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Song D, Tang T, Wang R, Liu H, Xie D, Zhao B, Dang Z, Lu G. Enhancing compound confidence in suspect and non-target screening through machine learning-based retention time prediction. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 347:123763. [PMID: 38492749 DOI: 10.1016/j.envpol.2024.123763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 02/26/2024] [Accepted: 03/09/2024] [Indexed: 03/18/2024]
Abstract
The retention time (RT) of contaminants of emerging concern (CECs) in liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is crucial for database matching in non-targeted screening (NTS) analysis. In this study, we developed a machine learning (ML) model to predict RTs of CECs in NTS analysis. Using 1051 CEC standards, we evaluated Random Forest (RF), XGBoost, Support Vector Regression (SVR), and Artificial Neural Network (ANN) with molecular fingerprints and chemical descriptors to establish an optimal model. The SVR model utilizing chemical descriptors resulted in good predictive capacity with R2ext = 0.850 and r2 = 0.925. The model was further validated through laboratory NTS compound characterization. When applied to examine CEC occurrence in a large wastewater treatment plant, we identified 40 level S1 CECs (confirmed structure by reference standard) and 234 level S2 compounds (probable structure by library spectrum match). The model predicted RTs for level S2 compounds, leading to the classification of 153 level S2 compounds with high confidence (ΔRT <2 min). The model served as a robust filtering mechanism within the analytical framework. This study emphasizes the importance of predicted RTs in NTS analysis and highlights the potential of prediction models. Our research introduces a workflow that enhances NTS analysis by utilizing RT prediction models to determine compound confidence levels.
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Affiliation(s)
- Dehao Song
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China
| | - Ting Tang
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China; The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, South China University of Technology, Guangzhou, 510006, China.
| | - Rui Wang
- South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou, 510655, China; Guangxi Key Laboratory of Emerging Contaminants Monitoring, Early Warning and Environmental Health Risk Assessment, Nanning, 530000, China
| | - He Liu
- South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou, 510655, China; Guangxi Key Laboratory of Emerging Contaminants Monitoring, Early Warning and Environmental Health Risk Assessment, Nanning, 530000, China
| | - Danping Xie
- South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou, 510655, China; Guangxi Key Laboratory of Emerging Contaminants Monitoring, Early Warning and Environmental Health Risk Assessment, Nanning, 530000, China
| | - Bo Zhao
- South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou, 510655, China; Guangxi Key Laboratory of Emerging Contaminants Monitoring, Early Warning and Environmental Health Risk Assessment, Nanning, 530000, China
| | - Zhi Dang
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China; Guangdong Provincial Key Laboratory of Solid Wastes Pollution Control and Recycling, South China University of Technology, Guangzhou, 510006, China; The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, South China University of Technology, Guangzhou, 510006, China
| | - Guining Lu
- School of Environment and Energy, South China University of Technology, Guangzhou, 510006, China; The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, South China University of Technology, Guangzhou, 510006, China
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2
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Tait JR, Anderson D, Nation RL, Creek DJ, Landersdorfer CB. Identifying and mathematically modeling the time-course of extracellular metabolic markers associated with resistance to ceftolozane/tazobactam in Pseudomonas aeruginosa. Antimicrob Agents Chemother 2024; 68:e0108123. [PMID: 38376189 PMCID: PMC10989016 DOI: 10.1128/aac.01081-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Accepted: 01/11/2024] [Indexed: 02/21/2024] Open
Abstract
Extracellular bacterial metabolites have potential as markers of bacterial growth and resistance emergence but have not been evaluated in dynamic in vitro studies. We investigated the dynamic metabolomic footprint of a multidrug-resistant hypermutable Pseudomonas aeruginosa isolate exposed to ceftolozane/tazobactam as continuous infusion (4.5 g/day, 9 g/day) in a hollow-fiber infection model over 7-9 days in biological replicates (n = 5). Bacterial samples were collected at 0, 7, 23, 47, 71, 95, 143, 167, 191, and 215 h, the supernatant quenched, and extracellular metabolites extracted. Metabolites were analyzed via untargeted metabolomics, including hierarchical clustering and correlation with quantified total and resistant bacterial populations. The time-courses of five (of 1,921 detected) metabolites from enriched pathways were mathematically modeled. Absorbed L-arginine and secreted L-ornithine were highly correlated with the total bacterial population (r -0.79 and 0.82, respectively, P<0.0001). Ribose-5-phosphate, sedoheptulose-7-phosphate, and trehalose-6-phosphate correlated with the resistant subpopulation (0.64, 0.64, and 0.67, respectively, P<0.0001) and were likely secreted due to resistant growth overcoming oxidative and osmotic stress induced by ceftolozane/tazobactam. Using pharmacokinetic/pharmacodynamic-based transduction models, these metabolites were successfully modeled based on the total or resistant bacterial populations. The models well described the abundance of each metabolite across the differing time-course profiles of biological replicates, based on bacterial killing and, importantly, resistant regrowth. These proof-of-concept studies suggest that further exploration is warranted to determine the generalizability of these findings. The metabolites modeled here are not exclusive to bacteria. Future studies may use this approach to identify bacteria-specific metabolites correlating with resistance, which would ultimately be extremely useful for clinical translation.
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Affiliation(s)
- Jessica R. Tait
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
| | - Dovile Anderson
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
| | - Roger L. Nation
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
| | - Darren J. Creek
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
| | - Cornelia B. Landersdorfer
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
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3
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Martelli F, Lin J, Mele S, Imlach W, Kanca O, Barlow CK, Paril J, Schittenhelm RB, Christodoulou J, Bellen HJ, Piper MDW, Johnson TK. Identifying potential dietary treatments for inherited metabolic disorders using Drosophila nutrigenomics. Cell Rep 2024; 43:113861. [PMID: 38416643 PMCID: PMC11037929 DOI: 10.1016/j.celrep.2024.113861] [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: 05/16/2023] [Revised: 12/09/2023] [Accepted: 02/08/2024] [Indexed: 03/01/2024] Open
Abstract
Inherited metabolic disorders are a group of genetic conditions that can cause severe neurological impairment and child mortality. Uniquely, these disorders respond to dietary treatment; however, this option remains largely unexplored because of low disorder prevalence and the lack of a suitable paradigm for testing diets. Here, we screened 35 Drosophila amino acid disorder models for disease-diet interactions and found 26 with diet-altered development and/or survival. Using a targeted multi-nutrient array, we examine the interaction in a model of isolated sulfite oxidase deficiency, an infant-lethal disorder. We show that dietary cysteine depletion normalizes their metabolic profile and rescues development, neurophysiology, behavior, and lifelong fly survival, thus providing a basis for further study into the pathogenic mechanisms involved in this disorder. Our work highlights the diet-sensitive nature of metabolic disorders and establishes Drosophila as a valuable tool for nutrigenomic studies for informing potential dietary therapies.
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Affiliation(s)
- Felipe Martelli
- School of Biological Sciences, Monash University, Clayton, VIC 3800, Australia
| | - Jiayi Lin
- School of Biological Sciences, Monash University, Clayton, VIC 3800, Australia
| | - Sarah Mele
- School of Biological Sciences, Monash University, Clayton, VIC 3800, Australia
| | - Wendy Imlach
- Department of Physiology, Monash Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Oguz Kanca
- Department of Molecular and Human Genetics and Duncan Neurological Research Institute at Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA
| | - Christopher K Barlow
- Monash Proteomics & Metabolomics Facility, Monash Biomedicine Discovery Institute & Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia
| | - Jefferson Paril
- School of BioSciences, The University of Melbourne, Melbourne, VIC 3052, Australia
| | - Ralf B Schittenhelm
- Monash Proteomics & Metabolomics Facility, Monash Biomedicine Discovery Institute & Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia
| | - John Christodoulou
- Murdoch Children's Research Institute, Parkville, VIC 3052, Australia; Department of Paediatrics, The University of Melbourne, Melbourne, VIC 3052, Australia
| | - Hugo J Bellen
- Department of Molecular and Human Genetics and Duncan Neurological Research Institute at Texas Children's Hospital, Baylor College of Medicine, Houston, TX, USA
| | - Matthew D W Piper
- School of Biological Sciences, Monash University, Clayton, VIC 3800, Australia.
| | - Travis K Johnson
- School of Biological Sciences, Monash University, Clayton, VIC 3800, Australia; Department of Biochemistry and Chemistry and La Trobe Institute for Molecular Science, La Trobe University, Bundoora, VIC 3086, Australia.
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4
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Martelli F, Quig A, Mele S, Lin J, Fulton TL, Wansbrough M, Barlow CK, Schittenhelm RB, Johnson TK, Piper MDW. A defined diet for pre-adult Drosophila melanogaster. Sci Rep 2024; 14:6974. [PMID: 38521863 PMCID: PMC10960813 DOI: 10.1038/s41598-024-57681-z] [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: 10/17/2023] [Accepted: 03/20/2024] [Indexed: 03/25/2024] Open
Abstract
Drosophila melanogaster is unique among animal models because it has a fully defined synthetic diet available to study nutrient-gene interactions. However, use of this diet is limited to adult studies due to impaired larval development and survival. Here, we provide an adjusted formula that reduces the developmental period, restores fat levels, enhances body mass, and fully rescues survivorship without compromise to adult lifespan. To demonstrate an application of this formula, we explored pre-adult diet compositions of therapeutic potential in a model of an inherited metabolic disorder affecting the metabolism of branched-chain amino acids. We reveal rapid, specific, and predictable nutrient effects on the disease state consistent with observations from mouse and patient studies. Together, our diet provides a powerful means with which to examine the interplay between diet and metabolism across all life stages in an animal model.
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Affiliation(s)
- Felipe Martelli
- School of Biological Sciences, Monash University, Clayton, VIC, 3800, Australia
- School of BioSciences, The University of Melbourne, Melbourne, VIC, 3052, Australia
| | - Annelise Quig
- School of Biological Sciences, Monash University, Clayton, VIC, 3800, Australia
| | - Sarah Mele
- School of Biological Sciences, Monash University, Clayton, VIC, 3800, Australia
| | - Jiayi Lin
- School of Biological Sciences, Monash University, Clayton, VIC, 3800, Australia
| | - Tahlia L Fulton
- School of Biological Sciences, Monash University, Clayton, VIC, 3800, Australia
| | - Mia Wansbrough
- School of Biological Sciences, Monash University, Clayton, VIC, 3800, Australia
| | - Christopher K Barlow
- Monash Proteomics and Metabolomics Platform, Monash Biomedicine Discovery Institute & Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC, 3800, Australia
| | - Ralf B Schittenhelm
- Monash Proteomics and Metabolomics Platform, Monash Biomedicine Discovery Institute & Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC, 3800, Australia
| | - Travis K Johnson
- School of Biological Sciences, Monash University, Clayton, VIC, 3800, Australia.
- Department of Biochemistry and Chemistry and La Trobe Institute for Molecular Science, La Trobe University, Bundoora, VIC, 3086, Australia.
| | - Matthew D W Piper
- School of Biological Sciences, Monash University, Clayton, VIC, 3800, Australia.
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5
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Varghese S, Srivastava A, Wong SW, Le T, Pitcher N, Mesnard M, Lallemand C, Rahmani R, Moawad SR, Huang F, He T, Sleebs BE, Barrett MP, Sykes ML, Avery VM, Creek DJ, Baell JB. Novel aroyl guanidine anti-trypanosomal compounds that exert opposing effects on parasite energy metabolism. Eur J Med Chem 2024; 268:116162. [PMID: 38394930 DOI: 10.1016/j.ejmech.2024.116162] [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] [Received: 11/07/2023] [Revised: 01/05/2024] [Accepted: 01/16/2024] [Indexed: 02/25/2024]
Abstract
Human African trypanosomiasis (HAT), or sleeping sickness, is a neglected tropical disease with current treatments marred by severe side effects or delivery issues. To identify novel classes of compounds for the treatment of HAT, high throughput screening (HTS) had previously been conducted on bloodstream forms of T. b. brucei, a model organism closely related to the human pathogens T. b. gambiense and T. b. rhodesiense. This HTS had identified a number of structural classes with potent bioactivity against T. b. brucei (IC50 ≤ 10 μM) with selectivity over mammalian cell-lines (selectivity index of ≥10). One of the confirmed hits was an aroyl guanidine derivative. Deemed to be chemically tractable with attractive physicochemical properties, here we explore this class further to develop the SAR landscape. We also report the influence of the elucidated SAR on parasite metabolism, to gain insight into possible modes of action of this class. Of note, two sub-classes of analogues were identified that generated opposing metabolic responses involving disrupted energy metabolism. This knowledge may guide the future design of more potent inhibitors, while retaining the desirable physicochemical properties and an excellent selectivity profile of the current compound class.
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Affiliation(s)
- Swapna Varghese
- Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia
| | - Anubhav Srivastava
- Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia
| | - Siu Wai Wong
- Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia
| | - Thuy Le
- Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia
| | - Noel Pitcher
- Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia
| | - Mathilda Mesnard
- Ensemble Scientifique des Cézeaux, 24 avenue des Landais, 63170, Aubière, France
| | - Camille Lallemand
- Ensemble Scientifique des Cézeaux, 24 avenue des Landais, 63170, Aubière, France
| | - Raphael Rahmani
- Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia
| | - Sarah R Moawad
- The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, 3052, Victoria, Australia
| | - Fei Huang
- School of Pharmaceutical Sciences, Nanjing Tech University, No. 30 South Puzhu Road, Nanjing, 211816, China
| | - Tiantong He
- School of Pharmaceutical Sciences, Nanjing Tech University, No. 30 South Puzhu Road, Nanjing, 211816, China
| | - Brad E Sleebs
- The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, 3052, Victoria, Australia; Department of Medical Biology, The University of Melbourne, Parkville, 3010, Australia
| | - Michael P Barrett
- Wellcome Trust Centre for Molecular Parasitology, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Melissa L Sykes
- Discovery Biology, Centre for Cellular Phenomics, Griffith University, Nathan, Queensland, 4111, Australia
| | - Vicky M Avery
- Discovery Biology, Centre for Cellular Phenomics, Griffith University, Nathan, Queensland, 4111, Australia; School of Environment and Science, Griffith University, Nathan, QLD, 4111, Australia
| | - Darren J Creek
- Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia.
| | - Jonathan B Baell
- Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, 3052, Australia; School of Pharmaceutical Sciences, Nanjing Tech University, No. 30 South Puzhu Road, Nanjing, 211816, China.
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6
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Zhang Y, Liu F, Li XQ, Gao Y, Li KC, Zhang QH. Generic and accurate prediction of retention times in liquid chromatography by post-projection calibration. Commun Chem 2024; 7:54. [PMID: 38459241 PMCID: PMC10923921 DOI: 10.1038/s42004-024-01135-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 02/21/2024] [Indexed: 03/10/2024] Open
Abstract
Retention time predictions from molecule structures in liquid chromatography (LC) are increasingly used in MS-based targeted and untargeted analyses, providing supplementary evidence for molecule annotation and reducing experimental measurements. Nevertheless, different LC setups (e.g., differences in gradient, column, and/or mobile phase) give rise to many prediction models that can only accurately predict retention times for a specific chromatographic method (CM). Here, a generic and accurate method is present to predict retention times across different CMs, by introducing the concept of post-projection calibration. This concept builds on the direct projections of retention times between different CMs and uses 35 external calibrants to eliminate the impact of LC setups on projection accuracy. Results showed that post-projection calibration consistently achieved a median projection error below 3.2% of the elution time. The ranking results of putative candidates reached similar levels among different CMs. This work opens up broad possibilities for coordinating retention times between different laboratories and developing extensive retention databases.
