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Andriyas T, Leksungnoen N, Pongchaidacha P, Uthairangsee A, Uthairatsamee S, Doomnil P, Ku-Or Y, Ngernsaengsaruay C, Andriyas S, Yarnvudhi A, Tansawat R. Integrating spatial mapping and metabolomics: A novel platform for bioactive compound discovery and saline land reclamation. Comput Struct Biotechnol J 2025; 27:1741-1753. [PMID: 40421159 PMCID: PMC12104716 DOI: 10.1016/j.csbj.2025.04.035] [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: 03/30/2025] [Revised: 04/23/2025] [Accepted: 04/24/2025] [Indexed: 05/28/2025] Open
Abstract
Saline lands pose significant environmental and agricultural challenges due to high soil salinity, which disrupts water uptake and ionic balances, limiting conventional crop productivity. Yet, certain endemic plants thrive under these conditions and may offer untapped bioactive compounds. This study proposes a novel platform that integrates species distribution modeling (SDM) and advanced metabolomics to screen for bioactive secondary metabolites, using Buchanania siamensis, a rare native species, as a case study. An ensemble SDM model incorporating environmental and soil parameters identified salinity as a critical factor influencing the species' distribution. Leaf samples were collected from naturally growing trees at both saline (SS) and non-saline (NS) sites. LC-QTOF metabolomic analysis annotated a total of 1106 metabolites across the leaf samples, with 175 found to be significantly different between the groups. Among them, 108 metabolites exhibited higher abundance in the SS group. Additionally, antioxidant assays including DPPH, FRAP, and total phenolic content tests, were conducted. Data were further analyzed using O-PLSR models to identify key metabolites most relevant to antioxidant properties. The results indicated that afzelin was the key metabolite responsible for the antioxidant properties of B. siamensis, with significantly higher levels in SS compared to NS samples (p < 0.05), as determined by peak area. By leveraging this multidisciplinary approach, we propose a framework to support both bioactive compound discovery and saline land reclamation, offering potential environmental and pharmaceutical benefits. This integrated platform may support pharmaceutical research, particularly in drug discovery efforts.
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Affiliation(s)
- Tushar Andriyas
- Department of Food and Pharmaceutical Chemistry, Faculty of Pharmaceutical Science, Chulalongkorn University, Bangkok, Thailand
- Center of Excellence in Metabolomics for Life Sciences, Chulalongkorn University, Bangkok, Thailand
| | - Nisa Leksungnoen
- Department of Forest Biology, Faculty of Forestry, Kasetsart University, Bangkok, Thailand
| | - Pichaya Pongchaidacha
- Department of Food and Pharmaceutical Chemistry, Faculty of Pharmaceutical Science, Chulalongkorn University, Bangkok, Thailand
- Center of Excellence in Metabolomics for Life Sciences, Chulalongkorn University, Bangkok, Thailand
| | - Arashaporn Uthairangsee
- Department of Food and Pharmaceutical Chemistry, Faculty of Pharmaceutical Science, Chulalongkorn University, Bangkok, Thailand
- Center of Excellence in Metabolomics for Life Sciences, Chulalongkorn University, Bangkok, Thailand
| | - Suwimon Uthairatsamee
- Department of Forest Biology, Faculty of Forestry, Kasetsart University, Bangkok, Thailand
| | - Peerapat Doomnil
- Forest Resource Management Office No.4 (Tak), Pa Mamuang sub-district, Muang Tak, Tak 63000, Thailand
| | - Yongkriat Ku-Or
- Department of Forest Biology, Faculty of Forestry, Kasetsart University, Bangkok, Thailand
| | | | - Sanyogita Andriyas
- Department of Irrigation and Drainage Engineering, Vaugh Institute of Agriculture Engineering and Technology, Sam Higginbottom University of Agriculture, Technology, and Sciences, Prayagraj, Uttar Pradesh, India
| | - Arerut Yarnvudhi
- Department of Forest Biology, Faculty of Forestry, Kasetsart University, Bangkok, Thailand
| | - Rossarin Tansawat
- Department of Food and Pharmaceutical Chemistry, Faculty of Pharmaceutical Science, Chulalongkorn University, Bangkok, Thailand
- Center of Excellence in Metabolomics for Life Sciences, Chulalongkorn University, Bangkok, Thailand
- Thailand Metabolomics Association, Bangkok, Thailand
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2
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Koech S, Plechatá M, Pathom-aree W, Kamenik Z, Jaisi A. Strategies for Actinobacteria Isolation, Cultivation, and Metabolite Production that Are Biologically Important. ACS OMEGA 2025; 10:15923-15934. [PMID: 40321516 PMCID: PMC12044489 DOI: 10.1021/acsomega.5c01344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2025] [Revised: 03/30/2025] [Accepted: 04/08/2025] [Indexed: 05/08/2025]
Abstract
Novel antimicrobial agents are urgently needed to combat antimicrobial resistance from multidrug-resistant organisms. Actinobacteria are key sources of bioactive metabolites with diverse biological activities. Despite their contributions to drug discovery, the process from strain identification to drug manufacturing faces many challenges, especially the rediscovery of known compounds. Recent technological and scientific advancements have accelerated drug development. Efforts to isolate and screen rare actinobacterial species could yield novel bioactive compounds. This review summarizes techniques for selectively isolating rare actinobacteria, improving bioactive metabolite production, and discovering potential strains. Notably, new genomic strategies and new discoveries regarding spectroscopic signature-based bioactive natural products containing specific structural motifs are also discussed. Furthermore, this review updates the compounds derived from rare actinobacteria and their biological applications.
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Affiliation(s)
- Samson
Cheruiyot Koech
- School
of Pharmacy, Walailak University, Thasala, Thai Buri, Nakhon Si Thammarat 80160, Thailand
- Graduate
School, Walailak University, Thasala, Thai Buri, Nakhon Si Thammarat 80160, Thailand
| | - Michaela Plechatá
- Institute
of Microbiology, Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech
Republic
| | - Wasu Pathom-aree
- Department
of Biology, Faculty of Science, Chiang Mai
University, Chiang
Mai 50200, Thailand
| | - Zdenek Kamenik
- Institute
of Microbiology, Czech Academy of Sciences, Videnska 1083, 14200 Prague, Czech
Republic
| | - Amit Jaisi
- School
of Pharmacy, Walailak University, Thasala, Thai Buri, Nakhon Si Thammarat 80160, Thailand
- Biomass
and Oil Palm Center of Excellence, Walailak
University, Thasala, Thai Buri, Nakhon Si Thammarat 80160, Thailand
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3
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Taunk K, Jajula S, Bhavsar PP, Choudhari M, Bhanuse S, Tamhankar A, Naiya T, Kalita B, Rapole S. The prowess of metabolomics in cancer research: current trends, challenges and future perspectives. Mol Cell Biochem 2025; 480:693-720. [PMID: 38814423 DOI: 10.1007/s11010-024-05041-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 05/18/2024] [Indexed: 05/31/2024]
Abstract
Cancer due to its heterogeneous nature and large prevalence has tremendous socioeconomic impacts on populations across the world. Therefore, it is crucial to discover effective panels of biomarkers for diagnosing cancer at an early stage. Cancer leads to alterations in cell growth and differentiation at the molecular level, some of which are very unique. Therefore, comprehending these alterations can aid in a better understanding of the disease pathology and identification of the biomolecules that can serve as effective biomarkers for cancer diagnosis. Metabolites, among other biomolecules of interest, play a key role in the pathophysiology of cancer whose levels are significantly altered while 'reprogramming the energy metabolism', a cellular condition favored in cancer cells which is one of the hallmarks of cancer. Metabolomics, an emerging omics technology has tremendous potential to contribute towards the goal of investigating cancer metabolites or the metabolic alterations during the development of cancer. Diverse metabolites can be screened in a variety of biofluids, and tumor tissues sampled from cancer patients against healthy controls to capture the altered metabolism. In this review, we provide an overview of different metabolomics approaches employed in cancer research and the potential of metabolites as biomarkers for cancer diagnosis. In addition, we discuss the challenges associated with metabolomics-driven cancer research and gaze upon the prospects of this emerging field.
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Affiliation(s)
- Khushman Taunk
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
- Department of Biotechnology, Maulana Abul Kalam Azad University of Technology, West Bengal, NH12 Simhat, Haringhata, Nadia, West Bengal, 741249, India
| | - Saikiran Jajula
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
| | - Praneeta Pradip Bhavsar
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
| | - Mahima Choudhari
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
| | - Sadanand Bhanuse
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India
| | - Anup Tamhankar
- Department of Surgical Oncology, Deenanath Mangeshkar Hospital and Research Centre, Erandawne, Pune, Maharashtra, 411004, India
| | - Tufan Naiya
- Department of Biotechnology, Maulana Abul Kalam Azad University of Technology, West Bengal, NH12 Simhat, Haringhata, Nadia, West Bengal, 741249, India
| | - Bhargab Kalita
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India.
- Amrita School of Nanosciences and Molecular Medicine, Amrita Institute of Medical Sciences and Research Centre, Amrita Vishwa Vidyapeetham, Ponekkara, Kochi, Kerala, 682041, India.
| | - Srikanth Rapole
- Proteomics Lab, National Centre for Cell Science, Ganeshkhind, Pune, Maharashtra, 411007, India.
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4
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Ghafari N, Sleno L. Challenges and recent advances in quantitative mass spectrometry-based metabolomics. ANALYTICAL SCIENCE ADVANCES 2024; 5:e2400007. [PMID: 38948317 PMCID: PMC11210748 DOI: 10.1002/ansa.202400007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 06/03/2024] [Accepted: 06/08/2024] [Indexed: 07/02/2024]
Abstract
The field of metabolomics has gained tremendous interest in recent years. Whether the goal is to discover biomarkers related to certain pathologies or to better understand the impact of a drug or contaminant, numerous studies have demonstrated how crucial it is to understand variations in metabolism. Detailed knowledge of metabolic variabilities can lead to more effective treatments, as well as faster or less invasive diagnostics. Exploratory approaches are often employed in metabolomics, using relative quantitation to look at perturbations between groups of samples. Most metabolomics studies have been based on metabolite profiling using relative quantitation, with very few studies using an approach for absolute quantitation. Using accurate quantitation facilitates the comparison between different studies, as well as enabling longitudinal studies. In this review, we discuss the most widely used techniques for quantitative metabolomics using mass spectrometry (MS). Various aspects will be addressed, such as the use of external and/or internal standards, derivatization techniques, in vivo isotopic labelling, or quantitative MS imaging. The principles, as well as the associated limitations and challenges, will be described for each approach.
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Affiliation(s)
- Nathan Ghafari
- Chemistry Department/CERMO‐FCUniversity of Quebec in Montreal (UQAM)MontrealCanada
| | - Lekha Sleno
- Chemistry Department/CERMO‐FCUniversity of Quebec in Montreal (UQAM)MontrealCanada
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5
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Ponce LF, Bishop SL, Wacker S, Groves RA, Lewis IA. SCALiR: A Web Application for Automating Absolute Quantification of Mass Spectrometry-Based Metabolomics Data. Anal Chem 2024; 96:6566-6574. [PMID: 38642077 DOI: 10.1021/acs.analchem.3c04988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/22/2024]
Abstract
Quantitative liquid chromatography-mass spectrometry (LC-MS)-based metabolomics is becoming an important approach for studying complex biological systems but presents several technical challenges that limit its widespread use. Computing metabolite concentrations using standard curves generated from standard mixtures of known concentrations is a labor-intensive process that is often performed manually. Currently, there are few options for open-source software tools that can automatically calculate metabolite concentrations. Herein, we introduce SCALiR (standard curve application for determining linear ranges), a new web-based software tool specifically built for this task, which allows users to automatically transform LC-MS signals into absolute quantitative data (https://www.lewisresearchgroup.org/software). SCALiR uses an algorithm that automatically finds the equation of the line of best fit for each standard curve and uses this equation to calculate compound concentrations from the LC-MS signal. Using a standard mix containing 77 metabolites, we show a close correlation between the concentrations calculated by SCALiR and the expected concentrations of each compound (R2 = 0.99 for a y = x curve fitting). Moreover, we demonstrate that SCALiR reproducibly calculates concentrations of midrange standards across ten analytical batches (average coefficient of variation 0.091). SCALiR can be used to calculate metabolite concentrations either using external calibration curves or by using internal standards to correct for matrix effects. This open-source and vendor agnostic software offers users several advantages in that (1) it requires only 10 s of analysis time to compute concentrations of >75 compounds, (2) it facilitates automation of quantitative workflows, and (3) it performs deterministic evaluations of compound quantification limits. SCALiR therefore provides the metabolomics community with a simple and rapid tool that enables rigorous and reproducible quantitative metabolomics studies.
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Affiliation(s)
- Luis F Ponce
- Alberta Centre for Advanced Diagnostics, Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
| | - Stephanie L Bishop
- Alberta Centre for Advanced Diagnostics, Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
| | - Soren Wacker
- Alberta Centre for Advanced Diagnostics, Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
| | - Ryan A Groves
- Alberta Centre for Advanced Diagnostics, Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
| | - Ian A Lewis
- Alberta Centre for Advanced Diagnostics, Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB T2N 1N4, Canada
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6
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Shebl N, El-Jaafary S, Saeed AA, Elkafrawy P, El-Sayed A, Shamma S, Elnemr R, Mekky J, Mohamed LA, Kittaneh O, El-Fawal H, Rizig M, Salama M. Metabolomic profiling reveals altered phenylalanine metabolism in Parkinson's disease in an Egyptian cohort. Front Mol Biosci 2024; 11:1341950. [PMID: 38516193 PMCID: PMC10955577 DOI: 10.3389/fmolb.2024.1341950] [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: 11/21/2023] [Accepted: 01/18/2024] [Indexed: 03/23/2024] Open
Abstract
Introduction: Parkinson's disease (PD) is the most common motor neurodegenerative disease worldwide. Given the complexity of PD etiology and the different metabolic derangements correlated to the disease, metabolomics profiling of patients is a helpful tool to identify patho-mechanistic pathways for the disease development. Dopamine metabolism has been the target of several previous studies, of which some have reported lower phenylalanine and tyrosine levels in PD patients compared to controls. Methods: In this study, we have collected plasma from 27 PD patients, 18 reference controls, and 8 high-risk controls to perform a metabolomic study using liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS). Results: Our findings revealed higher intensities of trans-cinnamate, a phenylalanine metabolite, in patients compared to reference controls. Thus, we hypothesize that phenylalanine metabolism has been shifted to produce trans-cinnamate via L-phenylalanine ammonia lyase (PAL), instead of producing tyrosine, a dopamine precursor, via phenylalanine hydroxylase (PAH). Discussion: Given that these metabolites are precursors to several other metabolic pathways, the intensities of many metabolites such as dopamine, norepinephrine, and 3-hydroxyanthranilic acid, which connects phenylalanine metabolism to that of tryptophan, have been altered. Consequently, and in respect to Metabolic Control Analysis (MCA) theory, the levels of tryptophan metabolites have also been altered. Some of these metabolites are tryptamine, melatonin, and nicotinamide. Thus, we assume that these alterations could contribute to the dopaminergic, adrenergic, and serotonergic neurodegeneration that happen in the disease.
