Article
Endocrinology & Metabolism
Afshan Masood, Minnie Jacob, Xinyun Gu, Mai Abdel Jabar, Hicham Benabdelkamel, Imran Nizami, Liang Li, Majed Dasouki, Anas M. Abdel Rahman
Summary: Metabolomic profiling revealed alterations in different amino acids and dipeptides in CF patients, with two metabolites identified as potentially highly sensitive biomarkers for CF.
Article
Biochemistry & Molecular Biology
Zhanxuan E. Wu, Marlena C. Kruger, Garth J. S. Cooper, Ivana R. Sequeira, Anne-Thea McGill, Sally D. Poppitt, Karl Fraser
Summary: Untargeted metabolomics of blood samples has been widely used to study metabolic alterations in diseases and identify biomarkers. This study found that the concentration of metabolites in plasma was more reflective of the liver profile than muscle or adipose tissue, highlighting the importance of considering the metabolomic relationship between different tissues and plasma.
Article
Plant Sciences
Alison Green, Guillermo Federico Padilla-Gonzalez, Methee Phumthum, Monique S. J. Simmonds, Nicholas J. Sadgrove
Summary: Commercially used for treating chronic venous insufficiency, A. hippocastanum L. fruits contain beta-aescin which exhibits anti-inflammatory effects. However, diverse organ-specific secondary metabolites have been overlooked as potential pharmacological opportunities. Untargeted metabolomics analysis revealed unique chemical profiles in different organs of Aesculus plants, with fruits showing the highest antifungal and antioxidant activities. This suggests potential therapeutic leads for further exploration in the entire genus of Aesculus.
Article
Food Science & Technology
Frank Klont, Stepan Stepanovic, Daan Kremer, Ron Bonner, Daan J. Touw, Eelko Hak, Stephan J. L. Bakker, Gerard Hopfgartner
Summary: This study describes improved strategies for detecting chemical exposures and their application in a non-targeted metabolomics study on kidney transplant recipients. The new methods can detect more chronic exposures and improve the reliability of detecting intermittent exposures.
FOOD AND CHEMICAL TOXICOLOGY
(2022)
Article
Psychiatry
Meng Song, Ya Liu, Jiahui Zhou, Han Shi, Xi Su, Minglong Shao, Yongfeng Yang, Xiujuan Wang, Jingyuan Zhao, Dong Guo, Qing Liu, Luwen Zhang, Yan Zhang, Luxian Lv, Wenqiang Li
Summary: Using liquid chromatography mass spectrometry, the study identified potential biomarkers associated with the diagnosis and treatment of schizophrenia. Biomarker panels were selected to distinguish between schizophrenia and healthy controls, as well as between schizophrenia before and after medication. Disturbances in lipid metabolism, sulfation modification, tryptophan metabolism, anti-inflammatory and antioxidant systems, and unsaturated fatty acids metabolism were observed in schizophrenia. These findings could contribute to the development of objective diagnostic and drug treatment monitoring tools for schizophrenia.
PSYCHIATRY RESEARCH
(2023)
Article
Immunology
Meilin Ding, Zha Zhen, Mei Ju, Suolang Quzong, Xuesi Zeng, Xiaoxia Guo, Rui Li, Mingming Xu, Jingjing Xu, Hongyang Li, Wei Zhang
Summary: Our study found significant differences in the metabolomic profiles between vitiligo patients and healthy subjects in both plateau and plain areas, with significantly higher levels of S1P in the serum of vitiligo patients and healthy subjects in the plateau area. These findings suggest that alterations in S1P metabolism may be involved in the pathogenesis of vitiligo.
CLINICAL IMMUNOLOGY
(2023)
Review
Chemistry, Analytical
Hanne Roberg-Larsen, Elsa Lundanes, Tuula A. Nyman, Frode S. Berven, Steven Ray Wilson
Summary: Single-cell analysis provides in-depth insights into diseases and diagnostics, with liquid chromatography playing a crucial role. The development of novel sample preparation techniques and improvements in mass spectrometry are enhancing the promise of single-cell analysis. However, technical challenges and the need for higher throughput and robustness may lead to the reinvention of alternative nano LC column formats.