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Affiliation(s)
- Yan Zhang
- Key Laboratory of Groundwater Conservation of MWR, China University of Geosciences, Beijing, 100083, People's Republic of China
- Division of Chemical Metrology and Analytical Science, National Institute of Metrology, Beijing, 100029, People's Republic of China
- Key Laboratory of Chemical Metrology and Applications on Nutrition and Health for State Market Regulation, Beijing, 100029, China
| | - Fei Liu
- Key Laboratory of Groundwater Conservation of MWR, China University of Geosciences, Beijing, 100083, People's Republic of China.
| | - Xiu Qin Li
- Division of Chemical Metrology and Analytical Science, National Institute of Metrology, Beijing, 100029, People's Republic of China
- Key Laboratory of Chemical Metrology and Applications on Nutrition and Health for State Market Regulation, Beijing, 100029, China
| | - Yan Gao
- Division of Chemical Metrology and Analytical Science, National Institute of Metrology, Beijing, 100029, People's Republic of China
- Key Laboratory of Chemical Metrology and Applications on Nutrition and Health for State Market Regulation, Beijing, 100029, China
| | - Kang Cong Li
- Division of Chemical Metrology and Analytical Science, National Institute of Metrology, Beijing, 100029, People's Republic of China
- Key Laboratory of Chemical Metrology and Applications on Nutrition and Health for State Market Regulation, Beijing, 100029, China
| | - Qing He Zhang
- Division of Chemical Metrology and Analytical Science, National Institute of Metrology, Beijing, 100029, People's Republic of China.
- Key Laboratory of Chemical Metrology and Applications on Nutrition and Health for State Market Regulation, Beijing, 100029, China.
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7
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Torigoe T, Takahashi M, Heravizadeh O, Ikeda K, Nakatani K, Bamba T, Izumi Y. Predicting Retention Time in Unified-Hydrophilic-Interaction/Anion-Exchange Liquid Chromatography High-Resolution Tandem Mass Spectrometry (Unified-HILIC/AEX/HRMS/MS) for Comprehensive Structural Annotation of Polar Metabolome. Anal Chem 2024; 96:1275-1283. [PMID: 38186224 DOI: 10.1021/acs.analchem.3c04618] [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: 01/09/2024]
Abstract
The accuracy of the structural annotation of unidentified peaks obtained in metabolomic analysis using liquid chromatography/tandem mass spectrometry (LC/MS/MS) can be enhanced using retention time (RT) information as well as precursor and product ions. Unified-hydrophilic-interaction/anion-exchange liquid chromatography high-resolution tandem mass spectrometry (unified-HILIC/AEX/HRMS/MS) has been recently developed as an innovative method ideal for nontargeted polar metabolomics. However, the RT prediction for unified-HILIC/AEX has not been developed because of the complex separation mechanism characterized by the continuous transition of the separation modes from HILIC to AEX. In this study, we propose an RT prediction model of unified-HILIC/AEX/HRMS/MS, which enables the comprehensive structural annotation of polar metabolites. With training data for 203 polar metabolites, we ranked the feature importance using a random forest among 12,420 molecular descriptors (MDs) and constructed an RT prediction model with 26 selected MDs. The accuracy of the RT model was evaluated using test data for 51 polar metabolites, and 86.3% of the ΔRTs (difference between measured and predicted RTs) were within ±1.50 min, with a mean absolute error of 0.80 min, indicating high RT prediction accuracy. Nontargeted metabolomic data from the NIST SRM 1950-Metabolites in frozen human plasma were analyzed using the developed RT model and in silico MS/MS prediction, resulting in a successful structural estimation of 216 polar metabolites, in addition to the 62 identified based on standards. The proposed model can help accelerate the structural annotation of unknown hydrophilic metabolites, which is a key issue in metabolomic research.
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Affiliation(s)
- Taihei Torigoe
- Department of Systems Life Sciences, Graduate School of Systems Life Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Masatomo Takahashi
- Department of Systems Life Sciences, Graduate School of Systems Life Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
- Division of Metabolomics/Mass Spectrometry Center, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Omidreza Heravizadeh
- Department of Systems Life Sciences, Graduate School of Systems Life Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Kazuki Ikeda
- Department of Systems Life Sciences, Graduate School of Systems Life Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Kohta Nakatani
- Department of Systems Life Sciences, Graduate School of Systems Life Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
- Division of Metabolomics/Mass Spectrometry Center, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Takeshi Bamba
- Department of Systems Life Sciences, Graduate School of Systems Life Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
- Division of Metabolomics/Mass Spectrometry Center, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Yoshihiro Izumi
- Department of Systems Life Sciences, Graduate School of Systems Life Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
- Division of Metabolomics/Mass Spectrometry Center, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
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Ruparelia AA, Salavaty A, Barlow CK, Lu Y, Sonntag C, Hersey L, Eramo MJ, Krug J, Reuter H, Schittenhelm RB, Ramialison M, Cox A, Ryan MT, Creek DJ, Englert C, Currie PD. The African killifish: A short-lived vertebrate model to study the biology of sarcopenia and longevity. Aging Cell 2024; 23:e13862. [PMID: 37183563 PMCID: PMC10776123 DOI: 10.1111/acel.13862] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Revised: 04/13/2023] [Accepted: 04/18/2023] [Indexed: 05/16/2023] Open
Abstract
Sarcopenia, the age-related decline in muscle function, places a considerable burden on health-care systems. While the stereotypic hallmarks of sarcopenia are well characterized, their contribution to muscle wasting remains elusive, which is partly due to the limited availability of animal models. Here, we have performed cellular and molecular characterization of skeletal muscle from the African killifish-an extremely short-lived vertebrate-revealing that while many characteristics deteriorate with increasing age, supporting the use of killifish as a model for sarcopenia research, some features surprisingly reverse to an "early-life" state in the extremely old stages. This suggests that in extremely old animals, there may be mechanisms that prevent further deterioration of skeletal muscle, contributing to an extension of life span. In line with this, we report a reduction in mortality rates in extremely old killifish. To identify mechanisms for this phenomenon, we used a systems metabolomics approach, which revealed that during aging there is a striking depletion of triglycerides, mimicking a state of calorie restriction. This results in the activation of mitohormesis, increasing Sirt1 levels, which improves lipid metabolism and maintains nutrient homeostasis in extremely old animals. Pharmacological induction of Sirt1 in aged animals was sufficient to induce a late life-like metabolic profile, supporting its role in life span extension in vertebrate populations that are naturally long-lived. Collectively, our results demonstrate that killifish are not only a novel model to study the biological processes that govern sarcopenia, but they also provide a unique vertebrate system to dissect the regulation of longevity.
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Affiliation(s)
- Avnika A. Ruparelia
- Australian Regenerative Medicine Institute, Monash UniversityClaytonAustralia
- Department of Anatomy and Physiology, School of Biomedical Sciences, Faculty of Medicine Dentistry and Health SciencesUniversity of MelbourneMelbourneAustralia
- Centre for Muscle Research, Department of Anatomy and PhysiologyUniversity of MelbourneMelbourneAustralia
| | - Adrian Salavaty
- Australian Regenerative Medicine Institute, Monash UniversityClaytonAustralia
- Systems Biology Institute Australia, Monash UniversityClaytonAustralia
| | - Christopher K. Barlow
- Department of Biochemistry and Molecular BiologyMonash UniversityClaytonAustralia
- Monash Proteomics and Metabolomics FacilityMonash Biomedicine Discovery Institute, Monash UniversityClaytonAustralia
| | - Yansong Lu
- Australian Regenerative Medicine Institute, Monash UniversityClaytonAustralia
| | - Carmen Sonntag
- Australian Regenerative Medicine Institute, Monash UniversityClaytonAustralia
| | - Lucy Hersey
- Australian Regenerative Medicine Institute, Monash UniversityClaytonAustralia
| | - Matthew J. Eramo
- Department of Biochemistry and Molecular BiologyMonash Biomedicine Discovery Institute, Monash UniversityClaytonAustralia
| | - Johannes Krug
- Leibniz Institute on Aging—Fritz Lipmann Institute (FLI)JenaGermany
| | - Hanna Reuter
- Leibniz Institute on Aging—Fritz Lipmann Institute (FLI)JenaGermany
| | - Ralf B. Schittenhelm
- Department of Biochemistry and Molecular BiologyMonash UniversityClaytonAustralia
- Monash Proteomics and Metabolomics FacilityMonash Biomedicine Discovery Institute, Monash UniversityClaytonAustralia
| | - Mirana Ramialison
- Australian Regenerative Medicine Institute, Monash UniversityClaytonAustralia
- Systems Biology Institute Australia, Monash UniversityClaytonAustralia
| | - Andrew Cox
- Peter MacCallum Cancer CentreMelbourneAustralia
- Department of Biochemistry and PharmacologyThe University of MelbourneMelbourneAustralia
| | - Michael T. Ryan
- Department of Biochemistry and Molecular BiologyMonash Biomedicine Discovery Institute, Monash UniversityClaytonAustralia
| | - Darren J. Creek
- Monash Proteomics and Metabolomics FacilityMonash Biomedicine Discovery Institute, Monash UniversityClaytonAustralia
- Drug Delivery, Disposition and DynamicsMonash Institute of Pharmaceutical Sciences, Monash UniversityParkvilleAustralia
| | - Christoph Englert
- Leibniz Institute on Aging—Fritz Lipmann Institute (FLI)JenaGermany
- Institute of Biochemistry and Biophysics, Friedrich‐Schiller‐University JenaJenaGermany
| | - Peter D. Currie
- Australian Regenerative Medicine Institute, Monash UniversityClaytonAustralia
- EMBL Australia, Victorian NodeMonash UniversityClaytonAustralia
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9
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Simwela NV, Guiguemde WA, Straimer J, Regnault C, Stokes BH, Tavernelli LE, Yokokawa F, Taft B, Diagana TT, Barrett MP, Waters AP. A conserved metabolic signature associated with response to fast-acting anti-malarial agents. Microbiol Spectr 2023; 11:e0397622. [PMID: 37800971 PMCID: PMC10714989 DOI: 10.1128/spectrum.03976-22] [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: 10/02/2022] [Accepted: 01/27/2023] [Indexed: 10/07/2023] Open
Abstract
IMPORTANCE In malaria drug discovery, understanding the mode of action of lead compounds is important as it helps in predicting the potential emergence of drug resistance in the field when these drugs are eventually deployed. In this study, we have employed metabolomics technologies to characterize the potential targets of anti-malarial drug candidates in the developmental pipeline at NITD. We show that NITD fast-acting leads belonging to spiroindolone and imidazothiadiazole class induce a common biochemical theme in drug-exposed malaria parasites which is similar to another fast-acting, clinically available drug, DHA. These biochemical features which are absent in a slower acting NITD lead (GNF17) point to hemoglobin digestion and inhibition of the pyrimidine pathway as potential action points for these drugs. These biochemical themes can be used to identify and inform on the mode of action of fast drug candidates of similar profiles in future drug discovery programs.
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Affiliation(s)
- Nelson V. Simwela
- Institute of Infection, Immunity and Inflammation, Wellcome Centre for Integrative Parasitology, University of Glasgow, Glasgow, United Kingdom
| | | | - Judith Straimer
- Novartis Institute for Tropical Diseases, Emeryville, California, USA
| | - Clement Regnault
- Institute of Infection, Immunity and Inflammation, Wellcome Centre for Integrative Parasitology, University of Glasgow, Glasgow, United Kingdom
| | - Barbara H. Stokes
- Institute of Infection, Immunity and Inflammation, Wellcome Centre for Integrative Parasitology, University of Glasgow, Glasgow, United Kingdom
| | - Luis E. Tavernelli
- Institute of Infection, Immunity and Inflammation, Wellcome Centre for Integrative Parasitology, University of Glasgow, Glasgow, United Kingdom
| | - Fumiaki Yokokawa
- Novartis Institute for Tropical Diseases, Emeryville, California, USA
| | - Benjamin Taft
- Novartis Institute for Tropical Diseases, Emeryville, California, USA
| | | | - Michael P. Barrett
- Institute of Infection, Immunity and Inflammation, Wellcome Centre for Integrative Parasitology, University of Glasgow, Glasgow, United Kingdom
| | - Andrew P. Waters
- Institute of Infection, Immunity and Inflammation, Wellcome Centre for Integrative Parasitology, University of Glasgow, Glasgow, United Kingdom
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10
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Lansink LIM, Skinner OP, Engel JA, Lee HJ, Soon MSF, Williams CG, SheelaNair A, Pernold CPS, Laohamonthonkul P, Akter J, Stoll T, Hill MM, Talman AM, Russell A, Lawniczak M, Jia X, Chua B, Anderson D, Creek DJ, Davenport MP, Khoury DS, Haque A. Systemic host inflammation induces stage-specific transcriptomic modification and slower maturation in malaria parasites. mBio 2023; 14:e0112923. [PMID: 37449844 PMCID: PMC10470790 DOI: 10.1128/mbio.01129-23] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Accepted: 06/02/2023] [Indexed: 07/18/2023] Open
Abstract
Maturation rates of malaria parasites within red blood cells (RBCs) can be influenced by host nutrient status and circadian rhythm; whether host inflammatory responses can also influence maturation remains less clear. Here, we observed that systemic host inflammation induced in mice by an innate immune stimulus, lipopolysaccharide (LPS), or by ongoing acute Plasmodium infection, slowed the progression of a single cohort of parasites from one generation of RBC to the next. Importantly, plasma from LPS-conditioned or acutely infected mice directly inhibited parasite maturation during in vitro culture, which was not rescued by supplementation, suggesting the emergence of inhibitory factors in plasma. Metabolomic assessments confirmed substantial alterations to the plasma of LPS-conditioned and acutely infected mice, and identified a small number of candidate inhibitory metabolites. Finally, we confirmed rapid parasite responses to systemic host inflammation in vivo using parasite scRNA-seq, noting broad impairment in transcriptional activity and translational capacity specifically in trophozoites but not rings or schizonts. Thus, we provide evidence that systemic host inflammation rapidly triggered transcriptional alterations in circulating blood-stage Plasmodium trophozoites and predict candidate inhibitory metabolites in the plasma that may impair parasite maturation in vivo. IMPORTANCE Malaria parasites cyclically invade, multiply, and burst out of red blood cells. We found that a strong inflammatory response can cause changes to the composition of host plasma, which directly slows down parasite maturation. Thus, our work highlights a new mechanism that limits malaria parasite growth in the bloodstream.
