors related to discovering and validating biomarkers through accurate diagnosis. Therefore, this review aimed to report the studies that applied zebrafish as a model for (eco)toxicological assays and essentially utilized NMR-based metabolomics analysis to assess the biochemical profile and thus suggest the potential biological marker.
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Affiliation(s)
- Viviane Amaral Porto
- Research Group on Therapeutic Strategies, Institute of Chemistry and Biotechnology, Federal University of Alagoas, Maceió, AL, Brazil.
| | | | - Jeferson Santana Ursulino
- Research Group on Therapeutic Strategies, Institute of Chemistry and Biotechnology, Federal University of Alagoas, Maceió, AL, Brazil
| | - Ricardo Silva Porto
- Institute of Chemistry and Biotechnology, Federal University of Alagoas, Maceió, AL, Brazil
| | - Marciliano da Silva
- Laboratory of Applied Animal Morphophysiology, Institute of Biological and Health Sciences, Federal University of Alagoas, Maceió, AL, Brazil
| | - Lázaro Wender Oliveira de Jesus
- Laboratory of Applied Animal Morphophysiology, Institute of Biological and Health Sciences, Federal University of Alagoas, Maceió, AL, Brazil
| | | | - Alessandre Carmo Crispim
- Research Group on Therapeutic Strategies, Institute of Chemistry and Biotechnology, Federal University of Alagoas, Maceió, AL, Brazil
| | | | - Thiago Mendonça de Aquino
- Research Group on Therapeutic Strategies, Institute of Chemistry and Biotechnology, Federal University of Alagoas, Maceió, AL, Brazil
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Du H, Gu X, Chen J, Bai C, Duan X, Hu K. GIPMA: Global Intensity-Guided Peak Matching and Alignment for 2D 1H- 13C HSQC-Based Metabolomics. Anal Chem 2023; 95:3195-3203. [PMID: 36728684 DOI: 10.1021/acs.analchem.2c03323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Two-dimensional (2D) 1H-13C heteronuclear single quantum coherence (HSQC) has been increasingly applied to metabolomics studies because it can greatly improve the resolving capability compared with one-dimensional (1D) 1H NMR. However, preprocessing methods such as peak matching and alignment tools for 2D NMR-based metabolomics have lagged behind similar methods for 1D 1H NMR-based metabolomics. Correct matching and alignment of 2D NMR spectral features across multiple samples are particularly important for subsequent multivariate data analysis. Considering different intensity dynamic ranges of a variety of metabolites and the chemical shift variation across the spectra of multiple samples, here, we developed an efficient peak matching and alignment algorithm for 2D 1H-13C HSQC-based metabolomics, called global intensity-guided peak matching and alignment (GIPMA). In GIPMA, peaks identified in all spectra are pooled together and sorted by intensity. Chemical shift of a stronger peak is regarded to be more accurate and reliable than that of a weaker peak. The strongest undesignated peak is chosen as the reference of a new cluster if it is not located within the chemical shift tolerance of any existing peak cluster (PC), or otherwise it is matched to an existing PC and the aligned chemical shift of the PC is updated as the intensity-weighted average of the chemical shifts of all peaks in the cluster. Setting an optimum chemical shift tolerance (Δδo) is critical for the peak matching and alignment across multiple samples. GIPMA dynamically searches for and intelligently selects the Δδo for peak matching to maximize the number of valid peak clusters (vPC), that is, spectral features, among multiple samples. By GIPMA, fully automatic peakwise matching and alignment do not require any spectrum as initial reference, while the chemical shift of each PC is updated as the intensity-weighted average of the chemical shifts of all peaks in the same PC, which is warranted to be statistically more accurate. Accurate chemical shifts for each representative spectral feature will facilitate subsequent peak assignment and are essential for correct metabolite identification and result interpretation. The proposed method was demonstrated successfully on the spectra of six model mixtures consisting of seven typical metabolites, yielding correct matching of all known spectral features. The performance of GIPMA was also demonstrated on 2D 1H-13C HSQC spectra of 87 real extracts of 29 samples of five Dendrobium species. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) of the 87 matched and aligned spectra by GIPMA generates correct classification of the 29 samples into five groups. In summary, the proposed algorithm of GIPMA provided a practical peak matching and alignment method to facilitate 2D NMR-based metabolomics studies.
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Affiliation(s)
- Huan Du
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.,School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
| | - Xiu Gu
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.,School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
| | - Jialuo Chen
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.,School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
| | - Caihong Bai
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.,School of Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
| | - Xiaohui Duan
- Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China.,School of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Kaifeng Hu
- State Key Laboratory of Southwestern Chinese Medicine Resources, Chengdu University of Traditional Chinese Medicine, Chengdu 611137, China.,Innovative Institute of Chinese Medicine and Pharmacy, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 611137, China
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11
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Lysak DH, Kock FVC, Mamone S, Soong R, Glöggler S, Simpson AJ. In vivo singlet state filtered nuclear magnetic resonance: towards monitoring toxic responses inside living organisms. Chem Sci 2023; 14:1413-1418. [PMID: 36794179 PMCID: PMC9906653 DOI: 10.1039/d2sc06624f] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 01/06/2023] [Indexed: 01/11/2023] Open
Abstract
In line with recent paradigm shifts in toxicity testing, in vivo nuclear magnetic resonance (NMR) is a powerful tool for studying the biological impacts and perturbations caused by toxicants in living organisms. However, despite the excellent molecular insights that can be obtained through this technique, in vivo NMR applications are hampered by considerable experimental challenges such as poor line shape and spectral overlap. Here, we demonstrate the application of singlet-filtered NMR to target specific metabolites and facilitate the study of metabolite fluxes in living Daphnia magna, an aquatic keystone species and model organism. Informed by mathematical simulations and experiments on ex vivo organisms, singlet state NMR is used to monitor the flux of metabolites such as d-glucose and serine in living D. magna, during the environmentally relevant processes of anoxic stress and reduced food availability. Overall, singlet state NMR is shown to have significant future potential for studying metabolic processes in vivo.
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Affiliation(s)
- Daniel H. Lysak
- Environmental NMR Centre, University of Toronto Scarborough1265 Military TrailScarboroughOntarioCanada
| | - Flavio V. C. Kock
- Environmental NMR Centre, University of Toronto Scarborough1265 Military TrailScarboroughOntarioCanada,Department of Chemistry, Federal University of São Carlos (UFSCar)Rod. Washington Luís, MonjolinhoSão Carlos–SP13565-905Brazil
| | - Salvatore Mamone
- NMR Signal Enhancement Group, Max Planck Institute for Multidisciplinary Sciences Am Fassberg 11 37077 Göttingen Germany
| | - Ronald Soong
- Environmental NMR Centre, University of Toronto Scarborough1265 Military TrailScarboroughOntarioCanada
| | - Stefan Glöggler
- NMR Signal Enhancement Group, Max Planck Institute for Multidisciplinary Sciences Am Fassberg 11 37077 Göttingen Germany
| | - Andre J. Simpson
- NMR Signal Enhancement Group, Max Planck Institute for Multidisciplinary SciencesAm Fassberg11 37077GöttingenGermany
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12
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Jeong S, Jang HB, Kim HJ, Lee HJ. Identification of Biomarkers Related to Metabolically Unhealthy Obesity in Korean Obese Adolescents: A Cross-Sectional Study. CHILDREN (BASEL, SWITZERLAND) 2023; 10:children10020322. [PMID: 36832451 PMCID: PMC9955165 DOI: 10.3390/children10020322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 01/25/2023] [Accepted: 02/02/2023] [Indexed: 02/11/2023]
Abstract
BACKGROUND The current study aimed to screen for relationships and different potential metabolic biomarkers involved between metabolically healthy obesity (MHO) and metabolically unhealthy obesity (MUO) in adolescents. METHODS The study included 148 obese adolescents aged between 14 and 16. The study participants were divided into MUO and MHO groups based on the age-specific adolescent metabolic syndrome (MetS) criteria of the International Diabetes Federation. The current study was conducted to investigate the clinical and metabolic differences between the MHO and MUO groups. Multivariate analyses were conducted to investigate the metabolites as independent predictors for the odds ratio and the presence of the MetS. RESULTS There were significant differences in the three acylcarnitines, five amino acids, glutamine/glutamate ratio, three biogenic amines, two glycerophospholipids, and the triglyceride-glucose index between the MUO group and those in the MHO group. Moreover, several metabolites were associated with the prevalence of MUO. Additionally, several metabolites were inversely correlated with MHO in the MUO group. CONCLUSIONS In this study, the biomarkers found in this study have the potential to reflect the clinical outcomes of the MUO group. These biomarkers will lead to a better understanding of MetS in obese adolescents.
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Affiliation(s)
| | | | | | - Hye-Ja Lee
- Correspondence: ; Tel.: +82-43-719-8452; Fax: +82-43-719-8709
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13
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Bodaghi A, Fattahi N, Ramazani A. Biomarkers: Promising and valuable tools towards diagnosis, prognosis and treatment of Covid-19 and other diseases. Heliyon 2023; 9:e13323. [PMID: 36744065 PMCID: PMC9884646 DOI: 10.1016/j.heliyon.2023.e13323] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 01/21/2023] [Accepted: 01/26/2023] [Indexed: 01/31/2023] Open
Abstract
The use of biomarkers as early warning systems in the evaluation of disease risk has increased markedly in the last decade. Biomarkers are indicators of typical biological processes, pathogenic processes, or pharmacological reactions to therapy. The application and identification of biomarkers in the medical and clinical fields have an enormous impact on society. In this review, we discuss the history, various definitions, classifications, characteristics, and discovery of biomarkers. Furthermore, the potential application of biomarkers in the diagnosis, prognosis, and treatment of various diseases over the last decade are reviewed. The present review aims to inspire readers to explore new avenues in biomarker research and development.
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Affiliation(s)
- Ali Bodaghi
- Department of Chemistry, Tuyserkan Branch, Islamic Azad University, Tuyserkan, Iran
| | - Nadia Fattahi
- Department of Chemistry, University of Zanjan, Zanjan, 45371-38791, Iran,Trita Nanomedicine Research and Technology Development Center (TNRTC), Zanjan Health Technology Park, 45156-13191, Zanjan, Iran
| | - Ali Ramazani
- Department of Chemistry, University of Zanjan, Zanjan, 45371-38791, Iran,Department of Biotechnology, Research Institute of Modern Biological Techniques (RIMBT), University of Zanjan, Zanjan, 45371-38791, Iran,Corresponding author. Department of Chemistry, University of Zanjan, Zanjan, 45371-38791, Iran.;
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14
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Wishart DS, Rout M, Lee BL, Berjanskii M, LeVatte M, Lipfert M. Practical Aspects of NMR-Based Metabolomics. Handb Exp Pharmacol 2023; 277:1-41. [PMID: 36271165 DOI: 10.1007/164_2022_613] [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
While NMR-based metabolomics is only about 20 years old, NMR has been a key part of metabolic and metabolism studies for >40 years. Historically, metabolic researchers used NMR because of its high level of reproducibility, superb instrument stability, facile sample preparation protocols, inherently quantitative character, non-destructive nature, and amenability to automation. In this chapter, we provide a short history of NMR-based metabolomics. We then provide a detailed description of some of the practical aspects of performing NMR-based metabolomics studies including sample preparation, pulse sequence selection, and spectral acquisition and processing. The two different approaches to metabolomics data analysis, targeted vs. untargeted, are briefly outlined. We also describe several software packages to help users process NMR spectra obtained via these two different approaches. We then give several examples of useful or interesting applications of NMR-based metabolomics, ranging from applications to drug toxicology, to identifying inborn errors of metabolism to analyzing the contents of biofluids from dairy cattle. Throughout this chapter, we will highlight the strengths and limitations of NMR-based metabolomics. Additionally, we will conclude with descriptions of recent advances in NMR hardware, methodology, and software and speculate about where NMR-based metabolomics is going in the next 5-10 years.
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Affiliation(s)
- David S Wishart
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada.
- Department of Computing Science, University of Alberta, Edmonton, AB, Canada.
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB, Canada.
- Faculty of Pharmacy and Pharmaceutical Sciences, University of Alberta, Edmonton, AB, Canada.
| | - Manoj Rout
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Brian L Lee
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Mark Berjanskii
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Marcia LeVatte
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Matthias Lipfert
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
- Reference Standard Management & NMR QC, Lonza Group AG, Visp, Switzerland
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15
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McKay RT. Metabolomics and NMR. Handb Exp Pharmacol 2023; 277:73-116. [PMID: 36355220 DOI: 10.1007/164_2022_616] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
The purpose of this manuscript will be to convince the reader to dive deeper into NMR spectroscopy and prevent the technique from being just another "black-box" in the lab. We will try to concisely highlight interesting topics and supply additional references for further exploration at each stage. The advantages of delving into the technique will be shown. The secondary objective, i.e., avoiding common problems before starting, will hopefully then become clear. Lastly, we will emphasize the spectrometer information needed for manuscript reporting to allow reproduction of results and confirm findings.