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Affiliation(s)
- Nourhan Shebl
- Institute of Global Health and Human Ecology (I-GHHE), The American University in Cairo, Cairo, Egypt
| | - Shaimaa El-Jaafary
- Neurology Department, Faculty of Medicine, Cairo University, Giza, Egypt
- Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
| | - Ayman A Saeed
- Applied Organic Chemistry Department, Chemical Industries Research Institute, National Research Centre (NRC), Giza, Egypt
| | - Passent Elkafrawy
- Technology and Energy Research Center, Effat University-College of Engineering-NSMTU, Jeddah, Saudi Arabia
| | - Amr El-Sayed
- Social Research Center, The American University in Cairo, Cairo, Egypt
| | - Samir Shamma
- Institute of Global Health and Human Ecology (I-GHHE), The American University in Cairo, Cairo, Egypt
| | - Rasha Elnemr
- Climate Change Information Center & Expert Systems (CCICES), Agriculture Research Center, Giza, Egypt
| | - Jaidaa Mekky
- Neurology Department, Faculty of Medicine, Alexandria University, Alexandria, Egypt
| | - Lobna A Mohamed
- Neurology Department, Faculty of Medicine, Alexandria University, Alexandria, Egypt
| | - Omar Kittaneh
- Technology and Energy Research Center, Effat University-College of Engineering-NSMTU, Jeddah, Saudi Arabia
| | - Hassan El-Fawal
- Institute of Global Health and Human Ecology (I-GHHE), The American University in Cairo, Cairo, Egypt
| | - Mie Rizig
- Queen Square, Institute of Neurology, University College London, London, United Kingdom
| | - Mohamed Salama
- Institute of Global Health and Human Ecology (I-GHHE), The American University in Cairo, Cairo, Egypt
- Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
- Faculty of Medicine, Mansoura University, Mansoura, Egypt
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7
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Li Q, Yin YH, Liu ZW, Liu LF, Xin GZ. FNICM: A New Methodology To Identify Core Metabolites Based on Significantly Perturbed Metabolic Subnetworks. Anal Chem 2024; 96:3335-3344. [PMID: 38363654 DOI: 10.1021/acs.analchem.3c04131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2024]
Abstract
Metabolomics has emerged as a powerful tool in biomedical research to understand the pathophysiological processes and metabolic biomarkers of diseases. Nevertheless, it is a significant challenge in metabolomics to identify the reliable core metabolites that are closely associated with the occurrence or progression of diseases. Here, we proposed a new research framework by integrating detection-based metabolomics with computational network biology for function-guided and network-based identification of core metabolites, namely, FNICM. The proposed FNICM methodology is successfully utilized to uncover ulcerative colitis (UC)-related core metabolites based on the significantly perturbed metabolic subnetwork. First, seed metabolites were screened out using prior biological knowledge and targeted metabolomics. Second, by leveraging network topology, the perturbations of the detected seed metabolites were propagated to other undetected ones. Ultimately, 35 core metabolites were identified by controllability analysis and were further hierarchized into six levels based on confidence level and their potential significance. The specificity and generalizability of the discovered core metabolites, used as UC's diagnostic markers, were further validated using published data sets of UC patients. More importantly, we demonstrated the broad applicability and practicality of the FNICM framework in different contexts by applying it to multiple clinical data sets, including inflammatory bowel disease, colorectal cancer, and acute coronary syndrome. In addition, FNICM was also demonstrated as a practicality methodology to identify core metabolites correlated with the therapeutic effects of Clematis saponins. Overall, the FNICM methodology is a new framework for identifying reliable core metabolites for disease diagnosis and drug treatment from a systemic and a holistic perspective.
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Affiliation(s)
- Qi Li
- State Key Laboratory of Natural Medicines, Department of Chinese Medicines Analysis, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Ying-Hao Yin
- State Key Laboratory of Natural Medicines, Department of Chinese Medicines Analysis, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 210009, China
- Shenzhen Key Laboratory of Hospital Chinese Medicine Preparation, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen 518033, China
| | - Zi-Wei Liu
- State Key Laboratory of Natural Medicines, Department of Chinese Medicines Analysis, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Li-Fang Liu
- State Key Laboratory of Natural Medicines, Department of Chinese Medicines Analysis, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 210009, China
| | - Gui-Zhong Xin
- State Key Laboratory of Natural Medicines, Department of Chinese Medicines Analysis, School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 210009, China
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8
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Goracci L, Tiberi P, Di Bona S, Bonciarelli S, Passeri GI, Piroddi M, Moretti S, Volpi C, Zamora I, Cruciani G. MARS: A Multipurpose Software for Untargeted LC-MS-Based Metabolomics and Exposomics. Anal Chem 2024; 96:1468-1477. [PMID: 38236168 PMCID: PMC10831794 DOI: 10.1021/acs.analchem.3c03620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 12/24/2023] [Accepted: 12/29/2023] [Indexed: 01/19/2024]
Abstract
Untargeted metabolomics is a growing field, in which recent advances in high-resolution mass spectrometry coupled with liquid chromatography (LC-MS) have facilitated untargeted approaches as a result of improvements in sensitivity, mass accuracy, and resolving power. However, a very large amount of data are generated. Consequently, using computational tools is now mandatory for the in-depth analysis of untargeted metabolomics data. This article describes MetAbolomics ReSearch (MARS), an all-in-one vendor-agnostic graphical user interface-based software applying LC-MS analysis to untargeted metabolomics. All of the analytical steps are described (from instrument data conversion and processing to statistical analysis, annotation/identification, quantification, and preliminary biological interpretation), and tools developed to improve annotation accuracy (e.g., multiple adducts and in-source fragmentation detection, trends across samples, and the MS/MS validator) are highlighted. In addition, MARS allows in-house building of reference databases, to bypass the limits of freely available MS/MS spectra collections. Focusing on the flexibility of the software and its user-friendliness, which are two important features in multipurpose software, MARS could provide new perspectives in untargeted metabolomics data analysis.
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Affiliation(s)
- Laura Goracci
- Department
of Chemistry, Biology and Biotechnology, Universita degli Studi di Perugia, via Elce di Sotto 8, Perugia 06123, Italy
| | - Paolo Tiberi
- Molecular
Discovery Ltd., Centennial
Park, Borehamwood, Hertfordshire WD6 4PJ, U.K.
| | - Stefano Di Bona
- Molecular
Horizon, Via Montelino,
30, Bettona (PG) 06084, Italy
| | - Stefano Bonciarelli
- Molecular
Discovery Ltd., Centennial
Park, Borehamwood, Hertfordshire WD6 4PJ, U.K.
| | | | - Marta Piroddi
- Molecular
Horizon, Via Montelino,
30, Bettona (PG) 06084, Italy
| | - Simone Moretti
- Molecular
Horizon, Via Montelino,
30, Bettona (PG) 06084, Italy
| | - Claudia Volpi
- Department
of Medicine and Surgery, P.le Gambuli 1, Perugia 06129, Italy
| | - Ismael Zamora
- Mass
Analytica, Rambla de
celler 113, Sant Cugat del Vallés 08173, Spain
| | - Gabriele Cruciani
- Department
of Chemistry, Biology and Biotechnology, Universita degli Studi di Perugia, via Elce di Sotto 8, Perugia 06123, Italy
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9
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Zubiri-Gaitán A, Martínez-Álvaro M, Blasco A, Hernández P. Cecal metabolomics of 2 divergently selected rabbit lines revealed microbial mechanisms correlated to intramuscular fat deposition. J Anim Sci 2024; 102:skae339. [PMID: 39497598 PMCID: PMC11638726 DOI: 10.1093/jas/skae339] [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: 04/18/2024] [Accepted: 11/04/2024] [Indexed: 12/12/2024] Open
Abstract
The gastrointestinal microbiota plays a key role in the host physiology and health through a complex host-microbiota co-metabolism. Metabolites produced by microbial metabolism can travel through the bloodstream to reach distal organs and affect their function, ultimately influencing the development of relevant production traits such as meat quality. Meat quality is a complex trait made up of a number of characteristics and intramuscular fat content (IMF) is considered to be one of the most important parameters. In this study, 52 rabbits from 2 lines divergently selected for IMF (high-IMF (H) and low-IMF (L) lines) were used to perform an untargeted metabolomic analysis of their cecal content, with the aim to obtain information on genetically determined microbial metabolism related to IMF. A large, correlated response to selection was found in their cecal metabolome composition. Partial least squares discriminant analysis was used to identify the pathways differentiating the lines, which showed a classification accuracy of 99%. On the other hand, 2 linear partial least squares analyses were performed, one for each line, to extract evidence on the specific pathways associated with IMF deposition within each line, which showed predictive abilities (estimated using the Q2) of approximately 60%. The most relevant pathways differentiating the lines were those related to amino acids (aromatic, branched-chain, and gamma-glutamyl), secondary bile acids, and purines. The higher content of secondary bile acids in the L-line was related to greater lipid absorption, while the differences found in purines suggested different fermentation activities, which could be related to greater nitrogen utilization and energy efficiency in the L-line. The linear analyses showed that lipid metabolism had a greater relative importance for IMF deposition in the L-line, whereas a more complex microbial metabolism was associated with the H-line. The lysophospholipids and gamma-glutamyl amino acids were associated with IMF in both lines; the nucleotide and secondary bile acid metabolisms were mostly associated in the H-line; and the long-chain and branched-chain fatty acids were mostly associated in the L-line. A metabolic signature consisting of 2 secondary bile acids and 2 protein metabolites was found with 88% classification accuracy, pointing to the interaction between lipid absorption and protein metabolism as a relevant driver of the microbiome activity influencing IMF.
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Affiliation(s)
- Agostina Zubiri-Gaitán
- Institute for Animal Science and Technology, Universitat Politècnica de València, Camino de Vera s/n, Valencia, Spain
| | - Marina Martínez-Álvaro
- Institute for Animal Science and Technology, Universitat Politècnica de València, Camino de Vera s/n, Valencia, Spain
| | - Agustín Blasco
- Institute for Animal Science and Technology, Universitat Politècnica de València, Camino de Vera s/n, Valencia, Spain
| | - Pilar Hernández
- Institute for Animal Science and Technology, Universitat Politècnica de València, Camino de Vera s/n, Valencia, Spain
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10
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Zubiri-Gaitán A, Blasco A, Hernández P. Plasma metabolomic profiling in two rabbit lines divergently selected for intramuscular fat content. Commun Biol 2023; 6:893. [PMID: 37653068 PMCID: PMC10471702 DOI: 10.1038/s42003-023-05266-3] [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: 03/02/2023] [Accepted: 08/21/2023] [Indexed: 09/02/2023] Open
Abstract
This study provides a thorough comparison of the plasma metabolome of two rabbit lines divergently selected for intramuscular fat content (IMF). The divergent selection led to a correlated response in the overall adiposity, turning these lines into a valuable animal material to study also the genetics of obesity. Over 900 metabolites were detected, and the adjustment of multivariate models, both discriminant and linear, allowed to identify 322 with differential abundances between lines, which also adjusted linearly to the IMF content. The most affected pathways were those of lipids and amino acids, with differences between lines ranging from 0.23 to 6.04 standard deviations, revealing a limited capacity of the low-IMF line to obtain energy from lipids, and a greater branched-chain amino acids catabolism in the high-IMF line related to its increased IMF content. Additionally, changes in metabolites derived from microbial activity supported its relevant role in the lipid deposition. Future research will focus on the analysis of the metabolomic profile of the cecum content, and on the integration of the several -omics datasets available for these lines, to help disentangle the host and microbiome biological mechanisms involved in the IMF deposition.
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Affiliation(s)
- Agostina Zubiri-Gaitán
- Institute for Animal Science and Technology, Universitat Politècnica de València, Valencia, Spain.
| | - Agustín Blasco
- Institute for Animal Science and Technology, Universitat Politècnica de València, Valencia, Spain
| | - Pilar Hernández
- Institute for Animal Science and Technology, Universitat Politècnica de València, Valencia, Spain.
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11
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Bishop SL, Ponce-Alvarez LF, Wacker S, Groves RA, Lewis IA. SCALiR: a web application for automating absolute quantification of mass spectrometry-based metabolomics data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.16.551807. [PMID: 37645808 PMCID: PMC10461962 DOI: 10.1101/2023.08.16.551807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Metabolomics is an important approach for studying complex biological systems. Quantitative liquid chromatography-mass spectrometry (LC-MS)-based metabolomics is becoming a mainstream strategy but presents several technical challenges that limit its widespread use. Computing metabolite concentrations using standard curves generated from standard mixtures of known concentrations is a labor-intensive process which is often performed manually. Currently, there are few options for open-source software tools that can automatically calculate metabolite concentrations. Herein, we introduce SCALiR (Standard Curve Application for determining Linear Ranges), a new web-based software tool specifically built for this task, which allows users to automatically transform LC-MS signal data into absolute quantitative data (https://www.lewisresearchgroup.org/software). The algorithm used in SCALiR automatically finds the equation of the line of best fit for each standard curve and uses this equation to calculate compound concentrations from their LC-MS signal. Using a standard mix containing 77 metabolites, we found excellent correlation between the concentrations calculated by SCALiR and the expected concentrations of each compound (R2 = 0.99) and that SCALiR reproducibly calculated concentrations of mid-range standards across ten analytical batches (average coefficient of variation 0.091). SCALiR offers users several advantages, including that it (1) is open-source and vendor agnostic; (2) requires only 10 seconds of analysis time to compute concentrations of >75 compounds; (3) facilitates automation of quantitative workflows; and (4) performs deterministic evaluation of compound quantification limits. SCALiR provides the metabolomics community with a simple and rapid tool that enables rigorous and reproducible quantitative metabolomics studies.
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Affiliation(s)
- Stephanie L. Bishop
- Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB, Canada, T2N 1N4
| | - Luis F. Ponce-Alvarez
- Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB, Canada, T2N 1N4
| | - Soren Wacker
- Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB, Canada, T2N 1N4
| | - Ryan A. Groves
- Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB, Canada, T2N 1N4
| | - Ian A. Lewis
- Department of Biological Sciences, University of Calgary, 2500 University Dr NW, Calgary, AB, Canada, T2N 1N4
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12
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Quintás G, Castell JV, Moreno-Torres M. The assessment of the potential hepatotoxicity of new drugs by in vitro metabolomics. Front Pharmacol 2023; 14:1155271. [PMID: 37214440 PMCID: PMC10196061 DOI: 10.3389/fphar.2023.1155271] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 04/19/2023] [Indexed: 05/24/2023] Open
Abstract
Drug hepatotoxicity assessment is a relevant issue both in the course of drug development as well as in the post marketing phase. The use of human relevant in vitro models in combination with powerful analytical methods (metabolomic analysis) is a promising approach to anticipate, as well as to understand and investigate the effects and mechanisms of drug hepatotoxicity in man. The metabolic profile analysis of biological liver models treated with hepatotoxins, as compared to that of those treated with non-hepatotoxic compounds, provides useful information for identifying disturbed cellular metabolic reactions, pathways, and networks. This can later be used to anticipate, as well to assess, the potential hepatotoxicity of new compounds. However, the applicability of the metabolomic analysis to assess the hepatotoxicity of drugs is complex and requires careful and systematic work, precise controls, wise data preprocessing and appropriate biological interpretation to make meaningful interpretations and/or predictions of drug hepatotoxicity. This review provides an updated look at recent in vitro studies which used principally mass spectrometry-based metabolomics to evaluate the hepatotoxicity of drugs. It also analyzes the principal drawbacks that still limit its general applicability in safety assessment screenings. We discuss the analytical workflow, essential factors that need to be considered and suggestions to overcome these drawbacks, as well as recent advancements made in this rapidly growing field of research.