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Affiliation(s)
- Lianne I. M. Lansink
- QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland, Australia
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Parkville, Victoria, Australia
- School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
- Department of Biology, University of York, Wentworth Way, York, Yorkshire, United Kingdom
| | - Oliver P. Skinner
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Parkville, Victoria, Australia
| | - Jessica A. Engel
- QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland, Australia
| | - Hyun Jae Lee
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Parkville, Victoria, Australia
| | - Megan S. F. Soon
- QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland, Australia
| | - Cameron G. Williams
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Parkville, Victoria, Australia
| | - Arya SheelaNair
- QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland, Australia
| | - Clara P. S. Pernold
- QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland, Australia
| | | | - Jasmin Akter
- QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland, Australia
| | - Thomas Stoll
- QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland, Australia
| | - Michelle M. Hill
- QIMR Berghofer Medical Research Institute, Herston, Brisbane, Queensland, Australia
| | - Arthur M. Talman
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom
- MIVEGEC, University of Montpellier, IRD, CNRS, Montpellier, France
| | - Andrew Russell
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Mara Lawniczak
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - Xiaoxiao Jia
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Parkville, Victoria, Australia
| | - Brendon Chua
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Parkville, Victoria, Australia
| | - Dovile Anderson
- Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
| | - Darren J. Creek
- Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria, Australia
| | - Miles P. Davenport
- The Kirby Institute, University of New South Wales, Kensington, Sydney, New South Wales, Australia
| | - David S. Khoury
- The Kirby Institute, University of New South Wales, Kensington, Sydney, New South Wales, Australia
| | - Ashraful Haque
- Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Parkville, Victoria, Australia
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11
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Wei Y, Sun Y, Jia S, Yan P, Xiong C, Qi M, Wang C, Du Z, Jiang H. Identification of endogenous carbonyl steroids in human serum by chemical derivatization, hydrogen/deuterium exchange mass spectrometry and the quantitative structure-retention relationship. J Chromatogr B Analyt Technol Biomed Life Sci 2023; 1226:123776. [PMID: 37311272 DOI: 10.1016/j.jchromb.2023.123776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 05/09/2023] [Accepted: 05/30/2023] [Indexed: 06/15/2023]
Abstract
Steroids are tetracyclic aliphatic compounds, and most of them contain carbonyl groups. The disordered homeostasis of steroids is closely related to the occurrence and progression of various diseases. Due to high structural similarity, low concentrations in vivo, poor ionization efficiency, and interference from endogenous substances, it is very challenging to comprehensively and unambiguously identify endogenous steroids in biological matrix. Herein, an integrated strategy was developed for the characterization of endogenous steroids in serum based on chemical derivatization, ultra-performance liquid chromatography quadrupole Exactive mass spectrometry (UPLC-Q-Exactive-MS/MS), hydrogen/deuterium (H/D) exchange, and a quantitative structure-retention relationship (QSRR) model. To enhance the mass spectrometry (MS) response of carbonyl steroids, the ketonic carbonyl group was derivatized by Girard T (GT). Firstly, the fragmentation rules of derivatized carbonyl steroid standards by GT were summarized. Then, carbonyl steroids in serum were derivatized by GT and identified based on the fragmentation rules or by comparing retention time and MS/MS spectra with those of standards. H/D exchange MS was utilized to distinguish derivatized steroid isomers for the first time. Finally, a QSRR model was constructed to predict the retention time of the unknown steroid derivatives. With this strategy, 93 carbonyl steroids were identified from human serum, and 30 of them were determined to be dicarbonyl steroids by the charge number of characteristic ions and the number of exchangeable hrdrogen or comparing with standards. The QSRR model built by the machine learning algorithms has an excellent regression correlation, thus the accurate structures of 14 carbonyl steroids were determined, among which three steroids were reported for the first time in human serum. This study provides a new analytical method for the comprehensive and reliable identification of carbonyl steroids in biological matrix.
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Affiliation(s)
- Yinyu Wei
- Tongji School of Pharmacy, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yi Sun
- Tongji School of Pharmacy, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Shuailong Jia
- Department of Pharmacy, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, 430030 Wuhan, China
| | - Pan Yan
- Department of Pharmacy, The Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha 410028, China
| | - Chaomei Xiong
- Tongji School of Pharmacy, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Meiling Qi
- Tongji School of Pharmacy, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Chenxi Wang
- Tongji School of Pharmacy, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Zhifeng Du
- Tongji School of Pharmacy, Huazhong University of Science and Technology, Wuhan 430030, China.
| | - Hongliang Jiang
- Tongji School of Pharmacy, Huazhong University of Science and Technology, Wuhan 430030, China.
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12
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Wang X, Zheng F, Sheng M, Xu G, Lin X. Retention time prediction for small samples based on integrating molecular representations and adaptive network. J Chromatogr B Analyt Technol Biomed Life Sci 2023; 1217:123624. [PMID: 36780745 DOI: 10.1016/j.jchromb.2023.123624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Revised: 01/13/2023] [Accepted: 01/27/2023] [Indexed: 02/07/2023]
Abstract
Retention time (RT) can provide orthogonal information different from that of mass spectrometry and contribute to identifying compounds. Many machine learning methods have been developed and applied to RT prediction. In application, the training data size is usually small in most chromatography systems. To enhance the performance of RT prediction, this study proposes a RT prediction method based on multi-data combinations and adaptive neural network (MDC-ANN). MDC-ANN establishes the RT prediction model for the target chromatographic system through transfer learning and a base deep learning model trained on a big dataset. It selects the optimal molecular representation combination from the multiple input candidates and automatically determines the neural network structure according to the determined input combination. MDC-ANN was compared with two new efficient deep learning methods, three transferring methods and four popular machine learning methods on 14 small datasets and showed advantages in MAE, MedAE, MRE and R2 in most cases. The experiment results illustrated that integrating multiple molecular representations can provide more information, improve the performance of RT prediction and contribute to compound annotation, different chromatographic systems may use different molecular representation combinations to obtain good RT prediction performance. Hence, MDC-ANN which automatically determines the best combination of molecular representations for a specific system is promising for predicting RTs accurately in real applications.
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Affiliation(s)
- Xiaoxiao Wang
- School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, Liaoning, China
| | - Fujian Zheng
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, Liaoning, China.
| | - Meizhen Sheng
- School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, Liaoning, China
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, Liaoning, China
| | - Xiaohui Lin
- School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, Liaoning, China.
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13
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Lenski M, Maallem S, Zarcone G, Garçon G, Lo-Guidice JM, Anthérieu S, Allorge D. Prediction of a Large-Scale Database of Collision Cross-Section and Retention Time Using Machine Learning to Reduce False Positive Annotations in Untargeted Metabolomics. Metabolites 2023; 13:metabo13020282. [PMID: 36837901 PMCID: PMC9962007 DOI: 10.3390/metabo13020282] [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: 01/09/2023] [Revised: 02/07/2023] [Accepted: 02/12/2023] [Indexed: 02/18/2023] Open
Abstract
Metabolite identification in untargeted metabolomics is complex, with the risk of false positive annotations. This work aims to use machine learning to successively predict the retention time (Rt) and the collision cross-section (CCS) of an open-access database to accelerate the interpretation of metabolomic results. Standards of metabolites were tested using liquid chromatography coupled with high-resolution mass spectrometry. In CCSBase and QSRR predictor machine learning models, experimental results were used to generate predicted CCS and Rt of the Human Metabolome Database. From 542 standards, 266 and 301 compounds were detected in positive and negative electrospray ionization mode, respectively, corresponding to 380 different metabolites. CCS and Rt were then predicted using machine learning tools for almost 114,000 metabolites. R2 score of the linear regression between predicted and measured data achieved 0.938 and 0.898 for CCS and Rt, respectively, demonstrating the models' reliability. A CCS and Rt index filter of mean error ± 2 standard deviations could remove most misidentifications. Its application to data generated from a toxicology study on tobacco cigarettes reduced hits by 76%. Regarding the volume of data produced by metabolomics, the practical workflow provided allows for the implementation of valuable large-scale databases to improve the biological interpretation of metabolomics data.
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Affiliation(s)
- Marie Lenski
- ULR 4483, IMPECS—IMPact de l’Environnement Chimique sur la Santé humaine, CHU Lille, Institut Pasteur de Lille, Université de Lille, F-59000 Lille, France
- CHU Lille, Unité Fonctionnelle de Toxicologie, F-59037 Lille, France
- Correspondence:
| | - Saïd Maallem
- ULR 4483, IMPECS—IMPact de l’Environnement Chimique sur la Santé humaine, CHU Lille, Institut Pasteur de Lille, Université de Lille, F-59000 Lille, France
| | - Gianni Zarcone
- ULR 4483, IMPECS—IMPact de l’Environnement Chimique sur la Santé humaine, CHU Lille, Institut Pasteur de Lille, Université de Lille, F-59000 Lille, France
| | - Guillaume Garçon
- ULR 4483, IMPECS—IMPact de l’Environnement Chimique sur la Santé humaine, CHU Lille, Institut Pasteur de Lille, Université de Lille, F-59000 Lille, France
| | - Jean-Marc Lo-Guidice
- ULR 4483, IMPECS—IMPact de l’Environnement Chimique sur la Santé humaine, CHU Lille, Institut Pasteur de Lille, Université de Lille, F-59000 Lille, France
| | - Sébastien Anthérieu
- ULR 4483, IMPECS—IMPact de l’Environnement Chimique sur la Santé humaine, CHU Lille, Institut Pasteur de Lille, Université de Lille, F-59000 Lille, France
| | - Delphine Allorge
- ULR 4483, IMPECS—IMPact de l’Environnement Chimique sur la Santé humaine, CHU Lille, Institut Pasteur de Lille, Université de Lille, F-59000 Lille, France
- CHU Lille, Unité Fonctionnelle de Toxicologie, F-59037 Lille, France
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14
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Mass Spectrometric Methods for Non-Targeted Screening of Metabolites: A Future Perspective for the Identification of Unknown Compounds in Plant Extracts. SEPARATIONS 2022. [DOI: 10.3390/separations9120415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Phyto products are widely used in natural products, such as medicines, cosmetics or as so-called “superfoods”. However, the exact metabolite composition of these products is still unknown, due to the time-consuming process of metabolite identification. Non-target screening by LC-HRMS/MS could be a technique to overcome these problems with its capacity to identify compounds based on their retention time, accurate mass and fragmentation pattern. In particular, the use of computational tools, such as deconvolution algorithms, retention time prediction, in silico fragmentation and sophisticated search algorithms, for comparison of spectra similarity with mass spectral databases facilitate researchers to conduct a more exhaustive profiling of metabolic contents. This review aims to provide an overview of various techniques and tools for non-target screening of phyto samples using LC-HRMS/MS.
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15
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Retention Time Prediction with Message-Passing Neural Networks. SEPARATIONS 2022. [DOI: 10.3390/separations9100291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2023] Open
Abstract
Retention time prediction, facilitated by advances in machine learning, has become a useful tool in untargeted LC-MS applications. State-of-the-art approaches include graph neural networks and 1D-convolutional neural networks that are trained on the METLIN small molecule retention time dataset (SMRT). These approaches demonstrate accurate predictions comparable with the experimental error for the training set. The weak point of retention time prediction approaches is the transfer of predictions to various systems. The accuracy of this step depends both on the method of mapping and on the accuracy of the general model trained on SMRT. Therefore, improvements to both parts of prediction workflows may lead to improved compound annotations. Here, we evaluate capabilities of message-passing neural networks (MPNN) that have demonstrated outstanding performance on many chemical tasks to accurately predict retention times. The model was initially trained on SMRT, providing mean and median absolute cross-validation errors of 32 and 16 s, respectively. The pretrained MPNN was further fine-tuned on five publicly available small reversed-phase retention sets in a transfer learning mode and demonstrated up to 30% improvement of prediction accuracy for these sets compared with the state-of-the-art methods. We demonstrated that filtering isomeric candidates by predicted retention with the thresholds obtained from ROC curves eliminates up to 50% of false identities.
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16
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Al-natour M, Abdelrazig S, Ghaemmaghami AM, Alexander C, Kim DH. Metabolic Signatures of Surface-Modified Poly(lactic- co-glycolic acid) Nanoparticles in Differentiated THP-1 Cells Derived with Liquid Chromatography-Mass Spectrometry-based Metabolomics. ACS OMEGA 2022; 7:28806-28819. [PMID: 36033713 PMCID: PMC9404530 DOI: 10.1021/acsomega.2c01660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 08/03/2022] [Indexed: 06/15/2023]
Abstract
Polymeric nanoparticles (NPs) are widely used in preclinical drug delivery investigations, and some formulations are now in the clinic. However, the detailed effects of many NPs at the subcellular level have not been fully investigated. In this study, we used differentiated THP-1 macrophage cells, as a model, to investigate the metabolic changes associated with the use of poly (lactic-co-glycolic acid) (PLGA) NPs with different surface coating or conjugation chemistries. Liquid chromatography-mass spectrometry-based metabolic profiling was performed on the extracts (n = 6) of the differentiated THP-1 cells treated with plain, Pluronic (F-127, F-68, and P-85)-coated and PEG-PLGA NPs and control (no treatment). Principal component analysis and orthogonal partial least squares-discriminant analysis (OPLS-DA) in conjunction with univariate and pathway analyses were performed to identify significantly changed metabolites and pathways related to exposure of the cells to NPs. OPLS-DA of each class in the study compared to the control showed clear separation and clustering with cross-validation values of R 2 and Q 2 > 0.5. A total of 105 metabolites and lipids were found to be significantly altered in the differentiated THP-1 cell profiles due to the NP exposure, whereas more than 20 metabolic pathways were found to be affected. These pathways included glycerophospholipid, sphingolipid, linoleic acid, arginine and proline, and alpha-linolenic acid metabolisms. PLGA NPs were found to perturb some amino acid metabolic pathways and altered membrane lipids to a different degree. The metabolic effect of the PLGA NPs on the cells were comparable to those caused by silver oxide NPs and other inorganic nanomaterials. However, PEG-PLGA NPs demonstrated a reduced impact on the cellular metabolism compared to Pluronic copolymer-coated PLGA and plain PLGA NPs.
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Affiliation(s)
- Mohammad
A. Al-natour
- Molecular
Therapeutics and Formulation Division, School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, U.K.
- Division
of Pharmaceutics and Pharmaceutical Sciences, Faculty of Pharmacy, University of Petra, Amman 11196, Jordan
| | - Salah Abdelrazig
- Centre
for Analytical Bioscience, Advanced Materials and Healthcare Technologies
Division, School of Pharmacy, University
of Nottingham, Nottingham NG7 2RD, U.K.
- Department
of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Khartoum, Khartoum 11115, Sudan
| | - Amir M. Ghaemmaghami
- Immunology
& Immuno-bioengineering Group, School of Life Sciences, Faculty
of Medicine and Health Sciences, Queen’s Medical Centre, University of Nottingham, Nottingham NG7 2RD, U.K.
| | - Cameron Alexander
- Molecular
Therapeutics and Formulation Division, School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, U.K.
| | - Dong-Hyun Kim
- Centre
for Analytical Bioscience, Advanced Materials and Healthcare Technologies
Division, School of Pharmacy, University
of Nottingham, Nottingham NG7 2RD, U.K.