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Affiliation(s)
- Ryan T McKay
- Department Chemistry, College of Natural and Applied Sciences, University of Alberta, Edmonton, AB, Canada.
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16
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Bifarin OO. Interpretable machine learning with tree-based shapley additive explanations: Application to metabolomics datasets for binary classification. PLoS One 2023; 18:e0284315. [PMID: 37141218 PMCID: PMC10159207 DOI: 10.1371/journal.pone.0284315] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 03/28/2023] [Indexed: 05/05/2023] Open
Abstract
Machine learning (ML) models are used in clinical metabolomics studies most notably for biomarker discoveries, to identify metabolites that discriminate between a case and control group. To improve understanding of the underlying biomedical problem and to bolster confidence in these discoveries, model interpretability is germane. In metabolomics, partial least square discriminant analysis (PLS-DA) and its variants are widely used, partly due to the model's interpretability with the Variable Influence in Projection (VIP) scores, a global interpretable method. Herein, Tree-based Shapley Additive explanations (SHAP), an interpretable ML method grounded in game theory, was used to explain ML models with local explanation properties. In this study, ML experiments (binary classification) were conducted for three published metabolomics datasets using PLS-DA, random forests, gradient boosting, and extreme gradient boosting (XGBoost). Using one of the datasets, PLS-DA model was explained using VIP scores, while one of the best-performing models, a random forest model, was interpreted using Tree SHAP. The results show that SHAP has a more explanation depth than PLS-DA's VIP, making it a powerful method for rationalizing machine learning predictions from metabolomics studies.
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Affiliation(s)
- Olatomiwa O Bifarin
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, Georgia, United States of America
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17
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Wallace CW, Hislop B, Hahn AK, Erdogan AE, Brahmachary PP, June RK. Correlations between metabolites in the synovial fluid and serum: A mouse injury study. J Orthop Res 2022; 40:2792-2802. [PMID: 35285551 PMCID: PMC9470782 DOI: 10.1002/jor.25310] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 12/03/2021] [Accepted: 02/02/2022] [Indexed: 02/04/2023]
Abstract
Osteoarthritis occurs frequently after joint injury. Currently, osteoarthritis is diagnosed by radiographic changes that are typically found after the disease has progressed to multiple tissues. The primary objective was to compare potential metabolomic biomarkers of joint injury between synovial fluid and serum in a mouse model of posttraumatic osteoarthritis. The secondary objective was to gain insight into the pathophysiology of osteoarthritis by examining metabolomic profiles after joint injury. Twelve-week-old adult female C57BL/6 mice (n = 12) were randomly assigned to control, Day 1, or Day 8 postinjury groups. Randomly selected stifle joints were subjected to a single rapid compression. At Days 1 and 8 postinjury, serum was extracted before mice were euthanized for synovial fluid collection. Metabolomic profiling detected ~2500 metabolites across serum and synovial fluid. Of these, 179 were positively correlated and 51 were negatively correlated between synovial fluid and serum, indicating the potential for the development of metabolomic biomarkers. Synovial fluid captured injury-induced differences in metabolomic profiles at both Days 1 and 8 after injury whereas serum did not. However, synovial fluid and serum were distinct at both time points after injury. In synovial fluid, pathways of interest mapped to amino acid synthesis and degradation, bupropion degradation, and transfer RNA (tRNA) charging. In serum, pathways were amino acid synthesis and degradation, the phospholipase pathway, and nicotine degradation. These results provide a rich picture of the injury response at early time points after joint injury. Furthermore, the correlations between synovial fluid and serum metabolites suggest the potential to gain insight into intra-articular pathophysiology through analysis of serum metabolites.
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Affiliation(s)
- Cameron W Wallace
- University of Washington School of Medicine, Seattle, Washington, USA
| | - Brady Hislop
- Department of Mechanical & Industrial Engineering, Montana State University, Bozeman, Montana, USA
| | | | - Ayten E Erdogan
- Department of Chemical & Biological Engineering, Montana State University, Bozeman, Montana, USA
| | - Priyanka P Brahmachary
- Department of Mechanical & Industrial Engineering, Montana State University, Bozeman, Montana, USA
| | - Ronald K June
- Department of Mechanical & Industrial Engineering and Department of Microbiology and Cell Biology, Montana State University, Bozeman, Montana, USA
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18
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Stabile M, Girelli CR, Lacitignola L, Samarelli R, Crovace A, Fanizzi FP, Staffieri F. 1H-NMR metabolomic profile of healthy and osteoarthritic canine synovial fluid before and after UC-II supplementation. Sci Rep 2022; 12:19716. [PMID: 36385297 PMCID: PMC9669020 DOI: 10.1038/s41598-022-23977-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 11/08/2022] [Indexed: 11/17/2022] Open
Abstract
The aim of the study was to compare the metabolomic synovial fluid (SF) profile of dogs affected by spontaneous osteoarthritis (OA) and supplemented with undenatured type II collagen (UC-II), with that of healthy control dogs. Client-owned dogs were enrolled in the study and randomized in two different groups, based on the presence/absence of OA (OA group and OA-free group). All dogs were clinically evaluated and underwent SF sampling for 1H-Nuclear Magnetic Resonance spectroscopy (1H-NMR) analysis at time of presentation. All dogs included in OA group were supplemented with UC-II orally administered for 30 days. After this period, they were reassessed (OA-T30). The differences in the 1H-NMR metabolic SFs profiles between groups (OA-free, OA-T0 and OA-T30) were studied. The multivariate statistical analysis performed on SFs under different conditions (OA-T0 vs OA-T30 SFs; OA-T0 vs OA-free SFs and OA-T30 vs OA-free SFs) gave models with excellent goodness of fit and predictive parameters, revealed by a marked separation between groups. β-Hydroxybutyrate was identified as a characteristic compound of osteoarthritic joints, showing the important role of fat metabolism during OA. The absence of β-hydroxybutyrate after UC-II supplementation suggests the supplement's effectiveness in rebalancing the metabolism inside the joint. The unexpectedly high level of lactate in the OA-free group suggests that lactate could not be considered a good marker for OA. These results prove that 1H-NMR-based metabolomic analysis is a valid tool to study and monitor OA and that UC-II improves clinical symptoms and the SF metabolic profile in OA dogs.
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Affiliation(s)
- Marzia Stabile
- grid.7644.10000 0001 0120 3326Section of Veterinary Clinics and Animal Production, Department of Emergency and Organ Transplantation, University of Bari, 70123 Bari, Italy
| | - Chiara Roberta Girelli
- grid.9906.60000 0001 2289 7785Department of Biological and Environmental Sciences and Technologies, University of Salento, 73100 Lecce, Italy
| | - Luca Lacitignola
- grid.7644.10000 0001 0120 3326Section of Veterinary Clinics and Animal Production, Department of Emergency and Organ Transplantation, University of Bari, 70123 Bari, Italy
| | - Rossella Samarelli
- grid.7644.10000 0001 0120 3326Section of Avian Pathology, Department of Veterinary Medicine, University of Bari, 70123 Bari, Italy
| | - Antonio Crovace
- grid.7644.10000 0001 0120 3326Section of Veterinary Clinics and Animal Production, Department of Emergency and Organ Transplantation, University of Bari, 70123 Bari, Italy
| | - Francesco Paolo Fanizzi
- grid.9906.60000 0001 2289 7785Department of Biological and Environmental Sciences and Technologies, University of Salento, 73100 Lecce, Italy
| | - Francesco Staffieri
- grid.7644.10000 0001 0120 3326Section of Veterinary Clinics and Animal Production, Department of Emergency and Organ Transplantation, University of Bari, 70123 Bari, Italy
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19
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Pillai MS, Paritala ST, Shah RP, Sharma N, Sengupta P. Cutting-edge strategies and critical advancements in characterization and quantification of metabolites concerning translational metabolomics. Drug Metab Rev 2022; 54:401-426. [PMID: 36351878 DOI: 10.1080/03602532.2022.2125987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Despite remarkable progress in drug discovery strategies, significant challenges are still remaining in translating new insights into clinical applications. Scientists are devising creative approaches to bridge the gap between scientific and translational research. Metabolomics is a unique field among other omics techniques for identifying novel metabolites and biomarkers. Fortunately, characterization and quantification of metabolites are becoming faster due to the progress in the field of orthogonal analytical techniques. This review detailed the advancement in the progress of sample preparation, and data processing techniques including data mining tools, database, and their quality control (QC). Advances in data processing tools make it easier to acquire unbiased data that includes a diverse set of metabolites. In addition, novel breakthroughs including, miniaturization as well as their integration with other devices, metabolite array technology, and crystalline sponge-based method have led to faster, more efficient, cost-effective, and holistic metabolomic analysis. The use of cutting-edge techniques to identify the human metabolite, including biomarkers has proven to be advantageous in terms of early disease identification, tracking the progression of illness, and possibility of personalized treatments. This review addressed the constraints of current metabolomics research, which are impeding the facilitation of translation of research from bench to bedside. Nevertheless, the possible way out from such constraints and future direction of translational metabolomics has been conferred.
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Affiliation(s)
- Megha Sajakumar Pillai
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research (NIPER), Ahmedabad, India
| | - Sree Teja Paritala
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research (NIPER), Ahmedabad, India
| | - Ravi P Shah
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research (NIPER), Ahmedabad, India
| | - Nitish Sharma
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research (NIPER), Ahmedabad, India
| | - Pinaki Sengupta
- Department of Pharmaceutical Analysis, National Institute of Pharmaceutical Education and Research (NIPER), Ahmedabad, India
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20
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Gagliano A, Murgia F, Capodiferro AM, Tanca MG, Hendren A, Falqui SG, Aresti M, Comini M, Carucci S, Cocco E, Lorefice L, Roccella M, Vetri L, Sotgiu S, Zuddas A, Atzori L. 1H-NMR-Based Metabolomics in Autism Spectrum Disorder and Pediatric Acute-Onset Neuropsychiatric Syndrome. J Clin Med 2022; 11:6493. [PMID: 36362721 PMCID: PMC9658067 DOI: 10.3390/jcm11216493] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 10/24/2022] [Accepted: 10/27/2022] [Indexed: 11/03/2023] Open
Abstract
We recently described a unique plasma metabolite profile in subjects with pediatric acute-onset neuropsychiatric syndrome (PANS), suggesting pathogenic models involving specific patterns of neurotransmission, neuroinflammation, and oxidative stress. Here, we extend the analysis to a group of patients with autism spectrum disorder (ASD), as a consensus has recently emerged around its immune-mediated pathophysiology with a widespread involvement of brain networks. This observational case-control study enrolled patients referred for PANS and ASD from June 2019 to May 2020, as well as neurotypical age and gender-matched control subjects. Thirty-four PANS outpatients, fifteen ASD outpatients, and twenty-five neurotypical subjects underwent physical and neuropsychiatric evaluations, alongside serum metabolomic analysis with 1H-NMR. In supervised models, the metabolomic profile of ASD was significantly different from controls (p = 0.0001), with skewed concentrations of asparagine, aspartate, betaine, glycine, lactate, glucose, and pyruvate. Metabolomic separation was also observed between PANS and ASD subjects (p = 0.02), with differences in the concentrations of arginine, aspartate, betaine, choline, creatine phosphate, glycine, pyruvate, and tryptophan. We confirmed a unique serum metabolomic profile of PANS compared with both ASD and neurotypical subjects, distinguishing PANS as a pathophysiological entity per se. Tryptophan and glycine appear as neuroinflammatory fingerprints of PANS and ASD, respectively. In particular, a reduction in glycine would primarily affect NMDA-R excitatory tone, overall impairing downstream glutamatergic, dopaminergic, and GABAergic transmissions. Nonetheless, we found metabolomic similarities between PANS and ASD that suggest a putative role of N-methyl-D-aspartate receptor (NMDA-R) dysfunction in both disorders. Metabolomics-based approaches could contribute to the identification of novel ASD and PANS biomarkers.
