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Wang Y, Du K, Wang Q, Yang X, Meng D. A multidimensional strategy for characterization, distinction, and quality control of two Clinopodium medicinal plants. JOURNAL OF ETHNOPHARMACOLOGY 2024; 327:118019. [PMID: 38467319 DOI: 10.1016/j.jep.2024.118019] [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: 01/14/2024] [Revised: 02/27/2024] [Accepted: 03/04/2024] [Indexed: 03/13/2024]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Clinopodium chinense Kuntze (CC) and Clinopodium polycephalum (Vaniot) C. Y. Wu & S. J. Hsuan (CP) are both included in the Pharmacopoeia of the People's Republic of China (edition 2020) as the legitimate source of "Duan Xue Liu" (DXL), which is a crucial traditional Chinese medicine used as a clinical remedy for bleeding diseases. However, the differences in plant endogenous metabolites and bioactivities between CC and CP are still unclear. AIM OF THE STUDY This study aims to provide a scientific basis to investigate the differences between CC and CP ensuring the efficient and safe use of DXL. MATERIALS AND METHODS A multidimensional strategy including plant metabolomics, digital reference standard (DRS) analyzer, and biological activities assay was creatively constructed for the characterization, distinction, and quality control of CC and CP. RESULTS There were apparent differences in the metabolites between CC and CP. 7 compounds contributing to the differences were successfully identified. On that basis, linear calibration using two reference substances (LCTRS) methods was proved as a more accurate and specific quality analysis method for CC and CP. In addition, bioactivity assays showed that both CC and CP exhibited obvious hemostatic activity, while CC showed greater potential to resist inflammation and free radicals. CONCLUSION In summary, it was the first time to investigate the chemical constituents and bioactivities differences between CC and CP with the help of plant metabolomics, DRS study, and biological activity assays. These two plants were significantly separated in the integrated analysis, suggesting that we should pay attention to the distinction to prevent unexpected risks caused by medicinal materials.
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Affiliation(s)
- Yumeng Wang
- School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, 110016, PR China
| | - Kaicheng Du
- School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, 110016, PR China
| | - Quanyou Wang
- School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, 110016, PR China
| | - Xinyong Yang
- School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, 110016, PR China
| | - Dali Meng
- School of Traditional Chinese Materia Medica, Shenyang Pharmaceutical University, Shenyang, 110016, PR China.
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Ilyas K, Iqbal H, Akash MSH, Rehman K, Hussain A. Heavy metal exposure and metabolomics analysis: an emerging frontier in environmental health. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024:10.1007/s11356-024-33735-7. [PMID: 38780845 DOI: 10.1007/s11356-024-33735-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Accepted: 05/16/2024] [Indexed: 05/25/2024]
Abstract
Exposure to heavy metals in various populations can lead to extensive damage to different organs, as these metals infiltrate and bioaccumulate in the human body, causing metabolic disruptions in various organs. To comprehensively understand the metal homeostasis, inter-organ "traffic," and extensive metabolic alterations resulting from heavy metal exposure, employing complementary analytical methods is crucial. Metabolomics is pivotal in unraveling the intricacies of disease vulnerability by furnishing thorough understandings of metabolic changes linked to different metabolic diseases. This field offers exciting prospects for enhancing the disease prevention, early detection, and tailoring treatment approaches to individual needs. This article consolidates the existing knowledge on disease-linked metabolic pathways affected by the exposure of diverse heavy metals providing concise overview of the underlying impact mechanisms. The main aim is to investigate the connection between the altered metabolic pathways and long-term complex health conditions induced by heavy metals such as diabetes mellitus, cardiovascular diseases, renal disorders, inflammation, neurodegenerative diseases, reproductive risks, and organ damage. Further exploration of common pathways may unveil the shared targets for treating associated pathological conditions. In this article, the role of metabolomics in disease susceptibility is emphasized that metabolomics is expected to be routinely utilized for the diagnosis and monitoring of diseases and practical value of biomarkers derived from metabolomics, as well as determining their appropriate integration into extensive clinical settings.
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Affiliation(s)
- Kainat Ilyas
- Department of Pharmaceutical Chemistry, Government College University, Faisalabad, Pakistan
| | - Hajra Iqbal
- Department of Pharmaceutical Chemistry, Government College University, Faisalabad, Pakistan
| | | | - Kanwal Rehman
- Department of Pharmacy, The Women University, Multan, Pakistan
| | - Amjad Hussain
- Institute of Chemistry, University of Okara, Okara, Pakistan
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3
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Wang M, Jin L, Hang-Mei Leung P, Wang-Ngai Chow F, Zhao X, Chen H, Pan W, Liu H, Li S. Advancements in magnetic nanoparticle-based biosensors for point-of-care testing. Front Bioeng Biotechnol 2024; 12:1393789. [PMID: 38725992 PMCID: PMC11079239 DOI: 10.3389/fbioe.2024.1393789] [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: 02/29/2024] [Accepted: 04/09/2024] [Indexed: 05/12/2024] Open
Abstract
The significance of point-of-care testing (POCT) in early clinical diagnosis and personalized patient care is increasingly recognized as a crucial tool in reducing disease outbreaks and improving patient survival rates. Within the realm of POCT, biosensors utilizing magnetic nanoparticles (MNPs) have emerged as a subject of substantial interest. This review aims to provide a comprehensive evaluation of the current landscape of POCT, emphasizing its growing significance within clinical practice. Subsequently, the current status of the combination of MNPs in the Biological detection has been presented. Furthermore, it delves into the specific domain of MNP-based biosensors, assessing their potential impact on POCT. By combining existing research and spotlighting pivotal discoveries, this review enhances our comprehension of the advancements and promising prospects offered by MNP-based biosensors in the context of POCT. It seeks to facilitate informed decision-making among healthcare professionals and researchers while also promoting further exploration in this promising field of study.
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Affiliation(s)
- Miaomiao Wang
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou, China
| | - Lian Jin
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou, China
| | - Polly Hang-Mei Leung
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Franklin Wang-Ngai Chow
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Xiaoni Zhao
- Guangzhou Wanfu Biotechnology Company, Guangzhou, China
| | - Hui Chen
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou, China
| | - Wenjing Pan
- Hengyang Medical School, University of South China, Hengyang, China
| | - Hongna Liu
- Hengyang Medical School, University of South China, Hengyang, China
| | - Song Li
- Hunan Key Laboratory of Biomedical Nanomaterials and Devices, Hunan University of Technology, Zhuzhou, China
- Hengyang Medical School, University of South China, Hengyang, China
- National Health Commission Key Laboratory of Birth Defect Research and Prevention, Hunan Provincial Maternal and Child Healthcare Hospital, Changsha, China
- Key Laboratory of Rare Pediatric Diseases, Ministry of Education, University of South China, Hengyang, China
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4
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Aresta AM, De Vietro N, Zambonin C. Analysis and Characterization of the Extracellular Vesicles Released in Non-Cancer Diseases Using Matrix-Assisted Laser Desorption Ionization/Mass Spectrometry. Int J Mol Sci 2024; 25:4490. [PMID: 38674075 PMCID: PMC11050240 DOI: 10.3390/ijms25084490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2024] [Revised: 04/09/2024] [Accepted: 04/16/2024] [Indexed: 04/28/2024] Open
Abstract
The extracellular vesicles (EVs) released by cells play a crucial role in intercellular communications and interactions. The direct shedding of EVs from the plasma membrane represents a fundamental pathway for the transfer of properties and information between cells. These vesicles are classified based on their origin, biogenesis, size, content, surface markers, and functional features, encompassing a variety of bioactive molecules that reflect the physiological state and cell type of origin. Such molecules include lipids, nucleic acids, and proteins. Research efforts aimed at comprehending EVs, including the development of strategies for their isolation, purification, and characterization, have led to the discovery of new biomarkers. These biomarkers are proving invaluable for diagnosing diseases, monitoring disease progression, understanding treatment responses, especially in oncology, and addressing metabolic, neurological, infectious disorders, as well as advancing vaccine development. Matrix-Assisted Laser Desorption Ionization (MALDI)/Mass Spectrometry (MS) stands out as a leading tool for the analysis and characterization of EVs and their cargo. This technique offers inherent advantages such as a high throughput, minimal sample consumption, rapid and cost-effective analysis, and user-friendly operation. This review is mainly focused on the primary applications of MALDI-time-of-flight (TOF)/MS in the analysis and characterization of extracellular vesicles associated with non-cancerous diseases and pathogens that infect humans, animals, and plants.
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Affiliation(s)
- Antonella Maria Aresta
- Department of Biosciences, Biotechnology and Environment, University of Bari “Aldo Moro”, Via E. Orabona 4, 70126 Bari, Italy; (N.D.V.)