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17
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Lipoprotein Deprivation Reveals a Cholesterol-Dependent Therapeutic Vulnerability in Diffuse Glioma Metabolism. Cancers (Basel) 2022; 14:cancers14163873. [PMID: 36010867 PMCID: PMC9405833 DOI: 10.3390/cancers14163873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 08/03/2022] [Accepted: 08/09/2022] [Indexed: 12/01/2022] Open
Abstract
Simple Summary High-grade gliomas are aggressive cancers that arise in children and adults, for which there is an urgent need for more effective drug therapies. Targeting the energy requirements (‘metabolism’) of these cancer cells may offer a new avenue for therapy. Cholesterol is a fatty substance found on the surface of cancer cells. Our research shows that childhood high-grade gliomas require cholesterol for their energy needs. By repurposing a drug called LXR-623 to reduce the levels of cholesterol inside high-grade glioma cancer cells, we could impair the growth of these cells in laboratory conditions. These results provide evidence for future experiments using LXR-623 to test whether this drug is able to increase the survival of mice with similar high-grade gliomas. Abstract Poor outcomes associated with diffuse high-grade gliomas occur in both adults and children, despite substantial progress made in the molecular characterisation of the disease. Targeting the metabolic requirements of cancer cells represents an alternative therapeutic strategy to overcome the redundancy associated with cell signalling. Cholesterol is an integral component of cell membranes and is required by cancer cells to maintain growth and may also drive transformation. Here, we show that removal of exogenous cholesterol in the form of lipoproteins from culture medium was detrimental to the growth of two paediatric diffuse glioma cell lines, KNS42 and SF188, in association with S-phase elongation and a transcriptomic program, indicating dysregulated cholesterol homeostasis. Interrogation of metabolic perturbations under lipoprotein-deficient conditions revealed a reduced abundance of taurine-related metabolites and cholesterol ester species. Pharmacological reduction in intracellular cholesterol via decreased uptake and increased export was simulated using the liver X receptor agonist LXR-623, which reduced cellular viability in both adult and paediatric models of diffuse glioma, although the mechanism appeared to be cholesterol-independent in the latter. These results provide proof-of-principle for further assessment of liver X receptor agonists in paediatric diffuse glioma to complement the currently approved therapeutic regimens and expand the options available to clinicians to treat this highly debilitating disease.
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18
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Deore P, Barlow CK, Schittenhelm RB, Beardall J, Noronha S. Profiling of grazed cultures of the chlorophyte alga Dunaliella tertiolecta using an untargeted LC-MS approach. JOURNAL OF PHYCOLOGY 2022; 58:568-581. [PMID: 35506918 DOI: 10.1111/jpy.13254] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Accepted: 03/21/2022] [Indexed: 06/14/2023]
Abstract
Extracellular signals are reported to mediate chemical cross-talk among pelagic microbes, including microalgal prey and predators. Water-soluble mediator compounds play a crucial role in extracellular communication which is vital for prey recognition, attraction, capture, and predator deterrence. A range of exo-metabolites including oxylipins and vitamins are released by prey in response to grazing stress. The temporal dynamics of such exo-metabolites largely remains unknown, especially in large-scale cultivation of microalgae such as closed or open ponds. In open ponds, infestation of predators is almost inevitable but highly undesirable due to the imminent threat of culture collapse. The early production of exo-metabolites emitted by microalgal prey in response to predator attack could be leveraged as diagnostic markers of possible culture collapse. This study uses an untargeted approach for temporal profiling of Dunaliella tertiolecta-specific exo-metabolites under grazing pressure from Oxyrrhis marina. We report 24 putatively identified metabolites, belonging to various classes such as short peptides, lipids, indole-derivatives, and free amino acids, as potential markers of grazing-mediated stress. In addition, this study outlines a clear methodology for screening of exo-metabolites in marine algal samples, the analysis of which is frequently hindered by high salt concentrations. In future, a chemistry-based targeted detection of these metabolites could enable a quick and on-site screening of predators in microalgal cultures.
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Affiliation(s)
- Pranali Deore
- IITB-MONASH Research Academy, Mumbai, 400076, India
- School of Biological Sciences, Monash University, Clayton, Victoria, 3800, Australia
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai, 400076, India
- School of BioSciences, The University of Melbourne, Melbourne, Victoria, 3010, Australia
| | - Christopher K Barlow
- Monash Proteomic and Metabolomic Facility, Monash University, Clayton, Victoria, 3800, Australia
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, 3800, Australia
| | - Ralf B Schittenhelm
- Monash Proteomic and Metabolomic Facility, Monash University, Clayton, Victoria, 3800, Australia
| | - John Beardall
- School of Biological Sciences, Monash University, Clayton, Victoria, 3800, Australia
- Faculty of Applied Sciences, UCSI University, Kuala Lumpur, Cheras, 56000, Malaysia
| | - Santosh Noronha
- Department of Chemical Engineering, Indian Institute of Technology Bombay, Mumbai, 400076, India
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19
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Lioupi A, Virgiliou C, Walter TH, Smith KM, Rainville P, Wilson ID, Theodoridis G, Gika HG. Application of a hybrid zwitterionic hydrophilic interaction liquid chromatography column in metabolic profiling studies. J Chromatogr A 2022; 1672:463013. [DOI: 10.1016/j.chroma.2022.463013] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2021] [Revised: 03/14/2022] [Accepted: 03/30/2022] [Indexed: 01/14/2023]
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20
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An Integrated Multi-Omic Network Analysis Identifies Seizure-Associated Dysregulated Pathways in the GAERS Model of Absence Epilepsy. Int J Mol Sci 2022; 23:ijms23116063. [PMID: 35682742 PMCID: PMC9181682 DOI: 10.3390/ijms23116063] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Revised: 05/01/2022] [Accepted: 05/02/2022] [Indexed: 11/17/2022] Open
Abstract
Absence epilepsy syndromes are part of the genetic generalized epilepsies, the pathogenesis of which remains poorly understood, although a polygenic architecture is presumed. Current focus on single molecule or gene identification to elucidate epileptogenic drivers is unable to fully capture the complex dysfunctional interactions occurring at a genetic/proteomic/metabolomic level. Here, we employ a multi-omic, network-based approach to characterize the molecular signature associated with absence epilepsy-like phenotype seen in a well validated rat model of genetic generalized epilepsy with absence seizures. Electroencephalographic and behavioral data was collected from Genetic Absence Epilepsy Rats from Strasbourg (GAERS, n = 6) and non-epileptic controls (NEC, n = 6), followed by proteomic and metabolomic profiling of the cortical and thalamic tissue of rats from both groups. The general framework of weighted correlation network analysis (WGCNA) was used to identify groups of highly correlated proteins and metabolites, which were then functionally annotated through joint pathway enrichment analysis. In both brain regions a large protein-metabolite module was found to be highly associated with the GAERS strain, absence seizures and associated anxiety and depressive-like phenotype. Quantitative pathway analysis indicated enrichment in oxidative pathways and a downregulation of the lysine degradation pathway in both brain regions. GSTM1 and ALDH2 were identified as central regulatory hubs of the seizure-associated module in the somatosensory cortex and thalamus, respectively. These enzymes are involved in lysine degradation and play important roles in maintaining oxidative balance. We conclude that the dysregulated pathways identified in the seizure-associated module may be involved in the aetiology and maintenance of absence seizure activity. This dysregulated activity could potentially be modulated by targeting one or both central regulatory hubs.
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21
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Pičmanová M, Moses T, Cortada-Garcia J, Barrett G, Florance H, Pandor S, Burgess K. Rapid HILIC-Z ion mobility mass spectrometry (RHIMMS) method for untargeted metabolomics of complex biological samples. Metabolomics 2022; 18:16. [PMID: 35229219 PMCID: PMC8885480 DOI: 10.1007/s11306-022-01871-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [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: 01/19/2022] [Indexed: 11/03/2022]
Abstract
INTRODUCTION Recent advances in high-throughput methodologies in the 'omics' and synthetic biology fields call for rapid and sensitive workflows in the metabolic phenotyping of complex biological samples. OBJECTIVE The objective of this research was to evaluate a straightforward to implement LC-MS metabolomics method using a commercially available chromatography column that provides increased throughput. Reducing run time can potentially impact chromatography and therefore the effects of ion mobility spectrometry to expand peak capacity were also evaluated. Additional confidence provided via collision cross section measurements for detected features was also explored. METHODS A rapid untargeted metabolomics workflow was developed with broad metabolome coverage, combining zwitterionic-phase hydrophilic interaction chromatography (HILIC-Z) with drift tube ion mobility-quadrupole time-of-flight (DTIM-qTOF) mass spectrometry. The analytical performance of our method was explored using extracts from complex biological samples, including a reproducibility study on chicken serum and a simple comparative study on a bacterial metabolome. RESULTS The method is acronymised RHIMMS for rapid HILIC-Z ion mobility mass spectrometry. We present the RHIMMS workflow starting with data acquisition, followed by data processing and analysis. RHIMMS demonstrates improved chromatographic separation for a selection of metabolites with wide physicochemical properties while maintaining reproducibility at better than 20% over 200 injections at 3.5 min per sample for the selected metabolites, and a mean of 13.9% for the top 50 metabolites by intensity. Additionally, the combination of rapid chromatographic separation with ion mobility allows improved annotation and the ability to distinguish isobaric compounds. CONCLUSION Our results demonstrate RHIMMS to be a rapid, reproducible, sensitive and high-resolution analytical platform that is highly applicable to the untargeted metabolomics analysis of complex samples.
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Affiliation(s)
- Martina Pičmanová
- Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK
| | - Tessa Moses
- EdinOmics, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK
| | - Joan Cortada-Garcia
- Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK
| | - Georgina Barrett
- Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK
| | - Hannah Florance
- Agilent Technologies UK Limited, Cheadle Royal Business Park Stockport, Cheshire, SK8 3GR, UK
| | - Sufyan Pandor
- Agilent Technologies UK Limited, Cheadle Royal Business Park Stockport, Cheshire, SK8 3GR, UK
| | - Karl Burgess
- Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK.
- EdinOmics, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK.
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22
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Abstract
The parasitic trypanosomatids cause lethal and debilitating diseases, the leishmaniases, Chagas disease, and the African trypanosomiases, with major impacts on human and animal health. Sustained research has borne fruit by assisting efforts to reduce the burden of disease and by improving our understanding of fundamental molecular and cell biology. But where has the research primarily been conducted, and which research areas have received the most attention? These questions are addressed below using publication and citation data from the past few decades.
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Affiliation(s)
- David Horn
- The Wellcome Trust Centre for Anti-Infectives Research, Division of Biological Chemistry & Drug Discovery, School of Life Sciences, University of Dundee, Dundee, United Kingdom
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23
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Ramaprasad A, Burda PC, Calvani E, Sait AJ, Palma-Duran SA, Withers-Martinez C, Hackett F, Macrae J, Collinson L, Gilberger TW, Blackman MJ. A choline-releasing glycerophosphodiesterase essential for phosphatidylcholine biosynthesis and blood stage development in the malaria parasite. eLife 2022; 11:82207. [PMID: 36576255 PMCID: PMC9886279 DOI: 10.7554/elife.82207] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 12/23/2022] [Indexed: 12/29/2022] Open
Abstract
The malaria parasite Plasmodium falciparum synthesizes significant amounts of phospholipids to meet the demands of replication within red blood cells. De novo phosphatidylcholine (PC) biosynthesis via the Kennedy pathway is essential, requiring choline that is primarily sourced from host serum lysophosphatidylcholine (lysoPC). LysoPC also acts as an environmental sensor to regulate parasite sexual differentiation. Despite these critical roles for host lysoPC, the enzyme(s) involved in its breakdown to free choline for PC synthesis are unknown. Here, we show that a parasite glycerophosphodiesterase (PfGDPD) is indispensable for blood stage parasite proliferation. Exogenous choline rescues growth of PfGDPD-null parasites, directly linking PfGDPD function to choline incorporation. Genetic ablation of PfGDPD reduces choline uptake from lysoPC, resulting in depletion of several PC species in the parasite, whilst purified PfGDPD releases choline from glycerophosphocholine in vitro. Our results identify PfGDPD as a choline-releasing glycerophosphodiesterase that mediates a critical step in PC biosynthesis and parasite survival.
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Affiliation(s)
- Abhinay Ramaprasad
- Malaria Biochemistry Laboratory, The Francis Crick InstituteLondonUnited Kingdom
| | - Paul-Christian Burda
- Centre for Structural Systems BiologyHamburgGermany,Bernhard Nocht Institute for Tropical MedicineHamburgGermany,University of HamburgHamburgGermany
| | - Enrica Calvani
- Metabolomics Science Technology Platform, The Francis Crick InstituteLondonUnited Kingdom
| | - Aaron J Sait
- Electron Microscopy Science Technology Platform, The Francis Crick InstituteLondonUnited Kingdom
| | | | | | - Fiona Hackett
- Malaria Biochemistry Laboratory, The Francis Crick InstituteLondonUnited Kingdom
| | - James Macrae
- Metabolomics Science Technology Platform, The Francis Crick InstituteLondonUnited Kingdom
| | - Lucy Collinson
- Electron Microscopy Science Technology Platform, The Francis Crick InstituteLondonUnited Kingdom
| | - Tim Wolf Gilberger
- Centre for Structural Systems BiologyHamburgGermany,Bernhard Nocht Institute for Tropical MedicineHamburgGermany,University of HamburgHamburgGermany
| | - Michael J Blackman
- Malaria Biochemistry Laboratory, The Francis Crick InstituteLondonUnited Kingdom,Faculty of Infectious and Tropical Diseases, London School of Hygiene & Tropical MedicineLondonUnited Kingdom
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24
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Tian Z, Liu F, Li D, Fernie AR, Chen W. Strategies for structure elucidation of small molecules based on LC–MS/MS data from complex biological samples. Comput Struct Biotechnol J 2022; 20:5085-5097. [PMID: 36187931 PMCID: PMC9489805 DOI: 10.1016/j.csbj.2022.09.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 09/03/2022] [Accepted: 09/03/2022] [Indexed: 11/06/2022] Open
Abstract
LC–MS/MS is a major analytical platform for metabolomics, which has become a recent hotspot in the research fields of life and environmental sciences. By contrast, structure elucidation of small molecules based on LC–MS/MS data remains a major challenge in the chemical and biological interpretation of untargeted metabolomics datasets. In recent years, several strategies for structure elucidation using LC–MS/MS data from complex biological samples have been proposed, these strategies can be simply categorized into two types, one based on structure annotation of mass spectra and for the other on retention time prediction. These strategies have helped many scientists conduct research in metabolite-related fields and are indispensable for the development of future tools. Here, we summarized the characteristics of the current tools and strategies for structure elucidation of small molecules based on LC–MS/MS data, and further discussed the directions and perspectives to improve the power of the tools or strategies for structure elucidation.