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Affiliation(s)
- Antonella Gagliano
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
- Department of Health Science, “Magna Graecia” University of Catanzaro, 88100 Catanzaro, Italy
| | - Federica Murgia
- Clinical Metabolomics Unit, Department of Biomedical Sciences, University of Cagliari, 09042 Cagliari, Italy
| | - Agata Maria Capodiferro
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
| | - Marcello Giuseppe Tanca
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
| | - Aran Hendren
- Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK
| | - Stella Giulia Falqui
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
| | - Michela Aresti
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
| | - Martina Comini
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
| | - Sara Carucci
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
| | - Eleonora Cocco
- Multiple Sclerosis Regional Center, ASSL Cagliari, Department of Medical Sciences and Public Health, University of Cagliari, 09126 Cagliari, Italy
| | - Lorena Lorefice
- Multiple Sclerosis Regional Center, ASSL Cagliari, 09126 Cagliari, Italy
| | - Michele Roccella
- Department of Psychology, Educational Science and Human Movement, University of Palermo, 90128 Palermo, Italy
| | - Luigi Vetri
- Oasi Research Institute-IRCCS, Via Conte Ruggero 73, 94018 Troina, Italy
| | - Stefano Sotgiu
- Child Neuropsychiatry Unit, Department of Medicine, Surgery and Farmacy, University of Sassari, 07100 Sassari, Italy
| | - Alessandro Zuddas
- Child & Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, “A. Cao” Paediatric Hospital, University of Cagliari, 09121 Cagliari, Italy
| | - Luigi Atzori
- Clinical Metabolomics Unit, Department of Biomedical Sciences, University of Cagliari, 09042 Cagliari, Italy
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21
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Tang F, Krishnamurthy K, Janovick J, Crawford L, Wang S, Hatzakis E. Advancing NMR-based metabolomics using Complete Reduction to Amplitude Frequency Table: Cultivar differentiation of black ripe table olives as a case study. Food Chem 2022; 405:134868. [DOI: 10.1016/j.foodchem.2022.134868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 10/24/2022] [Accepted: 11/03/2022] [Indexed: 11/09/2022]
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22
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Kim HC, Baek KH, Lee YE, Kang T, Kim HJ, Lee D, Jo C. Using 2D qNMR analysis to distinguish between frozen and frozen/thawed chicken meat and evaluate freshness. NPJ Sci Food 2022; 6:44. [PMID: 36138019 PMCID: PMC9500024 DOI: 10.1038/s41538-022-00159-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Accepted: 08/31/2022] [Indexed: 11/09/2022] Open
Abstract
We identified key metabolites reflecting microbial spoilage and differentiated unfrozen meat from frozen/thawed (FT) using 2D qNMR analysis. Unfrozen and FT chicken breasts were prepared, individually aerobically packaged, and stored for 16 days at 2 °C. Only volatile basic nitrogen (VBN) was significantly changed after 6 log CFU/g of total aerobic bacteria (p < 0.05). Extended storage resulted in an increase in organic acids, free amino acids, biogenic amines, and hypoxanthine and a decrease in N,N-dimethylglycine, inosine 5'-monophosphate, and proline. Acetic acid demonstrated the highest correlation with VBN (r = 0.97). Unfrozen and FT breast meat can be differentiated by uniform concentration of carnosine, β-alanine, and histidine levels, consistent changes in nucleotides by storage time, and changes in microbial metabolism patterns that are reflected by some free amino acids. Thus, NMR-based metabolomics can be used to evaluate chicken breast meat freshness and distinguish between unfrozen and FT meat.
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Affiliation(s)
- Hyun Cheol Kim
- Department of Agricultural Biotechnology, Center for Food and Bioconvergence, and Research Institute of Agriculture and Life Science, Seoul National University, Seoul, Republic of Korea.,Division of Chemical and Biological Metrology, Korea Research Institute of Standards and Science, Daejeon, Republic of Korea
| | - Ki Ho Baek
- Department of Agricultural Biotechnology, Center for Food and Bioconvergence, and Research Institute of Agriculture and Life Science, Seoul National University, Seoul, Republic of Korea.,Surface Technology Division, Korea Institute of Material Sciences, Changwon, Republic of Korea
| | - Yee Eun Lee
- Department of Agricultural Biotechnology, Center for Food and Bioconvergence, and Research Institute of Agriculture and Life Science, Seoul National University, Seoul, Republic of Korea
| | - Taemin Kang
- Department of Agricultural Biotechnology, Center for Food and Bioconvergence, and Research Institute of Agriculture and Life Science, Seoul National University, Seoul, Republic of Korea
| | - Hyun Jun Kim
- Department of Agricultural Biotechnology, Center for Food and Bioconvergence, and Research Institute of Agriculture and Life Science, Seoul National University, Seoul, Republic of Korea
| | - Dongheon Lee
- Department of Agricultural Biotechnology, Center for Food and Bioconvergence, and Research Institute of Agriculture and Life Science, Seoul National University, Seoul, Republic of Korea
| | - Cheorun Jo
- Department of Agricultural Biotechnology, Center for Food and Bioconvergence, and Research Institute of Agriculture and Life Science, Seoul National University, Seoul, Republic of Korea. .,Institute of Green Bio Science and Technology, Seoul National University, Pyeongchang, Republic of Korea.
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Dehghani F, Yousefinejad S, Walker DI, Omidi F. Metabolomics for exposure assessment and toxicity effects of occupational pollutants: current status and future perspectives. Metabolomics 2022; 18:73. [PMID: 36083566 DOI: 10.1007/s11306-022-01930-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 08/19/2022] [Indexed: 11/24/2022]
Abstract
INTRODUCTION Work-related exposures to harmful agents or factors are associated with an increase in incidence of occupational diseases. These exposures often represent a complex mixture of different stressors, challenging the ability to delineate the mechanisms and risk factors underlying exposure-disease relationships. The use of omics measurement approaches that enable characterization of biological marker patterns provide internal indicators of molecular alterations, which could be used to identify bioeffects following exposure to a toxicant. Metabolomics is the comprehensive analysis of small molecule present in biological samples, and allows identification of potential modes of action and altered pathways by systematic measurement of metabolites. OBJECTIVES The aim of this study is to review the application of metabolomics studies for use in occupational health, with a focus on applying metabolomics for exposure monitoring and its relationship to occupational diseases. METHODS PubMed, Web of Science, Embase and Scopus electronic databases were systematically searched for relevant studies published up to 2021. RESULTS Most of reviewed studies included worker populations exposed to heavy metals such as As, Cd, Pb, Cr, Ni, Mn and organic compounds such as tetrachlorodibenzo-p-dioxin, trichloroethylene, polyfluoroalkyl, acrylamide, polyvinyl chloride. Occupational exposures were associated with changes in metabolites and pathways, and provided novel insight into the relationship between exposure and disease outcomes. The reviewed studies demonstrate that metabolomics provides a powerful ability to identify metabolic phenotypes and bioeffect of occupational exposures. CONCLUSION Continued application to worker populations has the potential to enable characterization of thousands of chemical signals in biological samples, which could lead to discovery of new biomarkers of exposure for chemicals, identify possible toxicological mechanisms, and improved understanding of biological effects increasing disease risk associated with occupational exposure.
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Affiliation(s)
- Fatemeh Dehghani
- Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran
- Research Center for Health Sciences, Research Institute for Health, Department of Occupational Health and Safety Engineering, School of Health Shiraz, University of Medical Sciences, Shiraz, Iran
| | - Saeed Yousefinejad
- Research Center for Health Sciences, Research Institute for Health, Department of Occupational Health and Safety Engineering, School of Health Shiraz, University of Medical Sciences, Shiraz, Iran.
| | - Douglas I Walker
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Fariborz Omidi
- Research Center for Environmental Determinants of Health (RCEDH), Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
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Delvaux A, Rathahao-Paris E, Alves S. Different ion mobility-mass spectrometry coupling techniques to promote metabolomics. MASS SPECTROMETRY REVIEWS 2022; 41:695-721. [PMID: 33492707 DOI: 10.1002/mas.21685] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Metabolomics has become increasingly popular in recent years for many applications ranging from clinical diagnosis, human health to biotechnological questioning. Despite technological advances, metabolomic studies are still currently limited by the difficulty of identifying all metabolites, a class of compounds with great chemical diversity. Although lengthy chromatographic analyses are often used to obtain comprehensive data, many isobar and isomer metabolites still remain unresolved, which is a critical point for the compound identification. Currently, ion mobility spectrometry is being explored in metabolomics as a way to improve metabolome coverage, analysis throughput and isomer separation. In this review, all the steps of a typical workflow for untargeted metabolomics are discussed considering the use of an ion mobility instrument. An overview of metabolomics is first presented followed by a brief description of ion mobility instrumentation. The ion mobility potential for complex mixture analysis is discussed regarding its coupling with a mass spectrometer alone, providing gas-phase separation before mass analysis as well as its combination with different separation platforms (conventional hyphenation but also multidimensional ion mobility couplings), offering multidimensional separation. Various instrumental and analytical conditions for improving the ion mobility separation are also described. Finally, data mining, including software packages and visualization approaches, as well as the construction of ion mobility databases for the metabolite identification are examined.
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Affiliation(s)
- Aurélie Delvaux
- Faculté des Sciences et de l'Ingénierie, Institut Parisien de Chimie Moléculaire (IPCM), Sorbonne Université, Paris, 75005, France
| | - Estelle Rathahao-Paris
- Faculté des Sciences et de l'Ingénierie, Institut Parisien de Chimie Moléculaire (IPCM), Sorbonne Université, Paris, 75005, France
- Département Médicaments et Technologies pour la Santé (DMTS), SPI, Université Paris-Saclay, CEA, INRAE, Gif-sur-Yvette, 91191, France
| | - Sandra Alves
- Faculté des Sciences et de l'Ingénierie, Institut Parisien de Chimie Moléculaire (IPCM), Sorbonne Université, Paris, 75005, France
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Bourafai-Aziez A, Jacob D, Charpentier G, Cassin E, Rousselot G, Moing A, Deborde C. Development, Validation, and Use of 1H-NMR Spectroscopy for Evaluating the Quality of Acerola-Based Food Supplements and Quantifying Ascorbic Acid. Molecules 2022; 27:molecules27175614. [PMID: 36080394 PMCID: PMC9458237 DOI: 10.3390/molecules27175614] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2022] [Revised: 08/22/2022] [Accepted: 08/23/2022] [Indexed: 12/04/2022] Open
Abstract
Acerola (Malpighia emarginata D.C.) is an exotic fruit with high agro-industrial potential due to its high content of ascorbic acid (AA), phenolic compounds, and carotenoid pigments. Acerola fruit is processed into concentrated juice or powder to be incorporated into food supplements. The ascorbic acid content of concentrated juice or powders must be controlled and well assessed. Therefore, the development of optimal methods and procedures for the rapid and accurate determination of the ascorbic acid content in juice concentrate and juice powder remains of considerable commercial interest. NMR spectroscopy is currently a powerful spectroscopic tool for the qualitative and quantitative analysis of molecules of all types and sizes. Firstly, this article presents the NMR-based metabolomic profiling of acerola juice and concentrate powder to describe and compare their composition. Thirty-six metabolites were identified. The AA over choline ratio and the NMR metabolomic profiles could be used for authentication in the future. Secondly, a rapid (8 min), reliable, and non-destructive method for the quantification of ascorbic acid by 1D 1H-NMR spectroscopy was developed and validated. The LOD and LOQ were 0.05 and 0.15 mg/mL, respectively. These two approaches could be combined to better characterize ingredients derived from acerola and incorporated into food supplements.
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Affiliation(s)
- Asma Bourafai-Aziez
- EVEAR EXTRACTION, 48 Route de Gennes, LD Félines, CEDEX 4, F-49320 Coutures, France
- Correspondence: (A.B.-A.); (C.D.)
| | - Daniel Jacob
- INRAE, Univ. Bordeaux, Fruit Biology and Pathology, UMR1332, 71 Avenue E. Bourlaux, F-33140 Villenave d’Ornon, France
- Bordeaux Metabolome, MetaboHUB, PHENOME-EMPHASIS, 71 Avenue E. Bourlaux, F-33140 Villenave d’Ornon, France
| | - Gwladys Charpentier
- EVEAR EXTRACTION, 48 Route de Gennes, LD Félines, CEDEX 4, F-49320 Coutures, France
| | - Emmanuel Cassin
- EVEAR EXTRACTION, 48 Route de Gennes, LD Félines, CEDEX 4, F-49320 Coutures, France
| | - Guillaume Rousselot
- EVEAR EXTRACTION, 48 Route de Gennes, LD Félines, CEDEX 4, F-49320 Coutures, France
| | - Annick Moing
- INRAE, Univ. Bordeaux, Fruit Biology and Pathology, UMR1332, 71 Avenue E. Bourlaux, F-33140 Villenave d’Ornon, France
- Bordeaux Metabolome, MetaboHUB, PHENOME-EMPHASIS, 71 Avenue E. Bourlaux, F-33140 Villenave d’Ornon, France
| | - Catherine Deborde
- INRAE, Univ. Bordeaux, Fruit Biology and Pathology, UMR1332, 71 Avenue E. Bourlaux, F-33140 Villenave d’Ornon, France
- Bordeaux Metabolome, MetaboHUB, PHENOME-EMPHASIS, 71 Avenue E. Bourlaux, F-33140 Villenave d’Ornon, France
- Correspondence: (A.B.-A.); (C.D.)