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Raynor A, Haouari W, Lebredonchel E, Foulquier F, Fenaille F, Bruneel A. Biochemical diagnosis of congenital disorders of glycosylation. Adv Clin Chem 2024; 120:1-43. [PMID: 38762238 DOI: 10.1016/bs.acc.2024.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/20/2024]
Abstract
Congenital disorders of glycosylation (CDG) are one of the fastest growing groups of inborn errors of metabolism, comprising over 160 described diseases to this day. CDG are characterized by a dysfunctional glycosylation process, with molecular defects localized in the cytosol, the endoplasmic reticulum, or the Golgi apparatus. Depending on the CDG, N-glycosylation, O-glycosylation and/or glycosaminoglycan synthesis can be affected. Various proteins, lipids, and glycosylphosphatidylinositol anchors bear glycan chains, with potential impacts on their folding, targeting, secretion, stability, and thus, functionality. Therefore, glycosylation defects can have diverse and serious clinical consequences. CDG patients often present with a non-specific, multisystemic syndrome including neurological involvement, growth delay, hepatopathy and coagulopathy. As CDG are rare diseases, and typically lack distinctive clinical signs, biochemical and genetic testing bear particularly important and complementary diagnostic roles. Here, after a brief introduction on glycosylation and CDG, we review historical and recent findings on CDG biomarkers and associated analytical techniques, with a particular emphasis on those with relevant use in the specialized clinical chemistry laboratory. We provide the reader with insights and methods which may help them properly assist the clinician in navigating the maze of glycosylation disorders.
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Affiliation(s)
- Alexandre Raynor
- AP-HP, Biochimie Métabolique et Cellulaire, Hôpital Bichat, Paris, France
| | - Walid Haouari
- INSERM UMR1193, Faculté de Pharmacie, Université Paris-Saclay, Orsay, France
| | | | - François Foulquier
- Université de Lille, CNRS, UMR 8576-UGSF-Unité de Glycobiologie Structurale et Fonctionnelle, Lille, France
| | - François Fenaille
- Université Paris-Saclay, CEA, INRAE, Département Médicaments et Technologies pour la Santé, MetaboHUB, Gif sur Yvette, France.
| | - Arnaud Bruneel
- AP-HP, Biochimie Métabolique et Cellulaire, Hôpital Bichat, Paris, France; INSERM UMR1193, Faculté de Pharmacie, Université Paris-Saclay, Orsay, France.
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Jadoon S, Ali Q, Sami A, Haider MZ, Ashfaq M, Javed MA, Khan MA. DNA damage in inhabitants exposed to heavy metals near Hudiara drain, Lahore, Pakistan. Sci Rep 2024; 14:8408. [PMID: 38600156 PMCID: PMC11006874 DOI: 10.1038/s41598-024-58655-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 04/02/2024] [Indexed: 04/12/2024] Open
Abstract
The current study was conducted on the inhabitants living in the area adjacent to the Hudiara drain using bore water and vegetables adjacent to the Hudiara drain. Toxic heavy metals badly affect human health because of industrial environmental contamination. Particularly hundreds of millions of individuals globally have faced the consequences of consuming water and food tainted with pollutants. Concentrations of heavy metals in human blood were elevated in Hudiara drainings in Lahore city, Pakistan, due to highly polluted industrial effluents. The study determined the health effects of high levels of heavy metals (Cd, Cu, Zn, Fe, Pb, Ni, Hg, Cr) on residents of the Hudiara draining area, including serum MDA, 8-Isoprostane, 8-hydroxyguanosine, and creatinine levels. An absorption spectrophotometer was used to determine heavy metals in wate water, drinking water, soil, plants and human beings blood sampleas and ELISA kits were used to assess the level of 8-hydroxyguanosine, MDA, 8-Isoprostane in plasma serum creatinine level. Waste water samples, irrigation water samples, drinking water samples, Soil samples, Plants samples and blood specimens of adult of different weights and ages were collected from the polluted area of the Hudiara drain (Laloo and Mohanwal), and control samples were obtained from the unpolluted site Sheiikhpura, 60 km away from the site. Toxic heavy metals in blood damage the cell membrane and DNA structures, increasing the 8-hydroxyguanosine, MDA, creatinine, and 8-Isoprostane. Toxic metals contaminated bore water and vegetables, resulting in increased levels of creatinine, MDA, Isoprostane, and 8-hydroxy-2-guanosine in the blood of inhabitants from the adjacent area Hudiara drain compared to the control group. In addition,. This study also investigated heavy metal concentrations in meat and milk samples from buffaloes, cows, and goats. In meat, cow samples showed the highest Cd, Cu, Fe and Mn concentrations. In milk also, cows exhibited elevated Cu and Fe levels compared to goats. The results highlight species-specific variations in heavy metal accumulation, emphasizing the need for targeted monitoring to address potential health risks. The significant difference between the two groups i.e., the control group and the affected group, in all traits of the respondents (weight, age, heavy metal values MDA, 8-Isoprostane, 8-hydroxyguaniosine, and serum creatinine level). Pearson's correlation coefficient was calculated. The study has shown that the level of serum MDA, 8-Isoprostane, 8-hydroxyguaniosine, or creatinine has not significantly correlated with age, so it is independent of age. This study has proved that in Pakistan, the selected area of Lahore in the villages of Laloo and Mohanwal, excess of heavy metals in the human body damages the DNA and increases the level of 8-Isoprostane, MDA, creatinine, and 8-hydroxyguaniosine. As a result, National and international cooperation must take major steps to control exposure to heavy metals.
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Affiliation(s)
- Saima Jadoon
- Directorate of Curriculum and Teaching Education, Abbottabad, Pakistan.
- Institute of Molecular Biology and Biotechnology, University of Lahore, Lahore, Pakistan.
| | - Qurban Ali
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, University of the Punjab, P.O BOX. 54590, Lahore, Pakistan.
| | - Adnan Sami
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, University of the Punjab, P.O BOX. 54590, Lahore, Pakistan
| | - Muhammad Zeeshan Haider
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, University of the Punjab, P.O BOX. 54590, Lahore, Pakistan
| | - Muhammad Ashfaq
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, University of the Punjab, P.O BOX. 54590, Lahore, Pakistan
| | - Muhammad Arshad Javed
- Department of Plant Breeding and Genetics, Faculty of Agricultural Sciences, University of the Punjab, P.O BOX. 54590, Lahore, Pakistan
| | - Mudassar Ali Khan
- Department of Physiology, Rashid Latif Medical College, Lahore, 54000, Pakistan
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Singh R, Fatima E, Thakur L, Singh S, Ratan C, Kumar N. Advancements in CHO metabolomics: techniques, current state and evolving methodologies. Front Bioeng Biotechnol 2024; 12:1347138. [PMID: 38600943 PMCID: PMC11004234 DOI: 10.3389/fbioe.2024.1347138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 02/28/2024] [Indexed: 04/12/2024] Open
Abstract
Background: Investigating the metabolic behaviour of different cellular phenotypes, i.e., good/bad grower and/or producer, in production culture is important to identify the key metabolite(s)/pathway(s) that regulate cell growth and/or recombinant protein production to improve the overall yield. Currently, LC-MS, GC-MS and NMR are the most used and advanced technologies for investigating the metabolome. Although contributed significantly in the domain, each technique has its own biasness towards specific metabolites or class of metabolites due to various reasons including variability in the concept of working, sample preparation, metabolite-extraction methods, metabolite identification tools, and databases. As a result, the application of appropriate analytical technique(s) is very critical. Purpose and scope: This review provides a state-of-the-art technological insights and overview of metabolic mechanisms involved in regulation of cell growth and/or recombinant protein production for improving yield from CHO cultures. Summary and conclusion: In this review, the advancements in CHO metabolomics over the last 10 years are traced based on a bibliometric analysis of previous publications and discussed. With the technical advancement in the domain of LC-MS, GC-MS and NMR, metabolites of glycolytic and nucleotide biosynthesis pathway (glucose, fructose, pyruvate and phenylalanine, threonine, tryptophan, arginine, valine, asparagine, and serine, etc.) were observed to be upregulated in exponential-phase thereby potentially associated with cell growth regulation, whereas metabolites/intermediates of TCA, oxidative phosphorylation (aspartate, glutamate, succinate, malate, fumarate and citrate), intracellular NAD+/NADH ratio, and glutathione metabolic pathways were observed to be upregulated in stationary-phase and hence potentially associated with increased cell-specific productivity in CHO bioprocess. Moreover, each of technique has its own bias towards metabolite identification, indicating their complementarity, along with a number of critical gaps in the CHO metabolomics pipeline and hence first time discussed here to identify their potential remedies. This knowledge may help in future study designs to improve the metabolomic coverage facilitating identification of the metabolites/pathways which might get missed otherwise and explore the full potential of metabolomics for improving the CHO bioprocess performances.