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Affiliation(s)
- Guillermo Quintás
- Metabolomics and Bioanalysis, Health and Biomedicine, Leitat Technological Center, Barcelona, Spain
- Analytical Unit, Health Research Institute La Fe, Valencia, Spain
| | - José V. Castell
- Unidad Mixta de Hepatología Experimental, Instituto de Investigación Sanitaria del Hospital La Fe (IIS La Fe), Valencia, Spain
- Departamento de Bioquímica y Biología Molecular, Facultad de Medicina, Universidad de Valencia, Valencia, Spain
- CIBEREHD, Instituto de Salud Carlos III, Madrid, Spain
| | - Marta Moreno-Torres
- Unidad Mixta de Hepatología Experimental, Instituto de Investigación Sanitaria del Hospital La Fe (IIS La Fe), Valencia, Spain
- Departamento de Bioquímica y Biología Molecular, Facultad de Medicina, Universidad de Valencia, Valencia, Spain
- CIBEREHD, Instituto de Salud Carlos III, Madrid, Spain
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13
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Lee JY, Han Y, Styczynski MP. Towards inferring absolute concentrations from relative abundance in time-course GC-MS metabolomics data. Mol Omics 2023; 19:126-136. [PMID: 36374123 PMCID: PMC9974747 DOI: 10.1039/d2mo00168c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Metabolomics, the large-scale study of metabolites, has significant appeal as a source of information for metabolic modeling and other scientific applications. One common approach for measuring metabolomics data is gas chromatography-mass spectrometry (GC-MS). However, GC-MS metabolomics data are typically reported as relative abundances, precluding their use with approaches and tools where absolute concentrations are necessary. While chemical standards can be used to help provide quantification, their use is time-consuming, expensive, or even impossible due to their limited availability. The ability to infer absolute concentrations from GC-MS metabolomics data without chemical standards would have significant value. We hypothesized that when analyzing time-course metabolomics datasets, the mass balances of metabolism and other biological information could provide sufficient information towards inference of absolute concentrations. To demonstrate this, we developed and characterized MetaboPAC, a computational framework that uses two approaches-one based on kinetic equations and another using biological heuristics-to predict the most likely response factors that allow translation between relative abundances and absolute concentrations. When used to analyze noiseless synthetic data generated from multiple types of kinetic rate laws, MetaboPAC performs significantly better than negative control approaches when 20% of kinetic terms are known a priori. Under conditions of lower sampling frequency and high noise, MetaboPAC is still able to provide significant inference of concentrations in 3 of 4 models studied. This provides a starting point for leveraging biological knowledge to extract concentration information from time-course intracellular GC-MS metabolomics datasets, particularly for systems that are well-studied and have partially known kinetic structures.
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Affiliation(s)
- Justin Y Lee
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
| | - Yue Han
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
| | - Mark P Styczynski
- School of Chemical & Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
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14
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Optimized Fast Filtration-Based Sampling and Extraction Enables Precise and Absolute Quantification of the Escherichia coli Central Carbon Metabolome. Metabolites 2023; 13:metabo13020150. [PMID: 36837769 PMCID: PMC9965072 DOI: 10.3390/metabo13020150] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/07/2023] [Accepted: 01/15/2023] [Indexed: 01/20/2023] Open
Abstract
Precise and accurate quantification is a prerequisite for interpretation of targeted metabolomics data, but this task is challenged by the inherent instability of the analytes. The sampling, quenching, extraction, and sample purification conditions required to recover and stabilize metabolites in representative extracts have also been proven highly dependent on species-specific properties. For Escherichia coli, unspecific leakage has been demonstrated for conventional microbial metabolomics sampling protocols. We herein present a fast filtration-based sampling protocol for this widely applied model organism, focusing on pitfalls such as inefficient filtration, selective loss of biomass, matrix contamination, and membrane permeabilization and leakage. We evaluate the effect of and need for removal of extracellular components and demonstrate how residual salts can challenge analytical accuracy of hyphenated mass spectrometric analyses, even when sophisticated correction strategies are applied. Laborious extraction procedures are bypassed by direct extraction in cold acetonitrile:water:methanol (3:5:2, v/v%), ensuring compatibility with sample concentration and thus, any downstream analysis. By applying this protocol, we achieve and demonstrate high precision and low metabolite turnover, and, followingly, minimal perturbation of the inherent metabolic state. This allows us to herein report absolute intracellular concentrations in E. coli and explore its central carbon metabolome at several commonly applied cultivation conditions.
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15
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DE Almeida LR, Amaral Alves M, Mastella AMO, Garrett R, Pereira MJR. Neotropical mustelids: fecal metabolome diversity and its potential for taxonomic discrimination. Integr Zool 2022; 18:518-529. [PMID: 35275446 DOI: 10.1111/1749-4877.12645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Chemical profiles of non-invasive biological material, such as feces, have great potential to study elusive animals or those with low population densities. Here, we use a metabolomic approach to evaluate Neotropical mustelids as a biological model to describe the diversity of the metabolites present in fecal samples, as well as to evaluate the potential of chemical profiles for taxonomic discrimination. We collected fecal samples from captive individuals of five species of mustelids occurring in Brazil and analyzed them by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). Over 200 compounds have been annotated; "bile acids, alcohols and derivatives" was the most expressive class in the metabolome of all the species. We successfully discriminated three taxonomic groups: 1 - Tayra (Eira barbara); 2 - otters (Lontra longicaudis and Pteronura brasiliensis; 1); and 3 - grisons (Galictis vittata and Galictis cuja). Several compounds seemed to be associated with food intake and the digestive process, while others were found for the first time in Neotropical mustelids. We concluded that mustelids show high metabolome diversity and that species-specific identification through metabolomic profiles is possible, thus contributing to the development and implementation of additional non-invasive approaches in the study of mustelids. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Lana Resende DE Almeida
- Bird and Mammal Evolution, Systematics and Ecology Lab, Programa de Pós-Graduação em Biologia Animal, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.,Programa de Pós-Graduação em Biologia Animal, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Marina Amaral Alves
- Federal University of Rio de Janeiro, Chemistry Institute, Metabolomics Laboratory (LabMeta - LADETEC/IQ - UFRJ), Avenida Horácio Macedo, 1281 - Pólo de Química - Cidade Universitária, Ilha do Fundão, ZIP CODE, Rio de Janeiro, RJ, 21941-598, Brazil.,Universidade Federal do Rio de Janeiro, Walter Mors Institute of Research on Natural Products, Rio de Janeiro, RJ, 21941-599, Brazil
| | - Ana Maria Obino Mastella
- Bird and Mammal Evolution, Systematics and Ecology Lab, Programa de Pós-Graduação em Biologia Animal, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
| | - Rafael Garrett
- Federal University of Rio de Janeiro, Chemistry Institute, Metabolomics Laboratory (LabMeta - LADETEC/IQ - UFRJ), Avenida Horácio Macedo, 1281 - Pólo de Química - Cidade Universitária, Ilha do Fundão, ZIP CODE, Rio de Janeiro, RJ, 21941-598, Brazil
| | - Maria João Ramos Pereira
- Bird and Mammal Evolution, Systematics and Ecology Lab, Programa de Pós-Graduação em Biologia Animal, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.,Programa de Pós-Graduação em Biologia Animal, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
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16
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Bauermeister A, Mannochio-Russo H, Costa-Lotufo LV, Jarmusch AK, Dorrestein PC. Mass spectrometry-based metabolomics in microbiome investigations. Nat Rev Microbiol 2022; 20:143-160. [PMID: 34552265 PMCID: PMC9578303 DOI: 10.1038/s41579-021-00621-9] [Citation(s) in RCA: 238] [Impact Index Per Article: 79.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/03/2021] [Indexed: 02/08/2023]
Abstract
Microbiotas are a malleable part of ecosystems, including the human ecosystem. Microorganisms affect not only the chemistry of their specific niche, such as the human gut, but also the chemistry of distant environments, such as other parts of the body. Mass spectrometry-based metabolomics is one of the key technologies to detect and identify the small molecules produced by the human microbiota, and to understand the functional role of these microbial metabolites. This Review provides a foundational introduction to common forms of untargeted mass spectrometry and the types of data that can be obtained in the context of microbiome analysis. Data analysis remains an obstacle; therefore, the emphasis is placed on data analysis approaches and integrative analysis, including the integration of microbiome sequencing data.
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Affiliation(s)
- Anelize Bauermeister
- Institute of Biomedical Science, Universidade de São Paulo, São Paulo, SP, Brazil,Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, CA, USA
| | - Helena Mannochio-Russo
- Department of Biochemistry and Organic Chemistry, Institute of Chemistry, São Paulo State University, Araraquara, SP, Brazil,Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, CA, USA
| | | | - Alan K. Jarmusch
- Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, CA, USA
| | - Pieter C. Dorrestein
- Collaborative Mass Spectrometry Innovation Center, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, CA, USA.,Department of Pediatrics, University of California, San Diego, CA, USA.,Center for Microbiome Innovation, University of California, San Diego, CA, USA
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17
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Jennings E, Kremser A, Han L, Reemtsma T, Lechtenfeld OJ. Discovery of Polar Ozonation Byproducts via Direct Injection of Effluent Organic Matter with Online LC-FT-ICR-MS. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:1894-1904. [PMID: 35007417 DOI: 10.1021/acs.est.1c04310] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Effluent organic matter (EfOM), a major ozone consumer during wastewater ozonation, is a complex mixture of natural and anthropogenic organic molecules. Ozonation of EfOM adds to molecular complexity by introducing polar and potentially mobile ozonation byproducts (OBPs). Currently, nontargeted direct infusion (DI) ultrahigh resolution mass spectrometry (e.g. FT-ICR-MS) is used to study OBPs but requires sample extraction, limiting the accessible polarity range of OBPs. To better understand the impact of ozonation on EfOM and the formation of polar OBPs, nonextracted effluent was analyzed by direct injection onto a reversed-phase liquid chromatography system (RP-LC) online hyphenated with an FT-ICR-MS. Over four times more OBPs were detected in nonextracted EfOM compared to effluent extracted with solid phase extraction and measured with DI-FT-ICR-MS (13817 vs 3075). Over 1500 highly oxygenated OBPs were detected exclusively in early eluting fractions of nonextracted EfOM, indicating polar OBPs. Oxygenation of these newly discovered OBPs is higher than previously found, with an average molecular DBE-O value of -3.3 and O/C ratio of 0.84 in the earliest eluting OBP fractions. These polar OBPs are consistently lost during extraction but may play an important role in understanding the environmental impact of ozonated EfOM. Moreover, 316 molecular formulas classified as nonreactive to ozone in DI-FT-ICR-MS can be identified with LC-FT-ICR-MS as isomers with varying degrees of reactivity, providing for the first time experimental evidence of differential reactivity of complex organic matter isomers with ozone.
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Affiliation(s)
- Elaine Jennings
- Department of Analytical Chemistry, Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15, 04318 Leipzig, Germany
| | - Arina Kremser
- Department of Analytical Chemistry, Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15, 04318 Leipzig, Germany
| | - Limei Han
- Department of Analytical Chemistry, Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15, 04318 Leipzig, Germany
| | - Thorsten Reemtsma
- Department of Analytical Chemistry, Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15, 04318 Leipzig, Germany
- Institute of Analytical Chemistry, University of Leipzig, 04103, Leipzig, Germany
| | - Oliver J Lechtenfeld
- Department of Analytical Chemistry, Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15, 04318 Leipzig, Germany
- ProVIS-Centre for Chemical Microscopy, Helmholtz Centre for Environmental Research-UFZ, Permoserstrasse 15, 04318 Leipzig, Germany
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18
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Malinowska JM, Palosaari T, Sund J, Carpi D, Bouhifd M, Weber RJM, Whelan M, Viant MR. Integrating in vitro metabolomics with a 96-well high-throughput screening platform. Metabolomics 2022; 18:11. [PMID: 35000038 PMCID: PMC8743266 DOI: 10.1007/s11306-021-01867-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 12/16/2021] [Indexed: 02/07/2023]
Abstract
INTRODUCTION High-throughput screening (HTS) is emerging as an approach to support decision-making in chemical safety assessments. In parallel, in vitro metabolomics is a promising approach that can help accelerate the transition from animal models to high-throughput cell-based models in toxicity testing. OBJECTIVE In this study we establish and evaluate a high-throughput metabolomics workflow that is compatible with a 96-well HTS platform employing 50,000 hepatocytes of HepaRG per well. METHODS Low biomass cell samples were extracted for metabolomics analyses using a newly established semi-automated protocol, and the intracellular metabolites were analysed using a high-resolution spectral-stitching nanoelectrospray direct infusion mass spectrometry (nESI-DIMS) method that was modified for low sample biomass. RESULTS The method was assessed with respect to sensitivity and repeatability of the entire workflow from cell culturing and sampling to measurement of the metabolic phenotype, demonstrating sufficient sensitivity (> 3000 features in hepatocyte extracts) and intra- and inter-plate repeatability for polar nESI-DIMS assays (median relative standard deviation < 30%). The assays were employed for a proof-of-principle toxicological study with a model toxicant, cadmium chloride, revealing changes in the metabolome across five sampling times in the 48-h exposure period. To allow the option for lipidomics analyses, the solvent system was extended by establishing separate extraction methods for polar metabolites and lipids. CONCLUSIONS Experimental, analytical and informatics workflows reported here met pre-defined criteria in terms of sensitivity, repeatability and ability to detect metabolome changes induced by a toxicant and are ready for application in metabolomics-driven toxicity testing to complement HTS assays.
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Affiliation(s)
- Julia M Malinowska
- School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Taina Palosaari
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Jukka Sund
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Donatella Carpi
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Mounir Bouhifd
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
- European Chemicals Agency, Helsinki, Finland
| | - Ralf J M Weber
- School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK
- Phenome Centre Birmingham, University of Birmingham, Birmingham, B15 2TT, UK
| | - Maurice Whelan
- European Commission, Joint Research Centre (JRC), 21027, Ispra, Italy
| | - Mark R Viant
- School of Biosciences, University of Birmingham, Birmingham, B15 2TT, UK.
- Phenome Centre Birmingham, University of Birmingham, Birmingham, B15 2TT, UK.
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19
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Breger JC, Ellis GA, Walper SA, Susumu K, Medintz IL. Implementing Multi-Enzyme Biocatalytic Systems Using Nanoparticle Scaffolds. Methods Mol Biol 2022; 2487:227-262. [PMID: 35687240 DOI: 10.1007/978-1-0716-2269-8_15] [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: 06/15/2023]
Abstract
Interest in multi-enzyme synthesis outside of cells (in vitro) is becoming far more prevalent as the field of cell-free synthetic biology grows exponentially. Such synthesis would allow for complex chemical transformations based on the exquisite specificity of enzymes in a "greener" manner as compared to organic chemical transformations. Here, we describe how nanoparticles, and in this specific case-semiconductor quantum dots, can be used to both stabilize enzymes and further allow them to self-assemble into nanocomplexes that facilitate high-efficiency channeling phenomena. Pertinent protocol information is provided on enzyme expression, choice of nanoparticulate material, confirmation of enzyme attachment to nanoparticles, assay format and tracking, data analysis, and optimization of assay formats to draw the best analytical information from the underlying processes.
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Affiliation(s)
- Joyce C Breger
- Center for Bio/Molecular Science and Engineering, Code 6900, Washington, DC, USA
| | - Gregory A Ellis
- Center for Bio/Molecular Science and Engineering, Code 6900, Washington, DC, USA
| | - Scott A Walper
- Center for Bio/Molecular Science and Engineering, Code 6900, Washington, DC, USA
| | - Kimihiro Susumu
- Optical Sciences Division, Code 5611, U.S. Naval Research Laboratory, Washington, DC, USA
- Jacobs Corporation, Hanover, MD, USA
| | - Igor L Medintz
- Center for Bio/Molecular Science and Engineering, Code 6900, Washington, DC, USA.