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Coope A, Ghanameh Z, Kingston O, Sheridan CM, Barrett-Jolley R, Phelan MM, Oldershaw RA. 1H NMR Metabolite Monitoring during the Differentiation of Human Induced Pluripotent Stem Cells Provides New Insights into the Molecular Events That Regulate Embryonic Chondrogenesis. Int J Mol Sci 2022; 23:ijms23169266. [PMID: 36012540 PMCID: PMC9409419 DOI: 10.3390/ijms23169266] [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: 06/17/2022] [Revised: 08/05/2022] [Accepted: 08/11/2022] [Indexed: 11/16/2022] Open
Abstract
The integration of cell metabolism with signalling pathways, transcription factor networks and epigenetic mediators is critical in coordinating molecular and cellular events during embryogenesis. Induced pluripotent stem cells (IPSCs) are an established model for embryogenesis, germ layer specification and cell lineage differentiation, advancing the study of human embryonic development and the translation of innovations in drug discovery, disease modelling and cell-based therapies. The metabolic regulation of IPSC pluripotency is mediated by balancing glycolysis and oxidative phosphorylation, but there is a paucity of data regarding the influence of individual metabolite changes during cell lineage differentiation. We used 1H NMR metabolite fingerprinting and footprinting to monitor metabolite levels as IPSCs are directed in a three-stage protocol through primitive streak/mesendoderm, mesoderm and chondrogenic populations. Metabolite changes were associated with central metabolism, with aerobic glycolysis predominant in IPSC, elevated oxidative phosphorylation during differentiation and fatty acid oxidation and ketone body use in chondrogenic cells. Metabolites were also implicated in the epigenetic regulation of pluripotency, cell signalling and biosynthetic pathways. Our results show that 1H NMR metabolomics is an effective tool for monitoring metabolite changes during the differentiation of pluripotent cells with implications on optimising media and environmental parameters for the study of embryogenesis and translational applications.
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Affiliation(s)
- Ashley Coope
- Department of Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, Faculty of Health and Life Sciences, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool L7 8TX, UK
- Clinical Directorate Professional Services, Aintree University Hospital, Liverpool University Hospitals NHS Foundation Trust, Lower Lane, Liverpool L9 7AL, UK
| | - Zain Ghanameh
- Department of Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, Faculty of Health and Life Sciences, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool L7 8TX, UK
| | - Olivia Kingston
- Department of Eye and Vision Sciences, Institute of Life Course and Medical Sciences, Faculty of Health and Life Sciences, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool L7 8TX, UK
| | - Carl M. Sheridan
- Department of Eye and Vision Sciences, Institute of Life Course and Medical Sciences, Faculty of Health and Life Sciences, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool L7 8TX, UK
| | - Richard Barrett-Jolley
- Department of Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, Faculty of Health and Life Sciences, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool L7 8TX, UK
| | - Marie M. Phelan
- Department of Biochemistry, Institute of Systems, Molecular and Integrative Biology, Faculty of Health and Life Sciences, University of Liverpool, Biosciences Building, Crown Street, Liverpool L7 7BE, UK
- High Field NMR Facility, Liverpool Shared Research Facilities (LIV-SRF), Faculty of Health and Life Sciences, University of Liverpool, Crown Street, Liverpool L69 7ZB, UK
| | - Rachel A. Oldershaw
- Department of Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, Faculty of Health and Life Sciences, University of Liverpool, William Henry Duncan Building, 6 West Derby Street, Liverpool L7 8TX, UK
- Correspondence:
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Morgan EW, Perdew GH, Patterson AD. Multi-Omics Strategies for Investigating the Microbiome in Toxicology Research. Toxicol Sci 2022; 187:189-213. [PMID: 35285497 PMCID: PMC9154275 DOI: 10.1093/toxsci/kfac029] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Microbial communities on and within the host contact environmental pollutants, toxic compounds, and other xenobiotic compounds. These communities of bacteria, fungi, viruses, and archaea possess diverse metabolic potential to catabolize compounds and produce new metabolites. Microbes alter chemical disposition thus making the microbiome a natural subject of interest for toxicology. Sequencing and metabolomics technologies permit the study of microbiomes altered by acute or long-term exposure to xenobiotics. These investigations have already contributed to and are helping to re-interpret traditional understandings of toxicology. The purpose of this review is to provide a survey of the current methods used to characterize microbes within the context of toxicology. This will include discussion of commonly used techniques for conducting omic-based experiments, their respective strengths and deficiencies, and how forward-looking techniques may address present shortcomings. Finally, a perspective will be provided regarding common assumptions that currently impede microbiome studies from producing causal explanations of toxicologic mechanisms.
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Affiliation(s)
- Ethan W Morgan
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Gary H Perdew
- Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Andrew D Patterson
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania 16802, USA.,Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
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29
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Yang Z, Su HS, You EM, Liu S, Li Z, Zhang Y. High Uniformity and Enhancement Au@AgNS 3D Substrates for the Diagnosis of Breast Cancer. ACS OMEGA 2022; 7:15223-15230. [PMID: 35572747 PMCID: PMC9089677 DOI: 10.1021/acsomega.2c01453] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 04/08/2022] [Indexed: 06/15/2023]
Abstract
Breast cancer appears to be one of the leading causes of cancer-related morbidity and mortality for women worldwide. The accurate and rapid diagnosis of breast cancer is hence critical for the treatment and prognosis of patients. With the vibrational fingerprint information and high detection sensitivity, surface-enhanced Raman spectroscopy (SERS) has been extensively applied in biomedicine. Here, an optimized bimetallic nanosphere (Au@Ag NS) 3D substrate was fabricated for the aim of the diagnosis of breast cancer based on the SERS analysis of the extracellular metabolites. The unique stacking mode of 3D Au@Ag NSs provided multiple plasmonic hot spots according to the theoretical calculations of the electromagnetic field distribution. The low relative standard deviation (RSD = 2.7%) and high enhancement factor (EF = 1.42 × 105) proved the uniformity and high sensitivity. More importantly, the normal breast cells and breast cancer cells could be readily distinguished from the corresponding SERS spectra based on the extracellular metabolites. Furthermore, the clear clusters of SERS spectra from MCF-7 and MDA-MB-231 extracellular metabolites in the orthogonal partial least-squares discriminant analysis plot indicate the distinct metabolic fingerprint between breast cancer cells, which imply their potential clinical application in the diagnosis of breast cancer.
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Affiliation(s)
- Zhengxia Yang
- CAS
Key Laboratory of Design and Assembly of Functional Nanostructures,
and Fujian Provincial Key Laboratory of Nanomaterials, Fujian Institute
of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350002, P. R. China
- Xiamen
Institute of Rare Earth Materials, Haixi Institute, Xiamen Key Laboratory
of Rare Earth Photoelectric Functional Materials, Chinese Academy of Sciences, Xiamen 361021, P. R. China
| | - Hai-Sheng Su
- CAS
Key Laboratory of Design and Assembly of Functional Nanostructures,
and Fujian Provincial Key Laboratory of Nanomaterials, Fujian Institute
of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350002, P. R. China
- Xiamen
Institute of Rare Earth Materials, Haixi Institute, Xiamen Key Laboratory
of Rare Earth Photoelectric Functional Materials, Chinese Academy of Sciences, Xiamen 361021, P. R. China
| | - En-Ming You
- State
Key Laboratory of Physical Chemistry of Solid Surfaces, College of
Chemistry and Chemical Engineering, Xiamen
University, Xiamen 361005, China
| | - Siying Liu
- CAS
Key Laboratory of Design and Assembly of Functional Nanostructures,
and Fujian Provincial Key Laboratory of Nanomaterials, Fujian Institute
of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350002, P. R. China
- Xiamen
Institute of Rare Earth Materials, Haixi Institute, Xiamen Key Laboratory
of Rare Earth Photoelectric Functional Materials, Chinese Academy of Sciences, Xiamen 361021, P. R. China
- University
of Chinese Academy of Sciences, Beijing 100049, P. R.
China
| | - Zihang Li
- Wenzhou-Kean
University, 88 Daxue
Road, Ouhai, Wenzhou, Zhejiang
Province 325060, China
| | - Yun Zhang
- CAS
Key Laboratory of Design and Assembly of Functional Nanostructures,
and Fujian Provincial Key Laboratory of Nanomaterials, Fujian Institute
of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou 350002, P. R. China
- Xiamen
Institute of Rare Earth Materials, Haixi Institute, Xiamen Key Laboratory
of Rare Earth Photoelectric Functional Materials, Chinese Academy of Sciences, Xiamen 361021, P. R. China
- University
of Chinese Academy of Sciences, Beijing 100049, P. R.
China
- Ganjiang
Innovation Academy, Chinese Academy of Sciences, Ganzhou, Jiangxi 341000, P. R. China
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30
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Fecal 1H-NMR Metabolomics: A Comparison of Sample Preparation Methods for NMR and Novel in Silico Baseline Correction. Metabolites 2022; 12:metabo12020148. [PMID: 35208222 PMCID: PMC8875708 DOI: 10.3390/metabo12020148] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 01/28/2022] [Accepted: 02/01/2022] [Indexed: 11/17/2022] Open
Abstract
Analysis of enteric microbiota function indirectly through the fecal metabolome has the potential to be an informative diagnostic tool. However, metabolomic analysis of feces is hampered by high concentrations of macromolecules such as proteins, fats, and fiber in samples. Three methods—ultrafiltration (UF), Bligh–Dyer (BD), and no extraction (samples added directly to buffer, vortexed, and centrifuged)—were tested on multiple rat (n = 10) and chicken (n = 8) fecal samples to ascertain whether the methods worked equally well across species and individuals. An in silico baseline correction method was evaluated to determine if an algorithm could produce spectra similar to those obtained via UF. For both rat and chicken feces, UF removed all macromolecules and produced no baseline distortion among samples. By contrast, the BD and no extraction methods did not remove all the macromolecules and produced baseline distortions. The application of in silico baseline correction produced spectra comparable to UF spectra. In the case of no extraction, more intense peaks were produced. This suggests that baseline correction may be a cost-effective method for metabolomic analyses of fecal samples and an alternative to UF. UF was the most versatile and efficient extraction method; however, BD and no extraction followed by baseline correction can produce comparable results.
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Yong CH, Muhammad SA, Aziz FA, Ng JS, Nasir FI, Adenan M, Moosa S, Othman Z, Abdullah S, Sharif Z, Ismail F, Kelly SD, Cannavan A, Seow EK. Detection of adulteration activities in edible bird's nest using untargeted 1H-NMR metabolomics with chemometrics. Food Control 2022. [DOI: 10.1016/j.foodcont.2021.108542] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
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Yong CH, Muhammad SA, Aziz FA, Nasir FI, Mustafa MZ, Ibrahim B, Kelly SD, Cannavan A, Seow EK. Detecting adulteration of stingless bee honey using untargeted 1H NMR metabolomics with chemometrics. Food Chem 2022; 368:130808. [PMID: 34419793 DOI: 10.1016/j.foodchem.2021.130808] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 07/27/2021] [Accepted: 08/05/2021] [Indexed: 12/31/2022]
Abstract
As stingless bee honey (SBH) is gaining in popularity in the Malaysian market, it is now prone to adulteration. The higher price of SBH compared to floral honey has led to the use of unusual adulterants such as vinegar and even floral honey to mimic the unique taste and appearance of SBH. Since the current AOAC 998.12 method fails to detect these adulterants as their δ13C values are in the range for C3 plants, untargeted 1H NMR metabolomics was proposed. Principal component analysis of SBH 1H NMR fingerprints was able to distinguish authentic SBHs from adulterated ones down to 1% adulteration level for selected adulterants. Discriminant analysis showed promising results in distinguishing the preliminary datasets of authentic SBHs from the adulterated ones, including discriminating SBHs adulterated with different adulterants derived from C3 and C4 plants. Hence, to assure any emerging adulterant can be detected, all 1H NMR regions should be considered.