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Affiliation(s)
- Rita Singh
- Translational Health Science and Technology Institute, Faridabad, India
- Jawaharlal Nehru University, New Delhi, India
| | - Eram Fatima
- Translational Health Science and Technology Institute, Faridabad, India
- Jawaharlal Nehru University, New Delhi, India
| | - Lovnish Thakur
- Translational Health Science and Technology Institute, Faridabad, India
- Jawaharlal Nehru University, New Delhi, India
| | - Sevaram Singh
- Translational Health Science and Technology Institute, Faridabad, India
- Jawaharlal Nehru University, New Delhi, India
| | - Chandra Ratan
- Translational Health Science and Technology Institute, Faridabad, India
- Jawaharlal Nehru University, New Delhi, India
| | - Niraj Kumar
- Translational Health Science and Technology Institute, Faridabad, India
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Badmos S, Noriega-Landa E, Holbrook KL, Quaye GE, Su X, Gao Q, Chacon AA, Adams E, Polascik TJ, Feldman AS, Annabi MM, Lee WY. Urinary volatile organic compounds in prostate cancer biopsy pathologic risk stratification using logistic regression and multivariate analysis models. Am J Cancer Res 2024; 14:192-209. [PMID: 38323272 PMCID: PMC10839326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Accepted: 12/15/2023] [Indexed: 02/08/2024] Open
Abstract
Prostate cancer (PCa) is the second leading cause of cancer-related death in American men after lung cancer. The current PCa diagnostic method, the serum prostate-specific antigen (PSA) test, is not specific, thus, alternatives are needed to avoid unnecessary biopsies and over-diagnosis of clinically insignificant PCa. To explore the application of metabolomics in such effort, urine samples were collected from 386 male adults aged 44-93 years, including 247 patients with biopsy-proven PCa and 139 with biopsy-proven negative results. The PCa-positive group was further subdivided into two groups: low-grade (ISUP Grade Group = 1; n = 139) and intermediate/high-grade (ISUP Grade Group ≥ 2; n = 108). Volatile organic compounds (VOCs) in urine were extracted by stir bar sorptive extraction (SBSE) and analyzed using thermal desorption with gas chromatography and mass spectrometry (GC-MS). We used machine learning tools to develop and evaluate models for PCa diagnosis and prognosis. In total, 22,538 VOCs were identified in the urine samples. With regularized logistic regression, our model for PCa diagnosis yielded an area under the curve (AUC) of 0.99 and 0.88 for the training and testing sets respectively. Furthermore, the model for differentiating between low-grade and intermediate/high-grade PCa yielded an average AUC of 0.78 based on a repeated test-sample approach for cross-validation. These novel methods using urinary VOCs and logistic regression were developed to fill gaps in PCa screening and assessment of PCa grades prior to biopsy. Our study findings provide a promising alternative or adjunct to current PCa screening and diagnostic methods to better target patients for biopsy and mitigate the challenges associated with over-diagnosis and over-treatment of PCa.
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Affiliation(s)
- Sabur Badmos
- Department of Chemistry and Biochemistry, University of Texas at El PasoEl Paso, Texas, USA
| | | | - Kiana L Holbrook
- Department of Chemistry and Biochemistry, University of Texas at El PasoEl Paso, Texas, USA
| | - George E Quaye
- Department of Mathematical Sciences, University of Texas at El PasoEl Paso, Texas, USA
| | - Xiaogang Su
- Department of Mathematical Sciences, University of Texas at El PasoEl Paso, Texas, USA
| | - Qin Gao
- Department of Chemistry and Biochemistry, University of Texas at El PasoEl Paso, Texas, USA
- PDM Biologics Analytical Operations, Gilead Sciences Inc.Oceanside, California, USA
| | - Angelica A Chacon
- Department of Chemistry and Biochemistry, University of Texas at El PasoEl Paso, Texas, USA
| | - Eric Adams
- Department of Urological Surgery, Duke University Medical CenterDurham, North Carolina, USA
| | - Thomas J Polascik
- Department of Urological Surgery, Duke University Medical CenterDurham, North Carolina, USA
| | - Adam S Feldman
- Department of Urology, Massachusetts General HospitalBoston, Massachusetts, USA
| | | | - Wen-Yee Lee
- Department of Chemistry and Biochemistry, University of Texas at El PasoEl Paso, Texas, USA
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Mediani A, Baharum SN. Metabolomics: Challenges and Opportunities in Systems Biology Studies. Methods Mol Biol 2024; 2745:77-90. [PMID: 38060180 DOI: 10.1007/978-1-0716-3577-3_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2023]
Abstract
Metabolomics can provide diagnostic, prognostic, and therapeutic biomarker profiles of individual patients because a large number of metabolites can be simultaneously measured in biological samples in an unbiased manner. Minor stimuli can result in substantial alterations, making it a valuable target for analysis. Due to the complexity and sensitivity of the metabolome, studies must be devised to maintain consistency, minimize subject-to-subject variation, and maximize information recovery. This effort has been aided by technological advances in experimental design, rodent models, and instrumentation. Proton Nuclear Magnetic Resonance (1H-NMR) spectroscopy of biofluids, such as plasma, urine, and faeces provide the opportunity to identify biomarker change patterns that reflect the physiological or pathological status of an individual patient. Metabolomics has the ultimate potential to be useful in a clinical context, where it could be used to predict treatment response and survival and for early disease diagnosis. During drug treatment, an individual's metabolic status could be monitored and used to predict deleterious effects. Therefore, metabolomics has the potential to improve disease diagnosis, treatment, and follow-up care. In this chapter, we demonstrate how a metabolomics study can be used to diagnose a disease by classifying patients as either healthy or pathological, while accounting for individual variation.
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Affiliation(s)
- Ahmed Mediani
- Institute of Systems Biology (INBIOSIS), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
| | - Syarul Nataqain Baharum
- Institute of Systems Biology (INBIOSIS), Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
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Thu NQ, Tien NTN, Yen NTH, Duong TH, Long NP, Nguyen HT. Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management. J Pharm Anal 2024; 14:16-38. [PMID: 38352944 PMCID: PMC10859566 DOI: 10.1016/j.jpha.2023.09.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 08/25/2023] [Accepted: 09/18/2023] [Indexed: 02/16/2024] Open
Abstract
The spread of tuberculosis (TB), especially multidrug-resistant TB and extensively drug-resistant TB, has strongly motivated the research and development of new anti-TB drugs. New strategies to facilitate drug combinations, including pharmacokinetics-guided dose optimization and toxicology studies of first- and second-line anti-TB drugs have also been introduced and recommended. Liquid chromatography-mass spectrometry (LC-MS) has arguably become the gold standard in the analysis of both endo- and exo-genous compounds. This technique has been applied successfully not only for therapeutic drug monitoring (TDM) but also for pharmacometabolomics analysis. TDM improves the effectiveness of treatment, reduces adverse drug reactions, and the likelihood of drug resistance development in TB patients by determining dosage regimens that produce concentrations within the therapeutic target window. Based on TDM, the dose would be optimized individually to achieve favorable outcomes. Pharmacometabolomics is essential in generating and validating hypotheses regarding the metabolism of anti-TB drugs, aiding in the discovery of potential biomarkers for TB diagnostics, treatment monitoring, and outcome evaluation. This article highlighted the current progresses in TDM of anti-TB drugs based on LC-MS bioassay in the last two decades. Besides, we discussed the advantages and disadvantages of this technique in practical use. The pressing need for non-invasive sampling approaches and stability studies of anti-TB drugs was highlighted. Lastly, we provided perspectives on the prospects of combining LC-MS-based TDM and pharmacometabolomics with other advanced strategies (pharmacometrics, drug and vaccine developments, machine learning/artificial intelligence, among others) to encapsulate in an all-inclusive approach to improve treatment outcomes of TB patients.
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Affiliation(s)
- Nguyen Quang Thu
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, 47392, Republic of Korea
| | - Nguyen Tran Nam Tien
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, 47392, Republic of Korea
| | - Nguyen Thi Hai Yen
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, 47392, Republic of Korea
| | - Thuc-Huy Duong
- Department of Chemistry, University of Education, Ho Chi Minh City, 700000, Viet Nam
| | - Nguyen Phuoc Long
- Department of Pharmacology and PharmacoGenomics Research Center, Inje University College of Medicine, Busan, 47392, Republic of Korea
| | - Huy Truong Nguyen
- Faculty of Pharmacy, Ton Duc Thang University, Ho Chi Minh City, 700000, Viet Nam
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Jeppesen MJ, Powers R. Multiplatform untargeted metabolomics. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2023; 61:628-653. [PMID: 37005774 PMCID: PMC10948111 DOI: 10.1002/mrc.5350] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 03/29/2023] [Accepted: 03/30/2023] [Indexed: 06/19/2023]
Abstract
Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.