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20
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Unveiling Metabolic Phenotype Alterations in Anorexia Nervosa through Metabolomics. Nutrients 2021; 13:nu13124249. [PMID: 34959800 PMCID: PMC8706417 DOI: 10.3390/nu13124249] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 11/24/2021] [Accepted: 11/25/2021] [Indexed: 11/17/2022] Open
Abstract
Anorexia nervosa (AN) is a mental disorder characterized by an intense fear of weight gain that affects mainly young women. It courses with a negative body image leading to altered eating behaviors that have devastating physical, metabolic, and psychological consequences for the patients. Although its origin is postulated to be multifactorial, the etiology of AN remains unknown, and this increases the likelihood of chronification and relapsing. Thus, expanding the available knowledge on the pathophysiology of AN is of enormous interest. Metabolomics is proposed as a powerful tool for the elucidation of disease mechanisms and to provide new insights into the diagnosis, treatment, and prognosis of AN. A review of the literature related to studies of AN patients by employing metabolomic strategies to characterize the main alterations associated with the metabolic phenotype of AN during the last 10 years is described. The most common metabolic alterations are derived from chronic starvation, including amino acid, lipid, and carbohydrate disturbances. Nonetheless, recent findings have shifted the attention to gut-microbiota metabolites as possible factors contributing to AN development, progression, and maintenance. We have identified the areas of ongoing research in AN and propose further perspectives to improve our knowledge and understanding of this disease.
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21
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Nounu A, Richmond RC, Stewart ID, Surendran P, Wareham NJ, Butterworth A, Weinstein SJ, Albanes D, Baron JA, Hopper JL, Figueiredo JC, Newcomb PA, Lindor NM, Casey G, Platz EA, Marchand LL, Ulrich CM, Li CI, van Dujinhoven FJB, Gsur A, Campbell PT, Moreno V, Vodicka P, Vodickova L, Amitay E, Alwers E, Chang-Claude J, Sakoda LC, Slattery ML, Schoen RE, Gunter MJ, Castellví-Bel S, Kim HR, Kweon SS, Chan AT, Li L, Zheng W, Bishop DT, Buchanan DD, Giles GG, Gruber SB, Rennert G, Stadler ZK, Harrison TA, Lin Y, Keku TO, Woods MO, Schafmayer C, Van Guelpen B, Gallinger S, Hampel H, Berndt SI, Pharoah PDP, Lindblom A, Wolk A, Wu AH, White E, Peters U, Drew DA, Scherer D, Bermejo JL, Brenner H, Hoffmeister M, Williams AC, Relton CL. Salicylic Acid and Risk of Colorectal Cancer: A Two-Sample Mendelian Randomization Study. Nutrients 2021; 13:4164. [PMID: 34836419 PMCID: PMC8620763 DOI: 10.3390/nu13114164] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 11/10/2021] [Accepted: 11/17/2021] [Indexed: 12/21/2022] Open
Abstract
Salicylic acid (SA) has observationally been shown to decrease colorectal cancer (CRC) risk. Aspirin (acetylsalicylic acid, that rapidly deacetylates to SA) is an effective primary and secondary chemopreventive agent. Through a Mendelian randomization (MR) approach, we aimed to address whether levels of SA affected CRC risk, stratifying by aspirin use. A two-sample MR analysis was performed using GWAS summary statistics of SA (INTERVAL and EPIC-Norfolk, N = 14,149) and CRC (CCFR, CORECT, GECCO and UK Biobank, 55,168 cases and 65,160 controls). The DACHS study (4410 cases and 3441 controls) was used for replication and stratification of aspirin-use. SNPs proxying SA were selected via three methods: (1) functional SNPs that influence the activity of aspirin-metabolising enzymes; (2) pathway SNPs present in enzymes' coding regions; and (3) genome-wide significant SNPs. We found no association between functional SNPs and SA levels. The pathway and genome-wide SNPs showed no association between SA and CRC risk (OR: 1.03, 95% CI: 0.84-1.27 and OR: 1.08, 95% CI: 0.86-1.34, respectively). Results remained unchanged upon aspirin use stratification. We found little evidence to suggest that an SD increase in genetically predicted SA protects against CRC risk in the general population and upon stratification by aspirin use.
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Affiliation(s)
- Aayah Nounu
- Integrative Cancer Epidemiology Programme (ICEP), Medical Research Council (MRC) Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK; (R.C.R.); (C.L.R.)
- School of Cellular and Molecular Medicine, University of Bristol, Bristol BS8 1TD, UK;
| | - Rebecca C. Richmond
- Integrative Cancer Epidemiology Programme (ICEP), Medical Research Council (MRC) Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK; (R.C.R.); (C.L.R.)
| | - Isobel D. Stewart
- MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0SL, UK; (I.D.S.); (N.J.W.)
| | - Praveen Surendran
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (P.S.); (A.B.)
- British Heart Foundation Centre of Research Excellence, Division of Cardiovascular Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge CB10 1SA, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK;
| | - Nicholas J. Wareham
- MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0SL, UK; (I.D.S.); (N.J.W.)
| | - Adam Butterworth
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (P.S.); (A.B.)
- British Heart Foundation Centre of Research Excellence, Division of Cardiovascular Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
- Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge CB10 1SA, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge CB2 1TN, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge University Hospitals, Cambridge CB2 0QQ, UK
| | - Stephanie J. Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20814, USA; (S.J.W.); (D.A.); (S.I.B.)
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20814, USA; (S.J.W.); (D.A.); (S.I.B.)
| | - John A. Baron
- Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC 27516, USA;
| | - John L. Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3053, Australia; (J.L.H.); (G.G.G.)
- Department of Epidemiology, Institute of Health and Environment, School of Public Health, Seoul National University, Seoul 08826, Korea
| | - Jane C. Figueiredo
- Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA;
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - Polly A. Newcomb
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109-1024, USA; (P.A.N.); (C.I.L.); (L.C.S.)
- School of Public Health, University of Washington, Seattle, WA 98195, USA
| | - Noralane M. Lindor
- Department of Health Science Research, Mayo Clinic, Scottsdale, AZ 85259, USA;
| | - Graham Casey
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA;
| | - Elizabeth A. Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA;
| | - Loïc Le Marchand
- Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI 96813, USA;
| | - Cornelia M. Ulrich
- Huntsman Cancer Institute, Department of Population Health Sciences, University of Utah, Salt Lake City, UT 84112, USA;
| | - Christopher I. Li
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109-1024, USA; (P.A.N.); (C.I.L.); (L.C.S.)
| | - Fränzel J. B. van Dujinhoven
- Division of Human Nutrition and Health, Department of Agrotechnology and Food Sciences, Wageningen University & Research, 6700 HB Wageningen, The Netherlands; (F.J.B.v.D.); (T.A.H.); (Y.L.); (E.W.); (U.P.)
| | - Andrea Gsur
- Institute of Cancer Research, Department of Medicine I, Medical University Vienna, 1090 Vienna, Austria;
| | - Peter T. Campbell
- Department of Population Science, American Cancer Society, Atlanta, GA 30303, USA;
| | - Víctor Moreno
- Oncology Data Analytics Program, Catalan Institute of Oncology-IDIBELL, 08908 Barcelona, Spain;
- CIBER Epidemiología y Salud Pública (CIBERESP), 28029 Madrid, Spain
- Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, 08007 Barcelona, Spain
- ONCOBEL Program, Bellvitge Biomedical Research Institute (IDIBELL), 08908 Barcelona, Spain
| | - Pavel Vodicka
- Department of Molecular Biology of Cancer, Institute of Experimental Medicine of the Czech Academy of Sciences, 142 20 Prague, Czech Republic; (P.V.); (L.V.)
- Institute of Biology and Medical Genetics, First Faculty of Medicine, Charles University, Nové Město, 121 08 Prague, Czech Republic
- Faculty of Medicine and Biomedical Center in Pilsen, Charles University, 323 00 Pilsen, Czech Republic
| | - Ludmila Vodickova
- Department of Molecular Biology of Cancer, Institute of Experimental Medicine of the Czech Academy of Sciences, 142 20 Prague, Czech Republic; (P.V.); (L.V.)
- Institute of Biology and Medical Genetics, First Faculty of Medicine, Charles University, Nové Město, 121 08 Prague, Czech Republic
- Faculty of Medicine and Biomedical Center in Pilsen, Charles University, 323 00 Pilsen, Czech Republic
| | - Efrat Amitay
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; (E.A.); (E.A.)
| | - Elizabeth Alwers
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; (E.A.); (E.A.)
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; (J.C.-C.); (H.B.); (M.H.)
- Department of Oncology, Haematology and BMT, University Medical Centre Hamburg-Eppendorf, University Cancer Centre Hamburg (UCCH), 20251 Hamburg, Germany
| | - Lori C. Sakoda
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109-1024, USA; (P.A.N.); (C.I.L.); (L.C.S.)
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Martha L. Slattery
- Department of Internal Medicine, University of Utah, Salt Lake City, UT 84112, USA;
| | - Robert E. Schoen
- Department of Medicine and Epidemiology, University of Pittsburgh Medical Center, Pittsburgh, PA 15261, USA;
| | - Marc J. Gunter
- Nutrition and Metabolism Section, International Agency for Research on Cancer, World Health Organization, 69372 Lyon, France;
| | - Sergi Castellví-Bel
- Gastroenterology Department, Hospital Clínic, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), University of Barcelona, 08036 Barcelona, Spain;
| | - Hyeong-Rok Kim
- Department of Surgery, Chonnam National University Hwasun Hospital and Medical School, Hwasun 58128, Korea;
| | - Sun-Seog Kweon
- Department of Preventive Medicine, Chonnam National University Medical School, Gwangju 61186, Korea;
- Jeonnam Regional Cancer Center, Chonnam National University Hwasun Hospital, Hwasun 58128, Korea
| | - Andrew T. Chan
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA;
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA;
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
| | - Li Li
- Department of Family Medicine, University of Virginia, Charlottesville, VA 22903, USA;
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA;
| | - D. Timothy Bishop
- Leeds Institute of Cancer and Pathology, School of Medicine, University of Leeds, Leeds LS2 9JT, UK;
| | - Daniel D. Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, VIC 3010, Australia;
- Melbourne Medical School, University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, VIC 3010, Australia
- Genetic Medicine and Family Cancer Clinic, The Royal Melbourne Hospital, Parkville, VIC 3000, Australia
| | - Graham G. Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC 3053, Australia; (J.L.H.); (G.G.G.)
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC 3004, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, VIC 3168, Australia
| | - Stephen B. Gruber
- Department of Preventive Medicine & USC Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA;
| | - Gad Rennert
- Department of Community Medicine and Epidemiology, Lady Davis Carmel Medical Center, Haifa 3448516, Israel;
- Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa 3200003, Israel
- Clalit National Cancer Control Center, Haifa 3436212, Israel
| | - Zsofia K. Stadler
- Memorial Sloan Kettering Cancer Center, Department of Medicine, New York, NY 10065, USA;
| | - Tabitha A. Harrison
- Division of Human Nutrition and Health, Department of Agrotechnology and Food Sciences, Wageningen University & Research, 6700 HB Wageningen, The Netherlands; (F.J.B.v.D.); (T.A.H.); (Y.L.); (E.W.); (U.P.)
| | - Yi Lin
- Division of Human Nutrition and Health, Department of Agrotechnology and Food Sciences, Wageningen University & Research, 6700 HB Wageningen, The Netherlands; (F.J.B.v.D.); (T.A.H.); (Y.L.); (E.W.); (U.P.)
| | - Temitope O. Keku
- Center for Gastrointestinal Biology and Disease, School of Medicine, University of North Carolina, Chapel Hill, NC 27599-7555, USA;
| | - Michael O. Woods
- Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St. John’s, NL A1B 3V6, Canada;
| | - Clemens Schafmayer
- Department of General Surgery, University Hospital Rostock, 18057 Rostock, Germany;
| | - Bethany Van Guelpen
- Department of Radiation Sciences, Oncology Unit, Umeå University, 901 87 Umeå, Sweden;
- Wallenberg Centre for Molecular Medicine, Department of Biomedical and Clinical Sciences, Umeå University, 901 87 Umeå, Sweden
| | - Steven Gallinger
- Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, Faculty of Medicine, University of Toronto, Toronto, ON M5G 1X5, Canada;
| | - Heather Hampel
- Division of Human Genetics, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH 43210, USA;
| | - Sonja I. Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20814, USA; (S.J.W.); (D.A.); (S.I.B.)
| | - Paul D. P. Pharoah
- Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK;
| | - Annika Lindblom
- Department of Clinical Genetics, Karolinska University Hospital, 171 64 Solna, Sweden;
- Department of Molecular Medicine and Surgery, Karolinska Institutet, 171 64 Solna, Sweden
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska Institutet, 171 64 Solna, Sweden;
- Department of Surgical Sciences, Uppsala University, 751 85 Uppsala, Sweden
| | - Anna H. Wu
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA;
| | - Emily White
- Division of Human Nutrition and Health, Department of Agrotechnology and Food Sciences, Wageningen University & Research, 6700 HB Wageningen, The Netherlands; (F.J.B.v.D.); (T.A.H.); (Y.L.); (E.W.); (U.P.)
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA 98195, USA
| | - Ulrike Peters
- Division of Human Nutrition and Health, Department of Agrotechnology and Food Sciences, Wageningen University & Research, 6700 HB Wageningen, The Netherlands; (F.J.B.v.D.); (T.A.H.); (Y.L.); (E.W.); (U.P.)
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA 98195, USA
| | - David A. Drew
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA;
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Dominique Scherer
- Institute of Medical Biometry and Informatics, Medical Faculty, University of Heidelberg, Im Neuenheimer Feld 130.3, 69120 Heidelberg, Germany; (D.S.); (J.L.B.)
| | - Justo Lorenzo Bermejo
- Institute of Medical Biometry and Informatics, Medical Faculty, University of Heidelberg, Im Neuenheimer Feld 130.3, 69120 Heidelberg, Germany; (D.S.); (J.L.B.)
| | - Hermann Brenner
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; (J.C.-C.); (H.B.); (M.H.)
- Division of Preventive Oncology, German Cancer Research Center (DKFZ), National Center for Tumor Diseases (NCT), 69120 Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
| | - Michael Hoffmeister
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany; (J.C.-C.); (H.B.); (M.H.)
| | - Ann C. Williams
- School of Cellular and Molecular Medicine, University of Bristol, Bristol BS8 1TD, UK;
| | - Caroline L. Relton
- Integrative Cancer Epidemiology Programme (ICEP), Medical Research Council (MRC) Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK; (R.C.R.); (C.L.R.)
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22
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Proline as a Sparker Metabolite of Oxidative Metabolism during the Flight of the Bumblebee, Bombus impatiens. Metabolites 2021; 11:metabo11080511. [PMID: 34436452 PMCID: PMC8399816 DOI: 10.3390/metabo11080511] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 07/23/2021] [Accepted: 07/31/2021] [Indexed: 11/16/2022] Open
Abstract
Several insect species use the amino acid proline as a major energy substrate. Although initially thought to be limited to blood-feeding dipterans, studies have revealed this capability is more widespread. Recent work with isolated flight muscle showed that the bumblebee Bombus impatiens can oxidize proline at a high rate. However, its role as a metabolic fuel to power flight is unclear. To elucidate the extent to which proline is oxidized to power flight and how its contribution changes during flight, we profiled 14 metabolites central to energy and proline metabolism at key time points in flight muscle and abdominal tissues. Ultra-high performance liquid chromatography-electrospray ionization-quadrupole time of flight mass spectrometry (UPLC-ESI-QTOF MS) analysis revealed that proline is likely used as a sparker metabolite of the tricarboxylic acid cycle at the onset of flight, whereby it supplements the intermediates of the cycle. Carbohydrates are the major energy substrates, which is evidenced by marked decreases in abdominal glycogen stores and a lack of alanine accumulation to replenish flight muscle proline. The time course of fuel stores and metabolites changes during flight highlights homeostatic regulation of energy substrates and patterns of changes in metabolic intermediates within pathways. This study clarifies the role of proline and carbohydrate metabolism during flight in hymenopterans, such as B. impatiens.