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Affiliation(s)
- Chin-Hong Yong
- Environmental Technology Division, School of Industrial Technology, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia
| | - Syahidah Akmal Muhammad
- Environmental Technology Division, School of Industrial Technology, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia; Analytical Biochemistry Research Centre, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia.
| | - Fatimatuzzahra' Abd Aziz
- Discipline of Clinical Pharmacy, School of Pharmaceutical Sciences, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia
| | - Fatin Ilyani Nasir
- Analytical Biochemistry Research Centre, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia
| | - Mohd Zulkifli Mustafa
- Department of Neuroscience, School of Medical Sciences, Universiti Sains Malaysia, 16150 Kubang Kerian, Kelantan, Malaysia
| | - Baharudin Ibrahim
- Faculty of Pharmacy, University of Malaya, Kuala Lumpur 50603, Malaysia
| | - Simon D Kelly
- Food and Environmental Protection Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, PO Box 100, 1400 Vienna, Austria
| | - Andrew Cannavan
- Food and Environmental Protection Laboratory, Joint FAO/IAEA Centre of Nuclear Techniques in Food and Agriculture, Department of Nuclear Sciences and Applications, International Atomic Energy Agency, Vienna International Centre, PO Box 100, 1400 Vienna, Austria
| | - Eng-Keng Seow
- Department of Food Science and Technology, Faculty of Applied Sciences, Universiti Teknologi MARA, 40450 Shah Alam, Selangor, Malaysia
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Wang Y, Liu ZP. Identifying biomarkers for breast cancer by gene regulatory network rewiring. BMC Bioinformatics 2022; 22:308. [PMID: 35045805 PMCID: PMC8772043 DOI: 10.1186/s12859-021-04225-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Accepted: 06/01/2021] [Indexed: 12/09/2022] Open
Abstract
Background Mining gene regulatory network (GRN) is an important avenue for addressing cancer mechanism. Mutations in cancer genome perturb GRN and cause a rewiring in an orchestrated network. Hence, the exploration of gene regulatory network rewiring is significant to discover potential biomarkers and indicators for discriminating cancer phenotypes. Results Here, we propose a new bioinformatics method of identifying biomarkers based on network rewiring in different states. It firstly reconstructs GRN in different phenotypic conditions from gene expression data with a priori background network. We employ the algorithm based on path consistency algorithm and conditional mutual information to delete false-positive regulatory interactions between independent nodes/genes or not closely related gene pairs. And then a differential gene regulatory network (D-GRN) is constructed from the rewiring parts in the two phenotype-specific GRNs. Community detection technique is then applied for D-GRN to detect functional modules. Finally, we apply logistic regression classifier with recursive feature elimination to select biomarker genes in each module individually. The extracted feature genes result in a gene set of biomarkers with impressing ability to distinguish normal samples from controls. We verify the identified biomarkers in external independent validation datasets. For a proof-of-concept study, we apply the framework to identify diagnostic biomarkers of breast cancer. The identified biomarkers obtain a maximum AUC of 0.985 in the internal sample classification experiments. And these biomarkers achieve a maximum AUC of 0.989 in the external validations. Conclusion In conclusion, network rewiring reveals significant differences between different phenotypes, which indicating cancer dysfunctional mechanisms. With the development of sequencing technology, the amount and quality of gene expression data become available. Condition-specific gene regulatory networks that are close to the real regulations in different states will be established. Revealing the network rewiring will greatly benefit the discovery of biomarkers or signatures for phenotypes. D-GRN is a general method to meet this demand of deciphering the high-throughput data for biomarker discovery. It is also easy to be extended for identifying biomarkers of other complex diseases beyond breast cancer.
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Affiliation(s)
- Yijuan Wang
- Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan, 250061, Shandong, China
| | - Zhi-Ping Liu
- Department of Biomedical Engineering, School of Control Science and Engineering, Shandong University, Jinan, 250061, Shandong, China.
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Geller S, Lieberman H, Belanger AJ, Yew NS, Kloss A, Ivanov AR. Comparison of Microflow and Analytical Flow Liquid Chromatography Coupled to Mass Spectrometry Global Metabolomics Methods Using a Urea Cycle Disorder Mouse Model. J Proteome Res 2022; 21:151-163. [PMID: 34843255 PMCID: PMC8742624 DOI: 10.1021/acs.jproteome.1c00628] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Microscale-based separations are increasingly being applied in the field of metabolomics for the analysis of small-molecule metabolites. These methods have the potential to provide improved sensitivity, less solvent waste, and reduced sample-size requirements. Ion-pair free microflow-based global metabolomics methods, which we recently reported, were further compared to analytical flow ion-pairing reagent containing methods using a sample set from a urea cycle disorder (UCD) mouse model. Mouse urine and brain homogenate samples representing healthy, diseased, and disease-treated animals were analyzed by both methods. Data processing was performed using univariate and multivariate techniques followed by analyte trend analysis. The microflow methods performed comparably to the analytical flow ion-pairing methods with the ability to separate the three sample groups when analyzed by partial least-squares analysis. The number of detected metabolic features present after each data processing step was similar between the microflow-based methods and the ion-pairing methods in the negative ionization mode. The observed analyte trend and coverage of known UCD biomarkers were the same for both evaluated approaches. The 12.5-fold reduction in sample injection volume required for the microflow-based separations highlights the potential of this method to support studies with sample-size limitations.
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Affiliation(s)
- Sarah Geller
- Sanofi, Waltham, Massachusetts 02451, United States
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
| | | | | | - Nelson S Yew
- Sanofi, Waltham, Massachusetts 02451, United States
| | - Alla Kloss
- Sanofi, Waltham, Massachusetts 02451, United States
| | - Alexander R Ivanov
- Barnett Institute of Chemical and Biological Analysis, Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
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Beteinakis S, Papachristodoulou A, Mikros E, Halabalaki M. From sample preparation to NMR-based metabolic profiling in food commodities: The case of table olives. PHYTOCHEMICAL ANALYSIS : PCA 2022; 33:83-93. [PMID: 34096121 DOI: 10.1002/pca.3070] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 05/10/2021] [Accepted: 05/15/2021] [Indexed: 06/12/2023]
Abstract
INTRODUCTION Nuclear magnetic resonance (NMR)-based metabolic profiling has been widely used in food and plant sciences. Despite its simplicity and inherent reproducibility, the determination of the appropriate pre-processing procedures greatly affects the obtained metabolic profile. OBJECTIVES The current study represents a detailed guide of use for untargeted NMR-based metabolic profiling of table olives (Olea europaea L.). METHODS Greek Kalamon table olives from different geographical origins were selected as reference materials. Differently treated samples were extracted using different solvents and/or solvent systems. Chemical profiles were evaluated with high-performance thin layer chromatography (HPTLC). Different deuterated solvents and sample concentrations were evaluated for the recording of optimal quality spectra. RESULTS The methanol extract of freeze-dried table olives was found to contain the most representative secondary metabolites, in higher concentrations, as well. The optimal deuterated solvent for the NMR analysis was methanol-d4 , while final sample concentration should be within the range of 10 to 15 mg/mL. Multivariate data analysis was also used to estimate and confirm the variation and clustering caused by different characteristics of the samples. CONCLUSIONS Results of the present study make evident the necessity for thorough planning and method development prior to any extensive metabolomic study based on NMR spectroscopy. Pre-processing and sample preparation stages seemed to greatly affect the metabolic profile and spectral quality in the case of table olives, which by extrapolation could apply to other food commodities. Nevertheless, the nature of the samples must be fully described in general, in order to proceed to solid conclusions.
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Affiliation(s)
- Stavros Beteinakis
- Division of Pharmacognosy and Natural Products Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece
| | - Anastasia Papachristodoulou
- Division of Pharmacognosy and Natural Products Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece
| | - Emmanuel Mikros
- Division of Pharmaceutical Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece
| | - Maria Halabalaki
- Division of Pharmacognosy and Natural Products Chemistry, Department of Pharmacy, National and Kapodistrian University of Athens, Athens, Greece
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Ghassemi N, Poulhazan A, Deligey F, Mentink-Vigier F, Marcotte I, Wang T. Solid-State NMR Investigations of Extracellular Matrixes and Cell Walls of Algae, Bacteria, Fungi, and Plants. Chem Rev 2021; 122:10036-10086. [PMID: 34878762 DOI: 10.1021/acs.chemrev.1c00669] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Extracellular matrixes (ECMs), such as the cell walls and biofilms, are important for supporting cell integrity and function and regulating intercellular communication. These biomaterials are also of significant interest to the production of biofuels and the development of antimicrobial treatment. Solid-state nuclear magnetic resonance (ssNMR) and magic-angle spinning-dynamic nuclear polarization (MAS-DNP) are uniquely powerful for understanding the conformational structure, dynamical characteristics, and supramolecular assemblies of carbohydrates and other biomolecules in ECMs. This review highlights the recent high-resolution investigations of intact ECMs and native cells in many organisms spanning across plants, bacteria, fungi, and algae. We spotlight the structural principles identified in ECMs, discuss the current technical limitation and underexplored biochemical topics, and point out the promising opportunities enabled by the recent advances of the rapidly evolving ssNMR technology.
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Affiliation(s)
- Nader Ghassemi
- Department of Chemistry, Louisiana State University, Baton Rouge, Louisiana 70803, United States
| | - Alexandre Poulhazan
- Department of Chemistry, Louisiana State University, Baton Rouge, Louisiana 70803, United States.,Department of Chemistry, Université du Québec à Montréal, Montreal H2X 2J6, Canada
| | - Fabien Deligey
- Department of Chemistry, Louisiana State University, Baton Rouge, Louisiana 70803, United States
| | | | - Isabelle Marcotte
- Department of Chemistry, Université du Québec à Montréal, Montreal H2X 2J6, Canada
| | - Tuo Wang
- Department of Chemistry, Louisiana State University, Baton Rouge, Louisiana 70803, United States
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Ornelas-González A, Ortiz-Martínez M, González-González M, Rito-Palomares M. Enzymatic Methods for Salivary Biomarkers Detection: Overview and Current Challenges. Molecules 2021; 26:7026. [PMID: 34834116 PMCID: PMC8624596 DOI: 10.3390/molecules26227026] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 10/28/2021] [Accepted: 10/31/2021] [Indexed: 12/12/2022] Open
Abstract
Early detection is a key factor in patient fate. Currently, multiple biomolecules have been recognized as biomarkers. Nevertheless, their identification is only the starting line on the way to their implementation in disease diagnosis. Although blood is the biofluid par excellence for the quantification of biomarkers, its extraction is uncomfortable and painful for many patients. In this sense, there is a gap in which saliva emerges as a non-invasive and valuable source of information, as it contains many of the biomarkers found in blood. Recent technological advances have made it possible to detect and quantify biomarkers in saliva samples. However, there are opportunity areas in terms of cost and complexity, which could be solved using simpler methodologies such as those based on enzymes. Many reviews have focused on presenting the state-of-the-art in identifying biomarkers in saliva samples. However, just a few of them provide critical analysis of technical elements for biomarker quantification in enzymatic methods for large-scale clinical applications. Thus, this review proposes enzymatic assays as a cost-effective alternative to overcome the limitations of current methods for the quantification of biomarkers in saliva, highlighting the technical and operational considerations necessary for sampling, method development, optimization, and validation.
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Affiliation(s)
| | | | - Mirna González-González
- Escuela de Medicina y Ciencias de la Salud, Tecnologico de Monterrey, Av. Morones Prieto 3000, Monterrey 64710, N.L., Mexico; (A.O.-G.); (M.O.-M.)
| | - Marco Rito-Palomares
- Escuela de Medicina y Ciencias de la Salud, Tecnologico de Monterrey, Av. Morones Prieto 3000, Monterrey 64710, N.L., Mexico; (A.O.-G.); (M.O.-M.)
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Rispoli MG, Valentinuzzi S, De Luca G, Del Boccio P, Federici L, Di Ioia M, Digiovanni A, Grasso EA, Pozzilli V, Villani A, Chiarelli AM, Onofrj M, Wise RG, Pieragostino D, Tomassini V. Contribution of Metabolomics to Multiple Sclerosis Diagnosis, Prognosis and Treatment. Int J Mol Sci 2021; 22:ijms222011112. [PMID: 34681773 PMCID: PMC8541167 DOI: 10.3390/ijms222011112] [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: 09/15/2021] [Revised: 10/08/2021] [Accepted: 10/12/2021] [Indexed: 12/15/2022] Open
Abstract
Metabolomics-based technologies map in vivo biochemical changes that may be used as early indicators of pathological abnormalities prior to the development of clinical symptoms in neurological conditions. Metabolomics may also reveal biochemical pathways implicated in tissue dysfunction and damage and thus assist in the development of novel targeted therapeutics for neuroinflammation and neurodegeneration. Metabolomics holds promise as a non-invasive, high-throughput and cost-effective tool for early diagnosis, follow-up and monitoring of treatment response in multiple sclerosis (MS), in combination with clinical and imaging measures. In this review, we offer evidence in support of the potential of metabolomics as a biomarker and drug discovery tool in MS. We also use pathway analysis of metabolites that are described as potential biomarkers in the literature of MS biofluids to identify the most promising molecules and upstream regulators, and show novel, still unexplored metabolic pathways, whose investigation may open novel avenues of research.
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Affiliation(s)
- Marianna Gabriella Rispoli
- Institute for Advanced Biomedical Technologies (ITAB), Department of Neurosciences, Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy; (M.G.R.); (A.D.); (V.P.); (A.V.); (A.M.C.); (M.O.); (R.G.W.)