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Affiliation(s)
- Micah J. Jeppesen
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States
- Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States
| | - Robert Powers
- Department of Chemistry, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States
- Nebraska Center for Integrated Biomolecular Communication, University of Nebraska-Lincoln, Lincoln, NE 68588-0304, United States
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12
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Singh S, Sarma DK, Verma V, Nagpal R, Kumar M. Unveiling the future of metabolic medicine: omics technologies driving personalized solutions for precision treatment of metabolic disorders. Biochem Biophys Res Commun 2023; 682:1-20. [PMID: 37788525 DOI: 10.1016/j.bbrc.2023.09.064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 09/13/2023] [Accepted: 09/21/2023] [Indexed: 10/05/2023]
Abstract
Metabolic disorders are increasingly prevalent worldwide, leading to high rates of morbidity and mortality. The variety of metabolic illnesses can be addressed through personalized medicine. The goal of personalized medicine is to give doctors the ability to anticipate the best course of treatment for patients with metabolic problems. By analyzing a patient's metabolomic, proteomic, genetic profile, and clinical data, physicians can identify relevant diagnostic, and predictive biomarkers and develop treatment plans and therapy for acute and chronic metabolic diseases. To achieve this goal, real-time modeling of clinical data and multiple omics is essential to pinpoint underlying biological mechanisms, risk factors, and possibly useful data to promote early diagnosis and prevention of complex diseases. Incorporating cutting-edge technologies like artificial intelligence and machine learning is crucial for consolidating diverse forms of data, examining multiple variables, establishing databases of clinical indicators to aid decision-making, and formulating ethical protocols to address concerns. This review article aims to explore the potential of personalized medicine utilizing omics approaches for the treatment of metabolic disorders. It focuses on the recent advancements in genomics, epigenomics, proteomics, metabolomics, and nutrigenomics, emphasizing their role in revolutionizing personalized medicine.
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Affiliation(s)
- Samradhi Singh
- ICMR- National Institute for Research in Environmental Health, Bhopal Bypass Road, Bhouri, Bhopal, 462030, Madhya Pradesh, India
| | - Devojit Kumar Sarma
- ICMR- National Institute for Research in Environmental Health, Bhopal Bypass Road, Bhouri, Bhopal, 462030, Madhya Pradesh, India
| | - Vinod Verma
- Stem Cell Research Centre, Department of Hematology, Sanjay Gandhi Post-Graduate Institute of Medical Sciences, Lucknow, 226014, Uttar Pradesh, India
| | - Ravinder Nagpal
- Department of Nutrition and Integrative Physiology, College of Health and Human Sciences, Florida State University, Tallahassee, FL, 32306, USA
| | - Manoj Kumar
- ICMR- National Institute for Research in Environmental Health, Bhopal Bypass Road, Bhouri, Bhopal, 462030, Madhya Pradesh, India.
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13
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Shastry A, Dunham-Snary K. Metabolomics and mitochondrial dysfunction in cardiometabolic disease. Life Sci 2023; 333:122137. [PMID: 37788764 DOI: 10.1016/j.lfs.2023.122137] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 09/21/2023] [Accepted: 09/29/2023] [Indexed: 10/05/2023]
Abstract
Circulating metabolites are indicators of systemic metabolic dysfunction and can be detected through contemporary techniques in metabolomics. These metabolites are involved in numerous mitochondrial metabolic processes including glycolysis, fatty acid β-oxidation, and amino acid catabolism, and changes in the abundance of these metabolites is implicated in the pathogenesis of cardiometabolic diseases (CMDs). Epigenetic regulation and direct metabolite-protein interactions modulate metabolism, both within cells and in the circulation. Dysfunction of multiple mitochondrial components stemming from mitochondrial DNA mutations are implicated in disease pathogenesis. This review will summarize the current state of knowledge regarding: i) the interactions between metabolites found within the mitochondrial environment during CMDs, ii) various metabolites' effects on cellular and systemic function, iii) how harnessing the power of metabolomic analyses represents the next frontier of precision medicine, and iv) how these concepts integrate to expand the clinical potential for translational cardiometabolic medicine.
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Affiliation(s)
- Abhishek Shastry
- Department of Medicine, Queen's University, Kingston, ON, Canada
| | - Kimberly Dunham-Snary
- Department of Medicine, Queen's University, Kingston, ON, Canada; Department of Biomedical & Molecular Sciences, Queen's University, Kingston, ON, Canada.
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14
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Shields PG. Role of untargeted omics biomarkers of exposure and effect for tobacco research. ADDICTION NEUROSCIENCE 2023; 7:100098. [PMID: 37396411 PMCID: PMC10310069 DOI: 10.1016/j.addicn.2023.100098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Tobacco research remains a clear priority to improve individual and population health, and has recently become more complex with emerging combustible and noncombustible tobacco products. The use of omics methods in prevention and cessation studies are intended to identify new biomarkers for risk, compared risks related to other products and never use, and compliance for cessation and reinitation. to assess the relative effects of tobacco products to each other. They are important for the prediction of reinitiation of tobacco use and relapse prevention. In the research setting, both technical and clinical validation is required, which presents a number of complexities in the omics methodologies from biospecimen collection and sample preparation to data collection and analysis. When the results identify differences in omics features, networks or pathways, it is unclear if the results are toxic effects, a healthy response to a toxic exposure or neither. The use of surrogate biospecimens (e.g., urine, blood, sputum or nasal) may or may not reflect target organs such as the lung or bladder. This review describes the approaches for the use of omics in tobacco research and provides examples of prior studies, along with the strengths and limitations of the various methods. To date, there is little consistency in results, likely due to small number of studies, limitations in study size, the variability in the analytic platforms and bioinformatic pipelines, differences in biospecimen collection and/or human subject study design. Given the demonstrated value for the use of omics in clinical medicine, it is anticipated that the use in tobacco research will be similarly productive.
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Affiliation(s)
- Peter G. Shields
- Comprehensive Cancer Center, The Ohio State University and James Cancer Hospital, Columbus, OH
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15
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Ong ES. Urine Metabolites and Bioactive Compounds from Functional Food: Applications of Liquid Chromatography Mass Spectrometry. Crit Rev Anal Chem 2023:1-16. [PMID: 37454386 DOI: 10.1080/10408347.2023.2235442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/18/2023]
Abstract
Bioactive compounds in functional foods, medicinal plants and others are considered attractive value-added molecules based on their wide range of bioactivity. It is clear that an important role is occupied by polyphenol, phenolic compounds and others. Urine is an effective biofluid to evaluate and monitor alterations in homeostasis and other processes related to metabolism. The current review provides a detailed description of the formation of urine in human body, various aspects relevant to sampling and analysis of urinary metabolites before presenting recent developments leveraging on metabolite profiling of urine. For the profiling of small molecules in urine, advancement of liquid chromatography mass tandem spectrometry (LC/MS/MS), establishment of standardized chemical fragmentation libraries, computational resources, data-analysis approaches with pattern recognition tools have made it an attractive option. The profiling of urinary metabolites gives an overview of the biomarkers associated with the diet and evaluates its biological effects. Metabolic pathways such as glycolysis, tricarboxylic acid cycle, amino acid metabolism, energy metabolism, purine metabolism and others can be evaluated. Finally, a combination of metabolite profiling with chemical standardization and bioassay in functional food and medicinal plants will likely lead to the identification of new biomarkers and novel biochemical insights.
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Affiliation(s)
- Eng Shi Ong
- Singapore University of Technology and Design, Singapore, Republic of Singapore
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16
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Rahman M, Schellhorn HE. Metabolomics of infectious diseases in the era of personalized medicine. Front Mol Biosci 2023; 10:1120376. [PMID: 37275959 PMCID: PMC10233009 DOI: 10.3389/fmolb.2023.1120376] [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: 12/12/2022] [Accepted: 05/08/2023] [Indexed: 06/07/2023] Open
Abstract
Infectious diseases continue to be a major cause of morbidity and mortality worldwide. Diseases cause perturbation of the host's immune system provoking a response that involves genes, proteins and metabolites. While genes are regulated by epigenetic or other host factors, proteins can undergo post-translational modification to enable/modify function. As a result, it is difficult to correlate the disease phenotype based solely on genetic and proteomic information only. Metabolites, however, can provide direct information on the biochemical activity during diseased state. Therefore, metabolites may, potentially, represent a phenotypic signature of a diseased state. Measuring and assessing metabolites in large scale falls under the omics technology known as "metabolomics". Comprehensive and/or specific metabolic profiling in biological fluids can be used as biomarkers of disease diagnosis. In addition, metabolomics together with genomics can be used to differentiate patients with differential treatment response and development of host targeted therapy instead of pathogen targeted therapy where pathogens are more prone to mutation and lead to antimicrobial resistance. Thus, metabolomics can be used for patient stratification, personalized drug formulation and disease control and management. Currently, several therapeutics and in vitro diagnostics kits have been approved by US Food and Drug Administration (FDA) for personalized treatment and diagnosis of infectious diseases. However, the actual number of therapeutics or diagnostics kits required for tailored treatment is limited as metabolomics and personalized medicine require the involvement of personnel from multidisciplinary fields ranging from technological development, bioscience, bioinformatics, biostatistics, clinicians, and biotechnology companies. Given the significance of metabolomics, in this review, we discussed different aspects of metabolomics particularly potentials of metabolomics as diagnostic biomarkers and use of small molecules for host targeted treatment for infectious diseases, and their scopes and challenges in personalized medicine.