ANALYTICA CHIMICA ACTA
(2021)
Article
Chemistry, Analytical
Yasin El Abiead, Christoph Bueschl, Lisa Panzenboeck, Mingxun Wang, Maria Doppler, Bernhard Seidl, Juergen Zanghellini, Pieter C. Dorrestein, Gunda Koellensperger
Summary: This study utilized 13C labeled and unlabeled Pichia pastoris extracts to identify heterogeneous multimerization in biological samples and successfully annotated the monomeric partners of these heteromers. Additionally, they created the first MS/MS library that included data from heteromultimers and demonstrated the relevance of these newly annotated ions to other publicly available datasets. Furthermore, their workflow detected metabolite features originating from heterodimers in other datasets as well.
ANALYTICA CHIMICA ACTA
(2022)
Article
Biochemical Research Methods
Eva-Maria Harrieder, Fleming Kretschmer, Sebastian Boecker, Michael Witting
Summary: Metabolomics and lipidomics involve the large-scale analysis of metabolites, requiring advanced analytical methods. Liquid Chromatography-Mass Spectrometry (LC-MS) is a commonly used technique that provides different selectivities in separation and high sensitivity in detection. Due to the huge chemical diversity, there is no single analysis method that can cover the entire range of metabolites or lipids, leading to the use of different separation methods. This review explores the current use of LC-MS in metabolomics and lipidomics using data from public databases, and highlights potential future trends and improvements needed.
JOURNAL OF CHROMATOGRAPHY B-ANALYTICAL TECHNOLOGIES IN THE BIOMEDICAL AND LIFE SCIENCES
(2022)
Article
Biochemistry & Molecular Biology
Minnie Jacob, Refat M. Nimer, Mohamad S. Alabdaljabar, Essa M. Sabi, Mysoon M. Al-Ansari, Maged Housien, Khalid M. Sumaily, Lina A. Dahabiyeh, Anas M. Abdel Rahman
Summary: This study used liquid chromatography-mass spectrometry (LC-MS) metabolomics to analyze the metabolome of serum from patients with nephrotic syndrome (NS) and found significant changes in 176 metabolites compared to the control group. Dysregulation of arginine, proline, and tryptophan metabolism, as well as arginine, phenylalanine, tyrosine, and tryptophan biosynthesis, were the most common metabolic pathways affected in NS.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2022)
Article
Pharmacology & Pharmacy
Yanru Zhu, Feng Wang, Jiatong Han, Yunli Zhao, Miao Yu, Mingyan Ma, Zhiguo Yu
Summary: This study investigated the preventive effect and mechanism of L-theanine on depression in juvenile rats. The results confirmed the preventive effect of L-theanine and identified potential biomarkers related to its treatment. Overall, L-theanine achieved significant preventive results on depression by regulating various aspects of the body, such as amino acids, lipids, and inflammation.
JOURNAL OF PHARMACEUTICAL ANALYSIS
(2023)
Article
Food Science & Technology
Dhara Dixit
Summary: This study reveals the biochemical traits, mineral makeup, and secondary metabolite outline of Iyengaria stellata using untargeted metabolite profiling. A total of 108 putative metabolites were detected, including steroids, terpenoids, ketones, esters, polyphenols, anthraquinones, tocopherol, etc. The study highlights the potential of I. stellata as a natural source in pharmaceutical and nutraceutical compositions.
Article
Endocrinology & Metabolism
Jun Kou, Chunyang He, Lin Cui, Zhengping Zhang, Wei Wang, Li Tan, Da Liu, Wei Zheng, Wei Gu, Ning Xia
Summary: The study on Chinese postmenopausal women with osteoporosis identified potential biomarkers related to metabolic pathway disorders, providing new insights for early diagnosis. The findings suggest that metabonomic analysis has great potential for application in postmenopausal women with osteoporosis.
FRONTIERS IN ENDOCRINOLOGY
(2022)
Article
Agronomy
Yongquan Li, Bipei Zhang, Runsheng Huang, Min Wen, Leying Huang, Yiting Su, Yanjun Sun, Ning Wang, Wei Guo
Summary: The drought stress responses of plants are complex regulatory mechanisms that can be studied through metabolomics. In this study, the effect of drought stress on a drought-tolerant cultivar of Belosynapsis ciliata was investigated using metabolomic analysis. Different metabolites and pathways related to drought tolerance were identified.