- Department of Neurology, “SS. Annunziata” University Hospital, 66100 Chieti, Italy; (G.D.L.); (M.D.I.)
| | - Silvia Valentinuzzi
- Analytical Biochemistry and Proteomics Research Unit, Centre for Advanced Studies and Technology (CAST), University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy; (S.V.); (P.D.B.); (L.F.)
- Department of Pharmacy, “G. d’Annunzio” University of Chieti-Pescara, 66100 Chieti, Italy
| | - Giovanna De Luca
- Department of Neurology, “SS. Annunziata” University Hospital, 66100 Chieti, Italy; (G.D.L.); (M.D.I.)
| | - Piero Del Boccio
- Analytical Biochemistry and Proteomics Research Unit, Centre for Advanced Studies and Technology (CAST), University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy; (S.V.); (P.D.B.); (L.F.)
- Department of Pharmacy, “G. d’Annunzio” University of Chieti-Pescara, 66100 Chieti, Italy
| | - Luca Federici
- Analytical Biochemistry and Proteomics Research Unit, Centre for Advanced Studies and Technology (CAST), University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy; (S.V.); (P.D.B.); (L.F.)
- Department of Innovative Technologies in Medicine and Dentistry, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy
| | - Maria Di Ioia
- Department of Neurology, “SS. Annunziata” University Hospital, 66100 Chieti, Italy; (G.D.L.); (M.D.I.)
| | - Anna Digiovanni
- Institute for Advanced Biomedical Technologies (ITAB), Department of Neurosciences, Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy; (M.G.R.); (A.D.); (V.P.); (A.V.); (A.M.C.); (M.O.); (R.G.W.)
- Department of Neurology, “SS. Annunziata” University Hospital, 66100 Chieti, Italy; (G.D.L.); (M.D.I.)
| | - Eleonora Agata Grasso
- Department of Innovative Technologies in Medicine and Dentistry, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy
| | - Valeria Pozzilli
- Institute for Advanced Biomedical Technologies (ITAB), Department of Neurosciences, Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy; (M.G.R.); (A.D.); (V.P.); (A.V.); (A.M.C.); (M.O.); (R.G.W.)
- Department of Neurology, “SS. Annunziata” University Hospital, 66100 Chieti, Italy; (G.D.L.); (M.D.I.)
| | - Alessandro Villani
- Institute for Advanced Biomedical Technologies (ITAB), Department of Neurosciences, Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy; (M.G.R.); (A.D.); (V.P.); (A.V.); (A.M.C.); (M.O.); (R.G.W.)
| | - Antonio Maria Chiarelli
- Institute for Advanced Biomedical Technologies (ITAB), Department of Neurosciences, Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy; (M.G.R.); (A.D.); (V.P.); (A.V.); (A.M.C.); (M.O.); (R.G.W.)
| | - Marco Onofrj
- Institute for Advanced Biomedical Technologies (ITAB), Department of Neurosciences, Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy; (M.G.R.); (A.D.); (V.P.); (A.V.); (A.M.C.); (M.O.); (R.G.W.)
- Department of Neurology, “SS. Annunziata” University Hospital, 66100 Chieti, Italy; (G.D.L.); (M.D.I.)
| | - Richard G. Wise
- Institute for Advanced Biomedical Technologies (ITAB), Department of Neurosciences, Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy; (M.G.R.); (A.D.); (V.P.); (A.V.); (A.M.C.); (M.O.); (R.G.W.)
| | - Damiana Pieragostino
- Analytical Biochemistry and Proteomics Research Unit, Centre for Advanced Studies and Technology (CAST), University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy; (S.V.); (P.D.B.); (L.F.)
- Department of Paediatrics, “G. d’Annunzio” University of Chieti-Pescara, 66100 Chieti, Italy;
- Correspondence: (D.P.); (V.T.)
| | - Valentina Tomassini
- Institute for Advanced Biomedical Technologies (ITAB), Department of Neurosciences, Imaging and Clinical Sciences, University “G. d’Annunzio” of Chieti-Pescara, 66100 Chieti, Italy; (M.G.R.); (A.D.); (V.P.); (A.V.); (A.M.C.); (M.O.); (R.G.W.)
- Department of Neurology, “SS. Annunziata” University Hospital, 66100 Chieti, Italy; (G.D.L.); (M.D.I.)
- Correspondence: (D.P.); (V.T.)
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Araújo AM, Carvalho F, Guedes de Pinho P, Carvalho M. Toxicometabolomics: Small Molecules to Answer Big Toxicological Questions. Metabolites 2021; 11:692. [PMID: 34677407 PMCID: PMC8539642 DOI: 10.3390/metabo11100692] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 10/05/2021] [Accepted: 10/05/2021] [Indexed: 12/17/2022] Open
Abstract
Given the high biological impact of classical and emerging toxicants, a sensitive and comprehensive assessment of the hazards and risks of these substances to organisms is urgently needed. In this sense, toxicometabolomics emerged as a new and growing field in life sciences, which use metabolomics to provide new sets of susceptibility, exposure, and/or effects biomarkers; and to characterize in detail the metabolic responses and altered biological pathways that various stressful stimuli cause in many organisms. The present review focuses on the analytical platforms and the typical workflow employed in toxicometabolomic studies, and gives an overview of recent exploratory research that applied metabolomics in various areas of toxicology.
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Affiliation(s)
- Ana Margarida Araújo
- Associate Laboratory i4HB, Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (F.C.); (P.G.d.P.)
- UCIBIO—Applied Molecular Biosciences Unit, REQUIMTE, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, Rua de Jorge Viterbo Ferreira nº228, 4050-313 Porto, Portugal
| | - Félix Carvalho
- Associate Laboratory i4HB, Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (F.C.); (P.G.d.P.)
- UCIBIO—Applied Molecular Biosciences Unit, REQUIMTE, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, Rua de Jorge Viterbo Ferreira nº228, 4050-313 Porto, Portugal
| | - Paula Guedes de Pinho
- Associate Laboratory i4HB, Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (F.C.); (P.G.d.P.)
- UCIBIO—Applied Molecular Biosciences Unit, REQUIMTE, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, Rua de Jorge Viterbo Ferreira nº228, 4050-313 Porto, Portugal
| | - Márcia Carvalho
- Associate Laboratory i4HB, Institute for Health and Bioeconomy, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal; (F.C.); (P.G.d.P.)
- UCIBIO—Applied Molecular Biosciences Unit, REQUIMTE, Laboratory of Toxicology, Department of Biological Sciences, Faculty of Pharmacy, University of Porto, Rua de Jorge Viterbo Ferreira nº228, 4050-313 Porto, Portugal
- FP-I3ID, FP-ENAS, University Fernando Pessoa, Praça 9 de Abril, 349, 4249-004 Porto, Portugal
- Faculty of Health Sciences, University Fernando Pessoa, Rua Carlos da Maia, 296, 4200-150 Porto, Portugal
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Anaraki MT, Lysak DH, Downey K, Kock FVC, You X, Majumdar RD, Barison A, Lião LM, Ferreira AG, Decker V, Goerling B, Spraul M, Godejohann M, Helm PA, Kleywegt S, Jobst K, Soong R, Simpson MJ, Simpson AJ. NMR spectroscopy of wastewater: A review, case study, and future potential. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2021; 126-127:121-180. [PMID: 34852923 DOI: 10.1016/j.pnmrs.2021.08.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Revised: 08/12/2021] [Accepted: 08/13/2021] [Indexed: 06/13/2023]
Abstract
NMR spectroscopy is arguably the most powerful tool for the study of molecular structures and interactions, and is increasingly being applied to environmental research, such as the study of wastewater. With over 97% of the planet's water being saltwater, and two thirds of freshwater being frozen in the ice caps and glaciers, there is a significant need to maintain and reuse the remaining 1%, which is a precious resource, critical to the sustainability of most life on Earth. Sanitation and reutilization of wastewater is an important method of water conservation, especially in arid regions, making the understanding of wastewater itself, and of its treatment processes, a highly relevant area of environmental research. Here, the benefits, challenges and subtleties of using NMR spectroscopy for the analysis of wastewater are considered. First, the techniques available to overcome the specific challenges arising from the nature of wastewater (which is a complex and dilute matrix), including an examination of sample preparation and NMR techniques (such as solvent suppression), in both the solid and solution states, are discussed. Then, the arsenal of available NMR techniques for both structure elucidation (e.g., heteronuclear, multidimensional NMR, homonuclear scalar coupling-based experiments) and the study of intermolecular interactions (e.g., diffusion, nuclear Overhauser and saturation transfer-based techniques) in wastewater are examined. Examples of wastewater NMR studies from the literature are reviewed and potential areas for future research are identified. Organized by nucleus, this review includes the common heteronuclei (13C, 15N, 19F, 31P, 29Si) as well as other environmentally relevant nuclei and metals such as 27Al, 51V, 207Pb and 113Cd, among others. Further, the potential of additional NMR methods such as comprehensive multiphase NMR, NMR microscopy and hyphenated techniques (for example, LC-SPE-NMR-MS) for advancing the current understanding of wastewater are discussed. In addition, a case study that combines natural abundance (i.e. non-concentrated), targeted and non-targeted NMR to characterize wastewater, along with in vivo based NMR to understand its toxicity, is included. The study demonstrates that, when applied comprehensively, NMR can provide unique insights into not just the structure, but also potential impacts, of wastewater and wastewater treatment processes. Finally, low-field NMR, which holds considerable future potential for on-site wastewater monitoring, is briefly discussed. In summary, NMR spectroscopy is one of the most versatile tools in modern science, with abilities to study all phases (gases, liquids, gels and solids), chemical structures, interactions, interfaces, toxicity and much more. The authors hope this review will inspire more scientists to embrace NMR, given its huge potential for both wastewater analysis in particular and environmental research in general.
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Affiliation(s)
- Maryam Tabatabaei Anaraki
- Environmental NMR Center, University of Toronto Scarborough, 1265 Military Trail, Toronto M1C1A4, Canada
| | - Daniel H Lysak
- Environmental NMR Center, University of Toronto Scarborough, 1265 Military Trail, Toronto M1C1A4, Canada
| | - Katelyn Downey
- Environmental NMR Center, University of Toronto Scarborough, 1265 Military Trail, Toronto M1C1A4, Canada
| | - Flávio Vinicius Crizóstomo Kock
- Environmental NMR Center, University of Toronto Scarborough, 1265 Military Trail, Toronto M1C1A4, Canada; Department of Chemistry, Federal University of São Carlos-SP (UFSCar), São Carlos, SP, Brazil
| | - Xiang You
- Environmental NMR Center, University of Toronto Scarborough, 1265 Military Trail, Toronto M1C1A4, Canada
| | - Rudraksha D Majumdar
- Environmental NMR Center, University of Toronto Scarborough, 1265 Military Trail, Toronto M1C1A4, Canada; Synex Medical, 2 Bloor Street E, Suite 310, Toronto, ON M4W 1A8, Canada
| | - Andersson Barison
- NMR Center, Federal University of Paraná, CP 19081, 81530-900 Curitiba, PR, Brazil
| | - Luciano Morais Lião
- NMR Center, Institute of Chemistry, Universidade Federal de Goiás, Goiânia 74690-900, Brazil
| | | | - Venita Decker
- Bruker Biospin GmbH, Silberstreifen 4, 76287 Rheinstetten, Germany
| | | | - Manfred Spraul
- Bruker Biospin GmbH, Silberstreifen 4, 76287 Rheinstetten, Germany
| | | | - Paul A Helm
- Environmental Monitoring & Reporting Branch, Ontario Ministry of the Environment, Toronto M9P 3V6, Canada
| | - Sonya Kleywegt
- Technical Assessment and Standards Development Branch, Ontario Ministry of the Environment, Conservation and Parks, Toronto, ON M4V 1M2, Canada
| | - Karl Jobst
- Memorial University of Newfoundland, St. John's, NL A1C 5S7, Canada
| | - Ronald Soong
- Environmental NMR Center, University of Toronto Scarborough, 1265 Military Trail, Toronto M1C1A4, Canada
| | - Myrna J Simpson
- Environmental NMR Center, University of Toronto Scarborough, 1265 Military Trail, Toronto M1C1A4, Canada
| | - Andre J Simpson
- Environmental NMR Center, University of Toronto Scarborough, 1265 Military Trail, Toronto M1C1A4, Canada.