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Naviaux RK. Mitochondrial and metabolic features of salugenesis and the healing cycle. Mitochondrion 2023; 70:131-163. [PMID: 37120082 DOI: 10.1016/j.mito.2023.04.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 03/24/2023] [Accepted: 04/23/2023] [Indexed: 05/01/2023]
Abstract
Pathogenesis and salugenesis are the first and second stages of the two-stage problem of disease production and health recovery. Salugenesis is the automatic, evolutionarily conserved, ontogenetic sequence of molecular, cellular, organ system, and behavioral changes that is used by living systems to heal. It is a whole-body process that begins with mitochondria and the cell. The stages of salugenesis define a circle that is energy- and resource-consuming, genetically programmed, and environmentally responsive. Energy and metabolic resources are provided by mitochondrial and metabolic transformations that drive the cell danger response (CDR) and create the three phases of the healing cycle: Phase 1-Inflammation, Phase 2-Proliferation, and Phase 3-Differentiation. Each phase requires a different mitochondrial phenotype. Without different mitochondria there can be no healing. The rise and fall of extracellular ATP (eATP) signaling is a key driver of the mitochondrial and metabolic reprogramming required to progress through the healing cycle. Sphingolipid and cholesterol-enriched membrane lipid rafts act as rheostats for tuning cellular sensitivity to purinergic signaling. Abnormal persistence of any phase of the CDR inhibits the healing cycle, creates dysfunctional cellular mosaics, causes the symptoms of chronic disease, and accelerates the process of aging. New research reframes the rising tide of chronic disease around the world as a systems problem caused by the combined action of pathogenic triggers and anthropogenic factors that interfere with the mitochondrial functions needed for healing. Once chronic pain, disability, or disease is established, salugenesis-based therapies will start where pathogenesis-based therapies end.
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Affiliation(s)
- Robert K Naviaux
- The Mitochondrial and Metabolic Disease Center, Departments of Medicine, and Pediatrics, University of California, San Diego School of Medicine, 214 Dickinson St., Bldg CTF, Rm C107, MC#8467, San Diego, CA 92103.
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Wang T, Wang XW, Lee-Sarwar KA, Litonjua AA, Weiss ST, Sun Y, Maslov S, Liu YY. Predicting metabolomic profiles from microbial composition through neural ordinary differential equations. NAT MACH INTELL 2023; 5:284-293. [PMID: 38223254 PMCID: PMC10786629 DOI: 10.1038/s42256-023-00627-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 02/03/2023] [Indexed: 03/14/2023]
Abstract
Characterizing the metabolic profile of a microbial community is crucial for understanding its biological function and its impact on the host or environment. Metabolomics experiments directly measuring these profiles are difficult and expensive, while sequencing methods quantifying the species composition of microbial communities are well-developed and relatively cost-effective. Computational methods that are capable of predicting metabolomic profiles from microbial compositions can save considerable efforts needed for metabolomic profiling experimentally. Yet, despite existing efforts, we still lack a computational method with high prediction power, general applicability, and great interpretability. Here we develop a method - mNODE (Metabolomic profile predictor using Neural Ordinary Differential Equations), based on a state-of-the-art family of deep neural network models. We show compelling evidence that mNODE outperforms existing methods in predicting the metabolomic profiles of human microbiomes and several environmental microbiomes. Moreover, in the case of human gut microbiomes, mNODE can naturally incorporate dietary information to further enhance the prediction of metabolomic profiles. Besides, susceptibility analysis of mNODE enables us to reveal microbe-metabolite interactions, which can be validated using both synthetic and real data. The presented results demonstrate that mNODE is a powerful tool to investigate the microbiome-diet-metabolome relationship, facilitating future research on precision nutrition.
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Affiliation(s)
- Tong Wang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Xu-Wen Wang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Kathleen A. Lee-Sarwar
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Division of Allergy and Clinical Immunology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Augusto A. Litonjua
- Pediatric Pulmonology, Golisano Children’s Hospital, University of Rochester, Rochester, NY 14642, USA
| | - Scott T. Weiss
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Yizhou Sun
- Department of Computer Science, University of California, Los Angeles, USA
| | - Sergei Maslov
- Center for Artificial Intelligence and Modeling, The Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Yang-Yu Liu
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Center for Artificial Intelligence and Modeling, The Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
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19
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Ekmekciu L, Hopfgartner G. Liquid chromatography and differential mobility spectrometry-data-independent mass spectrometry for comprehensive multidimensional separations in metabolomics. Anal Bioanal Chem 2023; 415:1905-1915. [PMID: 36820908 PMCID: PMC10050028 DOI: 10.1007/s00216-023-04602-0] [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: 01/07/2023] [Revised: 02/09/2023] [Accepted: 02/13/2023] [Indexed: 02/24/2023]
Abstract
The benefits of combining drift time ion mobility (DTIMS) with liquid chromatography-high-resolution mass spectrometry (HRMS) have been reported for metabolomics but the use of differential time mobility spectrometry (DMS) is less obvious due to the need for rapid scanning of the DMS cell. Drift DTIMS provides additional precursor ion selectivity and collisional cross-section information but the separation resolution between analytes remains cell- and component-dependent. With DMS, the addition of 2-propanol modifier can improve the selectivity but on cost of analyte MS response. In the present work, we investigate the liquid chromatography-mass spectrometry (LC-MS) analysis of a mix of 50 analytes, representative for urine and plasma metabolites, using scanning DMS with the single modifiers cyclohexane (Ch), toluene (Tol), acetonitrile (ACN), ethanol (EtOH), and 2-propanol (IPA), and a binary modifier mixture (cyclohexane/2-propanol) with emphasis on selectivity and signal sensitivity. 1.5% IPA in the N2 stream was found to suppress the signal of 50% of the analytes which could be partially recovered with the use of IPA to 0.05% as a Ch/IPA mixture. The potential to use the separation voltage/compensation voltage/modifier (SV/CoV/Mod) feature as an additional analyte identifier for qualitative analysis is also presented and applied to a data-independent LCxDMS-SWATH-MS workflow for the analysis of endogenous metabolites and drugs of abuse in human urine samples from traffic control.
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Affiliation(s)
- Lysi Ekmekciu
- Life Sciences Mass Spectrometry, Department of Inorganic and Analytical Chemistry, University of Geneva, 24 Quai Ernest Ansermet, 1211, Geneva 4, Switzerland
| | - Gérard Hopfgartner
- Life Sciences Mass Spectrometry, Department of Inorganic and Analytical Chemistry, University of Geneva, 24 Quai Ernest Ansermet, 1211, Geneva 4, Switzerland.
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20
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Wang SJ, Liu BR, Zhang F, Li YP, Su XR, Yang CT, Cong B, Zhang ZH. Abnormal fatty acid metabolism and ceramide expression may discriminate myocardial infarction from strangulation death: A pilot study. Tissue Cell 2023; 80:101984. [PMID: 36434828 DOI: 10.1016/j.tice.2022.101984] [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: 09/13/2022] [Revised: 11/16/2022] [Accepted: 11/16/2022] [Indexed: 11/22/2022]
Abstract
Determining myocardial infarction (MI) and mechanical asphyxia (MA) was one of the most challenging tasks in forensic practice. The present study aimed to investigate the potential of fatty acid (FAs) metabolism, and lipid alterations in determining MI and MA. MA and MI mouse models were constructed, and metabolic profiles were obtained by LC-MS-based untargeted metabolomics. The metabolic alterations were explored using the PCA, OPLS-DA, the Wilcoxon test, and fold change analysis. The contents of lipid droplets (LDs) were detected by the transmission scanning electron microscope and Oil red O staining. The immunohistochemical assay was performed to detect CD36 and dysferlin. The ceramide was assessed by LC-MS. PCA showed considerable differences in the metabolite profiles, and the well-fitting OPLS-DA model was developed to screen differential metabolites. Thereinto, 9 metabolites in the MA were reduced, while metabolites were up- and down-regulated in MI. The increased CD36 suggested that MI and MA could enhance the intake of FAs and disturb energy metabolism. The increased LDs, decreased dysferlin, and increased ceramide (C18:0, C22:0, and C24:0) were observed in MI groups, confirming the lipid deposition. The present study indicated significant differences in myocardial FAs metabolism and lipid alterations between MI and MA, suggesting that FAs metabolism and related proteins, certain ceramide may harbor the potential as biomarkers for discrimination of MI and MA.
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Affiliation(s)
- Song-Jun Wang
- College of Forensic Medicine, Hebei Medical University, Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, China.
| | - Bing-Rui Liu
- College of Forensic Medicine, Hebei Medical University, Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, China.
| | - Fu Zhang
- Forensic Pathology Lab, Guangdong Public Security Department, China.
| | - Ya-Ping Li
- College of Forensic Medicine, Hebei Medical University, Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, China.
| | - Xiao-Rui Su
- College of Forensic Medicine, Hebei Medical University, Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, China.
| | - Chen-Teng Yang
- College of Forensic Medicine, Hebei Medical University, Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, China.
| | - Bin Cong
- College of Forensic Medicine, Hebei Medical University, Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, China.
| | - Zhi-Hua Zhang
- College of Forensic Medicine, Hebei Medical University, Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, China; HeBei Chest Hospital, China.