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25
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Ju R, Liu X, Zheng F, Lu X, Xu G, Lin X. Deep Neural Network Pretrained by Weighted Autoencoders and Transfer Learning for Retention Time Prediction of Small Molecules. Anal Chem 2021; 93:15651-15658. [PMID: 34780148 DOI: 10.1021/acs.analchem.1c03250] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Retention time (RT) prediction contributes to identification of small molecules measured by high-performance liquid chromatography coupled with high-resolution mass spectrometry. Deep learning algorithms based on big data can enhance the accuracy of RT prediction. But at different chromatographic conditions, RTs of compounds are different, and the number of compounds with known RTs is small in most cases. Therefore, the transfer of big data is necessary. In this work, a strategy using a deep neural network (DNN) pretrained by weighed autoencoders and transfer learning (DNNpwa-TL) was proposed to efficiently predict RTs of compounds. The loss function in the autoencoders was calculated with features weighted by mutual information. Then, a DNN pretrained by weighted autoencoders (DNNpwa) was produced. For other specific chromatographic methods, the transfer learning model DNNpwa-TLs were built through fine-tuning the DNNpwa with the help of some compounds with known RTs to conduct the RT prediction. With the above strategy, a DNNpwa was first built with the METLIN small molecule retention time data set containing 80 038 small molecule compounds. A median relative error of 3.1% and a mean relative error of 4.9% were achieved. Then, 17 data sets from different chromatographic methods were studied, and the results showed that the performance of DNNpwa-TL was better than those of other deep learning models. Besides, DNNpwa-TL outperformed random forest, gradient boost, least absolute shrinkage and selection operator regression, and DNN for most of the 17 data sets. Therefore, DNNpwa-TL can provide an efficient method to perform RT prediction of small molecule compounds for different chromatographic methods and conditions.
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Affiliation(s)
- Ran Ju
- School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China
| | - Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Fujian Zheng
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Xin Lu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Xiaohui Lin
- School of Computer Science and Technology, Dalian University of Technology, Dalian 116024, China
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26
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Damiati LA, Tsimbouri MP, Hernandez VL, Jayawarna V, Ginty M, Childs P, Xiao Y, Burgess K, Wells J, Sprott MR, Meek RMD, Li P, Oreffo ROC, Nobbs A, Ramage G, Su B, Salmeron-Sanchez M, Dalby MJ. Materials-driven fibronectin assembly on nanoscale topography enhances mesenchymal stem cell adhesion, protecting cells from bacterial virulence factors and preventing biofilm formation. Biomaterials 2021; 280:121263. [PMID: 34810036 DOI: 10.1016/j.biomaterials.2021.121263] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 11/03/2021] [Accepted: 11/14/2021] [Indexed: 01/07/2023]
Abstract
Post-operative infection is a major complication in patients recovering from orthopaedic surgery. As such, there is a clinical need to develop biomaterials for use in regenerative surgery that can promote mesenchymal stem cell (MSC) osteospecific differentiation and that can prevent infection caused by biofilm-forming pathogens. Nanotopographical approaches to pathogen control are being identified, including in orthopaedic materials such as titanium and its alloys. These topographies use high aspect ratio nanospikes or nanowires to prevent bacterial adhesion but these features also significantly reduce MSC adhesion and activity. Here, we use a poly (ethyl acrylate) (PEA) polymer coating on titanium nanowires to spontaneously organise fibronectin (FN) and to deliver bone morphogenetic protein 2 (BMP2) to enhance MSC adhesion and osteospecific signalling. Using a novel MSC-Pseudomonas aeruginosa co-culture, we show that the coated nanotopographies protect MSCs from cytotoxic quorum sensing and signalling molecules, enhance MSC adhesion and osteoblast differentiation and reduce biofilm formation. We conclude that the PEA polymer-coated nanotopography can both support MSCs and prevent pathogens from adhering to a biomaterial surface, thus protecting from biofilm formation and bacterial infection, and supporting osteogenic repair.
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Affiliation(s)
- Laila A Damiati
- Department of Biology, Collage of Science, University of Jeddah, Jeddah, 23890, Saudi Arabia; Centre for the Cellular Microenvironment, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Monica P Tsimbouri
- Centre for the Cellular Microenvironment, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Virginia-Llopis Hernandez
- Centre for the Cellular Microenvironment, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Vineetha Jayawarna
- Centre for the Cellular Microenvironment, Division of Biomedical Engineering, School of Engineering, University of Glasgow, Glasgow, G12 8LT, UK
| | - Mark Ginty
- School of Oral and Dental Sciences, University of Bristol, Bristol, BS1 2LY, UK
| | - Peter Childs
- Department of Biomedical Engineering, University of Strathclyde, Glasgow, G1 1QE, UK
| | - Yinbo Xiao
- Centre for the Cellular Microenvironment, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Karl Burgess
- Glasgow Polyomics Facility, College of Medical, Veterinary and Life Sciences, University of Glasgow, Switchback Rd, Bearsden, Glasgow, G61 1BD, UK
| | - Julia Wells
- Bone and Joint Research Group, Centre for Human Development, Stem Cells and Regeneration, Institute of Developmental Sciences, University of Southampton, Southampton, SO16 6YD, UK
| | - Mark R Sprott
- Centre for the Cellular Microenvironment, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - R M Dominic Meek
- Department of Orthopedics, Queen Elizabeth II University Hospital, Glasgow, G51 4TF, UK
| | - Peifeng Li
- Centre for the Cellular Microenvironment, Division of Biomedical Engineering, School of Engineering, University of Glasgow, Glasgow, G12 8LT, UK
| | - Richard O C Oreffo
- Bone and Joint Research Group, Centre for Human Development, Stem Cells and Regeneration, Institute of Developmental Sciences, University of Southampton, Southampton, SO16 6YD, UK
| | - Angela Nobbs
- School of Oral and Dental Sciences, University of Bristol, Bristol, BS1 2LY, UK
| | - Gordon Ramage
- Oral Sciences Research Group, Glasgow Dental School, School of Medicine, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8TA, UK
| | - Bo Su
- School of Oral and Dental Sciences, University of Bristol, Bristol, BS1 2LY, UK
| | - Manuel Salmeron-Sanchez
- Centre for the Cellular Microenvironment, Division of Biomedical Engineering, School of Engineering, University of Glasgow, Glasgow, G12 8LT, UK.
| | - Matthew J Dalby
- Centre for the Cellular Microenvironment, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK.
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27
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Bouwmeester R, Gabriels R, Hulstaert N, Martens L, Degroeve S. DeepLC can predict retention times for peptides that carry as-yet unseen modifications. Nat Methods 2021; 18:1363-1369. [PMID: 34711972 DOI: 10.1038/s41592-021-01301-5] [Citation(s) in RCA: 76] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 09/13/2021] [Indexed: 11/09/2022]
Abstract
The inclusion of peptide retention time prediction promises to remove peptide identification ambiguity in complex liquid chromatography-mass spectrometry identification workflows. However, due to the way peptides are encoded in current prediction models, accurate retention times cannot be predicted for modified peptides. This is especially problematic for fledgling open searches, which will benefit from accurate retention time prediction for modified peptides to reduce identification ambiguity. We present DeepLC, a deep learning peptide retention time predictor using peptide encoding based on atomic composition that allows the retention time of (previously unseen) modified peptides to be predicted accurately. We show that DeepLC performs similarly to current state-of-the-art approaches for unmodified peptides and, more importantly, accurately predicts retention times for modifications not seen during training. Moreover, we show that DeepLC's ability to predict retention times for any modification enables potentially incorrect identifications to be flagged in an open search of a wide variety of proteome data.
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Affiliation(s)
- Robbin Bouwmeester
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Ralf Gabriels
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Niels Hulstaert
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
| | - Lennart Martens
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium. .,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium.
| | - Sven Degroeve
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium.,Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
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28
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Yang Q, Ji H, Fan X, Zhang Z, Lu H. Retention time prediction in hydrophilic interaction liquid chromatography with graph neural network and transfer learning. J Chromatogr A 2021; 1656:462536. [PMID: 34563892 DOI: 10.1016/j.chroma.2021.462536] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 09/02/2021] [Accepted: 09/03/2021] [Indexed: 01/04/2023]
Abstract
The combination of retention time (RT), accurate mass and tandem mass spectra can improve the structural annotation in untargeted metabolomics. However, the incorporation of RT for metabolite identification has received less attention because of the limitation of available RT data, especially for hydrophilic interaction liquid chromatography (HILIC). Here, the Graph Neural Network-based Transfer Learning (GNN-TL) is proposed to train a model for HILIC RTs prediction. The graph neural network was pre-trained using an in silico HILIC RT dataset (pseudo-labeling dataset) with ∼306 K molecules. Then, the weights of dense layers in the pre-trained GNN (pre-GNN) model were fine-tuned by transfer learning using a small number of experimental HILIC RTs from the target chromatographic system. The GNN-TL outperformed the methods in Retip, including the Random Forest (RF), Bayesian-regularized neural network (BRNN), XGBoost, light gradient-boosting machine (LightGBM), and Keras. It achieved the lowest mean absolute error (MAE) of 38.6 s on the test set and 33.4 s on an additional test set. It has the best ability to generalize with a small performance difference between training, test, and additional test sets. Furthermore, the predicted RTs can filter out nearly 60% false positive candidates on average, which is valuable for the identification of compounds complementary to mass spectrometry.
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Affiliation(s)
- Qiong Yang
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, PR China
| | - Hongchao Ji
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, PR China
| | - Xiaqiong Fan
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, PR China
| | - Zhimin Zhang
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, PR China.
| | - Hongmei Lu
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, PR China.
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29
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Polymyxin-Induced Metabolic Perturbations in Human Lung Epithelial Cells. Antimicrob Agents Chemother 2021; 65:e0083521. [PMID: 34228550 DOI: 10.1128/aac.00835-21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Inhaled polymyxins are associated with toxicity in human lung epithelial cells that involves multiple apoptotic pathways. However, the mechanism of polymyxin-induced pulmonary toxicity remains unclear. This study aims to investigate polymyxin-induced metabolomic perturbations in human lung epithelial A549 cells. A549 cells were treated with 0.5 or 1.0 mM polymyxin B or colistin for 1, 4, and 24 h. Cellular metabolites were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS), and significantly perturbed metabolites (log2 fold change [log2FC] ≥ 1; false-discovery rate [FDR] ≤ 0.2) and key pathways were identified relative to untreated control samples. At 1 and 4 h, very few significant changes in metabolites were observed relative to the untreated control cells. At 24 h, taurine (log2FC = -1.34 ± 0.64) and hypotaurine (log2FC = -1.20 ± 0.27) were significantly decreased by 1.0 mM polymyxin B. The reduced form of glutathione (GSH) was significantly depleted by 1.0 mM polymyxin B at 24 h (log2FC = -1.80 ± 0.42). Conversely, oxidized glutathione (GSSG) was significantly increased by 1.0 mM both polymyxin B (log2FC = 1.38 ± 0.13 at 4 h and 2.09 ± 0.20 at 24 h) and colistin (log2FC = 1.33 ± 0.24 at 24 h). l-Carnitine was significantly decreased by 1.0 mM of both polymyxins at 24 h, as were several key metabolites involved in biosynthesis and degradation of choline and ethanolamine (log2FC ≤ -1); several phosphatidylserines were also increased (log2FC ≥ 1). Polymyxins perturbed key metabolic pathways that maintain cellular redox balance, mitochondrial β-oxidation, and membrane lipid biogenesis. These mechanistic findings may assist in developing new pharmacokinetic/pharmacodynamic strategies to attenuate the pulmonary toxicities of inhaled polymyxins and in the discovery of new-generation polymyxins.
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30
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Intratumour heterogeneity in microRNAs expression regulates glioblastoma metabolism. Sci Rep 2021; 11:15908. [PMID: 34354095 PMCID: PMC8342598 DOI: 10.1038/s41598-021-95289-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2020] [Accepted: 07/16/2021] [Indexed: 02/07/2023] Open
Abstract
While specific microRNA (miRNA) signatures have been identified in glioblastoma (GBM), the intratumour heterogeneity in miRNA expression has not yet been characterised. In this study, we reveal significant alterations in miRNA expression across three GBM tumour regions: the core, rim, and invasive margin. Our miRNA profiling analysis showed that miR-330-5p and miR-215-5p were upregulated in the invasive margin relative to the core and the rim regions, while miR-619-5p, miR-4440 and miR-4793-3p were downregulated. Functional analysis of newly identified miRNAs suggests their involvement in regulating lipid metabolic pathways. Subsequent liquid chromatography-mass spectrometry (LC-MS) and tandem mass spectroscopy (LC-MS/MS) profiling of the intracellular metabolome and the lipidome of GBM cells with dysregulated miRNA expression confirmed the alteration in the metabolite levels associated with lipid metabolism. The identification of regional miRNA expression signatures may underlie the metabolic heterogeneity within the GBM tumour and understanding this relationship may open new avenues for the GBM treatment.
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31
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Collins SL, Koo I, Peters JM, Smith PB, Patterson AD. Current Challenges and Recent Developments in Mass Spectrometry-Based Metabolomics. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2021; 14:467-487. [PMID: 34314226 DOI: 10.1146/annurev-anchem-091620-015205] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
High-resolution mass spectrometry (MS) has advanced the study of metabolism in living systems by allowing many metabolites to be measured in a single experiment. Although improvements in mass detector sensitivity have facilitated the detection of greater numbers of analytes, compound identification strategies, feature reduction software, and data sharing have not kept up with the influx of MS data. Here, we discuss the ongoing challenges with MS-based metabolomics, including de novo metabolite identification from mass spectra, differentiation of metabolites from environmental contamination, chromatographic separation of isomers, and incomplete MS databases. Because of their popularity and sensitive detection of small molecules, this review focuses on the challenges of liquid chromatography-mass spectrometry-based methods. We then highlight important instrumentational, experimental, and computational tools that have been created to address these challenges and how they have enabled the advancement of metabolomics research.