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Martínez Arbas S, Busi SB, Queirós P, de Nies L, Herold M, May P, Wilmes P, Muller EEL, Narayanasamy S. Challenges, Strategies, and Perspectives for Reference-Independent Longitudinal Multi-Omic Microbiome Studies. Front Genet 2021; 12:666244. [PMID: 34194470 PMCID: PMC8236828 DOI: 10.3389/fgene.2021.666244] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 04/30/2021] [Indexed: 12/21/2022] Open
Abstract
In recent years, multi-omic studies have enabled resolving community structure and interrogating community function of microbial communities. Simultaneous generation of metagenomic, metatranscriptomic, metaproteomic, and (meta) metabolomic data is more feasible than ever before, thus enabling in-depth assessment of community structure, function, and phenotype, thus resulting in a multitude of multi-omic microbiome datasets and the development of innovative methods to integrate and interrogate those multi-omic datasets. Specifically, the application of reference-independent approaches provides opportunities in identifying novel organisms and functions. At present, most of these large-scale multi-omic datasets stem from spatial sampling (e.g., water/soil microbiomes at several depths, microbiomes in/on different parts of the human anatomy) or case-control studies (e.g., cohorts of human microbiomes). We believe that longitudinal multi-omic microbiome datasets are the logical next step in microbiome studies due to their characteristic advantages in providing a better understanding of community dynamics, including: observation of trends, inference of causality, and ultimately, prediction of community behavior. Furthermore, the acquisition of complementary host-derived omics, environmental measurements, and suitable metadata will further enhance the aforementioned advantages of longitudinal data, which will serve as the basis to resolve drivers of community structure and function to understand the biotic and abiotic factors governing communities and specific populations. Carefully setup future experiments hold great potential to further unveil ecological mechanisms to evolution, microbe-microbe interactions, or microbe-host interactions. In this article, we discuss the challenges, emerging strategies, and best-practices applicable to longitudinal microbiome studies ranging from sampling, biomolecular extraction, systematic multi-omic measurements, reference-independent data integration, modeling, and validation.
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Affiliation(s)
- Susana Martínez Arbas
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Susheel Bhanu Busi
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Pedro Queirós
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Laura de Nies
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Malte Herold
- Department of Environmental Research and Innovation, Luxembourg Institute of Science and Technology, Belvaux, Luxembourg
| | - Patrick May
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Paul Wilmes
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
- Department of Life Sciences and Medicine, Faculty of Science, Technology and Medicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Emilie E. L. Muller
- Université de Strasbourg, UMR 7156 CNRS, Génétique Moléculaire, Génomique, Microbiologie, Strasbourg, France
| | - Shaman Narayanasamy
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
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24
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Kubacka A, Rojo D, Muñoz-Batista MJ, Barbas C, Fernández-García M, Ferrer M. Metabolomics reveals synergy between Ag and g-C 3N 4 in Ag/g-C 3N 4 composite photocatalysts: a unique feature among Ag-doped biocidal materials. Metabolomics 2021; 17:53. [PMID: 34061256 DOI: 10.1007/s11306-021-01804-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 05/24/2021] [Indexed: 10/21/2022]
Abstract
INTRODUCTION The silver/graphitic carbon nitride (Ag/g-C3N4) composite system exerts biocidal activity against the pathogenic bacterium Escherichia coli 1337-H that is stronger than that of well-known silver and titanium oxide (TiO2)-based composites. However, whether the Ag/g-C3N4 composite system has biocidal properties that the parent components do or do not have as separate chemical entities and whether they differ from those in Ag/TiO2 composite photocatalysts have not been clarified. OBJECTIVE We investigated the chemical (cooperative charge handling and electronic properties) and biological (metabolic) effects exerted by the addition of Ag to g-C3N4 and to TiO2. METHODS In this work, we undertook metabolome-wide analysis by liquid chromatography-electrospray ionization-quadrupole-time of flight-mass spectrometry to compare the metabolite profiles of untreated E. coli 1337-H cells or those subjected to disinfection with Ag, g-C3N4, 2Ag/g-C3N4, TiO2 and 2Ag/TiO2. RESULTS While Ag or g-C3N4 moderately affected microbial metabolism according to the mean of the altered metabolites, multiple cell systems contributing to rapid cell death were immediately affected by the light-triggered radical species produced when Ag and g-C3N4 were as xAg/g-C3N4. The effects include drastically reduced production of small metabolites essential for detoxifying reactive oxygen species and those that regulate DNA replication fidelity, cell morphology and energy status. These biological consequences were different from those caused by Ag/TiO2-based biocides, demonstrating the uniqueness of the Ag/g-C3N4 system. CONCLUSIONS Our results support the idea that the unique Ag/g-C3N4 biocidal properties are based on synergistic action and reveal new directions for designing future photocatalysts for use in disinfection and microbial control.
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Affiliation(s)
- Anna Kubacka
- Institute of Catalysis and Petrochemistry, Consejo Superior de Investigaciones Científicas, c/Marie Curie 2, 28049, Madrid, Spain
| | - David Rojo
- Department of Chemistry and Biochemistry, Facultad de Farmacia, Centre for Metabolomics and Bioanalysis (CEMBIO), Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, 28660 Boadilla del Monte, Madrid, Spain
| | - Mario J Muñoz-Batista
- Institute of Catalysis and Petrochemistry, Consejo Superior de Investigaciones Científicas, c/Marie Curie 2, 28049, Madrid, Spain
- Department of Chemical Engineering, University of Granada, Av. de La Fuente Nueva S/N, 18071, Granada, Spain
| | - Coral Barbas
- Department of Chemistry and Biochemistry, Facultad de Farmacia, Centre for Metabolomics and Bioanalysis (CEMBIO), Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, 28660 Boadilla del Monte, Madrid, Spain
| | - Marcos Fernández-García
- Institute of Catalysis and Petrochemistry, Consejo Superior de Investigaciones Científicas, c/Marie Curie 2, 28049, Madrid, Spain.
| | - Manuel Ferrer
- Institute of Catalysis and Petrochemistry, Consejo Superior de Investigaciones Científicas, c/Marie Curie 2, 28049, Madrid, Spain.
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25
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Kapoore RV, Padmaperuma G, Maneein S, Vaidyanathan S. Co-culturing microbial consortia: approaches for applications in biomanufacturing and bioprocessing. Crit Rev Biotechnol 2021; 42:46-72. [PMID: 33980092 DOI: 10.1080/07388551.2021.1921691] [Citation(s) in RCA: 52] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
The application of microbial co-cultures is now recognized in the fields of biotechnology, ecology, and medicine. Understanding the biological interactions that govern the association of microorganisms would shape the way in which artificial/synthetic co-cultures or consortia are developed. The ability to accurately predict and control cell-to-cell interactions fully would be a significant enabler in synthetic biology. Co-culturing method development holds the key to strategically engineer environments in which the co-cultured microorganism can be monitored. Various approaches have been employed which aim to emulate the natural environment and gain access to the untapped natural resources emerging from cross-talk between partners. Amongst these methods are the use of a communal liquid medium for growth, use of a solid-liquid interface, membrane separation, spatial separation, and use of microfluidics systems. Maximizing the information content of interactions monitored is one of the major challenges that needs to be addressed by these designs. This review critically evaluates the significance and drawbacks of the co-culturing approaches used to this day in biotechnological applications, relevant to biomanufacturing. It is recommended that experimental results for a co-cultured species should be validated with different co-culture approaches due to variations in interactions that could exist as a result of the culturing method selected.
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Affiliation(s)
- Rahul Vijay Kapoore
- Department of Chemical and Biological Engineering, The University of Sheffield, Sheffield, UK.,Department of Biosciences, College of Science, Swansea University, Swansea, UK
| | - Gloria Padmaperuma
- Department of Chemical and Biological Engineering, The University of Sheffield, Sheffield, UK
| | - Supattra Maneein
- Department of Chemical and Biological Engineering, The University of Sheffield, Sheffield, UK.,Department of Pharmaceutical, Chemical & Environmental Sciences, The University of Greenwich, Kent, UK
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26
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Xie G, Wang L, Chen T, Zhou K, Zhang Z, Li J, Sun B, Guo Y, Wang X, Wang Y, Zhang H, Liu P, Nicholson JK, Ge W, Jia W. A Metabolite Array Technology for Precision Medicine. Anal Chem 2021; 93:5709-5717. [PMID: 33797874 DOI: 10.1021/acs.analchem.0c04686] [Citation(s) in RCA: 155] [Impact Index Per Article: 38.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The application of metabolomics in translational research suffers from several technological bottlenecks, such as data reproducibility issues and the lack of standardization of sample profiling procedures. Here, we report an automated high-throughput metabolite array technology that can rapidly and quantitatively determine 324 metabolites including fatty acids, amino acids, organic acids, carbohydrates, and bile acids. Metabolite identification and quantification is achieved using the Targeted Metabolome Batch Quantification (TMBQ) software, the first cross-vendor data processing pipeline. A test of this metabolite array was performed by analyzing serum samples from patients with chronic liver disease (N = 1234). With high detection efficiency and sensitivity in serum, urine, feces, cell lysates, and liver tissue samples and suitable for different mass spectrometry systems, this metabolite array technology holds great potential for biomarker discovery and high throughput clinical testing. Additionally, data generated from such standardized procedures can be used to generate a clinical metabolomics database suitable for precision medicine in next-generation healthcare.
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Affiliation(s)
- Guoxiang Xie
- Shanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
- Human Metabolomics Institute, Inc., Shenzhen, Guangdong 518109, China
| | - Lu Wang
- Human Metabolomics Institute, Inc., Shenzhen, Guangdong 518109, China
| | - Tianlu Chen
- Shanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Kejun Zhou
- Human Metabolomics Institute, Inc., Shenzhen, Guangdong 518109, China
| | - Zechuan Zhang
- Department of Hepatobiliary Surgery, The Nanjing Drum Tower Hospital Affiliated to Nanjing University Medical School, Nanjing, Jiangsu 210009, China
| | - Jiufeng Li
- Hong Kong Traditional Chinese Medicine Phenome Research Centre, School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong 999077, China
| | - Beicheng Sun
- Department of Hepatobiliary Surgery, The Nanjing Drum Tower Hospital Affiliated to Nanjing University Medical School, Nanjing, Jiangsu 210009, China
| | - Yike Guo
- Hong Kong Traditional Chinese Medicine Phenome Research Centre, School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong 999077, China
| | - Xiaoning Wang
- E-Institute of Shanghai Municipal Education Committee, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Yixing Wang
- E-Institute of Shanghai Municipal Education Committee, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Hua Zhang
- E-Institute of Shanghai Municipal Education Committee, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Ping Liu
- E-Institute of Shanghai Municipal Education Committee, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China
| | - Jeremy K Nicholson
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia
| | - Weihong Ge
- Department of Pharmacy, The Nanjing Drum Tower Hospital Affiliated to Nanjing University Medical School, Nanjing, Jiangsu 210009, China
| | - Wei Jia
- Shanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
- Hong Kong Traditional Chinese Medicine Phenome Research Centre, School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong 999077, China
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27
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Rivera-Velez SM, Navas J, Villarino NF. Applying metabolomics to veterinary pharmacology and therapeutics. J Vet Pharmacol Ther 2021; 44:855-869. [PMID: 33719079 DOI: 10.1111/jvp.12961] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2020] [Accepted: 02/08/2021] [Indexed: 02/06/2023]
Abstract
Metabolomics is the large-scale study of low-molecular-weight substances in a biological system in a given physiological state at a given time point. Metabolomics can be applied to identify predictors of inter-individual variability in drug response, provide clinicians with data useful for decision-making processes in drug selection, and inform about the pharmacokinetics and pharmacodynamics of a drug. It is, therefore, an exceptional approach for gaining new understanding effects in the field of comparative veterinary pharmacology. However, the incorporation of metabolomics into veterinary pharmacology and toxicology is not yet widespread, and this is probably, at least in part, a result of its highly multidisciplinary nature. This article reviews the potential applications of metabolomics in veterinary pharmacology and therapeutics. It integrates key concepts for designing metabolomics studies and analyzing and interpreting metabolomics data, providing solid foundations for applying metabolomics to the study of drugs in all veterinary species.
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Affiliation(s)
- Sol M Rivera-Velez
- Molecular Determinants Core, Johns Hopkins All Children's Hospital, Saint Petersburg, Florida, USA
| | - Jinna Navas
- Program in Individualized Medicine, Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Washington State University, Pullman, Washington, USA
| | - Nicolas F Villarino
- Program in Individualized Medicine, Department of Veterinary Clinical Sciences, College of Veterinary Medicine, Washington State University, Pullman, Washington, USA
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Pretorius CJ, Tugizimana F, Steenkamp PA, Piater LA, Dubery IA. Metabolomics for Biomarker Discovery: Key Signatory Metabolic Profiles for the Identification and Discrimination of Oat Cultivars. Metabolites 2021; 11:165. [PMID: 33809127 PMCID: PMC8001698 DOI: 10.3390/metabo11030165] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 03/05/2021] [Accepted: 03/05/2021] [Indexed: 12/15/2022] Open
Abstract
The first step in crop introduction-or breeding programmes-requires cultivar identification and characterisation. Rapid identification methods would therefore greatly improve registration, breeding, seed, trade and inspection processes. Metabolomics has proven to be indispensable in interrogating cellular biochemistry and phenotyping. Furthermore, metabolic fingerprints are chemical maps that can provide detailed insights into the molecular composition of a biological system under consideration. Here, metabolomics was applied to unravel differential metabolic profiles of various oat (Avena sativa) cultivars (Magnifico, Dunnart, Pallinup, Overberg and SWK001) and to identify signatory biomarkers for cultivar identification. The respective cultivars were grown under controlled conditions up to the 3-week maturity stage, and leaves and roots were harvested for each cultivar. Metabolites were extracted using 80% methanol, and extracts were analysed on an ultra-high performance liquid chromatography (UHPLC) system coupled to a quadrupole time-of-flight (qTOF) high-definition mass spectrometer analytical platform. The generated data were processed and analysed using multivariate statistical methods. Principal component analysis (PCA) models were computed for both leaf and root data, with PCA score plots indicating cultivar-related clustering of the samples and pointing to underlying differential metabolic profiles of these cultivars. Further multivariate analyses were performed to profile differential signatory markers, which included carboxylic acids, amino acids, fatty acids, phenolic compounds (hydroxycinnamic and hydroxybenzoic acids, and associated derivatives) and flavonoids, among the respective cultivars. Based on the key signatory metabolic markers, the cultivars were successfully distinguished from one another in profiles derived from both leaves and roots. The study demonstrates that metabolomics can be used as a rapid phenotyping tool for cultivar differentiation.
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Affiliation(s)
| | | | | | | | - Ian A. Dubery
- Research Centre for Plant Metabolomics, Department of Biochemistry, University of Johannesburg, P.O. Box 524, Auckland Park, Johannesburg 2006, South Africa; (C.J.P.); (F.T.); (P.A.S.); (L.A.P.)