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21
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Díaz C, González-Olmedo C. Untargeted Metabolomics by Liquid Chromatography-Mass Spectrometry in Biomedical Research. Methods Mol Biol 2023; 2571:57-69. [PMID: 36152150 DOI: 10.1007/978-1-0716-2699-3_6] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Metabolomics, alone or in combination with other omics sciences, has shown great relevance in a large number of investigations in different branches of biomedicine, often providing novel discoveries and helping to expand the knowledge. Metabolomics analyses are carried out using different techniques, but in this chapter, we focus on liquid chromatography coupled to high-resolution mass spectrometry. The designated methodology consists of an untargeted approach for the analysis of plasma samples. The use of this method, with a reverse-phase column and electrospray ionization in positive mode, covers the detection of a broad range of metabolites, mainly of nonpolar and of intermediate polarity. This chapter also reviews the mass fragmentation spectra for the identification of bile acids, acylcarnitines, and glycerophospholipids.
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Affiliation(s)
- Caridad Díaz
- Fundación MEDINA, Centro de Excelencia en Investigación de Medicamentos Innovadores en Andalucía, Granada, Andalucía, Spain.
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22
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Trifonova OP, Maslov DL, Balashova EE, Lokhov PG. Current State and Future Perspectives on Personalized Metabolomics. Metabolites 2023; 13:metabo13010067. [PMID: 36676992 PMCID: PMC9863827 DOI: 10.3390/metabo13010067] [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: 12/05/2022] [Revised: 12/27/2022] [Accepted: 12/29/2022] [Indexed: 01/03/2023] Open
Abstract
Metabolomics is one of the most promising 'omics' sciences for the implementation in medicine by developing new diagnostic tests and optimizing drug therapy. Since in metabolomics, the end products of the biochemical processes in an organism are studied, which are under the influence of both genetic and environmental factors, the metabolomics analysis can detect any changes associated with both lifestyle and pathological processes. Almost every case-controlled metabolomics study shows a high diagnostic accuracy. Taking into account that metabolomics processes are already described for most nosologies, there are prerequisites that a high-speed and comprehensive metabolite analysis will replace, in near future, the narrow range of chemical analyses used today, by the medical community. However, despite the promising perspectives of personalized metabolomics, there are currently no FDA-approved metabolomics tests. The well-known problem of complexity of personalized metabolomics data analysis and their interpretation for the end-users, in addition to a traditional need for analytical methods to address the quality control, standardization, and data treatment are reported in the review. Possible ways to solve the problems and change the situation with the introduction of metabolomics tests into clinical practice, are also discussed.
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23
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Wang J, Yang WY, Li XH, Xu B, Yang YW, Zhang B, Dai CM, Feng JF. Study on potential markers for diagnosis of renal cell carcinoma by serum untargeted metabolomics based on UPLC-MS/MS. Front Physiol 2022; 13:996248. [PMID: 36523562 PMCID: PMC9745078 DOI: 10.3389/fphys.2022.996248] [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: 07/17/2022] [Accepted: 11/16/2022] [Indexed: 08/30/2023] Open
Abstract
Objective: Renal cell carcinoma (RCC) is the most common malignancy of the kidney. However, there is no reliable biomarker with high sensitivity and specificity for diagnosis and differential diagnosis. This study aims to analyze serum metabolite profile of patients with RCC and screen for potential diagnostic biomarkers. Methods: Forty-five healthy controls (HC), 40 patients with benign kidney tumor (BKT) and 46 patients with RCC were enrolled in this study. Serum metabolites were detected by ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS), and then subjected to multivariate statistical analysis, metabolic pathway analysis and diagnostic performance evaluation. Results: The changes of glycerophospholipid metabolism, phosphatidylinositol signaling system, glycerolipid metabolism, d-glutamine and d-glutamate metabolism, galactose metabolism, and folate biosynthesis were observed in RCC group. Two hundred and forty differential metabolites were screened between RCC and HC groups, and 64 differential metabolites were screened between RCC and BKT groups. Among them, 4 differential metabolites, including 3-β-D-Galactosyl-sn-glycerol, 7,8-Dihydroneopterin, lysophosphatidylcholine (LPC) 19:2, and γ-Aminobutyryl-lysine (an amino acid metabolite), were of high clinical value not only in the diagnosis of RCC (RCC group vs. HC group; AUC = 0.990, 0.916, 0.909, and 0.962; Sensitivity = 97.73%, 97.73%, 93.18%, and 86.36%; Specificity = 100.00%, 73.33%, 80.00%, and 95.56%), but also in the differential diagnosis of benign and malignant kidney tumors (RCC group vs. BKT group; AUC = 0.989, 0.941, 0.845 and 0.981; Sensitivity = 93.33%, 93.33%, 77.27% and 93.33%; Specificity = 100.00%, 84.21%, 78.38% and 92.11%). Conclusion: The occurrence of RCC may involve changes in multiple metabolic pathways. The 3-β-D-Galactosyl-sn-glycerol, 7,8-Dihydroneopterin, LPC 19:2 and γ-Aminobutyryl-lysine may be potential biomarkers for the diagnosis or differential diagnosis of RCC.
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Affiliation(s)
- Jun Wang
- College of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Wen-Yu Yang
- College of Medical Technology, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Xiao-Han Li
- Department of Medical Laboratory, Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Bei Xu
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
| | - Yu-Wei Yang
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
| | - Bin Zhang
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
| | - Chun-Mei Dai
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
| | - Jia-Fu Feng
- Department of Clinical Laboratory, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
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24
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Brezmes J, Llambrich M, Cumeras R, Gumà J. Urine NMR Metabolomics for Precision Oncology in Colorectal Cancer. Int J Mol Sci 2022; 23:11171. [PMID: 36232473 PMCID: PMC9569997 DOI: 10.3390/ijms231911171] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 11/16/2022] Open
Abstract
Metabolomics is a fundamental approach to discovering novel biomarkers and their potential use for precision medicine. When applied for population screening, NMR-based metabolomics can become a powerful clinical tool in precision oncology. Urine tests can be more widely accepted due to their intrinsic non-invasiveness. Our review provides the first exhaustive evaluation of NMR metabolomics for the determination of colorectal cancer (CRC) in urine. A specific search in PubMed, Web of Science, and Scopus was performed, and 10 studies met the required criteria. There were no restrictions on the query for study type, leading to not only colorectal cancer samples versus control comparisons, but also prospective studies of surgical effects. With this review, all compounds in the included studies were merged into a database. In doing so, we identified up to 100 compounds in urine samples, and 11 were found in at least three articles. Results were analyzed in three groups: case (CRC and adenomas)/control, pre-/post-surgery, and combining both groups. When combining the case-control and the pre-/post-surgery groups, up to twelve compounds were found to be relevant. Seven down-regulated metabolites in CRC were identified, creatinine, 4-hydroxybenzoic acid, acetone, carnitine, d-glucose, hippuric acid, l-lysine, l-threonine, and pyruvic acid, and three up-regulated compounds in CRC were identified, acetic acid, phenylacetylglutamine, and urea. The pathways and enrichment analysis returned only two pathways significantly expressed: the pyruvate metabolism and the glycolysis/gluconeogenesis pathway. In both cases, only the pyruvic acid (down-regulated in urine of CRC patients, with cancer cell proliferation effect in the tissue) and acetic acid (up-regulated in urine of CRC patients, with chemoprotective effect) were present.
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Affiliation(s)
- Jesús Brezmes
- Metabolomics Interdisciplinary Group, Institut d’Investigació Sanitària Pere Virgili (IISPV), Universitat Rovira i Virgili (URV), 43204 Reus, Spain
- Department of Electrical Electronic Engineering and Automation, Universitat Rovira i Virgili (URV), Institut d’Investigació Sanitària Pere Virgili (IISPV), 43007 Tarragona, Spain
| | - Maria Llambrich
- Metabolomics Interdisciplinary Group, Institut d’Investigació Sanitària Pere Virgili (IISPV), Universitat Rovira i Virgili (URV), 43204 Reus, Spain
- Department of Electrical Electronic Engineering and Automation, Universitat Rovira i Virgili (URV), Institut d’Investigació Sanitària Pere Virgili (IISPV), 43007 Tarragona, Spain
| | - Raquel Cumeras
- Metabolomics Interdisciplinary Group, Institut d’Investigació Sanitària Pere Virgili (IISPV), Universitat Rovira i Virgili (URV), 43204 Reus, Spain
- Department of Electrical Electronic Engineering and Automation, Universitat Rovira i Virgili (URV), Institut d’Investigació Sanitària Pere Virgili (IISPV), 43007 Tarragona, Spain
- Oncology Department, Hospital Universitari Sant Joan de Reus, Institut d’Investigació Sanitària Pere Virgili (IISPV), Universitat Rovira i Virgili (URV), 43204 Reus, Spain
| | - Josep Gumà
- Oncology Department, Hospital Universitari Sant Joan de Reus, Institut d’Investigació Sanitària Pere Virgili (IISPV), Universitat Rovira i Virgili (URV), 43204 Reus, Spain
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Szatmary P, Grammatikopoulos T, Cai W, Huang W, Mukherjee R, Halloran C, Beyer G, Sutton R. Acute Pancreatitis: Diagnosis and Treatment. Drugs 2022; 82:1251-1276. [PMID: 36074322 PMCID: PMC9454414 DOI: 10.1007/s40265-022-01766-4] [Citation(s) in RCA: 71] [Impact Index Per Article: 35.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/04/2022] [Indexed: 11/11/2022]
Abstract
Acute pancreatitis is a common indication for hospital admission, increasing in incidence, including in children, pregnancy and the elderly. Moderately severe acute pancreatitis with fluid and/or necrotic collections causes substantial morbidity, and severe disease with persistent organ failure causes significant mortality. The diagnosis requires two of upper abdominal pain, amylase/lipase ≥ 3 ×upper limit of normal, and/or cross-sectional imaging findings. Gallstones and ethanol predominate while hypertriglyceridaemia and drugs are notable among many causes. Serum triglycerides, full blood count, renal and liver function tests, glucose, calcium, transabdominal ultrasound, and chest imaging are indicated, with abdominal cross-sectional imaging if there is diagnostic uncertainty. Subsequent imaging is undertaken to detect complications, for example, if C-reactive protein exceeds 150 mg/L, or rarer aetiologies. Pancreatic intracellular calcium overload, mitochondrial impairment, and inflammatory responses are critical in pathogenesis, targeted in current treatment trials, which are crucially important as there is no internationally licenced drug to treat acute pancreatitis and prevent complications. Initial priorities are intravenous fluid resuscitation, analgesia, and enteral nutrition, and when necessary, critical care and organ support, parenteral nutrition, antibiotics, pancreatic exocrine and endocrine replacement therapy; all may have adverse effects. Patients with local complications should be referred to specialist tertiary centres to guide further management, which may include drainage and/or necrosectomy. The impact of acute pancreatitis can be devastating, so prevention or reduction of the risk of recurrence and progression to chronic pancreatitis with an increased risk of pancreas cancer requires proactive management that should be long term for some patients.