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Affiliation(s)
- Stephanie L Collins
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Imhoi Koo
- Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA;
- The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Jeffrey M Peters
- Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA;
| | - Philip B Smith
- The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Andrew D Patterson
- Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, Pennsylvania 16802, USA;
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32
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Steketee PC, Dickie EA, Iremonger J, Crouch K, Paxton E, Jayaraman S, Alfituri OA, Awuah-Mensah G, Ritchie R, Schnaufer A, Rowan T, de Koning HP, Gadelha C, Wickstead B, Barrett MP, Morrison LJ. Divergent metabolism between Trypanosoma congolense and Trypanosoma brucei results in differential sensitivity to metabolic inhibition. PLoS Pathog 2021; 17:e1009734. [PMID: 34310651 PMCID: PMC8384185 DOI: 10.1371/journal.ppat.1009734] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 08/24/2021] [Accepted: 06/21/2021] [Indexed: 11/18/2022] Open
Abstract
Animal African Trypanosomiasis (AAT) is a debilitating livestock disease prevalent across sub-Saharan Africa, a main cause of which is the protozoan parasite Trypanosoma congolense. In comparison to the well-studied T. brucei, there is a major paucity of knowledge regarding the biology of T. congolense. Here, we use a combination of omics technologies and novel genetic tools to characterise core metabolism in T. congolense mammalian-infective bloodstream-form parasites, and test whether metabolic differences compared to T. brucei impact upon sensitivity to metabolic inhibition. Like the bloodstream stage of T. brucei, glycolysis plays a major part in T. congolense energy metabolism. However, the rate of glucose uptake is significantly lower in bloodstream stage T. congolense, with cells remaining viable when cultured in concentrations as low as 2 mM. Instead of pyruvate, the primary glycolytic endpoints are succinate, malate and acetate. Transcriptomics analysis showed higher levels of transcripts associated with the mitochondrial pyruvate dehydrogenase complex, acetate generation, and the glycosomal succinate shunt in T. congolense, compared to T. brucei. Stable-isotope labelling of glucose enabled the comparison of carbon usage between T. brucei and T. congolense, highlighting differences in nucleotide and saturated fatty acid metabolism. To validate the metabolic similarities and differences, both species were treated with metabolic inhibitors, confirming that electron transport chain activity is not essential in T. congolense. However, the parasite exhibits increased sensitivity to inhibition of mitochondrial pyruvate import, compared to T. brucei. Strikingly, T. congolense exhibited significant resistance to inhibitors of fatty acid synthesis, including a 780-fold higher EC50 for the lipase and fatty acid synthase inhibitor Orlistat, compared to T. brucei. These data highlight that bloodstream form T. congolense diverges from T. brucei in key areas of metabolism, with several features that are intermediate between bloodstream- and insect-stage T. brucei. These results have implications for drug development, mechanisms of drug resistance and host-pathogen interactions.
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Affiliation(s)
- Pieter C Steketee
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom
| | - Emily A Dickie
- Wellcome Centre for Integrative Parasitology, Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, United Kingdom
| | - James Iremonger
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom
| | - Kathryn Crouch
- Wellcome Centre for Integrative Parasitology, Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, United Kingdom
| | - Edith Paxton
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom
| | - Siddharth Jayaraman
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom
| | - Omar A Alfituri
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom
| | | | - Ryan Ritchie
- Wellcome Centre for Integrative Parasitology, Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, United Kingdom
| | - Achim Schnaufer
- Institute of Immunology and Infection Research, University of Edinburgh, Edinburgh, United Kingdom
| | - Tim Rowan
- Global Alliance for Livestock Veterinary Medicines, Edinburgh, United Kingdom
| | - Harry P de Koning
- Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, United Kingdom
| | - Catarina Gadelha
- School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Bill Wickstead
- School of Life Sciences, University of Nottingham, Nottingham, United Kingdom
| | - Michael P Barrett
- Wellcome Centre for Integrative Parasitology, Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow, United Kingdom.,Glasgow Polyomics, University of Glasgow, Glasgow, United Kingdom
| | - Liam J Morrison
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom
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Turner RE, Harrison PF, Swaminathan A, Kraupner-Taylor CA, Goldie BJ, See M, Peterson AL, Schittenhelm RB, Powell DR, Creek DJ, Dichtl B, Beilharz TH. Genetic and pharmacological evidence for kinetic competition between alternative poly(A) sites in yeast. eLife 2021; 10:65331. [PMID: 34232857 PMCID: PMC8263057 DOI: 10.7554/elife.65331] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 06/22/2021] [Indexed: 01/23/2023] Open
Abstract
Most eukaryotic mRNAs accommodate alternative sites of poly(A) addition in the 3’ untranslated region in order to regulate mRNA function. Here, we present a systematic analysis of 3’ end formation factors, which revealed 3’UTR lengthening in response to a loss of the core machinery, whereas a loss of the Sen1 helicase resulted in shorter 3’UTRs. We show that the anti-cancer drug cordycepin, 3’ deoxyadenosine, caused nucleotide accumulation and the usage of distal poly(A) sites. Mycophenolic acid, a drug which reduces GTP levels and impairs RNA polymerase II (RNAP II) transcription elongation, promoted the usage of proximal sites and reversed the effects of cordycepin on alternative polyadenylation. Moreover, cordycepin-mediated usage of distal sites was associated with a permissive chromatin template and was suppressed in the presence of an rpb1 mutation, which slows RNAP II elongation rate. We propose that alternative polyadenylation is governed by temporal coordination of RNAP II transcription and 3’ end processing and controlled by the availability of 3’ end factors, nucleotide levels and chromatin landscape.
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Affiliation(s)
- Rachael Emily Turner
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Australia
| | - Paul F Harrison
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Australia.,Monash Bioinformatics Platform, Monash University, Melbourne, Australia
| | - Angavai Swaminathan
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Australia
| | - Calvin A Kraupner-Taylor
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Australia
| | - Belinda J Goldie
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Australia
| | - Michael See
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Australia.,Monash Bioinformatics Platform, Monash University, Melbourne, Australia
| | - Amanda L Peterson
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Australia
| | - Ralf B Schittenhelm
- Monash Proteomics & Metabolomics Facility, Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Melbourne, Australia
| | - David R Powell
- Monash Bioinformatics Platform, Monash University, Melbourne, Australia
| | - Darren J Creek
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Australia
| | - Bernhard Dichtl
- School of Life and Environmental Sciences, Deakin University, Geelong, Australia
| | - Traude H Beilharz
- Development and Stem Cells Program, Monash Biomedicine Discovery Institute and Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Australia
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Wang Y, Hou Y, Wang Q, Wang Y. The elucidation of the biodegradation of nitrobenzene and p-nitrophenol of nitroreductase from Antarctic psychrophile Psychrobacter sp. ANT206 under low temperature. JOURNAL OF HAZARDOUS MATERIALS 2021; 413:125377. [PMID: 33609870 DOI: 10.1016/j.jhazmat.2021.125377] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Revised: 02/06/2021] [Accepted: 02/06/2021] [Indexed: 06/12/2023]
Abstract
Psychrobacter is one important typical strain in the Antarctic environment. In our previous study, Psychrobacter sp. ANT206 from Antarctica with novel cold-adapted nitroreductase (PsNTR) could biodegrade nitrobenzene and p-nitrophenol in low temperature environment. In this study, the in-frame deletion mutant of psntr (Δpsntr-ANT206) that displayed well genetic stability and kanamycin resistance stability was constructed using allelic replacement method. Additionally, Δpsntr-ANT206 was more sensitive to nitrobenzene and p-nitrophenol in the comparison of heat and hyperosmolarity, suggesting that psntr gene participated in the regulation of the tolerance against nitro-aromatic compounds (NACs). Further analysis was conducted by integrated gas chromatography-mass spectrometry (GC-MS), and several metabolites were identified. Among them, ethylbenzene, L-Alanine, citric acid, aniline, 4-aminophenol and other metabolites were different between the wild-type strain and Δpsntr-ANT206 under nitrobenzene and p-nitrophenol stress at different time periods under low temperature, respectively. These data could increase the knowledge of the construction of deletion mutant strains and biodegradation mechanism of NACs of typical strains Psychrobacter from Antarctica, which would also provide the basis of the molecular technique on the regulation of bioremediation of the contaminants under low temperature in the future.
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Affiliation(s)
- Yifan Wang
- School of Environment, Harbin Institute of Technology, Harbin 150090, China
| | - Yanhua Hou
- School of Marine Science and Technology, Harbin Institute of Technology, Weihai 264209, China.
| | - Quanfu Wang
- School of Environment, Harbin Institute of Technology, Harbin 150090, China; School of Marine Science and Technology, Harbin Institute of Technology, Weihai 264209, China.
| | - Yatong Wang
- School of Environment, Harbin Institute of Technology, Harbin 150090, China
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Santamaria F, Barlow CK, Schlagloth R, Schittenhelm RB, Palme R, Henning J. Identification of Koala ( Phascolarctos cinereus) Faecal Cortisol Metabolites Using Liquid Chromatography-Mass Spectrometry and Enzyme Immunoassays. Metabolites 2021; 11:metabo11060393. [PMID: 34208684 PMCID: PMC8234238 DOI: 10.3390/metabo11060393] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 06/14/2021] [Accepted: 06/14/2021] [Indexed: 11/16/2022] Open
Abstract
The koala (Phascolarctos cinereus) is an arboreal folivorous marsupial endemic to Australia. Anthropogenic activities and climate change are threats to this species' survival and are potential stressors. A suitable non-invasive method is needed to objectively detect stress in koalas. Under conditions of stress, the concentration of the hormone cortisol in plasma or in saliva is elevated, and this would provide a convenient measure; however, collecting blood or saliva from wild animals is both practically difficult and stressful, and so likely to confound any measurement. In contrast, measurement of cortisol metabolites in faeces provides a practical and non-invasive method to objectively measure stress in koalas. Unfortunately, the identity of the main faecal cortisol metabolites of koalas is unknown. In this study, we have used both untargeted liquid chromatography-mass spectrometry (LC-MS) and enzyme immunoassays (EIAs) to identify several faecal cortisol metabolites in two koalas, one female (18 months old, 4.1 kg) and one male (4 years old, 6.95 kg) upon administration of hydrocortisone (cortisol) sodium succinate. The LC-MS analysis identified tetrahydrocortisol along with several other isomers as cortisol metabolites. After a survey of five enzyme immunoassays, we found that two metabolites, tetrahydrocortisol and 3β-allotetrahydrocortisol, could be detected by EIAs that used antibodies that were raised against their structurally similar corticosterone counterparts, tetrahydrocorticosterone and 3β-allotetrahydrocorticosterone, respectively. While the 3β-allotetrahydrocortisol metabolite was detected in the faeces of only one of the two animals studied, tetrahydrocortisol was detected in both. These results ultimately indicate that tetrahydrocortisol is likely the main faecal cortisol metabolite in koalas, and we demonstrate that it can be measured by an EIA (50c) that was originally developed to measure tetrahydrocorticosterone.
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Affiliation(s)
- Flavia Santamaria
- Flora, Fauna and Freshwater Research and Koala Research Central Queensland, School of Health, Medical and Applied Sciences, Central Queensland University, North Rockhampton, QLD 4702, Australia;
- Correspondence: (F.S.); (R.P.)
| | - Christopher K. Barlow
- Monash Proteomics and Metabolomics Facility, Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia; (C.K.B.); (R.B.S.)
| | - Rolf Schlagloth
- Flora, Fauna and Freshwater Research and Koala Research Central Queensland, School of Health, Medical and Applied Sciences, Central Queensland University, North Rockhampton, QLD 4702, Australia;
| | - Ralf B. Schittenhelm
- Monash Proteomics and Metabolomics Facility, Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia; (C.K.B.); (R.B.S.)
| | - Rupert Palme
- Department of Biomedical Sciences, University of Veterinary Medicine, 1210 Vienna, Austria
- Correspondence: (F.S.); (R.P.)
| | - Joerg Henning
- School of Veterinary Science, The University of Queensland, Gatton, QLD 4343, Australia;
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Abdul Rahim N, Zhu Y, Cheah SE, Johnson MD, Yu HH, Sidjabat HE, Butler MS, Cooper MA, Fu J, Paterson DL, Nation RL, Boyce JD, Creek DJ, Bergen PJ, Velkov T, Li J. Synergy of the Polymyxin-Chloramphenicol Combination against New Delhi Metallo-β-Lactamase-Producing Klebsiella pneumoniae Is Predominately Driven by Chloramphenicol. ACS Infect Dis 2021; 7:1584-1595. [PMID: 33834753 DOI: 10.1021/acsinfecdis.0c00661] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Carbapenem-resistant Klebsiella pneumoniae has been classified as an Urgent Threat by the Centers for Disease Control and Prevention (CDC). The combination of two "old" antibiotics, polymyxin and chloramphenicol, displays synergistic killing against New Delhi metallo-β-lactamase (NDM)-producing K. pneumoniae. However, the mechanism(s) underpinning their synergistic killing are not well studied. We employed an in vitro pharmacokinetic/pharmacodynamic model to mimic the pharmacokinetics of the antibiotics in patients and examined bacterial killing against NDM-producing K. pneumoniae using a metabolomic approach. Metabolomic analysis was integrated with an isolate-specific genome-scale metabolic network (GSMN). Our results show that metabolic responses to polymyxin B and/or chloramphenicol against NDM-producing K. pneumoniae involved the inhibition of cell envelope biogenesis, metabolism of arginine and nucleotides, glycolysis, and pentose phosphate pathways. Our metabolomic and GSMN modeling results highlight the novel mechanisms of a synergistic antibiotic combination at the network level and may have a significant potential in developing precision antimicrobial chemotherapy in patients.
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Affiliation(s)
- Nusaibah Abdul Rahim
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
- Biomedicine Discovery Institute, Department of Microbiology, Monash University, Clayton, Victoria 3800, Australia
| | - Yan Zhu
- Biomedicine Discovery Institute, Department of Microbiology, Monash University, Clayton, Victoria 3800, Australia
| | - Soon-Ee Cheah
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
| | - Matthew D. Johnson
- Biomedicine Discovery Institute, Department of Microbiology, Monash University, Clayton, Victoria 3800, Australia
| | - Heidi H. Yu
- Biomedicine Discovery Institute, Department of Microbiology, Monash University, Clayton, Victoria 3800, Australia
| | - Hanna E. Sidjabat
- University of Queensland Centre for Clinical Research, Herston, Queensland 4029, Australia
| | - Mark S. Butler
- Institute for Molecular Biosciences, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Matthew A. Cooper
- Institute for Molecular Biosciences, The University of Queensland, Brisbane, Queensland 4072, Australia
| | - Jing Fu
- Department of Mechanical and Aerospace Engineering, Faculty of Engineering, Monash University, Clayton, Victoria 3800, Australia
| | - David L. Paterson
- University of Queensland Centre for Clinical Research, Herston, Queensland 4029, Australia
- Pathology Queensland, Royal Brisbane and Women’s Hospital Campus, Herston, Queensland 4029, Australia
| | - Roger L. Nation
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
| | - John D. Boyce
- Biomedicine Discovery Institute, Department of Microbiology, Monash University, Clayton, Victoria 3800, Australia
| | - Darren J. Creek
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
| | - Phillip J. Bergen
- Biomedicine Discovery Institute, Department of Microbiology, Monash University, Clayton, Victoria 3800, Australia
- Centre for Medicine Use and Safety, Monash University, Parkville, Victoria 3052, Australia
| | - Tony Velkov
- Department of Pharmacology & Therapeutics, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Parkville, Victoria 3010, Australia
| | - Jian Li
- Drug Delivery, Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, Victoria 3052, Australia
- Biomedicine Discovery Institute, Department of Microbiology, Monash University, Clayton, Victoria 3800, Australia
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Peterson AL, Siddiqui G, Sloan EK, Creek DJ. β-Adrenoceptor regulation of metabolism in U937 derived macrophages. Mol Omics 2021; 17:583-595. [PMID: 34105576 DOI: 10.1039/d1mo00057h] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Macrophages have important roles in the immune system including clearing pathogens and wound healing. Metabolic phenotypes in macrophages have been associated with functional phenotypes, where pro-inflammatory macrophages have an increased rate of glycolysis and anti-inflammatory macrophages primarily use oxidative phosphorylation. β-adrenoceptor (βAR) signalling in macrophages has been implicated in disease states such as cancer, atherosclerosis and rheumatoid arthritis. The impact of βAR signalling on macrophage metabolism has not been defined. Using metabolomics and proteomics, we describe the impact of βAR signalling on macrophages treated with isoprenaline. We found that βAR signalling alters proteins involved in cytoskeletal rearrangement and redox homeostasis of the cell. We showed that βAR signalling in macrophages shifts glucose metabolism from glycolysis towards the tricarboxylic acid cycle and pentose phosphate pathways. We also show that βAR signalling perturbs purine metabolism by accumulating adenylate and guanylate pools. Taken together, these results indicate that βAR signalling shifts metabolism to support redox processes and upregulates proteins involved in cytoskeletal changes, which may contribute to βAR effects on macrophage function.