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Kumar K, Venkatraman V, Bruheim P. Adaptation of central metabolite pools to variations in growth rate and cultivation conditions in Saccharomyces cerevisiae. Microb Cell Fact 2021; 20:64. [PMID: 33750414 PMCID: PMC7941957 DOI: 10.1186/s12934-021-01557-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 03/01/2021] [Indexed: 11/19/2022] Open
Abstract
Background Saccharomyces cerevisiae is a well-known popular model system for basic biological studies and serves as a host organism for the heterologous production of commercially interesting small molecules and proteins. The central metabolism is at the core to provide building blocks and energy to support growth and survival in normal situations as well as during exogenous stresses and forced heterologous protein production. Here, we present a comprehensive study of intracellular central metabolite pool profiling when growing S. cerevisiae on different carbon sources in batch cultivations and at different growth rates in nutrient-limited glucose chemostats. The latest versions of absolute quantitative mass spectrometry-based metabolite profiling methodology were applied to cover glycolytic and pentose phosphate pathway metabolites, tricarboxylic acid cycle (TCA), complete amino acid, and deoxy-/nucleoside phosphate pools. Results Glutamate, glutamine, alanine, and citrate were the four most abundant metabolites for most conditions tested. The amino acid is the dominant metabolite class even though a marked relative reduction compared to the other metabolite classes was observed for nitrogen and phosphate limited chemostats. Interestingly, glycolytic and pentose phosphate pathway (PPP) metabolites display the largest variation among the cultivation conditions while the nucleoside phosphate pools are more stable and vary within a closer concentration window. The overall trends for glucose and nitrogen-limited chemostats were increased metabolite pools with the increasing growth rate. Next, comparing the chosen chemostat reference growth rate (0.12 h−1, approximate one-fourth of maximal unlimited growth rate) illuminates an interesting pattern: almost all pools are lower in nitrogen and phosphate limited conditions compared to glucose limitation, except for the TCA metabolites citrate, isocitrate and α-ketoglutarate. Conclusions This study provides new knowledge-how the central metabolism is adapting to various cultivations conditions and growth rates which is essential for expanding our understanding of cellular metabolism and the development of improved phenotypes in metabolic engineering. Supplementary Information The online version contains supplementary material available at 10.1186/s12934-021-01557-8.
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Affiliation(s)
- Kanhaiya Kumar
- Department of Biotechnology and Food Science, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
| | - Vishwesh Venkatraman
- Department of Chemistry, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway
| | - Per Bruheim
- Department of Biotechnology and Food Science, Norwegian University of Science and Technology (NTNU), 7491, Trondheim, Norway.
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Labine LM, Simpson MJ. Targeted Metabolomic Assessment of the Sub-Lethal Toxicity of Halogenated Acetic Acids (HAAs) to Daphnia magna. Metabolites 2021; 11:100. [PMID: 33578863 PMCID: PMC7916598 DOI: 10.3390/metabo11020100] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2021] [Revised: 02/03/2021] [Accepted: 02/05/2021] [Indexed: 12/19/2022] Open
Abstract
Halogenated acetic acids (HAAs) are amongst the most frequently detected disinfection by-products in aquatic environments. Despite this, little is known about their toxicity, especially at the molecular level. The model organism Daphnia magna, which is an indicator species for freshwater ecosystems, was exposed to sub-lethal concentrations of dichloroacetic acid (DCAA), trichloroacetic acid (TCAA) and dibromoacetic acid (DBAA) for 48 h. Polar metabolites extracted from Daphnia were analyzed using liquid chromatography hyphened to a triple quadrupole mass spectrometer (LC-MS/MS). Multivariate analyses identified shifts in the metabolic profile with exposure and pathway analysis was used to identify which metabolites and associated pathways were disrupted. Exposure to all three HAAs led to significant downregulation in the nucleosides: adenosine, guanosine and inosine. Pathway analyses identified perturbations in the citric acid cycle and the purine metabolism pathways. Interestingly, chlorinated and brominated acetic acids demonstrated similar modes of action after sub-lethal acute exposure, suggesting that HAAs cause a contaminant class-based response which is independent of the type or number of halogens. As such, the identified metabolites that responded to acute HAA exposure may serve as suitable bioindicators for freshwater monitoring programs.
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Affiliation(s)
- Lisa M. Labine
- Department of Chemistry, University of Toronto, 80 St. George St., Toronto, ON M5S 3H6, Canada;
- Environmental NMR Centre and Department of Physical and Environmental Sciences, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON M1C 1A4, Canada
| | - Myrna J. Simpson
- Department of Chemistry, University of Toronto, 80 St. George St., Toronto, ON M5S 3H6, Canada;
- Environmental NMR Centre and Department of Physical and Environmental Sciences, University of Toronto Scarborough, 1265 Military Trail, Toronto, ON M1C 1A4, Canada
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31
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Rollin JA, Bomble YJ, St. John PC, Stark AK. Biochemical Production with Purified Cell-Free Systems. Biochem Eng J 2021. [DOI: 10.1016/j.bej.2018.07.016] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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32
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Klupczynska A, Misiura M, Miltyk W, Oscilowska I, Palka J, Kokot ZJ, Matysiak J. Development of an LC-MS Targeted Metabolomics Methodology to Study Proline Metabolism in Mammalian Cell Cultures. Molecules 2020; 25:molecules25204639. [PMID: 33053735 PMCID: PMC7587214 DOI: 10.3390/molecules25204639] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Revised: 10/05/2020] [Accepted: 10/11/2020] [Indexed: 12/11/2022] Open
Abstract
A growing interest in metabolomics studies of cultured cells requires development not only untargeted methods capable of fingerprinting the complete metabolite profile but also targeted methods enabling the precise and accurate determination of a selected group of metabolites. Proline metabolism affects many crucial processes at the cellular level, including collagen biosynthesis, redox balance, energetic processes as well as intracellular signaling. The study aimed to develop a robust and easy-to-use targeted metabolomics method for the determination of the intracellular level of proline and the other two amino acids closely related to proline metabolism: glutamic acid and arginine. The method employs hydrophilic interaction liquid chromatography followed by high-resolution, accurate-mass mass spectrometry for reliable detection and quantification of the target metabolites in cell lysates. The sample preparation consisted of quenching by the addition of ice-cold methanol and subsequent cell scraping into a quenching solution. The method validation showed acceptable linearity (r > 0.995), precision (%RSD < 15%), and accuracy (88.5–108.5%). Pilot research using HaCaT spontaneously immortalized human keratinocytes in a model for wound healing was performed, indicating the usefulness of the method in studies of disturbances in proline metabolism. The developed method addresses the need to determine the intracellular concentration of three key amino acids and can be used routinely in targeted mammalian cell culture metabolomics research.
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Affiliation(s)
- Agnieszka Klupczynska
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 60-780 Poznan, Poland;
- Correspondence: ; Tel.: +48-61-854-66-16
| | - Magdalena Misiura
- Department of Analysis and Bioanalysis of Medicines, Medical University of Bialystok, 15-222 Bialystok, Poland; (M.M.); (W.M.)
| | - Wojciech Miltyk
- Department of Analysis and Bioanalysis of Medicines, Medical University of Bialystok, 15-222 Bialystok, Poland; (M.M.); (W.M.)
| | - Ilona Oscilowska
- Department of Medicinal Chemistry, Medical University of Bialystok, 15-222 Bialystok, Poland; (I.O.); (J.P.)
| | - Jerzy Palka
- Department of Medicinal Chemistry, Medical University of Bialystok, 15-222 Bialystok, Poland; (I.O.); (J.P.)
| | - Zenon J. Kokot
- Faculty of Health Sciences, State University of Applied Sciences in Kalisz, 62-800 Kalisz, Poland;
| | - Jan Matysiak
- Department of Inorganic and Analytical Chemistry, Poznan University of Medical Sciences, 60-780 Poznan, Poland;
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Balcerczyk A, Damblon C, Elena-Herrmann B, Panthu B, Rautureau GJP. Metabolomic Approaches to Study Chemical Exposure-Related Metabolism Alterations in Mammalian Cell Cultures. Int J Mol Sci 2020; 21:E6843. [PMID: 32961865 PMCID: PMC7554780 DOI: 10.3390/ijms21186843] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 09/11/2020] [Accepted: 09/14/2020] [Indexed: 12/12/2022] Open
Abstract
Biological organisms are constantly exposed to an immense repertoire of molecules that cover environmental or food-derived molecules and drugs, triggering a continuous flow of stimuli-dependent adaptations. The diversity of these chemicals as well as their concentrations contribute to the multiplicity of induced effects, including activation, stimulation, or inhibition of physiological processes and toxicity. Metabolism, as the foremost phenotype and manifestation of life, has proven to be immensely sensitive and highly adaptive to chemical stimuli. Therefore, studying the effect of endo- or xenobiotics over cellular metabolism delivers valuable knowledge to apprehend potential cellular activity of individual molecules and evaluate their acute or chronic benefits and toxicity. The development of modern metabolomics technologies such as mass spectrometry or nuclear magnetic resonance spectroscopy now offers unprecedented solutions for the rapid and efficient determination of metabolic profiles of cells and more complex biological systems. Combined with the availability of well-established cell culture techniques, these analytical methods appear perfectly suited to determine the biological activity and estimate the positive and negative effects of chemicals in a variety of cell types and models, even at hardly detectable concentrations. Metabolic phenotypes can be estimated from studying intracellular metabolites at homeostasis in vivo, while in vitro cell cultures provide additional access to metabolites exchanged with growth media. This article discusses analytical solutions available for metabolic phenotyping of cell culture metabolism as well as the general metabolomics workflow suitable for testing the biological activity of molecular compounds. We emphasize how metabolic profiling of cell supernatants and intracellular extracts can deliver valuable and complementary insights for evaluating the effects of xenobiotics on cellular metabolism. We note that the concepts and methods discussed primarily for xenobiotics exposure are widely applicable to drug testing in general, including endobiotics that cover active metabolites, nutrients, peptides and proteins, cytokines, hormones, vitamins, etc.
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Affiliation(s)
- Aneta Balcerczyk
- Department of Molecular Biophysics, Faculty of Biology and Environmental Protection, University of Lodz, Pomorska 141/143, 90-236 Lodz, Poland;
| | - Christian Damblon
- Unité de Recherche MolSys, Faculté des sciences, Université de Liège, 4000 Liège, Belgium;
| | | | - Baptiste Panthu
- CarMeN Laboratory, INSERM, INRA, INSA Lyon, Univ Lyon, Université Claude Bernard Lyon 1, 69921 Oullins CEDEX, France;
- Hospices Civils de Lyon, Faculté de Médecine, Hôpital Lyon Sud, 69921 Oullins CEDEX, France
| | - Gilles J. P. Rautureau
- Centre de Résonance Magnétique Nucléaire à Très Hauts Champs (CRMN FRE 2034 CNRS, UCBL, ENS Lyon), Université Claude Bernard Lyon 1, 69100 Villeurbanne, France
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Uengwetwanit T, Uawisetwathana U, Arayamethakorn S, Khudet J, Chaiyapechara S, Karoonuthaisiri N, Rungrassamee W. Multi-omics analysis to examine microbiota, host gene expression and metabolites in the intestine of black tiger shrimp ( Penaeus monodon) with different growth performance. PeerJ 2020; 8:e9646. [PMID: 32864208 PMCID: PMC7430268 DOI: 10.7717/peerj.9646] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 07/12/2020] [Indexed: 12/20/2022] Open
Abstract
Understanding the correlation between shrimp growth and their intestinal bacteria would be necessary to optimize animal's growth performance. Here, we compared the bacterial profiles along with the shrimp's gene expression responses and metabolites in the intestines between the Top and the Bottom weight groups. Black tiger shrimp (Penaeus monodon) were collected from the same population and rearing environments. The two weight groups, the Top-weight group with an average weight of 36.82 ± 0.41 g and the Bottom-weight group with an average weight of 17.80 ± 11.81 g, were selected. Intestines were aseptically collected and subjected to microbiota, transcriptomic and metabolomic profile analyses. The weighted-principal coordinates analysis (PCoA) based on UniFrac distances showed similar bacterial profiles between the two groups, suggesting similar relative composition of the overall bacterial community structures. This observed similarity was likely due to the fact that shrimp were from the same genetic background and reared under the same habitat and diets. On the other hand, the unweighted-distance matrix revealed that the bacterial profiles associated in intestines of the Top-weight group were clustered distinctly from those of the Bottom-weight shrimp, suggesting that some unique non-dominant bacterial genera were found associated with either group. The key bacterial members associated to the Top-weight shrimp were mostly from Firmicutes (Brevibacillus and Fusibacter) and Bacteroidetes (Spongiimonas), both of which were found in significantly higher abundance than those of the Bottom-weight shrimp. Transcriptomic profile of shrimp intestines found significant upregulation of genes mostly involved in nutrient metabolisms and energy storage in the Top-weight shrimp. In addition to significantly expressed metabolic-related genes, the Bottom-weight shrimp also showed significant upregulation of stress and immune-related genes, suggesting that these pathways might contribute to different degrees of shrimp growth performance. A non-targeted metabolome analysis from shrimp intestines revealed different metabolic responsive patterns, in which the Top-weight shrimp contained significantly higher levels of short chain fatty acids, lipids and organic compounds than the Bottom-weight shrimp. The identified metabolites included those that were known to be produced by intestinal bacteria such as butyric acid, 4-indolecarbaldehyde and L-3-phenyllactic acid as well as those produced by shrimp such as acyl-carnitines and lysophosphatidylcholine. The functions of these metabolites were related to nutrient absorption and metabolisms. Our findings provide the first report utilizing multi-omics integration approach to investigate microbiota, metabolic and transcriptomics profiles of the host shrimp and their potential roles and relationship to shrimp growth performance.
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Affiliation(s)
- Tanaporn Uengwetwanit
- Microarray Research Team, National Center for Genetic Engineering and Biotechnology, Pathum Thani, Thailand
| | - Umaporn Uawisetwathana
- Microarray Research Team, National Center for Genetic Engineering and Biotechnology, Pathum Thani, Thailand
| | - Sopacha Arayamethakorn
- Microarray Research Team, National Center for Genetic Engineering and Biotechnology, Pathum Thani, Thailand
| | - Juthatip Khudet
- Shrimp Genetic Improvement Center, National Center for Genetic Engineering and Biotechnology, Pathum Thani, Thailand
| | - Sage Chaiyapechara
- Aquaculture Service Development Research Team, National Center for Genetic Engineering and Biotechnology, Pathum Thani, Thailand
| | - Nitsara Karoonuthaisiri
- Microarray Research Team, National Center for Genetic Engineering and Biotechnology, Pathum Thani, Thailand
| | - Wanilada Rungrassamee
- Microarray Research Team, National Center for Genetic Engineering and Biotechnology, Pathum Thani, Thailand
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35
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Boruta T, Marczyk A, Rychta K, Przydacz K, Bizukojc M. Confrontation between Penicillium rubens and Aspergillus terreus: Investigating the production of fungal secondary metabolites in submerged co-cultures. J Biosci Bioeng 2020; 130:503-513. [PMID: 32758403 DOI: 10.1016/j.jbiosc.2020.06.012] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 06/10/2020] [Accepted: 06/27/2020] [Indexed: 12/24/2022]
Abstract
The production of secondary metabolites in the submerged co-cultures of Penicillium rubens Wisconsin 54-1255 and Aspergillus terreus ATCC 20542 was evaluated. The biosynthetic capabilities of the two strains were compared in a set of diverse liquid media that differed with respect to the initial levels of glucose, lactose and yeast extract, contained carrot juice or vegetable/turkey puree as additional nutrient sources or were supplemented with phenylacetic acid, the side-chain precursor of penicillin G. The main goal of the study was to investigate the interactions between A. terreus and P. rubens that might contribute to the changes of secondary metabolite titers. Briefly, the biosynthesis of octaketide metabolites (+)-geodin and asterric acid was visibly enhanced as a result of replacing the conventional monocultures with the co-culture systems, but solely in the media containing not more than 5 g L-1 of yeast extract. By contrast, no marked enhancement was observed with respect to the biosynthesis of penicillin G, lovastatin, chrysogine, 4a,5-dihydromevinolinic acid and 3α-hydroxy-3,5-dihydromonacolin L acid. It was shown that the relationships between medium composition and product titers were clearly different in monoculture variants than in the corresponding co-cultures. Finally, it was demonstrated that the utilization of penicillin precursors by P. rubens can be blocked under the conditions of co-cultivation.