Article
Dermatology
Qiying Xiong, Daoqing Zhong, Qian Li, Yihui Yu, Sanquan Zhang, Jingyao Liang, Xibao Zhang
Summary: Recent studies have found that certain metabolites in the blood and urine are involved in the development of psoriasis, but the research on skin metabolomics for psoriasis is limited. In this study, researchers compared the metabolic profiles of lesional and nonlesional skin from 12 psoriasis patients using liquid chromatography-mass spectrometry. They identified several metabolites that were significantly different between lesional and nonlesional skin, mainly related to amino acid, lipid, and nucleotide metabolism. Fourteen potential biomarkers were identified, some of which were correlated with disease severity.
EXPERIMENTAL DERMATOLOGY
(2023)
Article
Biochemical Research Methods
Susanta Das, Kiyoto Aramis Tanemura, Laleh Dinpazhoh, Mithony Keng, Christina Schumm, Lydia Leahy, Carter K. Asef, Markace Rainey, Arthur S. Edison, Facundo M. Fernandez, Kenneth M. Merz
Summary: In this study, an efficient CCS computational workflow was developed to accurately predict unknown structures using a machine learning model and standard DFT methods. TWIMS experiments were performed to validate the experimental values and assess uncertainties. The workflow yielded accurate structural predictions and provided unique insights into preferred conformations.
JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY
(2022)
Article
Multidisciplinary Sciences
Moran Frenkel-Pinter, Marcos Bouza, Facundo M. Fernandez, Luke J. Leman, Loren Dean Williams, Nicholas Hud, Aikomari Guzman-Martinez
Summary: In this study, the authors report the synthesis of thiodepsipeptides and HS-peptides under mild temperatures and various pH conditions, suggesting that they could have formed on early prebiotic Earth.
NATURE COMMUNICATIONS
(2022)
Article
Oncology
Samyukta Sah, Xin Ma, Andro Botros, David A. Gaul, Sylvia R. Yun, Eun Young Park, Olga Kim, Samuel G. Moore, Jaeyeon Kim, Facundo M. Fernandez
Summary: This study investigated the serum metabolomic and spatial lipidomic profiles of an ovarian cancer mouse model, revealing temporal trends of lipid classes, amino acids, and TCA cycle metabolites associated with HGSC progression. The results highlight the critical role of lipid and fatty acid metabolism, amino acid biosynthesis, TCA cycle, and ovarian steroidogenesis in the onset and development of HGSC.
Article
Biochemistry & Molecular Biology
Mehak Arora, Stephen C. Zambrzycki, Joshua M. Levy, Annette Esper, Jennifer K. Frediani, Cassandra L. Quave, Facundo M. Fernandez, Rishikesan Kamaleswaran
Summary: This study explores the use of SPME and ambient ionization MS to rapidly acquire VOC signatures of bacteria and fungi, and presents a new approach for the identification of pathogens as a potential non-invasive clinical diagnostic tool for point-of-care applications.
Editorial Material
Chemistry, Multidisciplinary
Cesar Menor-Salvan, Bradley T. Burcar, Marcos Bouza, David M. Fialho, Facundo M. Fernandez, Nicholas Hud
CHEMISTRY-A EUROPEAN JOURNAL
(2022)
Article
Biochemistry & Molecular Biology
Samyukta Sah, Sylvia R. Yun, David A. Gaul, Andro Botros, Eun Young Park, Olga Kim, Jaeyeon Kim, Facundo M. Fernandez
Summary: In this study, a targeted microchip CE-HRMS method was developed to analyze multiple metabolites in mouse serum samples, revealing metabolic alterations during the development and progression of high-grade serous carcinoma.
Article
Chemistry, Analytical
Carter K. Asef, Markace A. Rainey, Brianna M. Garcia, Goncalo J. Gouveia, Amanda O. Shaver, Franklin E. Leach, Alison M. Morse, Arthur S. Edison, Lauren M. McIntyre, Facundo M. Fernandez
Summary: Ion mobility spectrometry (IM) provides valuable data for identifying unknown metabolites in non-targeted metabolomics. This study presents a workflow using de novo molecular formula annotation, MS/MS structure elucidation, and machine learning predictions to identify differential unknown metabolites in Caenorhabditis elegans mutant strains. However, the performance of this approach is limited by instrumentation and data analysis challenges, resulting in a relatively low success rate in filtering candidate structures.
ANALYTICAL CHEMISTRY
(2023)
Article
Biochemical Research Methods
Malena Manzi, Nicolas Zabalegui, Maria Eugenia Monge
Summary: The study evaluated a lipid panel that differentiated healthy individuals from clear cell renal cell carcinoma patients, and found that it could serve as an indicator for metabolic restoration after surgery. Specific lipids were able to distinguish patients with poor prognosis and could be used as prognostic tools during patient follow-up care.