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Kikuchi J, Yamada S. The exposome paradigm to predict environmental health in terms of systemic homeostasis and resource balance based on NMR data science. RSC Adv 2021; 11:30426-30447. [PMID: 35480260 PMCID: PMC9041152 DOI: 10.1039/d1ra03008f] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 08/31/2021] [Indexed: 12/22/2022] Open
Abstract
The environment, from microbial ecosystems to recycled resources, fluctuates dynamically due to many physical, chemical and biological factors, the profile of which reflects changes in overall state, such as environmental illness caused by a collapse of homeostasis. To evaluate and predict environmental health in terms of systemic homeostasis and resource balance, a comprehensive understanding of these factors requires an approach based on the "exposome paradigm", namely the totality of exposure to all substances. Furthermore, in considering sustainable development to meet global population growth, it is important to gain an understanding of both the circulation of biological resources and waste recycling in human society. From this perspective, natural environment, agriculture, aquaculture, wastewater treatment in industry, biomass degradation and biodegradable materials design are at the forefront of current research. In this respect, nuclear magnetic resonance (NMR) offers tremendous advantages in the analysis of samples of molecular complexity, such as crude bio-extracts, intact cells and tissues, fibres, foods, feeds, fertilizers and environmental samples. Here we outline examples to promote an understanding of recent applications of solution-state, solid-state, time-domain NMR and magnetic resonance imaging (MRI) to the complex evaluation of organisms, materials and the environment. We also describe useful databases and informatics tools, as well as machine learning techniques for NMR analysis, demonstrating that NMR data science can be used to evaluate the exposome in both the natural environment and human society towards a sustainable future.
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Affiliation(s)
- Jun Kikuchi
- Environmental Metabolic Analysis Research Team, RIKEN Center for Sustainable Resource Science 1-7-22 Suehiro-cho, Tsurumi-ku Yokohama 230-0045 Japan
- Graduate School of Bioagricultural Sciences, Nagoya University Furo-cho, Chikusa-ku Nagoya 464-8601 Japan
- Graduate School of Medical Life Science, Yokohama City University 1-7-29 Suehiro-cho, Tsurumi-ku Yokohama 230-0045 Japan
| | - Shunji Yamada
- Environmental Metabolic Analysis Research Team, RIKEN Center for Sustainable Resource Science 1-7-22 Suehiro-cho, Tsurumi-ku Yokohama 230-0045 Japan
- Prediction Science Laboratory, RIKEN Cluster for Pioneering Research 7-1-26 Minatojima-minami-machi, Chuo-ku Kobe 650-0047 Japan
- Data Assimilation Research Team, RIKEN Center for Computational Science 7-1-26 Minatojima-minami-machi, Chuo-ku Kobe 650-0047 Japan
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Karimi MR, Karimi AH, Abolmaali S, Sadeghi M, Schmitz U. Prospects and challenges of cancer systems medicine: from genes to disease networks. Brief Bioinform 2021; 23:6361045. [PMID: 34471925 PMCID: PMC8769701 DOI: 10.1093/bib/bbab343] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 08/02/2021] [Accepted: 08/03/2021] [Indexed: 12/20/2022] Open
Abstract
It is becoming evident that holistic perspectives toward cancer are crucial in deciphering the overwhelming complexity of tumors. Single-layer analysis of genome-wide data has greatly contributed to our understanding of cellular systems and their perturbations. However, fundamental gaps in our knowledge persist and hamper the design of effective interventions. It is becoming more apparent than ever, that cancer should not only be viewed as a disease of the genome but as a disease of the cellular system. Integrative multilayer approaches are emerging as vigorous assets in our endeavors to achieve systemic views on cancer biology. Herein, we provide a comprehensive review of the approaches, methods and technologies that can serve to achieve systemic perspectives of cancer. We start with genome-wide single-layer approaches of omics analyses of cellular systems and move on to multilayer integrative approaches in which in-depth descriptions of proteogenomics and network-based data analysis are provided. Proteogenomics is a remarkable example of how the integration of multiple levels of information can reduce our blind spots and increase the accuracy and reliability of our interpretations and network-based data analysis is a major approach for data interpretation and a robust scaffold for data integration and modeling. Overall, this review aims to increase cross-field awareness of the approaches and challenges regarding the omics-based study of cancer and to facilitate the necessary shift toward holistic approaches.
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Affiliation(s)
| | | | | | - Mehdi Sadeghi
- Department of Cell & Molecular Biology, Semnan University, Semnan, Iran
| | - Ulf Schmitz
- Department of Molecular & Cell Biology, James Cook University, Townsville, QLD 4811, Australia
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"Fuel for the Damage Induced": Untargeted Metabolomics in Elite Rugby Union Match Play. Metabolites 2021; 11:metabo11080544. [PMID: 34436485 PMCID: PMC8400368 DOI: 10.3390/metabo11080544] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 08/09/2021] [Accepted: 08/13/2021] [Indexed: 01/22/2023] Open
Abstract
The metabolic perturbations caused by competitive rugby are not well characterized. Our aim is to utilize untargeted metabolomics to develop appropriate interventions, based on the metabolic fluctuations that occur in response to this collision-based team sport. Seven members of an English Premiership rugby squad consented to provide blood, urine, and saliva samples daily, over a competitive week including gameday (GD), with physical demands and dietary intake also recorded. Sample collection, processing and statistical analysis were performed in accordance with best practice set out by the metabolomics standards initiative employing 700 MHz NMR spectroscopy. Univariate and multivariate statistical analysis were employed to reveal the acute energy needs of this high intensity sport are met via glycolysis, the TCA cycle and gluconeogenesis. The recovery period after cessation of match play and prior to training recommencing sees a re-entry to gluconeogenesis, coupled with markers of oxidative stress, structural protein degradation, and reduced fatty acid metabolism. This novel insight leads us to propose that effective recovery from muscle damaging collisions is dependent upon the availability of glucose. An adjustment in the periodisation of carbohydrate to increase GD+1 provision may prevent the oxidation of amino acids which may also be crucial to allay markers of structural tissue degradation. Should we expand the ‘Fuel for the work required’ paradigm in collision-based team sports to include ‘Fuel for the damage induced’?
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Collins SL, Koo I, Peters JM, Smith PB, Patterson AD. Current Challenges and Recent Developments in Mass Spectrometry-Based Metabolomics. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2021; 14:467-487. [PMID: 34314226 DOI: 10.1146/annurev-anchem-091620-015205] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
High-resolution mass spectrometry (MS) has advanced the study of metabolism in living systems by allowing many metabolites to be measured in a single experiment. Although improvements in mass detector sensitivity have facilitated the detection of greater numbers of analytes, compound identification strategies, feature reduction software, and data sharing have not kept up with the influx of MS data. Here, we discuss the ongoing challenges with MS-based metabolomics, including de novo metabolite identification from mass spectra, differentiation of metabolites from environmental contamination, chromatographic separation of isomers, and incomplete MS databases. Because of their popularity and sensitive detection of small molecules, this review focuses on the challenges of liquid chromatography-mass spectrometry-based methods. We then highlight important instrumentational, experimental, and computational tools that have been created to address these challenges and how they have enabled the advancement of metabolomics research.
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Affiliation(s)
- Stephanie L Collins
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Imhoi Koo
- Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA;
- The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Jeffrey M Peters
- Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA;
| | - Philip B Smith
- The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Andrew D Patterson
- Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA;
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Modeling of Antioxidant Activity, Polyphenols and Macronutrients Content of Bee Pollen Applying Solid-State 13C NMR Spectra. Antioxidants (Basel) 2021; 10:antiox10071123. [PMID: 34356356 PMCID: PMC8301116 DOI: 10.3390/antiox10071123] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 07/08/2021] [Accepted: 07/12/2021] [Indexed: 12/31/2022] Open
Abstract
An application of solid 13C nuclear magnetic resonance (NMR) spectroscopy for the determination of macronutrients, total polyphenols content, antioxidant activity, N C S elements, and pH in commercially available bee pollens is reported herein. Solid-state 13C NMR spectra were recorded for homogenized pollen granules without chemical treatment or dissolution of samples. By combining spectral data with the results of reference analyses, partial least squares models were constructed and validated separately for each of the studied parameters. To characterize and compare the models’ quality, the relative standard errors of prediction (RSEP) were calculated for calibration and validation sets. In the case of the analysis of protein, fat and reducing sugars, these errors were in the 1.8–2.5% range. Modeling the elemental composition of bee pollen on the basis of 13C NMR spectra resulted in RSEPcal/RSEPval values of 0.3/0.6% for the sum of NHCS elements, 0.3/0.4% for C, 1.8/1.9% for N, and 4.2/6.1% for S quantification. Analyses of total phenolics and ABTS antioxidant activity resulted in RSEP values in the 2.7–3.5% and 2.8–3.8% ranges, respectively, whereas they were 1.4–2.1% for pH. The obtained results demonstrate the usefulness of 13C solid-state NMR spectroscopy for direct determination of various important physiochemical parameters of bee pollen.
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Kim HJ, Lee YR, Lee S, Kwon S, Chun YT, Hyun SH, Sung HJ, Lee J, Kang HG. Discovery of donor age markers from bloodstain by LC-MS/MS using a metabolic approach. Int J Legal Med 2021; 136:297-308. [PMID: 34218338 DOI: 10.1007/s00414-021-02640-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Accepted: 06/14/2021] [Indexed: 01/27/2023]
Abstract
Bloodstains are frequently encountered at crime scenes and they provide important evidence about the incident, such as information about the victim or suspect and the time of death or other events. Efforts have been made to identify the age of the bloodstain's donor through genomic approaches, but there are some limitations, such as the availability of databases and the quality dependence of DNA. There is a need for the development of a tool that can obtain information at once from a small blood sample. The aim of this study is to identify bloodstain metabolite candidates that can be used to determine donor age. We prepared bloodstain samples and analyzed metabolites using high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Eighteen molecular features (MFs) were selected as candidates using volcano plots and multivariate analysis. Based on the MS/MS spectrum of the MFs, the following nine metabolites were identified from the METaboliteLINk database: Δ2-cis eicosenoic acid, ergothioneine, adenosine 5'-monophosphate, benzaldehyde, phenacylamine, myristic acid ethyl ester, p-coumaric acid, niacinamide, and N-arachidonoyl-L-alanine. These nine age markers at high or low abundances could be used to estimate the age of a bloodstain's donor. This study was the first to develop metabolite age markers that can be used to analyze crime scene bloodstains.
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Affiliation(s)
- Hyo-Jin Kim
- Department of Senior Healthcare, Graduate School, Eulji University, 712, Dongil-ro, Uijeongbu-si, Gyeonggi-do, 11759, Republic of Korea
| | - You-Rim Lee
- Department of Senior Healthcare, Graduate School, Eulji University, 712, Dongil-ro, Uijeongbu-si, Gyeonggi-do, 11759, Republic of Korea
| | - Seungyeon Lee
- Department of Senior Healthcare, Graduate School, Eulji University, 712, Dongil-ro, Uijeongbu-si, Gyeonggi-do, 11759, Republic of Korea
| | - Sohyen Kwon
- Department of Senior Healthcare, Graduate School, Eulji University, 712, Dongil-ro, Uijeongbu-si, Gyeonggi-do, 11759, Republic of Korea
| | - Yeon Tae Chun
- Department of Biomedical Laboratory Science, College of Health Sciences, Eulji University, Seongnam, 13135, Republic of Korea.,Integrative Research Support Center, The Catholic University of Korea, School of Medicine, 222 Banpo-daero, Seocho-gu, Seoul, 06501, Republic of Korea
| | - Sung Hee Hyun
- Department of Senior Healthcare, Graduate School, Eulji University, 712, Dongil-ro, Uijeongbu-si, Gyeonggi-do, 11759, Republic of Korea.,Department of Biomedical Laboratory Science, College of Health Science, Eulji University, Uijeongbu, 11759, Republic of Korea
| | - Ho Joong Sung
- Department of Senior Healthcare, Graduate School, Eulji University, 712, Dongil-ro, Uijeongbu-si, Gyeonggi-do, 11759, Republic of Korea.,Department of Biomedical Laboratory Science, College of Health Sciences, Eulji University, Seongnam, 13135, Republic of Korea
| | - Jiyeong Lee
- Department of Biomedical Laboratory Science, College of Health Science, Eulji University, Uijeongbu, 11759, Republic of Korea.
| | - Hee-Gyoo Kang
- Department of Senior Healthcare, Graduate School, Eulji University, 712, Dongil-ro, Uijeongbu-si, Gyeonggi-do, 11759, Republic of Korea. .,Department of Biomedical Laboratory Science, College of Health Sciences, Eulji University, Seongnam, 13135, Republic of Korea.