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Affiliation(s)
- Peter Szatmary
- Liverpool Pancreatitis Research Group, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK
| | - Tassos Grammatikopoulos
- Paediatric Liver, GI and Nutrition Centre, King's College Hospital NHS Foundation Trust, London, UK
| | - Wenhao Cai
- Liverpool Pancreatitis Research Group, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,West China Centre of Excellence for Pancreatitis and West China-Liverpool Biomedical Research Centre, West China Hospital, Sichuan University, Chengdu, China
| | - Wei Huang
- West China Centre of Excellence for Pancreatitis and West China-Liverpool Biomedical Research Centre, West China Hospital, Sichuan University, Chengdu, China
| | - Rajarshi Mukherjee
- Liverpool Pancreatitis Research Group, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK.,Department of Molecular Physiology and Cell Signalling, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool , UK
| | - Chris Halloran
- Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK
| | - Georg Beyer
- Department of Medicine II, University Hospital, LMU Munich, Munich, Germany
| | - Robert Sutton
- Liverpool Pancreatitis Research Group, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK. .,Department of Molecular and Clinical Cancer Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK. .,Liverpool University Hospitals NHS Foundation Trust, Liverpool, UK.
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26
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Costanzo M, Caterino M, Sotgiu G, Ruoppolo M, Franconi F, Campesi I. Sex differences in the human metabolome. Biol Sex Differ 2022; 13:30. [PMID: 35706042 PMCID: PMC9199320 DOI: 10.1186/s13293-022-00440-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 06/02/2022] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND The sexual dimorphism represents one of the triggers of the metabolic disparities between the organisms, advising about wild implications in research or diagnostics contexts. Despite the mounting recognition of the importance of sex consideration in the biomedical fields, the identification of male- and female-specific metabolic signatures has not been achieved. MAIN BODY This review pointed the focus on the metabolic differences related to the sex, evidenced by metabolomics studies performed on healthy populations, with the leading aim of understanding how the sex influences the baseline metabolome. The main shared signatures and the apparent dissimilarities between males and females were extracted and highlighted from the metabolome of the most commonly analyzed biological fluids, such as serum, plasma, and urine. Furthermore, the influence of age and the significant interactions between sex and age have been taken into account. CONCLUSIONS The recognition of sex patterns in human metabolomics has been defined in diverse biofluids. The detection of sex- and age-related differences in the metabolome of healthy individuals are helpful for translational applications from the bench to the bedside to set targeted diagnostic and prevention approaches in the context of personalized medicine.
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Affiliation(s)
- Michele Costanzo
- Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131, Naples, Italy. .,CEINGE - Biotecnologie Avanzate s.c.ar.l., 80145, Naples, Italy.
| | - Marianna Caterino
- Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131, Naples, Italy.,CEINGE - Biotecnologie Avanzate s.c.ar.l., 80145, Naples, Italy
| | - Giovanni Sotgiu
- Clinical Epidemiology and Medical Statistics Unit, Department of Medical, Surgical and Experimental Sciences, University of Sassari, 07100, Sassari, Italy
| | - Margherita Ruoppolo
- Department of Molecular Medicine and Medical Biotechnology, School of Medicine, University of Naples Federico II, 80131, Naples, Italy.,CEINGE - Biotecnologie Avanzate s.c.ar.l., 80145, Naples, Italy
| | - Flavia Franconi
- Laboratory of Sex-Gender Medicine, National Institute of Biostructures and Biosystems, 07100, Sassari, Italy
| | - Ilaria Campesi
- Laboratory of Sex-Gender Medicine, National Institute of Biostructures and Biosystems, 07100, Sassari, Italy.,Department of Biomedical Sciences, University of Sassari, 07100, Sassari, Italy
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27
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Computational Screening of Anti-Cancer Drugs Identifies a New BRCA Independent Gene Expression Signature to Predict Breast Cancer Sensitivity to Cisplatin. Cancers (Basel) 2022; 14:cancers14102404. [PMID: 35626009 PMCID: PMC9139442 DOI: 10.3390/cancers14102404] [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: 04/11/2022] [Revised: 04/29/2022] [Accepted: 05/02/2022] [Indexed: 12/10/2022] Open
Abstract
Simple Summary Using a collection of publicly available drug screening resources, we identified different partners of genes associated with either sensitivity or resistance to 90 anti-cancer therapies. When subsequently applying these signatures to multiple datasets, we found that these predictive models could predict a large range of drug responses in patient samples. In particular, we discovered a new gene signature to identify breast cancer tumors that are likely to respond to cisplatin in the absence of BRCA1 mutations. This work constitutes an important advance to accelerate the application of platinum-based therapies in patient groups that are not routinely treated with these drugs. In the future, this approach may help to guide the choice of drugs based on the molecular profile of the tumors. Abstract The development of therapies that target specific disease subtypes has dramatically improved outcomes for patients with breast cancer. However, survival gains have not been uniform across patients, even within a given molecular subtype. Large collections of publicly available drug screening data matched with transcriptomic measurements have facilitated the development of computational models that predict response to therapy. Here, we generated a series of predictive gene signatures to estimate the sensitivity of breast cancer samples to 90 drugs, comprising FDA-approved drugs or compounds in early development. To achieve this, we used a cell line-based drug screen with matched transcriptomic data to derive in silico models that we validated in large independent datasets obtained from cell lines and patient-derived xenograft (PDX) models. Robust computational signatures were obtained for 28 drugs and used to predict drug efficacy in a set of PDX models. We found that our signature for cisplatin can be used to identify tumors that are likely to respond to this drug, even in absence of the BRCA-1 mutation routinely used to select patients for platinum-based therapies. This clinically relevant observation was confirmed in multiple PDXs. Our study foreshadows an effective delivery approach for precision medicine.
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28
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Anesi A, Berding K, Clarke G, Stanton C, Cryan JF, Caplice N, Ross RP, Doolan A, Vrhovsek U, Mattivi F. Metabolomic Workflow for the Accurate and High-Throughput Exploration of the Pathways of Tryptophan, Tyrosine, Phenylalanine, and Branched-Chain Amino Acids in Human Biofluids. J Proteome Res 2022; 21:1262-1275. [PMID: 35380444 PMCID: PMC9087329 DOI: 10.1021/acs.jproteome.1c00946] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The modulation of host and dietary metabolites by gut microbiota (GM) is important for maintaining correct host physiology and in the onset of various pathologies. An ultrahigh-performance liquid chromatography-electrospray ionization-tandem mass spectrometry method was developed for the targeted quantitation in human plasma, serum, and urine of 89 metabolites resulting from human-GM cometabolism of dietary essential amino acids tryptophan, tyrosine, and phenylalanine as well as branched-chain amino acids. Ninety-six-well plate hybrid-SPE enables fast clean-up of plasma and serum. Urine was diluted and filtered. A 15 min cycle enabled the acquisition of 96 samples per day, with most of the metabolites stable in aqueous solution for up to 72 h. Calibration curves were specifically optimized to cover expected concentrations in biological fluids, and limits of detection were at the order of ppb. Matrix effects were in acceptable ranges, and analytical recoveries were in general greater than 80%. Inter and intraday precision and accuracy were satisfactory. We demonstrated its application in plasma and urine samples obtained from the same individual in the frame of an interventional study, allowing the quantitation of 51 metabolites. The method could be considered the reference for deciphering changes in human-gut microbial cometabolism in health and disease. Data are available via Metabolights with the identifier MTBLS4399.