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Affiliation(s)
- Amanda L Peterson
- Drug Delivery, Disposition and Dynamics Theme, Monash Institute of Pharmaceutical Science, Monash University, Parkville, Victoria 3052, Australia.
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Chen Y, Guo J, Xing S, Yu H, Huan T. Global-Scale Metabolomic Profiling of Human Hair for Simultaneous Monitoring of Endogenous Metabolome, Short- and Long-Term Exposome. Front Chem 2021; 9:674265. [PMID: 34055742 PMCID: PMC8149753 DOI: 10.3389/fchem.2021.674265] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 04/06/2021] [Indexed: 12/20/2022] Open
Abstract
Hair is a unique biological matrix that adsorbs short-term exposures (e. g., environmental contaminants and personal care products) on its surface and also embeds endogenous metabolites and long-term exposures in its matrix. In this work, we developed an untargeted metabolomics workflow to profile both temporal exposure chemicals and endogenous metabolites in the same hair sample. This analytical workflow begins with the extraction of short-term exposures from hair surfaces through washing. Further development of mechanical homogenization extracts endogenous metabolites and long-term exposures from the cleaned hair. Both solutions of hair wash and hair extract were analyzed using ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS)-based metabolomics for global-scale metabolic profiling. After analysis, raw data were processed using bioinformatic programs recently developed specifically for exposome research. Using optimized experimental conditions, we detected a total of 10,005 and 9,584 metabolic features from hair wash and extraction samples, respectively. Among them, 274 and 276 features can be definitively confirmed by MS2 spectral matching against spectral library, and an additional 3,356 and 3,079 features were tentatively confirmed as biotransformation metabolites. To demonstrate the performance of our hair metabolomics, we collected hair samples from three female volunteers and tested their hair metabolic changes before and after a 2-day exposure exercise. Our results show that 645 features from wash and 89 features from extract were significantly changed from the 2-day exposure. Altogether, this work provides a novel analytical approach to study the hair metabolome and exposome at a global scale, which can be implemented in a wide range of biological applications for a deeper understanding of the impact of environmental and genetic factors on human health.
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Affiliation(s)
- Ying Chen
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver, BC, Canada
| | - Jian Guo
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver, BC, Canada
| | - Shipei Xing
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver, BC, Canada
| | - Huaxu Yu
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver, BC, Canada
| | - Tao Huan
- Department of Chemistry, Faculty of Science, University of British Columbia, Vancouver, BC, Canada
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Bride E, Heinisch S, Bonnefille B, Guillemain C, Margoum C. Suspect screening of environmental contaminants by UHPLC-HRMS and transposable Quantitative Structure-Retention Relationship modelling. JOURNAL OF HAZARDOUS MATERIALS 2021; 409:124652. [PMID: 33277075 DOI: 10.1016/j.jhazmat.2020.124652] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 10/02/2020] [Accepted: 11/20/2020] [Indexed: 06/12/2023]
Abstract
A Quantitative Structure-Retention Relationship (QSRR) model is proposed and aims at increasing the confidence level associated to the identification of organic contaminants by Ultra-High Performance Liquid Chromatography hyphenated to High Resolution Mass Spectrometry (UHPLC-HRMS) in environmental samples under a suspect screening approach. The model was built from a selection of 8 easily accessible physicochemical descriptors, and was validated from a set of 274 organic compounds commonly found in environmental samples. The proposed predictive figure approach is based on the mobile phase composition at solute elution (expressed as % acetonitrile), that has the major advantage of making the model reusable by other laboratories, since the elution composition is independent of both the column geometry and the UHPLC-system. The model quality was assessed and was altered neither by the columns from different lots, nor by the complex matrices of environmental water samples. Then, the solute retention of any organic compound present in water samples is expected to be predicted within ± 14.3% acetonitrile by our model. Solute retention can therefore be used as a supplementary tool for the identification of environmental contaminants by UHPLC-HRMS, in addition to mass spectrometry data already used in the suspect screening approach.
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Affiliation(s)
- Eloi Bride
- INRAE, UR RiverLy, F-69625 Villeurbanne, France
| | - Sabine Heinisch
- Université de Lyon, Institut des Sciences Analytiques, UMR 5280, CNRS, F-69100 Villeurbanne, France
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Integrated Metabolomics and Transcriptomics Using an Optimised Dual Extraction Process to Study Human Brain Cancer Cells and Tissues. Metabolites 2021; 11:metabo11040240. [PMID: 33919944 PMCID: PMC8070957 DOI: 10.3390/metabo11040240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 04/12/2021] [Accepted: 04/12/2021] [Indexed: 11/18/2022] Open
Abstract
The integration of untargeted metabolomics and transcriptomics from the same population of cells or tissue enhances the confidence in the identified metabolic pathways and understanding of the enzyme–metabolite relationship. Here, we optimised a simultaneous extraction method of metabolites/lipids and RNA from ependymoma cells (BXD-1425). Relative to established RNA (mirVana kit) or metabolite (sequential solvent addition and shaking) single extraction methods, four dual-extraction techniques were evaluated and compared (methanol:water:chloroform ratios): cryomill/mirVana (1:1:2); cryomill-wash/Econospin (5:1:2); rotation/phenol-chloroform (9:10:1); Sequential/mirVana (1:1:3). All methods extracted the same metabolites, yet rotation/phenol-chloroform did not extract lipids. Cryomill/mirVana and sequential/mirVana recovered the highest amounts of RNA, at 70 and 68% of that recovered with mirVana kit alone. sequential/mirVana, involving RNA extraction from the interphase of our established sequential solvent addition and shaking metabolomics-lipidomics extraction method, was the most efficient approach overall. Sequential/mirVana was applied to study a) the biological effect caused by acute serum starvation in BXD-1425 cells and b) primary ependymoma tumour tissue. We found (a) 64 differentially abundant metabolites and 28 differentially expressed metabolic genes, discovering four gene-metabolite interactions, and (b) all metabolites and 62% lipids were above the limit of detection, and RNA yield was sufficient for transcriptomics, in just 10 mg of tissue.
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Cobbold SA, V Tutor M, Frasse P, McHugh E, Karnthaler M, Creek DJ, Odom John A, Tilley L, Ralph SA, McConville MJ. Non-canonical metabolic pathways in the malaria parasite detected by isotope-tracing metabolomics. Mol Syst Biol 2021; 17:e10023. [PMID: 33821563 PMCID: PMC8022201 DOI: 10.15252/msb.202010023] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 02/02/2021] [Accepted: 02/04/2021] [Indexed: 12/26/2022] Open
Abstract
The malaria parasite, Plasmodium falciparum, proliferates rapidly in human erythrocytes by actively scavenging multiple carbon sources and essential nutrients from its host cell. However, a global overview of the metabolic capacity of intraerythrocytic stages is missing. Using multiplex 13 C-labelling coupled with untargeted mass spectrometry and unsupervised isotopologue grouping, we have generated a draft metabolome of P. falciparum and its host erythrocyte consisting of 911 and 577 metabolites, respectively, corresponding to 41% of metabolites and over 70% of the metabolic reaction predicted from the parasite genome. An additional 89 metabolites and 92 reactions were identified that were not predicted from genomic reconstructions, with the largest group being associated with metabolite damage-repair systems. Validation of the draft metabolome revealed four previously uncharacterised enzymes which impact isoprenoid biosynthesis, lipid homeostasis and mitochondrial metabolism and are necessary for parasite development and proliferation. This study defines the metabolic fate of multiple carbon sources in P. falciparum, and highlights the activity of metabolite repair pathways in these rapidly growing parasite stages, opening new avenues for drug discovery.
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Affiliation(s)
- Simon A Cobbold
- Department of Biochemistry and Molecular BiologyBio21 Institute of Molecular Science and BiotechnologyUniversity of MelbourneParkvilleVic.Australia
| | - Madel V Tutor
- Department of Biochemistry and Molecular BiologyBio21 Institute of Molecular Science and BiotechnologyUniversity of MelbourneParkvilleVic.Australia
| | - Philip Frasse
- Department of MedicineWashington University School of MedicineSt. LouisMOUSA
| | - Emma McHugh
- Department of Biochemistry and Molecular BiologyBio21 Institute of Molecular Science and BiotechnologyUniversity of MelbourneParkvilleVic.Australia
| | - Markus Karnthaler
- Department of Biochemistry and Molecular BiologyBio21 Institute of Molecular Science and BiotechnologyUniversity of MelbourneParkvilleVic.Australia
| | - Darren J Creek
- Monash Institute of Pharmaceutical SciencesMonash UniversityParkvilleVic.Australia
| | - Audrey Odom John
- The Children’s Hospital of PhiladelphiaUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Leann Tilley
- Department of Biochemistry and Molecular BiologyBio21 Institute of Molecular Science and BiotechnologyUniversity of MelbourneParkvilleVic.Australia
| | - Stuart A Ralph
- Department of Biochemistry and Molecular BiologyBio21 Institute of Molecular Science and BiotechnologyUniversity of MelbourneParkvilleVic.Australia
| | - Malcolm J McConville
- Department of Biochemistry and Molecular BiologyBio21 Institute of Molecular Science and BiotechnologyUniversity of MelbourneParkvilleVic.Australia
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42
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Data processing strategies for non-targeted analysis of foods using liquid chromatography/high-resolution mass spectrometry. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116188] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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43
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Phapale P, Palmer A, Gathungu RM, Kale D, Brügger B, Alexandrov T. Public LC-Orbitrap Tandem Mass Spectral Library for Metabolite Identification. J Proteome Res 2021; 20:2089-2097. [PMID: 33529026 DOI: 10.1021/acs.jproteome.0c00930] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics studies require high-quality spectral libraries for reliable metabolite identification. We have constructed EMBL-MCF (European Molecular Biology Laboratory-Metabolomics Core Facility), an open LC-MS/MS spectral library that currently contains over 1600 fragmentation spectra from 435 authentic standards of endogenous metabolites and lipids. The unique features of the library include the presence of chromatographic profiles acquired with different LC-MS methods and coverage of different adduct ions. The library covers many biologically important metabolites with some unique metabolites and lipids as compared with other public libraries. The EMBL-MCF spectral library is created and shared using an in-house-developed web application at https://curatr.mcf.embl.de/. The library is freely available online and also integrated with other mass spectral repositories.
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Affiliation(s)
- Prasad Phapale
- Metabolomics Core Facility, EMBL, Heidelberg 69117, Germany
| | - Andrew Palmer
- Metabolomics Core Facility, EMBL, Heidelberg 69117, Germany
| | | | - Dipali Kale
- Heidelberg University Biochemistry Center (BZH), Heidelberg 69120, Germany
| | - Britta Brügger
- Heidelberg University Biochemistry Center (BZH), Heidelberg 69120, Germany
| | - Theodore Alexandrov
- Metabolomics Core Facility, EMBL, Heidelberg 69117, Germany.,Structural and Computational Biology Unit, European Molecular Biology Laboratory (EMBL), Heidelberg 69117, Germany.,Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093, United States
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44
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Yang Q, Ji H, Lu H, Zhang Z. Prediction of Liquid Chromatographic Retention Time with Graph Neural Networks to Assist in Small Molecule Identification. Anal Chem 2021; 93:2200-2206. [PMID: 33406817 DOI: 10.1021/acs.analchem.0c04071] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The predicted liquid chromatographic retention times (RTs) of small molecules are not accurate enough for wide adoption in structural identification. In this study, we used the graph neural network to predict the retention time (GNN-RT) from structures of small molecules directly without the requirement of molecular descriptors. The predicted accuracy of GNN-RT was compared with random forests (RFs), Bayesian ridge regression, convolutional neural network (CNN), and a deep-learning regression model (DLM) on a METLIN small molecule retention time (SMRT) dataset. GNN-RT achieved the highest predicting accuracy with a mean relative error of 4.9% and a median relative error of 3.2%. Furthermore, the SMRT-trained GNN-RT model can be transferred to the same type of chromatographic systems easily. The predicted RT is valuable for structural identification in complementary to tandem mass spectra and can be used to assist in the identification of compounds. The results indicate that GNN-RT is a promising method to predict the RT for liquid chromatography and improve the accuracy of structural identification for small molecules.
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Affiliation(s)
- Qiong Yang
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China
| | - Hongchao Ji
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China
| | - Hongmei Lu
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China
| | - Zhimin Zhang
- College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, China
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45
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Hodgkinson T, Tsimbouri PM, Llopis-Hernandez V, Campsie P, Scurr D, Childs PG, Phillips D, Donnelly S, Wells JA, O'Brien FJ, Salmeron-Sanchez M, Burgess K, Alexander M, Vassalli M, Oreffo ROC, Reid S, France DJ, Dalby MJ. The use of nanovibration to discover specific and potent bioactive metabolites that stimulate osteogenic differentiation in mesenchymal stem cells. SCIENCE ADVANCES 2021; 7:7/9/eabb7921. [PMID: 33637520 PMCID: PMC7909882 DOI: 10.1126/sciadv.abb7921] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 01/12/2021] [Indexed: 05/02/2023]
Abstract
Bioactive metabolites have wide-ranging biological activities and are a potential source of future research and therapeutic tools. Here, we use nanovibrational stimulation to induce osteogenic differentiation of mesenchymal stem cells, in the absence of off-target, nonosteogenic differentiation. We show that this differentiation method, which does not rely on the addition of exogenous growth factors to culture media, provides an artifact-free approach to identifying bioactive metabolites that specifically and potently induce osteogenesis. We first identify a highly specific metabolite, cholesterol sulfate, an endogenous steroid. Next, a screen of other small molecules with a similar steroid scaffold identified fludrocortisone acetate with both specific and highly potent osteogenic-inducing activity. Further, we implicate cytoskeletal contractility as a measure of osteogenic potency and cell stiffness as a measure of specificity. These findings demonstrate that physical principles can be used to identify bioactive metabolites and then enable optimization of metabolite potency can be optimized by examining structure-function relationships.