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Affiliation(s)
- Tomasz Boruta
- Department of Bioprocess Engineering, Faculty of Process and Environmental Engineering, Lodz University of Technology, Ul. Wolczanska 213, 90-924 Lodz, Poland.
| | - Anna Marczyk
- Department of Bioprocess Engineering, Faculty of Process and Environmental Engineering, Lodz University of Technology, Ul. Wolczanska 213, 90-924 Lodz, Poland
| | - Katarzyna Rychta
- Department of Bioprocess Engineering, Faculty of Process and Environmental Engineering, Lodz University of Technology, Ul. Wolczanska 213, 90-924 Lodz, Poland
| | - Karolina Przydacz
- Department of Bioprocess Engineering, Faculty of Process and Environmental Engineering, Lodz University of Technology, Ul. Wolczanska 213, 90-924 Lodz, Poland
| | - Marcin Bizukojc
- Department of Bioprocess Engineering, Faculty of Process and Environmental Engineering, Lodz University of Technology, Ul. Wolczanska 213, 90-924 Lodz, Poland
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Kuhring M, Eisenberger A, Schmidt V, Kränkel N, Leistner DM, Kirwan J, Beule D. Concepts and Software Package for Efficient Quality Control in Targeted Metabolomics Studies: MeTaQuaC. Anal Chem 2020; 92:10241-10245. [PMID: 32603093 DOI: 10.1021/acs.analchem.0c00136] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Targeted quantitative mass spectrometry metabolite profiling is the workhorse of metabolomics research. Robust and reproducible data are essential for confidence in analytical results and are particularly important with large-scale studies. Commercial kits are now available which use carefully calibrated and validated internal and external standards to provide such reliability. However, they are still subject to processing and technical errors in their use and should be subject to a laboratory's routine quality assurance and quality control measures to maintain confidence in the results. We discuss important systematic and random measurement errors when using these kits and suggest measures to detect and quantify them. We demonstrate how wider analysis of the entire data set alongside standard analyses of quality control samples can be used to identify outliers and quantify systematic trends to improve downstream analysis. Finally, we present the MeTaQuaC software which implements the above concepts and methods for Biocrates kits and other target data sets and creates a comprehensive quality control report containing rich visualization and informative scores and summary statistics. Preliminary unsupervised multivariate analysis methods are also included to provide rapid insight into study variables and groups. MeTaQuaC is provided as an open source R package under a permissive MIT license and includes detailed user documentation.
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Affiliation(s)
- Mathias Kuhring
- Berlin Institute of Health (BIH), Charitéplatz 1, 10117 Berlin, Germany.,Max Delbrück Center (MDC) for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin, Germany
| | - Alina Eisenberger
- Berlin Institute of Health (BIH), Charitéplatz 1, 10117 Berlin, Germany.,Max Delbrück Center (MDC) for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin, Germany
| | - Vanessa Schmidt
- Max Delbrück Center (MDC) for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin, Germany
| | - Nicolle Kränkel
- Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.,DZHK (German Centre for Cardiovascular Research) Partner Site Berlin, Potsdamer Strasse 58, 10785 Berlin, Germany
| | - David M Leistner
- Berlin Institute of Health (BIH), Charitéplatz 1, 10117 Berlin, Germany.,Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany.,DZHK (German Centre for Cardiovascular Research) Partner Site Berlin, Potsdamer Strasse 58, 10785 Berlin, Germany
| | - Jennifer Kirwan
- Berlin Institute of Health (BIH), Charitéplatz 1, 10117 Berlin, Germany.,Max Delbrück Center (MDC) for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin, Germany
| | - Dieter Beule
- Berlin Institute of Health (BIH), Charitéplatz 1, 10117 Berlin, Germany.,Max Delbrück Center (MDC) for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin, Germany.,Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany
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37
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Metabolomics: A Tool for Cultivar Phenotyping and Investigation of Grain Crops. AGRONOMY-BASEL 2020. [DOI: 10.3390/agronomy10060831] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
The quality of plants is often enhanced for diverse purposes such as improved resistance to environmental pressures, better taste, and higher yields. Considering the world’s dependence on plants (nutrition, medicine, or biofuel), developing new cultivars with superior characteristics is of great importance. As part of the ‘omics’ approaches, metabolomics has been employed to investigate the large number of metabolites present in plant systems under well-defined environmental conditions. Recent advances in the metabolomics field have greatly expanded our understanding of plant metabolism, largely driven by potential application to agricultural systems. The current review presents the workflow for plant metabolome analyses, current knowledge, and future directions of such research as determinants of cultivar phenotypes. Furthermore, the value of metabolome analyses in contemporary crop science is illustrated. Here, metabolomics has provided valuable information in research on grain crops and identified significant biomarkers under different conditions and/or stressors. Moreover, the value of metabolomics has been redefined from simple biomarker identification to a tool for discovering active drivers involved in biological processes. We illustrate and conclude that the rapid advances in metabolomics are driving an explosion of information that will advance modern breeding approaches for grain crops and address problems associated with crop productivity and sustainable agriculture.
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Absolute Quantification of the Central Carbon Metabolome in Eight Commonly Applied Prokaryotic and Eukaryotic Model Systems. Metabolites 2020; 10:metabo10020074. [PMID: 32093075 PMCID: PMC7073941 DOI: 10.3390/metabo10020074] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 02/14/2020] [Accepted: 02/17/2020] [Indexed: 02/07/2023] Open
Abstract
Absolute quantification of intracellular metabolite pools is a prerequisite for modeling and in-depth biological interpretation of metabolomics data. It is the final step of an elaborate metabolomics workflow, with challenges associated with all steps—from sampling to quantifying the physicochemically diverse metabolite pool. Chromatographic separation combined with mass spectrometric (MS) detection is the superior platform for high coverage, selective, and sensitive detection of metabolites. Herein, we apply our quantitative MS-metabolomics workflow to measure and present the central carbon metabolome of a panel of commonly applied biological model systems. The workflow includes three chromatographic methods combined with isotope dilution tandem mass spectrometry to allow for absolute quantification of 68 metabolites of glycolysis, the pentose phosphate pathway, the tricarboxylic acid cycle, and the amino acid and (deoxy) nucleoside pools. The biological model systems; Bacillus subtilis, Saccharomyces cerevisiae, two microalgal species, and four human cell lines were all cultured in commonly applied culture media and sampled in exponential growth phase. Both literature and databases are scarce with comprehensive metabolite datasets, and existing entries range over several orders of magnitude. The workflow and metabolite panel presented herein can be employed to expand the list of reference metabolomes, as encouraged by the metabolomics community, in a continued effort to develop and refine high-quality quantitative metabolomics workflows.
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Peppoloni S, Pericolini E, Colombari B, Pinetti D, Cermelli C, Fini F, Prati F, Caselli E, Blasi E. The β-Lactamase Inhibitor Boronic Acid Derivative SM23 as a New Anti- Pseudomonas aeruginosa Biofilm. Front Microbiol 2020; 11:35. [PMID: 32117094 PMCID: PMC7018986 DOI: 10.3389/fmicb.2020.00035] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 01/09/2020] [Indexed: 12/15/2022] Open
Abstract
Pseudomonas aeruginosa is a Gram-negative nosocomial pathogen, often causative agent of severe device-related infections, given its great capacity to form biofilm. P. aeruginosa finely regulates the expression of numerous virulence factors, including biofilm production, by Quorum Sensing (QS), a cell-to-cell communication mechanism used by many bacteria. Selective inhibition of QS-controlled pathogenicity without affecting bacterial growth may represent a novel promising strategy to overcome the well-known and widespread drug resistance of P. aeruginosa. In this study, we investigated the effects of SM23, a boronic acid derivate specifically designed as β-lactamase inhibitor, on biofilm formation and virulence factors production by P. aeruginosa. Our results indicated that SM23: (1) inhibited biofilm development and production of several virulence factors, such as pyoverdine, elastase, and pyocyanin, without affecting bacterial growth; (2) decreased the levels of 3-oxo-C12-HSL and C4-HSL, two QS-related autoinducer molecules, in line with a dampened lasR/lasI system; (3) failed to bind to bacterial cells that had been preincubated with P. aeruginosa-conditioned medium; and (4) reduced both biofilm formation and pyoverdine production by P. aeruginosa onto endotracheal tubes, as assessed by a new in vitro model closely mimicking clinical settings. Taken together, our results indicate that, besides inhibiting β-lactamase, SM23 can also act as powerful inhibitor of P. aeruginosa biofilm, suggesting that it may have a potential application in the prevention and treatment of biofilm-associated P. aeruginosa infections.
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Affiliation(s)
- Samuele Peppoloni
- Department of Surgical, Medical, Dental and Morphological Sciences With Interest in Transplant, Oncological and Regenerative Medicine, University of Modena and Reggio Emilia, Modena, Italy
| | - Eva Pericolini
- Department of Surgical, Medical, Dental and Morphological Sciences With Interest in Transplant, Oncological and Regenerative Medicine, University of Modena and Reggio Emilia, Modena, Italy
| | - Bruna Colombari
- Department of Surgical, Medical, Dental and Morphological Sciences With Interest in Transplant, Oncological and Regenerative Medicine, University of Modena and Reggio Emilia, Modena, Italy
| | - Diego Pinetti
- Centro Interdipartimentale "Grandi Strumenti" (CIGS), University of Modena and Reggio Emilia, Modena, Italy
| | - Claudio Cermelli
- Department of Surgical, Medical, Dental and Morphological Sciences With Interest in Transplant, Oncological and Regenerative Medicine, University of Modena and Reggio Emilia, Modena, Italy
| | - Francesco Fini
- Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Fabio Prati
- Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Emilia Caselli
- Department of Life Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Elisabetta Blasi
- Department of Surgical, Medical, Dental and Morphological Sciences With Interest in Transplant, Oncological and Regenerative Medicine, University of Modena and Reggio Emilia, Modena, Italy
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Khan S, Ince-Dunn G, Suomalainen A, Elo LL. Integrative omics approaches provide biological and clinical insights: examples from mitochondrial diseases. J Clin Invest 2020; 130:20-28. [PMID: 31895050 PMCID: PMC6934214 DOI: 10.1172/jci129202] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
High-throughput technologies for genomics, transcriptomics, proteomics, and metabolomics, and integrative analysis of these data, enable new, systems-level insights into disease pathogenesis. Mitochondrial diseases are an excellent target for hypothesis-generating omics approaches, as the disease group is mechanistically exceptionally complex. Although the genetic background in mitochondrial diseases is in either the nuclear or the mitochondrial genome, the typical downstream effect is dysfunction of the mitochondrial respiratory chain. However, the clinical manifestations show unprecedented variability, including either systemic or tissue-specific effects across multiple organ systems, with mild to severe symptoms, and occurring at any age. So far, the omics approaches have provided mechanistic understanding of tissue-specificity and potential treatment options for mitochondrial diseases, such as metabolome remodeling. However, no curative treatments exist, suggesting that novel approaches are needed. In this Review, we discuss omics approaches and discoveries with the potential to elucidate mechanisms of and therapies for mitochondrial diseases.
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Affiliation(s)
- Sofia Khan
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
| | - Gulayse Ince-Dunn
- Research Programs Unit, Stem Cells and Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Anu Suomalainen
- Research Programs Unit, Stem Cells and Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Neuroscience Center, HiLife, University of Helsinki, Helsinki, Finland
- Helsinki University Hospital, HUSlab, Helsinki, Finland
| | - Laura L. Elo
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
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Modified Protocol of Harvesting, Extraction, and Normalization Approaches for Gas Chromatography Mass Spectrometry-Based Metabolomics Analysis of Adherent Cells Grown Under High Fetal Calf Serum Conditions. Metabolites 2019; 10:metabo10010002. [PMID: 31861324 PMCID: PMC7023238 DOI: 10.3390/metabo10010002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Revised: 12/09/2019] [Accepted: 12/11/2019] [Indexed: 12/22/2022] Open
Abstract
A gas chromatography mass spectrometry (GC-MS) metabolomics protocol was modified for quenching, harvesting, and extraction of metabolites from adherent cells grown under high (20%) fetal calf serum conditions. The reproducibility of using either 50% or 80% methanol for quenching of cells was compared for sample harvest. To investigate the efficiency and reproducibility of intracellular metabolite extraction, different volumes and ratios of chloroform were tested. Additionally, we compared the use of total protein amount versus cell mass as normalization parameters. We demonstrate that the method involving 50% methanol as quenching buffer followed by an extraction step using an equal ratio of methanol:chloroform:water (1:1:1, v/v/v) followed by the collection of 6 mL polar phase for GC-MS measurement was superior to the other methods tested. Especially for large sample sets, its comparative ease of measurement leads us to recommend normalization to protein amount for the investigation of intracellular metabolites of adherent human cells grown under high (or standard) fetal calf serum conditions. To avoid bias, care should be taken beforehand to ensure that the ratio of total protein to cell number are consistent among the groups tested. For this reason, it may not be suitable where culture conditions or cell types have very different protein outputs (e.g., hypoxia vs. normoxia). The full modified protocol is available in the Supplementary Materials.
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Ammonium fluoride-induced stabilization for anion attachment mass spectrometry: Facilitating the pseudotargeted profiling of bile acids submetabolome. Anal Chim Acta 2019; 1081:120-130. [DOI: 10.1016/j.aca.2019.07.006] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 06/30/2019] [Accepted: 07/04/2019] [Indexed: 01/06/2023]
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Ali A, Abouleila Y, Shimizu Y, Hiyama E, Emara S, Mashaghi A, Hankemeier T. Single-cell metabolomics by mass spectrometry: Advances, challenges, and future applications. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2019.02.033] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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Cheung PK, Ma MH, Tse HF, Yeung KF, Tsang HF, Chu MKM, Kan CM, Cho WCS, Ng LBW, Chan LWC, Wong SCC. The applications of metabolomics in the molecular diagnostics of cancer. Expert Rev Mol Diagn 2019; 19:785-793. [PMID: 31414918 DOI: 10.1080/14737159.2019.1656530] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2019] [Accepted: 08/13/2019] [Indexed: 02/06/2023]
Abstract
Introduction: Metabolomics, the study of metabolites, is a promising research field for cancers. The metabolic pathway in a tumor cell is different from a normal tissue cell. There are two approaches to study the metabolism, targeted and untargeted. The general approach is that metabolomic data are interpreted by bioinformatics tools correlating with metabolomic databases to obtain significant findings. With the use of specific analysis tools, such as nuclear magnetic resonance (NMR) and mass spectrometer (MS) combined with chromatography, metabolic profile or metabolic fingerprint of various biological specimens could be obtained. The applications of metabolomics are used to discover potential cancer biomarkers and monitor the metastatic state, therapeutic and drug response for better patient management. Areas covered: In this review, the author introduce metabolomics and discuss the use of metabolomics approaches in different cancers, including the study of colorectal cancer, prostate cancer, liver cancer, pancreatic cancer and breast cancer using NMR and MS. Expert opinion: Knowledge on the molecular basis of cancer metabolism and its potential clinical applications has been improving recently. However, there are still many challenges for the technological development and integration of metabolomics with other omics spaces such as genomics. In the near future, it is expected that metabolomics will play an important role in cancer molecular diagnostics.