JOURNAL OF PROTEOME RESEARCH
(2023)
Article
Multidisciplinary Sciences
Philip Fernandes, Yash Sharma, Fatima Zulqarnain, Brooklyn McGrew, Aman Shrivastava, Lubaina Ehsan, Dawson Payne, Lillian Dillard, Deborah Powers, Isabelle Aldridge, Jason Matthews, Subra Kugathasan, Facundo M. Fernandez, David Gaul, Jason A. Papin, Sana Syed
Summary: Crohn's disease is a chronic inflammatory disease of the gastrointestinal tract. The lack of highly specific biomarkers for disease management is a problem in current diagnostics and treatment approaches. This study presents a framework that utilizes machine learning and metabolic modeling to study altered metabolic reactions in patients with Crohn's disease, aiming to discover novel diagnostic biomarkers and therapeutic targets.
SCIENTIFIC REPORTS
(2023)
Article
Chemistry, Analytical
Arina A. Nikitina, Alexandria Van Grouw, Tanya Roysam, Danning Huang, Facundo M. Fernandez, Melissa L. Kemp
Summary: Induced pluripotent stem cells (iPSCs) have potential in regenerative medicine, but there is a lack of quality control algorithms for early differentiation stages. In this research, we studied changes in iPSC lipid profiles during initial loss of pluripotency using confocal microscopy and MALDI mass spectrometry imaging. We identified informative phosphatidylethanolamine (PE) and phosphatidylinositol (PI) species that can reveal iPSC lineage bifurcation metabolically. Machine learning analysis showed that PI species emerged as early metabolic markers of pluripotency loss, preceding changes in the Oct4 transcription factor. Manipulation of phospholipids and inhibition of phosphatidylethanolamine N-methyltransferase affected colony organization and pluripotency maintenance.
ANALYTICAL CHEMISTRY
(2023)
Article
Biochemical Research Methods
Olatomiwa O. Bifarin, Samyukta Sah, David A. Gaul, Samuel G. Moore, Ruihong Chen, Murugesan Palaniappan, Jaeyeon Kim, Martin M. Matzuk, Facundo M. Fernandez
Summary: Ovarian cancer is a deadly cancer that affects the female reproductive system and is often asymptomatic until later stages. Little is known about the metabolic changes in the early stages of high-grade serous ovarian cancer. This study used a mouse model and machine learning analysis to examine the temporal changes in serum lipidome. The results showed unique alterations in cell membrane stability, proliferation, and survival during cancer development and progression, providing potential targets for early detection and prognosis of ovarian cancer.
JOURNAL OF PROTEOME RESEARCH
(2023)
Article
Cell & Tissue Engineering
Alexandria Van Grouw, Maxwell B. Colonna, Ty S. Maughon, Xunan Shen, Andrew M. Larey, Samuel G. Moore, Carolyn Yeago, Facundo M. Fernandez, Arthur S. Edison, Steven L. Stice, Annie C. Bowles-Welch, Ross A. Marklein
Summary: Mesenchymal stromal cells (MSCs) have functional heterogeneity in immunomodulatory function. Metabolic profiling of MSCs during expansion process using nuclear magnetic resonance (NMR) and mass spectrometry (MS) identified predictive metabolites for MSC immunomodulatory function. Consensus intracellular metabolites included lipid classes while consensus media metabolites included proline, phenylalanine, and pyruvate. Pathway analysis revealed metabolic pathways associated with MSC function. This study provides a framework for identifying predictive metabolites and guiding MSC manufacturing efforts.
Article
Chemistry, Analytical
Daniel D. Vallejo, Aleksandra Popowich, Julie Arslanoglu, Caroline Tokarski, Facundo M. Fernandez
ANALYTICA CHIMICA ACTA
(2023)
Editorial Material
Biochemical Research Methods
Facundo Fernandez, Lingjun Li
JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY
(2023)
Article
Endocrinology & Metabolism
Gabriel Riquelme, Emmanuel Ezequiel Bortolotto, Matias Dombald, Maria Eugenia
Summary: This study presents a model to describe the sources of variation in LC-MS-based untargeted metabolomics measurements and provides a comprehensive curation pipeline and quality assessment tools for data quality review.