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Affiliation(s)
- Andrea Anesi
- Unit of Metabolomics, Department of Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach (FEM), 38010 San Michele all'Adige, Italy
| | - Kirsten Berding
- APC Microbiome Ireland, University College Cork, T12 YT20 Cork, Ireland
| | - Gerard Clarke
- APC Microbiome Ireland, University College Cork, T12 YT20 Cork, Ireland.,Department of Psychiatry and Neurobehavioural Sciences, University College Cork, T12 YT20 Cork, Ireland
| | - Catherine Stanton
- APC Microbiome Ireland, University College Cork, T12 YT20 Cork, Ireland
| | - John F Cryan
- APC Microbiome Ireland, University College Cork, T12 YT20 Cork, Ireland.,Department of Anatomy and Neuroscience, University College Cork, T12 YT20 Cork, Ireland
| | - Noel Caplice
- APC Microbiome Ireland, University College Cork, T12 YT20 Cork, Ireland.,Centre for Research in Vascular Biology, University College Cork, T12 YT20 Cork, Ireland
| | - R Paul Ross
- APC Microbiome Ireland, University College Cork, T12 YT20 Cork, Ireland
| | - Andrea Doolan
- Atlantia Food Clinical Trial, Blackpool, T23 R50R Cork, Ireland
| | - Urska Vrhovsek
- Unit of Metabolomics, Department of Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach (FEM), 38010 San Michele all'Adige, Italy
| | - Fulvio Mattivi
- Unit of Metabolomics, Department of Food Quality and Nutrition, Research and Innovation Centre, Fondazione Edmund Mach (FEM), 38010 San Michele all'Adige, Italy.,Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, 38123 Trento, Italy
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Sharma N, Bhat SH, Tripathi G, Yadav M, Mathew B, Bindal V, Sharma S, Gupta E, Maras JS, Sarin SK. Global metabolome profiling of COVID-19 respiratory specimen using high-resolution mass spectrometry (HRMS). STAR Protoc 2022; 3:101051. [PMID: 34877545 PMCID: PMC8639449 DOI: 10.1016/j.xpro.2021.101051] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
Here we describe a protocol for identifying metabolites in respiratory specimens of patients that are SARS-CoV-2 positive, SARS-CoV-2 negative, or H1N1 positive. This protocol provides step-by-step instructions on sample collection from patients, followed by metabolite extraction. We use ultra-high-pressure liquid chromatography (UHPLC) coupled with high-resolution mass spectrometry (HRMS) for data acquisition and describe the steps for data analysis. The protocol was standardized with specific customization for SARS-CoV-2-containing respiratory specimens. For complete details on the use and execution of this protocol, please refer to Maras et al. (2021).
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Affiliation(s)
- Nupur Sharma
- Department of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, New Delhi 110070, India
| | - Sadam H Bhat
- Department of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, New Delhi 110070, India
| | - Gaurav Tripathi
- Department of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, New Delhi 110070, India
| | - Manisha Yadav
- Department of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, New Delhi 110070, India
| | - Babu Mathew
- Department of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, New Delhi 110070, India
| | - Vasundhra Bindal
- Department of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, New Delhi 110070, India
| | - Shvetank Sharma
- Department of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, New Delhi 110070, India
| | - Ekta Gupta
- Departments of Virology, Institute of Liver and Biliary Sciences, New Delhi, India
| | - Jaswinder Singh Maras
- Department of Molecular and Cellular Medicine, Institute of Liver and Biliary Sciences, New Delhi 110070, India
| | - Shiv Kumar Sarin
- Department of Hepatology, Institute of Liver and Biliary Sciences, New Delhi 110070, India
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Abstract
Metabolomics is the laboratory analysis and scientific study of the metabolome—that is, the entire collection of small molecule chemicals in an organism. The metabolome represents the functional state of an organism and provides a multifaceted readout of the aggregate activity of endogenous (cellular) and exogenous (environmental) processes. In this review, we discuss how the integrative and dynamic properties of the metabolome create unique opportunities to study complex pathologies that evolve and oscillate over time, like epilepsy. We explain how the scientific progress and clinical applications of metabolomics remain hampered by biological and technical challenges, and we propose best practices to overcome these challenges so that metabolomics can be used in a rigorous and effective manner to further epilepsy research.
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Affiliation(s)
- Tore Eid
- Departments of Laboratory Medicine, of Neurosurgery, and of Cellular and Molecular Physiology, Yale School of Medicine, New Haven, CT, USA
- Clinical Chemistry Laboratory, Yale-New Haven Hospital, New Haven, CT, USA
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Comparative Evaluation of Plasma Metabolomic Data from Multiple Laboratories. Metabolites 2022; 12:metabo12020135. [PMID: 35208210 PMCID: PMC8877229 DOI: 10.3390/metabo12020135] [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: 01/07/2022] [Revised: 01/24/2022] [Accepted: 01/28/2022] [Indexed: 11/17/2022] Open
Abstract
In mass spectrometry-based metabolomics, the differences in the analytical results from different laboratories/machines are an issue to be considered because various types of machines are used in each laboratory. Moreover, the analytical methods are unique to each laboratory. It is important to understand the reality of inter-laboratory differences in metabolomics. Therefore, we have evaluated whether the differences in analytical methods, with the exception sample pretreatment and including metabolite extraction, are involved in the inter-laboratory differences or not. In this study, nine facilities are evaluated for inter-laboratory comparisons of metabolomic analysis. Identical dried samples prepared from human and mouse plasma are distributed to each laboratory, and the metabolites are measured without the pretreatment that is unique to each laboratory. In these measurements, hydrophilic and hydrophobic metabolites are analyzed using 11 and 7 analytical methods, respectively. The metabolomic data acquired at each laboratory are integrated, and the differences in the metabolomic data from the laboratories are evaluated. No substantial difference in the relative quantitative data (human/mouse) for a little less than 50% of the detected metabolites is observed, and the hydrophilic metabolites have fewer differences between the laboratories compared with hydrophobic metabolites. From evaluating selected quantitatively guaranteed metabolites, the proportion of metabolites without the inter-laboratory differences is observed to be slightly high. It is difficult to resolve the inter-laboratory differences in metabolomics because all laboratories cannot prepare the same analytical environments. However, the results from this study indicate that the inter-laboratory differences in metabolomic data are due to measurement and data analysis rather than sample preparation, which will facilitate the understanding of the problems in metabolomics studies involving multiple laboratories.
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A photonic crystal fiber-based fluorescence sensor for simultaneous and sensitive detection of lactic acid enantiomers. Anal Bioanal Chem 2022; 414:1641-1649. [PMID: 35024916 PMCID: PMC8756416 DOI: 10.1007/s00216-021-03788-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 11/07/2021] [Accepted: 11/10/2021] [Indexed: 11/30/2022]
Abstract
A photonic crystal fiber (PCF)–based fluorescence sensor is developed for rapid and sensitive detection of lactic acid (LA) enantiomers in serum samples. The sensor is fabricated by chemical binding dual enzymes on the inner surface of the PCF with numerous pore structures and a large specific surface area, which is suitable to be utilized as an enzymatic reaction carrier. To achieve simultaneous detection of l-LA and d-LA, the PCF with an aldehyde-activated surface is cut into two separate pieces, one of which is coated with l-LDH/GPT enzymes and the other with d-LDH/GPT enzymes. By being connected and carefully aligned to each other by a suitable sleeve tube connector, the responses of both l-LA and d-LA sensors are determined by laser-induced flourescence (LIF) detection. With the aid of enzyme-linked catalytic reactions, the proposed PCF sensor can greatly improve the sensitivity and analysis speed for the detection of LA enantiomers. The PCF sensor exhibits a low limit of detection of 9.5 μM and 0.8 μM, and a wide linear range of 25–2000 μM and 2–400 μM for l-LA and d-LA, respectively. The sensor has been successfully applied to accurate determination of LA enantiomers in human serum with satisfactory reproducibility and stability. It is indicated that the present PCF sensors would be used as an attractive analytical platform for quantitative detection of trace-amount LA enantiomers in real biological samples, and thus would play a role in disease diagnosis and clinical monitoring in point-of-care testing.
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Personal Metabolomics: A Global Challenge. Metabolites 2021; 11:metabo11110715. [PMID: 34822372 PMCID: PMC8618924 DOI: 10.3390/metabo11110715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Revised: 10/05/2021] [Accepted: 10/19/2021] [Indexed: 11/16/2022] Open
Abstract
Today, the introduction of metabolomics, like other omics sciences, into clinical practice as a personal omics test that realizes the perfect analytical capabilities of this science has become an important subject. The assembled data show that the metabolome of biosamples is a collection of highly informative and accurate signatures of virtually all diseases that are widespread in the population. However, we have not seen the emergence of personalized metabolomics in clinical practice. This article analyzes the causes of this problem. The complexity of personal metabolic data analysis and its incompatibility with widely accepted data treatment in metabolomics are shown. As a result, the impossibility of translating metabolic signatures accumulated in databases into a personal test is revealed. Problem-solving strategies that may radically change the situation and realize the analytical capabilities of metabolomics in medical laboratory practice are discussed.
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