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Affiliation(s)
- Pro Kit Cheung
- Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University , Kowloon , Hong Kong Special Administrative Region , China
| | - Man Hin Ma
- Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University , Kowloon , Hong Kong Special Administrative Region , China
| | - Hing Fung Tse
- Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University , Kowloon , Hong Kong Special Administrative Region , China
| | - Ka Fai Yeung
- Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University , Kowloon , Hong Kong Special Administrative Region , China
| | - Hin Fung Tsang
- Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University , Kowloon , Hong Kong Special Administrative Region , China
| | - Man Kee Maggie Chu
- Department of Life Science, The Hong Kong University of Science and Technology , Clear Water Bay , Hong Kong Special Administrative Region , China
| | - Chau Ming Kan
- Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University , Kowloon , Hong Kong Special Administrative Region , China
| | - William Chi Shing Cho
- Department of Clinical Oncology, Queen Elizabeth Hospital , Kowloon , Hong Kong Special Administrative Region , China
| | - Lawrence Bo Wah Ng
- Department of Pathology, Queen Elizabeth Hospital , Kowloon , Hong Kong Special Administrative Region , China
| | - Lawrence Wing Chi Chan
- Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University , Kowloon , Hong Kong Special Administrative Region , China
| | - Sze Chuen Cesar Wong
- Department of Health Technology and Informatics, Faculty of Health and Social Sciences, The Hong Kong Polytechnic University , Kowloon , Hong Kong Special Administrative Region , China
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de Wet T, Warner DF, Mizrahi V. Harnessing Biological Insight to Accelerate Tuberculosis Drug Discovery. Acc Chem Res 2019; 52:2340-2348. [PMID: 31361123 PMCID: PMC6704484 DOI: 10.1021/acs.accounts.9b00275] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2019] [Indexed: 12/12/2022]
Abstract
Tuberculosis (TB) is the leading cause of mortality globally resulting from an infectious disease, killing almost 1.6 million people annually and accounting for approximately 30% of deaths attributed to antimicrobial resistance (AMR). This despite the widespread administration of a neonatal vaccine, and the availability of an effective combination drug therapy against the causative agent, Mycobacterium tuberculosis (Mtb). Instead, TB prevalence worldwide is characterized by high-burden regions in which co-epidemics, such as HIV, and social and economic factors, undermine efforts to control TB. These elements additionally ensure conditions that favor the emergence of drug-resistant Mtb strains, which further threaten prospects for future TB control. To address this challenge, significant resources have been invested in developing a TB drug pipeline, an initiative given impetus by the recent regulatory approval of two new anti-TB drugs. However, both drugs have been reserved for drug-resistant disease, and the seeming inevitability of new resistance plus the recognized need to shorten the duration of chemotherapy demands continual replenishment of the pipeline with high-quality "hits" with novel mechanisms of action. This represents a massive challenge, which has been undermined by key gaps in our understanding of Mtb physiology and metabolism, especially during host infection. Whereas drug discovery for other bacterial infections can rely on predictive in vitro assays and animal models, for Mtb, inherent metabolic flexibility and uncertainties about the nutrients available to infecting bacilli in different host (micro)environments instead requires educated predictions or demonstrations of efficacy in animal models of arguable relevance to human disease. Even microbiological methods for enumeration of viable mycobacterial cells are fraught with complication. Our research has focused on elucidating those aspects of mycobacterial metabolism that contribute to the robustness of the bacillus to host immunological defenses and applied antibiotics and that, possibly, drive the emergence of drug resistance. This work has identified a handful of metabolic pathways that appear vulnerable to antibiotic targeting. Those highlighted, here, include the inter-related functions of pantothenate and coenzyme A biosynthesis and recycling and nucleotide metabolism-the last of which reinforces our view that DNA metabolism constitutes an under-explored area for new TB drug development. Although nonessential functions have traditionally been deprioritized for antibiotic development, a common theme emerging from this work is that these very functions might represent attractive targets because of the potential to cripple mechanisms critical to bacillary survival under stress (for example, the RelMtb-dependent stringent response) or to adaptability under unfavorable, potentially lethal, conditions including antibiotic therapy (for example, DnaE2-dependent SOS mutagenesis). The bar, however, is high: demonstrating convincingly the likely efficacy of this strategy will require innovative models of human TB disease. In the concluding section, we focus on the need for improved techniques to elucidate mycobacterial metabolism during infection and its impact on disease outcomes. Here, we argue that developments in other fields suggest the potential to break through this barrier by harnessing chemical-biology approaches in tandem with the most advanced technologies. As researchers based in a high-burden country, we are impelled to continue participating in this important endeavor.
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Affiliation(s)
- Timothy
J. de Wet
- SAMRC/NHLS/UCT
Molecular Mycobacteriology Research Unit and DST/NRF Centre of Excellence
for Biomedical TB Research, Department of Pathology and Institute
of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, Cape Town 7925, South
Africa
- Department
of Integrative Biomedical Sciences, University
of Cape Town, Observatory, Cape Town 7925, South
Africa
| | - Digby F. Warner
- SAMRC/NHLS/UCT
Molecular Mycobacteriology Research Unit and DST/NRF Centre of Excellence
for Biomedical TB Research, Department of Pathology and Institute
of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, Cape Town 7925, South
Africa
- Wellcome
Centre for Infectious Disease Research in Africa, University of Cape Town, Observatory, Cape Town 7925, South
Africa
| | - Valerie Mizrahi
- SAMRC/NHLS/UCT
Molecular Mycobacteriology Research Unit and DST/NRF Centre of Excellence
for Biomedical TB Research, Department of Pathology and Institute
of Infectious Disease and Molecular Medicine, University of Cape Town, Observatory, Cape Town 7925, South
Africa
- Wellcome
Centre for Infectious Disease Research in Africa, University of Cape Town, Observatory, Cape Town 7925, South
Africa
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Advances and challenges in development of precision psychiatry through clinical metabolomics on mood and psychotic disorders. Prog Neuropsychopharmacol Biol Psychiatry 2019; 93:182-188. [PMID: 30904564 DOI: 10.1016/j.pnpbp.2019.03.010] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Revised: 02/21/2019] [Accepted: 03/20/2019] [Indexed: 01/14/2023]
Abstract
Metabolomics is defined as the study of the global metabolite profile in a system under a given set of conditions. The objective of this review is to comprehensively assess the literature on metabolomics in mood disorders and schizophrenia and provide data for mental health researchers about the challenges and potentials of metabolomics. The majority of studies in metabolomics in Psychiatry uses peripheral blood or urine. The most widely used analytical techniques in metabolomics research are nuclear magnetic resonance (NMR) and mass spectrometry (MS). They are multiparametric and provide extensive structural and conformational information on multiple chemical classes. NMR is useful in untargeted analysis, which focuses on biosignatures or 'metabolic fingerprints' of illnesses. MS targeted metabolomics approach focuses on the identification and quantification of selected metabolites known to be involved in a particular metabolic pathway. The available studies of metabolomics in Schizophrenia, Bipolar Disorder and Major Depressive Disorder suggest a potential in investigating metabolic pathways involved in these diseases' pathophysiology and response to treatment, as well as its potential in biomarkers identification.
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Kervezee L, Cermakian N, Boivin DB. Individual metabolomic signatures of circadian misalignment during simulated night shifts in humans. PLoS Biol 2019; 17:e3000303. [PMID: 31211770 PMCID: PMC6581237 DOI: 10.1371/journal.pbio.3000303] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 05/15/2019] [Indexed: 02/07/2023] Open
Abstract
Misalignment of the daily sleep-wake and fasting-feeding cycles with the endogenous circadian timing system is an inevitable consequence of night shift work and is associated with adverse metabolic health effects. However, a detailed characterisation of the effects of night shifts on 24-h rhythms in the metabolome is missing. We performed targeted metabolomic profiling on plasma samples collected every 2 h from healthy human subjects during two 24-h measurement periods at baseline and on the fourth day of a simulated night shift protocol, in which the habitual sleep-wake cycle was delayed by 10 h. Thirty-two out of the 130 detected metabolites showed a 24-h rhythm both at baseline and during the night shift condition. Among these, 75% were driven by sleep-wake and fasting-feeding cycles rather than by the endogenous circadian clock, showing an average phase delay of 8.8 h during the night shift condition. Hence, the majority of rhythmic metabolites were misaligned relative to the endogenous circadian system during the night shift condition. This could be a key mechanism involved in the increased prevalence of adverse metabolic health effects observed in shift workers. On the individual level, the response to the night shift protocol was highly diverse, with phase shifts of rhythmic metabolite profiles ranging from a 0.2-h advance in one subject to a 12-h delay in another subject, revealing an individual metabolomic signature of circadian misalignment. Our findings provide insight into the overall and individual responses of the metabolome to circadian misalignment associated with night schedules and may thereby contribute to the development of individually tailored strategies to minimise the metabolic impacts of shift work. A study of simulated night shifts in humans shows that 24-hour rhythms in plasma metabolites are primarily influenced by behavioural cycles rather than the endogenous clock; in addition, a large degree of variability between individuals suggests the existence of individual metabolomic signatures of circadian misalignment.
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Affiliation(s)
- Laura Kervezee
- Centre for Study and Treatment of Circadian Rhythms, Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Canada
- Laboratory of Molecular Chronobiology, Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Canada
| | - Nicolas Cermakian
- Laboratory of Molecular Chronobiology, Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Canada
- * E-mail: (NC); (DBB)
| | - Diane B. Boivin
- Centre for Study and Treatment of Circadian Rhythms, Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Canada
- * E-mail: (NC); (DBB)
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Laíns I, Gantner M, Murinello S, Lasky-Su JA, Miller JW, Friedlander M, Husain D. Metabolomics in the study of retinal health and disease. Prog Retin Eye Res 2018; 69:57-79. [PMID: 30423446 DOI: 10.1016/j.preteyeres.2018.11.002] [Citation(s) in RCA: 107] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 10/06/2018] [Accepted: 11/07/2018] [Indexed: 02/06/2023]
Abstract
Metabolomics is the qualitative and quantitative assessment of the metabolites (small molecules < 1.5 kDa) in body fluids. The metabolites are the downstream of the genetic transcription and translation processes and also downstream of the interactions with environmental exposures; thus, they are thought to closely relate to the phenotype, especially for multifactorial diseases. In the last decade, metabolomics has been increasingly used to identify biomarkers in disease, and it is currently recognized as a very powerful tool with great potential for clinical translation. The metabolome and the associated pathways also help improve our understanding of the pathophysiology and mechanisms of disease. While there has been increasing interest and research in metabolomics of the eye, the application of metabolomics to retinal diseases has been limited, even though these are leading causes of blindness. In this manuscript, we perform a comprehensive summary of the tools and knowledge required to perform a metabolomics study, and we highlight essential statistical methods for rigorous study design and data analysis. We review available protocols, summarize the best approaches, and address the current unmet need for information on collection and processing of tissues and biofluids that can be used for metabolomics of retinal diseases. Additionally, we critically analyze recent work in this field, both in animal models and in human clinical disease, including diabetic retinopathy and age-related macular degeneration. Finally, we identify opportunities for future research applying metabolomics to improve our current assessment and understanding of mechanisms of vitreoretinal diseases, and to hence improve patient assessment and care.
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Affiliation(s)
- Inês Laíns
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, 02114, United States; Faculty of Medicine, University of Coimbra, 3000 Coimbra, Portugal.
| | - Mari Gantner
- Lowy Medical Research Institute, La Jolla, CA, 92037, United States; Scripps Research Institute, La Jolla, CA, 92037, United States.
| | - Salome Murinello
- Lowy Medical Research Institute, La Jolla, CA, 92037, United States; Scripps Research Institute, La Jolla, CA, 92037, United States.
| | - Jessica A Lasky-Su
- Systems Genetics and Genomics Unit, Channing Division of Network Medicine Brigham and Women's Hospital and Harvard Medical School, 75 Francis Street, Boston, MA, 02115, United States.
| | - Joan W Miller
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, 02114, United States.
| | - Martin Friedlander
- Lowy Medical Research Institute, La Jolla, CA, 92037, United States; Scripps Research Institute, La Jolla, CA, 92037, United States.
| | - Deeba Husain
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, 02114, United States.
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Quenching for Microalgal Metabolomics: A Case Study on the Unicellular Eukaryotic Green Alga Chlamydomonas reinhardtii. Metabolites 2018; 8:metabo8040072. [PMID: 30384421 PMCID: PMC6315863 DOI: 10.3390/metabo8040072] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2018] [Revised: 10/25/2018] [Accepted: 10/29/2018] [Indexed: 11/30/2022] Open
Abstract
Capturing a valid snapshot of the metabolome requires rapid quenching of enzyme activities. This is a crucial step in order to halt the constant flux of metabolism and high turnover rate of metabolites. Quenching with cold aqueous methanol is treated as a gold standard so far, however, reliability of metabolomics data obtained is in question due to potential problems connected to leakage of intracellular metabolites. Therefore, we investigated the influence of various parameters such as quenching solvents, methanol concentration, inclusion of buffer additives, quenching time and solvent to sample ratio on intracellular metabolite leakage from Chlamydomonas reinhardtii. We measured the recovery of twelve metabolite classes using gas chromatography mass spectrometry (GC-MS) in all possible fractions and established mass balance to trace the fate of metabolites during quenching treatments. Our data demonstrate significant loss of intracellular metabolites with the use of the conventional 60% methanol, and that an increase in methanol concentration or quenching time also resulted in higher leakage. Inclusion of various buffer additives showed 70 mM HEPES (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid) to be suitable. In summary, we recommend quenching with 60% aqueous methanol supplemented with 70 mM HEPES (−40 °C) at 1:1 sample to quenching solvent ratio, as it resulted in higher recoveries for intracellular metabolites with subsequent reduction in the metabolite leakage for all metabolite classes.
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Guan Y, Yin D, Du X, Ye X. Functional metabolomics approach reveals the reduced biosynthesis of fatty acids and TCA cycle is required for pectinase activity in Bacillus licheniformis. J Ind Microbiol Biotechnol 2018; 45:951-960. [PMID: 30178168 DOI: 10.1007/s10295-018-2071-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2018] [Accepted: 08/16/2018] [Indexed: 02/07/2023]
Abstract
Increase of pectinase activity is especially important in fermentation industry. Understanding of the metabolic mechanisms can find metabolic modulation approach to promote high yield of pectinase. Higher activity of pectinase was detected in DY1 than DY2, two strains of Bacillus licheniformis. GC-MS-based metabolomics identified differential metabolome of DY2 compared with DY1, characterizing the increased TCA cycle and biosynthesis of fatty acids. Elevated activity of pyruvate dehydrogenase (PDH), α-ketoglutaric dehydrogenase (KGDH) and succinate dehydrogenase (SDH) showed global elevation of carbon metabolism, which is consistent with the result that lowers glucose in DY2 than DY1. Inhibitors malonate, furfural and triclosan, of PDH, SDH and biosynthesis of fatty acids, promoted pectinase activity, where triclosan increased pectinase activity by 179%. These results indicate that functional metabolomics is an effective approach to understand metabolic mechanisms of fermentation production and provides clues to develop new methods for changing bacterial physiology and production.
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Affiliation(s)
- Yi Guan
- Fujian Key Laboratory of Marine Enzyme Engineering, College of Biological Sciences and Technology, Fuzhou University, No. 2 Xue Yuan Road, Fuzhou, 350108, Fujian, China.
| | - Di Yin
- Fujian Key Laboratory of Marine Enzyme Engineering, College of Biological Sciences and Technology, Fuzhou University, No. 2 Xue Yuan Road, Fuzhou, 350108, Fujian, China
| | - Xi Du
- Fujian Key Laboratory of Marine Enzyme Engineering, College of Biological Sciences and Technology, Fuzhou University, No. 2 Xue Yuan Road, Fuzhou, 350108, Fujian, China
| | - Xiuyun Ye
- Fujian Key Laboratory of Marine Enzyme Engineering, College of Biological Sciences and Technology, Fuzhou University, No. 2 Xue Yuan Road, Fuzhou, 350108, Fujian, China.
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