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Loras A, Segovia C, Ruiz-Cerdá JL. Epigenomic and Metabolomic Integration Reveals Dynamic Metabolic Regulation in Bladder Cancer. Cancers (Basel) 2021; 13:2719. [PMID: 34072826 PMCID: PMC8198168 DOI: 10.3390/cancers13112719] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 05/12/2021] [Accepted: 05/26/2021] [Indexed: 12/24/2022] Open
Abstract
Bladder cancer (BC) represents a clinical, social, and economic challenge due to tumor-intrinsic characteristics, limitations of diagnostic techniques and a lack of personalized treatments. In the last decade, the use of liquid biopsy has grown as a non-invasive approach to characterize tumors. Moreover, the emergence of omics has increased our knowledge of cancer biology and identified critical BC biomarkers. The rewiring between epigenetics and metabolism has been closely linked to tumor phenotype. Chromatin remodelers interact with each other to control gene silencing in BC, but also with stress-inducible factors or oncogenic signaling cascades to regulate metabolic reprogramming towards glycolysis, the pentose phosphate pathway, and lipogenesis. Concurrently, one-carbon metabolism supplies methyl groups to histone and DNA methyltransferases, leading to the hypermethylation and silencing of suppressor genes in BC. Conversely, α-KG and acetyl-CoA enhance the activity of histone demethylases and acetyl transferases, increasing gene expression, while succinate and fumarate have an inhibitory role. This review is the first to analyze the interplay between epigenome, metabolome and cell signaling pathways in BC, and shows how their regulation contributes to tumor development and progression. Moreover, it summarizes non-invasive biomarkers that could be applied in clinical practice to improve diagnosis, monitoring, prognosis and the therapeutic options in BC.
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Affiliation(s)
- Alba Loras
- Unidad Mixta de Investigación en TICs Aplicadas a la Reingeniería de Procesos Socio-Sanitarios (eRPSS), Universitat Politècnica de València-Instituto de Investigación Sanitaria La Fe, 46026 Valencia, Spain
| | - Cristina Segovia
- Epithelial Carcinogenesis Group, Centro Nacional de Investigaciones Oncológicas (CNIO), 28029 Madrid, Spain
| | - José Luis Ruiz-Cerdá
- Unidad Mixta de Investigación en Nanomedicina y Sensores, Universitat Politècnica de València-Instituto de Investigación Sanitaria La Fe, 46026 Valencia, Spain;
- Servicio de Urología, Hospital Universitario y Politécnico La Fe, 46026 Valencia, Spain
- Departamento de Cirugía, Facultad de Medicina y Odontología, Universitat de València, 46010 Valencia, Spain
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Murgia F, Gagliano A, Tanca MG, Or-Geva N, Hendren A, Carucci S, Pintor M, Cera F, Cossu F, Sotgiu S, Atzori L, Zuddas A. Metabolomic Characterization of Pediatric Acute-Onset Neuropsychiatric Syndrome (PANS). Front Neurosci 2021; 15:645267. [PMID: 34121984 PMCID: PMC8194687 DOI: 10.3389/fnins.2021.645267] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 04/27/2021] [Indexed: 01/21/2023] Open
Abstract
Introduction PANS is a controversial clinical entity, consisting of a complex constellation of psychiatric symptoms, adventitious changes, and expression of various serological alterations, likely sustained by an autoimmune/inflammatory disease. Detection of novel biomarkers of PANS is highly desirable for both diagnostic and therapeutic management of affected patients. Analysis of metabolites has proven useful in detecting biomarkers for other neuroimmune-psychiatric diseases. Here, we utilize the metabolomics approach to determine whether it is possible to define a specific metabolic pattern in patients affected by PANS compared to healthy subjects. Design This observational case-control study tested consecutive patients referred for PANS between June 2019 to May 2020. A PANS diagnosis was confirmed according to the PANS working criteria (National Institute of Mental Health [NIMH], 2010). Healthy age and sex-matched subjects were recruited as controls. Methods Thirty-four outpatients referred for PANS (mean age 9.5 years; SD 2.9, 71% male) and 25 neurotypical subjects matched for age and gender, were subjected to metabolite analysis. Serum samples were obtained from each participant and were analyzed using Nuclear Magnetic Resonance (NMR) spectroscopy. Subsequently, multivariate and univariate statistical analyses and Receiver Operator Curves (ROC) were performed. Results Separation of the samples, in line with the presence of PANS diagnosis, was observed by applying a supervised model (R2X = 0.44, R2Y = 0.54, Q2 = 0.44, p-value < 0.0001). The significantly altered variables were 2-Hydroxybutyrate, glycine, glutamine, histidine, tryptophan. Pathway analysis indicated that phenylalanine, tyrosine, and tryptophan metabolism, as well as glutamine and glutamate metabolism, exhibited the largest deviations from neurotypical controls. Conclusion We found a unique plasma metabolic profile in PANS patients, significantly differing from that of healthy children, that suggests the involvement of specific patterns of neurotransmission (tryptophan, glycine, histamine/histidine) as well as a more general state of neuroinflammation and oxidative stress (glutamine, 2-Hydroxybutyrate, and tryptophan-kynurenine pathway) in the disorder. This metabolomics study offers new insights into biological mechanisms underpinning the disorder and supports research of other potential biomarkers implicated in PANS.
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Affiliation(s)
- Federica Murgia
- Clinical Metabolomics Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Antonella Gagliano
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.,Child and Adolescent Neuropsychiatry Unit, "A. Cao" Peditric Hosptal, "G. Brotzu" Hospital Trust, Cagliari, Italy
| | - Marcello G Tanca
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Noga Or-Geva
- Interdepartmental Program in Immunology, Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Aran Hendren
- Clinical Metabolomics Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.,Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom
| | - Sara Carucci
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.,Child and Adolescent Neuropsychiatry Unit, "A. Cao" Peditric Hosptal, "G. Brotzu" Hospital Trust, Cagliari, Italy
| | - Manuela Pintor
- Child and Adolescent Neuropsychiatry Unit, "A. Cao" Peditric Hosptal, "G. Brotzu" Hospital Trust, Cagliari, Italy
| | - Francesca Cera
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Fausto Cossu
- Paediatric Clinic, "A. Cao" Hospital, Cagliari, Italy
| | - Stefano Sotgiu
- Child Neuropsychiatry Unit, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy
| | - Luigi Atzori
- Clinical Metabolomics Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy
| | - Alessandro Zuddas
- Child and Adolescent Neuropsychiatry Unit, Department of Biomedical Sciences, University of Cagliari, Cagliari, Italy.,Child and Adolescent Neuropsychiatry Unit, "A. Cao" Peditric Hosptal, "G. Brotzu" Hospital Trust, Cagliari, Italy
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Yan J, Kuzhiumparambil U, Bandodkar A, Bandodkar S, Dale RC, Fu S. Cerebrospinal fluid metabolites in tryptophan-kynurenine and nitric oxide pathways: biomarkers for acute neuroinflammation. Dev Med Child Neurol 2021; 63:552-559. [PMID: 33336374 DOI: 10.1111/dmcn.14774] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 11/13/2020] [Indexed: 12/11/2022]
Abstract
AIM To explore the cerebrospinal fluid (CSF) metabolite features in acute neuroinflammatory diseases and identify potential biomarkers to diagnose and monitor neuroinflammation. METHOD A cohort of 14 patients (five females, nine males; mean [median] age 7y 9mo [9y], range 6mo-13y) with acute encephalitis (acute disseminated encephalomyelitis n=6, unknown suspected viral encephalitis n=3, enteroviral encephalitis n=2, seronegative autoimmune encephalitis n=2, herpes simplex encephalitis n=1) and age-matched non-inflammatory neurological disease controls (n=14) were investigated using an untargeted metabolomics approach. CSF metabolites were analyzed with liquid chromatography coupled to high resolution mass spectrometry, followed by subsequent multivariate and univariate statistical methods. RESULTS A total of 35 metabolites could be discriminated statistically between the groups using supervised orthogonal partial least squares discriminant analysis and analysis of variance. The tryptophan-kynurenine pathway contributed nine key metabolites. There was a statistical increase of kynurenine, quinolinic acid, and anthranilic acid in patients with encephalitis, whereas tryptophan, 3-hydroxyanthrnailic acid, and kynurenic acid were decreased. The nitric oxide pathway contributed four metabolites, with elevated asymmetric dimethylarginine and argininosuccinic acid, and decreased arginine and citrulline in patients with encephalitis. An increase in the CSF kynurenine/tryptophan ratio (p<0.001), anthranilic acid/3-hydroxyanthranilic acid ratio (p<0.001), asymmetric dimethylarginine/arginine ratio (p<0.001), and neopterin (p<0.001) strongly predicted neuroinflammation. INTERPRETATION The combination of alterations in the tryptophan-kynurenine pathway, nitric oxide pathway, and neopterin represent a useful potential panel for neuroinflammation and holds potential for clinical translation practice. WHAT THIS PAPER ADDS The kynurenine/tryptophan and anthranilic acid/3-hydroxyanthranilic acid ratios hold great potential as biomarkers of neuroinflammation. Elevation of the asymmetric dimethylarginine/arginine ratio in acute brain inflammation shows dysregulation of the nitric oxide pathway.
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Affiliation(s)
- Jingya Yan
- Centre for Forensic Science, University of Technology Sydney, Sydney, New South Wales, Australia
| | | | - Ashvin Bandodkar
- Clinical School, The Children's Hospital at Westmead, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - Sushil Bandodkar
- Clinical School, The Children's Hospital at Westmead, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.,Department of Clinical Biochemistry, The Children's Hospital at Westmead, Sydney, New South Wales, Australia
| | - Russell C Dale
- Clinical School, The Children's Hospital at Westmead, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - Shanlin Fu
- Centre for Forensic Science, University of Technology Sydney, Sydney, New South Wales, Australia
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50
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Deutsch L, Osredkar D, Plavec J, Stres B. Spinal Muscular Atrophy after Nusinersen Therapy: Improved Physiology in Pediatric Patients with No Significant Change in Urine, Serum, and Liquor 1H-NMR Metabolomes in Comparison to an Age-Matched, Healthy Cohort. Metabolites 2021; 11:206. [PMID: 33808177 PMCID: PMC8065886 DOI: 10.3390/metabo11040206] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 03/25/2021] [Accepted: 03/29/2021] [Indexed: 02/07/2023] Open
Abstract
Spinal muscular atrophy (SMA) is a genetically heterogeneous group of rare neuromuscular diseases and was until recently the most common genetic cause of death in children. The effects of 2-month nusinersen therapy on urine, serum, and liquor 1H-NMR metabolomes in SMA males and females were not explored yet, especially not in comparison to the urine 1H-NMR metabolomes of matching male and female cohorts. In this prospective, single-centered study, urine, serum, and liquor samples were collected from 25 male and female pediatric patients with SMA before and after 2 months of nusinersen therapy and urine samples from a matching healthy cohort (n = 125). Nusinersen intrathecal application was the first therapy for the treatment of SMA by the Food and Drug Administration (FDA) and the European Medicines Agency (EMA). Metabolomes were analyzed using targeted metabolomics utilizing 600 MHz 1H-NMR, parametric and nonparametric multivariate statistical analyses, machine learning, and modeling. Medical assessment before and after nusinersen therapy showed significant improvements of movement, posture, and strength according to various medical tests. No significant differences were found in metabolomes before and after nusinersen therapy in urine, serum, and liquor samples using an ensemble of statistical and machine learning approaches. In comparison to a healthy cohort, 1H-NMR metabolomes of SMA patients contained a reduced number and concentration of urine metabolites and differed significantly between males and females as well. Significantly larger data scatter was observed for SMA patients in comparison to matched healthy controls. Machine learning confirmed urinary creatinine as the most significant, distinguishing SMA patients from the healthy cohort. The positive effects of nusinersen therapy clearly preceded or took place devoid of significant rearrangements in the 1H-NMR metabolomic makeup of serum, urine, and liquor. Urine creatinine was successful at distinguishing SMA patients from the matched healthy cohort, which is a simple systemic novelty linking creatinine and SMA to the physiology of inactivity and diabetes, and it facilitates the monitoring of SMA disease in pediatric patients through non-invasive urine collection.
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Affiliation(s)
- Leon Deutsch
- Department of Animal Science, Biotechnical Faculty, University of Ljubljana, SI-1000 Ljubljana, Slovenia;
| | - Damjan Osredkar
- Department of Pediatric Neurology, University Children’s Hospital, University Medical Centre Ljubljana, SI-1000 Ljubljana, Slovenia;
- Faculty of Medicine, University of Ljubljana, SI-1000 Ljubljana, Slovenia
| | - Janez Plavec
- National Institute of Chemistry, NMR Center, SI-1000 Ljubljana, Slovenia;
| | - Blaž Stres
- Department of Animal Science, Biotechnical Faculty, University of Ljubljana, SI-1000 Ljubljana, Slovenia;
- Department of Automation, Biocybernetics and Robotics, Jožef Stefan Institute, SI-1000 Ljubljana, Slovenia
- Faculty of Civil and Geodetic Engineering, Institute of Sanitary Engineering, University of Ljubljana, SI-1000 Ljubljana, Slovenia
- Department of Microbiology, University of Innsbruck, A-6020 Innsbruck, Austria
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