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Affiliation(s)
- Tom Hodgkinson
- Centre for the Cellular Microenvironment, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK
- Tissue Engineering Research Group, Department of Anatomy and Regenerative Medicine, Royal College of Surgeons in Ireland, Dublin D2, Ireland
| | - P Monica Tsimbouri
- Centre for the Cellular Microenvironment, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK
| | - Virginia Llopis-Hernandez
- Centre for the Cellular Microenvironment, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK
| | - Paul Campsie
- SUPA Department of Biomedical Engineering, University of Strathclyde, Glasgow G1 1QE, UK
| | - David Scurr
- School of Pharmacy, The University of Nottingham, Nottingham NG7 2RD, UK
| | - Peter G Childs
- Centre for the Cellular Microenvironment, Division of Biomedical Engineering, School of Engineering, University of Glasgow, Glasgow G12 8LT, UK
| | - David Phillips
- School of Chemistry, College of Science and Engineering, University of Glasgow, Glasgow G12 8QQ, UK
| | - Sam Donnelly
- Centre for the Cellular Microenvironment, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK
| | - Julia A Wells
- Bone and Joint Research Group, Centre for Human Development, Stem Cells and Regeneration, Institute of Developmental Sciences, University of Southampton, Southampton SO16 6YD, UK
| | - Fergal J O'Brien
- Tissue Engineering Research Group, Department of Anatomy and Regenerative Medicine, Royal College of Surgeons in Ireland, Dublin D2, Ireland
| | - Manuel Salmeron-Sanchez
- Centre for the Cellular Microenvironment, Division of Biomedical Engineering, School of Engineering, University of Glasgow, Glasgow G12 8LT, UK
| | - Karl Burgess
- Glasgow Polyomics, College of Medical, Veterinary and Life Sciences, University of Glasgow, Switchback Rd., Bearsden, Glasgow G61 1BD, UK
| | - Morgan Alexander
- School of Pharmacy, The University of Nottingham, Nottingham NG7 2RD, UK
| | - Massimo Vassalli
- Centre for the Cellular Microenvironment, Division of Biomedical Engineering, School of Engineering, University of Glasgow, Glasgow G12 8LT, UK
| | - Richard O C Oreffo
- Bone and Joint Research Group, Centre for Human Development, Stem Cells and Regeneration, Institute of Developmental Sciences, University of Southampton, Southampton SO16 6YD, UK
| | - Stuart Reid
- SUPA Department of Biomedical Engineering, University of Strathclyde, Glasgow G1 1QE, UK
| | - David J France
- School of Chemistry, College of Science and Engineering, University of Glasgow, Glasgow G12 8QQ, UK
| | - Matthew J Dalby
- Centre for the Cellular Microenvironment, Institute of Molecular, Cell and Systems Biology, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK.
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46
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Chang HY, Colby SM, Du X, Gomez JD, Helf MJ, Kechris K, Kirkpatrick CR, Li S, Patti GJ, Renslow RS, Subramaniam S, Verma M, Xia J, Young JD. A Practical Guide to Metabolomics Software Development. Anal Chem 2021; 93:1912-1923. [PMID: 33467846 PMCID: PMC7859930 DOI: 10.1021/acs.analchem.0c03581] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
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A growing number
of software tools have been developed for metabolomics
data processing and analysis. Many new tools are contributed by metabolomics
practitioners who have limited prior experience with software development,
and the tools are subsequently implemented by users with expertise
that ranges from basic point-and-click data analysis to advanced coding.
This Perspective is intended to introduce metabolomics software users
and developers to important considerations that determine the overall
impact of a publicly available tool within the scientific community.
The recommendations reflect the collective experience of an NIH-sponsored
Metabolomics Consortium working group that was formed with the goal
of researching guidelines and best practices for metabolomics tool
development. The recommendations are aimed at metabolomics researchers
with little formal background in programming and are organized into
three stages: (i) preparation, (ii) tool development, and (iii) distribution
and maintenance.
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Affiliation(s)
- Hui-Yin Chang
- Department of Pathology, University of Michigan, 1301 Catherine Street, Ann Arbor, Michigan 48109, United States.,Department of Biomedical Sciences and Engineering, National Central University, No. 300, Zhongda Road, Zhongli District, Taoyuan City 320, Taiwan
| | - Sean M Colby
- Biological Sciences Division, Pacific Northwest National Laboratory, P.O. Box 999, MSIN: K8-98, Richland, Washington 99352, United States
| | - Xiuxia Du
- Department of Bioinformatics & Genomics, University of North Carolina at Charlotte, 9201 University City Boulevard, Charlotte, North Carolina 28223, United States
| | - Javier D Gomez
- Department of Chemical and Biomolecular Engineering, Vanderbilt University, PMB 351604, 2301 Vanderbilt Place, Nashville, Tennessee 37235, United States
| | - Maximilian J Helf
- Boyce Thompson Institute and Department of Chemistry and Chemical Biology, Cornell University, 533 Tower Road, Ithaca, New York 14853, United States
| | - Katerina Kechris
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, 13001 East 17th Place B119, Aurora, Colorado 80045, United States
| | - Christine R Kirkpatrick
- San Diego Supercomputer Center, University of California San Diego, MC 0505, 9500 Gilman Drive, La Jolla, California 92093, United States
| | - Shuzhao Li
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, Connecticut 06032, United States
| | - Gary J Patti
- Department of Chemistry, Department of Medicine, and Siteman Cancer Center, Washington University in St. Louis, CB 1134, One Brookings Drive, St. Louis, Missouri 63130, United States
| | - Ryan S Renslow
- Biological Sciences Division, Pacific Northwest National Laboratory, P.O. Box 999, MSIN: K8-98, Richland, Washington 99352, United States.,Gene and Linda Voiland School of Chemical Engineering and Bioengineering, Washington State University, P.O. Box 646515, Pullman, Washington 99164, United States
| | - Shankar Subramaniam
- San Diego Supercomputer Center, University of California San Diego, MC 0505, 9500 Gilman Drive, La Jolla, California 92093, United States.,Department of Bioengineering, Department of Computer Science and Engineering, Department of Cellular and Molecular Medicine, and Department of Chemistry and Biochemistry, University of California San Diego, 9500 Gilman Drive #0412, La Jolla, California 92093, United States
| | - Mukesh Verma
- Epidemiology and Genomics Research Program, National Cancer Institute, National Institutes of Health, Suite 4E102, 9609 Medical Center Drive, MSC 9763, Rockville, Maryland 20850, United States
| | - Jianguo Xia
- Faculty of Agricultural and Environmental Sciences, McGill University, 21111 Lakeshore Road, Ste. Anne de Bellevue, Quebec H9X 3 V9, Canada
| | - Jamey D Young
- Department of Chemical and Biomolecular Engineering, Vanderbilt University, PMB 351604, 2301 Vanderbilt Place, Nashville, Tennessee 37235, United States.,Department of Molecular Physiology and Biophysics, Vanderbilt University, PMB 351604, 2301 Vanderbilt Place, Nashville, Tennessee 37235, United States
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47
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Sasi S, Rayaroth MP, Aravindakumar CT, Aravind UK. Occurrence, distribution and removal of organic micro-pollutants in a low saline water body. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 749:141319. [PMID: 32822914 DOI: 10.1016/j.scitotenv.2020.141319] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Revised: 07/19/2020] [Accepted: 07/27/2020] [Indexed: 06/11/2023]
Abstract
A low saline backwater canal, mainly utilized for domestic and agricultural purposes, has been analyzed for the possible presence of organic micropollutants (OMP) and their potential removal was explored by multilayered microfiltration membranes. The qualitative as well as quantitative analysis were carried out for a span of one year using the technique of liquid chromatography connected with high resolution mass spectrometry (LC-Q-TOF-MS). The identification of the formally unknown compounds was initially done using non-target analysis based on the mass accuracy, isotopic pattern and MS/MS spectral interpretation. Results of the non target screening revealed the presence of 11 OMPs. Five of these OMPs were confirmed using standards; these include chlorophene (CHP), oxybenzone (OXY), N, N-diethyl-meta-toluamide (DEET), N, N-diethyl-benzamide (DEB) and dibutyl phthalate (DBP). Among the confirmed OMPs, the highest concentration was observed for DBP (244.61 ng l-1). The most frequently observed OMP in the study area was DBP while the least was DEB which is an insect repellent as well as a degradation product of DEET. The ecological risk associated with the target compounds has also been analyzed by calculating the risk quotient (RQ) and the results revealed that at the detected levels, these compounds are capable of causing low to medium risk. Low pressure (<0.3 bar) filtrations of the compounds were attempted using microfiltration (MF) and, poly(ethyleneimine)/poly(styrene sulfonate) (PEI/PSS) multi-layered MF membrane for spiked ultrapure water and also for natural water from the back-water canal. The batch mode illustrates nearly complete removal of CHP and OXY in spiked solutions and a good removal efficiency from natural water. The effect of coexisting ions and surfactants in feed is also illustrated. The high efficiency of the removal of both CHP and OXY, in such a complex medium highlights the potential application of the present method for the removal of similar OMPs in natural waters.
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Affiliation(s)
- Subha Sasi
- Advanced Centre of Environmental Studies and Sustainable Development, Mahatma Gandhi University, Kottayam 686560, Kerala, India
| | - Manoj P Rayaroth
- School of Environmental Sciences, Mahatma Gandhi University, Kottayam 686560, Kerala, India
| | - Charuvila T Aravindakumar
- School of Environmental Sciences, Mahatma Gandhi University, Kottayam 686560, Kerala, India; Inter University Instrumentation Centre, Mahatma Gandhi University, Kottayam 686560, Kerala, India
| | - Usha K Aravind
- School of Environmental Studies, Cochin University of Science and Technology, Kochi 682022, Kerala, India.
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48
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Guo Z, Huang S, Wang J, Feng YL. Recent advances in non-targeted screening analysis using liquid chromatography - high resolution mass spectrometry to explore new biomarkers for human exposure. Talanta 2020; 219:121339. [DOI: 10.1016/j.talanta.2020.121339] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Revised: 05/16/2020] [Accepted: 06/09/2020] [Indexed: 12/29/2022]
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49
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Bjedov I, Cochemé HM, Foley A, Wieser D, Woodling NS, Castillo-Quan JI, Norvaisas P, Lujan C, Regan JC, Toivonen JM, Murphy MP, Thornton J, Kinghorn KJ, Neufeld TP, Cabreiro F, Partridge L. Fine-tuning autophagy maximises lifespan and is associated with changes in mitochondrial gene expression in Drosophila. PLoS Genet 2020; 16:e1009083. [PMID: 33253201 PMCID: PMC7738165 DOI: 10.1371/journal.pgen.1009083] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2019] [Revised: 12/15/2020] [Accepted: 08/26/2020] [Indexed: 01/26/2023] Open
Abstract
Increased cellular degradation by autophagy is a feature of many interventions that delay ageing. We report here that increased autophagy is necessary for reduced insulin-like signalling (IIS) to extend lifespan in Drosophila and is sufficient on its own to increase lifespan. We first established that the well-characterised lifespan extension associated with deletion of the insulin receptor substrate chico was completely abrogated by downregulation of the essential autophagy gene Atg5. We next directly induced autophagy by over-expressing the major autophagy kinase Atg1 and found that a mild increase in autophagy extended lifespan. Interestingly, strong Atg1 up-regulation was detrimental to lifespan. Transcriptomic and metabolomic approaches identified specific signatures mediated by varying levels of autophagy in flies. Transcriptional upregulation of mitochondrial-related genes was the signature most specifically associated with mild Atg1 upregulation and extended lifespan, whereas short-lived flies, possessing strong Atg1 overexpression, showed reduced mitochondrial metabolism and up-regulated immune system pathways. Increased proteasomal activity and reduced triacylglycerol levels were features shared by both moderate and high Atg1 overexpression conditions. These contrasting effects of autophagy on ageing and differential metabolic profiles highlight the importance of fine-tuning autophagy levels to achieve optimal healthspan and disease prevention.
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Affiliation(s)
- Ivana Bjedov
- Institute of Healthy Ageing, Research Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
- UCL Cancer Institute, Paul O'Gorman Building, London United Kingdom
- Max Planck Institute for Biology of Ageing, Cologne, Germany
| | - Helena M. Cochemé
- Institute of Healthy Ageing, Research Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
- Max Planck Institute for Biology of Ageing, Cologne, Germany
- MRC London Institute of Medical Sciences, Imperial College London, Du Cane Road, London, United Kingdom
| | - Andrea Foley
- Institute of Healthy Ageing, Research Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
- MRC London Institute of Medical Sciences, Imperial College London, Du Cane Road, London, United Kingdom
| | - Daniela Wieser
- EMBL European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Nathaniel S. Woodling
- Institute of Healthy Ageing, Research Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Jorge Iván Castillo-Quan
- Institute of Healthy Ageing, Research Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
- Max Planck Institute for Biology of Ageing, Cologne, Germany
- Section on Islet Cell and Regenerative Biology, Research Division, Joslin Diabetes Center, Boston MA, United States of America
- Department of Genetics and Harvard Stem Cell Institute, Harvard Medical School, Boston MA, United States of America
| | - Povilas Norvaisas
- Institute of Structural and Molecular Biology, University College London, London, United Kingdom
| | - Celia Lujan
- UCL Cancer Institute, Paul O'Gorman Building, London United Kingdom
| | - Jennifer C. Regan
- Institute of Healthy Ageing, Research Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
- Max Planck Institute for Biology of Ageing, Cologne, Germany
| | - Janne M. Toivonen
- Institute of Healthy Ageing, Research Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
- LAGENBIO, Facultad de Veterinaria-IIS, IA2-CITA, CIBERNED, Universidad de Zaragoza, Zaragoza, Spain
| | - Michael P. Murphy
- MRC Mitochondrial Biology Unit, the Keith Peters Building, University of Cambridge, Cambridge, United Kingdom
| | - Janet Thornton
- EMBL European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Kerri J. Kinghorn
- Institute of Healthy Ageing, Research Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
| | - Thomas P. Neufeld
- Department of Genetics, Cell Biology and Development, University of Minnesota, 321 Church St. SE, Minneapolis, MN, United States of America
| | - Filipe Cabreiro
- MRC London Institute of Medical Sciences, Imperial College London, Du Cane Road, London, United Kingdom
- Institute of Structural and Molecular Biology, University College London, London, United Kingdom
| | - Linda Partridge
- Institute of Healthy Ageing, Research Department of Genetics, Evolution and Environment, University College London, London, United Kingdom
- Max Planck Institute for Biology of Ageing, Cologne, Germany
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50
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Haddad PR, Taraji M, Szücs R. Prediction of Analyte Retention Time in Liquid Chromatography. Anal Chem 2020; 93:228-256. [DOI: 10.1021/acs.analchem.0c04190] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Paul R. Haddad
- Australian Centre for Research on Separation Science, School of Natural Sciences, University of Tasmania, Private Bag 75, Hobart, Tasmania, Australia 7001
| | - Maryam Taraji
- Australian Centre for Research on Separation Science, School of Natural Sciences, University of Tasmania, Private Bag 75, Hobart, Tasmania, Australia 7001
- The Australian Wine Research Institute, P.O. Box 197, Adelaide, South Australia 5064, Australia
- Metabolomics Australia, P.O. Box 197, Adelaide, South Australia 5064, Australia
| | - Roman Szücs
- Pfizer R&D UK Limited, Ramsgate Road, Sandwich CT13 9NJ, U.K
- Department of Analytical Chemistry, Faculty of Natural Sciences, Comenius University in Bratislava, Mlynská Dolina CH2, Ilkovičova 6, SK-84215 Bratislava, Slovakia
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